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Analyzing spatial and space-time clustering of facility-based deliveries in Bangladesh

Analyzing spatial and space-time clustering of facility-based deliveries in Bangladesh
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 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 Gi* 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.
1349-4147
1-12
Chowdhury, Atique Iqbal
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Abdullah, Abu Yousuf Md
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Haider, Rafiqul
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Alam, Asraful
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Billah, Sk Masum
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Bari, Sanwarul
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Rahman, Qazi Sadeq-ur
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Jochem, Warren
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Dewan, Ashraf
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El Arifeen, Shams
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Chowdhury, Atique Iqbal
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Abdullah, Abu Yousuf Md
5d843dcf-963a-42cb-8aac-f288328f9024
Haider, Rafiqul
887f0265-a144-4360-95fa-4c11d7339c59
Alam, Asraful
ed40fb62-7e62-4e3a-af1e-e2562d3e7c11
Billah, Sk Masum
2bfab2fe-9398-4b3c-ad75-6c929e47b3d8
Bari, Sanwarul
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Rahman, Qazi Sadeq-ur
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Jochem, Warren
ef65df67-4364-4438-92e9-f93ceedb8da1
Dewan, Ashraf
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El Arifeen, Shams
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Chowdhury, Atique Iqbal, Abdullah, Abu Yousuf Md, Haider, Rafiqul, Alam, Asraful, Billah, Sk Masum, Bari, Sanwarul, Rahman, Qazi Sadeq-ur, Jochem, Warren, Dewan, Ashraf and El Arifeen, Shams (2019) Analyzing spatial and space-time clustering of facility-based deliveries in Bangladesh. Tropical Medicine and Health, 47, 1-12, [44]. (doi:10.1186/s41182-019-0170-9).

Record type: Article

Abstract

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 Gi* 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.

Text
s41182-019-0170-9 - Version of Record
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More information

Accepted/In Press date: 20 June 2019
Published date: 16 July 2019

Identifiers

Local EPrints ID: 432582
URI: http://eprints.soton.ac.uk/id/eprint/432582
ISSN: 1349-4147
PURE UUID: 17fec2c5-3528-4d3e-bc7b-a688a1d89a2f
ORCID for Warren Jochem: ORCID iD orcid.org/0000-0003-2192-5988

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Date deposited: 19 Jul 2019 16:30
Last modified: 16 Mar 2024 04:24

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Contributors

Author: Atique Iqbal Chowdhury
Author: Abu Yousuf Md Abdullah
Author: Rafiqul Haider
Author: Asraful Alam
Author: Sk Masum Billah
Author: Sanwarul Bari
Author: Qazi Sadeq-ur Rahman
Author: Warren Jochem ORCID iD
Author: Ashraf Dewan
Author: Shams El Arifeen

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