Evidence map›Paper›PMID 31640631›Full record

ArticleBMC public health2019

Estimating the pattern of causes of death in Papua New Guinea.

Urarang Kitur, Tim Adair, Ian Riley, Alan D Lopez

Abstract read
In one paragraph

Article in BMC public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Article
  2. Denisovan admixture facilitated environmental adaptation in Papua New Guinean populations.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Physical activity and sitting time in occupational groups from Papua New Guinea.International archives of occupational and environmental health · 2022
    Article
  9. Article
  10. Article
  11. Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Urarang KiturMelbourne School of Population and Global Health, University of Melbourne, Melbourne, Carlton, Victoria, Australia. u.kitur@student.unimelb.edu.au.
Tim AdairMelbourne School of Population and Global Health, University of Melbourne, Melbourne, Carlton, Victoria, Australia.
Ian RileyMelbourne School of Population and Global Health, University of Melbourne, Melbourne, Carlton, Victoria, Australia.
Alan D LopezMelbourne School of Population and Global Health, University of Melbourne, Melbourne, Carlton, Victoria, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPapua New Guinea (PNG) is a diverse country with high mortality and evidence of increased prevalence of non-communicable diseases (NCDs), but there is no reliable cause of death (COD) data because civil registration is insufficient and routine health data comprise only a small proportion of deaths. This study aims to estimate cause-specific mortality fractions (CSMFs) for five broad groups of causes (endemic infections, emerging infections, endemic NCDs, emerging NCDs and injuries), by sex for each of PNG's provinces.

methodsCSMFs are calculated as the average of estimates obtained from: (1) Empirical cause method: Utilising available Verbal Autopsy (VA) data and Discharge Health Information System (DHIS) data, and applying statistical models of community versus facility CODs; and (2) Expected cause patterns method: Utilising existing estimates of mortality levels in each province and statistical models of the relationship between all-cause and cause-specific mortality using Global Burden of Disease (GBD) data.

resultsAn estimated 41% of male and 49% of female deaths in PNG are due to infectious, maternal (female only), neonatal and nutritional causes. Furthermore, 45% of male and 42% of female deaths arise from NCDs. Infectious diseases, maternal, neonatal and nutritional conditions account for more than half the deaths in a number of provinces, including lower socioeconomic status provinces of Gulf and Sandaun, while provinces with higher CSMFs from emerging NCDs (e.g. ischemic heart disease, stroke) tend to be those where socioeconomic status is comparatively high (e.g. National Capital District, Western Highlands Province, Manus Province, New Ireland Province and East New Britain Province). Provinces with the highest estimated proportion of deaths from emerging infectious diseases are readily accessible by road and have the highest rates of sexually transmitted infections (STIs), while provinces with the highest CSMFs from endemic infectious, maternal, neonatal and nutritional causes are geographically isolated, have high malaria and high all-cause mortality.

conclusionsInfectious, maternal, neonatal and nutritional causes continue to be an important COD in PNG, and are likely to be higher than what is estimated by the GBD. Nonetheless, there is evidence of the emergence of NCDs in provinces with higher socioeconomic status. The introduction of routine VA for non-facility deaths should improve COD data quality to support health policy and planning to control both infectious and NCDs.

Indexed as

Cause of DeathCommunicable DiseasesCommunicable Diseases, EmergingFemaleGlobal Burden of DiseaseHumansInfantMaleMortalityMyocardial IschemiaNoncommunicable DiseasesPapua New GuineaSocial ClassCause of deathCause-specific mortality fractionsEmerging diseasesInequalitiesInfectious diseaseNon-communicable diseasePapua New Guinea

Identifiers

PMID31640631
PMCPMC6805633

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.