Healthcare seeking behaviour during illness among older adults in Ghana: does food security status matter?
Bibliographic record
Abstract
BACKGROUND: Ghana's growing older adult population raises critical questions regarding healthcare for these older adults. At the same time, food insecurity is high among older adults in Ghana. This underscores the need to investigate the issues of food security and healthcare seeking behaviour among older adults. However, research on the association between food security status and healthcare seeking behaviour among older adults is scant in the Ghanaian context. In this study, we advance the social gerontology literature by examining the association between food security status and healthcare seeking behaviors among older adults. METHODS: Using a multi-stage sampling framework, we collected data from a representative sample of older adults across three regions in Ghana. Data were analyzed using logistic regression technique. We determined the significance of the test at a probability value of 0.05 or less. RESULTS: Over two-thirds (69%) of respondents did not seek care during their last illness. Additionally, 36% of respondents were severely food insecure, 21% were moderately food insecure, 7% were mildly food insecure, and 36% were food secure. After controlling for theoretically relevant variables, our multivariable analysis revealed a statistically significant association between food security status and healthcare seeking behaviors with older people who are food secure (OR = 1.80, p < 0.01) and mildly food insecure (OR = 1.89, p < 0.05) being more likely to seek healthcare compared with their counterparts who are food insecure. CONCLUSION: Our findings highlight the need for sustainable intervention programs to improve food access and health service use among older adults in Ghana and similar contexts.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 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".