GPS-based street-view greenspace exposure and wearable assessed physical activity in a prospective cohort of US women.

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Titel: GPS-based street-view greenspace exposure and wearable assessed physical activity in a prospective cohort of US women.
Autoren: Yi, Li, Hart, Jaime E., Wilt, Grete, Hu, Cindy R., Jimenez, Marcia Pescador, Lin, Pi-I Debby, Suel, Esra, Hystad, Perry, Hankey, Steve, Zhang, Wenwen, Chavarro, Jorge E., Laden, Francine, James, Peter
Quelle: International Journal of Behavioral Nutrition & Physical Activity; 7/6/2025, Vol. 22 Issue 1, p1-11, 11p
Schlagwörter: NATURE, WOMEN, RESEARCH funding, SEASONS, RESIDENTIAL patterns, SOCIOECONOMIC factors, WEARABLE technology, DESCRIPTIVE statistics, LONGITUDINAL method, WALKING, HUMIDITY, GEOGRAPHIC information systems, DEEP learning, TEMPERATURE, CONFIDENCE intervals, PHYSICAL activity, NEIGHBORHOOD characteristics, ALGORITHMS, SOCIAL classes
Geografische Kategorien: UNITED States
Abstract: Background: Increasing evidence positively links greenspace and physical activity (PA). However, most studies use measures of greenspace, such as satellite-based vegetation indices around the residence, which fail to capture ground-level views and day-to-day dynamic exposures, potentially misclassifying greenspace and limiting policy relevance. Methods: We analyzed data from the US-based Nurses' Health Study 3 Mobile Health Substudy (2018–2020). Participants wore Fitbits™ and provided smartphone global positioning system (GPS) for four 7-day periods throughout the year. Street-view greenspace (%trees, %grass, %other greenspace [flowers/plants/fields]) were derived from 2019 street-view imagery using deep-learning algorithms at a 100-meter resolution and linked to 10-minute GPS observations. Average steps-per-minute for were calculated for each 10-minute period following each GPS observation. Generalized Additive Mixed Models examined associations of street-view greenspace exposure with PA, adjusting for individual and area-level covariates. We considered effect modification by region, season, neighborhood walkability and socioeconomic status (SES), temperature, and precipitation. Results: Our sample included 335 participants (meanage= 39.4 years, n = 304,394 observations). Mean steps-per-minute per 10-minutes were 6.9 (SD = 14.6). An IQR increase (18.7%) in street-view trees was associated with a 0.36 steps-per-minute decrease (95%CI: -0.71, -0.01). In addition, an IQR increase (10.6%) in grass exposure was associated with a 0.59 steps-per-minute decrease (95% CI: -0.79, -0.40); however, the association was non-linear and flattened out after the 75th percentile of street-view grass. Conversely, an IQR increase (1.2%) in other greenspace was associated with a 1.99 steps-per-minute increase (95%CI: 0.01, 3.97). Associations were stronger in the spring and in higher SES neighborhoods, and among residents of the Northeast. Conclusions: In this prospective cohort, momentary street-view exposure to trees and grass was inversely associated with PA, while exposure to other greenspace was positively associated. Future research should confirm these results in other populations and explore the mechanisms through which specific greenspace components influence PA. [ABSTRACT FROM AUTHOR]
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Datenbank: Complementary Index
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Abstract:Background: Increasing evidence positively links greenspace and physical activity (PA). However, most studies use measures of greenspace, such as satellite-based vegetation indices around the residence, which fail to capture ground-level views and day-to-day dynamic exposures, potentially misclassifying greenspace and limiting policy relevance. Methods: We analyzed data from the US-based Nurses' Health Study 3 Mobile Health Substudy (2018–2020). Participants wore Fitbits™ and provided smartphone global positioning system (GPS) for four 7-day periods throughout the year. Street-view greenspace (%trees, %grass, %other greenspace [flowers/plants/fields]) were derived from 2019 street-view imagery using deep-learning algorithms at a 100-meter resolution and linked to 10-minute GPS observations. Average steps-per-minute for were calculated for each 10-minute period following each GPS observation. Generalized Additive Mixed Models examined associations of street-view greenspace exposure with PA, adjusting for individual and area-level covariates. We considered effect modification by region, season, neighborhood walkability and socioeconomic status (SES), temperature, and precipitation. Results: Our sample included 335 participants (mean<subscript>age</subscript>= 39.4 years, n = 304,394 observations). Mean steps-per-minute per 10-minutes were 6.9 (SD = 14.6). An IQR increase (18.7%) in street-view trees was associated with a 0.36 steps-per-minute decrease (95%CI: -0.71, -0.01). In addition, an IQR increase (10.6%) in grass exposure was associated with a 0.59 steps-per-minute decrease (95% CI: -0.79, -0.40); however, the association was non-linear and flattened out after the 75th percentile of street-view grass. Conversely, an IQR increase (1.2%) in other greenspace was associated with a 1.99 steps-per-minute increase (95%CI: 0.01, 3.97). Associations were stronger in the spring and in higher SES neighborhoods, and among residents of the Northeast. Conclusions: In this prospective cohort, momentary street-view exposure to trees and grass was inversely associated with PA, while exposure to other greenspace was positively associated. Future research should confirm these results in other populations and explore the mechanisms through which specific greenspace components influence PA. [ABSTRACT FROM AUTHOR]
ISSN:14795868
DOI:10.1186/s12966-025-01795-8