Dietary Supplement Use and Smoking Are Important Correlates of Biomarkers of Water-Soluble Vitamin Status after Adjusting for Sociodemographic and Lifestyle Variables in a Representative Sample of U.S. Adults

• DOI: 10.3945/jn.112.173021
• Publication Date: 2013-04-11T03:30:32Z
• Authors: Christine M. Pfei...; Maya R. Sternberg; Rosemary L. Schle...; Michael E. Rybak
• Keywords: Adult; Male; 0301 basic medicine; Alcohol Drinking; Nutritional Status; Body Mass Index; 03 medical and health sciences; Sex Factors; Ethnicity; Humans; Exercise; Life Style; 2. Zero hunger; Smoking; Age Factors; Middle Aged; Nutrition Surveys; 3. Good health; Socioeconomic Factors; Solubility; Dietary Supplements; Educational Status; Female; Biomarkers

Biochemical indicators of water-soluble vitamin (WSV) status were measured in a nationally representative sample of the U.S. population in NHANES 2003-2006. To examine whether demographic differentials in nutritional status were related to and confounded by certain variables, we assessed the association of sociodemographic (age, sex, race-ethnicity, education, income) and lifestyle (dietary supplement use, smoking, alcohol consumption, BMI, physical activity) variables with biomarkers of WSV status in adults (aged ≥ 20 y): serum and RBC folate, serum pyridoxal-5'-phosphate (PLP), serum 4-pyridoxic acid, serum total cobalamin (vitamin B-12), plasma total homocysteine (tHcy), plasma methylmalonic acid (MMA), and serum ascorbic acid. Age (except for PLP) and smoking (except for MMA) were generally the strongest significant correlates of these biomarkers (|r| ≤ 0.43) and together with supplement use explained more of the variability compared with the other covariates in bivariate analysis. In multiple regression models, sociodemographic and lifestyle variables together explained from 7 (vitamin B-12) to 29% (tHcy) of the biomarker variability. We observed significant associations for most biomarkers (≥ 6 of 8) with age, sex, race-ethnicity, supplement use, smoking, and BMI and for some biomarkers with PIR (5 of 8), education (1 of 8), alcohol consumption (4 of 8), and physical activity (5 of 8). We noted large estimated percentage changes in biomarker concentrations between race-ethnic groups (from -24 to 20%), between supplement users and nonusers (from -12 to 104%), and between smokers and nonsmokers (from -28 to 8%). In summary, age, sex, and race-ethnic differentials in biomarker concentrations remained significant after adjusting for sociodemographic and lifestyle variables. Supplement use and smoking were important correlates of biomarkers of WSV status.