Ability of Anthropometric Measurements to Predict Metabolic Health among Patients in Alberta: A Cross-sectional Study in Primary Care
Year: 2023
Type: article
Study design: Observational Study
Abstract: Purpose: This study compared anthropometric and body fat percent (BF%) equations in relation to measures of metabolic health. Methods: BF% calculations (Bergman, Fels, and Woolcott) and anthropometric measurements were used to determine obesity among a sample of patients attending primary care in Alberta, Canada. Anthropometric variables included body mass index (BMI), waist circumference, waist:hip ratio, waist:height ratio, and calculated BF%. Metabolic Z-score was computed as the average of the individual Z-scores of triglycerides, total cholesterol, and fasting glucose and the number of standard deviations from the sample mean. Results: Five hundred and fourteen individuals were included (41.2% male, age: 53 ± 16y, BMI: 27.4 ± 5.7 kg/m2). BMI ≥ 30 kg/m2 detected the smallest number of participants (n = 137) as having obesity, while Woolcott BF% equation categorized the largest number of participants as having obesity (n = 369). No anthropometric or BF% calculation predicted metabolic Z-score in males (all p ≥ 0.05). In females, age-adjusted waist:height ratio had the highest prediction power (R2 = 0.204, p < 0.001), followed by age-adjusted waist circumference (R2 = 0.200, p < 0.001) and age-adjusted BMI (R2 = 0.178, p < 0.001). Conclusions: This study did not find evidence that BF% equations more strongly predicted metabolic Z-scores than other anthropometric values. In fact, all anthropometric and BF% variables were weakly related to metabolic health parameters, with apparent sex differences.
Authors: Sunita Ghosh, Sarah A. Purcell, Ken Martin, Isac Lima, Carla M. Prado
Language: English
Subfield: Physiology (medical)
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W4323533166