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Long-term BMI change trajectories in Chinese adults and its association with the hazard of type 2 diabetes: evidence from a 20-year China Health and Nutrition Survey
  1. Baibing Mi1,2,3,
  2. Chenlu Wu1,
  3. Xiangyu Gao1,
  4. Wentao Wu1,
  5. Jiaoyang Du1,
  6. Yaling Zhao1,
  7. Duolao Wang4,
  8. Shaonong Dang1,2,3,
  9. Hong Yan1,2,3
  1. 1Department of Epidemiology and Biostatistics, Xi’an Jiaotong University Health Science Center, Xi’an, China
  2. 2Nutrition and Food Safety Engineering Research Center of Shaanxi Province, Xi’an Jiaotong University Health Science Center, Xi’an, China
  3. 3Key Laboratory of Environment and Genes Related to Diseases, Xi’an Jiaotong University, Ministry of Education, Xi’an, Shaanxi, China
  4. 4Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, UK
  1. Correspondence to Dr Shaonong Dang; tjdshn{at}; Dr Hong Yan; yanhonge{at}


Introduction To investigate the relationship between long-term change trajectory in body mass index (BMI) and the hazard of type 2 diabetes among Chinese adults.

Research design and methods Data were obtained from the China Health and Nutrition Survey (CHNS). Type 2 diabetes was reported by participants themselves in each survey wave. The duration of follow-up was defined as the period from the first visit to the first time self-reported type 2 diabetes, death, or other loss to follow-up from CHNS. The patterns of change trajectories in BMI were derived by latent class trajectory analysis method. The Fine and Gray regression model was used to estimate HRs with corresponding 95% CIs for type 2 diabetes.

Results Four patterns of the trajectories of change in BMI were identified among Chinese adults, 42.7% of participants had stable BMI change, 40.8% for moderate BMI gain, 8.9% for substantial BMI gain and 7.7% for weight loss. During the follow-up with mean 11.2 years (158 637 person-years contributed by 14 185 participants), 498 people with type 2 diabetes (3.7%) occurred. Risk of type 2 diabetes was increased by 47% among people who gained BMI more substantially and rapidly (HR: 1.47, 95% CI 1.08 to 2.02, p=0.016) and increased by 20% among those in people with the moderate BMI gain (HR: 1.20, 95% CI 0.98 to 1.48, p=0.078), compared with those with stable BMI change.

Conclusions Long-term substantial gain of BMI was significantly associated with an increased risk of type 2 diabetes in the Chinese adults.

  • BMI
  • type 2 diabetes
  • longitudinal study
  • Chinese

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  • Contributors BM, YZ, SD and HY designed the research. BM, CW, XG, YZ and SD conducted the study. BM, CW, XG, WW and JD analyzed the data. BM, CW, YZ, DW and SD wrote the initial draft of the manuscript. BM had the primary responsibility for the final content. All authors read and approved the final manuscript.

  • Funding This work was supported by the Chinese National Key Research and Development Program of China (grant numbers: 2017YFC0907200 and 2017YF0907201), the National Natural Science Foundation of China (grant number: 81230016), the Natural Science Basic Research Plan of the Shaanxi Province (grant Number: 2020JQ-090), the Fundamental Research Funds for the Central Universities (grant Number: xzy032020033) and the Shaanxi Health and Family Planning Commission (grant number: Sxwsjswzfcght2016-013).

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Ethics approval Informed consent was obtained from each participant, and the survey was approved by the institutional review committees of the University of North Carolina at Chapel Hill, the National Institute of Nutrition and Food Safety, the Chinese Center for Disease Control and Prevention, and the China-Japan Friendship Hospital, Ministry of Health. The current study was approved by the Human Research Ethics Committee of Xi’an Jiaotong University Health Science Center (No: XJTU 2020-32) and conducted according to the Declaration of Helsinki.

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

  • Data availability statement Data are available in a public, open access repository. Original data are available in Carolina Population Center of the University of North Carolina at Chapel Hill ( Please contact the corresponding author to access the analytic data set relevant to this study.

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