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      Challenge of ending TB in China: tuberculosis control in primary healthcare sectors under integrated TB control model–a systematic review and meta-analysis

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          Abstract

          Background

          China has the third-largest burden of tuberculosis (TB) cases in the world with great challenges towards ending TB. Primary health care (PHC) sectors play a critical role in TB prevention and control in communities under the Chinese integrated TB control model. However, there is a lack of comprehensive review of research evidence on TB control in PHC sectors under the integrated TB control model in China.

          Methods

          This review was conducted following the PRISMA guidelines. Articles published from 2012 to January 2022 were searched from four international and three Chinese databases. Studies conducted inside mainland China and relevant with TB control service in PHC sectors under the integrated model were included. After study selection, data extraction, and quality assessment, the meta-analysis was performed with RevMan using a random-effect model.When I 2 was more than 50%, subgroup analysis was performed to explore possible reasons for heterogeneity. We also conducted a post hoc sensitivity analysis for outcomes after meta-analysis by exclusion of studies with a high risk of bias or classified as low quality.

          Results

          Forty-three studies from 16 provinces/municipalities in China were included in this review, and most studies included were of medium quality. PHC sectors in East China delivered TB control service better overall than that in West China, especially in tracing of patients and TB case management (TCM). In meta-analyses, both the pooled arrival rate of tracing and pooled TCM rate in East China were higher than those in West China. TB patients had a low degree of willingness to receive TCM provided by healthcare workers in PHC sectors nationwide, especially among migrant TB patients. There were 9 studies reporting factors related to TB control service in PHC sectors, 6 (2 in East and 4 in West China) of which indentified several characteristics of patients as associated factors. The context of PHC sectors was demonstrated to influence delivery of TB control service in PHC sectors in 5 studies (3 in East, 1 in Middle and 1 in West China). Most studies on strategies to promoting TB control services in PHC sectors were conducted in East China and some of these studies identified several online and offline interventions and strategies improving patients’ treatment compliance [pooled OR (95% CI): 7.81 (3.08, 19.19] and awareness of TB [pooled OR (95% CI): 6.86 (2.16, 21.72)].

          Conclusion

          It is of urgent need to improve TB control in PHC sector in China, particularly in West China. Formative and implementation research with rigorous design are necessary to develop comprehensive, context-specific, and patient-centered TB control strategies to promote ending TB in China.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12889-023-16292-5.

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          Most cited references78

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          Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.

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            Quantifying heterogeneity in a meta-analysis.

            The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity. Copyright 2002 John Wiley & Sons, Ltd.
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              The Combination of Estimates from Different Experiments

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                Author and article information

                Contributors
                hcjwyhws@163.com
                lilyliying2012@163.com
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                11 January 2024
                11 January 2024
                2024
                : 24
                : 163
                Affiliations
                [1 ]Department of Social Medicine and Health Service Management, College of Preventive Medicine, Army Medical University (Third Military Medical University), ( https://ror.org/05w21nn13) No. 30 Gaotanyan Road, Shapingba District, Chongqing, 400038 China
                [2 ]GRID grid.410570.7, ISNI 0000 0004 1760 6682, Army Medical University (Third Military Medical University), ; Chongqing, China
                Article
                16292
                10.1186/s12889-023-16292-5
                10785344
                38212753
                41826491-b0f2-48d3-871d-aa1f01cd09b5
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 29 December 2022
                : 11 July 2023
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 81773489
                Funded by: Chongqing outstanding youth project
                Award ID: cstc2020jcyj- jq0035
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2024

                Public health
                tuberculosis,tuberculosis control service,primary health care sector,systematic review

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