Exploring the distribution of risk factors for drop-out from Ponseti treatment for clubfoot across Bangladesh using geospatial cluster analysis

Submitted: 28 November 2022
Accepted: 25 February 2023
Published: 25 May 2023
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Clubfoot is a congenital anomaly affecting 1/1,000 live births. Ponseti casting is an effective and affordable treatment. About 75% of affected children have access to Ponseti treatment in Bangladesh, but 20% are at risk of drop-out. We aimed to identify the areas in Bangladesh where patients are at high or low risk for drop-out. This study used a cross-sectional design based on publicly available data. The nationwide clubfoot program: ‘Walk for Life’ identified five risk factors for drop-out from the Ponseti treatment, specific to the Bangladeshi setting: household poverty, household size, population working in agriculture, educational attainment and travel time to the clinic. We explored the spatial distribution and clustering of these five risk factors. The spatial distribution of children <5 years with clubfoot and the population density differ widely across the different sub-districts of Bangladesh. Analysis of risk factor distribution and cluster analysis showed areas at high risk for dropout in the Northeast and the Southwest, with poverty, educational attainment and working in agriculture as the most prevalent driving risk factor. Across the entire country, twenty-one multivariate high-risk clusters were identified. As the risk factors for drop-out from clubfoot care are not equally distributed across Bangladesh, there is a need in regional prioritization and diversification of treatment and enrolment policies. Local stakeholders and policy makers can identify high-risk areas and allocate resources effectively.

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Alam MT, Akber EB, Alam QS, Reza MS, Mahboob AH, Salam SI, Islam MS, Ara I, 2015. Outcome of Percutaneous Tenotomy in the Management of Congenital Talipes Equino Varus by Ponseti Method. Mymensingh Med J 24:467–70.
Anselin L, 2019. A Local Indicator of Multivariate Spatial Association: Extending Geary’s C. Geographical Analysis 51:133–50. DOI: https://doi.org/10.1111/gean.12164
Bangladesh Bureau of Statistics, 2011. Sample characteristics: Bangladesh. IPUMS-I. Available from: https://international.ipums.org/international-action/sample_details/country/bd#tab_bd2011a
Benjamini Y, Hochberg Y, 1995. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. J R Stat Soc B Methodol 57:289–300. DOI: https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
Buda AM, Truche P, Izquierdo E, Izquierdo S de, Asturias S, Stankey M, Park KB, Peck G, Juran S, Evans FM, 2022. Use of geospatial analysis for priority setting in surgical system investment in Guatemala. Lancet Reg Health Americas 7:100145. DOI: https://doi.org/10.1016/j.lana.2021.100145
Central Intelligence Agency 2021. Bangladesh. The CIA World Factbook. Available from: https://www.cia.gov/the-world-factbook/countries/bangladesh/
Chi G, Shapley D, Yang TC, Wang D, 2019. Lost in the Black Belt South: health outcomes and transportation infrastructure. Environmental Monitoring and Assessment, 191(Suppl 2). DOI: https://doi.org/10.1007/s10661-019-7416-1
Evans AM, Chowdhury M, Karimi L, Rouf A, Uddin S, Haque O, 2020. Factors Affecting Parents to ‘Drop-Out’ from Ponseti Method and Children’s Clubfoot Relapse. Orthopaed Res Online J 6:601–9. DOI: https://doi.org/10.31031/OPROJ.2020.06.000638
Evans AM, Chowdhury M, Khan S, 2021. A community audit of 300 “drop-out” instances in children undergoing ponseti clubfoot care in bangladesh—what do the parents say? Int J Environ Res Public Health 18:1–12. DOI: https://doi.org/10.3390/ijerph18030993
Ganesan B, Luximon A, Al-Jumaily A, Balasankar SK, Naik GR, 2017. Ponseti method in the management of clubfoot under 2 years of age: A systematic review. PLoS ONE 12:0178299 DOI: https://doi.org/10.1371/journal.pone.0178299
Geary RC, 1954. The Contiguity Ratio and Statistical Mapping. Inc Stat 5:115–45. DOI: https://doi.org/10.2307/2986645
Global Clubfoot Initiative 2022. Bangladesh. Global Clubfoot Initiative - Countries. Available from http://globalclubfoot.com/countries/bangladesh/
Iyer HS, Flanigan J, Wolf NG, Schroeder LF, Horton S, Castro MC, Rebbeck TR, 2020. Geospatial evaluation of trade-offs between equity in physical access to healthcare and health systems efficiency. BMJ Global Health 5:003493 DOI: https://doi.org/10.1136/bmjgh-2020-003493
Jones M, Moeller EA, Meara JG, Juran S, 2021. The importance of geographic and demographic data from census for locating and mapping vulnerable populations. Statist J IAOS 37:13–17. DOI: https://doi.org/10.3233/SJI-200760
Juran S, Broer PN, Klug SJ, Snow RC, Okiro EA, Ouma PO, Snow RW, Tatem AJ, Meara JG, Alegana VA, 2018. Geospatial mapping of access to timely essential surgery in sub-Saharan Africa. BMJ Global Health 3:875. DOI: https://doi.org/10.1136/bmjgh-2018-000875
Kumar Gupta A, Ladusingh L, Borkotoky K, 2010. Spatial clustering and risk factors of infant mortality: district-level assessment of high-focus states in India. Annual Health Survey. Available from: https://doi.org/10.1186/s41118-016-0008-9 DOI: https://doi.org/10.1186/s41118-016-0008-9
Levesque JF, Harris MF, Russell G, 2013. Patient-centred access to health care: conceptualising access at the interface of health systems and populations. Int J Equity Health 12:18. DOI: https://doi.org/10.1186/1475-9276-12-18
Macintyre S, Ellaway A, Cummins S, 2002. Place effects on health: how can we conceptualise, operationalise and measure them? Social Sci & Med 55:125–139. DOI: https://doi.org/10.1016/S0277-9536(01)00214-3
Mandloi D, Zeng M, 2019. ArcGIS Online: Routing and Network Analysis using Web Services. http://esriurl.com/uc19nawago
Moran PAP, 1950. Notes on Continuous Stochastic Phenomena. Biometrika 37:17–23. DOI: https://doi.org/10.1093/biomet/37.1-2.17
Morcuende JA, Dolan LA, Dietz FR, Ponseti IV, 2004. Radical Reduction in the Rate of Extensive Corrective Surgery for Clubfoot Using the Ponseti Method. Pediatrics 113:376–380. DOI: https://doi.org/10.1542/peds.113.2.376
More R, Manjunath K, 2013. Deducing Rice Crop Dynamics and Cultural Types of Bangladesh Using Geospatial Techniques. J Indian Soc Remote Sensing 41:597–607. DOI: https://doi.org/10.1007/s12524-012-0228-1
Nations Online Project 2023. Political Map of Bangladesh. Nations Online Project. https://www.nationsonline.org/oneworld/map/Political-Map-of-Bangladesh.htm
Ottersen T, Norheim OF, on behalf of the World Health Organization Consultative Group on Equity and Universal Health Coverage 2014. Making Fair Choices on the Path to Universal Health Coverage. Bulletin World Health Organ 923:89. DOI: https://doi.org/10.2471/BLT.14.139139
Owen RM, Capper B, Lavy C, 2018. Clubfoot treatment in 2015: A global perspective. BMJ Global Health 3:e000852 DOI: https://doi.org/10.1136/bmjgh-2018-000852
Penny JN, 2005. The Neglected Clubfoot. Tech Orthopaed 20:153–66. DOI: https://doi.org/10.1097/01.bto.0000162987.08300.5e
Pigeolet M, Vital A, Daoud HA, Mita C, Corlew DS, Alkire BC, 2022. The impact of socio-economic factors on parental non-adherence to the Ponseti protocol for clubfoot treatment in low- and middle-income countries: A scoping review. E Clinical Medicine 48:101448. DOI: https://doi.org/10.1016/j.eclinm.2022.101448
Pirani S, Naddumba E, Mathias R, Konde-Lule J, Penny JN, Beyeza T, Mbonye B, Amone J, Franceschi F, 2009. Towards Effective Ponseti Clubfoot Care: The Uganda Sustainable Clubfoot Care Project. Clin Orthopaed Related Res 467:1154–63. DOI: https://doi.org/10.1007/s11999-009-0759-0
Ponseti IV, 1996. Congenital Clubfoot, Fundamentals of treatment (2nd edition). Oxford University Press. http://nebula.wsimg.com/ed4c586ff5f7f06473adf59d9fb25090?AccessKeyId=B17C75687FBF776E8655&disposition=0&alloworigin=1
Qin X, Wu H, Shan T, 2022. Rural infrastructure and poverty in China. PloS One 17:e0266528. DOI: https://doi.org/10.1371/journal.pone.0266528
Quattrochi JP, Hill K, Salomon JA, Castro, MC, 2020. The effects of changes in distance to nearest health facility on under-5 mortality and health care utilization in rural Malawi, 1980-1998. BMC Health Services Res 20:899. DOI: https://doi.org/10.1186/s12913-020-05738-w
Ridgway JP, Almirol EA, Schmitt J, Schuble T Schneider JA, 2018. Travel time to Clinic but not Neighborhood Crime Rate is associated with Retention in Care among HIV-positive Patients. AIDS and Behavior 22:3003. DOI: https://doi.org/10.1007/s10461-018-2094-5
Robin TA, Khan MA, Kabir N, Rahaman ST, Karim A, Mannan II., George J, Rashid I, 2019. Using spatial analysis and GIS to improve planning and resource allocation in a rural district of Bangladesh. BMJ Global Health 4:e000832. DOI: https://doi.org/10.1136/bmjgh-2018-000832
Sabaté E, 2003. Adherence to Long-Term Therapies: Evidence for action. World Health Organization. Available from: https://apps.who.int/iris/handle/10665/42682
Sattar MP, 2021. Health Sector Governance: An Overview of the Legal and Institutional Framework in Bangladesh. Open J Soc Sci 9:395–414. DOI: https://doi.org/10.4236/jss.2021.911027
Terzian AS, Younes N, Greenberg AE, Opoku J, Hubbard J, Happ LP, Kumar P, Jones RR, Castel AD, 2018. Identifying spatial variation along the HIV care continuum: The role of distance to care on retention and viral suppression. AIDS and Behavior 22,3009. DOI: https://doi.org/10.1007/s10461-018-2103-8
UNFPA, 2020. Technical Brief on the Implications of COVID-19 on Census. United Nations Populations Fund. Available from: https://www.unfpa.org/resources/technical-brief-implications-covid-19-census
United Nations Department of Population 2019. World Population Prospects 2019. Available from: https://population.un.org/wpp/
United Nations Statistics Division, 2020. World Population and Housing Census program, Impact of COVID-19. Demographic and Social Statistics. Available from: https://unstats.un.org/unsd/demographic-social/census/COVID-19-SurveyT2-1/
UNOCHA, 2022. Bangladesh. Humanitarian Data Exchange. United Nations Office for the Coordination of Humanitarian Affairs. Available from: https://data.humdata.org/group/bgd
Walk For Life, 2021. Clinic List - Walk For Life. Available from: http://walkforlife.org.au/en/clinic-list/
World Bank, 2014. What Areas Need the Most Assistance in Reducing Poverty? Bangladesh’s New Poverty Maps May Have Answers. Available from: https://www.worldbank.org/en/news/feature/2014/09/30/poverty-maps
Zeng C, Zhang J, Sun X, Li Z, Weissman S, Olatosi B, Li X, 2021. County-level predictors of retention in care status among people living with HIV in South Carolina from 2010 to 2016: A data-driven approach. AIDS (London, England) 35:S53. DOI: https://doi.org/10.1097/QAD.0000000000002832

How to Cite

Pigeolet, M., Kucchal, T., Hey, M. T., Castro, M. C., Evans, A. M., Uribe-Leitz, T., Chowhury, M. M. H., & Juran, S. (2023). Exploring the distribution of risk factors for drop-out from Ponseti treatment for clubfoot across Bangladesh using geospatial cluster analysis. Geospatial Health, 18(1). https://doi.org/10.4081/gh.2023.1174