Why the study?
Do body mass index and waist circumference correlate with local gray matter volumes in healthy adults?
Do body mass index and waist circumference correlate with local gray matter volumes in healthy adults?
Waist circumference may be a more sensitive indicator than BMI for determining the potential adverse effects of obesity on brain gray matter volume, especially in women.
Waist circumference may better mark obesity-related gray matter reductions than BMI in women; leaves open causality and clinical relevance pending longitudinal data.
Obesity and overweight are often defined by the body mass index (BMI), which associates with metabolic and cardiovascular disease, and possibly with dementia as well as variations in brain volume. However, body fat distribution and abdominal obesity (as measured by waist circumference) is more strongly correlated with cardiovascular and metabolic risk than is BMI. While prior studies have revealed negative associations between gray matter tissue volumes and BMI, the relationship with respect to waist circumference remains largely unexplored. We therefore investigated the effects of both BMI and waist circumference on local gray matter volumes in a group of 115 healthy subjects screened to exclude physical or mental disorders that might affect the central nervous system. Results revealed significant negative correlations for both BMI and waist circumference where regional gray matter effects were largest within the hypothalamus and further encompassed prefrontal, anterior temporal and inferior parietal cortices, and the cerebellum. However, associations were more widespread and pronounced for waist circumference than BMI. Follow-up analyses showed that these relationships differed significantly across gender. While associations were similar for both BMI and waist circumference for males, females showed more extensive correlations for waist circumference. Our observations suggest that waist circumference is a more sensitive indicator than BMI, particularly in females, for potentially determining the adverse effects of obesity and overweight on the brain and associated risks to health.
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Kurth et al. (2012) studied this question.
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