Publications by authors named "Taylor M Shockey"

Objective: To assess the prevalence of diagnosed diabetes among employed US adults from 36 states by occupation group using data from 2014 to 2018 Behavioral Risk Factor Surveillance System.

Methods: Prevalence of diabetes was calculated by 22 broad and 93 detailed occupation groups among a sample of 366,633 employed respondents. Wald chi-square values were used to determine the significance of associations between diabetes and occupation groups after adjusting for sex, age, and race/ethnicity.

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Excessive alcohol use, including binge drinking (i.e., ≥5 drinks (males); ≥4 drinks (females), per occasion during the past 30 days), is associated with work-related injuries, absenteeism, and lost productivity.

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Introduction: Workers' compensation (WC) insurers offer services and programs for prospective client selection and insured client risk control (RC) purposes. Toward these aims, insurers collect employer data that may include information on types of hazards present in the workplace, safety and health programs and controls in place to prevent injury/illness, and return-to-work programs to reduce injury/illness severity. Despite the potential impact of RC systems on workplace safety and health and the use of RC data in guiding prevention efforts, few research studies on the types of RC services provided to employers or the RC data collected have been published in the peer-reviewed literature.

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Workers' compensation (WC) insurers collect large amounts of industrial hygiene (IH) data in the United States. The data collected is not easily accessible for research or surveillance purposes. Individual WC insurers are using computerized systems to standardize and store the IH data, leaving a gap in standardization among the different WC insurers.

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Despite substantial financial and personnel resources being devoted to occupational exposure monitoring (OEM) by employers, workers' compensation insurers, and other organizations, the United States (U.S.) lacks comprehensive occupational exposure databases to use for research and surveillance activities.

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Repeated exposure to occupational ergonomic hazards, such as frequent exertion (repetitive bending or twisting) and frequent standing, can lead to injuries, most commonly musculoskeletal disorders (1). Work-related musculoskeletal disorders have been estimated to cost the United States approximately $2.6 billion in annual direct and indirect costs (2).

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Objectives: To examine the health-related quality of life among workers in 22 standard occupation groups using data from the 2013-2014 US Behavioral Risk Factor Surveillance System.

Methods: We examined the health-related quality of life measures of self-rated health, frequent physical distress, frequent mental distress, frequent activity limitation, and frequent overall unhealthy days by occupation group for 155 839 currently employed adults among 17 states. We performed multiple logistic regression analyses that accounted for the Behavioral Risk Factor Surveillance System's complex survey design to obtain prevalence estimates adjusted for potential confounders.

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The American Academy of Sleep Medicine and the Sleep Research Society have determined that adults require ≥7 hours of sleep per day to promote optimal health (1). Short sleep duration (<7 hours per day) has been linked to adverse health outcomes including cardiovascular disease, obesity, diabetes, depression, and anxiety, as well as safety issues related to drowsy driving and injuries (1,2). Additional research has found that sleep duration varies by characteristics such as race, education, marital status, obesity, and cigarette smoking (3).

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Cardiovascular disease (CVD) accounts for one of every three deaths in the United States, making it the leading cause of mortality in the country (1). The American Heart Association established seven ideal cardiovascular health behaviors or modifiable factors to improve CVD outcomes in the United States. These cardiovascular health metrics (CHMs) are 1) not smoking, 2) being physically active, 3) having normal blood pressure, 4) having normal blood glucose, 5) being of normal weight, 6) having normal cholesterol levels, and 7) eating a healthy diet (2).

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