Spatial distribution of neighborhood-level housing prices and its association with all-cause mortality in Seoul, Korea (2013–2018): A spatial panel data analysis

Ikhan Kim

doi:10.1016/j.ssmph.2021.100963

Abstract

Housing prices are known to be a relevant indicator of the socioeconomic position of the neighborhood. In a society where the market system mainly drives housing prices, residents' spatial patterning is formulated according to their socioeconomic position. Dividing the 2013–2018 entire study period into three periods, we explored the spatial distribution of housing prices and all-cause mortality and their association in Seoul, the country's capital city. The government authorities' data and 2015 census data were used for the study. We mapped the spatial distribution of housing prices and all-cause mortality and investigated the changes in distribution. We conducted a pooled ordinary least square (OLS) and spatial panel regression analysis to estimate housing prices elasticity of all-cause mortality. We also explored the possible mediating role of housing prices on the educational composition's effect on all-cause mortality. We found the common trends of increasing spatial patterning of housing prices and all-cause mortality. The magnitude of spatial patterning was far greater in housing prices than all-cause mortality. A pooled OLS regression analysis found that a 1% increase in housing price was associated with a 0.11% reduction in all-cause mortality after controlling the explanatory variables. Attenuation in the regression coefficient's magnitude was found after adding the neighborhood's educational composition to the model. As a result of spatial panel analysis, we found a direction and scale similar to the housing price elasticity of all-cause mortality in the final pooled OLS model. The results suggested that spatial health inequality in Korea's urban space mainly stems from socioeconomic inequality.

Highlights

Housing prices are known to be a relevant indicator of the socioeconomic position of the neighborhood
The results suggested that geographical health inequality in Korea's urban space mainly stemmed from the affinity of high socioeconomic position and the more developed spaces
This study explored the geographical distribution of all-cause mortality and housing prices and estimated the elasticity of housing prices to all-cause mortality

Summary

Introduction

Housing prices are known to be a relevant indicator of the socioeconomic position of the neighborhood. In a society where the market system mainly drives housing prices, residents' spatial patterning is formulated according to their socioeconomic position. Methods: Dividing the 2013–2018 entire study period into three periods, we explored the geographical distribution of housing prices and all-cause mortality and their association in Seoul, where the country's capital city. We conducted a pooled OLS and spatial panel regression analysis to estimate housing prices elasticity of all-cause mortality. In a pooled OLS regression analysis, we found that a 1% increase in housing price was associated with a 0.11% reduction in all-cause mortality after controlling the explanatory variables. As a result of spatial panel analysis, we found a direction and scale similar to the housing price elasticity of all-cause mortality in the final pooled OLS model. Economic inequality in urban areas is increasing [6,7,8]. [9] asserted that problems that arise in cities turn into a product of capital accumulation and class conflict when the assumption is converted from “where you live affects your life” to the belief that “your life affects where you live.” [10] argued that, to deal with urban health inequality, the question “where is power and who works?” should be asked. [11] stated that urban health inequalities stemmed from “systematically unequal distribution in power, prestige, and resources associated with relative position in the social hierarchy.” Taking the housing price into account would make it possible to examine cities’ health problems through the lens of health inequality

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