Regression modeling plan for twenty-nine biochemical indicators of diet and nutrition measured in NHANES 2003–2006

摘要

The collection of papers in this journal supplement provides insight into the association of various covariates with concentrations of biochemical indicators of diet and nutrition (biomarkers), beyond age, race and sex using linear regression. We studied 10 specific sociodemographic and lifestyle covariates in combination with 29 biomarkers from NHANES 2003–2006 for persons ≥20 y. The covariates were organized into 2 chunks, sociodemographic (age, sex, race-ethnicity, education, and income) and lifestyle (dietary supplement use, smoking, alcohol consumption, BMI, and physical activity) and fit in hierarchical fashion using each chunk or set of related variables to determine how covariates, jointly, are related to biomarker concentrations. In contrast to many regression modeling applications, all variables were retained in a full regression model regardless of statistical significance to preserve the interpretation of the statistical properties of beta coefficients, P-values and CI, and to keep the interpretation consistent across a set of biomarkers. The variables were pre-selected prior to data analysis and the data analysis plan was designed at the outset to minimize the reporting of false positive findings by limiting the amount of preliminary hypothesis testing. While we generally found that demographic differences seen in biomarkers were over- or under-estimated when ignoring other key covariates, the demographic differences generally remained statistically significant after adjusting for sociodemographic and lifestyle variables. These papers are intended to provide a foundation to researchers to help them generate hypotheses for future studies or data analyses and/or develop predictive regression models using the wealth of NHANES data.