Sunday, January 3, 2010

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.