{"title":"自我报告的肺结核发病率：揭示泰米尔纳德邦各地区的空间代表性。","authors":"Malaisamy Muniyandi, Kavi Mathiyazhagan, Nagarajan Karikalan","doi":"10.1093/inthealth/ihae072","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The objective of the current study was to estimate the self-reported individual-level crude prevalence and cluster-level adjusted prevalence of TB for the districts of Tamil Nadu and to understand the spatial distribution of TB cases through spatial autocorrelation and hotspot analysis.</p><p><strong>Methods: </strong>National Family Health Survey (NFHS) data, gathered during 2014-2015 (NFHS-4) and 2019-2021 (NFHS-5), were used in the current study to estimate district-wise, individual-level crude and cluster-level adjusted TB prevalence per 100 000 population in Tamil Nadu. This was illustrated with the help of spatial geographic representation for various districts of Tamil Nadu using SPSS and QGIS software. The spatial autocorrelation and hotspot analysis were performed using Geoda software.</p><p><strong>Results: </strong>The overall self-reported individual-level crude prevalence of TB was 337 (95% CI 302 to 375) and 169 (95% CI 144 to 197) per 100 000 population, whereas the cluster-level adjusted prevalence of TB was 356 (95% CI 311 to 405) and 184 (95% CI 154 to 219) per 100 000 population in NFHS-4 and NFHS-5, respectively.</p><p><strong>Conclusions: </strong>This study highlights those geographical areas with high rates of TB prevalence. This information would be useful for the state and district programme managers to identify areas of high TB prevalence where interventions can be focused.</p>","PeriodicalId":49060,"journal":{"name":"International Health","volume":" ","pages":""},"PeriodicalIF":2.3000,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Self-reported prevalence of tuberculosis: unveiling spatial representation in the districts of Tamil Nadu.\",\"authors\":\"Malaisamy Muniyandi, Kavi Mathiyazhagan, Nagarajan Karikalan\",\"doi\":\"10.1093/inthealth/ihae072\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The objective of the current study was to estimate the self-reported individual-level crude prevalence and cluster-level adjusted prevalence of TB for the districts of Tamil Nadu and to understand the spatial distribution of TB cases through spatial autocorrelation and hotspot analysis.</p><p><strong>Methods: </strong>National Family Health Survey (NFHS) data, gathered during 2014-2015 (NFHS-4) and 2019-2021 (NFHS-5), were used in the current study to estimate district-wise, individual-level crude and cluster-level adjusted TB prevalence per 100 000 population in Tamil Nadu. This was illustrated with the help of spatial geographic representation for various districts of Tamil Nadu using SPSS and QGIS software. The spatial autocorrelation and hotspot analysis were performed using Geoda software.</p><p><strong>Results: </strong>The overall self-reported individual-level crude prevalence of TB was 337 (95% CI 302 to 375) and 169 (95% CI 144 to 197) per 100 000 population, whereas the cluster-level adjusted prevalence of TB was 356 (95% CI 311 to 405) and 184 (95% CI 154 to 219) per 100 000 population in NFHS-4 and NFHS-5, respectively.</p><p><strong>Conclusions: </strong>This study highlights those geographical areas with high rates of TB prevalence. This information would be useful for the state and district programme managers to identify areas of high TB prevalence where interventions can be focused.</p>\",\"PeriodicalId\":49060,\"journal\":{\"name\":\"International Health\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2024-10-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Health\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1093/inthealth/ihae072\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/inthealth/ihae072","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Self-reported prevalence of tuberculosis: unveiling spatial representation in the districts of Tamil Nadu.
Background: The objective of the current study was to estimate the self-reported individual-level crude prevalence and cluster-level adjusted prevalence of TB for the districts of Tamil Nadu and to understand the spatial distribution of TB cases through spatial autocorrelation and hotspot analysis.
Methods: National Family Health Survey (NFHS) data, gathered during 2014-2015 (NFHS-4) and 2019-2021 (NFHS-5), were used in the current study to estimate district-wise, individual-level crude and cluster-level adjusted TB prevalence per 100 000 population in Tamil Nadu. This was illustrated with the help of spatial geographic representation for various districts of Tamil Nadu using SPSS and QGIS software. The spatial autocorrelation and hotspot analysis were performed using Geoda software.
Results: The overall self-reported individual-level crude prevalence of TB was 337 (95% CI 302 to 375) and 169 (95% CI 144 to 197) per 100 000 population, whereas the cluster-level adjusted prevalence of TB was 356 (95% CI 311 to 405) and 184 (95% CI 154 to 219) per 100 000 population in NFHS-4 and NFHS-5, respectively.
Conclusions: This study highlights those geographical areas with high rates of TB prevalence. This information would be useful for the state and district programme managers to identify areas of high TB prevalence where interventions can be focused.
期刊介绍：
International Health is an official journal of the Royal Society of Tropical Medicine and Hygiene. It publishes original, peer-reviewed articles and reviews on all aspects of global health including the social and economic aspects of communicable and non-communicable diseases, health systems research, policy and implementation, and the evaluation of disease control programmes and healthcare delivery solutions.
It aims to stimulate scientific and policy debate and provide a forum for analysis and opinion sharing for individuals and organisations engaged in all areas of global health.
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