Evidence map›Paper›PMID 25328757›Full record

ReviewScientifica2014

The Preventable Risk Integrated ModEl and Its Use to Estimate the Health Impact of Public Health Policy Scenarios.

Peter Scarborough, Richard A Harrington, Anja Mizdrak, Lijuan Marissa Zhou, Aiden Doherty

Abstract readReview
In one paragraph

Review in Scientifica, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed, 1 pooled it
–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

51 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Modeling the Impact of Behavior Changes on Mortality Attributable to Non-communicable Diseases in Canada.Journal of preventive medicine and public health = Yebang Uihakhoe chi · 2026
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  7. Costa Rica's trans-fat ban impact on cardiovascular disease: a macrosimulation study.Revista panamericana de salud publica = Pan American journal of public health · 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

5 authors.

Peter ScarboroughBritish Heart Foundation Centre on Population Approaches to Non-Communicable Disease Prevention, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK.
Richard A HarringtonBritish Heart Foundation Centre on Population Approaches to Non-Communicable Disease Prevention, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK.
Anja MizdrakBritish Heart Foundation Centre on Population Approaches to Non-Communicable Disease Prevention, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK.
Lijuan Marissa ZhouDCU School of Computing, Dublin City University, Dublin, Ireland.
Aiden DohertyBritish Heart Foundation Centre on Population Approaches to Non-Communicable Disease Prevention, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Noncommunicable disease (NCD) scenario models are an essential part of the public health toolkit, allowing for an estimate of the health impact of population-level interventions that are not amenable to assessment by standard epidemiological study designs (e.g., health-related food taxes and physical infrastructure projects) and extrapolating results from small samples to the whole population. The PRIME (Preventable Risk Integrated ModEl) is an openly available NCD scenario model that estimates the effect of population-level changes in diet, physical activity, and alcohol and tobacco consumption on NCD mortality. The structure and methods employed in the PRIME are described here in detail, including the development of open source code that will support a PRIME web application to be launched in 2015. This paper reviews scenario results from eleven papers that have used the PRIME, including estimates of the impact of achieving government recommendations for healthy diets, health-related food taxes and subsidies, and low-carbon diets. Future challenges for NCD scenario modelling, including the need for more comparisons between models and the improvement of future prediction of NCD rates, are also discussed.

Identifiers

PMID25328757
PMCPMC4195430

What OpenQuestion holds

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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.