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Social determinants of injury-attributed mortality in Papua New Guinea: new data from the Comprehensive Health and Epidemiological Surveillance System
OBJECTIVE: This study reported the prevalence and sociodemographic distribution of mortalities attributed to injuries in Papua New Guinea (PNG). SETTING: As part of a longitudinal study, mortality data were collected from the population who live in eight surveillance sites of the Comprehensive Healt...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9677002/ https://www.ncbi.nlm.nih.gov/pubmed/36400734 http://dx.doi.org/10.1136/bmjopen-2022-064777 |
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author | Pham, Bang Nguyen Maraga, Seri Kue, Lydia Silas, Vinson D Abori, Norah Jorry, Ronny Okely, Tony Pomat, William |
author_facet | Pham, Bang Nguyen Maraga, Seri Kue, Lydia Silas, Vinson D Abori, Norah Jorry, Ronny Okely, Tony Pomat, William |
author_sort | Pham, Bang Nguyen |
collection | PubMed |
description | OBJECTIVE: This study reported the prevalence and sociodemographic distribution of mortalities attributed to injuries in Papua New Guinea (PNG). SETTING: As part of a longitudinal study, mortality data were collected from the population who live in eight surveillance sites of the Comprehensive Health and Epidemiological Surveillance System, established in six major provinces in PNG. Verbal autopsy (VA) interviews were conducted by the surveillance team with close relatives of the deceased, using the WHO 2016 VA instrument from January 2018 to December 2020. PARTICIPANT AND INTERVENTION: Mortality data from 926 VA interviews were analysed, using the InterVA-5 diagnostic tool to assign specific cause of death (COD). Distributions of injury-attributed mortality were calculated and multinomial logistic regression analyses were conducted to identify sociodemographic factors and provide ORs, 95% CIs of estimates and p values. RESULT: Injury-attributed deaths accounted for 13% of the total deaths recorded in the surveillance population, with the highest proportion in Madang (22%), followed by Port Moresby and Central Province (13%). Road traffic accidents were the leading COD, accounting for 43% of the total injury-attributed deaths, followed by assaults (25%) and accidental falls (10%). Young adults (aged 15–24 years) accounted the largest proportion of injury-attributed deaths (34%) and were nearly six times more likely to die from injuries than those aged 75+ years (OR: 5.89 (95% CI: 2.18 to 15.9); p<0.001). Males were twice more likely to die from injuries than females (OR: 2.0 (95% CI: 1.19 to 3.36); p=0.009). Another significant sociodemographic factor associated with the increased injury-attributed mortalities included urban versus rural residence (OR: 2.0 (95% CI: 1.01 to 3.99); p=0.048). CONCLUSION: Young adults, particularly those who live in urban areas, were at the highest risk of dying from injuries. Public health policies and interventions are needed to reduce premature mortality from injuries in PNG. |
format | Online Article Text |
id | pubmed-9677002 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-96770022022-11-22 Social determinants of injury-attributed mortality in Papua New Guinea: new data from the Comprehensive Health and Epidemiological Surveillance System Pham, Bang Nguyen Maraga, Seri Kue, Lydia Silas, Vinson D Abori, Norah Jorry, Ronny Okely, Tony Pomat, William BMJ Open Global Health OBJECTIVE: This study reported the prevalence and sociodemographic distribution of mortalities attributed to injuries in Papua New Guinea (PNG). SETTING: As part of a longitudinal study, mortality data were collected from the population who live in eight surveillance sites of the Comprehensive Health and Epidemiological Surveillance System, established in six major provinces in PNG. Verbal autopsy (VA) interviews were conducted by the surveillance team with close relatives of the deceased, using the WHO 2016 VA instrument from January 2018 to December 2020. PARTICIPANT AND INTERVENTION: Mortality data from 926 VA interviews were analysed, using the InterVA-5 diagnostic tool to assign specific cause of death (COD). Distributions of injury-attributed mortality were calculated and multinomial logistic regression analyses were conducted to identify sociodemographic factors and provide ORs, 95% CIs of estimates and p values. RESULT: Injury-attributed deaths accounted for 13% of the total deaths recorded in the surveillance population, with the highest proportion in Madang (22%), followed by Port Moresby and Central Province (13%). Road traffic accidents were the leading COD, accounting for 43% of the total injury-attributed deaths, followed by assaults (25%) and accidental falls (10%). Young adults (aged 15–24 years) accounted the largest proportion of injury-attributed deaths (34%) and were nearly six times more likely to die from injuries than those aged 75+ years (OR: 5.89 (95% CI: 2.18 to 15.9); p<0.001). Males were twice more likely to die from injuries than females (OR: 2.0 (95% CI: 1.19 to 3.36); p=0.009). Another significant sociodemographic factor associated with the increased injury-attributed mortalities included urban versus rural residence (OR: 2.0 (95% CI: 1.01 to 3.99); p=0.048). CONCLUSION: Young adults, particularly those who live in urban areas, were at the highest risk of dying from injuries. Public health policies and interventions are needed to reduce premature mortality from injuries in PNG. BMJ Publishing Group 2022-11-17 /pmc/articles/PMC9677002/ /pubmed/36400734 http://dx.doi.org/10.1136/bmjopen-2022-064777 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Global Health Pham, Bang Nguyen Maraga, Seri Kue, Lydia Silas, Vinson D Abori, Norah Jorry, Ronny Okely, Tony Pomat, William Social determinants of injury-attributed mortality in Papua New Guinea: new data from the Comprehensive Health and Epidemiological Surveillance System |
title | Social determinants of injury-attributed mortality in Papua New Guinea: new data from the Comprehensive Health and Epidemiological Surveillance System |
title_full | Social determinants of injury-attributed mortality in Papua New Guinea: new data from the Comprehensive Health and Epidemiological Surveillance System |
title_fullStr | Social determinants of injury-attributed mortality in Papua New Guinea: new data from the Comprehensive Health and Epidemiological Surveillance System |
title_full_unstemmed | Social determinants of injury-attributed mortality in Papua New Guinea: new data from the Comprehensive Health and Epidemiological Surveillance System |
title_short | Social determinants of injury-attributed mortality in Papua New Guinea: new data from the Comprehensive Health and Epidemiological Surveillance System |
title_sort | social determinants of injury-attributed mortality in papua new guinea: new data from the comprehensive health and epidemiological surveillance system |
topic | Global Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9677002/ https://www.ncbi.nlm.nih.gov/pubmed/36400734 http://dx.doi.org/10.1136/bmjopen-2022-064777 |
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