Purpose: The present study aimed to assess the risk of incidence of metabolic syndrome depending on the body size phenotype and healthy lifestyle (smoking status, drinking status, and physical activity) of Korean adults (males and females).
Methods: This longitudinal study included 5,068 metabolically healthy subjects from the Korean Genome and Epidemiology Study (KoGES), which was tracked every two years from 2001 to 2016. After removing individuals with metabolic syndrome from the baseline and missing data, the sample size for each analysis was as follows: body size phenotype, n = 2,216; smoking status, n = 1,809; drinking status, n = 3,173; and physical activity, n = 1,444. Analysis was performed using the log-rank test, life table method, Cox’s proportional hazards regression model, and time-dependent Cox’s proportional hazards regression model. IBM SPSS Statistics version 26 was used for the analysis.
The results of the study were as follows:
1. The incidence of metabolic syndrome was 41.5% among males and 43.3% among females when followed for 14 years.
2. The incidence of metabolic syndrome depending on the body size phenotype significantly differed in males (F = 92.83, p < .001) and females (F = 81.48, p < .001). Compared with the metabolically healthy normal weight (MHNW) group, the hazard ratio (HR) for the risk of incidence of metabolic syndrome was 1.96 (95% CI = 1.67?2.30, p < .001) in the metabolically healthy overweight (MHOW) group and 3.11 (95% CI = 2.67?3.63, p < .001) in the metabolically healthy obese (MHO) group in males, while it was 1.89 (95% CI = 1.58?2.28, p < .001) in the MHOW group and 2.70 (95% CI = 2.28?3.21, p < .001) in the MHO group in females. In the time-dependent model, compared with the MHNW group, the HR was 1.92 (95% CI = 1.54?2.40, p < .001) in the MHOW group and 2.88 (95% CI = 2.32?3.58, p < .001) in the MHO group in males, while it was 1.89 (95% CI = 1.51?2.37, p < .001) in the MHOW group and 2.34 (95% CI = 1.88?2.90, p < .001) in the MHO group in females.
3. The incidence of metabolic syndrome depending on the smoking status significantly differed in males (F = 4.41, p = .004) but not in females (t = 1.56, p = .122). Compared with nonsmokers, the HR for the risk of incidence of metabolic syndrome was 1.28 (95% CI = 1.08?1.52, p = .005) in moderate smokers and 1.48 (95% CI = 1.21?1.81, p < .001) in heavy smokers in males; the risk of incidence was not significant in females. In the time-dependent model, compared with nonsmokers, the HR was 1.39 (95% CI = 1.10?1.76, p = .006) in moderate smokers and 1.56 (95% CI = 1.17?2.08, p = .003) in heavy smokers in males; the risk of incidence was not significant in females.\
4. The incidence of metabolic syndrome depending on the drinking status significantly differed in males (F = 4.02, p = .003) but not in females (t = 0.37, p = .715). Compared with nondrinkers, the HR for the risk of incidence of metabolic syndrome was 0.81 (95% CI = 0.66?0.99, p = .039) in very light drinkers and 1.26 (95% CI = 1.07?1.50, p = .007) in heavy drinkers in males; the risk of incidence was not significant in females. In the time-dependent model, compared with nondrinkers, the risk of incidence was not significant among drinkers in males; however, the HR was 1.23 (95% CI = 1.03?1.48, p = .025) among drinkers in females.
5. The risk of incidence of metabolic syndrome depending on physical activity was not significant in either gender. The same result was noted in the time-dependent model.
Conclusion: The results of the present study are expected to aid the development of interventions and policies for the prevention of metabolic syndrome and for obesity management in Korea in the future.