Control beliefs and risk for 4-year mortality in older adults: a prospective cohort study

Abstract Background Control beliefs are important psychological factors that likely contribute to heterogeneity in health outcomes for older adults. We evaluated whether control beliefs are associated with risk for 4-year mortality, after accounting for established \u201cclassic\u201d biomedical risk factors. We also determined if an enhanced risk model with control beliefs improved identification of individuals with low vs. high mortality risk. Methods We used nationally representative data from the Health and Retirement Study (2006\u20132012) for adults 50\ua0years or older in 2006 ( n \u2009=\u20097313) or 2008 ( n \u2009=\u20096301). We assessed baseline perceived global control (measured as 2 dimensions\u2014\u201cconstraints\u201d and \u201cmastery\u201d), and health-specific control. We also obtained baseline data for 12 established biomedical risk factors of 4-year mortality: age, sex, 4 medical conditions (diabetes mellitus, cancer, lung disease and heart failure), body mass index less than 25\ua0kg/m 2 , smoking, and 4 functional difficulties (with bathing, managing finances, walking several blocks and pushing or pulling heavy objects). Deaths within 4\ua0years of follow-up were determined through interviews with respondents\u2019 family and the National Death Index. Results After accounting for classic biomedical risk factors, perceived constraints were significantly associated with higher mortality risk (third quartile scores\ua0odds ratio [OR] 1.37, 95% CI 1.03\u20131.81; fourth quartile scores\ua0OR 1.45, 95% CI, 1.09\u20131.92), while health-specific control was significantly associated with lower risk (OR 0.69\u20130.78 for scores above first quartile). Higher perceived mastery scores were not consistently associated with decreased risk. The enhanced model with control beliefs found an additional 3.5% of participants ( n \u2009=\u2009222) with low predicted risk of 4-year mortality (i.e., 4% or less); observed mortality for these individuals was 1.8% during follow-up. Compared with participants predicted to have low mortality risk only by the classic biomedical model, individuals identified by only the enhanced model were older, had higher educational status, higher income, and higher prevalence of diabetes mellitus and cancer. Conclusion Control beliefs were significantly associated with risk for 4-year mortality; accounting for these factors improved identification of low-risk individuals. More work is needed to determine how assessment of control beliefs could enable targeting of clinical interventions to support at-risk older adults