The prevalence of fatigue, sleepiness, and sleep disorders among petrochemical employees in Iran

Choobineh, Alireza; Javadpour, Fouzieh; Azmoon, Hiva; Keshavarzi, Sareh; Daneshmandi, Hadi

doi:10.1080/21641846.2018.1461252

Cited by 9 publications

(8 citation statements)

References 28 publications

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“…In our study, long-term and momentary fatigue differed between the two groups simultaneously. Although substantial research has been conducted among occupational groups for better understanding of long-term fatigue and poor sleep [43], very few studies have explored both types of fatigue in relation to sleep health [17,44] similar to our study. Andrei et al [17] found that both accumulated and temporary fatigue were simultaneously associated with the poor quality of sleep in maritime workers.…”

Section: Discussionsupporting

confidence: 63%

Factors Associated with Poor Quality of Sleep in Construction Workers: A Secondary Data Analysis

Kim

Lee

Lim

et al. 2021

IJERPH

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This study aimed to explore factors associated with poor quality of sleep in construction workers. This study was cross-sectional, correlational in design and used secondary data from fatigue instrument development study. We analyzed the data from 206 participants aged over 19 years who worked at construction sites for more than 6 months. We used multivariate binary logistic regression to identify the factors associated with poor quality of sleep. We classified the two sleep quality groups based on the Pittsburgh Sleep Quality Index (PSQI) score, and almost 63% of them were classified as the poor quality of sleep group. Based on multivariate binary logistic regression (Cox and Snell R2 = 0.317, Nagelkerke R2 = 0.429), the poor quality of sleep group tended to sleep for a shorter duration before the working day, and not only showed lower sleep latency and higher levels of daytime dysfunction and discomfort in daily life, but also had more chronic disease, depressive symptoms, and higher physical fatigue. Our study findings support that there are many modifiable factors associated with poor sleep and a high rate of poor quality of sleep occurred in construction workers. Thus, clinicians should consider providing diverse options for applying interventions to ensure better sleep, fatigue management, and depression prevention in construction workers after considering their unique characteristics.

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Section: Discussionsupporting

confidence: 63%

Factors Associated with Poor Quality of Sleep in Construction Workers: A Secondary Data Analysis

Kim

Lee

Lim

et al. 2021

IJERPH

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“…It is estimated that 35% of employees in the EU (Eurofound, 2017) and 38% in the USA (Ricci et al, 2007) are affected by fatigue associated with work. Similar issues exist in Eastern countries (Yun et al, 2008;Guo et al, 2017;Kachi et al, 2020) and developing countries (Sabir and Isha, 2016;Krishnamurthy et al, 2017;Choobineh et al, 2018). The consequences of occupational fatigue are highly relevant, affecting employees' psychological and physical health (Rose et al, 2017;Lock et al, 2018), absenteeism from work (Sagherian et al, 2019), organizational productivity (Reynolds et al, 2004;Rosekind et al, 2010), and safety concerns (Techera et al, 2016).…”

Section: Introductionmentioning

confidence: 91%

Occupational Fatigue: Relationship With Personality Traits and Decent Work

2021

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Psychology of working theory (PWT) and psychology of working framework (PWF) offered a psychological view of decent work. The present study examined the associations among personality traits, decent work and Occupational Fatigue Exhaustion Recovery Scale (OFER). Two hundred and thirty four participants filled out the Big Five Questionnaire, the Italian version of the Decent Work Scale, and the Italian version of the OFER Scale. Hierarchical regressions showed that decent work explained incremental variance beyond personality traits with respect to OFER both considering total score and its three dimensions (chronic fatigue, acute fatigue, persistent fatigue). The present study underlined the value of decent work in relation to occupational fatigue beyond the contributions of personality, in particular in relation to the dimensions of Adequate compensation and Free time and rest for less occupational fatigue (both as total and as dimensions).

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“…This methodology is unique as it is the first RCT study design involving 88 shift workers in a remote mining operation. It is designed and based on the results of the limited studies involving the sleep habits of shift workers and effective interventions ( Legault et al, 2017 ; Barger et al, 2018 ; Choobineh et al, 2018 ), along with our industry knowledge of mining operations and the impact of sleep loss on shift workers. Although it is not possible to predict the exact outcomes of this study, there are several anticipated results.…”

Section: Results (Anticipated)mentioning

confidence: 99%

The Sleep of Shift Workers in a Remote Mining Operation: Methodology for a Randomized Control Trial to Determine Evidence-Based Interventions

et al. 2021

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Shiftwork may adversely impact an individual’s sleep-wake patterns and result in sleep loss (<6 h. following night shift), due to the circadian misalignment and the design of rosters and shifts. Within a mining operation, this sleep loss may have significant consequences due to fatigue, including an increased risk of accidents and chronic health conditions. This study aims to (i) determine the efficacy of an intervention that comprises a sleep education program and biofeedback through a smartphone app on sleep quality, quantity, and alertness (ii) determine the prevalence of risk for a potential sleep disorder, and (iii) quantify and describe the sleep habits and behaviors of shift workers in a remote mining operation. This study consists of a randomized controlled trial whereby eighty-eight shift workers within a remote mining operation are randomized to a control group or one of three different treatment groups that are: (i) a sleep education program, (ii) biofeedback on sleep through a smartphone app, or (iii) a sleep education program and biofeedback on sleep through a smartphone app. This study utilizes wrist-activity monitors, biomathematical modeling, and a survey instrument to obtain data on sleep quantity, quality, and alertness. A variety of statistical methods will determine the prevalence of risk for a potential sleep disorder and associations with body mass index, alcohol, and caffeine consumption. A generalized linear mixed model will examine the dependent sleep variables assessed at baseline and post-intervention for the control group and intervention groups, as well as within and between groups to determine changes. The findings from this study will contribute to the current understanding of sleep and alertness behaviors, and sleep problems and disorders amongst shift workers. Importantly, the results may inform fatigue policy and practice on interventions to manage fatigue risk within the mining industry. This study protocol may have a broader application in other shiftwork industries, including oil and gas, aviation, rail, and healthcare.

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The prevalence of fatigue, sleepiness, and sleep disorders among petrochemical employees in Iran

Cited by 9 publications

References 28 publications

Factors Associated with Poor Quality of Sleep in Construction Workers: A Secondary Data Analysis

Factors Associated with Poor Quality of Sleep in Construction Workers: A Secondary Data Analysis

Occupational Fatigue: Relationship With Personality Traits and Decent Work

The Sleep of Shift Workers in a Remote Mining Operation: Methodology for a Randomized Control Trial to Determine Evidence-Based Interventions

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