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Jae Hyuk Choi  (Choi JH) 1 Article
Obesity and Metabolic Syndrome
Impact of Longitudinal Changes in Metabolic Syndrome Status over 2 Years on 10-Year Incident Diabetes Mellitus
Ji Hye Huh, Sung Gyun Ahn, Young In Kim, Taehwa Go, Ki-Chul Sung, Jae Hyuk Choi, Kwang Kon Koh, Jang Young Kim
Diabetes Metab J. 2019;43(4):530-538.   Published online February 20, 2019
DOI: https://doi.org/10.4093/dmj.2018.0111
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  • 20 Web of Science
  • 23 Crossref
AbstractAbstract PDFPubReader   
Background

Metabolic syndrome (MetS) is a known predictor of diabetes mellitus (DM), but whether longitudinal changes in MetS status modify the risk for DM remains unclear. We investigated whether changes in MetS status over 2 years modify the 10-year risk of incident DM.

Methods

We analyzed data from 7,317 participants aged 40 to 70 years without DM at baseline, who took part in 2001 to 2011 Korean Genome Epidemiology Study. Subjects were categorized into four groups based on repeated longitudinal assessment of MetS status over 2 years: non-MetS, resolved MetS, incident MetS, and persistent MetS. The hazard ratio (HR) of new-onset DM during 10 years was calculated in each group using Cox models.

Results

During the 10-year follow-up, 1,099 participants (15.0%) developed DM. Compared to the non-MetS group, the fully adjusted HRs for new-onset DM were 1.28 (95% confidence interval [CI], 0.92 to 1.79) in the resolved MetS group, 1.75 (95% CI, 1.30 to 2.37) in the incident MetS group, and 1.98 (95% CI, 1.50 to 2.61) in the persistent MetS group (P for trend <0.001). The risk of DM in subjects with resolved MetS was significantly attenuated compared to those with persistent MetS over 2 years. In addition, the adjusted HR for 10-year developing DM gradually increased as the number of MetS components increased 2 years later.

Conclusion

We found that discrete longitudinal changes pattern in MetS status over 2 years associated with 10-year risk of DM. These findings suggest that monitoring change of MetS status and controlling it in individuals may be important for risk prediction of DM.

Citations

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