Three interpretations of an ecological study
The very interesting article by de Vocht et al (1) is a good opportunity to discuss possible interpretations of results obtained in ecological studies. The study included 165 nations as observations and found an association between mobile/cellular telecommunications (per 100 people) and brain cancer (national age-adjusted incidence rates). Although in this case authors were interested in the generation of individual-level causal hypotheses, the same results can be interpreted in two more ways based on multilevel causal approach,(2) promulgated by social epidemiologists.
One first alternative interpretation can be called "full-population approach". According to the classic article by Rose, determinants of individual cases are not necessarily determinants of incidence rate.(3) In this approach there is not interest in individual or other level inferences, thus results of one ecological study could be valid in the same aggregation level of observations analyzed. Until I know only one study used national data from Nordic countries,(4) and its inconsistent results can be explained per difficulties to explore latency periods. For this, my conclusion is that de Vocht et al study is the most valid study at national aggregation level.
The second alternative interpretation is interested in an ecological approach but in different aggregation levels. For instance, it occurs when ecological studies based on national data are evidence for national sub- regions inferences. It can be possible but the presence of fallacy is a threat. In this case is needed to explore cross-level fallacies similar to ecological fallacy.(5) A discussion on this same topic is available in two commentaries,(6,7) and inferences on different aggregation-levels can be responsible of heterogeneity observed.
Explanations of these alternatives approaches should not to be based on biomedical concepts. Macrodeterminants and population-level outcomes act according to ecologic, social, cultural or economical processes. Thus an initial explanation of results can be based on a previous study by Milham, where "civilization" is the main determinant of some diseases with high occurrence in recent years. (8)
In conclusion, I agree with the authors that in occupational and environmental health ecological studies can be a useful source of evidence. However their results can offer more evidence if they are analyzed according to different aggregation-level approaches.
1. de Vocht F, Hannam K, Buchan I. Environmental risk factors for cancers of the brain and nervous system: the use of ecological data to generate hypotheses. Occup Environ Med 2013 (in press).
2. Diez-Roux AV. A glossary for multilevel analysis. J Epidemiol Community Health 2002;56(8):588-94.
3. Rose G. Sick individuals and sick populations. Int J Epidemiol 1985;14(1):32-8.
4. Deltour I, Auvinen A, Feychting M, Johansen C, Klaeboe L, Sankila R, Schuz J. Mobile phone use and incidence of glioma in the Nordic countries 1979-2008: consistency check. Epidemiology 2012;23(2):301-7.
5. Idrovo AJ. Three criteria for ecological fallacy. Environ Health Perspect 2011;119:A332.
6. Soderqvist F, Carlberg M, Hansson Mild K, Hardell L. Childhood brain tumour risk and its association with wireless phones: a commentary. Environ Health 2011;10:106.
7. Aydin D, Feychting M, Schuz J, Roosli M; CEFALO study team. Childhood brain tumours and use of mobile phones: comparison of a case- control study with incidence data. Environ Health 2012;11:35.
8. Milham S. Historical evidence that electrification caused the 20th century epidemic of "diseases of civilization". Med Hypotheses 2010;74(2):337-45.
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