文章摘要
黄秋敏,姜红如,王柳森,张兵,王惠君,王志宏.中国15省份15~49岁女性心血管代谢性危险因素分析[J].中华流行病学杂志,2020,41(2):190-194
中国15省份15~49岁女性心血管代谢性危险因素分析
Analysis on detection status of cardio-metabolic related risk factors in women aged 15-49 years in 15 provinces in China
投稿时间:2019-03-13  
DOI:10.3760/cma.j.issn.0254-6450.2020.02.010
中文关键词: 心血管代谢性危险因素;社会经济因素;女性
英文关键词: Cardio-metabolic factor;Socio-economic factor;Women
基金项目:中国疾病预防控制中心营养与健康所和美国北卡罗莱纳大学人口中心合作项目(R01-HD30880,DK056350,R01-HD38700);财政拨款项目“中国居民营养状况变迁的队列研究”(13103110700015005);中国育龄期女性膳食及营养状况变化
作者单位E-mail
黄秋敏 中国疾病预防控制中心营养与健康所, 北京 100050  
姜红如 中国疾病预防控制中心营养与健康所, 北京 100050  
王柳森 中国疾病预防控制中心营养与健康所, 北京 100050  
张兵 中国疾病预防控制中心营养与健康所, 北京 100050  
王惠君 中国疾病预防控制中心营养与健康所, 北京 100050  
王志宏 中国疾病预防控制中心营养与健康所, 北京 100050 wangzh@ninh.chinacdc.cn 
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中文摘要:
      目的 分析我国15~49岁女性心血管代谢性危险因素的流行特征和聚集性。方法 利用2015年“中国居民营养状况变迁的队列研究”数据,分析15~49岁女性中心性肥胖、血压升高、血糖升高、TG升高、HDL-C降低和危险因素聚集的流行特征。采用国际糖尿病联盟于2005年发布的定义判定心血管代谢性危险因素,具有≥2项危险因素定义为危险因素聚集。采用多因素logistic回归模型分析社会经济因素与各代谢性危险因素之间的关系。结果 共纳入1 991名15~49岁女性,中心性肥胖、血压升高、血糖升高、TG升高、HDL-C降低、存在≥1项危险因素和危险因素聚集的人数(比例)分别为944(47.4%)、464(23.3%)、123(6.2%)、327(16.4%)、1 025(51.5%)、1 501(75.4%)、874(43.9%)。与15~19岁组相比,25~、30~、35~、40~、45~49岁年龄组中心性肥胖和30~、35~、40~、45~49岁年龄组血压升高的危险性较高,25~29岁血糖升高的危险性较低,45~49岁存在≥1项危险因素和聚集的危险性较高。BMI≥24.0 kg/m2者中心性肥胖、血压升高、血糖升高、TG升高、HDL-C降低、存在≥1项危险因素和危险因素聚集的危险性分别是BMI 18.5~24.0 kg/m2者的14.16、3.05、2.46、2.49、2.42、9.79、7.39倍。西部地区15~49岁女性血糖升高、TG升高和东部地区血压升高、血糖升高的危险性高于中部地区。未发现收入水平、城乡地区与各代谢性危险因素及聚集存在显著关联。结论 年龄、BMI水平和地域分布是心血管代谢性危险因素的主要影响因素,建议针对危险因素的不良变化采取精确的防控措施。
英文摘要:
      Objective To analyze the prevalence, co-prevalence of cardiovascular metabolic (CM) risk factors in women aged 15-49 years in China, and describe the influence of social economic factors on them. Methods The project data of Nutritional Status and Health Transition of Chinese Residents in 2015 were used. The changes in epidemiological characteristics of central obesity, elevated blood pressure, FPG and TG, decreased HDL-C and co-prevalence of the risk factors in women aged 15-49 years were analyzed. According to the definition of the metabolic syndrome released by the International Diabetes Federation in 2005, five cardio-metabolic risk factors appeared as central obesity, increased triglycerides, decreased HDL-C, increased blood pressure and increased plasma glucose. Co-prevalence of risk factors was defined as detecting 2 or more risk factors in a person at the same time. Multivariate logistic regression model was used to analyze the relationship between socioeconomic factors and metabolic risk factors. Results In 2015, in women aged 15-49 years in 15 provinces, the detection number (rates) of central obesity, elevated blood pressure, FPG and TG, decreased HDL-C, at least one CM risk factor and co-detection rate of CM risk factors were 944 (47.4%), 464 (23.3%), 123 (6.2%), 327 (16.4%), 1 025 (51.5%), 1 501 (75.4%), and 874 (43.9%), respectively. Compared with women aged 15-19 years, the women in age group of 25-, 30-, 35-, 40-, and 45-49 years were more likely to have central obesity (P < 0.05), the women in age group of 30-35-, 40-, and 45-49 years were more likely to have elevated blood pressure (P < 0.05), the women aged 45-49 years were more likely to be affected by one or more CM risk factors (P < 0.05), but the women in age group 25-29 years group had lower risk for elevated FPG (P < 0.05). The odds of having central obesity, elevated blood pressure, FPG and TG, decreased HDL-C, at least one CM risk factor and co-prevalence of CM risk factors in women with BMI ≥ 24.0 kg/m2 were 14.16, 3.05, 2.46, 2.49, 2.42, 9.79 and 7.39 times higher than those in the women with BMI of 18.5-24.0 kg/m2, respectively. The odds of having elevated FPG and TG in women aged 15-49 years in western China and the odds of having elevated blood pressure and FPG in women aged 15-49 years in eastern China were significantly higher than those in central China. No significant correlations were found between the prevalence and co-prevalence of CM risk factors and income level or urban and rural area residences in women aged 15-49 years. Conclusions Age, BMI level and living area were the major influencing CM risk factors. The precise prevention and control measures should be taken in time for the adverse changes in CM risk factor prevalence.
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