Association between food insecurity and anemia among women of reproductive age
Bibliographic record
Abstract
BACKGROUND: Food insecurity and hidden hunger (micronutrient deficiency) affect about two billion people globally. Household food insecurity (HFI) has been shown to be associated with one or multiple micronutrient (MMN) deficiencies among women and children. Chronic food insecurity leads to various deficiency disorders, among which anemia stands out as the most prevalent one. As a high malnutrition prevalent country, Bangladesh has one of the highest rates of anemia among all Asian countries. In this study, we wanted to investigate for any association exists between HFI and anemia among women of reproductive age in Bangladesh. METHODOLOGY: Information about demographics, socioeconomic and anemia status on 5,666 married women ageing between 13 and 40 years were collected from a nationally representative cross-sectional survey Bangladesh Demographic and Health Survey (BDHS 2011). Food security was measured by the Household Food Insecurity Access Scale (HFIAS). Capillary hemoglobin concentration (Hb) measured by HemoCue® was used as the biomarker of anemia. Data were analysed using cross-tabulation, chi-square tests and multiple logistic regression methods. RESULTS: Anemia prevalence was 41.7%. Logistic regression showed statistically significant association with anemia and type of residency (p = 0.459; OR = 0.953, 95%CI = 0.840-1.082), wealth status (Poorest: p < 0.001; OR = 1.369, 95%CI = 1.176-1.594; and average: p = 0.030; 95%CI = 1.017-1.398), educational attainment (p < 0.001; OR = 1.276, 95%CI = 1.132-1.439) and household food insecurity (p < 0.001; 95%CI = 1.348-1.830). Women who reported food insecurity were about 1.6 times more likely to suffer from anemia compared to their food secure counterparts. CONCLUSION: HFI is a significant predictor of anemia among women of reproductive age in Bangladesh. Programs targeting HFI could prove beneficial for anemia reduction strategies. Gender aspects of food and nutrition insecurity should be taken into consideration in designing national anemia prevention frameworks.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.000 |
| 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".