Greenness and job-related chronic stress in young adults: a prospective cohort study in Germany

OBJECTIVES

We aimed to prospectively study the association between normalised difference vegetation index (NDVI) as a measure of greenness around homes and occupational stress.

SETTING

A population-based cohort in Munich and Dresden cities was followed from age 16-18 years to age 20-23 years (n=1632).

PARTICIPANTS

At baseline, all participants attended high-school while at follow-up some had started working and others studying at university. At baseline and in each follow-up, we assigned NDVI based on participants' residential geocoded addresses and categorised it by quartiles.

OUTCOME MEASURES

School-related, university-related or job-related self-reported chronic stress was assessed at the two follow-ups by the Trier Scale for Assessment of Chronic Stress using work discontent and work overload as outcomes. We modelled the association employing ordinal generalised estimating equations model accounting for changes in sociodemographics, non-job-related stress, job history and environmental covariates. Stratified analysis by each city was performed.

RESULTS

NVDI at baseline was higher for participants from Dresden (median=0.36; IQR 0.31-0.41) than Munich (0.31; 0.26-0.34). At follow-up, it decreased only for participants in Dresden (0.34; 0.30-0.40). Higher greenness (quartile 4 vs quartile 1) was associated with less work discontent (OR 0.89; 95% CI 0.80 to 0.99) and less work overload (OR 0.87; 95% CI 0.78 to 0.96). In stratified analyses, results were more consistent for Munich than for Dresden.

CONCLUSIONS

Our results suggest that residential green spaces, using the vegetation index as a proxy for exposure, are inversely associated with two types of job-related chronic stress in German young adults transitioning from school to university or working life.

A cross-sectional analysis of the effects of residential greenness on blood pressure in 10-year old children: results from the GINIplus and LISAplus studies

BACKGROUND

According to Ulrich's psychoevolutionary theory, contact with green environments mitigates stress by activating the parasympathetic system, (specifically, by decreasing blood pressure (BP)). Experimental studies have confirmed this biological effect. However, greenness effects on BP have not yet been explored using an observational study design. We assessed whether surrounding residential greenness is associated with BP in 10 year-old German children.

METHODS

Systolic and diastolic BPs were assessed in 10 year-old children residing in the Munich and Wesel study areas of the German GINIplus and LISAplus birth cohorts. Complete exposure, outcome and covariate data were available for 2,078 children. Residential surrounding greenness was defined as the mean of Normalized Difference Vegetation Index (NDVI) values, derived from Landsat 5 TM satellite images, in circular 500-m buffers around current home addresses of participants. Generalized additive models assessed pooled and area-specific associations between BP and residential greenness categorized into area-specific tertiles.

RESULTS

In the pooled adjusted model, the systolic BP of children living at residences with low and moderate greenness was 0.90 ± 0.50 mmHg (p-value = 0.073) and 1.23 ± 0.50 mmHg (p-value = 0.014) higher, respectively, than the systolic BP of children living in areas of high greenness. Similarly, the diastolic BP of children living in areas with low and moderate greenness was 0.80 ± 0.38 mmHg (p-value = 0.033) and 0.96 ± 0.38 mmHg (p-value = 0.011) higher, respectively, than children living in areas with high greenness. These associations were not influenced by environmental stressors (temperature, air pollution, noise annoyance, altitude and urbanisation level). When stratified by study area, associations were significant among children residing in the urbanised Munich area but null for those in the rural Wesel area.

CONCLUSIONS

Lower residential greenness was positively associated with higher BP in 10 year-old children living in an urbanised area. Further studies varying in participants' age, geographical area and urbanisation level are required.

The association between neighborhood greenness and weight status: an observational study in Perth Western Australia

BACKGROUND

Few studies have examined the relationship between weight status and objectively measured neighborhood greenness and no study has examined this relationship across the different stages of adulthood. This research was an investigation of weight status and neighborhood greenness using objectively measured satellite remote sensing for a large population representative sample.

METHOD

Cross-sectional study of 10,208 young adults (16-24 years), mid-age adults (25-64 years) and older adults (65+ years) from a population representative sample for the period 2004-2009 in Perth, Western Australia. Neighborhood greenness was ascertained for a 1600m road network service area around each participant's address using the mean and standard deviation of the Normalized Difference Vegetation Index (NDVI) obtained from remote sensing. Multiple logistic regression was used to assess associations with weight status (overweight-or-obese, obese) adjusted for socio-demographics and health-related behaviors.

RESULTS

The adjusted odds ratio (OR) comparing obesity in the highest to the lowest tertile of mean greenness was 0.78 (95% CI 0.69-0.89). For the same comparison, the OR for overweight-or-obese was similar, 0.84 (95% CI 0.76-0.92). The OR comparing obesity in the highest to lowest tertile of variation in greenness was 0.75 (95% CI 0.66-0.85). For the same comparison, the OR for overweight-or-obese was similar, 0.75 (95% CI 0.68-0.82).

CONCLUSION

Higher levels and greater variation of neighborhood greenness are associated with lower odds of obesity among adults of all ages. Research examining neighborhood characteristics correlated with variability in greenness will help better understand these relationships.

Spatio-temporal analyses of cropland degradation in the irrigated lowlands of Uzbekistan using remote-sensing and logistic regression modeling

Advancing land degradation in the irrigated areas of Central Asia hinders sustainable development of this predominantly agricultural region. To support decisions on mitigating cropland degradation, this study combines linear trend analysis and spatial logistic regression modeling to expose a land degradation trend in the Khorezm region, Uzbekistan, and to analyze the causes. Time series of the 250-m MODIS NDVI, summed over the growing seasons of 2000-2010, were used to derive areas with an apparent negative vegetation trend; this was interpreted as an indicator of land degradation. About one third (161,000 ha) of the region's area experienced negative trends of different magnitude. The vegetation decline was particularly evident on the low-fertility lands bordering on the natural sandy desert, suggesting that these areas should be prioritized in mitigation planning. The results of logistic modeling indicate that the spatial pattern of the observed trend is mainly associated with the level of the groundwater table (odds = 330 %), land-use intensity (odds = 103 %), low soil quality (odds = 49 %), slope (odds = 29 %), and salinity of the groundwater (odds = 26 %). Areas, threatened by land degradation, were mapped by fitting the estimated model parameters to available data. The elaborated approach, combining remote-sensing and GIS, can form the basis for developing a common tool for monitoring land degradation trends in irrigated croplands of Central Asia.

Response of vegetation to drought time-scales across global land biomes

We evaluated the response of the Earth land biomes to drought by correlating a drought index with three global indicators of vegetation activity and growth: vegetation indices from satellite imagery, tree-ring growth series, and Aboveground Net Primary Production (ANPP) records. Arid and humid biomes are both affected by drought, and we suggest that the persistence of the water deficit (i.e., the drought time-scale) could be playing a key role in determining the sensitivity of land biomes to drought. We found that arid biomes respond to drought at short time-scales; that is, there is a rapid vegetation reaction as soon as water deficits below normal conditions occur. This may be due to the fact that plant species of arid regions have mechanisms allowing them to rapidly adapt to changing water availability. Humid biomes also respond to drought at short time-scales, but in this case the physiological mechanisms likely differ from those operating in arid biomes, as plants usually have a poor adaptability to water shortage. On the contrary, semiarid and subhumid biomes respond to drought at long time-scales, probably because plants are able to withstand water deficits, but they lack the rapid response of arid biomes to drought. These results are consistent among three vegetation parameters analyzed and across different land biomes, showing that the response of vegetation to drought depends on characteristic drought time-scales for each biome. Understanding the dominant time-scales at which drought most influences vegetation might help assessing the resistance and resilience of vegetation and improving our knowledge of vegetation vulnerability to climate change.

Surrounding greenness and pregnancy outcomes in four Spanish birth cohorts

BACKGROUND

Green spaces have been associated with improved physical and mental health; however, the available evidence on the impact of green spaces on pregnancy is scarce.

OBJECTIVES

We investigated the association between surrounding greenness and birth weight, head circumference, and gestational age at delivery.

METHODS

This study was based on 2,393 singleton live births from four Spanish birth cohorts (Asturias, Gipuzkoa, Sabadell, and Valencia) located in two regions of the Iberian Peninsula with distinct climates and vegetation patterns (2003-2008). We defined surrounding greenness as average of satellite-based Normalized Difference Vegetation Index (NDVI) (Landsat 4-5 TM data at 30 m × 30 m resolution) during 2007 in buffers of 100 m, 250 m, and 500 m around each maternal place of residence. Separate linear mixed models with adjustment for potential confounders and a random cohort effect were used to estimate the change in birth weight, head circumference, and gestational age for 1-interquartile range increase in surrounding greenness.

RESULTS

Higher surrounding greenness was associated with increases in birth weight and head circumference [adjusted regression coefficients (95% confidence interval) of 44.2 g (20.2 g, 68.2 g) and 1.7 mm (0.5 mm, 2.9 mm) for an interquartile range increase in average NDVI within a 500-m buffer] but not gestational age. These findings were robust against the choice of the buffer size and the season of data acquisition for surrounding greenness, and when the analysis was limited to term births. Stratified analyses indicated stronger associations among children of mothers with lower education, suggesting greater benefits from surrounding greenness.

CONCLUSIONS

Our findings suggest a beneficial impact of surrounding greenness on measures of fetal growth but not pregnancy length.

Surrounding greenness and exposure to air pollution during pregnancy: an analysis of personal monitoring data

BACKGROUND

Green spaces are reported to improve health status, including beneficial effects on pregnancy outcomes. Despite the suggestions of air pollution-related health benefits of green spaces, there is no available evidence on the impact of greenness on personal exposure to air pollution.

OBJECTIVES

We investigated the association between surrounding greenness and personal exposure to air pollution among pregnant women and to explore the potential mechanisms, if any, behind this association.

METHODS

In total, 65 rounds of sampling were carried out for 54 pregnant women who resided in Barcelona during 2008-2009. Each round consisted of a 2-day measurement of particulate matter with aerodynamic diameter ≤ 2.5 μm (PM₂.₅) and a 1-week measurement of nitric oxides collected simultaneously at both the personal and microenvironmental levels. The study participants were also asked to fill out a time-microenvironment-activity diary during the sampling period. We used satellite retrievals to determine the surrounding greenness as the average of Normalized Difference Vegetation Index (NDVI) in a buffer of 100 m around each maternal residential address. We estimated the impact of surrounding greenness on personal exposure levels, home-outdoor and home-indoor pollutant levels, and maternal time-activity.

RESULTS

Higher residential surrounding greenness was associated with lower personal, home-indoor, and home-outdoor PM₂.₅ levels, and more time spent at home-outdoor.

CONCLUSIONS

We found lower levels of personal exposure to air pollution among pregnant women residing in greener areas. This finding may be partly explained by lower home-indoor pollutant levels and more time spent in less polluted home-outdoor environment by pregnant women in greener areas.

Identification of "ever-cropped" land (1984-2010) using Landsat annual maximum NDVI image composites: Southwestern Kansas case study

A time series of 230 intra- and inter-annual Landsat Thematic Mapper images was used to identify land that was ever cropped during the years 1984 through 2010 for a five county region in southwestern Kansas. Annual maximum Normalized Difference Vegetation Index (NDVI) image composites (NDVI(ann-max)) were used to evaluate the inter-annual dynamics of cropped and non-cropped land. Three feature images were derived from the 27-year NDVI(ann-max) image time series and used in the classification: 1) maximum NDVI value that occurred over the entire 27 year time span (NDVI(max)), 2) standard deviation of the annual maximum NDVI values for all years (NDVI(sd)), and 3) standard deviation of the annual maximum NDVI values for years 1984-1986 (NDVI(sd84-86)) to improve Conservation Reserve Program land discrimination.Results of the classification were compared to three reference data sets: County-level USDA Census records (1982-2007) and two digital land cover maps (Kansas 2005 and USGS Trends Program maps (1986-2000)). Area of ever-cropped land for the five counties was on average 11.8 % higher than the area estimated from Census records. Overall agreement between the ever-cropped land map and the 2005 Kansas map was 91.9% and 97.2% for the Trends maps. Converting the intra-annual Landsat data set to a single annual maximum NDVI image composite considerably reduced the data set size, eliminated clouds and cloud-shadow affects, yet maintained information important for discriminating cropped land. Our results suggest that Landsat annual maximum NDVI image composites will be useful for characterizing land use and land cover change for many applications.

Stay-green in spring wheat can be determined by spectral reflectance measurements (normalized difference vegetation index) independently from phenology

The green area displayed by a crop is a good indicator of its photosynthetic capacity, while chlorophyll retention or 'stay-green' is regarded as a key indicator of stress adaptation. Remote-sensing methods were tested to estimate these parameters in diverse wheat genotypes under different growing conditions. Two wheat populations (a diverse set of 294 advanced lines and a recombinant inbred line population of 169 sister lines derived from the cross between Seri and Babax) were grown in Mexico under three environments: drought, heat, and heat combined with drought. In the two populations studied here, a moderate heritable expression of stay-green was found-when the normalized difference vegetation index (NDVI) at physiological maturity was estimated using the regression of NDVI over time from the mid-stages of grain-filling to physiological maturity-and for the rate of senescence during the same period. Under heat and heat combined with drought environments, stay-green calculated as NDVI at physiological maturity and the rate of senescence, showed positive and negative correlations with yield, respectively. Moreover, stay-green calculated as an estimation of NDVI at physiological maturity and the rate of senescence regressed on degree days give an independent measurement of stay-green without the confounding effect of phenology. On average, in both populations under heat and heat combined with drought environments CTgf and stay-green variables accounted for around 30% of yield variability in multiple regression analysis. It is concluded that stay-green traits may provide cumulative effects, together with other traits, to improve adaptation under stress further.