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Despite the impact of the COVID‑19 pandemic, myocardial infarction remains the leading cause of cardiovascular deaths in Europe. Body mass index (BMI)-defined obesity is a major risk factor for myocardial infarction. However, in the association of anthropometrics and myocardial infarction, the lack of balance between the simple body measurements when comparing healthy and unhealthy cases has demonstrated that affects the outcome. Thus, regardless of association strength of anthropometrics, other criteria to judge the biological causality must be investigated.
We aim to assess different studies worldwide to understand the key concepts to demonstrate association biases for anthropometrics when predicting myocardial infarction risk. In this approach, natural mathematical inequalities between simple measurements in healthy subjects were investigated. Weight, height, height/2, waist circumference and hip circumference mathematically represent absolute values that do not express mathematically equality for the true risk. That way, the mathematical concept of fraction or ratio in anthropometrics such as BMI, waist-to-hip ratio (WHR) or waist-to-height ratio (WHtR) plays an important role. Thus, some anthropometrics may be seen as confounding variables when measuring high-risk body composition. Weight is a confounding factor without indicating a high-risk body composition, meaning that BMI is not fully predictive. WHR is a confounding variable concerning waist and WHtR due to imbalances between the mean hip–waist and hip–height, respectively, which indicates a protective overestimation for hip concerning waist and height. Waist measure may be a confounding variable concerning WHtR due to an imbalance in the mean waist–height. This occurs if, and only if, WHtR risk cut-off is >0.5 and if height is ignored as volume factor, therefore creating an overestimation of risk for waist circumference in the tallest people and underestimation in the shortest. Mathematically/anthropometrically, only WHtR-associated risk above BMI, waist and WHR holds true while considering it as a relative risk volume linked to a causal pathway of higher cardiometabolic risk.
In conclusion, WHtR is the only metric that is directly associated to a risk volume and having more biological plausibility. It should be used to assess the anthropometrically-measured myocardial infarction risk, once the imbalances between measurements and association biases are recognised.
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