IJE Advance Access originally published online on August 22, 2006
International Journal of Epidemiology 2006 35(5):1261-1263; doi:10.1093/ije/dyl153
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Commentary |
Commentary: Dissecting disability trends—concepts, measures, and explanations
1 Department of Health Systems and Policy, School of Public Health, University of Medicine and Dentistry of New Jersey, New Brunswick, NJ 08903, USA
2 Institute of Medicine, The National Academies, Washington DC 20001, USA
* Corresponding author. E-mail: vfreedman{at}umdnj.edu
A fundamental question at the intersection of the epidemiology and demography of aging is whether mortality declines in late life are accompanied by a compression or expansion of morbidity and disability. The answer has both theoretical implications and practical consequences for many nations now facing population aging.
Sulander and colleagues1 find that the proportion of older people in Finland with difficulty in basic activities of daily living (BADLs; bathing, dressing, or eating) decreased between the early 1990s and early 2000s. Difficulty with only mobility (not with BADLs) increased for women and was flat for men. And educational gaps in BADLs persisted over the period. These findings join studies from the US and other industrialized countries in suggesting that disability may be declining in late life while socioeconomic disparities are persisting or growing.1
What are the challenges in interpreting this accumulating evidence and advancing our understanding of the implications of lengthening life? We believe three topics will continue to confront researchers in this line of inquiry: (i) linking measures of disability to clear concepts; (ii) ensuring validity of comparisons based on survey data; and (iii) moving beyond disparities to understand causal mechanisms.
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Linking clear concepts to measures of disability |
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Over the last few decades, the world's understanding of disability has evolved from a classic medical model, which attributes disability to underlying chronic conditions and impairments, to one that recognizes disability as a gap between functional ability (e.g. reaching, bending, walking) and the demands of the environment.2,3 Nevertheless, in practice the term disability and its measurement have been applied inconsistently. Even one of the most widely used scales to measure personal-care disability in old age, the Index of Activities of Daily Living,4 has many incarnations, not all of which measure the same concepts. Some surveys ask whether respondents have difficulty (generally but not always without accommodations, e.g. help or equipment); others ask about the need for help or inability to complete the activity without help; still others ask about the use of accommodations, that is, whether individuals get help or use special equipment. These wording differences are not only important conceptually but may yield quite different prevalence levels and trends.5
The Sulander paper combines individuals who cannot do activities even with assistance with individuals reporting they can carry out an activity with assistance and those who report they can carry out the activity independently but with difficulty. Additional insights about disability trends might be gleaned by separating out these groups. Moreover, combining their results with additional information on trends in assistive technology might enable the authors to discern the extent to which the decline in BADLs represents changes in accommodations vs changes in underlying functioning. In the US, this exercise has demonstrated the importance of both factors in recent declines in the use of help for personal-care activities.6
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Ensuring validity of survey comparisons |
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Studies that track population health trends place unusually high demands on the data in terms of its consistency over time. Considerations include: wording changes, the type and coverage of the sample frame, who is interviewed (proxy rates), the mode of interview, whether the survey is a repeated cross-section or a panel design, and the frequency and timing of interviews.7 These features, and any changes in them over time, may affect estimation of trends. Hence, a high degree of scepticism is in order in evaluating such trends.
The data used by Sulander and colleagues rate highly on many counts. The study used identical questions, included community-dwelling and institutionalized respondents, and involved repeated (cross-sectional) biannual surveys. Response rates were 80% averaged over the period, although changes over time in response rates were not reported. Importantly, unlike most of the work in the US and Europe, this study relied on postal surveys. Telephone and in-person surveys have been generally accepted as valid means for collecting data about disability, but mail surveys raise additional issues: Who fills out the survey? Are there literacy issues that may confound assessments and in doing so mask or inflate trends over time?
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Linking disparities to causal mechanisms |
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That late-life disability has declined in Finland is likely to be welcome news, but questions remain for Finland and other countries facing uncertainties due to increased longevity: What is causing the declines? Will they continue?
Sulander and colleagues' focus on education underscores one of the key pieces of the puzzle. In Finland, as in the US, there were large increases in educational attainment of the older population during the last decade of the 20th century. These dramatic changes are not uncommon among countries in which educational opportunities for young people were expanded significantly after the Second World War. In Finland, disability disparities by education have persisted, whereas US data suggest that such disparities are growing.8
How can analysis of disparities and shifts in compositional factors be used to identify mechanisms of the disability decline? Several approaches come to mind: First, time series of cross-sectional data can be used to decompose disability trends into changes associated with education and other factors.9 Second, projections of future characteristics of the older population may be possible for characteristics that are fixed relatively early in life, such as educational attainment, and may provide clues to possible future disability trends. Third, incorporating a more nuanced understanding of how education confers health benefits into trend analyses may offer insights. Social epidemiologists have suggested that social position, as reflected not only in education but also in income and occupation, influences health through a number of mechanisms, including differences in material resources, exposures, health-related behaviours, and psycho-social factors such as stress.10 Additional studies might address how these different elements have changed over time and whether their relationships to disability have strengthened or waned. Fourth, education may operate differentially in preventing the onset of a disease or disability vs in managing progression. For example, in the US, both income and education are associated with the onset of functional limitations in late life, but only the former influences improvement or deterioration.11 Exploring this longitudinal issue in Finland, as well as assessing whether or not disparities in health by education grow or shrink with age among birth cohorts,12 may help elucidate the mechanisms by which education influences late-life functioning.
Only by tracking of clearly delineated concepts and measures, and careful attention to the potential threats and pitfalls from survey-based analyses will researchers be able to reach fuller explanations of late-life disability trends. Such explanations are critical as nations plan for the costs—both human and technological—of caring for older adults with disabilities and attempt to maximize the benefits of enabling all adults to participate in society, irrespective of their age or ability.
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Acknowledgments |
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The authors gratefully acknowledge support for this commentary from the U.S. National Institute on Aging. The views expressed are those of the authors alone and do not represent those of the authors' affiliations or funding agency.
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References |
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1 Sulander T, Martelin T, Sainio P, Rahkonen O, Nissinen A, Uutela A. Trends and educational disparities in functional capacity among people aged 65–84 years. Int J Epidemiol 2006;35:1255–61.
2 Pope AM, Tarlov AR, eds. Disability in America: Toward a National Agenda for Prevention. Washington: National Academy Press, 1991.
3 World Health Organization. Towards a common language for functioning, disability, and health: International classification of functioning, disability and health. Geneva: World Health Organization, 2002.
4 Katz S, Ford AB, Moskowitz RW, Jackson BA, Jaffe MW. Studies of illness in the aged. The index of ADL: a standardized measure of biological and psychosocial function. JAMA 1963;185:914–19.
5 Freedman VA, Crimmins E, Schoeni RF et al. Resolving inconsistencies in old-age disability trends: report from a technical working group. Demography 2004;41:417–41.[CrossRef][Web of Science][Medline]
6 Freedman VA, Agree EM, Martin LG, Cornman JC. U.S. trends in assistive technology and personal care for disability in late life, 1992–2001. Gerontologist 2006;46:124–27.
7 Freedman VA, Martin LG, Schoeni RF. Recent trends in disability and functioning among older U.S. adults. JAMA 2002;288:3137–46.
8 Schoeni RF, Martin LG, Andreski P, Freedman VA. Persistent and growing disparities in disability among the elderly: 1982–2002. Am J Public Health.2005;95:2065–70.
9 Freedman VA, Martin LG. The role of education in explaining and forecasting trends in functional limitations among older Americans. Demography 1999;36:461–73.[Web of Science][Medline]
10 Lynch J, Kaplan G. Socioeconomic position. In: Berkman L, Kawachi I (eds). Social Epidemiology. Oxford University Press, New York, 2000, pp. 13–35.
11 Zimmer Z, House JS. Education, income, and functional limitation transitions among American adults: contrasting onset and progression. Int J Epidemiol 2003;32:1089–97.
12 Herd P. Do functional health inequalities decrease in old age? Educational status and functional decline among the 1931–1941 birth cohort. Res Aging 2006;28:375–92.
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