Locke Sarah J, Colt Joanne S, Stewart Patricia A, Armenti Karla R, Baris Dalsu, Blair Aaron, Cerhan James R, Chow Wong-Ho, Cozen Wendy, Davis Faith, De Roos Anneclaire J, Hartge Patricia, Karagas Margaret R, Johnson Alison, Purdue Mark P, Rothman Nathaniel, Schwartz Kendra, Schwenn Molly, Severson Richard, Silverman Debra T, Friesen Melissa C
Occupational and Environmental Epidemiology, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA.
Stewart Exposure Assessments, LLC, Arlington, Virginia, USA.
Occup Environ Med. 2014 Dec;71(12):855-64. doi: 10.1136/oemed-2013-101801. Epub 2014 Mar 28.
Growing evidence suggests that gender-blind assessment of exposure may introduce exposure misclassification, but few studies have characterised gender differences across occupations and industries. We pooled control responses to job-specific, industry-specific and exposure-specific questionnaires (modules) that asked detailed questions about work activities from three US population-based case-control studies to examine gender differences in work tasks and their frequencies.
We calculated the ratio of female-to-male controls that completed each module. For four job modules (assembly worker, machinist, health professional, janitor/cleaner) and for subgroups of jobs that completed those modules, we evaluated gender differences in task prevalence and frequency using χ(2) and Mann-Whitney U tests, respectively.
The 1360 female and 2245 male controls reported 6033 and 12 083 jobs, respectively. Gender differences in female:male module completion ratios were observed for 39 of 45 modules completed by ≥20 controls. Gender differences in task prevalence varied in direction and magnitude. For example, female janitors were significantly more likely to polish furniture (79% vs 44%), while male janitors were more likely to strip floors (73% vs 50%). Women usually reported more time spent on tasks than men. For example, the median hours per week spent degreasing for production workers in product manufacturing industries was 6.3 for women and 3.0 for men.
Observed gender differences may reflect actual differences in tasks performed or differences in recall, reporting or perception, all of which contribute to exposure misclassification and impact relative risk estimates. Our findings reinforce the need to capture subject-specific information on work tasks.
越来越多的证据表明,对暴露进行无性别区分的评估可能会导致暴露误分类,但很少有研究描述不同职业和行业中的性别差异。我们汇总了针对特定工作、特定行业和特定暴露的问卷(模块)的对照回答,这些问卷询问了来自三项美国基于人群的病例对照研究中关于工作活动的详细问题,以研究工作任务及其频率方面的性别差异。
我们计算了完成每个模块的女性对照与男性对照的比例。对于四个工作模块(装配工人、机械师、卫生专业人员、门卫/清洁工)以及完成这些模块的工作子组,我们分别使用χ²检验和曼-惠特尼U检验评估了任务患病率和频率方面的性别差异。
1360名女性对照和2245名男性对照分别报告了6033个和12083个工作。在≥20名对照完成的45个模块中,有39个观察到女性与男性模块完成比例存在性别差异。任务患病率的性别差异在方向和程度上各不相同。例如,女性门卫擦拭家具的可能性显著更高(79%对44%),而男性门卫更有可能拖地(73%对50%)。女性通常报告在任务上花费的时间比男性更多。例如,产品制造业中生产工人每周脱脂的中位数小时数,女性为6.3小时,男性为3.0小时。
观察到的性别差异可能反映了所执行任务的实际差异,或者回忆、报告或认知方面的差异,所有这些都导致暴露误分类并影响相对风险估计。我们 的研究结果强化了获取关于工作任务的特定对象信息的必要性。