2014—2023年厦门市肺结核时空动态分布及分布与降水量的相关性分析

doi:10.19983/j.issn.2096-8493.20250078

摘要/Abstract

摘要：

目的: 探究2014—2023年福建省厦门市肺结核发病率的时空动态分布特征及分布与降水量的相关性,为优化结核病防控策略提供科学依据。方法: 通过“中国疾病预防控制信息系统”收集厦门市2014年1月1日至2023年12月31日的肺结核(包含结核性胸膜炎)报告发病数据,共20207例。通过“国家科技基础条件平台—国家地球系统科学数据中心—黄土高原分中心”收集厦门市2014年1月至2023年12月的逐月降水量和逐年降水量。采用回顾性空间流行病学分析方法,分别应用卡方趋势检验、曼-肯德尔趋势检验法(Mann-Kendall trend test)对年度发病率、逐年降水量进行趋势分析;用回顾性离散泊松分布时空扫描统计,分析肺结核发病的时空动态分布;用卡方检验和逻辑回归分析(logistic回归)对扫描出的聚集区和非聚集区的逐月降水量进行分析,识别影响因素。统计检验水平均取α=0.05。结果: 2014—2023年,厦门市肺结核年均发病率为40.78/10万(20207/4955600),年度发病率呈下降趋势($\chi_{\text {趋势 }}^2$=253.000,P<0.001);时空扫描检出6个显著性聚集区,覆盖3个区,1、2级集群均为集美区,聚集时间分别为2017年6月至2019年9月[RR=1.52,P<0.001,年平均发病率为60.68/10万(1375/2265917)]和2014年3月至2016年9月,RR=1.33,P<0.001,年平均发病率为53.44/10万(1156/2163200);肺结核发病聚集与逐月降水量高低相关(χ²=5.829,P=0.016),降水量每升高10mm,聚集风险增加2.9%(OR=1.029,95%CI:1.003~1.055)。结论: 厦门市肺结核时空聚集缩减,降水量是肺结核报告发病聚集的影响因素。

关键词: 结核,肺, 流行病学研究, 时空聚类分析, 雨, 回归分析

Abstract:

Objective: With investigating the spatial-temporal dynamic distribution of pulmonary tuberculosis (PTB) incidence in Xiamen City, Fujian Province from 2014 to 2023, and analyzing the precipitation associated with spatiotemporal clustering, to provide a scientific basis for optimizing the strategies for tuberculosis prevention and control. Methods: This retrospective study employed spatial epidemiological methods to analyze the spatiotemporal clustering patterns of PTB in Xiamen from January 1, 2014 to December 31, 2023. A total of 20207 reported PTB (including tuberculous pleurisy) cases were collected through the China Information System for Disease Control and Prevention. The monthly and yearly precipitation data were collected from Loess Plateau Branch of National Earth System Science Data Center, National Science and Technology Infrastructure. The Chi-square trend test and Mann-Kendall trend test were respectively applied to analyze the trend of annual incidence and precipitation. With the retrospective discrete Poisson spatiotemporal scanning statistics, the spatiotemporal dynamics of PTB incidence was analyzed.With the Chi-square test and binary logistic regression analysis, the monthly precipitation in the scanned cluster/non-cluster areas was analyzed to identify the influencing factors.Statistical significance was set as α=0.05. Results: The average annual PTB incidence rate was 40.78 cases per 100000 population (20207/4955600) in Xiamen from 2014 to 2023, showing a generally fluctuating downward trend ($\chi_{\text {trend }}^2$=253.000,P<0.001); From 2014 to 2023, the spatiotemporal scanning statistics scanned 6 significant clusters, covering 3 districts.Both the Level 1 and Level 2 clusters were in Jimei District.The clustering occurred from June 2017 to September 2019 (RR=1.52, P<0.001), with an average annual incidence of 60.68/100000 population (1375/2265917) and from March 2014 to September 2016 (RR=1.33, P<0.001), with an average annual incidence of 53.44/100000 population (1156/2163167), respectively. A positive correlation was observed between monthly precipitation and the clustering of reported PTB incidence (χ²=5.829,P=0.016). For every 10 mm increase in precipitation, the risk of clustering of reported PTB incidence increased by 2.9% (OR=1.029,95%CI:1.003-1.055). Conclusion: The spatiotemporal clustering of PTB in Xiamen has decreased,and precipitation was identified as a factor influencing the clustering of reported PTB incidence in Xiamen.

Key words: Tuberculosis,pulmonary, Epidemiologic Study, Space-time clustering, Rain, Regression analysis

中图分类号:

R521
R181.2

柯然, 郑蓉蓉, 郑春梅, 薛剑航, 刘洵锐, 林伟奇, 李露, 曹红. 2014—2023年厦门市肺结核时空动态分布及分布与降水量的相关性分析[J]. 结核与肺部疾病杂志, 2025, 6(6): 696-702. doi: 10.19983/j.issn.2096-8493.20250078

Ke Ran, Zheng Rongrong, Zheng Chunmei, Xue Jianhang, Liu Xunrui, Lin Weiqi, Li Lu, Cao Hong. Analysis of spatiotemporal distribution dynamics of pulmonary tuberculosis and correlation with precipitation in Xiamen, China (2014—2023)[J]. Journal of Tuberculosis and Lung Disease, 2025, 6(6): 696-702. doi: 10.19983/j.issn.2096-8493.20250078

图/表 6

图1

图2

图3

表1

表2

表3

2014—2023 年厦门肺结核发病聚集与逐月降水量的回归分析

因素	β值	s $x ˉ$ 值	Wald χ²值	P值	OR值	95%CI值
逐月降水量(10mm)	0.029	0.013	4.931	0.026	1.029	1.003~1.055
常量	-1.831	0.168	118.223	0.000	0.160

表3

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聚集区域	聚集时间	区域	报告例数	理论例数	RR值	LLR值	P值
1级	2017/6/1—2019/9/30	集美区	1375	923.81	1.52	100.970	<0.001
2级	2014/3/1—2016/9/30	集美区	1156	883.51	1.33	40.193	<0.001
3级	2014/3/1—2014/10/31	湖里区	396	280.92	1.42	21.217	<0.001
4级	2018/3/1—2020/9/30	湖里区	1290	1090.56	1.20	18.259	<0.001
5级	2017/5/1—2019/7/31	海沧区	603	495.66	1.22	11.156	0.007
6级	2022/3/1—2022/4/30	集美区	114	74.30	1.54	9.140	0.038

月区	低降水量月区 (个数)	高降水量月区 (个数)	χ²值	P值	OR (高水/低水)值	95%CI值
非聚集月区	354	239	5.829	0.016	1.603	1.091~2.355
聚集月区	61	66