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Analyzing spatial and space-time clustering of facility-based deliveries in Bangladesh
BACKGROUND: A spatial and temporal study of the distribution of facility-based deliveries can identify areas of low and high facility usage and help devise more targeted interventions to improve delivery outcomes. Developing countries like Bangladesh face considerable challenges in reducing the mate...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6636060/ https://www.ncbi.nlm.nih.gov/pubmed/31346313 http://dx.doi.org/10.1186/s41182-019-0170-9 |
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author | Chowdhury, Atique Iqbal Abdullah, Abu Yousuf Md Haider, Rafiqul Alam, Asraful Billah, Sk Masum Bari, Sanwarul Rahman, Qazi Sadeq-ur Jochem, Warren Christopher Dewan, Ashraf El Arifeen, Shams |
author_facet | Chowdhury, Atique Iqbal Abdullah, Abu Yousuf Md Haider, Rafiqul Alam, Asraful Billah, Sk Masum Bari, Sanwarul Rahman, Qazi Sadeq-ur Jochem, Warren Christopher Dewan, Ashraf El Arifeen, Shams |
author_sort | Chowdhury, Atique Iqbal |
collection | PubMed |
description | BACKGROUND: A spatial and temporal study of the distribution of facility-based deliveries can identify areas of low and high facility usage and help devise more targeted interventions to improve delivery outcomes. Developing countries like Bangladesh face considerable challenges in reducing the maternal mortality ratio to the targets set by the Sustainable Development Goals. Recent studies have already identified that the progress of reducing maternal mortality has stalled. Giving birth in a health facility is one way to reduce maternal mortality. METHODS: Facility delivery data from a demographic surveillance site was analyzed at both village and Bari (comprising several households with same paternal origins) level to understand spatial and temporal heterogeneity. Global spatial autocorrelation was detected using Moran’s I index while local spatial clusters were detected using the local Getis G(i)* statistics. In addition, space-time scanning using a discrete Poisson approach facilitated the identification of space-time clusters. The likelihood of delivering at a facility when located inside a cluster was calculated using log-likelihood ratios. RESULTS: The three cluster detection approaches detected significant spatial and temporal heterogeneity in the distribution of facility deliveries in the study area. The hot and cold spots indicated contiguous and relocation type diffusion and increased in number over the years. Space-time scanning revealed that when a parturient woman is located in a Bari inside the cluster, the likelihood of delivering at a health facility increases by twenty-seven times. CONCLUSIONS: Spatiotemporal studies to understand delivery patterns are quite rare. However, in resource constraint countries like Bangladesh, detecting hot and cold spot areas can aid in the detection of diffusion centers, which can be targeted to expand regions with high facility deliveries. Places and periods with reduced health facility usages can be identified using various cluster detection techniques, to assess the barriers and facilitators in promoting health facility deliveries. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s41182-019-0170-9) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6636060 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-66360602019-07-25 Analyzing spatial and space-time clustering of facility-based deliveries in Bangladesh Chowdhury, Atique Iqbal Abdullah, Abu Yousuf Md Haider, Rafiqul Alam, Asraful Billah, Sk Masum Bari, Sanwarul Rahman, Qazi Sadeq-ur Jochem, Warren Christopher Dewan, Ashraf El Arifeen, Shams Trop Med Health Research BACKGROUND: A spatial and temporal study of the distribution of facility-based deliveries can identify areas of low and high facility usage and help devise more targeted interventions to improve delivery outcomes. Developing countries like Bangladesh face considerable challenges in reducing the maternal mortality ratio to the targets set by the Sustainable Development Goals. Recent studies have already identified that the progress of reducing maternal mortality has stalled. Giving birth in a health facility is one way to reduce maternal mortality. METHODS: Facility delivery data from a demographic surveillance site was analyzed at both village and Bari (comprising several households with same paternal origins) level to understand spatial and temporal heterogeneity. Global spatial autocorrelation was detected using Moran’s I index while local spatial clusters were detected using the local Getis G(i)* statistics. In addition, space-time scanning using a discrete Poisson approach facilitated the identification of space-time clusters. The likelihood of delivering at a facility when located inside a cluster was calculated using log-likelihood ratios. RESULTS: The three cluster detection approaches detected significant spatial and temporal heterogeneity in the distribution of facility deliveries in the study area. The hot and cold spots indicated contiguous and relocation type diffusion and increased in number over the years. Space-time scanning revealed that when a parturient woman is located in a Bari inside the cluster, the likelihood of delivering at a health facility increases by twenty-seven times. CONCLUSIONS: Spatiotemporal studies to understand delivery patterns are quite rare. However, in resource constraint countries like Bangladesh, detecting hot and cold spot areas can aid in the detection of diffusion centers, which can be targeted to expand regions with high facility deliveries. Places and periods with reduced health facility usages can be identified using various cluster detection techniques, to assess the barriers and facilitators in promoting health facility deliveries. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s41182-019-0170-9) contains supplementary material, which is available to authorized users. BioMed Central 2019-07-16 /pmc/articles/PMC6636060/ /pubmed/31346313 http://dx.doi.org/10.1186/s41182-019-0170-9 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Chowdhury, Atique Iqbal Abdullah, Abu Yousuf Md Haider, Rafiqul Alam, Asraful Billah, Sk Masum Bari, Sanwarul Rahman, Qazi Sadeq-ur Jochem, Warren Christopher Dewan, Ashraf El Arifeen, Shams Analyzing spatial and space-time clustering of facility-based deliveries in Bangladesh |
title | Analyzing spatial and space-time clustering of facility-based deliveries in Bangladesh |
title_full | Analyzing spatial and space-time clustering of facility-based deliveries in Bangladesh |
title_fullStr | Analyzing spatial and space-time clustering of facility-based deliveries in Bangladesh |
title_full_unstemmed | Analyzing spatial and space-time clustering of facility-based deliveries in Bangladesh |
title_short | Analyzing spatial and space-time clustering of facility-based deliveries in Bangladesh |
title_sort | analyzing spatial and space-time clustering of facility-based deliveries in bangladesh |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6636060/ https://www.ncbi.nlm.nih.gov/pubmed/31346313 http://dx.doi.org/10.1186/s41182-019-0170-9 |
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