Exposure Response Relationships for CTS and Epicondylitis from Pooled Data

描述(由申请人提供)：拟议的研究提供了一个独特的机会，可以提供测量的职业生物力学应激源、非职业性体力活动、人口统计学、病史、心理社会因素与腕管综合征(CTS)、外上髁炎(LEPI)和内侧上髁炎(MEPI)风险之间的暴露反应评估。三项前瞻性队列研究将汇集美国35个工作场所的数据，代表广泛的职业、行业和身体暴露水平。共招募了1,973名员工，对1,698名员工进行了长达110个月的跟踪调查(平均随访时间为34个月)。关于每个工人的生物力学应激源，体检动作，以及手腕的正中神经和尺神经传导研究，都有全面的数据。将评估生物力学应激源与CTS、LEPI和MEPI的患病率和发生率之间的暴露-反应关系，同时调整相关的效应调节剂和混杂因素。本研究中使用的生物力学应力源的测量方法包括建立的手部活动水平(HAL)的ACGIH阈值(TLV)模型和1995年的应变指数(SI)，以及新发展的模型：(I)修正应变指数(RevSI)，(Ii)综合应变指数(COSI)，和(Iii)累积应变指数(CUSI)。来自这些研究的综合身体暴露数据的特点是：(I)个体工人暴露随时间的变化，以及(Ii)每个力量、重复和姿势组合的详细数据(子任务数据)。这些数据使我们能够对生物力学应激源进行详细的建模，这是以前使用REVSI、COSI和CUSI等创新方法所不可能的。这三个网站都有关于潜在混杂因素和协变量的全面数据，包括工人人口统计数据、过去的病史、非职业爱好和活动以及心理社会因素。所有网站都使用了CTS、LEPI和MEPI的匹配病例定义，其中包括症状加上物理动作和神经传导研究。汇集三项研究的现有数据将使我们能够估计更广泛的生物力学应激源的相对风险函数的大小和形状：(I)以更高的置信度和精确度，(Ii)对于轮换工作的工人，以及(Iii)对于具有多种力、重复、 和姿势。这项拟议研究的结果将帮助雇主设计安全和生产性的工作，并为公共卫生机构和职业卫生研究人员提供信息，以更有效地指导预防计划。

DESCRIPTION (provided by applicant): The proposed research offers a unique opportunity to provide exposure-response estimates between measured occupational biomechanical stressors, non-occupational physical activities, demographics, medical history, psychosocial factors; and risk of carpal tunnel syndrome (CTS), lateral epicondylitis (LEPI), and medial epicondylitis (MEPI). Three prospective cohort studies will pool data from 35 US workplaces, representing a wide range of occupations, industries, and physical exposure levels. 1,973 employees were enrolled and 1,698 were followed for up to 110 months (average follow-up = 34 months). Comprehensive data are available on each worker's biomechanical stressors, physical examination maneuvers, and median and ulnar nerve conduction studies at the wrist. Exposure-response relationships will be estimated between biomechanical stressors and the prevalence and incidence of: CTS, LEPI, and MEPI, while adjusting for relevant effect modifiers and confounders. Measures of biomechanical stressors used in this study include established models of ACGIH Threshold Limit Value (TLV) for Hand Activity Level (HAL), and the 1995 Strain Index (SI), as well as newly developed models: (i) Revised Strain Index (RevSI), (ii) Composite Strain Index (COSI), and (iii) Cumulative Strain Index (CUSI). Comprehensive physical exposure data from these studies feature: (i) individual worker exposure with changes in exposure over time, and (ii) detailed data for each combination of force, repetition, and posture (sub-task data). These data allow us to model biomechanical stressors in detail not previously possible using innovative approaches such as RevSI, COSI, and CUSI. The three sites all have comprehensive data on potential confounders and covariates including worker demographics, past medical history, non-occupational hobbies and activities, and psychosocial factors. All sites used matching case definitions for CTS, LEPI, and MEPI that included symptoms plus physical maneuvers and nerve conduction studies. Pooling existing data across the three studies will enable us to estimate the magnitude and shape of the relative risk function across a wider range of biomechanical stressors: (i) with improved confidence and precision, (ii) for workers with job rotation, and (iii) for tasks with multiple combinations of force, repetition, and posture. Results from this proposed research will help employers to design safe and productive jobs and provide public-health agencies and occupational health researchers with information to more effectively guide prevention programs.