Evaluation of absenteeism and presenteeism status of factory employees

Abstract

BACKGROUND:

While absenteeism refers to not attending work, presenteeism is defined as not being present at work. These two conditions, which negatively affect employee health, can be indicators of work efficiency, work peace, work safety and work engagement.

OBJECTIVE:

Several factors were evaluated in this study concerning absenteeism and presenteeism among factory workers.

METHODS:

This cross-sectional study was conducted among workers in a factory operating in a heavy industry in southern Turkey in 2021. A survey consisting of 57 questions was applied to 152 factory workers by face-to-face interview method. The participants’ behaviour over the last month was evaluated regarding absenteeism and presenteeism.

RESULTS:

It was reported that 24 (15.8%) of all employees were absent from work in the last month (absenteeism), excluding holidays and sick leave, and that 20 (13.2%) employees engaged in presenteeism, working when they should not have been at the workplace. There was a high absenteeism rate among employees who had an acute illness and were dissatisfied with their jobs. Several factors have been associated with presenteeism, including poor economic conditions, family health problems, previous unemployment, working overtime, job dissatisfaction, poor relationships with colleagues and difficulty finding a replacement, acute illness, sleep problems and fatigue.

CONCLUSIONS:

To increase the productivity and commitment of employees, it may be useful to identify the reasons for absenteeism and present behaviours, to facilitate effective interpersonal communication skills by examining the organisational climate of employees, and to regulate workload based on a comprehensive assessment of the health status of employees.

Keywords

Presenteeism absenteeism occupational health employee health total worker health industry health

1 Introduction

As part of occupational health and employee health issues, absenteeism and presenteeism are preventable concepts affecting all employees, employers, and the country’s economy. They can adversely affect the labor market and production efficiency, create competition, cause inequality of opportunity, and disrupt the work-life balance.

Abstinence can be defined as the observed loss of expected working time for a particular job determined by the employees for various reasons, such as missed working days and hours and absences from work [1]. The general definition of absenteeism is “not being physically present when and where expected behavior is expected” [2]. Presenteeism may be a behavior intended to counter absenteeism, but in the long run, it contributes to similar losses in terms of labor and productivity. The concept of presenteeism was recently defined by Cooper as “being at work instead of being at home due to illness or inefficiency due to working for too long” and expressed the employees’ insecurity and the fear of losing their job to stay at work longer [3, 4].

Absenteeism and presenteeism can be attributed to various factors, such as work-related reasons, personal reasons, and social, psychological, economic, and cultural factors. It is commonly observed that abstinence is caused by organizational culture, stress, work pressure, nature of work, not being placed in a suitable position, lack of work peace, conflict at work, job satisfaction, mobbing, employee habits, addictions, family structure, educational status, economic well-being, gender, and age. Many factors can contribute to this situation, such as illness, family responsibilities, mode of transportation, and weather conditions [5 –7]. Among the factors that contribute to presenteeism is the nature of the job, the size of the organization, job stress, shift type, work pressure, relations between employees and employers, role ambiguity, job satisfaction, mobbing at work, discrimination, age, gender, economic situation, education level, family roles, employee habits, health status, social pressure, and stereotypes that have been learned in culture [2, 8].

There is a similarity between the causes of absenteeism and presenteeism manifested in their respective outcomes. Some expected results are poor employee health, occupational safety, decreased productivity, work efficiency, and organizational commitment. It is estimated that presenteeism impacts work efficiency and productivity more than absenteeism [6, 9]. There is a greater cost associated with presenteeism than absenteeism, and it is more difficult to detect than absenteeism. According to a study conducted in Japan, absenteeism costs $520 per person per year, while presenteeism costs $3055 per person and may also result in absenteeism in the future. There is a negative relationship between employees’ physical-mental health and job satisfaction, while a positive relationship exists between their physical-mental health and burnout [10 –13].

Total Worker Health revolutionizes the approach to occupational health and safety by encompassing a broader perspective. It defines occupational health and safety as the enhancement of workers’ health and well-being by considering the social implications of health and addressing workplace examinations and potential hazards. Factors such as workload, wages, relationships with coworkers, the work environment, and work-related stress significantly influence overall well-being [14]. It is crucial to recognize the social consequences of absenteeism and presenteeism when developing Total Worker Health practices. Concurrently, Total Worker Health practices have shown potential in reducing absenteeism [15].

Previous studies have indicated a correlation between absenteeism and presentism and employees’ lifestyles, habits, and health-related risk factors. Additionally, workplace and non-workplace stress have been found to impact these phenomena [6 , 16–18]. The aim of this study was to determine the frequency of absenteeism and presenteeism among factory workers in heavy industry and to identify some variables that may explain these patterns. If these factors are known, the continuity of employee health and productivity can be ensured with workplaces where working peace is ensured and a positive organizational climate can be created.

2 Methods

This cross-sectional study was conducted with workers working in a factory in the heavy industry field between November and December 2021. This survey was designed to reach all 157 employees at the factory, and no sampling was conducted. Face-to-face interviews were conducted with factory employees in the infirmary within the specified time frame. Five workers who refused to participate in the study were excluded from the study. A total of 152 workers participated in the study. The inclusion criteria were full-time, blue-collar employees aged 18 and over, while the exclusion criteria were temporary and white-collar employees.

In the study, a questionnaire comprising 57 questions prepared by the researchers following the literature was applied to assess the employees’ sociodemographic characteristics, including age, gender, economic status, absenteeism, and presenteeism [8 , 16–18]. The current weight and height of the employees were calculated and recorded with a weight and height gauge with an accuracy of 0.01 kg in barefoot and in sports clothes. The workers were asked to respond to questions about absenteeism and presenteeism according to the circumstances of the last month to avoid overreporting and misremembering. Medical reports and absences from work without leave were questioned for abstinence. Absenteeism for at least one day was considered absenteeism. Presenteeism was measured by the number of days worked by the employee, excluding overtime, even though they believed they should not be at work. Working despite being sick for at least one day was accepted as presenteeism.

2.1 Statistical analysis

The data collected for the study were analyzed and recorded using the SPSS 22 program. For descriptive statistics, frequency, percentage, mean value, standard deviation, and highest and lowest (min-max) values were used. Pearson’s chi-square test was applied for the statistical analysis of the categorical data, and Fisher’s exact test was applied for values below five in the four-eyed tables. The Shapiro— Wilk test was used to check the data’s conformity to the normal distribution. For the statistical analysis of quantitative data in independent groups, the unpaired t test was used for data with a normal distribution, and the Mann— Whitney U test was used for data that did not conform to a normal distribution. A statistically significant difference was accepted as p < 0.05.

3 Results

Out of the 152 participants in the study, 142 (93.4%) were male and 10 (6.6%) were female. The mean age of the employees was 36.5±8.5 years (min-max: 19–63). One hundred fourteen of the participants (75.0%) were married. Sixty-seven percent (103 out of 105) of the employees were high school or associate degree graduates, and 69.1% (105 out of 105) reported having a medium income. Table 1

Table 1
Some sociodemographic and health-related findings of the employees and their attendance at work

Variables		All workers		Absenteeism at work in the last month			Presenteeism at work in the last month
		n	% *	n	% **	p	n	% **	p
Gender	Male	142	93.4	22	15.5	0,659^a	19	13.4	1,000^a
	Female	10	6.6	2	20.0		1	10.0
Marital status	Married	114	75.0	17	14.9	0,607^b	16	14.0	0,579^b
	Single	38	25.0	7	18.4		4	10.5
Education level	Middle school and below	24	15.8	1	4.2	0,243^a	5	20.8	0,443^a
	High school and undergraduate	103	67.8	19	18.4		13	12.6
	Graduate	25	16.4	4	16.0		2	8.0
Economic level	Poor	24	15.8	4	16.7	0,279^a	7	29.2	0,057^a
	Medium	105	69.1	19	18.1		11	10.5
	Good	23	15.1	1	4.3		2	8.7
Family type	Nuclear family	125	82.2	20	16.0	1,000^a	19	15.2	0,237^a
	Single	17	11.2	3	17.6		0	0.0
	Extended family	10	6.6	1	10.0		1	10.0
Child	Yes	111	73.0	16	14.4	0,444^b	17	15.3	0,195^b
	No	41	27.0	8	19.5		3	7.3
Longest inhabited region	City	48	31.6	8	16.7	0,922^b	6	12.5	0,971^b
	District	69	45.4	10	14.5		9	13.0
	Village/Town	35	23.0	6	17.1		5	14.3
Live with the elderly	Yes	19	12.5	5	26.3	0,186^a	4	21.1	0,281^a
elderly	No	133	87.5	19	14.3		16	12.0
Family member health problem	Yes	22	14.5	4	18.2	0,754^a	8	36.4	0,002^a
health problem	No	130	85.5	20	15.4		12	9.2

*Column Percent,** Row Percentage, a: Fisher’s Exact Test, b: Pearson Chi-Square.

f provides some sociodemographic information about the employees. There were 24 (15.8%) employees who reported that they had been absent from work for the last month, excluding leave and report, and 20 (13.2%) reported that they continued to work despite not being at work (presenteeism) (Table 1).

The absenteeism status of workers did not differ significantly between sociodemographic groups. However, it was higher in women and those living with elderly individuals and lower in those with secondary school education and below, those with good economic status, and those with a large family structure. Those with secondary education or less (20.8%), those with poor economic status (29.2%), those with children (15.3%), and those with health problems in their families (36.4%) were found to have higher rates of presenteeism (Table 1).

Of the workers, 61 (40.1%) worked in shifts, 110 (72.4%) were intensive, 65 (42.8%) came to work by shuttle, 104 (68.4%) worked overtime in the last month, and 123 (80.9%) stated that they were satisfied with their job. It has been found that those absent from work are those who consider their jobs to be not intensive (23.8%) and unsatisfactory (34.5%). In contrast, those who were less absent had good relationships with their colleagues (14.3%) and had difficulty finding a replacement colleague (10.4%) (Table 2).

Table 2

Work-related findings and attendance status of workers

Variables		All workers		Absenteeism at work in the last month			Presenteeism at work in the last month
	n	% *	n	% **	p	n	% **	p
Working type	Daytime only	91	59.9	14	15.4	0,867^a	9	9.9	0,145^a
	Shift	61	40.1	10	16.4		11	18.0
Workload	Intensive	110	72.4	14	12.7	0,094^a	16	14.5	0,413^a
	Not intensive	42	27.6	10	23.8		4	9.5
Work stress	Very stressful	76	50.0	11	14.5	0,867^a	14	18.4	0,119^a
	Moderate stress	50	32.9	9	18.0		5	10.0
	Little/No stress	26	17.1	4	15.4		1	3.8
Transportation to the workplace	Own car	44	28.9	6	13.6	0,812^a	3	6.8	0,092^a
	Public transport	43	28.3	8	18.6		4	9.3
	Shuttle	65	42.8	10	15.4		13	20.0
Unemployment	Yes	85	55.9	14	16.5	0,795^a	16	18.8	0,020^a
before	No	67	44.1	10	14.9	4	6.0
Work accident last	Yes	6	3.9	1	16.7	1,000^a	2	33.3	0,178^b
year	No	146	96.1	23	15.8	18	12.3
Overtime in the last month	Yes	104	68.4	16	15.4	0,840^a	20	19.2	0,001^a
	No	48	31.6	8	16.7		0	0.0
Job satisfaction	Pleased	123	80.9	14	11.4	0,004^b	5	4.1	<0,001^b
	Not glad	29	19.1	10	34.5		15	51.7
Relationship with colleagues	Good	126	82.9	18	14.3	0,252^a	12	9.5	0,008^a
	Bad	26	17.1	6	23.1	8	30.8
Finding a replacement	Easy	53	34.9	11	20.8	0,363^b	4	7.5	0,013^b
	Difficult	48	31.6	5	10.4		12	25.0
	No idea	51	33.6	8	15.7		4	7.8

*Column Percentage,**Row Percentage, a: Pearson Chi-Square, b: Fisher’s Exact Test.

Those who showed presenteeism at work in the last month were those who mainly worked in shifts (18.0%), whose work was intensive (14.5%) and stressful (18.4%), who came to work by shuttle bus (20.0%), who had been unemployed before (18.8%), who had a work accident in the last year (33.3%), who worked overtime (19.2%), who were not satisfied with their job (51.7%), who had bad relations with their colleagues (30.8%), and who had difficulty in replacement (25.0%)(Table 2).

Twenty-four (15.8%) of the workers had chronic diseases, the smoking rate was 59.9%, and the alcohol consumption rate was 31.6%. It was observed that those absent from work often used alcohol (20.8%), suffered from acute illnesses (37.0%), sought medical attention in the last month (37.5%) and were sleepy(21.4%) and fatigued (20.0%) during the day. Most workers who exhibited the present behavior reported having an acute illness within the past month (29.6%), expressing sleepiness (23.2%) and fatigue during the day (27.5%), and having irregular (24.1%) and poor-quality sleep (22.5%) (Table 3).

Table 3

Health status, habits and attendance status of workers

Variables		All workers		Absenteeism at work in the last month			Presenteeism at work in the last month
		n	% *	n	% **	p	n	% **	p
Chronic disease problem	Yes	24	15.8	3	12.5	0,768^a	4	16.7	0,525^a
	No	128	84.2	21	16.4		16	12.5
Regular medication history	Yes	18	11.8	3	16.7	1,000^a	2	11.1	1,000^a
	No	134	88.2	21	15.7		18	13.4
Smoking	Yes	91	59.9	15	16.5	0,774^b	14	15.4	0,321^b
	No	61	40.1	9	14.8		6	9.8
Drinking alcohol	Yes	48	31.6	10	20.8	0,247^a	6	12.5	0,871^b
	No	104	68.4	14	13.5		14	13.5
Doing sports regularly	Yes	42	27.6	7	16.7	0,855^b	4	9.5	0,413^b
	No	136	72.4	17	15.5		16	14.5
History of illness in the past month	Yes	27	17.8	10	37.0	0,002^a	8	29.6	0,010^a
	No	125	82.2	14	11.2		12	9.6
Consulting a doctor in the last month	Yes	16	10.5	6	37.5	0,022^a	1	6.3	0,696^a
	No	136	89.5	18	13.2		19	14.0
Sleep pattern	Regular	94	61.8	14	14.9	0,700^b	6	6.4	0,002^b
	Irregular	58	38.2	10	17.2		14	24.1
Sleep quality	Quality	81	53.3	11	13.6	0,425^b	4	4.9	0,001^b
	Poor quality	71	46.7	13	18.3		16	22.5
Sleepiness during the day	Yes	56	36.8	12	21.4	0,145^b	13	23.2	0,005^b
	No	96	63.2	12	12.5		7	7.3
Too much fatigue during the day	Too much	40	26.3	8	20.0	0,395^b	11	27.5	0,002^b
	None/Very little	112	73.7	16	14.3		9	8.0

*Column Percent,**Row Percentage, a: Fisher’s Exact Test, b: Pearson Chi-Square.

Regarding absenteeism and presenteeism of the employees, there was no significant relationship between age, body mass index (BMI), years of service, weekly working hours, and the number of teammates within the unit. However, the number of teammates was higher for employees with presenteeism (Table 4).

Table 4

Relationship of some parameters of workers with their continuity

Variables	All workers				Absenteeism at work in the last month
	Yes		No		Yes		No
Mean		sd.	Mean	sd.	Mean	sd.	Mean	sd.
Age	34.62	8.54	36.87	8.49	36.65	7.48	36.50	8.68
	p: 0,236*				p: 0,942*
BMI	26.27	3.63	26.57	3.56	26.04	3.65	26.59	3.56
	p: 0,708*				p: 0,521*
Years of service	11.66	7.77	14.28	8.19	13.65	7.08	13.90	8.33
	p: 0,150*				p: 0,898*
Weekly working hours	50.00	5.81	48.21	4.49	49.50	5.05	48.34	4.70
	p: 0,231**				p: 0,346**
Number of friends in the unit	13.20	12.94	16.65	15.19	23.20	19.99	15.03	13.71
	p: 0,188**				p: 0,079**

BMI: body mass index, *Unpaired t Test, **Mann— Whitney U.

4 Discussion

Examining employee health from all aspects and determining the individual, social, and working conditions in the workplace that affect it is crucial. Absenteeism and presenteeism are often overlooked issues in the workplace, and it is important to identify their causes and consequences for employee health and productivity. This study investigates the underlying causes of absent and present behaviors. Our study in the heavy industry provides support for the limited number of studies conducted on blue-collar workers in our country and serves as a guide for future research.

4.1 Absenteeism

There was a 15.8% prevalence of absenteeism in our study. A study conducted in Finland found that absenteeism among municipal workers was 78.8% within two years, while a study conducted in Norway found that absenteeism in one year can range between 57% and 49% [16, 19]. Our study’s relatively low incidence of absenteeism may be explained by the fact that at least one day’s absence was considered for absenteeism in the last month.

The frequency of absenteeism in workers did not differ significantly between sociodemographic groups. However, it was higher in women and those living with elderly individuals and lower in those with secondary education and below, those with good economic status, and those with a large family structure. It was noted in a review by Belita et al. that absenteeism is a problem among women, and Kocakulah et al. cited familial responsibilities as a contributing factor to absenteeism [20, 21]. A study conducted in the food industry in Italy revealed that those who were economically stressed were more likely to be absent from work [22].

Similarly, in a study conducted on healthcare professionals in Uganda, familial factors were identified as determinants of absenteeism [23]. The fact that women have more family responsibilities suggests that those living with elderly individuals have to deal with their health problems, which may explain the low absence of absenteeism in this group, as those with poor economic status may experience a pay cut when they do not come to work. A large family structure may have also contributed to the pressure to work in countries with traditional structures such as ours.

In our study, it was seen that the groups with low absenteeism were those with busy jobs, were satisfied with their job, had good relations with their colleagues, and had difficulty finding a replacement friend. A study conducted in Brazil found that job stress and demands can contribute to teacher absenteeism [24]. In their study of five manufacturing company employees, Punnet et al. found that absenteeism decreased as job satisfaction and satisfaction with coworkers increased [25]. The increased organizational commitment may be attributed to job satisfaction and good relations with colleagues. Although the nature of the work is intense, work pressure and the inability to find a substitute friend may appear to reduce absenteeism, and there is a possibility that it may have triggered presenteeism. In the present study, presenteeism was higher among those who described their jobs as tiring and had difficulty finding a replacement.

It was observed that most of those who missed work in the last month used alcohol, suffered from an acute illness in the past month, and suffered from sleepiness and fatigue during the day. A study conducted with physicians and nurses found that a history of acute illness in the last month may affect absenteeism, while a study conducted in Iran found that poor sleep quality is associated with absenteeism [26, 27]. In another study conducted in Sweden, sleep disorders were associated with absenteeism [28]. Parsley et al. found that alcohol use disorder was a determinant of absenteeism, while Wee et al. identified income level, stress, sleep, and general health status as predictors of absenteeism [9, 29]. It was thought that the physical and mental health, behaviors and habits of employees could be effective in influencing absenteeism [30, 31].

4.2 Presenteeism

The final prevalence of presenteeism in our study was found to be 13.2%. In our study, the prevalence of presenteeism in pediatric residents in Canada was 59.1%; in a study from Belgium, it was 50.6%, and in Denmark, it was over 70% [32 –34]. In our study, the relatively low rates of present behavior are because the workers were asked about their last month for the study and that the study was conducted during the period in which preventive health practices were being practiced throughout the country due to the pandemic.

As a result of our study, the rate of presenteeism in the last month was higher in those with a secondary school education or less, who had a poor economic status, had children, and had family members with health problems. In addition, higher presenteeism can be observed in shift workers, those who describe their jobs as busy and stressful, those who travel by bus to work, those who have been unemployed previously, those who have been involved in work accidents within the last year, those who work overtime, those who are dissatisfied with their job, and those who describe their relationships with their colleagues as bad and seek out a friend as a replacement.

Furthermore, the number of teammates showing present behavior was higher. In addition, the number of teammates who showed present behavior was higher. Many studies have been conducted on the factors and causes of presenteeism in the literature [12 , 35–37]. For instance, Park et al. reported that employees with primary and lower education who were in poor health were more likely to engage in present behavior [35]. According to Yang et al., presenteeism was directly related to job stress [36]. Apart from health problems, Aronsson and Gustafsson described time pressure, difficulty finding a replacement, insufficient opportunities, and economic difficulties as determinants of presenteeism [12]. In addition, a study indicated that nurses who work a shift system experience a higher rate of presenteeism [37].

In some cases, employees may have been under pressure to work because of economic difficulties, having been unemployed before, or having dependents. In such large enterprises in our country, overtime wages are calculated and paid to employees in addition to their fixed monthly wages. As a result of the nature of the work, a factory serving heavy industry has a relatively high work intensity. It has been observed that organizational climate and interpersonal relations may also contribute to presenteeism. People unsatisfied with their job are estimated to have low job satisfaction. This may affect job performance negatively and delay the completion of the job. However, no inquiry has been made into this possibility.

Presenteeism was associated with acute illness, sleepiness, fatigue during the day, and irregular and poor-quality sleep among workers with presenteeism in the past month. According to a study conducted, fatigue has significantly impacted presenteeism among factory workers in Korea [30]. In a study in physicians and nurses, acute illnesses in the last month also negatively affected presenteeism, and another study found that nurses with sleep disorders and health problems were four times more likely to exhibit presenteeism behavior [26, 37].

Presenteeism may be caused by various individual factors, including work-related or non-work-related familial and social variables. When employees experience problems in the workplace and work peace is not achieved, presenteeism may occur. A study conducted in Latvia demonstrated that workplace conflict can lead to presenteeism [38]. In our country, employees do not experience a decrease in wages when taking annual or sick leave. However, employers may request compensation for the missed work through overtime, or employees may feel pressured to work due to fear of losing their job. If an employee struggles to balance work and personal life, lacks support at work, experiences low job satisfaction, or faces financial difficulties, they may continue to work despite being ill. This could lead to absenteeism, burnout syndrome, and a lack of commitment to work in the future.

5 Conclusion and recommendations

The present study examined the absent and present behaviors of factory workers in heavy industry and many individual, work-related, and social factors that may impact these two situations. The variables most associated with abstinence were acute illness in the last month and job dissatisfaction, poor economic situation, health problems in family members, previous unemployment, working overtime, dissatisfaction with their job, having a lousy relationship with coworkers, and substitution. Being hard to find someone, experiencing an acute illness in the last month, sleeping problems, and fatigue were associated with presenteeism.

Considering factors related to absenteeism and presenteeism, increasing professional satisfaction among employees, providing training to gain positive communication skills among colleagues, and organizing special social support programs for employees with family members with health problems, eliminating the sleepiness and fatigue of the employees by taking into account the working conditions of the job and reorganizing breaks and working hours can be positive steps. It is necessary to conduct new research that will support this study, examine different factors related to the topic, and explore activities to protect and improve worker health in various work environments.

5.1 Limitations

The study was conducted in a single centre and heavy industry branch of the factory; therefore its generalizability is limited. Additionally, the study only questioned absenteeism and presenteeism in the last month, and the lack of access to records for actual absenteeism of blue-collar workers could be seen as a limitation. Employee breaks and working hours were not analyzed in detail.

Ethical approval

Ethics approval was obtained from the Non-Invasive Clinical Research Ethics Committee at Hatay Mustafa Kemal University with a decision dated 04.10.2021 and numbered 29. The workers were informed of the issue, and their verbal consent was obtained.

Informed consent

Participants were given detailed information about the study and verbal consent was obtained.

Conflict of interest

The authors declare that they have no conflict of interest.

Footnotes

Acknowledgments

There is no acknowledgements.

Funding

The authors report no funding.

Author contributions

Conception and design: Oral B, Solak Y

Data collection: Solak Y, Durmuş H

Analysis: Oral B, Solak Y, Durmuş H

Writing: Oral B, Solak Y, Durmuş H

Data availability

The datasets generated during and/or analysed during the current study are not publicly available due [because it contains employer’s private data] but are available from the corresponding author on reasonable request.

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