Exploring Health Promotion Behaviors, Occupational Burnout, and Sleep Disturbances in Traditional Industry Workers

doi:10.21203/rs.3.rs-4761931/v1

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Research Article

Exploring Health Promotion Behaviors, Occupational Burnout, and Sleep Disturbances in Traditional Industry Workers

https://doi.org/10.21203/rs.3.rs-4761931/v1

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Background

Sleep disturbances can lead to poor job performance, increased work stress and absenteeism, and reduced job satisfaction and confidence among employees. Traditional industry employees experience significantly higher shift work and occupational burnout levels than other sectors. Therefore, this warrants exploring whether shift work, occupational burnout, and health promotion behavior are related to sleep disturbances among traditional industry employees.

Methods

A cross-sectional study with cluster sampling and structured questionnaires was conducted to collect data on the demographics, health promotion behavior, occupational burnout, and sleep disturbances of 365 employees from a traditional industry in Northern Taiwan. The study period was from 15 May 2023 to 17 June 2023. Data analysis was performed using Chi-square tests, independent sample t-tests, and logistic regression.

Results

The prevalence of sleep disturbances among the study subjects was 47.9%, with shift workers accounting for 63.3%. The mean score for the overall health promotion behavior scale was 2.34 ± 0.48, and the mean score for the overall occupational burnout scale was 1.96 ± 1.09. Factors associated with sleep disturbances included shift work, weekly working hours, health promotion behavior, and personal burnout.

Conclusion

We recommend adjusting the regularity of shift schedules and enhancing the lighting environment during night shifts to accommodate shift work, avoiding weekly working hours exceeding 40 hours, improving personal burnout levels, and encouraging the adoption of health-responsible behaviors to reduce sleep disturbances.

Traditional industries

health promotion behavior

occupational burnout

sleep disturbances

Sleep disturbances are one of the most common complaints among patients seeking medical care, with insomnia being the most prevalent type [1]. Sleep disturbances increase employees' feelings of stress and job insecurity and reduce job satisfaction and confidence [2], leading to poor job performance [3, 4]. Additionally, absenteeism rates rise by 16–17% [5]. A study that included 22,330 adults from 13 countries across four continents found an overall prevalence of sleep disturbances of 36.7% [6]. However, with the rapid global spread of the novel coronavirus (COVID-19) in 2019, people faced unprecedented health threats and lifestyle restrictions, causing the incidence of sleep disturbances to rise to 40.5% [7]. Therefore, the issue of sleep disturbances in current times is of significant concern.

According to statistics from the Directorate General of Budget, Accounting, and Statistics, Executive Yuan, R.O.C., the population employed in the manufacturing sector in March 2024 was approximately 2.993 million, accounting for 25.84% of the total labor force [8]. Previous studies on sleep disturbances among traditional industry workers found a prevalence of 22.6% among electronic product manufacturer workers in China [9], 35.3% and 42.0% among steel factory workers in China [10, 11], 16.7% among textile workers in China [12], 4.5% among manufacturing workers in South Korea [13], 33.2% among construction workers in India [14], and 36.5% among construction and civil engineering workers in Japan [3]. The prevalence of sleep disturbances among traditional industry workers in these countries varies significantly. However, there is currently no data on the prevalence of sleep disturbances among traditional industry workers in Taiwan.

Factors influencing sleep disturbances among workplace employees can be broadly categorized into personal background factors, work patterns, occupational burnout, and health promotion behavior. Factors associated with sleep disturbances include being female, age [15, 16, 17], smoking habits [15, 16], lower educational level, alcohol consumption, a higher number of chronic illnesses [11, 18, 19], and sleeping ≤ 6 hours per day [18, 20].

In terms of work patterns, factors such as shift work, higher work stress [11, 18, 21, 22]., excessive job involvement [9], shorter daily rest periods [23, 24], and working more than 40 hours per week [19, 20, 25] are associated with a higher likelihood of sleep disturbances. Many industries implement shift work to increase productivity and reduce downtime [26]. Since traditional manufacturing industry employees often work in shifts, the probability of sleep disturbances is expected to be higher.

The highly competitive pressure in global industries leads to occupational burnout [27], also known as occupational exhaustion. Its impacts include insomnia, depression, job dissatisfaction, increased absenteeism, and disability benefits [28, 29]. Occupational burnout is considered a crisis in modern society and life [30]. Both occupational burnout and sleep disturbances are significant policy issues in many countries, with higher occupational burnout associated with a greater likelihood of sleep disturbances [31, 32]. Xinjie [33] concluded that burnout among frozen food packaging workers increases the severity of sleep disturbances. Treating employees' sleep disturbances can enhance productivity and reduce occupational burnout [34]. Research on sleep disturbances and occupational burnout has mostly focused on physicians, teachers, police and firefighters, nurses, and tech workers [35, 36, 37, 38, 39].

Health promotion is the process of enabling people to increase control over and improve their health. Common behaviors used in health promotion include health responsibility, proper nutrition, stress management, self-actualization, exercise and leisure, and interpersonal support [40]. Adult health behaviors (AHBs) include stress management, exercise, health responsibility, life appreciation, healthy diet, and oral hygiene. This study found that these six behaviors are significantly correlated with life satisfaction, concluding that they can identify poor health behaviors in adults earlier than previous research [41]. Numerous studies have confirmed the correlation between health promotion behaviors and sleep disturbances, identifying health promotion behaviors as a major factor influencing sleep disturbances [42]. For instance, whole grain and Mediterranean diets are protective factors against sleep disturbances [17, 43]. Conversely, insufficient physical activity [16] and sedentary behavior [44] increase the likelihood of sleep disturbances [42]. Sleep disturbances can deplete physical energy and reduce time spent on physical activities after work and those with severe sleep disturbances engage in less high-intensity physical activity [45, 46, 47]. Therefore, a vicious cycle may arise between sleep disturbances and unhealthy lifestyles [45], leading to increasingly severe sleep disturbances.

Manufacturing is a major industry in many countries, and previous research on manufacturing employees has primarily focused on the health hazards of occupational exposure [48]. However, studies on sleep disturbances among traditional manufacturing industry employees in Taiwan are notably lacking. Moreover, research on the relationship between health promotion behaviors, occupational burnout, and sleep disturbances is even more scarce, warranting attention and further exploration. Therefore, this study aims to investigate the correlation between health promotion behaviors, occupational burnout, and sleep disturbances among employees in traditional industries.

Research design

This is a cross-sectional research study that utilizes structured questionnaires to collect data. It aims to explore the relationships between health promotion behaviors, occupational burnout, sleep disturbances, and the related factors of sleep disturbances among employees in traditional industries. The Reporting of Observational Studies in Epidemiology (STROBE) cross-sectional study checklist [49] was used as a reporting guide.

Study setting

This study is part of a collaborative research project conducted by a team of nurses, aiming to assess the relationship between sleep health and work-related factors and health promotion among workplace employees. It provides insights for occupational health nurses to promote workplace health initiatives.

Participants

The participants included employees at a traditional industrial complex in Northern Taiwan working in the textile industry or manufacturing nitrogen compounds, chemical raw materials, fertilizers, plastic and rubber raw materials, synthetic fibers, and plastic products. Inclusion criteria were as follows: participants had to be age 18 or older, having worked in traditional industries for at least three months, and agreed to participate in the study. Pregnant individuals were excluded.

Sampling and sample size

Cluster sampling was employed, with the study site comprising five factories: a cotton mill, Film Plant 1, Spinning Mill 3, Spinning Mill 4, and Utility Department. The main products produced by these factories include polyester cotton, polyester chips, polyester films, solid-state polymer chips, polyester partially oriented yarns, polyester fully drawn yarns, and polyester textured yarns. The work is labor-intensive, and each factory has both shift workers and administrative staff, with a predominantly male workforce aged between 35 and 64. Due to the similar background and work nature of the five factories, all employees from Film Plant 1 were randomly selected as the study subjects.

The required sample size for correlation analysis was calculated using the G*Power 3.1.0 software program for logistic regression analysis ("Z-test for Logistic regression"). Setting the odds ratio to 1.5, H0 to 0.5, significance level (α) to 0.05, and power to 0.9, the minimum sample size needed was 275. Data collection took place from 15 May 2023 to 17 June 2023, with 365 questionnaires distributed and all 365 valid questionnaires returned, yielding a response rate of 100%.

Measures

Data were collected using structured questionnaires, which included the following scales:

Demographic attributes

These included gender, age, education level, marital status, smoking, alcohol consumption, shift work, and weekly working hours, as referenced in [9, 11, 15, 16, 17, 18, 19, 20, 21, 22, 25]。

Health promotion behaviors

This was measured using the "Adult Health Behaviors - Short Form" (AHBs) developed by Chen et al. [41]. Participants completed the questionnaire regarding their lifestyle habits over the past year using a four-point Likert scale. The scoring criteria were as follows: 1 point for "Never" (approximately 0–10% ), 2 points for "Sometimes" (approximately 11–50% ), 3 points for "Often" (approximately 51–70% ), and 4 points for "Always" (approximately 71–100% ). Higher scores indicated healthier lifestyles. The scale covered six elements: stress management, physical activity, health responsibility, life appreciation, healthy eating, and oral hygiene behaviors. The internal consistency of the AHBs was 0.85. Lower scores on the six subscales and the total score of the SF-AHB were significantly associated with lower life satisfaction. Test–retest reliability for the total AHB was r = 0.91. The validity of the AHBs was confirmed through qualitative content validation by experts in metabolism/endocrinology, cardiology, dentistry, and nursing, with an average Content Validity Index (CVI) of 0.93 [41].

Occupational burnout

This study utilized the "Chinese Version of the Occupational Burnout Scale," developed by Yeh et al. [50], which references the Copenhagen Burnout Inventory (CBI) developed by Danish scholars and the Effort–Reward Imbalance Questionnaire (ERI-Q). The Cronbach's alpha for this scale was 0.86 overall (0.92 for men and 0.90 for women). The Cronbach's alpha for each subscale ranged between 0.85 and 0.87. The scale used a five-point Likert scale with the following scoring criteria: 5 points for "always" (100 points), 4 points for "often" (75 points), 3 points for "sometimes" (50 points), 2 points for "rarely" (25 points), and 1 point for "never" (0 points). Higher scores indicate a greater degree of perceived burnout [50].

Sleep disturbances

The Chinese version of the Athens Insomnia Scale-eight questions (CAIS-8), jointly translated by Jiang et al. [51], was used to measure the sleep status of the research subjects in the past month by filling in the questionnaire. The subjective feelings of the subjects regarding their nightly sleep were surveyed. The questionnaire included "nighttime symptoms": time to fall asleep, waking up at night, waking up earlier than expected, total sleep time, and total sleep quality; "daytime symptoms": daytime mood, daytime physical function, daytime sleepiness, for a total of eight questions. A four-point Likert scale was used, with each question scored from 0 to 3 points, with a total score of 0 to 24 points. A total score of less than 3 points (inclusive) indicated no sleep disturbances; a total score of 4 to 5 indicates suspected sleep disturbances, and a score greater or equal to 6 indicates sleep disturbances. The dependent variables analyzed at the end of this study were "no" (score 0 to 5 points) and "yes" (score ≧ 6 points) as the cut-off points for sleep disturbances [52].

Data processing and analysis

Data entry and statistical analysis were conducted using SPSS version 27.0, with an alpha value set to 0.05 (two-tailed test) as the criterion for statistical significance. Basic attributes were analyzed using percentages, frequency distributions, means, and standard deviations to understand the distribution characteristics of the measurements. Inferential statistics included the Chi-Squared Test to compare categorical variables of the study subjects with sleep disturbances (yes or no), an independent t-test to examine the differences in continuous variables of basic attributes, health promotion scale results, and occupational burnout scale results, and logistic regression to analyze the relationship between independent variables and sleep disturbances (yes or no) to identify factors related to sleep disturbances.

Ethical consideration

The Institutional Review Board approved this study with approval number A202305036. Participants were informed about the study through an information sheet, and data were collected using anonymous self-administered questionnaires. Participants were informed of their right to withdraw from the study at any time. Participants received small gifts after completing the questionnaire.

Descriptive statistics of basic attributes

A total of 365 subjects participated in this study. The average age was 43.86 years (SD = 11.74). The majority were not smokers (64.4%), with an average cigarette consumption of only 3.70 cigarettes per day (SD = 7.11). Most participants did not consume alcohol (72.3%). The average daily sleep duration was 6.61 hours (SD = 0.98). A significant portion of the participants were shift workers (63.3%). The majority worked ≤40 hours per week (67.4%), were non-supervisory staff (86%), and had a high school education (51.8%). Detailed information is provided in Table 1.

Descriptive statistical analysis results of health promotion behavior, occupational burnout, and sleep disturbances

Health promotion behavior

The original scale had a maximum average score of 4 points. The overall average score on the scale was 2.34 points, with a standard deviation of 0.48. The average scores of each sub-dimension, listed from highest to lowest, were as follows: "oral hygiene behavior" with an average of 2.56 points (SD = 0.69), "life appreciation behavior" with an average of 2.46 points (SD = 0.68), "healthy eating behavior" with an average of 2.44 points (SD = 0.58), "health responsibility behavior" with an average of 2.32 points (SD = 0.78), "stress management behavior" with an average of 2.28 points (SD = 0.56), and the lowest was "exercise behavior" with an average of 2.01 points (SD = 0.75). The scores for the first five sub-dimensions fell between "occasionally" and "frequently," while exercise behavior was rated as "occasionally," indicating 2–3 days per week.

Occupational burnout

The original scale had a maximum average score of 4 points. The overall average score on the scale was 1.96 points, with a standard deviation of 1.09. The total scores for each sub-dimension, listed from highest to lowest, were as follows: "personal burnout" with an average of 2.30 points (SD = 0.78), "work-related Burnout" with an average of 2.16 points (SD = 0.81), and "overcommitted to work" with an average of 2.07 points (SD = 0.75). All three sub-dimensions fell between "sometimes" and "often."

Sleep disturbance

A total score of less than or equal to 3 indicated no sleep disturbance, accounting for 32.3% of the subjects. A total score of 4 to 5 indicates suspected sleep disturbance, accounting for 19.7%. A total score of 6 or greater indicates the presence of sleep disturbance, with 47.9% of the subjects experiencing sleep disturbances. Details are shown in Table 2.

Bivariate analysis of factors affecting sleep disturbance

A bivariate analysis was conducted to understand the relationship between the study subjects' basic attributes, health promotion behaviors, occupational burnout, and sleep disturbance. The dependent variable was the presence or absence of sleep disturbances, while the independent variables included basic attributes, health promotion behaviors, and occupational burnout. Categorical variables were analyzed using the Chi-Squared Test, and continuous variables were analyzed using the Independent t-test. The results are as follows: significant differences were found for shift work (p < 0.001), shift groups (p = 0.004), weekly working hours (p = 0.027), stress management behavior (p = 0.001), exercise behavior (p < 0.001), health responsibility behavior (p < 0.001), life appreciation behavior (p < 0.001), healthy diet behavior (p < 0.001), oral hygiene behavior (p < 0.001), personal burnout (p < 0.001), work-related burnout (p < 0.001), and overcommitment to work (p = 0.001). Details are shown in Table 3.

Analysis of factors associated with sleep disturbances

Logistic regression analysis was conducted to identify the factors influencing sleep disturbance, incorporating basic attributes, work patterns, health promotion behaviors, and occupational burnout. The analysis was divided into four models: Model 1: The relationship between basic attributes, work patterns, and sleep disturbances. Model 2: The relationship between basic attributes, health promotion behaviors, and sleep disturbances. Model 3: The relationship between basic attributes, occupational burnout, and sleep disturbances. Model 4: The relationship between basic attributes, work patterns, health promotion behaviors, occupational burnout, and sleep disturbances.

For Model 1, logistic regression analysis was conducted using basic attributes and work patterns as independent variables and sleep disturbances as the dependent variable. The results are as follows:

smoking quantity, odds ratio (OR) = 1.03 (95% confidence interval (CI) 1.00~1.07), p = 0.048; shift work (yes/no), OR = 2.78 (95% CI 1.69~4.54), p < 0.001; weekly working hours (41~48 hours/≤40 hours), OR = 4.11 (95% CI 1.21~14.01), p = 0.024; and weekly working hours (˃48 hours/≤40 hours), OR = 2.41 (95% CI 1.45~4.01), p = 0.001. These results indicate that less smoking, non-shift work, and weekly working hours less than or equal to 40 hours are associated with a lower likelihood of sleep disturbance. The explanatory power (R²) of this model was 0.11. See Table 4 for detailed results.

Logistic regression analysis was conducted for Model 2, using basic attributes and health promotion behaviors as independent variables and sleep disturbance as the dependent variable. The results are as follows: health responsibility behavior, OR = 0.87 (95% CI 0.77~0.99), p = 0.030; life appreciation behavior, OR = 0.76 (95% CI 0.66~0.89), p < 0.001; and healthy eating behavior, OR = 0.86 (95% CI 0.76~0.97), p = 0.017. These results indicate that higher scores in health responsibility behavior, life appreciation behavior, and healthy eating behavior are associated with a lower likelihood of sleep disturbances. The explanatory power (R²) of this model was 0.21. See Table 4 for detailed results.

Logistic regression analysis was conducted for Model 3, using basic attributes and occupational burnout as independent variables and sleep disturbances as the dependent variable. The results are as follows: personal burnout, OR = 1.05 (95% CI 1.03~1.08), p < 0.001, and work-related burnout, OR = 1.03 (95% CI 1.01~1.05), p = 0.010. These results indicate that lower personal and work-related burnout scores are associated with a lower likelihood of sleep disturbances. The explanatory power (R²) of this model was 0.33. See Table 4 for detailed results.

For Model 4, logistic regression analysis was conducted using basic attributes, work patterns, health promotion behaviors, and occupational burnout as independent variables and sleep disturbances as the dependent variable. The results are as follows: shift work (Yes/No), OR = 3.03 (95% CI 1.64~5.56), p < 0.001; weekly working hours (>48 hours/≤40 hours), OR = 1.98 (95% CI 1.03~3.81), p = 0.040; health responsibility behavior, OR = 0.85 (95% CI 0.73~1.00), p = 0.049; and personal burnout, OR = 1.06 (95% CI 1.03~1.09), p < 0.001. These results indicate a lower likelihood of sleep disturbances associated with non-shift work, higher scores in health responsibility behavior, weekly working hours of 40 or less, and lower scores in personal burnout. The explanatory power (R²) of this model was 0.49. See Table 4 for detailed results.

Current status of sleep disturbances

The overall rate of sleep disturbances among the study subjects was 47.9%, with 48.7% for male employees and 35% for female employees. Therefore, the prevalence was found to be higher in our study compared to other manufacturing workers in Asian countries, such as 22.6% among Chinese electronics manufacturing employees [9], 35.3% and 42% among steel plant workers [11, 53], 16.7% among Chinese textile workers [12], 35.6% in Japanese construction and civil engineering employees [3], 33.2% among Indian construction workers [14], and 18.6% among Brazilian workers [54]. The higher rate of sleep disturbances in this study's subjects could be attributed to the majority of our participants being shift workers, with an average total daily sleep time of 6.61 hours, less than the recommended 7 hours. Additionally, most of their work involves standing or walking, which may increase burnout and contribute to a higher prevalence of sleep disturbances than workers in other countries' traditional industries.

Relationship between work patterns and sleep disturbances

According to the bivariate analysis, the sleep disturbance rate was 43.1% for those working ≤ 40 hours per week, 57% for those working 41–48 hours, and 61.5% for those working > 48 hours. The Model 1 results show that individuals working > 48 hours per week have 2.41 times higher odds of sleep disturbances than those working ≤ 40 hours. This aligns with findings by Halonen [25] and Lee [13], highlighting a higher probability of sleep disturbances with longer work hours. Referencing Taiwan's Hsiao [55], factors such as shift work, long hours (> 60 hours/week), heavy physical labor, and large company size (over 300 employees) are significantly related to sleep issues. This suggests that shift work and extended hours increase the risk of sleep disturbances. To reduce the rate of sleep disturbances, it is recommended to efficiently manage work hours, aiming for a standard work week of no more than 40 hours.

Relationship between health promotion behaviors and sleep disturbances

In Model 2, it was found that the participants’ behaviors related to "health responsibility," "appreciation of life," and "healthy eating" correlated with sleep disturbances. Drawing from the study by Weitzer [56], it was observed that practicing "appreciation of life" behaviors to maintain an optimistic outlook is a simple and effective strategy to improve sleep quality and reduce the risk of sleep disturbances. It is recommended that employees maintain a positive mindset, smile frequently, practice self-appreciation, and spend time outdoors appreciating nature, as this may lower the probability of sleep disturbances.

This study aligns with findings from Cao [17] and Castro-Diehl [57], suggesting that "healthy eating behavior" is also associated with sleep disturbances. Additionally, Castro-Diehl [57] noted that a healthy diet can promote sufficient sleep duration and reduce the risk of insomnia. Mediterranean dietary patterns [43] and whole grain patterns [17] emerged as protective factors against sleep disturbances. Therefore, it is advised to adopt healthy eating habits, including consuming at least three servings of vegetables and two servings of fruits and maintaining a water intake of 1500 milliliters daily. Seeking guidance from professional nutritionists and adjusting the meal categories offered in employee cafeterias may facilitate the establishment of healthy eating behaviors among employees.

"Health responsibility" aims to achieve overall well-being of body and mind, requiring individuals to adopt a proactive and responsible attitude towards their own health. This includes actively seeking knowledge and information on self-healthcare, being attentive to physiological changes and symptoms, and proactively seeking guidance and assistance from healthcare professionals when necessary. This study found that higher scores in "health responsibility" were associated with lower rates of sleep disturbances, possibly due to better management of one's physical and mental state, resulting in a lower susceptibility to sleep disturbances. While few studies have previously explored the relationship between health responsibility and sleep disturbances, future intervention-based follow-up studies could further investigate this association. While Xie [58] and Bjornsdottir [59] have shown that regular exercise can improve sleep quality and reduce insomnia severity and subjective daytime sleepiness among individuals with sleep disturbances, this study did not find a correlation between exercise behavior and sleep disturbances. This may be due to participants in this study generally not engaging in regular exercise, thus making it difficult to observe any correlation. Most participants were shift workers. Studies by Shah [60] and Shen [61] suggested that exercise can enhance cardiovascular health, leading to better sleep quality among shift workers and improving sleep disturbances caused by disrupted circadian rhythms. In the future, encouraging subjects to spend more time outdoors and actively establish a habit of regular exercise could be beneficial. This could be facilitated through technology such as smart bands, smartwatches, or workplace interventions like stair-climbing campaigns instead of using elevators, providing convenient access to exercise equipment in the workplace for stretching or physical activity during breaks. Additionally, intervention-based follow-up studies could be conducted to confirm the effectiveness of exercise in improving sleep disturbances.

Relationship between occupational burnout and sleep disturbances

The results of Model 3 indicate that individuals with lower scores in personal burnout and work burnout have lower rates of sleep disturbances. Baek et al. conducted a study on 18,744 Korean workers and found that higher levels of workplace burnout increased the likelihood of sleep disturbances [31]. Furthermore, significant correlations between workplace burnout and severe sleep disturbances were found among Hungarian postal workers [62]. Studies focusing on physicians [63] and nurses [32] have also shown a positive correlation between workplace burnout and sleep disturbances, with workplace burnout being a contributing factor to sleep disturbances, which aligns with the findings of this study. While many people find that they sleep better when experiencing burnout, this may not hold true for workers in labor-intensive traditional industries. Providing a comfortable work environment and allowing for short breaks (approximately 20 to 30 minutes), particularly for night shift workers, is expected to reduce personal and work burnout levels. Encouraging all employees to engage in leisure activities during breaks to relax their minds and bodies is also recommended. Additionally, hosting workshops on mental and physical health, such as aromatherapy, progressive exercise programs, and teaching and practical courses on muscle relaxation and deep breathing, is advised. These effective muscle relaxation techniques can help alleviate stress and anxiety, reduce personal burnout, and lower the likelihood of sleep disturbances, thus aiding employees in improving their burnout levels.

Overall findings indicate that shift rotation, weekly working hours, and health promotion behaviors correlate with personal burnout and sleep disturbances. Due to the significant threat sleep disturbances pose to employee health, it is recommended to adjust the shift rotation frequency for employees and develop more suitable shift schedules. For night shift workers, increasing the intensity of lighting in the work environment is advised to reduce sleep disturbances caused by circadian rhythm disruption and to assist employees in better adapting to shift work.

Occupational health nurses in the workplace should assist in promoting healthy behaviors among employees, including enhancing employees' self-health awareness and regularly organizing health education seminars on sleep, exercise, diet, and other relevant topics. This helps employees understand how to maintain a healthy lifestyle and alleviate feelings of burnout. Additionally, through employee health screenings, occupational health nurses can identify high-risk cases and provide preventative, diagnostic, and health advisory services to reduce the likelihood of sleep disturbances among workers in traditional industries.

Firstly, the questionnaire primarily relied on the subjective perceptions of the participants. However, incorporating objective data, such as physiological monitors (e.g., portable sleep trackers), could provide more objective data representation. Objective measurements of sleep processes may reduce research biases, enhance research credibility, and improve the impact and validity of the study. Secondly, participants making use of sleep aids should be excluded to more accurately represent the current status of sleep disturbances.

Ethics approval and consent to participate

This study protocol was approved by the Institutional Review Board of the Tri-Service General Hospital with protocol number A202305036. Participation in the study was voluntary, and informed consent was obtained from all participants.

Consent for publication

N/A

Availability of data and material

Data is available on request due to privacy/ethical restrictions.

Competing interests

The authors have declared that no competing interests exist.

Funding

This study was supported in part by grants TYAFGH_D_113021 from the Taoyuan Armed Forces General Hospital, Taoyuan, Taiwan.

Authors' contributions

YFY contributed to the study's conceptualization, methodology, data collection, data analysis, data interpretation and validation, original draft preparation, original draft revision and edit, and funding acquisition. YYC contributed to the revision and editing of the manuscript. SHC contributed to the study's conceptualization, data interpretation, validation, and revision and editing of the original draft. All authors have read and agreed to the final version of the manuscript.

Acknowledgements

Special thanks to nurse Zhang Jia-Zhen, the factory nurse, for her assistance

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Table 1 Descriptive statistics of basic attributes (N = 365)

Characteristics	n	(%)	M	SD
1. Gender Male Female	345 20	94.5 5.50
2. Age (years)			43.86	11.74
4. Marital Status Single Married Divorced Widowed	130 219 14 2	35.6 60.0 3.80 0.50
5. Smoking Habits None Quit Smoking Current Smoker	235 34 96	64.4 9.30 26.3
6. Number of Cigarettes Smoked (per/day)			3.70	7.11
7. Drinking Habits None Quit Drinking Occasionally (1–2 days/week) Frequently (3–5 days/week) Always (6–7 days/week)	264 7 83 7 4	72.3 1.90 22.7 1.90 1.10
8. Shift Work No Yes	134 231	36.7 63.3
11. Managerial position No Yes	314 51	86.0 14.0
12. Education level Primary, Secondary Senior High (including vocational) Associate degree Bachelor’s degree Master’s degree (including post-masters)	2 189 64 93 17	0.50 51.8 17.5 25.5 4.70

Note M = mean; SD = standard deviation

Table 2 Descriptive statistics of health promotion behaviors, occupational burnout, and sleep disturbances (N = 365)

Characteristics	n	(%)	M	SD
Health promotion behaviors			2.34	0.48
1. Stress management behaviors			2.28	0.56
2. Physical activity behaviors			2.01	0.75
3. Health responsibility behaviors			2.32	0.78
4. Life appreciation behaviors			2.46	0.68
5. Healthy eating behaviors			2.44	0.58
6. Oral hygiene behaviors			2.56	0.69
Occupational burnout			1.96	1.09
1. Personal burnout			2.30	0.78
2. Work-related burnout			2.16	0.81
3. Overcommitted to work			2.07	0.75
Sleep condition
1. No sleep disturbance	118	32.3
2. Suspected sleep disturbance	72	19.7
3. Sleep disturbance	175	47.9

Table 3 Analysis of Differences in basic attributes, health promotion behaviors, occupational burnout, and sleep disturbances (N = 365)

Characteristics	n	Sleep disturbances
Characteristics	n	Yes n (%)	No n (%)		*χ²/t*	p
1. Gender Male Female	345 20	168 (48.7) 7 (35.0)	177 (51.3) 13 (65.0)		1.42	.23
2. Age	365	43.3 ± 11.5	44.3 ± 12.0		0.17	.42
3. Number of Cigarettes Smoked	365	4.4 ± 7.7	3.09 ± 6.4		11.53	.09
4. Drinking Habits No Yes		129 (47.6) 46 (48.9)	142 (52.4) 48 (51.1)		0.05	.91
5. Shift Work No Yes	134 231	48 (35.8) 127 (55.0)	86 (64.2) 104 (45.0)		12.47	<.001
6. Weekly Working (hour) ≦40 41~48 ˃48	246 106 13	106 (43.1) 61 (57.5) 8 (61.5)	140 (56.9) 45 (42.5) 5 (38.5)		7.20	.027
7. Managerial position No Yes	314 51	152 (48.4) 23 (45.1)	162 (51.6) 28 (54.9)		0.19	.66
8. Health promotion behaviors
Stress management behaviors	365	2.18 ± 0.46	2.37 ± 0.63		3.31	.001
Physical activity behaviors	365	1.87 ± 0.62	2.14 ± 0.84		3.55	<.001
Health responsibility behaviors	365	2.09 ± 0.67	2.53 ± 0.82		5.68	<.001
Life appreciation behaviors	365	2.22 ± 0.60	2.69 ± 0.68		6.96	<.001
Healthy eating behaviors	365	2.26 ± 0.54	2.61 ± 0.58		5.60	<.001
Oral hygiene behaviors	365	2.43 ± 0.64		2.70 ± 0.72	3.82	<.001
9. Occupational burnout
Personal burnout	365	2.69 ± 0.78	1.95 ± 0.59		–10.10	<.001
Work-related burnout	365	2.53 ± 0.84	1.83 ± 0.62		–8.94	<.001
Overcommitted to work	365	2.20 ± 0.78	1.95 ± 0.71		–3.24	.001

Table 4 Logistic regression analysis of basic attributes, health promotion behaviors, occupational burnout, and sleep disturbances（N = 365）

Characteristics

Model 1 Odds ratio (95% CI)

Model 2 Odds ratio (95% CI)

Model 3 Odds ratio (95% CI)

Model 4 Odds ratio (95% CI)

Basic attributes

Gender (Male/Female^#)

Age

Number of Cigarettes Smoked

Drinking Habits

(No/Yes^#）

Work patterns

Shift Work（Yes/No^#）

Weekly Working

(hours)

41~48/≦40^#

˃48/≦40^#

0.93 (0.34~2.56)

0.98 (0.98~1.02)

1.03 (1.00~1.07)^*

0.96 (0.58~1.60)

2.78 (1.69~4.54)^***

4.11 (1.21~14.01)^*

2.41 (1.45~4.01)^**

1.12 (0.39~3.19)

0.98 (0.96~1.00)

1.00 (0.96~1.03)

0.85 (0.50~1.44)

0.34 (0.09~1.29)

1.00 (0.98~1.03)

1.00 (0.96~2.01)

0.81 (0.42~1.58)

0.51 (0.15~1.75)

1.00 (0.98~1.03)

1.01 (0.97~1.05)

0.81 (0.43~1.54)

3.03 (1.64~5.56)^***

1.30 (0.24~6.97)

1.98 (1.03~3.81)^*

Health promotion behaviors

Stress management

Physical activity

Health responsibility

Life appreciation

Healthy eating

Oral hygiene

1.00 (0.91~1.11)

1.01 (0.92~1.10)

0.87 (0.77~0.99)^*

0.76 (0.66~0.89)^***

0.86 (0.76~0.97)^*

1.04 (0.93~1.15)

0.91 (0.80~1.04)

0.99 (0.89~1.11)

0.85 (0.73~1.00)^*

0.87 (0.72~1.04)

0.88 (0.76~1.02)

1.00 (0.86~1.14)

Occupational burnout

Personal burnout

Work-related burnout

Overcommitted to work

1.05 (1.03~1.08)^***

1.03 (1.01~1.05)^**

0.98 (0.98~1.01)

1.06 (1.03~1.09)^***

1.02 (0.99~1.04)

1.00 (0.99~1.02)

R²

0.11

0.21

0.33

0.49

Note 1.^* p<0.05 ^**p<0.01 ^***p<0.001，2.^# reference group 3. CI= Confidence Interval

No competing interests reported.

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Exploring Health Promotion Behaviors, Occupational Burnout, and Sleep Disturbances in Traditional Industry Workers

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