Spatial analysis of tuberculosis cure in primary care in Rio de Janeiro, Brazil.
Spatial analysis of tuberculosis cure in primary care in Rio de Janeiro, Brazil.
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DOI：
10.1186/s12889-021-11834-1
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发表时间：
2021-10-12
影响因子：
4.5
通讯作者：
Medronho RA
中科院分区：
文献类型：
--
作者：
Prado Junior JC;Medronho RA
结核病（TB）是一种高疾病负担，被世界卫生组织（WHO）视为全球紧急情况，是成人传染病死亡的主要原因。结核病发病率与获得卫生服务的机会、社会经济决定因素和不平等直接相关。提供初级保健环境可以改善获得服务的机会，缩短病人的等待时间，并加强结核病病例的发现。本文旨在确定2012年至2014年巴西里约热内卢结核病的空间和时间风险区域以及结核病治疗与初级医疗保健覆盖范围之间的关系。在巴西里约热内卢进行了一项横断面研究。纳入了2012年至2014年向疾病通报信息系统（希南）报告的所有结核病病例。还增加了2010年巴西全国人口普查的社会经济变量。社会经济变量采用主因子分析从多变量分析中选择。采用广义加性模型（GAM）验证空间关联性。有可能确定结核病治愈失败风险较高的地区。结核病发病率表现出很强的正空间自相关性。结核病治愈率因学校教育而异（完成中学教育的人比文盲的人有更高的治愈率; OR 1.72，95% CI 1.30-2.29），饮酒（OR 0.47，95% CI 0.35-0.64），接触调查（OR 2.00，95% CI 1.56-2.57），HIV血清学阳性（OR 0.31，95% CI 0.23-0.42），以及老年人发病率较高的人口普查区（OR 9.39，95% CI 1.03-85.26）。与没有初级卫生保健覆盖的人相比，接受初级卫生保健（PHC）覆盖35至41个月的人的治愈几率高出1.64（95% CI 1.07-2.51）。制定了一份全面的风险图，以便采取公共卫生干预措施。空间分析可以确定里约热内卢市结核病治愈率较低的地区。结核病治愈率与初级保健覆盖时间在统计学上相关。结核病治愈率也因社会人口因素而异，如学校教育、酗酒和人口密度。这种方法可以推广到其他领域和/或其他公共卫生问题。我们研究了巴西社会不平等地区的标准化城市结核病治愈率。结核病发病率表现出很强的正空间自相关性。较高的发病率与人口密度和社会经济条件有关。不识字的人不太可能治愈结核病。患有艾滋病毒和酗酒的人治愈结核病的可能性较小。在初级保健覆盖率高的地区，结核病治愈率较高。
Tuberculosis (TB) presents a high burden of disease and is considered a global emergency by the World Health Organization (WHO), as the leading cause of death from infectious disease in adults. TB incidence is related directly to access to health services and socioeconomic determinants and inequality. Providing primary care settings can lead to improved access, shorter waiting times for patients, and enhanced TB case detection. The article aims to identify the spatial and temporal risk areas for TB and the relationship between TB cure and primary healthcare coverage from 2012 to 2014 in Rio de Janeiro, Brazil. A cross-sectional study was conducted in Rio de Janeiro, Brazil. All cases of TB reported to the Information System on Diseases of Notification (SINAN) from 2012 to 2014 were included. Socioeconomic variables from the 2010 Brazilian national census were also added. Socioeconomic variables were selected from multivariate analysis using principal factors analysis. Spatial association was verified with generalized additive model (GAM). It was possible to identify areas at higher risk of failure to cure TB. TB rates showed strong positive spatial autocorrelation. TB cure rate varied according to schooling (individuals with complete secondary schooling had higher cure rates than illiterate individuals; OR 1.72, 95% CI 1.30–2.29), alcohol consumption (OR 0.47, 95% CI 0.35–0.64), contact investigation (OR 2.00, 95% CI 1.56–2.57), positive HIV serology (OR 0.31, 95% CI 0.23–0.42), and census tracts with higher elderly rates (OR 9.39, 95% CI 1.03–85.26). Individuals who had been covered by primary healthcare (PHC) for 35 to 41 months had 1.64 higher odds of cure, compared to those with no PHC coverage (95% CI 1.07–2.51). A comprehensive risk map was developed, allowing public health interventions. Spatial analysis allowed identifying areas with lower odds of TB cure in the city of Rio de Janeiro. TB cure was associated statistically with time of coverage by primary healthcare. TB cure rate also varied according to sociodemographic factors like schooling, alcohol abuse, and population density. This methodology can be generalized to other areas and/or other public health problems. We studied standardized municipal TB cure rates in an area of social inequality in Brazil. TB rates showed strong positive spatial autocorrelation. Higher rates were associated with population density and socioeconomic conditions. Illiterate individuals were less likely to achieve TB cure. TB cure was less likely in individuals with HIV and alcohol abuse. TB cure was greater in areas with high primary healthcare coverage.
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