While physical activity has been associated with lower healthcare expenditures, existing studies relying on self-reports and linear models have struggled to characterize the non-linear shape of this association. Using a linked dataset of mHealth step counts and administrative claims data from 20,950 residents aged ≥40 years, this study employed Generalized Additive Models to elucidate the non-linear association between daily steps and future healthcare expenditures. The outcome was defined as the total healthcare expenditures accrued during the 6 months following each observation month; this 6-month window was chosen a priori for stability and interpretability, not because health effects of walking are assumed to emerge within exactly 6 months. Predicted 6-month healthcare expenditures decreased steeply as daily steps increased from low activity levels and then leveled off at approximately 10,000–12,000 steps/day, indicating a non-linear association between daily steps and subsequent expenditures. This low-expenditure plateau (point-estimate: ∼11,000 steps/day) was associated with a predicted geometric mean expenditure of 17,170 [16,174–18,229] JPY, though confidence intervals widened at higher step counts. Stratified analyses showed similar local nadirs in the data-dense range across age groups despite large differences in absolute magnitudes: the local nadir was 10,612 steps/day (48,407 [45,568–51,423] JPY) for older adults (≥65 years) versus 11,317 steps/day (1514 [1360–1685] JPY) for middle-aged adults, suggesting ∼11,000 steps/day as a common associational benchmark. These associations are observational and cannot establish that increasing walking causally lowers expenditures; rather, the non-linear shape suggests that strategies shifting population activity distributions toward this lower-expenditure range merit further evaluation. 

Suburban city centers are gradually declining due to the hollowing out of urban functions. Urban design strategies that seek to redirect stay behavior through a single catalytic project have therefore attracted increasing attention. However, there is limited empirical evidence on how the opening of a multifunctional facility—an intervention at the building scale—affects stay behavior in a suburban city. This study aims to clarify the impact of a new multifunctional facility on stay behavior using GPS trajectory data. The quasi-experimental case study was conducted using the high-resolution, empirical case of the Ibaraki City Cultural and Childcare Complex “ONIKURU.” This study used GPS trajectory data and applied propensity score matching and difference-in-differences to estimate the ATT among the stay group. Results show that opening ONIKURU significantly increased the frequency of weekly stays in the suburban city center among the stay group. Specifically, the ATT indicates an additional increase of approximately 0.471 [95% CI: 0.336, 0.607] times/week for the stay group relative to the non-stay group. However, spatial analysis revealed that ONIKURU's opening did not generate a uniform spillover effect throughout the suburban city center. Instead, it produced a spatially selective catalytic effect: while stay density increased near the facility and adjacent commercial areas, it concurrently decreased in another core area (near JR Ibaraki Station). This case quantifies the magnitude and spatial pattern of short-term stay reallocation following the opening of a multifunctional facility, informing debates on catalytic effects and providing a replicable evaluation approach.

Abstract

Urban design focused on improving walkability has received attention as a method of increasing physical activity among the population. However, only a few studies have examined the effect of walking time of opening multifunctional facilities as an architecture-scale intervention. This study aimed to clarify the effect of opening a multifunctional facility on residents’ daily walking time. In addition, this study analyzed the gender and age subgroups. The natural experiment was conducted using the case of the Ibaraki City Cultural and Childcare Complex “ONIKURU,” a public multifunctional facility. This study used GPS-trajectory data based on GPS tracking techniques, which is anonymized location data for smartphone users. The causal relationship was analyzed using propensity score matching and difference-in-differences analysis. The results showed that the opening of ONIKURU significantly increased the average walking time of visitors to 3.165 [− 1.697, 8.027] min/day compared with that of non-visitors. Specifically, visitors’ average daily walking time improved to a level comparable to that of non-visitors after the opening of ONIKURU. In addition, opening ONIKURU significantly increased female young adults’ average walking time to 3.385 [− 4.906, 11.676] min/day. Therefore, this study provides theoretical contributions to a health-promoting built environment significantly affecting walking at an architecture-scale intervention.

Introduction: The Japanese government has promoted the Compact Plus Network, which encourages people to live near train stations for health benefits. This study aimed to elucidate the impact of the opening of new train stations on the regional health expenditure per capita for medically treated middle-aged adults. The analysis provides insight into the characteristics of the stations that reduce the expenditure.

Materials and methods: This study employed a natural experiment design, utilizing the time difference in the opening period of the Osaka-Higashi Line. The Osaka-Higashi Line has a southern section that opened in 2008 and a northern section that opened in 2019. This study designated the four station areas surrounding the stations in the northern section, where a new station opened in 2019, as the exposure group. This analysis was conducted at two levels: the railway-line and individual station levels. The area surrounding the stations in the southern section was designated the covariate group. Our statistical analysis used the Causal-Impact algorithm on the medical dataset REZULT. This study analyzed 96-months before and after the opening of new stations.

Results: Our analysis sample has no significant changes in demographic characteristics before or after the stations’ opening. This study clarified that only the exposure groups (Shigino) reduced the cumulative health expenditure per capita by JPY 62,500.62 [95 %CI: −141218.67, 21306.54] over four years. However, the expenditure did not decrease in the exposure groups of the north section at the railway-line level, and JR-Awaji, Shirokitakōendōri, and JR-Noe stations at the individual station level.

Conclusion: New-station openings did not yield a significant overall line-level reduction in RHE over four years, but we observed station-level heterogeneity, with Shigino showing an estimated cumulative reduction (p = 0.06). Pre-opening higher RHE and stronger inter-network connectivity emerge as plausible moderators, suggesting targeted, station-screening approaches for health-informed rail planning.

Introduction: This study focuses on the opening of a new transit station as a possible approach to decreasing healthcare expenditure. The hypothesis was that opening a new transport station would encourage the employed people and their families to increase physical activity by improving transport accessibility. However, the causality between the building of the station and the decrease in healthcare expenditures has still not been fully understood. Therefore, this study aims to examine the impact of opening a public transport station on health expenditure per capita for medically treated employees and their families.

Methods: This study adopted a natural experiment using the case of the opening of the JR-Sojiji Station in Japan. Participants were selected from the medical dataset “REZULT,” which consists of aggregated health insurance claims data. The outcome was the average monthly health expenditures per capita. The exposure group was set as those who go to healthcare facilities in the Mishima and Oda districts, where JR Sojiji Station is located. The covariate group was set as those who go to healthcare facilities in other districts in Ibaraki City. The outcome was medical fee receipts from health insurers. The causal impact algorithm analyzed the causal relation using panel time series data.

Results and conclusion: These results of the causal impact algorithm indicated that opening a new public transport station was significantly associated with the decrease in average cumulative health expenditures per capita by approximately JPY 99257.31 (95% confidence interval is from JPY 62119.02 to JPY 136194.37) over four years. In conclusion, this study's results are consistent with previous studies suggesting that increased access to transit may increase physical activity among transit users and may lead to a decrease in healthcare expenditures.

Abstract

Introduction: During the COVID-19 pandemic, restrictions on human mobility caused health problems. Therefore, it is valuable to evaluate the human mobility restrictions during the pandemic from the population health viewpoint. This study aimed to clarify the correlation between changes in human mobility types and medical costs of lifestyle-related diseases during the pandemic.

Methods: The study design was set as a cross-sectional study regarding the human mobility types and the medical cost of lifestyle-related diseases. The population was Japanese people. Boosted tree analysis analyzed the nonlinear relationship between human mobility types and medical costs of lifestyle-related diseases in Japan. The boosted tree analysis can obtain high accurate models.

Results: The results of this analysis indicated that medical costs were differently affected by walking, driving, and public transit, depending on the type of prefecture. Increasing walking by over 70% reduced the medical costs of lifestyle-related diseases, even during the COVID-19 pandemic. In metropolitan prefectures, the total effect on medical cost was higher for walking and public transit. In addition, medical costs decreased by gradually increasing public transit use by over 110%. On the other hand, in other prefectures, the total effect of public transit was lower than driving, and medical costs increased from 80% to 160%. These results were significant because they indicated the target value for each human mobility type in metropolitan areas and other prefectures.

Conclusions: In conclusion, this analysis indicated that increasing walking and public transit use correlated with a decreasing in the medical costs of lifestyle-related diseases even during the COVID-19 pandemic. The results were significant because they indicate the target value for each human mobility type according to the metropolitan and the other prefectures. Based on the target values, our findings implicate that governments can take measures other than restricting walking and public transit during the pandemic.

In Japan, where the population is declining and aging significantly, walkability has attracted attention as a way to improve residents’ lifestyles. Therefore, it is essential to identify the residential clusters where walkability improvement would contribute to the maintenance of the population in order to select urban areas for the implementation of walkable designs. This study aimed to identify the residential clusters in which walkability affects the future population from the perspective of real estate prices. The reason for focusing on real estate prices is that they are expected to be a confounding factor connecting walkability and the future population. The method we used was to analyze the structural equation modeling of the impact of walkability index, real estate prices, and future population change ratio. This analysis was based on the neighborhood association scale. This study clarified that effective residential clusters are the business center cluster and the sprawl cluster. In the business center cluster and the sprawl cluster, the price of apartments for sale is the real estate value, through which the walkability index positively impacts the future population change ratio. This means that it is expected to contribute to the maintenance of the future population through a combination of walkable designs and housing policies that encourage people to change their residence types to apartments for sale when rebuilding old building stock using the location optimization plan policy.

This study aimed to clarify the effect of walkability on urban sustainability, according to the types of residential clusters in the Osaka Metropolitan fringe area. For this purpose, this study analyzed the statistical causal relationship between the Walkability Index and the Ecological Footprint to Biocapacity (EF/BC) ratio of each residential cluster. The EF/BC ratio is the ratio of the ecological footprint of the biocapacity of the residential clusters. As a result, the effect of walkability on urban sustainability was clarified depending upon the types of residential clusters in the Osaka Metropolitan fringe area. Specifically, it was found that the Walkability Index negatively affects the EF/BC ratio in the sprawl cluster. This suggests that, in the sprawl cluster, active efforts to improve the Walkability Index can contribute to the realization of SDGs (Sustainable Development Goals of the 2030 Agenda). However, Walkability Index has a strong positive effect on the EF/BC ratio in the old new-town cluster, etc. For the residential clusters, the results of this study suggested that there is a necessity to improve urban sustainability through approaches other than improving Walkability.

Urban shrinkage is a problem that is faced by some metropolitan areas globally in urban cities faced with depopulation. Therefore, these cities require “smart shrinking”, which consists of design methods intended to satisfy residents’living needs, even though the population is declining. The purpose of this paper is to develop a walkability indicator for visualizing smart shrinking. The methods include statistical analysis by GIS analysis and questionnaire in the Northern Osaka Metropolitan Area where there are many small-sprawl areas. The following four results were identified. First, the population decline in sprawl areas indicates the regional characteristics of each city. Second, this paper develops a walkability indicator composed of household density, convenience of facilities, road connectivity, and traffic safety. Third, Wi(i), which is walkability in each residential area, in sprawl areas, and in public housing areas, is important for future population change. Finally, the validity and effectiveness of the indicator is clarified by questionnaires regarding regional evaluation. In conclusion, the walkability indicator is able to visualize smart shrinking in sprawl areas.