Title

Suboptimal health status as an independent risk factor for type 2 diabetes mellitus in a community-based cohort: the China suboptimal health cohort study

Document Type

Journal Article

PubMed ID

30714488

Publisher

Springer International Publishing

School

School of Medical and Health Sciences

RAS ID

28429

Comments

Originally published as: Ge, S., Xu, X., Zhang, J., Hou, H., Wang, H., Liu, D., . . . Wang, W. (2019). Suboptimal health status as an independent risk factor for type 2 diabetes mellitus in a community-based cohort: The china suboptimal health cohort study. EPMA Journal, 10(1), 65-72. Original article available here.

Abstract

Background: The prevalence of diabetes, constituted chiefly by type 2 diabetes mellitus (T2DM), is a global public health threat. Suboptimal health status (SHS), a physical state between health and disease, might contribute to the progression or development of T2DM. Methods: We conducted a prospective cohort study, based on the China Suboptimal Health Cohort Study (COACS), to understand the impact of SHS on the progress of T2DM. We examined associations between SHS and T2DM outcomes using multivariable logistic regression models and constructed predictive models for T2DM onset based on SHS. Results: A total of 61 participants developed T2DM after an average of 3.1 years of follow-up. Participants with higher SHS scores had more T2DM outcomes (p = 0.036). Moreover, compared with the lowest quartile of SHS scores, participants with fourth, third, and second quartile SHS scores were found to be associated with a 1.7-fold, 1.6-fold, and 1.5-fold risk of developing T2DM, respectively. The predictive model constructed with SHS had higher discriminatory power (AUC = 0.848) than the model without SHS (AUC = 0.795). Conclusions: The present study suggests that a higher SHS score is associated with a higher incidence of T2DM. SHS is a new independent risk factor for T2DM and has the capability to act as a predictive tool for T2DM onset. The evaluation of SHS combined with the analysis of modifiable risk factors for SHS allows the risk stratification of T2DM, which may consequently contribute to the prevention of T2DM development. These findings might require further validation in a longer-term follow-up study. © 2019, European Association for Predictive, Preventive and Personalised Medicine (EPMA).

DOI

10.1007/s13167-019-0159-9

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