Angel Martin Castellanos*

Sports Medicine Center, Caceres and Member of the Research Group in Bio-Anthropology and Cardiovascular Sciences, Department of Anatomy, University of Extremadura, Faculty of Nursing and Occupational Therapy, Caceres, Spain

*Corresponding Author: Angel Martin Castellanos, Sports Medicine Center, Caceres and Member of the Research Group in Bio-Anthropology and Cardiovascular Sciences, Department of Anatomy, University of Extremadura, Faculty of Nursing and Occupational Therapy, Caceres, Spain.

Received: June 05, 2023; Published: June 20, 2023

Abstract

Elevated body mass index (BMI) and waist-to-hip ratio (WHR) are associated with increased health risks. However, both of these obesity metrics may present causal association biases when assessing different individuals with identical risk values for each anthropometric. Thus, an accurate interpretation of the body composition as well as body fat excess or musculoskeletal mass deficit is important before inferring any causal risk. Hence, although higher BMI and WHR may be associated with health outcomes, they might not be appropriate for causal inference due to different origins in the bodily components contributing to them (i.e., fat mass [FM] and fat-free mass [FFM] within BMI, and waist and hip circumferences within WHR).

Biologically, each body measurement and ratio between two measurements present a different relationship with the risk. Thus, two conflicting factors as being the numerator and denominator of an abstract fraction (e.g., FM vs. FFM and waist vs. hip) may generate over- or under-estimates of the overall risk if the mentioned factors are differentially distributed between groups being compared. That way, if the absolute differences between mean FM and FFM, or between mean waist circumference and hip, are not balanced when comparing healthy with unhealthy cases, false outcomes may be generated. This approach considers the absolute difference between two means (e.g., mean FFM minus FM) as a new variable or modulus |x|. Thus, any difference in means of non-zero (i.e., mean |x|>0) means that you are comparing for diferent “x” values between groups, and therefore, assessing for a different body composition.

After investigating, in most population studies, an unbalanced distribution for the corresponding mean differences of the |x| values may be demonstrated, irrespective of any anthropometrically or technologically-measured body composition. Thus, causal association biases occurred worldwide when using BMI-or WHR- cut-offs without taking into account the modulus |x| as potential confounding factor, and therefore, accepting a protective overestimate of FFM and hip with respect to FM and waist, respectively. It may be demonstrated mathematically and in the Cartesian space that any mean FM-to-FFM ratio <1 and WHR <1 may never represent the overall risk.

We recommend that the historical paradigm in predicting health risks from BMI and WHR should be shifted.

 Keywords: Body Mass Index; Waist-to-Hip Ratio; Cardiovascular Disease; Anthropometrics; Health Risk; Bias

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Citation

Citation: Angel Martin Castellanos. “Why Predicting Health Risks from Either Body Mass Index or Waist-to-Hip Ratio Presents Causal Association Biases Worldwide: A Mathematical Demonstration”.Acta Scientific Medical Sciences 7.7 (2023): 112-120.

Copyright

Copyright: © 2023 Angel Martin Castellanos. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.