Neil Pearce

Prof. Neil Pearce

Prof. Neil Pearce
Director of the Centre for Global Non-communicable Disease, London School of Hygiene and Tropical Medicine

Biography

The 2019 recipient of the EPICOH Award for Outstanding Contributions to Occupational Epidemiology is Professor Neil Pearce. Neil is currently Professor of Epidemiology and Biostatistics, and Director of the Centre for Global Non-communicable Disease, at the London School of Hygiene and Tropical Medicine. Prior to this, he was Director of the Centre for public Health Research at Massey University, Wellington campus, and was a co-founder of the Wellington Asthma Research Group (WARG) at the Wellington School of Medicine.

Since completion of his PhD in Epidemiology in 1985 he has been a world leader in occupational epidemiology research, having co-authored the leading textbook of occupational epidemiology, published by Oxford University Press in 1989 (the second edition was published in 2004). His research on occupational cancer, asthma and more recently neurodegenerative conditions has been highly original and has contributed important insights into the aetiological mechanisms of occupational disease. Neil’s work is not limited to traditional areas of occupational epidemiology (chronic diseases associated with a wide range of occupational exposures such as pesticides, dust, solvents, and other chemicals), but also includes work on health inequities related to differential occupational exposures in vulnerable populations including Māori (the indigenous population of New Zealand). Through his involvement in many national and international committees, including IARC working groups, he has also contributed significantly to policy changes designed to reduce hazards in the work place. He has published more than 600 papers in high impact journals, which are cited frequently in the international literature, and has an h-index many of us can only dream of. In addition to Neil’s excellent contributions to research in occupational epidemiology, he has played a major role in training new and emerging researchers. Thus, in addition to his own extraordinary achievements he has facilitated and boosted the careers of many others.

Keynote

The Evolution of Occupational Epidemiology

In this talk, I review the evolution of occupational epidemiology over the last 40 years. Methodologically, the field is almost unrecognizable compared to what was ‘standard practice’ 40 years ago. Methodological changes include the use of new study design and statistical methods, such as counterfactual theory, directed acyclic graphs (DAGs), IPW, g-estimation, g-computation, multiple imputation for missing values, sensitivity analysis, and bootstrapping. Biomarkers and various molecular and omics measures are increasingly used for exposure assessment, and exploration of mechanisms. The exposures and outcomes under study have also evolved, e.g. with increased consideration of psychosocial factors, work organisation, musculoskeletal problems, mental health and neurological disease. Despite all of these changes, many of the fundamentals of occupational epidemiology remain the same.

The discovery of new causes of occupational disease continues to be lead by astute observers (including astute clinicians and astute workers), rather than by ‘bigdata’ or ‘omics’ methods. The strategy for investigation of possible occupational causes of disease continues to require a variety of study designs and approaches, including ‘descriptive’ studies, and triangulation across study designs and populations (albeit while utilising new molecular biology and statistical techniques).

The causal assessment of occupational exposures and their health effects continues to require a wide variety of types of evidence in humans and animals, as well as mechanistic evidence. Forty years later, the Bradford-Hill considerations have been augmented but not been replaced, and the IARC ‘rules’ for combining various types of evidence remain the state-of-the-art. Reports of the death of ‘traditional epidemiology’ (and its replacement by ‘modern epidemiology’ and ‘causal inference’ methods) have been exaggerated.

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