Literature DB >> 17053019

Bias in occupational epidemiology studies.

Neil Pearce1, Harvey Checkoway, David Kriebel.   

Abstract

The design of occupational epidemiology studies should be based on the need to minimise random and systematic error. The latter is the focus of this paper, and includes selection bias, information bias and confounding. Selection bias can be minimised by obtaining a high response rate (and by appropriate selection of the control group in a case-control study). In general, it is important to ensure that information bias is minimised and is also non-differential (for example, that the misclassification of exposure is not related to disease status) by collecting data in a standardised manner. A major concern in occupational epidemiology studies usually relates to confounding, because exposure has not been randomly allocated, and the groups under study may therefore have different baseline disease risks. For each of these types of bias, the goal should be to avoid the bias by appropriate study design and/or appropriate control in the analysis. However, it is also important to attempt to assess the likely direction and strength of biases that cannot be avoided or controlled.

Mesh:

Year:  2006        PMID: 17053019      PMCID: PMC2078501          DOI: 10.1136/oem.2006.026690

Source DB:  PubMed          Journal:  Occup Environ Med        ISSN: 1351-0711            Impact factor:   4.402


  40 in total

1.  Fallibility in estimating direct effects.

Authors:  Stephen R Cole; Miguel A Hernán
Journal:  Int J Epidemiol       Date:  2002-02       Impact factor: 7.196

2.  Does nondifferential misclassification of exposure always bias a true effect toward the null value?

Authors:  M Dosemeci; S Wacholder; J H Lubin
Journal:  Am J Epidemiol       Date:  1990-10       Impact factor: 4.897

3.  A strategy to reduce healthy worker effect in a cross-sectional study of asthma and metalworking fluids.

Authors:  E A Eisen; C A Holcroft; I A Greaves; D H Wegman; S R Woskie; R R Monson
Journal:  Am J Ind Med       Date:  1997-06       Impact factor: 2.214

Review 4.  Confounding from smoking in occupational epidemiology.

Authors:  O Axelson
Journal:  Br J Ind Med       Date:  1989-08

5.  Identifiability, exchangeability, and epidemiological confounding.

Authors:  S Greenland; J M Robins
Journal:  Int J Epidemiol       Date:  1986-09       Impact factor: 7.196

6.  Toward a clearer definition of confounding.

Authors:  C R Weinberg
Journal:  Am J Epidemiol       Date:  1993-01-01       Impact factor: 4.897

Review 7.  Exposure measurement error: influence on exposure-disease. Relationships and methods of correction.

Authors:  D Thomas; D Stram; J Dwyer
Journal:  Annu Rev Public Health       Date:  1993       Impact factor: 21.981

8.  Assessing the possible extent of confounding in occupational case-referent studies.

Authors:  H Checkoway; G T Waldman
Journal:  Scand J Work Environ Health       Date:  1985-04       Impact factor: 5.024

9.  Correcting for misclassification in two-way tables and matched-pair studies.

Authors:  S Greenland; D G Kleinbaum
Journal:  Int J Epidemiol       Date:  1983-03       Impact factor: 7.196

10.  Aspects on confounding in occupational health epidemiology.

Authors: 
Journal:  Scand J Work Environ Health       Date:  1978-03       Impact factor: 5.024

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  95 in total

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2.  Healthy worker survivor bias in the Colorado Plateau uranium miners cohort.

Authors:  Alexander P Keil; David B Richardson; Melissa A Troester
Journal:  Am J Epidemiol       Date:  2015-04-01       Impact factor: 4.897

3.  What characterizes cleaners sustaining good musculoskeletal health after years with physically heavy work?

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Journal:  Int Arch Occup Environ Health       Date:  2009-02-08       Impact factor: 3.015

Review 4.  Lack of association between occupational exposure to diesel exhaust and risk of pancreatic cancer: a systematic evaluation of available data.

Authors:  Paolo Boffetta
Journal:  Int Arch Occup Environ Health       Date:  2013-07-13       Impact factor: 3.015

5.  Low-dose ionizing radiation increases the mortality risk of solid cancers in nuclear industry workers: A meta-analysis.

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Journal:  Mol Clin Oncol       Date:  2018-03-19

6.  The impact of different approaches to exposure assessment on understanding non-malignant respiratory disease risk in taconite miners.

Authors:  Nnaemeka U Odo; Jeffrey H Mandel; Bruce H Alexander; David M Perlman; Richard F MacLehose; Gurumurthy Ramachandran; Andrew D Ryan; Yuan Shao
Journal:  Int Arch Occup Environ Health       Date:  2019-08-01       Impact factor: 3.015

7.  Occupational kneeling and radiographic tibiofemoral and patellofemoral osteoarthritis.

Authors:  Søren Rytter; Niels Egund; Lilli Kirkeskov Jensen; Jens Peter Bonde
Journal:  J Occup Med Toxicol       Date:  2009-07-13       Impact factor: 2.646

8.  Self-perceived stress reactivity is an indicator of psychosocial impairment at the workplace.

Authors:  Heribert Limm; Peter Angerer; Mechthild Heinmueller; Birgitt Marten-Mittag; Urs M Nater; Harald Guendel
Journal:  BMC Public Health       Date:  2010-05-14       Impact factor: 3.295

9.  Effects of particulate matter on genomic DNA methylation content and iNOS promoter methylation.

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Journal:  Environ Health Perspect       Date:  2008-09-26       Impact factor: 9.031

10.  Exposure to metal-rich particulate matter modifies the expression of candidate microRNAs in peripheral blood leukocytes.

Authors:  Valentina Bollati; Barbara Marinelli; Pietro Apostoli; Matteo Bonzini; Francesco Nordio; Mirjam Hoxha; Valeria Pegoraro; Valeria Motta; Letizia Tarantini; Laura Cantone; Joel Schwartz; Pier Alberto Bertazzi; Andrea Baccarelli
Journal:  Environ Health Perspect       Date:  2010-01-08       Impact factor: 9.031

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