Rural women: the most vulnerable to food insecurity and poor health in the global south
Bibliographic record
Abstract
Rural women in developing countries have often been identified as one of the most vulnerable populations to food insecurity (FIS) and poor health status. Yet comparable evidence across countries is lacking. The objectives of this paper are (1) to identify which populations are most vulnerable to FIS in the global south; (2) to examine the association between FIS and health; and (3) to describe gender gaps in development outcomes that can explain gender differences. Data from surveys collected face‐to‐face in the global south through the 2014 Gallup World Poll (n=78304) were analyzed stratifying the sample by respondents' sex (female or male) and area of residence (rural, small town, suburban or city). This study was informed by Bourdieu's theory of practice. Results show an unequal distribution of food insecurity (FIS), with rural women presenting the highest prevalence across groups (57%). On the other end, city men had the lowest prevalence (35%). An unadjusted logistic regression of the global south showed that the likelihood of being FIS was significantly higher for women, independently of where they live, when compared to city men, with rural women having the highest odds ratio (OR=2.85). For all areas of residence, men consistently had lower OR compared to women. Regional stratification showed similar results, especially for Sub‐Saharan Africa and Latin America, but only partially for the Middle East, North Africa and Asia. A multivariate logistic analysis adjusted for education, income, age, marital status and household size showed a similar trend: rural women were significantly more likely to be FIS compared to city men (OR=1.44). In terms of personal health, findings from an adjusted logistic regression showed that being FIS or being a woman increased one's likelihood for poor health status (OR=2.35 and 1.17, respectively). Women, regardless of area of residence, were more likely to experience poor health compared to city men, with rural women showing the highest likelihood (OR=1.35). Results suggest that the differences in FIS and health status within the framework of gender inequality are associated with gender gaps in various development outcomes. Rural women had significantly lower levels of education, income and employment, and were significantly more likely to be divorced or widowed compared to rural men. Similar disadvantages were found when comparing rural women to women in other areas of residence. Results from multivariate logistic regressions show that better performance in the aforementioned development outcomes were protective against FIS and poor health, especially among women. To our knowledge, this is the first study to assess the difference in FIS by sex and area of residence using both a standardized measurement (Food Insecurity Experience Scale) and the same survey design across the global south. This paper presents novel evidence that women in the global south are more likely to experience FIS and poor health. Such disparities seem to be especially pronounced in rural women. Addressing current gender and residential location gaps in development outcomes (education, employment and income) by policy makers and practitioners should help address this phenomenon more effectively.
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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 | 0.001 |
| 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".