What triggers selective daily mobility among older adults? A study comparing trip and environmental characteristics between observed path and shortest path

Klein, Sylvain; Brondeel, Ruben; Chaix, Basile; Klein, Olivier; Thierry, Benoît; Kestens, Yan; Gerber, Philippe; Perchoux, Camille

doi:10.1016/j.healthplace.2021.102730

Cited by 8 publications

(9 citation statements)

References 54 publications

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“…By using large-scale human-mobility data, this study is one of the first to systematically demonstrate the existence of the SDMB in restaurant visits on the community level. Our results are in line with previous findings demonstrating the wide existence of the SDMB across various domains, such as choice of transportation mode, travel route, travel distance, daily travel-time, sports facility and general destinations in daily life [ 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 ]. For example, several studies examined the influence of individuals/households sociodemographic factors on travel route and mode [ 22 ], daily travel-time [ 25 ], and travel distance [ 26 ], and found peoples’ travel behaviors differ according to individual characteristics.…”

Section: Discussionsupporting

confidence: 93%

“…Our results are in line with previous findings demonstrating the wide existence of the SDMB across various domains, such as choice of transportation mode, travel route, travel distance, daily travel-time, sports facility and general destinations in daily life [ 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 ]. For example, several studies examined the influence of individuals/households sociodemographic factors on travel route and mode [ 22 ], daily travel-time [ 25 ], and travel distance [ 26 ], and found peoples’ travel behaviors differ according to individual characteristics. In addition, previous studies observed that individuals make intentional choices of sport facilities for physical activity, which often go beyond their residential neighborhood [ 19 , 20 ].…”

Section: Discussionsupporting

confidence: 93%

“…In addition, previous studies observed that individuals make intentional choices of sport facilities for physical activity, which often go beyond their residential neighborhood [ 19 , 20 ]. Another study found individual environmental preferences, such as green environments, can result in differences in travel route and mode selection [ 22 ]. While the manifestation of the SDMB in food environment research is emerging, most of the existing studies do not empirically evaluate the SDMB or consider it as a potential limitation [ 15 ].…”

Section: Discussionmentioning

confidence: 99%

“…The SDMB expands this concept to reflect the selective bias in peoples’ daily visited sites [ 17 ]. While the SDMB is an emerging issue that has been observed and identified across multiple contexts (e.g., choice of transportation mode, travel route, travel distance, daily travel time, facilities, and general choice of destinations in daily life [ 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 ]), to date, the SDMB has received scant attention in community food environmental research [ 15 ]. In addition, the issue has not been well discussed in the context of health inequity, meaning that people with different socioeconomic statuses could be affected by the SDMB unequally in their everyday procurement of food.…”

Section: Introductionmentioning

confidence: 99%

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Selective Daily Mobility Bias in the Community Food Environment: Case Study of Greater Hartford, Connecticut

et al. 2023

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The community food environment has potential influences on community members’ dietary health outcomes, such as obesity and Type II diabetes. However, most existing studies evaluating such health effects neglect human mobility. In food patrons’ daily travels, certain locations may be preferred and patronized more frequently than others. This behavioral uncertainty, known as the selective daily mobility bias (SDMB), is less explored in community-food-environment research. In this paper, we aim to confirm the existence of the SDMB by systematically exploring the large-scale GPS-based restaurant-visit patterns in the Greater Harford region, Connecticut. Next, we explore the restaurant and neighborhood characteristics that are associated with the restaurant-visit patterns. Our primary results demonstrate that (1) most restaurant customers originate from areas outside of the census tract where the restaurant is located, and (2) restaurants located in socially vulnerable areas attract more customers in total, more customers from local areas, and more customers from other socially vulnerable areas. These results confirm the relevance of the SDMB to the community food environment, and suggest ways that the SDMB can be moderated by an uneven socio-economic landscape. The findings demonstrate the necessity of incorporating human-mobility data into the study of the community food environment.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Selective Daily Mobility Bias in the Community Food Environment: Case Study of Greater Hartford, Connecticut

et al. 2023

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“…This observation may be due to selective daily mobility bias, potentially affecting individuals' choices and attitudes toward travel 74 . People tend to choose travel-friendly routes given choices in travel pattern creation 75 and ambient exposure levels 76 . In terms of exposure to PM 2.5 , traffic emissions have been recognized as one of the primary sources.…”

Section: Available Evidencementioning

confidence: 99%

Measuring environmental exposures in people’s activity space: The need to account for travel modes and exposure decay

Wei

Kwan

Vermeulen

et al. 2023

Preprint

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BackgroundAccurately quantifying people’s out-of-home environmental exposure is important for identifying disease risk factors. Several activity space-based exposure assessments exist, possibly leading to different exposure estimates, and have neither considered individual travel modes nor exposure-related distance decay effects.ObjectiveWe aimed 1) to develop an activity space-based exposure assessment approach that included travel modes and exposure-related distance decay effects and 2) to compare the size of such spaces and the exposure estimates derived from them across typically used activity space operationalizations.MethodsWe used 7-day-long global positioning system (GPS)-enabled smartphone-based tracking data of 269 Dutch adults. People’s GPS trajectory points were classified into passive and active travel modes. Exposure-related distance decay effects were modeled through linear, exponential, and Gaussian decay functions. We performed cross-comparisons on these three functional decay models and an unweighted model in conjunction with four activity space models (i.e., home-based buffers, minimum convex polygons, two standard deviational ellipses, and time-weighted GPS-based buffers). We applied non-parametric Kruskal-Wallis tests, pair-wise Wilcoxon signed-rank tests, and Spearman correlations to assess mean differences in the extent of the activity spaces and correlations across exposures to particulate matter (PM2.5), noise, green space, and blue space.ResultsParticipants spent, on average, 42% of their daily life out-of-home. We observed that including travel modes into activity space delineation resulted in significantly more compact activity spaces. Exposure estimates for PM2.5and blue space were significantly (p<0.05) different between exposure estimates that did or did not account for travel modes, unlike noise and green space, for which differences did not reach significance. While the inclusion of distance decay effects significantly affected noise and green space exposure assessments, the decay functions applied appear not to have had any impact on the results. We found that residential exposure estimates appear appropriate for use as proxy values for the overall amount of PM2.5exposure in people’s daily lives, while GPS-based assessments are suitable for noise, green space, and blue space.SignificanceFor some exposures, the tested activity space definitions, although significantly correlated, exhibited differing exposure estimate results based on inclusion or exclusion of travel modes or distance decay effect. Results only supported using home-based buffer values as proxies for individuals’ daily short-term PM2.5exposure.Impact statementAccurately quantifying people’s out-of-home environmental exposure is vital for identifying disease risk and protective factors. Although many activity space-based exposure assessments exist, these approaches possibly lead to different exposure estimates. We methodologically and conceptually innovate by developing an activity space-based exposure assessment considering people’s travel modes and exposure-related distance decay effect. Our comparison with other activity spaces provides novel insights into dynamic exposure assessment approaches. Despite most epidemiological studies still considering people’s homes as the sole exposure location, our study is fundamental because people are typically exposed to multiple out-of-home environmental contexts.

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Methodological Challenges of the Cross‐Analysis Between Daily Mobility, Environments and Health

PERCHOUX

2024

Everyday Mobility and Health

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What triggers selective daily mobility among older adults? A study comparing trip and environmental characteristics between observed path and shortest path

Cited by 8 publications

References 54 publications

Selective Daily Mobility Bias in the Community Food Environment: Case Study of Greater Hartford, Connecticut

Selective Daily Mobility Bias in the Community Food Environment: Case Study of Greater Hartford, Connecticut

Measuring environmental exposures in people’s activity space: The need to account for travel modes and exposure decay

Methodological Challenges of the Cross‐Analysis Between Daily Mobility, Environments and Health

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