Impact of disasters, including pandemics, on cardiometabolic outcomes across the life-course: A systematic review
Bibliographic record
Abstract
ABSTRACT Objectives Disasters, such as the current COVID-19 pandemic, disrupt daily life, increase uncertainty and stress, and may increase long-term risk of adverse cardiometabolic outcomes, including heart disease, obesity and diabetes. The objective was to conduct a systematic review to determine the impact of disasters, including pandemics, on cardiometabolic outcomes across the life-course. Design A systematic search was conducted in May 2020 using two electronic databases, EMBASE and Medline. All studies were screened in duplicate at title and abstract, and full-text level. Studies were eligible for inclusion if they assessed an association with population-level or community disaster and cardiometabolic outcomes. There were no restrictions on year of publication, country or population. Non-English and earthquake-related studies were excluded. Data were extracted on study characteristics, exposure (e.g., type of disaster, name of specific event, region, year), cardiometabolic outcomes, and measures of effect. Study quality was evaluated using the Joanna Briggs Institute critical appraisal tools. Results A total of 58 studies were included, with 24 studies reporting the effects of exposure to disaster during pregnancy/childhood and 34 studies reporting the effects of exposure during adulthood. Studies included exposure to natural (60%) and human-made (40%) disasters, with only 3 (5%) of these studies evaluating previous pandemics. Most studies were conducted in North America (62%). Most studies reported increased cardiometabolic risk, including increased cardiovascular disease incidence or mortality, diabetes, and obesity. Few studies investigated potential mechanisms or identified high risk subgroups. Conclusions Understanding the long-term consequences of disasters on cardiometabolic outcomes across the life-course may inform public health strategies for the current COVID-19 pandemic. This review found strong evidence of an increased association between disaster exposure and cardiometabolic outcomes across the life-course, although more research is needed to better understand the mechanisms and preventative efforts. PROSPERO registration CRD – 42020186074 Strengths and limitations of this study This systematic review is one of the first to review the literature on disasters, including pandemics, and subsequent cardiometabolic outcomes throughout the life-course. A comprehensive search strategy was developed in consultation with Health Science Librarians at McMaster University, which resulted in 58 studies that were eligible for inclusion into the review. Due to the heterogeneity of the included studies, a meta-analysis was not conducted. This review contributes a synthesis of the literature on the impact of disasters and cardiometabolic outcomes, that can help to inform public health strategies for the current COVID-19 pandemic.
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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 | 0.009 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".