Exploring the Potential Relationship Between Global Greenness and DALY Loss Due to Depressive Disorders

Association of Residential Greenness Exposure with Depression Incidence in Adults 50 Years of Age and Older: Findings from the Cohort Study on Global AGEing and Adult Health (SAGE) in China

BACKGROUND

Depression is a social and public health problem of great concern globally. Identifying and managing the factors influencing depression are crucial for preventing and decreasing the burden of depression.

OBJECTIVES

Our objectives are to explore the association between residential greenness and the incidence of depression in an older Chinese population and to calculate the disease burden of depression prevented by greenness exposure.

METHODS

This study was the Chinese part of the World Health Organization Study on Global AGEing and Adult Health (WHO SAGE). We collected the data of 8,481 residents ≥ 50 years of age in China for the period 2007-2018. Average follow-up duration was 7.00 (± 2.51 ) years. Each participant was matched to the yearly maximum normalized difference vegetation index (NDVI) at their residential address. Incidence of depression was assessed using the Composite International Diagnostic Interview (CIDI), self-reports of depression, and/or taking depression medication. Association between greenness and depression was examined using the time-dependent Cox regression model with stratified analysis by sex, age, urbanicity, annual family income, region, smoking, drinking, and household cooking fuels. Furthermore, the prevented fraction (PF) and attributable number (AN) of depression prevented by exposure to greenness were estimated.

RESULTS

Residential greenness was negatively associated with depression. Each interquartile range (IQR) increase in NDVI 500 -m buffer was associated with a 40% decrease [hazard ratio  ( HR ) = 0.60 ; 95% confidence interval (CI): 0.37, 0.97] in the risk of depression incidence among the total participants. Subgroup analyses showed negative associations in urban residents (HR = 0.32 ; 95% CI: 0.12, 0.86) vs. rural residents, in high-income residents (HR = 0.28 ; 95% CI: 0.11, 0.71) vs. low-income residents, and in southern China (HR = 0.50 ; 95% CI: 0.26, 0.95) vs. northern China. Over 8.0% (PF = 8.69 % ; 95% CI: 1.38%, 15.40%) and 1,955,199 (95% CI: 310,492; 3,464,909) new cases of depression may be avoided by increasing greenness exposures annually across China.

DISCUSSION

The findings suggest protective effects of residential greenness exposure on depression incidence in the older population, particularly among urban residents, high-income residents, and participants living in southern China. The construction of residential greenness should be included in community planning. https://doi.org/10.1289/EHP13947.

Association between residential greenness and depression symptoms in Chinese community-dwelling older adults

BACKGROUND

Studies of residential greenness and depression symptoms among community-dwelling older adults in China are limited. However, understanding the role of greenness in depression symptoms among older adults can inform depression prevention and interventions.

OBJECTIVE

This study explored the relationship between residential greenness and depression symptoms among community-dwelling older adults in China.

METHODS

A cluster random sampling method was used to survey 7512 community-dwelling adults aged 60 and above from three towns in Shanghai. Depression symptoms were assessed using the Geriatric Depression Scale (GDS30). Residential greenness was measured using the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI). Long-term greenspace exposure was defined as the mean NDVI and EVI in the three years prior to the baseline survey. Controlling for the covariates, the relationship between greenness and depression symptoms was assessed using binomial logistic regression and mixed-effects linear regression. Interaction analysis was conducted to explore which covariates potentially alter the association. We also assessed the mediating role of physical activity.

RESULTS

The prevalence of depression symptoms among the participants was 13.72%. Higher residential greenness was associated with lower odds of depression symptoms, after adjusting for covariates. In the logistic regression analysis, the odds of depression symptoms decreased with increasing NDVI and EVI. In linear regression analysis, GDS30 scores decreased with increasing NDVI and EVI. Interaction analyses revealed that higher NDVI and EVI were more protective against depression among male individuals and older adults living with others than among female individuals and older adults living alone. Additionally, physical activity had a masking effect on residential greenness and depression symptoms.

CONCLUSION

Higher residential greenness is associated with lower odds of depression symptoms in community-dwelling Chinese older adults. Increasing urban and neighborhood green spaces may contribute to the prevention and intervention of depression symptoms in community-dwelling older adults.

"Urban-Satellite" estimates in the ABCD Study: Linking Neuroimaging and Mental Health to Satellite Imagery Measurements of Macro Environmental Factors

While numerous studies over the last decade have highlighted the important influence of environmental factors on mental health, globally applicable data on physical surroundings are still limited. Access to such data and the possibility to link them to epidemiological studies is critical to unlocking the relationship of environment, brain and behaviour and promoting positive future mental health outcomes. The Adolescent Brain Cognitive Development (ABCD) Study is the largest ongoing longitudinal and observational study exploring brain development and child health among children from 21 sites across the United States. Here we describe the linking of the ABCD study data with satellite-based "Urban-Satellite" (UrbanSat) variables consisting of 11 satellite-data derived environmental indicators associated with each subject's residential address at their baseline visit, including land cover and land use, nighttime lights, and population characteristics. We present these UrbanSat variables and provide a review of the current literature that links environmental indicators with mental health, as well as key aspects that must be considered when using satellite data for mental health research. We also highlight and discuss significant links of the satellite data variables to the default mode network clustering coefficient and cognition. This comprehensive dataset provides the foundation for large-scale environmental epidemiology research.

Association of greenness with the disease burden of lower respiratory infections and mediation effects of air pollution and heat: a global ecological study

Exposure to greenness is increasingly linked to beneficial health outcomes, but the associations between greenness and the disease burden of lower respiratory infections (LRIs) are unclear. We used the normalized difference vegetation index (NDVI) and the leaf area index (LAI) to measure greenness and incidence, death, and disability-adjusted life years (DALYs) due to LRIs to represent the disease burden of LRIs. We applied a generalized linear mixed model to evaluate the association between greenness and LRI disease burden and performed a stratified analysis, after adjusting for covariates. Additionally, we assessed the potential mediating effects of fine particulate matter (PM2.5), ozone (O3), nitrogen dioxide (NO2), and heat on the association between greenness and the disease burden of LRIs. In the adjusted model, one 0.1 unit increase of NDVI and 0.5 increase in LAI were significantly inversely associated with incidence, death, and DALYs due to LRIs, respectively. Greenness was negatively correlated with the disease burden of LRIs across 15-65 age group, both sexes, and low SDI groups. PM2.5, O3, and heat mediated the effects of greenness on the disease burden of LRIs. Greenness was significantly negatively associated with the disease burden of LRIs, possibly by reducing exposure to air pollution and heat.