Head injuries in early childhood in the UK; is there a social gradient?

Objectives To examine if there is a social gradient in early childhood head injuries among UK children. Methods Cross-sectional study, using data from the UK Millennium Cohort Study (MCS). The second, third and fourth sweeps of the MCS were analysed separately, when children were 3, 5 and 7 years old. Logistic regression models were used to explore the associations between head injuries and family socioeconomic position (social class, household income, maternal education and area deprivation). Results The unadjusted analyses showed different associations with socioeconomic indicators at different ages. At age 3 and 5 years, head injuries were associated with higher area deprivation, lower household income and parents not being in work or in the routine social class. At age 5 years head injuries were also associated with lower maternal education. At age 7 years only associations with area deprivation and maternal education were found. In adjusted analyses (mutually adjusted for all four socioeconomic indicators, maternal age, child age and child sex), the following associations were observed: at ages 3 and 5 years, higher levels of area deprivation were related to higher odds of head injuries. At age 3 years only, lower levels of maternal education were related to lower odds of head injuries. No social gradients were observed. At age 7 years, there were no significant associations between head injuries and any of the SEP measures. Conclusion We observed no social gradients in early childhood head injuries. However, at ages 3 and 5 years, head injuries were more frequently reported for children living in more deprived areas

Life course socioeconomic position and general and oral health in later life: Assessing the role of social causation and health selection pathways

Objective: To examine the pathways between life course socioeconomic position (SEP) and general and oral health, assessing the role of two competing theories, social causation and health selection, on a representative sample of individuals aged 50 years and over in England. // Methods: Secondary analysis from the English Longitudinal Study of Ageing Wave 3 data (n = 8659). Structural equation models estimated the social causation pathways from childhood SEP to adult self-rated general health and total tooth loss, and the health selection pathways from childhood health to adult SEP. // Results: There were direct and indirect (primarily via education, but also adult SEP, and behavior) pathways from childhood SEP to both health outcomes in older adulthood. There was a direct pathway from childhood health to adult SEP, but no indirect pathway via education. The social causation path total effect estimate was three times larger for self-rated general health and four times larger for total tooth loss than the health selection path respective estimates. // Conclusions: The relationship between SEP and health is bidirectional, but with a clearly stronger role for the social causation pathway

Satellite-based prediction of pCO2 in coastal waters of the eastern North Pacific

Continental margin carbon cycling is complex, highly variable over a range of space and time scales, and forced by multiple physical and biogeochemical drivers. Predictions of globally significant air–sea CO2 fluxes in these regions have been extrapolated based on very sparse data sets. We present here a method for predicting coastal surface-water pCO2 from remote-sensing data, based on self organizing maps (SOMs) and a nonlinear semi-empirical model of surface water carbonate chemistry. The model used simple empirical relationships between carbonate chemistry (total dissolved carbon dioxide (TCO2) and alkalinity (TAlk)) and satellite data (sea surface temperature (SST) and chlorophyll (Chl)). Surface-water CO2 partial pressure (pCO2) was calculated from the empirically-predicted TCO2 and TAlk. This directly incorporated the inherent nonlinearities of the carbonate system, in a completely mechanistic manner. The model’s empirical coefficients were determined for a target study area of the central North American Pacific continental margin (22–50°N, within 370 km of the coastline), by optimally reproducing a set of historical observations paired with satellite data. The model-predicted pCO2 agreed with the highly variable observations with a root mean squared (RMS) deviation of 0.8 (r = 0.81; r2 = 0.66). This level of accuracy is a significant improvement relative to that of simpler models that did not resolve the biogeochemical sub-regions or that relied on linear dependences on input parameters. Air–sea fluxes based on these pCO2 predictions and satellite-based wind speed measurements suggest that the region is a ∼14 Tg C yr−1 sink for atmospheric CO2 over the 1997–2005 period, with an approximately equivalent uncertainty, compared with a ∼0.5 Tg C yr−1 source predicted by a recent bin-averaging and interpolation-based estimate for the same area.Fil: Hales, Burke. State University of Oregon; Estados UnidosFil: Strutton, Peter G.. University Of Tasmania; AustraliaFil: Saraceno, Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmosfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmosfera; ArgentinaFil: Letelier, Ricardo. State University of Oregon; Estados UnidosFil: Takahashi, Taro. Lamont-Doherty Earth Observatory; Estados UnidosFil: Feely, Richard. National Oceanic and Atmospheric Administration. Pacific Marine Environmental Laboratory; Estados UnidosFil: Sabine, Christopher. National Oceanic and Atmospheric Administration. Pacific Marine Environmental Laboratory; Estados UnidosFil: Chavez, Francisco. Monterey Bay Aquarium Research Institute; Estados Unido

Satellite-based prediction of pCO₂ in coastal waters of the eastern North Pacific

Continental margin carbon cycling is complex, highly variable over a range of space and time scales, and forced by multiple physical and biogeochemical drivers. Predictions of globally significant air–sea CO₂ fluxes in these regions have been extrapolated based on very sparse data sets. We present here a method for predicting coastal surface-water pCO₂ from remote-sensing data, based on self organizing maps (SOMs) and a nonlinear semi-empirical model of surface water carbonate chemistry. The model used simple empirical relationships between carbonate chemistry (total dissolved carbon dioxide (T[subscript CO₂]) and alkalinity (T[subscript Alk])) and satellite data (sea surface temperature (SST) and chlorophyll (Chl)). Surface-water CO₂ partial pressure (pCO₂) was calculated from the empirically-predicted T[subscript CO₂] and T[subscript Alk]. This directly incorporated the inherent nonlinearities of the carbonate system, in a completely mechanistic manner. The model’s empirical coefficients were determined for a target study area of the central North American Pacific continental margin (22–50°N, within 370 km of the coastline), by optimally reproducing a set of historical observations paired with satellite data. The model-predicted pCO₂ agreed with the highly variable observations with a root mean squared (RMS) deviation of 0.8 (r = 0.81; r² = 0.66). This level of accuracy is a significant improvement relative to that of simpler models that did not resolve the biogeochemical sub-regions or that relied on linear dependences on input parameters. Air–sea fluxes based on these pCO₂ predictions and satellite-based wind speed measurements suggest that the region is a ∼14 Tg C yr⁻¹ sink for atmospheric CO₂ over the 1997–2005 period, with an approximately equivalent uncertainty, compared with a ∼0.5 Tg C yr⁻¹ source predicted by a recent bin-averaging and interpolation-based estimate for the same area

Gravitating discs around black holes

Fluid discs and tori around black holes are discussed within different approaches and with the emphasis on the role of disc gravity. First reviewed are the prospects of investigating the gravitational field of a black hole--disc system by analytical solutions of stationary, axially symmetric Einstein's equations. Then, more detailed considerations are focused to middle and outer parts of extended disc-like configurations where relativistic effects are small and the Newtonian description is adequate. Within general relativity, only a static case has been analysed in detail. Results are often very inspiring, however, simplifying assumptions must be imposed: ad hoc profiles of the disc density are commonly assumed and the effects of frame-dragging and completely lacking. Astrophysical discs (e.g. accretion discs in active galactic nuclei) typically extend far beyond the relativistic domain and are fairly diluted. However, self-gravity is still essential for their structure and evolution, as well as for their radiation emission and the impact on the environment around. For example, a nuclear star cluster in a galactic centre may bear various imprints of mutual star--disc interactions, which can be recognised in observational properties, such as the relation between the central mass and stellar velocity dispersion.Comment: Accepted for publication in CQG; high-resolution figures will be available from http://www.iop.org/EJ/journal/CQ

An overview of MODIS capabilities for ocean science observations

The Moderate Resolution Imaging Spectroradiometer (MODIS) will add a significant new capability for investigating the 70% of the Earth's surface that is covered by oceans, in addition to contributing to the continuation of a decadal scale time series necessary for climate change assessment in the oceans. Sensor capabilities of particular importance for improving the accuracy of ocean products include high SNR and high stability for narrow or spectral bands, improved onboard radiometric calibration and stability monitoring, and improved science data product algorithms. Spectral bands for resolving solar-stimulated chlorophyll fluorescence and a split window in the 4-/spl mu/m region for SST will result in important new global ocean science products for biology and physics. MODIS will return full global data at 1-km resolution. The complete suite of Levels 2 and 3 ocean products is reviewed, and many areas where MODIS data are expected to make significant, new contributions to the enhanced understanding of the oceans' role in understanding climate change are discussed. In providing a highly complementary and consistent set of observations of terrestrial, atmospheric, and ocean observations, MODIS data will provide important new information on the interactions between Earth's major components