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BMJ Open ; 7(10): e016128, 2017 Oct 22.
Article in English | MEDLINE | ID: mdl-29061606

ABSTRACT

OBJECTIVES: We estimated associations between objectively determined neighbourhood 'walkability' attributes and accelerometer-derived sedentary time (ST) by sex, city or type of day. DESIGN: A cross-sectional study. SETTING: The URBAN (Understanding the Relationship between Activity and Neighbourhoods) study was conducted in 48 neighbourhoods across four cities in New Zealand (August 2008 to October 2010). PARTICIPANTS: The response rate was 41% (2029 recruited participants/5007 eligible households approached). In total, 1762 participants (aged 41.4±12.1, mean±SD) met the data inclusion criteria and were included in analyses. PRIMARY AND SECONDARY OUTCOME MEASURES: The exposure variables were geographical information system (GIS) measures of neighbourhood walkability (ie, street connectivity, residential density, land-use mix, retail footprint area ratio) for street network buffers of 500 m and 1000 m around residential addresses. Participants wore an accelerometer for 7 days. The outcome measure was average daily minutes of ST. RESULTS: Data were available from 1762 participants (aged 41.4±12.1 years; 58% women). No significant main effects of GIS-based neighbourhood walkability measures were found with ST. Retail footprint area ratio was negatively associated with sedentary time in women, significant only for 500 m residential buffers. An increase of 1 decile in street connectivity was significantly associated with a decrease of over 5 min of ST per day in Christchurch residents for both residential buffers. CONCLUSION: Neighbourhoods with proximal retail and higher street connectivity seem to be associated with less ST. These effects were sex and city specific.


Subject(s)
Cities , Environment Design , Residence Characteristics , Sedentary Behavior , Walking , Accelerometry/instrumentation , Adult , Cross-Sectional Studies , Female , Geographic Information Systems , Humans , Male , Middle Aged , New Zealand , Regression Analysis , Time Factors
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