Associations between green/blue spaces and mental health across 18 countries

Abstract

Living near, recreating in, and feeling psychologically connected to, the natural world are all associated with better mental health, but many exposure-related questions remain. Using data from an 18-country survey (n = 16,307) we explored associations between multiple measures of mental health (positive well-being, mental distress, depression/anxiety medication use) and: (a) exposures (residential/recreational visits) to different natural settings (green/inland-blue/coastal-blue spaces); and (b) nature connectedness, across season and country. People who lived in greener/coastal neighbourhoods reported higher positive well-being, but this association largely disappeared when recreational visits were controlled for. Frequency of recreational visits to green, inland-blue, and coastal-blue spaces in the last 4 weeks were all positively associated with positive well-being and negatively associated with mental distress. Associations with green space visits were relatively consistent across seasons and countries but associations with blue space visits showed greater heterogeneity. Nature connectedness was also positively associated with positive well-being and negatively associated with mental distress and was, along with green space visits, associated with a lower likelihood of using medication for depression. By contrast inland-blue space visits were associated with a greater likelihood of using anxiety medication. Results highlight the benefits of multi-exposure, multi-response, multi-country studies in exploring complexity in nature-health associations.

Figure 1

Relationships between: (1) Green space visits in last 4 weeks, (2) Inland-blue space visits in last 4 weeks, (3) Coastal-blue space visits in last 4 weeks, and (4) nature connectedness (1–7); and positive well-being (0–100; a,e,l,m), risk of mental distress (0–1; b,f,j,n), use of depression medication (0–1; c,g,k,o), and use of anxiety medication (0–1; d,h,l,p), averaged across 18 countries (n = 16,302). Plots are based on predicted values from linear and logistic mixed effects regression models including linear and quadratic terms (with 95% Confidence Intervals) for visit frequency and connectedness controlling for residential exposure, visit frequencies to alternative locations, connectedness (a–l only), age, gender, employment status, relationship status, household income, longstanding-illness, education level, household composition, dog ownership, car ownership, physical activity, season (sample wave), and country (as a random effect). Depression models also control for anxiety medication use and vice versa. Visit frequency was capped at n = 56 (i.e. two visits per day over 4 weeks). Covariates are held constant at their reference categories, or at their means for continuous predictors.

Figure 2

Average number of visits to green spaces, inland-blue spaces and coastal-blue spaces as a function of season across the whole sample (n = 16,302). Error bars represent 95% confidence intervals.

Figure 3

Country level relationships between positive well-being (0–100) and: (a) Green space visits in last 4 weeks; (b) Inland-blue space visits in last 4 weeks; (c) Coastal-blue space visits in last 4 weeks and (d) nature connectedness (1–7). Plots are based on aggregated predicted values across countries from our original mixed models controlling for residential exposure visit frequencies to alternative locations, connectedness (a–c), age, gender, employment status, household income, longstanding-illness, relationship status, education level, household composition, dog ownership, car ownership, physical activity, and season (sample wave).