The effect of population distribution measures on evaluating spatial accessibility of primary health-care institutions: A case study from China

Submitted: 2 September 2020
Accepted: 21 December 2020
Published: 11 March 2021
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Improvement of the equality of geographical allocation of limited health-care resources requires an accurate evaluation of spatial accessibility of the facilities. The adoption of appropriate population distribution measures is one of the leading factors affecting such an evaluation. Using primary health-care institutions in Hainan, China as an example, this study aimed to explore the disparities embedded in spatial accessibility evaluations based on six common measures of population distribution, namely community/ village population (VillagePop), average population distribution (AveragePop), population distribution by night-time light intensity (NighttimelightPop) together with the public population databases LandScan, WorldPop and PoiPop for construction of the weights. The enhanced two-step floating catchment area method, two-way analysis of variance (ANOVA), Dunnett test, root mean square error and the mean absolute error were employed to assess and compare spatial accessibilities based on these different population distribution measures. The spatial accessibility of primary health-care institutions in Hainan was found to vary when plotted using the various population distribution measures mentioned. As indicated by the statistical outcomes of both ANOVA and the Dunnett test, using the spatial accessibility calculated by VillagePop as reference, those calculated by AveragePop and PoiPop were found to be significantly different. In addition, the spatial accessibilities calculated by AveragePop and PoiPop demonstrated higher error rates in the identification of underserved areas compared with the reference. Considering the limitations of public population databases, the adoption of night-time light data is highly recommended for estimating population distribution in the absence of high-resolution data.



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How to Cite

Tan, J., Wang, X., & Pan, J. (2021). The effect of population distribution measures on evaluating spatial accessibility of primary health-care institutions: A case study from China. Geospatial Health, 16(1).

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