The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
The ecological fallacy strikes back
Open accessAbstract
When I first started studying epidemiology, ecological studies were briefly discussed as an inexpensive but unreliable method for studying individual level risk factors for disease. For example, rather than go to the time and expense to establish a cohort study or case-control study of fat intake and breast cancer, you could simply use national dietary and cancer incidence data and, with minimal time and expense, show a strong correlation internationally between fat intake and breast cancer. This approach was quite rightly regarded as inadequate and unreliable because of the many additional forms of bias that can occur in such studies compared with studies of individuals within a population. In particular, the “ecological fallacy” can occur in that factors that are associated with national disease rates may not be associated with disease in individuals.1 For example, almost any disease that is associated with affluence and Westernisation has in the past been associated at the national level with sales of television sets, and nowadays is probably associated at the national level with rates of internet use. Thus, ecological studies were not a good thing to do, and were a relic of the “pre-modern” phase of epidemiology before it became firmly established with a methodologic paradigm based on the theory of randomised controlled trials of individuals. This paradigm, which is very powerful when used appropriately, gave rise to increasingly sophisticated methods of study design and data analysis. In particular, biostatistical methods that were developed for randomised trials involving a single individual level exposure were used to reformulate and make more rigorous the previously ad hoc epidemiological methods of study design and data analysis.2 3 Thus, epidemiology courses have increasingly become restricted to discussing cohort and case-control studies and the methods of data analysis that fit the clinical trial paradigm on which …
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Cites
Prisoners of the Proximate: Loosening the Constraints on Epidemiology in an Age of Change
McMichael, A. J. (1999) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a009732 · Cited by 502
Invited commentary: ecologic studies—biases, misconceptions, and counterexamples
Greenland, S., & Robins, J. (1994) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a117069 · Cited by 494
Disease and Social Diversity: The European Impact on the Health of Non-Europeans
Kunitz, S. J. (1994) · doi:10.1093/oso/9780195085303.001.0001 · Cited by 166
Epidemiology as a population science
Pearce, N. (1999) · International Journal of Epidemiology · doi:10.1093/oxfordjournals.ije.a019904 · Cited by 75
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Cited by
The disaggregation of within-person and between-person effects in longitudinal models of change
Curran, P. J., & Bauer, D. J. (2011) · Annual Review of Psychology · doi:10.1146/annurev.psych.093008.100356 · Cited by 2,056
Campbell, O., Bann, D., & Patalay, P. (2020) · doi:10.1101/2020.06.12.20129312 · Cited by 484
The ISAAC Phase One Study Group, Asher, M. I., Stewart, A. W., Mallol, J., Montefort, S., Lai, C. K., Aït-Khaled, N., & Odhiambo, J. (2010) · Respiratory Research · doi:10.1186/1465-9921-11-8 · Cited by 144
The globalization of epidemiology: introductory remarks
Pearce, N. (2004) · International Journal of Epidemiology · doi:10.1093/ije/dyh114 · Cited by 27
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Metadata
- Authors
- PEARCE, N.
- Venue
- Journal of Epidemiology and Community Health
- Publisher
- BMJ
- Published
- 2000-05-01
- Volume
- 54
- Issue
- 5
- Pages
- 326-327
- ISSN
- 0141-7681 (ISSN-L)
- 0143-005X
- 1470-2738
- OpenAlex
- W2105459884
- Cited by
- 195
- References
- 4
- FWCI
- 2.25
- Type
- journal article
- Language
- en
- Open access
- bronze
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