Cited by 292Statistical Methods in EpidemiologyObesity, Physical Activity, DietInsurance, Mortality, Demography, Risk Management

What is a cohort effect? Comparison of three statistical methods for modeling cohort effects in obesity prevalence in the United States, 1971-2006

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Keyes, Katherine M., Utz, Rebecca L., Robinson, Whitney, Li, Guohua·2010·Social Science & Medicine

Abstract

Analysts often use different conceptual definitions of a cohort effect, and therefore different statistical methods, which lead to differing empirical results. A definition often used in sociology assumes that cohorts have unique characteristics confounded by age and period effects, whereas epidemiologists often conceive that period and age effects interact to produce cohort effects. The present study aims to illustrate these differences by estimating age, period, and cohort (APC) effects on obesity prevalence in the U.S. from 1971 to 2006 using both conceptual approaches. Data were drawn from seven cross-sectional waves of the National Health and Nutrition Examination Survey. Obesity was defined as BMI >or=30 for adults and >or=95th percentile for children under the age of 20. APC effects were estimated using the classic constraint-based method (first-order effects estimated and interpreted), the Holford method (first-order effects estimated but second-order effects interpreted), and median polish method (second-order effects are estimated and interpreted). Results indicated that all methods report significant age and period effects, with lower obesity prevalence in early life as well as increasing prevalence in successive surveys. Positive cohort effects for more recently born cohorts emerged based on the constraint-based model; when cohort effects were considered second-order estimates, no significant effects emerged. First-order estimates of age-period-cohort effects are often criticized because of their reliance on arbitrary constraints, but may be conceptually meaningful for sociological research questions. Second-order estimates are statistically estimable and produce conceptually meaningful results for epidemiological research questions. Age-period-cohort analysts should explicitly state the definition of a cohort effect under consideration. Our analyses suggest that the prevalence of obesity in the U.S. in the latter part of the 20th century rose across all birth cohorts, in the manner expected based on estimated age and period effects. As such, the absence or presence of cohort effects depends on the conceptual definition and therefore statistical method used.

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Authors
Keyes, K. M., Utz, R. L., Robinson, W., & Li, G.
Affiliations
  • Columbia University (US)
  • University of Utah (US)
  • University of Michigan (US)
Corresponding author
Keyes, Katherine M.
Venue
Social Science & Medicine
Publisher
Elsevier BV
Published
2010-04
Volume
70
Issue
7
Pages
1100-1108
ISSN
0277-9536 (ISSN-L)
OpenAlex
W2111534358
Cited by
292
References
1
Citations by year
2026: 20 · 2025: 17 · 2024: 20 · 2023: 19 · 2022: 23 · 2021: 20 · 2020: 27 · 2019: 25 · 2018: 13 · 2017: 16 · 2016: 21 · 2015: 16 · 2014: 18 · 2013: 15 · 2012: 7
FWCI
9.61
Type
journal article
Language
en
Open access
Locations
  • Social Science & Medicine (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
  • National Institutes of Health (2r24hd050924-06, 1f31da026689-01)
  • National Institute on Alcohol Abuse and Alcoholism (R01AA009963)
  • National Institute on Aging (R01AG013642)
  • National Institute of Mental Health (T32MH013043)
  • National Institute on Drug Abuse (F31-DA026689)
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development (R24 HD-050924)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
  • Social Sciences › Demography › Insurance, Mortality, Demography, Risk Management
Keywords
cohort effects, age-period-cohort analysis, obesity prevalence, age effects, period effects, constraint-based modeling, median polish, second-order effects, birth cohort, childhood obesity, NHANES
MeSH terms
Adolescent, Adult, Age Factors, Aged, Child, Child, Preschool, Cross-Sectional Studies, Epidemiologic Methods, Humans, Middle Aged, Obesity, Risk Factors, United States, Models, Statistical, Cohort Studies, Cohort Effect, Body Mass Index, Young Adult

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