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Record W3093312088 · doi:10.1136/bmjopen-2020-039278

Impact of incarceration on cardiovascular disease risk factors: a systematic review and meta-regression on weight and BMI change

2020· review· en· W3093312088 on OpenAlexaffabout
Constantin Bondolfi, Patrick Taffé, Aurélie Augsburger, Cécile Jaques, Mary Malebranche, Carole Clair, Patrick Bodenmann

Bibliographic record

VenueBMJ Open · 2020
Typereview
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicinePrisonMeta-regressionObesityBody mass indexSystematic reviewMeta-analysisGerontologyWeight changeMEDLINEDiseaseEnvironmental healthDemographyWeight lossInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Cardiovascular disease is an underappreciated issue in prison medicine. Recent studies have revealed a higher prevalence of cardiovascular disease risk factors (CVDRFs) among individuals in prison, but the impact of incarceration on CVDRFs over time is not well understood. This review aimed to assess available literature and quantify the relationship between incarceration and trends in major CVDRFs in high-income countries. DESIGN: Systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Meta-regression on weight change and obesity. DATA SOURCES: Medline, Embase, PubMed, Cochrane Central Wiley and Web of Science. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Longitudinal studies reporting on the incidence of, or trends in any CVDRF among current or former people in prison over time, in high-income countries. DATA EXTRACTION AND SYNTHESIS: Two authors independently screened articles for eligibility, extracted data and assessed quality using an adapted version of the Newcastle-Ottawa Scale. Trends in CVDRFs during and following incarceration were summarised and in those with sufficient data a meta-regression was performed. RESULTS: (95% CI -0.9 to 4.6) at 2 years. Weight gain appeared most pronounced right after entering prison and then plateaued at 2 years. Concerning hypertension, the results were inconclusive, despite a trend towards rising blood pressure or prevalence of hypertension during incarceration, and an increased incidence of hypertension following incarceration. Results are contradictory or inconclusive for the other CVDRFs reviewed. CONCLUSION: Possible explanations for the association between incarceration and weight include a sedentary lifestyle, unhealthy diet, forced smoking cessation, psychotropic medication use and high levels of stress. Incarceration may be an independent risk factor for cardiovascular disease.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.045
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0210.049
Bibliometrics0.0070.008
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.267
GPT teacher head0.483
Teacher spread0.217 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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

Citations39
Published2020
Admission routes2
Has abstractyes

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