The role of gender in health insurance enrollment among geriatric caregivers: results from the 2022 informal caregiving, health, and healthcare survey in Ghana
Bibliographic record
Abstract
BACKGROUND: Female informal caregivers of older adults experience a higher burden of physical and mental health problems compared to their male counterparts due to the greater intensity of care they provide. This is likely to result in an imbalance in health needs, including health insurance enrollment, between male and female informal caregivers of older adults. However, to date, no study is available on the role of gender in health insurance enrollment among informal caregivers of older adults in Ghana. This study examines the association between gender and health insurance enrollment among informal caregivers of older adults in Ghana. METHODS: Cross-sectional data from the Informal Caregiving, Health, and Healthcare Survey among caregivers of older adults aged 50 years or above (N = 1,853 and mean ages = 39.15 years and 75.08 years of informal caregivers and their care recipients, respectively) in Ghana were analyzed. A binary logit regression model was used to estimate the association between gender and health insurance enrollment. All statistical inferences were made at the 5% significance level. RESULTS: The final Model (3) showed that female informal caregivers were 2.70 times significantly more likely to enrol in a health insurance scheme than their male counterparts (AOR: 2.70, 95% CI: 2.09-3.48, p-value = 0.001). Apart from gender, the results revealed that participants aged 55-64 years (AOR = 2.38, 95%CI: 1.29-4.41, p-value = 0.006), with tertiary education (AOR: 3.62, 95% CI: 2.32-5.66, p-value = 0.001) and living with the care recipients (AOR: 1.50, 95% CI: 1.14-1.98, p-value = 0.003) were significantly more likely to enrol in a health insurance scheme than their counterparts. The findings further showed that those who earned between GH¢1000 and 1999 (US$99.50-198.50) monthly (AOR: 0.70, 95% CI: 0.52-0.95, p-value = 0.022) and were affiliated with African traditional religion (AOR: 0.30, 95%CI: 0.09-0.99, p-value = 0.048) were significantly less likely to enrol in a health insurance scheme than their counterparts. CONCLUSION: Gender was a significant predictor of health insurance enrollment among informal caregivers of older adults. This finding contributes to the empirical debates on the role of gender in health insurance enrollment among informal caregivers of older adults. Policymakers need to develop gender-specific measures to address gender gaps in health insurance enrollment among informal caregivers of older adults in Ghana. Such health policies and programs should consider other significant demographic and socioeconomic factors associated with health insurance enrolment among informal caregivers of older adults in Ghana.
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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 | 0.014 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".