Walking for transportation and built environment in Sao Paulo city, Brazil

Florindo, Alex Antônio; Barbosa, José Elpídio; Barrozo, Lígia Vizeu; Andrade, Douglas Roque; Aguiar, Breno Souza de; Failla, Marcelo Antunes; Gunn, Lucy; Mavoa, Suzanne; Turrell, Gavin; Goldbaum, Moisés

doi:10.1016/j.jth.2019.100611

Cited by 26 publications

(31 citation statements)

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“…We showed that better access to a mix of destinations was inversely associated with sedentary behavior in females. The mix of destinations involved access to green areas, physical activity and transportation facilities, primary health care units, supermarkets and food facilities in 500 m buffers of participant's residences and higher levels of this score was associated with more likelihood for walking in another study in this same sample [19].…”

Section: Resultsmentioning

confidence: 83%

“…Georeferencing resulted in 3,145 participants having their residential address geocoded: [18]. More details can be obtained from other publications [18,19,24]. This dataset will be used such as the baseline of the longitudinal study denominated of "ISA: Physical Activity and Environment" that will have such as objective to verify the relationship between the built environment and physical activity in adults from Sao Paulo city, Brazil.…”

Section: Sao Paulo Health Survey (Isa)mentioning

confidence: 99%

“…Walkable destinations within each participant's residential catchment were captured using georeferencing procedures [18,19] applied to publicly available datasets, and included: transportation (bus stops, train and subway stations), green areas (parks, squares), public recreation centres, bike paths, and primary health care units. The dataset for these items pertain to places in 2016 and were obtained mainly from the open site GEOSAMPA <http://geosampa.prefeitura.sp.gov.br/PaginasPublicas/_SBC.aspx>.…”

Section: Of Destinationsmentioning

confidence: 99%

“…In addition, we captured supermarkets, food stores, bakeries and coffee shops using the Health Surveillance Registration database from Sao Paulo city associated with National Economic Activity Classification in November 2016. We calculated the number of these destinations within a 500m radial buffer of each participant's home address: we used this distance because previous studies conducted in Sau Paulo city with the same sample found significant associations between the built environment and walking [18,19].…”

Section: Of Destinationsmentioning

confidence: 99%

“…First, we calculated the median number of destinations for the sample [median=3 and range 0 to 8] and grouped participants into two categories using a median-split (1=above median, 0=at or below median). Second, the distribution of destinations was divided into tertiles (high, medium, low): a similar measure using data from the Sao Paulo Health Survey found that participants who lived in areas with a greater mix of destinations were significantly more likely to walk for transport [19].…”

Section: Of Destinationsmentioning

confidence: 99%

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Mix Of Destinations And Sedentary Behavior Among Brazilian Adults

Florindo

Turrel

Garcia

et al. 2020

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Background: Sedentary behavior is influenced by contextual, social and individual factors, including the built environment. However, the associations between the built environment and sitting time have not been extensively investigated in countries with economies in transition such as Brazil. The objective of this study is to examine the relationship between sitting-time and access to a mix of destinations for adults from Sao Paulo city, Brazil.Methods: This study uses data from the Sao Paulo Health Survey (n=3,145). Sedentary behavior was assessed by questionnaire using two questions: total sitting time in minutes on a usual weekday; and on a usual weekend day. Mix of destinations was measured by summing the number of facilities (comprising bus stops, train/subway stations, parks, squares, public recreation centres, bike paths, primary health care units, supermarkets, food stores, bakeries, and coffee-shops) within 500m of each participant's residence. Linear and categorical (<4, ≥4 hours/day) measures of sitting time were derived and analyzed using linear and logistic multilevel regression. Models accounted for clustering within census-tracts and households, were stratified by gender, and adjusted for environmental, sociodemographic, and health-related factors.Results: Average minutes of sitting, and the likelihood of sitting for more than four hours, were significantly higher among males, younger people, the more educated, single persons, smokers, those who engaged in low levels of physical activity, the obese and those with chronic disease, and those who owned a private motor vehicle. Among females, mix of destinations was inversely related with minutes of sitting time on a weekday (β= -11 minutes; p=0.001) and weekend day (β= -8 minutes;p=0.012). Females who had a higher mix of destinations within their residential catchment had a significantly lower likelihood of sitting for four hours or more on weekdays (OR=0.66 IC95%0.47-0.94). No significant associations were found for males.Conclusion: This is the first-known study to examine the relationship between mix of destinations and sedentary behavior among adults in Sao Paulo City, Brazil. Our results suggest that health promotion and policy should focus on reducing sedentary behavior in the whole population, and especially those groups who engage in higher-levels of sitting time. 4

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Section: Resultsmentioning

confidence: 83%