How advanced is the epidemiological transition in Papua New Guinea? New evidence from verbal autopsy.

Autor:	Hart JD; Melbourne School of Population and Global Health, University of Melbourne, Carlton, VIC, Australia., Kwa V; Melbourne School of Population and Global Health, University of Melbourne, Carlton, VIC, Australia., Dakulala P; National Department of Health, Islander Drive, Port Moresby, Papua New Guinea., Ripa P; Western Highlands Provincial Health Authority, Mt Hagen, Papua New Guinea., Frank D; Milne Bay Provincial Health Authority, Alotau, Papua New Guinea., Golpak V; West New Britain Provincial Health Authority, Kimbe, Papua New Guinea., Adair T; Melbourne School of Population and Global Health, University of Melbourne, Carlton, VIC, Australia., Mclaughlin D; Melbourne School of Population and Global Health, University of Melbourne, Carlton, VIC, Australia., Riley ID; Melbourne School of Population and Global Health, University of Melbourne, Carlton, VIC, Australia., Lopez AD; Melbourne School of Population and Global Health, University of Melbourne, Carlton, VIC, Australia.
Jazyk:	angličtina
Zdroj:	International journal of epidemiology [Int J Epidemiol] 2022 Jan 06; Vol. 50 (6), pp. 2058-2069. Date of Electronic Publication: 2021 May 02.
DOI:	10.1093/ije/dyab088
Abstrakt:	Background: Reliable cause of death (COD) data are not available for the majority of deaths in Papua New Guinea (PNG), despite their critical policy value. Automated verbal autopsy (VA) methods, involving an interview and automated analysis to diagnose causes of community deaths, have recently been trialled in PNG. Here, we report VA results from three sites and highlight the utility of these methods to generate information about the leading CODs in the country. Methods: VA methods were introduced in one district in each of three provinces: Alotau in Milne Bay; Tambul-Nebilyer in Western Highlands; and Talasea in West New Britain. VA interviews were conducted using the Population Health Metrics Research Consortium (PHMRC) shortened questionnaire and analysed using the SmartVA automated diagnostic algorithm. Results: A total of 1655 VAs were collected between June 2018 and November 2019, 87.0% of which related to deaths at age 12 years and over. Our findings suggest a continuing high proportion of deaths due to infectious diseases (27.0%) and a lower proportion of deaths due to non-communicable diseases (NCDs) (50.8%) than estimated by the Global Burden of Disease Study (GBD) 2017: 16.5% infectious diseases and 70.5% NCDs. The proportion of injury deaths was also high compared with GBD: 22.5% versus 13.0%. Conclusions: Health policy in PNG needs to address a 'triple burden' of high infectious mortality, rising NCDs and a high fraction of deaths due to injuries. This study demonstrates the potential of automated VA methods to generate timely, reliable and policy-relevant data on COD patterns in hard-to-reach populations in PNG. (© The Author(s) 2021. Published by Oxford University Press on behalf of the International Epidemiological Association.)
Databáze:	MEDLINE
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