Work-life conflict and musculoskeletal disorders: a cross-sectional study of an unexplored association

BACKGROUND: The health consequences of work-family or rather work-life conflict (WLC) have been studied by numerous researchers. The work-related causes of musculoskeletal disorders (MSD) are also well explored. And stress (at work) has been found to be a consequence of WLC as well as a cause of MSD. But very little is known about a potential association between WLC and MSD and the possible mediating role of stress in this relationship. METHODS: Survey data collected in 2007 among the workforces of four large companies in Switzerland were used for this study. The study population covered 6091 employees. As the exposure variable and hypothesized risk factor for MSD, WLC was measured by using a 10-item scale based on an established 18-item scale on work-family conflict. The outcome variables used as indicators of MSD were (low) back pain and neck/shoulder pain. Stress as the assumed intervening variable was assessed by a validated single-item measure of general stress perception. Correlation coefficients (r), standardized regression coefficients (beta) and multiple adjusted odds ratios (OR) were calculated as measures of association. RESULTS: WLC was found to be quite strongly associated with MSD (beta=.21). This association turned out to be substantially confounded by physical strain at work, workload and job autonomy and was considerably reduced but far from being completely eliminated after adjusting for general stress as another identified risk factor of MSD and a proven strong correlate of WLC (r=.44). A significant and relevant association still remained (beta=.10) after having controlled for all considered covariates. This association could be fully attributed to only one direction of WLC, namely the work-to-life conflict. In subsequent analyses, a clear gradient between this WLC direction and both types of MSD was found, and proved to be consistent for both men and women. Employees who were most exposed to such work-to-life conflict were also most at risk and showed a fivefold higher prevalence rate (19%-42%) and also an up to sixfold increased relative risk (OR=3.8-6.3) of suffering greatly from these types of MSD compared with the least exposed reference group showing very low WLC in this direction. Including stress in the regression models again reduced the strength of the association significantly (OR=1.9-4.1), giving an indication for a possible indirect effect of WLC on MSD mediated by stress. CONCLUSION: Future research and workplace interventions for the prevention of MSD need to consider WLC as an important stressor, and the MSD risk factor identified in this study

Digital repeat photography for phenological research in forest ecosystems

Digital repeat photography has the potential to become an important long-term data source for phenological research given its advantages in terms of logistics, continuity, consistency and objectivity over traditional assessments of vegetation status by human observers. Red-green-blue (RGB) color channel information from digital images can be separately extracted as digital numbers, and subsequently summarized through color indices such as excess green (ExG = 2G − [R + B]) or through nonlinear transforms to chromatic coordinates or other color spaces. Previous studies have demonstrated the use of ExG and the green chromatic coordinate (gcc = G/[R + G + B]) from digital landscape image archives for tracking canopy development but several methodological questions remained unanswered. These include the effects of diurnal, seasonal and weather-related changes in scene illumination on ExG and gcc, and digital camera and image file format choice. We show that gcc is generally more effective than ExG in suppressing the effects of changes in scene illumination. To further reduce these effects we propose a moving window approach that assigns the 90th percentile of all daytime values within a three-day window to the center day (per90), resulting in three-day ExG and gcc. Using image archives from eleven forest sites in North America, we demonstrate that per90 is able to further reduce unwanted variability in ExG and gcc due to changes in scene illumination compared to previously used mean mid-day values of ExG and gcc. Comparison of eleven different digital cameras at Harvard Forest (autumn 2010) indicates that camera and image file format choice might be of secondary importance for phenological research: with the exception of inexpensive indoor webcams, autumn patterns of changes in gcc and ExG from images in common JPEG image file format were in good agreement, especially toward the end of senescence. Due to its greater effectiveness in suppressing changes in scene illumination, especially in combination with per90, we advocate the use of gcc for phenological research. Our results indicate that gcc from different digital cameras can be used for comparing the timing of key phenological events (e.g., complete leaf coloring) across sites. However, differences in how specific cameras “see” the forest canopy may obscure subtle phenological changes that could be detectable if a common protocol was implemented across sites

NDVI derived from near-infrared-enabled digital cameras: Applicability across different plant functional types

Time series of vegetation indices (e.g. normalized difference vegetation index [NDVI]) and color indices (e.g. green chromatic coordinate [G CC ]) based on radiometric measurements are now available at different spatial and temporal scales ranging from weekly satellite observations to sub-hourly in situ measurements by means of near-surface remote sensing (e.g. spectral sensors or digital cameras). In situ measurements are essential for providing validation data for satellite-derived vegetation indices. In this study we used a recently developed method to calculate NDVI from near-infrared (NIR) enabled digital cameras (NDVI C ) at 17 sites (for a total of 74 year-sites) encompassing six plant functional types (PFT) from the PhenoCam network.The seasonality of NDVI C was comparable to both NDVI measured by ground spectral sensors and by the moderate resolution imaging spectroradiometer (MODIS). We calculated site- and PFT-specific scaling factors to correct NDVI C values and recommend the use of site-specific NDVI from MODIS in order to scale NDVI C . We also compared G CC extracted from red-green-blue images to NDVI C and found PFT-dependent systematic differences in their seasonalities. During senescence, NDVI C lags behind G CC in deciduous broad-leaf forests and grasslands, suggesting that G CC is more sensitive to changes in leaf color and NDVI C is more sensitive to changes in leaf area. In evergreen forests, NDVI C peaks later than G CC in spring, probably tracking the processes of shoot elongation and new needle formation. Both G CC and NDVI C can be used as validation tools for the MODIS Land Cover Dynamics Product (MCD12Q2) for deciduous broad-leaf spring phenology, whereas NDVI C is more comparable than G CC with autumn phenology derived from MODIS. For evergreen forests, we found a poor relationship between MCD12Q2 and camera-derived phenology, highlighting the need for more work to better characterize the seasonality of both canopy structure and leaf biochemistry in those ecosystems.Our results demonstrate that NDVI C is in excellent agreement with NDVI obtained from spectral measurements, and that NDVI C and G CC can complement each other in describing ecosystem phenology. Additionally, NDVI C allows the detection of structural changes in the canopy that cannot be detected by visible-wavelength imagery

Earlier snowmelt may lead to late season declines in plant productivity and carbon sequestration in Arctic tundra ecosystems

Abstract Arctic warming is affecting snow cover and soil hydrology, with consequences for carbon sequestration in tundra ecosystems. The scarcity of observations in the Arctic has limited our understanding of the impact of covarying environmental drivers on the carbon balance of tundra ecosystems. In this study, we address some of these uncertainties through a novel record of 119 site-years of summer data from eddy covariance towers representing dominant tundra vegetation types located on continuous permafrost in the Arctic. Here we found that earlier snowmelt was associated with more tundra net CO₂ sequestration and higher gross primary productivity (GPP) only in June and July, but with lower net carbon sequestration and lower GPP in August. Although higher evapotranspiration (ET) can result in soil drying with the progression of the summer, we did not find significantly lower soil moisture with earlier snowmelt, nor evidence that water stress affected GPP in the late growing season. Our results suggest that the expected increased CO₂ sequestration arising from Arctic warming and the associated increase in growing season length may not materialize if tundra ecosystems are not able to continue sequestering CO₂ later in the season

Shallow soils are warmer under trees and tall shrubs across Arctic and Boreal ecosystems

Abstract Soils are warming as air temperatures rise across the Arctic and Boreal region concurrent with the expansion of tall-statured shrubs and trees in the tundra. Changes in vegetation structure and function are expected to alter soil thermal regimes, thereby modifying climate feedbacks related to permafrost thaw and carbon cycling. However, current understanding of vegetation impacts on soil temperature is limited to local or regional scales and lacks the generality necessary to predict soil warming and permafrost stability on a pan-Arctic scale. Here we synthesize shallow soil and air temperature observations with broad spatial and temporal coverage collected across 106 sites representing nine different vegetation types in the permafrost region. We showed ecosystems with tall-statured shrubs and trees (>40 cm) have warmer shallow soils than those with short-statured tundra vegetation when normalized to a constant air temperature. In tree and tall shrub vegetation types, cooler temperatures in the warm season do not lead to cooler mean annual soil temperature indicating that ground thermal regimes in the cold-season rather than the warm-season are most critical for predicting soil warming in ecosystems underlain by permafrost. Our results suggest that the expansion of tall shrubs and trees into tundra regions can amplify shallow soil warming, and could increase the potential for increased seasonal thaw depth and increase soil carbon cycling rates and lead to increased carbon dioxide loss and further permafrost thaw

The ABCflux database:Arctic–boreal CO₂ flux observations and ancillary information aggregated to monthly time steps across terrestrial ecosystems

Abstract Past efforts to synthesize and quantify the magnitude and change in carbon dioxide (CO₂) fluxes in terrestrial ecosystems across the rapidly warming Arctic–boreal zone (ABZ) have provided valuable information but were limited in their geographical and temporal coverage. Furthermore, these efforts have been based on data aggregated over varying time periods, often with only minimal site ancillary data, thus limiting their potential to be used in large-scale carbon budget assessments. To bridge these gaps, we developed a standardized monthly database of Arctic–boreal CO₂ fluxes (ABCflux) that aggregates in situ measurements of terrestrial net ecosystem CO₂ exchange and its derived partitioned component fluxes: gross primary productivity and ecosystem respiration. The data span from 1989 to 2020 with over 70 supporting variables that describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. Here, we describe these variables, the spatial and temporal distribution of observations, the main strengths and limitations of the database, and the potential research opportunities it enables. In total, ABCflux includes 244 sites and 6309 monthly observations; 136 sites and 2217 monthly observations represent tundra, and 108 sites and 4092 observations represent the boreal biome. The database includes fluxes estimated with chamber (19 % of the monthly observations), snow diffusion (3 %) and eddy covariance (78 %) techniques. The largest number of observations were collected during the climatological summer (June–August; 32 %), and fewer observations were available for autumn (September–October; 25 %), winter (December–February; 18 %), and spring (March–May; 25 %). ABCflux can be used in a wide array of empirical, remote sensing and modeling studies to improve understanding of the regional and temporal variability in CO₂ fluxes and to better estimate the terrestrial ABZ CO₂ budget