Systematic evaluation of environmental and behavioural factors associated with all-cause mortality in the United States National Health and Nutrition Examination Survey

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Environmental and behavioural factors are thought to contribute to all-cause mortality. Here, we develop a method to systematically screen and validate the potential independent contributions to all-cause mortality of 249 environmental and behavioural factors in the National Health and Nutrition Examination Survey (NHANES). We used Cox proportional hazards regression to associate 249 factors with all-cause mortality while adjusting for sociodemographic factors on data in the 1999-2000 and 2001-02 surveys (median 5.5 follow-up years). We controlled for multiple comparisons with the false discovery rate (FDR) and validated significant findings in the 2003-04 survey (median 2.8 follow-up years). We selected 249 factors from a set of all possible factors based on their presence in both the 1999-2002 and 2003-04 surveys and linkage with at least 20 deceased participants. We evaluated the correlation pattern of validated factors and built a multivariable model to identify their independent contribution to mortality. We identified seven environmental and behavioural factors associated with all-cause mortality, including serum and urinary cadmium, serum lycopene levels, smoking (3-level factor) and physical activity. In a multivariable model, only physical activity, past smoking, smoking in participant's home and lycopene were independently associated with mortality. These three factors explained 2.1% of the variance of all-cause mortality after adjusting for demographic and socio-economic factors. Our association study suggests that, of the set of 249 factors in NHANES, physical activity, smoking, serum lycopene and serum/urinary cadmium are associated with all-cause mortality as identified in previous studies and after controlling for multiple hypotheses and validation in an independent survey. Whereas other NHANES factors may be associated with mortality, they may require larger cohorts with longer time of follow-up to detect. It is possible to use a systematic association study to prioritize risk factors for further investigation.