Evidence map›Paper›PMID 32121199›Full record

ArticleNutrients2020

The Modelled Population Obesity-Related Health Benefits of Reducing Consumption of Discretionary Foods in Australia.

Anita Lal, Anna Peeters, Vicki Brown, Phuong Nguyen, Huong Ngoc Quynh Tran, Tan Nguyen, Utsana Tonmukayakul, Gary Sacks, Hanny Calache, Jane Martin and 2 more

Open access · goldAbstract read
In one paragraph

Article in Nutrients, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 4 pooled it
5.6field-weighted citation impact, top 3% of its field
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

17 citing papers in PubMed, 4 syntheses or guidelines pooled it, 35 citations in OpenAlex.

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  14. Diet in Scleroderma: Is There a Need for Intervention?Diagnostics (Basel, Switzerland) · 2021
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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

12 authors at 2 institutions in 1 country.

Anita LalDeakin Health Economics, Institute for Health Transformation, Deakin University, Geelong, VIC 3220, Australia.
Anna PeetersGlobal Obesity Centre (GLOBE), Institute for Health Transformation, Deakin University, Geelong, VIC 3220, Australia.
Vicki BrownDeakin Health Economics, Institute for Health Transformation, Deakin University, Geelong, VIC 3220, Australia.
Phuong NguyenDeakin Health Economics, Institute for Health Transformation, Deakin University, Geelong, VIC 3220, Australia.
Huong Ngoc Quynh TranDeakin Health Economics, Institute for Health Transformation, Deakin University, Geelong, VIC 3220, Australia.
Tan NguyenDeakin Health Economics, Institute for Health Transformation, Deakin University, Geelong, VIC 3220, Australia.
Utsana TonmukayakulDeakin Health Economics, Institute for Health Transformation, Deakin University, Geelong, VIC 3220, Australia.
Gary SacksGlobal Obesity Centre (GLOBE), Institute for Health Transformation, Deakin University, Geelong, VIC 3220, Australia.
Hanny CalacheDeakin Health Economics, Institute for Health Transformation, Deakin University, Geelong, VIC 3220, Australia.
Jane MartinObesity Policy Coalition, Cancer Council Victoria, Melbourne VIC 3004 Australia.
Marj MoodieDeakin Health Economics, Institute for Health Transformation, Deakin University, Geelong, VIC 3220, Australia.
Jaithri AnanthapavanDeakin Health Economics, Institute for Health Transformation, Deakin University, Geelong, VIC 3220, Australia.
Deakin University · AUCancer Council Victoria · AU

Funding

Deakin University SRG18-04National Health and Medical Research Council APP1152968
6 · The paper itself

Abstract

Over one third of Australians' daily energy intake is from discretionary foods and drinks. While many health promotion efforts seek to limit discretionary food intake, the population health impact of reductions in the consumption of different types of discretionary foods (e.g., sugar-sweetened beverages (SSBs), confectionery, sweet biscuits) has not been quantified. This study estimated the potential reductions in body weight, obesity-related disease incidence, and healthcare cost savings associated with consumption of one less serving per week of different discretionary foods. Reductions in the different types of discretionary food were modelled individually to estimate the impact on energy consumption and population body weight by 5-year age and sex groups. It was assumed that one serving of discretionary food each week was replaced with either a serving of fruit or popcorn, and a serving (375 mL) of SSBs was replaced with coffee, tea, or milk. Proportional multi-state multiple-cohort Markov modelling estimated likely resultant health adjusted life years (HALYs) gained and healthcare costs saved over the lifetime of the 2010 Australian population. A reduction of one serving of SSBs (375 mL) had the greatest potential impact in terms of weight reduction, particularly in ages 19-24 years (mean 0.31 kg, 95% UI: 0.23 kg to 0.37 kg) and overall healthcare cost savings of AUD 793.4 million (95% UI: 589.1 M to 976.1 M). A decrease of one serving of sweet biscuits had the second largest potential impact on weight change overall, with healthcare cost savings of $640.7 M (95% CI: $402.6 M to $885.8 M) and the largest potential weight reduction amongst those aged 75 years and over (mean 0.21 kg, 95% UI: 0.14 kg to 0.27 kg). The results demonstrate that small reductions in discretionary food consumption are likely to have substantial health benefits at the population level. Moreover, the study highlights that policy responses to improve population diets may need to be tailored to target different types of foods for different population groups.

Indexed as

Feeding BehaviorFoodModels, BiologicalPopulation HealthAdolescentAdultAgedAustraliaChildChild, PreschoolEnergy IntakeFemaleHumansMaleMiddle AgedObesitydiscretionary foodshealthcare costsobesitysugar-sweetened beverages

Identifiers

PMID32121199
PMCPMC7146305
OpenAlexW3010292379

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.