摘要目的:探讨长沙地区职业人群腰围和高尿酸血症之间的关系。方法:采用回顾性队列研究的方法，纳入2014年1月1日—2018年12月31日在中南大学湘雅医院健康管理中心连续体检4年及以上的70家单位共1 197例员工。以2014年1月1日—12月31日的体检数据作为基线数据，2015年1月1日—2018年12月31日的数据作为随访数据。按照四分位数间距，将受试者根据腰围分为4组：第1四分位数（ Q1），男性<77 cm，女性<68 cm；第2四分位数（ Q2），77 cm≤男性<82 cm、68 cm≤女性<73 cm；第3四分位数（ Q3）82 cm≤男性<87 cm、73 cm≤女性<78 cm；第4四分位数（ Q4）：男性≥87 cm、女性≥78 cm。其中 Q1为对照组， Q2、 Q3、 Q4为暴露组。对总人群、男性人群、女性人群分别建立3个模型，模型Ⅰ不调整混杂因素，模型Ⅱ调整年龄、性别、体质指数的混杂（男性人群和女性人群不调整性别），模型Ⅲ调整年龄、性别、体质指数、高血压、空腹血糖、血肌酐、三酰甘油、低密度脂蛋白胆固醇、高密度脂蛋白胆固醇的混杂。采用Cox回归分析比较不同腰围水平人群4年内发生高尿酸血症的风险比（ HR）和调整风险比（a HR）及其95%可信区间（ CI）。 结果:1 197例研究对象平均随访（2.05±1.18）年，共随访2 448人年。总人群4年共发生高尿酸血症208例（女45例/男163例），4年累积发病率17.4%（女6.4%/男33.3%），发病密度84.9/1 000人年（女31.8/1 000人年，男157.6/1 000人年）。 Q1~ Q4组分别随访626、609、629、584人年，4年发生高尿酸血症15、30、59、104例，4年累积发病率分别为5.5%、9.2%、20.8%、32.8%，发病密度分别为24.0/1 000人年、49.3/1 000人年、93.8/1 000人年、178.1/1 000人年。与 Q1组相比， Q4组高尿酸血症发生风险增高， HR（95% CI）为2.70（1.81~4.04）， P<0.05。总人群调整了混杂因素后，高尿酸血症的a HR（95% CI）为2.12（1.39~3.24）， P<0.05。按照性别分层并调整混杂因素后，这种风险仍然存在，与 Q1组相比，男性人群和女性人群 Q4组高尿酸血症的a HR（95% CI）分别为1.91（1.18~3.09）和2.93（1.14~7.56），均 P<0.05。 结论:随着腰围的增加，单位职工高尿酸血症的发病风险增高。

abstractsObjective:To investigate the relationship between waist circumference and hyperuricemia in occupational population in Changsha city.Methods:Based on a retrospective cohort design, a total of 1 197 employees from 70 organizations who received 4 or more years of continuous physical examinations in Xiangya hospital from January 1, 2014 to December 31, 2018 were included in this study. The physical examination data of the year 2014 were set as baseline data, while the data between January 1, 2015 and December 31, 2018 were used as follow-up data. According to interquartile range of the waist circumference, the subjects was divided into four groups: the first quartile ( Q1),<77 cm for men and <68 cm for women; the second quartile ( Q2), 77 cm ≤ and<82 cm for men, 68 cm ≤ and <73 cm for women; the third quartile ( Q3), 82 cm ≤ and <87 cm for men, 73 cm ≤and <78 cm for women; the fourth quartile ( Q4), ≥87 cm for men, ≥78 cm for women. Among them, Q1 was set as the control group, and Q2, Q3 and Q4 as the exposed groups. Three models were established for the total population, men and women, respectively. The confounding factors were not adjusted in model Ⅰ. The model Ⅱ was adjusted for age, gender and body mass index (the male or female population were not adjusted for sex). Confounders including age, gender, body mass index, hypertension, fasting glucose, blood creatinine, triacylglycerol, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol were adjusted for model Ⅲ. Cox regression analysis was used to compare the hazard ratio ( HR), adjusted hazardratio (a HR) and their 95% CIs for the development of hyperuricemia in the subjects with different waist circumference over the 4 years. Results:Total of 1 197 subjects were followed-up for (2.05±1.18) years and 2 448 person-years. A total of 208 cases of hyperuricemia were identified in the total population during the 4 years (45 women/163 men), with a cumulative incidence of 17.4% (6.4% in women/33.3% in men) and an incidence density of 84.9/1 000 person-years (31.8/1 000 person-years in women, 157.6/1 000 person-years in men). And 626, 609, 629, and 584 person-years were followed-up in the 4 groups, respectively; with 15, 30, 59, and 104 cases of hyperuricemia occurred during 4 years, respectively. The cumulative incidence rates of hyperuricemia in the 4 yearswas 5.5%, 9.2%, 20.8% and 32.8%, respectively; and the incidence densities was 24.0/1 000 person-years, 49.3/1 000 person-years, 93.8/1 000 person-years and 178.1/1 000 person-years, respectively. Compared with that in the Q1 group, the risk of hyperuricemia was increased in the Q4 group, with a HR (95% CI) of 2.70 (1.81 to 4.04), P<0.05. After adjusted for confounding factors in the total population, the a HR (95% CI) of hyperuricemia was 2.12 (1.39 to 3.24), P<0.05. This risk remained when stratified by gender and adjusted for confounding factors. Compared with the Q1 group, the a HR (95% CI) of hyperuricemia in the Q4 group was 1.91 (1.18 to 3.09) for the male population and 2.93 (1.14 to 7.56) for the female population, respectively (both P<0.05). Conclusion:Among the occupational population, the risk of hyperuricemia increases with increase of waist circumference.