Sao Paulo Health Survey (ISA)
This study used data from the Sao Paulo Health Survey. Data collection was completed in 2015, with 4,043 participants who lived in five health administrative areas in Sao Paulo city. The sampling process has been described in more detail elsewhere [15]. Briefly, the survey used a multi-stage sampling design: from the five health administration areas in Sao Paulo, 150 census tracts were randomly selected, and then households were sampled randomly from each tract. The data were collected using face-to-face interviews in households. The interviews were conducted between September 2014 and December 2015, and 73.4% of eligible residents who were contacted agreed to participate [15].
Georeferencing resulted in 3,145 participants aged 18 years or more having their residential address geocoded [16]. More details can be obtained from other publications [16-18]. The Sao Paulo Health Survey forms the baseline dataset for a recently funded longitudinal study of the physical activity and built environment among adults in Sao Paulo city, Brazil. A key focus of this prospective research will be to verify the robustness of the cross-sectional studies that have been conducted using the Sao Paulo Health Survey baseline.
Sedentary Behavior
Sedentary behavior data were collected using the International Physical Activity Questionnaire (IPAQ) [19] and measured on the basis of two questions: 1) Total sitting time on a usual weekday; 2) Total sitting time on a usual weekend day. For analysis, two outcomes were used: 1) Continuous measures of minutes of sitting time in a typical weekday; and 2) Continuous measures of minutes of sitting time in a typical weekend day.
Mix of Destinations
Walkable destinations within each participant’s residential catchment were captured using georeferencing procedures [16-18] applied to publicly available datasets, and included eleven destinations: 1. Bus stops; 2. Train/subway stations; 3. Parks; 4. Squares; 5. Public recreation centres; 6. Bike paths; 7. Primary health care units; .8 Supermarkets; 9. Food stores; 10. Bakeries; and 11. Coffee shops. The dataset for items 1 to 8 pertain to places in 2016 and were obtained mainly from the open site GEOSAMPA <http://geosampa.prefeitura.sp.gov.br/PaginasPublicas/_SBC.aspx>, and items 9 to 11 were sourced from the Health Surveillance Registration database from Sao Paulo city associated with the National Economic Activity Classification in November 2016.
We calculated a measure of destination diversity in three phases: 1) by firstly summing the number of each destination within a 500m radial buffer of each participant’s home address; 2) by secondly, we categorized the participants into two groups based on the sum for each destination. The participants that were at or below the sample median had scored 0, and participants were above the median had scored 1; 3) and thirdly, by the sum of all destination obtained in the second phase we created the mix destination score that ranged from 0 – 8 (mean=3.07, SD=1.70, median=3 interquartile range: 4; 2). This process has been described in more detail elsewhere in a study also used the Sao Paulo Health Survey which showed that the mix of destination score within a 500m buffer was significantly associated with walking for transport [18].
Covariates
We used age (18-29 years, 30-39 years, 40-49 years, 50-59 years, 60 years or more), education (incomplete elementary school, incomplete high school, complete high school, incomplete undergraduate or above), marital status (singles, married/with partners, separated/widowers), obesity (in two categories: BMI <30 kg/m2 or above), physical activity (<150 minutes per week or above evaluated by IPAQ long form), self-report of diseases diagnosed by physicians (none or at least one of the following: hypertension; diabetes; myocardial infarction; cardiac arrhythmia; other heart disease; cancer; arthritis, rheumatism or arthrosis; osteoporosis; asthma or asthmatic bronchitis; emphysema, chronic bronchitis or chronical obstructive pulmonary diseases; rhinitis; chronic sinusitis; other lung disease; tendonitis, repetitive strain injury or work-related musculoskeletal disorders; cerebral vascular accident or stroke; spine disease or spine problem), smoking status (yes or no), car or motorcycle ownership (yes or no); time living in the same residence ( <1 year, ≥1 year or <5 years, >5 years), and region where people lived in Sao Paulo city (North, South, Midwest, Southeast, and East). These covariates were selected based on the findings of systematic reviews about sedentary behavior correlates in adults [8, 12, 14] and in original study that examined the relationship between walking for transportation and physical activity [18].
Statistical Analysis
For this study we excluded from the analyses people who reported zero minutes of sitting time, those who did not answer the sitting time question in the survey, and those with missing data on the covariates. These exclusions resulted in a final analytic sample of n=3,052 participants for sitting time on a typical weekday, and n=2,993 participants for sitting time on a typical weekend day. The analyses are conducted in two stages. First, we present mean sitting times for each of the sociodemographic, health, and environmental covariates (Table 1), and for participants who were grouped into the two destination-mix categories based on the median split (Table 2). Second, we examine the multivariable association between the destination mix index and sitting time using multilevel linear regression without and with adjustment for the covariates (Table 3). The multilevel analysis accounted for clustering within census-tracts and households. All analyses were conducted using Stata version SE 12.1. (StataCorp LP, College Station, USA). We used the xtmixed command for linear models and the results are presented as beta coefficients (β) with 95% confidence intervals.
Ethics Approval
The Ethics Committee of the School of Arts, Sciences, and Humanities at the University of Sao Paulo approved the study (process number 55846116.6.0000.5390).