The International Labour Organization (ILO) estimates that some 2.3 million women and men around the world succumb to work-related accidents or diseases every year, corresponding to over 6000 deaths every single day. Worldwide, there are around 340 million occupational accidents and 160 million victims of work-related illnesses annually (1996-2020), according to International Labour Organization (ILO). Many government and industries have widely acknowledged workplace fatigue as a significant occupational health and safety risk. This has been particularly evident in several high consequence industries like transportation, medicine manufacturing, etc. 

In Kenya, however the impact of time factor and fatigue on occurrence of accident has never been taken into consideration. The Kenya law on safety and health [1] is completely silent on issues of fatigue, working hours and shift work. The directorate of Occupational Safety and Health (DOSH) is responsible for regulation and monitoring work related accidents in the country.

The Directorate of Occupational Safety and Health Services has been investigating and recommending preventive measures on occupational accidents since the inception of the Occupational Safety and Health Act [1], but the accident statistics shows that the numbers of occupational accidents have been on the increase over the years. DOSHS has been for a long time focusing its attention on the immediate cause of accident and neglecting the root causes. It is obvious that if DOSH aims to reduce occupational accident the department needs to look beyond the obvious factors and take into account all the various ways in which the human element can contribute to accidents. In the absence of the knowledge of the causes of accidents, prevention of the same is extremely difficult or impossible. It is necessary to gain more insight into human factor and characteristics that might be a cause of occupational accidents. Fatigue may be one of the human factors that have been ignored for a long time, hence the lack of success in reducing workplace accidents. 

Until now very little research has been done on the causes of workplace accident and the role of fatigue in the accident occurrence in Kenya. Research has been done by Kemei and Nyerere [2], Mwangi and Oduor [3] and Makori et al. [4] on accidents in construction sites, but construction is a unique field and does not represent all other workplaces, thus leaving a gap in scholarly knowledge. The main objective of this study was to establish the relationship of accidents with time of a working day and to identify factors that contribute to accidents, including the influence of fatigue on the frequency of occurrence of occupational accidents in Kenya. To achieve this objective the study set out the following specific objectives (1) to determine the number of accidents that occurred in Nairobi metropolitan between 2008 and 2009, (2) to evaluate the variation of time and frequency of accident occurrence, (3) to establish whether there is any correlation between accident frequencies and the fatigue level of workers. In this paper we report only results of the first two objectives and the third objective will be reported in subsequent papers.

Occupational accidents are unplanned occurrences that occur in the course of duty of a worker, with a consequence of injuries, fatalities, or damage to property and loss of production. Accidents cannot be eliminated, but risks can be reduced. However, to reduce occurrence of accidents there must be understanding of the causes of accidents. Many attempts have been made to develop a prediction theory of accident causation, but so far no theory can be taken as a universally accepted model of accident prediction because each accident may occur under unique circumstances and environments. 

Multiple causation theory, International Labour Organization (ILO), which is an outgrowth of the domino theory, postulates that for a single accident there may be many contributory factors, causes and sub-causes and that certain combinations of these give rise to accidents. According to this theory, the contributory factors can be grouped into the following two categories, behavioural, includes factors pertaining to the worker, such as improper attitude, lack of knowledge, lack of skills and inadequate physical and mental condition; environmental, includes improper guarding of other hazardous work elements and degradation of equipment through use and unsafe procedures and the administrative causes may include inadequate staffing, limited amounts of breaks and unrealistic output demands and general work environment.

Statistics published by Statista Research Department [5], shows the annual number of work-related deaths and accidents worldwide as of 2016, there were approximately 313 million accidents and 2.3 million deaths at the workplace per year. Fatigue is many times considered as the major cause of accident, but fatigue is a consequence of underlying factors. Although work shifts give some sort of break for workers to rest, prolonged shifts and irregular or insufficient sleep may also be associated with fatigue. In workplace, feelings of fatigue may arise from high temperatures, high noise levels, dim lighting or poor visibility, work tasks that are long, repetitive, paced, difficult, boring, or monotonous.

According to ILO Encyclopedia [6], the traditional view of occupational accidents so states that accidents are produced by technological as well as individual human failures. Nevertheless, during the three last decades researchers have increasingly recognized that industrial accidents are caused by a dynamic interaction between factors in the social and physical environments, that is, characteristics of the individual and the organization as well as technical forces. 

Demographic and lifestyle factors including age, gender, alcohol consumption and smoking; work environment and safety culture and climate fields comprising physical and psychosocial work environment factors such as noise, temperature and machinery, workplace and ergonomic conditions, work support and work pressure, risk perception and competence, are likely to favour accident occurrences and need to be studied, because by studying such factors, the root cause of accidents can be isolated and necessary steps taken to prevent the recurrence of the accidents. In their work, Hsiao and Simeonov [7] presented a model for structuring factors that play a role in falls from roofs, which can also be applied to occupational accidents in general. Their model consists of three categories of factors: work environment, task related factors and personal factors. The work environment includes factors such as noise and machinery, the physical environment in which tasks are performed. Task related factors describe the tasks of a certain job (for example, load handling, physical exertion and complexity of the task). Personal factors include, for instance, age, training and sensory interface with protective equipment. 

In their model, Hsiao and Simeonov [7] classify fatigue as a task related factor only, implying that performing tasks at a given intensity and duration can lead to fatigue. Fatigue may then decrease the ability of the worker to process important visual and perceptive information relevant to avoiding an accident. In contrast, fatigue can also be viewed as having a multi factorial origin, affected by non-work related circumstances and personal characteristics, with a prolonged character that may affect the individual’s performance and ability to function at work. To date, it is unknown whether fatigue is a mediator between work related factors and the occurrence of accidents, or whether fatigue is an independent risk factor [8].

The study used two sources of data, secondary occupational accident data from all the Work Injury Benefit Acts forms (WIBA) was obtained from the Directorate of Occupational Safety and Health Services (DOSH) by analyzing accident reporting forms, (DOSH 1, Appendix I) for the period between June 2008 and June 2009. In Kenya it is mandatory for all institutions employing staff to report accidents arising from work to the directorate. For each accident reported a comprehensive compilation of the circumstances surrounding it, including age of the injured worker, length of time on the job, occupation of the worker, the machine or tools involved, name and location of workplace and the time of the day when the accident occurred is required. 

This data was analysed in Microsoft excel in order to determine the number of accidents reported in one year, the organizations that had reported and the workplaces that had reported the highest number of accidents. Ten percent (10%) of all the total number of workplaces that had reported accidents through WIBA forms from June 2008 to June 2009 were picked for primary data. Within the 8 workplaces a sample of the workers (n = 320) were randomly picked to fill the questionnaires. Workplaces that had reported highest number of accidents were picked for the purposive sampling. Respondents were sought from each of the 8 workplaces that had reported the highest number of accidents in the year under review. Only workers who worked continuously for 8-9 hours daily and doing day shift were considered for the study.

The field study covered the Nairobi Metropolitan, which Nairobi City County and its satellite towns of Kitengela, Athi River, Thika and Kiambu and covering a total of eight different industries. The choice of workplaces was largely based on the data that was analyzed from the DOSHS reports. Nairobi was selected for the study because it has the largest concentration of industries and has all representatives of industries. Besides the all the industries that had reported the highest number of accident were found in the metropolitan. The area has a diverse nature of workplaces which includes steel rolling mills, horticulture and manufacturing among others.

Workers present during the visits were approached at random to participate in the filling of the questionnaire. Each respondent was required to answer two sets of questions, one on their demographic data and the other on factors of subjective fatigue, Checklist Individual Stregth (CIS checklist). The research assistants were available throughout the exercise to answer or clarify any questions or difficulties from the respondents, especially of the CIS checklist due to literacy levels associated with the kind of workforce in various workplaces. The sample consisted of 320 individuals, 298 men and 22 women, aged between 18 and 60 years, in employment in different organization. The choice of age bracket was guided by the fact that persons below the age of 18 years are not employable under the Kenyan law and the retirement age in Kenya is 60 years.

Out of the eight different occupations selected based on the number of accidents reported, four were steel making industries based in Nairobi and Athi River with a combined total of about 1000 workers and had reported a total of 187 accidents, plastic making industry with 415 workers, having reported 45 accidents, paper making industry with 205 workers with 34 reported accidents, printing industry with 180 workers having reported 30 accidents and horticultural industry employing 365 workers with 30 reported accidents. In total the eight industries had reported 326 accidents.

Descriptive statistical analysis method including percentages means and standard deviations were used and the results were presented in form of tables. Further analysis of data was done by use of SPSS where variances, significant levels and correlation factors were analyzed and tabulated. The accident frequency data from the DOSH1 form was being linked to the data on the level of subjective fatigue of workers at different times of the day and analysis on relationship between the two was assessed. 

The wider objective of this study was to establish the relationship of accidents with time of a working day and to identify factors that contribute to accidents, including the influence of fatigue on the frequency of occurrence of occupational accidents in Kenya. To achieve this objective the study relied on both desktop study and field data under the following specific objectives (1) to determine the number of accidents that occurred in Nairobi metropolitan between 2008 and 2009, (2) to evaluate the variation of time and frequency of accident occurrence (3) to establish whether there is any correlation between accident frequencies and the fatigue level of workers. In this paper we report mainly results of the first two objectives, whose data was mainly from desktop study and partly field data. The third objective will be reported in another upcoming paper.

Accident as a Function of Time

The results from DOSHS revealed that a total of 1472 occupational accidents had been reported in Kenya from 88 workplaces between June 2008 and June 2009. The results further showed that the highest number of accident was reported in eight occupations. Table 1 shows the frequency of accident occurrence at different times of the day.

From Table 1, it is noted that majority of accidents occurred between 10.00 am and 12.59 pm, when a total of 606 (41.17%) occurred with a peak of 226 (15.35%), occurring between 1100 and 1159 hours. This is the period when workers are most active and already getting fatigued by the job. There is a sharp decline between 1300 and 1359 hours with only 74 (5.03%) accidents reported. The rise in accidents again picked from 1400 to 1759 hours when a total of 448 (30.43%) accidents were recorded with a peak of 182 (12.36%) between 1600 and 1700 hours. This is the time when workers have been re-energized and rested. 

Table 1: Variation of Accident Occurrence with Time of Day

The Types of Industries Sampled

Table 2 shows the types of industries that were picked for the field study and the number of accidents that had been reported from each industry. From the table it is observed that steel related industries reported the highest number of occupational accidents. Large scale steel making, steel rolling mill and steel fabricating accounted for 48, 41 and 56 accidents respectively.

Table 2: The Nature of Industries that were evaluated

Demographic Profiles of Workers

Table 3 shows the profiles of the respondents. From the table, it can be observed that the largest number of workers were males. The majority of the workers were aged between 26 to 35 years, representing 49%.

From the same table it is observed that manual workers occupy 84% of the workforce in the sampled industries. 

Most workers usually worked for between 8 and 9 hours or more in a day, with only 15% working for eight hours or less. 61% of the respondents have reached primary school level, 8% secondary level and only 11% having college education. This can be explained by the fact that employees in these industries are mainly blue colour workers. The majority of workers interviewed were manual labourers 84%, 10% being supervisors with just 6% being office workers. 

Breaks during work varied with the different workplaces. Most of the workers got less than one hour break, with 54% getting 45 minutes break, 21% getting 30 minutes break and only a quarter getting one hour break. None of the workers reported getting more than one hour break. 

The study shows average hours of sleep obtained in 24 hours was 6.5 hours. 83.4% of respondents getting less than 8 hours sleep, with 16% reported getting 8 hours of sleep and less than one percent (0.6%) reported more than 8 hours of sleep per night. Further the majority of workers, 92%, reported having to work six days a week and only 8% having at least two days off in a week. 

In the sampled workplaces the most common method of payment was monthly rate, 45% with 30% receiving weekly wages and 25% getting paid on daily basis. 

Table 3: Profiles of Respondents

From Table 1, it is noted that majority of accidents occurred between 10.00 am and 12.59 pm. This is the period when workers are most active and already getting fatigued by the job. The sharp decline between 1300 and 1359 hours can be explained by the fact that this is the lunch hour in Kenya and this can explain the small number. Most workplaces that do manufacturing, workers go for lunch in shifts between 1200 to 1400 hours to avoid disruption of work. The second rise from 1400 to 1759 hours coincides with the time when workers have been re-energized and rested, whereas the minimum for the day between 1800 and 1859 hours comes at the time when most of the workers have either left their workplaces for home or a fresh shift may be starting for the day. 

These trends are in agreement with O’Neill and Panuwatwanich [9], where they reported that productivity starts with a low at the beginning of a day, peaks in the late morning then drops off towards the end of the day. In the same study they concluded that a higher level of fatigue is associated with lower level of productivity (lower LUF). In a study cited by Gatonye Gathura in the Standard newspaper of 13th Nov 2017, “It’s established that most accidents occur around just before the workers take a lunch break and it has been called 'lunch time effect',” The study came up with 10 main reasons for the increasing number of accidents at construction sites, top of these being reluctance to invest in safety, lack of training in safety and failure by regulators to enforce safety regulations.

Similar observations were reported by Hanecke et al. [10], where they reported accident peaks at 1000 and 1100 hours, a drop between 1200 and 1300 hours and a second peak at 1400 and 1500 hours for the German working population. They stated that they could assign any specific reason that could be assigned to the findings of their research. It is not easy to specify a single reason due to varied nature of the workplace environments and work culture. Weycer [11], argues that time of day, the time an employee spends on a certain task or performs repetitive tasks, environmental factors, such as poor indoor air quality and noise, worker’s personal factors, as well as a person’s age and health are factors that can lead to accident. 

In an investigation of occupational accidents among factory workers in Babadogo Industrial Area in Ruaraka -Nairobi, between September 1998 and December 1998, Boaz, found out that up to 47.2% of respondents have had occupational accidents in the previous twelve months under study, while 2.8% have had accidents at least 15 times or more and at least 38% of the injured workers did not report accidents to their employers. He also reported that accidents rates vary with time of the day with peaks at 12.00 noon (18.1%) and at 3.00 p.m. (21.0%). In the same study it was also shown that a significant number of workers had low level of education and they recommended training of workers, as this could be a contributing factor in accident causation. In their study on causes of accidents and time of day, Williamson and Feyer [12] have stated that in terms of absolute numbers, fatalities were most common in the late morning or early afternoon. They further found out that behavioural factors were the most common causes of fatalities at all times, but most common in the early hours of the morning.

The high response return rate of questionnaires from the field study, where a total of 316 questionnaires were returned out of the 320 sent out (98.7%) was due to the presence of assistants during the filling of the questionnaires. The observation that steel fabrication and large scale steel making are the industries with the highest number of occupational accidents may be attributed to the nature of work and the type of machines involved in those occupations, where there are many mobile machines and large amounts of metal cutting activities.

It was observed that the largest number of workers were males and 49% of the total respondents were aged between 26 to 35 years. This is logical because majority of industrial workers in Kenya are males due to the physical nature of work involved. This also coincides with the 7% were office workers, which is the same percentage of female respondents. In these types of industries female workers are deployed mainly in offices as secretaries and clerks. Employees in these industries are mainly blue colour workers, which explains the reason for most workers usually working for between 8 and 9 hours or more in a day, with only 15% working for eight hours or less. Majority of the respondents have only basic educations level with only 11% having college education. This explains why the large number of manual workers a small percentage being office workers. The college educated staff are mainly at the supervisory level.

The prolonged performance of repetitive tasks without the adequate chance of rest and recovery, coupled with low level of education, may result in an occupational overuse injury. Most of the workers got less than one hour break and of the workers getting more than one hour break. These are factors that lead to fatigue which is known to be detrimental to work performance and a risk factor for accidents because a fatigued worker has a reduced cognitive capacity.

Fatigue reduces a person’s power of judgment and can lead to accidents because it directly affects a number of key physical and mental abilities needed to carry out even basic motor tasks e.g. impaired concentration, poor judgment, reduced hand and eye coordination and reduced vigilance and slowed reaction time. These effects may be reduced or eliminated when a person has had adequate break and is fully rested. Sufficient time spent away from the work environment allows partial recovery from fatigue, which subsequently improves performance and reduce risks to accidents. 

The study shows average hours of sleep obtained in 24 hours was 6.5 hours and the majority of workers, have to work six days a week. This means the worker has very little time to recover thus raising the risk of fatigue. The short sleep hours may arise from waking early so as to report to work by the reporting time. Many workers commute long distances from their residences to places of work and traffic in Nairobi is chaotic during rush hours.

It is known that inadequate sleep and inadequate break time may increase levels of fatigue due to insufficient recovery time. Weycer [11] reported that sleep deprivation is a cause of workplace fatigue. He further argued that a fatigued worker is far more likely to miss critical steps in a safety process, forget safety precautions and misjudge or completely overlook hazardous conditions. La Duke [13] reports that a sleep-deprived worker is also far more likely to misjudge the height at which he/she is working, how much clutter could cause a trip, the speed of a forklift and the traction of a work surface.

Multiple sources quoted by Chan, found in La Duke [13], list fatigue as one of the top five causal factors in workplace incidents, so while experts may attribute upward of 90% of workplace injuries to unsafe behavior, most fail to answer the question of why a worker behaved unsafely. This study also showed most (63%) of the workers felt that fatigue does not affect the quality of their work and even fewer (26%) workers felt that fatigue affected their safety at work. This could be interpreted that, either the workers felt job insecurity if they reported that they were fatigued or the workers are not aware of factors that can cause accidents in the workplaces.

The type of contract engagement terms and mode of work compensation may also contribute to risks of accidents. For the workers who are paid per day the amounts usually depends on how much work was accomplished. Piece work for this category of workers, meeting or even surpassing the target is their driving force. These categories of workers more often than not are willing to work extra hours to earn more. They sometimes even forego or shorten their breaks in order to get more work done and get maximum pay.

The study concludes that the prevalence of occupational accidents is high and accidents occurrence varies with time of working day starting from low in the peaks in the late morning and late afternoon. We further conclude that fatigue is a risk factor in occupational accidents. We recommend that DOSHS should sponsor research to highlight the underlying factors in occupational accidents and ensure training of workers in basic accident preventive mechanisms [14].

Acknowledgement

The authors wish to appreciate the Directorate of Occupational Safety and Health Services for allowing and availing their accident reporting forms (DOSH 1).

Funding

This research did not have external funding. It was funded from own resources.

1. Williamson Government of Kenya. Occupational Safety and Health Act, 2007.

2. Kemei R. and J. Nyerere. “Occupational accident patterns and prevention measures in construction sites in Nairobi County, Kenya.” American Journal of Civil Engineering, vol. 4, no. 5, 2016, pp. 254–263.

3. Mwangi F.N. and R. Oduor. An investigation of the causes of accidents and health hazards on construction sites and their management in Kenya (case study of Nairobi County). Unpublished thesis, Department of Real Estate and Construction Management, School of Built Environment, University of Nairobi, 2016.

4. Makori G.O. et al. “Evaluation of factors that contribute to occurrence of accidents at construction sites in Nairobi County.” Scientific Research Journal (SCIRJ), vol. 6, no. 8, August 2018.

5. Statista Research Department. “Annual number of deaths and accidents at work worldwide.” Statista, January 2016

6. International Labour Organization. Encyclopedia of Occupational Health and Safety, 2005.

7. Hsiao H. and P. Simeonov. “Preventing falls from roofs: A critical review.” Ergonomics, vol. 44, no. 5, 2001, pp. 537–561.

8. Swaen G.M.H. et al. “Fatigue as a risk factor for being injured in an occupational accident.” Occupational and Environmental Medicine, vol. 60, 2003, pp. i88–i92.

9. O’Neill, C. and Kriengsak Panuwatwanich. “The impact of fatigue on labour productivity: case study of dam construction project in Queensland.” Proceedings of the 4th International Conference on Engineering, Project and Production Management (EPPM 2013), 2013.

10. Hanecke, K. et al. “Accident risk as a function of hour at work and time of day as determined from accident data and exposure models for the German working population.” Scandinavian Journal of Work, Environment & Health, vol. 24, suppl. 3, 1998, pp. 43–48.

11. Weycer, M. “The impact of worker fatigue on workplace injuries and employment-related accidents.” Construction Site Injuries, Personal Injury, March 2019.

12. Williamson, A.M. and Anne-Marie Feyer. “Causes of accidents and the time of day.” Occupational and Environmental Medicine, 2007, pp. 158–164. Published online September 2007.

13. La Duke, P. “Industrial safety and hygiene news.” Industrial Safety and Hygiene News, April 2014.

14. Ministry of Labour, Directorate of Occupational Safety and Health Services (DOSHS). Annual Occupational Safety Report, 2017.

Appendix 1 DOSH From 1