Summary Built environment attributes may be related to cardio‐metabolic diseases (e.g. type 2 diabetes, heart disease and stroke) and their risk factors, potentially by influencing residents' physical activity. However, existing literature reviews on the built environment and health for the most part focus on obesity as the outcome and rely on cross‐sectional studies. This systematic review synthesized current evidence on longitudinal relationships between built environment attributes and cardio‐metabolic health outcomes among adults and on the potential mediating role of physical inactivity. By searching eight databases for peer‐reviewed journal articles published in the English language between January 2000 and July 2016, the review identified 36 articles. A meta‐analysis method, weighted Z‐test, was used to quantify the strength of evidence by incorporating the methodological quality of the studies. We found strong evidence for longitudinal relationships of walkability with obesity, type 2 diabetes and hypertension outcomes in the expected direction. There was strong evidence for the impact of urban sprawl on obesity outcomes. The evidence on potential mediation by physical activity was inconclusive. Further longitudinal studies are warranted to examine which specific built environment attributes influence residents' cardio‐metabolic health outcomes and how physical inactivity may be involved in these relationships.

The relationships between socioeconomic characteristics and transport modes are complex, and provide challenges for those attempting to encourage active forms of transportation. Further work is required exploring the individual-level and neighbourhood-level mechanisms behind choice of transport mode, and what factors might influence individuals from different socioeconomic backgrounds to change to more active transport modes.

There will always be a trade-off between accuracy and available resources when choosing the best approach for measuring physical activity amongst youth. Unfortunately, cost and logistical challenges may prohibit the use of "gold standard" physical activity measurement approaches such as doubly labelled water. Other objective methods such as heart rate monitoring, accelerometry, pedometry, indirect calorimetry, or a combination of measures have the potential to better capture the duration and intensity of physical activity, while self-reported measures are useful for capturing the type and context of activity.

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IntroductionWalking as regular physical activity (PA) is central to healthy aging, and environments influence walking. Multilevel neighborhood-based studies that only report average (fixed-effect) walking differences for gender and age implicitly assume that neighborhood environments influence the walking behavior of men and women, and younger and older persons, similarly. This study tests this assumption by examining whether gender and age differences in walking for transport (WfT) and walking for recreation (WfR) are similar or different across neighborhoods.MethodsThis paper used data from the HABITAT multilevel study, with 7,866 participants aged 42–68 years in 2009 living in 200 neighborhoods in Brisbane, Australia. Respondents reported minutes spent WfT and WfR in the previous week, categorized as: none (0 mins), low (1–59mins), moderate (60–149mins) and high (≥ 150 mins). Multilevel multinomial logistic models were used to estimate average differences in walking by gender and age, followed by random coefficients to examine neighborhood variation in these individual-level relationships.ResultsOn average, women were more likely to engage in WfR at moderate and high levels (no gender differences found in WfT); and older persons were less likely to do WfT and more likely to do high levels of WfR. These average (Brisbane-wide) relationships varied significantly across neighborhoods.ConclusionRelationships between gender and walking, and age and walking, are not the same in all neighborhoods, (i.e. the Brisbane average conceals important information) suggesting that neighborhood-level factors differentially influence the walking behaviors of men and women and younger and older persons. Identifying these factors should be a priority for future research.