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Result: Survey of practices of handling exposure measurement errors in modern epidemiology: are the best practices in statistics being adopted by epidemiologists?

Title:
Survey of practices of handling exposure measurement errors in modern epidemiology: are the best practices in statistics being adopted by epidemiologists?
Authors:
Russell AJ; Integral Consulting, San Francisco, CA, USA., Hunter MK; Frank H. Netter MD School of Medicine, Quinnipiac University, North Haven, CT, USA., Maldonado G; Environmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, MN, USA., Burstyn I; Environmental and Occupational Health, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA. ib68@drexel.edu.
Source:
BMC medical research methodology [BMC Med Res Methodol] 2025 Aug 25; Vol. 25 (1), pp. 198. Date of Electronic Publication: 2025 Aug 25.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: BioMed Central Country of Publication: England NLM ID: 100968545 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2288 (Electronic) Linking ISSN: 14712288 NLM ISO Abbreviation: BMC Med Res Methodol Subsets: MEDLINE
Imprint Name(s):
Original Publication: London : BioMed Central, [2001-
MeSH Terms:
Epidemiologists* , Epidemiologic Studies* , Epidemiology*, Humans ; Reproducibility of Results ; Data Interpretation, Statistical ; Bias ; Surveys and Questionnaires ; Epidemiologic Methods
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Contributed Indexing:
Keywords: Bias; Epidemiologic methods; Exposure; Measurement error
Entry Date(s):
Date Created: 20250826 Date Completed: 20250826 Latest Revision: 20250829
Update Code:
20250903
PubMed Central ID:
PMC12376469
DOI:
10.1186/s12874-025-02651-w
PMID:
40855410
Database:
MEDLINE

Further Information

Background: Measurement errors in epidemiological studies can impact the validity and reliability of findings. Without proper context, inferences (causal or otherwise) based on these findings may be compromised. The consequences of measurement error are well known, but in practice commonly ignored when interpreting findings in epidemiological research.
Methods: We examined papers published in 2022 in three leading epidemiology journals (International Journal of Epidemiology, Epidemiology, and American Journal of Epidemiology) to assess the occurrence and handling of exposure measurement error (EME). We randomly sampled 64 papers that assessed exposure-outcome relationships. Two authors independently reviewed the selected papers and searched for (a) explicit definition of the exposure in question and how it was measured, (b) an acknowledgment of the possibility of exposure measurement error and (c) statistical investigation of the expected impact or adjustment for EME.
Results: Our review of recent epidemiological studies reveals encouraging progress on the interpretation and adjustment of EME; however, room of improvement still exists. Among our sample of 64 articles, 2 (3.1%) articles reported exposures for which measurement error did not exist, 3 (4.7%) articles lacked a well-defined research question which precluded proper classification, 8 (12.5%) articles ignored EME, 24 (37.5%) reported on EME or discussed EME as a limitation but treated it as "negligible" without investigating further, 14 (21.9%) articles conducted sensitivity analyses to describe the potential effect EME may have on the studies and 8 (12.5%) articles attempted to quantitatively estimate the impact of EME on the reported risk estimate. Further, 8 (12.5%) articles erroneously claimed that EME would bias risk estimates towards the null (2 of which were also included above).
Conclusions: Modern epidemiological research shows improved handling and interpretation of EME, while some concerns persist. For instance, the epidemiological literature indicates that it is still resistant to adoption of state-of-the-art methods for managing measurement errors. We recommend that the practice of qualitatively discussing the impact of measurement error in exposure in epidemiology be replaced with modern developments in statistics and comprehensively accounted for.
(© 2025. The Author(s).)

Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests. Not applicable.