DOI: 10.1590/1413-81232018238.18692016 2523 Socioeconomic factors and risk for hospitalisation due to asthma ARTICLE ARTIGO in children in the municipalities of Mato Grosso State, Brazil Fatores socioeconômicos e risco para a hospitalização por asma em crianças em municípios de Mato Grosso, Brasil Elaine Cardoso de Oliveira Souza 1 Emerson Soares dos Santos 2 Antonia Maria Rosa 3 Clóvis Botelho 4 Abstract This ecological study used data accu- Resumo Trata-se de um estudo ecológico com mulated between 2001 and 2012 hospital ad- dados de hospitalizações de crianças menores de missions of children under five years of age with cinco anos de idade com asma, entre 2001 a 2012, asthma in 141 municipalities in the Mato Grosso. nos 141 municípios do estado de Mato Grosso, Hospital data were extracted from the SIH/SUS com o objetivo de analisar a distribuição e o risco system, and hospitalisation rates were estimat- de hospitalização por esse problema em crianças ed using the Bayesian inference method. SaTS- no estado de Mato Grosso. Os dados hospitalares can software was used for the calculation of the foram extraídos do SIH/SUS e as taxas de inter- relative risk (RR). Differences in socioeconomic nação foram estimadas por meio do método de in- characteristics among municipalities with high ferência bayesiana. Para realização do cálculo do and low hospitalization rates were evaluated by risco relativo (RR) utilizou-se a técnica de varre- nonparametric Wilcoxon-Mann-Whitney test. dura espacial, com o software SatScan. Diferenças This test indicates that municipalities with better de características socioeconômicas entre municí- socioeconomic characteristics have lower hospital- pios com altas e com baixas taxas de hospitaliza- ization rates. The analysis of the linear models in ção foram avaliadas pelo teste não paramétrico de the two study periods indicated that the decreas- Wilcoxon-Mann-Whitney. Avaliou-se que mu- 1 Instituto de Saúde ing trend in the number of admissions was 3-fold nicípios com características socioeconômicas me- Coletiva, Faculdade higher in the 2005-2012 period compared with the lhores têm menores taxas de hospitalização. Além de Ciências da Saúde, Universidade Federal de 2001-2004 period. In addition, a decrease of 76% disso, foi verificada uma redução de 76% ao longo Mato Grosso (UFMT). in the hospitalisation incidence rate was observed de doze anos, mais evidenciada a partir de 2005. Av. Fernando Corrêa da during the 12-year study period; this decrease was Os municípios identificados com maior risco de Costa 2367, Boa Esperança. 78060-900 Cuiabá MT more evident from 2005 onward. The municipal- hospitalização de crianças por asma localizam-se Brasil. elaineoliveira_fisio@ ities identified as having increased risk of hospi- em áreas com intensa atividade de queimadas e hotmail.com talisation of children with asthma were located in baixo índice de desenvolvimento municipal. 2 Departamento de Geografia, Instituto de areas subjected to intense burning practices and Palavras-chave Asma, Risco relativo, Análise es- Geografia, História e with low municipal development indices. pacial, Criança Documentação, UFMT. Key words Asthma, Relative risk, Spatial ana- 3 Faculdade de Ciências da Saúde, Universidade do lyst, Child Estado de Mato Grosso. Cuiabá MT Brasil. 4 Faculdade de Medicina, UFMT. Cuiabá MT Brasil. 2524 et al. 9 Souza ECO Introduction inhabitants , and the study units consisted of the 141 municipalities in the state. Asthma is a chronic and multifactorial disease The study was conducted between 2001 and resulting from a complex interaction between 2012, and the cases investigated were the records genetic, socioeconomic, and environmental fac- of hospitalisation after the diagnosis of asthma tors1. in children living in these municipalities aged 4 The need for hospitalization suggests lack of years, 11 months, and 29 days until the date of disease control because of difficulties in treat- admission. The objective of this paper is not to ment, and increased exposure to risk factors that identify homogenous areas or the formation of trigger complications. In addition to causing high-risk groups of municipalities, instead, we considerable suffering and harm for the child aimed at identifying local-level associations be- and his/her family, the hospitalisation is costly tween social characteristics and asthma-related and can often be prevented via environmental hospitalizations scenarios by choosing munici- control measures, education of patients and their palities as units of areas for our analysis. families, and adequate drug therapy1. The demographic data used in this study The main risk factors for hospitalisation are were obtained from the Brazilian Institute of acute respiratory infections, being under five Geography and Statistics (Instituto Brasileiro de years of age, asthma severity, climatic factors, and Geografia e Estatística-IBGE), whereas the hos- exposure to environmental pollution2-6. All these pitalisation data were obtained from the Hospital characteristics are geographically heterogeneous, Information System of the Unified Health System with existence of areas that add favorable condi- (Sistema de Informações Hospitalares do Sistema tions for infection and subsequent worsening of Único de Saúde-SIH/SUS). The Authorisations asthma in children. of Hospital Admissions (Autorizações de Inter- In this context, understanding the spatial nações Hospitalares-AIH) that covered short distribution of hospitalisation of children with stay, paid, and non-elective hospitalisations were asthma in Mato Grosso may be important for used and clustered by municipality in the state of the implementation of public policies and health Mato Grosso according to the place of residence. surveillance strategies by providing information The AIH classified as asthma-related morbidities that can support the planning of actions aimed (ICD-10: J45.0, J45.1, J45.8, and J45.9) and diag- at expanding the control of asthma in priority nosed in children under five years of age in the geographic areas. The identification and char- period between 2001 and 2012 were included. acterization of these areas can be performed by scanning spatiotemporal Scan, that can be exe- Risk relative analysis cuted in SaTScan software7, which calculates the and spatiotemporal analysis relative risk of occurrence of an event within a study area. Epidemiologists worldwide use this For data analysis and calculation of the rel- software to describe spatial clusters of infectious ative risk (RR) with a significance level of 99%, and chronic diseases, disease vectors, and risk SaTScan software was used, available at www. factors8. satscan.org. Considering that the rate of hospitalisation In this software, the area is associated with for asthma is an indicator of disease severity and a single point in a polygon, designated the cen- of the success of disease control, this study aimed troid. The RR is calculated as the observed num- to assess the spatial distribution and the risk of ber of cases divided by the expected number of hospitalisation of children with asthma in Mato cases. RR > 1 indicates that the observed number Grosso according to the place of residence. of cases is greater than the expected value. The Relative Risk is a relative associations measure is based on the force of association that has been Methods commonly used in epidemiological studies10. Sta- tistical significance was defined in terms of a p This descriptive, epidemiological, and ecological value (0.05)11. study was conducted to assess the relative risk of To calculate the RR, data on the population hospitalisation of children with asthma in differ- profile, number of cases (adjusted for gender), ent municipalities. The study was conducted in and plane coordinates (Lambert Conformal Con- the state of Mato Grosso, located in the midwest ic Projection: Central Meridian: W56.0; Latitude region of Brazil, with a population of 3,182,113 of Origin: S13.0, Metric units) of the centroid of 2525 Ciência & Saúde Coletiva, 23(8):2523-2532, 2018 23(8):2523-2532, Coletiva, & Saúde Ciência each municipality were used. The Poisson proba- Terraview 4.1.0 software13 was used to pre- bility model was used, which involves the analysis pare maps of the spatial distribution of hospital- of count data, i.e., takes into account the number isation rates and RR, which analysed the digital of individuals with a certain disease12. Because grid of municipal boundaries provided by IBGE of the high amount of records during the years for the year 20129. of 2003 and 2004, in addition to the new type of data behavior started in 2005, in contrast to the Analysis of the socioeconomic previous years, the historical series have been di- characteristics of municipalities vided in two periods. The first period correspond to the years of 2001 to 2004 and the second pe- For analysis of the socioeconomic character- riod refers to 2005 to 2012. The data regarding istics of each municipality, the FIRJAN Index of both periods were analyzed separately. Municipal Development (Índice FIRJAN de De- The hospitalization rates for each city were senvolvimento Municipal-IFDM) was used. This estimated through the Bayesian inference meth- index is a composite indicator that assesses the od by using the Empirical Local Bayesian Model, level of regional socioeconomic development which estimates one rate for each city taking into using a simple average of the results obtained in account the values of neighbor municipalities, each of the three main areas of human develop- conducted with TerraView 4.1.0 software13. The ment: employment and income, education, and use of this technique decreases the reliability on health. The IFDM was created by the Federation the rate observed in the case of reduced popula- of Industries of Rio de Janeiro and is published tions14, however, its use diminishes the random annually; this index is analysed at the municipal fluctuation, caused majorly by great differences level and has a national coverage. The IFDM in- among the populations in the municipalities an- dex varies between 0 and 1 such that the closer to alyzed enabling to compare the municipalities, 1 the value is, the better the development index16.