Is uncertainty in complex disease epidemiology resolvable?
Author(s) -
Wasim Maziak
Publication year - 2015
Publication title -
emerging themes in epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.513
H-Index - 35
ISSN - 1742-7622
DOI - 10.1186/s12982-015-0028-5
Subject(s) - epidemiology , disease , public health , population , population health , field (mathematics) , medicine , environmental health , risk analysis (engineering) , data science , computer science , pathology , mathematics , pure mathematics
The imposed limitations on what we can know about nature have been long recognized. Yet in the field of epidemiology a futile search for lifestyle-related risk factors for common chronic diseases continues unabated. This has led to the production of a growing body of evidence about potential lifestyle risk factors that tend to be marginal, contradictory, irreproducible, or hard to interpret. While epidemiologists are calling for a more refined methodology, I argue that our limitation in studying complex diseases is insurmountable. This is because the study of lifestyle-related small risks requires accurate measurement of multiple behaviors-exposures over a long period of time. It is also because in complex systems such as population’s health, the effect of rich interactions between its parts cannot be predicted based on traditional causal models of epidemiology. Within complex systems, understanding the interactions between system components can be more important than the contribution of each to disease risk.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom