Associations between conditions of work and worker health and productivity indicators in small manufacturing companies.
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2017/06/07
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English
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Description:Statement of the Problem: In recent years we have seen the emergence of interventions aimed at simultaneously protecting and promoting both worker health and worker safety. Much of this work has been guided by the National Institute for Occupational Safety and Health's Total Worker Health® program. As a Center for Excellence within the TWH Program, the Center for Work, Health and Well-being (CWHW) at the Harvard T.H. Chan School of Public Health has developed a conceptual model to specify the causal pathways through which policies, programs and practices are expected to influence worker safety and health outcomes. The present research seeks to build on the conceptual model, by exploring associations between conditions of work as measured by organizational safety and health climates and worker outcomes including health behaviors and productivity measures. Procedures: Data used in this research were obtained as part of a pilot intervention study disseminating the CWHW's approach as outlined in the CWHW's SafeWell Guidelines. Participating companies included three small-to-medium size manufacturing companies in Minneapolis during the years 2014-15. As part of the study, employees at the participating companies completed a baseline health risk assessment in 2014 (n=959; 53% response rate). The overarching aim of this study was to examine associations among variables specified as part of the conceptual model. Three aims were identified: Specific Aim (1) Test the association between organizational safety and health climates and worker health behaviors. Behaviors included: physical activity, diet, tobacco use, sleep and alcohol use. Specific Aim (2) Test the association between organizational safety and health climates and physical abuse, emotional abuse, depression, job satisfaction, life satisfaction, back pain (frequency and severity), and self-perceived general health. Specific Aim (3) Test the association between organizational safety and health climates and two different productivity indicators: Work Limitations Questionnaire (WLQ) and Work Productivity and Activity Impairment Scale (WPAI). Analyses: The independent variables of interest, organizational health and safety climates, were originally coded from 0 to 10, with 10 being a strong health or safety climate. Both climate variables were coded as binary for the analyses, with 0 = weaker climate and 1 = stronger climate. Dependent variables were also expressed as binary variables. Physical activity, nutrition, sleep, satisfaction (job and life) and general health were coded with 1 being the optimal state. Tobacco, alcohol, abuse (physical and emotional), back pain (frequency and severity) and depression were coded with 0 as the optimal state. A series of logistic regression models were conducted corresponding to each of the specific aims. A two-step approach to modeling was used. Initial bivariate models tested relationship between the independent and dependent variables alone. When initial models demonstrated significant effects, full models were analyzed including covariates. Full models were adjusted for age, gender, education and job type. Results: Aim 1: Of the five worker health behaviors considered, sleep was the only variable for which significant relationships were found (OR= 1.82; 95%CI=1.35-2.45). In other words, the odds of someone reporting optimal sleep are 1.82 times higher for those who report a report strong worksite climate of safety. Sleep was also found to relate to worker perception of health and well-being climate (OR= 1.32; 95%CI=0.99-1.76), though marginally not at a statistically significant level (p=.058). Aim 2: Of the eight worker outcome variables considered, nearly all were associated with both worker perception variables (safety climate, health climate). Though no effects were identified for physical and emotional abuse outcomes, both perception of climate variables were related to depression, job satisfaction, life satisfaction, back pain (frequency and severity) and self-perceived general health. Aim 3: Two different indicators of productivity were considered for measuring Aim 3. Using the WPAI we found that the odds that a worker will be more productive are higher for those who report a strong culture of worksite safety (OR= .54; 95%CI=0.39-0.75) and culture of well-being (OR=.49; 95%CI=0.36-0.68). The WLQ was not associated with either climate variable. Practical implications and conclusions: This research demonstrated many of the linkages outlined in CWHW's conceptual model, giving further support to outcomes related to working conditions. We have shown that conditions of the worksite, specifically worker-perceived safety and health climates, are associated with health behaviors such as sleep, outcomes related to emotional and overall health, satisfaction, back pain, as well as worker productivity. All of the worker outcomes we considered are burdensome for the employee and costly for the employer. Worksite interventions that are coordinated and integrated across safety and health teams, policies and processes, may hold the most promise for promoting strong safety and health climates at the worksite. [Description provided by NIOSH]
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Pages in Document:1-2
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NIOSHTIC Number:nn:20065662 ; nn:20065664
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Citation:Work, Stress and Health 2017: Contemporary Challenges and Opportunities, The 12th International Conference on Occupational Stress and Health, June 7-10, 2017, Minneapolis, Minnesota. Washington, DC: American Psychological Association, 2017 Jun; :1-2
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Federal Fiscal Year:2017
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Performing Organization:Harvard University, Boston, Massachusetts
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Peer Reviewed:False
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Start Date:20070901
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Source Full Name:Work, Stress and Health 2017: Contemporary Challenges and Opportunities, The 12th International Conference on Occupational Stress and Health, June 7-10, 2017, Minneapolis, Minnesota
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End Date:20260831
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Main Document Checksum:urn:sha-512:f5b8b59ae0169bbae2ddef19be1c9e7ff54edf73a12e7e31dd6a59813bdd0eb272e7a4abcc458dbc3db420950021731a48a7b731febf1e8037cef9d64c16e4c5
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English
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