ORCID Profile
0000-0002-7153-4478
Current Organisations
Universiteit Utrecht
,
Drexel University School of Public Health
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Publisher: Oxford University Press (OUP)
Date: 03-02-2023
Abstract: Automatic job coding tools were developed to reduce the laborious task of manually assigning job codes based on free-text job descriptions in census and survey data sources, including large occupational health studies. The objective of this study is to provide a case study of comparative performance of job coding and JEM (Job-Exposure Matrix)-assigned exposures agreement using existing coding tools. We compared three automatic job coding tools [AUTONOC, CASCOT (Computer-Assisted Structured Coding Tool), and LabourR], which were selected based on availability, coding of English free-text into coding systems closely related to the 1988 version of the International Standard Classification of Occupations (ISCO-88), and capability to perform batch coding. We used manually coded job histories from the AsiaLymph case-control study that were translated into English prior to auto-coding to assess their performance. We applied two general population JEMs to assess agreement at exposure level. Percent agreement and PABAK (Prevalence-Adjusted Bias-Adjusted Kappa) were used to compare the agreement of results from manual coders and automatic coding tools. The coding per cent agreement among the three tools ranged from 17.7 to 26.0% for exact matches at the most detailed 4-digit ISCO-88 level. The agreement was better at a more general level of job coding (e.g. 43.8–58.1% in 1-digit ISCO-88), and in exposure assignments (median values of PABAK coefficient ranging 0.69–0.78 across 12 JEM-assigned exposures). Based on our testing data, CASCOT was found to outperform others in terms of better agreement in both job coding (26% 4-digit agreement) and exposure assignment (median kappa 0.61). In this study, we observed that agreement on job coding was generally low for the three tools but noted a higher degree of agreement in assigned exposures. The results indicate the need for study-specific evaluations prior to their automatic use in general population studies, as well as improvements in the evaluated automatic coding tools.
Publisher: Oxford University Press (OUP)
Date: 24-04-2009
DOI: 10.1093/NTR/NTP048
Abstract: Our main objective was to estimate smoking prevalence as well as sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of self-reported smoking among pregnant women in Edmonton, Canada, at 15-16 weeks of gestation. We used serum s les to assemble a cohort of pregnant women who underwent an optional second-trimester screening for chromosomal and developmental anomalies. We determined cotinine concentrations for 92 self-reported smokers (11% of the cohort) and for 285 self-reported nonsmoking mothers, using adapted urinary cotinine assay. Self-reports were collected at the time of delivery. In a validation study, serum cotinine was determined for known smokers and nonsmokers and used, within a Bayesian statistical framework, to define the distribution of cutoffs that differentiate true smokers from nonsmokers. This distribution of cutoffs was used to construct multiple two-by-two tables to obtain the distribution of sensitivity, specificity, PPV, NPV, and prevalence. Sensitivity was poor (M = 47.4%, SD = 17.3%), but specificity was nearly perfect (M = 94.9%, SD = 1.1%). PPV (M = 66.6%, SD = 11.7%) was smaller than NPV (M = 84.7%, SD = 14.3%). In our s le, the prevalence of true smoking at 15-16 weeks of gestation was described by a skewed distribution with a mean of 21.6% (SD = 13.8%) and a median of 16.6%. The strength of the present study includes blinding of subjects to the intention to test their sera for a biomarker of smoking. A limitation was the use of a nonrandom s le restricted to pregnancies that resulted in live births. We discuss data collection methods that would elicit more accurate smoking histories from pregnant women.
Publisher: Springer Science and Business Media LLC
Date: 03-2010
DOI: 10.1007/BF03404362
Publisher: Springer Science and Business Media LLC
Date: 31-01-2017
Publisher: Wiley
Date: 11-2009
DOI: 10.1002/AJIM.20753
Abstract: Although occupational asthma is a well recognized and preventable disease, the numbers of cases presenting for compensation may be far lower than the true incidence. Workers' Compensation Board (WCB) claims for any reason 1995-2004 were linked to physician billing data. New onset adult asthma (NOAA) was defined as a billing for asthma (ICD-9 code of 493) in the 12 months prior to a WCB claim without asthma in the previous 3 years. Incidence was calculated by occupation, industry and, in a case-referent analysis, exposures estimated from an asthma specific job exposure matrix. There were 782,908 WCB eligible claims, with an incidence rate for NOAA of 1.6%: 23 occupations and 21 industries had a significantly increased risk. Isocyanates (OR 1.54: 95% CI 1.01-2.36) and exposure to mixed agricultural allergens (OR = 1.59: 95% CI 1.17-2.18) were related to NOAA overall, as were exposures to cleaning chemicals in men (OR = 1.91:95% CI 1.34-2.73). Estimates of the number of cases of occupational asthma suggested a range of 4% to about half for the proportion compensated. Data linkage of administrative records can demonstrate under-reporting of occupational asthma and indicate areas for prevention.
Location: United States of America
No related grants have been discovered for Igor Burstyn.