Relationship between body mass index and cardiovascular metabolic multimorbidity: a systematic review and meta-analysis
Bibliographic record
Abstract
This study aimed to systematically evaluate the association between body mass index (BMI) and cardiovascular metabolic multimorbidity (CMM). Cochrane Library, CINAHL, EMBASE, Web of Science, and PubMed were searched for observational studies examining the relationship between BMI and CMM, with a search timeframe from database inception to May 16, 2024. The Newcastle-Ottawa Scale (NOS) and the Agency for Healthcare Research and Quality (AHRQ) criteria were used to evaluate the quality of included studies. The meta package in R was used to perform a meta-analysis. Subsequently, pooled odds ratios (OR) and their 95% confidence intervals (CIs) were computed. Eleven (11) studies involving 1,771,748 patients were included in this review, and the meta-analysis was conducted based on 10 studies. The meta-analysis revealed that when BMI was analyzed as a categorical variable, both overweight (pooled OR = 3.52, 95% CI: 1.23-10.05) and obesity (pooled OR = 3.68, 95% CI: 2.60-5.20) were significantly associated with CMM. When BMI was treated as a continuous variable, it was also significantly related to CMM (pooled OR = 2.90, 95% CI: 1.99-3.81). Furthermore, obesity was associated with an increased risk of CMM [hazard ratio (HR) = 3.27, 95% CI: 2.44-3.39]. This study highlighted a positive correlation between overweight/obesity and CMM. Consequently, it is essential to enhance health awareness among high-risk populations, such as older adults and those with obesity. Proactive screening for high-risk individuals and increased public education on CMM are recommended. Weight management strategies should be integrated into CMM management plans for obese patients to reduce the incidence of these conditions. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/, PROSPERO CRD42024602835.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.040 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".