A semi-parametric approach to estimate risk functions associated with multi-dimensional exposure profiles: application to smoking and lung cancer

A common characteristic of environmental epidemiology is the multi-dimensional aspect of exposure patterns, frequently reduced to a cumulative exposure for simplicity of analysis. By adopting a flexible Bayesian clustering approach, we explore the risk function linking exposure history to disease. This approach is applied here to study the relationship between different smoking characteristics and lung cancer in the framework of a population based case control study

Using funnel plots in public health surveillance

<p>Abstract</p> <p>Background</p> <p>Public health surveillance is often concerned with the analysis of health outcomes over small areas. Funnel plots have been proposed as a useful tool for assessing and visualizing surveillance data, but their full utility has not been appreciated (for example, in the incorporation and interpretation of risk factors).</p> <p>Methods</p> <p>We investigate a way to simultaneously focus funnel plot analyses on direct policy implications while visually incorporating model fit and the effects of risk factors. Health survey data representing modifiable and nonmodifiable risk factors are used in an analysis of 2007 small area motor vehicle mortality rates in Alberta, Canada.</p> <p>Results</p> <p>Small area variations in motor vehicle mortality in Alberta were well explained by the suite of modifiable and nonmodifiable risk factors. Funnel plots of raw rates and of risk adjusted rates lead to different conclusions; the analysis process highlights opportunities for intervention as risk factors are incorporated into the model. Maps based on funnel plot methods identify areas worthy of further investigation.</p> <p>Conclusions</p> <p>Funnel plots provide a useful tool to explore small area data and to routinely incorporate covariate relationships in surveillance analyses. The exploratory process has at each step a direct and useful policy-related result. Dealing thoughtfully with statistical overdispersion is a cornerstone to fully understanding funnel plots.</p

Richard Nixon, 1972-2016 Obituary

After a year-long journey with cancer, Dr Richard Nixon died on August 26th, 2016, aged only 43 years. He leaves behind his wife of 5 years, Valda, and their 1-year-old baby daughter, Kyra. Richard, a Yorkshireman, was born on September 8th, 1972. He attended Ilkley Grammar School, studied mathematics at Durham University (1991–1994) and was awarded the Diploma in Mathematical Statistics from the University of Cambridge in 1995. Richard then took a career break for a couple of years to volunteer on the ship Logos II, which visited ports throughout the world as part of the global Christian training and outreach movement by Operation Mobilization Ships International. This movement was very close to Richard’s heart