摘要
目的:评估人群血清谷氨酰转肽酶(GGT)与代谢综合征(MS)关联性。方法采用历史性队列研究方法,对深圳市4935名健康体检人群进行10年随访,其中男性占81.84%,女性占18.16%;平均年龄(60.54±10.38)岁。随访结局为MS事件发生,利用Cox比例风险模型计算GGT与MS发生关联强度。结果队列人群平均随访(5.0±2.9)年,共随访24713人年,发生MS事件1689例,MS累计发病率34.22%,发病密度(ID)68.34/千人年;无论男、女,ID与GGT呈现剂量?反应关系(男:χ2=32.78,P〈0.001;女:χ2=18.80,P〈0.001);拟合Cox比例风险模型,在调整年龄、性别、体质指数、收缩压、舒张压、高密度脂蛋白、低密度脂蛋白、三酰甘油、血尿酸、空腹血糖后,第3、4四分位数组GGT发病风险为1.45(95%CI:1.08-1.85)和1.52(95%CI:1.15-1.99)。结论 GGT水平与MS之间存在关联,有可能是MS发生的风险因素及预测因子。
Objective To analyze the relationship between baseline serum γ-glutamyhransferase (GGT) and risk of the metabolic syndrome (MS). Method A total of 4 935 adults from health checkup population in Shenzhen were enrolled into a 10-year follow-up study, of these adults 81.84% were male and 18.16% were female, the average age was 60.54± 10.38 years.The follow-up outcome measure was the occurrence of MS. The proportional hazards model was adopted to calculate the hazard ratios (HR) and 95% confidence intervals (95% C/) to analyze the association of GGT with the development of MS. Reslut The mean follow up period was 5.0±2.9 years, and there were 24 713 person-years of follow-up, and 1 689 subjects developed MS. During the follow-up, the cumulative incidence and incidence density of MS were 34.22% and 68.34/1 000 person-years, respectively. For both genders, the association between GGT and MS presented dose- response relationship trend (male: M- C X^2=32.78, P〈0.001; female: M- C X^2=18.80, P〈 0.001). After adjusting for age, gender, body mass index, systolic blood pressure, diastolic blood pressure, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, uric acid and fasting blood glucose in Cox regression model, the HR for MS in quartiles 3 and 4 level of GGT was 1.45 (95%CI: 1.08-1.85) and 1.52 (95%Ch 1.15-1.99), respectively. Conclusion The GGT level could be an important risk factor and predictor for the development of MS.
出处
《中华健康管理学杂志》
CAS
2015年第3期182-185,共4页
Chinese Journal of Health Management
关键词
代谢综合征X
队列研究
健康管理
Metabolic syndrome X
Cohort studies
Health management