An Introduction to Epidemiology

  • Cother Hajat
Part of the Methods in Molecular Biology book series (MIMB, volume 713)


Epidemiology as defined by Last is “the study of the distribution and determinants of health-related states or events in specified populations and the application of this study to the prevention and control of health problems”. Traditional epidemiological studies include quantitative and qualitative study designs. Quantitative study designs include observational and interventional methodology. Observational methods describe associations that are already present at population (descriptive) or individual (analytical) level. Although they form the mainstay of epidemiological studies, observational methods are prone to bias and confounding. These can be dealt with by various means involving both the study design and statistical analysis. Interventional methods involve changing variables in one or more groups of people and comparing outcomes between those with the changed and unchanged variable. Interventional studies can more readily account for bias (such as through randomisation) and confounding (such as through controlling) as is seen in randomised, controlled trials. Qualitative studies employ non-numeric methods to obtain “richer” information on how people perceive or experience situations. Much of epidemiology and epidemiological methods have been stable for many years. There are, however, emerging issues in epidemiology, including those of causal inference, counterfactuals and Mendelian randomisation, among others. There are also several modern and emerging uses of traditional epidemiological techniques in the fields of infectious disease, environmental, molecular and genetic epidemiology.

Key words

Observational studies Interventional studies Bias Confounding Emerging epidemiology 


  1. 1.
    Last JM. A Dictionary of Epidemiology, 3rd Ed. New York: Oxford University Press, 1995.Google Scholar
  2. 2.
    Self SG, Longton G, Kopecky JK, Ling KY. On estimating LHA/disease association with application to a study of aplastic anemia. Biometrics 1991;47:53–61.PubMedCrossRefGoogle Scholar
  3. 3.
    Khoury MJ and Flanders WD. Nontraditional epidemiologic approaches in the analyses if gene-environment interactions: Case-control studies with no controls! Am J Epidemiol 1996;144:207–213.PubMedCrossRefGoogle Scholar
  4. 4.
    Rothman JR, Greenland S, Lash TL. Modern Epidemiology, 3rd Ed. Philadelphia: Lippincott Williams & Wilkins, 2008.Google Scholar
  5. 5.
    Hill AB. The environment and disease: Association or causation? Proc R Soc Med 1965;58:295–300.PubMedGoogle Scholar
  6. 6.
    Hernán MA. A definition of causal effect for epidemiological research. J Epidemiol Comm­unity Health 2004;58(4):265–271.PubMedCrossRefGoogle Scholar
  7. 7.
    Maldonado G and Greenland S. Estimating causal effects. Int J Epidemiol 2002;31:422–429.PubMedCrossRefGoogle Scholar
  8. 8.
    Höfler M. The Bradford Hill considerations on causality: A counterfactual perspective. Emerg Themes Epidimol 2005;2:11.CrossRefGoogle Scholar
  9. 9.
    Snow J. On the Mode of Communication of Cholera. London: Churchill, 1855. (Reprinted in: Snow on cholera: A reprint of two papers. New York, Hafner Publishing Company, 1965).Google Scholar
  10. 10.
    Dawber TR, Kannel WB. An epidemiologic study of heart disease: The Framingham Study. Nutr Rev 1958;16(1):1–4.PubMedCrossRefGoogle Scholar
  11. 11.
    ARIC Investigators. The decline of ischaemic heart disease mortality in the ARIC Study communities. Int J Epidemiol 1989;18:588–598.Google Scholar
  12. 12.
    Burton PR, Hansell A. UK Biobank: The expected distribution of incident and prevalent cases of chronic disease and the statistical power of nested case-control studies. Technical Report for UK Biobank, 2005.

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Cother Hajat
    • 1
  1. 1.Public Health ProgrammesHealth Authority-Abu DhabiDubaiUnited Arab Emirates

Personalised recommendations