Federal University of Rio Grande do Norte. Natal, Rio Grande do Norte, Brazil.
College Nursing at Ribeirão Preto, University of Sao Paulo. Ribeirão Preto, Sao Paulo, Brazil.
J Infect Dev Ctries. 2020 Aug 31;14(8):869-877. doi: 10.3855/jidc.12196.
Tuberculosis (TB) is the primary cause of death among infectious diseases affecting groups in extreme poverty. Social improvements could reverse this situation in Brazil. This study aims to demonstrate the spatial relationship between social development (SD) and TB mortality in Natal, a city in northeastern Brazil.
Ecological study. The study population comprised TB deaths recorded in the Mortality Information System between 2008 and 2014. The units of analysis were 59 human development units (HDUs). Raw and smoothed mortality rates were calculated using the global empirical Bayes method. Primary components analysis was used to develop the SD indicators. An association between TB mortality and SD was verified using multiple linear regression analysis. Spatial autocorrelation was verified using models with global spatial effects. Analyses were performed using Statistica version 12.0, ArcGIS version 10.2, Statistical Package for the Social Sciences version 20.0, and OpenGeoDa 1.0.1. The significance level was established at 5% (p < 0.05).
The TB mortality rate with non-random spatial distribution ranged between 0.52 and 8.90 per 100,000 inhabitants. The spatial lag model was chosen because it presented the highest log-likelihood value, lowest AIC, and highest R2. A negative association was found between TB mortality and SD (R2 = 0.207; p = 0.03).
The results show a negative association between TB mortality and the high SD indicator. This study can support decision-making in terms of collective projects within public health in order to link the health field to other sectors, aiming for social well-being and human development.
结核病（TB）是影响极度贫困人群的传染病死亡的主要原因。社会进步可能会扭转巴西的这种局面。本研究旨在展示巴西东北部城市纳塔尔的社会发展（SD）与结核病死亡率之间的空间关系。
生态研究。研究人群包括 2008 年至 2014 年期间死亡信息系统中记录的结核病死亡人数。分析单位是 59 个人类发展单位（HDU）。使用全局经验贝叶斯法计算原始和平滑死亡率。使用主成分分析来开发 SD 指标。使用具有全局空间效应的多元线性回归分析来验证 TB 死亡率与 SD 之间的关联。使用具有全局空间效应的模型验证空间自相关。使用 Statistica 版本 12.0、ArcGIS 版本 10.2、社会科学统计软件包 20.0 和 OpenGeoDa 1.0.1 进行分析。显著性水平设定为 5%（p < 0.05）。
具有非随机空间分布的结核病死亡率范围在 0.52 至 8.90 每 100,000 居民之间。选择空间滞后模型是因为它具有最高的对数似然值、最低的 AIC 和最高的 R2。发现结核病死亡率与 SD 呈负相关（R2 = 0.207；p = 0.03）。
结果表明结核病死亡率与高 SD 指标之间存在负相关。本研究可以支持公共卫生领域内的集体项目决策，将卫生领域与其他部门联系起来，实现社会福利和人类发展。
