克山病病区居民居住特征对主动监测影响

Effects of residential features on active Keshan disease surveillance in endemic areas

目的探讨克山病病区居民居住特征对克山病监测、病情评估和人口负担等实际问题的影响。方法选择黑龙江省齐齐哈尔市富裕县繁荣乡5个克山病病区村,采用横断面调查方法于2015年12月调查村中户籍人口3 421人及常住人口2 235人。结果繁荣乡5村外出人口占户籍人口的35.4%(1 210人);各年龄组中外出人口占户籍人口比重最大年龄组为25~29岁63.0%(208人)、20~24岁55.9%(138人)、15~19岁50.6%(82人),55~59岁、60~64岁龄组外出人口占户籍人口比重最小,均为13.2%(22/167、29/219)。主动监测的现场应答率为29.9%(669/2 235),其中40~44岁、65~69岁和60~64岁年龄组检查人数占同年龄组常住人口的比重位于前3位,分别是51.4%(92/179)、50.3%(77/153)和50.0%(95/190)。少年人口系数为13.2%(296人),老年人口系数为18.5%(414人),老少比为139.9%。结论克山病病区人口性别和年龄构成扭曲,人口老龄化严重,主动监测的现场应答率低。病区居民居住特征影响主动监测结果,分析数据时应进行调整或标化。

Objective To explore effects of residential features on active Keshan disease（KD） surveillance, prevalence assessment, and population burden in endemic areas. Methods We selected 5 villages in Fanrong country, Heilongjiang province. We collected and analyzed data of 3 421 registered residents and 2 235 permanent residents in December, 2015.Results For the 5 villages, the outflow population accounted for 35.4% of the registered population. The proportion of outflow population was the highest（63.0%） among the registered residents aged 25 – 29 years, followed by the proportions of 55.9% and 50.6% among those aged 20 – 24 and 15 – 19 years; while, the lowest proportion was 13.2% among the registered population aged 55 – 64 years. The overall rate of response to a field survey of active surveillance was 29.9%（669/2 235） among the registered population and the top three response rates to the active surveillance were observed among the registered populations aged 40 – 44（51.4%）, 65 – 69（50.3%）, and 60 – 64 years old（50.0%）. The coefficient of juvenile and elderly population were 13.2% and 18.5%; the ratio of old population to juvenile population was 139.9%. ConclusionSkewed gender and age distribution and severe aging were observed in the population of KD endemic areas; the response rate to filed survey of KD active surveillance was low due to population characteristics in KD endemic areas. The results suggest that adjustment and standardization should be adopted in analyses on the data collected among the populations.