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

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Abstract

Aims

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.

Methods

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.

Results

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.

Conclusions

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.

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Abbreviations

BMI:

Body mass index

CI:

Confidence interval

DBP:

Diastolic blood pressure

FBG:

Fasting blood glucose

HDL-C:

High-density lipoprotein cholesterol

LDL-C:

Low-density lipoprotein cholesterol

MHNW:

Metabolically healthy normal weight

MHO:

Metabolically healthy obesity

MHOW:

Metabolically healthy overweight

MUNW:

Metabolically unhealthy normal weight

MUO:

Metabolically unhealthy obesity

MUOW:

Metabolically unhealthy overweight

RR:

Relative risk

SBP:

Systolic blood pressure

TC:

Total cholesterol

TG:

Triglyceride

2hPG:

Two hours plasma glucose

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Funding

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.

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Author notes

  1. The authors contributed equally: Miao Liu, Ru Tang.

Authors and Affiliations

  1. Institute of Geriatrics, State Key Laboratory of Kidney Diseases, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatrics Disease, Chinese PLA General Hospital, 100853, Beijing, China

    Miao Liu, Jianhua Wang & Yao He

  2. Clinical Department of Nanlou, Chinese PLA General Hospital, 28 Fuxing Road, 100853, Beijing, China

    Ru Tang

Authors
  1. Miao Liu
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  2. Ru Tang
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  3. Jianhua Wang
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  4. Yao He
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Corresponding author

Correspondence to Miao Liu.

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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).

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

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Liu, M., Tang, R., Wang, J. et al. Distribution of metabolic/obese phenotypes and association with diabetes: 5 years’ cohort based on 22,276 elderly. Endocrine 62, 107–115 (2018). https://doi.org/10.1007/s12020-018-1672-7

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  • DOI: https://doi.org/10.1007/s12020-018-1672-7

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