Notes from "Counting Working-Age People with Disabilities"

Book Discussed

Houtenville, A. J., Stapleton, D. C., Weathers, R. R. II, & Burkhauser, R. V. (Eds.). (2009). Counting working-age people with disabilities: What current data tell us and options for improvement.  Kalamazoo:  W. E. Upjohn Institute for Employment Research.

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I read several chapters of this inexpensive book.  This post presents my notes on (as distinct from a review of) those chapters.

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Preface

I had previously noticed that Cornell had a website with a lot of information on disability statistics.  This preface explains why.  The U.S. Department of Education’s National Institute for Disability and Rehabilitation Research (NIDRR) awarded Cornell a grant for a Rehabilitation, Research, and Training Center (RRTC) (which Cornell called StatsRRTC).This book grew out of a conference on disability statistics research in Washington, DC in October 2006.

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Chapter 1

Stapleton, D. C., Houtenville, A. J., Weathers, R. R. II, & Burkhauser, R. V. (2009). Purpose, overview, and key conclusions.  In A. J. Houtenville, D. C. Stapleton, R. R. Weathers, II, & R. V. Burkhauser (Eds.), Counting working-age people with disabilities: What current data tell us and options for improvement (pp. 1-26).  Kalamazoo:  W. E. Upjohn Institute for Employment Research.

The title's focus on working-age people follows from an earlier article by Weathers in which he identified the 18-64 age group as being the traditional group of working age, and further pared away the 18-24 group as being in a school-to-work transition stage, and the 62-64 group as being in a work-to-retirement transition stage.  As in that earlier article, this chapter (p. 6) focuses on the group of people aged 25-61.

The authors identify (p. 9) a number of reasons why state-level data on the prevalence of people with disabilities (PWDs) are important -- why, that is, federal data do not capture important local variations.  Some of the reasons include different physical, cultural, economic, and policy environments.  They refer (p. 13) to the National Disability Data System (NDDS), which does not exist in any formal sense (although it should) but can be understood, at present, as the aggregate of a number of disparate data collection and analysis efforts on federal and other levels.  For instance, data from administrative records suggest that only about half of the total number of PWDs estimated by the American Community Survey (ACS) are actually enrolled in federal programs that provide assistance to PWDs (p. 15).

One section of this chapter discusses shortcomings in statistical knowledge about disabilities.  The book has whole chapters that address this and related topics, so I did not read this section in any detail.  I was surprised, though, to see the authors praise the 2008 ACS as having “an improved set of disability questions” (p. 23).  I had not thought that the new set of questions was better, but of course I was not the expert.  So while I was not sure, at this point, that I would read those chapters in their entirety, I was interested to see what this book said about the new ACS.

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Chapter 2

Weathers, R. R., II (2009). The disability data landscape. In A. J. Houtenville, D. C. Stapleton, R. R. Weathers, II, & R. V. Burkhauser (Eds.), Counting working-age people with disabilities: What current data tell us and options for improvement (pp. 27-68).  Kalamazoo:  W. E. Upjohn Institute for Employment Research.

Weathers says that this book will be using concepts based on the International Classification of Functioning, Disability and Health (ICF) published by the World Health Organization (WHO).  The concepts from the ICF are “impairment,” “activity limitation,” “participation restriction,” and “disability.”  An impairment is “a significant deviation or loss in body function or structure” (p. 29).  An activity limitation is “a difficulty that an individual may have in executing activities,” particularly activities of daily living (ADLs) (i.e., activities inside the home, e.g., dressing).  A participation restriction is “an inability to engage in societal activities”; it can be either a work limitation or an instrumental activity of daily living (IADL) (i.e., an activity outside the home, e.g., shopping).  A disability is any one or more of these (e.g., an impairment that is also an activity limitation).  Weathers further divides impairments into sensory (e.g., hearing, seeing), physical (i.e., difficulty performing physical functions), and mental (i.e., difficulty performing mental functions).

Weathers uses these distinctions to talk about what one can learn from five major surveys:  the American Community Survey (ACS); the Community Population Survey (CPS), and especially its Annual Social and EConomic supplement (CPS-ASEC); the 2000 Decennial Census; the National Health Interview Survey (NHIS); and the Survey of Income and Program Participation (SIPP).  Weathers notes that “the disability data landscape is rapidly evolving” (p. 61); for example, he says new disability-related questions are being added to the CPS and to the Behavioral Risk Factor Surveillance System (BRFSS) produced by the Centers for Disease Control (CDC).  There have also been other changes since Weathers wrote this chapter (apparently around 2006), including the elimination of disability questions from the Census (which I therefore don’t discuss here) and the revision of disability questions in the ACS.

In an analysis that may not be entirely current, Weathers traces how each of these surveys operationalizes these concepts.  In the case of mental impairments, for example, the ACS asks about difficulty in learning, remembering, or concentrating because of a physical, mental, or emotional condition lasting at least six months; the CPS-ASEC has no questions; the NHIS asks about sadness, nervousness, worthlessness, etc. over the past 30 days; and the SIPP asks if you have a learning disability, mental retardation, a developmental disability, a problem with confusion or forgetfulness, or any other mental or emotional condition.

Weathers identifies four main kinds of questions that these surveys can be used to answer:  distinguishing subpopulations (e.g., the NHIS and the SIPP ask numerous questions, so you can tell what’s happening with with people who have severe vision disabilities, whereas the ACS doesn’t distinguish different types of impairments (see preceding paragraph)); capturing state and local disability data (only the ACS); capturing long-term trends (especially the CPS and the NHIS); and capturing changes in the circumstances of the same individuals through reinterviewing (especially the SIPP, also the CPS).  The message from this analysis is that the best results come from knowing what each tool can do and being able to use them in combination when necessary.

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Chapter 3

Houtenville, A. J., Potamites, E., Erickson, W. A., & Ruiz-Quintanilla, S. A. (2009). Disability prevalence and demographics. In A. J. Houtenville, D. C. Stapleton, R. R. Weathers, II, & R. V. Burkhauser (Eds.), Counting working-age people with disabilities: What current data tell us and options for improvement (pp. 69-100).  Kalamazoo:  W. E. Upjohn Institute for Employment Research.

The authors say that there is a “generally accepted conclusion that there has been a decline in disability among the elderly,” and there seems to have been no change for the working-age population (aged 25-61) from 1997 to 2000, but there was a sharp rise for the working-age population between 1984 and 1996 (pp. 72-73).  The total increase during that period varied by age group:  18%, for those aged 18-29; 52%, for those 30-39; 46%, for 40-49; and 20%, for 50-59.  This change is theorized to stem from either a change in health or an increase in reporting.

In 2006, working-age disability prevalence by state varied from 9.1% in New Jersey to 21.4% in West Virginia, with a median of 12.6%.  There were fairly strong regional tendencies.  All southern states from New Mexico to West Virginia (except Texas, Georgia, Florida, and Virginia) were in the worst bracket; no other states except Alaska, Maine, and Montana were in that bracket.  The second-worst group was dominated by the other states of the Northwest, from Wyoming westward, and by the midwestern states from Missouri to Pennsylvania (including Michigan, excluding Illinois).  The best rates were California-Nevada, Colorado, the north-central states (including Illinois, excluding North Dakota), and the small states (except Rhode Island and Delaware) from Massachusetts to Maryland.

Working-age disability rates in 2006 varied dramatically by age and race.  All categories of disability (e.g., physical, mental) appeared at least two to three times more frequently among people in the 55-61 group as in those aged 25-34.  Only 6% of Asian-Americans, but 22% of African Americans, reported any disability.

The authors note that differences in socioeconomic status (SES) may explain some of these variations among states and races.  SES can influence lifestyle factors (e.g., smoking, obesity), access to health care, and the kinds of jobs that people have.

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Chapters 4-7:  not covered here

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Chapter 8

Ballou, J., & Markesich, J. (2009). Survey data collection methods. In A. J. Houtenville, D. C. Stapleton, R. R. Weathers, II, & R. V. Burkhauser (Eds.), Counting working-age people with disabilities: What current data tell us and options for improvement (pp. 265-298).  Kalamazoo:  W. E. Upjohn Institute for Employment Research.

Here is the chapter's summary (pp. 290-291):

Recommended Best Practices

Include people with disabilities

PAR [participatory action research] must be considered. Although there is limited research to document the differences in research conducted with and without the participation of people with disabilities, current evidence suggests data quality can be improved by including people with disabilities. Researchers should be vigilant about addressing the need to include people with disabilities in all phases of the survey process.

Use available resources

Surveying Persons with Disabilities: A Source Guide (Markesich, Cashion, and Bleeker 2006) provides a starting point for any disability research project. Although the research included in the collection of sources may not be definitive, these citations provide extensive information related to the methodological issues associated with surveying persons with disabilities and include documentation on approaches that have been used to improve accessibility.

Plan your research

Using the guidelines listed in Table 8.2, researchers must keep in mind the key steps in the process that can impact data quality, particularly for research about and with people who have disabilities. At a minimum, reviewing these guidelines can help in making thoughtful and deliberate decisions about survey methods. In addition, information in this chapter identifies steps in the survey process where particular attention is needed to improve measurement quality.

Train interviewers

Current research identifies what interviewers should know to make sure they have the tools needed to communicate with people who have disabilities. This training should include recognition of types of disabilities, criteria for the selection of proxies, and options that can be used when interviewing people with disabilities, such as alternate wording of questions and qualitative approaches that may differ from interviews with people who do not have disabilities.

Provide documentation

The information presented in Table 8.1 shows what is needed to provide full disclosure of survey methods. It is feasible to provide complete and easily accessible documentation on disability survey information, and doing so has the added benefit of describing how various methods improve survey quality. This documentation is also essential for analysis to assist researchers in evaluating data quality.

Perfecting Best Practices

Meta-analysis of current research

A useful next step would be to conduct a meta-analysis that synthesizes data on similar topics. A systematic analysis of information would identify consistent research results that can be used to set best practice standards with increased confidence and to target the knowledge gaps that require research.

Conduct methodological and experimental research

We described examples of research that is needed to inform a set of best practices for surveying persons with disabilities in our discussion of the steps in the survey process: sampling, questionnaire design, and data collection methods. A goal of the planning group was to establish priorities for future research. This was a tremendous challenge because there are multiple issues that need to be addressed. Information from a meta-analysis could provide guidance on future research priorities.

Educating researchers, both those using data for analysis and those designing surveys to obtain data from and about people with disabilities, will result in improved disability information. One of the major changes needed in disability research is the inclusion of people with disabilities in all phases of the process. Being attentive to the methods used to collect survey information will increase the confidence that the data used for a range of public policy and service provision decisions more accurately represents people with disabilities.

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Chapter 9

Stapleton, D. C., Wittenburg, D. C., & Thornton, C. (2009). Program participants. In A. J. Houtenville, D. C. Stapleton, R. R. Weathers, II, & R. V. Burkhauser (Eds.), Counting working-age people with disabilities: What current data tell us and options for improvement (pp. 299-352).  Kalamazoo:  W. E. Upjohn Institute for Employment Research.

This chapter discusses programs that provide data about “working-age (aged 18-64) participants in the largest federal and federal-state programs that serve people with disabilities, including Social Security Disability Insurance (SSDI), Supplemental Security Income (SSI), Medicare, Medicaid, state vocational rehabilitation (VR) services, and disabled veterans benefits programs” (p. 299).  These are sometimes called “administrative” data sources, as distinct from “survey” data sources.

The authors are particularly interested in efforts to “match” administrative and survey data sources.  Generally, this appears to mean that survey participants agree to give researchers access to their personal files maintained in administrative databases.  Matching expands the amount of information that survey researchers can draw upon to understand groups of participants.  Given the sensitive nature of confidential medical and other administrative records, there are several major restrictions upon researchers’ access to such data.  The Census Bureau has come up with an alternative, known as a “synthetic” data file, in which the individual data points do not correspond with any actual human being, but collectively the data represent the characteristics of the target population.

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Chapter 10

She, P., & Stapleton, D. C. (2009). The group quarters population.  In A. J. Houtenville, D. C. Stapleton, R. R. Weathers, II, & R. V. Burkhauser (Eds.), Counting working-age people with disabilities: What current data tell us and options for improvement (pp. 353-380).  Kalamazoo:  W. E. Upjohn Institute for Employment Research.

There is the household population, and then there is the nonhousehold population.  The latter includes people who live in institutional group quarters (GQ), noninstitutional GQ, and homeless settings.  The ACS is in the process of becoming the main source of information on disabilities among the nonhousehold population.  That population is believed to have disabilities at far higher rates than the household population. 

The authors use the 2000 Census and three surveys of prison and jail inmates:  the Survey of Inmates of Local Jails (SILJ), the Survey of Inmates of State Correctional Facilities (SISCF), and the Survey of Inmates of Federal Correctional Facilities (SIFCF).  The authors welcome the recent expansion of the ACS to include the GQ population, but note that it “does not contain the wealth of information that can be found in other surveys of the household population” (p. 374).

In the institutional GQ, the authors observe that, up through 2000, there was a gradual decline in the percentage of the general population that lives in nursing homes, and a rapid rise in the share of the population that consists of people (especially young men) in correctional facilities.  The latter phenomenon seems posed to halt if not reverse, given current budget difficulties in many governmental entities. Nonetheless, the draining of people with (especially mental) disabilities from the household population into the nonhousehold population, especially into correctional facilities, may artificially depress the reported rate of disabilities in the household population:  “It is possible that growth in the incarceration of young adult males helps to substantially explain the decline in disability prevalence for young males” (p. 372).

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Chapter 11

Stapleton, D. C., Livermore, G. A., & She, P. (2009). Options for improving disability data collection. In A. J. Houtenville, D. C. Stapleton, R. R. Weathers, II, & R. V. Burkhauser (Eds.), Counting working-age people with disabilities: What current data tell us and options for improvement (pp. 381-418).  Kalamazoo:  W. E. Upjohn Institute for Employment Research.

The differences in time horizons and other features of the major surveys (see the last paragraph under Chapter 2, above) means that they can complement one another if they are asking the same questions.  To this end, the ACS questions are now used also by the CPS and NHIS.  But there is generally a tradeoff between large sample sizes (as in the ACS, which covers large numbers of people and therefore can provide estimates down to the county level) and the amount of information collected per person.  That is, the ACS questions do not capture the same amount of detail as some of the others (e.g., SIPP):  “One particular concern is that the ACS might fail to identify many people with significant psychiatric conditions” (p. 391).  Moreover, there are typically not enough people with a particular health condition to provide much detail from a statistical perspective.

According to the authors, “The surveys that provide the most in-depth information about people with disabilities are those that are conducted very infrequently or have only been conducted once” (p. 387).  In particular, “The NHIS Disability Supplement (NHIS-D) represents the most ambitious effort to date to collect a wide range of disability-relevant information from a large, nationally representative sample of people with disabilities of all ages.  The survey was conducted in two phases in 1994 and 1995.  The data are now more than a decade old, and the survey has not been repeated” (p. 388).

The authors advocate including the ACS questions in all federal surveys:  “In 1977, the [Office of Management and Budget] mandated the use of a standardized set of questions on race and ethnicity in all federal data collection.  A similar mandate for those at risk for disability now seems justified and would be welcomed by many users of disability data and statistics” (p. 392).  The reason is to provide comparability among surveys.  If, for example, the SIPP included the ACS questions, both would show the same prevalence of disabilities, but the ACS would then be supplemented with the greater data and somewhat longitudinal advantages of the SIPP.  That is, researchers would have much more insight into the characteristics of that 10% or 12% of the population that is identified as having a disability.  Presumably it would also be possible to speculate, at least, about county-level disability details (e.g., the numbers of people having a certain disability in a certain county) by interpreting SIPP data in light of ACS county-level data.

The authors advocate a number of other improvements to disability data collection, including stronger longitudinal data collection (especially in the SIPP), better matching of administrative and survey data, and better researcher access to matched records.  The authors want to see periodic disability supplements to existing surveys, periodic surveys of specific subpopulations, and periodic national disability surveys like the NHIS-D.  The top priorities, they say, are the inclusion of ACS questions in all federal surveys and the strengthening of longitudinal and administrative data (p. 410).

American Community Survey (2003): Disabilities Nationwide

In a previous post, I took a quick look at how the total household population figure in the American Community Survey (ACS) for 2003 was calculated.  The numbers involved are not precise in every case, but the general concept appears to be that the "resident population" is divided into people who live in households and those who live in group quarters (e.g., prisons, hospitals, dormitories).  In the 2003 ACS, only households were examined.  The total number of people in the U.S. who were living in households in 2003 was estimated to be 282,909,885.  Of those, an estimated 176,395,446 fell into the traditionally defined working-age population aged 18-64.

The next thing to figure out, in moving toward statistics on disabilities at the county level, was how many of those 176,395,446 people were considered to have various kinds of disabilities.  Here, as before, I relied on the analysis of 2003 ACS data provided by Weathers (2005) in his Guide to Disability Statistics from the American Community Survey.  The previous post notes that the ACS understates disabilities when compared to some other national surveys; however, it has the advantage of being updated on the county level, and thus provides an essential stepping-stone in this investigation.

Weathers (2005) divides that total of 176,395,446 working-age people into those with (12%) and without (88%) disabilities, as defined by the ACS.  Weathers further narrows the working-age population down to the 25-61 age range, considering the 18-24 group as being of a "school-to-work transition age" and the 62-64 group as being of "early Social Security retirement age" (p. 19).  Since the 25-61 group accounts for 83% (i.e., 17,146,845) of the total of 20,609,733 people with disabilities in the larger 18-64 group (p. 54), I will tend to focus on that 25-61 group in this post.

To summarize, then, the ACS gives us, in 2003, an estimated 17,146,845 U.S. residents who lived in households (as distinct from group homes), had one or more disabilities, and fell into the 25-61 age group.  These people comprised roughly 10% of the estimated working-age (18-64) population of about 176 million.

According to Weathers (2005, p. 35), the ACS draws upon World Health Organization (WHO) concepts of impairment, activity limitation, and participation restriction, as expressed in the International Classification of Functioning, Disability and Health (ICF) (pp. 4-5).  In the ICF, Weathers says, an impairment is a significant deviation or loss in body function or structure (e.g., vision loss).  An activity limitation is difficulty in executing activities of daily living (e.g., dressing).  A participation restriction is a problem that a person may have in a life situation (e.g., lack of employer accommodation to the person's severe health condition).

As Weathers (2005, pp. 10-11, 35) describes, the ACS uses six questions to operationalize those ICF concepts.  Three of the six ask about impairments:  sensory, physical, or mental.  One asks about activity limitation, in the form of an inability to care for oneself inside one’s home.  Two ask about participation restrictions, in the form of physical, mental, or emotional conditions that prevent the person from going outside the home (e.g., to shop) or from working at a job or business.  The ACS defines disabilities as the presence of any one or more of these kinds of disability. As an example of how these questions may fail to count some disabilities, Weathers (p. 27) indicates that the question of going outside the home, used on the ACS, is narrower than the concept of Instrumental Activities of Daily Living (IADLs) used in some surveys.

The 2003 ACS data indicate that, for the 25-61 group, two of these six questions (pertaining to physical impairment and employment restriction) account for 55% of all disabilities.  Those two plus the next most frequently cited disability, regarding mental impairment, account for 70% of all disabilities in that age group.  Yet within that statement lies an interesting age-related permutation.  First, as one might expect, age is a factor in the calculation of disability under the ACS.  The data show that disability prevalence rates rise from 6.3 in the 5-17 group (that is, 6.3% of people in that age group have a disability) to 39.9 in the 65+ group (Weathers, 2005, p. 39).  At the same time, however, while those top three questions account for about 70% of disabilities in all three working age groups (i.e., 18-24, 25-61, and 62-64), the share due to mental impairments steadily declines.  Mental impairments constitute 30% of all disabilities in the 18-24 group, but only 15% in the 25-61 group and 10% in the 62-64 group.

It is not that mental impairments actually decline with age, though that may be the case for some kinds of mental impairments.  It is, rather, that mental impairments rise only slightly, from 3.7 in the 18-24 group to 5.8 in the 62-64 group.  This is quite different from the ninefold rise in physical disabilities between those two groups.  One explanation for that contrast is that the ACS may undercount mental disabilities in adults.  There is evidence of reduced awareness of mental disability on the part of adults and their primary care physicians (e.g., Surman, Wigal, & Lakes, 2009).  Undercounting of mental disabilities in adults would also be unsurprising if significant mental disabilities are incompletely conceptualized among adults (e.g., Nijmeijer et al., 2008, p. 701).

So far in this series of posts on statistics pertaining to disabilities, I have rarely gone beyond the relatively general descriptive approach provided by commentators such as Weathers (2005).  The preceding paragraph suggests, though, that a look at more critical or focused literature may highlight a number of shortcomings with the ACS, for purposes of counting disabilities.  As an example of another area in which a more refined approach may considerably enhance the statistical picture, one may review Weathers's remark (above) about the refinement that the IADL concept adds to the question of going outside the home.  Unless Weathers meant to contrast IADL against the ACS's question regarding self-care, and simply misspeaks on that point (compare pp. 27 and 39), it seems appropriate to question the finding that 6.9% of people in the 25-61 age group experience a significant employment restriction due to disability, and yet only 2.0% report a limitation in their self-care activity.  Without a boss or other reminder of a set goal, people at home may be more likely to adjust their goals and lives to accommodate their disabilities.

Those examples of potential shortcomings in the ACS may or may not be borne out in the professional literature.  I can't say; I haven't gotten that far yet.  The purpose of those remarks was simply to highlight a few ways in which the ACS may undercount disabilities.  Having achieved that, the next step in this investigation is to move from the national-level ACS data to the state level.

American Community Survey (2003): National Population Statistics

As described in a previous post, I found that the Cornell University Disability Statistics website offered materials that seemed likely to help me estimate the number of people with disabilities (PWDs) in a particular county in the U.S.  The next step was to understand something about the general population terminology and concepts that formed the basis for census calculations.

I had learned that the American Community Survey (ACS) provided the most frequently updated and most recent county-by-county data.  The Guide to Disability Statistics from the American Community Survey (Weathers, 2005, p. 28) indicates that estimates of the numbers of PWDs depend directly upon the number of questions asked. According to Weathers (p. 4), the ACS approach has several limitations:

First, the ACS is limited to six questions that are used to identify the disability
population [as a whole] and it does not allow one to identify the prevalence of specific health conditions (e.g., cancer, paralysis, HIV/AIDS, etc.). Second, the ACS definition does not explicitly include important societal and environmental factors that may contribute to a disability such as discrimination and lack of reasonable accommodations. Finally, the ACS does not capture the population living in “group quarters.” Group quarters include individuals living in institutions, college dormitories, and other types of group quarters. This is a very important limitation in that it may leave out an important segment of the population with disabilities. The Census Bureau plans to address this last limitation of the ACS by including a sample of persons living in group quarters beginning in 2006.

By contrast, at the low end of the scale, according to the Guide to Disability Statistics from the Current Population Survey - Annual Social and Economic Supplement (March CPS) (Burkhauser & Houtenville, 2006, p. 19), the Current Population Survey asks just one question about disabilities -- regarding, specifically, the presence or absence of a work limitation -- and thus "misses a large part of the broader population with disabilities based on an ICF [i.e., International Classification of Functioning] disability conceptualization."  On the other extreme, as Burkhauser & Houtenville (2006, p. 19) also note, the Survey of Income and Program Participation (SIPP) uses 93 disability-related questions.  Generally, they say, "data sets that ask more questions to identify a population with disabilities and that contain a broader disability conceptualization will capture a larger disability population."

Weathers (2005) quantifies the difference made by these varying operationalizations of the concept of disability.  Weathers uses data from 2003.  To analyze these data, it may be helpful to begin by clarifying the meanings of some terms that the Census Bureau uses.

First, the resident population of the U.S. includes all U.S. residents living in the 50 states and the District of Columbia.  That is, it excludes residents of Puerto Rico and American possessions abroad, as well as U.S. citizens living abroad, whether in the military or as expatriates.  This post does not examine the question of whether PWDs may be disproportionately represented in the military -- whether, that is, the percentages of PWDs in their home counties would be noticeably higher (particularly in some age groups and locations) if those members of the Armed Forces were available for inclusion within the count of PWDs under the ACS.

The resident U.S. population as of July 1, 2003 was estimated to be 290,210,914.  According to the 2003 ACS Subject Definitions (p. 13), the resident population is divided into people who live in housing units (i.e., households) and those who live in group quarters.  "Housing units" can include any occupied "unit," including tents and railroad cars; but "If all the people staying in the unit at the time of the interview are staying there for two months or less, the unit is considered to be temporarily occupied, and classified as 'vacant'" (p. 14).  The data include transients (i.e., those who stay only briefly in any one place), however, by including them if there is no place where they usually stay.  Note that "Vacant units are excluded from the housing inventory if they are open to the elements; that is, the roof, walls, windows, and/or doors no longer protect the interior from the elements. Also, excluded are vacant units with a sign that they are condemned or they are to be demolished" (p. 14).  It preliminarily appears, then, that the 2003 ACS data undercount people who are not living in any kind of housing unit but, rather, are living outdoors (e.g., under a bridge) -- among whom, again, there may be a disproportionate number of PWDs.

The Census Bureau indicates that residents of group quarters were sampled in 1999 and 2001, but the 2003 data exclude people living in group quarters.  For purposes of introducing some relevant terms, then, it will be convenient to refer to the 2000 census.  According to the Statistical Abstract of the United States for 2003, table 77 (examining 2000 census data), about 7.8 million people (2.8% of the total resident population of 281,424,602 in 2000) lived in group quarters.  These people were divided almost equally into institutionalized and noninstitutionalized group quarters.  Among the institutionalized individuals in group quarters, by far the largest groups were males aged 18-64 in correctional institutions (44%) and females aged 65+ in nursing homes (29%).  Other institutions include mental hospitals and wards and juvenile facilities.  Among noninstitutionalized individuals in group quarters, 55% were living in college dormitories.  Other noninstitutional group quarters include military quarters, religious group quarters, shelters, and group homes. 

If 2.8% of the total resident population lived in group quarters in 2003, as was the case in 2000 (above), that would mean that just over 8 million (i.e., 2.8% of 290,210,914) lived in group quarters in 2003.  Subtracting those 8 million from the total resident population would produce something like the 282,909,885 people whom the Census Bureau estimated as the total household population in 2003.

The total household population included people of all ages.  In the analysis of disabilities done by Weathers (2005), however, the focus is on people who were between 18 and 64 years of age in 2003.  In the 2003 ACS, to use the slightly adjusted number provided by Weathers, the Census Bureau estimates that there were 176,395,446 people in this age group.  This number is quite close to the 176,305,337 estimated by the SIPP for that year, and roughly midway between the estimates of 172,761,000 from the NHIS and 179,132,544 provided by the CPS.

I will be using the ACS figure in the next step, which addresses the numbers and percentages of people with disabilities within that larger total.  At this point, I join Weathers (2005) in turning from the estimate of the total numbers of people with disabilities in the population, and focus (at least for the time being) upon the prevalence of disabilities among people of traditional working (i.e., post-high school, pre-retirement) age.