Genetic and environmental contributions to cannabis dependence in a national young adult twin sample

Background. This paper examines genetic and environmental contributions to risk of cannabis dependence. Method. Symptoms of cannabis dependence and measures of social, family and individual risk factors were assessed in a sample of 6265 young adult male and female Australian twins born 1964-1971. Results. Symptoms of cannabis dependence were common: 11(.)0% of sample (15(.)1% of men and 7(.)8% of women) reported two or more symptoms of dependence. Correlates of cannabis dependence included educational attainment, exposure to parental conflict, sexual abuse, major depression, social anxiety and childhood conduct disorder. However, even after control for the effects of these factors, there was evidence of significant genetic effects on risk of cannabis dependence. Standard genetic modelling indicated that 44(.)7% (95% CI = 15-72(.)2) of the variance in liability to cannabis dependence could be accounted for by genetic factors, 20(.)1% (95 CI = 0-43(.)6) could be attributed to shared environment factors and 35(.)3% (95% CI = 26(.)4-45(.)7) could be attributed to non-shared environmental factors. However, while there was no evidence of significant gender differences in the magnitude of genetic and environmental influences, a model which assumed both genetic and shared environmental influences on risks of cannabis dependence among men and shared environmental but no genetic influences among women provided an equally good fit to the data. Conclusions. There was consistent evidence that genetic risk factors are important determinants of risk of cannabis dependence among men. However, it remains uncertain whether there are genetic influences on liability to cannabis dependence among women.

Economic and environmental impacts of pollution control in a system of environment and economic interdependence

The importance of the rate of change of the pollution stock in determining the damage to the environment has been an issue of increasing concern in the literature. This paper uses a three-sector (economy, population and environment), non-linear, discrete time, calibrated model to examine pollution control. The model explicitly links economic growth to the health of the environment. The stock of natural resources is affected by the rate of pollution flows, through their impact on the regenerative capacity of the natural resource stock. This can shed useful insights into pollution control strategies, particularly in developing countries where environmental resources are crucial for production in many sectors of the economy. Simulation exercises suggested that, under plausible assumptions, it is possible to reverse undesirable transient dynamics through pollution control expenditure, but this is dependent upon the strategies used for control. The best strategy is to spend money fostering the development of production technologies that reduce pollution rather than spending money dealing with the effects of the pollution flow into the environment. (C) 2001 Elsevier Science Ltd. All rights reserved.

Work domain analysis and sensors II: Pasteurizer II case study

In this paper we use sensor-annotated abstraction hierarchies (Reising & Sanderson, 1996, 2002a,b) to show that unless appropriately instrumented, configural displays designed according to the principles of ecological interface design (EID) might be vulnerable to misinterpretation when sensors become unreliable or are unavailable. Building on foundations established in Reising and Sanderson (2002a) we use a pasteurization process control example to show how sensor-annotated AHs help the analyst determine the impact of different instrumentation engineering policies on a configural display that is part of an ecological interface. Our analyses suggest that configural displays showing higher-order properties of a system are especially vulnerable under some conservative instrumentation configurations. However, sensor-annotated AHs can be used to indicate where corrective instrumentation might be placed. We argue that if EID is to be effectively employed in the design of displays for complex systems, then the information needs of the human operator need to be considered while instrumentation requirements are being formulated. Rasmussen's abstraction hierarchy-and particularly its extension to the analysis of information captured by sensors and derived from sensors-may therefore be a useful adjunct to up-stream instrumentation design. (C) 2002 Elsevier Science Ltd. All rights reserved.

Work domain analysis and sensors I: principles and simple example

In this paper we establish a foundation for understanding the instrumentation needs of complex dynamic systems if ecological interface design (EID)-based interfaces are to be robust in the face of instrumentation failures. EID-based interfaces often include configural displays which reveal the higher-order properties of complex systems. However, concerns have been expressed that such displays might be misleading when instrumentation is unreliable or unavailable. Rasmussen's abstraction hierarchy (AH) formalism can be extended to include representations of sensors near the functions or properties about which they provide information, resulting in what we call a sensor-annotated abstraction hierarchy. Sensor-annotated AHs help the analyst determine the impact of different instrumentation engineering policies on higher-order system information by showing how the data provided from individual sensors propagates within and across levels of abstraction in the AH. The use of sensor-annotated AHs with a configural display is illustrated with a simple water reservoir example. We argue that if EID is to be effectively employed in the design of interfaces for complex systems, then the information needs of the human operator need to be considered at the earliest stages of system development while instrumentation requirements are being formulated. In this way, Rasmussen's AH promotes a formative approach to instrumentation engineering. (C) 2002 Elsevier Science Ltd. All rights reserved.

Linguistic evaluation method for the environmental assessment of infrastructure projects

A soft linguistic evaluation method is proposed for the environmental assessment of physical infrastructure projects based on fuzzy relations. Infrastructure projects are characterized in terms of linguistic expressions of 'performance' with respect to factors or impacts and the 'importance' of those factors/impacts. A simple example is developed to illustrate the method in the context of three road infrastructure projects assessed against five factors/impacts. In addition, a means to include hard or crisp factors is presented and illustrated with respect to a sixth factor.

Environmental factors associated with adults' participation in physical activity : A review

Background: Promoting physical activity is a public health priority, and changes in the environmental Contexts of adults' activity choices are believed to be crucial. However, of the factors associated with physical activity, environmental influences are among the least understood. Method: Using journal scans and computerized literature database searches, we identified 19 quantitative studies that assessed the relationships With physical activity behavior of perceived and objectively determined physical environment attributes. Findings were categorized into those examining five categories: accessibility of facilities, opportunities for activity, weather, safety, and aesthetic attributes. Results: Accessibility, opportunities, and aesthetic attributes had significant associations with physical activity, Weather and safety showed less-strong relationships. Where Studies pooled different categories to create composite variables, the associations were less likely to be statistically significant. Conclusions: Physical environment factors have consistent associations with physical activity behavior. Further development of ecologic and environmental models, together with behavior-specific and context-specific measurement strategies, should help in further understanding of these associations. Prospective Studies are required to identify possible causal relationships.

Genetic and Environmental Influences on Migraine: A Twin Study Across Six Countries

Migraine is a common neurovascular brain disorder that is manifested in recurrent episodes of disabling headache. The aim of the present study was to compare the prevalence and heritability of migraine across six of the countries that participate in GenomEutwin project including a total number of 29,717 twin pairs. Migraine was assessed by questionnaires that differed between most countries. It was most prevalent in Danish and Dutch females (32% and 34%, respectively), whereas the lowest prevalence was found in the younger and older Finnish cohorts (13% and 10%, respectively). The estimated genetic variance (heritability) was significant and the same between sexes in all countries. Heritability ranged from 34% to 57%, with lowest estimates in Australia, and highest estimates in the older cohort of Finland, the Netherlands, and Denmark. There was some indication that part of the genetic variance was non-additive, but this was significant in Sweden only. In addition to genetic factors, environmental effects that are non-shared between members of a twin pair contributed to the liability of migraine. After migraine definitions are homogenized among the participating countries, the GenomEUtwin project will provide a powerful resource to identify the genes involved in migraine.