The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Estimating the population attributable risk for multiple risk factors using case-control data.
Abstract
A straightforward and unified approach is presented for the calculation of the population attributable risk per cent (etiologic fraction) in the general multivariate setting, with emphasis on using data from case-control studies. The summary attributable risk for multiple factors can be estimated, with or without adjustment for other (confounding) risk factors. The relation of this approach to procedures in the literature is discussed. Given values of the relative risks for various combinations of factors, all that is required is the distribution of these factors among the cases only. The required information can often be estimated solely from case-control data, and in some situations relative risk estimates from one population can be applied to calculation of attributable risk for another population. The authors emphasize the benefits to be obtained from logistic regression models, so that risks need not be estimated separately in a large number of strata, some of which may contain inadequate numbers of individuals. This approach allows incorporation of important interactions between factors, but does not require that all possible interactions be included. The approach is illustrated with data on four risk factors from a pair-matched case-control study of participants in a multicenter breast cancer screening project.
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“However, if there is also a correlation between exposure and disease-specific mortality, due to correlations of exposure with other risks or other unobserved factors, the above equations may result in under- (when there is positive correlation) or over-estimation (negative correlation) of the true PAF when used with adjusted RRs [32]–[36].”
From The Preventable Causes of Death in the United States: Comparative Risk Assessment of Dietary, Lifestyle, and Metabolic Risk Factors (2009) · cites this paper as [34]
Citations
Cites
Statistical Methods in Cancer Research
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PROPORTION OF DISEASE CAUSED OR PREVENTED BY A GIVEN EXPOSURE, TRAIT OR INTERVENTION1
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The Estimation and Interpretation of Attributable Risk in Health Research
Walter, S. D. (1976) · Biometrics · doi:10.2307/2529268 · Cited by 449
Attributable risk percent in case-control studies.
Cole, P. T., & MacMahon, B. (1971) · Journal of Epidemiology & Community Health · doi:10.1136/jech.25.4.242 · Cited by 344
Calculation of Attributable Risks from Epidemiological Data
Walter, S. D. (1978) · International Journal of Epidemiology · doi:10.1093/ije/7.2.175 · Cited by 170
PREVENTION FOR MULTIFACTORIAL DISEASES
Walter, S. D. (1980) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a113007 · Cited by 165
Breast Cancer Risk Factors Among Screening Program Participants
Brinton, L. A., Williams, R. R., Hoover, R. N., Stegens, N. L., Feinleib, M., & Fraumeni, J. F. (1979) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/62.1.37 · Cited by 121
Self-citationStatistical methods for estimating attributable risk from retrospective data
Whittemore, A. S. (1982) · Statistics in Medicine · doi:10.1002/sim.4780010305 · Cited by 110
Interaction of Familial and Hormonal Risk Factors for Breast Cancer
Brinton, L. A., Hoover, R. N., & Fraumeni, J. F. (1982) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/69.4.817 · Cited by 107
Self-citationA computer program for the analysis of matched case-control studies
Lubin, J. H. (1981) · Computers and Biomedical Research · doi:10.1016/0010-4809(81)90031-8 · Cited by 99
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Yusuf, S., Hawken, S., Ôunpuu, S., Dans, T., Avezum, A., Lanas, F., McQueen, M., Budaj, A., Pais, P., Varigos, J., et al. (2004) · The Lancet · doi:10.1016/s0140-6736(04)17018-9 · Cited by 12,026
Kotloff, K. L., Nataro, J. P., Blackwelder, W. C., Nasrin, D., Farag, T. H., Panchalingam, S., Wu, Y., Sow, S. O., Sur, D., Breiman, R. F., et al. (2013) · The Lancet · doi:10.1016/s0140-6736(13)60844-2 · Cited by 3,560
Danaei, G., Ding, E. L., Mozaffarian, D., Taylor, B., Rehm, J., Murray, C. J. L., & Ezzati, M. (2009) · PLoS Medicine · doi:10.1371/journal.pmed.1000058 · Cited by 2,860
Determinants of low birth weight: methodological assessment and meta-analysis.
Kramer, M. S. (1987) · Europe PMC (PubMed Central) · Cited by 2,682
Use and misuse of population attributable fractions
Rockhill, B., Newman, B., & Weinberg, C. (1998) · American Journal of Public Health · doi:10.2105/ajph.88.1.15 · Cited by 1,683
Metadata
- Authors
- BRUZZI, P., GREEN, S. B., BYAR, D. P., BRINTON, L. A., & SCHAIRER, C.
- Affiliations
- National Institutes of Health (US)
- Corresponding author
- BYAR, DAVID P.
- Venue
- American Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 1985-11
- Volume
- 122
- Issue
- 5
- Pages
- 904-914
- ISSN
- 0002-9262 (ISSN-L)
- 1476-6256
- OpenAlex
- W2256786579
- Cited by
- 1,214
- References
- 16
- Citations by year
- 2026: 12 · 2025: 10 · 2024: 25 · 2023: 20 · 2022: 20 · 2021: 44 · 2020: 37 · 2019: 29 · 2018: 31 · 2017: 25 · 2016: 36 · 2015: 25 · 2014: 41 · 2013: 49 · 2012: 36
- FWCI
- 8.74
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Journal of Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Health Sciences › Medicine › Oncology › Global Cancer Incidence and Screening
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Keywords
- population attributable risk, population attributable fraction, multiple risk factors, case-control study, logistic regression, confounding adjustment, relative risk, breast cancer screening
- MeSH terms
- Biopsy, Breast, Breast Neoplasms, Epidemiologic Methods, Female, Humans, Maternal Age, Menarche, Models, Biological, Risk, Statistics as Topic
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