Evidence map›Paper›PMID 24975512›Full record

ArticleClinical nutrition (Edinburgh, Scotland)2015

Dietary indexes, food patterns and incidence of metabolic syndrome in a Mediterranean cohort: The SUN project.

Adriano M Pimenta, Estefanía Toledo, Maria C Rodriguez-Diez, Alfredo Gea, Roberto Lopez-Iracheta, Nitin Shivappa, James R Hébert, Miguel A Martinez-Gonzalez

Abstract read
In one paragraph

Article in Clinical nutrition (Edinburgh, Scotland), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
62citing 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

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

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  19. Dietary Inflammatory Index (DII)International journal of environmental research and public health · 2023
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2 more citing papers are in PubMed but not listed here.

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.

Adriano M PimentaDepartment of Preventive Medicine and Public Health, School of Medicine, University of Navarra, Pamplona, Spain; Department of Maternal and Child Nursing and Public Health, School of Nursing, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil. Electronic address: adrianomp@ufmg.br.
Estefanía ToledoDepartment of Preventive Medicine and Public Health, School of Medicine, University of Navarra, Pamplona, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, Madrid, Spain.
Maria C Rodriguez-DiezHuman Physiology Unit, School of Medicine, University of Navarra, Pamplona, Spain.
Alfredo GeaDepartment of Preventive Medicine and Public Health, School of Medicine, University of Navarra, Pamplona, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, Madrid, Spain.
Roberto Lopez-IrachetaDepartment of Preventive Medicine and Public Health, School of Medicine, University of Navarra, Pamplona, Spain.
Nitin ShivappaCancer Prevention and Control Program, University of South Carolina, Columbia, SC, USA; Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
James R HébertCancer Prevention and Control Program, University of South Carolina, Columbia, SC, USA; Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
Miguel A Martinez-GonzalezDepartment of Preventive Medicine and Public Health, School of Medicine, University of Navarra, Pamplona, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, Madrid, Spain.

Funding

Expanding Mentoring Capacity in High-Risk PopulationsK05CA136975 · NCI · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI HEBERT, JAMES R · 2009 to 2013
$801k
NCI NIH HHS K05 CA136975
6 · The paper itself

Abstract

BACKGROUND &

aimsWe prospectively assessed the association between adherence to several a priori defined healthy food patterns and risk of metabolic syndrome (MetS).

methodsWe assessed 6851 participants of a Spanish dynamic prospective cohort of university graduates, initially free of any MetS-specific definition criteria, and followed-up for a median of 8.3 years. We calculated the adherence to thirteen different a priori defined food patterns or dietary indexes. MetS was classified according to the updated harmonizing criteria. We estimated multivariable-adjusted Incidence Rate Ratios (IRR) of metabolic syndrome and their 95% Confidence Intervals (95% CI), using Poisson regression models.

resultsThe cumulative incidence of MetS was 5.0%. Moderate adherence to the Pro-Vegetarian Diet (PVEG) was significantly associated with a lower risk for developing MetS (IRR = 0.75, 95% CI = 0.59-0.97). Among women, an inverse association with the PVEG was significant not only for a moderate adherence (IRR = 0.54, 95% CI = 0.36-0.82), but also for higher adherence (IRR = 0.63, 95% CI = 0.43-0.93). A higher adherence to the Dietary Approaches to Stop Hypertension (DASH) diet showed an inverse association with the MetS among participants, but only if they had low alcohol intake (RR = 0.41, 95% CI = 0.20-0.85).

conclusionsOur findings support the adoption of a PVEG dietary pattern for the reduction of MetS risk. The same statement can be applied in relation to the DASH diet, insofar a limited consumption of alcoholic beverages is also maintained.

Indexed as

DietDiet, VegetarianAdultAlcoholic BeveragesFemaleFollow-Up StudiesHumansHypertensionIncidenceMaleMetabolic SyndromeMiddle AgedPatient ComplianceProspective StudiesRisk FactorsSpainAlcohol drinkingCohort studiesDiet, vegetarianMetabolic syndrome XSodium restrictedSpain

Identifiers

PMID24975512
PMCPMC4870043

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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.