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Background: There is limited evidence on the associations between residential greenness and cancer incidence in longitudinal studies., Objectives: The aim of the study was to evaluate the associations between weighted mean residential greenness exposure and cancer incidence., Methods: This is a registry based retrospective cohort study of 977,644 participants. The residential greenness exposure was estimated for every participant, as the weighted mean residential greenness exposure. This was based on the mean Normalized Difference Vegetation Index (NDVI) in the residential small geographic area and the duration of the residence in this area. Cancer incidence cases included consecutive newly diagnosed cases of primary cancer. Analyses were conducted for all cancer sites, lung cancer, bladder cancer, breast cancer, prostate cancer and melanoma-skin cancer. Cox regression models were used to evaluate the crude and adjusted associations (hazards ratios (HR) and its 95 % confidence intervals (CIs)) between tertiles of residential greenness and cancer incidence. Further adjusted models to nitrogen oxides (NO x ) were estimated., Results: After adjustment to covariates, exposure to the highest tertile of residential greenness, compared to the lowest, were associated with lower risk for all cancer sites (HR = 0.88, 95 % CI: 0.86-0.90), breast cancer (HR = 0.85, 95 % CI: 0.80-0.89) and prostate cancer (HR = 0.85, 95 % CI: 0.79-0.91). In addition, lower risk were observed for the middle tertile of exposure and all cancer sites (HR = 0.88, 95 % CI: 0.86-0.90), breast cancer (HR = 0.88, 95 % CI: 0.84-0.92) and prostate cancer (HR = 0.83, 95 % CI: 0.79-0.89). There was no evidence for mediation by air pollution (NO x )., Discussion: Residential greenness demonstrated beneficial associations with lower risk for all cancers, breast and prostate cancers. If our observations will be replicated, it may present a useful avenue for public-health intervention to reduce cancer burden through the provision of greenness exposure., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Greenery in the residential environment and in the hospital has been associated with improved surgical outcomes and recovery. We investigated the association between the level of residential greenness of patients with coronary disease and their heart disease-related Quality of Life (HRQoL) 1-year after a coronary artery bypass grafting (CABG) surgery. Participants in a prospective cohort study who underwent CABG surgery at seven cardiothoracic units throughout Israel during the years 2004–2007 filled in the MacNew HRQoL one day before and one year after surgery. Successful recovery was defined as ≥0.5 increase in the MacNew score between baseline and follow-up. Exposure to residential greenness in 90 m and 300 m buffers around the patient's home was assessed with Linear Spectral Unmixing analysis of Landsat 30 m imagery. The cohort comprised of 861 patients (22% female) with a mean age of 65.5 years, and 59.2% classified as low-income. In the total cohort, higher residential greenness was associated with an improvement in emotional HRQoL (OR = 1.33 (95%CI: 0.99–1.79)), adjusting for demographic and socio-economic factors, living in the periphery/center, presence of diabetes, attending cardiac rehabilitation following surgery, BMI, and change in physical fitness and depression over the 1-year follow-up. Although no association was found between greenness and change in the physical or social subscales, a positive association was specifically observed among the low-income patients for the global HRQoL score, OR = 1.42 (95%CI: 0.97–2.10), as compared to the higher-income patients, p for interaction = 0.03. Residential greenness is associated with improvement in HRQoL 1-year after CABG surgery, but not the physical and social scales, only in low-income patients. Ensuring greenery in the living environment may act as a social intervention that supports human health and disease recovery. • Residential greenness may enhance surgical recovery. • We studied greenness and quality of life post coronary artery bypass graft surgery. • Greenness was associated with improvement in the emotional domain of quality of life. • Greenness was particularly beneficial for low income, female, and sedentary patients. [ABSTRACT FROM AUTHOR]

• We compared different vegetation measures for application to epidemiology. • Linear Spectral Unmixing (LSU) outperforms NDVI in dense urban areas. • Compared to NDVI, LSU resulted in 20% of cohort changing exposure quartiles. • LSU can improve exposure assessment precision for epidemiological studies. Application of remote sensing-based metrics of exposure to vegetation in epidemiological studies of residential greenness is typically limited to several standard products. The Normalized Difference Vegetation Index (NDVI) is the most widely used, but its precision varies with vegetation density and soil color/moisture. In areas with heterogeneous vegetation cover, the Soil-adjusted Vegetation Index (SAVI) corrects for soil brightness. Linear Spectral Unmixing (LSU), measures the relative contribution of different land covers, and estimates percent of each over a unit area. We compared the precision of NDVI, SAVI and LSU for quantifying residential greenness in areas with high spatial heterogeneity in vegetation cover. NDVI, SAVI, and LSU in a 300 m radius surrounding homes of 3,188 cardiac patients living in Israel (Eastern Mediterranean) were derived from Landsat 30 m spatial resolution imagery. Metrics were compared to assess shifts in exposure quartiles and differences in vegetation detection as a function of overall greenness, climatic zones, and population density, using NDVI as the reference method. For the entire population, the dispersion (SD) of the vegetation values detected was 60% higher when greenness was measured using LSU compared to NDVI: mean (SD) NDVI: 0.17 (0.05), LSU (%): 0.23 (0.08), SAVI: 0.12 (0.03). Importantly, with an increase in population density, the sensitivity of LSU, compared to NDVI, doubled: There was a 95% difference between the LSU and NDVI interquartile range in the highest population density quartile vs 47% in the lowest quartile. Compared to NDVI, exposures estimated by LSU resulted in 21% of patients changing exposure quartiles. In urban areas, the shift in exposure quartile depended on land cover characteristics. An upward shift occurred in dense urban areas, while no shift occurred in high and low vegetated urban areas. LSU was shown to outperform the commonly used NDVI in terms of accuracy and variability, especially in dense urban areas. Therefore, LSU potentially improves exposure assessment precision, implying reduced exposure misclassification. [ABSTRACT FROM AUTHOR]