The Contribution of Body Mass Index in the Shared Etiology of Diabetes, Hypertension and Hyperlipidaemia: A Semi-Parametric Trivariate Probit Modeling Approach

Diabetes, hypertension, and hyperlipidaemia are three medical conditions usually linked to high body fat content. The Body Mass Index (BMI), calculated by dividing a person’s weight in kilograms by the square of their height in meters, is the most commonly used measure for monitoring the prevalence of excess body fat content. Past studies linking BMI to the prevalence of diabetes, hypertension and hyperlipidaemia have looked at the effects in isolation, hence assuming independence in their occurrences. This study takes a different approach, considering the potential interconnectedness of these three metabolic diseases, to model the effect of BMI on their joint likelihood for respondents in the 2008 Medical Expenditure Panel Survey (MEPS) dataset. For this, we specify and estimate a standard univariate probit model, then we move to a fully parametric trivariate probit specification to relax the independence assumption, followed by a semi-parametric trivariate probit specification to further relax the linearity assumption for the parametrically entering numerical risks factors (covariates) in each of the three equations for diabetes, hypertension, and hyperlipidaemia. The results suggest that the semi-parametric trivariate probit specification is better at capturing the true effects of BMI on the likelihood of these three metabolic diseases in a population. In fact the statistically significant correlation coefficients 0.278, 0.362, and 0.356 between the diabetes, hypertension and hyperlipidaemia equations suggest their joint positive dependence. Furthermore, BMI contributes significantly more to hypertension (5%), followed by diabetes (4.4%), and hyperlipidaemia (2.7%).

Author(s): Ibrahim Niankara and Aminata Niankara

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