|Title||Predicting mortality from 57 economic, behavioral, social, and psychological factors|
|Publication Type||Journal Article|
|Year of Publication||2020|
|Authors||Puterman, E, Weiss, J, Hives, BA, Gemmill, A, Karasek, D, Mendes, WBerry, Rehkopf, D|
|Journal||Proceedings of the National Academy of Sciences|
|Keywords||Behavioral Symptoms, Mortality, social, transdisciplinary|
In our prospective study using nationally representative data from 13,611 adults in the US Health and Retirement Study, we used traditional and machine-learning statistical approaches to reveal the most important factors across the behavioral and social sciences that predict mortality in older adults. In the study, we found that top predictors of mortality spanned all investigated domains, opening up opportunities for future hypothesis generation in observational and clinical studies and the identification of potential new targets for screening and policy.Behavioral and social scientists have identified many nonbiological predictors of mortality. An important limitation of much of this research, however, is that risk factors are not studied in comparison with one another or from across different fields of research. It therefore remains unclear which factors should be prioritized for interventions and policy to reduce mortality risk. In the current investigation, we compare 57 factors within a multidisciplinary framework. These include (i) adverse socioeconomic and psychosocial experiences during childhood and (ii) socioeconomic conditions, (iii) health behaviors, (iv) social connections, (v) psychological characteristics, and (vi) adverse experiences during adulthood. The current prospective cohort investigation with 13,611 adults from 52 to 104 y of age (mean age 69.3 y) from the nationally representative Health and Retirement Study used weighted traditional (i.e., multivariate Cox regressions) and machine-learning (i.e., lasso, random forest analysis) statistical approaches to identify the leading predictors of mortality over 6 y of follow-up time. We demonstrate that, in addition to the well-established behavioral risk factors of smoking, alcohol abuse, and lack of physical activity, economic (e.g., recent financial difficulties, unemployment history), social (e.g., childhood adversity, divorce history), and psychological (e.g., negative affectivity) factors were also among the strongest predictors of mortality among older American adults. The strength of these predictors should be used to guide future transdisciplinary investigations and intervention studies across the fields of epidemiology, psychology, sociology, economics, and medicine to understand how changes in these factors alter individual mortality risk.