Integration of the biophysical and social sciences using an indicator approach: Addressing water problems at different scales

To be operationally sustainable, any system of environmental management needs to be based on a truly holistic assessment of all of the relevant factors influencing it. This is of course a daunting task, demanding as it does detailed and reliable data, not only from both the physical and social sciences, but also incorporating some representation of that part of knowledge which could be described as non-scientific. This could be said to include the uncertainties of market forces and political will, as well as traditional knowledge systems, and artistic representation. Recognising the limitations of our own knowledge system is important if we are to make progress in the achievement of sustainability. The development of less deterministic models is a step forward in that direction. This paper provides some discussion on the challenges associated with the integration of data from different disciplines, and the application of that data at different scales. Alternative approaches to the assessment of water resources for policy making are highlighted, and the validity of using such assessments at different scales is discussed. Using the Water Poverty Index as illustration, examples are provided of how an integrated assessment framework can be used to provide consistency and transparency in decision-making, and how this can, in practice, be applied at a variety of scales

Genetic studies of body mass index yield new insights for obesity biology

Note: A full list of authors and affiliations appears at the end of the article. Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P 20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.</p