Space-time clustering and associated risk factors of pulmonary tuberculosis in southwest China

• Published in: Infectious diseases of poverty Vol. 7; no. 1; pp. 91 - 11
• Main Authors: Huang, Li, Abe, Eniola Michael, Li, Xin-Xu, Bergquist, Robert, Xu, Lin, Xue, Jing-Bo, Ruan, Yao, Cao, Chun-Li, Li, Shi-Zhu
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 17.08.2018; BioMed Central; BMC
• Subjects: Adolescent; Adult; Antitubercular Agents - therapeutic use; Bronchitis, Chronic - physiopathology; China; China - epidemiology; Cities; Communicable diseases; Female; Health risk assessment; Humans; Infectious diseases; Logistic Models; Male; Middle Aged; Mortality; Mycobacterium tuberculosis - isolation & purification; Outdoor air quality; Poverty; Public health; Pulmonary tuberculosis; Regression analysis; Regression analysis method; Risk Factors; Smoking - physiopathology; Social Class; Socioeconomic factors; Space-Time Clustering; Spatio-Temporal Analysis; Spatio-temporal clustering; Studies; Tuberculosis; Tuberculosis, Pulmonary - diagnosis; Tuberculosis, Pulmonary - drug therapy; Tuberculosis, Pulmonary - epidemiology; Tuberculosis, Pulmonary - transmission; Urban areas; China; Beijing China; Regression analysis method; Spatio-temporal clustering; China; Risk factors; Pulmonary tuberculosis
• ISSN: 2049-9957; 2095-5162; 2049-9957
• DOI: 10.1186/s40249-018-0470-z

Pulmonary tuberculosis (PTB,both smear positive and smear negative) is an airborne infectious disease of major public health concern in China and other parts of the world where PTB endemicity is reported. This study aims at identifying PTB spatio-temporal clusters and associated risk factors in Zhaotong prefecture-level city, located in southwest China, where the PTB notification rate was higher than the average rate in the entire country. Space-time scan statistics were carried out using PTB registered data in the nationwide TB online registration system from 2011 to 2015, to identify spatial clusters. PTB patients diagnosed between October 2015 and February 2016 were selected and a structured questionnaire was administered to collect a set of variables that includes socio-economic status, behavioural characteristics, local environmental and biological characteristics. Based on the discovery of detailed town-level spatio-temporal PTB clusters, we divided selected subjects into two groups including the cases that resides within and outside identified clusters. Then, logistic regression analysis was applied comparing the results of variables between the two groups. A total of 1508 subjects consented and participated in the survey. Clusters for PTB cases were identified in 38 towns distributed over south-western Zhaotong. Logistic regression analysis showed that history of chronic bronchitis (OR = 3.683, 95% CI: 2.180-6.223), living in an urban area (OR = 5.876, 95% CI: 2.381-14.502) and using coal as the main fuel (OR = 9.356, 95% CI: 5.620-15.576) were independently associated with clustering. While, not smoking (OR = 0.340, 95% CI: 0.137-0.843) is the protection factor of spatial clustering. We found PTB specially clustered in south-western Zhaotong. The strong associated factors influencing the PTB spatial cluster including: the history of chronic bronchitis, living in the urban area, smoking and the use of coal as the main fuel for cooking and heating. Therefore, efforts should be made to curtail these associated factors.