Performance of Body Fat Percentage, Fat Mass Index and Body Mass Index for Detecting Cardiometabolic Outcomes in Brazilian Adults

Abstract

Obesity is a recognized risk factor for the development of cardiometabolic outcomes. Therefore, it is essential to evaluate anthropometric and body composition indicators used for its diagnosis. This study aimed to assess the diagnostic performance of body fat percentage (BF%), fat mass index (FMI) and body mass index (BMI) for detecting cardiometabolic outcomes in adults. A cross-sectional study was conducted involving adults at 30 years of age from Pelotas, RS (n = 3517) and at 37–39 years from Ribeirão Preto, SP (n = 1696). Receiver operating characteristic (ROC) curves were used to determine the cut-off points for predicting cardiometabolic risk factors, including altered blood pressure, blood glucose, triglycerides, total cholesterol, low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDDL-c), C-reactive protein and glycated hemoglobin. The cut-off points of BF% ranged from 25.2 to 27.8 in men and from 37.4 to 39.7 in women at 30 years, and from 26.1 to 27.8 in men and from 38.5 to 42.2 in women at 37–39 years. For FMI (kg/m2), the cut-off points ranged from 6.3 to 7.5 in men and from 9.5 to 10.8 in women at 30 years, and from 7.3 to 7.8 in men and from 10.2 to 12.2 in women at 37–39 years. The BMI cut-off points (kg/m2) ranged from 26.3 to 27.3 in men and from 25.4 to 27.2 in women at 30 years, and from 28.3 to 29.0 in men and from 27.2 to 29.6 in women at 37–39 years. The areas under the curve were similar for the three indicators, ranging from 0.523 to 0.746. BMI showed a performance similar to that of the body fat-based indicators in identifying cardiometabolic outcomes. The cut-off points of the three indicators showed acceptable discriminatory power in subjects with cardiometabolic risk factors.

Body Mass Index and Waist Circumference as Predictors of Above-Average Increased Cardiovascular Risk Assessed by the SCORE2 and SCORE2-OP Calculators and the Proposition of New Optimal Cut-Off Values: Cross-Sectional Single-Center Study

“…In both genders, BMI was found to have a slightly higher value compared to WC; WHR and WHtR, which were not examined in our study, were found to have significantly lower quality values [15]. In another study, researchers from Brazil examined the relationship between body fat percentage, fat mass index, and BMI in relation to predicting different cardiometabolic risk factors such as hypertension, elevated C-reactive protein levels, hyperglycemia, or dyslipidemia-the researchers discovered that specific BMI cut-off values were effective in identifying the presence of three or more of these risk factors (for men, the optimal BMI cut-off values ranged from 27.0 to 28.4 kg/m 2 , while for women, the range was 26.9-28.5 kg/m 2 , varying by region), and the diagnostic results obtained from these cut-off values were deemed satisfactory [16]. In their study, Głuszek et al determined that a BMI of 27.2 kg/m 2 is the threshold for diagnosing metabolic disorders, applicable to both males and females [17].…”

Surrogate indices of insulin resistance using the Matsuda index as reference in adult men—a computational approach

“…The Matsuda index, HOMA-IR, QUICKI, TyG index, TG/HDL-c, VAI, TyG-WC, BMI (kg/m 2 ), TyG-BMI, WHtR, TyG-WHtR, LAP, and LAR were calculated as described elsewhere ( 12 , 22 , 26 – 33 ). Formulas for surrogate indices are described in the Supplementary Materials .…”

Association of body composition indicators with colorectal cancer: a hospital-based case-control study

“…However, BMI does not specifically distinguish between fat tissue and muscle mass, nor does it distinguish between fat accumulation in different body parts (Rontogiann et al 2024 ). Obesity is an abnormal or excessive accumulation of body fat that may damage health (Oliveira et al 2023 ). It is also a kind of physiological dysfunction caused by environmental, genetic, and endocrine factors (Mármol et al 2017 ).…”