ArticleInternational journal of health geographics2020
Is the closest health facility the one used in pregnancy care-seeking? A cross-sectional comparative analysis of self-reported and modelled geographical access to maternal care in Mozambique, India and Pakistan.
Article in International journal of health geographics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01911494 (The CLIP), which is not on this map. Cited by 12 papers.
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.
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.
The CLIP (Community Level Interventions for Pre-eclampsia) Cluster Randomized Controlled Trial
Who cites it
12 citing papers in PubMed, 46 citations in OpenAlex.
- Evaluating tuberculosis service accessibility in Pakistan by analyzing population movement patterns from telecom mobility and survey data.BMC global and public health · 2026Article
- Big data in modelling geographical accessibility to healthcare: a scoping review protocol.BMJ open · 2025Article
- Improving complex health systems and lived environments for maternal and perinatal well-being in urban sub-Saharan Africa: the UrbanBirth Collective.Journal of global health · 2025Article
- Ten-year mortality study of dengue in Malaysia.IJID regions · 2024Article
- Optimization of the emergency obstetric and neonatal care network in Benin through expert-based sub-national prioritizations.Frontiers in global women's health · 2024Article
- A geospatial database of close-to-reality travel times to obstetric emergency care in 15 Nigerian conurbations.Scientific data · 2023Article
- Spatial variation and inequities in antenatal care coverage in Kenya, Uganda and mainland Tanzania using model-based geostatistics: a socioeconomic and geographical accessibility lens.BMC pregnancy and childbirth · 2022Article
- Distance is "a big problem": a geographic analysis of reported and modelled proximity to maternal health services in Ghana.BMC pregnancy and childbirth · 2022Article
- An assessment of geographical access and factors influencing travel time to emergency obstetric care in the urban state of Lagos, Nigeria.Health policy and planning · 2021Article
- Defining service catchment areas in low-resource settings.BMJ global health · 2021Article
- How prepared is Mozambique to treat COVID-19 patients? A new approach for estimating oxygen service availability, oxygen treatment capacity, and population access to oxygen-ready treatment facilities.International journal for equity in health · 2021Article
- "In cities, it's not far, but it takes long": comparing estimated and replicated travel times to reach life-saving obstetric care in Lagos, Nigeria.BMJ global health · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 5 institutions in 5 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTravel time to care is known to influence uptake of health services. Generally, pregnant women who take longer to transit to health facilities are the least likely to deliver in facilities. It is not clear if modelled access predicts fairly the vulnerability in women seeking maternal care across different spatial settings.
objectivesThis cross-sectional analysis aimed to (i) compare travel times to care as modelled in a GIS environment with self-reported travel times by women seeking maternal care in Community Level Interventions for Pre-eclampsia: Mozambique, India and Pakistan; and (ii) investigate the assumption that women would seek care at the closest health facility.
methodsWomen were interviewed to obtain estimated travel times to health facilities (R). Travel time to the closest facility was also modelled (P) (closest facility tool (ArcGIS)) and time to facility where care was sought estimated (A) (route network layer finder (ArcGIS)). Bland-Altman analysis compared spatial variation in differences between modelled and self-reported travel times. Variations between travel times to the nearest facility (P) with modelled travel times to the actual facilities accessed (A) were analysed. Log-transformed data comparison graphs for medians, with box plots superimposed distributions were used.
resultsModelled geographical access (P) is generally lower than self-reported access (R), but there is a geography to this relationship. In India and Pakistan, potential access (P) compared fairly with self-reported travel times (R) [P (H
conclusionModelling access successfully predict potential vulnerability in populations. Differences between modelled (P) and self-reported travel times (R) are partially a result of women not seeking care at their closest facilities. Modelling access should not be viewed through a geographically static lens. Modelling assumptions are likely modified by spatio-temporal and/or socio-cultural settings. Geographical stratification of access reveals disproportionate variations in differences emphasizing the varied nature of assumptions across spatial settings. Trial registration ClinicalTrials.gov, NCT01911494. Registered 30 July 2013, https://clinicaltrials.gov/ct2/show/NCT01911494.
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Registered trials
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.