American Community Survey (2003): Disabilities on the State Level

In a previous post, I examined some statistics provided by the American Community Survey (ACS) for 2003, regarding the prevalence of certain kinds of disabilities on the national level.  Now I turn to the interpretation of the ACS on the state level.

Generally, as a Census Bureau methodological report explains, state population estimates are obtained by adding up the estimated numbers of people in each county.  The calculation of county population begins with the decennial census.  At present, that is the census taken in 2000, but of course there will be a new one this year (2010).  The Bureau makes adjustments from the previous year based on a variety of county-level sources, including tax records, estimates of migration, and registered births and deaths.  Previous years' estimates are revised as new information sheds light on actual developments.

State totals are not added up to produce the national population, however.  Instead, national totals are developed independently, and are used as a check upon county-level calculations.  Roughly speaking, if the sum of all state totals (that is, the sum of all county totals) were to exceed the independently developed national population estimate by 3%, then the population estimates for all counties would be reduced by 3% so that the state totals would match the national estimate.

Given this information, a lay reader might suggest that a parallel method of estimating the prevalence of disabilities within a county -- and thus within a state -- would supplement the ACS questionnaire by investigating actual records of disabilities, from such sources as hospital and school records, handicap-plate motor vehicle registrations, and Social Security records.  Presumably the efforts of researchers have uncovered shortcomings in decennial censuses; one might expect that these sorts of disability-related investigations would exert a similar beneficial influence on ACS disability estimates.

According to Weathers (2005, p. 61), the Census Bureau does investigate ways in which its statistical processes may produce errors.  Errors may be random, in which case statistical adjustments can be made or estimates of error can be produced.  Errors may also be nonrandom.  Nonrandom errors are also called systematic errors.  These occur, not because (for example) a predictable percentage of statistical typists will make a predictable percentage of typographical errors as they enter the data, but because some kind of atypical distortion occurs with respect to some particular kind of person or situation.  If, for example, followers of a certain religion were concentrated in a particular county, and if their religion taught that it was wrong to respond to surveys, then there could be a pronounced systematic, nonrandom undercounting of people in that county.  Along these lines, it would certainly seem that people who have physical disabilities that make every task a chore, or mental disabilities that discourage cooperation with governmental surveys they perceive as suspicious, could be systematically undercounted.

Weathers (2005, p. 61) indicates that the Census Bureau maintains information on identified systematic errors in the ACS at a page on its website.  A quick search of that webpage finds, at present, no entries pertaining to disabilities.  Weathers (pp. 68-70) does note certain regards, however, in which a redesign of the ACS disability questions resulted in dramatic and potentially erroneous declines in reported disabilities in 2003.  There have been substantial changes in the ACS measurement of disabilities since then.  A subsequent post will discuss those changes.  First, however, the following paragraphs explore the 2003 ACS in light of Weathers's comments, many of which are still applicable and/or have not yet been revisited.

ACS 2003 state-by-state disability prevalence rates (Weathers, 2005, pp. 45-46) raised questions of consistency in data collection procedures.  In the Midwest, for example, most states were fairly similar to one another:  overall disability rates were between 11.2 and 13.3 in Ohio, Indiana, Iowa, Michigan, Wisconsin, Missouri, Kansas, and Nebraska.  Indeed, without Indiana and Ohio, the range among those states would have been in the narrow band of 11.2 to 12.4.  Yet somehow, in the middle of those states, Illinois – right next to Indiana (13.3) – somehow produced a rate of 9.2.  Certainly it is plausible that a city like Chicago would manage to accommodate its persons with disabilities better than a more rural state; but why the presence of a large city would affect disability prevalence itself is not intuitively obvious.  If population density itself were a positive factor, Rhode Island (12.0) would not have had a rate considerably higher than those of its neighbors Connecticut (9.2) and Massachusetts (9.7).

Certainly the 2003 ACS state-level data are interesting.  Weathers (2005, pp. 23-24) compares states in terms of the levels of employment, poverty, and household income experienced by persons with disabilities.  His tables 7-9 (pp. 47-52) also provide relative comparisons of the experiences of people with and without disabilities in those several regards.  Thus, for example, whatever the rate of unemployment in West Virginia as a whole, the data reveal that that state’s people with disabilities are employed at only about one-third (35.8%) the rate of its people without disabilities -- as compared to Wyoming, on the opposite extreme among the lower 49 states, where the rate is more like two-thirds (65.5%).  Among the midwestern states just listed (including Illinois), that relative rate ranges from 48.4% (Michigan and Ohio) to 55.8% (Nebraska).

According to Weathers (2005), the relative experience of poverty for people with disabilities, like their relative level of employment, varies considerably among states.  At the low end, people with disabilities in Utah are only 2.1 times as likely to fall below the povety line as are people without disabilities.  At the high end, people in Nebraska are 4.9 times as likely to do so.  Nebraska aside, the midwestern states listed above are within the range of 3.4 (Illinois) to 3.8 (Kansas).

As with some of the other values discussed here, relative household incomes contrast western states against southern states.  Utah leads with a value of 75.9% – that is, the median household income of a person with disabilities in Utah is 75.9% of the median household income of a person without disabilities – and Louisiana (49.6%) and Alabama (50.4%) are beaten at the bottom end only by Delaware (which, with the slightly lower value of 48.3%, is an outlier in regional terms by several of these measures).  The midwestern range is from 54.2% (Ohio) to 62.3% (Wisconsin).  Relatively large differences among these states’ neighbors (e.g., 61.9% in Indiana, 56.4% in Michigan) raise the question of how state-level policies impact these numbers.

Some caveats are in order.  First, as with most of the observations in this post, it remains to be seen how these data have changed since 2003.  Note, too, that the foregoing analyses provided by Weathers (2005, p. 19) are focused upon the working-age population, ages 25-61.  Also, the ACS presents values on employment and poverty that are in some regards markedly divergent from those reported by most other national studies cited in a previous post in this series (Weathers, p. 29).

Across all age groups, Weathers (2005, pp. 20-21), notes that national counts of disabilities may be influenced by race, culture, gender, and education.  Black people comprise 13.8% of people with disabilities, as compared to 11.7% of the population without disabilities.  Hispanic people comprise 14.0% of the population without disabilities, but only 9.6% of the reported population with disabilities.  Women constitute 52.8% of the population with disabilities (versus 51% without), and are especially highly represented in disabilities involving self-care (58.9%) and going outside the home (63.6%).  People with less than a high school education account for 11.6% of people without a disability, but they account for 25.0% of people with a disability.  Disability rates may be correspondingly affected, in states that vary from the mean in any of these demographic regards.

Having provided an introduction to state-level measurement of disabilities through the ACS in 2003, largely as interpreted by Weathers (2005), the next step is to examine how ACS federal- and state-level measurements and results were changed in 2008.

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.