Clustering of home delivery in Bangladesh and its predictors : Evidence from the linked household and health facility level survey data
Copyright: © 2024 Fatima et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited..
Around half of births in Bangladesh occur at home without skilled birth personnel. This study aims to identify the geographical hot spots and cold spots of home delivery in Bangladesh and associated factors. We analyzed data from the 2017/2018 Bangladesh Demographic and Health Survey and the 2017 Bangladesh Health Facility Survey. The outcome variable was home delivery without skilled personnel supervision (yes, no). Explanatory variables included individual, household, community, and healthcare facility level factors. Moran's I was used to determine hot spots (geographic locations with notably high rates of home delivery) and cold spots (geographic areas exhibiting significantly low rates of home delivery) of home delivery. Geographically weighted regression models were used to identify cluster-specific predictors of home delivery. The prevalence of without skilled personnel supervised home delivery was 53.18%. Hot spots of non-supervised and unskilled supervised home delivery were primarily located in Dhaka, Khulna, Rajshahi, and Rangpur divisions. Cold spots of home delivery were mainly located in Mymensingh and Sylhet divisions. Predictors of higher home births in hot spot areas included women's illiteracy, lack of formal job engagement, higher number of children ever born, partner's agriculture occupation, higher community-level illiteracy, and larger distance to the nearest healthcare facility from women's homes. The study findings suggest home delivery is prevalent in Bangladesh. Awareness-building programs should emphasize the importance of skilled and supervised institutional deliveries, particularly among the poor and disadvantaged groups.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2024 |
|---|---|
| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:4 |
|---|---|
| Enthalten in: |
PLOS global public health - 4(2024), 2 vom: 15., Seite e0002607 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Fatima, Kaniz [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
|---|
| Anmerkungen: |
Date Revised 17.02.2024 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
|---|
| doi: |
10.1371/journal.pgph.0002607 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM368491552 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM368491552 | ||
| 003 | DE-627 | ||
| 005 | 20240217232403.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 240216s2024 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1371/journal.pgph.0002607 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1297.xml |
| 035 | |a (DE-627)NLM368491552 | ||
| 035 | |a (NLM)38359056 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Fatima, Kaniz |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Clustering of home delivery in Bangladesh and its predictors |b Evidence from the linked household and health facility level survey data |
| 264 | 1 | |c 2024 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Revised 17.02.2024 | ||
| 500 | |a published: Electronic-eCollection | ||
| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a Copyright: © 2024 Fatima et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | ||
| 520 | |a Around half of births in Bangladesh occur at home without skilled birth personnel. This study aims to identify the geographical hot spots and cold spots of home delivery in Bangladesh and associated factors. We analyzed data from the 2017/2018 Bangladesh Demographic and Health Survey and the 2017 Bangladesh Health Facility Survey. The outcome variable was home delivery without skilled personnel supervision (yes, no). Explanatory variables included individual, household, community, and healthcare facility level factors. Moran's I was used to determine hot spots (geographic locations with notably high rates of home delivery) and cold spots (geographic areas exhibiting significantly low rates of home delivery) of home delivery. Geographically weighted regression models were used to identify cluster-specific predictors of home delivery. The prevalence of without skilled personnel supervised home delivery was 53.18%. Hot spots of non-supervised and unskilled supervised home delivery were primarily located in Dhaka, Khulna, Rajshahi, and Rangpur divisions. Cold spots of home delivery were mainly located in Mymensingh and Sylhet divisions. Predictors of higher home births in hot spot areas included women's illiteracy, lack of formal job engagement, higher number of children ever born, partner's agriculture occupation, higher community-level illiteracy, and larger distance to the nearest healthcare facility from women's homes. The study findings suggest home delivery is prevalent in Bangladesh. Awareness-building programs should emphasize the importance of skilled and supervised institutional deliveries, particularly among the poor and disadvantaged groups | ||
| 650 | 4 | |a Journal Article | |
| 700 | 1 | |a Khanam, Shimlin Jahan |e verfasserin |4 aut | |
| 700 | 1 | |a Rahman, Md Mostafizur |e verfasserin |4 aut | |
| 700 | 1 | |a Kabir, Md Iqbal |e verfasserin |4 aut | |
| 700 | 1 | |a Khan, Md Nuruzzaman |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t PLOS global public health |d 2021 |g 4(2024), 2 vom: 15., Seite e0002607 |w (DE-627)NLM332849783 |x 2767-3375 |7 nnns |
| 773 | 1 | 8 | |g volume:4 |g year:2024 |g number:2 |g day:15 |g pages:e0002607 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1371/journal.pgph.0002607 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 4 |j 2024 |e 2 |b 15 |h e0002607 | ||