江苏省南京市5个行业人群健康体检中代谢相关性疾病的分析

Analysis of metabolism-related diseases in people of five industries with physical examinations in Nanjing City of Jiangsu Province

  • 摘要: 目的 分析江苏省南京市9年5个行业高血压、高血脂、高尿酸、高血糖4类代谢相关性疾病的检出率及变化趋势。 方法 通过江苏省南京市体检数据库,筛选江苏省南京市2008年—2016年公安系统、教育系统、医疗卫生系统、机关单位、事业单位体检人群有关血压、血糖、血脂、尿酸的数据,并进行回顾性分析。 结果 共纳入206 293体检人次,其中男136 732人次(66.28%), 女69 561人次(33.72%)。男性与女性代谢相关疾病指标异常检出率的前4位顺序有差异;高血脂、高血压及高尿酸主要集中于<40岁人群及≥65岁人群; 高血糖主要集中于≥50岁的人群。公安系统高血脂、高血压、高血糖及高尿酸的异常检出率显著高于其他4个行业(P<0.01)。 结论 高血脂、高血压、高血糖、高尿酸在该体检人群的不同性别、不同年龄、不同行业间检出率均有显著差异。因此,应结合性别、年龄及行业特点,调整医疗资源和服务方向,优化体检方案。

     

    Abstract: Objective To analyze the detection rates of hypertension, hyperlipidemia, hyperuricemia and hyperglycemia in five industries in Nanjing City in nine years and changes in trend. Methods Based on the physical examination database of Nanjing City of Jiangsu Province, the data related to blood pressure, blood glucose, blood lipid and uric acid from 2008 to 2016 in the physical examination data in public security system, education system, medical and health system, government department and public insititutions in Nanjing City of Jiangsu Province were screened for retrospective analysis. Results A total of 206 293 people were included in the physical examination, including 136 732 men(66.28%), and 69 561 women(33.72%). The top four abnormal detection rates of metabolic related diseases in men and women showed a difference in order. High blood fat, high blood pressure and high uric acid were mainly concentrated in the population group aged <40 years and ≥65 years; hyperglycemia was mainly concentrated in group aged ≥50 years. The abnormal detection rates of hyperlipidemia, hypertension, hyperglycemia and hyperuricemia in the public security system were significantly higher than those in other four industries(P<0.01). Conclusion The detection rates of hyperlipidemia, hypertension, hyperglycemia and hyperuricemia are different in different genders, ages and industries. Therefore, we should adjust the direction of medical resources and services, and optimize the physical examination program according to features of gender, age and industries.

     

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