Fruit and vegetable consumption and anemia among adult non-pregnant women: Ghana Demographic and Health Survey
Bibliographic record
Abstract
BACKGROUND: Anemia is the most widely prevalent form of micronutrient deficiency that affects over a quarter of the global population. Evidence suggests that the burden of anemia is higher in the developing countries with women of reproductive age and children being the most at-risk groups. The most common causes are believed to be malnutrition and low bioavailability of micronutrients, which usually result from poor dietary habits and inadequate intake of food rich in micronutrients such as fresh fruits and vegetables. Regular consumption of F&V was shown to have protective effect against NCDs; however, evidence on this protective effect against micronutrient deficiency diseases are limited. OBJECTIVES: (1) To measure the prevalence of anemia among adult non-pregnant women in Ghana, and (2) to investigate if there is any cross-sectional relationship between F&V consumption and anemia. METHODS: hemoglobin-meter. Association between anemia and F&V consumption was assessed by multivariable regression methods. RESULTS: Findings indicate that well over half (57.9%) of the women were suffering from anemia of some level. The percentage of women consuming at least five servings of fruits and vegetables a day were 5.4% and 2.5% respectively. Results of multivariable analysis indicated that among urban women, consumption of <5 servings fruits/day was associated with significantly higher odds of severe [AOR = 9.27; 95% CI [5.15-16.70]] and moderate anemia [AOR = 6.63; 95% CI [4.21-10.44]], and consumption of <5 servings of vegetables/day was associated with higher odds of moderate anemia [AOR = 2.39; 95% CI [1.14-5.02]] compared with those who consumed >5 servings/day. CONCLUSION: The findings indicate that urban women who did not maintain WHO recommended level of F&V consumption bear a significantly higher likelihood of being moderate to severely anemic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".