文章摘要
王柳森,张兵,王惠君,郭春雷,张一平,张继国,杜文雯,王志宏.中国15个省份农民心血管代谢性危险因素分析[J].中华流行病学杂志,2018,39(9):1239-1243
中国15个省份农民心血管代谢性危险因素分析
Analysis on cardio-metabolic related risk factors in farmers of 15 provinces in China
投稿时间:2017-11-06  
DOI:10.3760/cma.j.issn.0254-6450.2018.09.018
中文关键词: 农民;心血管代谢性危险因素;社会经济因素
英文关键词: Farmer;Cardio-metabolic factor;Socio-economic factor
基金项目:财政拨款项目“中国居民营养状况变迁的队列研究”(13103110700015005)
作者单位E-mail
王柳森 100050 北京, 中国疾病预防控制中心营养与健康所  
张兵 100050 北京, 中国疾病预防控制中心营养与健康所  
王惠君 100050 北京, 中国疾病预防控制中心营养与健康所  
郭春雷 100050 北京, 中国疾病预防控制中心营养与健康所  
张一平 102206 北京, 中国疾病预防控制中心  
张继国 100050 北京, 中国疾病预防控制中心营养与健康所  
杜文雯 100050 北京, 中国疾病预防控制中心营养与健康所  
王志宏 100050 北京, 中国疾病预防控制中心营养与健康所 wangzh@ninh.chinacdc.cn 
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中文摘要:
      目的 分析我国≥18岁农民心血管代谢性危险因素的流行特征及聚集性,并探讨相关影响因素。方法 利用2015年“中国居民营养状况变迁的队列研究”中的人口经济因素、血样检测数据和体格测量数据,选择≥18岁农民共3 367人作为研究对象。采用国际糖尿病联盟(IDF)于2005年发布的定义判定心血管代谢性危险因素,具有≥2个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联性。结果 2015年我国15省(直辖市、自治区)农民中,中心性肥胖、血压升高、血糖升高、血脂升高和HDL-C降低的人群比例分别为51.8%、59.0%、17.0%、25.5%、38.7%。多因素logistic回归分析显示女性中心性肥胖(OR=3.69,95% CI:3.17~4.28)和HDL-C降低(OR=3.28,95% CI:2.81~3.82)的相对危险性高于男性,血压升高(OR=0.73,95% CI:0.63~0.84)、血糖升高(OR=0.80,95% CI:0.67~0.97)的相对危险性低于男性;年龄与代谢性危险因素及聚集性呈显著的正相关(趋势检验,P<0.05)。西部地区的农民中心性肥胖的相对危险性明显低于中部地区农民。未发现农民收入水平、文化程度与代谢性危险因素存在显著关联。结论 我国15省约有85.5%的农民有≥1种心血管代谢性危险因素,约有60%的农民存在危险因素聚集性,农民的性别、年龄与心血管代谢性危险及聚集性存在显著相关性。建议根据分布特征,采取有针对性的营养干预措施及健康宣教,重视人群疾病的初级阶段。
英文摘要:
      Objective To analyze the prevalence and co-prevalence of cardio-metabolic related risk factors in farmers aged ≥ 18 years in China, to explore the influence of population economic factors on them. Methods A total of 3 367 farmers, including fishermen or hunters, aged ≥ 18 years were selected as study subjects from the database of Nutritional Status and Health Transition of Chinese Residents Project in 2015. Basic information (age, gender), data on anthropometric (body height, weight and waist size), blood biochemical and socioeconomic (occupation, income, education level and living area) were included. According to the definition of the metabolic syndrome released by the International Diabetes Federation (IDF) 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 3 367 framers of 15 provinces (autonomous region and municipality), the prevalence rates of central obesity, increased blood pressure, increased plasma glucose, increased triglycerides and decreased HDL-C were 51.8%, 59.0%, 17.0%, 25.5% and 38.7% respectively. Multivariate logistic regression analysis showed that the risks for central obesity (OR=3.69, 95% CI:3.17-4.28) and decreased HDL-C (OR=3.28, 95% CI:2.81-3.82) were higher in women than in men, and the risks for increased blood pressure (OR=0.73, 95% CI:0.63-0.84), increased blood glucose (OR=0.80, 95% CI:0.67-0.97) were lower in women than in men. Age was positively correlated with the prevalence or co-prevalence of metabolic risk factors (trend P<0.05). Framers in western China had obviously lower risk for central obesity compared with farmers in central China. No significant correlation was found between farmers' income level, education level or the prevalence of metabolic risk factors. Conclusion In 15 provinces of China, the prevalence of at least 1 kind of cardio-metabolic risk factor was found in 85.5% of the farmers, and the co-prevalence of cardio-metabolic risk factor was found in 60% of farmers. The prevalence and co-prevalence of cardio-metabolic risk factors were significantly associated with age and gender. It is suggested to take targeted nutritional intervention and health education according to the distribution characteristics of prevalence and co-prevalence of cardio-metabolic factors and strengthen the early prevention and control programs of the diseases.
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