Exploring impacts of land use characteristics in residential neighborhood and activity space on non-work travel behaviors

Li, Jingjing; Kim, Changjoo; Sang, Sunhee

doi:10.1016/j.jtrangeo.2018.06.001

Cited by 22 publications

(10 citation statements)

References 49 publications

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“…We employed a spatial–temporal aggregated predictor (STAP) modeling [ 24 ] to detect how associations between walkable destinations and transport walking varied across distances, and found that associations were negligible for distances larger than 0.25 km, which was in line with findings in a previous MESA study that smaller spatial scale of 0.2 km had stronger effects than larger ones [ 25 ]. Prior work among adults has widely used 1 km (equivalent to a 10–15 min walking distance) to represent the size of a residential neighborhood [ 8 , 11 , 20 , 23 ], and 5 km (~ 3.11 mile) represents the maximum distance because most US residents are unwilling to walk for transport farther that this [ 31 ].…”

Section: Methodsmentioning

confidence: 99%

Comparing effects of Euclidean buffers and network buffers on associations between built environment and transport walking: the Multi-Ethnic Study of Atherosclerosis

Peterson

Auchincloss

et al. 2022

Int J Health Geogr

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Background Transport walking has drawn growing interest due to its potential to increase levels of physical activities and reduce reliance on vehicles. While existing studies have compared built environment-health associations between Euclidean buffers and network buffers, no studies have systematically quantified the extent of bias in health effect estimates when exposures are measured in different buffers. Further, prior studies have done the comparisons focusing on only one or two geographic regions, limiting generalizability and restricting ability to test whether direction or magnitude of bias are different by context. This study aimed to quantify the degree of bias in associations between built environment exposures and transport walking when exposures were operationalized using Euclidean buffers rather than network buffers in diverse contexts. Methods We performed a simulations study to systematically evaluate the degree of bias in associations between built environment exposures in Euclidean buffers and network buffers and transport walking, assuming network buffers more accurately captured true exposures. Additionally, we used empirical data from a multi-ethnic, multi-site cohort to compare associations between built environment amenities and walking for transport where built environment exposures were derived using Euclidean buffers versus network buffers. Results Simulation results found that the bias induced by using Euclidean buffer models was consistently negative across the six study sites (ranging from -80% to -20%), suggesting built environment exposures measured using Euclidean buffers underestimate health effects on transport walking. Percent bias was uniformly smaller for the larger 5 km scale than the 1 km and 0.25 km spatial scales, independent of site or built environment categories. Empirical findings aligned with the simulation results: built environment-health associations were stronger for built environment exposures operationalized using network buffers than using Euclidean buffers. Conclusion This study is the first to quantify the extent of bias in the magnitude of the associations between built environment exposures and transport walking when the former are measured in Euclidean buffers vs. network buffers, informing future research to carefully conceptualize appropriate distance-based buffer metrics in order to better approximate real geographic contexts. It also helps contextualize existing research in the field that used Euclidean buffers when that were the only option. Further, this study provides an example of the uncertain geographic context problem. Supplementary Information The online version contains supplementary material available at 10.1186/s12942-022-00310-7.

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Section: Methodsmentioning

confidence: 99%

Comparing effects of Euclidean buffers and network buffers on associations between built environment and transport walking: the Multi-Ethnic Study of Atherosclerosis

Peterson

Auchincloss

et al. 2022

Int J Health Geogr

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“…Several studies have suggested that urban attributes (e.g., urban development factors and urban facilities) play a more important role in shaping resident's health and SWB (27,34) than neighborhood attributes. On the one hand, people often travel from their neighborhoods to other neighborhoods for diverse reasons (e.g., working and shopping) (35). A study from Shanghai has suggested that both perceived residential and workplace environmental attributes can affect people's SWB by influencing commuting satisfaction and place satisfaction (36).…”

Section: Literature Reviewmentioning

confidence: 99%

Urban and individual correlates of subjective well-being in China: An application of gradient boosting decision trees

Huang

Kang

Yin

et al. 2023

Front. Public Health

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IntroductionSubjective well-being (SWB) is attributable to both individual and environmental attributes. However, extant studies have paid little attention to the contribution of environmental attributes at the urban level to SWB or their nonlinear associations with SWB.MethodsThis study applies a machine learning approach called gradient boosting decision trees (GBDTs) to the 2013 China Household Income Survey data to investigate the relative importance of urban and individual attributes to and their nonlinear associations with SWB.ResultsThe urban and individual attributes make similar relative contributions to SWB. Income and age are the most important predictors. Urban facilities make a larger contribution than urban development factors. Moreover, urban attributes exert nonlinear and threshold effects on SWB. Cultural facilities and green space have inverted U-shaped correlations with SWB. Educational facilities, medical facilities, and population size are monotonically associated with SWB and have specific thresholds.DiscussionImproving urban attributes is important to enhancing residents’ SWB.

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“…Many researchers have explored how the built environment afects individual travel behavior [35][36][37][38]. Lucas studied the travel diary of adults in Merseyside, northwest England, and found that a person's actual location in the city had a greater impact on their travel mode than social factors such as family income, age, gender, and employment status [37].…”

Section: Associations Between the Built Environment And Travelmentioning

confidence: 99%

Effects of Individual and Built Environmental Features on Commuting Mode Shifts before and after the COVID-19 Outbreak in Guangzhou, China

Gao

Chen

et al. 2023

Journal of Advanced Transportation

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The novel coronavirus disease (COVID-19) pandemic has had a significant impact on transportation. Understanding how the epidemic in China has affected people’s travel mode choices can help city managers analyze the travel mode of different populations in the postepidemic phase. Based on a travel behavior questionnaire conducted in Guangzhou, China, during the COVID-19 epidemic and points-of-interest data, this study explored the impact of the built environment, travel characteristics, and socioeconomic factors on changes in commuters’ travel modes during the postepidemic phase. We found that gender, age, occupation, the decline in the rate of travel frequency, and built environment characteristics significantly influenced the change in travel mode. When respondents had to give up public transport, those in different professions had different options for alternative means of transportation. The density of residential facilities, bus stations, and government institutions had a more significant impact on the change in the travel mode of commuters. The research results provide a theoretical basis for policy and practice. After the outbreak of a major public health event, urban transport managers and policymakers should consider individual heterogeneity and environmental factors when formulating strategies to address public travel in unconventional situations.

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Exploring impacts of land use characteristics in residential neighborhood and activity space on non-work travel behaviors

Cited by 22 publications

References 49 publications

Comparing effects of Euclidean buffers and network buffers on associations between built environment and transport walking: the Multi-Ethnic Study of Atherosclerosis

Comparing effects of Euclidean buffers and network buffers on associations between built environment and transport walking: the Multi-Ethnic Study of Atherosclerosis

Urban and individual correlates of subjective well-being in China: An application of gradient boosting decision trees

Effects of Individual and Built Environmental Features on Commuting Mode Shifts before and after the COVID-19 Outbreak in Guangzhou, China

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