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. 2022 Feb 27;19(5):2765.
doi: 10.3390/ijerph19052765.

Equity in Health-Seeking Behavior of Groups Using Different Transportations

Fangye Du  1   2 , Jiaoe Wang  1   2 , Yu Liu  3 , Zihao Zhou  4 , Haitao Jin  5
Affiliations

Equity in Health-Seeking Behavior of Groups Using Different Transportations

Fangye Du et al. Int J Environ Res Public Health. .

Abstract

The equity of health-seeking behaviors of groups using different transportations is an important metric for health outcome disparities among them. Recently, smart card data and taxi trajectory data have been used extensively but separately to quantify the spatiotemporal patterns of health-seeking behavior and healthcare accessibility. However, the differences in health-seeking behavior among groups by different transportations have hitherto received scant attention from scholars. To fill the gap, this paper aimed to investigate the equity in health-seeking behavior of groups using different transportations. With sets of spatial and temporal constraints, we first extracted health-seeking behaviors by bus and taxi from smart card data and taxi trajectory data from Beijing during 13-17 April 2015. Then, health-seeking behaviors of groups by bus and taxi were compared regarding the coverage of hospital service areas, time efficiency to seek healthcare, and transportation access. The results indicated that there are inequities in groups using different travel modes to seek healthcare regarding the coverage of hospital service areas, time efficiency to seek healthcare, and transportation access. They provide some suggestions for mode-specific interventions to narrow health disparity, which might be more efficient than a one-size-fits-all intervention.

Keywords: comparative analysis; equity; healthcare accessibility; smart card data; taxi trajectory data.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
(a) Study area within the sixth ring road of Beijing; (b) distribution of primary, secondary, and tertiary general hospitals and the population density in subdistricts.
Figure 2
Figure 2
(a) Distribution of bus trips by subdistrict and (b) distribution of taxi trips.
Figure 3
Figure 3
Frequency distribution of distance between drop-off points and nearest hospitals.
Figure 4
Figure 4
Distribution of the origins of health-seeking trips by bus and taxi.
Figure 5
Figure 5
Analytical framework. Source: designed by the author.
Figure 6
Figure 6
Comparison of the hospital service areas estimated by smart card data and taxi trajectory data for (a) Chinese P.L.A. General Hospital, (b) Peking University Third Hospital, (c) Beijing Anzhen Hospital, and (d) Beijing Tongren Hospital.
Figure 7
Figure 7
Distance decay of health-seeking trips by bus and taxi.
Figure 8
Figure 8
Distribution of average travel time of health-seeking behavior by bus (a) and taxi (b).
Figure 9
Figure 9
Hourly variation of (a) health-seeking trips extracted from smart card data and taxi trajectory data, and (b) travel mode preference.
Figure 10
Figure 10
Travel mode preference by subdistrict.
See this image and copyright information in PMC

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