Underweight and Associated Factors Among Teenage Adolescent Girls in Resource-poor Settings: A Cross-sectional Study
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Understanding the undernutrition status of teenage adolescent girls living in urban slums and its associated factors is meaningful to formulate customized health strategies. This study aimed to determine the prevalence of being underweight and associated factors among teenage adolescent girls in urban slums. MATERIALS AND METHODS: In this cross-sectional study, we enrolled a total of 418 teenage adolescent girls from five of 210 urban slums of Varanasi district, Uttar Pradesh, India employing two-stage probability sampling for the selection of households and subjects, between September 2016 and July 2017. The study of underwight subjects was assessed with BMI for age using standard criteria. Factors associated with being underweight were determined by multivariable logistic regression analysis. RESULTS: Of 418 study subjects, 49.76% (208/418) were underweight. Results revealed that sociodemographic factors such as teenage adolescent girls who were from SC/ST (schedule caste/schedule tribe) caste/ethnicity (adjusted odds ratio (AOR)=2.02, 95%CI: 1.00-4.23), subjects whose father's education level was primary or lower (AOR=1.87, 95%CI: 1.12-3.11), and number of people in the family >4 (AOR=2.18, 95%CI: 1.18-4.03) were associated with being underweight. Likewise, dietary behavior-related factors such as vegetarian (AOR=2.21, 95%CI: 1.25-3.92), and <3 meals per day (AOR=2.36, 95%CI: 1.40-3.98) than their counterparts were associated with being underweight. In addition, teenage adolescent girls from food-insecure households (AOR=3.33, 95%CI: 2.01-5.51) were more likely to be underweight than those from food-secure households. CONCLUSION: The higher burden of underweight among teenage adolescent girls in Indian urban slums needs to be addressed through specific public health interventions such as by improving education, providing education regarding dietary behavior, and having access to sufficient, safe, and nutritious foods.
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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 | 0.001 |
| 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 | 0.000 |
| 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".