Health & place · 2010
Longitudinal associations between neighborhood-level street network with walking, bicycling, and jogging: the CARDIA study.
СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Hou Ningqi, Popkin Barry M, Jacobs David R, Song Yan, Guilkey David, Lewis Cora E, Gordon-Larsen Penny
Аннотация
OBJECTIVE: To investigate the differential association between neighborhood-level street network with walking, bicycling, and jogging by urbanicity and gender.
METHODS: We used prospective data from 4 repeated exams on 5115 young adults recruited in 1985-1986, followed through 2000-2001, with self-reported walking, bicycling, and jogging. Using a Geographic Information System, we spatially and temporally linked time-varying residential locations to street network data within a 1 km Euclidean buffer. Two-part marginal effect modeling assessed longitudinal associations between neighborhood-level street network with walking, bicycling, and jogging, by urbanicity and gender, controlling for time-varying individual- and census-level covariates.
RESULTS: Neighborhood street density was positively associated with walking, bicycling, and jogging in low urbanicity areas, but in middle and high urbanicity areas, these associations became null (men) or inverse (women).
CONCLUSION: Characteristics of neighborhood streets may influence adult residents' walking, bicycling, and jogging, particularly in less urban areas. This research may inform policy efforts to encourage physical activity.
METHODS: We used prospective data from 4 repeated exams on 5115 young adults recruited in 1985-1986, followed through 2000-2001, with self-reported walking, bicycling, and jogging. Using a Geographic Information System, we spatially and temporally linked time-varying residential locations to street network data within a 1 km Euclidean buffer. Two-part marginal effect modeling assessed longitudinal associations between neighborhood-level street network with walking, bicycling, and jogging, by urbanicity and gender, controlling for time-varying individual- and census-level covariates.
RESULTS: Neighborhood street density was positively associated with walking, bicycling, and jogging in low urbanicity areas, but in middle and high urbanicity areas, these associations became null (men) or inverse (women).
CONCLUSION: Characteristics of neighborhood streets may influence adult residents' walking, bicycling, and jogging, particularly in less urban areas. This research may inform policy efforts to encourage physical activity.