Liu P, Zhang X, Deng G, Guo W. Sociodemographic factors impacting the spatial distribution of private dental clinics in major cities of Peoples Republic of China.
Int Dent J 2024;
74:1089-1101. [PMID:
38631944 PMCID:
PMC11563162 DOI:
10.1016/j.identj.2024.03.009]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 03/04/2024] [Accepted: 03/15/2024] [Indexed: 04/19/2024] Open
Abstract
OBJECTIVES
Investigate the geographical distribution of private dental practices in major Chinese cities and analyze the variables influencing this distribution.
METHODS
This study used Python to extract various types of Point of Interest (POI) data spanning from 2016 to 2022 from the AutoNavi map. A 1km*1km grid was constructed to establish the study sample. Additional spatial pattern data, including nighttime lighting, population, and air quality data, were integrated into this grid. Global Moran's I index was used to analyze the spatial autocorrelation. The spatial lag model was used to explore the influencing factors of private dental practice distribution.
RESULTS
This study reveals a specific clustering pattern for private dental practices in major Chinese cities. The primary influencing factors include nighttime lights, population density, and housing prices, suggesting that dental practices are typically concentrated in highly developed regions with dense populations and high housing costs. Additionally, we discovered that patterns vary across different metropolises, with the most pronounced clustering patterns and substantial inequalities found in the most developed areas.
CONCLUSIONS
This study establishes that factors such as regional development and population density positively correlate with private dental practice. Additionally, it reveals a strong mutual correlation in the clustering of dental practices, which does not show a substantial correlation with public resources. Finally, it suggests that the spatial heterogeneity pattern implies a rising necessity to tackle inequality issues within urban areas as economic development progresses.
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