Evidence map›Paper›PMID 29516222›Full record

ArticleEuropean journal of nutrition2019

Burden and trend of diet-related non-communicable diseases in Australia and comparison with 34 OECD countries, 1990-2015: findings from the Global Burden of Disease Study 2015.

Yohannes Adama Melaku, Andre Renzaho, Tiffany K Gill, Anne W Taylor, Eleonora Dal Grande, Barbora de Courten, Estifanos Baye, David Gonzalez-Chica, Elina Hyppӧnen, Zumin Shi and 3 more

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in European journal of nutrition, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 2 pooled it
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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

37 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

13 authors.

Yohannes Adama MelakuAdelaide Medical School, The University of Adelaide, Adelaide, Australia. adamayohannes@gmail.com.ORCID http://orcid.org/0000-0002-3051-7313
Andre RenzahoSchool of Social Sciences and Psychology, Western Sydney University, Sydney, NSW, Australia.
Tiffany K GillAdelaide Medical School, The University of Adelaide, Adelaide, Australia.
Anne W TaylorAdelaide Medical School, The University of Adelaide, Adelaide, Australia.
Eleonora Dal GrandeAdelaide Medical School, The University of Adelaide, Adelaide, Australia.
Barbora de CourtenMonash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, Australia.
Estifanos BayeMonash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, Australia.
David Gonzalez-ChicaAdelaide Medical School, The University of Adelaide, Adelaide, Australia.
Elina HyppӧnenCentre for Population Health Research, Sansom Institute, University of South Australia, Adelaide, Australia.
Zumin ShiAdelaide Medical School, The University of Adelaide, Adelaide, Australia.
Malcolm RileyCommonwealth Scientific and Industrial Research Organisation (CSIRO), Adelaide, SA, Australia.
Robert AdamsHealth Observatory, Discipline of Medicine, The Queen Elizabeth Hospital Campus, The University of Adelaide, Adelaide, Australia.
Yohannes KinfuFaculty of Health, University of Canberra, Canberra, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiet is a major determining factor for many non-communicable chronic diseases (NCDs). However, evidence on diet-related NCD burden remains limited. We assessed the trends in diet-related NCDs in Australia from 1990 to 2015 and compared the results with other countries of the Organization for Economic Co-operation and Development (OECD).

methodsWe used data and methods from the Global Burden of Disease (GBD) 2015 study to estimate the NCD mortality and disability-adjusted life years (DALYs) attributable to 14 dietary risk factors in Australia and 34 OECD nations. Countries were further ranked from the lowest (first) to highest (35th) burden using an age-standardized population attributable fraction (PAF).

resultsIn 2015, the estimated number of deaths attributable to dietary risks was 29,414 deaths [95% uncertainty interval (UI) 24,697 - 34,058 or 19.7% of NCD deaths] and 443,385 DALYs (95% UI 377,680-511,388 or 9.5% of NCD DALYs) in Australia. Young (25-49 years) and middle-age (50-69 years) male adults had a higher PAF of diet-related NCD deaths and DALYs than their female counterparts. Diets low in fruits, vegetables, nuts and seeds and whole grains, but high in sodium, were the major contributors to both NCD deaths and DALYs. Overall, 42.3% of cardiovascular deaths were attributable to dietary risk factors. The age-standardized PAF of diet-related NCD mortality and DALYs decreased over the study period by 28.2% (from 27.0% in 1990 to 19.4% in 2015) and 41.0% (from 14.3% in 1990 to 8.4% in 2015), respectively. In 2015, Australia ranked 12th of 35 examined countries in diet-related mortality. A small improvement of rank was recorded compared to the previous 25 years.

conclusionsDespite a reduction in diet-related NCD burden over 25 years, dietary risks are still the major contributors to a high burden of NCDs in Australia. Interventions targeting NCDs should focus on dietary behaviours of individuals and population groups.

Indexed as

Cost of IllnessAdultAgedAged, 80 and overAge FactorsAustraliaChronic DiseaseDietFemaleGlobal Burden of DiseaseGlobal HealthHumansMaleMiddle AgedNoncommunicable DiseasesOrganisation for Economic Co-Operation and DevelopmentAustraliaBurden of diseaseDietary risk factorsNon-communicable diseasesOECD countries

Identifiers

PMID29516222

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.