Evidence map›Paper›PMID 39209490›Full record

ArticleBMJ open2024

Health insurance, social safety net and maternal health service utilisation in Pakistan: a population based cross-sectional study.

Nadia Shah, Sidra Zaheer, Uzma Iram

Abstract read
In one paragraph

Article in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Nadia ShahApplied Economics Research Centre, University of Karachi, Karachi, Sindh, Pakistan nadia.shah@live.com.ORCID 0000-0002-0377-9561
Sidra ZaheerSchool of Public Health, Dow University of Health Sciences, Karachi, Sindh, Pakistan.
Uzma IramApplied Economics Research Centre, University of Karachi, Karachi, Sindh, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe objective of the study is to examine the impact of health insurance and social safety net programmes on maternal health service utilisation (MHSU) in Pakistan.

designCross-sectional. SETTINGS: Data were obtained from Pakistan Demographic Health Survey 2017-2018.

participantsOut of 12 364 Pakistani ever-married women aged 15-49 years included in the survey sample, 7752 were included in the study.

main outcome measuresThree response variables (antenatal care (ANC) by skilled attendants (<4 visits=inadequate vs 4 or more visits=adequate), health facility-based delivery (home vs health) and postnatal care (yes vs no) were combined to assess MHSU. Health insurance was derived from the question 'are you covered with any health insurance?' and social safety net was derived from enrolment in social safety net programmes. Logistic regression analyses were conducted, and results were reported as ORs with 95% CIs. Results of adjusted logistic regression models were fit to control for individual and community-level factors.

resultPrevalence of social safety net was larger than health insurance (7.7% vs 2.0%) while attendance of ANC+4, facility-based delivery and postnatal care was 48.5% (n=3760), 65.9% (n=5097) and 22.6% (n=1745) respectively, among respondents. Women were twice more likely to access maternal health services when they were covered by health insurance (adjusted OR 2.61, 95% CI 1.19 to 5.74, p<0.017) after adjusting for age at marriage, education level, wealth index, rural/urban area, parity, employment, empowerment status, exposure to media, visits and distance to health facility while no significant association of social safety net programmes with MHSU was found.

conclusionExpanding access to health insurance can provide comprehensive coverage for maternal healthcare services. Social safety net programmes can be made conditional, subject to regular health checkups for mothers and children to improve maternal and child health outcomes.

Indexed as

Health Services AccessibilityInsurance, HealthMaternal Health ServicesAdolescentAdultCross-Sectional StudiesFemaleHumansLogistic ModelsMiddle AgedPakistanPatient Acceptance of Health CarePostnatal CarePregnancyPrenatal CareYoung Adulthealth economicshealth services accessibilitypublic health

Identifiers

PMID39209490
PMCPMC11367345

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.