The average age was 43.4±16.1 years old for all 20,862 subjects. The average age was 43.3±16.7 years old for 9864 males and 43.4±15.6 years old for 10,998 females. The subjects came from dozens of ethnicities, including Han (13, 279, 63.7%), Yi (2031, 9.7%), Miao (343, 1.6%), Mongolia (1143, 5.5%), Tibetan (608, 2.9%), Korean (717, 3.4%), Hui (1808, 8.7%), Tujia (625, 3.0%) and others (308, 1.5%).
65.70% (N=13,707) of all subjects had at least one clinical feature of MetS (1 or more components). 32.74%, 18.93%, 10.25%, 3.25% and 0.53% of all subjects had one, two, three, four and five risk factors respectively. Components in order of prevalence were elevated blood pressure (41.90%), elevated triglyceride (28.14%), low HDL-C (27.14%), elevated blood glucose (10.82%) and abdominal obesity (9.21%). The most prevalent grouping of two components was blood pressure and low HDL-C (9.64%). The most prevalent grouping of three components was elevated blood pressure, elevated triglyceride and low HDL-C (5.56%).
All in all, 2926 subjects were diagnosed as MetS and the prevalence rate was 14.03%. The prevalence rate of MetS for males (12.31%) was lower than females (15.57%), P<0.0001. The average age was 53.4±12.9 years old for subjects with MetS and 41.8±16.0 years old for subjects without MetS. The prevalence rate of MetS was 3.59% for youths, 16.72% for middle-aged adults and 26.13% for elders. With aging, the prevalence rates increased gradually, P<0.0001. Among minorities, Tibetan subjects held the lowest prevalence rate of MetS (5.59%) and Korean subjects the highest one (20.50%). Physical laborers had higher prevalence rates (17.39%) of MetS than counterparts. Subjects with hyperuricemia (26.56%) or enjoying high-salted diet (15.74%) had higher prevalence rates of MetS than counterparts. Compared to subjects without disease family history, subjects with family history of cardiovascular diseases (17.41%) or cerebrovascular diseases (17.75%) had higher prevalence rates of MetS. Subjects who were accustomed to sleeping less than six hours per day had higher prevalence rates (15.50%) of MetS than counterparts. Compared to subjects with normal body mass, overweight and obese subjects had higher prevalence rates (21.10% and 46.40%) of MetS. The average PBF was 26.9%±7.9% for subjects with MetS and 21.0%±8.6% for subjects without MetS. The prevalence and related componens of MetS as related to different demographic characteristics were shown in details in table 1.
Table 2 gives the results of the univariate and multivariate multi-level generalized estimation equation models of associated factors for MetS. After controlling the cluster effect of living areas and other covariates, no significant association was found between gender, smoker and MetS. Compared to youths, middle-aged (OR=1.461, 95%CI: 1.371-1.557) and elder subjects (OR=1.667, 95%CI: 1.535-1.812) were associated with higher prevalence odds of MetS. Compared to normal-weight subjects, overweight (OR=1.670, 95%CI: 1.600-1.743) and obese subjects (OR=2.287, 95%CI: 2.136-2.449) were associated with higher prevalence odds of MetS. The higher age or BMI means higher prevalence odds of MetS. Compared to Hans, Koreans had more odds of MetS (OR=1.120, 95%CI: 1.053-1.191), however Yis (OR=0.953, 95%CI: 0.923-0.984) and Tibetans (OR=0.853, 95%CI: 0.813-0.895) had less odds of MetS. Current drinkers (OR=1.053, 95%CI: 1.020-1.086), physical laborers (OR=1.070, 95%CI: 1.040-1.101), subjects enjoying high-salted diet (OR=1.040, 95%CI: 1.009-1.071), subjects with hyperuricemia (OR=1.264, 95%CI: 1.215-1.316), subjects who were accustomed to sleeping less than six hours per day (OR=1.032, 95%CI: 1.009-1.055), subjects with family history of cardiovascular diseases (OR=1.065, 95%CI: 1.019-1.113) or cerebrovascular diseases (OR=1.055, 95%CI: 1.007-1.104) could increase prevalence risk of MetS. We found the risk of MetS would increase 6.9% (OR=1.069, 95%CI: 1.053-1.085) with each 5-percent increase of PBF. Contrary to univariate analysis results, association of smoking conditions and MetS was not significant in the multivariate model.
In summary, after controlling the cluster effect of living areas, age, gender, occupation, ethnicity, alcohol drinking, high-salted diet, BMI, PBF, sleep duration and disease family history were associated with MetS.