The Determinants of Dietary Diversity among Women of Reproductive Age in the Kolda Region in 2020
Bibliographic record
Abstract
INTRODUCTION: The lack of dietary diversity among women of reproductive age (WRA) is a public health problem in Senegal, particularly in the southern regions. The good nutritional status of women is one of the factors in the fight against maternal mortality and thus promotes a healthy pregnancy. The aim of this study was to investigate the determinants of dietary diversity among WRA in the Kolda region. METHODS: The quantitative, descriptive and analytical cross-sectional study took place in January-February 2020 in the Kolda region. It covered 1231 women of reproductive age (15- 49 years) in the Kolda region. Data were collected at household level using a questionnaire administered after informed consent. Ordinal logistic regression was performed to identify factors associated with dietary diversity among WRA in the Kolda region. RESULTS: A total of 1,231 WRA were surveyed, of whom 59.5% were neither pregnant nor breastfeeding, 30.7% breastfeeding and 9.8% pregnant. The mean age of the women was 27.62 years, with a standard deviation of 7.2 years. The median age was 27. Most women surveyed lived in rural areas (72.1%) and 58.5% were uneducated. Taking classification into account, 44% of WRAs in the Kolda region had average dietary diversity, compared with 24.7% who had low diversity and 31.3% who had high diversity. Risk factors associated with dietary diversity in WRA after adjustment were living in an urban environment (OR=1.52 [1.29 ; 1.78]), breastfeeding (OR=1.43 [1.13 ; 1.82]), head of household with higher level of education (OR=2.59 [1.55 ; 4.41]), household income greater than or equal to minimum wage (OR=1.23 [1.04 ; 1.45]), existence of fruit trees in the household (OR=1.28 [1.06 ; 1.55]), the existence of funding or support for processing local produce (OR=1.56 [1.10 ; 2.22]), knowledge of micronutrient-rich foods (OR=1.39 [1.13 ; 1.71]), good level of knowledge of good nutritional practices (OR=1.61 [1.35 ; 1.92]), women's average level of information on good hygiene and care practices (OR=1.27 [1.08 ; 1.48 ]). CONCLUSION: the accessibility and availability of nutrient-rich foods, the level of education of the head of household, the household's standard of living, awareness-raising, access to financing and the empowerment of women all help to improve the dietary diversity of WRA. Consequently, in the fight against food insecurity and malnutrition, the synergy of actions across sectors such as health, agriculture, the economy and social development, in particular gender and women's empowerment, is paramount for good women's nutritional status.
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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 | 0.000 | 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) | 0.002 | 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".