Obesity and weight change during the COVID‐19 pandemic in children and adults: A systematic review and meta‐analysis
Bibliographic record
Abstract
Summary Many obesity risk factors have increased during the COVID‐19 pandemic, including physical inactivity, poor diet, stress, and poverty. The aim of this systematic review was to evaluate the impact of the COVID‐19 pandemic, as well as associated lockdowns or restrictions, on weight change in children and adults. We searched five databases from January 2020 to November 2021. We included only longitudinal studies with measures from before and during the pandemic that evaluated the change in weight, body mass index (BMI) (or BMI z ‐scores for children), waist circumference, or the prevalence of obesity. Random effects meta‐analyses were conducted to obtain pooled estimates of the mean difference in outcomes. Subgroups were evaluated for age groups and diabetes or obesity at baseline. The risk of bias was assessed using a modified version of the Newcastle‐Ottawa Scale, and the certainty of the evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach. A total of 74 studies were included (3,213,776 total participants): 31 studies of children, 41 studies of adults, and 2 studies of children and adults. In children, the pooled mean difference was 1.65 kg (95% confidence interval [CI]: 0.40, 2.90; 9 studies) for weight and 0.13 (95% CI 0.10, 0.17; 20 studies) for BMI z ‐scores, and the prevalence of obesity increased by 2% (95% CI 1%, 3%; 12 studies). In adults, the pooled mean difference was 0.93 kg (95% CI 0.54, 1.33; 27 studies) for weight and 0.38 kg/m 2 (95% CI 0.21, 0.55; 25 studies) for BMI, and the prevalence of obesity increased by 1% (95% CI 0%, 3%; 11 studies). In children and adults, the pooled mean difference for waist circumference was 1.03 cm (95% CI −0.08, 2.15; 4 studies). There was considerable heterogeneity observed for all outcomes in both children and adults, and the certainty of evidence assessed using GRADE was very low for all outcomes. During the first year of the COVID‐19 pandemic, small but potentially clinically significant increases in weight gain, BMI, and increased prevalence of obesity in both children and adults were observed. Increases were greater in children, and targeted prevention interventions may be warranted.
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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 | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.030 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".