title: Should age-period-cohort studies return to the methodologies of the 1970s?
abstract: Social scientists have recognized the importance of age-period-cohort (APC) models for half a century, but have spent much of this time mired in debates about the feasibility of APC methods. Recently, a new class of APC methods based on modern statistical knowledge has emerged, offering potential solutions. In 2009, Reither, Hauser and Yang used one of these new methods - hierarchical APC (HAPC) modeling - to study how birth cohorts may have contributed to the U.S. obesity epidemic. They found that recent birth cohorts experience higher odds of obesity than their predecessors, but that ubiquitous period-based changes are primarily responsible for the rising prevalence of obesity. Although these findings have been replicated elsewhere, recent commentaries by Bell and Jones call them into question - along with the new class of APC methods. Specifically, Bell and Jones claim that new APC methods do not adequately address model identification and suggest that "solid theory" is often sufficient to remove one of the three temporal dimensions from empirical consideration. They also present a series of simulation models that purportedly show how the HAPC models estimated by Reither et al. (2009) could have produced misleading results. However, these simulation models rest on assumptions that there were no period effects, and associations between period and cohort variables and the outcome were perfectly linear. Those are conditions under which APC models should never be used. Under more tenable assumptions, our own simulations show that HAPC methods perform well, both in recovering the main findings presented by Reither et al. (2009) and the results reported by Bell and Jones. We also respond to critiques about model identification and theoretically-imposed constraints, finding little pragmatic support for such arguments. We conclude by encouraging social scientists to move beyond the debates of the 1970s and toward a deeper appreciation for modern APC methodologies.
authors.affiliation: Department of Sociology and the Yun Kim Population Research Laboratory, Utah State University, 0730 Old Main Hill, Logan, UT 84322-0730, USA. Electronic address: eric.reither@usu.edu.
authors.forename: Eric N
authors.initials: EN
authors.lastname: Reither
authors.affiliation: Department of Sociology and Institute of Behavioral Science, University of Colorado at Boulder, USA.
authors.forename: Ryan K
authors.initials: RK
authors.lastname: Masters
authors.affiliation: Department of Sociology and the Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, USA.
authors.forename: Yang Claire
authors.initials: YC
authors.lastname: Yang
authors.affiliation: Department of Sociology, Population Research Center, The University of Texas at Austin, USA.
authors.forename: Daniel A
authors.initials: DA
authors.lastname: Powers
authors.affiliation: Department of Sociology, The Ohio State University, USA.
authors.forename: Hui
authors.initials: H
authors.lastname: Zheng
authors.affiliation: Department of Sociology and Center for Population Health and Aging, Duke University, USA.
authors.forename: Kenneth C
authors.initials: KC
authors.lastname: Land
mesh_terms: D015988:Cohort Effect; D005260:Female; D054624:Health Status Disparities; D006801:Humans; D008297:Male; D015233:Models, Statistical; D009765:Obesity / Q000453:epidemiology*; D012107:Research Design; D012922:Social Change
keywords: Age-period-cohort models; Body mass index; Cohort effects; Hierarchical modeling; Obesity epidemic; Random effects; Research methods; Social change