ArticleBMJ open2022
Association of predicted fat mass, predicted lean mass and predicted percent fat with diabetes mellitus in Chinese population: a 15-year prospective cohort.
Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed, 11 citations in OpenAlex.
- Methodologies for establishing and validating cut-points and comparative standards in medical imaging-based body composition analysis: a scoping review protocol.Systematic reviews · 2026Article
- Association Between Body Composition and Risk of Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis.Diabetes, metabolic syndrome and obesity : targets and therapy · 2026Review
- Development and validation of a nomogram model integrating noninvasive detection of radial pulse wave for predicting diabetic foot risk in type 2 diabetes mellitus.Frontiers in endocrinology · 2026Article
- Identification of preschool children's physical fitness phenotypes and their association with multidimensional body shape indicators: a data-driven approach with risk prediction modeling.Frontiers in public health · 2026Article
- Lean body mass index and the risk of diabetes onset: A nationwide epidemiological cohort study.Journal of diabetes investigation · 2025Article
- Associations of the fat-free mass index and the fat mass index with the risk of developing diabetes and prediabetes in US adults: a nationally representative cross-sectional study.Lipids in health and disease · 2024Article
- Association of Body Composition Changes with the Development of Diabetes Mellitus: A Nation-Wide Population Study.Diabetes & metabolism journal · 2024Article
- Association between predicted fat mass, predicted lean mass, predicted percent fat and type 2 diabetes mellitus in Japanese adults: a retrospective study.BMC endocrine disorders · 2024Article
- Association of organ damage with predicted fat mass in a community-dwelling elderly: the Northern Shanghai study.Aging clinical and experimental research · 2024Article
- The role of predicted lean body mass and fat mass in non-alcoholic fatty liver disease in both sexes: Results from a secondary analysis of the NAGALA study.Frontiers in nutrition · 2023Article
- Association of predicted fat mass and lean body mass with diabetes: a longitudinal cohort study in an Asian population.Frontiers in nutrition · 2023Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesWith body mass index (BMI) failing to distinguish the mass of fat from lean, several novel predicted equations for predicted fat mass (FM), predicted lean mass (LM) and predicted per cent fat (PF) were recently developed and validated. Our aim was to explore whether the three novel parameters could better predict diabetes mellitus (DM) than the commonly used obesity indicators, including BMI, waist circumference, hip circumference and waist-hip ratio.
designA 15-year prospective cohort was used.
settingIt was a prospective cohort, consisting of a general Chinese population from 1992 to 2007.
participantsThis cohort enrolled 711 people. People suffering from DM at baseline (n=24) were excluded, and 687 non-diabetics with complete data were included to the analysis. PRIMARY OUTCOME: New-onset DM.
resultsAfter the follow-up, 74 (48 men and 26 women) incidences of DM were documented. For men, the adjusted HRs were 1, 5.19 (p=0.003) and 7.67 (p<0.001) across predicted PF tertiles; 1, 2.86 (p=0.029) and 5.60 (p<0.001) across predicted FM tertiles; 1, 1.21 (p=0.646) and 2.27 (p=0.025) across predicted LM tertiles. Predicted FM performed better than other commonly used obesity indicators in discrimination with the highest Harrell's C-statistic among all the body composition parameters. Whereas, for women, none of the three novel parameters was the independent predictor.
conclusionPredicted PF, predicted LM and predicted FM could independently predict the risk of DM for men, with predicted FM performing better in discrimination than other commonly used obesity indicators. For women, larger samples were further needed.
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