Evidence map›Paper›PMID 31963262›Full record

ArticleInternational journal of environmental research and public health2020

Eating Out and Consumers' Health: Evidence on Obesity and Balanced Nutrition Intakes.

Dahye Kim, Byeong-Il Ahn

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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  6. Purchase of food for away-from-home consumption according to urban and rural areas of Brazil between 2002 and 2018.Revista brasileira de epidemiologia = Brazilian journal of epidemiology · 2025
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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

2 authors.

Dahye KimDepartment of Agricultural, Food, and Resource Economics, Michigan State University, East Lansing, MI 48823, USA.
Byeong-Il AhnDepartment of Food and Resource Economics, Korea University, Seoul 02841, Korea.ORCID 0000-0002-3504-2898

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Changes in demographic and socioeconomic characteristics have contributed to an increase in away-from-home food consumption. Although consumers are increasingly demanding higher quality food, unbalanced nutrition intakes and health issues such as obesity remain prominent predicaments. This paper investigates the relationship between the frequency of having Food Away From Home (FAFH), balanced dietary intakes, and obesity (controlling for covariates) among Korean adults aged 19 to 64. Whether there exists a linear relationship between the number of having FAFH and health outcome is investigated and the optimal number of having FAFH that leads to the best health outcome is identified in the study. The results suggest that Food Away From Home generally increases deviations of dietary intakes from the reference intakes and high-frequency FAFH consumers have an elevated chance of being obese (36.22%). However, having FAFH 1-7 times per week is associated with decreased body mass index (BMI) and a lower chance of being obese in comparison to the outcomes of having food at home. The optimal level of consuming FAFH is identified to be 5-7 times per week in terms of BMI and obesity. However, consuming no FAFH is suggested to be the best in terms of balanced nutrition intake.

Indexed as

Feeding BehaviorNutritional StatusNutrition SurveysObesityAdultBody Mass IndexData CollectionEnergy IntakeFemaleFoodHumansMaleMiddle AgedRepublic of KoreaYoung Adultbalanced dietary intakesdoubly robust estimationfood away from homeinverse probability weighted regression adjustmentobesity

Identifiers

PMID31963262
PMCPMC7014261

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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.