摘要
目的：了解重庆市部分离退休干部人群的身体健康状况及发生发展动态，为疾病防治奠定基础。方法：收集2008年1月至2014年7月来我院体检的2942例重庆市离退休干部人群的体检结果，包括体格检查、胸部X光、超声检查、血液生化检查、心电图检查等。不同年份各疾病异常率的比较采用χ2检验。结果：连续7年体检结果显示离退休干部人群主要疾病以前列腺增生（76.56%）、白内障（73.62%）、高血压（52.62%）、血脂异常（52.28%）、心电图改变（41.73%）、甲状腺病变（40.81%）、肝囊肿（27.97%）、肾囊肿（26.15%）、慢支炎肺气肿（20.86%）、高血糖（17.61%）、高尿酸血症（15.67%）为主；除前列腺增生及高尿酸血症疾病外，不同年份各疾病患病率具有统计学意义（P＜0.01），且前列腺增生、甲状腺病变、肝囊肿、肾囊肿和高血糖等疾病随着年龄的增长有增高的趋势；而血脂异常检出率逐年下降。结论：生活行为方式以及年龄的增长是影响离退休干部人群慢性非传染性疾病的主要因素，应加强离退休干部人群的健康管理，有针对性的进行健康干预。
Abstract
Objective:To analyze the health condition, occurrence and development trends of the part of the retired leaders in Chongqing to lay a foundation for the disease prevention and treatment.Methods:The health examination results of 2 942 government retired leaders in Chongqing who had the health examination in our center from January 2008 to July 2014 were collected, which included the physical, X-ray, ultrasonic, blood biochemical, and electrocardiogram examinations, etc. The abnormal rates of the diseases in the different years were compared with the chi-square test.Results: The health examination results of 7 years showed that the major diseases of the retired leaders were prostatic hyperplasia (76.56%), cataract (73.62%), hypertension (52.62%), dyslipidemias (52.28%), electrocardiogram (41.73%), thyroid nodules (40.81%), liver cysts (27.97%), renal cyst (26.15%), chronic bronchitis and emphysema (20.86%), hyperglycemia (17.61%) and hyperuricemia (15.67%). Except prostatic hyperplasia and hyperuricemia, the prevalence of each disease in the different years had the statistical significance (P<0.01), and the prevalence of prostatic hyperplasia, thyroid nodules, liver and kidney cysts and hyperglycemia increased gradually with the age increase, however, the prevalence of dyslipidemias was contrary.Conclusion:The life style behavior and increase of the age are the main factors to inlfuence the chronic non-communicable diseases in the government retired leaders. The health management should be strengthened and the targeted health intervention taken to them.
NETL
NSTL
维普
万方数据