What is on your greatest hits album for epidemiology?
If you could compile a list of the best epidemiology papers of all time, what would be at the top? We’re talking about those papers that you actually print out, cover with yellow highlighter, and scribble notes in all of the margins. Papers that changed the way you thought about or solved a problem. Let’s see what we come up with!
Kathleen E. Wirth, Research Fellow at Harvard School of Public Health, asked this question on SER’s LinkedIn Group Page. We have compiled the responses here in the LinkedIn Greatest Hits playlist. This list is part two of two.
Do you have additional papers to add to the playlist. Leave a comment below!
Purnima Madhivanan – Rose’s paper seems relevant even today
Sick individuals and sick populations.
Rose G. International Journal of Epidemiology. 2001;30:427-432
Purnima Madhivanan – When we were training in epi methods, these papers appeared multiple times and have been great tools to learn from
Coffee and Cancer of the Pancreas.
MacMahon B, Yen S, Trichopoulos D, et al. NEJM. 1981; 304:630-633
On the need for the rare disease assumption in case-control studies.
Greenland S, Thomas D. Am J Epidemiology. 1982; 116: 547-553
Substance versus semantics.
Greenland S. Induction versus Popper: Int J Epidemiol 1988; 27:543-548
Selection of controls in case-control studies series by Wacholder
Alex Keil- This article was formative for me – it helped define a logical and systematic framework for thinking about long-term exposures, in general.
Assessment of long-term exposures to toxic substances in air.
Rappaport, S. (1991). Annals of Occupational Hygiene, 35(1):61
5. Absence of confounding does not correspond to collapsibility of the rate ratio or rate difference
Alex Keil- This article, which is always in the back of my mind when I think about confounding
Absence of confounding does not correspond to collapsibility of the rate ratio or rate difference
Greenland, S. (1996). Epidemiology, 7(5):498–501
Neil Traven – I’d suggest a “classic” that I’ve found to be ever more valuable as the Big Data sledgehammer spreads into more research fields
The environment and disease: association or causation?
Hill AB. Proc R Soc Med 1965;58:295-300
Stephen Gange – The table of ‘independent risk factors’ in this paper is very instructive whenever someone claims to find a newly identified biomarker that should be immediately integrated into clinical practice. Certainly tempered my own enthusiasm and thinking of this area
In search of fewer independent risk factors.
Brotman DJ, Walker E, Lauer MS, O’Brien RG. Arch Intern Med. 2005 Jan 24;165(2):138-45. Review. PubMed PMID: 15668358
Thomas Glass – this paper altered thinking and illustrated the role of theory and its interaction with data
Aging, natural death, and the compression of morbidity.
Fries, J.F. (1980). New England Journal of Medicine, 303:130-35
Thomas Glass – Put the spider under the lamp. Controversial still
Epidemiology and the web of causation: has anyone seen the spider?
Krieger, N. (1994). Social Science & Medicine, 39:887-903
Layer the foundation for sufficient-component causes
Rothman, K.J. (1976). Causes. American Journal of Epidemiology, 104:587-92
The Epidemiologic Transition: A Theory of the Epidemiology of Population Change.
Omran A. Milbank Q. Dec 2005; 83(4): 731-757