gms | German Medical Science

Background: A large number of studies have investigated associations of anthropometric, body composition, and fat distribution markers with pre-diabetes [1], [2], [3]. Similarly, there are only two studies that reported sex-specific associations of body composition markers with prediabetes [4], [5]. However, previous studies have certain limitations. Only a few studies used data from bioelectrical impedance analysis (BIA) to define body composition [3], [5], whereas most of them used indirect methods for body composition like body mass index (BMI) and waist circumferences (WC) [1], [2]. Further, prior studies failed to use an oral glucose tolerance test (OGTT) for prediabetes categories as proposed by the American Diabetes Association.

Aim: Therefore, in a population-based study, our study aimed to assess the associations of different body characteristics derived from various modalities with OGTT data and compare their effect size. A second aim of our study was to determine which markers show the strongest association with prediabetes.

Methods: Cross-sectional data of 3,628 (1,898 women, 52 %) individuals aged between 20 to 84 years were taken from the Study of Health in Pomerania (SHIP-Trend-0). We investigated associations of markers from body anthropometry, bioelectrical impedance analysis and magnetic resonance imaging with markers from an OGTT including fasting glucose (FG), fasting insulin (FI), the homeostasis model assessment-insulin resistance index (HOMA-IR), 2-hour postload glucose (2HG), 2-hour postload insulin (2HI), and glucose tolerance categories. For this, we used linear and multinomial logistic regression models stratified by sex and adjusted for confounding

Results: All body composition markers were significantly associated with continuous markers of glucose metabolism and glucose tolerance categories in both men and women. In men, waist-to-height ratio (WHtR) was the body composition marker most strongly associated with all OGTT parameters. Specifically, a 1 standard deviation (SD) higher WHtR was associated with a 0.32 mmol/L (95% confidence interval [CI]: 0.26 to 0.39) higher FG, a 0.83 mmol/L (95% CI: 0.68 to 0.98) higher 2-HG, a 6.69 µU/mL (95% CI: 5.91 to 7.47) higher FI, a 31.6 µU/mL (95% CI: 28.0 to 35.3) higher 2HI, and a 2.00 (95% CI: 1.75; 2.25) higher HOMA-IR. VAT showed a stronger association with all OGTT parameters in women than men. Specifically, a 1 SD higher VAT was associated with a 0.29 mmol/L (95% CI: 0.23 to 0.36) higher FG, a 1.04 mmol/L (95% CI: 0.84 to 1.25) higher 2HG, a 7.12 µU/mL (95% CI: 6.38 to 7.87) higher FI, a 46.7 µU/mL (95% CI: 40.8 to 52.7) higher 2HI, and a 1.97 (95% CI: 1.74 to 2.20) higher HOMA-IR. Relative fat-free mass was the only marker inversely associated with the OGTT parameters in both men and women. Overall, the associations of all body composition markers were more pronounced in men than in women.

Conclusion: Our study highlights that associations between body composition markers and OGTT parameters differ between men and women with a tendency of stronger association in men than in women. Sex-specific body composition markers may have to be considered in clinical practice to predict future prediabetes and type 2 diabetes. Further, particularly longitudinal, studies are needed to verify our findings.

The authors declare that they have no competing interests.

The authors declare that a positive ethics committee vote has been obtained.