Associations between a body shape index and cardiometabolic risk markers: age- and sex-specific patterns in a Brazilian population

Background/Introduction Visceral adiposity is a major determinant of cardiometabolic risk; however, conventional anthropometric measures such as Body Mass Index may inadequately capture age- and sex-related differences in fat distribution. A Body Shape Index has been proposed as an alternative anthropometric indicator that more accurately reflects abdominal adiposity. Calculated from waist circumference, height, and weight, A Body Shape Index was developed to overcome the limitations of traditional measures by better capturing abdominal fat distribution. Purpose This study aims to characterize sex- and age-specific patterns of A Body Shape Index and to assess its independent associations with cardiometabolic risk markers, beyond Body Mass Index, among Brazilian adults. Methods This cross-sectional study included 1,248 adults participating in the Brazilian National Health Survey. Participants were stratified by sex and age groups (<45, 45–59, and ≥60 years). Anthropometric measurements, blood pressure, fasting plasma glucose, and lipid profile were assessed using standardised procedures. Group comparisons were conducted using parametric or non-parametric tests, as appropriate. Multivariable linear and logistic regression analyses were performed to examine associations between A Body Shape Index and cardiometabolic outcomes, adjusting for Body Mass Index and lifestyle-related covariates. Results A Body Shape Index increased progressively across age groups in both sexes (p <0.001), with a more pronounced increase observed in women after midlife. Among participants aged <45 years, values did not differ between sexes, whereas women aged ≥60 years exhibited higher values than men of the same age (0.085 vs. 0.082, p=0.02). Higher A Body Shape Index was independently associated with increased odds of hypertension (odds ratio 1.38; 95% confidence interval 1.16–1.64) and dyslipidaemia (odds ratio 1.29; 95% confidence interval 1.08–1.54) after adjustment for Body Mass Index. In contrast, Body Mass Index showed stronger associations with hypertriglyceridaemia and low high-density lipoprotein cholesterol. A Body Shape Index was not independently associated with fasting plasma glucose in fully adjusted models. Conclusion(s) In a nationally representative sample of Brazilian adults, A Body Shape Index captured age- and sex-related differences in body fat distribution that were not reflected by Body Mass Index and was independently associated with blood pressure and lipid abnormalities. These findings indicate that A Body Shape Index may complement traditional anthropometric measures for cardiometabolic risk assessment, particularly in older populations.