Evidence map›Paper›PMID 27572276›Full record

ArticlePublic health nutrition2017

Discretionary food and beverage consumption and its association with demographic characteristics, weight status, and fruit and vegetable intakes in Australian adults.

Zhixian Sui, Weng Kei Wong, Jimmy Chun Yu Louie, Anna Rangan

Open access · bronzeAbstract read
In one paragraph

Article in Public health nutrition, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 1 pooled it
5.4field-weighted citation impact, top 4% 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

37 citing papers in PubMed, 1 synthesis or guideline pooled it, 77 citations in OpenAlex.

  1. Social media use for nutrition outcomes in young adults: a mixed-methods systematic review.The international journal of behavioral nutrition and physical activity · 2018
    Pooled it
  2. Trial
  3. Trial
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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 at 2 institutions in 2 countries.

Zhixian Sui1Level 4 EAST,Charles Perkins Centre (D17),The University of Sydney, Johns Hopkins Drive,Camperdown,NSW 2050,Australia.
Weng Kei Wong1Level 4 EAST,Charles Perkins Centre (D17),The University of Sydney, Johns Hopkins Drive,Camperdown,NSW 2050,Australia.
Jimmy Chun Yu Louie1Level 4 EAST,Charles Perkins Centre (D17),The University of Sydney, Johns Hopkins Drive,Camperdown,NSW 2050,Australia.
Anna Rangan1Level 4 EAST,Charles Perkins Centre (D17),The University of Sydney, Johns Hopkins Drive,Camperdown,NSW 2050,Australia.
University of Sydney · AUUniversity of Hong Kong · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveExcessive consumption of discretionary foods/beverages in the Australian population has been identified, increasing the risk of obesity and chronic disease. The present study aimed to examine the associations between demographic, anthropometric and dietary factors and the consumption of discretionary foods, discretionary beverages and discretionary foods/beverages combined.

designDiscretionary food/beverage consumption reported in two 24 h recalls was analysed, stratified by gender, age, socio-economic status, country of birth, BMI, waist circumference, and fruit and vegetable intakes.

setting2011-12 National Nutrition and Physical Activity Survey. SUBJECTS: Australian adults (n 7873) aged 19 years or above.

resultsMean discretionary food and beverage consumption was 631 g (28 % by weight from foods; 72 % from beverages), providing 2721 kJ of energy intake (72 % from foods; 28 % from beverages). Total discretionary food/beverage consumption was higher in younger age groups (P<0·001), those in lower socio-economic categories (P<0·001), those born in Australia (P<0·001), those with higher BMI (P<0·001) and those with lower fruit (P<0·001) or vegetable intake (P<0·001). Discretionary beverage consumption (β=6·6, P<0·001) was more strongly associated with BMI than discretionary food consumption (β=0·5, P=0·01).

conclusionsTotal discretionary food/beverage consumption as well as discretionary foods alone and discretionary beverages alone were associated with BMI in Australian adults. In addition, high intakes were associated with younger age, lower socio-economic status, and lower consumption of fruit and vegetables.

Indexed as

Body Mass IndexFruitVegetablesAdultAge FactorsAustraliaBeveragesDemographyDietEatingEnergy IntakeFemaleHumansMaleSocial ClassYoung AdultAustraliaBMIDietary patternDiscretionary foodExtra food

Identifiers

PMID27572276
PMCPMC10261270
OpenAlexW2512322411

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.