Still Living Without The Basics

rcap_cover_final 6/2/04 2:21 PM Page 1
Still Living
Without the Basics
in the 21st Century
Analyzing the
Availability of Wa t e r
and Sanitation Services
in the United States
Rural Community Assistance Partnership

Still Living Without the Basics
Table of Contents
Foreword.............................................................................................................................................................1
Executive Summary...........................................................................................................................................3
Still Living Without the Basics in the 21st Century ......................................................................................3
Still Living Without the Basics: Analyzing the Availability of Water and Sanitation Services in the
United States.......................................................................................................................................................7
Introduction........................................................................................................................................................7
Methodological Layout of the Study...............................................................................................................8
Part I of the Analysis......................................................................................................................................8
Part II of the Analysis....................................................................................................................................9
Information Gaps ............................................................................................................................................10
Report Findings and Discussions ..................................................................................................................11
How Many People in the United States Live Without Basic Water and Sanitation Services?..............11
Who Are the People Living Without Basic Water and Sanitation Services?...........................................12
Rural – Urban Divide...................................................................................................................................13
Analysis by Race and Ethnicity...................................................................................................................16
In Which States Are Basic Water Services Most Lacking? ........................................................................26
State-Level Analysis......................................................................................................................................26
County-Level Analysis .................................................................................................................................26
Rural-Urban Analysis ...................................................................................................................................28
Ethnic Distribution ......................................................................................................................................29
Why Are Water and Sanitation Services Important? ..................................................................................34
Factors Affecting People Living Without Basic Services...........................................................................36
Socioeconomic Conditions .........................................................................................................................36
Ruralness........................................................................................................................................................38
Cost and Quality of Water and Sanitation Services.................................................................................39
Demographics...............................................................................................................................................40
Factors Influencing Trends in Access to Water and Sanitation................................................................40
Socioeconomic Immigration.......................................................................................................................40
Housing Development.................................................................................................................................41
What Has Been and Is Being Done to Address These Issues?.................................................................42
Ensuring That Water Infrastructure Is Adequately Maintained ...............................................................42
Key Program and Policy Concerns Related to These Issues.....................................................................44
State-by-State Analysis at County Level .......................................................................................................55
Explanation of Terms .....................................................................................................................................57
Glossary.......................................................................................................................................................... 199
i
Foreword
Still Living Without the Basics in the 21st Century is the culmination of nearly a year of research and
analysis that documents the availability of adequate water and sanitation service in U.S. homes. It is
based in large part on data from the 2000 decennial census, supplemented by other publicly available
information. This publication is a sequel, updating an analysis published in 1995 by the Rural
Community Assistance Partnership (RCAP, Inc.) that focused on data from the 1990 decennial
census.
In comparing these documents, two points stand out clearly. The efforts of the Rural Community
Assistance Partnership – and other agencies and organizations working tirelessly in thousands of
small rural communities – have paid off significantly. And still, much remains to be done.
The 1990 census showed that 405,855 rural households lacked complete indoor plumbing. Rural
households represented more than half of all U.S. homes that lacked adequate water and sanitation
services. By the 2000 census, 226,967 rural households were without complete indoor plumbing,
representing about one-third of the national total. This is real progress.
Despite the success to date, more than 600,000 residents of rural communities still do not have the
basic water and sanitation services the rest of us take for granted. It is no surprise that they are likely
to be economically disadvantaged, ethnic minorities, and geographically isolated.
There is much more to the story, of course. This report also looks at the quality of water and
sanitation services and the health consequences of inadequate service. Just as there is much to do,
there also is much to learn about the causes and effects of inadequate basic infrastructure.
The research, analysis, and writing for this report was done by Stephen Gasteyer, Ph.D., RCAP’s
Director of Community Development, and Rahul T. Vaswani, M.A., Research Associate at RCAP.
Their work was made possible by grants from the U.S. Environmental Protection Agency’s Office
of Ground Water and Drinking Water as well as U.S. EPA’s Office of Wastewater Management and
the U.S. Department of Agriculture Rural Utility Service’s Water and Environmental Programs.
As a nation, we have succeeded in bringing proper water and sanitation service to almost every
home. What’s left is likely to be the most difficult part of making water and sanitation services truly
universal.
Randolph A. Adams, Ph.D.

Executive Director
Rural Community Assistance Partnership, Inc.
1
Executive Summary
Still Living Without the Basics in the 21st Century

The United States has achieved remarkable success in improving access to modern water and
sanitation services for its citizens in the past five decades. Today only 0.64 percent of U.S.
households lack complete plumbing facilities. This is a monumental leap from 1950, when more
than one-fourth of the nation, and more than half of all rural residents, lacked those facilities. Yet
we have more to accomplish – and in more complex ways.
The U.S. 2000 Census reveals that more than 1.7 million people in the United States, 670,986
households, still lack the basic plumbing facilities that most of us have come to take for granted. To
some observers, these Americans may appear to be lost or insignificant within the larger population,
but the hardships they endure in their daily lives are very real.
It may seem reasonable to assume that people who live in the 21st century with services more
characteristic of a bygone era choose to live in places or situations where modern services are not
available, or to live in such conditions only temporarily. A closer look at the numbers and trends
reveals the opposite. A combination of circumstances – some of them persistent – have excluded
these people from the reach of development.
Some of the people affected are the poorest of the poor, living in sparsely populated rural areas or
in densely populated urban areas. They live in almost every state from coast to coast – in the vast
reaches of Alaska; the urban centers of southern California, New York, and Illinois; the sprawling
colonias bordering Mexico; the Indian reservations and counties of the Four Corners region in the
West; the underserved rural communities of West Virginia and the New England states. More than a
third of them have household incomes below the federal poverty level. In fact, if you were born in
2000 into a family living below the poverty level in the United States, you were four times as likely as
a fellow American living above the poverty level to be in a home without adequate indoor plumbing.
These people are spread across all racial and ethnic categories, but they are more prominent in the
minority groups. Among American Indians and Alaska Natives, nearly one in 20 households across
the nation lacks complete working indoor plumbing. In the state of Alaska alone, one in every 16
households lacks these facilities, and in some boroughs, such as the Bethel Census area, more than
half of all Native homes do not have adequate plumbing. Similarly, one in every three American
Indian homes in Apache and Navajo counties in Arizona goes without these services. The majority
of these homes are rural.
Among Hispanics, the people most affected live in the traditional centers of large Hispanic
populations – Los Angeles in California; Miami-Dade in Florida; Harris and Hidalgo counties in
Texas; Bronx, Kings, and New York counties in New York – and in the rural areas of New England,
the South, and the West, where groups of Hispanics, including immigrants in the past decade, work
as agricultural and farm workers.
The largest proportion of African-Americans living without adequate water services is in Montana,
where almost 4 percent of African-American households lack complete plumbing facilities. More
than 1 percent of African-Americans lacked these facilities in the southern states of Virginia, South
Carolina, Mississippi, Louisiana, and Georgia, as well as northeast states such as Rhode Island and
Massachusetts.
3
Native Hawaiian and other Pacific Islanders also often lacked complete facilities in relatively high
proportion to their population. For instance, more than 11 percent in Vermont and 10 percent in
North Dakota reported lacking services.
A look at the state-level information shows that Alaska has the highest percentage of households
without plumbing – 6.32 percent of all its households – and Nebraska has the lowest, with only 0.36
percent of its households. More than half (53 percent) of all households lacking proper plumbing
facilities in the United States are concentrated in just one-fifth of the states – California, New York,
Texas, Florida, Pennsylvania, Illinois, Arizona, Virginia, Ohio, and North Carolina. This is not
surprising because these states also have more than half (52 percent) of the nation’s population and
more than half (55 percent) of the people who live below the poverty level. What is surprising,
though, is that only half of these states have done better than in 1990 in reducing the numbers of
people without adequate plumbing. In the other half, the numbers of households without services
have increased.
While the rural-urban divide has lessened over the last five decades – in 1950 it was almost five to
one, with 50 percent of rural homes and 11 percent of urban homes lacking plumbing – it still
persists at two to one. And with a larger share of rural homes in poverty, rural households are more
greatly affected. Today, a poor rural home is two and a half times more likely than a poor urban
home to lack proper indoor plumbing. As the home gets more rural – that is, as the population level
decreases within the area – the chances of not having such services increase further. In five of the
states – New Mexico, Arizona, West Virginia, Kentucky, and Mississippi – half or almost half of the
homes that lack adequate indoor plumbing also are below the poverty level.
Disaggregating the picture to look at county-level information gives a clearer understanding of the
dynamics of the social and economic variables that affect basic water and sanitation services. The
counties that are persistently poor, non-metro, and rural, with a larger share of their populations
composed of minority groups, are more likely to have inadequate plumbing services than are urban
counties with a more diverse racial and ethnic mix of groups. More important, these inadequate
systems pose significant health risks for vulnerable populations. Smaller community water systems
that have limited access to the resources they need to enhance these basic services are likely also to
be in violation of health and safety standards set by national environmental authorities.
Studies by the U.S. Centers for Disease Control and Prevention have found more outbreaks of
waterborne diseases in the United States in the 1999–2000 period than in the previous seven years.
U.S. Environmental Protection Agency reports also show that 8.2 percent of the 48,271 community
water systems in the United States that serve populations of less than 10,000 were in violation of
health and safety standards for drinking water quality in 2003.
Couple these statistics with an aging infrastructure that needs to be replaced or improved, and the
recent reductions in spending for programs to enhance water and sanitation services, and we see an
imposing and complex situation that will require careful attention and multifaceted solutions in the
coming years. The social and economic impacts of this situation are likely to be great, as are the
ecological effects of diminishing water supplies in vulnerable areas.
These are only some aspects of basic water and sanitation services in the United States that public
policy should be concerned about. Other important aspects involve the efficacy and efficiency of
our collection and presentation of information about these services. How we define questions about
water and sanitation services in national surveys, and how we tabulate the responses for subsequent
analysis and understanding of national realities, are crucial if the resulting reports are to be
substantive and meaningful. How we define the categories of “rural,” “urban,” and “poverty”
4
becomes even more critical when the largest sources of funds – both federal and private – for
improving the socioeconomic conditions of people who live in poverty in both urban and rural areas
rely on these definitions as they disperse funds and institute programs.
There is an intrinsic link between the quality of basic services such as water and sanitation and the
economic opportunities that follow their improvement, especially in communities that are in close
proximity to developing urban centers. While we have seen a slight shift in the population from rural
to urban in the past decade, the conditions of many rural Americans have not improved, and the
quality of their basic services is an important reason.
While the United States has made great improvements in the quality of life for many urban and rural
Americans, there is more to be achieved – even in something as simple and essential as bringing
safe, clean water and basic water and sanitation services to the entirety of the U.S. populace. The gap
has been reduced to less than 1 percent of the entire population in the past century. Now our efforts
must focus on closing the gap. This task requires developing a more complex and detailed
understanding of the social, economic, and ecological reasons why communities lack these services,
and constructing solutions that are not only acceptable and feasible, but also sustainable.
Still Living Without the Basics is intended to inform the public’s understanding of access to water and
sanitation services in the United States and to contribute to the debate on how to structure policy
decisions for improving these services, especially for those groups that have been excluded or
overlooked in the development process. We hope to build on this research in the near future,
further investigating the links between people’s access to services and the various social, economic,
and ecological outcomes that affect those people.
Stephen Gasteyer, Ph.D., Director of Community Development

Rahul T. Vaswani, M.A., Research Associate
5
Still Living Without the Basics: Analyzing the Availability of Water

and Sanitation Services in the United States
Introduction
For the vast majority of United States citizens in the 21st century, household water has become so
readily available that we barely consider it. Turn on the tap, jump in the shower, flush the toilet – we
take for granted our access to potable water and modern sanitation and assume that everyone across
the country has access to these services. Indeed, almost everyone does – more than 99 percent of
U.S. residents, according to the 2000 Census.
Most international health and socioeconomic development institutions, including the World Health
Organization (WHO), the United Nations Children’s Fund (UNICEF), and the World Bank (WB),
simply round up that percentage and report that 100 percent of U.S. citizens have access to
developed water and sanitation services.1 They suggest that the few Americans who lack these
amenities are extreme exceptions – exceedingly rare and subject to extraordinary circumstances,
probably temporary.2
The number of households involved may indeed seem statistically small, at 0.64 percent of all U.S.
households. But that 0.64 percent translates into 670,986 households, representing more than 1.7
million people3 who lack complete plumbing facilities (Table 1).4 This is the number of people who
are falling through the cracks. Makers of public policy – urban and rural, social and economic – need
to focus on these 1.7 million and their needs.
These numbers are indicative of larger and more severe realities that policy makers often overlook
or fail to comprehend. Beyond those people who live without access to proper plumbing services,
increasing numbers of people live in areas where the groundwater they use for household purposes
is contaminated or where the supply of water is dwindling because of water losses and overuse.
Even communities that have had piped water for some time are now confronting the reality of
having to replace or upgrade aging infrastructure and water treatment facilities that no longer
comply with U.S. Environmental Protection Agency (USEPA) health and safety regulations.5
Drawing on data from the U.S. Census surveys of 1990 and 2000 and other related sources, this
report describes some of the characteristics of the people who still live without access to basic water
and sanitation services in the United States. It tries to answer some elementary questions: What is
1 See, for example, the water and sanitation statistics available for the United States on the WHO and UNICEF websites at
http://www.who.int/docstore/water_sanitation_health/Globassessment/Global11-2.htm or
http://www.who.int/water_sanitation_health/monitoring/en/Glassessment11.pdf – page 3, and at
http://www.childinfo.org/eddb/water/Euroam/usa_water1.pdf.
2 “Americans” in this report refers only to U.S. citizens, U.S. residents, or U.S. nationals, any of whom reside in the 50 states and the
District of Columbia, and, where specified, in Puerto Rico and the Island Areas (the U.S. Virgin Islands, Guam, American Samoa, and
the Northern Mariana Islands).
3 These statistics include information from only the 50 U.S. states and the District of Columbia. They are tabulated from the
responses to Item 39 of the Long Form of U.S. Census 2000.

4 It is important to note that the U.S. Census definition of “lacking complete plumbing facilities” is the lack of any of the following
services within the housing unit: (a) hot and cold piped water, (b) bathtub or shower, (c) flush toilet. This definition has been more or
less consistent since 1970. We take this definition to be equivalent, for purposes of this report, to the more general understanding of
what constitutes basic water and sanitation facilities. See also the section on information gaps in this report for a better understanding
of the limitations of information on plumbing and sanitation facilities.
5 For more information, see USEPA, The Clean Water and Drinking Water Gap Analysis, Office of Water (4606M) EPA-816-R-02-020,
2002, or www.epa.gov/safewater. Also see West Central Initiative, Infrastructure for West Central Minnesota Communities, West Central
Initiative, Fergus Falls, Minnesota, 2002, or http://www.wcif.org/publications/pdf/infra_2003/infrastructurestudy2003.pdf; accessed
May 2, 2004.
7
the number of households and people lacking these services? What regions, states, and counties are
home to these people? Do these people tend to live more in rural or urban areas? What are their
ethnicities? What is their socioeconomic status? The report also tries to address some key policy
questions that arise from this analysis: How have the numbers of people living without services
changed over time – particularly in the past decade? What has contributed to this change? What is
the relationship of water and sanitation services to other basic services? What do policy makers need
to understand more clearly about this information to make further improvements in the availability
of water and sanitation services? What efforts need to be taken in this direction?
Methodological Layout of the Study

This report provides an analysis of the access to complete plumbing facilities in the United States –
the 50 states, the District of Columbia, Puerto Rico, and the Island Areas (the U.S. Virgin Islands,
Guam, American Samoa, and the Commonwealth of Northern Mariana Islands).6 Where possible,
the analysis looks beyond the U.S. Census levels to cover regional, state, and county place levels as
well.
The basic research for our analysis was done in two parts.
Part I of the Analysis

In the first part, we relied entirely on the information provided by the U.S. Census for 1990 and
2000, and undertook our research in four successively complex stages.
The first stage involved collecting data and arranging it for subsequent analysis. This stage included
determining how the demographic and socioeconomic data relate to each other. We did this
primarily at the state and national levels and disaggregated it across six of the eight major race and
ethnicity categories used in the Census 2000 survey. The categories included in this study are the six
races of “White,” “Black or African American,” “American Indian and Alaska Native” (AIAN),
“Native Hawaiian and Other Pacific Islander” (NHOPI), “Asian,” “Some Other Race,” and the
ethnic category of “Spanish/Hispanic/Latino.”
In the second stage, we analyzed the data down to the county level7 for the 50 U.S. states, the
District of Columbia, and Puerto Rico, and to the Census-designated place (CDP) level for the
Island Areas. In the case of the four Island Areas, we made this change in geographic level, from
county to CDP, to obtain a more meaningful representation of information at a disaggregated level.
At both of these substate geographic levels, we analyzed the data for the number of households and
the number of people lacking complete plumbing facilities. Where possible, we also tracked the
breakdown of these numbers for the six race and ethnicity categories listed above. This was not
always possible, because the size of some counties is so small that the Census Bureau does not
release information about housing and population characteristics in order to maintain the
confidentiality of the respondents.
In the third stage, we determined the possible lack of adequate water and sanitation facilities for
households and people disaggregated by race and by ethnicity, in urban and rural areas, at both the
6 The District of Columbia, Puerto Rico, and the Island Areas are each treated as the statistical equivalent of a state for U.S. Census
purposes. However, figures quoted by the U.S. Census Bureau for the United States as a whole include numbers for the District of
Columbia but not for the other equivalent states, and this report treats those figures the same way unless otherwise stated in the text.
7 While tabulation of data below the county level was not practical for this endeavor, we fully recognize the limitations of county data,
specifically for recognizing rural/urban differential. Urban counties in the West often contain rural places.
8
state and the county or CDP levels. This gave a clearer picture of how the numbers were
geographically placed.
In the fourth stage, we determined the correlation between the lack of adequate water and sanitation
facilities and the level of poverty, at both the state and county or CDP levels. We also did these
correlations with similar information available for the race and ethnic categories above, and for
households in urban and rural areas.
Using ArcView Geographic Information System (GIS) applications, we mapped our findings for the
states, counties, and CDP areas, showing the percentages and absolute numbers of households and
people lacking adequate water and sanitation services.
Part II of the Analysis

In the second part of our analysis, we took information from additional data sources to help us
address some of the important questions that either were based on the assumptions that led to our
analysis or arose in the process of the research itself. For this we used the following sources:
§ The Safe Drinking Water Information System (SDWIS) datasets of the USEPA to find the
relationship between the number of people without access to services and the size, ownership,
and health safety violations of small community water systems.
§ Data from the Advanced Query Data Finder of the U.S. Census Bureau to find the relationship
between the lack of complete plumbing facilities and the cost of water and sanitation services in
rural and urban locations across the United States.
§ The information compiled in the first part of our research at the state and county levels, the
correlations determined above, and other available socioeconomic and demographic indicators
to develop hypotheses about certain areas that have a relatively higher number or percentage of
households reporting lack of water and sanitation services. This was necessary to understand the
underlying causes for the lack of adequate water and sanitation services in different
socioeconomic and demographic conditions.
Using the methodology described above, we were able to determine how many households or
people of any race or ethnic group do not have access to complete plumbing facilities, at the state
and county levels, in both urban and rural areas. We were also able to determine some important
correlations between the lack of complete plumbing facilities and other variables, such as these:
1. The poverty level in each of these states and counties, and likewise in each of the urban
and rural areas in each state and county.
2. The monthly cost of water and sewer facilities per household.
3. The health safety violations of codes and regulations that occur in the small community
water systems serving these households in each county.
Our analysis has helped us better understand, and at the same time has affirmed some of our pre-
analytical assumptions on, the relationships between economic conditions, geographic location,
conditions of infrastructure, and kinds of communities. More important, these understandings have
helped us identify some of the resources, services, and assistance underserved communities need in
the coming years to meet the gap in water and sanitation infrastructure.
9
Information Gaps
In the course of our research, we encountered some important information gaps that readers of this
report should be aware of as they try to understand the analysis.
§ Not all people answering the U.S. Census Long Form interpreted the question about plumbing
services in the same way.8 For instance, the 2000 Census revealed that more than 1,100
households, or more than 3,200 people, in Fairfax County, Virginia (a relatively affluent suburb
of Washington, D.C.), lacked complete plumbing services. This finding raises the possibility that
some responses were not what the Census question intended to elicit. Some respondents, for
instance, may have noted that they lacked complete plumbing services when those services were
in fact available to them but had been turned off for lack of payment – presumably a temporary
condition, not a permanent one. While we view this issue as critically related to our concerns, it
is beyond the scope of this report. It is worth noting here, though, that other organizations have
increasingly focused on how the inability to pay affects people’s access to water services,
whether temporarily (as when water is cut off for nonpayment) or permanently.9
§ It is possible that many people who probably lack access to basic services were not included
in the Census. Among these people may be the homeless in the United States, as well as
immigrants or migrant laborers who might have worried about responding to the Census data
collectors out of fear that the information would be turned over to law enforcement or
immigration authorities. While the Census Bureau maintains confidentiality of the data it
collects, the fact that the bureau is part of the U.S. government can make it suspect in the eyes
of many people in such categories.
§ Several key questions about plumbing and sanitation facilities were eliminated from the U.S.
Census questionnaires between 1990 and 2000. These included data about the source of water,
the type of water and wastewater facilities, and water system ownership. In the U.S. 2000
Census, they exist only in the questionnaires distributed in the Island Areas. If they had been
included in all of the questionnaires, these questions would have allowed for a more detailed
analysis of not only the numbers of people lacking plumbing and sanitation services but also the
population living with inadequate water services.10
§ Because of confidentiality considerations in small counties and inconsistencies between the data
available from the U.S. Census Bureau and data from the State Drinking Water Information
System, wherever possible we concentrated our correlations on the counties whose information
appeared in both databases. The same is true for correlations between U.S. Census information
and the data taken from the query results of Advanced Factfinder. For example, the correlation
between the lack of plumbing facilities and the monthly cost of water and sewer facilities was
possible for only 2,336 of the total 3,219 U.S. counties.11
§ The definition of "urban" and "rural" changed between the 1990 and 2000 U.S. Census surveys.
Thus, the information for these categories is not directly comparable between the two surveys.12
Nonetheless, we have shown the comparative data from the two years in our ranking tables to
give readers a general idea of the magnitude of changes in "urban" and "rural" numbers between
the two censuses.
8 See the glossary at the end of this report for a description of the Long Form.
9 See the work of Public Citizen and the Welfare Rights Association on water cutoffs in Detroit, Michigan
(www.citizen.org/facts/detroit), and the report of the National Drinking Water Advisory Council on water system affordability
(www.epa.gov/safewater/ndwac/affordability).
10 The distinction here is among drinking water, water for other household purposes, and sanitation/sewer facilities.
11 The total number of counties (municipios, in the case of Puerto Rico) for the 50 U.S. states, the District of Columbia, and Puerto
Rico is 3,219.
12 For a more detailed description of “urban” and “rural,” see the glossary at the end of this report.
10
Report Findings and Discussions

In this report we cover the following related issues:
§ Households and populations without access to basic water and sanitation services, mapped by
each state and down to the county level where possible.
§ The breakdown of the population living without these services by race/ethnicity – specifically
for the six race/ethnicity categories included in this report – at the state and county levels.
§ An analysis of rural-urban differences and similarities related to lack of these services.
§ Public health implications of not having access to basic water and sanitation services.
§ Factors that influence access to water and sanitation in the United States.
§ Steps that are being taken to address these issues.
§ Key issues for rural water infrastructure.
§ Key program and policy concerns related to these issues.
We provide county-level information tables and GIS maps representing the numbers of households
in each county that lack access to complete plumbing services. We have used information from the
U.S. Census to document these numbers. We have correlated this information with data from
SDWIS and discussed some of our findings, where applicable. While we clearly have not exhausted
the data available on water and sanitation, we hope this report will contribute to an understanding of
the work still to be done in the United States on this issue.
How Many People in the United States Live Without Basic Water and
Sanitation Services?
The United States has made great progress over the past 50 years in providing its residents with
access to improved water and sewer facilities. In 1950, 27 percent of all households in the country
lacked access to complete plumbing facilities. The rural-urban divide then was more substantial –
close to a five-to-one ratio. More than 50 percent of rural households and 11 percent of urban
households lacked these services in 1950. Significant rural infrastructure investments by the federal
and local governments through the 1950s and 1960s led to a dramatic decrease in the households
without proper plumbing facilities. By 1970, only 5.9 percent of all U.S. households lacked piped
water, although the ratio of rural to urban still remained close to five to one (14.5 percent of rural
and 3.1 percent of urban households lacked proper plumbing facilities in 1970).
Table 1: Percentage of Occupied Housing Units Lacking Complete Plumbing Facilities, 1950–200013
% of occupied housing units lacking 1950 1960 1970 1980 1990 2000
plumbing (U.S.)
Rural 56 31.5 14.5 4.5 1.9 1.0
14
Rural – farm 55 NA NA 3.9 NA 1.2
Urban 11 8.2 3.1 2.2 0.5 0.5
Total 27 14.7 5.9 2.7 0.78 0.64
13 U.S. Bureau of the Census, Census of Housing 1950, Washington, D.C., Government Printing Office, 1952; Census of Housing
1960 (1962); Census of Housing 1970 (1972); Census of Housing 1980 (1982); Census of Housing 1990 (1992); Census of Housing
2000 (2002). Also see Dennis Warner and Jaris S. Dajani, Water and Sewer Development in Rural America: A Study of Community Impacts,
Lexington Books, Lexington, Massachusetts, 1975.
14 The “Rural”category includes all non-farm and farm households. The “Rural – farm” category includes all households located in a
rural farm area and concerned with growing crops or raising livestock.
11
By 1990, the United States had installed basic plumbing infrastructure for more than 99 percent of
its citizens. Most of the people who lacked plumbing services were elderly, poor, and living in rural
areas.15 Rural households were still four times as likely as urban households to lack proper plumbing.
By the 2000 Census, only 0.64 percent of occupied households lacked complete plumbing facilities
(Table 2). Indeed, the percentage was low enough in 2000 that UNICEF stated in its global reports
on access to water and sanitation services that the United States had 100 percent water and
sanitation coverage. While the 0.64 percent may appear to be statistically insignificant, it represents
more than 1.7 million people across the country, most of whom are the hidden poor – people who
live in rural, and often underserved or marginalized, areas that lack the services that most Americans
take for granted. The rural-urban divide is still at two to one – a rural household is twice as likely as
an urban one to have inadequate plumbing facilities in the United States (Table 2).16 U.S. Census
2000 figures suggest that more than 1.1 million urban citizens (equal to 0.5 percent of the total
urban population) and more than 600,000 rural citizens (equal to 1.04 percent of the total rural
population) still lack proper plumbing facilities.
Table 2. Total and Percentage of Occupied Housing Units Lacking Complete Plumbing Facilities,
1990–2000
Occupied Housing Units Lacking Complete Plumbing Facilities
Census
Total – Percentage – Total – Percentage –
Year Total Percentage
Rural Rural Urban Urban
2000 670,986 0.64 226,967 1.03 444,019 0.53
1990 721,693 0.78 405,855 1.85 315,838 0.45
Who Are the People Living Without Basic Water and Sanitation Services?
The people who lack these basic services live in some of the most productive farmland in the United
States, along the U.S.-Canada and U.S.-Mexico borders, on Indian reservations, and in the states of
the South and the Southeast. They are people working and living in rural and urban areas with
dilapidated or nonexistent infrastructure. The Census 2000 data show that 0.64 percent of all
occupied households in the country lack adequate plumbing (see Maps 1 and 2). This translates to
670,986 households in the 50 states and the District of Columbia, or more than 1.7 million people.
When the numbers for Puerto Rico are included, the total households lacking plumbing increase to
736,626, and the number of people lacking these services increases to more than 1.95 million.17 In
addition, 11,033 households and an estimated population of 47,800 in the Island Areas lack com-
plete plumbing facilities; this calculation brings the total figure close to 2 million U.S. residents.18
15 See Still Living Without the Basics: A Report on the Lack of Complete Plumbing That Still Exists in Rural America, Rural Community
Assistance Program, Washington, D.C., 1995.

16 It is important to note that the U.S. Census 2000 survey does not have a precise definition of what constitutes “rural” areas. Rather,
it goes about defining urban areas, accounting for core areas, urbanized areas, and urban clusters differentiated by population density,
proximity to metropolitan centers, and so on. What is left is given the status of “rural.” The 1990 Census found 62 million people
living in rural parts of the country. The number dropped by about 5 percent in the 2000 Census, although the total U.S. population
increased by about 13 percent. It is likely that at least some of this decrease results from the change in the definition of what
constitutes “rural” between the 1990 and 2000 Censuses, rather than from socioeconomic changes in that decade.
17 This figure of more than 1.95 million is obtained from the Advanced Query Data Finder of the Census Bureau and corroborates to
the population estimates obtained from the Summary File 3 of the U.S. Census 2000 survey.
18 The U.S. Census information does not include the numbers for Puerto Rico or the Island Areas in its tabulations of the total
households and people lacking complete plumbing facilities.
12
Rural – Urban Divide

When we break down the numbers and percentages of households lacking proper water and
sanitation services among rural areas, rural places with populations of less than 1,000 and rural farm
populations have the highest percentage of homes lacking services, well above the national average
of 0.64 percent. In the case of urban areas, the highest percentage of households lacking these
services is in the most densely populated urbanized areas (those with populations of 5 million or
more) and in the fringe areas of urban clusters that are adjacent to rural areas and have populations
ranging from 2,500 to 4,999. The relative difference in lack of services between urban and rural areas
ranges from about 1.5 to 3 times, depending on the population level of the area (Table 3).
Table 3. Households and Population in Rural and Urban Areas Lacking Complete Plumbing
Facilities, 2000
Occupied Housing Units Lacking Plumbing Facilities
Geography Percentage of Total Estimated Population
Total
Households Lacking Plumbing19
United States as a whole 670,986 0.64 1,737,814
Rural 226,967 1.03 599,193
Rural – total in a place 41,704 0.84 105,511
Rural – in a place of 2,500 or
9,156 0.61 23,897
more people
Rural – in a place of 1,000 to
13,288 0.68 33,087
2,500 people
Rural – in a place of fewer than
19,260 1.27 48,150
1,000 people
Rural – not in a place 185,263 1.09 496,505
Rural – farm 13,172 1.19 35,564
Urban 444,019 0.53 1,145,569
Urban – in an urbanized area 389,261 0.54 1,012,079
Urban – in an urbanized area of
121,651 0.80 335,757
5,000,000 or more
85,380 0.58 223,696
2,500,000 to 4,999,999
56,563 0.43 143,670
1,000,000 to 2,499,999
43,161 0.48 109,629
500,000 to 999,999
29,399 0.42 74,379
250,000 to 499,999
32,175 0.41 81,081
100,000 to 249,999
20,932 0.41 52,121
50,000 to 99,999
Urban – in an urban cluster 54,758 0.48 136,347
Urban – in an urban cluster of
14,045 0.43 34,832
25,000 to 49,999
12,162 0.51 30,405
5,000 to 9,999
9,540 0.54 23,659
2,500 to 4,999
19 The estimated population is calculated by multiplying the number of households lacking plumbing facilities by the average
household size for that category (as given in Summary File 3 of the U.S. Census 2000 survey).
13
14
15
Table 3 shows that rural areas generally have a higher percentage of the population lacking
plumbing. Within rural households, the proportion of those lacking plumbing is highest in
communities of fewer than 1,000 residents and among farm households. For urbanized areas or
urban clusters, the trend is different. Within urban areas, the most densely populated areas (those of
5 million or more) have the highest percentage lacking services – 0.80 percent. The percentage drops
steadily as the population size of the urban area decreases, reaching 0.41 percent of households
lacking proper plumbing in urban areas of only 50,000 to 99,999 people. In the smaller, urban
cluster category, the percentage rises as the population decreases – from 0.43 percent in larger
clusters of 25,000 to 49,999 people, to 0.54 percent in the smallest urban clusters of 2,500 to 4,999
people.
Rural areas have traditionally been the most difficult to reach with water services, because they lack
the economies of scale to support such services without subsidization or they lack the technical
assistance and financing. A total of 226,967 rural households lack adequate plumbing, which
includes 13,172 rural farm households.20 Despite the rise in American economic and living standards
with the boom in agricultural capacity, it is clear that rural-farm households remain some of the
most deprived in the nation in terms of basic services. The relatively high percentage of those
lacking services in the highly urbanized areas is presumably the result of two factors: low-income
populations living in substandard housing and people reporting water cutoffs as lacking plumbing
facilities. In either case, more research may be needed to identify the reasons for this statistic.
Analysis by Race and Ethnicity

The figures for the percentage of households and the total population lacking complete plumbing
facilities vary greatly by race and ethnicity. Among race categories, American Indians and Alaska
Natives (AIANs) have the greatest percentage of households nationwide lacking complete plumbing
facilities, at 4.41 percent or 33,781 of their households (Tables 4 and 5, Maps 3 and 4), and Whites
have the lowest, at 0.47 of their households. Alaska has the highest percentage of households
without services – 6.32 percent – with the proportion in rural areas more than 18 percent. More
than half of all rural AIAN communities in the Bethel, Nome, Wade Hampton, and Yukon-
Koyukuk census areas, for example, do not have services. More than a third (38.79 percent) of all
rural AIAN communities across Alaska live in similar conditions. This is in part because of the
isolation of much of Alaska from modern infrastructure and the resulting cost of installing water
services, which most Alaska Native communities are unwilling or unable to bear. It is also a result
of the geology of Alaska, because the severe cold makes drilling and maintaining water lines difficult.
While many Alaska Natives have said that they would prefer living without services to dealing with
the problems of piped water, there are increasing efforts to improve sanitation services. This
situation is described this way:
Many rural Alaskans live without running water and flush toilets. The basic sanitation needs
in nearly one-half of Alaska’s 192 Native villages have yet to be met. Another 76 rural
communities are not considered to be Native villages; however, the Federal Field Work
Group on Alaska Rural Water and Wastewater Sanitation Issues reported in 1995 "sanitation
facilities in a number of these communities are known to be similar to those of Alaska
Native villages." The work group, which was commissioned by Congress, reviewed the
social-economic factors contributing to sanitation inadequacy and noted that one-fourth of
Alaska’s Native residents "live without running water and use plastic buckets for toilets." In
20Of the 670,986 households lacking complete plumbing facilities in the United States, 444,019 are urban households and 226,967 are
rural households. See Tables 2 and 3 in the text.
16
many villages, residents must haul water to their homes. Due to the high need for housing,
many homes are constructed without adequate sanitation facilities being available to connect
homes or provide safe running water or proper sewage disposal. Communities are often
faced with having to make difficult decisions between adequate housing and adequate
sanitation..21
Table 4. Total and Percentage of Rural and Urban Occupied Housing Units Lacking Complete
Plumbing Facilities, by Race or Ethnic Category, 2000
Race/ Occupied Housing Units Lacking Complete Plumbing Facilities
Ethnic Total % Rural – % Rural Total %
Total %
Category Rural Rural Farm – Farm Urban Urban
White 389,415 0.47 158,653 0.79 11,449 1.09 230,762 0.36
Black 131,382 1.10 30,724 2.66 1,109 3.64 100,658 0.93
AIAN 33,781 4.41 27,256 9.62 253 4.36 6,525 1.35
Asian 27,780 0.89 644 0.82 53 1.81 27,136 0.89
NHOPI 1,383 1.40 338 3.88 4 1.61 1,045 1.16
SOR 62,687 1.63 5,090 2.18 213 2.87 57,597 1.60
Hispanic 134,723 1.47 12,256 2.16 451 2.55 122,467 1.42
The American Indians living without complete plumbing services are most numerous in the
reservations and pueblos of New Mexico and Arizona. An investigation of the county-level
information indicates that this ethnic group is most affected in the Four Corners area of New
Mexico and Arizona – in other words, on the large Hopi, Navajo, and Apache Reservations. In
Arizona, for instance, 35 percent of American Indians in Apache County and 27 percent in Navajo
County lack adequate plumbing. Significant numbers of American Indians do not have basic services
in areas such as the Pine Ridge Reservation of South Dakota, which covers three counties – Bennett,
Jackson, and Shannon – where 2.49, 2.65, and 12.96 percent of households, respectively, report not
having complete plumbing facilities.
The Some Other Race (SOR) category is a catch-all category chosen by those who feel that their
race is not represented in the other six race categories. Based on an evaluation done by the U.S.
Census Bureau, more than 95 percent of those who filled in this category are of Mexican,
Panamanian, Caribbean, Central American, and/or South American origin.22
21 Rural Alaska Sanitation Coalition, Mission and Goals, Alaska Native Health Board, http://www.anhb.org/sub/rasc/, accessed May 2,
2004.
22 Census Bureau, “Results of 2003 National Census Test of Race and Hispanic Questions of 2003,” Suitland, Maryland, U.S. Census
Bureau, Department of Commerce, 2004.
17
18
19
Hispanics (including Puerto Ricans) are the next largest group, at 1.47 percent (or 134,723
households) (Maps 5 and 6). More than 64,000 of these households are located in Puerto Rico.
Another 36,505 are in California, and 28,157 are in Texas. The largest numbers of people living
without services are in the urban, coastal, southern California counties of Los Angeles and San
Diego. The counties with the highest proportions of people living without services, though, are in
California’s Central Valley, a lucrative agricultural area with many farm workers from Central and
South America. These workers often struggle for a meager living, and large numbers of them remain
persistently poor and without access to basic services. The Texas population is from the colonias
along the Mexican border, where the lack of water and sanitation stems from a combination of land
tenure problems, poverty, and unresolved immigration status. The USEPA has described the
situation as follows:
There are more than 1,300 “colonias” in Texas and New Mexico along the border with an
estimated population of more than 300,000. A few colonias may exist in Arizona and some
possibly in California. However, most colonias are concentrated in the Las Cruces, New
Mexico, El Paso, Texas, and the lower Rio Grande Valley area, and west surrounding
Brownsville, Texas. Colonias developed in the border area (especially in Texas) as land
developers sold small plots of land in unincorporated subdivisions to low-income families.
These land purchases are generally financed with a low down payment and low monthly
payments. A deed of ownership is rarely transferred. At the time this activity took place,
State law only required road access and drainage. Providing solutions to public health
problems in the colonias is a unique situation in that they are not political subdivisions.
Financial programs are normally designed to deal with an identified political entity. The
typical colonia does not have any basic community infrastructure such as safe drinking water,
sewage disposal, or garbage collection and disposal.23
In absolute numbers of people lacking complete plumbing facilities in the country as a whole, the
White race category has the highest numbers, with more than 950,000 people, followed by Hispanics
at more than 475,000 people and Black or African Americans at more than 350,000 people. On
analyzing these numbers more closely at the county level, we find that for the race/ethnic categories
of White, Black or African Americans, Asian, and Hispanic, more than 96 percent of all households
lacking plumbing in the top 10 counties for each race category in the nation are urban households.
This is starkly different for the race category of AIAN. More than 96 percent of all AIANs lacking
plumbing facilities in the top 10 counties are rural. For the NHOPI category, two-thirds of the
homes in the top 10 counties are urban, and the rest are rural.24
23 U.S. Environmental Protection Agency, U.S. Mexico Border: Colonias Fact Sheet, USEPA, Washington, D.C., 2003,
http://www.epa.gov/owm/mab/mexican/clnfcts.pdf, accessed May 2, 2004.
24 It is important to note that the numbers for households lacking complete plumbing facilities in the top 10 counties in each
race/ethnicity category represent a substantial percentage of the total households lacking services for each of these race/ethnicity
categories. For example, the top 10 counties for AIAN, NHOPI and Asian race categories have 60 percent, 50 percent, and 45
percent, respectively, of the total households lacking plumbing in these categories all over the nation.
20
21
22
Table 5. Top Five States With Highest Percentage of Households Lacking Complete Plumbing
Facilities, for Six Race and Ethnic Categories, 200025
Race/
Ethnic 1 2 3 4 5
Category State % State % State % State % State %
White AK 4.28 HI 1.10 WV 1.00 KY 0.94 ME 0.84
Black MT 3.99 MS 1.73 RI 1.64 VA 1.53 MA 1.50
AIAN AK 22.98 AZ 17.02 NM 14.18 UT 9.89 DC 6.08
Asian ND 2.19 SD 2.01 MN 1.96 RI 1.75 NH 1.64
NHOPI VT 11.11 ND 10.81 CT 9.12 ME 6.82 LA 4.93
SOR MA 3.61 AK 3.46 ME 3.09 DC 3.04 CT 2.61
Hispanic MA 3.39 AK 2.45 NY 2.18 CT 2.17 RI 1.92
The percentages for each of the race/ethnic groups lacking services vary widely geographically. A
critical commonality for all minority race/ethnicity groups except AIAN is that the states where they
have the highest percentage without water services is where they have a smaller population (Table 5).
The highest percentage of Hispanic households with inadequate plumbing is located in the
urbanized northeastern states and Alaska, where the population of Hispanics is relatively low. The
majority of AIAN households lacking plumbing are located in Alaska, as discussed above, and in the
predominantly Indian and rural, underserved counties of the west in Arizona, New Mexico, and
Utah. The highest percentage of Blacks without services is in Montana, which has a very low Black
population. More than 1.5 percent of Blacks in Rhode Island, which also has a small Black
population, reported lacking water services. The percentages of Blacks without services were also
high in the persistently poor, predominantly African American counties of Mississippi and Virginia.
The case of Bayview, Virginia, in Northampton County, is illustrative.
On a sun-kissed afternoon, Victoria Cummings fetches her 5-year-old daughter, Kadijah,
from the Head Start bus stop up on the asphalt road….Once home, Kadijah exerts her tiny
biceps by pumping a dishpan full of off-color rust-flavored water from the outdoor hand
pump that her mother will use for her "bath." Cummings plans a trip to the store to buy
bottled water for drinking and cooking with her food stamps. Her 12-year-old, Latoya, gets
home about 3:30 p.m., and Cummings leaves shortly after that for her night-shift job cutting
fat off plucked chickens.…The small settlement of Bayview sits on a peninsula across the
Chesapeake Bay from the rest of Virginia. One in a string of Eastern Shore communities
settled by freed slaves, it slowly has sunk into abject poverty in a state where much of the
economy hums with the promise of the next century. Bayview’s 114 residents are among the
most impoverished in what, by some measures, is Virginia’s poorest county….Cummings’s
dream is simple: "Water – running water – inside the house," she says.26
It is notable that through community initiative and collaboration with multiple government and
nongovernment organizations, Bayview is installing new housing and water facilities. Over time,
collective action has improved the situation.27
When we look at the states where minority groups are concentrated in large numbers, though, we
find that they constitute a predominantly large share of the people in the state who lack complete
plumbing facilities. For example, in Mississippi, Louisiana, South Carolina, Georgia, Maryland, and
25 Puerto Rico has some of the highest rates of households lacking complete plumbing facilities, for all race and ethnic categories
(White 4.88%; Black 6.76%; AIAN 9.29%; Asian 5.84%; NHOPI 16.24%; Hispanic 5.22%), but it is not listed in the table, in keeping
with the convention used in this report, as explained earlier.
26 Sylvia Moreno, “In the Spotlight, A Community's Poverty,” Washington Post, May 10, 1998, page A1.
27Anne Raver, “Town of Worn Bootstraps Lifts Itself Up,” New York Times, August 21, 2003, Section F, page 1.
23
Alabama, where Blacks constitute more than 25 percent of each state’s total population, more than
half of all people who lack plumbing in each of these states are Blacks (Table 6). This is similar for
AIAN and Hispanic race/ethnicity categories (Tables 7 and 8). The AIAN populations in Alaska,
New Mexico, and Arizona comprise from about 5 percent (in Arizona) to just over 15 percent (in
Alaska) of the state population, but well over half of all people lacking plumbing in each of these
states are from the AIAN race group.
Table 6. Percentage of Black or African American Population Lacking Complete Plumbing
Facilities, Top 10 Ranked States, 2000 28
Black or African American Race Only
Overall Population Population Lacking
(all counted races) Population Complete Plumbing
Facilities
Percentage
Difference
State of Total
Percentage of Between
Total State
Total State (1) and (2)
Total Lacking Total Total Population
Population
Plumbing Lacking
(1)
Plumbing
(2)
DC 536,373 5,508 326,611 60.89 3,603 65.41 –4.52
MS 2,749,237 23,800 990,315 36.02 16,746 70.36 –34.34
LA 4,332,884 27,289 1,378,421 31.81 16,979 62.22 –30.41
SC 3,876,875 22,092 1,130,688 29.16 13,154 59.54 –30.38
GA 7,952,484 45,094 2,244,187 28.22 23,455 52.01 –23.79
MD 5,162,381 23,421 1,416,133 27.43 10,730 45.81 –18.38
AL 4,332,570 24,962 1,104,937 25.50 13,416 53.75 –28.24
NC 7,795,305 45,335 1,653,612 21.21 20,724 45.71 –24.50
VA 6,846,703 45,332 1,306,377 19.08 18,205 40.16 –21.08
DE 758,963 2,530 140,774 18.55 1,069 42.25 –23.70
28 Source: Advanced Query Data Finder of the U.S. Census Bureau, http://advancedquery.census.gov, accessed June 4, 2004.
24
Table 7. Percentage of AIAN Population Lacking Complete Plumbing Facilities, Top 10 Ranked
States, 2000 29
AIAN Race Only
Facilities
Percentage
Difference
State Percentage of Total
Between (1)
Total of Total State
and (2)
Total Lacking Total State Total Population
Plumbing Population Lacking
(1) Plumbing
(2)
AK 607,641 38,561 93,355 15.36 22,842 59.24 –43.87
NM 1,782,718 33,841 168,670 9.46 21,239 62.76 –53.30
SD 726,335 4,288 58,550 8.06 1,904 44.40 –36.34
OK 3,338,046 16,890 259,950 7.79 2,108 12.48 –4.69
MT 877,381 5,359 53,031 6.04 528 9.85 –3.81
AZ 5,020,851 64,238 246,667 4.91 37,218 57.94 –53.02
ND 618,494 2,024 30,253 4.89 235 11.61 –6.72
WY 479,676 2,085 11,021 2.30 223 10.70 –8.40
WA 5,757,636 28,272 88,174 1.53 882 3.12 –1.59
ID 1,262,397 6,442 16,897 1.34 302 4.69 –3.35
Table 8. Percentage of Hispanic Population Lacking Complete Plumbing Facilities, Top 10 Ranked
States, 2000 30
Hispanic Ethnicity Only
Facilities
Percentage
Difference
State Percentage of Total
Between
Total of Total State
(1) and (2)
Total Lacking Total State Total Population
Plumbing Population) Lacking
(1) Plumbing
(2)
NM 1,782,718 33,841 752,793 42.23 7,985 23.60 18.63
CA 33,052,189 273,629 10,782,193 32.62 156,731 57.28 –24.66
TX 20,290,302 167,633 6,547,417 32.27 106,761 63.69 –31.42
AZ 5,020,851 64,238 1,270,930 25.31 14,736 22.94 2.37
NV 1,964,572 9,498 389,461 19.82 3,842 40.45 –20.63
CO 4,198,094 17,574 718,590 17.12 6,076 34.57 –17.46
FL 15,593,328 80,332 2,630,311 16.87 29,389 36.58 –19.72
NY 18,395,693 155,482 2,792,797 15.18 59,162 38.05 –22.87
NJ 8,219,436 45,090 1,096,410 13.34 17,629 39.10 –25.76
IL 12,096,973 68,220 1,511,718 12.50 23,697 34.74 –22.24
29 Ibid.
30 Ibid.
25
In Which States Are Basic Water Services Most Lacking?
State-Level Analysis
Fourteen states, including New York, California, Texas, and Virginia, have figures above the national
average of 0.64 percent of total occupied households lacking adequate plumbing. Alaska has the
highest: 6.32 percent, or 14,003 households, lacking complete plumbing facilities. Nebraska has the
lowest: 0.36 percent, or 2,408 households. Calculations for numbers of people show that California
has the largest number, with more than 240,000 people (or 85,460 occupied households) lacking
complete plumbing. Wyoming has the least, with about 2,500 people (or 1,011 occupied
households). The top 10 states with the highest numbers for households with inadequate plumbing
(Table 9) hold more than half of such households in the United States. Within these states, the
AIAN population has the highest level of inadequate plumbing – an average of 3.21 percent of
AIAN households. Of these 10 states, 5 have had an average 25 percent increase in households
lacking plumbing facilities, and the other 5 have had an average 24 percent decrease. These 10 states
had an average overall increase of 16 percent in the number of total households lacking complete
plumbing services from 1990 to 2000. There are myriad reasons why the percentages decreased in
some states and increased in others. These include different levels of investment in water and
sanitation infrastructure and access to safe drinking water and sanitation, in-migration of low-wage
laborers, and existing employment and infrastructure base.
Table 9. Total and Percentage of Occupied Housing Units Lacking Complete Plumbing Facilities,
in Top 10 States Ranked for 2000
Occupied Housing Units Lacking Complete Plumbing Percentage
Change
Percentage
U.S./State Total Percentage Total Percentage From 1990 to
Change from
(2000) (2000) (1990) (1990) 2000 in Total
1990 to 2000
Households
United States 670,986 0.64 721,693 0.78 –7.03 14.72
California 85,460 0.74 57,974 0.56 47.41 10.8
New York 58,418 0.83 50,428 0.76 15.84 6.29
Texas 54,853 0.74 56,844 0.94 –3.5 21.78
Florida 30,134 0.48 22,061 0.43 36.59 23.43
Pennsylvania 24,450 0.51 26,355 0.59 –7.23 6.25
Illinois 23,959 0.52 21,572 0.51 11.07 9.27
Arizona 21,088 1.11 18,352 1.34 14.91 38.9
Virginia 19,550 0.72 35,788 1.56 –45.37 17.77
Ohio 19,407 0.44 24,394 0.60 –20.44 8.76
North Carolina 19,295 0.62 33,192 1.32 –41.87 24.43
County-Level Analysis
As we took a closer look at the counties within the states (Map 7), we found several areas lacking in
plumbing services that were not possible to identify at the state level. In terms of percentage of
households lacking plumbing, the highest numbers showed up in the colonias along the Texas and
New Mexico borders with Mexico; in several counties in West Virginia, Kentucky, Maryland,
Virginia, North and South Carolina, Georgia, and Alabama; along the Washington border with
Canada; in South Dakota and the predominantly Indian counties in Oklahoma; and around the Four
Corners region in Arizona, New Mexico, Colorado and Utah. Almost all of Alaskan boroughs and
census areas and the great majority of the municipios in Puerto Rico have higher percentages of
households lacking plumbing than show up in any other regions. Interestingly, 16 of the 20 counties
26
27
in the United States (including Puerto Rico here) with the highest percentages of households lacking
plumbing facilities – ranging from 10.66 percent in Alta Vega municipio in Puerto Rico to 51.87
percent in Wade Hampton census area in Alaska – are in Alaska and Puerto Rico. Of the remaining
four, three are in the Four Corners region, and one is in South Dakota.
If we look at the population figures, we see that Apache and Navajo counties in northeastern
Arizona, the colonias in southern Texas, and several highly urban counties in California, Texas, New
York, Michigan, Illinois, Pennsylvania, and Florida show some of the largest populations with
inadequate plumbing. Together, the top 20 counties with the highest figures for population lacking
complete plumbing hold more than a quarter of the total estimated U.S. population lacking proper
plumbing services.
Rural-Urban Analysis
The rural-urban analysis for the states shows that the states with the highest percentage of rural and
rural-farm homes lacking proper plumbing are fairly similar across both areas (Table 10), with the
exception of Pennsylvania, which has a higher percentage of its farm households with plumbing.
Alaska stands out as the state with the highest percentages across all the three areas – urban, rural,
and rural-farm. Most of the affected urban areas are in densely populated cities on the coasts or
rivers in the South, Southwest, Northeast, and Hawaii.
Table 10. Percentage of Rural, Rural-Farm, and Urban Occupied Housing Units Lacking Complete
Plumbing Facilities, in Top 10 States, Ranked for 2000
Rank Rural Rural-Farm Urban
State % State % State %
1 Alaska 16.89 Alaska 11.63 Alaska 1.04
2 Arizona 6.20 Hawaii 7.32 New York 0.86
3 New Mexico 5.73 Arizona 3.64 District of Columbia 0.85
4 Hawaii 4.55 Pennsylvania 2.75 California 0.73
5 Kentucky 1.71 West Virginia 2.51 Texas 0.65
6 Virginia 1.66 New Mexico 2.38 Massachusetts 0.64
7 West Virginia 1.55 Maine 2.38 Louisiana 0.60
8 Utah 1.43 Virginia 2.09 Hawaii 0.60
9 Maine 1.26 Wisconsin 1.89 Mississippi 0.56
10 Montana 1.18 Kentucky 1.85 Rhode Island 0.56
Rural households in the United States total 226,967, and more than 600,000 people live in homes
that lack adequate plumbing. Another 6,868 rural households, or more than 23,000 people, in Puerto
Rico and the Island Areas live in similar or worse conditions. The 10 states with the highest
populations lacking plumbing in rural-farm and urban areas are shown in Table 11.
28
Table 11. Estimated Rural, Rural-Farm, and Urban Population Lacking Complete Plumbing
Facilities, in Top 10 States, Ranked for 2000
Estimated Population Lacking Complete Plumbing Facilities
Rank Rural Rural-Farm Urban
State Pop. State Pop. State Pop.
1 Texas 41,411 Wisconsin 2,588 California 226,584
2 Arizona 36,529 Ohio 2,442 New York 137,966
3 Alaska 35,392 Kentucky 2,383 Texas 109,131
4 Virginia 30,926 Pennsylvania 2,349 Florida 66,143
5 Kentucky 30,230 Missouri 2,031 Illinois 56,243
6 North Carolina 27,044 Texas 1,840 New Jersey 42,832
7 New Mexico 25,648 Indiana 1,805 Pennsylvania 39,701
8 Pennsylvania 21,416 Minnesota 1,362 Massachusetts 36,048
9 Tennessee 21,213 Virginia 1,331 Michigan 30,973
10 Ohio 20,079 Iowa 1,315 Ohio 29,166
In the top 10 rural states shown in Table 11, plumbing is lacking in 1.5 percent of the rural
households. This number is almost 1.5 times the national rural average and 3 times the national
urban average. In the case of rural-farm populations in the top 10 states shown in Table 11, a rural-
farm resident is almost three times as likely as an average urban American to lack complete
plumbing facilities.
In general, rural residents are 2 times and rural-farm residents are 2.5 times more likely to lack
plumbing than their urban counterparts.
Ethnic Distribution
In terms of ethnic distribution, Whites have higher percentages of households without adequate
plumbing in the socioeconomically marginalized areas in West Virginia, Kentucky, Montana, Alaska,
and Maine (Maps 8 and 9), and Blacks have higher percentages in Virginia, New York, Louisiana,
Alabama, North and South Carolina, Oregon and Montana (Maps 10 and 11). Hispanic households
that are affected have higher percentages in most of the New England states and in the states with
larger Latino or Spanish-speaking populations – California, Texas, and New Mexico. The most
affected AIAN communities are concentrated in the Four Corners region and in Alaska.
29
30
31
32
33
Why Are Water and Sanitation Services Important?

Several studies have documented the critical importance of water and sanitation systems. A 1996
study by the University of Texas System’s Texas-Mexico Border Health Coordination Office found
that diseases such as hepatitis A, salmonellosis, shigellosis, and tuberculosis occurred at a much
higher rate in the colonias than in the rest of the state.31 The rate of reported hepatitis A, for
example, was more than double the statewide rate. Other health problems included high rates of
gastroenteritis and problems related to water quality. Medical services are rarely available, which
compounds health problems in the colonias. For children, these problems result in slower growth
and lower educational development rates.
Improved availability of water and sanitation has been among the greatest contributors to improved
public health in industrialized countries. The eradication of the diseases mentioned above came
about because of the implementation of basic sanitation and piped water systems in urban and rural
areas. When these services are lacking, public health suffers, and with it economic growth, because ill
people are inefficient students, workers, and contributors to society. It is for this reason that
industrialized nations spent billions of dollars on water and sanitation during the development
initiatives of the 1950s, 1960s, and 1970s. Still, as is evidenced in this report, there are groups of
people who have not received the benefits of these initiatives. Clearly, one of the key steps to
eliminating persistent poverty in these areas will be improved water services. Figure 1 demonstrates
the impacts that investments in water and sanitation infrastructure can have on health.32 Those
nations with a higher percentage of the population served by safe drinking water have fewer deaths
of children under the age of five. Egypt, Pakistan, and Sudan were significant outliers in the trends.
Their situation might be explained by their substantial problems of political violence and chronic
problems with developing effective mother-child health campaigns during the 1990s.
Figure 1: Relationship Between Access to Safe Drinking Water and Child Mortality
Access to safe drinking water saves lives
31 Cited in Border Environment Research Reports (July 1996), Improving the Quality of Drinking Water in Colonias in the Ciudad Juárez–El
Paso Area, Institute for Regional Studies of the Californias, San Diego State University, San Diego, California,
http://www.scerp.org/scerp/docs/berr3.html.
32 UNICEF, State of the World’s Children 2000, United Nations, UNICEF, New York, New York, http://www.unicef.org, accessed May
2, 2004.
34
Typhoid, cholera, hepatitis A, and various other gastrointestinal maladies associated with waterborne
disease were common in U.S. cities and rural areas through the early 1900s. As municipalities seized
control of urban water systems, public health steadily improved in these areas through the first part
of the 20th century.33 It improved in rural areas with a steady increase in water and sanitation
infrastructure investment, starting in the 1930s, accelerating in the 1950s, and further increasing
substantially in the 1960s and 1970s, when government invested in basic services as part of President
Lyndon Johnson’s Great Society initiatives.34 Since 1970, the number of people living without access
to basic services and the number of waterborne disease outbreaks in rural America have steadily
declined, as investments in both infrastructure and technical assistance to help rural areas develop
water infrastructure have combined with the development of national regulations to protect
groundwater and drinking water under the Safe Drinking Water Act (SDWA) of 1973. This act was
strengthened in 1986 and amended in 1996 to provide both an ongoing process for assessing risk to
drinking water systems and processes for stakeholders to assess the feasibility of implementing new
safety rules.
It is important to recognize a major concern for those working to provide water and sanitation
infrastructure: While water infrastructure may be in place in many parts of the country, people may not be drinking
safe water. In 1999–2000, for instance, the Centers for Disease Control and Prevention reported 39
outbreaks of waterborne disease in 23 states, affecting 2,098 people. This was the highest number of
reported outbreaks since 1991–1992. The number of cases, however, should be distinguished from
their seriousness. While there were only 32 outbreaks of waterborne disease in 1993–1994 (Figure 2),
more than 400,000 people in Milwaukee, for instance, were affected by Cryptosporidiosis, the diarrheal
disease caused by a microscopic parasite Cryptosporidium parvum.35
Figure 2: Number of Reported Drinking Water Outbreaks, 1991–2000
Number of Drinking Water Outbreaks, 1991–2000
1991–92 1993–94 1995–96 1997–98 1999–00

Time Period
33 National Academy of Sciences Committee on Privatization Services, Privatization of Water Services in the United States: An Assessment of
Issues and Experience, National Academy Press, Washington, D.C., 2000.

34 Dennis Warner and Jaris S. Dajani, Water and Sewer Development in Rural America: A Study of Community Impacts, Lexington, MA:
Lexington Books, 1975.

35 Sherline H. Lee, Deborah Levy, Gunther Craun, Michael Beach, and Rebecca Calderon, Surveillance for Waterborne-Disease Outbreaks—
United States, 1999–2000, Centers for Disease Control and Prevention Morbidity and Mortality Weekly Report 51 (SS08), Surveillance
Summaries, Atlanta, November 22, 2002, pages 1–28, http://www.cdc.gov/mmwr/preview/mmwrhtml/ss5108a1.htm, accessed May
4, 2004.
35
In addition, USEPA reports that 91 percent of the total U.S. population is drinking water that meets
established health and safety standards for maximum contaminant levels. This percentage varies for
USEPA regions. It is 62 percent in the northeastern states (EPA Region 1: Connecticut, Maine,
Massachusetts, New Hampshire, Rhode Island, Vermont); 76 percent in the Mid-Atlantic states and
territories (EPA Region 2: New Jersey, New York, Puerto Rico, Virgin Islands); 83 percent for EPA
Region 10 (Alaska, Idaho, Oregon, Washington); and over 90 percent for all other regions. U.S.
Geological Survey samples of drinking water from 12 water supply systems from 1999 to 2001
found atrazine and simazine in 85 percent of all raw and finished water samples and triazine-
herbicide degradation in 60 percent of raw and finished water samples.36 Volatile organic
compounds such as methyl teri-butyl ether have been found in 9 percent of community water
systems (at higher concentrations in systems serving urban rather than rural areas).37 All these
compounds have impacts on human health if continuously ingested in large enough quantities over
time.
While drinking water is relatively safe in the United States, the number of threats to its quality is
never-ending. Increasingly, one hears stories of communities once dependent on private wells that
have had to move to a centralized supply because of pollution of well supplies or diminishing
supplies caused by development or other pressures. The number is even greater for community
wastewater issues. In response to the 2000 Census, the residents in these communities are likely to
have answered that they had complete plumbing facilities. In considering the challenge of serving
those who still do not have access to basic services, it will be important to remember those
communities that may have to be transformed from having individual wells to community water
and wastewater systems in order to protect public health and the environment. The cost to the
communities is likely to be just as great, if not greater. And in many of these communities, income
levels are not likely to be high enough to support the investment in infrastructure without assistance.
Factors Affecting People Living Without Basic Services

So how, in the richest nation on earth, do whole populations find themselves still living without
plumbing facilities?
Socioeconomic Conditions
For some populations that lack service, such as Alaska Natives, it is difficult to install and maintain
water infrastructure because of distance and climatic conditions. Sociocultural and economic factors
also are critical. Some Alaska Native villages, suffering from high unemployment and poverty, are
reluctant to put in conventional water and sanitation systems because the cost of installing and
maintaining systems in that environment would be unacceptably high. These factors explain, in part,
Alaska’s ranking as the state with the highest percentage of its population living with inadequate
access to complete plumbing services. But a range of other issues at the local level also come into
play, related to social organization and leadership, availability of technical expertise, and lack of
access to funding to support water infrastructure development. These same conditions affect access
to complete plumbing facilities in other parts of the United States where households still lack access
to water and sanitation.
36 U.S. Geological Survey, Pesticides in Selected Water Supply Reservoirs and Finished Drinking Water, 2001,
http://water.usgs.gov/nawqa/whatsnew.html, accessed December 10, 2003.

37 USGS, MTBE and other Volatile Organic Compounds—New Findings and Implications on the Quality of Source Waters Used for Drinking Water
Supplies, Reston, Virginia, USGS, 2001, http://water.usgs.gov/FS/fs10501/, accessed December 10, 2003.
36
The relationship between poverty and inadequate plumbing is clear. Of the 670,986 households
without access to complete plumbing facilities in the United States, one-third, or 222,906, had an
income in 1999 that was below the federal poverty level. Roughly the same proportions applied in a
rural-urban breakdown – 30.82 percent of all urban households lacking proper plumbing were poor,
and 37.92 percent of rural homes lacking plumbing were poor (Table 12).
Table 12. Percentage of Occupied Housing Units Lacking Complete Plumbing Facilities
With Income in 1999 Below the Federal Poverty Level
% of Units With Income Below 1999
Total
Poverty Level
U.S. – Overall 670,986 33.22
U.S. – Urban 444,019 30.82
U.S. – Rural 226,967 37.92
Nationwide, 1.79 percent of all poor households lacked plumbing, as did 1.37 percent of all urban
poor households and 3.52 percent of all rural poor households. Thus, a poor rural household is
almost 2.5 times as likely as a poor urban household in the United States to lack proper plumbing.
Of all the states, Alaska had the highest proportion: 18.85 percent of all its homes that were poor
also lacked proper plumbing. Kansas had the lowest proportion, at 0.83 percent. Taking into
account only the homes that lacked plumbing facilities, New Mexico had the highest percentage that
were also poor – 50.37 percent of its homes without plumbing were also below the federal poverty
level (Table 13).
Table 13. Percentage of Occupied Housing Units Lacking Complete Plumbing Facilities and
With Income in 1999 Below the Poverty Level, Top 10 States
State % of Units With Income Below 1999
Total
Poverty Level
New Mexico 11,905 50.37
Arizona 21,088 47.60
West Virginia 7,451 46.84
Kentucky 14,947 46.58
Mississippi 9,015 46.00
Louisiana 10,717 42.10
Alabama 11,005 41.98
Texas 54,853 39.89
Arkansas 8,327 39.59
South Dakota 1,858 39.56
We also found that owner-occupied households below the poverty level were statistically more likely
than renter-occupied households to lack access to complete plumbing facilities, probably because of
regulations that require landlords to provide basic facilities. Of the owner-occupied households
living in poverty, 2.02 percent, or 88,211 households, lacked complete plumbing facilities in 2000.
Of the renter-occupied households below the poverty level, 1.67 percent, or 134,695 households,
reported lacking these facilities (Table 14). While people living in poverty were almost 4 times more
likely not to have complete plumbing facilities than those living above the poverty level, in pure
numeric terms more households above the poverty level than below who lack complete water and
sanitation. In some cases, the explanation may be that these people have chosen to live in isolation.
37
Or, because of high home prices on the coasts, even people with incomes above the poverty level
may live in substandard housing.
Table 14 also shows that households above the poverty level were statistically less likely to have
incomplete plumbing facilities than households below the poverty level. Only 0.37 percent of
owner-occupied houses above the poverty level and 0.75 percent of renter-occupied houses above
the poverty level lacked complete facilities. The percentages demonstrate that income is a significant
variable in whether people have complete plumbing services. But the fact that the majority of people
living without complete water and sanitation facilities were not below the poverty level in 2000
indicates the importance of recognizing the geographic and social aspects of water services. Even
relatively wealthy people may lack certain services because they live in larger communities that lack
services.
Table 14. Plumbing Facilities by Household Type, 2000
Households Total Percentage
Total 105,480,101
Owner-occupied 69,816,513
Income in 1999 below poverty level 4,371,712
Complete plumbing facilities 4,283,501
Lacking complete plumbing facilities 88,211 2.02%
Income in 1999 at or above poverty level 65,444,801
Renter-occupied 35,663,588
Income in 1999 below poverty level 8,086,254
Income in 1999 at or above poverty level 27,577,334
Ruralness
A more significant finding is the relationship between ruralness and access to complete plumbing
facilities. Rural households, as has been discussed above, are more likely than urban ones to lack
access to complete plumbing facilities. Furthermore, all the counties where the percentage without
complete plumbing facilities is particularly high are non-metro—such as Star County, Texas, and
Navajo County, Arizona. As Table 1 showed, this has been the case for at least the past 50 years. By
their very nature, rural communities are hard to reach with basic services. They are also less likely to
have the human, financial, and built capital (e.g., buildings, facilities, plants) necessary for the
implementation of improved water systems. Equally important is the relationship among ruralness,
lack of proper plumbing, and level of poverty. As Table 15 shows, the more desolate (less
populated) the rural area, the more likely it is that a household that lacks proper plumbing is
also poor, by as much as 39 percent.
38
Table 15. Percentage of Rural Occupied Housing Units Lacking Complete Plumbing Facilities
With Income Below Poverty Level in 1999
Occupied Housing Units Lacking Complete Plumbing
Rural Level Percentage With Income in
Total
1999 Below Poverty Level
U.S. – Rural 226,967 37.92
U.S. – Rural – in a place 41,704 35.40
Rural – in a place of 2,500 or
9,156 29.51
more people
Rural – in a place of 1,000 to
13,288 37.45
2,500 people
Rural – in a place of fewer
19,260 36.80
than 1,000 people
Rural – not in a place 185,263 38.49
Nationally, rural communities are also more likely to be in violation of SDWA health and safety
regulations. The SDWIS 2003 Factoids demonstrate that smaller water systems are significantly
more likely to be in violation of health and safety standards. In keeping with that finding, this
analysis demonstrates that systems in violation of SDWA standards tend to be in counties where
more people lack complete plumbing facilities.
Cost and Quality of Water and Sanitation Services

An additional issue of concern is the quality of the water people are drinking. While we did not have
access to specific water quality data by locality for analysis in this report, USEPA databases on
drinking source water quality indicate that 10 percent of surface-based source water did not meet
USEPA clean water and safe drinking water standards.38 In addition, SDWIS indicates that 8.2
percent of very small to medium-size community water systems that meet the needs of populations
below 10,000 had health safety violations in 2003; these situations affected a total of 4,242,015
people.39
Because rural areas have fewer people to pay the cost of providing services, the cost of water service
is higher overall in rural than in urban areas.40 We used statistical tools to analyze the cost of water
service in areas where a relatively high percentage of the population reported lacking plumbing
services and found a weak relationship between the cost of water services and rural households
without plumbing (R2 of 0.018). Nonetheless, this relationship was significant (0.000 level).
Additional analysis shows that the cost of water services is rising at a higher rate than inflation,
especially in rural areas. Many observers are concerned that replacements or upgrades of obsolete
water systems in much of America, combined with the costs of complying with safe drinking water
standards, are likely to raise the cost of water infrastructure even more in the near future. While the
overall percentage of household income going to pay for water and sanitation services in the United
States is among the lowest in the world, there is a danger that certain portions of the population may
38 USEPA, Office of Watersheds, Oceans and Wetlands, Index of Watershed Indicators, 2004, http://www.epa.gov/iwi/;
http://www.epa.gov/safewater/data/pdfs/factoids_2003.pdf; http://www.epa.gov/safewater/data/pivottables.html, accessed May 25,
2004. There were 49,497 very small, small, and medium-size community water systems in the United States, of which 4,057 had health
safety violations in 2003.
39 USEPA Office of Groundwater and Drinking Water, Safe Drinking Water Information System (SDWIS), 2004,
http://www.epa.gov/safewater/sdwis/, accessed May 2, 2004.

40 John McCarthy, Anna Mehrotra, Stephen Gasteyer, Rahul Vaswani, and Blanca Surgeon, "The Price of Good Water: Water and
Sanitation Affordability," Rural Matters, Spring 2004, Rural Community Assistance Partnership, Washington, D.C.
39
find themselves unable to afford water services without sacrificing other basic needs, even though
water services may be available.41
Demographics
Our analysis shows that the breakdown by age of the people lacking water and sanitation services
more or less mirrors the age distribution for the general population. The elderly (age 65 years and
older) make up just over 10 percent of the people who lack plumbing services (Table 16). People
younger than 15 constitute just over 32 percent of the total population that lacks plumbing facilities.
The elderly and children are most at risk from the consequences of waterborne disease. For this
reason, it will be important to continue to track the access to services as well as the quality of water
and sanitation services specifically for these age groups.
Table 16. Population in Occupied Housing Units Lacking Complete Plumbing Facilities,
by Age Group, 2000
Population in Occupied Housing Units Lacking Complete Plumbing Facilities
Above 15 and
Below 5 years Below 15 years 65 years and above
below 65 years
Total Percentage Total Percentage Total Percentage Total Percentage
U.S. 143,117 8.01 443,291 24.80 1,019,009 57.01 181,897 10.18
Factors Influencing Trends in Access to Water and Sanitation
Socioeconomic Immigration
As documented above, people living without access to plumbing services are not evenly distributed
across ethnic groups or across geographic areas. American Indians and Alaska Natives, Hispanics,
and African Americans all disproportionately lack access to services. Similarly, the populations living
with inadequate access to services are highest in four regions—the Four Corners region of the
Southwest; the Black Belt across the southern United States; California; and the Mexican border
regions of Texas, New Mexico, and Arizona.
Of these four regions, California is the most striking because in this area the population that
reported lacking services actually increased between 1990 and 2000. At first glance, this increase
appears strange because during most of that decade California’s economy boomed, led by the dot-
com boom in Silicon Valley. We hypothesize that two factors contributed to the rise of populations
in California living without access to water services. First, the boom of the 1990s led to an increase
in housing prices that far outstripped inflation and earning power for many people in California.
This situation was exacerbated when the economy began a downturn at the end of the decade. As
the economy soured, a relatively high number of people found themselves either homeless or living
in substandard housing. The socioeconomic conditions between 1995 and 2000, for example, led
345,573 Hispanics to leave California for nearby states.42 Second, the boom did open up high
numbers of very low-paying service jobs, which attracted immigrant labor. We suspect that most of
the immigrants came from Central and South America, where weakened economies made the
agricultural and service sector jobs in California seem an attractive economic opportunity. This
41Ibid.
42The net out-migration in this period was 345,573. Actually, 505,947 Hispanics left California but 160,374 Hispanics in-migrated
from other states into California during the same period. See http://www.census.gov/population/www/cen2000/phc-t25.html,
accessed May 19, 2004.
40
relative prosperity, though, did not provide these immigrants with adequate remuneration to pay for
housing with improved services, especially in California’s inflated housing market.
The Census records show that a total of 660,076 Hispanic immigrants moved to California during
the latter half of the 1990s.43 The large majority of these immigrants presumably worked in low-
paying service sector positions. Of a total of 5,781,105 Hispanic workers above the age of 16 in
California in 2000, more than 41 percent were employed in medium-, low- and very low-paying jobs
or were unemployed (Table 17).44 In addition, 19.55 percent of the Hispanic population in California
between the ages of 18 and 64 years were below the poverty level in 1999.45
Table 17. Number of Hispanics Employed by Occupation in California, 2000
Occupation Employed
Cooks and food preparation workers; waiters and waitresses 257,683
Other food preparation and serving workers, including supervisors 100,843
Building and grounds cleaning and maintenance occupations 486,966
Secretaries and administrative assistants 92,185
Agricultural workers, including supervisors 283,245
Carpenters, painters, paperhangers, woodworkers, metal and plastic workers 266,255
Construction laborers; other construction workers and helpers 140,504
Food-processing workers 40,393
Textile, apparel, and furnishings workers 146,848
Bus drivers; driver/sales workers and truck drivers 184,004
Motor vehicle operators, except bus and truck drivers 9,374
Laborers and material movers, hand; other material moving workers, except laborers 291,749
Unemployed, with no work experience since 1995 80,340
Total 2,380,389
Tulare County, California, the poorest county in California, is an example. Tulare County is largely
agricultural and employs a high number of people as agricultural laborers. According to the Census,
more than 1,500 people in this county live without access to complete plumbing services. Onsite
observation by Public Citizen, a national nonprofit organization, revealed “communities without
running water, many issues of contaminated water from the fertilizers and pesticides used in
farming, and communities that buy their water from tanker trucks for 25 cents a gallon.”46
Housing Development
In contrast, the decrease in the numbers of people living without access to basic services in
Alabama, Louisiana, and Mississippi may be attributable to marginally better economic conditions.
With the improved economy, people began to move out of substandard housing units into
manufactured housing units, which often come with piped water units included. The number of
people living in mobile homes from 1990 to 2000 increased, on average in the three states, by 38.38
percent (Table 18). A critical issue of concern is that community or noncommunity water systems
that serve mobile home communities are more prone than other water systems to be in violation of
state and federal standards for health and the environment. Thus, while people may have access to
piped water, the water they are drinking may not be up to standards.
43 U.S. Census 2000, Migration by Race and Hispanic Origin for the Population 5 Years and Over for the United States, Regions,
States, and Puerto Rico: 2000, http://www.census.gov/population/www/cen2000/phc-t25.html, accessed May 19, 2004.
44 Advanced Query Data Finder, http://advancedquery.census.gov, accessed May 19, 2004.
45Also, more than half (52.15 percent) of all poor Hispanic residents of California are in the age group of 18 to 64 years. Source: U.S.
Census 2000, http://www.fact.finder.census.gov, accessed May 19, 2004.

46Communication between the authors and John Gibler and Sara Grusky of Public Citizen, "Water for All Campaign,” Stephen
Gasteyer, May 15, 2004.
41
Table 18. Mobile Occupied Housing Units in Alabama, Louisiana, and Mississippi, 1990–2000
Mobile Occupied Housing Units
State
2000 1990 % Change from 1990
Alabama 269,000 187,613 43.38
Louisiana 204,912 161,751 26.68
Mississippi 168,520 114,900 46.67
Clearly, these are associations, as opposed to verifiable relationships. But they do provide an insight
into some of the hypotheses that will need to be developed and tested as we try to understand
further the relationships that contribute to the access to or loss of water and sanitation service.
What Has Been and Is Being Done to Address These Issues?

The progress made since the 1950s has been the result of synergy among government investments,
community initiatives, and the assistance provided by several nongovernmental organizations. The
federal government has developed nationwide programs such as the Clean Water and Safe Drinking
Water State Revolving Funds to capitalize improvements in access to and quality of water and
sanitation services. The U.S. Department of Agriculture’s Rural Utilities Service provides a
combination of loans and grants to rural communities for the same purpose. In addition, federal
funds are available for infrastructure, including Community Development Block Grants and grants
from agencies such as the Indian Health Service – the latter obviously targeted toward American
Indians and Alaska Natives.
In addition, the federal government now funds an infrastructure of technical assistance programs
designed to aid communities in improving access to water and sanitation services, such as the Rural
Community Assistance Partnership, the National Rural Water Association, and the Environmental
Finance Centers. The USEPA also funds applied research and demonstration programs such as the
National Drinking Water Clearinghouse and the Technical Assistance Centers.
While this institutional infrastructure has made a significant difference in providing water and
sanitation services over the past 30 years, it is important that these institutions are maintained for the
future. The challenges facing water systems are increasing rather than decreasing.
Ensuring That Water Infrastructure Is Adequately Maintained

While a greater proportion of the U.S. population than ever before has access to water and
sanitation services, new threats are emerging to those services, as follows:
§ New immigrant laborer populations are moving in to work as farm laborers or in other low-paid
sectors. These populations may live in substandard conditions, lacking basic services. This risk is
high if workers continue to come into the country as undocumented workers, especially in rural
areas, leaving them open to exploitation by their employers.
§ Water infrastructure in the United States was installed over three development waves: the early
1900s, the 1930s, and the 1950s–1970s. Because of the lifespan of the materials used during each
of these building eras, infrastructure replacement for all three is likely to be needed in the next
20 years. This will be tremendously costly, at a time when government resources are scarcer than
in the past. If local communities are expected to shoulder the cost of replacement themselves,
especially in rural areas, concerns about maintaining basic infrastructure will increase.
§ New environmental conditions and elements threaten our water supply. As regulations are
developed to try to address these threats, the costs of treatment are likely to rise. Treatment
42
costs will be especially problematic for rural community water systems, because they are not
likely to have economies of scale to help them afford the treatment technology.
Even as the United States continues to provide some of the best and least costly access to basic
services in the world, new challenges are threatening those services. The combination of aging
infrastructure, new population distribution, and growing demands creates complex challenges to
overcome for ensuring that people have access to services. Indeed, in a time when both federal and
state governments claim record deficits and are cutting popular programs, communities are facing
expensive new demands for water and sanitation services. Many small, low-income communities are
looking at costs in the hundreds of thousands or even millions of dollars to repair, upgrade, or
expand water systems to meet new needs.
For example, a study by the West Central Initiative in Minnesota found that in the west central
counties of Minnesota – where the percentages of people without plumbing service are lower than
the national average – communities were increasingly faced with the challenge of repairing or
replacing aging infrastructure. The study found that these communities faced a funding gap of $813
million to upgrade infrastructure systems, many of which were initially installed in the 1930s.47
Donaldson, Minnesota, is one of those communities. With a population of only 57, a median
household income of $15,938 in 1999, and an annual city operating budget of less then $15,000, the
city was dumbfounded by the need to eliminate two serious public health hazards: untreated sewage
that was being discharged into a road ditch, and a half-dozen rundown housing structures that were
homes to vermin. The municipal storm water system, built in 1936, discharged into a highway ditch
west of town. Septic systems installed for indoor plumbing in the 1950s and 1960s let the effluent
discharge directly into the city storm water system. A high water table and tight clay soils made
drainfields very expensive, and they typically performed poorly. Although this type of system was
effective in getting the wastewater out of town, the untreated sewage draining down the highway
ditch created a public health violation. In addition to the costs of constructing a new wastewater
system, the city faced penalties and fines from the Minnesota Pollution Control Agency. The city
council also identified six properties that were in severe stages of neglect. Some had basements that
had six to eight feet of stagnant water, and others had dead animal carcasses and feces. All housed
some type of vermin. The structures had broken glass doors and windows, making it very easy for
children to gain access to the dangerous environment. Forcing the homeowners to clean up the
properties was not an option because the costs were insurmountable.
With the help of intermediaries to provide technical assistance, Donaldson has been able to contract
with an engineering firm to develop a solution that fits within the financial constraints of the
community. It also was able to secure a combination of loans and grants from state and federal
agencies, and it worked out a way to lower costs by doing some of the work itself, using local labor
and resources.48
While this case is taken from Minnesota, communities throughout the country are grappling with
similar issues. The critical point is that many communities will have to deal with such issues in the
future, even though the vast majority of U.S. residents have access to water and sanitation services.
47 West Central Initiative, West Central Initiative Infrastructure Study for West Central Minnesota Communities, 2000,
http://www.wcif.org/publications/infrastructurestudy.shtml, accessed May 24, 2004.
48 Case study taken from the Midwest Rural Community Assistance Program, New Prague, Minnesota.
43
Key Program and Policy Concerns Related to These Issues

We think of water and sanitation as a given in the United States. Yet the building and maintenance
of the infrastructure systems that make these resources available to us involve expensive
technologies and engineering expertise. More important are the resources that are managed through
social and institutional relationships.
USEPA estimates the shortfall in resources for infrastructure in the United States at between $200
billion and $500 billion over the next 20 years. Government resources will be critically important in
addressing this gap in funding. But government resources will also need to leverage private and
nonprofit resources. Ultimately, it is the communities and the counties that will incur these costs.
It would be a mistake to assume that the money needed to resolve this issue should be restricted to
resources for pipes and fittings. The provision and maintenance of water and sanitation over time
involves building the civic and social infrastructure so that communities themselves have the
capacity to make decisions about the scope and type of infrastructure that will ensure them water
and sanitation that is safe and affordable. Peter Gleick of the Pacific Institute in California, for
example, has been calling for more attention to the soft path (development of the social
infrastructure) to ensure access to adequate water and sanitation all over the world, including the
United States. He argues that advances in management and delivery of water resources of the last
two centuries have come about largely through implementing hard systems, meaning technology and
physical infrastructure that require high capital investment. Often these built and financial capital
investments have been made without regard to local desires and needs and without attention to
issues of representation and social justice.49
As a result, we have the community along Coal Run Road, outside Zanesville, Ohio, which was
systematically denied water services until recently, even though it was located next to a significant
urbanized area. The lack of water services had much more to do with social injustice than with
technology and financing.50 Similarly, the Environmental Finance Center at the University of
North Carolina at Chapel Hill documented systematic lack of access to water services by African
American neighborhoods in the middle of larger metropolitan North Carolina communities.51
Critically related to these concerns is the very serious concern about the quality of drinking water. As
cited above, USEPA has found that significant portions of the population are subjected to water
that does not meet standards of safety and quality. A good portion of community water system
violations of SDWA standards are actually administrative in nature, indicating that management
capacity is as critical as technology.
The infrastructure investments of the future must combine reinvestment in physical infrastructure
with investment in a civic infrastructure. This civic infrastructure must involve improved training of
local water operators and water boards and investment of the time and effort to build participatory
networks that can create local support for water system maintenance and source water protection. It
may involve acceptance of alternative technologies that deliver safe drinking water at lower cost. The
soft path should provide opportunities for continual improvement in access to water and sanitation
through building human and social capacity.
As a society, we have made substantial progress since the 1950s in providing our citizens with access
to water and sanitation systems. In percentage terms, the number of people without services is small,
49 Peter Gleick, The World’s Water: The Biennial Report on Freshwater Resources, Island Press, Washington, D.C., 2003.
50 James Dao, “Ohio Town’s Water at Last Runs Past a Color Line,” New York Times, February 17, 2004, page A1.
51 Personal communication between the authors and the Environmental Finance Center, University of North Carolina at Chapel Hill,
November 2003.
44
yet more than 670,000 households–close to 2 million people–still lack these very basic services.
Getting water to this population will require explicitly addressing the environmental justice issues
that are embedded in social and economic frameworks related to access to water services. In
addition, as costs of managing water systems rise, more low-income residents will be hardpressed to
pay water bills, even as the states are cutting programs that subsidize low-income residents.
Ultimately, a significant effort that draws on government and private resources is needed to address
the gap in water service and make certain it slows in the next decade.
This report shows that the lack of plumbing services is still very real for almost 2 million Americans.
While the rural-urban divide in the provision of these services has narrowed in the last decade, it
persists and is intrinsically related to the socioeconomic status of the people who lack these services.
Rural populations are still at a larger risk of lacking proper services, as infrastructure ages and
traditional funding for improvement programs is slowly being reduced. Across the United States,
in general, minority communities are affected more acutely. There are wide fluctuations across
geographic locations and areas. Some prominent areas are the Four Corners region and the
underserved parts of the Northeast and the South. Alaska stands out as a single state that needs
much improvement in infrastructure. Given Alaska’s unique condition, policy makers must pay
attention to enhancing services there that are socially acceptable, economically feasible, and
environmentally sustainable.
A closer look at the numbers within states, at the county or Census-designated place levels, provides
a clearer understanding of the reality of lack in plumbing services. The information at the substate
level, disaggregated, also allows for relative geographic comparisons within and among states and
permits a clearer comprehension of the larger nationwide picture. Our hypothesis and affirmed
assumptions are based on this examination and understanding of the numbers at the disaggregated
level, which are shown in the pages ahead and which the readers might find useful.
In the future, we hope to take this research toward a more complex analysis of the links among
social, economic, geographic, environmental, and public health variables that affect the positive
outcomes in services for traditionally and currently underserved communities. Our findings will
allow us to understand better how to enhance communities’ capacity for improving infrastructure
and services and ultimately achieving sustainable development.
The following maps and ranking tables disaggregate the population without plumbing for all states at
the county level and for the D.C., Puerto Rico, and the island areas to the Census designated place
(CDP) level.
45
46
47
48
49
States Ranked by Total Occupied Housing Units Lacking Complete Plumbing Facilities (2000)
Total
Percent of Percent change
occupied Total occupied Percent of Percent change in total
occupied in total
housing units housing units occupied occupied housing units
housing units occupied
lacking lacking housing units lacking complete
State / Territory lacking housing units
complete complete lacking complete plumbing facilities, from
complete from 1990 to
plumbing plumbing plumbing 1990 to 2000 (base
plumbing 2000 (base
facilities facilities (1990) facilities (1990) year = 1990)
facilities (2000) year = 1990)
(2000)
California 85460 0.74 57974 0.56 47.41 10.80
Puerto Rico 65640 5.20 NA NA NA NA
New York 58418 0.83 50428 0.76 15.84 6.29
Texas 54853 0.74 56844 0.94 -3.50 21.78
Florida 30134 0.48 22061 0.43 36.59 23.43
Pennsylvania 24450 0.51 26355 0.59 -7.23 6.25
Illinois 23959 0.52 21572 0.51 11.07 9.27
Arizona 21088 1.11 18352 1.34 14.91 38.90
Virginia 19550 0.72 35788 1.56 -45.37 17.77
Ohio 19407 0.44 24394 0.60 -20.44 8.76
North Carolina 19295 0.62 33192 1.32 -41.87 24.43
Georgia 17117 0.57 22921 0.97 -25.32 27.03
Michigan 16971 0.45 14687 0.43 15.55 10.71
New Jersey 16530 0.54 12914 0.46 28.00 9.66
Massachusetts 15211 0.62 9096 0.40 67.23 8.74
Kentucky 14947 0.94 33623 2.44 -55.55 15.28
Tennessee 14340 0.64 23840 1.29 -39.85 20.46
Alaska 14003 6.32 13489 7.14 3.81 17.30
Washington 12457 0.55 10128 0.54 23.00 21.31
Missouri 11923 0.54 14263 0.73 -16.41 11.90
New Mexico 11905 1.76 11898 2.19 0.06 24.92
Alabama 11005 0.63 20819 1.38 -47.14 15.28
Louisiana 10717 0.65 14318 0.95 -25.15 10.46
Wisconsin 10648 0.51 11780 0.65 -9.61 14.40
Indiana 10599 0.45 11288 0.55 -6.10 13.12
Minnesota 9581 0.51 9382 0.57 2.12 15.01
South Carolina 9521 0.62 16626 1.32 -42.73 21.92
Maryland 9033 0.46 10206 0.58 -11.49 13.26
Mississippi 9015 0.86 17625 1.93 -48.85 14.82
Arkansas 8327 0.80 13030 1.46 -36.09 17.00
Oklahoma 7546 0.56 7145 0.59 5.61 11.29
West Virginia 7451 1.01 15972 2.32 -53.35 6.96
Colorado 7243 0.44 4592 0.36 57.73 29.30
Oregon 7025 0.53 6426 0.58 9.32 20.88
Connecticut 6466 0.50 4383 0.36 47.52 5.79
Iowa 4832 0.42 5333 0.50 -9.39 7.98
Maine 4468 0.86 7477 1.61 -40.24 11.37
Kansas 4057 0.39 3695 0.39 9.80 9.86
Hawaii 3833 0.95 3365 0.94 13.91 13.18
Nevada 3638 0.48 1893 0.41 92.18 61.09
Utah 2906 0.41 2163 0.40 34.35 30.53
Montana 2776 0.77 2357 0.77 17.78 17.15
Idaho 2720 0.58 2246 0.62 21.10 30.20
Nebraska 2408 0.36 2253 0.37 6.88 10.60
New Hampshire 2254 0.47 2363 0.57 -4.61 15.42
Rhode Island 2194 0.54 1670 0.44 31.38 8.06
District of Columbia 2112 0.85 1585 0.63 33.25 -0.52
South Dakota 1858 0.64 2315 0.89 -19.74 12.05
Vermont 1481 0.62 1952 0.93 -24.13 14.23
North Dakota 1124 0.44 1558 0.65 -27.86 6.76
Delaware 1119 0.37 1160 0.47 -3.53 20.70
Wyoming 1011 0.52 897 0.53 12.71 14.67
50
States of Territories Ranked by Percent of Occupied Housing Units Lacking Complete Plumbing Facilities (2000)
Total
Percent of Total occupied Percent change in
occupied Percent of Percent change
occupied housing units total occupied
housing units occupied housing in total occupied
housing units lacking housing units lacking
lacking units lacking housing units
State / Territory lacking complete complete plumbing
complete complete from 1990 to
complete plumbing facilities, from 1990 to
plumbing plumbing facilities 2000 (base year
plumbing facilities 2000 (base year =
facilities (1990) = 1990)
facilities (2000) (1990) 1990)
(2000)
Alaska 14003 6.32 13489 7.14 3.81 17.30
New Mexico 11905 1.76 11898 2.19 0.06 24.92
Arizona 21088 1.11 18352 1.34 14.91 38.90
West Virginia 7451 1.01 15972 2.32 -53.35 6.96
Hawaii 3833 0.95 3365 0.94 13.91 13.18
Kentucky 14947 0.94 33623 2.44 -55.55 15.28
Maine 4468 0.86 7477 1.61 -40.24 11.37
Mississippi 9015 0.86 17625 1.93 -48.85 14.82
District of Columbia 2112 0.85 1585 0.63 33.25 -0.52
New York 58418 0.83 50428 0.76 15.84 6.29
Arkansas 8327 0.80 13030 1.46 -36.09 17.00
Montana 2776 0.77 2357 0.77 17.78 17.15
California 85460 0.74 57974 0.56 47.41 10.80
Texas 54853 0.74 56844 0.94 -3.50 21.78
Virginia 19550 0.72 35788 1.56 -45.37 17.77
Louisiana 10717 0.65 14318 0.95 -25.15 10.46
Tennessee 14340 0.64 23840 1.29 -39.85 20.46
South Dakota 1858 0.64 2315 0.89 -19.74 12.05
Alabama 11005 0.63 20819 1.38 -47.14 15.28
Massachusetts 15211 0.62 9096 0.40 67.23 8.74
South Carolina 9521 0.62 16626 1.32 -42.73 21.92
North Carolina 19295 0.62 33192 1.32 -41.87 24.43
Vermont 1481 0.62 1952 0.93 -24.13 14.23
Idaho 2720 0.58 2246 0.62 21.10 30.20
Georgia 17117 0.57 22921 0.97 -25.32 27.03
Oklahoma 7546 0.56 7145 0.59 5.61 11.29
Washington 12457 0.55 10128 0.54 23.00 21.31
Missouri 11923 0.54 14263 0.73 -16.41 11.90
New Jersey 16530 0.54 12914 0.46 28.00 9.66
Rhode Island 2194 0.54 1670 0.44 31.38 8.06
Oregon 7025 0.53 6426 0.58 9.32 20.88
Wyoming 1011 0.52 897 0.53 12.71 14.67
Illinois 23959 0.52 21572 0.51 11.07 9.27
Pennsylvania 24450 0.51 26355 0.59 -7.23 6.25
Wisconsin 10648 0.51 11780 0.65 -9.61 14.40
Minnesota 9581 0.51 9382 0.57 2.12 15.01
Connecticut 6466 0.50 4383 0.36 47.52 5.79
Nevada 3638 0.48 1893 0.41 92.18 61.09
Florida 30134 0.48 22061 0.43 36.59 23.43
New Hampshire 2254 0.47 2363 0.57 -4.61 15.42
Maryland 9033 0.46 10206 0.58 -11.49 13.26
Indiana 10599 0.45 11288 0.55 -6.10 13.12
Michigan 16971 0.45 14687 0.43 15.55 10.71
North Dakota 1124 0.44 1558 0.65 -27.86 6.76
Colorado 7243 0.44 4592 0.36 57.73 29.30
Ohio 19407 0.44 24394 0.60 -20.44 8.76
Iowa 4832 0.42 5333 0.50 -9.39 7.98
Utah 2906 0.41 2163 0.40 34.35 30.53
Kansas 4057 0.39 3695 0.39 9.80 9.86
Delaware 1119 0.37 1160 0.47 -3.53 20.70
Nebraska 2408 0.36 2253 0.37 6.88 10.60
51
States Ranked by Total Rural Occupied Housing Units Lacking Complete Plumbing Facilities
Total rural Total rural
Percent of rural Percent change in Percent change
occupied occupied Percent of rural
occupied total rural occupied in total rural
housing units housing units occupied housing
housing units housing units lacking occupied
lacking lacking units lacking
State / Territory lacking complete plumbing housing units
complete complete complete
complete facilities, from 1990 to from 1990 to
plumbing plumbing plumbing facilities
plumbing 2000 (base year = 2000 (base year
facilities facilities (1990)
facilities (2000) 1990) = 1990)
(2000) (1990)
Texas 15169 1.16 26028 2.23 -41.72 12.33

Arizona 13093 6.20 14007 8.65 -6.53 30.46
Alaska 12462 16.89 11564 20.17 7.77 28.71
Virginia 12128 1.66 30003 4.38 -59.58 6.88
Kentucky 11672 1.71 30921 4.84 -62.25 6.91
North Carolina 10564 0.85 27743 2.26 -61.92 0.84
New Mexico 9095 5.73 10173 7.60 -10.60 18.56
Tennessee 8222 1.04 19438 2.78 -57.70 13.70
Pennsylvania 8112 0.77 14210 1.08 -42.91 -20.16
Ohio 7355 0.79 14480 1.49 -49.21 -3.84
California 6785 1.01 8302 1.12 -18.27 -9.58
Alabama 6299 0.83 15812 2.74 -60.16 31.44
Georgia 6234 0.74 15443 1.85 -59.63 1.36
Missouri 6147 0.94 9717 1.65 -36.74 10.67
Mississippi 6109 1.15 14849 3.18 -58.86 13.65
West Virginia 5896 1.55 14925 3.55 -60.50 -9.28
Arkansas 5498 1.12 10328 2.56 -46.77 21.30
South Carolina 5476 0.93 12715 2.31 -56.93 7.45
New York 5354 0.61 7750 0.78 -30.92 -11.17
Wisconsin 4879 0.77 7115 1.20 -31.43 7.29
Michigan 4680 0.50 6137 0.64 -23.74 -3.41
Indiana 4602 0.71 7000 1.02 -34.26 -5.18
Minnesota 4367 0.82 6022 1.28 -27.48 13.00
Washington 4066 1.05 5016 1.22 -18.94 -6.05
Oklahoma 3883 0.87 4741 1.28 -18.10 21.23
Maine 3786 1.26 6562 2.63 -42.30 20.77
Louisiana 3411 0.78 8335 1.83 -59.08 -3.61
Florida 3137 0.49 5176 0.71 -39.39 -12.31
Illinois 2655 0.47 5331 0.84 -50.20 -10.72
Iowa 2508 0.57 3677 0.90 -31.79 7.30
Colorado 2423 0.97 2369 1.12 2.28 17.98
Oregon 2256 0.82 3567 1.16 -36.75 -10.64
Maryland 2176 0.82 5308 1.74 -59.01 -13.16
Montana 1873 1.18 1678 1.22 11.62 14.71
Hawaii 1634 4.55 1253 3.19 30.41 -8.62
Kansas 1589 0.55 2462 0.87 -35.46 3.23
Idaho 1581 1.03 1741 1.19 -9.19 4.74
South Dakota 1312 0.98 1984 1.59 -33.87 7.23
New Hampshire 1296 0.69 1746 0.90 -25.77 -3.25
Vermont 1215 0.83 1732 1.24 -29.85 4.93
Utah 1164 1.43 1092 1.66 6.59 23.32
Nebraska 985 0.49 1189 0.60 -17.16 0.20
Massachusetts 734 0.37 1150 0.35 -36.17 -40.43
North Dakota 675 0.61 1209 1.10 -44.17 -0.11
Wyoming 590 0.92 609 1.08 -3.12 14.55
New Jersey 488 0.30 973 0.35 -49.85 -42.05
Nevada 471 0.76 483 0.96 -2.48 22.74
Connecticut 417 0.27 813 0.33 -48.71 -36.60
Delaware 344 0.59 744 1.12 -53.76 -12.39
Rhode Island 100 0.29 233 0.47 -57.08 -30.61
52
States Ranked by Percent of Rural Occupied Housing Units Lacking Complete Plumbing Facilities
Total rural Total rural

occupied Percent of rural occupied Percent change in Percent change
housing units occupied housing units Percent of rural total rural occupied in total rural
State / Territory lacking housing units lacking occupied housing housing units lacking occupied
complete lacking complete units lacking complete plumbing housing units
plumbing complete plumbing complete facilities, from 1990 to from 1990 to
facilities plumbing facilities plumbing facilities 2000 (base year = 2000 (base year
(2000) facilities (2000) (1990) (1990) 1990) = 1990)
Alaska 12462 16.89 11564 20.17 7.77 28.71
Arizona 13093 6.20 14007 8.65 -6.53 30.46
New Mexico 9095 5.73 10173 7.60 -10.60 18.56
Hawaii 1634 4.55 1253 3.19 30.41 -8.62
Kentucky 11672 1.71 30921 4.84 -62.25 6.91
Virginia 12128 1.66 30003 4.38 -59.58 6.88
West Virginia 5896 1.55 14925 3.55 -60.50 -9.28
Utah 1164 1.43 1092 1.66 6.59 23.32
Maine 3786 1.26 6562 2.63 -42.30 20.77
Montana 1873 1.18 1678 1.22 11.62 14.71
Texas 15169 1.16 26028 2.23 -41.72 12.33
Mississippi 6109 1.15 14849 3.18 -58.86 13.65
Arkansas 5498 1.12 10328 2.56 -46.77 21.30
Washington 4066 1.05 5016 1.22 -18.94 -6.05
Tennessee 8222 1.04 19438 2.78 -57.70 13.70
Idaho 1581 1.03 1741 1.19 -9.19 4.74
California 6785 1.01 8302 1.12 -18.27 -9.58
South Dakota 1312 0.98 1984 1.59 -33.87 7.23
Colorado 2423 0.97 2369 1.12 2.28 17.98
Missouri 6147 0.94 9717 1.65 -36.74 10.67
South Carolina 5476 0.93 12715 2.31 -56.93 7.45
Wyoming 590 0.92 609 1.08 -3.12 14.55
Oklahoma 3883 0.87 4741 1.28 -18.10 21.23
North Carolina 10564 0.85 27743 2.26 -61.92 0.84
Alabama 6299 0.83 15812 2.74 -60.16 31.44
Vermont 1215 0.83 1732 1.24 -29.85 4.93
Minnesota 4367 0.82 6022 1.28 -27.48 13.00
Maryland 2176 0.82 5308 1.74 -59.01 -13.16
Oregon 2256 0.82 3567 1.16 -36.75 -10.64
Ohio 7355 0.79 14480 1.49 -49.21 -3.84
Louisiana 3411 0.78 8335 1.83 -59.08 -3.61
Pennsylvania 8112 0.77 14210 1.08 -42.91 -20.16
Wisconsin 4879 0.77 7115 1.20 -31.43 7.29
Nevada 471 0.76 483 0.96 -2.48 22.74
Georgia 6234 0.74 15443 1.85 -59.63 1.36
Indiana 4602 0.71 7000 1.02 -34.26 -5.18
New Hampshire 1296 0.69 1746 0.90 -25.77 -3.25
North Dakota 675 0.61 1209 1.10 -44.17 -0.11
New York 5354 0.61 7750 0.78 -30.92 -11.17
Delaware 344 0.59 744 1.12 -53.76 -12.39
Iowa 2508 0.57 3677 0.90 -31.79 7.30
Kansas 1589 0.55 2462 0.87 -35.46 3.23
Michigan 4680 0.50 6137 0.64 -23.74 -3.41
Florida 3137 0.49 5176 0.71 -39.39 -12.31
Nebraska 985 0.49 1189 0.60 -17.16 0.20
Illinois 2655 0.47 5331 0.84 -50.20 -10.72
Massachusetts 734 0.37 1150 0.35 -36.17 -40.43
New Jersey 488 0.30 973 0.35 -49.85 -42.05
Rhode Island 100 0.29 233 0.47 -57.08 -30.61
Connecticut 417 0.27 813 0.33 -48.71 -36.60
53
State-by-State
Analysis at County Level
55
Explanation of Terms
Abbreviation Full Term Explanation

HU Housing Unit A housing unit is defined by the U.S. Census
2000 as: “A house, an apartment, a mobile
home or trailer, a group of rooms, or a single
room occupied as separate living quarters, or
if vacant, intended for occupancy as separate
living quarters. Separate living quarters are
those in which the occupants live separately
from any other individuals in the building and
which have direct access from outside the
building or through a common hall. For
vacant units, the criteria of separateness and
direct access are applied to the intended
occupants whenever possible.” This is the
same definition which applies to all housing
units shown in the tables in this report.
OHU Occupied Housing Units This denotes all the housing units that were
occupied at the time of the census (both for
1990 and 2000 censuses).
OHULP Occupied Housing Units This denotes all the occupied housing units, at
Lacking Complete the time of the census, that lacked complete
Plumbing Facilities plumbing facilities. “Lacking complete
plumbing facilities” indicates lack of any of
the three following facilities inside the
housing unit (this the same for the 1990 and
2000 censuses):
1) Hot and cold piped water
2) Bathtub or shower
3) Flush toilet
%OHULP Percentage of Occupied This is the percentage of occupied housing
Housing Units Lacking units (i.e. as a percentage of the total
Complete Plumbing occupied housing units) that lack complete
Facilities plumbing facilities. This is calculated as:
( OHULP
OHU
) X 100 = % OHULP
ROHU Rural Occupied Housing This denotes all the rural occupied housing
Units units. The U.S. Census 2000 defines all
territories, population and housing units to be
rural which are not classified as “urban”. (For
a detailed definition of “urban”, please look at
the glossary.)
ROHULP Rural Occupied Housing This denotes all the rural occupied housing
Units Lacking Complete units, at the time of the census, that lacked
Plumbing Facilities complete plumbing facilities.
%ROHULP Percentage of Rural This is the percentage of rural occupied
Occupied Housing Units housing units (i.e. as a percentage of the total
Lacking Complete rural occupied housing units) that lack
Plumbing Facilities complete plumbing facilities. This is
calculated as:
( ROHULP
ROHU
) X 100 = % ROHULP
57
Abbreviation Full Term Explanation

OHULP with Householder below Occupied Housing Units This denotes all the occupied housing units
Poverty Level in 1999 Lacking Complete that lack complete plumbing facilities, with
Plumbing Facilities, with householder having an income in 1999 below
Householder having Income the poverty level. (For a detailed description
in 1999 below the Poverty of “poverty level” please see the definition
Level for “poverty” in the glossary.)
Percent of OHULP below poverty Percentage of Occupied This is the percentage of occupied housing
level in 1999 Housing Units Lacking units that lack complete plumbing facilities,
Complete Plumbing and having a householder with an income in
Facilities, with Householder 1999 below the poverty level. The percentage
having Income in 1999 is calculated as:
below the Poverty Level OHULP below
( OHU below poverty

level in 1999
)
poverty level in 1999
X 100 =
%OHULP below
Rural OHULP below poverty level in Rural Occupied Housing This denotes all the rural occupied housing
1999 Units Lacking Complete units that lack complete plumbing facilities,
Plumbing Facilities, with and having a householder with an income in
Householder having Income 1999 below the poverty level.
in 1999 below the Poverty
Level
Percent of Rural OHULP below Percentage of Rural This is the percentage of rural occupied
poverty level in 1999 Occupied Housing Units housing units that lack complete plumbing
Lacking Complete facilities, and having a householder with an
Plumbing Facilities, with income in 1999 below the poverty level. The
Householder having Income percentage is calculated as:
in 1999 below the Poverty
ROHULP below
Level
( ROHU below poverty
level in 1999
)
X 100 =
% ROHULP below
poverty level in
1999
Percent of population above 65 years Percentage of the This denotes the percentage of the population
in OHULP Population above 65 years that is above 65 years and is living in
living in Occupied Housing occupied housing units lacking complete
Units Lacking Complete plumbing facilities. This is calculated as:
Plumbing Facilities Population above
( 65 years in OHULP
Population above
65 years in OHU
) X 100 = % Population above
65 year
Total population in OHULP Total Population in This denotes the total number of people living
Occupied Housing Units in occupied housing units that lack complete
Lacking Complete plumbing facilities.
Plumbing Facilities
58
ALABAMA (AL)
Occupied Housing Units (OHU)

Lacking Percent of Percent of
Complete Percent of Rural Rural
Plumbing OHULP OHULP OHULP
Facilities (as % of Percent of Rural (as % of Rural (as % of
Ranking (OHULP) OHU) OHULP OHULP OHULP Rural OHU) OHULP Rural OHU)
2000 2000 2000 1990 1990 2000 2000 1990 1990
20 11005 0.63 20819 1.38 6299 0.83 15812 2.74
Alabama (AL) Occupied Housing Units (OHU)

Percent of
Lacking Rural Percent of Percent of Percent of
Complete Percent of OHULP population OHULP Rural OHULP
Plumbing OHULP (as % of above 65 below below Total
Total Facilities (as % of Rural years in poverty level poverty level population
County OHU (OHULP) OHU) OHU) OHULP in 1999 in 1999 in OHULP
Autauga 16003 82 0.51 0.59 0.76 1.74 2.71 164
Baldwin 55336 264 0.48 0.72 0.24 1.33 2.15 634
Barbour 10409 68 0.65 0.64 0.70 1.47 1.67 134
Bibb 7421 88 1.19 1.14 1.80 2.30 2.48 178
Blount 19265 103 0.53 0.52 0.83 0.92 1.08 273
Bullock 3986 27 0.68 0.95 1.07 1.33 2.01 65
Butler 8398 65 0.77 0.97 1.61 2.39 3.50 206
59

Percent of
Calhoun 45307 252 0.56 0.36 0.47 1.09 0.73 572
Chambers 14522 118 0.81 1.57 0.63 1.37 2.92 312
Cherokee 9719 49 0.50 0.50 0.74 0.00 0.00 97
Chilton 15287 88 0.58 0.42 0.57 1.24 0.62 207
Choctaw 6363 117 1.84 1.84 2.47 2.98 2.98 276
Clarke 10578 143 1.35 1.37 0.93 2.53 3.53 242
Clay 5765 80 1.39 1.39 1.24 4.46 4.46 175
Cleburne 5590 50 0.89 0.89 1.60 2.46 2.46 91
Coffee 17421 139 0.80 1.21 0.71 1.11 1.39 281
Colbert 22461 93 0.41 0.36 0.39 0.75 0.76 196
Conecuh 5792 60 1.04 1.04 1.56 2.53 2.53 142
Coosa 4682 19 0.41 0.41 0.47 1.08 1.08 27
Covington 15640 110 0.70 0.87 0.94 1.02 1.51 246
Crenshaw 5577 31 0.56 0.56 1.29 1.24 1.24 49
Cullman 30706 147 0.48 0.55 0.69 1.15 1.56 361
Dale 18878 92 0.49 0.57 0.17 0.65 0.97 256
Dallas 17841 151 0.85 1.34 0.71 1.39 2.33 340
DeKalb 25113 247 0.98 1.08 0.71 2.35 2.43 490
Elmore 22737 99 0.44 0.36 0.93 1.98 1.55 266
Escambia 14297 106 0.74 0.85 1.27 1.63 2.07 235
Etowah 41615 117 0.28 0.34 0.35 0.49 0.53 242
Fayette 7493 44 0.59 0.65 1.07 2.12 2.76 85
Franklin 12259 48 0.39 0.45 0.30 0.70 0.98 196
Geneva 10477 54 0.52 0.50 0.81 0.88 0.58 74
Greene 3931 137 3.49 3.49 4.56 6.21 6.21 346
Hale 6415 193 3.01 3.31 4.70 6.12 6.96 415
Henry 6525 85 1.30 1.30 0.88 3.69 3.69 232
Houston 35834 243 0.68 0.73 0.76 1.59 2.52 530
Jackson 21615 164 0.76 0.74 0.95 2.12 2.38 272
Jefferson 263265 1132 0.43 0.33 0.36 0.95 1.00 2622
Lamar 6468 28 0.43 0.43 0.50 1.68 1.68 47
Lauderdale 36088 177 0.49 0.57 0.59 1.06 1.61 456
Lawrence 13538 162 1.20 1.08 1.50 2.06 1.61 313
Lee 45702 257 0.56 0.89 0.82 1.08 2.21 562
Limestone 24688 141 0.57 0.49 0.47 1.62 2.08 266
Lowndes 4909 118 2.40 2.40 2.16 3.98 3.98 267
Macon 8950 187 2.09 2.16 1.83 4.03 3.69 471
Madison 109955 366 0.33 0.47 0.49 1.22 1.91 708
Marengo 8767 190 2.17 2.72 1.11 2.72 3.17 512
Marion 12697 101 0.80 0.80 0.68 1.04 1.05 192
Marshall 32547 126 0.39 0.51 0.23 0.85 1.34 193
Mobile 150179 915 0.61 0.60 0.65 1.38 0.77 2468
Monroe 9383 134 1.43 1.73 0.96 2.85 3.35 376
Montgomery 86068 520 0.60 0.87 0.48 1.65 5.39 1167
Morgan 43602 197 0.45 0.24 0.12 1.50 0.95 520
Perry 4333 96 2.22 2.22 3.71 4.70 4.70 168
Pickens 8086 104 1.29 1.29 1.39 3.15 3.15 226
Pike 11933 55 0.46 0.48 0.72 1.09 1.13 124
Randolph 8642 152 1.76 1.60 1.68 5.31 4.94 343
Russell 19741 144 0.73 1.31 0.99 1.50 3.34 339
St. Clair 24143 154 0.64 0.66 0.47 2.60 3.04 323
60

Percent of
Shelby 54631 225 0.41 0.48 0.44 1.35 0.35 500
Sumter 5708 129 2.26 2.26 1.49 3.51 3.51 232
Talladega 30674 275 0.90 1.17 1.25 2.82 3.71 577
Tallapoosa 16656 134 0.80 0.74 1.07 1.75 1.65 239
Tuscaloosa 64517 284 0.44 0.51 0.55 0.69 0.60 653
Walker 28364 150 0.53 0.54 0.44 1.38 1.49 349
Washington 6705 149 2.22 2.22 2.42 6.06 6.06 298
Wilcox 4776 179 3.75 3.75 3.66 6.65 6.65 460
Winston 10107 51 0.50 0.48 0.42 1.45 1.14 84
61
ALASKA (AK)

2000 2000 2000 1990 1990 2000 2000 1990 1990
1 14003 6.32 13489 7.14 12462 16.89 11564 20.17
Alaska (AK) Occupied Housing Units (OHU)

Percent of
Lacking Percent of Percent of OHULP Percent of
Complete Percent of Rural population below Rural OHULP
Plumbing OHULP OHULP above 65 poverty below Total
Borough/ Total Facilities (as % of (as % of years in level in poverty level population
Census Area OHU (OHULP) OHU) Rural OHU) OHULP 1999 in 1999 in OHULP
Aleutians East
Borough 526 4 0.76 0.76 NA 3.85 3.85 NA
Aleutians West
Census Area 1270 17 1.34 1.96 NA 6.25 7.41 42
Anchorage
Municipality 94822 472 0.50 3.55 0.39 1.33 7.48 1080
Bethel Census Area 4226 2091 49.48 68.63 61.47 70.16 79.94 8853
Bristol Bay Borough 490 8 1.63 1.63 NA 13.51 13.51 14
Denali Borough 785 193 24.59 24.59 15.25 36.21 36.21 374
Dillingham Census
Area 1529 285 18.64 18.64 24.72 35.09 35.09 937
Fairbanks North
Star Borough 29777 2092 7.03 17.54 3.63 15.38 45.21 3551
Haines Borough 991 157 15.84 15.84 4.71 27.17 27.17 334
62

Percent of
Juneau City and
Borough 11543 133 1.15 2.09 0.00 1.94 0.00 236
Kenai Peninsula
Borough 18438 1336 7.25 8.54 6.17 15.42 18.67 2598
Ketchikan Gateway
Borough 5399 91 1.69 2.38 0.83 2.15 0.00 164
Kodiak Island
Borough 4424 81 1.83 4.48 1.44 1.98 5.95 124
Lake and Peninsula
Borough 588 82 13.95 13.95 12.50 28.45 28.45 155
Matanuska-Susitna
Borough 20556 1708 8.31 12.30 4.33 20.41 26.85 3746
Nome Census Area 2693 883 32.79 49.11 37.20 61.99 73.08 3189
North Slope
Borough 2109 598 28.35 54.93 43.60 53.92 81.48 2070
Northwest Arctic
Borough 1780 399 22.42 38.37 20.56 45.29 55.61 1578
Prince of Wales-
Outer Ketchikan
Census Area 2262 140 6.19 6.19 10.20 16.85 16.85 258
Sitka City and
Borough 3278 46 1.40 1.43 NA 0.00 0.00 61
Skagway-Hoonah-
Angoon Census
Area 1369 144 10.52 10.52 8.23 30.91 30.91 261
Southeast Fairbanks
Census Area 2098 461 21.97 21.97 10.67 42.17 42.17 1176
Valdez-Cordova
Census Area 3884 472 12.15 12.15 13.33 36.50 36.50 881
Wade Hampton
Census Area 1602 831 51.87 51.87 48.18 69.29 69.29 3757
Wrangell-Petersburg
Census Area 2587 124 4.79 7.07 2.66 15.65 16.37 228
Yakutat City and
Borough 265 16 6.04 6.04 NA 2.94 2.94 38
Yukon-Koyukuk
Census Area 2309 1139 49.33 49.33 38.17 64.11 64.11 2850
Aleutians East
Borough 526 4 0.76 0.76 NA 3.85 3.85 NA
Aleutians West
Census Area 1270 17 1.34 1.96 NA 6.25 7.41 42
Anchorage
Municipality 94822 472 0.50 3.55 0.39 1.33 7.48 1080
Bethel Census Area 4226 2091 49.48 68.63 61.47 70.16 79.94 8853
Bristol Bay Borough 490 8 1.63 1.63 NA 13.51 13.51 14
Denali Borough 785 193 24.59 24.59 15.25 36.21 36.21 374
Dillingham Census
Area 1529 285 18.64 18.64 24.72 35.09 35.09 937
Fairbanks North
Star Borough 29777 2092 7.03 17.54 3.63 15.38 45.21 3551
Haines Borough 991 157 15.84 15.84 4.71 27.17 27.17 334
Juneau City and
Borough 11543 133 1.15 2.09 0.00 1.94 0.00 236
Kenai Peninsula
Borough 18438 1336 7.25 8.54 6.17 15.42 18.67 2598
63

Percent of
Ketchikan Gateway
Borough 5399 91 1.69 2.38 0.83 2.15 0.00 164
Kodiak Island
Borough 4424 81 1.83 4.48 1.44 1.98 5.95 124
Lake and Peninsula
Borough 588 82 13.95 13.95 12.50 28.45 28.45 155
64
ARIZONA (AZ)

2000 2000 2000 1990 1990 2000 2000 1990 1990
4 21088 1.11 18352 1.34 13093 6.20 14007 8.65
Arizona (AZ) Occupied Housing Units (OHU)

Lacking Percent of Percent of Percent of Percent of
Complete Percent of Rural population OHULP Rural OHULP
Plumbing OHULP OHULP above 65 below below Total
Total Facilities (as % of (as % of years in poverty poverty level population
County OHU (OHULP) OHU) Rural OHU) OHULP level in 1999 in 1999 in OHULP
Apache 19971 5155 25.81 33.54 34.14 43.95 50.80 16908
Cochise 43893 476 1.08 1.89 1.23 2.58 5.12 1058
Coconino 40448 2196 5.43 13.57 11.32 16.90 38.52 7251
Gila 20140 270 1.34 1.54 0.60 4.50 6.73 668
Graham 10116 191 1.89 2.97 0.53 4.73 7.23 486
Greenlee 3117 39 1.25 1.97 0.83 0.58 0.88 72
La Paz 8362 140 1.67 2.08 1.17 3.32 4.87 292
Maricopa 1132886 4992 0.44 1.06 0.22 1.44 6.46 15889
65
Arizona (AZ) Occupied Housing Units (OHU)

Mohave 62809 492 0.78 1.92 0.58 1.86 4.49 911
Navajo 30043 3427 11.41 19.07 13.81 26.62 37.03 11019
Pima 332350 1891 0.57 2.48 0.38 1.69 12.83 4994
Pinal 61364 692 1.13 2.16 0.37 3.80 7.78 1828
Santa Cruz 11809 119 1.01 1.31 0.28 1.92 1.62 398
Yavapai 70171 410 0.58 1.04 0.51 1.14 2.50 729
Yuma 53848 598 1.11 1.85 0.71 2.48 7.47 1735
66
ARKANSAS (AR)

2000 2000 2000 1990 1990 2000 2000 1990 1990
12 8327 0.80 13030 1.46 5498 1.12 10328 2.56
Arkansas (AR) Occupied Housing Units (OHU)

Lacking Percent of Percent of Percent of
Complete Percent of Percent of population OHULP Rural OHULP
Plumbing OHULP Rural OHULP above 65 below below Total
Total Facilities (as % of (as % of years in poverty level poverty level population
County OHU (OHULP) OHU) Rural OHU) OHULP in 1999 in 1999 in OHULP
Arkansas 8457 84 0.99 1.19 0.58 2.61 5.20 176
Ashley 9384 76 0.81 1.21 1.58 1.64 2.12 211
Baxter 17052 126 0.74 0.82 0.37 2.38 3.04 253
Benton 58212 317 0.54 0.76 0.43 0.92 1.52 716
Boone 13851 136 0.98 1.30 1.10 1.87 2.70 266
Bradley 4834 58 1.20 1.41 1.22 1.00 1.50 139
Calhoun 2317 16 0.69 0.69 NA 3.53 3.53 21
Carroll 10189 160 1.57 1.85 1.55 4.73 6.06 334
Chicot 5205 74 1.42 2.45 0.53 3.09 5.21 251
Clark 8912 95 1.07 1.55 0.85 3.25 5.49 155
Clay 7417 32 0.43 0.40 0.24 1.72 2.20 63
Cleburne 10190 45 0.44 0.50 0.31 0.41 0.57 81
Cleveland 3273 34 1.04 1.04 0.72 3.37 3.37 67
Columbia 9981 116 1.16 1.84 0.72 2.96 5.14 330
Conway 7967 55 0.69 0.74 0.76 2.35 3.41 164
Craighead 32301 110 0.34 0.32 0.25 0.67 0.00 196
Crawford 19702 208 1.06 1.65 0.41 1.90 2.95 465
67

Crittenden 18471 174 0.94 1.47 1.53 1.84 3.75 458
Cross 7391 54 0.73 0.56 1.02 1.06 1.94 127
Dallas 3519 53 1.51 1.88 0.53 3.54 2.51 178
Desha 5922 58 0.98 1.42 1.21 1.68 3.80 129
Drew 7337 54 0.74 1.37 1.09 1.88 3.55 187
Faulkner 31882 207 0.65 1.08 0.35 2.47 6.07 480
Franklin 6882 62 0.90 1.08 0.43 2.58 3.39 126
Fulton 4810 38 0.79 0.83 0.49 0.88 1.02 68
Garland 37813 171 0.45 0.46 0.47 1.26 1.16 323
Grant 6241 38 0.61 0.35 1.49 0.29 0.38 120
Greene 14750 53 0.36 0.57 NA 1.02 1.52 76
Hempstead 8959 77 0.86 1.10 0.72 2.17 4.02 192
Hot Spring 12004 96 0.80 0.81 0.40 3.33 3.80 207
Howard 5471 37 0.68 0.94 0.00 1.11 1.35 104
Independence 13467 114 0.85 1.02 1.50 2.30 3.27 249
Izard 5440 87 1.60 1.60 1.38 4.16 4.16 140
Jackson 6971 32 0.46 0.49 NA 1.19 0.48 73
Jefferson 30555 257 0.84 0.78 0.93 1.67 1.18 608
Johnson 8738 106 1.21 1.39 0.99 1.88 1.97 266
Lafayette 3434 56 1.63 1.63 3.56 2.91 2.91 150
Lawrence 7108 43 0.60 0.47 0.35 1.08 1.69 70
Lee 4182 67 1.60 1.77 2.01 0.91 0.88 193
Lincoln 4265 32 0.75 0.75 0.53 2.07 2.07 53
Little River 5465 85 1.56 1.45 1.56 2.10 2.10 184
Logan 8693 81 0.93 1.33 0.94 1.48 2.35 163
Lonoke 19262 119 0.62 0.73 1.07 2.43 4.06 360
Madison 5463 220 4.03 4.03 3.79 6.93 6.93 424
Marion 6776 130 1.92 1.92 1.25 6.11 6.11 269
Miller 15637 94 0.60 0.46 0.93 0.75 0.64 179
Mississippi 19349 137 0.71 0.83 1.08 1.12 1.47 293
Monroe 4105 50 1.22 1.32 1.73 3.31 3.51 119
Montgomery 3785 41 1.08 1.08 0.85 4.04 4.04 87
Nevada 3893 80 2.05 2.29 3.09 5.07 6.72 170
Newton 3500 247 7.06 7.06 6.82 12.40 12.40 509
Ouachita 11613 123 1.06 0.99 1.57 2.00 1.58 333
Perry 3989 33 0.83 0.83 NA 4.26 4.26 59
Phillips 9711 115 1.18 1.47 1.59 2.42 3.62 182
Pike 4504 30 0.67 0.67 0.45 2.46 2.46 47
Poinsett 10026 53 0.53 0.71 0.49 1.25 1.64 95
Polk 8047 92 1.14 1.50 1.41 2.42 2.91 148
Pope 20701 161 0.78 1.10 0.30 1.98 2.24 346
Prairie 3894 26 0.67 0.67 0.65 1.02 1.02 43
Pulaski 147942 699 0.47 0.40 0.38 1.25 1.54 1570
Randolph 7265 80 1.10 1.64 1.67 3.95 6.67 149
St. Francis 10043 109 1.09 0.81 0.66 2.36 2.50 253
Saline 31778 192 0.60 0.66 0.75 2.35 1.74 414
Scott 4323 35 0.81 0.74 NA 2.53 1.79 77
Searcy 3523 106 3.01 3.01 1.43 5.31 5.31 198
Sebastian 45300 199 0.44 0.45 0.34 0.46 1.41 447
Sevier 5708 58 1.02 1.52 1.30 2.99 5.65 92
Sharp 7211 70 0.97 1.20 0.70 2.63 2.97 123
Stone 4768 127 2.66 2.66 2.68 6.09 6.09 203
68

Union 17989 172 0.96 0.94 0.82 2.18 3.19 485
Van Buren 6825 103 1.51 1.51 0.90 3.95 3.95 238
Washington 60151 448 0.74 1.61 0.67 2.06 5.36 996
White 25148 191 0.76 1.20 0.67 2.01 3.32 404
Woodruff 3531 32 0.91 0.91 0.79 2.90 2.90 59
Yell 7922 81 1.02 1.26 0.90 2.26 2.91 244
69
CALIFORNIA (CA)

2000 2000 2000 1990 1990 2000 2000 1990 1990
14 85460 0.74 57974 0.56 6785 1.01 8302 1.12
California (CA) Occupied Housing Units (OHU)

Alameda 523366 3293 0.63 0.42 0.53 1.52 0.00 9978
Alpine 483 17 3.52 3.52 NA 3.66 3.66 23
Amador 12759 52 0.41 0.50 0.19 0.54 0.83 97
Butte 79566 437 0.55 1.00 0.37 1.41 3.87 973
Calaveras 16469 128 0.78 0.78 0.42 2.84 2.97 312
Colusa 6097 75 1.23 1.08 0.61 2.26 1.81 290
Contra Costa 344129 1311 0.38 0.65 0.28 1.39 4.89 4054
Del Norte 9170 74 0.81 0.88 1.42 2.28 2.67 243
70
California (CA) Occupied Housing Units (OHU)

El Dorado 58939 218 0.37 0.37 0.17 0.97 0.67 521
Fresno 252940 2294 0.91 1.06 0.58 1.97 2.36 9415
Glenn 9172 33 0.36 0.38 0.46 1.68 1.15 84
Humboldt 51238 575 1.12 2.54 0.72 2.32 6.72 1327
Imperial 39384 439 1.11 2.52 1.05 1.62 6.13 1095
Inyo 7703 79 1.03 1.27 1.29 3.28 3.30 184
Kern 208652 1507 0.72 0.90 0.48 1.66 1.95 5373
Kings 34418 193 0.56 0.95 0.75 0.74 0.00 591
Lake 23974 215 0.90 0.83 0.13 1.99 2.07 604
Lassen 9625 43 0.45 0.71 0.48 0.92 1.57 55
Los Angeles 3133774 31288 1.00 1.09 0.65 2.28 3.76 105129
Madera 36155 278 0.77 0.86 0.72 1.48 1.16 1016
Marin 100650 523 0.52 1.23 0.37 0.81 2.04 1199
Mariposa 6613 58 0.88 0.88 1.05 0.86 0.86 108
Mendocino 33266 653 1.96 3.45 0.64 4.01 7.22 1388
Merced 63815 800 1.25 0.97 0.87 3.13 1.69 3515
Modoc 3784 40 1.06 1.27 0.00 1.95 1.65 49
Mono 5137 17 0.33 0.35 0.00 2.05 4.57 35
Monterey 121236 743 0.61 0.58 0.43 1.41 0.17 3043
Napa 45402 170 0.37 0.43 0.31 0.77 0.00 502
Nevada 36894 303 0.82 1.57 0.08 2.36 4.79 671
Orange 935287 5060 0.54 0.00 0.31 1.44 0.00 20916
Placer 93382 353 0.38 0.63 0.23 0.32 0.79 1012
Plumas 9000 25 0.28 0.32 0.22 1.44 1.73 36
Riverside 506218 2516 0.50 0.82 0.35 1.24 3.51 8889
Sacramento 453602 1991 0.44 0.46 0.25 1.15 0.00 5816
San Benito 15885 120 0.76 0.63 0.51 2.66 2.92 458
San Bernardino 528594 3371 0.64 1.60 0.37 1.38 4.22 11585
San Diego 994677 6037 0.61 0.83 0.37 1.60 2.98 17369
San Francisco 329700 6803 2.06 0.00 2.11 6.28 0.00 12007
San Joaquin 181629 1173 0.65 0.94 0.41 1.58 2.23 3952
San Luis Obispo 92739 340 0.37 0.33 0.24 0.57 0.85 700
San Mateo 254103 1279 0.50 1.28 0.32 1.42 0.00 4568
Santa Barbara 136622 815 0.60 1.09 0.41 1.49 2.25 2857
Santa Clara 565863 2867 0.51 1.10 0.44 1.17 0.00 9953
Santa Cruz 91139 924 1.01 1.85 0.52 2.99 6.37 2468
Shasta 63426 274 0.43 0.79 0.52 1.18 3.60 704
Sierra 1520 31 2.04 2.04 0.00 11.92 11.92 42
Siskiyou 18556 209 1.13 1.48 0.62 2.41 3.56 392
Solano 130403 661 0.51 0.92 0.47 1.09 1.80 1946
Sonoma 172403 840 0.49 0.67 0.22 1.05 3.21 2049
Stanislaus 145146 827 0.57 0.54 0.47 1.22 0.90 2955
Sutter 27033 157 0.58 0.59 NA 1.29 2.04 555
Tehama 21013 90 0.43 0.65 0.12 1.59 2.12 196
Trinity 5587 101 1.81 1.81 1.16 3.35 3.35 170
Tulare 110385 1065 0.96 1.12 0.85 1.99 2.26 4230
Tuolumne 21004 96 0.46 0.58 0.17 1.60 2.36 177
Ventura 243234 1153 0.47 0.77 0.27 1.47 3.46 4429
Yolo 59375 241 0.41 0.37 0.39 0.60 0.00 628
Yuba 20535 185 0.90 0.75 0.83 1.80 2.40 696
71
COLORADO (CO)

2000 2000 2000 1990 1990 2000 2000 1990 1990
46 7243 0.44 4592 0.36 2423 0.97 2369 1.12
Colorado (CO) Occupied Housing Units (OHU)

Adams 128156 425 0.33 0.12 0.37 0.55 0.41 1486
Alamosa 5467 26 0.48 1.26 0.75 0.60 2.40 43
Arapahoe 190909 582 0.30 0.12 0.27 0.83 0.00 1779
Archuleta 3980 90 2.26 3.18 1.77 7.17 11.39 139
Baca 1905 14 0.73 0.73 0.85 1.99 1.99 23
Bent 2003 21 1.05 1.89 NA 1.70 1.60 38
Boulder 114680 410 0.36 1.48 0.05 0.82 3.17 821
Chaffee 6584 54 0.82 1.10 0.00 0.77 0.00 77
Cheyenne 880 0 0.00 0.00 0.00 0.00 0.00 0
Clear Creek 4019 60 1.49 1.53 NA 6.74 7.14 85
Conejos 2980 34 1.14 1.14 0.65 3.16 3.16 53
Costilla 1503 93 6.19 6.19 5.54 12.47 12.47 159
Crowley 1358 1 0.07 0.07 0.00 0.41 0.41 9
Custer 1480 94 6.35 6.35 2.10 11.11 11.11 180
Delta 11058 110 0.99 1.22 0.29 4.03 5.54 242
72
Colorado (CO) Occupied Housing Units (OHU)

Denver 239235 1377 0.58 0.00 0.42 1.27 0.00 3320
Dolores 785 28 3.57 3.57 4.35 8.26 8.26 64
Douglas 60924 128 0.21 0.30 0.35 0.57 0.00 391
Eagle 15148 84 0.55 0.80 1.46 1.48 2.55 163
Elbert 6770 33 0.49 0.49 NA 1.86 1.86 110
El Paso 192409 570 0.30 0.67 0.23 0.93 2.07 1571
Fremont 15232 111 0.73 1.61 0.53 2.33 5.25 397
Garfield 16229 37 0.23 0.15 0.29 0.80 0.00 60
Gilpin 2043 61 2.99 2.99 NA 30.26 30.26 97
Grand 5075 53 1.04 1.04 0.75 5.29 5.29 88
Gunnison 5649 36 0.64 1.15 0.77 0.00 0.00 50
Hinsdale 359 9 2.51 2.51 0.00 0.00 0.00 9
Huerfano 3082 53 1.72 2.88 1.15 5.36 9.52 110
Jackson 661 0 0.00 0.00 0.00 0.00 0.00 0
Jefferson 206067 657 0.32 0.88 0.35 0.90 1.83 1343
KIA 665 0 0.00 0.00 0.00 0.00 0.00 0
Kit Carson 2990 45 1.51 1.71 3.96 2.87 5.65 125
Lake 2977 28 0.94 2.24 NA 4.01 11.27 31
La Plata 17342 129 0.74 0.95 0.77 1.26 1.26 279
Larimer 97164 195 0.20 0.67 0.29 0.26 4.01 419
Las Animas 6173 92 1.49 2.56 1.47 2.35 5.09 218
Lincoln 2058 3 0.15 0.15 NA 0.00 0.00 NA
Logan 7551 34 0.45 0.00 0.43 0.93 0.00 84
Mesa 45823 147 0.32 0.56 0.48 0.67 0.95 229
Mineral 377 2 0.53 0.53 NA 5.13 5.13 NA
Moffat 4983 13 0.26 0.45 0.00 0.00 0.00 50
Montezuma 9201 74 0.80 1.13 0.78 2.02 2.62 146
Montrose 13043 26 0.20 0.31 0.00 0.13 0.31 82
Morgan 9539 30 0.31 0.33 0.47 0.00 0.00 86
Otero 7920 37 0.47 0.52 0.23 0.29 0.97 108
Ouray 1576 8 0.51 0.51 0.00 0.00 0.00 15
Park 5894 109 1.85 1.85 1.85 7.21 7.21 188
Phillips 1781 8 0.45 0.45 1.40 2.04 2.04 18
Pitkin 6807 49 0.72 1.03 0.00 6.87 13.97 100
Prowers 5307 20 0.38 1.02 NA 1.31 3.60 48
Pueblo 54579 276 0.51 0.78 0.50 0.64 2.86 598
Rio Blanco 2306 0 0.00 0.00 0.00 0.00 0.00 0
Rio Grande 4701 24 0.51 0.82 0.60 1.07 2.09 70
Routt 7953 38 0.48 0.67 0.00 1.11 2.76 45
Saguache 2300 63 2.74 2.74 2.24 5.70 5.70 155
San Juan 269 6 2.23 2.23 0.00 7.14 7.14 9
San Miguel 3015 51 1.69 1.69 NA 2.80 2.80 92
Sedgwick 1165 2 0.17 0.17 0.00 0.00 0.00 NA
Summit 9120 39 0.43 1.24 0.00 0.00 0.00 70
Teller 7993 52 0.65 1.09 1.02 1.16 1.80 107
Washington 1989 17 0.85 0.85 1.60 1.96 1.96 39
Weld 63247 368 0.58 0.54 0.26 1.38 0.86 1233
Yuma 3800 7 0.18 0.27 NA 0.00 0.00 11
73
CONNECTICUT (CT)

2000 2000 2000 1990 1990 2000 2000 1990 1990
38 6466 0.50 4383 0.36 417 0.27 813 0.33

Fairfield 324232 1557 0.48 0.43 0.34 1.28 2.83 4573
Hartford 335098 2012 0.60 0.11 0.39 1.97 0.00 5440
Litchfield 71551 208 0.29 0.33 0.44 1.62 2.28 392
Middlesex 61341 166 0.27 0.12 0.20 0.75 0.00 351
New Haven 319040 1862 0.58 0.16 0.42 1.67 5.33 4473
New London 99835 360 0.36 0.36 0.26 1.19 0.00 1030
Tolland 49431 109 0.22 0.27 0.08 0.56 1.40 186
Windham 41142 192 0.47 0.29 0.19 1.04 0.61 566
74
DELAWARE (DE)

2000 2000 2000 1990 1990 2000 2000 1990 1990
51 1119 0.37 1160 0.47 344 0.59 744 1.12

Kent 47224 147 0.31 0.60 0.36 1.06 2.41 321
New Castle 188935 605 0.32 0.19 0.29 0.86 0.00 1395
Sussex 62577 367 0.59 0.71 0.49 1.06 0.87 814
75
DISTRICT OF COLUMBIA (DC)

2000 2000 2000 1990 1990 2000 2000 1990 1990
10 2112 0.85 1585 0.63 0 0.00 0 0.00

Complete Percent Rural population OHULP Rural OHULP
Plumbing of OHULP OHULP above 65 below below Total
District of Columbia 248338 2112 0.85 0.00 0.55 1.73 0.00 5508
76
FLORIDA (FL)

2000 2000 2000 1990 1990 2000 2000 1990 1990
40 30134 0.48 22061 0.43 3137 0.49 5176 0.71
Florida (FL) Occupied Housing Units (OHU)

Alachua 87509 387 0.44 0.49 0.48 0.90 1.34 934
Baker 7043 45 0.64 0.78 0.99 3.19 3.97 142
Bay 59597 154 0.26 0.42 0.19 0.85 0.71 287
Bradford 8497 77 0.91 0.80 1.63 2.57 2.05 152
Brevard 198195 590 0.30 0.61 0.26 0.66 1.05 1367
Broward 654445 2617 0.40 0.00 0.27 0.92 0.00 7350
Calhoun 4468 51 1.14 1.08 1.27 1.33 1.25 108
Charlotte 63864 144 0.23 0.38 0.14 0.35 0.00 270
77

Citrus 52634 132 0.25 0.30 0.22 1.04 1.24 392
Clay 50243 130 0.26 0.14 0.25 1.40 0.90 396
Collier 102973 545 0.53 0.77 0.24 2.80 3.27 1480
Columbia 20925 55 0.26 0.08 0.28 0.90 0.11 95
DeSoto 10746 42 0.39 0.54 0.55 0.86 1.24 103
Dixie 5205 47 0.90 0.85 0.00 1.88 1.26 89
Duval 303747 1429 0.47 0.38 0.49 1.06 1.36 3088
Escambia 111049 435 0.39 0.38 0.44 0.77 0.52 957
Flagler 21294 31 0.15 0.24 0.05 0.13 0.33 75
Franklin 4096 20 0.49 0.70 NA 1.84 2.88 26
Gadsden 15867 200 1.26 1.41 1.39 2.99 4.50 564
Gilchrist 5021 14 0.28 0.28 0.96 0.51 0.51 32
Glades 3852 15 0.39 0.36 0.40 0.73 1.03 33
Gulf 4931 12 0.24 0.38 NA 0.46 0.69 13
Hamilton 4161 27 0.65 0.63 NA 1.46 1.26 57
Hardee 8166 57 0.70 0.58 0.20 1.13 1.74 282
Hendry 10850 81 0.75 1.05 0.27 1.04 0.00 298
Hernando 55425 141 0.25 0.29 0.19 0.31 0.00 335
Highlands 37471 108 0.29 0.25 0.15 0.95 1.05 307
Hillsborough 391357 1924 0.49 0.52 0.34 1.14 0.73 5468
Holmes 6921 54 0.78 0.83 1.52 2.34 2.51 70
Indian River 49137 108 0.22 0.51 0.15 0.52 4.43 262
Jackson 16620 132 0.79 0.71 0.63 2.25 2.31 217
Jefferson 4695 29 0.62 0.62 1.75 1.09 1.09 111
Lafayette 2142 12 0.56 0.56 NA 2.69 2.69 34
Lake 88413 279 0.32 0.37 0.18 0.71 0.52 660
Lee 188599 743 0.39 0.52 0.19 1.09 2.53 2091
Leon 96521 336 0.35 0.47 0.32 0.81 2.97 712
Levy 13867 98 0.71 0.71 0.88 1.75 1.75 251
Liberty 2222 14 0.63 0.63 0.00 0.46 0.46 46
Madison 6629 113 1.70 1.18 3.51 2.66 1.24 298
Manatee 112460 284 0.25 0.23 0.10 0.75 0.00 704
Marion 106755 305 0.29 0.35 0.26 0.76 0.77 718
Martin 55288 151 0.27 0.33 0.15 0.21 0.00 395
Miami-Dade 776774 7948 1.02 1.15 1.00 1.84 5.63 23598
Monroe 35086 279 0.80 1.07 0.65 2.31 3.27 551
Nassau 21980 101 0.46 0.40 0.22 1.36 2.03 288
Okaloosa 66269 235 0.35 0.60 0.28 1.50 2.17 595
Okeechobee 12593 101 0.80 0.30 0.48 1.98 0.00 211
Orange 336286 1896 0.56 0.79 0.48 1.22 5.29 5474
Osceola 60977 257 0.42 0.33 0.17 1.09 1.76 819
Palm Beach 474175 2140 0.45 0.44 0.26 1.27 3.72 5514
Pasco 147566 345 0.23 0.47 0.25 0.34 1.00 836
Pinellas 414968 1232 0.30 0.00 0.23 0.75 0.00 2540
Polk 187233 656 0.35 0.31 0.15 0.98 0.79 1867
Putnam 27839 148 0.53 0.60 0.32 1.21 1.46 380
St. Johns 49614 95 0.19 0.25 0.25 0.37 0.00 249
St. Lucie 76933 382 0.50 0.57 0.46 1.59 0.00 973
Santa Rosa 43793 136 0.31 0.45 0.41 1.22 1.48 297
Sarasota 149937 410 0.27 0.15 0.24 0.58 0.00 912
Seminole 139572 495 0.35 1.08 0.41 0.41 0.00 1167
Sumter 20779 84 0.40 0.47 0.27 0.87 0.35 158
78

Suwannee 13460 102 0.76 0.77 0.53 2.28 2.42 267
Taylor 7176 80 1.11 0.65 1.84 1.75 0.00 191
Union 3367 12 0.36 0.24 0.00 1.55 1.92 29
Volusia 184723 580 0.31 0.33 0.24 0.84 2.30 1605
Wakulla 8450 65 0.77 0.77 NA 2.40 2.40 194
Walton 16548 106 0.64 0.51 0.72 1.32 1.11 159
Washington 7931 81 1.02 0.99 0.78 2.00 1.90 189
79
GEORGIA (GA)

2000 2000 2000 1990 1990 2000 2000 1990 1990
26 17117 0.57 22921 0.97 6234 0.74 15443 1.85
Georgia (GA) Occupied Housing Units (OHU)

Percent of
Lacking Percent of Percent of OHULP
Complete Percent of Rural population below Percent of
Plumbing OHULP OHULP above 65 poverty Rural OHULP Total
Total Facilities (as % of (as % of years in level in below poverty population
County OHU (OHULP) OHU) Rural OHU) OHULP 1999 level in 1999 in OHULP
Appling 6606 24 0.36 0.52 0.50 0.16 0.25 67
Atkinson 2717 35 1.29 1.29 0.99 3.32 3.32 129
Bacon 3833 5 0.13 0.18 0.00 0.00 0.00 10
Baker 1514 13 0.86 0.86 1.45 0.00 0.00 66
Baldwin 14758 89 0.60 1.05 0.39 0.86 2.33 186
Banks 5364 43 0.80 0.85 1.33 2.18 2.32 107
80

Percent of
Barrow 16354 109 0.67 0.39 0.86 1.21 1.33 268
Bartow 27176 97 0.36 0.35 0.62 1.08 1.03 260
Ben Hill 6673 37 0.55 0.85 NA 0.81 2.89 114
Berrien 6261 4 0.06 0.09 NA 0.00 0.00 22
Bibb 59667 319 0.53 0.18 0.35 1.11 0.90 832
Bleckley 4372 48 1.10 1.77 1.10 0.87 2.28 148
Brantley 5436 29 0.53 0.43 0.57 0.91 0.23 59
Brooks 6155 75 1.22 1.34 0.63 2.18 2.38 203
Bryan 8089 33 0.41 0.68 0.43 1.01 1.55 88
Bulloch 20743 81 0.39 0.47 0.36 0.36 0.61 263
Burke 7934 111 1.40 1.45 3.22 4.41 5.17 225
Butts 6455 75 1.16 1.03 1.92 4.31 1.83 218
Calhoun 1962 24 1.22 1.22 NA 2.92 2.92 47
Camden 14705 91 0.62 0.74 1.14 1.14 1.84 215
Candler 3375 33 0.98 1.00 1.35 0.00 0.00 69
Carroll 31568 138 0.44 0.47 0.78 1.19 2.30 323
Catoosa 20425 16 0.08 0.00 0.00 0.77 0.00 83
Charlton 3342 30 0.90 0.31 0.00 0.56 0.00 119
Chatham 89865 510 0.57 0.21 0.57 1.32 1.01 1508
Chattahoochee 2932 27 0.92 1.28 0.00 3.74 5.29 51
Chattooga 9577 38 0.40 0.67 0.32 1.55 2.79 61
Cherokee 49495 203 0.41 0.73 0.65 2.50 5.84 556
Clarke 39706 175 0.44 0.48 0.42 0.59 1.90 468
Clay 1347 23 1.71 1.71 NA 1.65 1.65 36
Clayton 82243 306 0.37 0.00 NA 0.73 0.00 1141
Clinch 2512 27 1.07 0.62 2.80 1.88 2.47 70
Cobb 227487 763 0.34 0.00 0.47 0.90 0.00 1820
Coffee 13354 89 0.67 0.59 1.50 2.39 2.33 212
Colquitt 15495 109 0.70 0.45 0.21 1.83 2.13 169
Columbia 31120 132 0.42 0.51 0.89 1.74 1.72 395
Cook 5882 58 0.99 0.77 0.47 2.14 2.27 133
Coweta 31442 191 0.61 0.71 0.31 1.51 4.57 441
Crawford 4461 27 0.61 0.61 1.07 2.48 2.48 60
Crisp 8337 72 0.86 0.74 1.65 2.01 1.72 160
Dade 5633 82 1.46 1.37 0.58 4.81 5.42 135
Dawson 6069 0 0.00 0.00 0.00 0.00 0.00 0
Decatur 10380 66 0.64 0.92 0.89 2.35 3.56 173
DeKalb 249339 1161 0.47 0.00 0.31 0.77 0.00 3282
Dodge 7062 111 1.57 1.72 1.26 1.82 2.30 261
Dooly 3909 34 0.87 0.78 1.94 1.02 0.88 99
Dougherty 35552 330 0.93 0.55 1.34 1.84 0.00 1045
Douglas 32822 78 0.24 0.09 0.00 0.61 0.00 183
Early 4695 71 1.51 1.27 1.01 3.86 3.45 295
Echols 1264 0 0.00 0.00 0.00 0.00 0.00 0
Effingham 13151 115 0.87 1.03 1.30 4.80 5.42 443
Elbert 8004 60 0.75 0.81 0.82 2.43 3.98 148
Emanuel 8045 72 0.89 1.19 NA 2.23 3.15 160
Evans 3778 22 0.58 0.74 NA 0.31 0.19 47
Fannin 8369 43 0.51 0.51 0.55 1.43 1.43 73
Fayette 31524 121 0.38 0.60 NA 0.00 0.00 346
Floyd 34028 171 0.50 0.45 0.67 1.44 1.36 355
Forsyth 34565 129 0.37 0.46 0.37 0.51 0.00 440
81

Percent of
Franklin 7888 24 0.30 0.34 0.87 0.00 0.00 76
Fulton 321242 1967 0.61 0.61 0.54 1.54 0.00 5317
Gilmer 9071 57 0.63 0.56 1.53 2.12 2.20 122
Glascock 1004 9 0.90 0.90 NA 0.00 0.00 23
Glynn 27208 200 0.74 0.58 0.38 1.07 0.00 396
Gordon 16173 87 0.54 0.59 0.64 0.34 0.21 184
Grady 8797 36 0.41 0.55 0.41 0.99 2.26 66
Greene 5477 58 1.06 1.12 1.28 2.95 3.44 164
Gwinnett 202317 646 0.32 1.06 0.28 0.86 0.00 2304
Habersham 13259 68 0.51 0.42 0.53 1.17 1.54 226
Hall 47381 255 0.54 0.31 0.59 1.33 1.29 881
Hancock 3237 103 3.18 3.51 4.27 4.48 5.52 230
Haralson 9826 63 0.64 0.54 0.51 1.21 0.92 139
Harris 8822 79 0.90 0.93 1.44 3.30 3.37 183
Hart 9106 61 0.67 0.56 0.00 0.50 0.00 134
Heard 4043 47 1.16 1.16 1.52 3.19 3.19 81
Henry 41373 105 0.25 0.11 0.50 1.41 1.50 315
Houston 40911 95 0.23 0.50 0.17 0.33 1.38 341
Irwin 3644 18 0.49 0.23 0.98 1.46 1.73 18
Jackson 15057 91 0.60 0.58 1.38 1.00 1.16 241
Jasper 4175 53 1.27 1.27 1.30 2.64 2.64 237
Jeff Davis 4828 41 0.85 1.02 0.00 0.62 1.05 92
Jefferson 6339 83 1.31 1.41 2.05 2.47 3.06 150
Jenkins 3214 44 1.37 1.43 0.72 2.56 4.56 67
Johnson 3130 42 1.34 1.34 1.81 2.36 2.36 67
Jones 8659 19 0.22 0.07 0.69 0.97 0.43 63
Lamar 5712 50 0.88 0.79 2.10 2.53 0.00 114
Lanier 2593 12 0.46 0.49 NA 1.13 1.13 29
Laurens 17083 138 0.81 1.09 0.93 1.35 1.49 293
Lee 8229 92 1.12 1.58 2.32 3.07 5.74 284
Liberty 19383 155 0.80 1.33 2.06 3.04 5.13 363
Lincoln 3251 68 2.09 2.09 NA 5.63 5.63 152
Long 3574 29 0.81 0.90 5.17 0.75 0.87 54
Lowndes 32654 143 0.44 0.29 0.26 0.80 0.59 298
Lumpkin 7537 54 0.72 0.72 0.72 0.56 0.00 101
McDuffie 7970 114 1.43 0.43 0.65 3.50 1.24 261
McIntosh 4202 57 1.36 1.45 1.29 4.13 5.60 113
Macon 4834 68 1.41 1.32 1.37 1.77 1.78 188
Madison 9800 58 0.59 0.52 1.18 1.11 1.16 250
Marion 2668 28 1.05 1.05 1.67 2.27 2.27 82
Meriwether 8248 112 1.36 1.55 0.50 3.52 4.36 236
Miller 2487 19 0.76 0.76 1.12 1.85 1.85 19
Mitchell 8063 89 1.10 0.71 1.29 1.67 0.99 315
Monroe 7719 91 1.18 1.04 1.71 4.98 7.09 183
Montgomery 2919 33 1.13 1.15 0.92 1.80 1.82 89
Morgan 5558 50 0.90 1.19 1.83 1.98 3.08 93
Murray 13286 75 0.56 0.58 0.89 0.16 0.23 146
Muscogee 69819 326 0.47 0.00 0.45 0.76 0.00 876
Newton 21997 173 0.79 0.90 1.35 1.05 1.99 491
Oconee 9051 25 0.28 0.26 0.89 1.75 4.42 38
Oglethorpe 4849 66 1.36 1.36 1.71 3.52 3.52 144
82

Percent of
Paulding 28089 65 0.23 0.37 0.41 1.41 1.91 163
Peach 8436 55 0.65 0.74 1.18 0.49 0.00 95
Pickens 8960 37 0.41 0.37 0.49 1.49 2.29 64
Pierce 5958 7 0.12 0.15 0.00 0.62 0.93 11
Pike 4755 56 1.18 1.18 1.17 3.89 3.89 141
Polk 14012 104 0.74 0.82 1.21 1.00 1.26 207
Pulaski 3407 66 1.94 0.68 0.94 1.77 2.24 209
Putnam 7402 66 0.89 0.67 1.02 1.70 0.00 195
Quitman 1047 9 0.86 0.75 0.00 1.68 0.00 16
Rabun 6279 63 1.00 1.00 1.53 2.96 2.96 107
Randolph 2909 43 1.48 1.62 0.88 1.07 2.43 152
Richmond 73920 415 0.56 0.99 0.47 1.01 2.32 1080
Rockdale 24052 88 0.37 0.69 0.15 1.19 3.40 265
Schley 1435 9 0.63 0.63 1.90 3.13 3.13 16
Screven 5797 43 0.74 0.92 0.44 1.02 1.21 61
Seminole 3573 48 1.34 1.23 0.58 1.40 2.33 163
Spalding 21519 201 0.93 0.59 0.67 2.95 1.48 455
Stephens 9951 33 0.33 0.43 0.43 1.08 2.41 57
Stewart 2007 72 3.59 3.59 4.66 6.58 6.58 139
Sumter 12025 90 0.75 0.67 0.28 1.97 1.92 264
Talbot 2538 50 1.97 1.97 1.39 3.14 3.14 92
Taliaferro 870 24 2.76 2.76 4.95 3.24 3.24 27
Tattnall 7057 80 1.13 0.80 0.65 3.29 2.26 250
Taylor 3281 25 0.76 0.76 0.72 2.38 2.38 47
Telfair 4140 38 0.92 0.74 1.87 1.72 1.89 60
Terrell 4002 82 2.05 2.69 1.63 1.36 1.85 249
Thomas 16309 93 0.57 0.59 0.29 1.05 0.69 247
Tift 13919 64 0.46 0.26 0.32 0.88 0.00 241
Toombs 9877 79 0.80 0.69 0.84 3.31 3.38 179
Towns 3998 2 0.05 0.05 0.00 0.37 0.37 NA
Treutlen 2531 11 0.43 0.76 0.93 1.60 3.55 14
Troup 21920 190 0.87 0.72 1.00 1.62 3.62 425
Turner 3435 46 1.34 1.42 1.23 4.39 4.84 277
Twiggs 3832 80 2.09 2.09 3.07 6.78 6.78 144
Union 7159 54 0.75 0.75 0.59 2.11 2.11 57
Upson 10722 94 0.88 0.90 0.95 1.53 3.29 185
Walker 23605 163 0.69 1.11 0.88 2.53 3.09 390
Walton 21307 173 0.81 0.68 0.60 1.46 1.87 441
Ware 13475 51 0.38 0.42 0.22 0.80 3.21 69
Warren 2435 29 1.19 1.19 NA 1.35 1.35 68
Washington 7435 173 2.33 2.75 2.91 6.47 9.58 385
Wayne 9324 80 0.86 0.88 1.62 1.13 0.94 227
Webster 911 15 1.65 1.65 2.56 5.29 5.29 36
Wheeler 2011 21 1.04 1.04 NA 3.36 3.36 36
White 7731 22 0.28 0.28 0.00 0.93 0.93 47
Whitfield 29385 103 0.35 0.30 0.54 0.38 0.00 237
Wilcox 2785 52 1.87 1.87 1.68 3.19 3.19 136
Wilkes 4314 64 1.48 1.90 0.61 3.40 5.83 149
Wilkinson 3827 42 1.10 1.10 2.15 2.08 2.08 115
Worth 8106 96 1.18 0.60 0.84 4.63 2.42 186
83
HAWAII (HI)

2000 2000 2000 1990 1990 2000 2000 1990 1990
6 3833 0.95 3365 0.94 1634 4.55 1253 3.19

Lacking Percent of
Complete Percent of Percent of Percent of OHULP Percent of
Plumbing OHULP Rural OHULP population below Rural OHULP Total
Total Facilities (as % of (as % of above 65 years poverty level below poverty population
County OHU (OHULP) OHU) Rural OHU) in OHULP in 1999 level in 1999 in OHULP
Hawaii 52985 1450 2.74 5.53 0.97 7.52 13.54 3069
Honolulu 286450 1760 0.61 2.67 0.47 1.70 12.63 5083
Kalawao 115 0 0.00 0.00 NA 0.00 0.00 NA
Kauai 20183 178 0.88 1.86 0.34 2.25 3.84 546
Maui 43507 445 1.02 3.98 0.88 3.99 16.84 1148
84
IDAHO (ID)

2000 2000 2000 1990 1990 2000 2000 1990 1990
25 2720 0.58 2246 0.62 1581 1.03 1741 1.19
Idaho (ID) Occupied Housing Units (OHU)

Ada 113408 465 0.41 0.49 0.23 0.90 2.31 1129
Adams 1421 17 1.20 1.20 NA 0.00 0.00 40
Bannock 27192 81 0.30 0.91 NA 0.69 3.66 164
Bear Lake 2259 22 0.97 1.02 0.00 0.00 0.00 48
Benewah 3580 99 2.77 4.13 1.92 6.69 9.71 208
Bingham 13317 47 0.35 0.43 NA 0.45 0.88 120
Blaine 7780 12 0.15 0.08 0.00 1.75 0.00 10
Boise 2616 48 1.83 1.83 NA 5.92 5.92 89
85
Idaho (ID) Occupied Housing Units (OHU)

Bonner 14693 454 3.09 3.92 1.21 8.52 11.23 982
Bonneville 28753 123 0.43 0.61 0.10 1.46 2.24 351
Boundary 3707 91 2.45 3.46 1.59 7.85 13.11 158
Butte 1089 3 0.28 0.28 NA 0.00 0.00 NA
Camas 396 4 1.01 1.01 0.00 5.00 5.00 13
Canyon 45018 163 0.36 0.49 0.25 0.77 1.16 403
Caribou 2560 14 0.55 0.54 NA 2.29 0.00 22
Cassia 7060 43 0.61 0.67 1.50 2.00 5.34 174
Clark 340 1 0.29 0.29 0.00 0.00 0.00 NA
Clearwater 3456 34 0.98 1.44 NA 1.16 0.75 86
Custer 1770 23 1.30 1.30 NA 1.56 1.56 39
Elmore 9092 30 0.33 1.23 1.86 0.34 1.01 81
Franklin 3476 15 0.43 0.13 0.00 0.00 0.00 30
Fremont 3885 44 1.13 1.23 NA 5.80 5.67 155
Gem 5539 23 0.42 0.20 0.63 0.65 1.87 66
Gooding 5046 12 0.24 0.33 0.00 0.00 0.00 21
Idaho 6084 88 1.45 1.84 0.69 2.03 2.55 149
Jefferson 5901 35 0.59 0.66 0.57 1.93 1.67 145
Jerome 6298 35 0.56 0.41 0.50 1.24 0.00 111
Kootenai 41308 155 0.38 0.56 0.23 0.59 1.01 362
Latah 13059 88 0.67 0.92 1.25 0.86 3.50 158
Lemhi 3275 16 0.49 0.41 0.54 1.20 2.56 32
Lewis 1554 2 0.13 0.13 0.00 0.00 0.00 NA
Lincoln 1447 5 0.35 0.35 NA 1.76 1.76 32
Madison 7129 22 0.31 0.17 0.00 0.00 0.00 53
Minidoka 6973 56 0.80 0.90 0.89 1.68 2.48 164
Nez Perce 15286 40 0.26 0.69 0.17 0.68 4.80 64
Oneida 1430 6 0.42 0.42 0.00 0.00 0.00 NA
Owyhee 3710 28 0.75 0.68 NA 2.57 2.18 155
Payette 7371 60 0.81 1.35 1.58 0.00 0.00 146
Power 2560 7 0.27 0.63 0.00 0.52 1.47 22
Shoshone 5906 36 0.61 0.76 0.62 1.48 2.08 52
Teton 2078 20 0.96 0.96 NA 1.44 1.44 22
Twin Falls 23853 130 0.55 0.67 0.75 0.85 1.39 312
Valley 3208 12 0.37 0.37 NA 0.97 0.97 36
Washington 3762 11 0.29 0.24 NA 0.00 0.00 20
86
ILLINOIS (IL)

2000 2000 2000 1990 1990 2000 2000 1990 1990
34 23959 0.52 21572 0.51 2655 0.47 5331 0.84
Illinois (IL) Occupied Housing Units (OHU)

Adams 26860 107 0.40 0.53 0.44 1.22 1.71 181
Alexander 3808 57 1.50 1.52 1.32 1.25 0.66 147
Bond 6155 35 0.57 0.68 0.50 1.09 0.00 100
Boone 14597 32 0.22 0.35 0.00 0.91 0.00 70
Brown 2108 30 1.42 2.61 1.22 2.83 6.82 44
Bureau 14182 19 0.13 0.15 0.51 0.40 0.68 64
Calhoun 2046 39 1.91 1.91 1.74 8.56 8.56 63
Carroll 6794 24 0.35 0.46 0.64 0.00 0.00 72
Cass 5347 22 0.41 0.46 0.71 0.00 0.00 39
87

Champaign 70597 214 0.30 0.54 0.18 0.42 0.00 457
Christian 13921 64 0.46 0.23 0.74 0.28 0.83 132
Clark 6971 45 0.65 0.82 1.31 0.00 0.00 83
Clay 5839 24 0.41 0.63 0.32 1.41 2.21 50
Clinton 12754 20 0.16 0.04 0.23 0.00 0.00 50
Coles 21043 90 0.43 0.39 0.55 0.29 1.51 146
Cook 1974181 14546 0.74 0.00 0.46 1.87 0.00 44315
Crawford 7842 14 0.18 0.29 0.56 0.81 1.41 29
Cumberland 4368 35 0.80 0.80 1.02 4.04 4.04 57
DeKalb 31674 106 0.33 0.14 0.22 0.38 0.29 461
De Witt 6770 22 0.32 0.41 0.40 0.35 1.02 43
Douglas 7574 24 0.32 0.37 0.27 0.55 0.78 35
DuPage 325601 968 0.30 0.00 0.28 0.44 0.00 2990
Edgar 7874 60 0.76 0.77 1.53 1.09 2.63 98
Edwards 2905 6 0.21 0.21 NA 0.70 0.70 13
Effingham 13001 89 0.68 0.95 0.86 1.74 2.26 174
Fayette 8146 43 0.53 0.69 0.53 1.93 2.22 55
Ford 5639 16 0.28 0.69 0.84 1.19 3.13 32
Franklin 16408 116 0.71 0.89 0.67 1.12 1.43 206
Fulton 14877 88 0.59 0.53 0.35 1.20 1.54 159
Gallatin 2726 17 0.62 0.62 NA 0.70 0.70 21
Greene 5757 20 0.35 0.33 NA 0.26 0.46 37
Grundy 14293 34 0.24 0.21 0.44 0.24 0.80 70
Hamilton 3462 20 0.58 0.90 1.02 2.51 4.90 30
Hancock 8069 33 0.41 0.58 0.62 2.22 3.11 51
Hardin 1987 42 2.11 2.11 2.80 3.67 3.67 116
Henderson 3365 18 0.53 0.45 0.54 2.44 2.45 34
Henry 20056 44 0.22 0.22 0.28 0.00 0.00 80
Iroquois 12220 35 0.29 0.28 0.27 0.49 0.83 96
Jackson 24215 134 0.55 0.59 0.36 0.98 2.48 224
Jasper 3930 13 0.33 0.51 1.12 3.52 6.10 18
Jefferson 15374 107 0.70 0.94 1.63 2.39 4.22 202
Jersey 8096 42 0.52 0.42 0.35 1.79 1.63 102
Jo Daviess 9218 23 0.25 0.30 0.65 0.28 0.41 36
Johnson 4183 47 1.12 1.13 1.36 2.95 2.97 117
Kane 133901 704 0.53 0.25 0.31 1.31 0.00 2383
Kankakee 38182 147 0.38 0.59 0.50 1.14 2.04 301
Kendall 18798 47 0.25 0.00 0.72 0.00 0.00 159
Knox 22056 60 0.27 0.58 0.30 0.43 0.66 105
Lake 216297 775 0.36 0.08 0.25 1.36 2.17 3054
La Salle 43417 134 0.31 0.30 0.29 0.50 1.03 364
Lawrence 6309 41 0.65 0.93 0.68 1.05 0.56 121
Lee 13253 14 0.11 0.13 NA 0.30 0.86 27
Livingston 14374 39 0.27 0.54 0.35 0.00 0.00 74
Logan 11113 27 0.24 0.28 NA 0.00 0.00 66
McDonough 12360 66 0.53 0.75 NA 0.79 1.66 357
McHenry 89403 183 0.20 0.24 0.25 1.61 4.59 427
McLean 56746 106 0.19 0.18 0.29 0.26 1.62 263
Macon 46561 148 0.32 0.37 0.20 0.72 1.98 295
Macoupin 19253 65 0.34 0.55 0.33 0.52 0.99 151
Madison 101953 376 0.37 0.29 0.43 0.69 1.73 1008
Marion 16619 82 0.49 0.87 0.67 0.70 2.16 157
88

Marshall 5225 25 0.48 0.40 0.72 6.02 6.22 34
Mason 6389 37 0.58 0.54 0.78 2.16 2.27 80
Massac 6261 58 0.93 0.73 1.05 3.21 1.50 105
Menard 4873 12 0.25 0.34 0.00 0.00 0.00 34
Mercer 6624 16 0.24 0.31 0.27 0.00 0.00 18
Monroe 10275 42 0.41 0.37 0.36 0.00 0.00 131
Montgomery 11507 55 0.48 0.31 0.83 2.16 1.63 115
Morgan 14039 70 0.50 1.01 0.61 1.36 3.51 143
Moultrie 5405 17 0.31 0.31 NA 1.16 2.09 21
Ogle 19278 121 0.63 0.60 0.70 1.97 0.00 279
Peoria 72733 221 0.30 0.24 0.27 1.18 2.16 508
Perry 8504 45 0.53 0.74 0.96 0.25 0.71 112
Piatt 6475 9 0.14 0.21 NA 0.00 0.00 18
Pike 6876 59 0.86 0.98 0.78 1.91 1.28 128
Pope 1769 11 0.62 0.62 1.24 0.77 0.77 11
Pulaski 2893 24 0.83 0.83 2.20 1.51 1.51 42
Putnam 2415 2 0.08 0.08 0.00 0.00 0.00 NA
Randolph 12084 73 0.60 1.11 1.01 1.95 4.85 131
Richland 6660 26 0.39 0.63 0.88 0.34 1.28 37
Rock Island 60712 215 0.35 0.03 0.33 0.83 0.00 454
St. Clair 96810 329 0.34 0.14 0.35 1.07 0.65 915
Saline 10992 80 0.73 0.98 0.20 1.80 2.39 136
Sangamon 78722 228 0.29 0.21 0.26 0.60 0.89 389
Schuyler 2975 27 0.91 0.95 2.33 5.69 3.93 83
Scott 2222 0 0.00 0.00 0.00 0.00 0.00 0
Shelby 9056 40 0.44 0.57 0.79 1.89 2.64 66
Stark 2525 20 0.79 0.79 1.65 4.13 4.13 39
Stephenson 19785 72 0.36 0.38 0.28 0.00 0.00 163
Tazewell 50327 75 0.15 0.10 0.04 0.42 0.00 162
Union 7290 47 0.64 0.98 0.42 1.26 2.12 107
Vermilion 33406 134 0.40 0.42 0.42 1.29 2.22 299
Wabash 5192 30 0.58 1.18 1.22 1.22 4.55 70
Warren 7166 25 0.35 0.50 NA 0.31 0.88 41
Washington 5848 21 0.36 0.46 0.68 2.02 2.59 35
Wayne 7143 45 0.63 0.70 0.65 0.63 1.01 93
White 6534 20 0.31 0.32 0.58 1.08 0.47 29
Whiteside 23684 140 0.59 0.49 0.75 1.29 1.93 246
Will 167542 318 0.19 0.31 0.19 0.20 0.00 806
Williamson 25358 112 0.44 0.53 0.51 0.81 2.80 206
Winnebago 107980 430 0.40 0.09 0.34 1.38 0.00 962
Woodford 12797 30 0.23 0.28 0.28 0.53 0.79 57
89
INDIANA (IN)

2000 2000 2000 1990 1990 2000 2000 1990 1990
43 10599 0.45 11288 0.55 4602 0.71 7000 1.02
Indiana (IN) Occupied Housing Units (OHU)

Adams 11818 675 5.71 11.31 2.96 20.88 45.43 4027
Allen 128745 691 0.54 2.46 0.38 0.78 10.17 2625
Bartholomew 27936 99 0.35 0.67 0.68 0.76 3.85 186
Benton 3558 42 1.18 1.18 1.57 11.44 11.44 82
Blackford 5690 22 0.39 0.33 0.34 1.50 0.88 20
Boone 17081 62 0.36 0.28 0.48 0.21 0.51 134
Brown 5897 50 0.85 0.85 0.76 3.90 3.90 178
Carroll 7718 69 0.89 1.13 0.87 3.87 5.41 287
Cass 15715 72 0.46 0.69 0.90 0.00 0.00 134
90

Clark 38751 146 0.38 0.78 0.28 1.31 5.23 294
Clay 10216 46 0.45 0.44 0.27 1.07 0.00 96
Clinton 12545 54 0.43 0.37 NA 0.00 0.00 95
Crawford 4181 59 1.41 1.41 2.22 3.61 3.61 109
Daviess 10894 84 0.77 0.93 0.33 1.93 3.80 232
Dearborn 16832 59 0.35 0.58 0.74 1.38 3.28 139
Decatur 9389 44 0.47 0.47 0.72 1.21 0.56 67
DeKalb 15134 91 0.60 0.88 0.42 2.51 4.56 219
DE 47131 118 0.25 0.24 0.22 0.33 0.00 259
Dubois 14813 52 0.35 0.43 0.50 0.89 2.34 96
Elkhart 66154 227 0.34 0.36 0.33 1.07 1.62 564
Fayette 10199 73 0.72 1.10 0.00 1.42 3.93 207
Floyd 27511 124 0.45 0.58 0.48 1.04 0.00 280
Fountain 7041 61 0.87 1.11 1.72 1.79 2.86 165
Franklin 7868 69 0.88 1.05 1.20 2.20 3.00 135
Fulton 8082 38 0.47 0.76 0.76 1.31 2.46 107
Gibson 12847 33 0.26 0.38 0.19 0.80 0.48 92
Grant 28319 95 0.34 0.25 0.44 0.43 0.40 189
Greene 13372 91 0.68 0.94 0.58 0.39 0.79 171
Hamilton 65933 197 0.30 0.65 0.45 0.94 4.26 499
Hancock 20718 17 0.08 0.04 0.00 0.00 0.00 36
Harrison 12917 67 0.52 0.53 1.63 1.73 2.23 119
Hendricks 37275 105 0.28 0.23 0.53 0.00 0.00 183
Henry 19486 54 0.28 0.14 0.21 0.33 0.00 116
Howard 34800 94 0.27 0.15 0.35 0.64 0.00 162
Huntington 14242 15 0.11 0.07 0.26 0.35 1.01 25
Jackson 16052 73 0.45 0.56 0.34 0.14 0.42 193
Jasper 10686 8 0.07 0.03 0.00 0.70 0.00 21
Jay 8405 114 1.36 1.99 0.97 4.39 8.48 591
Jefferson 12148 69 0.57 0.58 0.26 1.32 3.20 139
Jennings 10134 57 0.56 0.91 0.83 0.65 1.55 75
Johnson 42434 101 0.24 0.57 0.25 0.00 0.00 259
Knox 15552 49 0.32 0.34 0.66 0.64 0.92 99
Kosciusko 27283 99 0.36 0.38 0.64 0.00 0.00 282
LaGrange 11225 102 0.91 0.94 1.05 4.51 5.15 349
Lake 181633 775 0.43 0.20 0.39 1.19 0.00 2129
LaPorte 41050 186 0.45 0.51 0.41 1.39 2.13 376
Lawrence 18535 108 0.58 0.60 0.52 1.32 2.29 231
Madison 53052 170 0.32 0.49 0.66 0.61 0.44 336
Marion 352164 1366 0.39 0.00 0.41 0.87 0.00 3000
Marshall 16519 59 0.36 0.32 0.14 0.00 0.00 143
Martin 4183 49 1.17 1.38 0.63 4.73 7.42 119
Miami 13716 67 0.49 0.46 0.38 1.03 0.56 173
Monroe 46898 235 0.50 0.62 0.64 1.37 3.04 401
Montgomery 14595 69 0.47 0.57 0.68 0.76 1.97 201
Morgan 24437 109 0.45 0.51 0.49 0.99 2.19 260
Newton 5340 12 0.22 0.23 0.57 0.63 0.63 16
Noble 16696 106 0.63 0.49 0.69 1.16 0.33 213
Ohio 2201 9 0.41 0.41 0.96 0.00 0.00 7
Orange 7621 136 1.78 2.04 1.21 5.95 7.58 437
Owen 8282 96 1.16 1.16 0.27 3.07 3.07 249
Parke 6415 68 1.06 1.35 1.48 5.28 7.13 205
91

Perry 7270 48 0.66 0.97 1.15 0.80 2.33 86
Pike 5119 25 0.49 0.52 0.38 1.51 2.24 52
Porter 54649 182 0.33 0.17 0.21 0.76 0.00 445
Posey 10205 50 0.49 0.73 0.90 0.90 1.78 89
Pulaski 5170 37 0.72 0.66 0.92 0.00 0.00 104
Putnam 12374 55 0.44 0.35 0.46 0.19 0.30 109
Randolph 10937 67 0.61 0.43 NA 1.52 0.88 129
Ripley 9842 35 0.36 0.38 0.73 1.74 1.30 86
Rush 6923 54 0.78 0.72 0.72 0.99 0.00 129
St. Joseph 100743 345 0.34 0.41 0.18 0.94 0.00 866
Scott 8832 52 0.59 0.52 0.58 2.72 5.90 93
Shelby 16561 76 0.46 0.63 0.46 1.22 2.73 187
Spencer 7569 18 0.24 0.24 0.53 0.76 0.76 23
Starke 8740 59 0.68 0.40 0.76 0.95 1.57 133
Steuben 12738 54 0.42 0.54 NA 1.85 1.83 256
Sullivan 7819 66 0.84 0.89 0.38 1.21 0.00 206
Switzerland 3435 69 2.01 2.01 NA 10.14 10.14 242
Tippecanoe 55226 161 0.29 0.30 0.67 0.36 0.00 302
Tipton 6469 13 0.20 0.33 0.00 0.00 0.00 29
Union 2793 18 0.64 0.64 1.79 2.58 2.58 29
Vanderburgh 70623 198 0.28 0.14 0.27 0.26 0.00 420
Vermillion 6762 48 0.71 0.75 0.70 3.53 2.67 95
Vigo 40998 227 0.55 0.84 0.78 0.57 0.73 496
Wabash 13215 44 0.33 0.21 0.00 0.73 2.35 94
Warren 3219 7 0.22 0.22 0.00 0.00 0.00 21
Warrick 19438 29 0.15 0.41 0.27 0.74 2.53 49
Washington 10264 141 1.37 1.84 1.11 5.00 7.01 541
Wayne 28469 117 0.41 0.24 0.35 0.80 1.77 163
Wells 10402 17 0.16 0.34 0.23 0.00 0.00 67
White 9727 25 0.26 0.10 NA 0.00 0.00 95
Whitley 11711 75 0.64 0.69 NA 2.24 3.88 215
92
IOWA (IA)

2000 2000 2000 1990 1990 2000 2000 1990 1990
48 4832 0.42 5333 0.50 2508 0.57 3677 0.90
Iowa (IA) Occupied Housing Units (OHU)

Adair 3398 13 0.38 0.38 1.39 0.63 0.63 27
Adams 1867 4 0.21 0.21 0.00 1.09 1.09 NA
Allamakee 5722 20 0.35 0.33 0.33 2.19 1.49 45
Appanoose 5779 49 0.85 1.12 0.98 2.08 2.95 69
Audubon 2773 5 0.18 0.18 NA 0.00 0.00 14
Benton 9746 74 0.76 0.62 0.41 0.00 0.00 164
Black Hawk 49683 146 0.29 0.12 0.42 0.74 0.00 414
Boone 10374 19 0.18 0.12 0.32 1.03 0.77 39
Bremer 8860 11 0.12 0.18 NA 0.00 0.00 21
Buchanan 7933 164 2.07 2.97 1.05 8.36 11.50 989
Buena Vista 7499 27 0.36 0.37 NA 0.77 1.59 48
93

Butler 6175 29 0.47 0.47 0.77 1.68 1.68 68
Calhoun 4513 22 0.49 0.49 NA 0.00 0.00 33
Carroll 8486 33 0.39 0.48 0.71 0.81 0.00 82
Cass 6120 26 0.42 0.66 0.59 2.17 3.18 43
Cedar 7147 56 0.78 0.77 0.82 4.79 6.05 106
Cerro Gordo 19374 45 0.23 0.32 0.18 0.55 0.40 70
Cherokee 5378 47 0.87 0.19 NA 2.44 0.00 98
Chickasaw 5192 14 0.27 0.37 0.60 0.00 0.00 29
Clarke 3584 20 0.56 1.10 0.49 1.02 1.92 49
Clay 7259 38 0.52 0.51 0.00 1.48 1.25 138
Clayton 7375 47 0.64 0.67 0.74 1.76 1.88 165
Clinton 20105 115 0.57 0.43 0.53 1.22 0.97 254
Crawford 6441 19 0.29 0.41 0.67 1.76 1.98 54
Dallas 15584 78 0.50 0.70 0.56 0.00 0.00 157
Davis 3207 59 1.84 1.84 1.65 5.79 5.79 144
Decatur 3337 46 1.38 1.38 0.50 1.13 1.13 177
Delaware 6834 28 0.41 0.61 NA 0.48 0.84 112
Des Moines 17270 35 0.20 0.26 0.53 0.41 0.00 92
Dickinson 7103 28 0.39 0.24 NA 0.98 1.94 51
Dubuque 33690 142 0.42 0.27 0.51 0.72 0.00 194
Emmet 4450 2 0.04 0.11 NA 0.00 0.00 NA
Fayette 8778 24 0.27 0.30 0.80 0.66 1.03 39
Floyd 6828 37 0.54 0.88 0.72 2.67 4.12 75
Franklin 4356 12 0.28 0.43 NA 1.18 2.26 35
Fremont 3199 30 0.94 0.94 1.53 5.19 5.19 50
Greene 4205 26 0.62 0.34 0.78 1.51 0.88 38
Grundy 4984 20 0.40 0.40 0.36 0.00 0.00 35
Guthrie 4641 7 0.15 0.15 0.33 0.24 0.24 16
Hamilton 6692 10 0.15 0.30 0.29 0.89 2.13 10
Hancock 4795 14 0.29 0.40 0.45 0.00 0.00 27
Hardin 7628 26 0.34 0.47 0.75 1.01 1.55 43
Harrison 6115 30 0.49 0.62 0.36 1.09 1.31 43
Henry 7626 32 0.42 0.69 0.66 2.60 4.88 54
Howard 3974 60 1.51 2.21 0.72 8.17 8.80 148
Humboldt 4295 25 0.58 0.34 0.39 0.00 0.00 42
Ida 3213 9 0.28 0.28 NA 2.31 2.31 18
Iowa 6163 20 0.32 0.32 0.50 0.00 0.00 28
Jackson 8078 63 0.78 1.54 0.34 0.99 2.18 170
Jasper 14689 52 0.35 0.25 0.62 0.39 0.41 96
Jefferson 6649 46 0.69 0.68 0.59 0.90 4.17 92
Johnson 44080 257 0.58 0.77 0.19 1.25 2.36 479
Jones 7560 21 0.28 0.48 NA 0.91 1.53 42
Keokuk 4586 34 0.74 0.74 0.74 0.84 0.84 60
Kossuth 6974 29 0.42 0.38 0.72 1.88 1.60 95
Lee 15161 59 0.39 0.51 0.62 0.76 0.00 92
Linn 76753 227 0.30 0.30 0.42 0.87 0.00 413
Louisa 4519 47 1.04 1.04 1.99 4.69 4.69 115
Lucas 3811 47 1.23 2.12 NA 3.25 7.77 247
Lyon 4428 19 0.43 0.43 1.65 0.54 0.54 52
Madison 5326 25 0.47 0.47 0.52 2.11 4.27 38
Mahaska 8880 44 0.50 0.85 1.01 1.30 2.14 112
Marion 12017 62 0.52 0.74 0.72 2.39 4.36 143
94

Marshall 15338 102 0.67 0.86 0.70 3.18 7.06 229
Mills 5324 8 0.15 0.23 NA 0.73 1.18 8
Mitchell 4294 54 1.26 1.92 1.10 7.11 11.07 244
Monona 4211 36 0.85 0.87 1.31 1.32 1.78 45
Monroe 3228 4 0.12 0.24 0.00 0.00 0.00 NA
Montgomery 4886 33 0.68 0.45 0.37 1.14 0.00 52
Muscatine 15847 63 0.40 0.38 0.22 1.85 3.18 173
O'Brien 6001 23 0.38 0.34 0.56 0.00 0.00 32
Osceola 2778 5 0.18 0.30 0.57 2.29 3.31 7
Page 6708 25 0.37 0.65 NA 0.24 1.32 62
Palo Alto 4119 3 0.07 0.11 NA 0.00 0.00 17
Plymouth 9372 23 0.25 0.28 NA 0.00 0.00 51
Pocahontas 3617 15 0.41 0.41 NA 2.51 2.51 30
Polk 149112 486 0.33 0.18 0.32 1.08 0.00 1289
Pottawattamie 33844 116 0.34 0.41 0.21 0.59 0.00 206
Poweshiek 7398 36 0.49 0.61 0.40 0.43 0.00 68
Ringgold 2245 35 1.56 1.56 3.15 7.85 7.85 99
Sac 4746 11 0.23 0.23 0.00 1.43 1.43 21
Scott 62334 164 0.26 0.35 0.17 0.76 2.54 279
Shelby 5173 26 0.50 0.49 0.49 0.00 0.00 70
Sioux 10693 30 0.28 0.50 0.83 0.27 0.47 71
Story 29383 68 0.23 0.29 0.14 0.40 0.00 202
Tama 7018 45 0.64 0.89 1.24 0.87 1.28 106
Taylor 2824 35 1.24 1.24 2.44 2.87 2.87 84
Union 5242 18 0.34 0.92 NA 0.97 2.93 31
Van Buren 3181 68 2.14 2.14 1.45 9.47 9.47 276
Wapello 14784 51 0.34 0.37 0.27 1.05 0.52 110
Warren 14708 33 0.22 0.36 0.24 0.00 0.00 69
Washington 8056 25 0.31 0.36 0.43 2.24 1.99 142
Wayne 2821 30 1.06 1.06 1.36 4.60 4.60 50
Webster 15878 47 0.30 0.21 0.19 0.99 0.57 77
Winnebago 4749 6 0.13 0.00 NA 1.57 0.00 NA
Winneshiek 7734 76 0.98 1.48 1.71 3.14 5.16 151
Woodbury 39151 133 0.34 0.48 0.26 1.00 1.37 448
Worth 3278 3 0.09 0.09 0.00 0.00 0.00 NA
Wright 5940 21 0.35 0.60 0.25 1.56 2.66 59
95
KANSAS (KS)

2000 2000 2000 1990 1990 2000 2000 1990 1990
50 4057 0.39 3695 0.39 1589 0.55 2462 0.87
Kansas (KS) Occupied Housing Units (OHU)

Allen 5775 37 0.64 0.60 1.22 2.10 3.13 51
Anderson 3221 45 1.40 2.55 0.99 2.15 4.09 92
Atchison 6275 24 0.38 0.30 0.33 0.12 0.63 57
Barber 2235 10 0.45 0.45 NA 0.84 0.84 24
Barton 11393 57 0.50 0.72 0.80 1.67 1.31 169
Bourbon 6161 36 0.58 0.98 0.47 0.94 0.00 53
Brown 4318 16 0.37 0.32 0.00 2.59 2.02 26
Butler 21527 61 0.28 0.44 0.28 0.00 0.00 179
Chase 1246 8 0.64 0.64 NA 2.46 2.46 10
Chautauqua 1796 20 1.11 1.11 1.17 1.72 1.72 49
Cherokee 8875 49 0.55 0.81 0.28 2.32 3.72 84
96

Cheyenne 1360 11 0.81 0.81 NA 5.11 5.11 27
Clark 979 4 0.41 0.41 NA 0.00 0.00 NA
Clay 3617 2 0.06 0.12 NA 0.00 0.00 NA
Cloud 4163 17 0.41 0.11 0.61 2.08 1.20 14
Coffey 3489 28 0.80 1.00 1.58 0.00 0.00 53
Comanche 872 1 0.11 0.11 0.00 0.00 0.00 NA
Cowley 14039 69 0.49 0.60 0.43 0.75 1.97 185
Crawford 15504 95 0.61 0.62 0.43 1.19 1.95 174
Decatur 1494 2 0.13 0.13 0.00 1.32 1.32 15
Dickinson 7903 38 0.48 0.64 0.55 0.00 0.00 76
Doniphan 3173 17 0.54 0.61 NA 1.36 1.66 23
Douglas 38486 109 0.28 0.40 0.37 0.41 7.53 230
Edwards 1455 4 0.27 0.27 0.00 2.65 2.65 NA
Elk 1412 12 0.85 0.85 NA 3.26 3.26 24
Ellis 11193 20 0.18 0.44 0.22 0.00 0.00 36
Ellsworth 2481 9 0.36 0.59 NA 0.94 1.59 15
Finney 12948 86 0.66 0.94 0.67 1.27 6.79 330
Ford 10852 61 0.56 0.85 0.29 1.39 3.97 227
Franklin 9452 71 0.75 1.12 0.76 2.03 4.36 132
Geary 10458 39 0.37 0.00 0.00 0.57 0.00 74
Gove 1245 4 0.32 0.32 NA 0.00 0.00 NA
Graham 1263 8 0.63 0.63 NA 1.32 1.32 12
Grant 2742 0 0.00 0.00 0.00 0.00 0.00 0
Gray 2045 6 0.29 0.29 0.00 0.00 0.00 22
Greeley 602 2 0.33 0.33 NA 0.00 0.00 NA
Greenwood 3234 31 0.96 1.37 0.81 2.91 5.86 59
Hamilton 1054 12 1.14 1.14 0.00 2.82 2.82 25
Harper 2773 6 0.22 0.22 0.59 0.00 0.00 16
Harvey 12581 24 0.19 0.27 0.00 1.06 4.44 83
Haskell 1481 15 1.01 1.01 4.93 0.00 0.00 40
Hodgeman 796 12 1.51 1.51 NA 3.03 3.03 36
Jackson 4727 21 0.44 0.62 1.26 0.50 0.81 39
Jefferson 6830 35 0.51 0.51 0.59 1.54 1.54 80
Jewell 1695 2 0.12 0.12 0.00 0.00 0.00 NA
Johnson 174570 471 0.27 0.22 0.20 0.62 0.00 1255
Kearny 1542 11 0.71 0.71 NA 0.62 0.62 39
Kingman 3371 21 0.62 0.34 0.66 0.00 0.00 32
KIA 1365 4 0.29 0.29 NA 1.31 1.31 8
Labette 9194 34 0.37 0.74 0.77 0.84 1.93 58
Lane 910 4 0.44 0.44 0.00 2.47 2.47 NA
Leavenworth 23071 94 0.41 0.40 0.46 1.33 2.20 226
Lincoln 1529 4 0.26 0.26 0.00 2.53 2.53 7
Linn 3807 28 0.74 0.74 0.00 2.07 2.07 46
Logan 1243 0 0.00 0.00 0.00 0.00 0.00 0
Lyon 13691 94 0.69 0.46 0.70 1.33 0.00 162
McPherson 11205 24 0.21 0.09 0.00 0.67 0.00 44
Marion 5114 24 0.47 0.47 NA 1.17 0.00 37
Marshall 4458 6 0.13 0.19 NA 0.00 0.00 9
Meade 1728 6 0.35 0.35 NA 1.31 1.31 11
Miami 10365 91 0.88 1.25 0.81 3.47 8.16 197
Mitchell 2850 13 0.46 0.96 0.80 0.70 1.50 11
Montgomery 14903 45 0.30 0.39 0.29 1.18 0.30 71
97

Morris 2539 4 0.16 0.16 NA 0.00 0.00 12
Morton 1306 16 1.23 1.23 NA 6.11 6.11 25
Nemaha 3959 23 0.58 0.58 0.37 0.49 0.49 40
Neosho 6739 55 0.82 1.31 0.68 0.98 3.02 92
Ness 1516 0 0.00 0.00 0.00 0.00 0.00 0
Norton 2266 12 0.53 0.65 NA 1.73 3.70 12
Osage 6490 33 0.51 0.51 NA 0.33 0.33 110
Osborne 1940 10 0.52 0.52 0.68 1.28 1.28 9
Ottawa 2430 16 0.66 0.66 1.37 1.30 1.30 61
Pawnee 2739 11 0.40 0.32 NA 1.34 5.45 19
Phillips 2496 16 0.64 1.18 0.68 0.79 1.61 29
Pottawatomie 6771 8 0.12 0.15 NA 0.31 0.42 17
Pratt 3963 21 0.53 0.77 1.18 0.49 2.41 35
Rawlins 1269 6 0.47 0.47 NA 2.47 2.47 10
Reno 25498 147 0.58 0.34 0.66 1.45 1.65 271
Republic 2557 10 0.39 0.39 NA 2.37 2.37 12
Rice 4050 16 0.40 0.33 0.66 0.44 1.23 37
Riley 22137 60 0.27 0.09 0.00 0.19 0.00 131
Rooks 2362 13 0.55 0.55 0.00 0.00 0.00 18
Rush 1548 16 1.03 1.03 NA 5.06 5.06 19
Russell 3207 22 0.69 1.01 0.78 0.00 0.00 31
Saline 21436 25 0.12 0.41 0.13 0.00 0.00 45
Scott 2045 0 0.00 0.00 0.00 0.00 0.00 0
Sedgwick 176444 568 0.32 0.21 0.23 0.55 1.26 1460
Seward 7419 23 0.31 0.88 0.52 0.00 0.00 61
Shawnee 68920 216 0.31 0.24 0.28 0.56 0.00 533
Sheridan 1124 18 1.60 1.60 2.10 2.07 2.07 24
Sherman 2758 6 0.22 0.86 NA 0.00 0.00 NA
Smith 1953 21 1.08 1.08 0.88 0.00 0.00 29
Stafford 2010 2 0.10 0.10 0.00 0.85 0.85 NA
Stanton 858 11 1.28 1.28 5.63 0.00 0.00 17
Stevens 1988 18 0.91 1.33 2.34 0.00 0.00 31
Sumner 9888 39 0.39 0.46 0.27 1.20 2.35 82
Thomas 3226 8 0.25 0.00 0.00 0.00 0.00 7
Trego 1412 8 0.57 0.57 0.00 4.60 4.60 40
Wabaunsee 2633 32 1.22 1.22 1.31 5.10 5.10 55
Wallace 674 0 0.00 0.00 0.00 0.00 0.00 0
Washington 2673 40 1.50 1.50 2.28 2.80 2.80 82
Wichita 967 7 0.72 0.72 0.00 3.48 3.48 23
Wilson 4203 31 0.74 0.92 0.59 1.98 2.96 57
Woodson 1642 8 0.49 0.49 NA 1.06 1.06 NA
Wyandotte 59700 251 0.42 0.39 0.44 0.70 4.76 763
98
KENTUCKY (KY)

2000 2000 2000 1990 1990 2000 2000 1990 1990
7 14947 0.94 33623 2.44 11672 1.71 30921 4.84
Kentucky (KY) Occupied Housing Units (OHU)

Adair 6747 138 2.05 2.75 3.29 4.96 7.20 398
Allen 6910 163 2.36 2.82 1.87 6.43 9.82 574
Anderson 7320 43 0.59 1.25 0.47 2.66 5.85 137
Ballard 3395 16 0.47 0.47 0.65 0.41 0.41 34
Barren 15346 143 0.93 1.34 1.17 3.50 6.80 600
Bath 4445 93 2.09 2.09 2.65 4.98 4.98 216
Bell 12004 159 1.32 2.06 2.39 2.39 3.42 252
Boone 31258 136 0.44 0.85 0.30 1.55 6.40 308
Bourbon 7681 20 0.26 0.40 NA 0.44 1.33 31
Boyd 20010 104 0.52 0.39 0.61 1.10 0.00 257
Boyle 10574 78 0.74 1.15 0.54 1.58 4.14 204
Bracken 3228 61 1.89 1.89 3.91 2.58 2.58 140
Breathitt 6170 245 3.97 4.60 4.09 8.12 9.83 585
Breckinridge 7324 112 1.53 1.53 2.77 2.66 2.66 267
99

Bullitt 22171 140 0.63 1.48 0.21 2.77 6.67 322
Butler 5059 51 1.01 1.01 1.02 1.68 1.68 124
Caldwell 5431 47 0.87 1.39 1.13 3.41 7.85 80
Calloway 13862 70 0.50 0.55 0.23 1.01 1.21 119
Campbell 34742 96 0.28 1.03 0.38 1.08 4.18 229
Carlisle 2208 2 0.09 0.09 NA 0.00 0.00 NA
Carroll 3940 24 0.61 1.08 1.08 1.90 5.03 28
Carter 10342 180 1.74 2.00 1.57 3.25 4.00 416
Casey 6260 217 3.47 3.47 2.41 8.17 8.17 550
Christian 24857 205 0.82 1.81 0.44 2.99 9.62 702
Clark 13015 55 0.42 0.83 0.89 0.41 1.88 110
Clay 8556 253 2.96 3.48 5.03 5.60 6.50 489
Clinton 4086 67 1.64 1.64 2.03 2.62 2.62 121
Crittenden 3829 58 1.51 2.04 0.63 3.88 7.30 229
Cumberland 2976 83 2.79 2.79 3.59 5.61 5.61 205
Daviess 36033 121 0.34 0.86 0.40 0.86 3.28 310
Edmonson 4648 48 1.03 1.03 1.56 2.68 2.68 161
Elliott 2638 65 2.46 2.46 3.29 5.80 5.80 141
Estill 6108 241 3.95 5.60 4.64 7.17 10.32 501
Fayette 108288 358 0.33 1.16 0.35 0.62 3.15 785
Fleming 5367 181 3.37 4.27 3.49 10.28 14.34 419
Floyd 16881 163 0.97 1.05 1.63 1.82 2.04 317
Franklin 19907 147 0.74 1.77 1.06 2.43 10.90 315
Fulton 3237 15 0.46 0.75 NA 0.59 1.02 17
Gallatin 2902 48 1.65 1.65 3.51 1.62 1.62 76
Garrard 5741 76 1.32 1.87 1.36 3.38 5.61 199
Grant 8175 48 0.59 0.75 0.84 0.22 0.31 108
Graves 14841 58 0.39 0.47 0.16 1.14 1.73 132
Grayson 9596 115 1.20 1.55 2.12 4.01 5.79 170
Green 4706 67 1.42 1.42 1.33 5.23 5.23 154
Greenup 14536 178 1.22 2.49 1.05 3.09 5.86 474
Hancock 3215 47 1.46 1.52 1.15 0.86 0.98 147
Hardin 34497 201 0.58 1.21 0.96 2.54 7.52 527
Harlan 13291 260 1.96 2.79 2.07 3.56 4.60 480
Harrison 7012 64 0.91 1.50 1.01 3.22 6.73 123
Hart 6769 128 1.89 2.05 2.07 3.23 3.24 296
Henderson 18095 102 0.56 0.88 0.41 1.29 3.31 205
Henry 5844 98 1.68 1.68 2.73 5.74 5.74 224
Hickman 2188 13 0.59 0.59 1.28 1.41 1.41 36
Hopkins 18820 166 0.88 1.43 0.91 1.87 3.60 334
Jackson 5307 188 3.54 3.54 3.97 6.48 6.48 290
Jefferson 287012 1086 0.38 0.84 0.26 0.86 3.78 2401
Jessamine 13867 150 1.08 2.65 1.59 2.58 7.30 444
Johnson 9103 123 1.35 1.75 1.27 3.47 4.51 293
Kenton 59444 245 0.41 1.67 0.47 1.21 5.77 584
Knott 6717 165 2.46 2.46 1.75 6.21 6.21 372
Knox 12416 197 1.59 2.09 0.78 2.64 3.61 344
Larue 5275 86 1.63 1.97 2.16 6.06 8.01 239
Laurel 20353 182 0.89 1.02 1.16 2.23 2.84 409
Lawrence 5954 133 2.23 2.73 2.47 4.53 5.54 348
Lee 2985 95 3.18 3.18 2.72 6.36 6.36 236
Leslie 4885 163 3.34 3.34 4.04 6.06 6.06 302
100

Letcher 10085 197 1.95 1.96 1.84 3.74 3.74 342
Lewis 5422 248 4.57 4.57 4.41 8.75 8.75 549
Lincoln 9206 200 2.17 2.72 3.24 4.86 6.12 448
Livingston 3996 53 1.33 1.33 0.78 0.42 0.42 114
Logan 10506 116 1.10 1.23 1.00 3.01 4.48 219
Lyon 2898 33 1.14 1.14 NA 1.86 1.86 55
McCracken 27736 116 0.42 0.40 0.56 1.14 2.24 241
McCreary 6520 161 2.47 2.47 3.01 4.94 4.94 299
McLean 3984 39 0.98 0.98 NA 1.64 1.64 112
Madison 27152 183 0.67 1.22 1.02 2.55 7.03 439
Magoffin 5024 74 1.47 1.47 2.59 3.13 3.13 197
Marion 6613 120 1.81 2.32 2.55 4.12 7.31 280
Marshall 12412 47 0.38 0.44 0.26 0.57 0.70 110
Martin 4776 89 1.86 1.86 3.86 2.62 2.62 145
Mason 6847 78 1.14 1.90 1.47 3.96 8.53 135
Meade 9470 44 0.46 0.55 0.00 0.38 0.43 94
Menifee 2537 64 2.52 2.52 2.73 3.08 3.08 149
Mercer 8423 40 0.47 0.85 0.72 1.27 3.04 74
Metcalfe 4016 107 2.66 2.66 5.13 6.82 6.82 284
Monroe 4741 97 2.05 2.05 2.21 3.63 3.63 166
Montgomery 8902 66 0.74 0.75 1.32 1.34 1.52 158
Morgan 4752 106 2.23 2.51 4.04 3.84 4.28 229
Muhlenberg 12357 80 0.65 0.79 0.94 2.13 2.69 203
Nelson 13953 141 1.01 1.48 1.34 2.94 5.02 343
Nicholas 2710 33 1.22 1.22 1.26 5.07 5.07 45
Ohio 8899 167 1.88 2.45 0.86 4.88 6.38 400
Oldham 14856 40 0.27 0.22 0.24 1.22 0.00 117
Owen 4086 123 3.01 3.01 5.52 6.30 6.30 327
Owsley 1894 88 4.65 4.65 6.40 5.83 5.83 195
Pendleton 5170 109 2.11 2.11 1.48 7.48 7.48 224
Perry 11460 335 2.92 3.64 2.57 5.83 7.24 872
Pike 27612 293 1.06 1.00 0.69 2.52 2.36 592
Powell 5044 138 2.74 3.62 3.01 6.54 8.41 332
Pulaski 22719 341 1.50 2.25 2.33 3.30 5.51 692
Robertson 866 27 3.12 3.12 7.41 6.78 6.78 60
Rockcastle 6544 187 2.86 3.30 3.50 4.25 5.19 381
Rowan 7927 72 0.91 1.29 NA 1.90 2.86 137
Russell 6941 94 1.35 1.35 2.01 1.61 1.61 212
Scott 12110 45 0.37 0.32 NA 0.51 1.65 69
Shelby 12104 92 0.76 0.41 0.61 3.28 4.73 214
Simpson 6415 45 0.70 1.72 0.63 2.88 8.88 142
Spencer 4251 41 0.96 0.96 2.28 3.36 3.36 95
Taylor 9233 117 1.27 2.53 2.22 4.28 9.62 172
Todd 4569 84 1.84 1.84 4.88 4.98 4.98 248
Trigg 5215 58 1.11 1.23 1.16 3.49 4.87 97
Trimble 3137 61 1.94 2.03 1.72 4.09 4.76 126
Union 5710 30 0.53 0.37 0.74 2.59 0.97 38
Warren 35365 150 0.42 0.40 0.31 1.74 2.87 435
Washington 4121 83 2.01 2.01 1.37 8.04 8.04 189
Wayne 7913 262 3.31 4.97 5.00 4.74 7.69 579
Webster 5560 38 0.68 0.88 0.62 2.62 3.97 99
Whitley 13780 251 1.82 2.10 2.10 2.83 2.81 553
101

Wolfe 2816 128 4.55 4.55 6.30 5.75 5.75 277
Woodford 8893 36 0.40 0.33 0.60 1.99 3.35 68
102
LOUISIANA (LA)

2000 2000 2000 1990 1990 2000 2000 1990 1990
17 10717 0.65 14318 0.95 3411 0.78 8335 1.83
Louisiana (LA) Occupied Housing Units (OHU)

Parish OHU (OHULP) OHU) Rural OHU) OHULP in 1999 in 1999 in OHULP
Acadia 21142 61 0.29 0.39 0.64 0.31 0.63 153
Allen 8102 71 0.88 0.67 0.91 2.19 2.38 160
Ascension 26691 146 0.55 1.51 0.58 1.62 5.51 482
Assumption 8239 84 1.02 0.65 1.41 3.58 1.99 278
Avoyelles 14736 97 0.66 0.60 0.77 0.84 1.04 183
Beauregard 12104 40 0.33 0.17 0.67 0.00 0.00 79
Bienville 6108 82 1.34 1.39 1.32 3.03 3.39 141
Bossier 36628 183 0.50 1.11 1.02 1.61 3.34 471
Caddo 97974 723 0.74 1.41 0.43 1.84 4.79 1626
Calcasieu 68613 380 0.55 0.21 0.62 1.19 0.37 760
Caldwell 3941 27 0.69 0.69 0.74 2.23 2.23 40
Cameron 3592 32 0.89 0.89 1.93 1.23 1.23 102
Catahoula 4082 43 1.05 1.05 0.76 2.82 2.82 108
103
Louisiana (LA) Occupied Housing Units (OHU)

Parish OHU (OHULP) OHU) Rural OHU) OHULP in 1999 in 1999 in OHULP
Claiborne 6270 90 1.44 1.58 0.96 3.23 3.81 185
Concordia 7521 43 0.57 0.49 0.94 1.30 1.64 135
De Soto 9691 147 1.52 1.81 2.71 3.60 4.93 287
East Baton Rouge 156365 768 0.49 0.27 0.38 1.01 0.00 1945
East Carroll 2969 14 0.47 1.01 0.79 0.81 2.45 32
East Feliciana 6699 103 1.54 1.58 1.82 3.75 4.06 251
Evangeline 12736 118 0.93 0.90 0.94 1.23 1.43 270
Franklin 7754 54 0.70 0.63 0.54 1.97 2.16 102
Grant 7073 65 0.92 0.92 1.33 3.03 3.03 128
Iberia 25381 169 0.67 0.39 0.35 1.77 1.28 543
Iberville 10674 148 1.39 1.50 1.94 2.02 2.76 408
Jackson 6086 66 1.08 0.96 1.72 2.01 2.29 160
Jefferson 176234 959 0.54 0.00 0.43 0.82 0.00 2700
Jefferson Davis 11480 61 0.53 0.30 0.62 1.45 1.07 136
Lafayette 72372 251 0.35 0.22 0.32 0.60 0.48 669
Lafourche 32057 137 0.43 0.54 0.34 1.16 1.08 307
La Salle 5291 38 0.72 0.84 1.20 1.03 1.46 67
Lincoln 15235 54 0.35 0.34 0.25 0.47 0.32 128
Livingston 32630 194 0.59 0.77 NA 1.41 1.38 423
Madison 4469 76 1.70 0.67 3.15 2.64 0.91 125
Morehouse 11382 89 0.78 0.82 0.53 2.22 2.55 240
Natchitoches 14263 120 0.84 1.05 0.60 1.39 2.05 277
Orleans 188251 1856 0.99 0.00 0.78 1.80 0.00 5192
Ouachita 55216 332 0.60 0.22 0.30 1.02 0.61 844
Plaquemines 9021 97 1.08 1.81 NA 3.76 6.87 347
Pointe Coupee 8397 88 1.05 1.22 0.72 2.37 3.02 226
Rapides 47120 206 0.44 0.50 0.11 0.94 1.02 606
Red River 3414 38 1.11 0.74 1.17 2.13 2.29 132
Richland 7490 100 1.34 1.26 1.40 2.32 1.93 281
Sabine 9221 71 0.77 0.71 0.53 2.62 2.91 145
St. Bernard 25123 118 0.47 0.00 0.31 1.95 0.00 339
St. Charles 16422 72 0.44 0.22 0.51 1.41 1.24 182
St. Helena 3873 97 2.50 2.50 2.33 5.73 5.73 240
St. James 6992 60 0.86 1.35 0.79 2.28 3.87 199
St. John the Baptist 14283 24 0.17 0.53 0.00 0.00 0.00 64
St. Landry 32328 285 0.88 0.92 0.99 1.26 2.04 639
St. Martin 17164 127 0.74 1.00 0.84 1.12 1.89 274
St. Mary 19317 142 0.74 1.15 0.69 0.95 1.78 412
St. Tammany 69253 190 0.27 0.43 0.28 0.40 0.29 465
Tangipahoa 36558 276 0.75 0.83 0.72 1.85 2.42 620
Tensas 2416 24 0.99 0.99 NA 2.32 2.32 43
Terrebonne 35997 181 0.50 0.84 0.35 1.49 2.87 566
Union 8857 80 0.90 1.04 0.70 2.73 3.44 137
Vermilion 19832 81 0.41 0.38 0.53 0.87 1.25 165
Vernon 18260 67 0.37 0.33 0.53 0.43 0.87 189
Washington 16467 149 0.90 1.05 0.91 1.90 2.46 317
Webster 16501 118 0.72 0.85 0.55 1.34 1.66 289
West Baton Rouge 7663 35 0.46 0.52 0.00 0.16 0.00 94
West Carroll 4458 21 0.47 0.47 0.46 1.89 1.89 52
West Feliciana 3645 26 0.71 0.71 1.86 0.41 0.41 94
Winn 5930 23 0.39 0.63 1.24 0.65 1.30 35
104
MAINE (ME)

2000 2000 2000 1990 1990 2000 2000 1990 1990
8 4468 0.86 7477 1.61 3786 1.26 6562 2.63
Maine (ME) Occupied Housing Units (OHU)

Androscoggin 42028 228 0.54 0.59 0.68 0.47 1.58 431
Aroostook 30356 329 1.08 1.29 1.23 2.06 2.70 618
Cumberland 107989 369 0.34 0.59 0.20 1.01 3.44 795
Franklin 11806 185 1.57 1.89 0.90 2.58 3.79 348
Hancock 21864 370 1.69 1.79 1.13 5.25 5.56 673
Kennebec 47683 332 0.70 0.91 1.01 1.28 2.12 620
Knox 16608 159 0.96 1.33 0.80 2.73 4.15 249
Lincoln 14158 146 1.03 1.03 1.21 3.52 3.52 256
Oxford 22314 294 1.32 1.60 1.39 3.13 4.34 571
Penobscot 58096 578 0.99 1.43 1.10 2.73 4.62 1097
105
Maine (ME) Occupied Housing Units (OHU)

Piscataquis 7278 130 1.79 1.79 0.91 5.19 5.19 262
Sagadahoc 14117 118 0.84 1.11 1.02 2.24 2.77 230
Somerset 20496 341 1.66 2.18 0.74 3.52 4.88 700
Waldo 14726 263 1.79 1.98 1.35 3.13 3.44 462
Washington 14118 299 2.12 2.32 1.69 4.66 5.13 511
York 74563 327 0.44 0.65 0.57 1.22 2.12 710
106
MARYLAND (MD)

2000 2000 2000 1990 1990 2000 2000 1990 1990
42 9033 0.46 10206 0.58 2176 0.82 5308 1.74
Maryland (MD) Occupied Housing Units (OHU)

County/City OHU (OHULP) OHU) Rural OHU) OHULP in 1999 in 1999 in OHULP
Allegany 29322 162 0.55 1.15 0.58 1.58 3.65 314
Anne Arundel 178670 542 0.30 0.42 0.43 1.01 2.96 1328
Baltimore 299877 875 0.29 0.55 0.24 0.70 1.65 2267
Calvert 25447 137 0.54 0.91 0.93 0.76 1.34 284
Caroline 11097 96 0.87 1.12 1.67 2.23 3.20 230
Carroll 52503 167 0.32 0.33 0.34 2.14 0.84 422
Cecil 31223 140 0.45 0.44 0.34 1.08 1.98 280
Charles 41668 338 0.81 1.64 1.16 3.22 10.41 875
Dorchester 12706 165 1.30 1.74 1.49 1.89 2.47 369
Frederick 70060 260 0.37 0.95 0.92 2.08 6.76 587
Garrett 11476 90 0.78 0.74 0.63 1.75 1.66 177
107
Maryland (MD) Occupied Housing Units (OHU)

Harford 79667 401 0.50 0.67 0.43 1.56 3.60 1037
Howard 90043 240 0.27 0.38 0.39 2.00 5.17 585
Kent 7666 73 0.95 1.04 0.91 1.94 3.02 149
Montgomery 324565 1122 0.35 0.44 0.25 1.00 0.00 3134
Prince George's 286610 1268 0.44 0.98 0.37 0.73 2.66 3780
Queen Anne's 15315 120 0.78 1.23 1.04 4.47 6.02 248
St. Mary's 30642 251 0.82 1.10 1.04 4.73 6.05 1020
Somerset 8361 80 0.96 1.17 0.76 2.55 5.27 141
Talbot 14307 93 0.65 0.79 0.62 1.81 3.40 171
Washington 49726 200 0.40 0.93 0.73 0.67 3.72 388
Wicomico 32218 79 0.25 0.33 0.40 0.56 2.44 150
Worcester 19694 66 0.34 0.83 0.51 0.29 0.73 130
Baltimore City 257996 2068 0.80 0.00 0.63 1.46 0.00 5355
108
MASSACHUSETTS (MA)

2000 2000 2000 1990 1990 2000 2000 1990 1990
21 15211 0.62 9096 0.40 734 0.37 1150 0.35
Massachusetts (MA) Occupied Housing Units (OHU)

Lacking Percent Percent of Percent of Percent of Percent of
complete of Rural population OHULP Rural OHULP
plumbing OHULP OHULP (as above 65 below below Total
Total facilities (as % of % of Rural years in poverty level poverty level population
Barnstable 94822 280 0.30 0.29 0.34 0.97 0.00 719
Berkshire 56006 211 0.38 0.38 0.31 0.86 0.92 412
Bristol 205411 1028 0.50 0.28 0.32 1.19 1.62 2831
Dukes 6421 20 0.31 0.51 0.00 0.00 0.00 26
Essex 275419 2479 0.90 0.22 0.50 2.38 1.70 6440
Franklin 29466 133 0.45 0.60 0.38 1.57 2.40 245
Hampden 175288 1435 0.82 0.55 0.47 2.28 1.42 3639
Hampshire 55991 257 0.46 0.40 0.24 1.03 0.50 567
Middlesex 561220 2917 0.52 0.26 0.37 1.36 0.00 7286
Nantucket 3699 0 0.00 0.00 0.00 0.00 0.00 0
Norfolk 248827 898 0.36 0.38 0.37 1.13 0.00 2077
Plymouth 168361 704 0.42 0.48 0.41 1.22 2.57 1661
Suffolk 278722 3199 1.15 0.00 0.97 2.09 0.00 8986
Worcester 283927 1650 0.58 0.31 0.37 1.81 1.50 4161
109
MICHIGAN (MI)

2000 2000 2000 1990 1990 2000 2000 1990 1990
44 16971 0.45 14687 0.43 4680 0.50 6137 0.64
Michigan (MI) Occupied Housing Units (OHU)

Alcona 5132 36 0.70 0.71 NA 2.95 2.99 63
Alger 3785 40 1.06 1.06 1.66 1.95 1.95 69
Allegan 38165 157 0.41 0.40 0.60 1.36 1.91 378
Alpena 12818 24 0.19 0.29 0.18 0.27 0.70 69
Antrim 9222 64 0.69 0.69 0.51 2.02 2.02 117
Arenac 6710 44 0.66 0.66 0.59 1.95 1.95 94
Baraga 3353 26 0.78 0.78 0.71 3.08 3.08 51
Barry 21035 69 0.33 0.35 0.11 0.64 0.88 121
Bay 43930 63 0.14 0.21 0.25 0.43 0.68 151
Benzie 6500 20 0.31 0.31 NA 1.04 1.04 32
110

Berrien 63569 256 0.40 0.58 0.26 0.99 1.55 869
Branch 16349 191 1.17 1.49 1.19 5.07 7.67 965
Calhoun 54100 210 0.39 0.36 0.36 0.69 0.35 435
Cass 19676 79 0.40 0.33 0.52 2.03 1.53 164
Charlevoix 10400 75 0.72 0.77 0.24 0.94 1.56 142
Cheboygan 10835 44 0.41 0.50 NA 0.85 1.23 78
Chippewa 13474 66 0.49 0.60 0.36 1.33 3.88 107
Clare 12686 120 0.95 1.15 0.50 2.09 2.98 394
Clinton 23653 60 0.25 0.38 0.36 0.33 0.67 134
Crawford 5625 27 0.48 0.61 0.31 1.24 1.62 64
Delta 15836 71 0.45 0.85 0.64 1.35 2.96 141
Dickinson 11386 42 0.37 0.86 0.30 0.53 2.15 86
Eaton 40167 72 0.18 0.23 0.28 0.66 0.83 293
Emmet 12577 61 0.49 0.57 0.61 0.95 0.99 99
Genesee 169825 691 0.41 0.19 0.20 1.05 0.46 1782
Gladwin 10561 122 1.16 1.29 0.64 4.56 5.23 550
Gogebic 7425 45 0.61 0.69 0.41 2.82 3.20 69
Grand Traverse 30396 70 0.23 0.24 0.14 0.61 0.00 140
Gratiot 14501 47 0.32 0.28 0.57 1.01 1.10 79
Hillsdale 17335 166 0.96 1.19 0.86 3.75 5.14 660
Houghton 13793 139 1.01 1.55 1.35 1.38 3.13 241
Huron 14597 76 0.52 0.53 0.78 1.28 1.52 116
Ingham 108593 392 0.36 0.16 0.47 0.82 0.31 1038
Ionia 20606 103 0.50 0.41 0.33 2.02 1.12 258
Iosco 11727 54 0.46 0.73 0.49 0.50 0.85 88
Iron 5748 56 0.97 1.33 0.75 1.32 2.31 77
Isabella 22425 83 0.37 0.44 0.97 0.61 2.08 179
Jackson 58168 193 0.33 0.31 0.31 1.08 1.57 452
Kalamazoo 93479 213 0.23 0.23 0.20 0.39 1.74 514
Kalkaska 6428 36 0.56 0.60 0.32 1.56 2.04 58
Kent 212890 939 0.44 0.26 0.46 1.32 0.74 2404
Keweenaw 998 27 2.71 2.71 2.58 3.70 3.70 39
Lake 4704 85 1.81 1.81 1.22 3.32 3.32 186
Lapeer 30729 101 0.33 0.44 NA 0.58 0.99 252
Leelanau 8436 26 0.31 0.33 NA 1.26 1.26 40
Lenawee 35930 146 0.41 0.26 0.60 1.21 0.89 329
Livingston 55384 129 0.23 0.42 0.33 2.02 4.66 272
Luce 2481 39 1.57 2.35 0.70 2.69 3.72 63
Mackinac 5067 48 0.95 1.12 NA 3.00 3.82 72
Macomb 309203 753 0.24 0.10 0.19 0.80 1.87 1863
Manistee 9860 59 0.60 0.60 0.54 0.75 1.33 109
Marquette 25767 125 0.49 0.98 0.55 1.31 3.96 255
Mason 11406 56 0.49 0.56 0.18 1.22 1.29 96
Mecosta 14915 112 0.75 0.92 0.53 1.79 3.78 521
Menominee 10529 71 0.67 0.79 0.76 1.43 2.62 124
Midland 31769 65 0.20 0.13 0.32 0.54 0.77 101
Missaukee 5450 37 0.68 0.68 0.77 1.23 1.23 73
Monroe 53772 170 0.32 0.34 0.73 1.04 0.77 427
Montcalm 22079 137 0.62 0.71 0.75 2.43 2.70 520
Montmorency 4455 26 0.58 0.58 0.38 1.64 1.64 59
Muskegon 63330 255 0.40 0.29 0.33 0.89 0.76 615
Newaygo 17599 99 0.56 0.54 0.62 1.09 0.91 229
111

Oakland 471115 1356 0.29 0.16 0.26 1.08 2.67 3545
Oceana 9778 48 0.49 0.49 NA 2.02 2.02 102
Ogemaw 8842 64 0.72 0.72 1.04 2.11 2.11 119
Ontonagon 3456 60 1.74 1.74 1.42 5.20 5.20 108
Osceola 8861 66 0.74 0.80 0.79 2.27 2.72 166
Oscoda 3921 38 0.97 0.97 0.97 0.75 0.75 47
Otsego 8995 24 0.27 0.24 NA 0.81 1.27 28
Ottawa 81662 243 0.30 0.30 0.57 0.82 1.99 734
Presque Isle 6155 43 0.70 0.88 0.51 1.85 2.14 66
Roscommon 11250 35 0.31 0.41 NA 0.15 0.29 66
Saginaw 80430 347 0.43 0.40 0.37 1.28 2.64 990
St. Clair 62072 165 0.27 0.34 0.31 0.61 1.58 353
St. Joseph 23381 129 0.55 0.57 0.73 1.39 2.01 389
Sanilac 16871 129 0.76 0.86 0.46 3.02 3.11 534
Schoolcraft 3606 25 0.69 1.08 0.63 1.34 1.90 49
Shiawassee 26896 94 0.35 0.19 0.49 0.96 0.80 155
Tuscola 21454 111 0.52 0.41 0.30 1.89 1.88 218
Van Buren 27982 139 0.50 0.56 0.82 1.42 1.97 396
Washtenaw 125327 483 0.39 0.21 0.29 0.53 0.53 1002
Wayne 768440 5404 0.70 0.33 0.37 1.84 2.01 15096
Wexford 11824 60 0.51 0.68 0.70 1.54 3.33 115
112
MINNESOTA (MN)

2000 2000 2000 1990 1990 2000 2000 1990 1990
37 9581 0.51 9382 0.57 4367 0.82 6022 1.28
Minnesota (MN) Occupied Housing Units (OHU)

Aitkin 6644 157 2.36 2.36 1.64 6.62 6.62 294
Anoka 106428 331 0.31 0.51 0.45 1.24 2.89 947
Becker 11844 139 1.17 1.35 0.82 2.67 4.00 284
Beltrami 14337 153 1.07 1.32 0.28 2.85 3.68 370
Benton 13065 34 0.26 0.72 0.64 1.01 2.91 66
Big Stone 2377 8 0.34 0.34 0.79 0.72 0.72 10
Blue Earth 21062 71 0.34 0.46 0.60 0.80 1.11 170
Brown 10598 29 0.27 0.61 0.22 0.61 2.02 47
Carlton 12064 99 0.82 1.24 0.81 2.78 3.44 156
Carver 24356 76 0.31 0.29 0.58 0.64 3.02 139
Cass 10893 144 1.32 1.32 1.30 3.87 3.87 274
113

Chippewa 5361 12 0.22 0.46 0.29 0.00 0.00 14
Chisago 14454 49 0.34 0.37 0.29 0.83 1.49 113
Clay 18670 31 0.17 0.14 0.17 0.40 0.00 45
Clearwater 3330 57 1.71 1.71 1.30 6.09 6.09 107
Cook 2350 157 6.68 6.68 NA 6.38 6.38 297
Cottonwood 4917 10 0.20 0.32 0.42 0.20 0.35 15
Crow Wing 22250 151 0.68 0.68 0.53 1.25 1.85 284
Dakota 131151 324 0.25 0.25 0.14 0.16 0.86 807
Dodge 6420 16 0.25 0.37 0.70 1.15 1.51 25
Douglas 13276 42 0.32 0.39 0.52 0.80 1.70 70
Faribault 6652 12 0.18 0.23 0.49 0.30 0.39 22
Fillmore 8228 183 2.22 2.22 1.81 7.94 7.94 890
Freeborn 13356 83 0.62 0.76 0.64 2.48 4.47 178
Goodhue 16983 87 0.51 0.47 0.69 2.40 4.03 188
Grant 2534 17 0.67 0.67 NA 0.84 0.84 26
Hennepin 456129 1936 0.42 0.12 0.27 1.61 0.00 5445
Houston 7633 36 0.47 0.64 0.52 1.39 2.29 79
Hubbard 7435 105 1.41 1.33 0.67 3.63 3.06 251
Isanti 11236 67 0.60 0.68 1.13 1.46 2.70 118
Itasca 17789 229 1.29 1.49 0.78 3.63 3.79 410
Jackson 4556 25 0.55 0.79 0.55 0.00 0.00 39
Kanabec 5759 99 1.72 1.96 1.47 4.91 5.13 160
Kandiyohi 15936 64 0.40 0.47 0.18 1.26 2.68 140
Kittson 2167 14 0.65 0.65 1.27 1.65 1.65 22
Koochiching 6040 48 0.79 1.82 0.71 3.03 8.28 127
Lac qui Parle 3316 23 0.69 0.69 0.59 3.34 3.34 60
Lake 4646 86 1.85 2.28 0.70 1.69 3.05 145
Lake of the Woods 1903 28 1.47 1.47 0.95 4.55 4.55 41
Le Sueur 9630 55 0.57 0.67 0.48 2.07 3.74 121
Lincoln 2653 25 0.94 0.94 0.87 2.22 2.22 47
Lyon 9715 49 0.50 0.58 0.56 0.56 1.49 109
McLeod 13449 58 0.43 0.42 0.38 1.14 0.00 109
Mahnomen 1969 4 0.20 0.20 NA 0.00 0.00 NA
Marshall 4101 30 0.73 0.73 0.90 1.34 1.34 59
Martin 9067 35 0.39 0.56 0.63 0.62 1.39 69
Meeker 8590 42 0.49 0.47 0.34 1.26 1.00 66
Mille Lacs 8638 82 0.95 1.17 1.00 1.63 1.98 185
Morrison 11816 84 0.71 0.94 0.47 1.92 3.05 184
Mower 15582 79 0.51 0.48 0.47 1.07 0.49 170
Murray 3722 22 0.59 0.59 0.55 2.22 2.22 32
Nicollet 10642 43 0.40 0.50 NA 0.50 2.53 93
Nobles 7939 48 0.60 0.43 0.77 2.72 1.04 136
Norman 3010 14 0.47 0.47 0.86 2.14 2.14 16
Olmsted 47807 160 0.33 0.16 0.52 1.32 0.00 334
Otter Tail 22671 138 0.61 0.70 0.77 1.71 2.37 259
Pennington 5525 36 0.65 0.61 NA 0.60 2.60 48
Pine 9939 187 1.88 2.14 1.52 4.98 5.94 367
Pipestone 4069 17 0.42 0.27 NA 0.00 0.00 37
Polk 12070 87 0.72 0.73 1.44 1.36 2.13 151
Pope 4513 26 0.58 0.58 0.60 1.87 1.87 42
Ramsey 201236 930 0.46 0.00 0.29 1.55 0.00 3148
Red Lake 1727 6 0.35 0.35 1.14 0.91 0.91 11
114

Redwood 6674 19 0.28 0.42 0.61 0.85 1.33 32
Renville 6779 26 0.38 0.38 0.23 1.45 1.45 38
Rice 18888 52 0.28 0.36 0.40 0.47 1.96 82
Rock 3843 6 0.16 0.31 0.39 1.62 3.75 7
Roseau 6190 64 1.03 1.11 1.57 3.71 4.83 127
St. Louis 82619 748 0.91 1.70 0.61 1.95 4.93 1279
Scott 30692 159 0.52 0.33 0.22 1.68 1.23 441
Sherburne 21581 58 0.27 0.29 0.33 0.85 2.71 100
Sibley 5772 31 0.54 0.54 0.71 2.41 2.41 38
Stearns 47604 164 0.34 0.43 0.59 1.39 1.06 330
Steele 12846 54 0.42 0.66 0.94 2.44 0.00 153
Stevens 3751 18 0.48 0.51 NA 0.66 1.23 35
Swift 4353 18 0.41 0.64 0.44 1.40 3.57 33
Todd 9342 115 1.23 1.32 0.69 2.35 3.03 413
Traverse 1717 4 0.23 0.23 NA 0.00 0.00 8
Wabasha 8277 51 0.62 0.68 0.61 6.23 5.00 100
Wadena 5426 67 1.23 1.87 1.31 1.89 2.85 118
Waseca 7059 21 0.30 0.28 NA 1.49 3.54 24
Washington 71462 107 0.15 0.12 0.13 0.35 0.00 271
Watonwan 4627 16 0.35 0.29 NA 0.45 0.80 69
Wilkin 2752 22 0.80 0.53 0.87 0.00 0.00 31
Winona 18744 137 0.73 1.14 0.42 2.92 7.12 389
Wright 31465 124 0.39 0.40 0.52 1.32 2.14 290
Yellow Medicine 4439 11 0.25 0.31 0.60 0.72 0.95 28
115
MISSISSIPPI (MS)

2000 2000 2000 1990 1990 2000 2000 1990 1990
9 9015 0.86 17625 1.93 6109 1.15 14849 3.18
Mississippi (MS) Occupied Housing Units (OHU)

Adams 13677 91 0.67 1.27 1.10 1.67 3.87 193
Alcorn 14224 80 0.56 0.72 0.56 1.57 2.04 164
Amite 5271 73 1.38 1.38 2.17 2.81 2.81 186
Attala 7567 105 1.39 1.96 1.76 3.84 5.36 257
Benton 2999 38 1.27 1.27 0.92 2.49 2.49 168
Bolivar 13776 209 1.52 2.59 2.17 3.34 5.09 590
Calhoun 6019 40 0.66 0.64 0.72 0.33 0.21 79
Carroll 4071 43 1.06 1.06 2.77 1.05 1.05 89
Chickasaw 7253 64 0.88 0.92 0.70 1.92 2.43 136
116

Choctaw 3686 29 0.79 0.79 NA 1.36 1.36 164
Claiborne 3685 85 2.31 2.46 1.70 3.81 4.55 203
Clarke 6978 89 1.28 1.28 0.88 2.07 2.07 267
Clay 8152 60 0.74 0.80 NA 1.84 3.21 186
Coahoma 10553 170 1.61 1.69 1.46 2.69 2.76 432
Copiah 10142 237 2.34 2.80 1.26 5.15 7.02 712
Covington 7126 68 0.95 0.95 0.00 2.53 2.53 227
DeSoto 38792 264 0.68 0.99 0.64 2.39 4.29 690
Forrest 27183 151 0.56 0.77 0.55 1.11 3.04 378
Franklin 3211 55 1.71 1.71 1.43 3.18 3.18 133
George 6742 64 0.95 0.95 1.88 3.02 3.02 160
Greene 4148 34 0.82 0.82 NA 2.20 2.20 92
Grenada 8820 69 0.78 0.32 0.49 1.30 0.00 114
Hancock 16897 57 0.34 0.44 0.00 0.90 0.80 115
Harrison 71538 261 0.36 0.54 0.19 0.69 0.60 597
Hinds 91030 635 0.70 1.19 0.68 1.50 3.97 1898
Holmes 7314 118 1.61 2.11 2.24 2.19 2.72 355
Humphreys 3765 92 2.44 2.72 1.32 4.05 5.53 361
Issaquena 726 19 2.62 2.62 3.69 2.55 2.55 37
Itawamba 8773 36 0.41 0.46 0.78 1.82 2.17 48
Jackson 47676 263 0.55 0.83 0.55 1.10 1.64 617
Jasper 6708 108 1.61 1.61 1.46 1.54 1.54 281
Jefferson 3308 75 2.27 2.20 1.75 2.35 1.85 198
Jefferson Davis 5177 63 1.22 1.22 0.79 2.70 2.70 206
Jones 24275 105 0.43 0.50 0.21 0.51 0.58 256
Kemper 3909 81 2.07 2.07 2.66 3.38 3.38 199
Lafayette 14373 81 0.56 0.87 0.50 1.37 3.73 186
Lamar 14396 26 0.18 0.27 0.54 0.00 0.00 40
Lauderdale 29990 238 0.79 0.75 0.74 1.95 3.80 572
Lawrence 5040 48 0.95 0.95 1.02 1.58 1.58 105
Leake 7611 88 1.16 1.37 0.35 2.72 3.21 343
Lee 29200 123 0.42 0.60 0.59 1.64 2.04 210
Leflore 12956 100 0.77 0.70 0.90 1.59 2.53 268
Lincoln 12538 81 0.65 0.91 1.12 1.49 3.11 163
Lowndes 22849 78 0.34 0.18 0.47 0.68 0.71 184
Madison 27219 217 0.80 1.88 1.44 2.72 6.56 576
Marion 9336 86 0.92 1.24 0.45 1.32 1.70 243
Marshall 12163 204 1.68 1.73 1.62 4.74 5.05 448
Monroe 14603 107 0.73 0.85 0.75 2.00 2.50 253
Montgomery 4690 32 0.68 0.71 NA 2.63 2.95 79
Neshoba 10694 76 0.71 0.76 0.56 1.53 1.30 199
Newton 8221 94 1.14 1.22 1.78 2.24 2.49 210
Noxubee 4470 75 1.68 1.96 2.00 3.07 3.91 256
Oktibbeha 15945 100 0.63 1.16 0.73 1.09 2.55 236
Panola 12232 215 1.76 1.88 2.42 2.93 3.19 543
Pearl River 18078 105 0.58 0.52 0.99 1.43 1.49 226
Perry 4420 64 1.45 1.45 2.99 3.11 3.11 147
Pike 14792 154 1.04 0.92 0.94 2.72 2.32 331
Pontotoc 10097 106 1.05 1.17 1.48 3.71 4.18 313
Prentiss 9821 83 0.85 0.88 1.29 2.23 2.45 166
Quitman 3565 39 1.09 1.02 0.85 1.92 2.21 119
Rankin 42089 301 0.72 1.18 0.62 2.31 4.20 903
117

Scott 10183 201 1.97 2.64 2.39 3.85 5.27 511
Sharkey 2163 62 2.87 2.87 3.16 7.02 7.02 194
Simpson 10076 153 1.52 1.65 2.23 2.90 3.17 345
Smith 6046 85 1.41 1.41 0.50 4.96 4.96 215
Stone 4747 65 1.37 1.74 NA 3.32 5.04 245
Sunflower 9637 178 1.85 1.80 0.99 2.71 2.12 686
Tallahatchie 5263 112 2.13 2.15 2.66 3.81 3.83 263
Tate 8850 135 1.53 1.98 1.57 3.43 4.22 220
Tippah 8108 65 0.80 1.03 0.93 1.98 2.76 97
Tishomingo 7917 53 0.67 0.67 0.80 1.09 1.09 78
Tunica 3258 53 1.63 1.29 1.98 3.23 2.40 124
Union 9786 68 0.69 0.66 0.32 0.99 0.89 152
Walthall 5571 123 2.21 2.21 1.41 3.84 3.84 323
Warren 18756 69 0.37 0.34 0.00 0.77 0.82 246
Washington 22158 149 0.67 1.09 0.23 1.22 2.38 556
Wayne 7857 80 1.02 1.34 1.22 2.21 3.11 161
Webster 3905 39 1.00 1.00 0.44 4.09 4.09 64
Wilkinson 3578 55 1.54 1.54 3.37 2.92 2.92 251
Winston 7578 96 1.27 1.56 1.32 2.73 3.39 302
Yalobusha 5260 69 1.31 1.63 1.48 1.68 2.24 121
Yazoo 9178 153 1.67 1.39 0.93 2.77 2.76 539
118
MISSOURI (MO)

Lacking
Complete Percent of Percent of
Plumbing Percent of Rural Rural
Facilities OHULP (as Percent of Rural OHULP (as Rural OHULP (as
Ranking (OHULP) % of OHU) OHULP OHULP OHULP % of Rural OHULP % of Rural
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
29 11923 0.54 14263 0.73 6147 0.94 9717 1.65
Missouri (MO) Occupied Housing Units (OHU)

Adair 9669 43 0.44 0.95 0.54 0.63 3.02 123
Andrew 6273 49 0.78 1.08 1.60 0.71 1.22 123
Atchison 2722 6 0.22 0.22 NA 0.00 0.00 9
Audrain 9844 197 2.00 4.38 0.23 8.89 22.94 919
Barry 13398 145 1.08 1.23 0.81 3.01 3.87 250
Barton 4895 13 0.27 0.26 NA 0.28 0.46 43
Bates 6511 70 1.08 1.30 0.97 3.51 4.22 191
Benton 7420 79 1.06 1.06 0.38 3.74 3.74 154
Bollinger 4576 56 1.22 1.22 0.82 0.83 0.83 94
Boone 53094 203 0.38 0.44 0.10 0.57 1.41 500
Buchanan 33557 114 0.34 0.43 0.13 0.58 0.00 312
Butler 16718 114 0.68 0.84 1.05 1.44 2.22 199
Caldwell 3523 28 0.79 0.79 0.72 1.52 1.52 61
Callaway 14416 61 0.42 0.60 0.97 2.88 5.38 117
119

Camden 15779 82 0.52 0.54 0.85 0.25 0.00 206
Cape Girardeau 26980 109 0.40 0.74 0.32 0.62 2.12 216
Carroll 4169 62 1.49 1.76 0.52 2.65 5.10 185
Carter 2378 28 1.18 1.18 NA 2.71 2.71 39
Cass 30168 63 0.21 0.21 0.17 1.23 0.75 164
Cedar 5685 45 0.79 1.11 0.71 1.75 2.94 89
Chariton 3469 25 0.72 0.72 1.62 3.69 3.69 38
Christian 20425 48 0.24 0.37 NA 0.93 2.00 71
Clark 2966 30 1.01 1.01 0.79 2.68 2.68 97
Clay 72558 214 0.29 0.26 0.21 0.79 0.00 502
Clinton 7152 51 0.71 0.71 0.53 2.80 3.95 118
Cole 27040 81 0.30 0.28 0.22 0.97 0.49 117
Cooper 5932 48 0.81 1.25 1.13 1.34 2.54 94
Crawford 8858 74 0.84 0.85 1.26 1.84 2.35 149
Dade 3202 30 0.94 0.94 1.12 1.89 1.89 37
Dallas 6030 65 1.08 1.34 2.68 1.60 2.27 182
Daviess 3178 25 0.79 0.79 0.51 1.43 1.43 55
DeKalb 3528 20 0.57 0.67 0.84 1.72 2.23 45
Dent 5982 79 1.32 1.92 1.55 3.66 4.85 136
Douglas 5201 100 1.92 2.52 1.72 3.73 5.36 156
Dunklin 13411 94 0.70 0.47 0.70 1.15 0.88 192
Franklin 34945 165 0.47 0.57 0.61 1.41 2.27 321
Gasconade 6171 80 1.30 1.57 2.33 4.52 5.48 104
Gentry 2747 28 1.02 1.02 0.89 2.44 2.44 60
Greene 97859 270 0.28 0.18 0.28 0.63 1.11 495
Grundy 4382 25 0.57 1.09 1.09 1.87 5.51 87
Harrison 3658 54 1.48 2.17 1.59 2.07 3.17 153
Henry 9133 46 0.50 0.92 NA 1.10 2.78 114
Hickory 3911 30 0.77 0.77 0.58 2.89 2.89 68
Holt 2237 23 1.03 1.03 1.32 1.66 1.66 33
Howard 3836 24 0.63 0.87 0.88 0.45 0.84 47
Howell 14762 146 0.99 1.13 0.55 2.04 2.62 363
Iron 4197 73 1.74 2.03 0.71 4.94 6.72 132
Jackson 266294 1121 0.42 0.45 0.27 1.01 1.97 2793
Jasper 41412 171 0.41 0.35 0.40 0.66 0.92 315
Jefferson 71499 201 0.28 0.28 0.41 0.78 1.09 431
Johnson 17410 92 0.53 0.70 0.51 2.20 3.75 226
Knox 1791 23 1.28 1.28 0.81 2.99 2.99 43
Laclede 12760 101 0.79 1.12 0.61 2.17 3.90 137
Lafayette 12569 40 0.32 0.28 0.41 0.47 0.68 108
Lawrence 13568 88 0.65 0.93 0.25 1.19 2.14 226
Lewis 3956 52 1.31 1.31 0.60 4.35 4.35 288
Lincoln 13851 97 0.70 0.82 0.95 1.32 1.90 181
Linn 5697 22 0.39 0.40 NA 1.40 0.99 76
Livingston 5736 15 0.26 0.73 NA 0.98 3.69 41
McDonald 8113 147 1.81 1.81 0.34 3.91 3.91 378
Macon 6501 91 1.40 1.96 0.92 5.12 8.32 293
Madison 4711 51 1.08 1.32 0.77 1.73 2.78 98
Maries 3519 53 1.51 1.51 1.25 3.73 3.73 85
Marion 11066 37 0.33 0.23 NA 1.09 0.00 97
Mercer 1600 29 1.81 1.81 1.69 1.79 1.79 65
Miller 9284 21 0.23 0.16 NA 0.53 0.78 70
120

Mississippi 5383 17 0.32 0.14 0.35 0.07 0.27 27
Moniteau 5259 39 0.74 1.34 0.84 2.32 5.08 146
Monroe 3656 60 1.64 1.64 1.11 5.83 5.83 247
Montgomery 4775 68 1.42 1.42 2.41 4.17 4.17 138
Morgan 7850 69 0.88 0.88 1.18 1.47 1.47 150
New Madrid 7824 56 0.72 0.55 1.55 2.04 2.14 97
Newton 20140 147 0.73 1.01 0.42 2.50 3.29 271
Nodaway 8138 27 0.33 0.42 0.37 1.19 1.69 73
Oregon 4263 91 2.13 2.57 1.70 5.27 6.62 223
Osage 4922 34 0.69 0.69 2.23 2.05 2.05 76
Ozark 3950 97 2.46 2.46 2.41 5.29 5.29 134
Pemiscot 7855 64 0.81 1.13 1.55 1.19 2.31 166
Perry 6904 34 0.49 0.73 NA 1.57 1.73 73
Pettis 15568 149 0.96 1.07 0.87 1.46 1.27 289
Phelps 15683 102 0.65 0.87 NA 1.41 2.81 248
Pike 6451 142 2.20 3.75 1.52 6.17 12.18 522
Platte 29278 96 0.33 0.47 0.31 1.15 3.51 180
Polk 9917 86 0.87 1.17 0.63 1.93 3.17 231
Pulaski 13433 62 0.46 0.73 1.55 2.07 3.05 142
Putnam 2228 14 0.63 0.63 NA 0.00 0.00 27
Ralls 3736 24 0.64 0.66 1.23 3.10 3.13 62
Randolph 9199 36 0.39 0.73 0.72 1.20 3.47 106
Ray 8743 43 0.49 0.71 0.71 0.88 1.70 84
Reynolds 2721 50 1.84 1.84 1.32 4.63 4.63 86
Ripley 5416 102 1.88 1.88 1.85 3.47 3.47 192
St. Charles 101663 248 0.24 0.14 0.24 1.61 0.00 603
St. Clair 4040 72 1.78 1.78 1.56 3.19 3.19 151
Ste. Genevieve 6586 53 0.80 1.08 1.06 3.92 5.34 84
St. Francois 20793 100 0.48 0.69 0.85 1.64 1.96 210
St. Louis 404312 1070 0.26 0.20 0.24 0.65 0.00 2639
Saline 9015 70 0.78 0.99 0.61 1.35 0.00 168
Schuyler 1725 13 0.75 0.75 1.69 0.00 0.00 25
Scotland 1902 23 1.21 1.21 1.31 2.38 2.38 34
Scott 15626 77 0.49 0.72 0.41 1.09 1.66 172
Shannon 3319 110 3.31 3.31 NA 6.69 6.69 236
Shelby 2745 27 0.98 0.98 NA 3.45 3.45 39
Stoddard 12064 56 0.46 0.42 0.82 1.40 1.02 131
Stone 11822 45 0.38 0.38 0.36 1.54 1.54 69
Sullivan 2925 28 0.96 0.96 0.73 1.14 1.14 60
Taney 16158 82 0.51 0.64 0.61 0.78 0.24 213
Texas 9378 172 1.83 1.85 1.48 4.20 4.22 379
Vernon 7966 75 0.94 1.54 1.29 3.35 6.14 226
Warren 9185 80 0.87 0.99 1.17 1.18 0.35 176
WA 8406 144 1.71 2.01 1.49 3.19 3.73 243
Wayne 5551 78 1.41 1.41 1.98 3.70 3.70 132
Webster 11073 300 2.71 3.46 2.44 11.68 14.91 1364
Worth 1009 6 0.59 0.59 0.00 1.22 1.22 11
Wright 7081 69 0.97 1.15 0.67 2.41 2.80 150
St. Louis City 147076 1249 0.85 0.00 0.50 1.51 0.00 3049
121
MONTANA (MT)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
13 2776 0.77 2357 0.77 1873 1.18 1678 1.22
Montana (MT) Occupied Housing Units (OHU)

Beaverhead 3684 50 1.36 0.95 2.79 3.92 0.68 70
Big Horn 3924 81 2.06 2.64 1.83 3.11 3.81 232
Blaine 2501 39 1.56 1.56 2.55 3.06 3.06 81
Broadwater 1752 10 0.57 0.57 0.00 4.85 4.85 21
Carbon 4065 31 0.76 0.76 1.04 1.06 1.06 54
Carter 543 10 1.84 1.84 4.89 0.00 0.00 11
Cascade 32547 221 0.68 0.91 0.45 1.11 1.99 324
Chouteau 2226 2 0.09 0.09 NA 0.00 0.00 NA
Custer 4768 33 0.69 0.78 NA 2.12 2.47 64
Daniels 892 0 0.00 0.00 0.00 0.00 0.00 0
Dawson 3625 10 0.28 0.18 0.00 1.83 1.23 36
Deer Lodge 3995 10 0.25 0.44 0.00 0.00 0.00 20
122
Montana (MT) Occupied Housing Units (OHU)

Fallon 1140 4 0.35 0.35 0.00 1.53 1.53 NA
Fergus 4860 17 0.35 0.53 NA 0.73 1.74 28
Flathead 29588 301 1.02 1.69 0.84 3.25 7.10 588
Gallatin 26323 113 0.43 0.39 NA 0.90 0.50 303
Garfield 532 7 1.32 1.32 2.98 4.67 4.67 12
Glacier 4304 53 1.23 2.73 1.18 4.43 10.77 112
Golden Valley 365 4 1.10 1.10 NA 3.64 3.64 10
Granite 1200 31 2.58 2.58 NA 3.91 3.91 52
Hill 6457 25 0.39 0.89 0.60 0.17 0.56 43
Jefferson 3747 48 1.28 1.28 NA 0.82 0.82 74
Judith Basin 951 7 0.74 0.74 NA 1.23 1.23 21
Lake 10192 80 0.78 0.95 0.55 1.99 2.58 145
Lewis and Clark 22850 150 0.66 1.48 1.16 1.68 5.50 293
Liberty 833 6 0.72 0.72 NA 1.49 1.49 10
Lincoln 7764 277 3.57 4.23 1.06 7.98 10.17 545
McCone 810 5 0.62 0.62 2.14 1.40 1.40 8
Madison 2956 8 0.27 0.27 0.00 0.52 0.52 15
Meagher 803 11 1.37 1.37 NA 2.92 2.92 13
Mineral 1584 35 2.21 2.21 1.36 7.20 7.20 81
Missoula 38439 259 0.67 1.21 0.27 1.90 4.95 493
Musselshell 1878 32 1.70 1.70 1.07 4.57 4.57 48
Park 6828 44 0.64 1.07 NA 0.88 2.24 104
Petroleum 211 0 0.00 0.00 0.00 0.00 0.00 0
Phillips 1848 5 0.27 0.27 NA 1.58 1.58 NA
Pondera 2410 16 0.66 0.88 NA 1.69 3.11 29
Powder River 737 11 1.49 1.49 NA 5.83 5.83 20
Powell 2422 9 0.37 1.06 0.00 0.65 1.60 39
Prairie 537 8 1.49 1.49 NA 2.38 2.38 9
Ravalli 14289 96 0.67 0.84 0.00 1.59 2.17 207
Richland 3878 22 0.57 0.36 NA 0.00 0.00 80
Roosevelt 3581 11 0.31 0.70 0.00 0.51 1.58 17
Rosebud 3307 41 1.24 1.24 2.56 2.93 2.93 124
Sanders 4273 93 2.18 2.18 1.51 3.59 3.59 148
Sheridan 1741 13 0.75 0.75 1.88 3.08 3.08 17
Silver Bow 14432 96 0.67 0.74 0.18 2.39 0.00 141
Stillwater 3234 27 0.83 0.83 NA 2.63 2.63 32
Sweet Grass 1476 13 0.88 0.88 NA 2.04 2.04 25
Teton 2538 49 1.93 1.93 0.97 4.48 4.48 140
Toole 1962 7 0.36 0.47 0.00 0.92 1.79 19
Treasure 357 6 1.68 1.68 NA 0.00 0.00 14
Valley 3150 17 0.54 0.23 0.00 0.00 0.00 51
Wheatland 853 4 0.47 0.47 0.00 0.00 0.00 NA
Wibaux 421 0 0.00 0.00 0.00 0.00 0.00 0
Yellowstone 52084 218 0.42 0.73 0.27 1.06 2.17 319
123
NEBRASKA (NE)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
52 2408 0.36 2253 0.37 985 0.49 1189 0.60
Nebraska (NE) Occupied Housing Units (OHU)

Adams 12141 29 0.24 0.36 NA 0.32 2.03 85
Antelope 2953 8 0.27 0.27 NA 1.38 1.38 8
Arthur 185 2 1.08 1.08 NA 0.00 0.00 NA
Banner 311 2 0.64 0.64 NA 0.00 0.00 NA
Blaine 238 5 2.10 2.10 NA 6.82 6.82 NA
Boone 2454 10 0.41 0.41 NA 0.68 0.68 17
Box Butte 4780 26 0.54 1.20 0.64 1.82 3.17 56
Boyd 1014 9 0.89 0.89 NA 4.03 4.03 17
Brown 1530 6 0.39 0.39 NA 1.18 1.18 8
Buffalo 15930 37 0.23 0.20 NA 0.11 0.45 102
Burt 3155 24 0.76 0.76 1.63 0.00 0.00 35
124

Butler 3426 27 0.79 0.81 0.97 2.05 1.06 44
Cass 9161 40 0.44 0.51 NA 0.41 0.00 58
Cedar 3623 20 0.55 0.55 0.80 0.57 0.57 30
Chase 1662 5 0.30 0.30 NA 0.00 0.00 16
Cherry 2508 13 0.52 0.30 0.91 2.74 2.05 27
Cheyenne 4071 18 0.44 1.16 0.62 2.00 4.55 32
Clay 2756 15 0.54 0.54 0.59 1.48 1.48 35
Colfax 3682 10 0.27 0.15 0.00 0.26 0.46 23
Cuming 3945 18 0.46 0.46 0.66 0.83 1.29 52
Custer 4826 21 0.44 0.64 0.61 0.70 1.03 32
Dakota 7095 24 0.34 0.50 NA 1.06 6.06 80
Dawes 3512 15 0.43 1.05 0.78 0.28 1.07 52
Dawson 8824 45 0.51 0.59 NA 1.79 1.01 170
Deuel 908 8 0.88 0.88 NA 0.00 0.00 10
Dixon 2413 17 0.70 0.70 0.00 3.08 3.08 33
Dodge 14433 39 0.27 0.30 0.29 0.48 0.00 49
Douglas 182194 648 0.36 0.09 0.25 1.07 0.00 1452
Dundy 961 8 0.83 0.83 0.00 0.00 0.00 9
Fillmore 2689 0 0.00 0.00 0.00 0.00 0.00 0
Franklin 1485 7 0.47 0.47 NA 2.62 2.62 7
Frontier 1192 5 0.42 0.42 0.00 1.95 1.95 NA
Furnas 2278 11 0.48 0.48 0.78 1.61 1.61 22
Gage 9316 23 0.25 0.40 0.20 0.00 0.00 41
Garden 1020 8 0.78 0.78 NA 2.00 2.00 13
Garfield 813 4 0.49 0.49 0.00 0.00 0.00 NA
Gosper 863 0 0.00 0.00 0.00 0.00 0.00 0
Grant 292 3 1.03 1.03 0.00 0.00 0.00 NA
Greeley 1077 0 0.00 0.00 0.00 0.00 0.00 0
Hall 20356 90 0.44 0.76 0.59 1.04 2.10 248
Hamilton 3503 7 0.20 0.38 0.54 1.17 2.11 9
Harlan 1597 9 0.56 0.56 1.49 0.58 0.58 17
Hayes 430 11 2.56 2.56 5.07 2.74 2.74 14
Hitchcock 1287 10 0.78 0.78 1.09 1.18 1.18 9
Holt 4608 19 0.41 0.26 0.94 0.31 0.45 26
Hooker 335 0 0.00 0.00 0.00 0.00 0.00 0
Howard 2546 8 0.31 0.31 NA 1.23 1.23 22
Jefferson 3527 20 0.57 1.23 0.62 0.00 0.00 44
Johnson 1887 12 0.64 0.64 NA 2.00 2.00 26
Kearney 2643 18 0.68 1.21 NA 0.00 0.00 46
Keith 3707 29 0.78 0.57 0.52 0.00 0.00 47
Keya Paha 409 5 1.22 1.22 NA 2.91 2.91 22
Kimball 1727 6 0.35 0.32 1.36 0.00 0.00 14
Knox 3811 23 0.60 0.60 1.08 1.77 1.77 50
Lancaster 99187 303 0.31 0.32 0.21 0.66 1.32 748
Lincoln 14076 30 0.21 0.44 NA 0.87 1.52 62
Logan 316 0 0.00 0.00 0.00 0.00 0.00 0
Loup 289 0 0.00 0.00 0.00 0.00 0.00 0
McPherson 202 0 0.00 0.00 0.00 0.00 0.00 0
Madison 13436 42 0.31 0.45 0.40 0.64 1.29 105
Merrick 3209 16 0.50 0.53 NA 0.00 0.00 28
Morrill 2138 15 0.70 0.70 NA 2.03 2.03 35
Nance 1577 7 0.44 0.44 NA 0.00 0.00 16
Nemaha 3047 2 0.07 0.13 0.00 0.00 0.00 NA
125

Nuckolls 2218 11 0.50 0.50 NA 1.13 1.13 13
Otoe 6060 22 0.36 0.53 0.28 1.33 0.75 61
Pawnee 1339 14 1.05 1.05 1.66 0.00 0.00 27
Perkins 1275 0 0.00 0.00 0.00 0.00 0.00 0
Phelps 3844 12 0.31 0.40 0.46 0.00 0.00 25
Pierce 2979 18 0.60 0.60 NA 0.00 0.00 52
Platte 12076 38 0.31 0.56 0.47 0.20 0.59 63
Polk 2259 8 0.35 0.35 0.86 1.40 1.40 13
Red Willow 4710 4 0.08 0.29 NA 0.00 0.00 NA
Richardson 3993 14 0.35 0.66 0.43 0.91 1.40 23
Rock 763 2 0.26 0.26 NA 0.00 0.00 NA
Saline 5188 41 0.79 0.54 1.36 2.00 0.82 88
Sarpy 43426 96 0.22 0.22 0.14 1.09 0.00 286
Saunders 7498 33 0.44 0.56 NA 0.76 1.08 75
Scotts Bluff 14887 69 0.46 0.53 0.55 0.90 0.57 142
Seward 6013 20 0.33 0.54 0.31 0.19 0.30 41
Sheridan 2549 8 0.31 0.31 0.00 1.30 1.30 16
Sherman 1394 12 0.86 0.86 1.84 3.96 3.96 18
Sioux 605 6 0.99 0.99 NA 0.00 0.00 19
Stanton 2297 19 0.83 1.08 1.47 2.60 3.11 25
Thayer 2541 18 0.71 0.71 NA 4.14 4.14 26
Thomas 325 0 0.00 0.00 0.00 0.00 0.00 0
Thurston 2255 14 0.62 0.62 NA 0.84 0.84 32
Valley 1965 0 0.00 0.00 0.00 0.00 0.00 0
Washington 6940 15 0.22 0.36 0.36 2.05 5.45 21
Wayne 3437 10 0.29 0.50 NA 1.25 2.94 19
Webster 1708 5 0.29 0.29 NA 0.00 0.00 12
Wheeler 352 0 0.00 0.00 0.00 0.00 0.00 0
York 5722 7 0.12 0.28 0.30 0.43 1.23 10
126
NEVADA (NV)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
39 3638 0.48 1893 0.41 471 0.76 483 0.96
Nevada (NV) Occupied Housing Units (OHU)

Churchill 8912 33 0.37 1.09 NA 0.00 0.00 69
Clark 512253 2178 0.43 0.43 0.37 0.99 1.71 5809
Douglas 16401 58 0.35 0.33 0.00 2.80 2.07 254
Elko 15638 162 1.04 1.09 1.44 3.45 5.40 410
Esmeralda 455 7 1.54 1.54 NA 9.09 9.09 15
Eureka 666 16 2.40 2.40 NA 6.25 6.25 39
Humboldt 5733 34 0.59 0.93 NA 2.40 2.44 46
Lander 2093 0 0.00 0.00 0.00 0.00 0.00 0
Lincoln 1540 5 0.32 0.32 0.00 0.65 0.65 7
127
Nevada (NV) Occupied Housing Units (OHU)

Lyon 13007 93 0.71 1.22 0.68 2.10 4.21 213
Mineral 2197 8 0.36 1.21 0.00 1.16 2.40 14
Nye 13309 134 1.01 1.06 0.44 3.35 1.41 346
Pershing 1962 28 1.43 1.43 3.42 1.79 1.79 57
Storey 1462 7 0.48 0.50 3.74 0.00 0.00 17
Washoe 132084 844 0.64 0.44 0.37 1.70 1.41 2132
White Pine 3282 4 0.12 0.00 0.00 0.00 0.00 8
Carson City 20171 27 0.13 0.23 0.00 0.00 0.00 62
128
NEW HAMPSHIRE (NH)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
41 2254 0.47 2363 0.57 1296 0.69 1746 0.90

Belknap 22459 70 0.31 0.33 0.32 0.68 0.44 181
Carroll 18351 160 0.87 0.87 0.52 2.63 2.63 315
Cheshire 28299 211 0.75 1.02 0.67 2.05 4.09 370
Coos 13961 84 0.60 0.81 0.78 0.61 1.08 152
Grafton 31598 217 0.69 0.96 0.78 2.87 5.11 368
Hillsborough 144455 538 0.37 0.56 0.19 0.70 1.58 1256
Merrimack 51843 287 0.55 0.79 0.54 2.19 4.55 527
Rockingham 104529 306 0.29 0.28 0.27 1.74 1.74 737
Strafford 42581 280 0.66 0.70 0.63 1.22 2.85 547
Sullivan 16530 101 0.61 0.82 0.35 1.64 4.38 218
129
NEW JERSEY (NJ)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
30 16530 0.54 12914 0.46 488 0.30 973 0.35
New Jersey (NJ) Occupied Housing Units (OHU)

Atlantic 95024 419 0.44 0.29 0.26 1.08 1.59 1140
Bergen 330817 1483 0.45 1.53 0.34 1.29 0.00 3905
Burlington 154371 321 0.21 0.54 0.24 0.57 1.72 788
Camden 185744 1078 0.58 0.36 0.31 2.30 0.00 3295
Cape May 42148 126 0.30 0.58 0.15 0.73 0.22 339
Cumberland 49143 235 0.48 0.20 0.32 0.70 0.00 600
Essex 283736 2651 0.93 0.00 0.74 2.00 0.00 6891
Gloucester 90717 244 0.27 0.20 0.29 1.22 1.55 594
Hudson 230546 2758 1.20 0.00 0.84 2.24 0.00 7050
Hunterdon 43678 155 0.35 0.38 0.45 0.81 0.34 317
Mercer 125807 589 0.47 0.00 0.35 1.75 0.00 1697
Middlesex 265815 1023 0.38 0.77 0.24 0.85 0.00 3200
Monmouth 224236 800 0.36 0.35 0.25 1.29 1.03 2183
Morris 169711 569 0.34 0.16 0.27 0.79 0.00 1532
Ocean 200402 502 0.25 0.16 0.16 0.44 0.00 1418
Passaic 163856 1436 0.88 0.33 0.41 2.57 0.00 4517
130
New Jersey (NJ) Occupied Housing Units (OHU)

Salem 24295 107 0.44 0.42 0.47 1.20 0.79 216
Somerset 108984 351 0.32 0.36 0.13 1.66 0.00 949
Sussex 50831 108 0.21 0.12 0.07 1.26 0.00 207
Union 186124 1465 0.79 0.00 0.28 2.65 0.00 4040
Warren 38660 110 0.28 0.29 0.37 0.86 0.57 212
131
NEW MEXICO (NM)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
3 11905 1.76 11898 2.19 9095 5.73 10173 7.60
New Mexico (NM) Occupied Housing Units (OHU)

Bernalillo 220936 1051 0.48 3.31 0.46 1.12 14.99 2774
Catron 1584 75 4.73 4.73 1.65 11.90 11.90 143
Chaves 22561 128 0.57 0.70 0.41 1.56 1.66 324
Cibola 8327 454 5.45 9.53 7.13 10.59 17.06 1361
Colfax 5821 23 0.40 0.34 0.64 0.71 1.80 64
Curry 16766 74 0.44 1.00 0.71 1.33 6.45 175
De Baca 922 4 0.43 0.43 NA 2.29 2.29 8
Dona Ana 59556 524 0.88 1.17 0.86 2.12 2.93 1903
Eddy 19379 146 0.75 1.05 0.64 2.21 4.32 375
Grant 12146 166 1.37 2.47 1.18 3.68 7.89 307
Guadalupe 1655 16 0.97 1.58 2.15 1.01 0.52 22
Harding 371 8 2.16 2.16 0.00 7.58 7.58 15
132
New Mexico (NM) Occupied Housing Units (OHU)

Hidalgo 2152 44 2.04 2.76 1.20 3.58 4.72 70
Lea 19699 86 0.44 0.34 0.35 1.30 1.07 178
Lincoln 8202 72 0.88 1.43 0.50 1.94 2.82 110
Los Alamos 7497 11 0.15 0.00 0.00 0.00 0.00 31
Luna 9397 143 1.52 1.83 1.17 3.04 4.41 399
McKinley 21476 3917 18.24 30.21 24.10 31.31 42.50 12666
Mora 2017 109 5.40 5.40 6.44 11.25 11.25 248
Otero 22984 196 0.85 1.00 0.75 1.52 1.00 515
Quay 4201 68 1.62 1.91 1.81 3.20 7.89 160
Rio Arriba 15044 471 3.13 4.72 2.24 6.90 10.80 1177
Roosevelt 6639 27 0.41 0.39 0.00 0.39 1.47 117
Sandoval 31411 594 1.89 7.36 1.51 11.36 21.76 1853
San Juan 37711 1686 4.47 10.77 5.42 13.54 25.26 5015
San Miguel 11134 257 2.31 4.61 1.26 4.52 10.66 531
Santa Fe 52482 361 0.69 1.66 0.24 1.91 6.35 645
Sierra 6113 84 1.37 3.05 0.26 3.50 6.93 134
Socorro 6675 177 2.65 4.35 1.75 5.64 10.65 554
Taos 12675 578 4.56 6.15 2.23 8.05 12.53 1064
Torrance 6024 137 2.27 2.39 2.41 2.83 2.99 316
Union 1733 0 0.00 0.00 0.00 0.00 0.00 0
Valencia 22681 218 0.96 1.67 0.18 2.22 6.79 587
133
NEW YORK (NY)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
11 58418 0.83 50428 0.76 5354 0.61 7750 0.78
New York (NY) Occupied Housing Units (OHU)

Percent of
Total Facilities (as % of (as % of years in level in poverty level population
County OHU (OHULP) OHU) Rural OHU) OHULP 1999 in 1999 in OHULP
Albany 120512 537 0.45 0.40 0.34 1.20 1.85 1104
Allegany 18009 158 0.88 0.99 0.69 2.35 2.65 348
Bronx 463212 7440 1.61 0.00 1.08 2.42 0.00 22340
Broome 80749 359 0.44 0.52 0.36 1.31 2.72 660
Cattaraugus 32023 372 1.16 1.86 1.16 3.59 6.57 1652
Cayuga 30558 131 0.43 0.62 0.50 1.17 1.91 261
Chautauqua 54515 291 0.53 0.85 0.20 1.16 2.44 764
Chemung 35049 145 0.41 0.63 0.40 1.46 4.24 244
Chenango 19926 123 0.62 0.75 0.57 1.88 2.49 237
Clinton 29423 212 0.72 0.76 0.62 1.65 1.63 396
134

Percent of
Columbia 24796 74 0.30 0.26 0.24 0.40 0.76 113
Cortland 18210 113 0.62 0.57 1.77 1.00 1.78 202
Delaware 19270 115 0.60 0.52 0.77 1.25 0.98 149
Dutchess 99536 381 0.38 0.38 0.23 1.00 0.58 858
Erie 380873 1637 0.43 0.43 0.30 1.19 1.38 3735
Essex 15028 86 0.57 0.61 0.29 0.87 1.04 170
Franklin 17931 116 0.65 0.77 0.57 1.56 2.56 215
Fulton 21884 153 0.70 0.96 0.96 1.61 2.24 275
Genesee 22770 73 0.32 0.56 0.42 1.19 2.77 220
Greene 18256 81 0.44 0.58 0.68 1.42 2.04 175
Hamilton 2362 20 0.85 0.85 1.30 1.59 1.59 31
Herkimer 25734 128 0.50 0.70 0.60 1.26 1.96 255
Jefferson 40068 243 0.61 0.64 0.66 1.13 2.41 587
Kings 880727 13114 1.49 0.00 1.23 2.41 0.00 37260
Lewis 10040 80 0.80 0.92 1.19 1.86 2.22 164
Livingston 22150 76 0.34 0.38 0.31 0.69 1.42 173
Madison 25368 107 0.42 0.47 0.39 0.71 0.91 225
Monroe 286512 1207 0.42 0.19 0.44 0.97 0.00 2720
Montgomery 20038 146 0.73 1.06 0.46 2.08 3.59 503
Nassau 447387 1605 0.36 0.41 0.31 0.95 0.00 4938
New York 738644 11061 1.50 0.00 1.50 3.39 0.00 23740
Niagara 87846 346 0.39 0.27 0.28 1.07 1.25 808
Oneida 90496 314 0.35 0.49 0.42 0.61 1.20 593
Onondaga 181153 782 0.43 0.37 0.28 0.98 0.51 1617
Ontario 38370 148 0.39 0.47 0.17 1.61 1.83 332
Orange 114788 428 0.37 0.33 0.27 1.19 0.66 1094
Orleans 15363 65 0.42 0.35 0.47 0.56 1.29 117
Oswego 45522 154 0.34 0.38 0.24 0.33 0.27 357
Otsego 23291 80 0.34 0.42 0.39 0.58 0.74 156
Putnam 32703 84 0.26 0.21 0.00 0.00 0.00 203
Queens 782664 7628 0.97 0.00 0.68 1.85 0.00 23956
Rensselaer 59894 351 0.59 0.84 0.54 1.82 2.11 733
Richmond 156341 710 0.45 0.00 0.42 1.06 0.00 1909
Rockland 92675 430 0.46 0.96 0.60 0.34 0.00 1368
St. Lawrence 40506 461 1.14 1.53 0.60 2.47 3.93 1525
Saratoga 78165 212 0.27 0.54 0.36 0.86 2.26 442
Schenectady 59684 195 0.33 0.55 0.26 0.68 0.00 407
Schoharie 11991 94 0.78 0.85 0.74 1.79 2.25 144
Schuyler 7374 39 0.53 0.66 NA 3.15 4.23 101
Seneca 12630 53 0.42 0.69 0.53 0.83 1.94 168
Steuben 39071 307 0.79 1.19 0.46 1.98 3.66 993
Suffolk 469299 1575 0.34 0.34 0.33 0.71 1.09 5086
Sullivan 27661 214 0.77 0.65 0.55 0.85 0.52 446
Tioga 19725 77 0.39 0.38 0.44 2.22 1.35 122
Tompkins 36420 206 0.57 0.52 0.45 1.57 2.43 333
Ulster 67499 317 0.47 0.38 0.54 1.07 1.26 640
Warren 25726 162 0.63 0.94 0.38 3.99 5.40 359
Washington 22458 158 0.70 0.89 0.47 1.76 3.19 311
Wayne 34908 158 0.45 0.50 0.88 1.92 2.86 362
Westchester 337142 2178 0.65 0.06 0.32 1.44 0.00 5857
Wyoming 14906 42 0.28 0.44 0.20 0.51 0.88 85
135

Percent of
Yates 9029 66 0.73 1.02 1.18 0.61 1.02 144
136
NORTH CAROLINA (NC)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
23 19295 0.62 33192 1.32 10564 0.85 27743 2.26
North Carolina (NC) Occupied Housing Units (OHU)

Percent of Percent of
Lacking Rural Percent of OHULP Percent of
Complete Percent of OHULP population below Rural OHULP
Plumbing OHULP (as % of above 65 poverty below Total
Total Facilities (as % of Rural years in level in poverty level population
County OHU (OHULP) OHU) OHU) OHULP 1999 in 1999 in OHULP
Alamance 51584 223 0.43 0.58 0.56 0.80 2.19 468
Alexander 13137 62 0.47 0.51 1.18 0.46 0.56 99
Alleghany 4593 23 0.50 0.50 NA 1.82 1.82 26
Anson 9204 103 1.12 1.30 1.21 1.74 1.93 217
Ashe 10411 99 0.95 0.95 1.77 0.78 0.78 161
Avery 6532 27 0.41 0.41 0.51 2.08 2.08 40
Beaufort 18319 208 1.14 1.46 1.60 2.71 4.20 574
Bertie 7743 192 2.48 2.48 1.98 5.75 5.75 411
Bladen 12897 116 0.90 0.70 0.68 2.49 2.60 252
Brunswick 30438 188 0.62 0.61 0.36 1.22 1.56 357
Buncombe 85776 272 0.32 0.26 0.54 0.54 1.47 517
Burke 34528 166 0.48 0.76 0.99 0.69 1.13 358
Cabarrus 49519 138 0.28 0.40 0.58 0.00 0.00 302
Caldwell 30768 161 0.52 0.56 0.53 1.12 1.22 335
137

Camden 2662 21 0.79 0.79 3.59 0.00 0.00 64
Carteret 25204 60 0.24 0.41 0.32 0.00 0.00 109
Caswell 8670 123 1.42 1.42 0.72 2.78 2.78 265
Catawba 55533 204 0.37 0.43 0.33 1.15 1.43 397
Chatham 19741 219 1.11 1.29 1.58 3.73 4.65 547
Cherokee 10336 96 0.93 0.93 0.81 3.18 3.18 150
Chowan 5580 67 1.20 1.00 1.14 3.88 4.07 153
Clay 3847 54 1.40 1.40 1.34 3.11 3.11 173
Cleveland 37046 195 0.53 0.74 0.24 1.64 2.09 568
Columbus 21308 211 0.99 1.01 0.43 2.33 2.30 444
Craven 34582 193 0.56 0.83 0.42 0.73 0.81 509
Cumberland 107358 711 0.66 0.58 0.60 1.26 2.10 1787
Currituck 6902 32 0.46 0.46 1.17 0.00 0.00 104
Dare 12690 27 0.21 0.40 0.00 0.58 0.00 44
Davidson 58156 445 0.77 0.39 0.76 0.88 0.00 804
Davie 13750 101 0.73 0.76 1.26 2.50 2.23 170
Duplin 18267 276 1.51 1.75 1.15 2.90 3.61 643
Durham 89015 430 0.48 0.57 0.54 0.83 0.00 1207
Edgecombe 20392 300 1.47 2.20 1.22 2.97 5.67 962
Forsyth 123851 505 0.41 0.32 0.42 0.82 0.46 1261
Franklin 17843 291 1.63 1.66 2.82 5.42 5.82 653
Gaston 73936 367 0.50 0.38 0.58 1.45 1.68 868
Gates 3901 72 1.85 1.85 1.01 4.76 4.76 158
Graham 3354 10 0.30 0.30 0.49 1.45 1.45 9
Granville 16654 269 1.62 2.10 2.67 6.39 9.33 641
Greene 6696 149 2.23 2.23 4.27 8.53 8.53 427
Guilford 168667 816 0.48 0.62 0.28 1.06 1.44 2025
Halifax 22122 530 2.40 3.49 1.83 5.99 8.14 1143
Harnett 33800 237 0.70 0.82 0.87 1.79 2.62 602
Haywood 23100 104 0.45 0.80 0.51 1.93 3.14 177
Henderson 37414 143 0.38 0.48 0.21 1.08 0.41 402
Hertford 8953 110 1.23 1.31 1.53 1.62 1.94 308
Hoke 11373 152 1.34 2.03 2.60 2.90 4.16 456
Hyde 2185 24 1.10 1.10 1.88 4.16 4.16 42
Iredell 47360 156 0.33 0.39 0.38 0.85 0.51 300
Jackson 13191 129 0.98 1.07 1.47 1.37 1.36 333
Johnston 46595 236 0.51 0.53 0.76 1.53 1.81 521
Jones 4061 40 0.98 0.98 1.15 4.09 4.09 51
Lee 18466 75 0.41 0.17 0.18 2.49 2.03 254
Lenoir 23862 229 0.96 0.87 0.94 2.20 2.35 467
Lincoln 24041 96 0.40 0.27 0.54 1.29 0.56 278
McDowell 16604 115 0.69 0.75 0.98 1.98 2.94 201
Macon 12828 50 0.39 0.48 0.56 1.10 1.54 76
Madison 8000 120 1.50 1.50 2.38 2.29 2.29 193
Martin 10020 152 1.52 1.66 1.09 3.47 4.62 352
Mecklenburg 273416 1118 0.41 0.41 0.47 0.94 0.00 3200
Mitchell 6551 66 1.01 1.01 1.86 1.90 1.90 111
Montgomery 9848 90 0.91 0.96 0.50 1.10 1.21 217
Moore 30713 234 0.76 1.24 0.82 3.05 4.76 548
Nash 33644 516 1.53 2.21 1.33 3.97 5.56 1174
New Hanover 68183 237 0.35 0.00 0.42 0.63 0.00 562
138

Northampton 8691 177 2.04 2.18 1.42 4.91 5.60 330
Onslow 48122 213 0.44 0.65 0.66 0.71 1.89 378
Orange 45863 297 0.65 0.71 0.35 2.82 4.46 560
Pamlico 5178 43 0.83 0.83 1.50 2.91 2.91 129
Pasquotank 12907 73 0.57 0.57 0.51 1.80 2.87 137
Pender 16054 69 0.43 0.44 0.68 1.58 1.63 133
Perquimans 4645 51 1.10 1.10 1.27 2.91 2.91 145
Person 14085 166 1.18 1.56 1.79 2.76 3.68 404
Pitt 52539 382 0.73 1.27 0.87 1.36 3.26 983
Polk 7908 51 0.64 0.58 0.91 2.13 2.35 150
Randolph 50659 276 0.54 0.59 1.16 1.45 2.19 595
Richmond 17873 130 0.73 1.10 0.34 1.20 2.30 238
Robeson 43677 341 0.78 0.81 0.97 1.25 1.43 781
Rockingham 36989 225 0.61 0.64 0.39 1.32 2.00 546
Rowan 49940 181 0.36 0.38 0.43 0.80 0.39 487
Rutherford 25191 165 0.65 0.64 0.45 2.13 2.59 393
Sampson 22273 237 1.06 1.20 1.23 2.95 3.27 527
Scotland 13399 140 1.04 1.04 1.87 1.64 1.57 256
Stanly 22223 98 0.44 0.45 0.46 1.73 2.72 185
Stokes 17579 173 0.98 1.23 1.22 4.05 4.77 429
Surry 28408 259 0.91 0.76 1.59 1.83 1.51 523
Swain 5137 73 1.42 1.42 0.49 4.52 4.52 129
Transylvania 12320 32 0.26 0.33 0.24 0.48 0.00 64
Tyrrell 1537 34 2.21 2.21 1.15 4.89 4.89 67
Union 43390 162 0.37 0.49 0.40 0.76 1.17 451
Vance 16199 217 1.34 1.69 1.15 2.77 4.76 602
Wake 242040 839 0.35 0.56 0.35 0.99 1.95 2046
Warren 7708 139 1.80 1.80 2.03 4.73 4.73 336
Washington 5367 63 1.17 1.37 0.00 0.62 0.00 188
Watauga 16540 94 0.57 0.68 1.03 0.39 0.48 155
Wayne 42612 264 0.62 0.48 0.55 1.30 1.84 652
Wilkes 26650 112 0.42 0.44 0.81 0.66 0.92 248
Wilson 28613 243 0.85 0.91 0.29 1.58 1.38 632
Yadkin 14505 49 0.34 0.31 0.25 0.79 0.83 138
Yancey 7472 46 0.62 0.62 0.36 1.75 1.75 91
139
NORTH DAKOTA (ND)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
45 1124 0.44 1558 0.65 675 0.61 1209 1.10
North Dakota (ND) Occupied Housing Units (OHU)

Adams 1121 8 0.71 0.71 1.46 1.39 1.39 13
Barnes 4884 37 0.76 1.30 0.75 1.44 4.69 55
Benson 2328 22 0.95 0.95 1.20 2.33 2.33 27
Billings 366 6 1.64 1.64 NA 0.00 0.00 9
Bottineau 2962 16 0.54 0.54 1.36 0.00 0.00 23
Bowman 1358 2 0.15 0.15 0.00 0.00 0.00 NA
Burke 1013 6 0.59 0.59 NA 1.17 1.17 15
Burleigh 27670 47 0.17 0.41 0.10 0.54 0.97 74
Cass 51315 213 0.42 0.18 0.41 0.73 0.31 332
Cavalier 2017 10 0.50 0.50 0.81 1.79 1.79 12
140
North Dakota (ND) Occupied Housing Units (OHU)

Dickey 2283 9 0.39 0.39 0.84 0.91 0.91 10
Divide 1005 8 0.80 0.80 NA 1.75 1.75 10
Dunn 1378 9 0.65 0.65 0.00 0.00 0.00 15
Eddy 1164 0 0.00 0.00 0.00 0.00 0.00 0
Emmons 1786 2 0.11 0.11 NA 0.00 0.00 NA
Foster 1540 4 0.26 0.26 0.00 0.00 0.00 19
Golden Valley 761 2 0.26 0.26 0.00 0.00 0.00 NA
Grand Forks 25435 96 0.38 0.53 0.41 0.94 2.70 166
Grant 1195 9 0.75 0.75 NA 0.84 0.84 14
Griggs 1178 2 0.17 0.17 0.00 0.00 0.00 NA
Hettinger 1152 4 0.35 0.35 NA 0.00 0.00 NA
Kidder 1158 7 0.60 0.60 NA 0.00 0.00 9
LaMoure 1942 19 0.98 0.98 0.87 1.78 1.78 38
Logan 963 12 1.25 1.25 1.95 0.00 0.00 17
McHenry 2526 36 1.43 1.43 1.54 4.90 4.90 61
McIntosh 1467 9 0.61 0.61 NA 0.79 0.79 16
McKenzie 2151 16 0.74 0.74 1.42 1.39 1.39 45
McLean 3815 18 0.47 0.47 0.52 0.54 0.54 38
Mercer 3346 11 0.33 0.50 0.72 0.00 0.00 31
Morton 9889 51 0.52 0.78 0.29 2.03 3.75 98
Mountrail 2560 20 0.78 0.78 NA 1.57 1.57 30
Nelson 1628 2 0.12 0.12 0.00 0.00 0.00 NA
Oliver 791 10 1.26 1.26 NA 5.41 5.41 17
Pembina 3535 4 0.11 0.11 NA 0.00 0.00 25
Pierce 1964 12 0.61 1.69 NA 2.47 9.86 43
Ramsey 4957 20 0.40 0.68 0.54 0.98 3.70 29
Ransom 2350 15 0.64 0.64 0.68 0.00 0.00 22
Renville 1085 4 0.37 0.37 NA 0.00 0.00 9
Richland 6885 44 0.64 0.50 0.66 0.56 1.64 70
Rolette 4556 37 0.81 0.81 NA 1.22 1.22 110
Sargent 1786 9 0.50 0.50 NA 1.11 1.11 15
Sheridan 731 7 0.96 0.96 0.00 3.90 3.90 11
Sioux 1095 31 2.83 2.83 0.00 4.11 4.11 73
Slope 313 3 0.96 0.96 0.00 4.62 4.62 NA
Stark 8932 27 0.30 0.80 0.69 1.19 2.76 47
Steele 923 5 0.54 0.54 NA 4.29 4.29 NA
Stutsman 8954 37 0.41 1.21 0.54 0.40 1.68 72
Towner 1218 4 0.33 0.33 0.00 1.63 1.63 13
Traill 3341 15 0.45 0.45 NA 1.10 1.10 27
Walsh 5029 30 0.60 0.93 0.95 2.39 3.63 59
Ward 23041 68 0.30 0.34 0.43 1.31 1.49 122
Wells 2215 14 0.63 0.63 1.39 0.00 0.00 33
Williams 8095 15 0.19 0.34 0.37 0.20 0.72 17
141
OHIO (OH)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
47 19407 0.44 24394 0.60 7355 0.79 14480 1.49
Ohio (OH) Occupied Housing Units (OHU)

Adams 10501 294 2.80 3.07 3.92 6.68 7.25 632
Allen 40646 88 0.22 0.15 0.20 0.50 0.00 185
Ashland 19524 217 1.11 1.90 0.68 5.33 13.34 1276
Ashtabula 39397 250 0.63 1.00 0.84 2.06 5.41 816
Athens 22501 274 1.22 2.35 1.09 1.88 6.23 470
Auglaize 17376 59 0.34 0.50 0.33 1.10 3.59 100
Belmont 28309 201 0.71 1.21 0.58 1.35 2.43 485
Brown 15555 140 0.90 0.99 1.65 2.34 3.49 315
Butler 123082 399 0.32 0.50 0.31 0.88 1.93 817
Carroll 11126 52 0.47 0.57 0.68 0.89 1.55 111
Champaign 14952 69 0.46 0.57 1.37 2.03 3.64 127
142

Clark 56648 190 0.34 0.18 0.17 1.01 0.33 348
Clermont 66013 192 0.29 0.44 0.56 0.87 0.82 521
Clinton 15416 101 0.66 0.85 1.05 2.10 2.17 176
Columbiana 42973 167 0.39 0.50 0.43 0.77 1.32 323
Coshocton 14356 99 0.69 0.81 1.10 2.75 4.65 274
Crawford 18957 74 0.39 0.25 0.25 0.29 1.56 180
Cuyahoga 571457 2589 0.45 0.00 0.32 1.11 0.00 6068
Darke 20419 69 0.34 0.42 0.31 1.35 2.03 122
Defiance 15138 82 0.54 0.56 0.77 2.00 2.47 118
Delaware 39674 53 0.13 0.23 NA 0.13 0.00 112
Erie 31727 120 0.38 0.72 0.33 1.32 1.35 331
Fairfield 45425 83 0.18 0.27 0.24 0.53 2.04 186
Fayette 11054 19 0.17 0.29 0.24 0.72 2.02 55
Franklin 438778 1552 0.35 0.16 0.29 0.93 0.00 3091
Fulton 15480 57 0.37 0.44 0.52 1.77 3.42 87
Gallia 12060 120 1.00 1.16 0.93 2.67 3.23 229
Geauga 31630 185 0.58 0.85 0.52 3.01 5.07 918
Greene 55312 166 0.30 0.45 0.30 0.92 4.15 348
Guernsey 16094 184 1.14 1.73 0.31 1.52 3.23 620
Hamilton 346790 1388 0.40 0.40 0.21 1.08 2.63 3327
Hancock 27898 49 0.18 0.29 0.20 0.94 1.83 124
Hardin 11963 140 1.17 1.74 1.00 4.61 9.06 775
Harrison 6398 62 0.97 1.05 0.59 2.03 1.63 98
Henry 10935 34 0.31 0.39 0.21 1.63 1.38 143
Highland 15587 123 0.79 0.92 1.68 2.60 3.31 266
Hocking 10843 154 1.42 1.98 1.69 3.83 6.40 261
Holmes 11337 175 1.54 1.72 2.47 5.60 6.29 858
Huron 22307 107 0.48 0.42 0.20 1.67 2.52 223
Jackson 12619 122 0.97 1.59 0.71 2.68 5.10 196
Jefferson 30417 149 0.49 0.65 0.32 1.11 1.64 317
Knox 19975 210 1.05 1.64 1.13 2.67 5.69 668
Lake 89700 170 0.19 0.00 0.16 0.74 0.00 380
Lawrence 24732 195 0.79 1.47 1.24 1.54 2.69 496
Licking 55609 187 0.34 0.58 0.35 1.25 4.42 444
Logan 17956 70 0.39 0.58 0.59 1.99 3.61 254
Lorain 105836 217 0.21 0.14 0.16 0.66 0.32 510
Lucas 182847 688 0.38 0.64 0.46 0.80 1.24 1425
Madison 13672 54 0.39 0.53 0.58 2.19 5.12 101
Mahoning 102587 442 0.43 0.40 0.25 1.07 0.88 1173
Marion 24578 102 0.42 0.62 NA 0.26 1.48 281
Medina 54542 224 0.41 0.93 0.44 2.69 8.76 1028
Meigs 9234 144 1.56 1.78 2.70 4.08 4.58 287
Mercer 14756 72 0.49 0.63 0.47 1.70 3.49 148
Miami 38437 66 0.17 0.12 0.15 0.67 0.00 126
Monroe 6021 157 2.61 2.67 4.60 4.68 4.75 600
Montgomery 229229 693 0.30 0.36 0.19 0.85 0.00 1627
Morgan 5890 147 2.50 3.11 3.03 5.62 6.99 306
Morrow 11499 102 0.89 1.01 0.23 3.64 4.51 511
Muskingum 32518 221 0.68 1.01 0.70 1.11 2.74 415
Noble 4546 121 2.66 3.36 1.77 8.77 11.62 368
Ottawa 16474 58 0.35 0.51 0.52 1.73 3.90 99
Paulding 7773 55 0.71 0.87 0.37 5.20 6.40 92
143

Perry 12500 83 0.66 0.83 0.38 1.69 1.87 162
Pickaway 17599 73 0.41 0.36 0.61 2.72 3.05 191
Pike 10444 148 1.42 1.84 1.53 5.17 6.07 441
Portage 56449 188 0.33 0.34 0.33 0.20 0.46 435
Preble 16001 75 0.47 0.44 0.00 3.75 3.97 183
Putnam 12200 57 0.47 0.49 0.36 2.74 3.28 112
Richland 49534 279 0.56 0.90 0.31 2.56 9.59 787
Ross 27136 277 1.02 1.29 1.30 3.52 4.68 516
Sandusky 23717 31 0.13 0.27 0.00 0.00 0.00 68
Scioto 30871 263 0.85 1.18 0.63 1.36 1.95 417
Seneca 22292 113 0.51 0.43 0.42 2.05 2.13 268
Shelby 17636 44 0.25 0.26 0.30 0.68 0.00 101
Stark 148316 480 0.32 0.28 0.25 0.98 1.77 1096
Summit 217788 697 0.32 0.02 0.30 0.93 0.00 1461
Trumbull 89020 310 0.35 0.64 0.27 1.00 3.12 886
Tuscarawas 35653 119 0.33 0.31 0.46 0.31 0.61 209
Union 14346 69 0.48 0.53 0.57 2.21 4.42 123
Van Wert 11587 68 0.59 0.81 0.68 1.88 2.55 156
Vinton 4892 156 3.19 3.37 3.31 5.74 5.94 284
Warren 55966 131 0.23 0.52 0.41 0.19 1.06 243
Washington 25137 184 0.73 1.05 0.65 2.38 4.13 413
Wayne 40445 350 0.87 1.39 0.44 4.90 10.97 1652
Williams 15105 50 0.33 0.22 NA 0.51 0.87 145
Wood 45172 90 0.20 0.37 0.14 0.55 0.86 156
Wyandot 8882 29 0.33 0.08 0.22 2.24 0.00 46
144
OKLAHOMA (OK)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
27 7546 0.56 7145 0.59 3883 0.87 4741 1.28
Oklahoma (OK) Occupied Housing Units (OHU)

Adair 7471 130 1.74 2.09 0.79 4.58 5.89 269
Alfalfa 2199 8 0.36 0.36 NA 0.00 0.00 12
Atoka 4964 67 1.35 1.61 0.56 1.80 2.50 134
Beaver 2245 4 0.18 0.18 NA 0.00 0.00 9
Beckham 7356 29 0.39 0.89 0.58 1.63 4.62 26
Blaine 4159 21 0.50 0.41 NA 0.62 0.90 46
Bryan 14422 92 0.64 0.81 0.36 1.47 2.01 183
Caddo 10957 68 0.62 0.68 0.19 1.42 1.44 160
Canadian 31484 100 0.32 0.75 0.32 0.71 2.70 243
Carter 17992 93 0.52 0.65 0.30 1.22 1.75 206
145

Cherokee 16175 203 1.26 1.78 1.03 1.69 3.13 399
Choctaw 6220 71 1.14 1.47 0.84 1.75 2.43 153
Cimarron 1257 8 0.64 0.64 NA 3.92 3.92 8
Cleveland 79186 288 0.36 0.62 0.41 0.39 1.50 731
Coal 2373 33 1.39 1.39 1.66 2.15 2.15 48
Comanche 39808 200 0.50 0.74 0.21 0.47 2.04 451
Cotton 2614 20 0.77 0.91 1.07 2.17 3.21 45
Craig 5620 35 0.62 0.79 0.44 1.86 2.37 65
Creek 25289 149 0.59 0.87 0.46 1.28 2.64 256
Custer 10136 56 0.55 0.55 0.85 0.89 0.95 136
Delaware 14838 160 1.08 1.32 0.70 2.48 2.90 356
Dewey 1962 4 0.20 0.20 NA 0.62 0.62 9
Ellis 1769 13 0.73 0.73 NA 1.69 1.69 22
Garfield 23175 64 0.28 0.44 0.31 0.66 0.68 128
Garvin 10865 85 0.78 1.17 0.43 2.24 3.52 157
Grady 17341 51 0.29 0.37 0.21 1.15 1.85 119
Grant 2089 4 0.19 0.19 0.00 0.00 0.00 NA
Greer 2237 22 0.98 2.11 0.59 0.68 1.70 29
Harmon 1266 6 0.47 0.47 0.00 0.00 0.00 10
Harper 1509 8 0.53 0.53 NA 0.00 0.00 20
Haskell 4624 79 1.71 2.08 1.44 2.46 3.49 180
Hughes 5319 62 1.17 1.67 0.63 2.23 2.81 120
Jackson 10590 30 0.28 0.44 0.26 0.71 1.36 55
Jefferson 2716 18 0.66 0.66 0.90 1.25 1.25 37
Johnston 4057 54 1.33 1.25 1.23 1.87 2.21 115
Kay 19157 64 0.33 0.62 0.30 1.10 2.18 103
Kingfisher 5247 13 0.25 0.22 0.61 0.37 0.54 19
Kiowa 4208 39 0.93 0.55 0.53 0.94 0.38 109
Latimer 3951 33 0.84 1.14 0.60 0.91 1.45 81
Le Flore 17861 121 0.68 0.84 0.64 1.04 1.59 250
Lincoln 12178 81 0.67 0.72 0.49 1.73 1.93 200
Logan 12389 75 0.61 0.68 0.69 1.67 2.20 147
Love 3442 15 0.44 0.44 NA 1.08 1.08 22
McClain 10331 50 0.48 0.38 0.54 2.30 1.43 149
McCurtain 13216 79 0.60 0.67 0.97 1.06 1.68 206
McIntosh 8085 134 1.66 1.75 1.38 2.31 2.24 337
Major 3046 6 0.20 0.20 NA 0.49 0.49 13
Marshall 5371 39 0.73 0.74 0.45 1.56 1.82 61
Mayes 14823 128 0.86 0.92 0.50 1.91 2.38 271
Murray 5003 41 0.82 1.28 1.54 2.44 3.38 79
Muskogee 26458 192 0.73 1.01 0.38 1.97 2.04 514
Noble 4504 30 0.67 0.85 0.88 3.04 3.01 31
Nowata 4147 46 1.11 0.35 1.03 2.63 1.51 50
Okfuskee 4270 53 1.24 1.40 0.68 1.98 1.83 96
Oklahoma 266834 1206 0.45 0.49 0.35 0.95 1.38 2920
Okmulgee 15300 144 0.94 1.34 1.42 1.97 2.92 316
Osage 16617 124 0.75 0.91 0.70 1.12 1.64 258
Ottawa 12984 105 0.81 1.02 0.49 1.44 1.83 245
Pawnee 6383 63 0.99 1.06 NA 2.49 2.93 126
Payne 26680 150 0.56 0.83 0.18 0.70 2.40 260
Pittsburg 17157 202 1.18 1.60 0.75 1.98 2.21 403
Pontotoc 13978 62 0.44 0.60 0.36 0.80 1.97 113
146

Pottawatomie 24540 146 0.59 0.88 0.57 1.50 2.74 429
Pushmataha 4739 96 2.03 2.03 0.95 4.64 4.64 166
Roger Mills 1428 2 0.14 0.14 NA 0.00 0.00 NA
Rogers 25724 102 0.40 0.64 0.68 1.57 3.07 205
Seminole 9575 64 0.67 0.72 1.22 1.26 1.54 119
Sequoyah 14761 169 1.14 1.36 1.47 1.54 1.97 396
Stephens 17463 107 0.61 0.70 0.13 1.35 1.54 255
Texas 7153 24 0.34 0.17 0.00 0.00 0.00 74
Tillman 3594 15 0.42 0.50 0.00 0.66 1.33 25
Tulsa 226892 884 0.39 0.39 0.28 0.85 0.77 2192
Wagoner 21010 125 0.59 0.78 0.70 1.38 2.03 348
Washington 20179 116 0.57 0.53 0.84 0.99 2.30 210
Washita 4506 27 0.60 0.40 0.62 1.80 1.71 58
Woods 3684 14 0.38 0.56 NA 0.00 0.00 27
Woodward 7141 25 0.35 0.26 0.00 0.00 0.00 63
147
OREGON (OR)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
32 7025 0.53 6426 0.58 2256 0.82 3567 1.16
Oregon (OR) Occupied Housing Units (OHU)

Baker 6883 96 1.39 1.45 0.93 4.25 2.65 203
Benton 30145 103 0.34 0.62 0.00 0.78 5.30 233
Clackamas 128201 378 0.29 0.30 0.26 1.21 2.22 895
Clatsop 14703 139 0.95 0.97 0.62 3.28 3.35 267
Columbia 16375 99 0.60 0.70 0.60 3.14 4.28 134
Coos 26213 232 0.89 1.25 0.53 2.94 4.08 416
Crook 7354 35 0.48 0.58 0.56 1.94 2.09 115
Curry 9543 82 0.86 0.73 0.58 1.67 1.46 126
Deschutes 45595 179 0.39 0.51 0.22 1.22 0.29 372
Douglas 39821 251 0.63 0.83 0.26 1.39 2.34 518
148
Oregon (OR) Occupied Housing Units (OHU)

Gilliam 819 2 0.24 0.24 NA 2.38 2.38 NA
Grant 3246 55 1.69 1.69 2.21 3.72 3.72 124
Harney 3036 29 0.96 2.13 1.13 2.43 5.92 40
Hood River 7248 75 1.03 1.35 0.00 2.97 4.42 208
Jackson 71532 307 0.43 0.98 0.32 0.92 2.30 754
Jefferson 6727 77 1.14 1.58 0.35 2.49 4.35 155
Josephine 31000 413 1.33 2.10 0.51 3.69 6.33 796
Klamath 25205 201 0.80 1.13 0.79 2.39 4.62 397
Lake 3084 29 0.94 1.03 1.34 1.67 2.80 47
Lane 130453 587 0.45 0.87 0.20 1.28 3.33 1299
Lincoln 19296 128 0.66 1.40 0.40 2.14 5.17 234
Linn 39541 148 0.37 0.33 0.32 1.10 1.13 443
Malheur 10221 50 0.49 0.31 0.00 1.76 1.97 190
Marion 101641 314 0.31 0.39 0.33 0.96 2.26 778
Morrow 3776 26 0.69 0.67 0.80 0.92 0.00 76
Multnomah 272098 1894 0.70 0.67 0.49 2.05 0.00 3650
Polk 23058 132 0.57 1.51 0.36 1.22 3.66 275
Sherman 797 3 0.38 0.38 0.00 2.54 2.54 NA
Tillamook 10200 37 0.36 0.29 0.32 0.72 1.01 52
Umatilla 25195 187 0.74 0.70 0.62 2.24 1.91 430
Union 9740 45 0.46 0.43 0.49 0.27 0.40 105
Wallowa 3029 36 1.19 1.19 1.45 2.10 2.10 92
Wasco 9401 50 0.53 1.03 0.27 1.24 2.11 95
Washington 169162 514 0.30 0.37 0.22 0.86 1.23 1299
Wheeler 653 7 1.07 1.07 NA 0.00 0.00 14
Yamhill 28732 85 0.30 0.53 NA 1.18 1.55 188
149
PENNSYLVANIA (PA)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
35 24450 0.51 26355 0.59 8112 0.77 14210 1.08
Pennsylvania (PA) Occupied Housing Units (OHU)

Percent of
Complete Percent Rural population below Rural OHULP
Plumbing of OHULP OHULP above 65 poverty below Total
Adams 33652 177 0.53 0.67 0.51 1.36 1.42 324
Allegheny 537150 1932 0.36 0.39 0.35 0.73 0.83 4037
Armstrong 29005 196 0.68 0.84 0.74 2.69 3.46 364
Beaver 72576 271 0.37 0.55 0.55 0.89 3.46 558
Bedford 19768 171 0.87 0.88 0.87 3.12 2.71 373
Berks 141570 881 0.62 0.66 0.49 2.04 3.65 2418
150

Percent of
Blair 51518 111 0.22 0.37 0.29 0.40 0.96 240
Bradford 24453 151 0.62 0.66 0.70 1.59 1.36 246
Bucks 218725 614 0.28 0.37 0.14 0.75 0.00 1713
Butler 65862 215 0.33 0.53 0.48 1.14 2.24 440
Cambria 60531 270 0.45 0.75 0.46 0.98 2.71 556
Cameron 2465 10 0.41 0.98 0.80 0.00 0.00 26
Carbon 23701 103 0.43 0.42 0.70 1.34 1.76 193
Centre 49323 248 0.50 0.60 0.36 0.72 2.31 622
Chester 157905 435 0.28 0.42 0.35 0.92 2.20 1036
Clarion 16052 229 1.43 0.92 1.12 5.97 2.74 584
Clearfield 32785 225 0.69 0.93 0.80 1.94 3.05 551
Clinton 14773 58 0.39 0.63 0.33 0.84 2.15 123
Columbia 24915 131 0.53 0.79 0.61 1.05 2.61 284
Crawford 34678 575 1.66 2.31 0.74 4.89 7.23 2519
Cumberland 83015 273 0.33 0.41 0.28 0.75 0.78 646
Dauphin 102670 449 0.44 0.48 0.41 1.10 0.00 1043
Delaware 206320 661 0.32 0.36 0.19 0.64 0.00 1673
Elk 14124 80 0.57 0.63 0.37 0.89 1.02 185
Erie 106507 454 0.43 0.46 0.33 0.96 1.92 1244
Fayette 59969 348 0.58 0.61 0.81 1.09 1.35 619
Forest 2000 36 1.80 1.80 1.15 4.28 4.28 76
Franklin 50633 353 0.70 1.10 0.86 2.72 5.46 942
Fulton 5660 39 0.69 0.69 1.57 1.42 1.42 58
Greene 15060 174 1.16 1.30 0.67 3.37 4.82 333
Huntingdon 16759 118 0.70 0.79 0.87 2.21 2.72 235
Indiana 34123 418 1.22 1.80 1.11 2.72 5.04 1768
Jefferson 18375 162 0.88 1.25 0.68 2.23 4.47 639
Juniata 8584 65 0.76 0.70 1.16 2.65 2.76 200
Lackawanna 86218 239 0.28 0.28 0.29 0.91 0.83 477
Lancaster 172560 1114 0.65 1.23 0.78 2.62 4.25 3309
Lawrence 37091 360 0.97 1.87 0.96 4.07 9.92 1197
Lebanon 46551 209 0.45 0.72 0.38 1.52 3.00 413
Lehigh 121906 559 0.46 0.35 0.38 1.74 2.04 1450
Luzerne 130687 583 0.45 0.57 0.43 0.84 1.34 1331
Lycoming 47003 184 0.39 0.63 0.36 0.57 1.55 392
McKean 18024 69 0.38 0.45 0.34 1.07 1.07 155
Mercer 46712 466 1.00 1.85 0.48 3.36 8.01 1833
Mifflin 18413 283 1.54 2.71 1.32 4.11 9.78 1097
Monroe 49454 140 0.28 0.32 0.41 0.95 1.59 397
Montgomery 286098 798 0.28 0.07 0.31 0.64 0.00 1977
Montour 7085 54 0.76 0.97 0.68 2.65 6.10 226
Northampton 101541 523 0.52 0.48 0.48 1.45 1.23 1148
Northumberland 38835 207 0.53 0.71 0.63 0.58 0.96 511
Perry 16695 100 0.60 0.64 0.63 2.69 2.92 196
Philadelphia 590071 4877 0.83 0.00 0.60 1.77 0.00 13087
Pike 17433 75 0.43 0.42 0.58 0.24 0.27 184
Potter 7005 51 0.73 0.73 0.76 1.29 1.29 146
Schuylkill 60530 335 0.55 0.60 0.76 1.97 2.82 605
Snyder 13654 294 2.15 2.74 1.71 8.00 12.11 1209
Somerset 31222 164 0.53 0.58 0.51 1.50 1.52 393
Sullivan 2660 45 1.69 1.69 1.60 5.04 5.04 74
Susquehanna 16529 78 0.47 0.50 0.61 1.48 1.59 150
151

Percent of
Tioga 15925 96 0.60 0.63 0.62 1.13 1.50 203
Union 13178 40 0.30 0.47 0.67 1.35 2.50 47
Venango 22747 119 0.52 0.70 0.45 1.05 1.52 255
Warren 17696 136 0.77 1.30 0.53 4.49 7.97 589
Washington 81130 377 0.46 0.42 0.48 1.25 1.34 776
Wayne 18350 68 0.37 0.44 0.15 1.18 1.44 165
Westmoreland 149813 460 0.31 0.50 0.26 0.95 1.55 1068
Wyoming 10762 61 0.57 0.56 0.63 1.16 1.38 133
York 148219 653 0.44 0.52 0.51 1.24 1.08 1421
152
RHODE ISLAND (RI)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
31 2194 0.54 1670 0.44 100 0.29 233 0.47

Total Facilities (as % of (as % of Rural years in poverty level poverty level population
Bristol 19033 59 0.31 0.00 NA 1.07 0.00 160
Kent 67320 285 0.42 0.16 0.36 1.59 0.00 601
Newport 35228 194 0.55 0.13 0.14 3.01 0.00 304
Providence 239936 1531 0.64 0.38 0.42 1.33 0.00 4300
Washington 46907 125 0.27 0.28 0.22 0.79 1.61 223
153
SOUTH CAROLINA (SC)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
22 9521 0.62 16626 1.32 5476 0.93 12715 2.31
South Carolina (SC) Occupied Housing Units (OHU)

Percent of
Abbeville 10131 99 0.98 0.81 0.38 1.70 1.36 193
Aiken 55587 234 0.42 0.72 0.37 1.04 1.71 506
Allendale 3915 73 1.86 2.14 2.86 2.64 3.49 174
Anderson 65649 268 0.41 0.42 0.42 0.85 1.33 679
Bamberg 6123 50 0.82 0.76 0.00 1.31 1.75 97
Barnwell 9021 123 1.36 1.39 1.65 3.14 2.84 261
Beaufort 45532 139 0.31 0.50 0.05 1.33 2.58 325
Berkeley 49922 203 0.41 0.58 0.71 0.87 0.50 458
Calhoun 5917 81 1.37 1.37 1.71 3.40 3.40 191
Charleston 123326 658 0.53 1.74 0.51 1.15 3.93 1516
Cherokee 20495 131 0.64 0.81 0.53 0.76 0.82 259
154
South Carolina (SC) Occupied Housing Units (OHU)

Percent of
Chester 12880 93 0.72 0.98 0.82 1.17 2.03 184
Chesterfield 16557 235 1.42 1.55 2.28 3.59 4.18 432
Clarendon 11812 165 1.40 1.42 2.21 3.05 3.06 401
Colleton 14470 207 1.43 1.68 1.29 3.29 4.03 588
Darlington 25793 202 0.78 1.03 1.35 1.71 2.72 487
Dillon 11199 209 1.87 2.27 2.66 3.90 4.88 657
Dorchester 34709 237 0.68 1.64 0.41 2.38 3.56 484
Edgefield 8270 65 0.79 0.82 0.91 2.32 3.26 168
Fairfield 8774 152 1.73 2.06 2.19 3.34 5.00 343
Florence 47147 263 0.56 0.59 0.61 1.58 1.64 580
Georgetown 21659 175 0.81 1.41 0.71 1.81 3.33 415
Greenville 149556 630 0.42 0.47 0.40 0.79 1.53 1359
Greenwood 25729 119 0.46 0.64 0.65 0.83 2.30 296
Hampton 7444 67 0.90 0.87 0.85 2.27 2.15 165
Horry 81800 464 0.57 1.02 0.34 2.01 3.28 1094
Jasper 7042 94 1.33 1.52 0.60 1.98 2.28 227
Kershaw 20188 141 0.70 0.53 1.03 2.46 1.91 222
Lancaster 23178 106 0.46 0.55 0.39 1.62 3.17 187
Laurens 26290 177 0.67 0.81 0.99 1.46 2.26 474
Lee 6886 94 1.37 1.52 0.68 1.36 1.45 150
Lexington 83240 332 0.40 0.65 0.52 1.28 2.13 751
McCormick 3558 59 1.66 1.66 1.79 1.36 1.36 160
Marion 13301 170 1.28 1.55 1.74 2.72 3.81 338
Marlboro 10478 137 1.31 2.02 0.80 1.51 3.85 361
Newberry 14026 126 0.90 1.06 1.31 1.88 2.46 294
Oconee 27283 190 0.70 0.79 0.72 1.64 2.71 382
Orangeburg 34118 351 1.03 1.05 1.06 2.54 2.46 854
Pickens 41306 235 0.57 0.75 0.45 1.79 3.22 515
Richland 120101 607 0.51 0.40 0.60 1.18 2.20 1581
Saluda 7127 75 1.05 1.27 1.31 1.89 2.59 259
Spartanburg 97735 507 0.52 0.56 0.43 1.42 2.26 1037
Sumter 37728 241 0.64 0.78 0.79 1.84 1.91 591
Union 12087 115 0.95 1.02 1.94 2.44 3.33 230
Williamsburg 13714 210 1.53 1.62 1.80 2.77 3.09 631
York 61051 212 0.35 0.58 0.64 0.97 2.36 536
155
SOUTH DAKOTA (SD)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
19 1858 0.64 2315 0.89 1312 0.98 1984 1.59
South Dakota (SD) Occupied Housing Units (OHU)

Aurora 1165 10 0.86 0.86 1.76 3.38 3.38 13
Beadle 7210 19 0.26 0.72 NA 0.70 0.88 74
Bennett 1123 28 2.49 2.49 0.00 3.54 3.54 52
Bon Homme 2635 24 0.91 0.91 1.33 1.09 1.09 41
Brookings 10665 38 0.36 0.87 0.60 0.99 6.08 71
Brown 14638 37 0.25 0.35 0.19 0.12 0.60 54
Brule 1998 7 0.35 0.35 NA 1.82 1.82 12
Buffalo 526 18 3.42 3.42 5.88 4.42 4.42 33
Butte 3516 12 0.34 0.00 1.67 0.00 0.00 34
156

Campbell 725 0 0.00 0.00 0.00 0.00 0.00 0
Charles Mix 3343 22 0.66 0.66 0.55 1.65 1.65 41
Clark 1598 2 0.13 0.13 NA 0.90 0.90 NA
Clay 4878 54 1.11 0.00 0.58 3.32 0.00 130
Codington 10357 43 0.42 0.59 0.36 0.18 1.22 108
Corson 1271 50 3.93 3.93 NA 5.86 5.86 166
Custer 2970 26 0.88 0.88 1.67 3.61 3.61 30
Davison 7585 18 0.24 0.13 0.60 0.00 0.00 44
Day 2586 23 0.89 0.89 1.04 3.89 3.89 29
Deuel 1843 11 0.60 0.60 1.16 3.41 3.41 16
Dewey 1863 31 1.66 1.66 NA 0.71 0.71 102
Douglas 1321 11 0.83 0.83 NA 0.00 0.00 25
Edmunds 1681 6 0.36 0.36 NA 0.00 0.00 19
Fall River 3127 47 1.50 1.96 0.64 2.78 3.30 52
Faulk 1014 0 0.00 0.00 0.00 0.00 0.00 0
Grant 3116 25 0.80 0.79 1.67 3.64 3.61 45
Gregory 2022 20 0.99 0.99 NA 2.20 2.20 65
Haakon 870 12 1.38 1.38 2.03 1.71 1.71 34
Hamlin 2048 2 0.10 0.10 0.00 0.00 0.00 NA
Hand 1543 3 0.19 0.19 NA 0.00 0.00 NA
Hanson 1115 21 1.88 1.88 NA 10.00 10.00 80
Harding 525 2 0.38 0.38 0.00 1.75 1.75 NA
Hughes 6512 31 0.48 1.20 0.66 1.39 5.93 60
Hutchinson 3190 17 0.53 0.53 0.87 1.03 1.03 28
Hyde 679 0 0.00 0.00 0.00 0.00 0.00 0
Jackson 945 25 2.65 2.65 NA 6.86 6.86 93
Jerauld 987 0 0.00 0.00 0.00 0.00 0.00 0
Jones 509 3 0.59 0.59 NA 0.00 0.00 NA
Kingsbury 2406 9 0.37 0.37 NA 3.63 3.63 10
Lake 4372 36 0.82 0.63 0.48 2.30 1.49 38
Lawrence 8881 46 0.52 1.18 0.23 0.64 2.11 110
Lincoln 8782 16 0.18 0.30 0.57 2.65 5.16 21
Lyman 1400 2 0.14 0.14 0.00 0.70 0.70 NA
McCook 2204 18 0.82 0.82 2.13 4.15 4.15 34
McPherson 1227 6 0.49 0.49 1.39 0.74 0.74 11
Marshall 1844 17 0.92 0.92 0.91 1.54 1.54 38
Meade 8805 61 0.69 1.23 0.72 0.82 0.00 83
Mellette 694 22 3.17 3.17 5.36 5.17 5.17 43
Miner 1212 9 0.74 0.74 1.43 1.89 1.89 16
Minnehaha 57996 174 0.30 0.32 0.33 1.23 3.17 481
Moody 2526 18 0.71 0.71 1.30 0.78 0.78 37
Pennington 34641 143 0.41 1.13 0.14 0.84 2.96 333
Perkins 1429 10 0.70 0.70 0.94 1.29 1.29 13
Potter 1145 0 0.00 0.00 0.00 0.00 0.00 0
Roberts 3683 27 0.73 0.73 0.66 1.96 1.96 39
Sanborn 1043 8 0.77 0.77 NA 0.67 0.67 17
Shannon 2785 361 12.96 13.75 7.56 15.92 16.70 985
Spink 2847 9 0.32 0.29 0.59 1.78 0.94 13
Stanley 1111 8 0.72 0.00 2.30 3.92 0.00 18
Sully 630 0 0.00 0.00 0.00 0.00 0.00 0
Todd 2462 48 1.95 1.95 2.57 2.30 2.30 118
Tripp 2550 21 0.82 1.77 NA 2.66 5.28 83
157

Turner 3510 13 0.37 0.37 NA 2.01 2.01 18
Union 4927 14 0.28 0.28 NA 0.61 0.73 36
Walworth 2506 13 0.52 0.20 0.00 2.48 0.00 37
Yankton 8187 25 0.31 0.64 0.53 0.75 0.00 61
Ziebach 741 26 3.51 3.51 NA 3.69 3.69 33
158
TENNESSEE (TN)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
18 14340 0.64 23840 1.29 8222 1.04 19438 2.78
Tennessee (TN) Occupied Housing Units (OHU)

Anderson 29780 64 0.21 0.36 0.00 0.37 0.36 128
Bedford 13905 116 0.83 0.57 1.77 2.35 0.26 244
Benton 6863 51 0.74 0.96 0.75 1.20 1.62 127
Bledsoe 4430 99 2.23 2.23 2.10 5.53 5.53 280
Blount 42667 186 0.44 0.84 0.29 1.96 3.96 413
Bradley 34281 150 0.44 0.47 0.29 0.94 0.00 399
Campbell 16125 189 1.17 1.64 0.51 2.51 3.69 337
Cannon 4998 44 0.88 0.88 0.55 0.76 0.76 113
Carroll 11779 46 0.39 0.47 0.63 0.44 0.55 104
Carter 23486 199 0.85 1.45 1.52 2.43 4.39 306
Cheatham 12878 44 0.34 0.37 NA 0.40 0.44 85
Chester 5660 56 0.99 1.09 0.67 4.91 5.58 101
Claiborne 11799 201 1.70 2.36 1.80 5.24 7.15 553
Clay 3379 60 1.78 1.78 1.58 2.21 2.21 103
Cocke 13762 269 1.95 2.89 2.47 4.54 7.57 416
Coffee 18885 86 0.46 0.67 0.46 1.03 2.14 165
Crockett 5632 21 0.37 0.37 1.44 0.99 0.99 68
Cumberland 19508 106 0.54 0.80 0.38 2.14 3.37 217
159

Davidson 237405 1062 0.45 0.63 0.38 0.98 2.17 2907
Decatur 4908 47 0.96 0.96 1.09 3.20 3.20 103
DeKalb 6984 54 0.77 0.99 0.74 0.91 1.34 103
Dickson 16473 64 0.39 0.50 0.25 0.94 0.90 122
Dyer 14751 78 0.53 0.58 1.65 1.30 2.96 194
Fayette 10467 102 0.97 0.97 1.17 3.43 3.43 248
Fentress 6693 87 1.30 1.30 2.03 3.58 3.58 228
Franklin 15003 94 0.63 0.72 0.52 2.24 2.85 179
Gibson 19518 98 0.50 0.62 0.80 0.41 0.60 189
Giles 11713 126 1.08 1.43 0.74 2.61 4.40 327
Grainger 8270 227 2.74 2.74 3.85 9.05 9.05 547
Greene 25756 208 0.81 1.08 1.02 1.60 2.71 396
Grundy 5562 64 1.15 1.15 0.81 3.23 3.23 136
Hamblen 23211 90 0.39 0.51 0.64 0.22 0.00 223
Hamilton 124444 588 0.47 0.93 0.39 0.84 4.07 1445
Hancock 2769 212 7.66 7.66 6.95 11.14 11.14 446
Hardeman 9412 154 1.64 1.84 1.39 3.50 4.45 337
Hardin 10426 112 1.07 1.15 1.60 2.89 3.25 224
Hawkins 21936 365 1.66 2.48 2.30 3.75 5.72 704
Haywood 7558 94 1.24 1.47 2.02 1.80 2.31 247
Henderson 10306 63 0.61 0.80 0.56 1.86 2.42 111
Henry 13019 50 0.38 0.59 0.47 0.81 1.52 69
Hickman 8081 105 1.30 1.30 1.06 2.68 2.68 284
Houston 3216 40 1.24 1.24 1.56 1.43 1.43 47
Humphreys 7238 46 0.64 0.82 0.55 3.17 4.95 107
Jackson 4466 73 1.63 1.63 2.36 2.43 2.43 164
Jefferson 17155 105 0.61 0.81 0.64 2.29 3.75 189
Johnson 6827 172 2.52 2.91 2.84 5.22 6.61 360
Knox 157872 533 0.34 0.86 0.36 0.68 1.74 1137
Lake 2410 26 1.08 1.08 1.86 2.86 2.86 43
Lauderdale 9567 86 0.90 1.02 1.22 1.61 2.39 200
Lawrence 15480 312 2.02 2.82 1.44 5.69 8.46 1424
Lewis 4381 50 1.14 1.66 NA 1.80 3.17 113
Lincoln 12503 110 0.88 1.13 2.10 1.70 2.43 193
Loudon 15944 42 0.26 0.12 0.29 0.41 0.00 103
McMinn 19721 125 0.63 0.79 0.63 1.36 2.66 239
McNairy 9980 77 0.77 0.83 0.28 2.44 2.47 103
Macon 7916 134 1.69 1.99 2.68 5.00 5.80 243
Madison 35552 148 0.42 0.33 0.63 1.20 2.23 395
Marion 11037 123 1.11 1.29 1.52 1.94 2.03 277
Marshall 10307 37 0.36 0.38 0.48 1.00 2.43 63
Maury 26444 124 0.47 0.67 0.64 1.59 4.03 201
Meigs 4304 52 1.21 1.21 0.73 4.67 4.67 214
Monroe 15329 163 1.06 1.33 1.40 2.68 3.49 315
Montgomery 48330 243 0.50 0.47 0.39 1.06 0.70 567
Moore 2211 5 0.23 0.23 NA 1.98 1.98 NA
Morgan 6990 92 1.32 1.37 1.19 4.67 5.49 238
Obion 13182 70 0.53 0.42 0.79 1.23 0.56 123
Overton 8110 123 1.52 1.72 3.13 5.03 6.37 366
Perry 3023 35 1.16 1.16 NA 4.02 4.02 133
Pickett 2091 31 1.48 1.48 3.97 0.57 0.57 74
Polk 6448 84 1.30 1.30 1.40 3.54 3.54 204
160

Putnam 24865 162 0.65 0.90 1.02 1.52 1.96 358
Rhea 11184 86 0.77 0.71 0.23 1.71 2.35 171
Roane 21200 84 0.40 0.63 0.96 1.13 2.46 150
Robertson 19906 80 0.40 0.46 0.25 0.57 1.17 321
Rutherford 66443 218 0.33 0.63 0.55 0.94 3.45 475
Scott 8203 122 1.49 1.67 1.44 2.41 2.88 193
Sequatchie 4463 67 1.50 1.50 0.00 3.33 3.33 136
Sevier 28467 188 0.66 1.03 0.59 1.78 2.96 383
Shelby 338366 2057 0.61 0.58 0.63 1.39 4.05 5496
Smith 6878 66 0.96 1.01 2.25 4.41 5.76 112
Stewart 4930 91 1.85 1.85 4.24 6.04 6.04 154
Sullivan 63556 329 0.52 0.75 0.83 1.47 3.45 604
Sumner 48941 315 0.64 0.82 0.96 0.57 1.49 894
Tipton 18106 119 0.66 0.83 0.93 1.12 2.24 237
Trousdale 2780 7 0.25 0.25 0.00 1.66 1.66 NA
Unicoi 7516 42 0.56 0.96 0.36 1.57 3.33 74
Union 6742 107 1.59 1.59 2.16 2.55 2.55 154
Van Buren 2180 52 2.39 2.39 1.83 4.11 4.11 94
Warren 15181 57 0.38 0.57 0.14 0.86 1.93 78
Washington 44195 232 0.52 1.05 0.68 1.33 3.30 527
Wayne 5936 59 0.99 0.99 1.11 2.30 2.30 99
Weakley 13599 59 0.43 0.41 0.29 0.64 1.11 188
White 9229 65 0.70 0.69 0.41 1.58 2.15 139
Williamson 44725 170 0.38 0.75 0.73 2.09 6.15 393
Wilson 32798 114 0.35 0.50 0.33 1.30 2.21 180
161
TEXAS (TX)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
15 54853 0.74 56844 0.94 15169 1.16 26028 2.23
Texas (TX) Occupied Housing Units (OHU)

Anderson 15678 129 0.82 1.07 1.02 2.00 3.12 264
Andrews 4601 28 0.61 2.15 0.52 1.31 8.20 147
Angelina 28685 181 0.63 0.74 0.60 1.36 2.31 537
Aransas 9132 57 0.62 1.00 0.40 1.58 2.17 137
Archer 3345 14 0.42 0.47 0.00 1.81 1.85 20
Armstrong 802 2 0.25 0.25 NA 2.38 2.38 NA
162

Atascosa 12816 334 2.61 3.68 2.32 6.09 10.33 914
Austin 8747 92 1.05 1.65 1.03 4.46 6.79 190
Bailey 2348 35 1.49 3.99 0.00 0.00 0.00 151
Bandera 7010 72 1.03 1.03 NA 4.88 4.88 119
Bastrop 20097 317 1.58 1.97 1.03 4.99 7.70 691
Baylor 1791 0 0.00 0.00 0.00 0.00 0.00 0
Bee 9061 113 1.25 1.46 1.17 3.07 4.16 286
Bell 85507 381 0.45 0.58 0.42 0.97 2.17 936
Bexar 488942 2960 0.61 1.63 0.59 1.50 5.40 8276
Blanco 3303 34 1.03 1.03 0.71 0.00 0.00 70
Borden 292 3 1.03 1.03 NA 7.32 7.32 NA
Bosque 6726 30 0.45 0.55 NA 1.06 1.38 65
Bowie 33058 231 0.70 1.14 0.82 1.12 2.77 538
Brazoria 81954 375 0.46 0.66 0.28 1.16 2.61 1027
Brazos 55202 268 0.49 1.12 0.56 0.94 6.59 535
Brewster 3669 54 1.47 2.40 NA 1.48 7.69 179
Briscoe 724 6 0.83 0.83 NA 3.42 3.42 24
Brooks 2711 94 3.47 5.03 0.70 5.68 11.04 279
Brown 14306 87 0.61 1.01 0.35 1.49 2.89 181
Burleson 6363 72 1.13 1.35 0.93 4.44 5.31 117
Burnet 13133 46 0.35 0.42 0.14 1.22 1.06 106
Caldwell 10816 146 1.35 1.82 1.97 3.13 4.44 498
Calhoun 7442 76 1.02 1.45 0.41 2.04 4.45 222
Callahan 5061 30 0.59 0.70 0.98 0.95 1.20 57
Cameron 97267 1870 1.92 4.05 1.53 3.98 8.10 7262
Camp 4336 31 0.71 0.98 NA 0.65 0.00 64
Carson 2470 7 0.28 0.29 NA 1.47 1.47 12
Cass 12190 189 1.55 1.83 1.27 2.52 3.22 499
Castro 2761 35 1.27 1.45 NA 4.10 7.51 176
Chambers 9139 70 0.77 1.13 1.03 3.36 4.55 167
Cherokee 16651 231 1.39 1.53 1.01 4.46 6.37 571
Childress 2474 22 0.89 4.06 0.76 0.00 0.00 45
Clay 4323 14 0.32 0.44 NA 1.25 1.70 22
Cochran 1309 7 0.53 0.53 0.00 0.00 0.00 18
Coke 1544 14 0.91 0.91 0.79 2.61 2.61 28
Coleman 3889 24 0.62 0.68 0.56 1.14 3.20 50
Collin 181970 498 0.27 0.62 0.39 1.24 2.19 1257
Collingsworth 1294 7 0.54 0.54 1.04 0.00 0.00 13
Colorado 7641 148 1.94 2.48 2.36 3.07 3.73 286
Comal 29066 98 0.34 0.24 0.17 0.30 0.00 302
Comanche 5522 23 0.42 0.43 0.58 1.91 1.96 63
Concho 1058 5 0.47 0.47 NA 1.39 1.39 NA
Cooke 13643 74 0.54 0.69 0.76 0.60 1.40 183
Coryell 19950 85 0.43 0.78 0.69 1.58 3.34 197
Cottle 820 6 0.73 0.73 0.00 0.00 0.00 19
Crane 1360 4 0.29 3.03 0.00 0.00 0.00 10
Crockett 1524 11 0.72 0.00 1.62 3.54 0.00 20
Crosby 2512 24 0.96 0.96 1.69 1.72 1.72 80
Culberson 1052 8 0.76 0.76 NA 0.74 0.74 21
Dallam 2317 7 0.30 0.00 NA 1.80 0.00 NA
Dallas 807621 5058 0.63 1.10 0.38 1.47 7.86 16573
Dawson 4726 30 0.63 0.81 0.52 1.18 0.00 71
163

Deaf Smith 6180 50 0.81 1.52 0.93 1.79 0.00 131
Delta 2094 19 0.91 0.91 1.26 1.55 1.55 44
Denton 158903 429 0.27 0.41 0.14 0.51 1.51 1120
DeWitt 7207 78 1.08 1.13 1.27 1.41 2.04 141
Dickens 980 10 1.02 1.02 NA 2.20 2.20 21
Dimmit 3308 111 3.36 3.62 4.51 5.01 6.44 325
Donley 1578 2 0.13 0.13 0.00 0.00 0.00 NA
Duval 4350 94 2.16 3.06 1.60 3.32 5.25 225
Eastland 7321 50 0.68 0.86 0.85 1.07 1.07 115
Ector 43846 283 0.65 0.45 0.78 1.31 2.31 792
Edwards 801 15 1.87 1.87 NA 2.51 2.51 49
Ellis 37020 253 0.68 0.74 1.12 2.38 3.69 593
El Paso 210022 2338 1.11 6.01 1.06 2.13 10.95 8253
Erath 12568 107 0.85 1.22 NA 2.40 4.58 465
Falls 6496 84 1.29 1.22 2.04 1.26 2.56 189
Fannin 11105 72 0.65 0.55 0.90 0.97 0.63 142
Fayette 8722 99 1.14 1.46 2.43 2.89 4.73 148
Fisher 1785 18 1.01 1.01 1.05 2.16 2.16 16
Floyd 2730 50 1.83 2.10 2.51 4.65 4.39 69
Foard 664 0 0.00 0.00 0.00 0.00 0.00 0
Fort Bend 110915 607 0.55 1.68 0.51 2.14 5.31 2203
Franklin 3754 49 1.31 1.40 2.05 2.77 2.93 87
Freestone 6588 53 0.80 1.16 0.87 3.28 5.22 101
Frio 4743 77 1.62 2.02 2.37 3.41 12.90 229
Gaines 4681 15 0.32 0.08 0.00 0.78 0.00 16
Galveston 94782 558 0.59 0.54 0.41 1.74 1.80 1374
Garza 1663 10 0.60 0.00 0.00 2.49 0.00 77
Gillespie 8521 19 0.22 0.33 0.30 0.67 1.33 38
Glasscock 483 3 0.62 0.62 NA 0.00 0.00 14
Goliad 2644 19 0.72 0.72 1.03 2.49 2.49 45
Gonzales 6782 130 1.92 1.94 2.06 4.54 5.68 342
Gray 8793 18 0.20 0.00 0.00 0.37 0.00 28
Grayson 42849 221 0.52 0.62 0.35 1.22 2.09 498
Grayson 42849 221 0.52 0.62 0.35 1.22 2.09 498
Gregg 42687 219 0.51 0.58 0.63 1.18 3.26 490
Grimes 7753 188 2.42 3.07 3.03 5.06 9.09 405
Guadalupe 30900 199 0.64 1.08 0.53 1.89 3.69 570
Hale 11975 59 0.49 0.67 0.28 1.62 3.10 226
Hall 1548 13 0.84 0.84 NA 0.82 0.82 46
Hamilton 3374 14 0.41 0.64 0.47 0.44 0.73 17
Hansford 2005 9 0.45 0.70 0.00 1.05 2.78 35
Hardeman 1943 12 0.62 0.63 NA 0.91 0.00 28
Hardin 17805 133 0.75 0.86 0.76 2.20 1.83 371
Harris 1205516 8405 0.70 0.58 0.53 1.77 0.68 26878
Harrison 23087 225 0.97 1.03 1.19 2.84 3.20 479
Hartley 1604 10 0.62 1.45 0.00 0.00 0.00 39
Haskell 2569 28 1.09 1.10 0.76 2.92 3.77 65
Hays 33410 163 0.49 0.80 0.49 1.23 4.16 423
Hemphill 1280 4 0.31 0.31 NA 2.56 2.56 8
Henderson 28804 192 0.67 0.65 0.76 2.02 2.60 682
Hidalgo 156824 4844 3.09 7.19 1.71 6.49 13.54 19920
Hill 12204 85 0.70 0.64 0.34 1.80 1.98 183
164

Hockley 7994 52 0.65 0.94 NA 1.10 2.25 128
Hood 16176 82 0.51 0.48 0.52 2.41 1.20 166
Hopkins 12286 75 0.61 0.62 NA 0.85 1.26 233
Houston 8259 108 1.31 1.72 1.49 3.57 5.89 230
Howard 11389 35 0.31 0.58 0.00 0.28 0.00 84
Hudspeth 1092 53 4.85 4.85 6.44 10.44 10.44 137
Hunt 28742 199 0.69 0.65 0.73 2.01 1.99 510
Hutchinson 9283 53 0.57 0.23 0.53 1.75 1.35 139
Irion 694 9 1.30 1.30 NA 6.25 6.25 17
Jack 3047 14 0.46 0.56 0.80 2.78 3.72 22
Jackson 5336 25 0.47 0.38 0.81 1.66 2.03 31
Jasper 13450 116 0.86 0.97 1.17 1.82 2.35 224
Jeff Davis 896 15 1.67 1.67 NA 10.34 10.34 23
Jefferson 92880 533 0.57 0.60 0.60 1.05 2.77 1361
Jim Hogg 1815 18 0.99 0.00 0.98 3.58 0.00 47
Jim Wells 12961 214 1.65 1.81 1.42 3.69 5.73 575
Johnson 43636 252 0.58 0.83 0.63 1.41 1.43 572
Jones 6140 81 1.32 1.37 0.94 3.23 2.60 161
Karnes 4454 63 1.41 1.64 1.10 2.57 2.86 130
Kaufman 24367 186 0.76 0.77 0.75 1.92 1.96 512
Kendall 8613 66 0.77 0.85 0.67 3.35 4.03 169
Kenedy 138 3 2.17 2.17 NA 0.00 0.00 NA
Kent 353 2 0.57 0.57 0.00 0.00 0.00 9
Kerr 17813 97 0.54 0.72 0.57 0.66 0.38 248
Kimble 1866 13 0.70 0.97 0.77 0.00 0.00 21
King 108 0 0.00 0.00 NA 0.00 0.00 0
Kinney 1314 6 0.46 0.46 NA 0.38 0.38 19
Kleberg 10896 84 0.77 1.81 0.39 1.12 3.80 223
Knox 1690 4 0.24 0.24 0.95 0.82 0.82 10
Lamar 19077 143 0.75 0.96 1.09 2.02 4.00 282
Lamb 5360 39 0.73 0.62 1.30 0.99 0.53 99
Lampasas 6554 40 0.61 0.38 0.38 0.34 0.77 101
La Salle 1819 53 2.91 4.12 3.90 7.39 9.40 94
Lavaca 7669 96 1.25 1.53 1.91 2.66 3.42 234
Lee 5663 70 1.24 1.66 2.74 2.90 4.06 188
Leon 6189 79 1.28 1.28 2.10 3.52 3.52 179
Liberty 23242 145 0.62 0.82 0.20 2.25 3.91 541
Limestone 7906 71 0.90 1.48 0.60 2.47 5.06 126
Lipscomb 1205 11 0.91 0.91 NA 3.61 3.61 23
Live Oak 4230 22 0.52 0.27 0.59 1.80 0.60 62
Llano 7879 64 0.81 0.61 NA 2.92 1.86 117
Loving 31 0 0.00 0.00 NA 0.00 0.00 NA
Lubbock 92516 323 0.35 0.66 0.21 0.75 1.19 859
Lynn 2354 24 1.02 0.84 1.00 3.40 1.95 71
McCulloch 3277 29 0.88 0.52 1.23 1.78 3.05 75
McLennan 78859 440 0.56 0.44 0.55 0.87 2.97 1124
McMullen 355 13 3.66 3.66 4.32 9.38 9.38 24
Madison 3914 28 0.72 0.60 0.47 0.32 0.65 55
Marion 4610 114 2.47 2.47 3.17 3.81 3.81 333
Martin 1624 11 0.68 0.64 NA 1.64 1.85 26
Mason 1607 13 0.81 0.81 1.06 5.49 5.49 17
Matagorda 13901 87 0.63 0.64 0.30 1.80 2.48 183
165

Maverick 13089 408 3.12 7.36 3.23 4.26 8.25 1564
Medina 12880 171 1.33 1.40 1.22 4.46 6.95 433
Menard 990 11 1.11 1.11 NA 0.87 0.87 36
Midland 42745 135 0.32 0.72 0.24 1.23 3.27 412
Milam 9199 114 1.24 2.04 1.24 3.07 5.24 236
Mills 2001 28 1.40 1.40 1.88 2.20 2.20 43
Mitchell 2837 17 0.60 0.79 1.42 0.90 2.42 45
Montague 7770 50 0.64 0.86 0.52 1.59 0.68 82
Montgomery 103296 606 0.59 0.80 0.54 1.99 3.09 1715
Moore 6774 29 0.43 0.40 NA 1.33 3.25 88
Morris 5215 63 1.21 1.37 1.47 4.14 4.59 181
Motley 606 4 0.66 0.66 0.00 3.88 3.88 NA
Nacogdoches 22006 176 0.80 0.95 0.65 1.80 2.91 435
Navarro 16491 113 0.69 0.70 0.65 1.77 2.15 341
Newton 5583 75 1.34 1.34 1.98 3.71 3.71 164
Nolan 6170 18 0.29 0.35 NA 0.74 1.48 55
Nueces 110365 691 0.63 1.82 0.51 1.43 4.17 1896
Ochiltree 3261 0 0.00 0.00 0.00 0.00 0.00 0
Oldham 735 0 0.00 0.00 0.00 0.00 0.00 0
Orange 31642 157 0.50 0.39 0.28 1.39 1.66 280
Palo Pinto 10594 61 0.58 0.49 0.45 1.64 1.68 164
Panola 8821 105 1.19 1.35 1.43 2.92 2.33 194
Parker 31131 119 0.38 0.43 0.49 0.90 0.99 255
Parmer 3322 23 0.69 0.83 NA 2.31 2.05 98
Pecos 5153 61 1.18 1.55 0.65 2.18 5.28 124
Polk 15119 136 0.90 0.99 0.67 1.43 1.39 320
Potter 40760 283 0.69 1.12 0.15 1.45 0.00 744
Presidio 2530 76 3.00 4.51 2.70 4.58 6.76 191
Rains 3617 33 0.91 0.91 1.16 3.54 3.54 54
Randall 41240 168 0.41 0.39 0.43 0.58 0.51 465
Reagan 1107 4 0.36 0.00 NA 0.00 0.00 NA
Real 1245 24 1.93 1.93 NA 1.22 1.22 38
Red River 5827 85 1.46 1.76 2.09 2.17 3.03 145
Reeves 4091 61 1.49 1.71 0.93 3.74 0.68 206
Refugio 2985 39 1.31 1.53 0.56 1.29 2.33 96
Roberts 362 0 0.00 0.00 0.00 0.00 0.00 0
Robertson 6179 63 1.02 1.39 1.01 1.85 2.99 166
Rockwall 14530 60 0.41 0.52 NA 1.94 1.89 201
Runnels 4428 66 1.49 1.43 0.66 3.17 1.56 164
Rusk 17364 213 1.23 1.51 1.10 3.23 4.09 406
Sabine 4485 40 0.89 0.89 0.92 3.68 3.68 56
San Augustine 3575 43 1.20 1.20 1.64 1.52 1.52 72
San Jacinto 8651 215 2.49 2.49 2.88 5.48 5.48 430
San Patricio 22093 242 1.10 2.32 0.95 3.59 8.26 754
San Saba 2289 18 0.79 0.22 1.37 3.30 0.00 28
Schleicher 1115 6 0.54 0.54 0.00 0.00 0.00 10
Scurry 5756 24 0.42 0.61 0.56 1.30 3.67 82
Shackelford 1300 4 0.31 0.31 0.00 0.50 0.50 NA
Shelby 9595 60 0.63 0.58 NA 0.72 0.98 170
Sherman 1124 7 0.62 0.62 NA 1.41 1.41 34
Smith 65692 499 0.76 1.00 0.79 2.23 2.78 1344
Somervell 2438 20 0.82 0.82 NA 0.89 0.89 45
166

Starr 14410 679 4.71 5.76 2.43 7.50 9.63 2511
Stephens 3661 6 0.16 0.00 0.00 0.00 0.00 NA
Sterling 513 0 0.00 0.00 0.00 0.00 0.00 0
Stonewall 713 4 0.56 0.56 NA 1.44 1.44 NA
Sutton 1515 10 0.66 0.00 2.53 0.00 0.00 14
Swisher 2925 26 0.89 0.40 0.00 0.00 0.00 67
Tarrant 533864 1945 0.36 0.27 0.27 0.94 0.00 6155
Taylor 47274 246 0.52 0.50 0.30 1.19 1.13 635
Terrell 443 11 2.48 2.48 3.57 6.14 6.14 11
Terry 4278 26 0.61 0.61 NA 2.38 1.19 45
Throckmorton 765 4 0.52 0.52 0.00 0.00 0.00 10
Titus 9552 63 0.66 0.70 NA 2.00 2.99 203
Tom Green 39503 224 0.57 0.52 0.39 1.73 2.13 614
Travis 320766 1590 0.50 1.14 0.40 1.41 7.61 4381
Trinity 5723 45 0.79 0.79 1.38 2.21 2.21 122
Tyler 7775 109 1.40 1.45 0.96 4.49 5.11 228
Upshur 13290 119 0.90 1.02 0.81 3.89 4.43 242
Upton 1256 6 0.48 0.48 NA 2.71 2.71 13
Uvalde 8559 115 1.34 0.92 2.06 4.03 4.65 314
Val Verde 14151 217 1.53 1.14 1.10 3.66 2.69 684
Van Zandt 18195 161 0.88 0.97 0.56 2.51 2.82 369
Victoria 30071 161 0.54 0.41 0.30 1.35 1.96 505
Walker 18303 155 0.85 1.06 0.86 1.61 2.97 332
Waller 10557 138 1.31 1.55 1.04 1.65 2.59 468
Ward 3964 39 0.98 0.67 0.95 1.72 1.10 117
Washington 11322 143 1.26 1.72 1.54 4.66 9.39 240
Webb 50740 1493 2.94 28.13 2.53 5.39 42.81 6098
Wharton 14799 202 1.36 2.25 1.48 3.83 7.02 535
Wheeler 2152 4 0.19 0.19 NA 0.57 0.57 8
Wichita 48441 118 0.24 0.00 0.19 1.02 0.00 268
Wilbarger 5537 21 0.38 1.01 0.34 2.35 7.41 23
Willacy 5584 165 2.95 2.83 3.20 6.42 6.47 672
Williamson 86766 258 0.30 0.61 0.43 1.30 2.80 686
Wilson 11038 156 1.41 1.43 1.99 4.23 3.81 459
Winkler 2584 2 0.08 0.43 0.00 0.41 2.70 NA
Wise 17178 96 0.56 0.54 0.44 1.99 2.20 241
Wood 14583 89 0.61 0.54 0.25 1.56 2.05 194
Yoakum 2469 16 0.65 0.75 0.00 2.88 2.86 54
Young 7167 29 0.40 0.17 NA 1.10 0.00 51
Zapata 3921 96 2.45 4.84 1.07 3.84 10.80 353
Zavala 3428 159 4.64 6.51 5.31 7.17 10.46 462
167
UTAH (UT)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
49 2906 0.41 2163 0.40 1164 1.43 1092 1.66
Utah (UT) Occupied Housing Units (OHU)

Beaver 1982 18 0.91 0.91 2.02 0.00 0.00 57
Box Elder 13144 51 0.39 0.46 0.54 0.92 0.00 127
Cache 27543 44 0.16 0.14 0.00 0.47 0.00 103
Carbon 7413 27 0.36 0.42 NA 1.25 2.20 68
Daggett 340 2 0.59 0.59 0.00 0.00 0.00 NA
Davis 71201 88 0.12 0.00 0.10 0.42 0.00 346
Duchesne 4559 57 1.25 1.63 1.19 3.58 5.54 109
Emery 3468 17 0.49 0.49 NA 0.51 0.51 40
Garfield 1576 5 0.32 0.32 0.00 0.00 0.00 12
168
Utah (UT) Occupied Housing Units (OHU)

Grand 3434 64 1.86 5.62 NA 8.49 32.58 154
Iron 10627 21 0.20 0.38 0.29 0.11 0.41 58
Juab 2456 16 0.65 1.48 NA 2.50 5.60 43
Kane 2237 13 0.58 1.10 0.00 2.60 4.85 36
Millard 3840 13 0.34 0.32 0.94 0.00 0.00 49
Morgan 2046 0 0.00 0.00 0.00 0.00 0.00 0
Piute 509 2 0.39 0.39 0.00 0.00 0.00 NA
Rich 645 3 0.47 0.47 0.00 0.00 0.00 10
Salt Lake 295141 1074 0.36 0.94 0.27 0.97 0.00 3253
San Juan 4089 723 17.68 22.12 19.29 39.95 45.08 2692
Sanpete 6547 39 0.60 0.78 0.66 1.31 1.43 100
Sevier 6081 29 0.48 0.56 NA 0.29 0.45 105
Summit 10332 9 0.09 0.11 0.00 0.00 0.00 53
Tooele 12677 32 0.25 0.70 NA 0.43 3.10 72
Uintah 8187 30 0.37 0.70 NA 0.18 0.31 87
Utah 99937 258 0.26 0.51 0.08 0.42 2.79 883
Wasatch 4743 10 0.21 0.35 0.00 0.00 0.00 32
Washington 29939 64 0.21 0.28 0.20 0.10 0.56 146
Wayne 890 10 1.12 1.12 NA 4.76 4.76 20
Weber 65698 187 0.28 0.25 0.26 0.39 0.00 461
169
VERMONT (VT)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
24 1481 0.62 1952 0.93 1215 0.83 1732 1.24
Vermont
(VT) Occupied Housing Units (OHU)
Addison 13068 81 0.62 0.70 0.74 2.76 3.07 138
Bennington 14846 65 0.44 0.55 0.24 0.71 0.79 137
Caledonia 11663 84 0.72 0.99 0.57 1.67 2.70 190
Chittenden 56452 197 0.35 0.38 0.10 0.52 0.49 414
Essex 2602 49 1.88 1.88 1.26 2.83 2.83 86
Franklin 16765 98 0.58 0.59 0.63 0.47 0.00 183
Grand Isle 2761 11 0.40 0.40 NA 0.00 0.00 16
Lamoille 9221 70 0.76 0.76 0.44 1.75 1.75 158
Orange 10936 156 1.43 1.46 1.67 3.93 3.98 356
Orleans 10446 92 0.88 1.03 0.97 1.77 2.29 166
Rutland 25678 115 0.45 0.67 0.48 0.75 1.52 252
Washington 23659 173 0.73 1.18 0.31 1.67 3.42 330
Windham 18375 140 0.76 1.04 0.49 0.92 1.66 284
Windsor 24162 150 0.62 0.75 0.38 2.51 3.04 247
170
VIRGINIA (VA)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
16 19550 0.72 35788 1.56 12128 1.66 30003 4.38
Virginia (VA) Occupied Housing Units (OHU)

County/City OHU (OHULP) OHU) OHU) OHULP 1999 in 1999 in OHULP
Accomack 15299 404 2.64 2.90 2.11 6.77 7.44 987
Albemarle 31876 291 0.91 0.78 1.17 4.00 3.08 491
Alleghany 5149 76 1.48 1.99 1.96 3.42 4.64 175
Amelia 4240 85 2.00 2.00 4.57 11.58 11.58 161
Amherst 11941 124 1.04 1.61 2.01 3.15 4.55 267
Appomattox 5322 45 0.85 0.85 1.78 2.90 2.90 60
Arlington 86352 516 0.60 0.00 0.41 1.71 0.00 1740
Augusta 24818 281 1.13 1.37 2.37 5.12 5.94 683
Bath 2053 31 1.51 1.51 2.38 8.52 8.52 57
Bedford 23838 202 0.85 1.00 1.20 3.10 3.50 340
171

Bland 2568 47 1.83 1.83 3.42 8.67 8.67 127
Botetourt 11700 99 0.85 1.14 1.42 5.51 5.50 195
Brunswick 6277 174 2.77 2.86 2.72 7.96 8.93 428
Buchanan 10464 163 1.56 1.56 2.69 3.60 3.60 282
Buckingham 5324 161 3.02 3.02 4.30 8.12 8.12 423
Campbell 20639 153 0.74 0.84 0.23 3.56 3.58 240
Caroline 8021 197 2.46 2.46 3.97 6.09 6.09 551
Carroll 12186 222 1.82 1.86 3.01 4.69 4.80 403
Charles City 2670 73 2.73 2.73 4.01 5.71 5.71 208
Charlotte 4951 179 3.62 3.62 3.79 9.48 9.48 516
Chesterfield 93772 256 0.27 0.58 0.31 1.24 5.56 672
Clarke 4942 35 0.71 0.94 0.69 4.71 7.44 93
Craig 2060 37 1.80 1.80 2.30 3.78 3.78 62
Culpeper 12141 201 1.66 1.99 2.87 3.63 4.79 414
Cumberland 3528 59 1.67 1.77 3.01 5.08 5.54 218
Dickenson 6732 135 2.01 2.01 0.74 5.38 5.38 214
Dinwiddie 9107 156 1.71 1.91 0.82 7.33 9.99 304
Essex 3995 96 2.40 2.88 3.90 6.38 7.52 189
Fairfax 350714 1122 0.32 0.15 0.26 0.72 0.00 3291
Fauquier 19842 259 1.31 1.70 2.05 8.14 10.19 700
Floyd 5791 117 2.02 2.02 1.08 7.18 7.18 193
Fluvanna 7387 64 0.87 1.29 1.17 3.37 3.74 145
Franklin 18963 159 0.84 0.88 1.27 3.51 4.15 213
Frederick 22097 242 1.10 1.63 1.57 2.54 3.68 524
Giles 6994 59 0.84 0.88 0.82 2.21 1.88 112
Gloucester 13127 101 0.77 0.73 0.97 0.81 0.00 169
Goochland 6158 101 1.64 1.58 1.82 8.73 8.73 153
Grayson 7259 121 1.67 1.68 1.01 3.23 3.25 270
Greene 5574 49 0.88 0.88 0.94 1.80 1.80 90
Greensville 3375 37 1.10 1.24 1.51 1.23 1.35 63
Halifax 15018 454 3.02 3.73 3.28 7.44 9.78 1000
Hanover 31121 190 0.61 1.13 1.75 7.97 15.94 387
Henrico 108121 384 0.36 0.55 0.53 0.87 3.24 975
Henry 23910 176 0.74 0.93 0.72 1.91 2.18 326
Highland 1131 26 2.30 2.30 4.10 0.00 0.00 61
Isle of Wight 11319 42 0.37 0.57 0.78 0.83 1.47 111
James City 19003 35 0.18 0.52 0.17 2.22 7.55 111
King and Queen 2673 46 1.72 1.72 2.42 3.41 3.41 84
King George 6091 44 0.72 0.72 0.86 1.81 1.81 79
King William 4846 114 2.35 2.91 4.00 11.11 12.85 230
Lancaster 5004 113 2.26 2.26 0.89 6.90 6.90 246
Lee 9706 228 2.35 2.30 2.71 5.08 5.09 417
Loudoun 59900 233 0.39 1.12 1.12 2.59 6.30 713
Louisa 9945 144 1.45 1.45 2.10 7.33 7.33 316
Lunenburg 4998 100 2.00 2.00 2.17 3.50 3.50 198
Madison 4739 149 3.14 3.14 3.95 7.20 7.20 321
Mathews 3932 83 2.11 2.11 3.60 12.03 12.03 182
Mecklenburg 12951 306 2.36 2.84 3.95 6.89 9.43 580
Middlesex 4253 42 0.99 0.99 2.16 4.09 4.09 87
Montgomery 30997 136 0.44 0.83 0.69 0.82 2.44 322
Nelson 5887 194 3.30 3.30 5.19 11.15 11.15 481
172

New Kent 4925 14 0.28 0.28 0.92 2.82 2.82 20
Northampton 5321 245 4.60 4.60 2.76 10.73 10.73 601
Northumberland 5470 158 2.89 2.89 1.80 7.55 7.55 361
Nottoway 5664 87 1.54 2.24 1.08 1.55 2.93 271
Orange 10150 96 0.95 1.44 0.96 2.33 3.52 223
Page 9305 154 1.66 1.84 2.15 5.96 6.89 244
Patrick 8141 88 1.08 1.08 1.67 2.77 2.77 194
Pittsylvania 24684 440 1.78 1.95 1.82 6.08 6.44 804
Powhatan 7258 76 1.05 1.05 1.61 3.15 3.15 180
Prince Edward 6561 102 1.55 1.84 2.34 2.14 2.22 194
Prince George 10159 36 0.35 0.17 0.46 2.48 2.13 89
Prince William 94570 250 0.26 0.57 0.25 0.94 9.50 848
Pulaski 14643 156 1.07 1.46 1.36 3.59 6.96 332
Rappahannock 2788 78 2.80 2.80 1.76 4.64 4.64 184
Richmond 2937 78 2.66 3.12 0.85 9.20 11.22 182
Roanoke 34686 103 0.30 0.49 0.33 0.79 0.00 277
Hanover 31121 190 0.61 1.13 1.75 7.97 15.94 387
Henrico 108121 384 0.36 0.55 0.53 0.87 3.24 975
Henry 23910 176 0.74 0.93 0.72 1.91 2.18 326
Highland 1131 26 2.30 2.30 4.10 0.00 0.00 61
Isle of Wight 11319 42 0.37 0.57 0.78 0.83 1.47 111
James City 19003 35 0.18 0.52 0.17 2.22 7.55 111
King and Queen 2673 46 1.72 1.72 2.42 3.41 3.41 84
King George 6091 44 0.72 0.72 0.86 1.81 1.81 79
King William 4846 114 2.35 2.91 4.00 11.11 12.85 230
Lancaster 5004 113 2.26 2.26 0.89 6.90 6.90 246
Lee 9706 228 2.35 2.30 2.71 5.08 5.09 417
Loudoun 59900 233 0.39 1.12 1.12 2.59 6.30 713
Louisa 9945 144 1.45 1.45 2.10 7.33 7.33 316
Lunenburg 4998 100 2.00 2.00 2.17 3.50 3.50 198
Madison 4739 149 3.14 3.14 3.95 7.20 7.20 321
Mathews 3932 83 2.11 2.11 3.60 12.03 12.03 182
Mecklenburg 12951 306 2.36 2.84 3.95 6.89 9.43 580
Middlesex 4253 42 0.99 0.99 2.16 4.09 4.09 87
Montgomery 30997 136 0.44 0.83 0.69 0.82 2.44 322
Nelson 5887 194 3.30 3.30 5.19 11.15 11.15 481
New Kent 4925 14 0.28 0.28 0.92 2.82 2.82 20
Northampton 5321 245 4.60 4.60 2.76 10.73 10.73 601
Northumberland 5470 158 2.89 2.89 1.80 7.55 7.55 361
Nottoway 5664 87 1.54 2.24 1.08 1.55 2.93 271
Orange 10150 96 0.95 1.44 0.96 2.33 3.52 223
Page 9305 154 1.66 1.84 2.15 5.96 6.89 244
Patrick 8141 88 1.08 1.08 1.67 2.77 2.77 194
Pittsylvania 24684 440 1.78 1.95 1.82 6.08 6.44 804
Powhatan 7258 76 1.05 1.05 1.61 3.15 3.15 180
Prince Edward 6561 102 1.55 1.84 2.34 2.14 2.22 194
Prince George 10159 36 0.35 0.17 0.46 2.48 2.13 89
Prince William 94570 250 0.26 0.57 0.25 0.94 9.50 848
Pulaski 14643 156 1.07 1.46 1.36 3.59 6.96 332
Rappahannock 2788 78 2.80 2.80 1.76 4.64 4.64 184
Richmond 2937 78 2.66 3.12 0.85 9.20 11.22 182
173

Roanoke 34686 103 0.30 0.49 0.33 0.79 0.00 277
Rockbridge 8486 188 2.22 2.30 3.20 5.65 6.34 395
Rockingham 25355 405 1.60 2.21 2.88 5.21 7.49 936
Russell 11789 197 1.67 1.91 3.28 3.67 4.24 345
Scott 9795 302 3.08 3.74 2.50 7.93 9.35 647
Shenandoah 14296 290 2.03 2.41 3.21 5.79 7.13 612
Smyth 13493 136 1.01 1.19 1.83 2.77 3.73 251
Southampton 6279 263 4.19 4.28 4.79 13.10 13.10 571
Spotsylvania 31308 168 0.54 1.08 0.70 4.15 9.39 389
Stafford 30187 71 0.24 0.45 1.23 1.92 2.60 204
Surry 2619 53 2.02 2.02 1.66 5.44 5.44 149
Sussex 4126 116 2.81 2.81 1.59 7.48 7.48 216
Tazewell 18277 203 1.11 1.56 1.45 2.09 2.44 406
Warren 12087 147 1.22 2.05 0.94 2.43 7.93 226
Washington 21056 245 1.16 1.62 1.25 2.98 4.05 519
Westmoreland 6846 198 2.89 3.99 2.54 7.90 12.24 557
Wise 16013 112 0.70 1.03 0.40 1.69 3.11 240
Wythe 11511 148 1.29 1.54 1.66 5.27 8.27 231
York 20000 17 0.09 0.46 NA 1.20 14.06 29
Alexandria City 61889 295 0.48 0.00 0.52 2.50 0.00 889
Bedford City 2519 35 1.39 0.00 0.00 5.05 0.00 46
Bristol City 7678 8 0.10 0.00 0.00 0.00 0.00 30
Buena Vista City 2547 0 0.00 0.00 0.00 0.00 0.00 0
Charlottesville City 16851 67 0.40 0.00 0.39 0.70 0.00 107
Chesapeake City 69900 284 0.41 0.27 0.68 1.65 0.00 807
Clifton Forge City 1841 0 0.00 0.00 0.00 0.00 0.00 0
Colonial Heights City 7027 6 0.09 0.00 0.34 0.00 0.00 18
Covington City 2835 15 0.53 0.00 NA 2.24 0.00 18
Danville City 20607 173 0.84 1.86 0.44 0.73 4.07 343
Emporia City 2226 0 0.00 0.00 0.00 0.00 0.00 0
Fairfax City 8035 24 0.30 0.00 0.42 0.00 0.00 150
Falls Church City 4471 15 0.34 0.00 0.00 0.00 0.00 35
Franklin City 3384 6 0.18 0.00 NA 0.00 0.00 10
Fredericksburg City 8102 15 0.19 0.00 0.00 0.00 0.00 74
Galax City 2950 32 1.08 0.00 1.41 2.62 0.00 72
Hampton City 53887 107 0.20 0.00 0.20 1.24 0.00 228
Harrisonburg City 13133 64 0.49 0.00 0.60 1.04 0.00 208
Hopewell City 9055 26 0.29 0.00 NA 0.82 0.00 46
Lexington City 2232 0 0.00 0.00 0.00 0.00 0.00 0
Lynchburg City 25477 52 0.20 0.52 0.24 0.00 0.00 79
Manassas City 11757 5 0.04 0.00 0.00 0.00 0.00 17
Manassas Park City 3254 11 0.34 0.00 0.00 0.00 0.00 22
Martinsville City 6498 24 0.37 0.00 0.58 1.43 0.00 29
Newport News City 69686 381 0.55 0.00 0.41 1.11 0.00 962
Norfolk City 86210 560 0.65 0.00 0.44 0.96 0.00 1458
Norton City 1730 5 0.29 0.00 NA 1.28 0.00 NA
Petersburg City 13799 114 0.83 0.00 0.49 1.72 0.00 368
Poquoson City 4166 7 0.17 0.00 0.00 0.00 0.00 7
Portsmouth City 38170 214 0.56 0.00 0.33 0.78 0.00 607
Radford City 5809 9 0.15 0.00 0.00 0.50 0.00 42
Richmond City 84549 454 0.54 0.00 0.38 1.04 0.00 1022
174

Roanoke City 42003 215 0.51 0.00 0.43 1.32 0.00 341
Salem City 9954 9 0.09 0.00 0.00 0.00 0.00 18
Staunton City 9676 21 0.22 0.00 0.65 0.00 0.00 55
Suffolk City 23283 207 0.89 1.92 1.24 3.78 11.49 457
Virginia Beach City 154455 433 0.28 1.13 0.21 0.64 6.06 1046
Waynesboro City 8332 45 0.54 0.00 0.00 0.67 0.00 88
Williamsburg City 3619 7 0.19 0.00 0.00 0.00 0.00 26
Winchester City 10001 17 0.17 0.00 0.00 0.70 0.00 24
175
WASHINGTON (WA)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
28 12457 0.55 10128 0.54 4066 1.05 5016 1.22
Washington (WA) Occupied Housing Units (OHU)

Percent of
Adams 5229 18 0.34 0.44 0.00 1.17 2.73 53
Asotin 8364 45 0.54 2.10 0.26 0.73 13.79 93
Benton 52866 200 0.38 0.68 0.11 1.62 0.00 658
Chelan 25021 228 0.91 1.14 0.20 2.58 2.80 751
Clallam 27164 220 0.81 1.36 0.15 1.70 2.58 510
Clark 127208 433 0.34 0.53 0.26 1.08 0.69 918
Columbia 1687 16 0.95 1.23 0.97 0.00 0.00 23
Cowlitz 35850 128 0.36 0.43 0.18 0.80 1.58 260
Douglas 11726 105 0.90 1.96 0.89 2.70 4.24 301
Ferry 2823 128 4.53 4.53 1.33 9.07 9.07 226
176
Washington (WA) Occupied Housing Units (OHU)

Percent of
Franklin 14840 89 0.60 1.08 0.22 1.59 6.51 344
Garfield 987 9 0.91 0.91 2.13 1.61 1.61 18
Grant 25204 194 0.77 0.67 0.61 2.46 2.55 534
Grays Harbor 26808 156 0.58 0.80 0.46 1.31 2.62 351
Island 27784 136 0.49 0.72 0.14 2.83 2.86 268
Jefferson 11645 208 1.79 1.73 0.35 6.02 5.29 340
King 710916 3662 0.52 0.76 0.29 1.63 3.03 7606
Kitsap 86416 329 0.38 0.43 0.33 0.85 2.41 683
Kittitas 13382 105 0.78 0.49 0.72 1.52 0.79 166
Klickitat 7473 83 1.11 1.29 1.22 1.36 2.83 137
Lewis 26306 186 0.71 0.82 0.43 1.65 2.37 406
Lincoln 4151 17 0.41 0.41 0.00 1.20 1.20 52
Mason 18912 125 0.66 0.76 0.14 2.61 2.64 253
Okanogan 15027 415 2.76 3.34 1.04 6.17 7.57 1029
Pacific 9096 66 0.73 1.06 0.31 1.62 1.19 107
Pend Oreille 4639 151 3.26 3.26 3.25 5.79 5.79 302
Pierce 260800 952 0.37 0.63 0.27 1.05 2.17 2420
San Juan 6466 260 4.02 4.02 1.73 9.79 9.79 504
Skagit 38852 299 0.77 1.42 0.10 2.48 4.19 828
Skamania 3755 56 1.49 1.49 NA 4.14 4.14 101
Snohomish 224852 854 0.38 1.10 0.30 1.10 5.57 1982
Spokane 163611 829 0.51 0.48 0.35 1.72 1.21 1414
Stevens 15017 323 2.15 2.69 1.06 5.94 7.15 813
Thurston 81625 362 0.44 0.66 0.37 1.56 1.47 685
Wahkiakum 1553 22 1.42 1.42 1.62 1.57 1.57 32
Walla Walla 19647 105 0.53 0.30 0.10 0.75 0.00 307
Whatcom 64446 292 0.45 0.81 0.10 1.08 3.15 665
Whitman 15257 53 0.35 0.32 0.22 0.42 0.39 107
Yakima 73993 598 0.81 0.77 0.31 2.20 2.14 2025
177
WEST VIRGINIA (WV)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
5 7451 1.01 15972 2.32 5896 1.55 14925 3.55
West Virginia (WV) Occupied Housing Units (OHU)

Barbour 6123 139 2.27 2.72 3.37 4.58 5.93 256
Berkeley 29569 133 0.45 0.36 0.31 1.56 1.59 279
Boone 10291 116 1.13 1.17 1.81 2.42 2.76 253
Braxton 5771 207 3.59 3.59 2.20 9.31 9.31 463
Brooke 10396 41 0.39 0.46 NA 1.09 1.75 70
Cabell 41180 170 0.41 0.77 0.33 0.78 1.94 444
Calhoun 3071 134 4.36 4.36 7.21 9.84 9.84 235
Clay 4020 89 2.21 2.21 3.14 4.11 4.11 155
Doddridge 2845 98 3.44 3.44 4.09 9.91 9.91 242
178
West Virginia (WV) Occupied Housing Units (OHU)

Fayette 18945 255 1.35 1.87 1.76 3.81 5.54 469
Gilmer 2768 14 0.51 0.51 0.00 0.86 0.86 20
Grant 4591 65 1.42 1.77 1.19 4.81 6.34 160
Greenbrier 14571 174 1.19 1.50 1.51 3.22 4.03 278
Hampshire 7955 184 2.31 2.31 3.62 4.08 4.08 329
Hancock 13678 58 0.42 0.35 0.35 1.56 0.00 91
Hardy 5204 166 3.19 3.19 5.81 8.65 8.65 290
Harrison 27867 142 0.51 0.65 0.78 1.41 2.47 253
Jackson 11061 130 1.18 1.12 1.23 3.30 3.58 181
Jefferson 16165 79 0.49 0.69 0.92 1.84 3.73 209
Kanawha 86226 494 0.57 0.93 0.68 1.41 2.61 973
Lewis 6946 92 1.32 1.69 2.04 3.66 4.72 235
Lincoln 8664 210 2.42 2.42 1.02 5.10 5.10 397
Logan 14880 108 0.73 0.70 0.84 1.67 1.95 219
McDowell 11169 186 1.67 1.79 1.35 3.52 3.60 395
Marion 23652 152 0.64 0.65 0.73 0.82 0.76 242
Marshall 14207 89 0.63 0.96 0.54 1.62 3.42 234
Mason 10587 135 1.28 1.66 0.32 3.85 6.00 232
Mercer 26509 213 0.80 1.31 0.73 1.41 2.35 339
Mineral 10784 51 0.47 0.57 0.64 1.32 1.95 107
Mingo 11303 141 1.25 1.22 1.68 1.87 2.18 320
Monongalia 33446 189 0.57 0.85 0.73 0.87 1.62 380
Monroe 5447 102 1.87 1.89 2.17 5.15 5.25 240
Morgan 6145 66 1.07 1.07 1.73 1.91 1.91 116
Nicholas 10722 149 1.39 1.73 2.32 3.16 4.05 271
Ohio 19733 67 0.34 0.53 0.40 1.13 1.28 105
Pendleton 3350 109 3.25 3.25 5.75 8.77 8.77 234
Pleasants 2887 49 1.70 2.88 2.33 7.27 16.36 78
Pocahontas 3835 95 2.48 2.48 4.29 6.32 6.32 151
Preston 11544 163 1.41 1.53 1.86 3.17 3.66 329
Putnam 20028 167 0.83 1.42 0.65 3.15 6.24 345
Raleigh 31793 287 0.90 1.53 1.05 2.46 4.62 621
Randolph 11072 122 1.10 1.58 1.34 3.79 5.85 197
Ritchie 4184 104 2.49 2.49 2.90 8.81 8.81 170
Roane 6161 162 2.63 3.18 2.81 6.08 8.34 305
Summers 5530 125 2.26 2.85 1.48 3.80 4.47 243
Taylor 6320 49 0.78 1.10 1.80 3.03 4.79 104
Tucker 3052 36 1.18 1.18 1.85 4.53 4.53 67
Tyler 3836 59 1.54 2.00 0.93 4.01 5.84 92
Upshur 8972 194 2.16 3.24 3.59 4.71 7.92 405
Wayne 17239 241 1.40 2.10 1.21 2.65 3.83 467
Webster 4010 184 4.59 4.59 4.50 8.53 8.53 325
Wetzel 7164 83 1.16 2.23 1.12 3.92 7.35 166
Wirt 2284 59 2.58 2.58 3.56 7.08 7.08 182
Wood 36275 172 0.47 0.82 0.56 1.35 3.67 384
Wyoming 10454 153 1.46 1.57 1.88 2.99 3.37 300
179
WISCONSIN (WI)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
36 10648 0.51 11780 0.65 4879 0.77 7115 1.20
Wisconsin (WI) Occupied Housing Units (OHU)

Adams 7900 51 0.65 0.65 0.32 2.21 2.21 106
Ashland 6718 107 1.59 2.15 0.53 4.56 5.84 209
Barron 17851 129 0.72 1.03 0.91 3.01 4.49 345
Bayfield 6207 146 2.35 2.35 1.05 5.31 5.31 274
Brown 87295 286 0.33 0.45 0.29 0.65 0.50 619
Buffalo 5511 58 1.05 1.05 1.07 4.22 4.22 150
Burnett 6613 80 1.21 1.21 1.12 3.47 3.47 142
Calumet 14910 28 0.19 0.39 0.22 0.00 0.00 65
Chippewa 21356 103 0.48 0.63 0.62 1.39 1.70 275
Clark 12047 227 1.88 2.05 1.25 8.04 8.74 1150
180

Columbia 20439 86 0.42 0.51 0.62 1.32 2.51 239
Crawford 6677 90 1.35 2.13 0.92 4.50 6.30 203
Dane 173484 645 0.37 0.26 0.17 1.50 1.40 1340
Dodge 31417 109 0.35 0.30 0.26 1.81 0.75 232
Door 11828 26 0.22 0.32 0.43 0.77 1.26 49
Douglas 17808 143 0.80 1.76 1.03 1.23 4.67 268
Dunn 14337 102 0.71 0.80 0.40 2.05 3.00 184
Eau Claire 35822 233 0.65 1.99 0.52 2.69 15.07 1021
Florence 2133 35 1.64 1.64 1.45 6.07 6.07 55
Fond du Lac 36931 83 0.22 0.41 0.34 1.09 2.60 159
Forest 4043 46 1.14 1.14 0.84 2.42 2.42 70
Grant 18465 84 0.45 0.50 0.61 1.13 0.82 210
Green 13212 26 0.20 0.30 NA 0.88 0.58 65
Green Lake 7703 45 0.58 0.78 0.48 1.79 2.56 182
Iowa 8764 39 0.45 0.55 0.43 1.91 2.28 53
Iron 3083 19 0.62 0.91 0.73 0.00 0.00 45
Jackson 7070 64 0.91 1.16 0.75 2.69 3.97 170
Jefferson 28205 75 0.27 0.37 0.52 0.55 1.70 150
Juneau 9696 59 0.61 0.59 0.37 1.66 1.39 131
Kenosha 56057 145 0.26 0.00 0.10 0.83 0.00 504
Kewaunee 7623 37 0.49 0.50 0.81 1.84 2.26 65
La Crosse 41599 109 0.26 0.50 0.19 0.57 3.05 484
Lafayette 6211 22 0.35 0.35 0.49 0.70 0.70 58
Langlade 8452 71 0.84 1.19 0.88 2.15 2.88 151
Lincoln 11721 73 0.62 0.85 0.75 2.51 5.19 125
Manitowoc 32721 112 0.34 0.39 0.26 2.16 2.26 261
Marathon 47702 248 0.52 0.64 0.61 2.20 2.26 713
Marinette 17585 159 0.90 1.38 0.93 1.98 3.44 230
Marquette 5986 44 0.74 0.74 0.26 3.70 3.70 115
Menominee 1345 10 0.74 0.74 NA 0.60 0.60 36
Milwaukee 377729 2683 0.71 0.00 0.45 2.10 0.00 6003
Monroe 15399 299 1.94 3.53 1.10 11.17 23.02 1529
Oconto 13979 69 0.49 0.57 0.57 1.54 2.22 114
Oneida 15333 101 0.66 0.77 0.76 1.03 1.63 221
Outagamie 60530 82 0.14 0.14 0.25 0.61 1.32 199
Ozaukee 30857 48 0.16 0.18 0.20 0.00 0.00 71
Pepin 2759 25 0.91 0.91 1.08 4.12 4.12 100
Pierce 13015 51 0.39 0.54 0.24 0.63 1.49 75
Polk 16254 93 0.57 0.62 0.41 2.14 2.32 168
Portage 25040 143 0.57 0.79 0.95 1.65 4.12 474
Price 6564 99 1.51 1.51 1.59 5.77 5.77 195
Racine 70819 221 0.31 0.20 0.14 0.98 0.79 550
Richland 7118 72 1.01 1.37 0.76 4.00 6.83 209
Rock 58617 205 0.35 0.27 0.26 1.35 0.54 483
Rusk 6095 64 1.05 1.26 1.31 2.96 2.85 141
St. Croix 23410 82 0.35 0.36 0.87 0.37 0.81 215
Sauk 21644 93 0.43 0.80 0.65 1.78 4.58 380
Sawyer 6640 77 1.16 1.16 0.75 3.27 3.27 136
Shawano 15815 105 0.66 0.62 0.74 1.76 2.58 221
Sheboygan 43545 156 0.36 0.31 0.19 1.06 3.44 515
Taylor 7529 122 1.62 2.17 1.63 7.63 10.31 397
Trempealeau 10747 86 0.80 0.80 0.95 4.40 4.40 231
Vernon 10825 396 3.66 4.33 1.65 14.51 18.37 1958
181

Vilas 9066 44 0.49 0.49 0.35 1.38 1.38 74
Walworth 34522 114 0.33 0.25 0.42 1.28 1.15 190
Washburn 6604 54 0.82 0.99 0.85 1.78 2.31 71
Washington 43842 107 0.24 0.33 0.11 0.44 2.11 204
Waukesha 135229 270 0.20 0.13 0.22 0.40 0.00 659
Waupaca 19863 111 0.56 0.59 0.66 1.53 2.62 238
Waushara 9336 62 0.66 0.67 0.47 3.02 3.04 184
Winnebago 61157 192 0.31 0.42 0.52 0.71 1.20 378
Wood 30135 68 0.23 0.43 0.25 0.50 2.12 212
182
WYOMING (WY)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
33 1011 0.52 897 0.53 590 0.92 609 1.08
Wyoming (WY) Occupied Housing Units (OHU)

Albany 13269 68 0.51 1.35 0.00 0.69 0.00 78
Big Horn 4312 31 0.72 0.72 NA 2.42 2.42 84
Campbell 12207 61 0.50 0.79 1.87 0.52 0.00 153
Carbon 6129 19 0.31 0.32 0.00 0.25 0.60 66
Converse 4694 21 0.45 0.63 NA 0.00 0.00 80
Crook 2308 4 0.17 0.17 NA 0.00 0.00 NA
Fremont 13545 192 1.42 2.74 1.30 3.69 6.26 430
183
Wyoming (WY) Occupied Housing Units (OHU)

Goshen 5061 0 0.00 0.00 0.00 0.00 0.00 0
Hot Springs 2108 20 0.95 1.00 0.81 0.00 0.00 23
Johnson 2959 6 0.20 0.45 0.00 1.80 3.77 8
Laramie 31927 91 0.29 0.06 0.00 0.82 0.00 186
Lincoln 5266 22 0.42 0.49 0.63 2.71 3.37 47
Natrona 26819 156 0.58 1.89 0.13 1.37 7.25 266
Niobrara 1011 17 1.68 1.68 1.98 4.83 4.83 42
Park 10312 49 0.48 0.51 0.37 1.98 3.34 154
Platte 3625 33 0.91 1.18 NA 0.51 0.76 45
Sheridan 11167 62 0.56 0.97 0.72 1.38 2.59 64
Sublette 2371 18 0.76 0.76 0.00 3.86 3.86 65
Sweetwater 14105 51 0.36 1.46 0.00 1.80 9.20 110
Teton 7688 67 0.87 0.99 0.58 1.96 4.85 129
Uinta 6823 10 0.15 0.37 0.00 0.00 0.00 35
Washakie 3278 2 0.06 0.20 0.00 0.00 0.00 NA
Weston 2624 11 0.42 0.77 0.00 0.00 0.00 13
184
PUERTO RICO (PR)

Lacking
2000 2000 2000 1990 1990 2000 OHU) 2000 1990 OHU) 1990
2 65640 5.20 NA NA 5673 8.47 NA NA
Puerto Rico (PR) Occupied Housing Units (OHU)

Municipio OHU (OHULP) OHU) Rural OHU) OHULP in 1999 in 1999 in OHULP
Adjuntas 5895 226 3.83 3.82 5.44 4.42 3.85 651
Aguada 13520 1380 10.21 0.00 10.47 12.44 0.00 4014
Aguadilla 22087 1068 4.84 0.00 5.32 6.15 0.00 2770
Aguas Buenas 9240 474 5.13 6.81 7.20 5.29 4.79 1251
Aibonito 8408 270 3.21 3.96 4.80 4.45 5.20 773
Añasco 9398 657 6.99 7.95 7.13 9.56 11.00 1754
Arecibo 34245 2034 5.94 8.07 6.51 7.75 10.82 5232
Arroyo 6166 366 5.94 18.03 6.79 7.45 22.73 1189
Barceloneta 7508 1221 16.26 19.54 13.84 20.64 0.00 3537
Barranquitas 8663 317 3.66 5.85 4.87 3.89 8.73 959
Bayamón 73693 1294 1.76 0.00 1.95 2.76 0.00 3829
Cabo Rojo 17114 1067 6.23 7.81 5.09 9.43 10.84 2849
Caguas 46937 1573 3.35 3.86 3.73 5.38 3.47 4535
Camuy 11457 500 4.36 9.97 4.17 5.74 14.02 1230
Canóvanas 13446 1099 8.17 13.83 8.75 10.37 24.05 3286
Carolina 63546 1820 2.86 0.00 3.05 5.15 0.00 5097
Cataño 9638 363 3.77 0.00 3.46 5.03 0.00 1284
185

Cayey 15634 405 2.59 5.74 4.41 3.69 6.58 1067
Ceiba 5750 206 3.58 6.47 4.76 5.11 11.82 595
Ciales 6047 395 6.53 7.03 6.44 8.27 7.69 1195
Cidra 13204 493 3.73 5.03 4.09 4.61 5.40 1547
Coamo 11749 584 4.97 5.65 6.67 5.75 6.23 1695
Comerío 6311 197 3.12 3.49 1.36 3.54 2.82 556
Corozal 11264 526 4.67 6.04 7.14 5.87 7.96 1444
Culebra 699 40 5.72 5.72 NA 4.00 4.00 106
Dorado 10887 584 5.36 0.00 5.13 8.01 0.00 1693
Fajardo 14176 447 3.15 4.35 3.16 4.44 0.00 1045
Florida 3962 235 5.93 6.99 8.85 7.30 9.02 575
Guánica 7291 672 9.22 10.15 8.19 10.67 6.31 1981
Guayama 14225 1036 7.28 9.87 8.57 9.58 10.98 2826
Guayanilla 7209 642 8.91 9.47 9.40 11.87 14.15 1652
Guaynabo 34068 860 2.52 25.00 2.49 4.79 50.00 2489
Gurabo 11741 542 4.62 5.85 3.78 8.30 10.42 1318
Hatillo 12685 670 5.28 5.97 6.10 6.19 8.80 1875
Hormigueros 5820 231 3.97 15.79 3.27 6.18 0.00 674
Humacao 19293 927 4.80 9.23 4.00 6.94 0.00 2670
Isabela 14970 945 6.31 8.70 8.95 7.68 5.43 2756
Jayuya 5083 259 5.10 6.87 5.82 5.82 6.43 917
Juana Díaz 14954 1271 8.50 11.31 9.93 11.12 12.79 3844
Juncos 11933 634 5.31 0.00 8.28 6.29 0.00 1651
Lajas 9007 630 6.99 9.74 5.80 9.22 13.48 1553
Lares 10974 814 7.42 11.42 6.22 8.56 11.90 2481
Las Marías 3564 332 9.32 12.52 10.24 13.06 17.29 920
Las Piedras 11145 365 3.28 5.32 3.82 3.58 9.19 1303
Loíza 9597 495 5.16 13.64 5.51 6.30 13.64 1482
Luquillo 6573 271 4.12 4.39 7.38 6.07 3.45 838
Manatí 15266 653 4.28 3.47 5.35 5.64 3.10 1981
Maricao 2013 127 6.31 7.78 7.59 7.29 9.95 354
Maunabo 3994 418 10.47 14.05 8.95 12.39 22.09 1225
Mayagüez 34742 2221 6.39 11.50 6.17 8.08 17.15 5905
Moca 12712 778 6.12 9.89 7.16 7.53 14.54 2199
Morovis 8801 541 6.15 8.53 6.42 8.03 10.40 1794
Naguabo 7872 329 4.18 6.90 5.52 4.51 7.87 910
Naranjito 8932 378 4.23 0.00 6.27 5.68 0.00 1013
Orocovis 7083 366 5.17 6.39 5.38 6.29 6.83 967
Patillas 6576 559 8.50 11.07 8.25 10.42 12.03 1664
Peñuelas 7698 763 9.91 22.95 7.20 12.79 32.26 2775
Ponce 59607 4198 7.04 8.98 5.88 10.18 11.46 12979
Quebradillas 8280 418 5.05 5.61 7.19 6.80 5.18 1143
Rincón 5147 340 6.61 0.00 5.27 7.45 0.00 1029
Río Grande 16430 1010 6.15 2.55 6.91 7.93 3.02 2713
Sabana Grande 8865 535 6.03 9.74 6.17 7.59 13.04 1566
Salinas 10184 759 7.45 7.60 8.86 9.27 11.16 2264
San Germán 12809 689 5.38 5.15 5.07 7.61 6.18 1715
San Juan 163462 6358 3.89 0.00 3.22 6.09 0.00 17663
San Lorenzo 13138 1102 8.39 7.99 9.25 10.47 8.81 3339
San Sebastián 14970 1356 9.06 10.96 9.29 10.87 12.26 3607
Santa Isabel 6781 533 7.86 4.98 10.70 9.56 5.24 1383
Toa Alta 19420 582 3.00 0.00 5.13 5.40 0.00 1912
Toa Baja 30453 1440 4.73 0.00 5.20 7.30 0.00 4306
Trujillo Alto 24160 1251 5.18 0.00 4.02 10.12 0.00 3552
186

Utuado 11207 666 5.94 5.71 5.36 7.14 7.35 1833
Vega Alta 11894 1268 10.66 4.17 10.80 14.26 7.74 3987
Vega Baja 19758 1199 6.07 12.23 11.05 8.44 15.56 3494
Vieques 3319 230 6.93 14.94 10.08 7.43 10.00 644
Villalba 7722 572 7.41 12.25 9.25 9.49 15.12 2069
Yabucoa 12242 877 7.16 14.55 8.31 9.18 14.51 2875
Yauco 15012 1687 11.24 21.07 9.96 16.15 24.26 5292
187
American Samoa (AS)
American Samoa (AS) Housing Units (HU) Occupied Housing Units (OHU)
Means of Sewage Disposal Lacking Complete Plumbing Facilities
Percent OHULP with
HU using HU using of OHULP Householder
Total HU using septic tank other Total Total (as % of below Poverty
District/Village HU public sewer or cesspool means (OHU) (OHULP) OHU) Level in 1999
Eastern District 4111 1829 2069 213 3845 1397 36.33 1028
Eastern District, Rural 382 74 290 18 339 146 43.07 113
Manu'a District 323 7 302 14 273 86 31.50 59
Manu'a District, Rural 323 7 302 14 273 86 31.50 59
Rose Island 0 0 0 0 0 0 0.00 0
Rose Island, Rural 0 0 0 0 0 0 0.00 0
Swains Island 8 0 7 1 7 6 85.71 4
Swains Island, Rural 8 0 7 1 7 6 85.71 4
Western District 5610 1956 3359 295 5224 2070 39.62 1657
Western District, Rural 551 3 493 55 491 262 53.36 209
Village
Aasu Village 57 1 51 5 50 31 62.00 28
Afao Village 23 0 22 1 22 9 40.91 8
Afono Village 109 0 104 5 90 40 44.44 31
Agugulu Village 8 0 7 1 7 2 28.57 1
188
Percent OHULP with
Alao Village 104 9 92 3 93 52 55.91 41
Alega Village 13 3 9 1 13 4 30.77 2
Alofau Village 86 1 83 2 84 30 35.71 19
Amaluia Village 41 0 36 5 36 18 50.00 12
Amanave Village 58 0 50 8 52 38 73.08 29
Amaua Village 23 7 16 0 20 7 35.00 6
Amouli Village 76 0 71 5 74 28 37.84 20
Anua Village 11 8 3 0 9 3 33.33 2
Aoa Village 96 3 74 19 83 56 67.47 44
Aoloau Village 162 1 145 16 136 58 42.65 46
Asili Village 36 0 33 3 34 14 41.18 11
Atu'u Village 59 53 4 2 58 23 39.66 16
Aua Village 386 22 334 30 347 126 36.31 86
Auasi Village 19 0 17 2 17 7 41.18 5
Aumi Village 37 1 34 2 35 13 37.14 11
Aunu'u Village 88 59 25 4 79 40 50.63 31
Auto Village 45 4 36 5 42 12 28.57 6
Avaio Village 9 0 8 1 9 1 11.11 0
Faga'alu Village 204 130 64 10 195 66 33.85 48
Faga'itua Village 90 12 73 5 82 28 34.15 17
Fagali'i Village 48 0 39 9 44 27 61.36 24
Fagamalo Village 14 0 13 1 9 5 55.56 4
Faganeanea Village 31 3 27 1 29 8 27.59 6
Fagasa Village 137 35 91 11 130 53 40.77 44
Fagatogo Village 359 319 33 7 351 96 27.35 74
Failolo Village 21 0 17 4 20 13 65.00 11
Faleasao Village 37 1 34 2 29 5 17.24 3
Faleniu Village 315 91 212 12 308 171 55.52 146
Fatumafuti Village 19 6 10 3 16 6 37.50 4
Futiga Village 105 3 99 3 104 43 41.35 30
Ili'ili Village 470 91 354 25 423 136 32.15 103
Lauli'i Village 155 2 145 8 153 69 45.10 54
Leloaloa Village 93 9 76 8 81 27 33.33 16
Leone Village 600 29 547 24 577 170 29.46 129
Leusoali'i Village 34 0 34 0 32 10 31.25 7
Luma Village 58 2 56 0 52 8 15.38 7
Maia Village 30 1 26 3 25 8 32.00 3
Malaeimi Village 189 85 90 14 179 87 48.60 76
Malaeloa/Aitulagi Village 93 1 90 2 90 33 36.67 25
Malaeloa/Ituau Village 87 0 85 2 86 38 44.19 26
Maloata Village 5 0 5 0 4 2 50.00 2
Mapusagafou Village 285 17 249 19 272 129 47.43 116
Masausi Village 35 0 22 13 32 21 65.63 14
Masefau Village 73 2 66 5 68 33 48.53 24
Matu'u Village 71 6 64 1 70 4 5.71 3
Mesepa Village 80 69 9 2 73 26 35.62 20
Nua Village 28 0 27 1 26 12 46.15 8
Nu'uuli Village 905 727 136 42 868 332 38.25 259
Ofu Village 75 0 71 4 63 15 23.81 13
Olosega Village 62 0 58 4 48 34 70.83 22
Onenoa Village 29 0 29 0 26 17 65.38 11
Pagai Village 20 1 18 1 20 11 55.00 7
189
Percent OHULP with
Pago Pago Village 742 579 140 23 708 226 31.92 169
Pava'ia'i Village 401 47 319 35 357 150 42.02 117
Poloa Village 37 0 34 3 36 24 66.67 18
Sa'ilele Village 18 0 16 2 18 12 66.67 7
Se'etaga Village 44 0 43 1 41 15 36.59 12
Sili Village 5 0 4 1 2 2 100.00 2
Si'ufaga Village 22 3 19 0 22 4 18.18 2
Swains Village 8 0 7 1 7 6 85.71 4
Tafuna Village 1488 1174 268 46 1362 446 32.75 348
Taputimu Village 100 8 84 8 97 44 45.36 36
Tula Village 81 3 73 5 75 35 46.67 29
Utulei Village 158 148 7 3 141 32 22.70 24
Utumea East Village 13 0 13 0 13 5 38.46 4
Utumea West Village 9 1 7 1 8 2 25.00 2
Vailoatai Village 159 3 147 9 158 62 39.24 52
Vaitogi Village 243 12 217 14 228 96 42.11 75
190
Guam (GU)
Guam (GU) Housing Units (HU) Occupied Housing Units (OHU)

Percent OHULP with
County/Census Total HU using septic tank other Total Total (as % of below Poverty
Designated Place HU public sewer or cesspool means (OHU) (OHULP) OHU) Level in 1999
Guam 47677 34067 12443 1167 38769 3411 8.80 944
Guam, Rural 2946 1559 1255 132 2309 321 13.90 102
Census Designated
Place
Agana Heights 1126 945 180 1 995 81 8.14 8
Agat 1041 957 65 19 906 95 10.49 23
Andersen AFB 1072 1048 15 9 938 6 0.64 0
Apra Harbor 1379 1347 17 15 751 2 0.27 0
Asan 312 247 63 2 272 14 5.15 1
Astumbo 1459 1012 352 95 1167 177 15.17 100
Barrigada 1083 484 576 23 1004 123 12.25 24
Barrigada Heights 325 293 29 3 292 21 7.19 3
Chalan Pago 841 301 489 51 697 90 12.91 28
Dededo 902 843 49 10 756 71 9.39 12
Finegayan Station 857 791 61 5 464 3 0.65 1
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Guam (GU) Housing Units (HU) Occupied Housing Units (OHU)

Percent OHULP with
County/Census Total HU using septic tank other Total Total (as % of below Poverty
Hagåtña 403 374 27 2 276 13 4.71 5
Inarajan 148 64 76 8 134 23 17.16 6
Latte Heights 410 347 60 3 373 30 8.04 3
Maina 246 71 171 4 231 19 8.23 3
Maite 303 295 8 0 171 2 1.17 0
Mangilao 2463 1675 742 46 1883 127 6.74 23
Merizo 390 324 57 9 341 40 11.73 9
Mongmong 1207 964 226 17 958 62 6.47 18
Nimitz Hill Annex 64 61 3 0 14 1 7.14 0
Ordot 1079 477 563 39 876 71 8.11 22
Piti 212 177 28 7 185 24 12.97 6
Santa Rita 311 254 47 10 279 37 13.26 6
Santa Rosa 144 140 3 1 130 8 6.15 1
Sinajana 578 562 14 2 518 37 7.14 5
Talofofo 556 174 342 40 497 89 17.91 27
Tamuning 4735 4478 230 27 3550 116 3.27 23
Tiyan 2 0 2 0 2 0 0.00 0
Toto 592 318 253 21 504 83 16.47 18
Umatac 115 94 16 5 104 18 17.31 6
Yigo 1841 1032 753 56 1515 111 7.33 35
Yona 532 355 158 19 470 62 13.19 18
192
Northern Mariana Islands (MP)
193
Northern Mariana Islands (MP) continued
No. Mariana Is. (MP) Housing Units (HU) Occupied Housing Units (OHU)
Percent OHULP with
Municipality/Census Total HU using septic tank other Total Total (as % of below Poverty
Northern Islands
Municipality 3 2 1 0 1 0 0.00 0
Northern Islands
Municipality, Rural 3 2 1 0 1 0 0.00 0
Rota Municipality 981 93 776 112 757 97 12.81 45
Rota Municipality, Rural 981 93 776 112 757 97 12.81 45
Saipan Municipality 15527 8251 6052 1224 12507 2004 16.02 1224
Saipan Municipality, Rural 299 89 151 59 213 58 27.23 33
Tinian Municipality 1055 253 695 107 790 200 25.32 113
Tinian Municipality, Rural 236 53 134 49 155 52 33.55 24
Census Designated
Place
Capital Hill 458 158 279 21 358 23 6.42 11
Chalan Kanoa 1035 902 80 53 856 116 13.55 75
Dandan 648 60 505 83 543 108 19.89 68
Garapan 1307 1166 120 21 979 82 8.38 41
Gualo Rai 348 182 153 13 305 58 19.02 31
194
No. Mariana Is. (MP) Housing Units (HU) Occupied Housing Units (OHU)
Percent OHULP with
Municipality/Census Total HU using septic tank other Total Total (as % of below Poverty
Kagman 946 62 575 309 653 207 31.70 113
Koblerville 901 493 359 49 783 92 11.75 56
Navy Hill 310 273 35 2 221 21 9.50 13
San Antonio 888 606 270 12 743 53 7.13 31
San Jose (Saipan) 254 196 48 10 213 46 21.60 29
San Jose (Tinian) 529 159 331 39 383 85 22.19 53
San Roque 319 202 95 22 247 40 16.19 29
San Vicente 827 175 604 48 669 113 16.89 74
Songsong 364 63 291 10 298 19 6.38 11
Susupe 467 398 49 20 393 53 13.49 38
Tanapag 482 222 167 93 397 110 27.71 66
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U.S. Virgin Islands (VI)
U.S. Virgin Islands (VI) Housing Units (HU) Occupied Housing Units (OHU)
HU using HU using
Island/Census Total HU using septic tank other Total Total Percent of OHULP
Designated Place HU public sewer or cesspool means (OHU) (OHULP) (as % of OHU)
St. Croix Island 23782 11758 11177 847 19455 939 4.83
St. Croix Island, Rural 2850 503 2103 244 2063 57 2.76
St. John Island 2390 371 1855 164 1735 167 9.63
St. John Island, Rural 856 106 654 96 642 99 15.42
St. Thomas Island 24030 13748 9514 768 19458 656 3.37
St. Thomas Island, Rural 947 171 733 43 755 11 1.46
Census Designated
Place
Anna's Retreat CDP 3080 2456 528 96 2643 43 1.63
Charlotte Amalie town 5195 4859 237 99 4292 218 5.08
Charlotte Amalie East
CDP 1072 999 69 4 951 34 3.58
Charlotte Amalie West
CDP 2291 1955 317 19 1921 74 3.85
Christiansted town 1459 1347 75 37 1116 77 6.90
Cruz Bay CDP 1529 265 1197 67 1090 67 6.15
Frederiksted town 512 464 42 6 327 59 18.04
196
U.S. Virgin Islands (VI) Housing Units (HU) Occupied Housing Units (OHU)
HU using HU using
Island/Census Total HU using septic tank other Total Total Percent of OHULP
Designated Place HU public sewer or cesspool means (OHU) (OHULP) (as % of OHU)
Frederiksted Southeast
CDP 1154 748 389 17 986 52 5.27
Grove Place CDP 1073 706 341 26 980 70 7.14
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Glossary of Terms
Alaska Native race/ethnic categories

Self-identification among people of Alaska Native descent. These are the five detailed Alaska Native
race and ethnic categories used in tabulating data in the Census 2000:
Alaska Athabaskan
Aleut
Eskimo
Tlingit-Haida
All other tribes
American Indian tribe/Selected American Indian categories

Self-identification among people of American Indian descent. Many American Indians are members
of a principal tribe or group empowered to negotiate and make decisions on behalf of the individual
members. Census 2000 data are available for 36 tribes or selected American Indian categories:
Apache Houma Pueblo
Blackfeet Iroquois Puget Sound Salish
Cherokee Kiowa Seminole
Cheyenne Latin American (Aztec, Shoshone
Chickasaw Inca, Mayan, etc.) Sioux
Chippewa Lumbee Tohomo O’Odham
Chocktaw Menominee Ute
Colville Navajo Yakama
Comanche Osage Yaqui
Cree Ottawa Yuman
Creek Paiute All other
Crow Pima
Delaware Potawatomi
These tribes were selected based on a 1990 population threshold of 7,500.

Related term: Race
Asian
Self-identification among people of Asian descent. There are 17 detailed Asian race and ethnic
categories used in for tabulating data in the Census 2000:
Asian Indian Indonesian Sri Lankan

Bangladeshi Japanese Taiwanese
Cambodian Korean Thai
Chinese, except Taiwanese Laotian Vietnamese
Filipino Malaysian Other Asian
Hmong Pakistani
Related term: Race
Borough
A county equivalent in Alaska, a minor civil division in New York, and an incorporated place in
Connecticut, New Jersey, and Pennsylvania.
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Central place
The core incorporated place(s) or a census designated place of an urban area, usually consisting of
the most populous place(s) in the urban area plus additional places that qualify under Census Bureau
criteria. If the central place is also defined as an extended place, only the portion of the central place
contained within the urban area is recognized as the central place.
Census
A complete enumeration, usually of a population, but also of businesses and commercial
establishments, farms, governments, and so forth.
Census (decennial)
The census of population and housing, taken by the Census Bureau in years ending in 0 (zero).
Article I of the Constitution requires that a census be taken every ten years for the purpose of
reapportioning the U.S. House of Representatives.
Census area
The statistical equivalent of a county in Alaska. Census areas are delineated cooperatively by the state
of Alaska and the Census Bureau for statistical purposes in the portion of Alaska not within an
organized borough.
Census county division (CCD)

A subdivision of a county that is a relatively permanent statistical area established cooperatively by
the Census Bureau and state and local government authorities. Used for presenting decennial census
statistics in those states that do not have well-defined and stable minor civil divisions that serve as
local governments.
Census designated place (CDP)

A statistical entity, defined for each decennial census according to Census Bureau guidelines,
comprising a densely settled concentration of population that is not within an incorporated place,
but is locally identified by a name. CDPs are delineated cooperatively by state and local officials and
the Census Bureau, following Census Bureau guidelines. Beginning with Census 2000 there are no
size limits.
Related term: Incorporated place
Central city
The largest city of a Metropolitan area (MA). Central cities are a basis for establishment of an MA.
Additional cities that meet specific criteria also are identified as central cities. In a number of
instances, only part of a city qualifies as central, because another part of the city extends beyond the
MA boundary.
Related term: Metropolitan area (MA)
City
A type of incorporated place in 49 states and the District of Columbia. In 23 states and the District
of Columbia, some or all cities are not part of any Minor Civil Division (MCD), and the Census
Bureau also treats these as county subdivisions, statistically equivalent to MCDs.
Related terms: Incorporated place, Minor civil division (MCD)
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Comunidad
Represents a census designated place that is not the representing governmental center of the
municipio in Puerto Rico. There are no incorporated places in Puerto Rico. For Census 2000 there
are no minimum population requirements. For 1990 comunidades had to have at least 1,000 people.
Related term: Municipio
Confidentiality
The guarantee made by law (Title 13, United States Code) to individuals who provide census
information regarding nondisclosure of that information to others.
For US Code, Title 13, see
http://factfinder.census.gov/home/en/epss/glossary_t.html#title_13_u.s._code
Consolidated city
An incorporated place that has combined its governmental functions with a county or sub-county
entity but contains one or more other incorporated places that continue to function as local
governments within the consolidated government.
Related term: Incorporated place
Consolidated metropolitan statistical area (CMSA)

A geographic entity defined by the federal Office of Management and Budget for use by federal
statistical agencies. An area becomes a CMSA if it meets the requirements to qualify as a
metropolitan statistical area, has a population of 1,000,000 or more, if component parts are
recognized as primary metropolitan statistical areas, and local opinion favors the designation.
Related terms: Metropolitan statistical area (MSA), Primary metropolitan statistical area (PMSA)
County and equivalent entity

The primary legal subdivision of most states. In Louisiana, these subdivisions are known as parishes.
In Alaska, which has no counties, the county equivalents are boroughs, a legal subdivision, and
census areas, a statistical subdivision. In four states (Maryland, Missouri, Nevada and Virginia), there
are one or more cities that are independent of any county and thus constitute primary subdivisions
of their states. The District of Columbia has no primary divisions, and the entire area is considered
equivalent to a county for statistical purposes. In Puerto Rico, municipios are treated as county
equivalents.
Related term: Borough
County subdivision
A legal or statistical division of a county recognized by the Census Bureau for data presentation. The
two major types of county subdivisions are census county divisions and minor civil divisions.
Related terms: Minor civil division (MCD), Unorganized territory
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Householder
The person, or one of the people, in whose name the home is owned, being bought, or rented. If
there is no such person present, any household member 15 years old and over can serve as the
householder for the purposes of the census.
Housing unit
A house, an apartment, a mobile home or trailer, a group of rooms, or a single room occupied as
separate living quarters, or if vacant, intended for occupancy as separate living quarters. Separate
living quarters are those in which the occupants live separately from any other individuals in the
building and which have direct access from outside the building or through a common hall. For
vacant units, the criteria of separateness and direct access are applied to the intended occupants
whenever possible.
Hispanic or Latino origin

For Census 2000, American Community Survey: People who identify with the terms "Hispanic" or
"Latino" are those who classify themselves in one of the specific Hispanic or Latino categories listed
on the Census 2000 or ACS questionnaire—"Mexican," "Puerto Rican," or "Cuban"—as well as
those who indicate that they are "other Spanish, Hispanic, or Latino." Origin can be viewed as the
heritage, nationality group, lineage, or country of birth of the person or the person’s parents or
ancestors before their arrival in the United States. People who identify their origin as Spanish,
Hispanic, or Latino may be of any race.
1990 Census of Population and Housing: A self-designated classification for people whose origins
are from Spain, the Spanish-speaking countries of Central or South America, the Caribbean, or those
identifying themselves generally as Spanish, Spanish-American, etc. Origin can be viewed as
ancestry, nationality, or country of birth of the person or person’s parents or ancestors prior to their
arrival in the United States.
Income
"Total income" is the sum of the amounts reported separately for wages, salary, commissions,
bonuses, or tips; self-employment income from own non-farm or farm businesses, including
proprietorships and partnerships; interest, dividends, net rental income, royalty income, or income
from estates and trusts; Social Security or Railroad Retirement income; Supplemental Security
Income (SSI); any public assistance or welfare payments from the state or local welfare office;
retirement, survivor, or disability pensions; and any other sources of income received regularly such
as Veterans' (VA) payments, unemployment compensation, child support, or alimony.
Incorporated place
A type of governmental unit incorporated under state law as a city, town (except the New England
states, New York, and Wisconsin), borough (except in Alaska and New York), or village and having
legally prescribed limits, powers, and functions.
Related terms: Census designated place (CDP), Place
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Living quarters
A housing unit is a house, an apartment, a mobile home or trailer, a group of rooms or a single
room occupied as separate living quarters or, if vacant, intended for occupancy as separate living
quarters. Separate living quarters are those in which the occupants live separately from any people in
the building and which have direct access from outside the building or through a common hall.
Related term: Housing unit
Long form
The decennial census questionnaire, sent to approximately one in six households for the 1980, 1990,
and 2000 censuses, contains all of the questions on the short form, as well as additional detailed
questions relating to the social, economic, and housing characteristics of each individual and
household. Information derived from the long form is referred to as sample data, and is tabulated
for geographic entities as small as the block group level in 1980, 1990, and 2000 census data
products.
Related terms: Census (decennial), Sample data, Short form
Metropolitan
Refers to those areas surrounding large and densely populated cities or towns.
Metropolitan area (MA)

A collective term, established by the federal Office of Management and Budget, to refer to
metropolitan statistical areas, consolidated metropolitan statistical areas, and primary metropolitan
statistical areas.
Metropolitan statistical area (MSA)

statistical agencies, based on the concept of a core area with a large population nucleus, plus adjacent
communities having a high degree of economic and social integration with that core. Qualification
of an MSA requires the presence of a city with 50,000 or more inhabitants, or the presence of an
Urbanized Area (UA) and a total population of at least 100,000 (75,000 in New England). The
county or counties containing the largest city and surrounding densely settled territory are central
counties of the MSA. Additional outlying counties qualify to be included in the MSA by meeting
certain other criteria of metropolitan character, such as a specified minimum population density or
percentage of the population that is urban. MSAs in New England are defined in terms of minor
civil divisions, following rules concerning commuting and population density.
Related terms: Consolidated metropolitan statistical area (CMSA), Primary metropolitan statistical
area (PMSA)
Minor civil division (MCD)

A primary governmental and/or administrative subdivision of a county, such as a township,
precinct, or magisterial district. MCDs exist in 28 states and the District of Columbia. In 20 states,
all or many MCD’s are general-purpose governmental units: Connecticut, Illinois, Indiana, Kansas,
Maine, Massachusetts, Michigan, Minnesota, Missouri, Nebraska, New Hampshire, New Jersey, New
York, North Dakota, Ohio, Pennsylvania, Rhode Island, South Dakota, Vermont, and Wisconsin.
Most of these MCD’s are legally designated as towns or townships.
Related Terms: Census county division (CCD), County subdivision, Unorganized territory
203
Municipio
Primary legal divisions of Puerto Rico. These are treated as county equivalents.
Native Hawaiian and Pacific Islander race and ethnic categories

Self-identification among people of Native Hawaiian and Pacific Islander descent. These are the 12
detailed Native Hawaiian and Pacific Islander race and ethnic categories used in displaying data from
Census 2000:
Polynesian: Micronesian: Melanesian:
Native Hawaiian Guanamanian or Fijian
Samoan Chamorro Other Melanesian
Tongan Other Micronesian Other Pacific Islander
Other Polynesian
Nonmetropolitan
The area and population not located in any Metropolitan area (MA).
Occupied housing unit

A housing unit is classified as occupied if it is the usual place of residence of the person or group of
people living in it at the time of enumeration.
Parish
A type of governmental unit that is the primary legal subdivision of Louisiana, similar to a county in
other states.
Place
A concentration of population either legally bounded as an incorporated place, or identified as a
Census Designated Place (CDP) including comunidades and zonas urbanas in Puerto Rico.
Incorporated places have legal descriptions of borough (except in Alaska and New York), city, town
(except in New England, New York, and Wisconsin), or village.
Related terms: Census designated place (CDP), City, Comunidad, Incorporated place, Town, Zona
urbana
Plumbing facilities
The data on plumbing facilities were obtained from both occupied and vacant housing units.
Complete plumbing facilities include: (1) hot and cold piped water; (2) a flush toilet; and (3) a
bathtub or shower. All three facilities must be located in the housing unit.
Population
All people, male and female, child and adult, living in a given geographic area.
Population density
Total population or number of housing units within a geographic entity (for example, United States,
state, county, place) divided by the land area of that entity measured in square kilometers or square
miles. Density is expressed as both "people (or housing units) per square kilometer" and "people (or
housing units) per square mile" of land area.
Poverty
Following the Office of Management and Budget’s (OMB’s) Directive 14, the Census Bureau uses a
set of money income thresholds that vary by family size and composition to detect who is poor. If
204
the total income for a family or unrelated individual falls below the relevant poverty threshold, then
the family or unrelated individual is classified as being "below the poverty level."
For a detailed description of how the poverty level is determined, see:
http://www.census.gov/hhes/poverty/povdef.html
Related term: Income
Primary metropolitan statistical area (PMSA)

statistical agencies. If an area meets the requirements to qualify as a metropolitan statistical area and
has a population of one million or more, two or more PMSAs may be defined within it if statistical
criteria are met and local opinion is in favor. A PMSA consists of one or more counties (county
subdivisions in New England) that have substantial commuting interchange. When two or more
PMSAs have been recognized, the larger area of which they are components then is designated a
consolidated metropolitan statistical area.
Related terms: Consolidated metropolitan statistical area (CMSA), Metropolitan statistical area
(MSA)
Puerto Rico
The U.S. Census Bureau treats the Commonwealth of Puerto Rico as the equivalent of a state for
data presentation purposes. Puerto Rico is divided into legal government municipios, which are
statistically equivalent to counties.
Race
Race is a self-identification data item in which respondents choose the race or races with which they
most closely identify.
For Census 2000:
In 1997, after a lengthy analysis and public comment period, the Federal Office of Management and
Budget (OMB) revised the standards for how the Federal government would collect and present
data on race and ethnicity.
These new guidelines revised some of the racial categories used in 1990 and preceding censuses and
allowed respondents to report as many race categories as were necessary to identify themselves on
the Census 2000 questionnaire. The full report is available at
http://www.whitehouse.gov/omb/inforeg/race.pdf.
How the new guidelines affect Census 2000 results and the comparison with data from 1990:
Census 2000 race data are not directly comparable with data from 1990 and previous censuses. See
the Census 2000 Brief, "Overview of Race and Hispanic Origin" at
http://www.census.gov/prod/2001pubs/c2kbr01-1.pdf.
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Race Alone categories (6):

Includes the minimum five race categories required by OMB, plus the ‘some other race alone’
included by the Census Bureau for Census 2000, with the approval of OMB.
White alone
Black or African-American alone
American Indian or Alaska Native alone
Asian alone
Native Hawaiian or other Pacific Islander alone
Some other race alone
Race Alone or in combination categories (63):
There are other tabulations where ‘race alone or in combination’ are shown. These tabulations
include not only persons who marked only one race (the ‘race alone’ category) but also those who
marked that race and at least one other race. For example, a person who indicated that she was of
Filipino and African-American background would be included in the African-American alone or in
combination count, as well as in the Asian alone or in combination count. The alone or in
combination totals are tallies of responses, rather than respondents. So the sum of the race alone or
in combination will add to more than the total population.
Some tabulations show the number of persons who checked ‘two or more races’.
In some tables, including the first release of Census 2000 information, data is tabulated for 63
possible combinations of race:
6 race alone categories
15 categories of 2 races (e.g., White and African American, White and Asian, etc.)
20 categories of 3 races
1 category of 6 races
=63 possible combinations
Some tables show data for seven race categories: the six (mutually exclusive) major race-alone
categories (White, African-American, American Indian and Alaska Native, Asian, Native Hawaiian
and Other Pacific Islander, and some other race) and a ‘two or more races’ category. The sum of
these seven categories adds to 100 percent of the population.
Related terms: Alaska Native race/ethnic categories, American Indian tribe/Selected American
Indian categories, Asian, Native Hawaiian and Pacific Islander race and ethnic categories,
Spanish/Hispanic/Latino
Rural
Territory, population and housing units not classified as urban. “Rural” classification cuts across
other hierarchies and can be in metropolitan or non-metropolitan areas.
Related terms: Urban, Metropolitan
Sample data
Population and housing information collected from the census long form for a one in six sample of
households in the United States and Puerto Rico, and on a continuous basis for selected areas in the
American Community Survey.
Related terms: Census (decennial), Long form
206
Short Form
The decennial census questionnaire, sent to approximately five of six households for the 1980, 1990,
and 2000 censuses. For Census 2000, the questionnaire asked population questions related to
household relationship, sex, race, age and Hispanic or Latino origin and housing questions related to
tenure, occupancy, and vacancy status. The 1990 short form contained a question on marital status.
The questions contained on the short form also are asked on the long form, along with additional
questions.
Related terms: Census (decennial), Long form
Spanish/Hispanic/Latino
For Census 2000 and the American Community Survey: People who identify with the terms
"Hispanic" or "Latino" are those who classify themselves in one of the specific Hispanic or Latino
categories listed on the Census 2000 or ACS questionnaire—"Mexican," "Puerto Rican," or
"Cuban"—as well as those who indicate that they are "other Spanish, Hispanic, or Latino." Origin
can be viewed as the heritage, nationality group, lineage, or country of birth of the person or the
person’s parents or ancestors before their arrival in the United States. People who identify their
origin as Spanish, Hispanic, or Latino may be of any race.
For 1990 Census of Population and Housing:

A self-designated classification for people whose origins are from Spain, the Spanish-speaking
countries of Central or South America, the Caribbean, or those identifying themselves generally as
Spanish, Spanish-American, etc. Origin can be viewed as ancestry, nationality, or country of birth of
the person or person’s parents or ancestors prior to their arrival in the United States.
Spanish/Hispanic/Latino people may be of any race.

Listed below are the 28 Hispanic or Latino categories used in Census 2000 tabulations:
Mexican South American: Other Hispanic or Latino:
Puerto Rican Argentinian Spaniard
Cuban Bolivian Spanish
Dominican Republic Chilean Spanish American
Central American: Colombian All other Hispanic or
Costa Rican Ecuadorian Latino
Guatemalan Paraguayan
Honduran Peruvian
Nicaraguan Uruguayan
Panamanian Venezuelan
Salvadoran Other South American
Other Central American
Summary File 3 (SF 3)

This file presents data on the population and housing long form subjects such as income and
education. It includes population totals for ancestry groups. It also includes selected characteristics
for a limited number of race and Hispanic or Latino categories. The data are available for the U.S.,
regions, divisions, states, counties, county subdivisions, places, census tracts, block groups,
metropolitan areas, American Indian and Alaska Native areas, tribal subdivisions, Hawaiian home
lands, congressional districts, and Zip Code Tabulation Areas.
Related term: Long form
207
Town
A type of minor civil division in the New England states, New York, and Wisconsin and a type of
incorporated place in 30 states and the Virgin Islands of the United States.
Related term: County subdivision
Unorganized Territory
Occur in 10 minor civil division (MCD) states where portions of counties are not included in any
legally established MCD or independent incorporated place. The pieces are recognized as one or
more separate county subdivisions for statistical data presentation purposes.
Urban
All territory, population and housing units in urbanized areas and in places of more than 2,500
persons outside of urbanized areas. "Urban" classification cuts across other hierarchies and can be in
metropolitan or non-metropolitan areas.
Related terms: Metropolitan, Rural
Urban Area
Collective term referring to all areas that are urban. For Census 2000, there are two types of urban
areas: urban clusters and urbanized areas.
Urban Cluster
A densely settled territory that has at least 2,500 people but fewer than 50,000. This is new for
Census 2000.
Urbanized area (UA)

An area consisting of a central place(s) and adjacent territory with a general population density of at
least 1,000 people per square mile of land area that together have a minimum residential population
of at least 50,000 people. The Census Bureau uses published criteria to determine the qualification
and boundaries of UAs.
Usual residence
The living quarters where a person spends more nights during a year than any other place.
Related term: Living quarters
Usual residence elsewhere

A housing unit temporarily occupied at the time of enumeration entirely by people with a usual
residence elsewhere is classified as vacant. The occupants are classified as having a "Usual residence
elsewhere" and are counted at the address of their usual place of residence.
Village
A type of incorporated place in 20 states and American Samoa. The Census Bureau treats all villages
in New Jersey, South Dakota, and Wisconsin and some villages in Ohio as county subdivisions.
Zona Urbana
Represents a census designated place that is the governmental center of each municipio in Puerto
Rico. There are no incorporated places in Puerto Rico.
Related term: Municipio
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The RCAP Network
To determine what services are available
in your community, contact:
Great Lakes RCAP

WSOS Community Action Commission
109 South Front Street
Fremont, Ohio 43420
(419) 334-8911
www.wsos.org
Midwest RCAP
Midwest Assistance Program
212 Lady Slipper Avenue NE
Post Office Box 81
New Prague, Minnesota 56071
(952) 758-4334
www.map-inc.org
Northeast RCAP
RCAP Solutions
218 Central Street
Winchendon, Massachusetts 01475
(978) 297-5300
www.rcapsolutions.org
Southeast RCAP
Southeast Rural Community Assistance Project
145 Campbell Avenue SW
Post Office Box 2868
Roanoke, Virginia 24001-2868
(540) 345-1184
www.sercap.org
Southern RCAP
Community Resource Group
Post Office Box 1543
Fayetteville, Arkansas 72702
(479) 443-2700
www.crg.org
Western RCAP
Rural Community Assistance Corporation
3120 Freeboard Drive, Suite 201 Funded by
West Sacramento, California 95691 Technical Assistance and Training Grant, United States
(916) 447-2854 Department of Agriculture (USDA), Rural Utilities Service,
Water and Environmental Programs
www.rcac.org
Community Capacity Development for Safe Drinking Water,
RCAP, Inc. United States Enviromental Protection Agency (USEPA),
Office of Ground Water and Drinking Water
1522 K Street NW, Suite 400
Solid Waste Management Grant, United States Department of Agriculture
Washington, DC 20005 (USDA), Rural Utilities Service, Water and Environmental Programs
(202) 408-1273 Small Community Wastewater Project, Environmental Protection Agency
www.rcap.org (USEPA), Office of Wastewater Management
Still Living Without the Basics in the 21st Century
(SPINE -- To be dropped in)

Still Living Without The Basics

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rcap_cover_final 6/2/04 2:21 PM Page 1

Rural Community Assistance Partnership

Randolph A. Adams, Ph.D.

Still Living Without the Basics in the 21st Century

Stephen Gasteyer, Ph.D., Director of Community Development

Still Living Without the Basics: Analyzing the Availability of Water

responses to Item 39 of the Long Form of U.S. Census 2000.

Methodological Layout of the Study

Part I of the Analysis

Part II of the Analysis

Report Findings and Discussions

Assistance Program, Washington, D.C., 1995.

households and people lacking complete plumbing facilities.

Rural – Urban Divide

Analysis by Race and Ethnicity

Bureau, Department of Commerce, 2004.

In Which States Are Basic Water Services Most Lacking?

Why Are Water and Sanitation Services Important?

Access to safe drinking water saves lives

Figure 2: Number of Reported Drinking Water Outbreaks, 1991–2000

Number of Drinking Water Outbreaks, 1991–2000

1991–92 1993–94 1995–96 1997–98 1999–00

Issues and Experience, National Academy Press, Washington, D.C., 2000.

Lexington Books, 1975.

Factors Affecting People Living Without Basic Services

http://water.usgs.gov/nawqa/whatsnew.html, accessed December 10, 2003.

Cost and Quality of Water and Sanitation Services

http://www.epa.gov/safewater/sdwis/, accessed May 2, 2004.

Factors Influencing Trends in Access to Water and Sanitation

Census 2000, http://www.fact.finder.census.gov, accessed May 19, 2004.

Gasteyer, May 15, 2004.

What Has Been and Is Being Done to Address These Issues?

Ensuring That Water Infrastructure Is Adequately Maintained

Key Program and Policy Concerns Related to These Issues

Texas 15169 1.16 26028 2.23 -41.72 12.33

Total rural Total rural

Abbreviation Full Term Explanation

Abbreviation Full Term Explanation

( OHU below poverty

Occupied Housing Units (OHU)

Alabama (AL) Occupied Housing Units (OHU)

Alabama (AL) Occupied Housing Units (OHU)

Alabama (AL) Occupied Housing Units (OHU)

Occupied Housing Units (OHU)

Alaska (AK) Occupied Housing Units (OHU)

Alaska (AK) Occupied Housing Units (OHU)

Alaska (AK) Occupied Housing Units (OHU)

Occupied Housing Units (OHU)

Arizona (AZ) Occupied Housing Units (OHU)

Arizona (AZ) Occupied Housing Units (OHU)

Occupied Housing Units (OHU)

Arkansas (AR) Occupied Housing Units (OHU)

Arkansas (AR) Occupied Housing Units (OHU)

Arkansas (AR) Occupied Housing Units (OHU)

Occupied Housing Units (OHU)

California (CA) Occupied Housing Units (OHU)

California (CA) Occupied Housing Units (OHU)

Occupied Housing Units (OHU)

Colorado (CO) Occupied Housing Units (OHU)

Colorado (CO) Occupied Housing Units (OHU)

Occupied Housing Units (OHU)

Occupied Housing Units (OHU)