Abstract
Background Central obesity is known to be associated with diabetes. Increasing lower extremity circumference was hypothesized in association with lower risk of diabetes. Objective This study determined which anthropometric patterns correlates the best with pre-diabetic and diabetic status among healthy adults. Design Cross-sectional study with nationwide population sampling of participants was designed. Participants In total, 1,358 ethnic Chinese adult participants were recruited from the Nutrition and Health Survey in Taiwan 2013–2016; the whole-body composition was measured through dual-energy X-ray absorptiometry. Main outcome measures Fat and lean mass in whole and specific parts of body among heathy Asian adults with normal glycemic, pre-diabetic, and diabetic states were measured, separately. Statistical analyses performed The generalized linear model was used to investigate the association between body composition (lean and fat mass) and hyperglycemic status. The reduced rank regression (RRR) was used to confirm the correlation between glycemic status and predicting factors (body composition parameters). Results Trunk fat positively correlated with the fasting glucose level (r = 0.327, P < 0.001) and HbA1c (r = 0.329, P < 0.001), whereas limb fat negatively correlated with the fasting glucose level (r = −0.325, P < 0.001) and HbA1c (ρ = −0.342, P < 0.001), respectively. In RRR analyses, fasting glucose and HbA1c exhibited a high positive association on fat amount per lean mass of the trunk (factor loading = 0.5319 and 0.5599, respectively) and of android area (0.6422 and 0.6104) and a high negative association fat amount per lean mass of the legs (−0.3863 and −0.3083) and gynoid area (−0.3414 and −0.3725). Conclusions For healthy community participants, increasing trunk fat had a greater risk of hyperglycemic status. Increasing lower extremity mass may confer lower risk of diabetes.
| Original language | English |
|---|---|
| Article number | e0241121 |
| Journal | PLoS ONE |
| Volume | 15 |
| Issue number | 11 November |
| DOIs | |
| State | Published - 11 2020 |
Bibliographical note
Publisher Copyright:© 2020 Lin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
