The prevalence and risk factors of metabolic syndrome in Chinese population based on the multi center cross-sectional survey
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摘要:
目的 调查中国不同民族人群代谢综合征流行状况及危险因素。 方法 通过多阶段分层随机抽样,检测调查对象的代谢综合征相关指标,并按照国家第六次人口普查数据进行标化,多因素及对数线性模型分析危险因素及交互作用。 结果 多民族人群的代谢综合征(metabolic syndrome,MS)患病率为19.58%,朝鲜族的MS患病率最高,其次是汉族,哈萨克族的MS患病率最低;MS及超重肥胖等4项指标检出率,男性高于女性,随着年龄的升高而升高;多因素分析结果显示,女性患MS风险是男性的0.556倍;年龄越大,患MS的风险越大;中心型肥胖人群MS的风险比2.765,同时腰身比大于0.52的风险比为4.259;利用对数线性模型,分析超重/肥胖,高血糖、高血压和血脂紊乱,4个指标之间的关系,显示4个指标有独立的效应,因素之间又有交互作用,且存在部分3因素交互作用。 结论 不同民族MS发生率存在明显差异,MS的高发生率及各指标间存在正向交互作用。应从公共卫生的防控角度,检出更多的MS,并进行干预,减少MS的患病危险因素,降低心脑血管疾病和糖尿病等发生的风险。 Abstract:Objective To understand the prevalence and risk factors of metabolic syndrome (MS) among different ethnic groups. Methods A multicenter cross-sectional survey was conducted. Subjects were selected by multistage stratified random sampling. Physical examination and laboratory testing were performed to collect MS related indicators, and the prevalence was standardized by the 6th general survey data. Further multivariate and logarithmic linear model methods were applied to analyze the risk factors and interaction. Results The overall prevalence of MS was 19.58%. The highest prevalence of MS was in Korean, followed by Han, while the lowest was in Kazakh. The rates of MS, overweight and obesity were higher in men than those in women, and increased along with age. Multivariate analysis result showed that the odds ratio (OR) of female to male was 0.556, and aging increased the risk of MS. The OR of central obesity was 2.765, and would reach to 4.259 when the waist-to-body ratio was over 0.52. The logarithmic linear model showed that the overweight/obesity, hyperglycemia, hypertension and dyslipidemia had independent effects on the risk of MS. Also, there were interactions in the four indicators. Conclusions The incidence of MS is high and the positive interaction between the overweight/obesity, hyperglycemia, hypertension and dyslipidemia is observed, making MS a common crisis to clinical and public health. In order to prevent and control MS, and to reduce the risk of cardiovascular and cerebrovascular diseases and diabetes, early screening of MS should be strengthened and lifestyle intervention should be carried out. -
Key words:
- Metabolic syndrome /
- Prevalence /
- Risk factors /
- Interaction
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表 1 多中心横断面调查人群基本情况
Table 1. The basic information of respondents of multi-center cross-sectional survey
人群 频数(%) MS检出率(%) 年龄(岁) 身高(cm) 体重(kg) WC(cm) WHR 中心性肥胖(%) BMI(kg/m2) 性别 男 3 396(31.46) 26.97 49.33±13.30 166.79±6.97 70.25±11.96 86.91±10.49 0.52±0.06 36.72 25.21±3.74 女 7 398(68.54) 16.18 49.07±12.05 155.57±6.23 59.72±10.39 80.67±10.56 0.52±0.07 29.74 24.66±3.96 年龄(岁) ≤25 399(3.70) 2.51 22.85±1.73 164.40±8.82 60.13±12.13 77.63±10.06 0.47±0.06 14.04 22.16±3.62 25~ 1 498(13.88) 5.67 30.93±2.84 161.66±8.39 62.57±13.01 80.24±11.20 0.50±0.06 25.90 23.84±4.04 35~ 2 005(18.58) 13.77 40.97±2.91 159.75±7.92 64.19±12.22 81.93±11.11 0.51±0.06 30.92 25.06±3.81 45~ 3 195(29.60) 21.00 50.85±2.85 158.52±7.94 63.68±11.87 82.93±10.88 0.52±0.06 32.02 25.27±3.86 55~ 2 803(25.97) 28.36 60.61±2.77 157.84±8.27 62.54±11.31 84.02±10.60 0.53±0.07 36.18 25.05±3.78 ≥65 894(8.28) 30.87 67.80±1.34 157.02±8.14 61.76±11.22 85.02±10.09 0.54±0.06 38.70 24.99±3.80 民族 朝鲜族 1 351(12.52) 21.84 50.91±11.32 160.08±7.32 61.54±10.47 78.68±9.20 0.49±0.05 17.02 23.94±3.23 傣族 1 949(18.06) 19.04 47.85±11.02 154.28±7.23 58.14±9.58 76.31±8.54 0.49±0.05 10.21 24.39±3.39 汉族 3 084(28.57) 23.67 53.70±10.77 160.53±8.19 64.55±11.40 84.21±9.77 0.53±0.06 37.65 24.98±3.51 哈萨克族 853(7.90) 15.36 46.16±12.22 160.89±8.43 71.46±13.79 90.15±12.21 0.56±0.08 61.20 27.59±4.81 维吾尔族 1 682(15.58) 11.77 38.52±11.80 162.11±8.32 67.30±12.85 88.52±11.33 0.55±0.07 52.73 25.61±4.56 壮族 1 875(17.37) 20.69 52.66±11.66 157.54±7.72 59.05±10.24 80.77±9.71 0.51±0.06 23.89 23.76±3.57 文化程度 小学及以下 3 328(30.83) 22.51 53.26±10.20 155.88±8.07 61.51±11.71 82.42±11.16 0.53±0.07 31.82 25.24±3.95 初中 3 468(32.13) 18.37 48.05±13.01 159.55±8.14 63.47±12.10 82.98±11.02 0.52±0.07 33.30 24.88±4.01 高中 1 802(16.69) 22.59 50.83±12.07 160.67±8.00 64.42±11.79 83.82±10.57 0.52±0.06 35.29 24.89±3.72 大专大学 910(8.43) 19.34 46.23±12.98 161.92±7.90 65.31±12.62 83.64±10.93 0.52±0.06 34.07 24.82±3.88 大学以上 1 286(11.91) 11.20 41.22±11.60 162.03±7.33 62.23±11.36 79.89±10.07 0.49±0.06 22.32 23.62±3.47 合计 19.58 49.15±12.46 159.10±8.31 63.03±11.95 82.63±10.93 0.52±0.07 31.93 表 2 不同性别和年龄段人群标化后MS患病率及各指标检出情况(%)
Table 2. The standardized prevalence of MS and detection of various indicators in different genders and age groups(%)
分类 MS检出率 超重/肥胖 高血糖 高血压 血脂紊乱 性别 男 26.97 50.47 35.78 44.55 36.01 女 16.18 41.08 28.67 31.82 25.48 年龄(岁) ≤25 2.51 20.55 4.51 8.77 11.53 25~ 5.67 32.64 10.61 8.54 20.09 35~ 13.77 46.53 22.24 21.55 25.84 45~ 21.00 47.79 32.33 38.18 32.33 55~ 28.36 46.27 44.02 53.73 33.04 ≥65 30.87 47.54 49.89 61.07 31.77 合计 19.58 44.03 30.91 35.83 28.79 表 3 不同民族标化后MS患病率及各指标检出情况(%)
Table 3. The standardized prevalence of MS and detection of various indicators in different ethnic groups(%)
民族 MS检出率 超重/肥胖 高血糖 高血压 血脂紊乱 朝鲜族 21.09 33.62 34.60 29.22 33.66 傣族 17.31 36.31 20.03 33.40 32.72 汉族 19.91 47.45 29.98 25.99 30.99 哈萨克族 11.70 59.72 14.24 20.59 19.69 维吾尔族 12.60 50.82 15.17 17.35 26.79 壮族 12.73 27.71 21.62 35.66 20.25 表 4 多元Logistic回归模型的变量赋值表
Table 4. Variable assignment of multicariate Logistic regression model
变量 赋值 MS(结局变量) 0=无,1=有 年龄分组(岁) 1=≤25,2=25~,3=35~,4=45~,5=55~,6=≥65 性别 1=男,2=女 腰身比(WHR) 1= > 0.52,0=≤0.52 饮酒(哑变量) 从不(0, 0),曾经(0, 1),现在饮(1, 0) 吸烟(哑变量) 从不(0, 0),曾经(0, 1),现在吸(1, 0) 民族(哑变量) 哈萨克族(0, 0, 0, 0, 0),维吾尔族(0, 0, 0, 1, 0),壮族(0, 0, 0, 0, 1), 汉族(0, 0, 1, 0, 0),傣族(0, 1, 0, 0, 0),朝鲜族(1, 0, 0, 0, 0) 中心型肥胖 0=否,1=是 表 5 代谢征影响因素非条件Logistic回归分析
Table 5. Non-conditional Logistic regression analysis of influencing factors of MS
因素 β sx Wald值 P值 OR(95% CI)值 常量 -4.115 0.202 416.306 < 0.001 性别 -0.587 0.069 71.882 < 0.001 0.556(0.486~0.637) 年龄组 0.352 0.026 182.219 < 0.001 1.422(1.351~1.496) 中心性肥胖 1.017 0.074 190.967 < 0.001 2.765(2.394~3.194) 腰身比 1.449 0.079 339.599 < 0.001 4.259(3.651~4.969) 饮酒(从不) 10.128 0.006 饮酒(曾经) 0.243 0.081 9.067 0.003 1.274(1.088~1.492) 饮酒(现在饮) -0.033 0.138 0.056 0.814 0.968(0.738~1.270) 哈萨克族 234.378 < 0.001 朝鲜 1.393 0.134 108.417 < 0.001 4.026(3.097~5.232) 傣族 1.428 0.128 123.481 < 0.001 4.169(3.241~5.363) 汉族 0.820 0.114 51.778 < 0.001 2.271(1.816~2.839) 维吾尔族 -0.028 0.130 0.046 0.830 0.972(0.753~1.255) 壮族 0.898 0.124 52.766 < 0.001 2.456(1.927~3.129) 表 6 对数线性模型拟合的参数估计
Table 6. Parameter estimation of log-linear model
因素效应 β sx χ2值 P值 独立效应 超重/肥胖 -0.058 2 0.011 8 24.24 < 0.001 高血糖 0.289 2 0.011 6 619.96 < 0.001 高血压 0.164 9 0.011 8 194.37 < 0.001 血脂紊乱 0.369 5 0.011 7 1000.19 < 0.001 二因素交互作用(正向) 超重/肥胖*高血糖 0.129 3 0.011 3 132.08 < 0.001 超重/肥胖*高血压 0.107 5 0.011 8 83.06 < 0.001 超重/肥胖*血脂紊乱 0.214 7 0.011 5 351.58 < 0.001 高血糖*高血压 0.199 9 0.011 1 324.33 < 0.001 高血糖*血脂紊乱 0.175 5 0.011 7 225.01 < 0.001 高血压*血脂紊乱 0.108 2 0.011 6 87.27 < 0.001 三因素交互作用(正向) 超重/肥胖*高血糖*高血压 0.022 5 0.011 1 4.12 0.042 超重/肥胖*高血压*血脂紊乱 0.030 2 0.011 4 7.02 0.008 -
[1] 中华医学会糖尿病学分会代谢综合征研究协作组. 中华医学会糖尿病学分会关于代谢综合征的建议[J]. 中华糖尿病杂志, 2004, 12(3): 156-161. DOI: 10.3321/j.issn:1006-6187.2004.03.002.Metabolic Syndrome Research Collaboration Group. The suggestions on metabolic syndrome from diabetes society of Chinese medical association[J]. Chin J Diabete, 2004, 12(3): 156-161. DOI: 10.3321/j.issn:1006-6187.2004.03.002. [2] Ma X, Zhu S. Metabolic syndrome in the prevention of cardiovascular diseases and diabetes——still a matter of debate?[J]. Eur J Clin Nutr, 2013, 67(5): 518-521. DOI: 10.1038/ejcn.2013.24. [3] 中华医学会糖尿病学分会. 中国2型糖尿病防治指南(2013年版)[J]. 中华糖尿病杂志, 2014, 22(8): 2-42. DOI: 10.3760/cma.j.issn.1674-5809.2014.07.004.Chinese Diabetes Society. Guidelines for the prevention and treatment of type 2 diabetes in China[J]. Chin J Diabetes Mellitus, 2014, 22(8): 2-42. DOI: 10.3760/cma.j.issn.1674-5809.2014.07.004. [4] 刘勤, 金丕焕. 分类数据的统计分析及SAS编程[M]. 上海: 复旦大学出版社, 2002.Liu Q, Jin PH. Statistical analysis of classified data and SAS programming[M]. ShangHai: Fudan University Press, 2002. [5] Riediger ND, Clara I. Prevalence of metabolic syndrome in the Canadian adult population[J]. CMAJ, 2011, 183(15): 1127-1134. DOI: 10.1503/cmaj.110070. [6] 孙焕珍, 金来润, 左翔, 等. 社区体检人群代谢综合征患病情况及相关影响因素的调查分析[J]. 中华疾病控制杂志, 2017, 21(5): 465-468. DOI: 10.16462/j.cnki.zhjbkz.2017.05.009.Sun HZ, Jin LR, Zuo X, et al. Study on the prevalence of metabolic syndrome and its influencing factors in a community medical check-up crowd[J]. Chin J Dis Control Prev, 2017, 21(5): 465-468. DOI: 10.16462/j.cnki.zhjbkz.2017.05.009. [7] 卢伟, 刘美霞, 李锐, 等. 上海15~74岁居民代谢综合征的流行特征[J]. 中华预防医学杂志, 2006, 40(4): 262-268. DOI: 10.3760/j:issn:0253-9624.2006.04.012.Lu W, Liu MX, Li R, et al. Epidemiological feature of metabolic syndrome in Shanghai residents aged 15-74 years[J]. Chin J Prevent Med, 2006, 40(4): 262-268. DOI: 10.3760/j:issn:0253-9624.2006.04.012. [8] 涂萍, 李圣坚, 段鹏, 等. 不同诊断标准下南昌市成人代谢综合征的流行特征比较[J]. 中国全科医学, 2013, 16(3A): 761-763, 769. DOI: 10.3969/j.issn.1007-9572.2013.07.014.Tu P, Li SJ, Duan P, et al. Comparison on prevalence features of adult metabolic syndrome by different diagnosing creteria in Nanchang[J]. Chinese Gen Pract, 2013, 16(3A): 761-763, 769. DOI: 10.3969/j.issn.1007-9572.2013.07.014. [9] 何宇纳, 赵文华, 赵丽云, 等. 中国2010-2012年成年人代谢综合征流行特征[J]. 中华流行病学杂志, 2017, 38(2): 212-215. DOI: 10.3760/cma.j.issn.0254-6450.2017.02.015.He YN, Zhao WH, Zhao LY, et al. Prevalence of metabolic syndrome in Chinese adults in 2010-2012[J]. Chin J Epidemiol, 2017, 38(2): 212-215. DOI: 10.3760/cma.j.issn.0254-6450.2017.02.015. [10] 张虎军, 顾建文, 张楠楠, 等. 家庭健康指标监护系统的构建[J]. 北京生物医学工程, 2010, 29(6): 633-637. DOI: 10.3969/j.issn.1002-3208.2010.06.16.Zhang HJ, Gu JW, Zhang NN, et al. Building of the household health indicator monitoring system[J]. Beijing Biomed Eng, 2010, 29(6): 633-637. DOI: 10.3969/j.issn.1002-3208.2010.06.16. [11] 王细川, 黄颖, 吴鹭萍, 等. 代谢综合征与腰身比值及脉压的关系[J]. 中国慢性病预防与控制, 2007, 15(4): 381-382. DOI: 10.3969/j.issn.1004-6194.2007.04.030.Wang XC, Huang Y, Wu LP, et al. The relationship of the metabolic syndrome and waist body ratio and pulse pressure[J]. Chin J Prevent Control Chronic Dis, 2007, 15(4): 381-382. DOI: 10.3969/j.issn.1004-6194.2007.04.030. [12] 王增武, 范国辉, 张林峰, 等. 北方农村地区男性代谢综合征与饮酒关系研究[J]. 中华疾病控制杂志, 2015, 19(4): 348-351. DOI: 10.16462/j.cnki.zhjbkz.2015.04.008.Wang ZW, Fan GH, Zhang LF, et al. Association study between metabolic syndrome and alcohol consumption among rural male residents in northern China[J]. Chin J Dis Control Prev, 2015, 19(4): 348-351. DOI: 10.16462/j.cnki.zhjbkz.2015.04.008. [13] 唐文婷, 喻谦. 2型糖尿病视网膜病变患者内脂素水平与代谢综合征的关系探讨[J]. 实用医院临床杂志, 2018, 15(3): 141-143. https://www.cnki.com.cn/Article/CJFDTOTAL-YYLC201803043.htmTang WT, Yu Q. Relationship between visfatin level and metabolic syndrome in patients with type 2 diabetic retinopathy[J]. Pract J Clin Med, 2018, 15(3): 141-143. https://www.cnki.com.cn/Article/CJFDTOTAL-YYLC201803043.htm [14] 朱智明, 杨晔. 代谢综合征与心血管疾病[J]. 人民军医, 2008, 51(11): 715-716. https://www.cnki.com.cn/Article/CJFDTOTAL-RMJZ200811025.htmZhu ZM, Yang Y. Metabolic syndrome and cardiovascular disease[J]. People's Military Surgeon, 2008, 51(11): 715-716. https://www.cnki.com.cn/Article/CJFDTOTAL-RMJZ200811025.htm [15] 时颖, 张普洪, 焦淑芳. 代谢综合征流行水平及其危险因素研究进展[J]. 中国慢性病预防与控制, 2007, 15(6): 615-617. DOI: 10.3969/j.issn.1004-6194.2007.06.042.Shi Y, Zhang PH, Jiao SF. The advance on the epidemic status and its risk factors of metabolic syndrome[J]. Chin J Prevent Control Chronic Dis, 2007, 15(6): 615-617. DOI: 10.3969/j.issn.1004-6194.2007.06.042. [16] 黄贤, 盘庆飞, 何秀丽, 等. 不同代谢综合征诊断标准在高血压人群中的比较[J]. 中华临床医师杂志(电子版), 2016, 10(3): 377-380. DOI: 10.3877/cma.j.issn.1674-0785.2016.03.015.Huang X, Pan QF, He XL, et al. Predictive value of the different definitions of metabolic syndrome among hypertension population[J]. Chin J Clin, 2016, 10(3): 377-380. DOI: 10.3877/cma.j.issn.1674-0785.2016.03.015.