Arsenic in dust and aerosol generated by mining, mineral processing and metallurgical extraction industries, is a serious threat to human populations throughout the world. Major sources of contamination include smelting operations, coal combustion, hard rock mining, as well as their associated waste products, including fly ash, mine wastes and tailings. The number of uncontained arsenic-rich mine waste sites throughout the world is of growing concern, as is the number of people at risk of exposure. Inhalation exposures to arsenic-bearing dusts and aerosol, in both occupational and environmental settings, have been definitively linked to increased systemic uptake, as well as carcinogenic and non-carcinogenic health outcomes. It is therefore becoming increasingly important to identify human populations and sensitive sub-populations at risk of exposure, and to better understand the modes of action for pulmonary arsenic toxicity and carcinogenesis. In this paper we explore the contribution of smelting, coal combustion, hard rock mining and their associated waste products to atmospheric arsenic. We also report on the current understanding of the health effects of inhaled arsenic, citing results from various toxicological, biomedical and epidemiological studies. This review is particularly aimed at those researchers engaged in the distinct, but complementary areas of arsenic research within the multidisciplinary field of medical geology.

Physical inactivity has major impacts on health and productivity. Our aim was to estimate the health and economic benefits of reducing the prevalence of physical inactivity in the 2008 Australian adult population. The economic benefits were estimated as 'opportunity cost savings', which represent resources utilized in the treatment of preventable disease that are potentially available for re-direction to another purpose from fewer incident cases of disease occurring in communities.

A large proportion of disease burden is attributed to behavioural risk factors. However, funding for public health programs in Australia remains limited. Government and non-government organisations are interested in the productivity effects on society from reducing chronic diseases. We aimed to estimate the potential health status and economic benefits to society following a feasible reduction in the prevalence of six behavioural risk factors: tobacco smoking; inadequate fruit and vegetable consumption; high risk alcohol consumption; high body mass index; physical inactivity; and intimate partner violence.

Please cite this paper as: Pearce et al. (2011) Understanding mortality in the 1918–1919 influenza pandemic in England and Wales. Influenza and Other Respiratory Viruses 5(2), 89–98.Background  The causes of recurrent waves in the 1918–1919 influenza pandemic are not fully understood.Objectives  To identify the risk factors for influenza onset, spread and mortality in waves 1, 2 and 3 (summer, autumn and winter) in England and Wales in 1918–1919.Methods  Influenza mortality rates for 333 population units and putative risk factors were analysed by correlation and by regressions weighted by population size and adjusted for spatial trends.Results  For waves 1 and 3, influenza mortality was higher in younger, northerly and socially disadvantaged populations experiencing higher all‐cause mortality in 1911–1914. Influenza mortality was greatest in wave 2, but less dependent on underlying population characteristics. Wave duration was shorter in areas with higher influenza mortality, typically associated with increasing population density. Regression analyses confirmed the importance of geographical factors and pre‐pandemic mortality for all three waves. Age effects were complex, with the suggestion that younger populations with greater mortality in wave 1 had lesser mortality in wave 2.Conclusions  Our findings suggest that socially disadvantaged populations were more vulnerable, that older populations were partially protected by prior immunity in wave 1 and that exposure of (younger) populations in one wave could protect against mortality in the subsequent wave. An increase in viral virulence could explain the greater mortality in wave 2. Further modelling of causal processes will help to explain, in considerable detail, how social and geographical factors, season, pre‐existing and acquired immunity and virulence affected viral transmission and pandemic mortality in 1918–1919.