The continuing use of complementary and alternative medicine in South Australia: costs and beliefs in 2004

Objective: To survey the use, cost, beliefs and quality of life of users of complementary and alternative medicine (CAM). Design: A representative population survey conducted in 2004 with longitudinal comparison to similar 1993 and 2000 surveys. Participants: 3015 South Australian respondents over the age of 15 years (71.7% participation). Results: In 2004, CAMs were used by 52.2% of the population. Greatest use was in women aged 25-34 years, with higher income and education levels. CAM therapists had been visited by 26.5% of the population. In those with children, 29.9% administered CAMs to them and 17.5% of the children had visited CAM therapists. The total extrapolated cost in Australia of CAMs and CAM therapists in 2004 was AUD$1.8 billion, which was a decrease from AUD$2.3 billion in 2000. CAMs were used mostly to maintain general health. The users of CAM had lower quality-of-life scores than non-users. Among CAM users, 49.7% used conventional medicines on the same day and 57.2% did not report the use of CAMs to their doctor. About half of the respondents assumed that CAMs were independently tested by a government agency; of these, 74.8% believed they were tested for quality and safety, 21.8% for what they claimed, and 17.9% for efficacy. Conclusions: Australians continue to use high levels of CAMs and CAM therapists. The public is often unaware that CAMs are not tested by the Therapeutic Goods Administration for efficacy or safety.

Optimising profitability and environmental trade-offs in managing cropping systems using differential evolution

Whilst traditional optimisation techniques based on mathematical programming techniques are in common use, they suffer from their inability to explore the complexity of decision problems addressed using agricultural system models. In these models, the full decision space is usually very large while the solution space is characterized by many local optima. Methods to search such large decision spaces rely on effective sampling of the problem domain. Nevertheless, problem reduction based on insight into agronomic relations and farming practice is necessary to safeguard computational feasibility. Here, we present a global search approach based on an Evolutionary Algorithm (EA). We introduce a multi-objective evaluation technique within this EA framework, linking the optimisation procedure to the APSIM cropping systems model. The approach addresses the issue of system management when faced with a trade-off between economic and ecological consequences.