Invited commentary: ecologic studies—biases, misconceptions, and counterexamples
Abstract
Many authors have pointed out that relative-risk estimates derived from ecologic data are vulnerable to biases not found in estimates derived from individual-level data. Nevertheless, biases in ecologic studies still are often dealt with in the same manner as biases in other observational studies, and so are not given adequate treatment. This commentary reviews and illustrates some of the more recent findings about bias in ecologic estimates. Special attention is given to problems of ecologic confounder control when individual risks follow a nonlinear model, and to misconceptions about ecologic bias that have appeared in the literature.
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Ecological studies cannot establish that the exposed individual is the same as the diagnosed individual and cannot account for individual-level confounding.
“In aggregate outcome data, it cannot be known that the individual experiencing the exposure is the same individual within the group that had an autism diagnosis. Furthermore, it is not possible to account for individual-level confounding influences in this type of design”
From Environmental Chemical Exposures and Autism Spectrum Disorders: A Review of the Epidemiological Evidence (2014) · cites this paper as [17]
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Freedman, D. A. (2001) · Elsevier eBooks · doi:10.1016/b0-08-043076-7/00410-1 · Cited by 79 · see citing works
Groundwater uranium and cancer incidence in South Carolina
Wagner, S. E., Burch, J. B., Bottai, M., Puett, R. C., Porter, D. E., Bolick-Aldrich, S., Temples, T. J., Wilkerson, R. C., Vena, J. E., & Hébert, J. R. (2010) · Cancer Causes & Control · doi:10.1007/s10552-010-9669-4 · Cited by 77 · see citing works
Ecological Studies of Antidepressant Treatment and Suicidal Risks
Baldessarini, R. J., Tondo, L., Strombom, I., Dominguez, S., FAWCETT, J. A., Licinio, J., Oquendo, M. A., Tollefson, G. D., Valuck, R. J., & Tohen, M. F. (2007) · Harvard Review of Psychiatry · doi:10.1080/10673220701551102 · Cited by 77 · see citing works
Inequalities in COVID19 mortality related to ethnicity and socioeconomic deprivationPreprint
Rose, T. C., Mason, K., Pennington, A., McHale, P., Buchan, I. E., Taylor-Robinson, D. C., & Barr, B. (2020) · medRxiv · doi:10.1101/2020.04.25.20079491 · Cited by 77 · see citing works
Bello, N. M., Stevenson, J. S., & Tempelman, R. J. (2012) · Journal of Dairy Science · doi:10.3168/jds.2012-5564 · Cited by 75 · see citing works
- Authors
- Greenland, S., & Robins, J.
- Affiliations
- University of California, Los Angeles (US)
- Harvard University (US)
- Corresponding author
- Greenland, Sander
- Venue
- American Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 1994-04-15
- Volume
- 139
- Issue
- 8
- Pages
- 747-760
- ISSN
- 0002-9262 (ISSN-L)
- 1476-6256
- OpenAlex
- W2131305454
- Cited by
- 494
- References
- 21
- Citations by year
- 2026: 22 · 2025: 7 · 2024: 8 · 2023: 10 · 2022: 10 · 2021: 19 · 2020: 14 · 2019: 6 · 2018: 7 · 2017: 8 · 2016: 15 · 2015: 15 · 2014: 19 · 2013: 16 · 2012: 11
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Journal of Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5k04es000180-03)
- National Institute of Allergy and Infectious Diseases (R01AI032475)
- National Institute of Environmental Health Sciences (P30ES000002, K04-ES00180)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- ecological study, relative risk estimation, confounder control, microdata, bias in observational studies
- MeSH terms
- Ecology, Epidemiologic Methods, Humans, Regression Analysis, Risk, Models, Statistical, Bias, Confounding Factors, Epidemiologic
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