Association of nutritional and psychosocial factors with early gestational weight gain
Bibliographic record
Abstract
Background: Maternal compliance with gestational weight gain (GWG) guidelines is poor; approximately 20% of women have inadequate weight gain and because 50% gain excessively, pregnancy is now considered obesogenic. Even though multiple factors influence GWG, psychosocial and behavioural factors have not been studied. Methodology: Three studies were designed to assess: 1) evidence for early maternal perinatal counseling; 2) compliance with, and determinants of, Eating Well with Canada's Food Guide (CFG); and 3) sociodemographic, biomedical, psychosocial, and behavioural determinants of inadequate and excessive GWG in the first trimester. A total of 594 women (mean age = 33.0 ± 4.4 years) were recruited at 14.2 ± 1.4 wks. Online validated questionnaires assessed psychosocial factors (e.g. depression, stress, emotional eating, mindfulness, attitudes/barriers, and self-efficacy) and behavioural factors (e.g. diet, physical activity, and sleep). GWG was calculated and standardized using: [(weight at recruitment – pre-pregnancy weight)/gestational weeks] x 14.0]. A hierarchical multivariate statistical regression analysis was used to identify determinants of adherence to CFG and of inadequate and excessive GWG. Results: Women did not receive preconception counseling about vitamin use (43%), tobacco use (71%), alcohol consumption (69%), physical activity (77%), or being a healthy weight (79%). Only 26% received GWG counseling. Overall adherence to CFG was poor: <15% met the recommended servings of vegetables and fruit (13.6%) and grain products (14.9%). Results from the hierarchical regression model identified age, attitudes towards healthful eating, snacking, and nutrition self-efficacy as predictive of greater adherence to CFG; immigration status, pregnancy intention, and barriers to healthful eating were associated with lesser adherence to CFG.The prevalence of excessive GWG during the first trimester (>2.0 kg) was 50.8% (n=206); appropriate GWG (0.5kg ≤ GWG ≥ 2.0kg) was 26.2% (n=106); and inadequate GWG (<0.5kg) was 23.0% (n=93). Greater depressive symptoms were associated with an increased likelihood of inadequate (OR: 2.38; p=0.03) and excessive GWG (OR: 2.32; p=0.01). In contrast, improved dietary quality was associated with a decreased likelihood of inadequate (OR: 0.82; p=0.04) and excessive GWG (OR: 0.82; p=0.01). Moreover, greater mindfulness (OR: 2.22; p<0.001), increased BMI (OR: 1.72; p=0.02), and poor sleep quality (OR: 1.16; p=0.02) were associated with an increased likelihood of inadequate GWG whereas increased household physical activity (OR: 0.99; p=0.01) decreased the likelihood. Interestingly, a higher planned GWG (OR: 1.21; p<0.001) and greater nutritional self-efficacy (OR: 1.12; p=0.01) increased the odds of excessive GWG.Implications: Maternal depression screening and nutrition counseling in early pregnancy, combined with tailored interventions, may improve GWG compliance given the interplay among GWG determinants.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".