Prevalence and determinants of food insecurity among households headed by mothers who are female sex workers in three African Countries: Validation and application of food insecurity experience scale
Bibliographic record
Abstract
Abstract Reduction in prevalence of food insecurity, a key factor in reaching the United Nations Sustainable Development Goal 2.2, was challenged by COVID-19 lockdowns in low- and middle-income countries, which impacted the affordability and accessibility of food. Prevalence and determinants of food insecurity among female sex workers who are mothers (FSWM) and heads of households (FSWM-HH) in the African region have not been previously assessed. This study validated the food insecurity experience scale (FIES) using data collected from 852 FSWM-HH living in the Democratic Republic of the Congo (DRC), Kenya, or Nigeria. Results were calibrated on the global metric to compare with the country-level prevalence of household severe food insecurity (HSFI). Associated individual and household determinants and their intersections were examined to identify vulnerable sub-groups. The FIES reliably assessed (fit index=0.75) household food insecurity among FSWM-HH using a 7-item scale, omitting the item of being worried about not having enough food to eat. The prevalence of HSFI was 59.6% in the DRC, 77.8% in Kenya, and 89.0% in Nigeria and compared to FAO 2016-2018 country levels, 1.5, 3.0, and 4.5 times higher, respectively, than previous estimates. Determinants of HSFI among FSWM-HH were similar to the African region, except FSWM-HH composition of children, but the magnitudes of odds were higher. Multiple logistic regression revealed important ecological relationships. FSWM-HH with 0-3 children living with them (AOR=1.63,95% CI:1.13-2.37, reference > 4 children) and mothers having no schooling or primary education (AOR=1.92,95% CI:1.33-2.78, reference with higher education) significantly determined HSFI. Prevalence of HSFI was highest among two subgroups of FSWM-HH: those > 30 years of age, without partners (93.7%, p=0.002) and those with low levels of education with 0-3 children living with them (85%, p=0.03). Food programs and welfare policies may be effective strategies to reduce HSFI among this high-risk group of mothers with children.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".