Nicole M Niehoff1, Alexander P Keil2, Katie M O'Brien3, Brian P Jackson4, Margaret R Karagas5, Clarice R Weinberg6, Alexandra J White3. 1. Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA. Electronic address: nicole.niehoff@nih.gov. 2. Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA; Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA. 3. Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA. 4. Department of Earth Sciences, Dartmouth College, Hanover, NH, USA. 5. Department of Epidemiology and Children's Environmental Health and Disease Prevention Research Center at Dartmouth, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA. 6. Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA.
Abstract
BACKGROUND: Epidemiologic studies on the association between metals and body mass index (BMI) have been cross-sectional and have demonstrated inconsistent associations. Our study prospectively examined whether metals measured at baseline were associated with later BMI. We considered metals individually and as joint exposure to pre-defined metal groupings. METHODS: We measured concentrations of 16 metals in toenails collected at baseline (2003-2009) in a subset of 1221 women from the Sister Study. We calculated BMI from height and weight reported on a follow-up questionnaire an average of 5.2 years (range = 3.5-8.3) after baseline. Multivariable linear regression was used to estimate β coefficients and 95% confidence intervals (CIs) for associations between BMI and individual metals (with estimates given per interquartile range (IQR) increase or in quartiles). Quantile g-computation was used to examine joint associations between groups of metals and BMI. Groups considered were (1) all metals combined, and metals classified as (2) non-essential or (3) essential. RESULTS: In individual metal models we found that, with the exception of cobalt, no single metal was strongly related to BMI. In our mixture analyses, a quartile increase in all non-essential metals was associated with higher BMI (β = 0.32; 95%CI: 0.00, 0.63 kg/m2), whereas essential metals were suggestively associated with lower BMI (β = -0.25; 95%CI: 0.58, 0.07 kg/m2). CONCLUSIONS: In this population of women who were, on average, overweight, essential metals were jointly associated with slightly healthier, lower BMI whereas non-essential metals were jointly associated with slightly higher, unhealthier BMI, after controlling for other health indicators and predictors of metals exposures.
BACKGROUND: Epidemiologic studies on the association between metals and body mass index (BMI) have been cross-sectional and have demonstrated inconsistent associations. Our study prospectively examined whether metals measured at baseline were associated with later BMI. We considered metals individually and as joint exposure to pre-defined metal groupings. METHODS: We measured concentrations of 16 metals in toenails collected at baseline (2003-2009) in a subset of 1221 women from the Sister Study. We calculated BMI from height and weight reported on a follow-up questionnaire an average of 5.2 years (range = 3.5-8.3) after baseline. Multivariable linear regression was used to estimate β coefficients and 95% confidence intervals (CIs) for associations between BMI and individual metals (with estimates given per interquartile range (IQR) increase or in quartiles). Quantile g-computation was used to examine joint associations between groups of metals and BMI. Groups considered were (1) all metals combined, and metals classified as (2) non-essential or (3) essential. RESULTS: In individual metal models we found that, with the exception of cobalt, no single metal was strongly related to BMI. In our mixture analyses, a quartile increase in all non-essential metals was associated with higher BMI (β = 0.32; 95%CI: 0.00, 0.63 kg/m2), whereas essential metals were suggestively associated with lower BMI (β = -0.25; 95%CI: 0.58, 0.07 kg/m2). CONCLUSIONS: In this population of women who were, on average, overweight, essential metals were jointly associated with slightly healthier, lower BMI whereas non-essential metals were jointly associated with slightly higher, unhealthier BMI, after controlling for other health indicators and predictors of metals exposures.
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