|Year : 2016 | Volume
| Issue : 1 | Page : 25-32
Knowledge of occupational hazards among sawmill workers in Kwara state, Nigeria
Busayo Emmanuel Agbana1, Alabi Oladele Joshua1, Moses A Daikwo2, Loveth Olufunto Metiboba3
1 Department of Community Medicine, Faculty of Clinical Sciences, College of Health Sciences, Kogi State University, Anyigba, Kogi, Nigeria
2 Department of Biochemistry, Kogi State University, Anyigba, Kogi, Nigeria
3 Health Services Unit, Kogi State University, Anyigba, Kogi, Nigeria
|Date of Web Publication||13-Apr-2016|
Busayo Emmanuel Agbana
Department of Community Medicine, Faculty of Clinical Sciences, College of Health Sciences, Kogi State University, Anyigba, Kogi
Source of Support: None, Conflict of Interest: None
Background: This study was aimed at assessing the knowledge of sawmill workers on occupational hazards in Kwara State.
Subjects and Methods: It was a cross-sectional analytical study using a multi-stage sampling technique to recruit sawmill workers into the study group in Kwara State. One hundred and ninety-six workers who had been in continuous employment in sawmill factories for a minimum of 6 months were studied. Semi-structured questionnaire adapted from British Medical Council questionnaire on occupational hazards was used for data collection. A 15-point scale was used to assess knowledge of respondents by awarding 1 and 0 point to correct and wrong responses, respectively. Respondents with total score of >5, 5-7 and >7 were classified as having poor, fair and good knowledge of occupational hazards. The data generated were entered and analysed using SPSS version 16 computer software. A P > 0.05 was considered to be statistically significant at 95% confidence level for the study.
Results: The knowledge of sawmill workers on occupational hazards was low, 61.7% of the respondents had poor knowledge, whereas 15.8% had good knowledge. Half of the respondents knew that exposure to hazards could be reduced by limiting their work hours to a maximum of 8 hours per day. More than three-quarters had experienced noise, closely followed by heat and injuries among the study group.
Conclusion: Sawmill workers experience various work-related hazards and health problems. This study revealed the need for an increased knowledge on occupational hazards and its prevention among sawmill workers in Kwara State.
Keywords: Health problems, knowledge, occupational hazards, sawmill workers
|How to cite this article:|
Agbana BE, Joshua AO, Daikwo MA, Metiboba LO. Knowledge of occupational hazards among sawmill workers in Kwara state, Nigeria. Niger Postgrad Med J 2016;23:25-32
|How to cite this URL:|
Agbana BE, Joshua AO, Daikwo MA, Metiboba LO. Knowledge of occupational hazards among sawmill workers in Kwara state, Nigeria. Niger Postgrad Med J [serial online] 2016 [cited 2020 Nov 25];23:25-32. Available from: https://www.npmj.org/text.asp?2016/23/1/25/180176
| Introduction|| |
Occupational health could be said to have started with the Italian doctor Bernadino Ramazzini in the early part of the 18 th century when he set into motion a drive for the recognition of the role of occupations in the dynamics of health and disease.  Occupational health can be defined as the sum total of all the activities and programmes that are engaged upon with the aim of attaining and maintaining the highest level of health and safety for all people who are engaged in any type of work whatsoever.  Occupational health does this through the approaches of disease prevention, safety assurance and general health promotion. Hazards are work materials, substances, work processes or conditions that may result or predispose one to accidents, injuries or diseases. Occupational hazards are degree or risk posed by activities and programmes engaged upon at workplace. 
Sawmilling is the process of breaking down of timbers into further different sizes of boards after passing through various machines in the sawmill plant.  Sawmill workers are grouped into machine operators, saw technicians, dust packers, overseers, wood loaders, machine off-loaders and administrative staff with different duration of exposure to wood dust at the workplace.  Several studies have shown direct relationship between various occupational-related diseases and sawmill work. Therefore, assessing knowledge of hazards among sawmill workers would be cardinal in providing promotive, preventive, curative and rehabilitative occupational health services to sawmill workers.
Adverse health effects of wood dust arose from poor practices of occupational safety measures among sawmill workers. It is estimated that at least two million people are routinely exposed occupationally to wood dust worldwide.  Workers in sawmill and other wood industries exposed to a variety of natural chemicals, fungi and bacteria in raw barks and woods, and all these have been associated with diverse occupational illnesses and hazards, including cancers.  Research in occupational exposures in sawmills has suggested that the workers in sawmills are at risk of developing allergic disorders, lung diseases, some nasal tumours, deafness and cataracts. This has been linked to hazards such as dust (28.1%) and noise (26.1%) which according to respondents interviewed were the major hazards, they were exposed to. 
World Health Organization (WHO) revealed that poor occupational health and reduced working capacity of workers may cause economic loss up to 10-20% of the gross national product (GNP) of a country.  Occupational injuries alone account for more than 10 million disability-adjusted life years or healthy years of life lost whether to disability or premature death and 8% of unintentional injuries worldwide.  Poor occupational health and reduced working capacity of workers may cause economic loss up to 10-20% of the GNP of a country (WHO, 1994). Globally, occupational deaths, diseases and illnesses account for an estimated loss of 4% of the GDP.  A survey conducted in 2007/2008 by Health and Safety Executive on work-related illness estimated 34 million lost work days, 28 million due to work-related illness and 6 million due to workplace injury. 
Lack of comprehensive occupational health services policy, poor infrastructure and funding, insufficient number of qualified occupational health and safety practitioners and general lack of adequate information are among the main drawbacks to the provision of effective enforcement and inspection services in most African countries. ,
A healthy workforce is vital to sustainable social and economic development of a nation by promoting high productivity and economic gain which are positive effects of work on health.  These have not been possible due to poor compliance to health and safety standards in developing countries, especially in small and medium size workplaces. 
The study is expected to contribute or help to improve the knowledge of the sawmill workers on various hazards associated with the wood dust and ways to reduce their exposure to these hazards by the use of occupational safety equipment. The data generated from this study will help policy makers to develop guidelines to regulate operations of sawmill industries in Nigeria, as information on health status of the sawmill workers would be revealed.
This study assessed the knowledge of occupational hazards and identified work hazards sawmill workers are exposed to.
| Subjects and Methods|| |
Kwara State was created on 27 th May 1967 as one of the 12 states that replaced former four regional structures, the Northern, Western, Mid-Western and Eastern regions of Nigeria. Benue State was later carved out of both Benue-Plateau and Kwara States, taken away the Igala speaking part of old Kwara State. Kogi State was again later carved away from the Eastern half of the state (still), and now consists of only the western part of the original and second Kwara States. It is located in the geographical and cultural confluence of the North and South of Nigeria (North Central Zone). 
The major religions are Islam and Christianity, Yoruba is the main language spoken by the people, whereas minority ethnic groups are Hausa, Igbo, Fulani and Nupe. The people of the state are mainly civil servants, farmers, traders, artisans and organised private sectors.
There are 1092 sawmill workers registered with the association of sawmill workers in Kwara State. There are 65 sawmill industries in the three senatorial districts of which they are all privately owned.  There is only one tertiary health centre in the state, University of Ilorin Teaching Hospital (UITH), the Epidemiology and Community Health Department offers promotive, preventive, curative and rehabilitative occupational health services to factory workers including sawmill workers when the services are needed. The state has 17 general hospitals, one in each local government area (LGA) with the exception of Ilorin West that has two general hospitals. There are primary health care centres and private hospitals.
This was a cross-sectional analytical study. The study population consisted registered workers in sawmill industries in Kwara State. There were 65 sawmill industries in the three senatorial districts of Kwara State. Sawmill workers were grouped into machine operators, saw technicians, dust packers, overseers, wood loaders, machine off-loaders and administrative staff. A typical sawmill workshop in the state consists of open space that encloses plain machine and circular machine for cutting woods and slab shops, where cut wood is displayed for commercial purposes.
Sample size determination
The minimum sample size for the study for each group was calculated using the formula for the comparison of two proportions  (comparing the study group with the control group).
n = Minimum sample size
u = Standard normal deviate (SND) corresponding to the power of 80% (one-tail) = 1.28
v = SND corresponding to the confidence level of 95% for one-tailed test = 1.96
p1 = 25.4% (prevalence of respiratory symptoms among sawmillers resulting from poor knowledge of occupational hazards among sawmillers in Ile-Ife. 
p2 = 12.1% (prevalence of respiratory symptoms among administrative workers resulting from poor knowledge of occupational hazards among sawmillers in Benin). 
To compensate for non-response sample size was calculated as follows using the formula:
ns = n/0.90
Assuming 10% non-response rate
Where ns = Sample size to compensate for non-response
n = calculated sample size
0.90 = Taken as 90% response rate is anticipated
ns = 176/0.90
ns = 196.
One hundred and ninety-six sawmill workers were recruited for the study group and another 196 electrical traders as control.
Multi-stage sampling technique was adopted in this study using the following stages:
Simple random technique (balloting) was used to select six LGAs out of the 16 available LGAs in the state. All the zones in the selected LGAs were involved in the study. Thus, Kwara Central, Ilorin East LGA with eight zones, Kwara South, Ifelodun LGA with four zones, Oke-Ero LGA with three zones, Ekiti LGA with five zones, Kwara North, Moro LGA with two zones and Edu LGA with three zones were used.
All the zones in each selected LG (total 25) were included in the study.
The list of registered sawmill workers in each selected LGA (sampling frame) was generated, and added up and proportional allocation was further used to select the eligible respondents in the selected LGAs.
Systematic sampling technique was used to select final respondents in each stratum/section. The sampling frame was arrived at by counting the total number of registered sawmill workers in each register of the local government.
Selection of controls
From the list of electrical workers obtained from the register of Kwara State Traders Association. A sampling frame of eligible respondents (electrical traders) was obtained (567). Systematic sampling technique was used to select the control. The list of registered electrical traders in selected LGAs as in study group were obtained (sampling frame), proportional allocation was further used to select the eligible respondents in each LGAs and sampling interval was obtained. Simple random sampling technique (balloting) was used to select the first respondent; subsequent respondents were selected by adding sampling interval until the final respondent was selected.
History of current ill health was ascertained, and those who were not apparently healthy were exempted.
A purpose designed interviewer-administered semi-structured questionnaire was used for the data collection in the survey. It was adapted from British Medical Council questionnaire on occupational hazards. The questionnaire elicited information on the respondents' socio-demographic characteristics and knowledge of occupational hazards.
Scoring system was used for assessing the knowledge of the respondents in the study group on the hazards of sawdust on health by awarding marks based on their responses. The maximum score for each of the question on knowledge was 1 mark, and each wrong response and missing response carried 0 marks. The total score for each of the respondents was obtained by the summation of the scores obtained from each of the question on the knowledge of the respondent on the hazards of sawdust mentioned above.
The maximum score accrued to knowledge on occupational hazards was 15. Respondents with a total score of >7 were classified good knowledge on the hazards of sawdust, whereas respondents with total score of between 5 and 7 had average or fair knowledge on the hazards of sawdust and respondents with total score <5 had poor knowledge on the hazards of sawdust in the workplace. This categorisation was informed by review of literatures. The questions used in scoring total knowledge were internally consistent and reliable with a Cronbach's alpha value of 0.839.
Data were collected from the respondents by the researcher and trained research assistants using interviewer-administered questionnaire. The research assistants are Master of Public Health students. They were trained on data collection, using the interviewer-administered questionnaire. They were required to explain to respondents in situations where respondents did not understand the questions.
Data were entered using and SPSS version 16 (SPSS Inc. Released 2007. SPSS for Windows, Version 16.0. Chicago, SPSS Inc.) software package before the analysis of the data. Chi-squared test was used for qualitative data such as sex, educational status, religion, marital status and ethnicity, whereas t-test was used for continuous variables that were normal in distribution such as age, height, weight and income. Fisher exact statistical test of association was used when any of the expected cells is <5. Level of significance was set at a P < 0.05.
Ethical approval for the study was obtained from the Ethical Review Committee, UITH, Ilorin. The ethical approval dated from 30 th May 2013 through 29 th of May 2014.
| Results|| |
Socio-demographic characteristic of respondents
As seen in [Table 1], the mean age of the study group respondents was 37.78 ± 14.7 years, whereas that of the unexposed group was 36.09 ± 13.2 years. There was no statistically significant difference in the mean age of the two groups (P = 0.797). The mean income of the study group respondents was N24,622 (±5310), whereas that of the control group was N25,702 (±7060) (N = Naira). The difference in income between the control and study group respondents was statistically significant (P = 0.000).
Majority of the respondents in the study group 177 (90.3%) and in the unexposed group 179 (91.3%) were males. About half of the respondents in the study group 96 (49.0%) and more than half 116 (59.2%) in the control group had completed their secondary education. Among the study group, 26 (13.3%) of respondents did not have any form of education. However, all the respondents in the control group had one form of education or the other. Similarly, among the control group, a greater proportion 45 (23.0%) had completed their tertiary education compared with 36 (18.4%) among the study group. The observed difference among the two groups with respect to level of education was statistically significant (P < 0.001).
Occupational characteristic of respondents
The respondents who had spent < 10 years in employment were 85 (43.4%) and 121 (61.7%) made up a greater proportion of study and control groups, respectively. Less than one-third 28.6% and 23.5% of the study and control group had spent 10-19 years duration of employment as seen in [Table 2]. The observed difference between respondents and duration of employment was statistically significant (P = 0.002). The mean number of years spent in the study was 13.27 ± 10.19 years, while the control grouP value was 9.16 ± 8.22 years, though similar, but there was statistically significant difference between the groups.
With respect to the history of dusty job, a higher proportion of sawmill workers respondents 27 (13.8%) had been exposed previously to dusty job compared to 13 (6.6%) among the control group. This difference was statistically significant.
Respondents place of job training
Majority 179 (91.3%) and 182 (92.8%) of the respondents in the study and control groups, respectively, had apprenticeship training, whereas very few 6 (3.1%) and 6 (3.1%) were formally trained in the technical school in the study and control groups, respectively.
Knowledge of occupational-related hazards among sawmill workers
Knowledge score of the sawmill workers on occupational hazards was poor. As shown in [Table 3], about two-third of the respondents 121 (61.7%) had poor knowledge, whereas 31 (15.8%) of the respondents had good knowledge and 44 (22.5%) of the respondents had average knowledge among the study group.
Respondents knowledge of hazard reduction by working limit of 8 hours
Half of the respondents 98 (50%) knew that exposure to hazards could be reduced by limiting the working hours to a maximum of 8 hours/day, while 98 (50%) lacked this knowledge.
Respondents' knowledge of dust affecting health
A greater proportion of the respondents (138 or 70.4%) claimed that they knew that dust could affect their health in the workplace, whereas 58 (29.6%) lacked this knowledge.
Respondent's knowledge of acceptable maximum working hours per day
A greater proportion of the respondents 123 (62.8%) claimed that they did not know the maximum acceptable working hours per day, whereas 73 (37.2%) had the knowledge.
Predictors of poor knowledge of occupational-related hazards among the sawmill workers from logistic regression
Hausa ethnic group was more likely to have poor knowledge of occupational-related hazards (odds ratio [OR] 4.832, 95% confidence interval [1.039-22.467], P = 0.045) compared with other ethnic groups. Furthermore, the odds of having poor knowledge of hazards were 1.739 times more among divorced sawmill workers as compared with married sawmill workers (OR 1.739, 95% CI = 0.106-28.565; P > 0.05). As shown in [Table 4], those with primary education were more likely to have poor knowledge of workplace hazards when compared with tertiary form of education, as odds of having poor knowledge were 2.936 higher among the primary level of education (OR 2.936, 95% CI = 0.965-8.928, P > 0.05).
|Table 4: Predictors of poor knowledge of occupational-related hazards among the sawmill workers from logistic regression|
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Self-reported health hazards experienced by respondents
More than three-quarter 157 (80.1%) had experienced noise, followed by heat 118 (60.2%) and injuries 66 (33.7%) among the study group as evident in [Table 5]. However, among the control group, the most common hazards were heat 145 (74.0%), noise 99 (50.5%) and electric shock 41 (20.9%), respectively. The differences in the presence of noise, heat, injuries, electric shock and slips/fall were significantly different between study and control groups.
|Table 5: Types of self - reported health hazards experienced by respondents|
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Work-related health problems experienced by respondents
The most prevalent health problems among the study group were stress and exhaustion, 153 (78.1%), followed by eye irritation 102 (52.0%). Similarly, among the control group, the most prevalent health problems were stress and exhaustion 120 (61.2%) followed by eye irritation 49 (25.0%). The difference in the prevalence of difficulty in breathing, eye irritation, skin irritation, accident and stress/exhaustion were statistically significant between the study and control groups. [Table 6] shows work related health problems experienced by respondents.
| Discussion|| |
The socio-demographic characteristics of the respondents showed that the mean age of the respondents was 37.78 ± 14.69 and 36.09 ± 13.24 years among the sawmill workers and the control group, respectively. The mean age of respondents from this study was higher than what was found among carpentry workers in Kaduna, North West Nigeria, and Sunsari, Nepal, Jute Mill workers where the mean values were 24.60 ± 0.61 and 28.43 ± 7.58 years, respectively. , However, it was similar to that found among sawmill workers, in Ilorin, dock and elevators workers in the port city of Vancouver, Canada. 
Majority of the respondents were males and this was not out of place considering the strenuous and dusty nature of the job. The male dominance was similar to that found among Danish furniture industry in Denmark  and among flour processing bakery workers in Transkei, South Africa. 
The highest educational qualification of more than half of the respondents in the control group and close to half of the respondents in the study group was a secondary school. The finding was similar to the findings of Awoyemi in Ilorin, North Central Nigeria, where the secondary school was the major qualification among sawmill workers studied.  The rest had either no formal education at all or only primary education as in the control group of this study. These findings may not be surprising as the majority of these workers were unskilled who only required apprenticeship to carry out their job.
Almost all the respondents in the study (91.3%) and control group (92.9%) received their training
through apprenticeship. This was similar to the findings in Northern Nigeria, where all the respondents interviewed received their training through apprenticeship.  The shortcoming of apprentice training is that the trainee is exposed to only what the trainer knows and practices.
The most common work-related hazards experienced by the sawmill workers were noise, heat, injuries and electric shock. This finding was similar to the result obtained from studies in Ilorin, Osogbo and Colombia. ,,
The most common self-reported health problems by respondents in both study and control groups were stress and exhaustion followed by eye irritation. The stress or exhaustion observed among the study population could aggravate the severity of injuries as a result of increased risk of accidents. This was similar to findings of a study carried out in Benin City that found a high prevalence of work-related ocular trauma injury among sawmills workers.  The stress or exhaustion found in this study was not surprising as majority of the respondents in both study and control group spent more than 5 days at workshop and this could reduce productivity at work apart from the tendency to increase the likelihood of predisposing workers to occupational hazards, while the occurrence of eye irritation in study group could be due to non-availability of eye goggles for the respondents.
Majority of respondents in the study groups had a poor knowledge of the danger of sawmill dust and health effects of the dust. This was probably due to the fact that most of the respondents received their training through apprenticeship and thereby rely on their masters for information on the job especially knowledge of hazards associated with wood dust of which the master too probably have insufficient knowledge. This lack of formal training for the job might not allow the workers to learn about the hazards associated with their occupation as well as possible precautions to be taken in the practice of their vocation. The poor knowledge could explain hazards and probably health problems associated with sawmill workers due to their poor knowledge hence exposure of workers to wood dust and subsequent development of diverse occupational diseases.
This finding was similar to what was obtained in a related study done in Kota Bharu, (Turkey), and Kelantan that reported poor knowledge of occupationally related hazards among sawmills workers. 
The predictor of having poor knowledge of work-related health hazards was found to be low level of education as the likelihood of poor knowledge of hazards decreased as the level of education increased. This could have been due to the fact that being educated increases access to information education and communication materials and increased awareness on various workplace hazards. The implications of this are that sawmill workers are likely to develop various respiratory symptoms and occupational lung diseases of obstructive and restrictive patterns.
| Conclusion|| |
Sawmill workers experience noise, heat and injury compared to heat, noise and electric shock among the control group; the two groups had stress and exhaustion as the most common work-related health problems.
Based on the findings of the study, the following recommendations are made with the hope that if implemented there will be improvement in the health of sawmill workers and subsequently boost their productivity.
The Local Government Authority (Health Department) in partnership with Federal Ministry of Labour and Productivity and other relevant agencies and trade unions need to organise periodic workshops and training programmes on health and safety to cover proper education on workplace hazards, types and proper use of different protective devices to safeguard their health. There is a need to re-emphasise formal training of sawmill workers by the technical schools to increase awareness and knowledge of work-related hazards.
Financial support and sponsorship
Tertiary Education Trust Fund.
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]