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Alcohol-Induced Death in the USA from 1999 to 2020: a Comparison of Age–Period–Cohort Methods

Abstract

Purpose of this review

Alcohol-induced mortality has been increasing in the USA for over a decade, but whether increases are specific to particular birth cohorts remains inadequately understood, in part because estimating age–period–cohort (APC) models is methodologically controversial. The present study compares four different age–period–cohort models for alcohol-induced death in the USA from 1999 to 2020.

Recent findings

We utilized US vital statistics data from 1999 to 2020; alcohol-induced deaths included those fully attributable to alcohol excluding poisoning. Age–period–cohort models included first derivatives, intrinsic estimator (IE), hierarchical APC, and Bayesian estimation. APC models were convergent in demonstrating that alcohol-induced death peak between age 45 and 60 in the USA. Models were also convergent in demonstrating a positive period effect, with deaths increasing across age groups particularly since 2010–2012. Models were divergent, however, in the presence and magnitude of cohort effects. The first derivative approach demonstrated that the peak positive cohort effect was for individuals born in the 1950s and peaking in the 1960s, which have higher risks of death across the lifecourse compared with other cohorts. This effect was less observable in other APC models. The IE model did not generate a cohort effect for those born in the 1950s–1960s, but did show a positive cohort effect for those born in the early to mid 1980s. Hierachical and Bayesian models also demonstrated a positive cohort effect for those born in the late 1970s and early 1980s, birth cohorts who are beginning to enter the peak age of risk for alcohol-related deaths.

Summary

Age–period–cohort models can provide useful quantitative framing in unpacking and understanding trends in alcohol-induced deaths, yet there are differences across methods in assumptions and modeling strategies, and thus some differences in results. First-derivative methods most closely approximated data visualizations and may provide the most robust statistical model of APC processes in alcohol-related death in the USA, especially given consistency with several other models. Comparison across methods is a critical strategy for triangulating evidence. Emerging evidence of a cohort effect for those born 1970s–1980s suggests an increased burden of alcohol-induced mortality as they enter the age band of highest risk in the next decade.

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Acknowledgements

The authors wish to thank Dr. Timothy Naimi for feedback on earlier versions of the manuscript.

Funding

Funding was provided by R01-AA026861 and 2U54GM104942.

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Correspondence to Katherine M. Keyes.

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K. Keyes, C. Rutherford, and G. Smith have been compensated for expert witness work in litigation.

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Appendix

Appendix

Table 2

Table 2 Model fit statistics for age–period–cohort model (first-derivative approach) for alcohol-induced death rates in the USA from 1999 to 2020

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Keyes, K.M., Rutherford, C. & Smith, G.S. Alcohol-Induced Death in the USA from 1999 to 2020: a Comparison of Age–Period–Cohort Methods. Curr Epidemiol Rep 9, 161–174 (2022). https://doi.org/10.1007/s40471-022-00300-0

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Keywords

  • Alcohol
  • Age-period-cohort
  • Alcohol-related death
  • Time trend
  • United States