Residential greenness and lower breast and prostate cancer incidence: Evidence from a retrospective cohort study of 977,644 participants from Israel.

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 (NOx) 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 (NOx). 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.

"Residential greenness and site-specific cancer: A registry based cohort of 144,427 participants with a 21-years of follow-up, Tel-Aviv district, Israel".

BACKGROUND: Few longitudinal studies evaluated the beneficial associations between cumulative residential greenness and site-specific cancer. Our objective was to evaluate the associations between cumulative residential greenness exposure and site-specific cancer incidence (lung, bladder, breast, prostate, and skin cancer) within a registry-based cohort study. METHODS: This study was based on 144,427 participants who lived in the Tel Aviv district during 1995-2015. The residential greenness exposure was estimated for every participant, as the weighted mean residential greenness exposure, based on the mean Normalized Difference Vegetation Index (NDVI) in the residential area and the duration of the residence in this area. Cox regression models were used to evaluate the unadjusted and adjusted associations between exposure to greenness and cancer incidence during 1998-2015 (Hazard Ratios (HRs) and 95% Confidence Intervals (CIs)). Covariates included in adjusted models were selected based on prior knowledge and directed acyclic graphs. We imputed missing data and further sensitivity analyses were conducted. RESULTS: After adjustments, beneficial associations between exposure to greenness and cancer incidence were observed. An interquartile range (IQR) increase in NDVI was associated with a lower HRs for lung cancer (HRadj. = 0.75 95% CI: 0.66-0.85), bladder cancer (HRadj. = 0.71, 95% CI: 0.62-0.82), breast cancer (HRadj. = 0.81, 95% CI: 0.74-0.88), prostate cancer (HRadj. = 0.77, 95% CI: 0.70-0.86) and skin cancer (HRadj. = 0.78, 95% CI: 0.69-0.88). Generally, the patterns of associations were consistent between complete-case models and imputed models, when estimated for participants aged 16 years or 40 years and older at baseline, when stratified by area level socioeconomic status, when evaluated for non-movers participants and after further adjustment to social determinants of health. CONCLUSION: Residential greenness may reduce the risk for lung, bladder, breast, prostate, and skin cancers. If our observations will be replicated, it may present a useful avenue for public-health intervention to reduce cancer burden.

Change of nutrients, microorganisms, and physical properties of exposed extensive green roof substrate.

Green roofs (GR) can be used as a nature-based solution to tackle eco-environmental problems caused by climate change and rapid urbanization. The substrate in the GRs is the growing medium for vegetation, and its properties directly affect the ecosystem services of GRs. To investigate the characteristic changes of an exposed substrate after the removal of vegetation, a one-year field experiment was conducted. Substrate properties were comprehensively compared for areas in GR that were planted with Sedum lineare and those with bare substrate. Results show that vegetation cover not only prevented substrate loss by 5.14% (p < 0.05) but also protected the chemical, microbial, and physical properties of the substrate. Moreover, the structure of the substrate changed, as evidenced by a significant increase in fine sand (p < 0.05). The results highlight that attention should be paid to maintaining vegetation cover during GR management. In addition, extensive GRs may not be suitable for fallowing. Once a GR has been established, it needs regular maintenance. Otherwise, the ecological and economic benefits of the GR may be reduced. The findings of the present study can be used to determine the life-cycle costs. Further research should focus on differences in the substrate loss rates, runoff, and temperatures of the substrates under exposure and vegetation cover. The microbial changes after revegetation should also be studied to clarify the role of vegetation in GR ecosystems. The present study provides a reference for improving GR management and ensuring their sustainability.

Low and High Ambient Temperatures during Pregnancy and Birth Weight among 624,940 Singleton Term Births in Israel (2010-2014): An Investigation of Potential Windows of Susceptibility.

BACKGROUND: Exposure to heat during pregnancy has been associated with reduced fetal growth. Less is known about associations with cold and the potential for critical time windows of exposure. OBJECTIVES: We aimed to evaluate, in a national retrospective cohort, critical windows of susceptibility during pregnancy to extreme temperatures (low and high) and fetal growth, among 624,940 singleton term births in Israel during the period 2010-2014. METHODS: Temperature exposures were estimated using a spatially refined gridded climate data set with a 1-h and 1-km2 resolution. Percentiles of temperature were categorized by climatic zone for the entire pregnancy and by trimesters and weeks. Generalized additive models with the distributed lag nonlinear model framework were used to estimate unadjusted and adjusted associations between percentiles and categories of temperature and fetal growth markers: term [births after 36 weeks of gestational age (GA)] mean birth weight and term low birth weight (tLBW, term infants with birth weight below 2,500g). RESULTS: After adjustment, extreme temperatures (percentiles) during the entire pregnancy were associated with a lower mean birth weight {≤10th vs. 41st-50th percentile: -56g [95% confidence interval (CI): -63g, -50g)]; >90th vs. 41st-50th percentile: -65g; 95% CI: -72g, -58g}. Similar inverse U-shaped patterns were observed for all trimesters, with stronger associations for heat than for cold and for exposures during the third trimester. For heat, results suggest critical windows between 3-9 and 19-34 GA-weeks, with the strongest association estimated at 3 GA-weeks (temperature >90th vs. 41st-50th percentiles: -3.8g; 95% CI: -7.1g, -0.4g). For cold, there was a consistent trend of null associations early in pregnancy and stronger inverse associations over time, with the strongest association at 36 GA-week (≤10th vs. 41st-50th percentiles: -2.9g; 95% CI: -6.5g, 0.7g). For tLBW, U-shape patterns were estimated for the entire pregnancy and third trimester exposures, as well as nonsignificant associations with heat for 29-36 GA-weeks. Generally, the patterns of associations with temperatures during the entire pregnancy were consistent when stratified by urbanicity and geocoding hierarchy, when estimated for daily minimum and maximum temperatures, when exposures were classified based on temperature distributions in 49 natural regions, and when estimated for all live births. DISCUSSION: Findings from our study of term live births in Israel (2010-2014) suggest that exposure to extreme temperatures, especially heat, during specific time windows may result in reduced fetal growth. https://doi.org/10.1289/EHP8117.

Worldwide continuous gap-filled MODIS land surface temperature dataset.

Satellite land surface temperature (LST) is vital for climatological and environmental studies. However, LST datasets are not continuous in time and space mainly due to cloud cover. Here we combine LST with Climate Forecast System Version 2 (CFSv2) modeled temperatures to derive a continuous gap filled global LST dataset at a spatial resolution of 1 km. Temporal Fourier analysis is used to derive the seasonality (climatology) on a pixel-by-pixel basis, for LST and CFSv2 temperatures. Gaps are filled by adding the CFSv2 temperature anomaly to climatological LST. The accuracy is evaluated in nine regions across the globe using cloud-free LST (mean values: R2 = 0.93, Root Mean Square Error (RMSE) = 2.7 °C, Mean Absolute Error (MAE) = 2.1 °C). The provided dataset contains day, night, and daily mean LST for the Eastern Mediterranean. We provide a Google Earth Engine code and a web app that generates gap filled LST in any part of the world, alongside a pixel-based evaluation of the data in terms of MAE, RMSE and Pearson's r.

Forecasting fire risk with machine learning and dynamic information derived from satellite vegetation index time-series.

Fire risk mapping - mapping the probability of fire occurrence and spread - is essential for pre-fire management as well as for efficient firefighting efforts. Most fire risk maps are generated using static information on variables such as topography, vegetation density, and fuel instantaneous wetness. Satellites are often used to provide such information. However, long-term vegetation dynamics and the cumulative dryness status of the woody vegetation, which may affect fire occurrence and spread, are rarely considered in fire risk mapping. Here, we investigate the impact of two satellite-derived metrics that represent long-term vegetation status and dynamics on fire risk mapping - the long-term mean normalized difference vegetation index (NDVI) of the woody vegetation (NDVIW) and its trend (NDVIT). NDVIW represents the mean woody density at the grid cell, while NDVIT is the 5-year trend of the woody NDVI representing the long-term dryness status of the vegetation. To produce these metrics, we decompose time-series of satellite-derived NDVI following a method adjusted for Mediterranean woodlands and forests. We tested whether these metrics improve fire risk mapping using three machine learning (ML) algorithms (Logistic Regression, Random Forest, and XGBoost). We chose the 2007 wildfires in Greece for the analysis. Our results indicate that XGBoost, which accounts for variable interactions and non-linear effects, was the ML model that produced the best results. NDVIW improved the model performance, while NDVIT was significant only when NDVIW was high. This NDVIW-NDVIT interaction means that the long-term dryness effect is meaningful only in places of dense woody vegetation. The proposed method can produce more accurate fire risk maps than conventional methods and can supply important dynamic information that may be used in fire behavior models.

Mean and variance of greenness and pregnancy outcomes in Tel Aviv during 2000-14: longitudinal and cross-sectional approaches.

BACKGROUND: Natural environments may have beneficial impacts on pregnancy outcomes. However, longitudinal evidence is limited and the associations with variance in surrounding greenness is unknown. Our objective was to evaluate these associations among 73 221 live births in Tel Aviv, Israel. METHODS: Longitudinal exposure to mean of greenness during pregnancy and trimesters were calculated using satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) Normalised Difference Vegetation Index (NDVI) data. In addition, exposure to mean and variation of NDVI from high-resolution satellite and percentage of tree cover [Vegetation Continuous Fields (VCF)] at 300-m buffer were evaluated in a cross-sectional approach. Generalized linear models were used to estimate the crude and adjusted associations. We explore the possible mediating role of ambient exposures and distance to 'outdoor gyms' located in parks. RESULTS: Crude beneficial associations between exposure to higher mean NDVI during pregnancy and pregnancy outcomes were observed [for birthweight, 3rd/1st tertile exposure increased the mean by 25.5 g, 95% confidence intervals (CIs): 15.4, 35.5] and decreased the odds of low birthweight, small for gestational age, preterm deliveries (PTD) and very PTD. Adjustment for individual and neighbourhood-level markers of socio-economic status (SES) attenuated all the associations. Strongest associations were observed during the first and second trimesters. Cross-sectional associations for mean greenness were similar with narrower CIs, and associations with NDVI were stronger than with tree cover and stronger for mean compared with variance of greenness. Associations were consistent for term births, different buffer sizes and for further adjustment to maternal education. Stronger associations were observed for lowest SES. Distance to 'outdoor gyms' and variance of greenness had the largest estimates of mediation. CONCLUSION: This study adds to the limited information on when exposure to greenness is most beneficial, on the association with variance of greenness and the possible pathways. These observations require confirmation in other populations.

Forests growing under dry conditions have higher hydrological resilience to drought than do more humid forests.

More frequent and intense droughts are projected during the next century, potentially changing the hydrological balances in many forested catchments. Although the impacts of droughts on forest functionality have been vastly studied, little attention has been given to studying the effect of droughts on forest hydrology. Here, we use the Budyko framework and two recently introduced Budyko metrics (deviation and elasticity) to study the changes in the water yields (rainfall minus evapotranspiration) of forested catchments following a climatic drought (2006-2010) in pine forests distributed along a rainfall gradient (P = 280-820 mm yr-1 ) in the Eastern Mediterranean (aridity factor = 0.17-0.56). We use a satellite-based model and meteorological information to calculate the Budyko metrics. The relative water yield ranged from 48% to 8% (from the rainfall) in humid to dry forests and was mainly associated with rainfall amount (increasing with increased rainfall amount) and bedrock type (higher on hard bedrocks). Forest elasticity was larger in forests growing under drier conditions, implying that drier forests have more predictable responses to drought, according to the Budyko framework, compared to forests growing under more humid conditions. In this context, younger forests were shown more elastic than older forests. Dynamic deviation, which is defined as the water yield departure from the Budyko curve, was positive in all forests (i.e., less-than-expected water yields according to Budyko's curve), increasing with drought severity, suggesting lower hydrological resistance to drought in forests suffering from larger rainfall reductions. However, the dynamic deviation significantly decreased in forests that experienced relatively cooler conditions during the drought period. Our results suggest that forests growing under permanent dry conditions might develop a range of hydrological and eco-physiological adjustments to drought leading to higher hydrological resilience. In the context of predicted climate change, such adjustments are key factors in sustaining forested catchments in water-limited regions.

Olive Fruit Fly (Bactrocera oleae) Population Dynamics in the Eastern Mediterranean: Influence of Exogenous Uncertainty on a Monophagous Frugivorous Insect.

Despite of the economic importance of the olive fly (Bactrocera oleae) and the large amount of biological and ecological studies on the insect, the factors driving its population dynamics (i.e., population persistence and regulation) had not been analytically investigated until the present study. Specifically, our study investigated the autoregressive process of the olive fly populations, and the joint role of intrinsic and extrinsic factors molding the population dynamics of the insect. Accounting for endogenous dynamics and the influences of exogenous factors such as olive grove temperature, the North Atlantic Oscillation and the presence of potential host fruit, we modeled olive fly populations in five locations in the Eastern Mediterranean region. Our models indicate that the rate of population change is mainly shaped by first and higher order non-monotonic, endogenous dynamics (i.e., density-dependent population feedback). The olive grove temperature was the main exogenous driver, while the North Atlantic Oscillation and fruit availability acted as significant exogenous factors in one of the five populations. Seasonal influences were also relevant for three of the populations. In spite of exogenous effects, the rate of population change was fairly stable along time. We propose that a special reproductive mechanism, such as reproductive quiescence, allows populations of monophagous fruit flies such as the olive fly to remain stable. Further, we discuss how weather factors could impinge constraints on the population dynamics at the local level. Particularly, local temperature dynamics could provide forecasting cues for management guidelines. Jointly, our results advocate for establishing monitoring programs and for a major focus of research on the relationship between life history traits and populations dynamics.

Novel description of force of infection and risk factors associated with Theileria equi in horses in Israel and in The Palestinian Authority.

The objectives of this study were to determine the force of infection (FOI) for Theileria equi in horses in Israel and to evaluate risk factors associated with seroprevalence a decade after it was last determined by PCR, in 2002. Using a commercial cELISA kit, we demonstrated a widespread and constant exposure to T. equi in Israel (110/216; 50.9%) and the Palestinian Authority (32/108; 29.6%). Owing to the paired samples collected from the same horses approximately one year apart, we were able to determine the FOI rate with which susceptible individuals become infected. Out of the 75 naïve horses in the first collection, four seroconverted during 10-16 months, demonstrating an FOI of 5% for that period. Similar results were obtained by calculating FOI using age-specific seroprevalence (4.2% per year). Housing management type was significantly associated with T. equi seroprevalence with 87.9% seropositivity in horses on pasture and 32.6% seropositivity in horses in stalls/yards. This strong association and the very high seroprevalence found in horses held on pasture, prompted stratification of data accordingly. Geographical location of horses in Israel showed a strong association with seroprevalence to T. equi ranging from 34.5% in central Israel to 80.8% in the northern part of the country. However, when analyzing this association only in horses held in stalls/yards, the lower seroprevalence was noted in the north. In addition, age was significantly associated with seroprevalence for T. equi only in horses held in stalls/yards (R(2)=0.94). Environmental variables were not found to be associated with seroprevalence for T. equi. Here, we report for the first time the FOI for T. equi in horses and highlight the influence housing management type has on the evaluation of risk factors associated with a vector-borne disease, perhaps leading to the discrepancies observed between studies throughout the world.

Demographic and environmental risk factors for infection by Theileria equi in 590 horses in Israel.

The prevalence of Theileria equi infection as well as the environmental and demographic risk factors for infection was studied in 590 healthy horses from 46 farms in Israel. The prevalence of T. equi DNA was assessed using a polymerase chain reaction for a segment of the Theileria 18S rRNA gene. The overall prevalence was 26.4% (156/590). There was a significant geographical variation in the prevalence of T. equi infection, ranging from 9.3% (25/270) in the central lowlands to 81.7% (49/60) in the Golan Heights. The prevalence of T. equi infection was found to be significantly associated with management types with more horses with access to pasture being positive. Breed was identified as a risk factor for T. equi infection in a univariate analysis with relatively high infection rates in the Quarter horse and local breeds (41.1% and 36.3% respectively), while ponies and Arabian horses had a relatively low prevalence (10% and 9.1%, respectively). However, since a correlation between geographic location and breed was found, it is difficult to draw definite conclusions regarding this risk factor. Age and gender were not found as risk factors for T. equi infection in this study. The environmental variables that were significantly associated with positivity were relative humidity and minimum land surface temperature at day which both showed negative correlation with T. equi prevalence. In conclusion, Israel was found to be enzootic for T. equi infection, as indicated by the high sub-clinical infection rate, which differed between geographical areas.