Space–Time Clustering and Socioeconomic Factors Associated with Mortality from Diarrhea in Alagoas, Northeastern Brazil: A 20-Year Population-Based Study
Abstract
:1. Introduction
2. Materials and Methods
2.1. Design and Study Area
2.2. Data Source and Collection
2.3. Variables and Indicators
- Number of deaths from diarrhea and gastroenteritis registered in the 102 municipalities of Alagoas, and categorized according to the sociodemographic variables of sex, age group, ethnicity or color, and educational level.
- Annual gross mortality rates by municipality, inland municipality, and metropolitan area per 100,000 inhabitants (we considered the number of annual deaths as the numerator and the corresponding population as the denominator).
- Average mortality rates by municipality and in the state of Alagoas per 100,000 inhabitants (we considered the number of total deaths as the numerator and the central population of the period as the denominator, divided by the number of selected years).
- Proportion of municipalities with diarrhea- and gastroenteritis-related deaths.
2.4. Temporal Trend Analysis
2.5. Spatial Analysis of Mortality Rates from Diarrhea and Gastroenteritis in Alagoas
2.6. Space–Time Scanning Analysis and Identification of Risk Clusters
2.7. Correlation Analysis between Deaths from Diarrhea and Gastroenteritis and SDH
2.8. Ethical Considerations
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- WHO World Health Organization. Diarrhoeal Disease. Published 2017. Available online: https://www.who.int/news-room/fact-sheets/detail/diarrhoeal-disease (accessed on 3 May 2021).
- Bühler, H.F.; Ignotti, E.; da Neves, S.M.A.S.; Hacon, S.S. Análise espacial de indicadores integrados determinantes da mortalidade por diarreia aguda em crianças menores de 1 ano em regiões geográficas. Cien Saude Colet. 2014, 19, 4131–4140. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Scallan, E.; Crim, S.M.; Runkle, A.; Henao, O.L.; Mahon, B.E.; Hoekstra, R.M.; Griffin, P.M. Bacterial Enteric Infections Among Older Adults in the United States: Foodborne Diseases Active Surveillance Network, 1996–2012. Foodborne Pathog. Dis. 2015, 12, 492–499. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Marmot, M.; Bell, R. Social inequalities in health: A proper concern of epidemiology. Ann. Epidemiol. 2016, 26, 238–240. [Google Scholar] [CrossRef] [PubMed]
- Melli, L.C.F.L.; Waldman, E.A. Tendência temporal e desigualdades na mortalidade por diarreias em menores de 5 anos. J. Pediatr 2009, 85, 21–27. [Google Scholar] [CrossRef]
- Rufino, R.; Gracie, R.; Sena, A.; de Freitas, C.M.; Barcellos, C. Surtos de diarreia na região Nordeste do Brasil em 2013, segundo a mídia e sistemas de informação de saúde—Vigilância de situações climáticas de risco e emergências em saúde. Cien Saude Colet. 2016, 21, 777–788. [Google Scholar] [CrossRef] [Green Version]
- Santos, C.B.; Araújo, K.C.G.; Jardim-Botelho, A.; Santos, M.B.; Rodrigues, A.; Dolabella, S.S.; Gurgel, R.Q. Diarrhea incidence and intestinal infections among rotavirus vaccinated infants from a poor area in Brazil: A spatial analysis. BMC Public Health 2014, 14, 399. [Google Scholar] [CrossRef] [Green Version]
- Imada, K.S.; de Araújo, T.S.; Muniz, P.T.; de Pádua, V.L. Socioeconomic, hygienic, and sanitation factors in reducing diarrhea in the Amazon. Rev. Saude Publica 2016, 50, 1–11. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Bern, C.; Martines, J.; de Zoysa, I.; Glass, R.I. The magnitude of the global problem of diarrhoeal disease: A ten-year update. Bull. World Health Organ. 1992, 70, 705–714. [Google Scholar]
- NCI—NÚCLEO CIÊNCIA PELA INFÂNCIA. Impactos Da Estratégia Saúde Da Família e Desafios Para o Desenvolvimento; NCPI: São Paulo, Brazil, 2019. Available online: https://ncpi.org.br/wp-content/uploads/2020/03/NCPI-WP_5.pdf (accessed on 1 October 2022).
- Datasus, Sistema de Informação Sobre Mortalidade. Estatísticas Vitais—Mortalidade por Diarreia e Gastroenterite Infecsiosa—Brasil/Óbitos por Residência (1996–2019). Published 2020. Available online: http://tabnet.datasus.gov.br/cgi/deftohtm.exe?sim/cnv/obt10uf.def (accessed on 20 January 2021).
- Mendes, P.S.d.A.; Ribeiro, H.d.C.; Mendes, C.M.C. Temporal trends of overall mortality and hospital morbidity due to diarrheal disease in Brazilian children younger than 5 years from 2000 to 2010. J. Pediatr. (Rio J). 2013, 89, 315–325. [Google Scholar] [CrossRef] [Green Version]
- IBGE. Instituto Brasileiro de Geografia e Estatística—Brasil, Alagoas, Panorama. Available online: https://cidades.ibge.gov.br/brasil/al/panorama (accessed on 20 January 2021).
- Lopes, F.C.; Sousa, G.G.D.S.; Silva, W.M.D.; Costa, A.C.P.J.; Santos, F.S.; Pascoal, L.M.; Santos Neto, M. Spatial-temporal analysis of leprosy in a priority Brazilian northeast municipality for disease control. Rev. Bras. Enferm. 2021, 74, e20201101. [Google Scholar] [CrossRef]
- Sousa, L.C.; Silva, T.C.; Ferreira, T.F.; Caldas, A.J.M. Spatial analysis of AIDS in the state of Maranhão: An ecological study 2011–2018. Rev. Bras. Enferm. 2021, 75, e20210131. [Google Scholar] [CrossRef]
- Dias, B.R.L.; Rodrigues, T.B.; Botelho, E.P.; Oliveira, M.F.V.; Feijão, A.R.; Polaro, S.H.I. Integrative review on the incidence of HIV infection and its socio-spatial determinants. Rev. Bras. Enferm. 2021, 74, e20200905. [Google Scholar] [CrossRef]
- Souza, K.O.C.; Fracolli, L.A.; Ribeiro, C.J.N.; Menezes, A.F.; Silva, G.M.; Santos, A.D.D. Quality of basic health care and social vulnerability: A spatial analysis. Rev. Esc Enferm USP. 2021, 55, e20200407. [Google Scholar] [CrossRef] [PubMed]
- IBGE. Instituto Brasileiro de Geografia e Estatística. Portal Cidades e Estados. Published 2021. Available online: http://www.ibge.gov.br/home (accessed on 30 July 2020).
- PNUD. Programa das Nações Unidas Para o Desenvolvimento. Atlas do Desevolvimento Humano no Brasil. Published 2021. Available online: http://www.atlasbrasil.org.br/ (accessed on 10 January 2021).
- IPEA. Instituto de Pesqisa Econômica Aplicada. Atlas da Vulnerabilidade Social nos Municípios Brasileiros. Published 2021. Available online: http://ivs.ipea.gov.br/index.php/pt (accessed on 22 January 2021).
- Antunes, J.L.F.; Cardoso, M.R.A. Uso da análise de séries temporais em estudos epidemiológicos. Epidemiol e Serviços Saúde. 2015, 24, 565–576. [Google Scholar] [CrossRef]
- Brasil, Ministério da Saúde. Sistemas de Informações Geográficas e Análise Espacial Na Saúde Pública. 2a. Fundação Oswaldo Cruz. 2007. Available online: https://ares.unasus.gov.br/acervo/html/ARES/1198/1/livro_2.pdf (accessed on 22 January 2021).
- Anselin, L. Local Indicators of Spatial Association—LISA. Geogr. Anal. 1995, 27, 93–115. [Google Scholar] [CrossRef]
- Chen, Y. New Approaches for Calculating Moran’s Index of Spatial Autocorrelation. Schumann GJ-P, ed. PLoS ONE 2013, 8, e68336. [Google Scholar] [CrossRef] [Green Version]
- Kulldorff, M. Theory and Methods A spatial scan statistic. Commun. Stat. 1997, 26, 1481–1496. [Google Scholar] [CrossRef]
- Zhang, W.Y.; Wei, Z.W.; Wang, B.H.; Han, X.P. Measuring mixing patterns in complex networks by Spearman rank correlation coefficient. Phys A Stat. Mech. Its Appl. 2016, 451, 440–450. [Google Scholar] [CrossRef]
- Lund, B.M.; O’Brien, S.J. The Occurrence and Prevention of Foodborne Disease in Vulnerable People. Foodborne Pathog. Dis. 2011, 8, 961–973. [Google Scholar] [CrossRef] [Green Version]
- Banerjee, S. Spatial Data Analysis. Annu. Rev. Public Health 2016, 37, 47–60. [Google Scholar] [CrossRef] [Green Version]
- Latorre, M.d.R.D.O.; Cardoso, M.R.A. Análise de séries temporais em epidemiologia: Uma introdução sobre os aspectos metodológicos. Rev. Bras. Epidemiol. 2001, 4, 145–152. [Google Scholar] [CrossRef]
- Paz, W.S.; Gomes, D.S.; Ramos, R.E.S.; Cirilo, T.M.; Santos, I.G.A.; Ribeiro, C.J.N.; Araújo, K.C.G.M.; Jesus, A.M.R.; Santos, A.D.; Bezerra-Santos, M. Spatiotemporal clusters of schistosomiasis mortality and association with social determinants of health in the Northeast region of Brazil (1980–2017). Acta Trop. 2020, 212, 105668. [Google Scholar] [CrossRef] [PubMed]
- Paz, W.S.; Duthie, M.S.; Jesus, A.R.; Araújo, K.C.G.M.; dos Santos, A.D.; Bezerra-Santos, M. Population-based, spatiotemporal modeling of social risk factors and mortality from schistosomiasis in Brazil between 1999 and 2018. Acta Trop. 2021, 218, 105897. [Google Scholar] [CrossRef]
- Buchalla, C.M.; Waldman, E.A.; Laurenti, R. A mortalidade por doenças infecciosas no início e no final do século XX no Município de São Paulo. Rev. Bras. Epidemiol. 2003, 6, 335–344. [Google Scholar] [CrossRef] [Green Version]
- Oliveira, L.H.; Giglio, N.; Ciapponi, A.; Martí, S.G.; Kuperman, M.; Sanwogou, N.J.; Ruiz-Matus, C.; Marinho de Sousa, M.F. Temporal trends in diarrhea-related hospitalizations and deaths in children under age 5 before and after the introduction of the rotavirus vaccine in four Latin American countries. Vaccine 2013, 31, C99–C108. [Google Scholar] [CrossRef]
- Castro, M.C.; Massuda, A.; Almeida, G.; Menezes-Filho, N.A.; Andrade, M.V.; de Souza Noronha, K.V.M.; Rocha, R.; Macinko, J.; Hone, T.; Tasca, R.; et al. Brazil’s unified health system: The first 30 years and prospects for the future. Lancet 2019, 394, 345–356. [Google Scholar] [CrossRef] [Green Version]
- Fernandes, E.G.; Sato, H.K.; Leshem, E.; Flannery, B.; Konstantyner, T.C.R.d.O.; Veras, M.A.d.S.M.; Patel, M.M. Impact of rotavirus vaccination on diarrhea-related hospitalizations in São Paulo State, Brazil. Vaccine 2014, 32, 3402–3408. [Google Scholar] [CrossRef]
- Esposti, C.D.D.; Oliveira, A.E.; dos Santos Neto, E.T.; Travassos, C. Representações sociais sobre o acesso e o cuidado pré-natal no Sistema Único de Saúde da Região Metropolitana da Grande Vitória, Espírito Santo. Saúde e Soc. 2015, 24, 765–779. [Google Scholar] [CrossRef] [Green Version]
- Vaz, F.P.C.; Nascimento, L.F.C. Spatial distribution for diarrhea hospitalization in São Paulo State. Rev. Bras. Saúde Matern Infant. 2017, 17, 475–482. [Google Scholar] [CrossRef]
Variables | N | % |
---|---|---|
Sex | ||
Male | 1853 | 53.37 |
Female | 1619 | 46.63 |
Age group (year) | ||
<1 | 1627 | 46.86 |
1 to 4 | 251 | 7.23 |
5 to 19 | 55 | 1.58 |
20 to 39 | 89 | 2.56 |
40 to 59 | 242 | 6.97 |
≥60 | 1208 | 34.79 |
Race and ethnicity | ||
Caucasian | 619 | 17.83 |
African descent | 121 | 3.49 |
Asian descent | 8 | 0.23 |
Mixed race | 1707 | 49.16 |
Amerindians | 15 | 0.43 |
Missing data | 1002 | 28.86 |
Educational level (years) | ||
None | 743 | 21.4 |
1 to 7 | 268 | 7.72 |
≥8 | 58 | 1.67 |
Missing data | 2403 | 69.21 |
Indicators/Variables | Mortality Rate Per 100,000 Inhabitants | APC (95% CI) | p-Value | Trend | |
---|---|---|---|---|---|
2000 | 2019 | ||||
Alagoas | 9.41 | 2.21 | −6.7 (−8.6 to −4.7) | <0.001 | Decreasing |
Sex | |||||
Male | 10.04 | 1.93 | −7.6 (−9.7 to −5.4) | <0.001 | Decreasing |
Female | 8.47 | 2.47 | −5.1(−7.2 to −3) | <0.001 | Decreasing |
Age group (years) | |||||
<1 | 275.82 | 14.99 | −13.5 (−15.3 to −11.6) | <0.001 | Decreasing |
1 to 4 | 12.23 | 0.49 | −10.1 (−12.2 to −7.9) | <0.001 | Decreasing |
5 to 19 | 0.10 | 0.32 | 1.3 (−7.1 to 10.6) | 0.787 | Stable |
20 to 39 | 0.92 | 8.51 | −3.5 (−8.2 to 1.5) | 0.194 | Stable |
40 to 59 | 3.44 | 1.76 | −2.5 (−5.8 to 0.9) | 0.187 | Stable |
≥60 | 14.22 | 14.74 | 11.9 (−2 to 27.9) | 0.183 | Stable |
State area | |||||
Metropolitan area | 7.64 | 1.86 | −7.3 (−9.4 to −5.3) | <0.001 | Decreasing |
Inland municipalities | 10.10 | 2.37 | −4.0 (−6.6 to −1.3) | <0.001 | Decreasing |
Proportion of municipalities with deaths | 0.61 | 0.34 | −3.3 (−4.6 to −1.9) | <0.001 | Decreasing |
Clusters | Period | Municipalities | Deaths | Expected Deaths | Annual Mortality Rate * | RR | LLR | p-Value |
---|---|---|---|---|---|---|---|---|
Retrospective | ||||||||
1 | 2000–2007 | 67 | 1336 | 733 | 10.11 | 3.34 | 270.85 | <0.001 |
2 | 2000–2008 | 20 | 280 | 123.77 | 12.53 | 2.37 | 76.05 | <0.001 |
Prospective | ||||||||
1 | 2013–2019 | 1 | 32 | 18.5 | 9.61 | 1.74 | 4.06 | <0.021 |
2 | 2015–2019 | 1 | 6 | 1.48 | 25.52 | 4.06 | 3.88 | <0.038 |
SDH/Socioeconomic Indicators | Rho | 95% CI | p-Value |
---|---|---|---|
Percentage of children aged 0–5 years who did not attend school | 0.4012 | 0.2186 to 0.5566 | <0.001 |
Mortality up to 1 year of age | 0.3449 | 0.1555 to 0.5098 | 0.004 |
Social vulnerability index (SVI) | 0.3374 | 0.1473 to 0.5035 | 0.001 |
GINI index | 0.2976 | 0.1045 to 0.2920 | 0.008 |
Percentage of people in households with inadequate water supply and sanitation | 0.2975 | 0.1036 to 0.4697 | 0.002 |
Percentage of children living in households where none of the residents have completed primary education | 0.2683 | 0.0720 to 0.4445 | 0.006 |
Illiteracy rate of the population aged 15 and over | 0.2334 | 0.0349 to 0.4141 | 0.018 |
Percentage of people aged 18 or over without complete elementary school and in informal occupation | 0.2358 | 0.0374 to 0.4162 | 0.317 |
% of people aged 6 to 14 who do not attend school | 0.2100 | 0.0103 to 0.3935 | 0.034 |
Infant mortality rate | 0.1117 | −0.0903 to −0.3050 | 0.002 |
Percentage of admissions for primary care-sensitive conditions | −0.0313 | −0.2300 to 0.1698 | 0.754 |
Percentage of urban population residing in households connected to the water supply network | −0.1829 | −0.3822 to −0.0326 | 0.002 |
Unemployment rate for the population aged 18 and over | −0.2264 | −0.4080 to −0.0276 | 0.222 |
Percentage of 18 to 20 years old with complete secondary | −0.2277 | −0.4102 to −0.0302 | 0.020 |
Percentage of people covered by supplementary health plans | −0.2433 | −0.4228 to −0.0454 | 0.018 |
Percentage of people covered by supplementary health plans | −0.2433 | −0.4228 to −0.0454 | 0.013 |
Percentage of children aged 5 to 6 years in school | −0.2803 | −0.4549 to −0.0850 | 0.004 |
Per capita income of vulnerable to poverty | −0.3289 | −0.2101 to −0.5302 | 0.005 |
Municipal human development index (MHDI) | −0.3455 | −0.5103 to −0.1562 | 0.004 |
Life expectancy at birth | −0.3470 | −0.5116 to −0.1579 | 0.001 |
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Lima, D.d.S.; da Paz, W.S.; Lopes de Sousa, Á.F.; de Andrade, D.; Conacci, B.J.; Damasceno, F.S.; Bezerra-Santos, M. Space–Time Clustering and Socioeconomic Factors Associated with Mortality from Diarrhea in Alagoas, Northeastern Brazil: A 20-Year Population-Based Study. Trop. Med. Infect. Dis. 2022, 7, 312. https://doi.org/10.3390/tropicalmed7100312
Lima DdS, da Paz WS, Lopes de Sousa ÁF, de Andrade D, Conacci BJ, Damasceno FS, Bezerra-Santos M. Space–Time Clustering and Socioeconomic Factors Associated with Mortality from Diarrhea in Alagoas, Northeastern Brazil: A 20-Year Population-Based Study. Tropical Medicine and Infectious Disease. 2022; 7(10):312. https://doi.org/10.3390/tropicalmed7100312
Chicago/Turabian StyleLima, Deanna dos Santos, Wandklebson Silva da Paz, Álvaro Francisco Lopes de Sousa, Denise de Andrade, Beatriz Juliana Conacci, Flávia Silva Damasceno, and Márcio Bezerra-Santos. 2022. "Space–Time Clustering and Socioeconomic Factors Associated with Mortality from Diarrhea in Alagoas, Northeastern Brazil: A 20-Year Population-Based Study" Tropical Medicine and Infectious Disease 7, no. 10: 312. https://doi.org/10.3390/tropicalmed7100312