Study design and statistical analysis

Our goal is to design informative studies, surveys, and interventions, and apply robust statistical methods to assess human health risks from environmental and occupational exposures.

The rigorous design of studies, encompassing epidemiological and toxicological research, is essential to help understand the health risks from environmental and occupational exposures. There are many different lifestyles, environmental, genetic, socioeconomic, and other factors that all interact with one another, so ensuring a study and analysis account for these variables is needed to provide reliable results.

These findings can be used to inform evidence-based policy and practice, e.g. implementing and evaluating interventions to ensure population exposures are kept to safe levels.

Areas in which we work include:

• epidemiological studies (e.g. cohort, case-control, and cross-sectional)
• investigation of exposure measurements
• evaluation of intervention studies
• surveys of occupational groups
• toxicology
• literature reviews

The statistics team at IOM has applied this expertise in a range of settings. For example, we have been at the forefront of the development of life-tables for the health impact assessment of air pollution (IOMLIFET). We have also been heavily involved in the risk assessment of engineered nanoparticles, developing models to predict the personal exposure following emission from a source, and analysing results from in-vitro toxicity testing of nanoparticles with the aim of linking toxicity to particle characteristics.

We successfully lead on research funding applications and regularly publish the results of our work in the peer-reviewed literature. Members of our team also serve on government committees and are often invited to present at conferences and events.

We provide statistical expertise to studies outwith IOM and have been employed in legal cases as advisors on individuals’ health risks. Our team is also part of the European Food Safety Agency (EFSA) framework for statistical assistance, within which we offer to provide statistical expertise (analysis and/or advice) to specific EFSA projects.

The team is proficient in many statistical and mathematical packages including R, Minitab, SAS, Stata and Matlab.