Changes in Dietary Intake After an 8-week Meal-Kit Delivery Program in Adults With an Overweight Condition or Obesity
Bibliographic record
Abstract
This study aimed to explore changes in dietary intake and body composition in adults living with an overweight condition and obesity who participated in an 8-week meal kit delivery program that included tutorials on nutrition and eating behaviours. Thirty-four healthy adults (aged 18--65 y) classified as either overweight or obese (25 < body mass index [BMI] <40 kg/m2) were randomly (1:1:1) divided into three groups: Control, Nutrition, and Behaviour. At baseline and at 10-weeks, anthropometrics were measured and body composition was analyzed using dual energy x-ray absorptiometry. Participants recorded their food intake for three non-consecutive days at both time points, which was then analyzed for macronutrients, water consumption and fruit and vegetable intakes. Over the 8-weeks, meal-kits were delivered to all participants. Each week, the control (n = 11) received weekly handout of healthy eating and nutrition education, Nutrition (n = 11) had access to online tutorials about healthy eating and nutrition education and the Behaviour group had access to online eating behaviour tutorials. Repeated-measures, mixed model ANOVA were used to compare changes in outcome measures. Thirty-four participants completed the food diaries and body composition analysis (mean age 30.8 ± 11.2 y and mean BMI 30.7 ± 3.9 kg/m2). Significant differences were seen in water intake between Nutrition (791.2 ± 273.0 g) and Behaviour (1112.5 ± 197.6 g) (P = 0.03). Body composition and macronutrient intakes did not significantly differ among groups and/or over time. However, total intake of fruits and vegetables after the intervention was significantly different between Behaviour (5.85 ± 2.8 serving) and Nutrition (3.4 ± 1.4 serving) (P = 0.01). Meal-kit delivery with the added nutrition education and eating behaviours resulted in positive changes in food intake in adults living with an overweight condition and obesity. Future work should consider longer-term follow-up with larger sample sizes to confirm these findings. R. Howard Webster Foundation
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".