Divorced women who are in informal unions are most vulnerable to food insecurity
Bibliographic record
Abstract
Divorced women in Africa experience economic disadvantages. This analysis uses baseline data from the Nutrition Links project to determine if marital experience of women is associated with food insecurity (FI). 1094 Households (HH) with an infant (< 12 months) were selected from 137 villages in the Upper Manya Krobo district in Ghana. FI was assessed using the Latin‐American and Caribbean Food Security Scale (ELCSA). HH where caregivers were the mothers of the index child and where the ELCSA questionnaire was completed are included in this analysis (n=1065). Internal validity of ELCSA was confirmed using the Rasch model. The relative severity of the items was according to the theoretical framework underlying the ELCSA. Additionally, no substantial DIF CONTRASTS were found when comparing groups by primary education (DIF <0.52 logit), and all items had INFIT values within acceptable range (0.7 to 1.3 logit). Principal Components Analysis was performed with HH assets to create a score as a proxy of wealth. Women's age and age at first pregnancy were 27.1±0.2 and 19.2±0.1 years, respectively. FI affected 57% of HH (27% mild, 18% moderate, and 12% severe). FI was associated with HH wealth score, women's education level, and age at first pregnancy (p<0.05) but not with age. Sixty percent of women in severely food insecure HH had not finished primary school compared to 44% in food secure HH (p=0.01). Age at first pregnancy and wealth score decreased with severity of FI (p<0.01). Marital experience was also associated with FI. Women who were in an informal union (i.e.: cohabiting or in a union), either divorced or never married, had higher odds for being food insecure (OR: 1.68 and 2.27, respectively) compared to women who were in their first marriage (p<0.01). After adjusting for education level, age, age at first pregnancy, and wealth, only divorced women in informal unions still had higher odds for being food insecure when compared to those in their first marriage (OR: 1.59, p<0.05). These results are consistent with previous publications, implying that poorer never‐married and divorced women may enter into informal relationships out of economic necessity. They also suggest that much more attention must be placed in better understanding marital history of women and the social aspects that are linking these informal unions to FI. Considering that divorce is not uncommon, and that informal unions are increasing in Ghana, a large number of women and their children could be experiencing FI. Finally, this study highlights the importance of identifying divorced women, specially divorced women in new informal unions as a vulnerable population for interventions against FI.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".