, Volume 62, Issue 1, pp 107–115 | Cite as

Distribution of metabolic/obese phenotypes and association with diabetes: 5 years’ cohort based on 22,276 elderly

  • Miao LiuEmail author
  • Ru Tang
  • Jianhua Wang
  • Yao He
Original Article



To describe the distribution and changes of different metabolic/obese phenotypes among more than 22,000 male elderly in China, and also explore the association with diabetes incidence.


A cohort study based on 22,276 male elderly was conducted in Beijing, from 2009 to 2013. Multiple Cox model was used to calculate the relative risk.


There were only 53.8% of total participants who kept the same phenotype for the 5 years. On the whole, participants with metabolically unhealthy phenotypes had higher relative risks (RRs) than those with metabolically healthy phenotypes. RRs for diabetes showed an increasing trend along with metabolic abnormalities (p < 0.001). However, no statistically significant difference was found across different obese status with the same number of metabolic abnormalities. Changes of metabolic/obese status also showed the same trend. Those who had kept metabolic unhealthy had the highest RRs for diabetes incidence, which was higher than those who kept obesity.


Both metabolically healthy obesity and metabolically unhealthy normal weight phenotypes had an increased risk for diabetes incidence, and metabolic abnormalities might have more influence on diabetes than obesity itself. Changes of metabolic/obese status also had an important impact on diabetes incidence.


Metabolically healthy obesity Metabolically unhealthy normal weight Diabetes Cohort study Elderly 



Body mass index


Confidence interval


Diastolic blood pressure


Fasting blood glucose


High-density lipoprotein cholesterol


Low-density lipoprotein cholesterol


Metabolically healthy normal weight


Metabolically healthy obesity


Metabolically healthy overweight


Metabolically unhealthy normal weight


Metabolically unhealthy obesity


Metabolically unhealthy overweight


Relative risk


Systolic blood pressure


Total cholesterol




Two hours plasma glucose



This study is supported by research grants from Beijing Nova Program (Z181100006218085), Opening Foundation of State Key Laboratory of Kidney Diseases (KF-01-115), Opening Foundation of National Clinical Research Center of Geriatrics (NCRCG-PLAGH-2017017), National Natural Science Foundation of China (81703285), Beijing Natural Science Foundation (7174350), Beijing Municipal Science and Technology Commission (Z161100005016021), Military Fund (15BJZ41, 17BJZ51). The views and opinions expressed in this paper are those of the authors and do not necessarily reflect the official position of the study sponsors.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. And this study protocol had been approved by the Ethics Committees of Chinese PLA General Hospital (EC0411-2001).

Informed consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

12020_2018_1672_MOESM1_ESM.doc (78 kb)
Appendix Tables
12020_2018_1672_MOESM2_ESM.jpg (49 kb)
Appendix Figure 1Flow Chart of Inclusion of Participants
12020_2018_1672_MOESM3_ESM.jpg (524 kb)
Appendix Figure 2 Diabetes-free survival curve according to six phenotypes
12020_2018_1672_MOESM4_ESM.doc (33 kb)
Appendix Figure 3 RRs of diabetes according to changes of combination of metabolic status and BMI


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Institute of Geriatrics, State Key Laboratory of Kidney Diseases, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatrics DiseaseChinese PLA General HospitalBeijingChina
  2. 2.Clinical Department of NanlouChinese PLA General HospitalBeijingChina

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