Household food insecurity, sociodemographic and lifestyle risk factors associated with high blood pressure among women in farming communities in Ghana
Bibliographic record
Abstract
BACKGROUND: Hypertension remains a primary contributor to avoidable mortality and impairment. This study aimed to examine the association between household food insecurity (HFI), another public health concern, and hypertension among women farmers in peri-urban and rural communities in Ghana. METHODS: Self-reported hypertension status, blood pressure measurement, and HFI were assessed using data on 430 women from a cross-sectional survey. We examined the odds of hypertension in women experiencing different categories of food insecurity while controlling for other known factors. RESULTS: Close to 74% (n = 319) of respondents belonged to households that were food-secure with 26% (n = 111) in food-insecure households. At the time of the survey, about a fifth of the participants (19%) reported to have ever been diagnosed with hypertension and 22% were living with high blood pressure (i.e., systolic: 140 mm Hg or higher and diastolic: 90 mm Hg or higher). Living in a rural community compared to a peri-urban community was associated with lower odds of living with high blood pressure. Older women were more likely than younger women to report having known hypertension and living with high blood pressure. Dangbe women were less likely to have high blood pressure than women from other ethnic groups. An increase in physical/morbidity activity was associated with a decreased likelihood of high blood pressure among food-insecure women. CONCLUSIONS: This study buttresses the importance of hypertension awareness among older women, particularly, in urbanizing communities, and the need to explore mediating factors through which ethnicity may influence living with high blood pressure.
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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 | 0.000 | 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".