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OP51 Associations between the social environment and cardiometabolic health outcomes: systematic review (and meta-analysis)

2022· article· en· W4298187864 on OpenAlexaboutno aff
Taymara C. Abreu, Joline W.J. Beulens, Linda Schoonmade, Joreintje D. Mackenbach

Bibliographic record

VenueSSM Annual Scientific Meeting · 2022
Typearticle
Languageen
FieldMedicine
TopicHyperglycemia and glycemic control in critically ill and hospitalized patients
Canadian institutionsnot available
Fundersnot available
KeywordsHyperinsulinismMedicinePediatricsCongenital hyperinsulinismHypertrophic cardiomyopathyInternal medicineHypoglycemiaGestational diabetesHeart diseaseInsulinCardiologyPregnancyGestationInsulin resistance

Abstract

fetched live from OpenAlex

<h3>Background</h3> A number of studies has investigated the relationship between the social environment and lifestyle behaviours. However, to what extent the relation between the social environment (<i>i.e.,</i> the social relationships and social context in which groups of people live and interact) and lifestyle behaviours extends to cardiometabolic disease outcomes is unknown. This systematic review and meta-analysis systematically summarizes the available evidence. <h3>Methods</h3> We systematically searched PubMed (Medline), Scopus, and Web of Science from inception to 16 February 2021. Outcomes of included studies were type 2 diabetes mellitus and cardiovascular diseases and determinants were social environmental factors such as area-level deprivation and social network size. Titles and abstracts were screened in duplicate. We assessed the quality of the studies using the Newcastle-Ottawa Scale (NOS). We meta-analysed associations when ≥3 binary associations were available per social environment dimension and when those were generated by high quality papers. For the sake of this abstract, we only present results for stroke outcomes but full results will be available at the time of the conference. The protocol was registered in PROSPERO (ID:CRD42021223035). <h3>Results</h3> From 7,671 records screened, 218 were included and 35 focused on stroke. Of these, 33 were conducted in high income countries, 60% (n=21) applied a longitudinal design, and 50% (n=17) were of poor or fair quality. Among the 35 studies, 97 relevant associations were investigated. The largest number of associations investigated was related to the dimension <i>Economic and Social Disadvantage</i> (71%), followed by<i> Social Relationships and Norms</i> (16%), <i>Discrimination and Segregation</i> (8%),and <i>Social Cohesion and Social Capital</i> (2%). Limited evidence was found for the remaining dimensions (<i>Crime and Safety</i>, <i>Civic Participation and Engagement</i> and <i>Disorder and Incivilities)</i> in relation to stroke. Meta-analysis of binary data from high quality studies was only possible for <i>Economic and Social Disadvantage</i>. More <i>Economic and Social Disadvantage</i> was associated with higher stroke risk/prevalence (n=5; OR=1.10; 95% CI, 1.03–1.17; I<sup>2</sup>=<i>39.76%</i>). <h3>Conclusion</h3> Higher levels of economic and social disadvantage seem to contribute to increased stroke risk. During the conference we will present full results of the systematic review and meta-analysis, including underexplored dimensions such as <i>Discrimination and Segregation, Crime and Safety, Civic Participation and Engagement</i> and<i> Disorder and Incivilities</i>.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.636
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.335
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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