Abstract
Among the components of Life’s Essential 8, body mass index is the anthropometric used in the scoring algorithm of cardiovascular health. Concerning myocardial infarction, the waist-to-hip ratio may show more predictive value than body mass index, waist circumference, and waist-to-height ratio, and has showed a greater excess risk of myocardial infarction in women than in men. However, bias has occurred in global research because of inadequate comparisons with the high-risk body composition. Hence, cardiology may have been confused for a long time because bias-related errors were always overlooked. This situation occurred when risk association was distorted by over- or under-estimating some simple measurements over others. Our aim was to determine whether the historical risk associated with some anthropometrics might provide a bias in causal inferences. Our study design was a review on data of the body of literature. We created new anthropometric variables, which were always omitted in previous large studies. In most studies, mathematical inequalities between the simple measurements in anthropometrically healthy subjects were overlooked, including disparities between lean and fat masses. That way, in omitting the difference in means between the simple measurements of length and body mass components, association findings and causality cannot be assumed. No anthropometric will be equivalent for estimating the same high-risk body composition if the difference in means between the simple measurements present an unbalanced distribution, and besides, being associated as confounding factors. Therefore, after describing new anthropometric variables termed as “x” and demonstrating that the simple measurements showed means of differences differentially distributed between healthy and unhealthy cases worldwide, association biases for the body mass index, waist-to-hip ratio or waist circumference alone may be endorsed, indicating the importance of these results. From a new anthropometric perspective, the waist-to-height ratio may indicate the concrete volume of an abdominal three-dimensional disc in direct-inverse relationship with waist-body height without showing association biases. This index may represent a new construct by defining a risk abdominal volume and avoiding potential confounding factors. In a paradigm shift, only the waist-to-height ratio meets causality criteria as the optimal index to predict myocardial infarction risk and to promote cardiovascular health.