Evidence map›Paper›PMID 35203081›Full record

ArticleObesity facts2022

Overweight/Obesity and Time Preference: Evidence from a Survey among Adults in the UK.

Morro M L Touray, David R Cohen, Simon Robert Pask Williams, Mohammed Fasihul Alam, Sam Groves, Mirella Longo, Heather Gage

Abstract read
In one paragraph

Article in Obesity facts, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. The hidden cost of sophistication: economic complexity and obesity.The European journal of health economics : HEPAC : health economics in prevention and care · 2025
    Article
  2. Article
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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

7 authors.

Morro M L TouraySurrey Health Economics Centre, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom.
David R CohenSchool of Care Sciences, Faculty of Life Sciences and Education, University of South Wales, Pontypridd, United Kingdom.
Simon Robert Pask WilliamsInstitute of Management & Health, University of Wales Trinity Saint David, Carmarthen, United Kingdom.
Mohammed Fasihul AlamDepartment of Public Health, College of Health Sciences, QU-Health, Qatar University, Doha, Qatar.
Sam GrovesSwansea Centre for Health Economics, Swansea University, Swansea, United Kingdom.
Mirella LongoMarie Curie Palliative Care Research Centre, School of Medicine, Cardiff University, Cardiff, United Kingdom.
Heather GageSurrey Health Economics Centre, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionOverweight and obesity is a global problem incurring substantial health and economic implications. This has also been highlighted by the ongoing COVID-19 pandemic which has disproportionately affected overweight and obese individuals. Most of the interventions have concentrated on promotion of physical activities and healthy eating which may involve current sacrifices for future health gains. The purpose of this study was to explore the relationship between bodyweight and how individuals state they would trade-off immediate income for higher amounts in the future (time preference).

methodsAn online survey was conducted targeting adults aged >16 years in the UK (England, Northern Ireland, Scotland, and Wales) from January 1, 2016 to July 31, 2016. Using paid online adverts, as well as personal and professional networks for distribution of links to the online survey, the questionnaire asked respondents to report socio-economic and demographic information, height, and weight and to complete a time preference exercise. Data were analysed using descriptive statistics; associations were explored between BMI and respondents' characteristics and time preference using Spearman rank-order correlation and χ2 tests as appropriate. We adopted STROBE guidelines for the reporting of the study.

resultsA total of 561 responses were analysed (female = 293, males = 268). The relationship between time preference and overweight/obesity, using BMI as the measure is highly significant (χ2 = 95.92: p < 0.001). Individuals of normal weight have low time preferences and are more likely to invest in activities in a bid to reap future health benefits. There are also significant relationships between BMI and employment status (χ2 = 37.03; p < 0.001), physical activities (p < 0.0001), income levels (χ2 = 6.68; p < 0.035), family orientation, i.e., with or without children (χ2 = 12.88; p < 0.012), and ethnicity (χ2 = 18.31; p < 0.001). These imply that individuals in employment and with children in their families are less likely to be overweight or obese compared to those who do not. People from black backgrounds are also more likely to be overweight or obese and have higher time preferences compared to people from white backgrounds. DISCUSSIONS/

conclusionsPeople's preventive behaviours today can be predicted by their time preference and this understanding could be vital in improving population's uptake and maintenance of overweight and obesity prevention actions. People who have low time preference are more likely to invest time and resources in physical activities and healthy lifestyles to reap future health benefits hence value utilities-in-anticipation. Public health programmes should therefore use the knowledge of the association between time preference and overweight/obesity to inform designs of intervention programmes.

Indexed as

COVID-19OverweightAdultBody Mass IndexChildFemaleHumansMaleObesityPandemicsSurveys and QuestionnairesUnited KingdomBehavioural economicsEconomics of obesityIntertemporal choiceObesityOverweightPhysical activitiesTime preference

Identifiers

PMID35203081
PMCPMC9210003

What OpenQuestion holds

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Registered trials

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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.