Spatial analysis of cerebral palsy in children and adolescents and its association with health vulnerability
Cerebral Palsy (CP) is commonly associated with low socioeconomic status. Use of spatial statistics and a Geographic Information Systems (GIS) are scarce and may contribute to the understanding of CP in a social context. To that end a spatial analysis of CP in children and adolescents was performed to analyze the association of CP with levels of vulnerability in a city (Aracaju, Sergipe) in north-eastern Brazil. In addition, an ecological study was conducted with data obtained from a populationbased survey and secondary data. Exploratory spatial data analysis and linear regression were used. A total of 288 CP cases were identified, with a prevalence of 1.65/1,000 and differences among city neighbourhoods ranging from 0-4/1,000. The mean age of cases studied was 9 years 1 month, with a standard deviation of 5 years 2 months. Most study subjects with cerebral palsy (163) were male (56.4%). The distribution of CP in the study population was not homogeneous throughout the territory. Some areas had clusters, with more cases associated with areas of high vulnerability. Spatial data analysis using GIS was useful to gain an epidemiological understanding of CP distribution that can guide decisionmaking with respect to production, distribution, and regulation of health goods as well as services at the local level.
Anselin L, 2005 Exploring Spatial Data with GeoDa: A Workbook. Geography.244.
Brasil, 2007. Introdução à Estatística Espacial para Saúde Pública. Volume 3. Brasília-DF: Ministério da Saúde. Secretaria de Vigilância em Saúde.
Brasil, 2018. Instituto Brasileiro de Geografia e Estatística.
Braun KN, Maenner MJ, Christensen D, Doernberg NS, Durkin MS, Kirby RS, 2015. The role of migration and choice of denominator on the prevalence of cerebral palsy. Dev Med Child Neurol. 55(6):520–6.
Charreire H, Combier E, 2009 Poor prenatal care in an urban area: A geographic analysis. Heal Place.15(2):412–9.
Chi W, Wang J, Li X, Zheng X, Liao Y, 2008 Analysis of geographical clustering of birth defects in Heshun county, Shanxi province. Int J Environ Health Res.18(4):243–52.
Chong S, Nelson M, Byun R, Harris L, Eastwood J, Jalaludin B, 2013. Geospatial analyses to identify clusters of adverse antenatal factors for targeted interventions. Int J Health Geogr.12:1–10.
Colver A, Fairhurst C, Pharoah POD, 2014. Cerebral palsy. Lancet. 383(9924):1240–9.
Cutter SL, Boruff BJ, Shirley WL, 2003. Social Vulnerability to Environmental Hazards n. Soc Sci Q. 84(2):242–61.
Dolk H, Parkes J, Hill N, 2006. Trends in the prevalence of cerebral palsy in Northern Ireland, 1981-1997. Dev Med Child Neurol. 48(6):406–12.
Dolk H, Pattenden S, Bonellie S, Colver A, King A, Kurinczuk JJ, Parkesb J,
Plattg MJ, Surman G, 2010. Socio-economic inequalities in cerebral palsy prevalence in the United Kingdom: a register-based study. Paediatr Perinat Epidemiol.;24(2):149–55.
Dolk H, Pattenden S, Johnson A, 2001. Cerebral palsy , low birthweight and socio-economic deprivation : inequalities in a major cause of childhood disability. Paediatr Perinat Epidemiol.15(4):359-63
Drachler M de L, Lobato MA de O, Lermen JI, Fagundes S, Ferla AA, Drachler CW, Teixeira LB, Leite JCC, 2014. Desenvolvimento e validação de um índice de vulnerabilidade social aplicado a políticas públicas do SUS. Cien Saude Colet.;19(9):3849–58.
Durkin MS, Benedict RE, Christensen D, Dubois LA, Fitzgerald RT, Kirby RS, Maenner MJ, Van Naarden Braun K, Wingate MS, Yeargin-Allsopp M, 2016. Prevalence of Cerebral Palsy among 8-Year-Old Children in 2010 and Preliminary Evidence of Trends in Its Relationship to Low Birthweight. Paediatr Perinat Epidemiol. 30(5):496–510.
Durkin MS, Maenner MJ, Benedict RE, Van Naarden Braun K, Christensen D, Kirby RS, Wingate M, and Yeargin-Allsopp M, 2015. The role of socio-economic status and perinatal factors in racial disparities in the risk of cerebral palsy. Dev Med Child Neurol.57(9):835–43.
Graham HK, Rosenbaum P, Paneth N, Dan B, Lin J-P, Damiano DL, Lin JP7, Damiano DL, Becher JG, Gaebler-Spira D, Colver A, Reddihough DS, Crompton KE, Lieber RL, 2016. Cerebral palsy. Nat Rev Dis Prim.15082.
Insaf TZ, Talbot T, 2016. Identifying areas at risk of low birth weight using spatial epidemiology: A small area surveillance study. Prev Med (Baltim) 88:108–14.
Kakooza-Mwesige A, Andrews C, Peterson S, Wabwire Mangen F, Eliasson AC, Forssberg H, 2017. Prevalence of cerebral palsy in Uganda: a population-based study. Lancet Glob Heal. 5(12):e1275–82.
Kirby RS, Delmelle E, Eberth JM, 2017. Advances in spatial epidemiology and geographic information systems. Ann Epidemiol. 27(1):1–9.
Liao Y, Zhang Y, He L, Wang J, Liu X, Zhang N and Xu B, 2016. Temporal and spatial analysis of Neural tube defects and detection of geographical factors in Shanxi Province, China. PLoS One. 11(4):1–14.
McIntyre S, Taitz D, Keogh J, Goldsmith S, Badawi N, Blair E, 2013. A systematic review of risk factors for cerebral palsy in children born at term in developed countries. Dev Med Child Neurol. 55(6):499–508.
McNally RJQ, Colver AF, 2008. Space-time clustering analyses of occurrence of cerebral palsy in Northern England for births 1991 to 2003. Ann Epidemiol. 18(2):108–12.
Oskoui M, Coutinho F, Dykeman J, Jetté N, Pringsheim T, 2013. An update on the prevalence of cerebral palsy: A systematic review and meta-analysis. Dev Med Child Neurol. 55(6):509–19.
Oskoui M, Messerlian C, Blair A, Gamache P, Shevell M, 2016. Variation in cerebral palsy profile by socio-economic status. Dev Med Child Neurol. 58(2):160–6.
Sellier E, Platt MJMJ, Andersen GLGL, Krägeloh-Mann I, De La Cruz J, Cans C, 2016. Decreasing prevalence in cerebral palsy: A multi-site European population-based study, 1980 to 2003. Dev Med Child Neurol. 58(1):85–92.
Shih STF, Tonmukayakul U, Imms C, Reddihough D, Graham HK, Cox L, Carter R, 2018. Economic evaluation and cost of interventions for cerebral palsy: a systematic review. Dev Med Child Neurol. 1–16.
Solaski M, Majnemer A, Oskoui M, 2014. Contribution of socio-economic status on the prevalence of cerebral palsy: a systematic search and review. Dev Med Child Neurol. 1–9.
Tallman PS, 2016. The Index of Vulnerability: An anthropological method linking social-ecological systems to mental and physical health outcomes. Soc Sci Med. 162:68–78.
Tseng S-H, Lee J-Y, Chou Y-L, Sheu M-L, Lee Y-W, 2018 Association between socioeconomic status and cerebral palsy. Papadelis C, editor. PLoS One. 13(1):e0191724.
World Health Organization, 2012. Relatório mundial sobre a deficiência. 334.
- Abstract views: 73
- PDF: 50
Copyright (c) 2020 The Authors
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.