Clarifying assumptions in age-period-cohort analyses and validating results. 2020

Ryan Masters, and Daniel Powers
University of Colorado Boulder, Boulder, CO, United States of America.

Age-period-cohort (APC) models are often used to decompose health trends into period- and cohort-based sources, but their use in epidemiology and population sciences remains contentious. Central to the contention are researchers' failures to 1) clearly state their analytic assumptions and/or 2) thoroughly evaluate model results. These failures often produce varying conclusions across APC studies and generate confusion about APC methods. Consequently, scholarly exchanges about APC methods usually result in strong disagreements that rarely offer practical advice to users or readers of APC methods. We use research guidelines to help practitioners of APC methods articulate their analytic assumptions and validate their results. To demonstrate the usefulness of the guidelines, we apply them to a 2015 American Journal of Epidemiology study about trends in black-white differences in U.S. heart disease mortality. The application of the guidelines highlights two important findings. On the one hand, some APC methods produce inconsistent results that are highly sensitive to researcher manipulation. On the other hand, other APC methods estimate results that are robust to researcher manipulation and consistent across APC models. The exercise shows the simplicity and effectiveness of the guidelines in resolving disagreements over APC results. The cautious use of APC models can generate results that are consistent across methods and robust to researcher manipulation. If followed, the guidelines can likely reduce the chance of publishing variable and conflicting results across APC studies.

UI MeSH Term Description Entries
D008297 Male Males
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D012107 Research Design A plan for collecting and utilizing data so that desired information can be obtained with sufficient precision or so that an hypothesis can be tested properly. Experimental Design,Data Adjustment,Data Reporting,Design, Experimental,Designs, Experimental,Error Sources,Experimental Designs,Matched Groups,Methodology, Research,Problem Formulation,Research Methodology,Research Proposal,Research Strategy,Research Technics,Research Techniques,Scoring Methods,Adjustment, Data,Adjustments, Data,Data Adjustments,Design, Research,Designs, Research,Error Source,Formulation, Problem,Formulations, Problem,Group, Matched,Groups, Matched,Matched Group,Method, Scoring,Methods, Scoring,Problem Formulations,Proposal, Research,Proposals, Research,Reporting, Data,Research Designs,Research Proposals,Research Strategies,Research Technic,Research Technique,Scoring Method,Source, Error,Sources, Error,Strategies, Research,Strategy, Research,Technic, Research,Technics, Research,Technique, Research,Techniques, Research
D001741 Black or African American A person having origins in any of the black racial groups of Africa (https://www.federalregister.gov/documents/1997/10/30/97-28653/revisions-to-the-standards-for-the classification-of-federal-data-on-race-and-ethnicity). In the United States it is used for classification of federal government data on race and ethnicity. Race and ethnicity terms are self-identified social construct and may include terms outdated and offensive in MeSH to assist users who are interested in retrieving comprehensive search results for studies such as in longitudinal studies. African American,African Americans,African-American,Afro-American,Afro-Americans,Black Americans,Blacks,Negroes,African-Americans,Negro,Afro American,Afro Americans,American, African,American, Black,Black American
D005260 Female Females
D006331 Heart Diseases Pathological conditions involving the HEART including its structural and functional abnormalities. Cardiac Disorders,Heart Disorders,Cardiac Diseases,Cardiac Disease,Cardiac Disorder,Heart Disease,Heart Disorder
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000076782 Race Factors A constituent element or influence that could be used in studies for racial disparities as variables such as those related to risk factors and disease and or differential access to services. Racial Factors,Race Factor,Racial Factor
D000328 Adult A person having attained full growth or maturity. Adults are of 19 through 44 years of age. For a person between 19 and 24 years of age, YOUNG ADULT is available. Adults
D000367 Age Factors Age as a constituent element or influence contributing to the production of a result. It may be applicable to the cause or the effect of a circumstance. It is used with human or animal concepts but should be differentiated from AGING, a physiological process, and TIME FACTORS which refers only to the passage of time. Age Reporting,Age Factor,Factor, Age,Factors, Age

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