Exploring the link between home garden use and severe obesity: Insights from a nationwide survey in Tuvalu
Bibliographic record
Abstract
Abstract Background Obesity is prevalent and increasing but understudied across Pacific Islanders. Tuvalu is a South Pacific country with a high obesity rate and faces multiple threats of food insecurity. Home garden serves as a sustainable food source and can be a possible intervention for the obesity pandemic in Tuvalu. This study investigated Tuvaluans' home garden use and obesity, and explored factors associated with increased use of home gardens. Methods We conducted a nationwide, cross-sectional study in Tuvalu during 2022. Structured questionnaires were administered during the in-person interviews, and trained interviewers measured the height and weight of each participant. The association between home garden use, obesity and severe obesity were tested with univariate and multivariable logistic regression. We also applied overlapping weights to balance the distribution of baseline demographic factors. Results The average body mass index was 34.87 kilogrammes (kg) / square metre (m2) among the study population of 1024 adults (630 from Funafuti and 394 from other islands in Tuvalu). Overall, people having home gardens was associated lower odds for severe obesity compared to those without a home garden in overlap weighting models (odds ratio (OR) = 0.946, 95% CI = 0.897-0.997, P = 0.039) and the association was stronger in Funafuti (OR = 0.927, 95% CI = 0.866-0.991, P = 0.027) than in the outlying islands (OR = 0.967, 95% CI = 0.889-1.052, P = 0.435). Furthermore, increased age was positively associated with having a home garden in Funafuti, and smoking showed an inverse association. Conclusions Having a home garden is associated with lower odds of severe obesity in Tuvalu, and the association is stronger in Funafuti. Smokers are less likely to have home gardens, and increased age is positively associated with having home gardens. These findings promote more home garden utilisation and provide evidence for targeted interventions in Tuvalu.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".