Socio-economic, environmental and nutritional characteristics of urban and rural South Indian women in early pregnancy: findings from the South Asian Birth Cohort (START)
Bibliographic record
Abstract
OBJECTIVE: High frequency of low birth weight (LBW) is observed in rural compared with urban Indian women. Since maternal BMI is known to be associated with pregnancy outcomes, the present study aimed to investigate factors associated with BMI in early pregnancy of urban and rural South Indian women. DESIGN: Prospective observational cohort. SETTING: A hospital-based study conducted at an urban and a rural health centre in Karnataka State. SUBJECTS: Pregnant women (n 843) aged 18-40 years recruited in early pregnancy from whom detailed sociodemographic, environmental, anthropometric and dietary intake information was collected. RESULTS: A high proportion of low BMI (32 v. 26 %, P<0·000) and anaemia (48 v. 23 %, P<0·000) was observed in the rural v. the urban cohort. Rural women were younger, had lower body weight, tended to be shorter and less educated. They lived in poor housing conditions, had less access to piped water and good sanitation, used unrefined fuel for cooking and had lower standard of living score. The age (β=0·21, 95 % CI 0·14, 0·29), education level of their spouse (β=1·36, 95 % CI 0·71, 2·71) and fat intake (β=1·24, 95 % CI 0·20, 2·28) were positively associated with BMI in urban women. CONCLUSIONS: Our findings indicate that risk factors associated with BMI in early pregnancy are different in rural and urban settings. It is important to study population-specific risk factors in relation to perinatal health.
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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 | 0.001 |
| 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".