Does waist circumference uncorrelated with BMI add valuable information?

Area of Science:

• Obesity research
• Cardiometabolic health
• Population health surveys

Background:

• Accurate estimation of health outcomes requires regression models including both Body Mass Index (BMI) and waist circumference (WC).
• Multicollinearity between BMI and WC can lead to biased regression estimates.
• Addressing multicollinearity is crucial for reliable obesity metric analysis.

Purpose of the Study:

• To evaluate the relative contributions of BMI and WC to cardiometabolic risk factors.
• To investigate the utility of a residual model approach for addressing multicollinearity between BMI and WC.
• To assess the independent effects of overall adiposity (BMI) and fat distribution (residual WC) on health outcomes.

Main Methods:

• Employed a residual model approach to mitigate multicollinearity between BMI and WC.
• Regressed standard WC on BMI to derive residual WC.
• Analyzed data from Nunavik Inuit and James vVertex Cree population surveys, examining associations with insulin, triglycerides, systolic blood pressure, and HDL levels.

Main Results:

• Both standard WC and BMI showed significant associations with cardiometabolic outcomes in multivariate models.
• Residual WC was not significantly associated with any of the cardiometabolic risk factors.
• Including standard WC attenuated the effect of BMI, whereas including residual WC did not alter the BMI effect.

Conclusions:

• The high correlation between standard WC and BMI hinders the assessment of their independent contributions to health outcomes due to potential estimation errors.
• In Inuit and Cree populations, fat distribution (residual WC) provides no additional valuable information for cardiometabolic risk models that already include overall adiposity (BMI).
• The residual model approach may not be effective in disentangling the effects of highly correlated obesity measures.