Built environment influence on the incidence of elderly pedestrian collisions in a medium-large city in southern Brazil: a spatial analysis

References

• Antoniadis, A., & Oppenheim, G. (1995). Wavelets and statistics: Lecture notes in statistics (p. 281). Springer.
   Google Scholar
• Bailey, T. C., & Gatrell, A. C. (1995). Interactive spatial data analysis. Longman Scientific & Technical.
   Google Scholar
• Bates, D., Chambers, J., & Dalgaard, P. (2013). The R project for statistical computing. Retrieved February 5, 2022, from https://www.r-project.org/.
   Google Scholar
• Bithell, J. F. (1990). An application of density estimation to geographical epidemiology. Statistics in Medicine, 9(6), 691–701. https://doi.org/10.1002/sim.4780090616
   PubMed Web of Science ®Google Scholar
• Bithell, J. F. (1991). Estimation of relative risk functions. Statistics in Medicine, 10(11), 1745–1751. https://doi.org/10.1002/sim.4780101112
   PubMed Web of Science ®Google Scholar
• Bonne, S., & Schuerer, D. J. E. (2013). Trauma in the older adult. Epidemiology and evolving geriatric trauma principles. Clinics in Geriatric Medicine, 29(1), 137–150. https://doi.org/10.1016/j.cger.2012.10.008
   PubMed Web of Science ®Google Scholar
• Brand, S., Otte, D., Mueller, C. W., Petri, M., Haas, P., Stuebig, T., Krettek, C., & Haasper, C. (2012). Injury patterns of seniors in traffic accidents: A technical and medical analysis. World Journal of Orthopedics, 3(9), 151–155. https://doi.org/10.5312/wjo.v3.i9.151
   PubMedGoogle Scholar
• Câmara, G., Neves, M., Monteiro, A. M. V., Souza, R. C. M., Paiva, J. A., & Vinhas, L. Ú. B. I. A. (2002). SPRING and TerraLib: Integrating spatial analysis and GIS. In Proceedings of the SCISS specialist meeting new tools for spatial data analysis.
   Google Scholar
• Camargos, M. C. S., Gonzaga, M. R., Costa, J. V., & Bomfim, W. (2019). Disability-free life expectancy estimates for Brazil and Major Regions, 1998 and 2013. Ciencia & Saude Coletiva, 24(3), 737–747. https://doi.org/10.1590/1413-81232018243.07612017
   PubMed Web of Science ®Google Scholar
• Caro, F. G., & Fitzgerald, K. G. (2016). International perspectives on age-friendly cities. Routledge Studies in Human Geography.
   Google Scholar
• Chandran, A., Sousa, T. R. V., Guo, Y., Bishai, D., & Pechansky F.. (2012). Road traffic deaths in Brazil: Rising trends in pedestrian and motorcycle occupant deaths. Traffic Injury Prevention, 13(sup1), 11–16. https://doi.org/10.1080/15389588.2011.633289
   PubMed Web of Science ®Google Scholar
• Choi, J., Tay, R., Kim, S., & Jeong, S. (2019). Behaviors of older pedestrians at crosswalks in South Korea. Accident; Analysis and Prevention, 127, 231–235. https://doi.org/10.1016/j.aap.2019.03.005
   PubMed Web of Science ®Google Scholar
• Congiu, T., Sotgiu, G., Castiglia, P., Azara, A., Piana, A., Saderi, L., & Dettori, M. (2019). Built environment features and pedestrian accidents: An Italian retrospective study. Sustainability, 11(4), 1064. https://doi.org/10.3390/su11041064
   Web of Science ®Google Scholar
• Cuschieri, S. (2019). The STROBE guidelines. Saudi Journal of Anaesthesia, 13(suppl. 1), S31–S34. https://doi.org/10.4103/sja.SJA_543_18
   PubMed Web of Science ®Google Scholar
• Dai, D., Taquechel, E., Steward, J., & Strasser, S. (2010). The impact of the built environment on pedestrian crashes and the identification of crash clusters on an urban university campus. The Western Journal of Emergency Medicine, 11(3), 294–301. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2941370/.
   PubMedGoogle Scholar
• Davies, T. M., & Hazelton, M. L. (2010). Adaptive kernel estimation of spatial relative risk. Statistics in Medicine, 29(23), 2423–2437. https://doi.org/10.1002/sim.3995
   PubMed Web of Science ®Google Scholar
• Davies, T. M., Marshall, J. C., & Hazelton, M. L. (2011). sparr: Analyzing spatial relative risk using fixed and adaptive kernel density estimation in R. Journal of Statistical Software, 39(1), 01–14. https://doi.org/10.18637/jss.v039.i01
   PubMed Web of Science ®Google Scholar
• Davies, T. M., Marshall, J. C., & Hazelton, M. L. (2018). Tutorial on kernel estimation of continuous spatial and spatiotemporal relative risk. Statistics in Medicine, 37(7), 1191–1221. https://doi.org/10.1002/sim.7577
   PubMed Web of Science ®Google Scholar
• de Andrade, L., Vissoci, J. R. N., Rodrigues, C. G., Finato, K., Carvalho, E., Pietrobon, R., de Souza, E. M., Nihei, O. K., Lynch, C., & de Barros Carvalho, M. D. (2014). Brazilian road traffic fatalities: A spatial and environmental analysis. PLoS One, 9(1), e87244. https://doi.org/10.1371/journal.pone.0087244
   PubMed Web of Science ®Google Scholar
• Distefano, N., Pulvirenti, G., & Leonardi, S. (2021). Neighborhood walkability: Elderly’s priorities. Research in Transportation Business & Management, 40, 100547. https://doi.org/10.1016/j.rtbm.2020.100547
   Web of Science ®Google Scholar
• Dusa, A., Paduraru, C., & jQuery, F. (2022). QCA: Qualitative comparative analysis. https://CRAN.R-project.org/package=QCA.
   Google Scholar
• Gao, C. H., Yu, G., & Cai, P. (2021). ggVennDiagram: An intuitive, easy-to-use, and highly customizable R package to generate Venn diagram. Frontiers in Genetics, 12, 706907. https://doi.org/10.3389/fgene.2021.706907
   PubMed Web of Science ®Google Scholar
• IBGE: Instituto Brasileiro de Geografia e Estatística. (2019). Idosos indicam caminhos para uma melhor idade. https://censo2020.ibge.gov.br.
   Google Scholar
• IBGE: Instituto Brasileiro de Geografia e Estatística. (2021). Malhas de Setores Censitários. https://www.ibge.gov.br/geociencias/organizacao-do-territorio/estrutura-territorial/26565-malhas-de-setores-censitarios-divisoes-intramunicipais.html?=&t=acesso-ao-produto.
   Google Scholar
• IPEA: Instituto de Pesquisa Econômica Aplicada. (2020). Brasil gasta 132 bilhões por ano com acidentes de transporte. https://ipea.gov.br.
   Google Scholar
• Keall, M. D. (1995). Pedestrian exposure to risk of road accident in New Zealand. Accident Analysis & Prevention, 27(5), 729–740. https://doi.org/10.1016/0001-4575(95)00019-V
   PubMed Web of Science ®Google Scholar
• Kerr, J., Rosenberg, D., & Frank, L. (2012). The role of the built environment in healthy aging: Community design, physical activity and health among older adults. Journal of Planning Literature, 27(1), 43–60. https://doi.org/10.1177/0885412211415283
   Web of Science ®Google Scholar
• Killerby, M. E., Link-Gelles, R., Haight, S. C., Schrodt, C. A., England, L., Gomes, D. J., Shamout, M., Pettrone, K., O’Laughlin, K., Kimball, A., Blau, E. F., Burnett, E., Ladva, C. N., Szablewski, C. M., Tobin-D’Angelo, M., Oosmanally, N., Drenzek, C., Murphy, D. J., Blum, J. M., … Tate, J. E., & CDC COVID-19 Response Clinical Team. (2020). Characteristics Associated with Hospitalization Among Patients. MMWR. Morbidity and Mortality Weekly Report, 69(25), 790–794. https://doi.org/10.15585/mmwr.mm6925e1 external icon.
   PubMed Web of Science ®Google Scholar
• Kim, D. (2019). The transportation safety of elderly pedestrians: Modeling contributing factors to elderly pedestrian collisions. Accident; Analysis and Prevention, 131, 268–274. https://doi.org/10.1016/j.aap.2019.07.009
   PubMed Web of Science ®Google Scholar
• Kothari, P., Kreiss, S., & Alahi, A. (2021). Human trajectory forecasting in crowds: A deep learning perspective. IEEE Transactions on Intelligent Transportation Systems, 1, 1–17. https://doi.org/10.48550/arXiv.2007.0363
   Google Scholar
• Kröyer, H. R. (2015). Is 30 km/ha ‘safe’speed. Injury severity of pedestrians struck by a vehicle and the relation to travel speed and age. IATSS Research, 39(1), 42–50. https://doi.org/10.1016/j.iatssr.2014.08.001
   Web of Science ®Google Scholar
• Lee, H. H., Cho, J. S., Lim, Y. S., Hyun, S. Y., Woo, J. H., Jang, J. H., & Yang, H. J. (2019). Relationship between age and injury severity in traffic accidents involving elderly pedestrians. Clinical and Experimental Emergency Medicine, 6(3), 235–241. https://doi.org/10.15441/ceem.18.052
   PubMed Web of Science ®Google Scholar
• Lee, S., Yoon, J., & Woo, A. (2020). Does elderly safety matter? Associations between built environments and pedestrian crashes in Seoul, Korea. Accident; Analysis and Prevention, 144, 105621. https://doi.org/10.1016/j.aap.2020.105621
   PubMed Web of Science ®Google Scholar
• Liu, Y., Wheaton, A. G., Chapman, D. P., Cunningham, T. J., Lu, H., & Croft, J. B. (2016). Prevalence of healthy sleep duration among adults—United States, 2014. MMWR. Morbidity and Mortality Weekly Report, 65(6), 137–141. https://doi.org/10.15585/mmwr.mm6506a1
   PubMed Web of Science ®Google Scholar
• Lv, M., Wang, N., Yao, S., Wu, J., & Fang, L. (2021). Towards healthy aging: Influence of the built environment on elderly pedestrian safety at the micro-level. International Journal of Environmental Research and Public Health, 18(18), 9534. https://doi.org/10.3390/ijerph1818953
   PubMed Web of Science ®Google Scholar
• Maciejewski, R., Hafen, R., Rudolph, S., Larew, S. G., Mitchell, M. A., Cleveland, W. S., & Ebert, D. S. (2011). Forecasting hotspots-A predictive analytics approach. IEEE Transactions on Visualization and Computer Graphics, 17(4), 440–453. https://doi.org/10.1109/TVCG.2010.82
   PubMed Web of Science ®Google Scholar
• Macrotrends. (n.d.). World Life Expectancy 1950-2023. https://www.macrotrends.net/countries/WLD/world/life-expectancy.
   Google Scholar
• McElroy, L. M., Juern, J. J., Bertleson, A., Xiang, Q., Szabo, A., & Weigelt, J. (2013). A single urban center experience with adult pedestrians struck by motor vehicles. Wisconsin Medical Journal, 112(3), 117–122. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3845352/.
   Google Scholar
• Meredith, W., Ibingira, T. J., Andrade, L., Mmbaga, B. T., Vissoci, J. R. N., Mvungi, M., & Staton, C. A. (2018). Built environment analysis for road traffic hotspot locations in Moshi, Tanzania. International Journal of Injury Control and Safety Promotion, 25(3), 272–278. https://doi.org/10.1080/17457300.2018.1431941
   PubMed Web of Science ®Google Scholar
• Moradi, A., Soori, H., Kavousi, A., Eshghabadi, F., Nematollahi, S., & Zeini, S. (2017). Effective environmental factors on geographical distribution of traffic accidents on pedestrians, downtown Tehran city. International Journal of Critical Illness and Injury Science, 7(2), 101–106. https://doi.org/10.4103/2229-5151.207750
   PubMedGoogle Scholar
• O’hern, S., Oxley, J., & Logan, D. (2015). Older adults at increased risk as pedestrians in Victoria, Australia: An examination of crash characteristics and injury outcomes. Traffic Injury Prevention, 16(sup2), S161–S167. https://doi.org/10.1080/15389588.2015.1061662
   PubMed Web of Science ®Google Scholar
• Olszewski, P., Szagała, P., Wolański, M., & Zielińska, A. (2015). Pedestrian fatality risk in accidents at unsignalized zebra crosswalks in Poland. Accident; Analysis and Prevention, 84, 83–91. https://doi.org/10.1016/j.aap.2015.08.008
   PubMed Web of Science ®Google Scholar
• Organização Pan-Americana de Saúde (PAHO). (2019). Segurança no trânsito. https://www.paho.org/pt/topicos/seguranca-no-transito.
   Google Scholar
• Pappas, I. O., & Woodside, A. G. (2021). Fuzzi-set Qualitative Comparative Analyssi (fsQCA): Guidelines for research practice in Information Systems and marketing. International Journal of Information Management, 58, 102310. https://doi.org/10.1016/j.ijinfomgt.2021.102310
   Web of Science ®Google Scholar
• Park, S., & Ko, D. (2020). A multilevel model approach for investigating individual accident characteristics and neighborhood environment characteristics affecting pedestrian-vehicle crashes. International Journal of Environmental Research and Public Health, 17(9), 3107. https://doi.org/10.3390/ijerph17093107
   PubMed Web of Science ®Google Scholar
• Ragin, C. C. (1987). The comparative method: Moving beyond qualitative and quantitative strategies. Berkeley. https://www.jstor.org/stable/10.1525/j.ctt6wqbwk.
   Google Scholar
• Romero, D. L., Barros, D. M., Belizario, G. O., & Serafim, A. P. (2019). Personality traits and risky behavior among motorcyclists: An exploratory study. Plos One, 14(12), e0225949. https://doi.org/10.1371/journal.pone.0225949
   PubMed Web of Science ®Google Scholar
• Slaughter, W. N., Williams, N., Wall, S. P., Glass, N. E., Simon, R., Todd, S. R., Bholat, O. S., Jacko, S., Roe, M., Wilson, C. T., Levine, D. A., Marshall, G., Chee, P. A., Pachter, H. L., & Frangos, S. G. (2014). A community traffic safety analysis of pedestrian and bicyclist injuries based on the catchment area of a trauma center. The Journal of Trauma and Acute Care Surgery, 76(4), 1103–1110. https://doi.org/10.1097/TA.0000000000000176
   PubMedGoogle Scholar
• Staton, C. A., Silva, V. D., Krebs, E., Andrade, L., Rulisa, S., Mallawaarachchi, B. S., Jin, K., Vissoci, J. R., & Ostbye, T. (2015). High road utilizers surveys compared to police data for road traffic crash hotspot localization in Rwanda and Sri Lanka. BMC Public Health, 16(1), 1–8. https://doi.org/10.1186/s12889-015-2609-1
   Google Scholar
• Tapiro, H., Gilad, T. O., & Parmet, Y. (2020). Pedestrian distraction: The effects of road environment complexity and age on pedestrian’s visual attention and crossing behavior. Journal of Safety Research, 72, 101–109. https://doi.org/10.1016/j.jsr.2019.12.003
   PubMed Web of Science ®Google Scholar
• Tatem, A. J. (2017). WorldPop, open data for spatial demography. Scientific Data, 4(1), 2–5. https://doi.org/10.1038/sdata.2017.4
   Google Scholar
• Thomson, D. R., Leasure, D. R., Bird, T., Tzavidis, N., & Tatem, A. J. (2022). How accurate are WorldPop-Global-Unconstrained gridded population data at the cell-level?: A simulation analysis in urban Namibia. PloS One, 17(7), e0271504. https://doi.org/10.1371/journal.pone.0271504
   PubMed Web of Science ®Google Scholar
• van Hoof, J., Kazak, J., Perek-Białas, J., & Peek, S. (2018). Challenges of urban ageing: Making cities age-friendly in Europe. International Journal of Environmental Research and Public Health, 15(11), 2473. https://doi.org/10.3390/ijerph15112473
   PubMed Web of Science ®Google Scholar
• Wei, T., & Simko, V. (2020). An introduction to corrplot package. https://cran.r-project.org/web/packages/corrplot/vignettes/corrplot-intro.html.
   Google Scholar
• World Health Organization. (2007). Global age-friendly cities: A guide. World Health Organization.
   Google Scholar
• World Health Organization. (2018). Global status report on road safety 2018: Summary. World Health Organization
   Google Scholar
• WorldPop. (2020). Top-down estimation modeling: Constrained vs unconstrained. www.worldpop.org/methods/top_down_constrained_vs_unconstrained.
   Google Scholar