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Record W4406542471 · doi:10.1136/bmjph-2023-000672

Universal health coverage for women of reproductive ages: a survey-based comprehensive assessment of service utilisation and health expenditure in Tanzania

2025· article· en· W4406542471 on OpenAlexaff
Sophia Kagoye, Mark Urassa, Charles Mangya, Coleman Kishamawe, Jim Todd, Milly Marston, Peter Binyaruka, Ties Boerma

Bibliographic record

VenueBMJ Public Health · 2025
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsUniversity of ManitobaManitoba Health
FundersAgency for Healthcare Research and QualityBill and Melinda Gates Foundation
KeywordsTanzaniaEnvironmental healthReproductive healthHealth servicesService (business)BusinessGeographySocioeconomicsMedicinePopulationMarketingEnvironmental planningEconomics

Abstract

fetched live from OpenAlex

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.

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

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 armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: yes
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.166
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.079
GPT teacher head0.410
Teacher spread0.331 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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