Increased urbanisation and the associated reduced contact of individuals with natural environments have led to a rise in mental disorders, including depression. Residential greenness, a fundamental component of urban design, has been shown to reduce the public health burden of mental disorders. The present study investigates the association between residential green exposure and prevalence of major depressive disorders using a large and diverse cross-sectional dataset from the UK Biobank. In this cross-sectional, observational, associational study, we used baseline data from the UK Biobank cohort of participants aged 37-73 years from across the UK. Environmental exposure data were derived from a modelled and linked built environment database. Residential greenness was assessed with a 0·5 m resolution Normalised Difference Vegetation Index, which is derived from spectral reflectance measurements in remotely sensed colour infrared data and measured within geocoded dwelling catchments. Other environment metrics included street-level movement density, terrain, and fine particulate exposures. A series of logistic models examined associations between residential greenness and odds of major depressive disorder after adjusting for activity-influencing environments and individual covariates. Of 122 993 participants with data on major depressive disorder, the study analytical sample comprised 94 879 (77·1%) participants recruited across ten UK Biobank assessment centres between April 29, 2009, and Oct 1, 2010. A protective effect of greenness on depression was consistently observed, with 4·0% lower odds of major depressive disorder per interquartile increment in Normalised Difference Vegetation Index greenness (odds ratio 0·960, 95% CI 0·93-0·99; p=0·0044). Interaction analyses indicated that the beneficial effects of greenness were more pronounced among women, participants younger than 60 years, and participants residing in areas with low neighbourhood socioeconomic status or high urbanicity. The results point to the benefits of well designed green environments on mental health. Further longitudinal studies are needed to decipher causal pathways. In the UK, policies aimed at optimising allocation and design of green spaces might help preserve psychological ecosystem services, thereby, improving the mental wellbeing of populations and enhancing the mental capital of cities. University of Hong Kong, UK Biobank, and the UK Economic & Social Research Council.

With the rapid urbanization and prevailing obesity pandemic, the role of residential green exposures in obesity prevention has gained renewed focus. The study investigated the effects of residential green exposures on adiposity using a large and diverse population sample drawn from the UK Biobank. This was a population based cross-sectional study of 333,183 participants aged 38-73years with individual-level data on residential greenness and built environment exposures. Residential greenness was assessed through 0.50-metre resolution normalized difference vegetation index (NDVI) derived from spectral reflectance measurements in remotely sensed colour infrared data and measured around geocoded participants' dwelling. A series of continuous and binary outcome models examined the associations between residential greenness and markers of adiposity, expressed as body-mass index (BMI) in kg/m2, waist circumference (WC) in cm, whole body fat (WBF) in kg and obesity (BMI≥30kg/m2) after adjusting for other activity-influencing built environment and individual-level confounders. Sensitivity analyses involved studying effect modification by gender, age, urbanicity and SES as well as examining relationships between residential greenness and active travel behaviour. Residential greenness was independently and consistently associated with lower adiposity, the association being robust to adjustments. An interquartile increment in NDVI greenness was associated with lower BMI (βBMI=-0.123kg/m2, 95% CI: -0.14, -0.10kg/m2), WC (βWC=-0.551cm, 95% CI: -0.61, -0.50cm), and WBF (βWBF=-0.138kg, 95% CI: -0.18, -0.10kg) as well as a reduced relative risk of obesity (RR=0.968, 95% CI: 0.96, 0.98). Residential greenness was beneficially related with active travel, being associated with higher odds of using active mode for non-work travel (OR=1.093, 95% CI: 1.08, 1.11) as well as doing >30min walking (OR=1.039, 95% CI: 1.03, 1.05). Residing in greener areas was associated with healthy weight outcomes possibly through a physical activity-related mechanism. Green allocation and design may act as upstream-level public health interventions ameliorating the negative health externalities of obesogenic urban environments. Further prospective studies are needed to identify potential causal pathways and thereby effectively guide such interventions.

Household income (as a marker of socioeconomic position) and neighbourhood fast-food outlet exposure may be related to diet and body weight, which are key risk factors for non-communicable diseases. However, the research evidence is equivocal. Moreover, understanding the double burden of these factors is a matter of public health importance. The purpose of this study was to test associations of neighbourhood fast-food outlet exposure and household income, in relation to frequency of consumption of processed meat and multiple measures of adiposity, and to examine possible interactions. We employed an observational, cross-sectional study design. In a cohort of 51,361 adults aged 38–72 years in Greater London, UK, we jointly classified participants based on household income (£/year, four groups) and GIS-derived neighbourhood fast-food outlet proportion (counts of fast-food outlets as a percentage of all food outlets, quartiles). Multivariable regression models estimated main effects and interactions (additive and multiplicative) of household income and fast-food outlet proportion on odds of self-reported frequent processed meat consumption (> 1/week), measured BMI (kg/m2), body fat (%), and odds of obesity (BMI ≥ 30). Income and fast-food proportion were independently, systematically associated with BMI, body fat, obesity and frequent processed meat consumption. Odds of obesity were greater for lowest income participants compared to highest (OR = 1.54, 95% CI: 1.41, 1.69) and for those most-exposed to fast-food outlets compared to least-exposed (OR = 1.51, 95% CI: 1.40, 1.64). In jointly classified models, lowest income and highest fast-food outlet proportion in combination were associated with greater odds of obesity (OR = 2.43, 95% CI: 2.09, 2.84), with relative excess risk due to interaction (RERI = 0.03). Results were similar for frequent processed meat consumption models. There was no evidence of interaction on a multiplicative scale between fast-food outlet proportion and household income on each of BMI (P = 0.230), obesity (P = 0.054) and frequent processed meat consumption (P = 0.725). Our study demonstrated independent associations of neighbourhood fast-food outlet exposure and household income, in relation to diet and multiple objective measures of adiposity, in a large sample of UK adults. Moreover, we provide evidence of the double burden of low income and an unhealthy neighbourhood food environment, furthering our understanding of how these factors contribute jointly to social inequalities in health.