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Human environments influence human health in both positive and negative ways. Green space is considered an environmental exposure that confers benefits to human health and has attracted a high level of interest from researchers, policy makers, and increasingly clinicians. Green space has been associated with a range of health benefits, such as improvements in physical, mental, and social wellbeing. There are different sources, metrics and indicators of green space used in research, all of which measure different aspects of the environment. It is important that readers of green space research understand the terminology used in this field, and what the green space indicators used in the studies represent in the real world. This paper provides an overview of the major definitions of green space and the indicators used to assess exposure for health practitioners, public health researchers, and health policy experts who may be interested in understanding this field more clearly, either in the provision of public health-promoting services or to undertake research. [ABSTRACT FROM AUTHOR]

Aim: To examine associations of neighborhood greenery, air pollution and walkability with cardiometabolic disease in adults aged ≥45 years in the Frankston–Mornington Peninsula region, Victoria, Australia. Methods: A cross‐sectional, ecological study design was used. We assessed mean annual neighborhood greenery using the Normalized Difference Vegetation Index; air pollution (fine particulate matter of diameter ≤2.5 μm [PM2.5] and NO2) using land‐use regression models; and walkability using Walk Score (possible values 0–100). Medically diagnosed diabetes (~95% type‐2), heart disease and stroke were self‐reported in the Australian Census (2021). Multivariable regression was used to model associations between environmental exposures and area‐level (neighborhood) cardiometabolic disease prevalence (age group ≥45 years), with socioeconomic status, age and sex as covariates. Air pollution was examined as a mediator of associations between greenery and disease prevalence. Results: Our sample comprised 699 neighborhoods with the following mean (SD) values: Normalized Difference Vegetation Index 0.47 (0.09), PM2.5, 8.5 (0.6) μg/m3 and NO2, 5.2 (1.6) ppb. Disease prevalences were: heart disease, mean 8.9% (4.5%); diabetes, mean 10.3% (4.7%); and stroke, median 1.2% (range 0–10.9%). Greenery was negatively associated with diabetes (β = −5.85, 95% CI −9.53, −2.17) and stroke prevalence (β = −1.26, 95% CI −2.11, −0.42). PM2.5 and NO2 were positively associated with diabetes (β = 1.59, 95% CI 1.00, 2.18; β = 0.42, 95% CI 0.22, 0.62) and stroke prevalence (β = 0.15, 95% CI 0.01, 0.29; β = 0.06, 95% CI 0.01, 0.10). The association between greenery and diabetes was partially mediated by PM2.5 (mediated effect −5.38, 95% CI −7.84, −3.03). Conclusions: Greenery and air pollutants were associated with lower and higher prevalence, respectively, of self‐reported diabetes and, to a lesser extent, stroke. These ecological findings require further exploration with stronger, longitudinal study designs to inform public health policy and directions. Geriatr Gerontol Int 2024; 24: 208–214. [ABSTRACT FROM AUTHOR]