Association Between Lifestyle Characteristics and Body Mass Index of Mothers of Children With Allergic Diseases
Bibliographic record
Abstract
BACKGROUND: For mothers of children with allergic diseases, the amount of physical activity involved in childcare increases owing to factors, such as the need for diet therapy and environmental improvements. Reportedly, the body mass index (BMI) of mothers of children with food allergies (FAs) is significantly lower than that of those of children without allergies (non-FA mothers). The aim of this study was to evaluate the characteristics of diet and physical activity in FA mothers and to clarify their effects on BMI. METHODS: To investigate the association between lifestyle characteristics and BMI in 69 mothers of children with FA, bronchial asthma and atopic dermatitis, their diets and physical activity pattern (using a three-axis accelerometer) were investigated; dietary and physical activity patterns (every hour) were extracted using principal component analysis, and multiple regression analyses were performed. RESULTS: Multiple regression analyses revealed a significant positive correlation (P = 0.037) between BMI and the third principal component of dietary patterns (positive correlation with cereals and negative correlation with sweets), a significant negative correlation (P = 0.004) between BMI and FA and the total daily duration of performing low- and moderate-intensity physical activity (P = 0.031) and a significant positive correlation (P = 0.008) between FA and the first principal component of physical activity expenditure patterns (patterns of ongoing physical activity throughout the day). In FA mothers (n = 51), a significant positive correlation (P = 0.042) was observed between the third principal component of dietary patterns and BMI. CONCLUSION: Low BMI in FA mothers may be related to reduced cereal intake, increased sweets intake and prolonged and continuous low- and moderate-intensity physical activity.
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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) | 0.002 | 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".