ArticleInternational journal of obesity (2005)2018
Data visualisation to support obesity policy: case studies of data tools for planning and transport policy in the UK.
Article in International journal of obesity (2005), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.
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.
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.
Who cites it
9 citing papers in PubMed.
- The UK Food Environment: A Systematic Review of Domains, Methodologies, and Outcomes.Current developments in nutrition · 2025Review
- A spatial obesity risk score for describing the obesogenic environment using kernel density estimation: development and parameter variation.BMC medical research methodology · 2023Article
- Interactive Visualization Applications in Population Health and Health Services Research: Systematic Scoping Review.Journal of medical Internet research · 2022Article
- Stakeholder experiences of using online spatial data visualisation tools for local public health decision support: A qualitative study.Health & place · 2021Article
- Developing effective data visualization tools for nutrition: reflections on the design of a Nutrition Scorecard in Nigeria.Gates open research · 2021Article
- Dissemination Strategies to Accelerate the Policy Impact of Children's Mental Health Services Research.Psychiatric services (Washington, D.C.) · 2020Article
- Overweight and obesity of school-age children in El Salvador according to two international systems: a population-based multilevel and spatial analysis.BMC public health · 2020Article
- Evidence from big data in obesity research: international case studies.International journal of obesity (2005) · 2020Article
- Creating a long-term future for big data in obesity research.International journal of obesity (2005) · 2019Article
Corrections and comments
- Erratum issued
- Erratum issued
Authors and funding
6 authors.
Funding
Abstract
Data visualisation is becoming an established way to drive discovery and develop theory and hypotheses among researchers. Data visualisations can also serve as tools for knowledge translation with policy makers, who are increasingly using data and evidence to inform and implement policy. For obesity policy, data visualisation tools can help policy makers and other professionals understand the socio-spatial distribution of risk factors and quantify social and environmental conditions that are recognised upstream determinants of diet, activity and obesity. The demand for and use of data visualisation tools can be driven by an identified policy need, which can be met by researchers and data scientists. Alternatively, researchers are developing and testing data visualisations, which may be subsequently adapted for, and adopted by policy users.Two recently-released interactive data visualisation tools in the UK illustrate these points. The Propensity to Cycle Tool (PCT) was developed with funding from the UK government to inform the investment of cycling infrastructure in England. The Food environment assessment tool (Feat) evolved as a translational output from a programme of epidemiological research. This article uses PCT and Feat as case studies, drawing parallels and contrasts between them. We discuss these two tools from policy context and scientific underpinnings, to product launch and evaluation. We review challenges inherent in the development and dissemination of data tools for policy, including the need for technical expertise, feedback integration, long-term sustainability, and provision of training and user support. Finally, we attempt to derive learning points that may help overcome challenges associated with the creation, dissemination and sustaining of data tools for policy. We contend that, despite a number of challenges, data tools provide a novel gateway between researchers and a range of stakeholders, who are seeking ways of accessing and using evidence to inform obesity programs and policies.
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What OpenQuestion holds
Registered trials
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.