Article Text

Original research
Association of predicted fat mass, predicted lean mass and predicted percent fat with diabetes mellitus in Chinese population: a 15-year prospective cohort
  1. Lu Liu1,
  2. Chao Ban2,
  3. Shanshan Jia1,
  4. Xiaoping Chen1,
  5. Sen He1
  1. 1 Department of Cardiology, Sichuan University West China Hospital, Chengdu, Sichuan, China
  2. 2 Department of Equipment, Sichuan University West China Hospital, Chengdu, Sichuan, China
  1. Correspondence to Dr Sen He; hesensubmit{at}163.com; Dr Xiaoping Chen; xiaopingchen0196{at}163.com

Abstract

Objectives With 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.

Design A 15-year prospective cohort was used.

Setting It was a prospective cohort, consisting of a general Chinese population from 1992 to 2007.

Participants This 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.

Results After 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.

Conclusion Predicted 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.

  • Diabetes & endocrinology
  • INTERNAL MEDICINE
  • Risk management

Data availability statement

Data are available on reasonable request. The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

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Data availability statement

Data are available on reasonable request. The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

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Footnotes

  • LL and CB contributed equally.

  • Correction notice This article has been corrected since published online. The affiliations of last three authors are corrected along with the equal contribution statement.

  • Contributors LL and SJ: Participated in the conception and design of the study, performed data collection and statistical analysis and wrote the draft of the manuscript. CB: Participated in the conception and design of the study, performed statistical analysis and wrote the revision version. SH and XC: Guarantors and participated in the design of the study, performed the statistical analysis and revised subsequent drafts. All authors read and approved the final manuscript.

  • Funding This work was supported by the Key R&D Projects of Science and Technology Department of Sichuan Province, China (grant no: 22ZDYF1527); the National Natural Science Foundation of China (grant no: 81600299); a project from China’s eighth national Five-year research plan (grant no: 85-915-01-02); and the megaprojects of science research for China’s 11th Five-year plan (grant no: 2006BAI01A01).

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, conduct, reporting or dissemination plans of this research.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.