Scientists have known for years that having more adipose tissue, or fat, around the middle of your body, in the abdominal cavity is a greater health risk than having fat in other parts of the body.<\/p>\n
\u201cThere is clear evidence that fat located in certain places, mainly in the visceral cavity, is really the fat that increases most of your metabolic risk,\u201d Earp says.<\/p>\n
Additionally, fat distribution looks different between different ethnic populations and between women and men. This fact influences which interventions work best for different groups.<\/p>\n
To generate their equations, Earp\u2019s team looked at data from 12,000 full-body DXA scans logged in the National Health Nutrition Examination Survey.<\/p>\n One significant finding was that Hispanic individuals are at a higher risk of poor fat distribution and its associated diseases.<\/p>\n Additionally, they found that men who are commonly classified as being either underweight or obese using BMI had unhealthier adipose tissue distribution than normally believed, and the opposite was true for women.<\/p>\n \u201cOn the high end, women still had higher abdominal fat in general because as that body mass index or waist circumference increases, abdominal adiposity increased, but we actually found that the distribution gets worse in men,\u201d Earp says. \u201cFor women, as they got to those higher levels of obesity, they were better able to distribute that fat in a healthier fashion.\u201d<\/p>\n Earp says he hopes these equations can serve as a tool for physicians and researchers who can input simple measurements of a patient\u2019s height, weight, and waist and hip circumference to get a sense of how that patient\u2019s fat is distributed based on their sex and ethnicity.<\/p>\n This will help physicians assess a patient\u2019s risk of obesity-related conditions more accurately than using BMI which may mislabel people and recommend inappropriate lifestyle interventions.<\/p>\n \u201cIt\u2019s our hope that these equations can be used to identify people who are misclassified based on BMI alone,\u201d Earp says.<\/p>\n For example, someone may have a high weight and be flagged as obese, but their weight is due to muscle and bone mass and their fat distribution is actually very healthy. By contrast, someone with a lower weight would not be labeled as at-risk but they may have high abdominal fat.<\/p>\n Earp\u2019s group is also working with recently obtained data from the UConn Center on Aging and the Pepper Center to study fat distribution within muscles. In this study they only looked at fat beneath the skin and stored in around the hips. But as people age, fat within muscle becomes a significant concern.<\/p>\n The next steps for this research are looking at how to adapt the equations to populations with chronic illnesses like diabetes and COPD which create atypical fat distribution.<\/p>\n \u201cWe know the obesity crisis is something we\u2019ll be facing for years to come. These tools help us better address a major health issue across a broad range of Americans,\u201d says Earp.<\/p>\n \u00a0<\/em><\/p>\n This work relates to CAHNR\u2019s Strategic Vision area focused on\u00a0Enhancing Health and Promoting Diversity, Equity, Inclusion and Justice.<\/a><\/em><\/p>\n![\"Men](\"https:\/\/today.uconn.edu\/wp-content\/uploads\/2023\/03\/DEXA-image-300x200.jpg\")