Associations of street-view greenspace with Parkinson's disease hospitalizations in an open cohort of elderly US Medicare beneficiaries.

INTRODUCTION: Protective associations of greenspace with Parkinson's disease (PD) have been observed in some studies. Visual exposure to greenspace seems to be important for some of the proposed pathways underlying these associations. However, most studies use overhead-view measures (e.g., satellite imagery, land-classification data) that do not capture street-view greenspace and cannot distinguish between specific greenspace types. We aimed to evaluate associations of street-view greenspace measures with hospitalizations with a PD diagnosis code (PD-involved hospitalization). METHODS: We created an open cohort of about 45.6 million Medicare fee-for-service beneficiaries aged 65 + years living in core based statistical areas (i.e. non-rural areas) in the contiguous US (2007-2016). We obtained 350 million Google Street View images across the US and applied deep learning algorithms to identify percentages of specific greenspace features in each image, including trees, grass, and other green features (i.e., plants, flowers, fields). We assessed yearly average street-view greenspace features for each ZIP code. A Cox-equivalent re-parameterized Poisson model adjusted for potential confounders (i.e. age, race/ethnicity, socioeconomic status) was used to evaluate associations with first PD-involved hospitalization. RESULTS: There were 506,899 first PD-involved hospitalizations over 254,917,192 person-years of follow-up. We found a hazard ratio (95% confidence interval) of 0.96 (0.95, 0.96) per interquartile range (IQR) increase for trees and a HR of 0.97 (0.96, 0.97) per IQR increase for other green features. In contrast, we found a HR of 1.06 (1.04, 1.07) per IQR increase for grass. Associations of trees were generally stronger for low-income (i.e. Medicaid eligible) individuals, Black individuals, and in areas with a lower median household income and a higher population density. CONCLUSION: Increasing exposure to trees and other green features may reduce PD-involved hospitalizations, while increasing exposure to grass may increase hospitalizations. The protective associations may be stronger for marginalized individuals and individuals living in densely populated areas.

Green Space and Internalizing or Externalizing Symptoms Among Children.

Importance: Evidence suggests that living near green space supports mental health, but studies examining the association of green space with early mental health symptoms among children are rare. Objective: To evaluate the association between residential green space and early internalizing (eg, anxiety and depression) and externalizing (eg, aggression and rule-breaking) symptoms. Design, Setting, and Participants: Data for this cohort study were drawn from the Environmental Influences on Child Health Outcomes cohort; analysis was conducted from July to October 2023. Children born between 2007 and 2013 with outcome data in early (aged 2-5 years) and/or middle (aged 6-11 years) childhood who resided in 41 states across the US, drawing from clinic, hospital, and community-based cohorts, were included. Cohort sites were eligible if they recruited general population participants and if at least 30 children had outcome and residential address data to measure green space exposure. Nine cohorts with 13 sites met these criteria. Children diagnosed with autism or developmental delay were excluded, and 1 child per family was included. Exposures: Green space exposure was measured using a biannual (ie, summer and winter) Normalized Difference Vegetation Index, a satellite image-based indicator of vegetation density assigned to monthly residential history from birth to outcome assessment. Main Outcome and Measures: Child internalizing and externalizing symptoms were assessed using the Child Behavior Checklist for Ages 1½ to 5 or 6 to 18. The association between green space and internalizing and externalizing symptoms was modeled with multivariable linear regression using generalized estimating equations, adjusting for birthing parent educational level, age at delivery, child sex, prematurity, and neighborhood socioeconomic vulnerability. Models were estimated separately for early and middle childhood samples. Results: Among 2103 children included, 1061 (50.5%) were male; 606 (29.1%) identified as Black, 1094 (52.5%) as White, 248 (11.9%) as multiple races, and 137 (6.6%) as other races. Outcomes were assessed at mean (SD) ages of 4.2 (0.6) years in 1469 children aged 2 to 5 years and 7.8 (1.6) years in 1173 children aged 6 to 11 years. Greater green space exposure was associated with fewer early childhood internalizing symptoms in fully adjusted models (b = -1.29; 95% CI, -1.62 to -0.97). No associations were observed between residential green space and internalizing or externalizing symptoms in middle childhood. Conclusions and Relevance: In this study of residential green space and children's mental health, the association of green space with fewer internalizing symptoms was observed only in early childhood, suggesting a sensitive period for nature exposure. Policies protecting and promoting access to green space may help alleviate early mental health risk.

Diversity of Studies on Neighborhood Greenspace and Brain Health by Racialized/Ethnic Group and Geographic Region: A Rapid Review.

Studies examining associations between greenspace and Alzheimer's disease and related dementia (ADRD) outcomes are rapidly on the rise, yet no known literature reviews have summarized the racialized/ethnic group and geographic variation of those published studies. This is a significant gap given the known disparities in both greenspace access and ADRD risk between racialized/ethnic groups and between developed versus developing countries. In this rapid literature review, we (1) describe the diversity of published greenspace-brain health studies with respect to racialized/ethnic groups and geographic regions; (2) determine the extent to which published studies have investigated racialized/ethnic group differences in associations; and (3) review methodological issues surrounding studies of racialized/ethnic group disparities in greenspace and brain health associations. Of the 57 papers meeting our inclusion criteria as of 4 March 2022, 21% (n = 12) explicitly identified and included individuals who were Black, Hispanic/Latinx, and/or Asian. Twenty-one percent of studies (n = 12) were conducted in developing countries (e.g., China, Dominican Republic, Mexico), and 7% (n = 4) examined racialized/ethnic group differences in greenspace-brain health associations. None of the studies were framed by health disparities, social/structural determinants of health, or related frameworks, despite the known differences in both greenspace availability/quality and dementia risk by racialized/ethnic group and geography. Studies are needed in developing countries and that directly investigate racialized/ethnic group disparities in greenspace-brain health associations to target and promote health equity.

Development of a global urban greenness indicator dataset for 1,000+ cities.

Global climate change has sparked efforts to adapt to increasing temperatures, especially in urban areas that experience increased day and nighttime temperatures due to the urban heat island effect. The addition of greenspace has been suggested as a possible means for urban centers to respond to increasing urban temperatures. Thus, it is important for urban planning and policymakers to have access to data on greenspace specific at a fine spatial resolution. This dataset consists of information on peak and annual average 1 × 1 km Normalized Difference Vegetation Index (NDVI) for over 1,000 global urban centers, which is an objective satellite-based measure of vegetation. Population-weighted values for both peak and annual average NDVI and include an indicator of greenness, with seven levels ranging from extremely low to extremely high are provided. Additional information regarding the climate zone (using the Köppen-Geiger climate classification) and level of development (using the Human Development Index or HDI) for each city is included. Analyses were repeated in 2010, 2015, and 2020 to provide the ability to track urban greenness over time. Data are provided in tabular format with summaries presented in both tables and graphics. These data can be used to inform policy and planning and can be used as an indicator for a variety of climate and health investigations.

Determinants of self-rated health and the role of acculturation: implications for health inequalities.

OBJECTIVES: Self-rated health (SRH) is an important indicator of overall health, predicting morbidity and mortality. This paper investigates what individuals incorporate into their self-assessments of health and how acculturation plays a part in this assessment. The relationship of acculturation to SRH and whether it moderates the association between indicators of health and SRH is also examined. DESIGN: The paper is based on data from adults in the Boston Puerto Rican Health Study, living in the greater Boston area (n=1357) mean age 57.2 (SD = 7.6). We used multiple regression analysis and testing for moderation effects. RESULTS: The strongest predictors of poor SRH were the number of existing medical conditions, functional problems, allostatic load and depressive symptoms. Poor SRH was also associated with being female, fewer years of education, heavy alcohol use, smoking, poverty, and low emotional support. More acculturated Puerto Rican adults rated their health more positively, which corresponded to better indicators of physical and psychological health. Additionally, acculturation moderated the association between some indicators of morbidity (functional status and depressive symptoms) and SRH.Self-assessments of overall health integrate diverse indicators, including psychological symptoms, functional status and objective health indicators such as chronic conditions and allostatic load. However, adults' assessments of overall health differed by acculturation, which moderated the association between health indicators and SRH. The data suggest that when in poor health, those less acculturated may understate the severity of their health problems when rating their overall health, thus SRH might thus conceal disparities. Using SRH can have implications for assessing health disparities in this population.