The findings indicated that even high levels of muscle mass did not counteract the negative effects of excessive adiposity (fat tissue) on a person’s cardiometabolic health.
An analysis of muscle and fat mass data from a large sample population has revealed the limitations in accurately predicting cardiometabolic risks.
Researchers from Concordia University, who were investigating body phenotypes (observable traits such as height, behavior, appearance, and other measurable characteristics), discovered that regardless of their muscle mass, high levels of fat mass in an individual were associated with lower overall health.
The results of the study, published in the journal Preventive Medicine, were based on data from a long-term study in the United States. The findings revealed that high levels of muscle mass did not counteract the detrimental effects of excessive adiposity (fat tissue) on a person’s cardiometabolic health.
The researchers based their study on data from NHANES, a cross-sectional representative sample of the US population collected between 1999 and 2006. The data was collected using dual energy X-ray absorptiometry (DEXA), a diagnostic framework that analyzes adiposity and muscle mass. Based on which side of the 50th percentile they ranked, individuals were categorized into one of four proposed phenotypes: low-adiposity/high-muscle, high-adiposity/high-muscle, low-adiposity/high-muscle or low-adiposity/low-muscle.
The researchers looked at how the adiposity/muscle phenotypes related to lipid levels, including cholesterol and triglycerides, as well as blood sugar glucose and blood pressure. Results were also adjusted for age, sex, race, and education.
Sylvia Santosa, an associate professor in the Department of Health, Kinesiology, and Applied Physiology at Concordia University. Credit: Concordia University
“We wanted to see whether this proposed categorization was better than the traditional body-mass index (BMI) at predicting all these different cardiometabolic outcomes,” says Sylvia Santosa, an associate professor in the Department of Health, Kinesiology, and Applied Physiology and one of the authors of the paper.
Surprisingly, they found BMI, though far from perfect, was in some cases a better predictor of cardiometabolic risks like diabetes and hypertension.
Associate professor Lisa Kakinami, Concordia alumna and current Rhodes Scholar Sabine Plummer, BSc 22, Ph.D. student Jessica Murphy and Tamara Cohen of the University of British Columbia co-authored the paper.
Benefits of BMI
Nevertheless, the data did reveal several striking findings. In comparison to the low-adiposity/high-muscle group, which was the healthiest of the four, the researchers noted the following results:
The two high-adiposity groups were less likely to be physically active and more likely to have abnormal lipids and less healthy diets.
- The high-adiposity/low-muscle group had higher total cholesterol levels, lower levels of high-density lipoprotein (“good” cholesterol), and lower nutrient intake. This group was also 56 to 66 percent less likely to meet weekly physical activity recommendations.
- The high-adiposity/high-muscle group had unfavorable values for all cardiometabolic and adiposity measures. Nutrient intake was also lower. This group was also 49 to 67 percent less likely to meet physical activity recommendations, roughly 80 percent more likely to have hypertension, and 23 to 35 percent more likely to exceed recommended saturated fat intake.
- Overall, the high-adiposity/high-muscle phenotype was the least likely to meet physical activity and nutrient recommendations and was at the greatest risk of poor cardiometabolic health.
- The low-adiposity/low-muscle group had significantly lower BMI and waist circumferences. This group also had the lowest grip strength across the four phenotypes.
“If we are looking at cardiometabolic risk at the population level, BMI can give you a cheap and quick idea about what is happening,” Santosa says.
Reference: “Body-composition phenotypes and their associations with cardiometabolic risks and health behaviours in a representative general US sample” by Lisa Kakinami, Sabine Plummer, Tamara R. Cohen, Sylvia Santosa and Jessica Murphy, 30 September 2022, Preventive Medicine.
DOI: 10.1016/j.ypmed.2022.107282
