Association of predicted fat mass and lean body mass with diabetes: a longitudinal cohort study in an Asian population

Maobin Kuang; Song Lu; Ruijuan Yang; Huaigang Chen; Shuhua Zhang; Guotai Sheng; Yang Zou

doi:10.3389/fnut.2023.1093438

Association of predicted fat mass and lean body mass with diabetes: a longitudinal cohort study in an Asian population

Front Nutr. 2023 May 9:10:1093438. doi: 10.3389/fnut.2023.1093438. eCollection 2023.

Authors

Maobin Kuang^{1

2}, Song Lu^{1

2}, Ruijuan Yang^{1

3}, Huaigang Chen¹, Shuhua Zhang², Guotai Sheng⁴, Yang Zou²

Affiliations

¹ Medical College of Nanchang University, Nanchang, Jiangxi, China.
² Jiangxi Cardiovascular Research Institute, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China.
³ Department of Endocrinology, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China.
⁴ Jiangxi Provincial Geriatric Hospital, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China.

Abstract

Objective: The relationship between body composition fat mass (FM) and lean body mass (LBM) and diabetes risk is currently debated, and the purpose of this study was to examine the association of predicted FM and LBM with diabetes in both sexes.

Methods: The current study was a secondary analysis of data from the NAGALA (NAfld in the Gifu Area, Longitudinal Analysis) cohort study of 15,463 baseline normoglycemic participants. Predicted LBM and FM were calculated for each participant using anthropometric prediction equations developed and validated for different sexes based on the National Health and Nutrition Examination Survey (NHANES) database, and the outcome of interest was diabetes (types not distinguished) onset. Multivariate Cox regression analyses were applied to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations of predicted FM and LBM with diabetes risk and further visualized their associations using a restricted cubic spline function.

Results: The incidence density of diabetes was 3.93/1000 person-years over a mean observation period of 6.13 years. In women, predicted LBM and FM were linearly associated with diabetes risk, with each kilogram increase in predicted LBM reducing the diabetes risk by 65% (HR 0.35, 95%CI 0.17, 0.71; P < 0.05), whereas each kilogram increase in predicted FM increased the diabetes risk by 84% (HR 1.84, 95%CI 1.26, 2.69; P < 0.05). In contrast, predicted LBM and FM were non-linearly associated with diabetes risk in men (all P for non-linearity < 0.05), with an L-shaped association between predicted LBM and diabetes risk and a saturation point that minimized the risk of diabetes was 45.4 kg, while predicted FM was associated with diabetes risk in a U-shape pattern and a threshold point with the lowest predicted FM-related diabetes risk was 13.76 kg.

Conclusion: In this Asian population cohort, we found that high LBM and low FM were associated with lower diabetes risk according to anthropometric equations. Based on the results of the non-linear analysis, we believed that it may be appropriate for Asian men to keep their LBM above 45.4 kg and their FM around 13.76 kg.

Keywords: diabetes; predicted fat mass; predicted lean body mass; protective factors; risk management.

Grants and funding

This study was supported by the Natural Science Foundation of Jiangxi Province (no. 20192BAB205007), Jiangxi Provincial Education Department foundation Project (no. GJJ218911), and Applied Research and Cultivation Program of Jiangxi Provincial Department of Science and Technology (no. 20212BAG70036).