ABSTRACT
IntroductionOne of the principal challenges in community-based occupational studies is retrospective assessment of exposure. Job-exposure-matrices (JEMs) have been proposed as a cost-effective tool. However, most JEMs are built from the assessment of jobs held by men, with few studies assessing the applicability of those JEMs to the same jobs when held by women.ObjectiveTo compare within-occupation exposure assessments for jobs held by men versus women in a Canadian JEM (CANJEM).MethodTwo sex-specific JEMs were created using data from CANJEM, a JEM based on the expert assessment of exposure to 258 chemicals in >30,000 jobs held during 1933–2005, by participants in five Montreal-based case-control studies. Each cell in the JEMs provided the probability, intensity, frequency, and frequency-weighted intensity (FWI) of exposure to a selected occupational agent, for a specific combination of a 4-digit Canadian Classification and Dictionary of Occupations code and one of four time periods. We used intra-class correlation coefficients (ICC) to compare the probability, frequency and FWI between cells considered exposed in the two JEMs;‘exposed’ cells were defined by probability ≥ 5%. Given the semi-quantitative nature of intensity, Kendall’s Tau (τ) was used. We further compared differences between the JEMs using empirical cumulative distribution functions (ECDF).ResultsIn total, 1,488 cells considered exposed in both JEMs were included in the analysis. ICC (95% confidence interval) of 0.58 (0.55–0.61), 0.55 (0.52–0.58) and 0.12 (0.07–0.17) were found for probability, frequency and FWI of exposure, respectively. For intensity, a τ of 0.24 (0.20–0.29) was found. The ECDFs showed a tendency for frequency to be higher in the female-JEM, but for intensity and FWI to be higher in the male-JEM. No clear trend was observed for probability of exposure.ConclusionOur results suggest that CANJEM assessment of jobs held by men was inadequate to estimate exposure in women’s.
ABSTRACT
Owing to the rapidly evolving coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, quick public health investigations of the relationships between behaviors and infection risk are essential. Recently the test-negative design (TND) was proposed to recruit and survey participants who are symptomatic and being tested for SARS-CoV-2 infection with the goal of evaluating associations between the survey responses (including behaviors and environment) and testing positive on the test. It was also proposed to recruit additional controls who are part of the general population as a baseline comparison group to evaluate risk factors specific to SARS-CoV-2 infection. In this study, we consider an alternative design where we recruit among all individuals, symptomatic and asymptomatic, being tested for the virus in addition to population controls. We define a regression parameter related to a prospective risk factor analysis and investigate its identifiability under the two study designs. We review the difference between the prospective risk factor parameter and the parameter targeted in the typical TND where only symptomatic and tested people are recruited. Using missing data directed acyclic graphs, we provide conditions and required data collection under which identifiability of the prospective risk factor parameter is possible and compare the benefits and limitations of the alternative study designs and target parameters. We propose a novel inverse probability weighting estimator and demonstrate the performance of this estimator through simulation study.