Review of epidemiological factors (other than maternal age) that determine the prevalence of common autosomal trisomies

The birth prevalence of each common autosomal trisomy (21, 18 and 13) increases with advancing maternal age and this is the most important epidemiological risk factor. Prevalence during pregnancy is also dependent on gestational age. Other factors claimed to influence prevalence include paternal age, ethnicity, family history, premature reproductive aging, parity, twinning, smoking, environmental exposures, maternal medical conditions, and predispositions. We review the evidence for these associations since they may provide insights into causal mechanisms. When investigating potential co-factors it is important to adequately allow for maternal age and minimize its confounding contribution. This is well illustrated by reports of an inverse paternal age effect where there is strong correlation between parental ages. Gestational age at diagnosis, availability of prenatal screening, diagnostic testing, and elective termination of affected pregnancies and healthcare disparities also confound the studies on ethnicity, medical conditions, and predispositions or environmental factors. Data from twin zygosity studies demonstrate the importance of differences in fetal viability for affected pregnancies. We conclude that existing epidemiological evidence for most of the co-factors discussed should currently be considered tenuous; history of Down syndrome, albeit biased, may be an exception. The co-factors may yet provide clues to hitherto poorly understood causal pathways.     

Strategic environmental noise mapping: Methodological issues concerning the implementation of the EU Environmental Noise Directive and their policy implications

This paper explores methodological issues and policy implications concerning the implementation of the EU Environmental Noise Directive (END) across Member States. Methodologically, the paper focuses on two key thematic issues relevant to the Directive: (1) calculation methods and (2) mapping methods. For (1), the paper focuses, in particular, on how differing calculation methods influence noise prediction results as well as the value of the EU noise indicator L_den and its associated implications for comparability of noise data across EU states. With regard to (2), emphasis is placed on identifying the issues affecting strategic noise mapping, estimating population exposure, noise action planning and dissemination of noise mapping results to the general public. The implication of these issues for future environmental noise policy is also examined.     

Mental health outcomes of job stress among Chinese teachers: role of stress resource factors and burnout

This study examined the mental health outcomes of job stress among Chinese teachers in Hong Kong. A total of 269 Chinese teachers participated in Study 1 which provided cross‐sectional data regarding the associations among stress resource factors, burnout, and negative mental health. Study 2 was a six‐month longitudinal study which aimed to establish the direction of the associations among the hypothesized variables across two time points with a separate sample of 61 Chinese secondary school teachers. Results of the structural equation modelling analyses on the cross‐sectional data at T1 showed that stress resource factors of self‐efficacy and proactive attitude were negatively related to burnout, which in turn had a direct effect on negative mental health. Stress resource factors were also directly linked to mental health status of teachers. Results of similar analyses on the longitudinal data at T2 further indicated that burnout at T1 had a direct impact on burnout at T2, which in turn had a direct effect on negative mental health at T2. Findings and limitations of the study were discussed. Copyright © 2001 John Wiley & Sons, Ltd.     

Heterozygosity‐Fitness Correlations and Inbreeding Depression in Two Critically Endangered Mammals

The relation among inbreeding, heterozygosity, and fitness has been studied primarily among outbred populations, and little is known about these phenomena in endangered populations. Most researchers conclude that the relation between coefficient of inbreeding estimated from pedigrees and fitness traits (inbreeding‐fitness correlations) better reflects inbreeding depression than the relation between marker heterozygosity and fitness traits (heterozygosity‐fitness correlations). However, it has been suggested recently that heterozygosity‐fitness correlations should only be expected when inbreeding generates extensive identity disequilibrium (correlations in heterozygosity and homozygosity across loci throughout the genome). We tested this hypothesis in Mohor gazelle (Gazella dama mhorr) and Iberian lynx (Lynx pardinus). For Mohor gazelle, we calculated the inbreeding coefficient and measured heterozygosity at 17 microsatellite loci. For Iberian lynx, we measured heterozygosity at 36 microsatellite loci. In both species we estimated semen quality, a phenotypic trait directly related to fitness that is controlled by many loci and is affected by inbreeding depression. Both species showed evidence of extensive identity disequilibrium, and in both species heterozygosity was associated with semen quality. In the Iberian lynx the low proportion of normal sperm associated with low levels of heterozygosity was so extreme that it is likely to limit the fertility of males. In Mohor gazelle, although heterozygosity was associated with semen quality, inbreeding coefficient was not. This result suggests that when coefficient of inbreeding is calculated on the basis of a genealogy that begins after a long history of inbreeding, the coefficient of inbreeding fails to capture previous demographic information because it is a poor estimator of accumulated individual inbreeding. We conclude that among highly endangered species with extensive identity disequilibrium, examination of heterozygosity‐fitness correlations may be an effective way to detect inbreeding depression, whereas inbreeding‐fitness correlations may be poor indicators of inbreeding depression if the pedigree does not accurately reflect the history of inbreeding. Correlaciones Heterocigosidad‐ Adaptabilidad y Depresión Endogámica en Dos Especies de Mamíferos Críticamente en Peligro     

Stochastic Transfer Function Model and Neural Networks to Estimate Soil Moisture1

Abstract: A practical methodology is proposed to estimate the three‐dimensional variability of soil moisture based on a stochastic transfer function model, which is an approximation of the Richard’s equation. Satellite, radar and in situ observations are the major sources of information to develop a model that represents the dynamic water content in the soil. The soil‐moisture observations were collected from 17 stations located in Puerto Rico (PR), and a sequential quadratic programming algorithm was used to estimate the parameters of the transfer function (TF) at each station. Soil texture information, terrain elevation, vegetation index, surface temperature, and accumulated rainfall for every grid cell were input into a self‐organized artificial neural network to identify similarities on terrain spatial variability and to determine the TF that best resembles the properties of a particular grid point. Soil moisture observed at 20 cm depth, soil texture, and cumulative rainfall were also used to train a feedforward artificial neural network to estimate soil moisture at 5, 10, 50, and 100 cm depth. A validation procedure was implemented to measure the horizontal and vertical estimation accuracy of soil moisture. Validation results from spatial and temporal variation of volumetric water content (vwc) showed that the proposed algorithm estimated soil moisture with a root mean squared error (RMSE) of 2.31% vwc, and the vertical profile shows a RMSE of 2.50% vwc. The algorithm estimates soil moisture in an hourly basis at 1 km spatial resolution, and up to 1 m depth, and was successfully applied under PR climate conditions.