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This study investigated associations of neighborhood context with active transportation among women with children after controlling for sociodemographic variables. We used data from the Geographic Research on Wellbeing study (GROW). In 2012–2013, GROW surveyed mothers who participated in California's Maternal and Infant Health Assessment. The dependent variable was active vs. inactive transportation. Mothers were coded as doing active transportation if they responded that they “walked,” “walked and took public transportation,” or ‘rode a bike,” to most places they went in the previous 7 days, and were coded as doing inactive transportation if they responded that they “drove” any kind of vehicle or “got rides from someone else.” The independent variables were neighborhood-level (census tract) poverty, income inequality, and perceived neighborhood safety. Using a stratified sample of poor or near-poor (≤200% of the federal poverty level, N = 1231) and non-poor mothers (201+% of the federal poverty level, N = 1465), weighted logistic regression was conducted to estimate associations between neighborhood-level factors with active transportation after controlling for age, race/ethnicity, marital status, number of children, car ownership, education, family income, and population density. One in seven mothers reported active transportation with mothers in poor/near-poor families having a higher proportion of active transportation than mothers in higher income families (24% vs. 3%). In adjusted models, poor/near-poor mothers had twice the odds of using active transportation in very or somewhat unsafe neighborhoods compared with those in very safe neighborhoods. Neighborhood-level poverty and income inequality were not statistically significant. Results suggest that individual poverty is a primary driver of active transportation among mothers. Poor and near-poor mothers who perceived their neighborhoods as unsafe had higher odds of using active transportation. Policy and community resources should be allocated to provide safe routes in very unsafe areas where poor women live and where active transport is most likely to occur.

Research has rarely distinguished between non-work (NW) and work (W) active transport (AT) or investigated relationships to other domains of physical activity ([PA], like leisure time [LTPA] or work [WPA]). We investigated correlates of AT by employment status, accounting for LTPA and WPA, in a population-based sample of California mothers (N=2906) in the Geographic Research on Wellbeing (GROW) study (2012–2013). AT was measured by the National Household Travel Survey. LTPA was measured using the Stanford Leisure-Time Activity Categorical Item. WPA was measured with the Stanford Brief Activity Survey. Most employed mothers (53%) worked in sedentary jobs, and few (

Background Active transportation (AT) is a form of physical activity (PA), which improves cardiometabolic risk factors among non-Hispanic white adults in the United States. However, research among minority women is sparse. This study explored associations between AT and cardiometabolic risk factors among urban African American and Hispanic women (N=410). Methods This was a secondary analysis of data from the Health is Power study, a randomized controlled trial conducted in Houston and Austin, Texas (2006–2008) to increase PA or fruit and vegetable consumption among minority women. The sample comprised 63% African American and 37% Hispanic/Latina women (N=367 M=45.0±9.4 years). Sociodemographics (ethnicity, age, education, household income) and the International Physical Activity Questionnaire metabolic equivalent of task (MET)-minutes per week spent in AT and total PA were measured via interviewer administered questionnaire. Cardiometabolic risk factors (body mass index [BMI], body fat percentage [BF%], resting heart rate [RHR], systolic [SBP] and diastolic blood pressures [DBP]) were collected using established protocols. Unadjusted bivariate associations and associations adjusted for covariates (sociodemographics, site, total PA minus AT) between dichotomized AT use (any AT use [n=159] versus no AT use [n=208]) and cardiometabolic risk factors were examined. Results Participants reported mean AT MET-min/wk of 219.86±827.3. AT use was not significantly related to sociodemographic factors. AT users reported more AT MET-min/wk (M=507.5±1199.4) and total PA (M=3408.5±3930.0 MET-min/wk) than non-users (M=2324.3±3552.9 MET-min/wk; t(365)=-2.77, p=.006). When comparing PA levels excluding AT, the PA levels of AT users remained higher (M=2901.0±3499.0 MET-min/wk), though this difference was not significant (p=.122). SBP was lower for AT users (M=122.8±18.9) compared to non-users (M=125.0±13.4), but not significantly so (p=.208). AT was not associated with BMI, RHR, BF%, SBP, or DBP (all ps>.05). Conclusions Results showed no significant associations between AT use and cardiometabolic outcomes; however, SBP was slightly lower for AT users. Mean MET-min/wk of AT use was slightly lower than the minimum recommended PA guideline of 600 MET-min/wk to achieve health benefits with most (82%) AT users falling below 500 MET-min/wk. Total PA for both AT users and non-users was well above recommended guidelines, demonstrating small doses of AT may not provide additional benefits when meeting current recommendations. Further research should investigate the presence of a dose response in larger samples with participants engaging in higher levels of AT. This study was supported by a grant from the National Cancer Institute (1R01CA109403) to Dr. Rebecca E. Lee and Jonas Scholar Nurse Leader Cohort 2016–2018 to Elizabeth Lorenzo.

Background Women are typically less physically active than men, and active transport can help women meet physical activity recommendations. Little is known about special populations of women, such as women with young children, who may be especially sensitive to neighborhood conditions. The purpose of this study was to investigate the associations of neighborhood context with active transport among women with children after controlling for sociodemographic variables. Methods We used data from the Geographic Research on Wellbeing study (GROW). In 2012-2013, GROW surveyed mothers who participated in California’s Maternal and Infant Health Assessment. The dependent variable was active transport vs. inactive transport. Mothers were coded as doing active transport if they responded that they “walked,” “walked and took public transportation,” or ‘rode a bike,” to most places they went in the past 7 days, and were coded as doing inactive transport if they responded that they “drove” any kind of vehicle or “got rides from someone else.” The independent variables were neighborhood-level (census tract) poverty rates, and income inequality, and perceived neighborhood safety. Using a stratified sample of poor or near-poor ( Results One seventh of mothers reported active transport with mothers in poor/near-poor families having higher proportion of active transport than mothers in higher income families (24% vs. 3%). In adjusted models, poor/near-poor mothers in very unsafe neighborhoods had 2.5 times higher odds of active transport compared with those in very safe neighborhoods, and non-poor mothers in very unsafe neighborhoods had 7.5 times higher odds of active transport compared with those in very safe neighborhoods. Neighborhood-level poverty and income inequality were not statistically significant in the adjusted models. Conclusions Both poor and non-poor women with young children have higher rates of active transportation if they perceive their neighborhoods as very unsafe vs. very safe, presenting added risk for crime, injury, and psychological distress to these most vulnerable women. In contrast, objectively measured poverty rates and income inequality were not related to active transportation. Policy and community resources should be allocated to provide safe routes for women in very unsafe areas where active transport is most likely to occur.