https://doi.org/10.4081/gh.2022.1051
Spatial patterns of the total mortality over the first 24 hours of life and that due to preventable causes
Submitted: 12 November 2021
Accepted: 9 March 2022
Published: 17 May 2022
Accepted: 9 March 2022
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Appendix: 63
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All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
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This is an ecological study analysing spatial patterns of the total mortality over the first 24 hours of life and that due to preventable causes using data from the mortality information system (SIM) and live birth information system (SINASC) based on the municipalities of Pernambuco State, Brazil. The total mortality rates over the first 24 hours and that due to preventable causes were calculated for each municipality for the decades of 2000 to 2009 and for 2010 to 2019 to enable a comparison of the spatial patterns with spatial scan statistic used to identify clusters. Over the first 24 hours of life, a total of 13,571 deaths were reported, out of which 10,476 (77.2%) were preventable. The total mortality rate over the first 24 hours of life decreased from 5.5 in the 2000- 2009 period to 3.7 per 1000 live births in the following decade: a reduction of 32.7%, while the mortality rate due to preventable causes decreased from 4.4 to 2.8 per 1000 live births, a reduction of 36.7%. In the first decade, spatial exploratory analysis found three mortality rate clusters encompassing 56 municipalities over the first 24 hours of life. With respect to preventable causes over the first 24 hours of life, two mortality rate clusters were identified encompassing 41 municipalities. Risk areas for mortality over the first 24 hours of life were detected through spatial scan statistic. This method, directed towards uncovering the geographical distribution of deaths of very premature infants, can act as a tool for identifying priority areas to guide healthcare interventions.
Adeyinka DA, Olakunde BO, Muhajarine N, 2019. Evidence of health inequity in childsurvival: spatial and Bayesian network analysis of stillbirth rates in 194 countries. Sci Rep 9:19755, 1-11.
DOI: https://doi.org/10.1038/s41598-019-56326-w
Al-Sheyab NA, Khader YS, Shattnawi KK, Alyahya MS, Batieha A, 2020. Rate, risk factors, and causes of neonatal deaths in Jordan: analysis of data from Jordan Stillbirth and Neonatal Surveillance System (JSANDS). Front Public Health 595379:1-10.
DOI: https://doi.org/10.3389/fpubh.2020.595379
Assunção RM, Barreto SM, Guerra HL, Sakurai E, 1998. Maps of epidemiological rates: a Bayesian approach. Cad Saúde Pública 14:713-23.
DOI: https://doi.org/10.1590/S0102-311X1998000400013
Baqui AH, Mitra DK, Begum N, Hurt L, Soremekun S, Edmond K, Kirkwood B, Bhandari N, Teneja S, Mazumder S, Nisar MI, Jehan F, Ilyas M, Ali M, Ahmed I, Ariff S, Soofi SB, Dhingra U, Dutta A, Ali SM, Ame SM, Semrau K, Hamomba FM, Grogan C, Hamer DH, Bahl R, Yoshida S, Manu A, 2016. Neonatal mortality within 24 hours of birth in six low- and lower-middle-income countries. Bull World Health Organ 94:752-8.
DOI: https://doi.org/10.2471/BLT.15.160945
Boutayeb A, Lamlili M, Ouazza A, Abdu M, Azouagh N, 2020. Infant mortality in Sudan: Health equity, territorial disparity and social determinants of health. J Public Health Afr 10:133-6.
DOI: https://doi.org/10.4081/jphia.2019.1015
Brazilian Ministry of Health, 2021. Departamento de Informática do SUS; Ministério da Saúde. DATASUS [Online]. Available from: https://datasus.saude.gov.br/informacoes-de-saude-tabnet/
Canuto IMB, Macêdo VM, Frias PG, Oliveira CM, Costa HVV, Portugal JL, Bonfim CV, 2021. Spatial patterns of avoidable fetal mortality and social deprivation. Rev Bras Epidemiol 24 [Epub ahead of print]. doi: 10.1590/1980-549720210007.supl.1.
DOI: https://doi.org/10.1590/1980-549720210007.supl.1
Castro ECM, Leite AJM, Guinsburg R, 2016. Mortality in the first 24h of very low birth weight preterm infants in the Northeast of Brazil. Rev Paul Pediatr 34:106-13.
DOI: https://doi.org/10.1016/j.rppede.2015.12.008
Desalew A, Gelano TF, Semahegn A, Geda B, Ali T, 2020. Childhood hearing impairment and its associated factors in sub-Saharan Africa in the 21st century: A systematic review and meta-analysis. SAGE OpenMed 8:1-11.
DOI: https://doi.org/10.1177/2050312120919240
Grady SC, Frake AN, Zhang Q, Bene M, Jordan DR, Vertalka J, DosSantos TC, Kadhim A, Namanya J, Pierre LM, Fan Y, Zhou P, Barry FB, Kutch L, 2017. Neonatal mortality in East Africa and West Africa: a geographic analysis of district-leveldemographic and health survey data. Geospat Health 12:137-50.
DOI: https://doi.org/10.4081/gh.2017.501
Guerra AB, Guerra LM, ProbstLF,Gondinho BVC, Ambrosano GMB, Melo EA, Brizon VSC, Bulgareli JV, Cortellazzi KL, Pereira AC, 2019. Can the primary health care model affect the determinants of neonatal, post-neonatal and maternal mortality? A study from Brazil. BMC Health Serv Res 19:1-11.
DOI: https://doi.org/10.1186/s12913-019-3953-0
Instituto Brasileiro de Geografia e Estatística, 2017. IBGE Cidades [Online]. Available from: https://cidades.ibge.gov.br/brasil/pe/panorama
Justino DCP, Lopes MS, Santos DCP, Andrade FB, 2019. Historicalevaluationof children’spublic health policies in Brazil: integrative review. Rev Ciência Plural 5:71-88.
DOI: https://doi.org/10.21680/2446-7286.2019v5n1ID17946
Kc A, Jha AK, Shrestha MP, Zhou H, Gurung A, Thapa J, Budhathoki SS, 2020. Trends for Neonatal Deaths in Nepal (2001-2016) to Project Progress Towards the SDG Target in 2030, and Risk Factor Analyses to Focus Action. Matern Child Health J 23:5-14.
DOI: https://doi.org/10.1007/s10995-019-02826-0
Kulldorf M. SaTScan User Guide. Software for the spatial, temporal, and space-time scan statistics, 2021 [Online]. Available from: https://www.satscan.org/techdoc.html
Lima SS, Braga MC, Vanderlei LCM, Luna CF, Frias PG, 2020. Assessment of the impact of prenatal, childbirth, and neonatal care on avoidable neonatal deaths in Pernambuco State, Brazil: an adequacy study. Cad Saúde Públ 36:1-12.
DOI: https://doi.org/10.1590/0102-311x00039719
Lohela TJ, Nesbitt RC, Pekkanen J, Gabrysch S, 2019. Comparing socioeconomic inequalities between early neonatal mortality and facility delivery: cross-sectional data from 72 low- and middle-income countries. Sci Rep 9:1-11.
DOI: https://doi.org/10.1038/s41598-019-45148-5
Malta DC, Duarte EC, Almeida MF, Dias MAS, Morais Neto OL, Moura L, Ferraz W, Souza MFM, 2007. List of avoidable causes of deaths due to interventions of the Brazilian Health System. Epidemiol Serv Saúde 16:233-44.
DOI: https://doi.org/10.5123/S1679-49742007000400002
Malta DC, Sardinha LMV, Moura L, Lansky S, Leal MC, Szwarcwald CL, França E, Almeida MF, Duarte EC. Update of avoidable causes of deaths due to interventions at the Brazilian Health System. Epidemiol Serv Saúde 19:173-6.
Mendes RB, Santos JMJ, Prado DS, Gurgel RQ, Bezerra FD, Gurgel RQ, 2019. Maternal characteristics and type of prenatal care associated with peregrination before childbirth. Rev Saúde Públ 53:1-10.
DOI: https://doi.org/10.11606/s1518-8787.2019053001087
Pernambuco State Secretariat of Health, 2016. Perfil socioeconômico, demográfico e epidemiológico: Pernambuco 2016. 1ª Ed. Recife. Pernambuco Secretaria Estadual de Saúde, Secretaria Executiva de Vigilância em Saúde, Diretoria Geral de Promoção, Monitoramento e Avaliação da Vigilância em Saúde, 238 pp. Available from: http://portal.saude.pe.gov.br/secretaria/perfil-socioeconomico-demografico-e-epidemiologico
Pinto LF, Freita MPS, Figueiredo AWS, 2018. National Information and Population Survey Systems: selected contributions from the Ministry of Health and the IBGE for analysis of Brazilian state capitals over the past 30 years. Ciênc Saúde Colet 23:1859-70.
DOI: https://doi.org/10.1590/1413-81232018236.05072018
QGIS.org, 2021. QGIS geographic information system. QGIS Association. Available from: http://www.qgis.org
Root ED, Bailey ED, Gorham T, Browning C, Song C, Salsberry P, 2020. Geovisualization and Spatial Analysis of Infant Mortality and Preterm Birth in Ohio, 2008-2015: Opportunities to Enhance Spatial Thinking. Public Health Rep 135:472-82.
DOI: https://doi.org/10.1177/0033354920927854
Rutstein DD, Berenberg W, Chalmers TC, Child CG, Fishman AP, Perrin EB, Feldman JJ, Leaverton PE, Lane JM, Sencer DJ, Evans CC, 1976. Measuring the Quality of Medical Care- A Clinical Method. N Engl J Med 294:582-8.
DOI: https://doi.org/10.1056/NEJM197603112941104
SaTScan™️, 2016. Software for the spatial, temporal and space-time scan statistics. SaTScan v9.4.4 [Internet]. Available from: https://www.satscan.org/
Teixeira JAM, Araújo WRM, Maranhão AGK, Cortez-Escalante JJ, Rezende LFM, Matijasevich A, 2019. Mortality on the first day of life: trends, causes of death and avoidability in eight Brazilian Federative Units, between 2010 and 2015. Epidemiol Serv Saude 28:1-11.
DOI: https://doi.org/10.5123/S1679-49742019000100006
Tesema GA, Teshale AB, 2021. Residential inequality and spatial patterns of infant mortality in Ethiopia: evidence from Ethiopian Demographic and Health Surveys. Trop Med Health 49:1-15.
DOI: https://doi.org/10.1186/s41182-021-00299-y
Weiland M, Santana P, Costa C, Doetsch J, Pilot E, 2021. Spatial access matters: an analysis of policy change and its effects on avoidable infant mortality in Portugal. Int J Environ Res Public Health 18:1-18.
DOI: https://doi.org/10.3390/ijerph18031242
World Bank Group. World Bank Open Data, 2021 [Online]. Available from: https://data.worldbank.org/ Available from: April 14, 2021.
Yourkavitch J, Burgert-Brucker C, Assaf S, Delgado S, 2018. Using geographical analysis to identify child health inequality in sub-Saharan Africa. PLoS One 13:1-23.
DOI: https://doi.org/10.1371/journal.pone.0201870
Zhao P, Han X, You L, Zhao Y, Yang L, Liu Y, 2020. Effect of basic public health service project on neonatal health services and neonatal mortality in China: a longitudinal time-series study. BMJ Open 10:1-6.
DOI: https://doi.org/10.1136/bmjopen-2019-034427
How to Cite
Silva, A. B. dos S., de Melo Araújo, A. C. ., Cabral Silva, A. P. de S. ., Rodrigues Vilela, M. B. ., & do Bonfim, C. V. (2022). Spatial patterns of the total mortality over the first 24 hours of life and that due to preventable causes. Geospatial Health, 17(1). https://doi.org/10.4081/gh.2022.1051
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