The "curve" representing the percentage of the population with a disability isn't a single, universally agreed-upon curve, but rather a trend observed over time and varying significantly based on several factors. There isn't a single, simple story behind it, but rather a complex interplay of contributing elements. The apparent "curve" – whether it's perceived as rising, plateauing, or fluctuating – depends heavily on how disability is defined and measured.

Here's a breakdown of the factors influencing the perceived curve:
 

Changing Definitions and Measurement:

This is the most significant factor. Over time, societal understanding of disability has evolved. What was once considered a disability might now be accommodated or even celebrated as neurodiversity. Similarly, advances in medical technology and assistive devices mean conditions once disabling may now be manageable. Different surveys and censuses employ varying definitions and methodologies, making direct comparisons challenging. For example, the inclusion of hidden disabilities like autism or chronic pain conditions in surveys significantly impacts the reported percentage.
 

Improved Reporting and Awareness:

Greater awareness of disability rights and the importance of accurate data collection has likely led to more people self-identifying as having a disability. This doesn't necessarily mean there's a dramatic increase in the prevalence of disabilities, but rather a more accurate reflection of the existing population.
 

Aging Population:

As populations age globally, the prevalence of age-related disabilities (e.g., arthritis, dementia) increases. This naturally inflates the overall percentage of the population with a disability, creating an upward trend in the curve.
 

Environmental Factors:

Exposure to environmental toxins, increased stress levels, and other societal factors might influence the incidence of certain disabilities. The impact of these factors is difficult to isolate and quantify but could contribute to shifts in the curve.
 

Advances in Medical Care:

While some advancements reduce the impact of disabilities, others can lead to increased identification of previously undiagnosed conditions. Early diagnosis of conditions like autism or ADHD, for instance, could appear to increase the overall prevalence.
 

In summary:

There isn't a single, simple "story" behind any perceived curve in disability prevalence. The apparent trend is highly dependent on how disability is defined, measured, and reported, as well as on demographic shifts and societal changes. Any observed increase might not represent a true rise in disability incidence but rather an improvement in data collection, broadened understanding, and the inclusion of previously under-represented groups. Critical analysis of the methodologies employed in different studies is crucial for accurately interpreting any perceived trend.

US Census Bureau | ACS 5-yr Estimates

Data Notes: DISABILITY CHARACTERISTICS

Survey/Program: American Community Survey

Estimates: 5-Year

Although the American Community Survey (ACS) produces population, demographic, and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties.

Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website. Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section.

Source: U.S. Census Bureau, 2023 American Community Survey 5-Year Estimates

Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables.

The Census Bureau introduced a new set of disability questions in the 2008 ACS questionnaire. Accordingly, comparisons of disability data from 2008 or later with data from prior years are not recommended. For more information on these questions and their evaluation in the 2006 ACS Content Test, see the Evaluation Report Covering Disability. For cognitive difficulty, ambulatory difficulty, and self-care difficulty, the 'Population under 18 years' includes persons aged 5 to 17. Children under 5 are not included in these measures.

The 2022 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities. Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization.

Citation: U.S. Census Bureau. "DISABILITY CHARACTERISTICS." American Community Survey, ACS 5-Year Estimates Subject Tables, Table S1810, 2018, https://data.census.gov/table/ACSST1Y2018.S1810?q=disability chemung county. Accessed on 4.22.25