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Distribution of cause of death in rural Bangladesh during 2003–2010: evidence from two rural areas within Matlab Health and Demographic Surveillance site

OBJECTIVE: This study used the InterVA-4 computerised model to assign probable cause of death (CoD) to verbal autopsies (VAs) generated from two rural areas, with a difference in health service provision, within the Matlab Health and Demographic Surveillance site (HDSS). This study aimed to compare...

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Autores principales: Alam, Nurul, Chowdhury, Hafizur R., Ahmed, Ali, Rahman, Mahfuzur, Streatfield, P. Kim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Co-Action Publishing 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4220145/
https://www.ncbi.nlm.nih.gov/pubmed/25377333
http://dx.doi.org/10.3402/gha.v7.25510
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author Alam, Nurul
Chowdhury, Hafizur R.
Ahmed, Ali
Rahman, Mahfuzur
Streatfield, P. Kim
author_facet Alam, Nurul
Chowdhury, Hafizur R.
Ahmed, Ali
Rahman, Mahfuzur
Streatfield, P. Kim
author_sort Alam, Nurul
collection PubMed
description OBJECTIVE: This study used the InterVA-4 computerised model to assign probable cause of death (CoD) to verbal autopsies (VAs) generated from two rural areas, with a difference in health service provision, within the Matlab Health and Demographic Surveillance site (HDSS). This study aimed to compare CoD by gender, as well as discussing possible factors which could influence differences in the distribution of CoD between the two areas. DESIGN: Data for this study came from the Matlab the HDSS maintained by the International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) since 1966. In late 1977, icddr,b divided HDSS and implemented a high-quality maternal, newborn and child health and family planning (MNCH-FP) services project in one half, called the icddr,b service area (SA), in addition to the usual public and private MNCH-FP services that serve the other half, called the government SA. HDSS field workers registered 12,144 deaths during 2003–2010, and trained interviewers obtained VA for 98.9% of them. The probabilistic model InterVA-4 probabilistic model (version 4.02) was used to derive probable CoD from VA symptoms. Cause-specific mortality rates and fractions were compared across gender and areas. Appropriate statistical tests were applied for significance testing. RESULTS: Mortality rates due to neonatal causes and communicable diseases (CDs) were lower in the icddr,b SA than in the government SA, where mortality rates due to non-communicable diseases (NCDs) were lower. Cause-specific mortality fractions (CSMFs) due to CDs (23.2% versus 18.8%) and neonatal causes (7.4% versus 6%) were higher in the government SA, whereas CSMFs due to NCDs were higher (58.2% versus 50.7%) in the icddr,b SA. The rank-order of CSMFs by age group showed marked variations, the largest category being acute respiratory infection/pneumonia in infancy, injury in 1–4 and 5–14 years, neoplasms in 15–49 and 50–64 years, and stroke in 65+ years. CONCLUSIONS: Automated InterVA-4 coding of VA to determine probable CoD revealed the difference in the structure of CoD between areas with prominence of NCDs in both areas. Such information can help local planning of health services for prevention and management of disease burden.
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spelling pubmed-42201452014-12-02 Distribution of cause of death in rural Bangladesh during 2003–2010: evidence from two rural areas within Matlab Health and Demographic Surveillance site Alam, Nurul Chowdhury, Hafizur R. Ahmed, Ali Rahman, Mahfuzur Streatfield, P. Kim Glob Health Action Indepth Network Cause-Specific Mortality OBJECTIVE: This study used the InterVA-4 computerised model to assign probable cause of death (CoD) to verbal autopsies (VAs) generated from two rural areas, with a difference in health service provision, within the Matlab Health and Demographic Surveillance site (HDSS). This study aimed to compare CoD by gender, as well as discussing possible factors which could influence differences in the distribution of CoD between the two areas. DESIGN: Data for this study came from the Matlab the HDSS maintained by the International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) since 1966. In late 1977, icddr,b divided HDSS and implemented a high-quality maternal, newborn and child health and family planning (MNCH-FP) services project in one half, called the icddr,b service area (SA), in addition to the usual public and private MNCH-FP services that serve the other half, called the government SA. HDSS field workers registered 12,144 deaths during 2003–2010, and trained interviewers obtained VA for 98.9% of them. The probabilistic model InterVA-4 probabilistic model (version 4.02) was used to derive probable CoD from VA symptoms. Cause-specific mortality rates and fractions were compared across gender and areas. Appropriate statistical tests were applied for significance testing. RESULTS: Mortality rates due to neonatal causes and communicable diseases (CDs) were lower in the icddr,b SA than in the government SA, where mortality rates due to non-communicable diseases (NCDs) were lower. Cause-specific mortality fractions (CSMFs) due to CDs (23.2% versus 18.8%) and neonatal causes (7.4% versus 6%) were higher in the government SA, whereas CSMFs due to NCDs were higher (58.2% versus 50.7%) in the icddr,b SA. The rank-order of CSMFs by age group showed marked variations, the largest category being acute respiratory infection/pneumonia in infancy, injury in 1–4 and 5–14 years, neoplasms in 15–49 and 50–64 years, and stroke in 65+ years. CONCLUSIONS: Automated InterVA-4 coding of VA to determine probable CoD revealed the difference in the structure of CoD between areas with prominence of NCDs in both areas. Such information can help local planning of health services for prevention and management of disease burden. Co-Action Publishing 2014-10-29 /pmc/articles/PMC4220145/ /pubmed/25377333 http://dx.doi.org/10.3402/gha.v7.25510 Text en © 2014 Nurul Alam et al. http://creativecommons.org/licenses/by/4.0/ 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 work is properly cited.
spellingShingle Indepth Network Cause-Specific Mortality
Alam, Nurul
Chowdhury, Hafizur R.
Ahmed, Ali
Rahman, Mahfuzur
Streatfield, P. Kim
Distribution of cause of death in rural Bangladesh during 2003–2010: evidence from two rural areas within Matlab Health and Demographic Surveillance site
title Distribution of cause of death in rural Bangladesh during 2003–2010: evidence from two rural areas within Matlab Health and Demographic Surveillance site
title_full Distribution of cause of death in rural Bangladesh during 2003–2010: evidence from two rural areas within Matlab Health and Demographic Surveillance site
title_fullStr Distribution of cause of death in rural Bangladesh during 2003–2010: evidence from two rural areas within Matlab Health and Demographic Surveillance site
title_full_unstemmed Distribution of cause of death in rural Bangladesh during 2003–2010: evidence from two rural areas within Matlab Health and Demographic Surveillance site
title_short Distribution of cause of death in rural Bangladesh during 2003–2010: evidence from two rural areas within Matlab Health and Demographic Surveillance site
title_sort distribution of cause of death in rural bangladesh during 2003–2010: evidence from two rural areas within matlab health and demographic surveillance site
topic Indepth Network Cause-Specific Mortality
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4220145/
https://www.ncbi.nlm.nih.gov/pubmed/25377333
http://dx.doi.org/10.3402/gha.v7.25510
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