Food groups and risk of chronic disease: a protocol for a systematic review and network meta-analysis of cohort studies View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-12

AUTHORS

Lukas Schwingshackl, Anna Chaimani, Angela Bechthold, Khalid Iqbal, Marta Stelmach-Mardas, Georg Hoffmann, Carolina Schwedhelm, Sabrina Schlesinger, Heiner Boeing

ABSTRACT

BACKGROUND: There is a lack of systematic and comprehensive evaluations whether food intakes lower or increase risk of chronic diseases. In this network meta-analysis of prospective cohort studies, we aim to evaluate the effects of different foods on risk of chronic diseases. METHODS/DESIGN: We will search PubMed and EMBASE. This will be supplemented by a hand search and author contacts. Citations, abstracts, and relevant papers will be screened for eligibility by two reviewers independently. Prospective cohort studies will be included if they meet the following criteria: (1) evaluate the association of single food or food groups with all-cause mortality, cardiovascular diseases (incidence and mortality), cancer (incidence and mortality) or risk of type 2 diabetes. The following food groups will be evaluated: whole grains, refined grains, vegetables, fruits, nuts, legumes, eggs, dairy products, fish, red meat, processed meat and sugar-sweetened beverages; (2) include participants ≥18 years of age; and (3) study population were free of outcome(s) of interest at the onset of the study. To assess study quality, we will extract the following characteristics: study size, duration of follow-up, dietary assessment method, assessment of outcome and adjustment factors. If the identified studies appear sufficiently similar within and across the different comparisons between pairs of food groups, we will estimate summary-relative effects using random effects network meta-analysis. Subgroup and meta-regression analyses will be performed stratified by different follow-up cut-points, geographical region and sex. DISCUSSION: This is a presentation of the study protocol only. Results and conclusions are pending completion of this study. Our systematic review will be of great value to national and international authorities for evidence-based nutritional recommendation/guidelines, regarding the implementation of food-based dietary guidelines for prevention of chronic diseases. Moreover, our results can be implemented to develop new diet quality indices/scores. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42016037069. More... »

PAGES

125

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s13643-016-0302-9

DOI

http://dx.doi.org/10.1186/s13643-016-0302-9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1018476224

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/27460907


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s13643-016-0302-9'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s13643-016-0302-9'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s13643-016-0302-9'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s13643-016-0302-9'


 

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