Journal of Occupational Safety and Health, December 2013, Vol 10, No. 2

JOURNAL OF
OCCUPATIONAL
SAFETY AND HEALTH
National Institute of Occupational Safety and Health
National Institute of Occupational Safety and Health (NIOSH)
Ministry of Human Resources Malaysia
December 2013, Vol 10, No. 2
ISSN 1675-5456
PP13199/12/2012(032005)

Journal of Occupational
Safety and Health
Editor-in-chief
Ir. Haji Rosli bin Hussin
Executive Director
NIOSH, Malaysia
Secretariat
Editorial Board
Prof. Dr. Krishna Gopal Rampal
Universiti Kebangsaan Malaysia
NIOSH, Malaysia
Ir. Daud Sulaiman
Fadzil Osman
NIOSH, Malaysia
Raemy Md. Zein
NIOSH, Malaysia
The Journal
- Aims to serve as a forum for the sharing of research ﬁndings and information across broad areas in
Occupational Safety and Health.
- Publishes original research reports, topical article reviews, book reviews, case reports, short
communications, invited editorial and letters to editor.
- Welcomes articles in Occupational Safety and Health related ﬁelds.
Associate Editors
Prof. Dr. Ismail Bahri
Universiti Kebangsaan Malaysia
Dr. Jeffereli Shamsul Bahrin
BASF East Asia Regional Headquartes Ltd.
Dr. Abu Hasan Samad
Prince Court Medical Centre
Mohd Rashidi Rohmad
Roslina Md Husin
Nor Akmar Yussuf

i
December 2013 Vol.10 No.2
Contents
Journal of Occupational
Safety and Health
1. The Origin of Workers Hearing Level – A Finding Based on Chances of Occurrence
By Gan Chun Chet, MSc (UK), BSc (Hons) (UK), Peng
2. Occupational Lung Carcinogens and Factors in Relation to Lung Cancer Risk
Fauziah Nordin1,3, Richard Booton2, Paul O’Donnell2, Philip Barber2, Andrew Povey1 1Centre for
Occupational & Environmental Health, Faculty of Medical & Human Sciences, The University of
Manchester, United Kingdom 2North West Lung Centre, Wythenshawe Hospital, Manchester, United
Kingdom 3Institute for Public Health, Ministry of Health Malaysia, WP Kuala Lumpur, Malaysia
Corresponding author:
Dr Fauziah Nordin,
Institute for Public Health,
Ministry of Health Malaysia,
Jalan Bangsar, 50590 WP Kuala Lumpur,
Malaysia
(Tel: +60322979400, Fax: +60322823114, email: drfauziahn@iku.moh.gov.my)
3. OHSAS 18001 and MS 1722 Certification Initiatives Prove the Commitment to
Sustainability
Wai Onn Hong
Processing Department, Genting Plantations Berhad,
10th Floor, Wisma Genting, Jalan Sultan Ismail, Kuala Lumpur, Malaysia
Tel: +60 3 2333 6506 Fax: + 60 3 2161 9689 Email: hongwaionn@gmail.com
4. The Extent of Predictability of Noise-Induced Problems – A Cross-Over from the
Healthy Limit to Off-Limit Conditions
By Ir. Gan Chun Chet
MSc (UK), BSc (Hons) (UK), PEng
5. Prevalence Of Work Related Musculoskeletal Disorder Among Port Workers:
Quantitative Analysis At The Physiotherapy Centre Of Malaysian Shipping Industry,
Selangor
Izham Zain¹, Azrul Anuar¹, Asrina Asri¹, Shamsul Azhar²
¹ KPJ Healthcare University College
² Physiotherapy Department, Malaysia Shipping Industry, Selangor
Corresponding author: zainizham@yahoo.com.my
1 - 11
13 - 25
27 - 36
37 - 50
51 - 66

This page has been intentionally left blank

Journal of Occupational Safety and Health
1 1
The Origin of Workers Hearing Level – A Finding Based on
Chances of Occurrence
By Gan Chun Chet, MSc (UK), BSc (Hons) (UK), Peng
_____________________________________________________________________
Abstract
The paper writes on the possible origin of off-limit cases found in a noise
project conducted internally in a factory in Malaysia. Out of 691 sampled workers’
that attended audiometric test results (some repeated), it was found that the mode of
hearing ability is between 20 to 30 dB depending on individual worker’s age ranging
from 20 to 55 years. Out of the total results, approximately 100 workers are above a
limit defined here in this paper as the off-limit condition. The chance of a worker
originating from a good condition to an unhealthy condition is about 1 percent. The
data are tabulated to show that a sway pattern could be an explanation of workers’
origin. Although the data is profound, there is no evidence of a trace due to a short
test period. Possibilities are highlight here to outline the severity of a cross over to the
unhealthy condition (here defined as the off-limit condition). Some advises are
mentioned here with individual susceptibility on the matter though there is no data to
substantiate. Further findings are required to show a trace. In conclusion, the severity
is highlight. A chart, developed to know the limits of hearing ability, is illustrated
based the findings.
_____________________________________________________________________
Introduction
Scientific data induced to formulate a theory or depicted from an observation
and subsequently utilizing an existing theory to explain a fact, are used as a base for
an answer or a comparison. However, scientific disillusionment exists, drawing from
the base of data in question where different views exist from the same set of
observations. While scientific breakthroughs are remarkable yet a theory is falsifiable
if other research is concluded differently. This leave a myth to the underlying truth
based on the truth of facts due to a possible change in a hypothetical assumption or a
change in a theory, etc. Is this possible?
The following are findings of a real case on noise induced problems in a
factory. The trace of historical origin of these workers’ hearing ability is unknown.
The data is profound because it shows the actual truth but unknown to others. After
going through the analysis, my personal opinion is that the truth lies within these
individuals. Here defined the off limit cases (red line) as shown in the diagram below,

2 2
grids with utterly puzzled and astonished findings. A possible explanation to the
situation is that sway pattern might had happened and a possible origin based on the
possibilities might be the explanation. This article tries to uncover the origin of their
hearing abilities based on the chances of occurrence in each of the sway pattern are
illustrated in the sections.
Background of the Research Data
The total number of workers attended the test, including repeated cases,
amounts to 691 in number. The hearing abilities of the workers are checked using an
audiogram by an independent test company. The workers average hearing abilities at
500, 1000, 2000 and 3000Hz were plotted against age; regardless of the number of
year of service with the company. This is shown in graph 1 (Right Ear). This article
investigates the possible origin of hearing ability of Right Ear when they are at the
age of 16 to 20 years old (started and joined the industry). Some of these workers
discovered at later age that they had hearing problem. The findings found that about
10 – 16 percent of the workers are able to hear loud noises (possibly with hearing
impaired). Regardless of the area noise in this factory or area noise in previous
company, the graph below shows their hearing abilities.
Graph 1 : Workers Hearing
Abilities (Right Ear Only)

3 3
Methodology
The method is based on possible sway patterns of a worker that might not have
eluded noisy area. However, a worker might be employed with a noise problem.
Unfortunately nearing to the end of employment, between the age of 40 to 55,
problems were noticed. This is shown in the graph. It is thoughtful to know but the
actual origin (occurrence) cannot be traced. Possibly these patterns exists, as shown in
the graph below (2 to 6). The possible path called the “sway patterns”. In the diagram
below, the ability either started off from a healthy condition or an off limit condition.
Both these conditions are the possible origin. At the end of employment is here called
the “end destination” of a sway pattern. The numbers of off limit cases were counted
to calculate the possible occurrences shown in a grid matrix below. The findings are
as shown in the next section.

4
4
Category 3
Category 2
Category 1
A B C
2
Graph 3 : From Category 3
(Sheet 2)
Category 3
Category 2
Category 1
A B C
1
Very rareGraph 2 : From Individual
Categories (Category 1, 2 or 3)
(Sheet 1)
Category 3 : Caution Level
Category 2 : Healthy Level
Category 1 : Very Good Level

5
5
Category 3
Category 2
Category 1
A B C
3
(Sheet 3)
A B C
4
(Sheet 4)

6
6
Findings
The following are the findings from graph 2 to 6. The numbers of hearing
ability in each of the possible pattern are counted. This is tabulated in table 1 below.
Separated by “below 10 counts”, “10 to 19 counts” and “above or equal to 20 counts”,
most of these workers are in the two circles shown the table below.
The most probable occurrence is 40 cases as defined here by the count of
occurrences above the limit (red line), could originated from Category 2 and swayed
to C. The second most probable occurrence is 38, with the origin from Category 1 and
the end destination is C. The probable occurrences are tabulate in table 2 together
Category 3
Category 2
Category 1
Very low level
Graph 6: From Off Limit (Sheet 5)

7 7
with the number of occurrences in descending order. The high chances of origin
shown in the table might have originated from Category 1 or 2 defined here applicable
to this situation.
Discussion
The numbers shows the count in each of the pattern. It does not tell that a
person hearing ability originated from a point above the off limit condition or from
any point on the Y-axis of the graphs (2 to 6). In addition, it is not possible to say that
a person will move to a point with certainty after exposure to noise years later. It is to
note that a sway of a possible situation might have originated from these defined
limits, with the possibility that each of the condition is considered independent from
each other.
The pattern cannot compute specifically which employee has a good hearing
ability and later have a problem at the age of 40 to 50. Neither does the pattern shows
that a person in a good condition, as defined, ended up with a problem due to noise
problem in the plant. The patterns are the possibilities of an origin by the count of
occurrence in the sway pattern.
By counting the possibility of an occurrence, out of an estimate off limit cases
with reference to the mode occurrence, the chance on one person originated from
either side of the limit is approximately 1 percent. Out of the number of workers (691
records), about 109 records a fifty fifty chance on either sides. Half of which might be
healthy, with an increment of approximately 1 percent on an addition case.
The Development of A Chart Defining the Possibilities of An Origin
The chart as shown below represents and shows the origin in a graphical form.
It could be used as to explain a point of reference origin in this situation.

8 8
Category Possibly From The Following Sound Limit
Off Limit 21 and 40 dB
Category 3 17 to 20 dB
Low Level Less than 8dB!
Category of age range
[O] – 16 to 20 years old
[A] – 30 to 40 years old
[B] – 40 to 50 years old
[C] – 50 to 60 years old
[D] – More than 60
Diagram 1: A Pattern that is to Be Avoided
From
Category 3
Category 2
Category 1 10
20
View 1
Off Limit
A
Age
40
0
10
20
0
30 40
0
50 60
B C DO
Noise, dB
See View
1
To
Limit

9 9
The shaded area, as shown in the graphic above, shows the sway pattern of a
worker from healthy condition (below the red line) to either [A], [B] or [C]. This is to
be avoided. The [O]s are unknown condition as the problem occurs at a very early
age. The [D] end destination are old or elderly people.
The hearing level should be below the limit by avoiding exposure to unwanted
sound.
• Some Advises regarding Noise Problem Based on this Situation
Different factory conditions will have different impact on the workers. The
hearing ability of every worker is different, whether they are new or an existing
worker. A few advises as listed below.
Opinion alone not substantiated by data is not real. A change in theory is a
change of a hypothetical question forming a paradox. In this case, the origin of
workers noise level, based by factual data by the count of workers falling in the sub-
diagram, is in fact forming a set of suggestions and fitting it into the box.
In this article, it is only to suggest that there might be possibilities that the off
limit workers might have came from an off limit condition or a healthy condition
(whether Category 1 then Category 2, etc) in the order. It is difficult to conclude that
this is where the workers condition came from.
Disclaiming the facts, that workers are from healthy condition and the cause of
their hearing disability is from the plant, the point of origin cannot be traced exactly.
In fact, in my opinion, it can only be know of possible origins. This is only one plant
that encountered this problem. What about others? The truth lies in the workers
themselves.

10 10
The Line below the Limit (Red Line)
The conditions below the limit are healthy conditions. This line is drawn based
on the majority of the workers being below this limit in clusters due to employment
years shown in graph 1. The general view shows that the workers are healthy below
the red line in the diagram below. The equation to this line is calculated. With this
line, different factors to categorize healthy workers are possible, with a caution region
to warn the workers that the condition might cross above the limit. If this happens,
then the group will be in the possible pattern of origin as highlighted in this article.
Ideally, workers should come in healthy and maintain a healthy condition at
later stage of their employment. Noise induced problems are caused by prolong
exposure of unwanted sound into the ear. Age related losses might be the reason for
the increased in hearing ability of the workers at later age. The problem about noise is
that if it is detected will cause a failure in hearing ability. If it is purely due to age
related reasons, as already known, then the reason of workers moving up to a new
level of hearing ability is due to an over exposure can be identify, assuming that there
is no disease to the ears or other medical reasons linked to this, which requires
qualified medical practitioner to inform and a cure.
The plot of audiometric results shows the location of a person hearing level.
The results from the workers in the graph above (graph 1) show remarkable truth in it.
Worker’s Age (Year)
20
dB
30
dB
20 60
10
dB
30 40 50
Normal Hearing
Ability
Category 3
Category 2
Category 1
Category 1 : Very Good
Category 2 : Good
Category 3 : Caution
Chart 1: A Noise Chart of Healthy Workers

11 11
The inadequacy of health information might be the reason to a high number of off
limit cases. It is might be only known at that instant of time that the ears have been
affected that medical examiners are only able to comfort these patience. It might be
that the workers are not aware of the problem and have caused a shift in hearing.
How is it possible to trace the point of origin at a test or a series of test within
the short time frame? If an earlier test was conducted, there might be able to locate the
origin, subject also to age related losses and other unknown factors like susceptibility,
etc. In this article, it is stated by rough approximation that the count of numbers in the
pattern of possible sway from the start of employment might have happened.
Otherwise, without the count, it is just a guess.
In Conclusion
The purpose of the article is to highlight the severity of the problem. Noise
induced problem should be avoided. From a layman point of view, it is advised to
consult an expert in this area or an ear specialist should problem arise.
Please note that the off limit in this article is based on the general mode limit
of a plant. It does not mean that it is applicable to other situations. Please refer to an
ear consultant for medical advice for the permissible levels.
(Note : The data is also key in by the author to analyze the problem)
The author expresses his personal opinions on the above out of interest to the topic and
indemnifies himself from the readers for any charges. It is not to depict any information from
this article and is only to be referred to a qualified medical practitioner for expert advice if a
problem is encountered. The article writes on the possible origin based on data collected to
help other to avoid a hearing problem.
Author Contact:
chun_gan@hotmail.com
Info to Reviewer:
Qualifications:
MSc (UK), University of Manchester Institute of Science and Technology in Operations
Management
BSc (Hons) (UK), University of Manchester in Mechanical Engineering
Professional Registration:
PEng Registration, Board of Engineers Malaysia, Mechanical Branch (Registration No.
12539)

13
Occupational Lung Carcinogens and Factors in Relation to Lung
Cancer Risk
Fauziah Nordin1,3
, Richard Booton2
, Paul O’Donnell2
, Philip Barber2
, Andrew Povey1
1
Centre for Occupational & Environmental Health, Faculty of Medical & Human Sciences, The
University of Manchester, United Kingdom 2
North West Lung Centre, Wythenshawe Hospital,
Manchester, United Kingdom 3
Institute for Public Health, Ministry of Health Malaysia, WP Kuala
Lumpur, Malaysia
Corresponding author:
Dr Fauziah Nordin,
Institute for Public Health,
Ministry of Health Malaysia,
Jalan Bangsar, 50590 WP Kuala Lumpur,
Malaysia
(Tel: +60322979400, Fax: +60322823114, email: drfauziahn@iku.moh.gov.my )
_______________________________________________________________________________
Abstract
Introduction:
Although smoking is the most important cause of lung cancer, occupational factors can also play
an important role. Worldwide, approximately 10% of lung cancer deaths in men (88,000 deaths)
and 5% in women (14,300 deaths) were attributable to exposure to occupational carcinogens,
referred to the report on the global burden of disease due to occupational carcinogens
Methods:
We examined the risks associated with occupational exposures in a case-referent study of lung
cancer that was carried out between November 1998 to March 2000. Cases were patients attended
a bronchoscopy clinic at the North West Lung Centre, Wythenshawe Hospital in Manchester
during that period who were subsequently found to have lung cancer. Referents were patients
found not to have lung cancer at bronchoscopy.
Results:
There were 121 subjects in the study (39 cases, 82 referents). Smoking status was significantly
associated with lung cancer risk: the odds ratio of having lung cancer in ever smokers (vs never
smokers) was 3.21 (95% CI: 1.02 - 10.07). There were also significant association between
number of cigarettes smoked (p = 0.01) and years smoked (p = 0.04) with lung cancer risk.

14 2
Years of exposure to occupational carcinogens was also associated with the development of lung
cancer (p = 0.02). Workers who were exposed for 45 years or more, had an increase risk when
compared to those who had worked for less than 17 years (OR, 95% CI = 2.54, 1.12 – 6.34). Job
category was found to be borderline significant with lung cancer risk. The adjusted odds ratio of
having lung cancer among unskilled manual job worker (vs management, professional & associate
professional) was 4.75 (95% CI: 1.06 - 21.4).
Conclusion:
This study shows an exposure to occupational carcinogens was associated with an elevated lung
cancer risk. Unskilled manual job workers had a higher lung cancer risk compared with other
categories, such as management, professional & associate professional.
Keywords:
Occupational Lung Carcinogens, Lung Cancer, Smoking
_______________________________________________________________________________
1. INTRODUCTION
1.1. Occupational exposure to known lung carcinogens
Lung cancer is the second ranked after bladder cancer among all occupational cancers worldwide
(Hansen, 2008). The risk of occupational substances causing lung cancer depends on certain
occupational characteristics, including the nature of work or job category (direct or indirect
exposure), how much exposure (the quantities), for how long (age of employment, length of
exposure, frequency been exposed), types of the substance (gas or mist form, individual or mixed
form) and whether the substance is organic or non-organic (Hansen, 2008).
The carcinogen list based on IARC category (“Lists of IARC evaluations according to IARC
monographs - International occupational safety & health information centre,” n.d.) such as list A
(confirmed human carcinogen) and list B (suspected human carcinogen), is still being updated
periodically to uncover the harmful effects particularly for those where there are still substantial
uncertainties. A recent population-based study found an increased risk of lung cancer in list A
occupation category with OR 1.74 (95% CI 1.27 – 2.38) compared with list B category. Lung
cancer risk in increased in several industrial sectors; the ceramic and refractory brick sector (OR,
95% CI = 2.64, 1.13– 6.19) and nonferrous metals industry (OR, 95% CI = 2.45, 1.31– 4.60)
(Consonni et al., 2010). They estimated that 4.9 % (95% CI 2.0 – 7.8) of lung cancers in men were
attributable to occupation (Consonni et al., 2010).

15 3
1.2. Risk factors and specific occupational lung carcinogen
Based on a recent number of occupations or occupational exposures listed by IARC (“Lists of
IARC evaluations according to IARC monographs - International occupational safety & health
information centre,” n.d.) studies have reported on the magnitude of the association between
specific occupational carcinogen and lung cancer risk. As reported in the IARC and the National
Toxicology Program (NTP) (“Lists of IARC evaluations according to IARC monographs -
International occupational safety & health information centre,” n.d.), workers in a specific job
category and particular type of industry are often at an increased risk of lung cancer. For example,
workers in shoe manufacturing are exposed to a group of carcinogenic substances such as organic
solvents (toluene, xylene, methyl ethyl ketone, formaldehyde), chromium, nickel, arsenic, vinyl
chloride or others (Galán Dávila, Romero Candeira, Sánchez Payá, Orts Giménez, & Llorca
Martínez, 2005).
A cohort study of 7828 workers in a shoe manufacturing plant in USA found a significant excess
of lung cancer deaths with a SMR = 1.36 (95% CI 1.19-1.54)(Lehman & Hein, 2006). This was
associated with exposure to chronic, low levels of organic solvents and the finding has persisted
with increasing years of follow up of the cohort. The evidence regarding the risk of lung cancer
related to solvents continues to emerge. Another study with 6000 subjects in European countries
looking at the exposure to specific organic solvents (acrylnitrile, vinyl chloride and styrene)
reported a significant increase in the risk of lung cancer for ever exposure to acrylnitrile (OR, 95%
CI = 2.20, 1.11 – 4.36) and vinyl chloride (OR, 95% CI = 1.05, 0.68– 1.62). There was a positive
dose-response relationship although not significant, between estimated cumulative exposure
(maximum cumulative exposure compared to non-exposed) and lung cancer risk for both
acrylnitrile (OR, 95% CI = 2.87, 0.85 – 9.66) and vinyl chloride (OR, 95% CI = 1.51, 0.65– 3.47)
(“Lists of IARC evaluations according to IARC monographs - International occupational safety &
health information centre,” n.d.)
Two occupations met the criteria of having sufficient evidence of carcinogenicity for the human
lung, namely painters and welders (“Lists of IARC evaluations according to IARC monographs -
International occupational safety & health information centre,” n.d.). A significant association
between risk of lung cancer and occupational exposure to paint dust (RR, 95% CI = 2.48, 0.88-
6.97) and welding fumes (RR, 95% CI = 1.73, 1.05 – 2.85) has been reported in a large cohort
study in the Netherlands with 58,279 participants (van Loon et al., 1997). The same finding was

16 4
reported in a recent meta-analysis study on lung cancer and welding with 60 studies of welders of
shipyard, mild steel and stainless steel. The combined relative risks (CRR) for lung cancer in all
the welders as compared with non-welders was 1.26 (95% CI 1.20 – 1.32) (Ambroise, Wild, &
Moulin, 2006).
Figure 1: Forest plot of lung cancer risk with occupational exposure
(van Loon et al., 1997),(Ambroise et al., 2006),(Berry, 2004),(Cassidy et al., 2007),(Olsson et
al., 2010),(Scélo et al., 2004)
However the study failed to detect any dose-response relationship between lung cancer incidence
and cumulative exposure to chromium and nickel in welders (Ambroise et al., 2006). The
magnitude of association between occupational exposure and lung cancer risk from previous
studies is summarized in figure 1.
In another study in the Netherlands an increased risk of lung cancer was reported for employment
of 15 years and more in blue collar jobs in the “electronics and optical instruments” industry (RR,
5.02.0
_________________
Asbestos (OR, 95% CI = 1.85, 1.07-3.21)
Vinyl chloride (OR, 95% CI = 1.05, 0.68– 1.62)
Acrylnitrile (OR, 95% CI = 2.20, 1.11 – 4.36)
PAHs (OR, 95% CI = 1.97, 1.16 – 3.35)
Silica (OR, 95% CI = 1.37, 1.14-1.65)
Welding fumes (RR, 95% CI = 1.73, 1.05 – 2.85)
Paint dust (RR, 95% CI = 2.48, 0.88-6.97)
Occupational Exposure
Magnitude of association
____________________
_______________________
____________
____________________________
_______________
1.0

17 5
95% CI = 1.99, 1.18 – 3.35), “construction and homebuilding business” industry (RR, 95% CI =
1.64, 1.21 – 2.22) and “railway company” (RR, 95% CI = 2.40, 1.00 – 5.73) (Preller, Balder,
Tielemans, Brandt, & Goldbohm, 2008). The risk of lung cancer was observed for lengthy
employment in certain high-risk industries and research on specific occupational category is
needed to further investigate causative factors.
The aim of this study was to examine occupational exposures and lung cancer risk in a North West
population. The ultimate aim of this work is to compare the occupational exposure and the
development of lung cancer in previous studies carried out in Wythenshawe, which have been
looking at the factors and determinants for lung cancer risk and susceptibility.
2. METHODOLOGY
2.1. Study population
Self-reported occupational histories and exposures were collected in a case-referent study that was
carried out between November 1998 to March 2000. Cases were patients attended a bronchoscopy
clinic at the North West Lung Centre, Wythenshawe Hospital who were subsequently found to
have lung cancer. Referents were patients found not to have lung cancer at bronchoscopy.
2.2. Occupational exposure analysis
The occupational history was assessed by questions on the employment status, the title of the job,
period of employment and working duration (hours) per week. For each person, information of a
maximum of five occupations was registered, starting with the current or most recent job first and
working backwards. In the few cases where more than five occupations were mentioned, similar
consecutive jobs for different employers were deleted. If more than five jobs still remained, the job
with the least information provided was omitted unless it lasted for a very long time.
The information on occupational exposure was obtained by asking the participants whether they
were exposed to smoke, dust, fumes or asbestos. The type of industry was coded according to the
UK Standard Industrial Classification (2003) and occupation was coded according to the Standard
Occupational Classification (2000), both from the UK Office for National Statistics (ONS) (Office
for National Statistics, 2010).

18 6
2.3. Statistical analysis
Frequencies are presented for categorical data and means with standard deviations for continuous
data. All statistical analysis was carried out in SPSS (version 15.0). Comparisons were made
between two groups (e.g. cases and referents) to determine the risk of lung cancer. χ 2
-test was
used for 2 X 2 table and binary logistic regression was used for variable with 2 or more categorical
groups. Odds Ratio (OR) and its 95% confidence interval (96% CI) was measured to determine the
magnitude of association for occupational and other factors (smoking, alcohol consumption and
family history of lung cancer) with lung cancer risk. The variables were further stratified for
smoking status to control for confounding factor and adjusted odds ratio were then measured.
3. RESULTS
3.1. Study population
There are 121 subjects in the study (39 cases, 82 referents), which 74 (61.2%) of them were men
with a mean age of total study population was 61.1 + 13.7 years old. (Table 1)
Table 1.Frequency distribution of lung cancer incidence by gender and age group
Variable Lung Cancer
Yes No
n (%) n (%)
Total
n (%)
Gender
Male
Female
Age group (years)
< 55
55 - 64
65 - 74
≥ 75
(mean + SD)
29 (74.4)
10 (25.6)
6 (17.1)
10 (28.6)
14 (40.0)
5 (14.3)
64.6 + 10.7
45 (54.9)
37 (45.1)
32 (40.5)
15 (19.0)
18 (22.8)
14 (17.7)
59.7 + 14.6
74 (61.2)
47 (38.8)
38 (33.3)
25 (21.9)
32 (28.1)
19 (16.7)
61.1+ 13.7
3.2. Smoking characteristics and alcohol intake with lung cancer
Smoking status was significantly associated with lung cancer risk: the odds ratio (OR) of having
lung cancer in ever smokers (vs. never smokers) were 3.21 (95% CI: 1.02 - 10.07). The duration of
years cigarette smoked was longer in the lung cancer group with mean of 42.7 + 13.1 years
compared with mean of 32.1 + 16.0 for referents, and was significantly associated with lung cancer
risk. Other characteristics were not significantly associated with lung cancer risk (Table 2)

19 7
Table 2. Smoking characteristics and alcohol intake in cases and referents
Variable Lung Cancer
Yes No
n (%) n (%)
Crude Odds Ratio
(95% CI)
a
Ever smoking
Yes
Nob
Smoking status
Current smoker
Ex-smokerb
Age smoking began
(years)
< 15b
15 - 19
20 - 24
≥ 25
(mean + SD)
Cigarettes smoked
(per day)
1 - 9
10 - 19
20 - 39
≥ 40 b
(mean + SD)
Years smoked
1 - 9
10 - 29
30 - 49
≥ 50
b
(mean + SD)
Passive smoker
Yes
No
b
Ever drink alcohol
Yes
No
b
Alcohol intake
(units per week)
0
b
1 - 13
14 - 27
≥ 28
(mean + SD)
35 (89.7)
4 (10.3)
17 (48.6)
18 (51.4)
22 (62.9)
10 (28.6)
3 (8.6)
0 (0)
15.2 + 2.9
0 (0)
10 (28.6)
18 (51.4)
7 (20.0)
24.0 + 12.6
0 (0)
5 (14.7)
17 (50.0)
12 (35.3)
42.7 + 13.1
17 (43.6)
22 (56.4)
29 (74.4)
10 (25.6)
10 (25.6)
17 (43.6)
6 (15.4)
6 (15.4)
14.5 + 16.1
60 (73.2)
22 (26.8)
23 (38.3)
37 (61.7)
28 (46.7)
23 (38.3)
7 (11.7)
2 (3.3)
16.4 + 3.3
8 (13.6)
11 (18.6)
34 (57.6)
6 (10.2)
21.0 + 12.4
3 (5.9)
19 (37.3)
19 (37.3)
10 (19.6)
32.1 + 16.0
34 (41.5)
48 (58.5)
66 (80.5)
16 (19.5)
17 (21.0)
39 (48.1)
17 (21.0)
8 (9.9)
12.3 + 12.2
3.21 (1.02-10.07)
1*
1.52 (0.65-3.53)
1
1
0.55 (0.22-1.40)
0.54 (0.13-2.36)
0.78 (0.19-3.11)
0.45 (0.13-1.55)
1
0.22 (0.60-0.80)
0.75 (0.26-2.16)
1*
1.09 (0.50-2.36)
1
0.70 (0.29-1.73)
1
1
0.74 (0.28-1.94)
0.60 (0.18-2.02)
1.23 (0.34-4.75)
* significant difference p<0.05.
a
Odds ratio is for incidence of lung cancer in each group versus incidence in
patients in group
b

20 8
3.3. Occupational exposure and lung cancer risk
The variables of occupational characteristic were stratified for smoking status to control for
confounding factor and adjusted odds ratio (aOR) are tabulated in Table 3. Lung cancer risk varied
with job category with an aOR among unskilled manual job workers (vs. management,
professional & associate professional) of 4.75 (95% CI: 1.06-21.36). Exposure to occupational
carcinogens was associated with an elevated but non-significant lung cancer risk: the aOR in ever
exposed (vs never exposed) was 1.93 (95% CI: 0.77-4.82). There was no association with duration
of exposure. Workers who were exposed to smoke or asbestos, had an increased risk when
compared to those who had no exposure: aOR = 3.56 (95% CI: 0.96-13.13) for smoke and aOR =
4.00 (95% CI: 1.10-14.47) for asbestos.
Table 3. Occupational characteristics in cases and referents
Variable
Lung Cancer
Yes No
n (%) n (%)
Crude Odds Ratio
(95% CI)
a
Adjusted Odds Ratio
(95% CI)
c
Employment status
Employed
Not employedb
Job category
Management, professional &
associate professionalb
Clerical and secretarial
Sales and service
Skilled manual
Unskilled manual
Exposure to carcinogen
Yes
Nob
Years of exposure
1 - 17b
18 - 32
33 - 44
≥ 45
(mean + SD)
Exposure to specific carcinogen
No exposureb
Exposed to smoke
Exposed to dust
Exposed to fumes
Exposed to asbestos
5 (12.8)
34 (87.2)
8 (20.5)
7 (17.9)
8 (20.5)
8 (20.5)
8 (20.5)
30 (76.9)
9 (23.1)
13 (43.3)
11 (36.7)
4 (13.3)
2 (6.7)
20.6 + 13.7
9 (23.1)
9 (23.1)
6 (15.4)
6 (15.4)
9 (23.1)
27 (31.7)
55 (68.3)
26 (32.1)
12 (14.8)
24 (29.6)
15 (18.5)
4 (4.9)
46 (56.1)
36 (43.9)
26 (56.5)
10 (21.7)
9 (19.6)
1 (2.2)
18.1 + 13.3
36 (43.9)
9 (11.0)
15 (18.3)
14 (17.1)
8 ( 9.8)
0.30 (0.10-0.85)
1*
1
1.89 (0.56-6.44)
1.08 (0.35-3.34)
1.73 (0.54-5.57)
6.50(1.54-27.4)
2.61 (1.10-6.18)
1*
1
2.20 (0.74-6.51)
0.89 (0.23-3.44)
4.00 (0.33-48.3)
1
4.00 (1.23-13.0)
1.60 (0.48-5.29)
1.71 (0.51-5.71)
4.50 (1.35-14.9)
0.33 (0.11-0.99)
1*
1
2.38 (0.63-9.02)
0.96 (0.27-3.42)
1.97 (0.56-6.94)
4.75 (1.06-21.4)
1.93 (0.77-4.82)
1
1
2.73 (0.81-9.15)
1.09 (0.26-4.55)
1.91 (0.11-33.5)
1
3.56 (0.96-13.1)
0.89 (0.23-3.49)
1.11 (0.30-4.05)
4.00 (1.10-14.5)
* significant difference p<0.05.
a
Odds ratio is for incidence of lung cancer in each group versus incidence in
patients in group
b
.
c
Adjusted odds ratio (aOR) for smoking status

21 9
3.4. Family history of lung cancer and lung cancer risk
Table 4 shows the number of patients with a family history of lung cancer. The majority of the
lung cancer patients had no family history of lung cancer (94.9%) and there was no significant
association with lung cancer risk.
Table 4. Family history of lung cancer in cases and referents
Variable
Lung Cancer
Yes No
n (%) n (%)
Odds Ratio
(95% CI)
a
Relatives with lung cancer
No
Yesb
Unknown
37 (94.9)
2 (5.1)
0 (0)
75 (91.5)
6 (7.3)
1 (1.2)
1
0.68 (0.13-3.51)
a
Odds ratio is for incidence of lung cancer in each group versus incidence in patients in group
b
4. DISCUSSION
In this study, we examined the risks associated with occupational exposures in a case-referent
study of lung cancer. The completed self-reported occupational histories and exposures were
analysed. This is a small pilot study using general job questionnaires to assess the occupational
exposure and the findings will be used as part of the reference for the main study that will be
undertaken in the same population.
From this study, smoking status was significantly associated with lung cancer risk, with three-fold
higher risk to get lung cancer. The risk also associated with the duration of years smoked. The
findings were consistent with the other studies (Doll & Hill, 1950), (Peto, Lopez, Boreham, Thun,
& Heath, 1992) which indicating the duration of smoking is one of the strongest determinants of
lung cancer risk in smokers. The risk increases with the number of years a person has smoked and
also the number of cigarettes smoked (Lubin & Caporaso, 2006).
Different job category having different types of exposure to occupational hazards particularly
occupational carcinogens. In this study, unskilled manual job workers had a higher lung cancer
risk compared with other categories, such as management, professional & associate professional. It
is suggested that those who worked in the unskilled manual workers are prone to be more exposed
to different kind of occupational carcinogens.

22 10
Exposure to occupational carcinogens was associated with an elevated lung cancer risk; however
there was no association with duration of exposure. Workers who were exposed to smoke or
asbestos had an increased risk when compared to those who had no exposure. It is consistent with
other studies which showed workers who are exposed to smoke or asbestos, which include in the
list A IARC list are in the higher risk to get the occupational lung cancer (Driscoll et al., 2005),
(Berry, 2004).
5. CONCLUSION
This study shows an exposure to occupational carcinogens was associated with an elevated lung
cancer risk. Unskilled manual job workers had a higher lung cancer risk compared with other
categories, such as management, professional & associate professional.

23 11
6. REFERENCES
Ambroise, D., Wild, P., & Moulin, J.-J. (2006). Update of a meta-analysis on lung cancer and
welding. Scandinavian Journal of Work, Environment & Health, 32(1), 22–31.
doi:10.5271/sjweh.973
Berry, G. (2004). The Interaction of Asbestos and Smoking in Lung Cancer: A Modified Measure
of Effect. Annals of Occupational Hygiene, 48(5), 459–462. doi:10.1093/annhyg/meh023
Cassidy, A., ’t Mannetje, A., van Tongeren, M., Field, J. K., Zaridze, D., Szeszenia-Dabrowska,
N., Boffetta, P. (2007). Occupational exposure to crystalline silica and risk of lung cancer: a
multicenter case-control study in Europe. Epidemiology (Cambridge, Mass.), 18(1), 36–43.
doi:10.1097/01.ede.0000248515.28903.3c
Consonni, D., De Matteis, S., Lubin, J. H., Wacholder, S., Tucker, M., Pesatori, A. C., … Landi,
M. T. (2010). Lung cancer and occupation in a population-based case-control study. American
Journal of Epidemiology, 171(3), 323–333. doi:10.1093/aje/kwp391
Doll, R., & Hill, A. B. (1950). Smoking and Carcinoma of the Lung. British Medical Journal,
2(4682), 739–748.
Driscoll, T., Nelson, D. I., Steenland, K., Leigh, J., Concha-Barrientos, M., Fingerhut, M., &
Prüss-Ustün, A. (2005). The global burden of disease due to occupational carcinogens.
American Journal of Industrial Medicine, 48(6), 419–431. doi:10.1002/ajim.20209
Galán Dávila, A., Romero Candeira, S., Sánchez Payá, J., Orts Giménez, D., & Llorca Martínez, E.
(2005). Lung Cancer Risk in Shoe Manufacturing. Archivos de Bronconeumología ((English
Edition)), 41(4), 202–205. doi:10.1016/S1579-2129(06)60426-6

24 12
Hansen, H. (Ed.). (2008). Textbook of Lung Cancer, Second Edition (2nd ed.). Informa
Healthcare.
Lehman, E. J., & Hein, M. J. (2006). Mortality of workers employed in shoe manufacturing: an
update. American Journal of Industrial Medicine, 49(7), 535–546.
Lists of IARC evaluations according to IARC monographs - International occupational safety &
health information centre. (n.d.). Retrieved May 1, 2012, from
http://www.ilo.org/legacy/english/protection/safework/cis/products/safetytm/iarclist.htm
Lubin, J. H., & Caporaso, N. E. (2006). Cigarette smoking and lung cancer: modeling total
exposure and intensity. Cancer Epidemiology, Biomarkers & Prevention: A Publication of the
American Association for Cancer Research, Cosponsored by the American Society of
Preventive Oncology, 15(3), 517–523. doi:10.1158/1055-9965.EPI-05-0863
Office for National Statistics, E. L. and S. A. (2010, June 23). Standard Occupational
Classification 2010 (SOC2010). Office for National Statistics. Text. Retrieved July 29, 2013,
from http://www.ons.gov.uk/ons/guide-method/classifications/current-standard-
classifications/soc2010/index.html
Olsson, A. C., Fevotte, J., Fletcher, T., Cassidy, A., ’t Mannetje, A., Zaridze, D., Boffetta, P.
(2010). Occupational exposure to polycyclic aromatic hydrocarbons and lung cancer risk: a
multicenter study in Europe. Occupational and Environmental Medicine, 67(2), 98–103.
doi:10.1136/oem.2009.046680
Peto, R., Lopez, A. D., Boreham, J., Thun, M., & Heath, C., Jr. (1992). Mortality from tobacco in
developed countries: indirect estimation from national vital statistics. Lancet, 339(8804),
1268–1278.

25
13
Preller, L., Balder, H. F., Tielemans, E., Brandt, P. A. van den, & Goldbohm, R. A. (2008).
Occupational lung cancer risk among men in the Netherlands. Occupational and
Environmental Medicine, 65(4), 249–254. doi:10.1136/oem.2006.030353
Scélo, G., Constantinescu, V., Csiki, I., Zaridze, D., Szeszenia-Dabrowska, N., Rudnai, P., …
Boffetta, P. (2004). Occupational Exposure to Vinyl Chloride, Acrylonitrile and Styrene and
Lung Cancer Risk (Europe). Cancer Causes & Control, 15(5), 445–452.
Van Loon, A. J., Kant, I. J., Swaen, G. M., Goldbohm, R. A., Kremer, A. M., & van den Brandt, P.
A. (1997). Occupational exposure to carcinogens and risk of lung cancer: results from The
Netherlands cohort study. Occupational and Environmental Medicine, 54(11), 817–824.

27 1
OHSAS 18001 and MS 1722 Certification Initiatives Prove the
Commitment to Sustainability
Wai Onn Hong
Processing Department, Genting Plantations Berhad,
10th
Floor, Wisma Genting, Jalan Sultan Ismail, Kuala Lumpur, Malaysia
Tel: +60 3 2333 6506 Fax: + 60 3 2161 9689 Email: hongwaionn@gmail.com
__________________________________________________________________________________
Abstract
Malaysia’s palm oil industry is growing in complexity and successively to succeed on the global
level by accounts for about 36% of the word production of palm oil [1]. But, Occupational Health
and Safety (OHS) issues are still problematic areas that need to be addressed by all parties
concerned in this industry. In the olden days, unlike construction or manufacturing industry, palm
oil industry was green in OHS management system. However, due to stringent in the legislative
enforcement in the past few years, it has lead some of the plantation companies to develop OHS
management system, which are based on Occupational Health and Safety Assessment Series
(OHSAS), towards corporate sustainability. Sustainability is not about paying lip-service to the
latest corporate buzzword; neither is it about superficially meeting minimum requirements for the
sake of compliance. Rather, sustainability is a core value that lies at the heart of the companies’
business conduct. In practical terms, this means strive to operate with due consideration for the
interest of all stakeholders by making the health and safety of all workers a priority. This paper
describes the certification of OHSAS 18001 and MS 1722 in Genting Plantations Berhad (GENP)
prove the commitment to sustainability by forming guiding principle on safety management.
Further, this paper also demonstrates that the implementation of safety management can help to
reduce the accident rate, especially fatal accident.
Keywords: palm oil industry, OHSAS 18001, MS 1722, safety management, sustainability
_________________________________________________________________________________
Introduction
The working population is a valuable asset to our nation especially palm oil industry, therefore we
cannot afford to have many accidents which will eventually jeopardize our valued human resources.
Workers involved in palm oil industry can be divided into two broad categories: those working in
the plantations and those employed to work in the palm oil mill. The former are mainly the
harvesters who harvest the fresh fruit bunches while the second category includes the workers
employed to operate and maintain machineries in palm oil mills. Accidents involving both of these
categories are not rare in Malaysia. Statistic of occupational accidents in the country published by

28 2
Department of Occupational Safety and Health (DOSH) show that the total number of accidents as
well as the number of fatalities has not much improvement between 2007 and 2011 (Figure 1).
In view of OHS issues still remain an important matter in palm oil industry throughout the decade,
government has in fact stringent in the legislative enforcement since recent years. It is at a time like
this that the palm oil industry needs to consolidate and be proactive in meeting upcoming
challenges. The palm oil industry also needs to meet challenges with more evidence of sustainable
safety management system throughout the implementation.
This paper not only describes the certification of OHSAS 18001 and MS 1722 in Genting
Plantations Berhad proves the commitment to sustainability by forming guiding principle on safety
management, but also demonstrates that the implementation of safety management can help to
reduce the accident rate, especially fatal accident.
The OHSAS 18001 and the MS 1722 standard enable an organization to manage its OHS risks and
improve its OHS performance. The requirements of the standard are intended to address OHS for
employees, temporary employees, contractors and other personnel on site rather than the safety of
products and services. The standards provide a more effective method of protecting employees and
others from workplace injuries and illnesses and demonstrate management commitment in meeting
OHS requirements [2, 3, 4].

29 3
Figure 1: National accident rate per 1,000 workers and fatality rate per 100,000 workers from year 2007 – 2011
GENP’s Response and Initiative
In Malaysia, legislation concerning OHS for palm oil industry comprises the following Acts and
Regulations:
a) Occupational Safety and Health Act 1994
b) Factories and Machineries Act 1967
c) Electricity Supply Act 1990
d) Fire Services Act 1994
Although with all these Acts and Regulations in placed, it is always an argument that who should
responsible and accountable for accident prevention, employers, employees or relevant authorities.
GENP’s commitment to these areas, which are of paramount importance to the Group’s overall
sustainability agenda, was displayed clearly through important certification initiatives undertaken at
the palm oil mill level. As part of the palm oil mill improvement efforts, GENP’s palm oil mills
embarked on a third party, independent verification exercise of their OHS Management System,
guided by a road map began in year 2010. Under the standards subscribes, OHS management
system composed of standards, procedures and monitoring arrangement that aim at promoting the
OHS of people at workplace and to protect the public from accident shall be established and
implemented.

30 4
Implementation of OHSAS 18001 and MS 1722
The initiatives on certification of OHSAS 18001 and MS 1722 started with gap analysis at GENP’s
oil mills to determine the status of existing OHS processes and controls in place. Recommendations
were provided to bridge the gaps in that analysis. Having completed the gap analysis, a series of
training were held to cover variety of topics, including ISO Awareness, Hazard Identification, Risk
Assessment and Risk Control, Safe Operating Procedure and Emergency Preparedness. This was
followed by the challenging task of preparing documentations in accordance with the unique
features of each palm oil mill and these have been structured into four levels as follows:
• Level 1 - Manual. This document gives an overview of the OHS Management Systems, includes
the policies and all the non-operations procedures. It also outlines the structure of the
documentation used in the OHS Management System.
• Level 2 – System Procedure. These documents specify principles, strategies and the general
procedures of operations related actions (system process).
• Level 3 – Operations Procedure Documents. These documents specify in details the current
practices or processes in any operations related action (core process).
• Level 4 – Records, forms and checklists. These documents further specify the manner of
processes in an action. They also demonstrate conformance to specified OHS Management
Systems.
The pyramid of OHS management system documentation is shown in Figure 2.
Figure 2: The pyramid of OHS management system documentation

31 5
Meanwhile, at the operation sites, proactive measures were taken to improve the safety and health
performances. At the same time, safety and health awareness was also actively promoted at the
palm oil mills during daily morning muster and periodically training. Last stage of this project is to
conduct internal auditing of OHS performance. The internal auditors aim to ensure compliance with
OHSAS 18001 and MS 1722 standards thereby ensuring the success of OHS programs through the
implementation of safety management system. In additional, internal audit also serves as a platform
to identify OHS opportunities for continual improvement. After about one year implementation
period, SIRIM QAS International Sdn Bhd, the country’s leading and internationally-recognized
certification, inspection and testing body, was engaged to carry out a series of audits, culminate in
all palm oil mills successfully securing recommendation for certification of their Health and Safety
Management System under OHSAS 18001 and MS 1722 by the end of January 2011.
Implementation stages of OHSAS 18001 and MS 1722 was summarized in Figure 3.
Figure 3: Road map for implementation of OHSAS 18001 and MS 1722
Guiding Principle on Safety Management
OHSAS 18001 and MS 1722 implemented by GENP is applicable company-wide and information
is disseminated to all employees in order to ensure successful implementation. A generic safety
management system has been established in order to sustain OHSAS 18001 and MS 1722. In this
management system, a number of important elements are specified and these are related to the
setting of policy and creation of plans and organizational capacity to realize that policy (Plan), the
analysis of hazards and effects leading to planning and implementation of those plans in order to
manage the risks (Do) and the control on the effective performance of those steps (Check). A

32 6
feedback loop is in placed to enable all the information gained are sent to management for their
respond (Act/Feedback). [2, 3, 4, 5]. Further, there is an element extended out of the loop where
the organization has to establish an OHS management system with continual improvement activities
in order to ensure the sustainability of OHSAS 18001 and MS 1722 subscribes. This safety
management system is simplified in Figure 4.
Figure 4: Generic OHS management system with elements of Plan-Do-Check-Act
Evolution of Safety Culture
The systematic approach to safety management in OHSMS is not the end the journey as
management system is a primarily rational inventions, defined on paper in offices and capable of
objective in audits. The next stage is to build generative safety culture. As the premier level in safety
cultures, generative safety culture is the situation where people carry out what they know has to be
done not because they have to, but they want to. In other words, it is where the safe behavior is fully
integrated into everything the organization does [5].

33 7
In order to promote generative safety culture, GENP encouraging to have combination of a top-
down commitment to improve and the realization that the workforce is where that improvement has
to take place. To have this premier safety culture implant, information is actively sought and
responsibilities are shared among employees and employers. Furthermore, new ideas are welcomed
in generative safety culture regardless it is from which level of employees, workers, staffs or
executives.
Figure 5 shows the evolution of safety culture in GENP. Initial stage of safety culture at individual
oil mill might vary from reactive to proactive due to different level of safety awareness.
Nevertheless, all have successfully built and implant premier level of generative safety culture after
implementation of OHSMS.
Figure 5: Evolution of safety culture in GENP after implementing safety management
The effect of Implementing OHSAS 18001 and MS 1722
The most important and measurable benefit resulting from safety management system and evolution
to generative safety culture is decrease in occupational accident rate and fatality rate. Figure 6
summarizes the statistic of occupational accidents recorded during last five years in GENP oil mills.
2007 2008 2009 2010 2011 2012*
Number of
accidents
5 9 13 6 4 3
Number of
fatalities
2 2 1 0 0 0

34 8
Accident rate
per 100
workers
0.35 0.62 0.85 0.38 0.25 0.19
Fatality rate
per 100
workers
0.14 0.14 0.07 0.00 0.00 0.00
Remark: Data updated as at June 2012.
Figure 6: Statistic of occupational accidents recorded during last five years in GENP oil mills
Figure 7 clearly shows that there was significant decrease in accident rate since year 2009 after
implementation of Occupational Health and Safety Management System. Furthermore, the accident
rate of 0.38 and 0.25 per 100 workers recorded in year 2010 and 2011 were greatly lower than
national accident rate for the same period, 0.65 and 0.62 per 100 workers respectively.
Figure 8 shows the fatality rate per 100 workers from year 2007 to 2012 (June). It was clearly shows
that implementation of OHSMS proves the commitment to sustainability as GENP oil mills
continuously recorded zero fatal accident since year 2009.
Figure 7: Accident rate per 100 workers from year 2007 – 2012 (June)

35 9
Figure 8: Fatality rate per 100 workers from year 2007 – 2012 (June)
Conclusion
Owing to increase in complexity of operations, the palm oil industry has become more challenging
than ever before. Plantation companies are faced with the challenge of having to close monitor their
business to minimize occupational hazards, while simultaneously trying to sustain profits in a
competitive marketplace. In Malaysia, government agencies such as DOSH have done their part to
promote safety awareness in the industry in order to reduce accidents rate in workplace. However,
the key to proper safety execution is neither through strict guidelines nor stringent in enforcement,
but through an effective safety management initiative, first approved by an organization’s top
management, then integrated via specific safety management implementation tools and system, and
finally by continuous follow up and monitoring to ensure quality and continuous improvement. In
order to prove the commitment to sustainability, GENP has to ensure consistency in the adoption
and implementation of the OHSMS among Group operating units as only those companies that take
on aggressive safety management will prove the commitment to sustainability and guarantee the
improvement of work conditions, the decrease of occupational accident rate as well as lowering of
the occupational fatality rate.
Acknowledgement
The writer would like to thank the Senior Vice President – Group Processing, Genting plantations
Berhad for permission to present this paper...

36 10
References
[1] Foreign Agricultural Service, United States Department of Agriculture, 2012, Oilseeds: World
Markets and Trade.
[2] Department of Standards Malaysia, 2005, Occupational Safety and Health Management Systems,
Part 1: Requirements.
[3] Department of Standards Malaysia, 2003, Occupational Safety and Health Management Systems,
Part 2: Guidelines.
[4] OHSAS Project Group, 2007, Occupational Health and Safety Management Systems –
Requirements.
[5] Patrick Hudson, 2001, Safety Management and Safety Culture The Long, Hard and Winding Road
(Edited by Warwick Pearse, Clare Gallagher and Liz Bluff). Occupational Health & Safety
Management Systems, 3-32.

37
The Extent of Predictability of Noise-Induced Problems – A
Cross-Over from the Healthy Limit to Off-Limit Conditions
By Ir. Gan Chun Chet
MSc (UK), BSc (Hons) (UK), PEng
___________________________________________________________________________
Abstract
The paper examines the method of predicting noise induced problems among factory
workers. The pattern of an impaired condition above the off-limit condition defined here is
exponential. The age-related losses are linear with approximately 3.3 dB decibel loss below
the age of 35 at an interval of 10 years on the job, and 4 decibel dB loss above the age of 35
(inclusive) at the same interval.
The equations of age losses show that hearing losses due to noise exposure are caused
by hearing deterioration. The projection based on the data shows the extent of the prediction.
The extent of predictability for off-limit conditions derived from the records depicted shows
that it is applicable to some situations but not all. It is impossible to postulate all types of
patterns, but the pattern as shown, exponential in nature, can be utilised by other similar
occurrences.
The facts derived from the data show that hearing loss is inevitable, noise exposure
among workers must be avoided. The number of workers with hearing level higher than the
normal level, between 10 to 16 percent of the total number of data sampled from the factory
workers, is an indication that the noise-induced problem exists. It is applicable to many other
factories and we hope that in a range of other situations, such problems can be prevented.
Due to these facts, the extent of predictability of these equations are worth noting. The
aim of this paper to show that the data points can be traced, with the explanation that the
sway patterns occurred as denoted by the exponential growth pattern of defined interval.
That could account for the data observed.
___________________________________________________________________________
Introduction
The issue of whether a cross-over does occur during the course of a workers’ duration
on the job is relevant when the hearing condition deteriorated from a normal condition to a
worst condition. The extent of the deterioration after an exposure which caused the
impairment is subject to the variable of the accumulated amount of noise that a person is
exposed to during his or her work duration. Due to this, the starting condition, i.e. the initial
state of an individual at start off is important to note. The matter of an impairment arises

38
when heavy exposure to noise causes hearing deterioration, so that the condition of the
person at work is a possible explanation of the deterioration. It is important then to establish
whether the person is susceptible to the given noise level while others are not.
This study seeks to provide a possible basis for prediction. However, subject to the
condition of the factory or the activity of a particular worker, the mathematical equation
derived from the test result of a scatter plot (based on real audiometric test result) points to a
possible explanation that an exponential equation that can be extended forward or backwards
to find out the person past or a possible future condition. This is applicable to off-limit
conditions.
Age-related losses are definitely a factor to be considered. In relation to the facts as
shown in the scatter plot, the drift from a normal hearing level to off-limit level defined the
need to inform others of the susceptibility of workers. Due to this, keeping a good record of
the audiometric test result is suggested here to ensure that workers hearing levels are
protected. It was also noticed that there might be cases where the hearing condition has been
affected due the work environment. This paper points to a “cross-over” range that noise
custodians should be aware of should this be the situation.
Thus, due to the range that some might question and the subjective initial point, the
equation, an exponential growth in nature, postulates the situation, assuming that a healthy
condition is the healthy beginning and that the work condition affects the worker (this does
not rule out the possibility that the worker had the impairment already when entering the
firm). The result as shown is important: there are many precautions that can be taken to
prevent the shift, but susceptibility is noticed from the scattered plot where the same scatter
pattern below 35 years old or above 35 years old shows that workers in the same age group
have the same deterioration pattern (as contrasted with a slightly lower level for workers
under age 35). Thus, one should take special note of a possible increase regardless of age,
where exposure to noise is dangerous, which will cause this pattern as shown.

39
Methodology
The mathematical equation suggested here is an exponential curve for off-limit cases
defined here as workers with hearing ability above the normal hearing limit. The workers
initial condition started off healthy (below the healthy limit) and swayed to an off-limit
condition known as the limit line. The high points observed in the scatter plot show that it is
exponential behaviour. The starting point began from a healthy condition due to the steep
exponential curve as shown here, and the increase is significant. The cross-over ranges for
two data points are estimated here in Graph 1a to show that it is true in this condition where
even younger workers (early 20s, see Graph 1b) are found with the same condition as
compared to older workers; this is reflected in the scattered plot. As for older workers in their
30s and 40s, these cross-over ranges as shown here deteriorate exponentially to their
conditions as plotted, and the situation as shown is significantly high.
The method employed here shows the growth patterns of deterioration for these off-
limit workers. With the equations derived (typically exponential in nature), the projection is
feasible and the starting point assured, with probability of percentage based on counts of
these data points discussed in a later section. Considering that the pattern is true, then it
should be exponential, subject to these deterioration factors (that the sign of aging exists in
these off-limit cases).
The exponential equation has three (3) variables showing the sign of deteriorated hearing.
The equation is as follows:
y = A + B exp (C * x) – (1) where y is the backward or forward projection of worker
hearing level in decibel dB, x is the age of the worker, A,B or C are the variables that signify
(a) the starting hearing level (A+B at x=17), (b) the hearing deterioration (the invert of a
growth pattern) C at x=current age/result,
These aging losses can then be subtracted from y depending on the workers’ age to calculate
the impact of noise on their hearing.
  The predictability of normal limit shows that it is an increment of factored linear lines
due to age-related losses, within the intervals (of 10 years), and it is significant that the
hearing losses show about 3.3 decibel dB below the age of 35 and about 4 decibel dB above
the age of 35 (inclusive). This paper proposes that susceptibility be investigated by recording
the test result and the equations verified (or confirmed) by other results to prove that these

40
could be the projected patterns. With this, a plausible explanation is elaborated, although the
equations might not be applicable to some situations. The equations derived from the scatter
plot are explained in the next section.
Derivation of The Mathematical Equations
‐ Off-Limit Conditions
The equation that represents this pattern is derived to be exponential, as stated in the
previous section. It has an age-related loss factor which is embedded into this equation
(equation 1). By removing the age losses symptom, the equation becomes as follows: 
y = { A + B exp (C * x) } – { 0.3 x + 16.5 } + 22.1 ; for less than 35 years of age - (2)
y = { A + B exp (C * x) } – { 0.4 x + 14 } + 22.1 ; for more than 35 years of age - (3)
(inclusive of 35)
; where A, B and C are variable coefficients depending on individual case
The first part of the equation is exponential, whereas the second part of the equation is
linear due to age-related losses and the third part of the equation is the baseline of a person
(the starting point at 17 years old, or just having joined the industry as an employee. Equation
(2) and (3) are corrected due to age-related losses. Omitting the first part and the second part,
this will signify the present reading at x is equal to the age of the person at the time of the
test.
The exponential curve shown here is based on an observed pattern on the scattered
plot. The so-called sway pattern is explained elsewhere [1]. These are the possible
explanations for these situations based on observation. Below are the explanations for
workers with healthy limits.
By shifting the curve away from the y-axis to a starting age, the equation that includes
this is
y = A + B exp [C * (x-21)] ; where 21 is the age at which a person that enters the
company with baseline checked. – [equation 2/3 shift]

41
‐ Below the Healthy Limit
The limit line defined here is the off-limit reading of the workers where there is no
“cross-over” above this limit line. The result is clustered below this defined limit line. Due to
this, there are certain factors that are considered to be true, i.e. that an age-related loss will
occur and in this internal study, it was found that the hearing level will deteriorate about 3.3
dB among workers below age 35 and 4 dB above 35 years of age (inclusive of 35) at an
interval of 10 years. In fact, every year, the hearing ability of a worker deteriorates on
average of 0.33 dB below 35 years old or 0.4 decibel above 35 years of age (inclusive 35).
Thus, the fact that workers’ hearing deteriorates is an age-related loss. It needs to be
subtracted from the equation as shown here and the loss in decibel level in this study is also
noted. But the reason of noise exposure caused by the noise in the factory or from outside the
factory could not be shown here except for a similar pattern of points recorded leaving the
cluster group.
The situation of a cross-over below the healthy limit is due to access noise exposure
or an accumulation of noise affecting the ear as shown in an increase in the hearing level,
signified by a cross-over between healthy limits. Whereas age loss is significant after 10
years, a cross-over between healthy limit in 1 to 2 years is a sign of a significant loss. Thus, it
is important to calculate and determine the significant loss related to over-exposure.
The equations of healthy hearing limits with respect to age are shown below:
y1 = 0.3 x + 16.5; for less than 35 years of age - (4) - Off-limit
y1’ = 0.86y1 - (3 (i)) - Caution limit
y1’’ = 0.7y1 - (3 (ii)) - Good limit
y1’’’ = 0.5y1 - (3 (iii)) - Very good limit
y2 = 0.4 x + 14; for more than 35 years of age (inclusive of 35) – (5) - Off-limit
y2’ = 0.83y2 - (4 (i)) - Caution limit
y2’’ = 0.68y2 - (4 (ii)) - Good limit
y2’’’ = 0.48y2 - (4 (iii)) - Very good limit
<graph 1>, <graph 2>, <graph 3>
The cross-over point is merely the intersection between the exponential curve (1 - 2,
3) and the off-limit line (4) & (5) for workers with long exposure. And an arithmetic
subtraction of increment shows workers within the healthy limit.

42
The Sampling of Workers in the Audiometric Test
  The estimated sample of audiometric test records of the workers who took the test
with the hearing level is given in the table below. These figures show that the number of
workers with hearing level above 30 decibel dB is approximately 10 – 16 percent of the total.
A rough approximation shows that workers’ hearing level does occur above the normal
hearing level. This estimate indicates that a benchmark is required based on data from other
factories. The estimated count in this factory is as follows:
<Table 1>
Taking note that there are hidden points in the cluster below the healthy limit as
described in the section below, this shows that will appear in the off-limit conditions. Thus,
the 10 – 16 percent as counted might not depict the true numbers. This figure shows only
point records.
Discussion
Since the current points of off-limit cases are observed to be exponential on the scatter
plot, the forward projection of 5 intervals is acceptable for some applications. This means that
a noise-induced problem faced by factory workers that is caused by excessive noise exposure,
showing signs of deterioration in hearing ability, is an empirically verified fact that must be
looked into seriously. Some workers might be vulnerable to the same noise. On the other
hand, noise-induced problems might be due to other noise factors external to the factory.
However, in this internal study analysis, a similar pattern of two distinctive age groups
(above 35-years-old or below 35 years old) is noticed, one above the cluster and the other
below that cluster We have found that the record points as shown on the plot are either dotted
plots above the cluster groups (which are substantially above the healthy limit) or solid dotted
plots inside the cluster group.
Thus, the forward projection is valid for application where there is an observed point
of distinct high level distinguishable or separated from the main cluster group of normal
hearing level. This is shown in Figure 1. Similar patterns are shown by the two cluster groups
in Figure 2. From here, the two equations that show two rough interception curves of the
approximate records, where a few points way above the two clusters, known as the points
leaving the cluster group, are exponential. That is shown in the equations below:

43
y = 18 + 5 exp (0.1x) - (5); above cluster
y = 21 + exp (0.09x) - (6); above cluster
The above equations represent the two sway patterns, with their hearing ability
deteriorating as shown in Figure 2; these indicate the starting point of about 20 to 23 decibels.
A rectification factor on the overall equation (5) to increase the steepness is multiplied as
shown in Figure 3. This represents a slow deterioration at an early age and presumed to lead
to a more rapid increase in hearing deterioration at a later age.
y = 0.9 (18 + 5 exp (0.1x)) - (7); to curve the radius near the y-axis with steeper slope as x
(age) increases.
<figure 1, 2 & 3>
  With these off-limit cases, the limit of healthy workers is linear as age increases
instead of an exponential curve. However, it is noticed that the age -related losses lie between
0.33 to 0.4 dB annually, depending on the age. If it is below 35 years old, the increase is 0.33
dB every year. If it is above 35 years old, the increase is 0.4 every year. Thus, if the increase
is higher than this figure, then most probably an exposure to noise is probably the factor - the
noise levels at their work place have harmed healthy hearing capacity. It is advisable to have
the ear checked early and to stay below the permissible exposure level as stated in Factories
Machinery Act 1967, Noise Regulation 1989, with the risk of a possible cross-over or
deterioration due to noise exposure.
Where it is noted that a person’s susceptible limit is different from another person’s
limit, the risk here is whether that person will have the same deterioration pattern with
another person, given the same noise exposure. Although there is no substantial evidence
from this study, this should be explored in future research.
With regard to individual susceptibility, it is found that the deterioration patterns are
signified by the coefficient B and C in equations 1, 2 & 3. Noteworthy is that the individual
sway patterns of these off-limit cases differ in all cases. This could be an age-related
increment due to the age factor. The losses are more severe after a time period. Losses are
less at the beginning stage, with a possible double age effect factor due to severe weakness
and the possibility of an immediate loss pattern occurring.
y = B * x’ * exp (C * (x – 16)) – (8) ; age incremental factor, or double the age effect 2x’.

44
Conclusion
  Workers are at risk at their work place when an increase in their hearing limit (i.e.
hearing ability during the test) is recorded. Long exposure to noise is very dangerous, as it
will damage hearing. The equations here can help to trace the origin of a worker’s hearing
condition (including a cross-over range). It is also able to a certain extent to predict the
deterioration caused by noise, exponential for off-limit cases and linear due to age-related
losses. Thus, it is important to take note of the work environment (the noise levels), to have
noise test results be recorded (susceptibility) and to avoid noise exposure where possible.
Age-related losses are natural but the impact of noise after exposure will cause substantial
additional deterioration.
References
[1] C.C. Gan, The Cause of Damage in Workers’ Hearing Levels – A Finding Based on The
Chances of Occurrence in the Possible Sway Patterns, NIOSH Journal,? 2010
[2] Factories and Machinery Act, 1967, Noise Regulation 1989.

45
Graphs
 
Graph 1a : Off-limit Conditions and tThe Variables of the Exponential Equations
12.8 initial point - intersection at y-axis
A B C
11.5 1.3 0.08
y = A + B * e (c*x)
Sway Pattern - based on highest possible condition, "Category 2" to "C".
- the exponential curve from the highest count in the pattern. Approx 40 out of
100.
10.2 initial point - intersection at y-axis
A B C
9.2 1.0 0.07
y = A + B * e (c*x)
Sway Pattern - based on 2nd highest possible condition, "Category 1" to "C".
- the exponential curve from the second highest count in the pattern. Approx 38 out of 100.

46
Graph 1b : Off-limit Conditions (Workers in their early 20s)
 
Lower Range
15 dB
initial point, intersect with earliest start
age at 16 years old.
A B C Overall Factor
-20 2.5 0.1 1.2
y = A + B * e (c*x)
1.1y - (Lower - i)
Upper Range
18 dB
initial point – start age at 27 yrs old when problem
occurs, presumably 15dB at 16 years old (intersection
with lower range), with hearing level 19.1dB. Cross
over at the same age, indicating drastic deterioration.
A B C Overall Factor
-50 10 0.1 2
y = A + B * e (c*x)
2y - (Lower - ii)

47
 
Graph 2 : The Healthy Limits (off-limit, caution, good and very good)
 
 
Graph 3 : The Scatter Plot of the Workers’ Audiometric Test Results

48
Table 1: Statistics of Sampled Workers
(please consider the numbers as an estimate for a rough indication of percentage instead of
the exact number)
Audiometric Test Results above 30 dB 
20 – 35 yrs old  35 – 55 yrs old 
7  10 
12 14 
10% 
30  yrs old and above 
18 
21 
16% 
>=40 
<40 & >=30 
dB  No. No. 
Less than 10 years of service  More than 10 years of service 
7 (2%)
10 (2%)
26 (6%)
397 (90%)
Less than 10 years of
service
60 dB
40 dB
30 dB
4 (2%)
14 (6%)
21 (8%)
212 (84%)
More than 10 years
of service
60 dB
40 dB
30 dB

49
Figure 1: Clusters and Points Record Leaving Cluster Group
 
Figure 2: Sway Patterns of Workers Noise Hearing Level to the Off-Limit Conditions.
 
High distinct points

50
Figure 3: Corrected to Show Slow Increase at Early Stage and Deteriation Pattern at Later
Stage

51
1 
 
PREVALENCE OF WORK RELATED MUSCULOSKELETAL
DISORDER AMONG PORT WORKERS: QUANTITATIVE ANALYSIS
AT THE PHYSIOTHERAPY CENTRE OF MALAYSIAN SHIPPING
INDUSTRY, SELANGOR
Izham Zain¹, Azrul Anuar¹, Asrina Asri¹, Shamsul Azhar²
¹ KPJ Healthcare University College
² Physiotherapy Department, Malaysia Shipping Industry, Selangor
Corresponding author: zainizham@yahoo.com.my
Abstract
The objective of this study is to identify the type of occupational related musculoskeletal
disorder among Malaysian Shipping Industry workers and to determine the relationship
between workers sosio demographic factors with occupational related musculoskeletal
disorder and injuries. This is a cross sectional, retrospective study using secondary data that
is available at the physiotherapy centre of Malaysia Shipping in Selangor. The study
population is the shipping port workers received physiotherapy treatment from 2011 and
2012. A total of 90 samples comprise of 85 male workers and the remaining is female. The
mean age is 34.1 (±7.36). Crane operator is the largest number of workers seeks for
physiotherapy treatment (68), office (15) and 7 from maintenance. The mean of employment
duration is 8.02 (±4.47) years with the maintenance group of workers have longest working
duration of 9 years. Muscle and ligament sprain strain known to be the commonest condition
(80%) refer for physiotherapy rehabilitation, tendinitis (14%) and fracture (6%). Young age
group of workers were significantly 9 times higher (95% CI 1.83 – 40.35) of getting back
injuries. The prevalence of musculoskeletal disorder based on work categories vary with
office type workers has 4.5 times higher (95% CI 1.06 – 19.7) on hand injuries. This study
has revealed that workers age, different type of work categories, working experience, and
body mass composition were associates with the occupational related injuries. The training
programme emphasise on preventive measures should be tailored to empower the employee
on safety measures at work.
Keywords: Shipping Industry Workers, Physiotherapy, Occupational related injuries

52
2 
 
Introduction.
According to the World Health Organisation, work-related musculoskeletal disorders arise
when exposed to work activities and work conditions that significantly contribute to
development of such derangement. (World Health Organization, 1985). The scientific
committee for musculoskeletal disorders of the International Commission on Occupational
Health (ICOH) describe work-related musculoskeletal disorders as a wide range of
inflammatory and degenerative diseases and disorders that result in pain and functional
impairment (Kilbom et al., 1996). Musculoskeletal disorders are known to be most common
work-related illness, it representing a third or more of all listed occupational diseases in the
developed countries (National research council. 2001). In the United States, Canada, Finland,
Sweden, and England, musculoskeletal disorders cause more work absenteeism or disability
with substantial costs and negative impact on quality of life than any other group of diseases.
There is a conclusive evidence indicate that organizations who fail to control workplace
injuries will experience an increase in loss-related expenses, mainly on workers
compensation insurance premiums. The current insurance premiums are determined based on
organization’s reported on work related injuries yearly. A report on business metal industry
performance in United State indicate that the cost of insurance premiums for the workers of
heavy steel industry is escalating gradually for the past 5 years. Therefore it is important for
companies to be in constant control of its human-related losses in order to secure reasonably
profit (Spengler et al 1986). A Korea Occupational safety and health Agency reported in
2005, a total of 9114 employees in Korea received workers compensation due to illness. Out
of these, 6223 cases (68.3%) were work related injuries. Highly physical demanding task are
known to be high risk sector of developing musculoskeletal injuries. Upper extremity work
related musculoskeletal disorders are highly found in manual-intensive type of occupations,
such as clerical work, postal service, cleaning, industrial inspection and packaging (Rampel
and Punner. 1997). Back and lower limb disorders occur more commonly on truck drivers,
warehouse workers, airplane baggage handlers, construction trades, nurses, other patient-care
workers, and operators of cranes or other large vehicles driver (Pope et al. 1991). The
European survey on working conditions ( 2001) estimated 45.5% of workers reported
working in painful or tiring positions, 35% were required to handle heavy loads in their work
and 62.3% reported repetitive hand or arm movements. All of such activities were known to
correlates closely with musculoskeletal disorders. In 2011, occupational injuries following
transportation activities, storage and courier services contribute 13.3% of total injury in

53
3 
 
Malaysia. Lifting, poor working posture, performing repetitive movements are among the
known caused of occupational related musculoskeletal injuries. Treatment and recovery are
often unsatisfactory especially for chronic injuries. The end result can be permanent disability
and sometimes with the loss of employment. Study on the occupational related
musculoskeletal injuries among port workers especially in Malaysia is still limited. Therefore
this study will explore the patterns and trends of occupational related injury that has been
treated at the physiotherapy department. The objective of this study is to identify the type of
occupational related musculoskeletal disorder among Malaysian Shipping Industry workers
and to determine the relationship between workers sosiodemographic factors with
occupational related musculoskeletal disorder and injuries. The outcome from this study will
give some insight and be able to suggest preventive and advice suitable corrective measures.
Literature review.
Cross sectional study conducted by Azmi Hassan and Rampal (1995) to determine the
prevalence of back pain among the bus drivers and office workers in a Bus company in
Kelantan found that majority of workers (60.8%) complaining of neck and back pain. The
prevalence of neck and back pain is significantly associated with unsuitable sitting posture
and time spending on driving a bus. The work nature seems to be consistent with the port
workers engaged with prolong sitting posture and it should have the same effects on them.
There are limited study that has examined the impact of work duration on the musculoskeletal
disorders and injuries. Azmi and Rampal (1995) examine the association of musculoskeletal
injuries with time spending on driving a bus. There’s a statistically significant relation of
back pain and time spending on driving. Even though majority (32.2%) of bus drivers
complains of low back pain however the onset is strongly associated with the uncomfortable
driver seat. Prevalence study conducted by Evangelos et al (2006) on musculoskeletal
disorders in shipyard industry found that 25% of total workers (998) have an episode of
musculoskeletal injury. Data collection was done through questionnaires circulated to the
respective employee. They found that, employees with middle age category of 31 – 44 years
old were prone to have musculoskeletal injuries (OR= 5.1, 95% CI 1.19 – 10.34) compare
with younger and older age group. The blue collar workers were 9 times higher to encounter
occupational related injury compare to other type of work category. Most of the data were
based on self reports and it indicates elements of biasness since the employee needs to recall

54
4 
 
the musculoskeletal injuries episode. In order to minimize the internal validity on data
collection exercise, the researcher should utilize the secondary data collection method
through employee medical records. Marlise et al (2012) conducted a prevalence study on
musculoskeletal diseases among dock workers. This is a retrospective and quantitative study. The
data were taken from medical files of dockworkers from 2000 to 2009. Individuals older than 52
years of age and with more than 21 years working experience in the field were predominated.
The most frequent musculoskeletal diseases included low back pain (38.8%), tendinitis
(19.7%), and neck pain (12.5%). The author belief that age and working experience were
important factors in the development of musculoskeletal related injury among dock workers.
However there are other contributing factors that might trigger the musculoskeletal symptoms
among dock workers such as types of work categories, working hours, and the effects of
work related vibration. All these elements in combination with each other were likely to
increase the incidence of work related injuries and disorders. Habibi et al (2008) conducted a
Prevalence study on Musculoskeletal Disorders and associated lost work days in Steel
Making Industry, they found that workers age between 25 – 31 years old were among the
highest age group of people absent from work due to the occupational injuries. There is
numerous risk factors that might contribute to the absenteeism among them, namely because
of poor posture at work, lack of job rotation, poor work station and the effects of vibrating
tools. The implications are seemed to be serious once the workers reach to older age because
the untreated occupational related disorders will effects workers productivities. Therefore it is
important to consider different age of groups as variable to enable an appropriate measures be
carried out.
Methodology.
Malaysia shipping Industry situated in Selangor and is a multicargo port which handles all
types of cargoes in containers, dry bulk, liquid bulk, vehicles and other conventional cargoes.
The industry has more than 4,000 staff responsible in ensuring the smooth running of port
activities. To ensure the optimum health of staff the port management provide Health clinic
and Physiotherapy centre that operate during office hours and runs by qualified medical
personnel. This is a retrospective study, using secondary data (Physiotherapy treatment card)
that is available at the Physiotherapy centre of Malaysia Shipping Industry. It involves port
workers that underwent physiotherapy treatment of the year 2011. The eligibility criteria to
enable the samples to enrol in this study are it should be port workers and had been diagnosed

55
5 
 
of musculoskeletal disorders / injuries and being referred for physiotherapy treatment. The
exclusion criteria, been diagnosed as non musculoskeletal disorders / injuries and has
underwent surgery due to motor vehicles accident. The patient name list was obtained from
the physiotherapy registration book of the year 2011. The head of physiotherapy service of
Westport physiotherapy centre will assist the researcher to trace the physiotherapy treatment
card. The researcher will evaluate each treatment card to determine it eligibility prior to data
collection exercise. The data collection exercise will be carried out by the researcher using
study data collection form. This study has received approval and permission from the
Malaysia port authority management and University research ethic committee to enable the
researcher to conduct a data collection exercise.
Results.
Majority of samples were male employee, it represents 85 (94%) of total samples and the
remaining 5% were female (Graph 1). The mean age of study sample is 34.1 (±7.36) with the
youngest age is 21 and the oldest is 55 years old. Employment duration is varies with
minimum duration of 1 years and the maximum employment duration is 17 years. The mean
employment duration is 8.02 (±4.47) years. Maintenance personnel are known to have
longest employment duration of 9 years and the shortest duration is employee working and
attach to office related task. Majority (82%) of port workers were obese with mean BMI is
25.8. (Table 1)
Majority of crane related task operator were from younger aged group (72%) and 17%
engage in office related task. Interestingly out of 15 workers engaged in office related task,
14 of them were overweight category. (Table 2)
Descriptive statistical tool was used to describe the diagnosis of musculoskeletal injuries
among port workers. Sprain and strain are the commonest injury on workers follow by
tendinitis and fracture. It represents 80%, 14% and 6% respectively. The anatomical structure
involves varies. Sprain and strain were more obvious on workers with back and knee injuries.
A total of 46% (n=41) cases referred for physiotherapy rehabilitation are due to such injury.
Prevalence of such injury on knee and neck area is 12% (n=11) and 10% (9) respectively.
Tendinitis is significantly higher over hand (n=5) and shoulder (n=4) area. Fracture cases is
more common on hand (n=3) and only 1 fracture cases found on shoulder and ankle area
respectively (Table 3). The Odd ratio was used to determine the association between
exposure and outcome. Pearson correlation analysis was conducted to assess the intensity and

56
6 
 
direction of the association between variables. Workers age category of 21 – 39 years old
seems to have 9 times (95% CI 1.83 – 40.55) higher suffering back injury. However, workers
with aged category of 40 – 55 years old were significantly 5 times higher of getting hand
injury (p < 0.05. 95% CI 1.42 – 22.6) and 2 time higher on elbow injury (p<0.05. 95% CI
0.19 – 25.0). The relationship between older age group workers with elbow and hand injury is
strongly associated and consistent. The prevalence of occupational related injury based on
work category is varies. Workers doing office type of task is significantly high on hand injury
(p <0.05) with 4 times higher compared to other work categories. However, maintenance
group of workers was associated with an approximately 4 times increase on elbow injury
(95% CI 1.06 – 19.7). Back pain was significantly more common among workers with
working experience of 1 – 7 years. The prevalence of such injury is 3 times higher compared
to those of more than 8 years of working experience. However, for workers with more than 8
years working experience, neck pain seems to be more dominant. The incidence is 5 times
(95% CI 0.43 – 69.3) higher compared to younger age category. There is no statistically
relationship between excessive BMI with occupational related injury. In this prevalence
study, BMI less that 23.9 kg / m² were found to have 2 times higher of elbow pain (p< 0.05.
95% CI 0.20 – 28.2). However, relatively excessive BMI were known to have any of the
musculoskeletal injuries regardless the anatomical area. (Table 4.1 and Table 4.2)
Discussion.
This prevalence study reveal that 75% (n=68) of total patients coming to physiotherapy
department for rehabilitation purposes is from crane operator work category and subsequently
the small percentage were from office and maintenance category. This finding is similar with
study of Evangelos et al (2006) who reported, blue collar workers were 9 times higher to
encounter occupational related disorders. However, the recurrence rate of occupational
related injuries and diseases after receiving physiotherapy rehabilitation were not reported
because it was not within the scope of this study.
Limitation of study.
There is a limitation of the study need to be considered in the interpretation of the result. This
is a cross sectional study using secondary data that is available at the physiotherapy centre.
Obviously secondary data is limited in details and therefore it difficult to draw a
comprehensive conclusion of prevalence on occupational related injuries. This study is not

57
7 
 
able to evaluate workers knowledge on health and safety aspects at work place because of
limitation mention. Therefore the association of occupational injuries and knowledge on
health and safety at work place cannot be drawned. Although this limitation cannot be
excluded, our findings are in line with other studies on prevalence of occupational related
injuries. The strength of this study, there is no evidence of bias in data collection since it
involves secondary data collection that available at the physiotherapy centre.
Work categories and occupational related disorders.
Marlise et al (2012) found that 38.8% of port workers would suffer from low back pain.
Interestingly the data from this study show that there is no statistical association between
back pain and different category of port workers. However, the statistic is relatively indicate
that prevalence of back pain is high on crane operator and office workers. Interestingly, crane
operator (n=68) were the majority group of workers seeks physiotherapy treatment. This
finding may be due to vibration effects from heavy vehicle and prolong sitting duration at
work. Hand injuries were significantly high on office work category with odd ratio of 4 time
higher compare to other categories. The effects of using lots of hand and finger movement
during computer work might contribute to such injuries. This finding is consistent with
numerous of study conducted in evaluating the association of work categories and
occupational related injuries (Christina et al. 2005).
Age and Occupational related musculoskeletal disorders.
Obviously younger age group workers (81%) were the most group to encounter an episode of
back pain compare to older age group. It is found that the younger age group workers were
involve in a high demand of physical related task and the continuous vibration effects from
the heavy vehicle itself (Azmi and Rampal.1995). This study were not evaluating the
contributing factors of occupational related injuries and diseases, however such effects on the
younger aged group workers cannot be denied. Interestingly, the older aged group workers
were significantly high of getting hand and elbow pain. This finding is not consistent with the
study conducted by Papageorgiou et al (1996) which found that the highest incidence of back
pain among workers were between 49 – 59 years old. The high percentage of younger aged
worker suffering from occupational related disorders cannot be used to inference the true
picture of occupational related injuries among port workers because of limitation in samples

58
8 
 
size spectrum. Majority of samples were within younger age group, it represents 73% and the
remaining percentage were samples of 40 – 55 years old. Obviously, the age distributions
were not equal between 2 age groups. In order to have a clearer picture of occupational
related trends of injuries, the study should include the data available at the health centre.
However, this study was conducted within the physiotherapy centre therefore it cannot
represent the whole population of such organization.
BMI and work related disorders.
There is no statistical significant indicate the relation of BMI and work related disorders.
However, descriptive statistic showed that 93% of office workers were overweight. These
phenomena may be due their work nature of less active and small physical movement. If this
trend continues without preventive intervention and active involvement from both employees
and employer, it can contribute to an increase number of non communicable diseases in
future. Few studies have examined the relation of excessive body weight with occupational
related diseases and suggested that excessive body weight increased the risk of
musculoskeletal injuries and cardiovascular disorders (Paul et al.2007). The combination
effects of excessive body weight with occupational related stress and working environment
will increase the risk of occupational related disorders. Therefore, it can conclude that obesity
should consider a significant occupation hazards. Since there are complete gymnasium
equipments and it is easily access by employees, the BMI might not be a good assessment
tools to assess the excessive fat composition. The possibility of excessive body composition
may be due to increase muscle flash resulting from weight training programme. The
alternative measurement of taking fat composition should consider in order determining the
actual scenario. The best option available is through body fat calipers which are feasible to do
by taking primary data method.
Work experience and occupational related injuries.
Noorul Huda (2012) found that there is strong association between work experience and
occupational injuries. Majority of samples were working as crane operator. Workers with 8 –
17 years working experience were significantly 5 times higher suffering from neck pain.
However, those workers with less than 8 years were significantly 3 times higher suffering
back pain. In this prevalence study, samples knowledge on occupational related injuries and

59
9 
 
working experience were not measures and therefore the relation and association between
these two factors were unable to rule out. There are numerous studies indicate that there are
significant relations between knowledge and occupational related injuries. In fact working
experience has a significant impact in improving knowledge, skills and even positive
behaviour towards safety at work (Hong Wang et al. 2003). However in this prevalence study
such variables were not measure because of limitation in data collection itself. Evaluating the
knowledge is best to carry out through collection of primary data.
Conclusion
This study has revealed that workers age, different type of work categories, working
experience, and body mass composition were associates with the occupational related
injuries. The preventive programme should be tailored to empower the employee on safety
measures at work place. The training on preventive aspect of occupational injuries can be
conducted to employee in order to equip them with adequate knowledge on safety and
preventive measures at work place. The preventive measure is known to be a most valuable
strategy rather that cure. The physiotherapy department should play an important role in
assisting and organizing such training session. Both parties, employer and employee should
involve actively and work together to achieve this aim

Journal of Occupational Safety and Health, December 2013, Vol 10, No. 2

Journal of Occupational Safety and Health, December 2013, Vol 10, No. 2

Recommended

Recommended

More Related Content

Similar to Journal of Occupational Safety and Health, December 2013, Vol 10, No. 2

Similar to Journal of Occupational Safety and Health, December 2013, Vol 10, No. 2 (20)

More from Gan Chun Chet

More from Gan Chun Chet (20)

Journal of Occupational Safety and Health, December 2013, Vol 10, No. 2