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
Background: Travel time to care is known to infuence 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...
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| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BioMed Central Ltd.
2021
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| Subjects: | |
| Online Access: | https://ij-healthgeographics.biomedcentral.com/track/pdf/10.1186/s12942-020-0197-5.pdf http://hdl.handle.net/11408/4245 |
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| Summary: | Background: Travel time to care is known to infuence 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 diferent spatial settings.
Objectives: This 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.
Methods: Women 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 fnder (ArcGIS)). Bland–Altman analysis compared spatial variation in diferences 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.
Results: Modelled 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
(H0: Mean diference=0)]<.001, limits of agreement: [−273.81; 56.40] and [−264.10; 94.25] respectively. In Mozambique, mean diferences between the two measures of access were signifcantly diferent from 0 [P (H0: Mean diference=0)=0.31, limits of agreement: [−187.26; 199.96]].
Conclusion: Modelling access successfully predict potential vulnerability in populations. Diferences between modelled (P) and self-reported travel times (R) are partially a result of women not seeking care at their closest facilities. |
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