Identifying gender differences in reported occupational information from three US population-based case-control studies.

Identifying gender differences in reported occupational information from three US population-based case-control studies.
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DOI:
10.1136/oemed-2013-101801
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发表时间:
2014-12
影响因子:
4.9
通讯作者:
Friesen MC
Friesen MC
中科院分区:
医学2区
文献类型:
--
作者:
Locke SJ;Colt JS;Stewart PA;Armenti KR;Baris D;Blair A;Cerhan JR;Chow WH;Cozen W;Davis F;De Roos AJ;Hartge P;Karagas MR;Johnson A;Purdue MP;Rothman N;Schwartz K;Schwenn M;Severson R;Silverman DT;Friesen MC

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越来越多的证据表明,不考虑性别因素的暴露评估可能会导致暴露错误分类,但很少有研究表明不同职业和行业的性别差异。我们汇总了对工作、行业和职业特定问卷(模块)的控制反应,这些问卷询问了三项基于美国人群的病例对照研究中有关工作活动的详细问题,以研究工作任务及其频率的性别差异。我们计算了完成每个模块的女性与男性对照的比例。对于四个工作模块(装配工人,机械师,卫生专业人员,看门人/清洁工)和完成这些模块的工作的亚组,我们分别使用卡方和Mann-Whitney U检验评估了任务流行率和频率的性别差异。1,360名女性和2,245名男性对照组分别报告了6,033和12,083份工作。在由≥20名对照完成的45个模块中,观察到39个模块的男女模块完成率存在性别差异。任务流行率的性别差异在方向和程度上各不相同。例如,女性清洁工更有可能抛光家具(79%对44%),而男性清洁工更有可能剥离地板(73%对50%)。据报告,妇女通常比男子花更多的时间在任务上。例如,产品制造业生产工人每周平均工作时间为妇女6.3小时,男子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回忆、报告或感知的差异,所有这些都会导致暴露错误分类并影响相对风险估计。我们的研究结果加强了需要捕捉特定主题的工作任务的信息。
Growing evidence suggests that gender-blind assessment of exposure may introduce exposure misclassification, but few studies have characterized gender differences across occupations and industries. We pooled control responses to job-, industry-, 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 Chi-square and Mann-Whitney U-tests, respectively. The 1,360 female and 2,245 male controls reported 6,033 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.
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