Prevalence and associated factors of metabolic syndrome in Chinese middle-aged and elderly population: a national cross-sectional study

Abstract

Background

Currently, China has an increasingly aging population. However, the prevalence of metabolic syndrome (MetS) in this high-risk population for metabolic diseases remains unknown. This study investigates the age- and gender-specific prevalence and associated factors of MetS in the middle-aged and elderly Chinese population.

Methods

Data were collected and subjected to descriptive statistics. Further, univariate logistic regression was used to evaluate the relevant factors, and then multivariate logistic regression was selected to construct the final model.

Results

A total of 10,834 participants were included in the present study. The overall prevalence of MetS is 32.97% as defined by International Diabetes Federation (IDF) and 29.75% under National Cholesterol Education Program-The Adult Treatment Panel III (NCEP-ATP III) criteria. With aging, the prevalence of MetS descends in males while ascends in females. In the >70 years old group, the prevalence of MetS is three times higher in females than that in males (50.43% versus 16.03%). Across all age groups and sexes, the prevalence of MetS in urban areas is significantly higher than in rural areas. Besides, regardless of gender, the prevalence of MetS is the highest for those living in the north region (28.41% for males and 51.74% for females) and the lowest for those living in the southwest region (13.91% for males and 31.58% for females). Finally, an afternoon nap has been identified as a positively associated factor, while blood urea nitrogen (BUN) has been identified as a negatively associated factor (p < 0.05).

Conclusion

The prevalence of MetS varies in different age groups, sexes, living areas, and regions. An afternoon nap is positively associated with the prevalence of MetS, while BUN is negatively associated with MetS.

Keywords:

• Age
• aging population
• gender
• metabolic syndrome
• prevalence

Acknowledgments

The authors express thanks to the office of China Health and Retirement Longitudinal Study (CHARLS) and the assistance from Dr Xiaoyingzi Huang for her suggestions.

Author contributions

Conceptualization: Y. X. and Y. C. Z. Data curation: Y. X., Y. C. Z., and F. X. Z. Formal analysis: Y. X. and Y. C. Z. Funding acquisition: J. H. Y. Investigation: Y. C. Z., F. X. Z., and C. J. W. Methodology: Y. X. and F. Q. Project administration: J. H. Y. and F. Q. Resources: Y. X. and Y. C. Z. Software: Y. X. and S. W. Supervision: J. H. Y. and F. Q. Validation: Y. X. and F. Q. Visualization: Y. C. Z. Writing – original draft: Y. X. Writing – review and editing: J. H. Y. and F. Q.

Ethics approval and consent to participate

The CHARLS study was approved by research ethics committees of Peking University (IRB00001052-13074). All participants provided written informed consent. No experimental interventions were performed.

Disclosure statement

The authors declare no conflict of interest.

Data availability statement

The data that support the findings of this study are available from China Health and Retirement Longitudinal Study (CHARLS) website (http://charls.pku.edu.cn/). The full datasets used in this analysis are available from the corresponding author upon reasonable request.

Additional information

Funding

This work was supported by the Natural Science Foundation of China from Jiuhong Yuan [Nos. 81871147 and 81671453]

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