Evidence map›Paper›PMID 42266554›Full record

ArticleWomen2024

Identifying Geographic Inequities in Family Planning Service Uptake in Pakistan: A Comparative Study of PDHS 2006 and 2017 Using Cluster Hotspot Analysis.

Kamran Baig, Ebele Okoye, Mary Shaw

Abstract read
In one paragraph

Article in Women, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Kamran BaigSindh Social Protection Authority, Karachi 75500, Pakistan.
Ebele OkoyeDepartment of Epidemiology & Biostatistics, College of Health Sciences, Jackson, MS 39213, USA.
Mary ShawDepartment of Behavioral & Environmental Health, College of Health Sciences, Jackson, MS 39213, USA.

Funding

Training ProgramU54HD113238 · NICHD · JACKSON STATE UNIVERSITY · PI Dr Beryl POLK, Mary D Shaw · 2023 to 2026
$12.5M
NICHD NIH HHS U54 HD113238
6 · The paper itself

Abstract

Family planning (FP) services are crucial interventions for improving maternal and child health outcomes and promoting gender equity. However, ensuring equitable access to these services remains a significant challenge, particularly in countries like Pakistan, where sociocultural norms, economic disparities, and geographic barriers hinder FP uptake. This study utilized spatial analysis techniques, including hotspot analysis, to investigate geographic disparities in FP uptake in Pakistan using data from Pakistan Demographic and Health Surveys (PDHS) conducted in 2006-2007 and 2017-2018. ArcMap 10.1 was used for spatial analysis and Stata 12.0 for statistical analysis. Results revealed significant spatial variations in FP uptake, with urban areas exhibiting higher uptake rates than rural regions. Hotspot analysis identified dynamic changes in contraceptive prevalence rates (CPR), with significant clustering in some regions and dispersion in others. It also identified areas with high unmet need, low intention to use FP services, and preference for family size (>3 children), highlighting the need for targeted behavioral change interventions. This innovative spatial approach provides nuanced insights for policymakers and program planners to develop targeted interventions based on localized data to improve FP service delivery, mitigate disparities, and ultimately advance efforts to improve maternal and child health outcomes. The application of geospatial analysis is an effective tool for enhancing program planning, evaluation, and resource allocation in diverse geographical contexts.

Indexed as

contraceptionfamily planninggender inequityhotspot analysismaternal healthPakistan

Identifiers

PMID42266554
PMCPMC13246157

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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.