Universal health coverage for women of reproductive ages: a survey-based comprehensive assessment of service utilisation and health expenditure in Tanzania
Bibliographic record
Abstract
Introduction: Universal health coverage (UHC) for women of reproductive ages is a critical component of country and global health strategies but most evidence in high-fertility settings is limited to maternity care. Our study aimed to comprehensively assess women's health service utilisation and expenditure, including an equity dimension. Methods: We conducted a household survey among 15-49 years as a nested study within the Magu health and demographic surveillance study, northwest Tanzania, during 2020-2021. Data were collected on self-reported health, fertility, utilisation of health services, health expenditure and health insurance. We analysed key indicators by household wealth quintiles, place of residence and health insurance, using logistic regression models controlling for age and other confounders. Results: Among 8665 women aged 15-49 years (response rate 81%), 3.0% reported poor or very poor health, 13% gave birth in the preceding year, and health insurance coverage was 5.1%. Coverage of antenatal (99.5%) and institutional delivery care (88%) were high; 7.3% of women reported at least one outpatient visit in the last 4 weeks, of which 81% were for their own non-maternal healthcare; 9.3% had been admitted to a hospital during the last year, and 74% of these admissions were for deliveries. The total average annual health expenditure per woman was about TZS 16 860 (US$7.50), of which 82% was for her own healthcare and 18% for maternity care. Additionally, women spent about TZS 23 172 (US$10.00) per year on self-treatment. The poorest women had poorer self-reported health, lower coverage of maternity care, lower utilisation of services for their own healthcare and lower health insurance coverage, and limited their expenditure by making greater use of nearby public services than richer women. Conclusion: Women spent more financial resources on their own non-maternal healthcare than maternity care with poorer women still facing disadvantages for their own healthcare. Health insurance programmes were hardly but were associated with an increase in service use. Comprehensive assessments of women's health needs, service use and expenditures with an equity focus are crucial for shaping UHC strategies tailored to women of reproductive ages.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | high |
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".