Evidence map›Paper›PMID 26781488›Full record

ArticleBMC public health2016

Estimating the potential contribution of stroke treatments and preventative policies to reduce the stroke and ischemic heart disease mortality in Turkey up to 2032: a modelling study.

Duygu Islek, Kaan Sozmen, Belgin Unal, Maria Guzman-Castillo, Ilonca Vaartjes, Julia Critchley, Simon Capewell, Martin O'Flaherty

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 22% 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
  2. Review
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

8 authors at 5 institutions in 3 countries.

Duygu IslekDepartment of Public Health, Dokuz Eylul University, Faculty of Medicine, İzmir, Turkey. duyguislek@hotmail.com.
Kaan SozmenDepartment of Public Health, Faculty of Medicine, Katip Celebi University, İzmir, Turkey. drmelihkaan@hotmail.com.
Belgin UnalDepartment of Public Health, Dokuz Eylul University, Faculty of Medicine, İzmir, Turkey. belgin.unal@deu.edu.tr.
Maria Guzman-CastilloInstitute of Psychology, Health & Society, University of Liverpool, Liverpool, UK. m.guzman-castillo@liverpool.ac.uk.
Ilonca VaartjesDeparment of Public Health and Policy, Institute of Psychology, Health and Society, University of Liverpool, Liverpool, UK. c.h.vaartjes@umcutrecht.nl.
Julia CritchleyDeparment of Public Health and Policy, Institute of Psychology, Health and Society, University of Liverpool, Liverpool, UK. jcritchl@sgul.ac.uk.
Simon CapewellInstitute of Psychology, Health & Society, University of Liverpool, Liverpool, UK. capewell@liverpool.ac.uk.
Martin O'FlahertyInstitute of Psychology, Health & Society, University of Liverpool, Liverpool, UK. moflaher@liv.ac.uk.
University of Liverpool · GBDokuz Eylül University · TRIzmir Kâtip Çelebi University · TRSt George's, University of London · GBUniversity Medical Center Utrecht · NL

Funding

Medical Research Council G0900847
6 · The paper itself

Abstract

backgroundStroke and Ischemic Heart Diseases (IHD) are the main cause of premature deaths globally, including Turkey. There is substantial potential to reduce stroke and IHD mortality burden; particularly by improving diet and health behaviours at the population level. Our aim is to estimate and compare the potential impact of ischemic stroke treatment vs population level policies on ischemic stroke and IHD deaths in Turkey if achieved like other developed countries up to 2022 and 2032.

methodsWe developed a Markov model for the Turkish population aged >35 years. The model follows the population over a time horizon of 10 and 20 years. We modelled seven policy scenarios: a baseline scenario, three ischemic stroke treatment improvement scenarios and three population level policy intervention scenarios (based on target reductions in dietary salt, transfat and unsaturated fat intake, smoking prevalence and increases in fruit and vegetable consumption). Parameter uncertainty was explored by including probabilistic sensitivity analysis.

resultsIn the baseline scenario, we forecast that approximately 655,180 ischemic stroke and IHD deaths (306,500 in men; 348,600 in women) may occur in the age group of 35-94 between 2012 and 2022 in Turkey. Feasible interventions in population level policies might prevent approximately 108,000 (62,580-326,700) fewer stroke and IHD deaths. This could result in approximately a 17% reduction in total stroke and IHD deaths in 2022. Approximately 32%, 29%, 11% and 6% of that figure could be attributed to a decreased consumption of transfat, dietary salt, saturated fats and fall in smoking prevalence and 22% could be attributed to increased fruit and vegetable consumption. Feasible improvements in ischemic stroke treatment could prevent approximately 9% fewer ischemic stroke and IHD deaths by 2022.

conclusionsOur modeling study suggests that effective and evidence-based food policies at the population level could massively contribute to reduction in ischemic stroke and IHD mortality in a decade and deliver bigger gains compared to healthcare based interventions for primary and secondary prevention.

Indexed as

DietAdultAgedAged, 80 and overCoronary Artery DiseaseDietary FatsFeeding BehaviorFemaleHumansMaleMiddle AgedMyocardial IschemiaSecondary PreventionSmoking CessationSodium Chloride, DietaryStrokeDietary FatsSodium Chloride, Dietary

Identifiers

PMID26781488
PMCPMC4717543
OpenAlexW2267508258

What OpenQuestion holds

Textmetadata
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.