A novel evolutionary-concordance lifestyle score is inversely associated with all-cause, all-cancer, and all-cardiovascular disease mortality risk.

PURPOSE: Evolutionary discordance may contribute to the high burden of chronic disease-related mortality in modern industrialized nations. We aimed to investigate the associations of a 7-component, equal-weight, evolutionary-concordance lifestyle (ECL) score with all-cause and cause-specific mortality. METHODS: Baseline data were collected in 2003-2007 from 17,465 United States participants in the prospective REasons for Geographic and Racial Differences in Stroke (REGARDS) study. The ECL score's components were: a previously reported evolutionary-concordance diet score, alcohol intake, physical activity, sedentary behavior, waist circumference, smoking history, and social network size. Diet was assessed using a Block 98 food frequency questionnaire and anthropometrics by trained personnel; other information was self-reported. Higher scores indicated higher evolutionary concordance. We used multivariable Cox proportional hazards regression models to estimate ECL score-mortality associations. RESULTS: Over a median follow-up of 10.3 years, 3771 deaths occurred (1177 from cardiovascular disease [CVD], 1002 from cancer). The multivariable-adjusted hazard ratios (HR) (95% confidence intervals [CI]) for those in the highest relative to the lowest ECL score quintiles for all-cause, all-CVD, and all-cancer mortality were, respectively, 0.45 (0.40, 0.50), 0.47 (0.39, 0.58), and 0.42 (0.34, 0.52) (all P trend < 0.01). Removing smoking and diet from the ECL score attenuated the estimated ECL score-all-cause mortality association the most, yielding fifth quintile HRs (95% CIs) of 0.56 (0.50, 0.62) and 0.50 (0.46, 0.55), respectively. CONCLUSIONS: Our findings suggest that a more evolutionary-concordant lifestyle may be inversely associated with all-cause, all-CVD, and all-cancer mortality. Smoking and diet appeared to have the greatest impact on the ECL-mortality associations.

Duke Scholars

Author Tomi Akinyemiju Population Health Sciences