巴西无家可归者中结核病治疗中断的趋势和群集:个人、社会和方案因素的影响。

IF 2
Gabriel Pavinati, Lucas Vinícius de Lima, Melisane Regina Lima Ferreira, Simone Teresinha Protti Zanatta, Gabriela Tavares Magnabosco
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引用次数: 0

摘要

目的:分析巴西无家可归人群结核病治疗中断指标的时间趋势和州级聚类。方法:这是一项生态学研究,评估2015年至2023年无家可归者结核病患者的治疗中断情况。采用联结点回归进行趋势分析,按社会人口学和流行病学变量分层。基于社会经济和规划指标,通过k-均值聚类分析确定了州集群。结果:男性结核病治疗中断增加(平均季度百分比变化- AQPC=0.15;95%置信区间- 95% ci 0.04-0.29), 40-59岁个体(AQPC=0.38;95%CI 0.25-0.53)、吸烟者(AQPC=0.72;95%CI 0.61-0.82),社会项目受益人(AQPC=4.59;95%CI 3.69 ~ 6.02),无直接观察治疗组(AQPC=0.49;95%CI 0.39-0.63),无HIV合并感染(AQPC=0.38;95%CI 0.30-0.51),北部地区(AQPC=1.51;95%CI 0.96-2.21)和Midwest (AQPC=0.83;95%CI 0.17-1.59)。聚类分析显示,聚类A治疗中断率最低,艾滋病发病率低,规划指标较好。B组贫困率高,教育水平和收入水平低,但初级卫生保健表现较好。C组因其更高的人类发展水平、更好的社会指标和更低的不平等而脱颖而出。D类集中了最坏的结果:治疗中断率更高、不平等程度更大、艾滋病发病率更高、初级卫生保健更弱。结论:巴西无家可归者在获得和接受结核病治疗方面存在明显的社会经济和方案不平等。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Trends and clusters of tuberculosis treatment interruption among people experiencing homelessness in Brazil: influence of individual, social and programmatic factors.

Objective: To analyze temporal trends and state-level clusters of tuberculosis treatment interruption indicators among the homeless population in Brazil.

Methods: This is an ecological study, in which treatment interruption among homeless people with tuberculosis was assessed from 2015 to 2023. Joinpoint regression was used for trend analysis, stratified by sociodemographic and epidemiological variables. State clusters were identified by k-means clustering analysis, based on socioeconomic and programmatic indicators.

Results: Tuberculosis treatment interruption increased among: men (average quarterly percent change - AQPC=0.15; 95% confidence interval - 95%CI 0.04-0.29), individuals aged 40-59 years (AQPC=0.38; 95%CI 0.25-0.53), tobacco users (AQPC=0.72; 95%CI 0.61-0.82), beneficiaries of social programs (AQPC=4.59; 95%CI 3.69-6.02), those without directly observed treatment (AQPC=0.49; 95%CI 0.39-0.63), without HIV coinfection (AQPC=0.38; 95%CI 0.30-0.51), and in the North (AQPC=1.51; 95%CI 0.96-2.21) and Midwest (AQPC=0.83; 95%CI 0.17-1.59) regions. According to the cluster analysis, cluster A had the lowest treatment interruption rate, low AIDS incidence, and better programmatic indicators. Cluster B had high poverty and low level of education and income, but strong primary health care performance. Cluster C stood out for its higher human development, better social indicators, and lower inequality. Cluster D concentrated the worst outcomes: higher treatment interruption, greater inequality, higher AIDS incidence, and weaker primary health care.

Conclusion: Socioeconomic and programmatic inequalities were evident in access and attachment to tuberculosis treatment among people experiencing homelessness in Brazil.

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