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Towards Healthy Aging: Influence of the Built Environment on Elderly Pedestrian Safety at the Micro-Level

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  • Muhan Lv

    (Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China
    School of Geographic Sciences, East China Normal University, Shanghai 200241, China)

  • Ningcheng Wang

    (Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China
    School of Geographic Sciences, East China Normal University, Shanghai 200241, China)

  • Shenjun Yao

    (Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China
    School of Geographic Sciences, East China Normal University, Shanghai 200241, China
    Research Center for China Administrative Division, East China Normal University, Shanghai 200241, China)

  • Jianping Wu

    (Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China
    School of Geographic Sciences, East China Normal University, Shanghai 200241, China)

  • Lei Fang

    (Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China)

Abstract

As vulnerable road users, elderly pedestrians are more likely to be injured in road crashes due to declining physical and perceptual capabilities. Most previous studies on the influence of the built environment on elderly pedestrian safety focused on intersections or areal units. Using a district of Shanghai as the study area, this research investigated the effects of the built environment at the road segment level with elderly pedestrian collision, taxi tracking point, point of interest, street view image, open street map, land use, housing price, and elderly population datasets. In particular, this research employed both Poisson and geographically weighted Poisson regression (GWPR) models to account for spatial nonstationarity. The Poisson model indicates that green space, sidewalks, and junctions on the roads significantly affected elderly pedestrian safety, and roads around nursing homes, schools, bus stops, metro stations, traditional markets, and supermarkets were hazardous for elderly pedestrians. The results of the GWPR model suggest that the influence of factors varied across the study area. Green space could decrease the risk of elderly pedestrian collisions only in areas without congested environments. Separations need to be installed between roadways and sidewalks to improve elderly road safety.

Suggested Citation

  • Muhan Lv & Ningcheng Wang & Shenjun Yao & Jianping Wu & Lei Fang, 2021. "Towards Healthy Aging: Influence of the Built Environment on Elderly Pedestrian Safety at the Micro-Level," IJERPH, MDPI, vol. 18(18), pages 1-14, September.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:18:p:9534-:d:632958
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    References listed on IDEAS

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    1. Peng Zang & Xuhong Liu & Yabo Zhao & Hongxu Guo & Yi Lu & Charlie Q. L. Xue, 2020. "Eye-Level Street Greenery and Walking Behaviors of Older Adults," IJERPH, MDPI, vol. 17(17), pages 1-9, August.
    2. Lachapelle, Ugo & Cloutier, Marie-Soleil, 2017. "On the complexity of finishing a crossing on time: Elderly pedestrians, timing and cycling infrastructure," Transportation Research Part A: Policy and Practice, Elsevier, vol. 96(C), pages 54-63.
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    4. Ningcheng Wang & Yufan Liu & Jinzi Wang & Xingjian Qian & Xizhi Zhao & Jianping Wu & Bin Wu & Shenjun Yao & Lei Fang, 2019. "Investigating the Potential of Using POI and Nighttime Light Data to Map Urban Road Safety at the Micro-Level: A Case in Shanghai, China," Sustainability, MDPI, vol. 11(17), pages 1-14, August.
    5. A. Stewart Fotheringham & Martin Charlton & Chris Brunsdon, 1997. "Measuring Spatial Variations in Relationships with Geographically Weighted Regression," Advances in Spatial Science, in: Manfred M. Fischer & Arthur Getis (ed.), Recent Developments in Spatial Analysis, chapter 4, pages 60-82, Springer.
    6. Ye Sun & Wei Lu & Peijin Sun, 2021. "Optimization of Walk Score Based on Street Greening—A Case Study of Zhongshan Road in Qingdao," IJERPH, MDPI, vol. 18(3), pages 1-13, January.
    7. Lord, Dominique & Mannering, Fred, 2010. "The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(5), pages 291-305, June.
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    Citations

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    Cited by:

    1. Daniel Gálvez-Pérez & Begoña Guirao & Armando Ortuño, 2024. "Age-Friendly Urban Design for Older Pedestrian Road Safety: A Street Segment Level Analysis in Madrid," Sustainability, MDPI, vol. 16(19), pages 1-23, September.
    2. Daniel Gálvez-Pérez & Begoña Guirao & Armando Ortuño & Luis Picado-Santos, 2022. "The Influence of Built Environment Factors on Elderly Pedestrian Road Safety in Cities: The Experience of Madrid," IJERPH, MDPI, vol. 19(4), pages 1-20, February.
    3. Yiwen Zhang & Haizhi Luo & Jiami Xie & Xiangzhao Meng & Changdong Ye, 2023. "The Influence and Prediction of Built Environment on the Subjective Well-Being of the Elderly Based on Random Forest: Evidence from Guangzhou, China," Land, MDPI, vol. 12(10), pages 1-16, October.
    4. Wudong Zhao & Liwei Zhang & Xupu Li & Lixian Peng & Pengtao Wang & Zhuangzhuang Wang & Lei Jiao & Hao Wang, 2022. "Residents’ Preference for Urban Green Space Types and Their Ecological-Social Services in China," Land, MDPI, vol. 11(12), pages 1-20, December.
    5. Xiaoran Huang & Pixin Gong & Marcus White, 2022. "Study on Spatial Distribution Equilibrium of Elderly Care Facilities in Downtown Shanghai," IJERPH, MDPI, vol. 19(13), pages 1-17, June.

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