Evidence is mounting to suggest a causal relationship between the built environment and people’s physical activity behaviours, particularly active transport. The evidence base has been hindered to date by restricted consideration of cost and economic factors associated with built environment interventions, investigation of socioeconomic or ethnic differences in intervention effects, and an inability to isolate the effect of the built environment from other intervention types. The aims of this systematic review were to identify which environmental interventions increase physical activity in residents at the local level, and to build on the evidence base by considering intervention cost, and the differential effects of interventions by ethnicity and socioeconomic status. A systematic database search was conducted in June 2015. Articles were eligible if they reported a quantitative empirical study (natural experiment or a prospective, retrospective, experimental, or longitudinal research) investigating the relationship between objectively measured built environment feature(s) and physical activity and/or travel behaviours in children or adults. Quality assessment was conducted and data on intervention cost and whether the effect of the built environment differed by ethnicity or socioeconomic status were extracted. Twenty-eight studies were included in the review. Findings showed a positive effect of walkability components, provision of quality parks and playgrounds, and installation of or improvements in active transport infrastructure on active transport, physical activity, and visits or use of settings. There was some indication that infrastructure improvements may predominantly benefit socioeconomically advantaged groups. Studies were commonly limited by selection bias and insufficient controlling for confounders. Heterogeneity in study design and reporting limited comparability across studies or any clear conclusions to be made regarding intervention cost. Improving neighbourhood walkability, quality of parks and playgrounds, and providing adequate active transport infrastructure is likely to generate positive impacts on activity in children and adults. The possibility that the benefits of infrastructure improvements may be inequitably distributed requires further investigation. Opportunities to improve the quality of evidence exist, including strategies to improve response rates and representativeness, use of valid and reliable measurement tools, cost-benefit analyses, and adequate controlling for confounders.

Objective To determine whether insulating existing houses increases indoor temperatures and improves occupants' health and wellbeing.Design Community based, cluster, single blinded randomised study.Setting Seven low income communities in New Zealand.Participants 1350 households containing 4407 participants.Intervention Installation of a standard retrofit insulation package.Main outcome measures Indoor temperature and relative humidity, energy consumption, self reported health, wheezing, days off school and work, visits to general practitioners, and admissions to hospital.Results Insulation was associated with a small increase in bedroom temperatures during the winter (0.5°C) and decreased relative humidity (−2.3%), despite energy consumption in insulated houses being 81% of that in uninsulated houses. Bedroom temperatures were below 10°C for 1.7 fewer hours each day in insulated homes than in uninsulated ones. These changes were associated with reduced odds in the insulated homes of fair or poor self rated health (adjusted odds ratio 0.50, 95% confidence interval 0.38 to 0.68), self reports of wheezing in the past three months (0.57, 0.47 to 0.70), self reports of children taking a day off school (0.49, 0.31 to 0.80), and self reports of adults taking a day off work (0.62, 0.46 to 0.83). Visits to general practitioners were less often reported by occupants of insulated homes (0.73, 0.62 to 0.87). Hospital admissions for respiratory conditions were also reduced (0.53, 0.22 to 1.29), but this reduction was not statistically significant (P=0.16).Conclusion Insulating existing houses led to a significantly warmer, drier indoor environment and resulted in improved self rated health, self reported wheezing, days off school and work, and visits to general practitioners as well as a trend for fewer hospital admissions for respiratory conditions.

Multi-level research that attempts to describe ecological effects in themselves (for example, the effect on individual health from living in deprived communities), while also including individual level effects (for example, the effect of personal socioeconomic disadvantage), is now prominent in research on the socioeconomic determinants of health and disease. Such research often involves the application of advanced statistical multi-level methods. It is hypothesised that such research is at risk of reaching beyond an epidemiological understanding of what constitutes an ecological effect, and what sources of error may be influencing any observed ecological effect. This paper aims to present such an epidemiological understanding. Three basic types of ecological effect are described: a direct cross level effect (for example, living in a deprived community directly affects individual personal health), cross level effect modification (for example, living in a deprived community modifies the effect of individual socioeconomic status on individual health), and an indirect cross level effect (for example, living in a deprived community increases the risk of smoking, which in turn affects individual health). Sources of error and weaknesses in study design that may affect estimates of ecological effects include: a lack of variation in the ecological exposure (and health outcome) in the available data; not allowing for intraclass correlation; selection bias; confounding at both the ecological and individual level; misclassification of variables; misclassification of units of analysis and assignment of individuals to those units; model mis-specification; and multicollinearity. Identification of ecological effects requires the minimisation of these sources of error, and a study design that captures sufficient variation in the ecological exposure of interest.