Gerard Ngueta1, Elhadji A Laouan-Sidi1, Michel Lucas2. 1. Population Health and Optimal Health Practices Research Unit, CHU de Québec Research Centre, Québec, Québec, Canada. 2. Population Health and Optimal Health Practices Research Unit, CHU de Québec Research Centre, Québec, Québec, Canada Department of Social and Preventive Medicine, Faculty of Medicine, Laval University, Québec, Québec, Canada.
Abstract
BACKGROUND: Estimation of relative contribution of Body Mass Index (BMI) and waist circumference (WC) on health outcomes requires a regression model that includes both obesity metrics. But, multicollinearity could yield biased estimates. METHODS: To address the multicollinearity issue between BMI and WC, we used the residual model approach. The standard WC (Y-axis) was regressed on the BMI (X-axis) to obtain residual WC. Data from two adult population surveys (Nunavik Inuit and James Bay Cree) were analysed to evaluate relative effect of BMI and WC on four cardiometabolic risk factors: insulin, triglycerides, systolic blood pressure and high-density lipoprotein levels. RESULTS: In multivariate models, standard WC and BMI were significantly associated with cardiometabolic outcomes. Residual WC was not linked with any outcomes. The BMI effect was weakened by including standard WC in the model, but its effect remained unchanged if residual WC was considered. CONCLUSIONS: The strong correlation between standard WC and BMI does not allow assessment of their relative contributions to health in the same model without a risk of making erroneous estimations. By contrast with BMI, fat distribution (residual WC) does not add valuable information to a model that already contains overall adiposity (BMI) in Inuit and Cree. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
BACKGROUND: Estimation of relative contribution of Body Mass Index (BMI) and waist circumference (WC) on health outcomes requires a regression model that includes both obesity metrics. But, multicollinearity could yield biased estimates. METHODS: To address the multicollinearity issue between BMI and WC, we used the residual model approach. The standard WC (Y-axis) was regressed on the BMI (X-axis) to obtain residual WC. Data from two adult population surveys (Nunavik Inuit and James Bay Cree) were analysed to evaluate relative effect of BMI and WC on four cardiometabolic risk factors: insulin, triglycerides, systolic blood pressure and high-density lipoprotein levels. RESULTS: In multivariate models, standard WC and BMI were significantly associated with cardiometabolic outcomes. Residual WC was not linked with any outcomes. The BMI effect was weakened by including standard WC in the model, but its effect remained unchanged if residual WC was considered. CONCLUSIONS: The strong correlation between standard WC and BMI does not allow assessment of their relative contributions to health in the same model without a risk of making erroneous estimations. By contrast with BMI, fat distribution (residual WC) does not add valuable information to a model that already contains overall adiposity (BMI) in Inuit and Cree. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
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