jurnal of occupational safety and health

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jurnal of occupational safety and health

  1. 1. Journal of Occupational Safety and HealthDec 2004 Vol. 1 No. 2ContentsErgonomic Study for Optimum Printing Workstation Using Factorial 43 - 49Experiment and Response Surface MethodologyIqbal M., Soewardi H., Hassan A. and Che Haron C.H.Occupational Lead Exposure of Soldering Workers in an Electronic 51 - 57FactoryMimala A., Zailina H. and Shamsul Bahari S.Occupational Heat Exposure of Workers in a Plastic Industry Factory 59 - 66Goh S.B., Zailina H. and Shamsul Bahari S.The Need of Industrial and Organizational Psychologist in Malaysia 67 - 76Shukran Abdul RahmanStress Intervention Study Among Health Nursing Staff In Two Health 77 - 81Districts In Terengganu, MalaysiaAgus Salim MB, Noor Hassim I, Jefferelli SBRoad Safety Audit : An Exploratory Study 83 - 85Veera Pandiyan, V.G.R. Chandran Govindaraju and Nagatheesan V.M.A Report on Needle Stick Injuries for the year 2000 86 - 93Lim Jac FangEmerging Infectious Diseases: Ministry of Health Practice and 95 - 97PlanningFadzilah Hj. Kamaludin
  2. 2. Ergonomic Study for Optimum Printing Workstation Using Factorial Experiment and Response Surface Methodology Mohammad Iqbal, Hartomo Soewardi, Azmi Hassan, Che Hassan Che Haron Faculty of Engineering, Universiti Kebangsaan MalaysiaAbstract This paper presents the use of factorial experiments and response surface methodology to determine thebest workstation design configuration of an existing electronic industry. The aim is to find the value of physicaldimensions that gives the best performance for the workstation. Four performance measures are selected; the cycletime, the metabolic energy expenditure, worker’s posture during the task and lifting limitations. The methodologyused in this study consists of two parts. The first part is based on factorial experiments and handles discrete searchover combinations of factor-levels for improving the initial solution. In the second part, the solution that was obtainedearlier is further refined by changing the continuous factors by using response surface methodology. The result of thisoptimization study shows that the optimum value of physical dimensions gives a significant improvement for theperformance measures of the workstation.Impact on Industry: Demonstrate how the ergonomic optimization study could improve the productivity and working practices.Key words: ergonomics, optimization, workstation design, factorial experiment, RSM.Introduction This paper presents a case study of an workstation configurations and four performanceergonomic design of a workstation. The measures are selected for this study. Performanceworkstation considered here is a printing measures that are associated with the workstationworkstation of an existing electronic industry in design problem are usually characterized asMalaysia. Most of the routine tasks of the economical or ergonomic measures. Theelectronic industry studied here are fully measures depend both on the work proceduresautomated. However, some of the workstations and workstation design. This study deals with theare manually operated or semi automated where workstation design only. We assume that thethe workers and the automated machine work structure of the task is already given and the aimtogether simultaneously. The bottleneck for the to provide the most suitable physicalwhole production line is the printing department. environment for doing the job. Accordingly, theThe worker performs the repetitive task of measures that are considered here are those thatworking, while staying at the same positions all are affected by the workstation design rather thanday long. Many workers are complaining of the work orders. Measures such as number ofshoulder aches and lower back aches. This repetitions and exposure time to the risk factorsituation explains the need of redesigning the are disregarded in this study. The performanceworkstation in order to maximize the throughput measures in this study consist of four factors; (i)rate and to create suitable ergonomic working the cycle time (economical measure); (ii) thecondition for the workers. metabolic energy consumption (physiological In order to achieve optimal economic measure); (iii) worker’s posture during the taskand ergonomic results, a comprehensive study of that may indicate risk of injury; and (iv) liftingthe job tasks must be conducted and several limitations (biomechanical).parameters and constraints have to be In this study, we follow theconsidered. There are four parameters of the methodology proposed by Ben-Gal and Bukchin 42
  3. 3. (2002). They suggest a systematic design consumption rates multiplied by theheuristic based on Factorial Experiments (FE) workshift time, t s (minute).and Response Surface Methodology (RSM). FEis used to generate candidate configurations of a  m  Eshift = t  ∑ e ×t  Ttask (Kcal) (2)workstation and to build empirical models s  i =1 i i relating design factors to various objective  functions. Based on this model, RSM is utilizedto optimize the design factors with respect to Where, the energy consumption rate pereconomic and ergonomic multi-objective each individual operation ( ei , i = 1, …, m)measures. is generated using the Garg formula (Garg et al., 1978).Methodology • Ptask The methodology used in this study is The worker’s posture during task that mightbased on improving an initial workstation indicate the risk of injury. This measureconfiguration, called the initial solution. The considers the worker’s body position duringinitial solution was obtained from the existing the printing task according to the OWASworkstation. A set of system factors (design guidelines (Karhu et al., 1981; Scott andparameters) has to be defined in order to be Lambe, 1996). The objective is to shortenmodified during the optimization stage. The operations that require inconvenient bodyheuristic of the methodology consists of two positioning. A good solution requires thatparts. The first part is based on factorial during all operations the body positionexperiments and handles discrete search over remains in category one. This category,combinations of factor-levels for improving the called the natural position, insures that noinitial solution. In the second part, the solution damage is caused to the worker. The Ptask isthat was obtained earlier is further refined by the time weighted average of the positionchanging the continuous factors using RSM. categories that are denoted by pi , and i = 1, All of the four performance measuresthat are selected and later integrated using a …, m. Thus,multi-objective function would be described in  m the following section: Ptask =  ∑ p ×t  Ttask    i =1 i i • Ttask (posture category) (3) The printing cycle time (an economical measure) is a measure for the productivity of • Wtask the workstation, and therefore should be The lifting limitations (a biomechanical minimized. The task cycle time consists of measure) are according to the NIOSH m individual operations, where the time to guideline (Waters et al., 1993). This measure perform each operation, denoted by t i , i = takes into account the upper weight limits 1, …, m, is obtained from MTM table. that the worker is allowed to carry in each position during the task time. Wtask is the m time weighted average of the weight limits, Ttask = ∑ t (min/unit) (1) i =1 i denoted for each position by wi , i = 1, …, m, calculated only for those operations that• Eshift involve weights, The metabolic energy consumption in a shift  m   m  is according to Garg guidelines Wtask =  ∑ l ×t × w     ∑ l ×t  (Kg)   (physiological measure). It is measured in  i =1 i i i   i =1 i i  Kcal units and has to be minimized. Eshift is (4) the time weighted average of the energy Where, 43
  4. 4. l = { 1 if operation i involves a weight lift i 0 otherwise ~ k ( Wk = W − L ′ w ) (1.2(U w − Lw )) k = 1, ..., K, (5) Where UT (LT ) , U E (LE ) , U P (LP ) and The next stage is to use a multiple UW (LW ) are the upper (lower) limits of theobjective function in order to compare alternativedesign solutions and select the optimal one. In four performance measures respectively andthis study, we follow the multiple–response U T E PW = UT E PW + 0.1(UT E PW − LT E PW ) ′procedure suggested by Myers and Montgomery LT E PW = LT E PW − 0.1(U T E PW − LT E PW ) ′(2002). They constructed a multiple objectivefunction for each alternative, denoted by Dk The desirability function of solution k isand called the desirability function. It reflects the based on geometric mean of its normalizedcombined desirable grade of the kth solution with performance measures, as follows:respect to all performance measures. 1 ∑ rv V r  Assume that the designer has to Dk =  d k ,v ∏ v  k = 1, ..., K, (8)evaluate K different configurations. Accordingly,    v =1 Tk , Ek , Pk and Wk denote respectively the Where d k , v denotes the vth performanceTtask, Eshift, Ptask and Wtask performancemeasure values for solution k = 1, ..., K. Since measure of solution k; and rv is the relativemany multi-objective functions require the importance that is assigned subjectively andperformance measure values to be between zero respectively to each performance measure. Inand one, the following normalization procedure ~ ~will be applied: this study, v = 4, d k ,1 = Tk , d k ,2 = Ek , ~ (Tk = U ′ − T T k )( ( 1.2 U − L T T )) k = 1, ..., K, ~ ~ d k ,3 = Pk and d k ,4 = Wk . Accordingly the ~ (Ek = U ′ − E E k )( ( 1.2 U − L E E )) k = 1, ..., K, desirability function is the following: (6) ~ (Pk = U ′ − P P k )( ( 1.2 U − L P P ))k = 1, ..., K, (a) (b) Fig. 1. The drawing of printing workstation; (a) back view of the worker; (b) right hand view of the worker 44
  5. 5. ~ ( ~ ~ ~ 16 D = T 2 × E 2 × P ×W k k k k k ) • Factor C is the vertical attitude in millimeters of the lower edge of the material box k = 1, ..., K, (9) • Factor D is the angle in degrees of the slope of the material box.Where the first two performance measures areconsidered to be twice as important as the last A feasible initial configuration of thetwo. printing workstation is presented in Table 1. The solution is characterized by measures of the fourDescription of the system design factors ( n = 4 ); A, B, C and D respectively. The initial values of the parameters Printing workstation studied here is a (factor level 0) were predicted according to thesemi-automated workstation where worker and position and anthropometrics data of theautomated printing machine work together workers.simultaneously. An aluminum plate (a cashingpart of an electronic equipment) was polishedand printed by the printing machine Result and analysisautomatically. Accordingly, the working table ofthe machine consists of two parts, polishing area The desirability function in equation (9)and printing area. Two workers perform the task is applied to the multiple objectives. Theof this printing operation. The first worker loads desirability values for each configuration arethe aluminum plate (material) to the polish area listed in Table 2. As can be seen from Table2, noof the machine, and then removes it to the dominant solution (solution which is superior toprinting area. After printing operation finished, all other solutions in allthe second worker (stays at the other side of themachine) unloads the material from the machine Table 1. The initial values and the selectedto perform another operation. This study focus ranges of the design factorson the ergonomic improvement related to the Factor level Parameter Deltafirst worker. 0 1 2 A drawing of the workstation is A (mm) 410 380 440 30presented in Fig. 1. The worker takes the B (mm) 1000 970 1030 30material from the material box by his right hand C (mm) 380 350 410 30(Fig. 1.a), delivers it to the polishing area and D (deg) 15 12 18 3then removes it (by using both right and lefthand) to the printing area of the machine. In this performance measures) exists; yet, the initialstage, the machine performs printing operation solution (0000) may be improved. The followingautomatically, and a new cycle begins. analysis includes examination of each Four design factors (parameters) are performance measures separately and evaluationconsidered. All the factors are locations of the multi objective (desirability) functions for(positioning) factors of the workstation. In all measures.particular: The cycle time per task (Ttask) is• Factor A is the horizontal distance in considerably affected by changes in the factors’ millimeters between the edge of the printing values. There is a large difference of about 17.5 machine and the position of the worker % between the best solution (1121 with Ttask =• Factor B is the vertical height in millimeters 3.66 seconds) and the worst solution (2212 with of the working table of the printing machine Ttask = 4.30 seconds). In the mass production environment, such as in this case, this - 45
  6. 6. Table 2. Results of the alternative design solutionAlter- Exp. Ttask (sec) Eshift(Kcal) Ptask Wtask (kg) Desir-native (ABCD) Actual Norm. Actual Norm. Actual Norm. Actual Norm. ability 0 0000 3.87 0.62 799.82 0.44 1.67 0.21 3.51 0.40 0.43 1 1111 4.03 0.45 797.82 0.48 1.67 0.21 2.86 0.13 0.33 2 2111 3.78 0.72 799.75 0.44 1.50 0.75 3.63 0.45 0.57 3 2211 4.28 0.20 795.21 0.54 1.55 0.58 3.49 0.61 0.40 4 1211 4.19 0.29 799.60 0.44 1.67 0.21 2.80 0.11 0.27 5 1221 4.01 0.47 798.91 0.46 1.66 0.25 2.72 0.08 0.31 6 2221 4.12 0.36 794.11 0.56 1.54 0.62 3.74 0.39 0.46 7 2121 3.93 0.56 796.54 0.53 1.67 0.21 2.79 0.11 0.36 8 1121 3.66 0.84 796.74 0.51 1.50 0.75 3.61 0.44 0.63 9 1122 3.69 0.81 796.88 0.50 1.47 0.83 3.72 0.49 0.64 10 2122 3.96 0.53 794.91 0.55 1.66 0.25 2.90 0.15 0.38 11 2222 4.14 0.34 795.15 0.54 1.52 0.67 3.58 0.43 0.46 12 1222 4.08 0.40 798.15 0.48 1.66 0.25 2.84 0.13 0.32 13 1212 4.21 0.27 799.42 0.45 1.67 0.21 3.76 0.50 0.34 14 2212 4.30 0.17 795.04 0.54 1.55 0.58 4.68 0.88 0.41 15 2112 4.08 0.40 797.27 0.49 1.68 0.17 2.97 0.18 0.33 16 1112 3.85 0.64 798.62 0.46 1.50 0.75 3.75 0.50 0.57Upper limit 4.39 815.82 1.71 4.77Lower limit 3.59 778.23 1.44 2.73Table 3. Search region and definition parameters for the multiple desirability method Lower Upper Name Goal Lower limit Upper limit Importance weight weightmachine_d (A) 0.8..2.20 0.8 2.2 1 1 -machine_h (B) 0.8..2.20 0.8 2.2 1 1 -matbox_h (C) 0.8..2.20 0.8 2.2 1 1 -matbox_angle (D) 0.8..2.20 0.8 2.2 1 1 -Ttask ≤ 3.59 3.59 4.38 1 1 2Eshift ≤ 778.22 778.22 815.82 1 1 2Ptask ≤ 1.43 1.43 1.71 1 1 1Wtask ≥ 4.77 2.73 4.77 1 1 1improvement is economically significant. At next stage, the desirability function The variation in the energy of each alternative is evaluated. The performanceconsumption during a work shift (Eshift) among measures are first normalized and the desirabilitythe different solutions is relatively small. That’s function is then calculated using the relativewhy this measure is further considered in this importance values given in Equation (9). It isstudy for illustration purposes only, whereas in seen that the best solution is configuration 1122reality it would have been eliminated. with a desirability value of 0.64. The initial Both of the body position category solution is ranked in 7th place with a desirability(Ptask) and the average weight limit (Wtask) are value of 0.43. It means that the configurationsconsiderably affected by configuration changes. ranked from 1st to 6th place are considered betterNote from Table 2 that factor A has a clear affect for any set of relative importance values.on the Ptask and Wtask value. It is seen that the Finally, The RSM is applied to find thebest solutions are obtained when factor A is fixed best solution from configuration 1122. Table 3on its higher level. presents the initial conditions of both the performance measure and the design factors that 46
  7. 7. Table 4. Design solution improvement using the RSM Desir- No. machine_d machine_h matbox_h matbox_angle Ttask Eshift Ptask Wtask ability 1 2.20 1.08 2.20 0.80 3.61 796.86 1.44 3.95 0.688 2 2.17 1.04 2.20 0.80 3.60 796.98 1.46 3.92 0.683 3 2.20 1.26 2.20 0.95 3.71 796.11 1.46 3.95 0.663 4 2.20 1.28 2.18 0.81 3.71 796.08 1.46 3.95 0.662 5 2.15 1.18 2.20 0.80 3.67 796.40 1.47 3.90 0.661 6 2.20 1.23 2.20 1.40 3.71 796.26 1.46 3.94 0.660 7 2.20 1.24 2.20 1.88 3.74 796.22 1.46 3.95 0.654 8 2.20 1.29 2.20 1.51 3.75 796.01 1.46 3.95 0.652 9 2.20 1.38 2.20 0.80 3.77 795.63 1.47 3.94 0.652DBS 1 1 2 2 3.69 796.88 1.47 3.72 0.64IS 0 0 0 0 3.87 799.82 1.67 3.51 0.43are used by the optimization procedure. ConclusionExtrapolation presented in Equation (6) was usedhere. That is the four design factors that were In this paper, a case study of anexperimented earlier with level values of one or ergonomic design of a workstation wastwo (in coded terms) are now allowed to vary presented. The aim is to increase the throughputbetween 0.8 to 2.2. The reason for such rate (capacity) of the workstation, as well as toextrapolation is the assumption that one can create a suitable and adjustable ergonomicestimate the response functions over a wider environment, which could accommodate a largesearch region by using the responses obtained in percentage of the workers population. Factoriala smaller experimental region (Myers and Experiment (FE) and Response SurfaceMontgomery, 2002). Methodology (RSM) were used in this study. FE Table 4 presents nine design solutions is used to generate candidate configurations of asorted in a decreasing order by their desirability workstation and to build empirical modelsgrades. Convergence is achieved when the relating design factors to various objectivedistance moved or objective function change is functions. Based on this model, RSM is utilized −6 to optimize the design factors with respect toless than a 10 ratio. For comparison purpose,two solutions from previous steps (as presented economic and ergonomic multi-objectivein Table 2) were added to the table: the initial measures. Compare to the initial solution, thesolution (denoted in the Table by IS), and the final solution of this optimization study gives abest discrete solution (denoted in the Table by better result for the performance measures of theDBS). The best design solution that is obtained workstation.by the response optimization procedure (design Finally, this case of study has demonstrated howNo.1) achieves a desirability grade of 0.688. the ergonomic optimization study will benefit the Compare to the best discrete solution, manufacturing industry. Design modification toapplying the final solution of this optimization the workstation, based on the result of thisstudy gives a significant improvement for the optimization study, would improve theperformance measures of the workstation. productivity and working practices. This mayAlthough the change in the energy consumption also improve the product quality since, if theduring a work shift (Eshift) is relatively small, workers are more comfortable, the product willthere are significant changes in the cycle time per be handled more carefully.task (Ttask) (about 2.2%), the body positioncategory (Ptask) (about 2.1%) and the averageweight limit (Wtask) (about 5.8%) 47
  8. 8. References application. Applied Ergonomics 12 (1), 13- 17.Ben-Gal, I., & Bukchin, J. (2002). The Myers, R. H., & Montgomery, D. C. (2002). ergonomic design of workstation using Response surface methodology. 2nd edition. virtual manufacturing and response surface John Wiley & Sons. New York, NY. methodology. IIE Transaction, 34. Scott, G.B., & Lambe, N.R. (1996). WorkingGarg, A., Chaffin, D.B., & Herrin, G.D. (1978). practices in a perchery system using the Prediction of metabolic rates for manual OWAS. Applied Ergonomics 27 (4), 281- materials handling jobs. American Industrial 284. Hygiene Association Journal, 39 (8), 661- Waters, T. R., Putz-Anderson, V., Garg, A. and 674. Fine, L. J. (1993). Revished NIOSH equationKarhu, O., Karkonen, R., Sorvali, P., & for design and evaluation of manual lifting Vepsalainen, P. (1981). Observing working tasks. Ergonomics, 36(7), 749-776. postures in industry: examples of OWAS 48
  9. 9. Occupational Lead Exposure Of Soldering Workers In An Electronic Factory Mimala Arasaratnam, Zailina Hashim, Shamsul Bahari Shamsudin Environmental and Occupational Health Unit, Department of Community Health Faculty Of Medicine And Health Sciences, University Putra MalaysiaAbstract A cross-sectional study was conducted on 83 female electronics factory workers. The respondentscomprised 50 exposed workers who use lead alloy solder and 33 unexposed workers. The objective of this study wasto assess the lead exposure of these workers. Breathing zone were sampled using air sampling pumps. Dust sampleswere collected by wipe method. Venous blood collected and blood pressure were measured. All lead analyses werecarried out with Graphite Furnace Atomic Absorption Spectrophotometer. The mean air lead for exposed workers (570. ± 0.93 µg/m³) was significantly higher than the unexposed workers (0.0067 ± 0.0045µg/m³) (p<0.001). The rightside surface area ( 49.10 ± 34.19 µg/dl) was significantly higher than the left side (8.45 ± 9.04 µg/cm² ) ( p<0.001).The mean blood lead for the exposed workers (5.10 ± 1.42 µg/dl) was not significantly higher than the unexposedworkers ( 5.09 ± 0.88 µg/dl ) . The mean blood pressure was 121 / 72 mmHg and 117 / 72 mmHg for the exposedand unexposed workers respectively. No significant difference between the blood lead concentration (p = 0.786),systolic blood pressure (p = 0.554) and diastolic blood pressure (p = 0.955) between the 2 groups. No significantcorrelation found between blood lead with personal air lead (p = 0.447), left side surface area dust lead (p = 0.937),right side surface area dust lead (p = 0.291), systolic blood pressure (p = 0.201) and diastolic blood pressure (p =0.485). In conclusion, since the biological indicators showed normal values, the electronic circuit board solderingworkers, are not at high risk of exposure to occupational lead.Key words: blood lead, blood pressure, personal air lead concentrations, surface dust lead concentrations, electronic factory worker.Introduction cause tiredness, mood changes, headaches, stomach problems and trouble sleeping. Higher The lead being referred to in this study levels may cause aching, weakness inis in the form of inorganic lead, usually in the concentration or memory problems (Nurunniza,form of metallic lead such as lead oxide or lead 2001; Mazrura, 2000; Kovala et al., 1997;salts. The main routes of exposure to lead in Cooper, 1996).workers are through inhalation into the This study would aim to create arespiratory system. (Proctor et al., 1989). The background data on lead exposure of womenprocess of manufacturing electronic board is workers as well as to create an understanding andquite lengthy. It begins with wafer fabrication, awareness of the dangers of lead and how towafer sawing, die bonding, wire bonding, protect themselves from exposure. Theplating, soldering if necessary, testing and finally objectives of this study are to assess the leadpackaging. Exposure to lead would mainly be exposure of a group of circuit board solderingfrom the soldering process as fumes from the workers and a comparative group in ansoldering material is an alloy containing 40% electronics factory by determining their bloodlead and 60%. The chronic exposure to low pressure, blood lead concentrations, the air leadconcentrations of lead over a long period would and surface dust lead concentrations in the workcause detrimental effects on humans (Nurunniza, areas; to compare the blood lead concentrations,2001; Mazrura, 1996; Megat, 2000; Kovala et al., blood pressure between the 2 groups of workers;1997). to find any correlation between blood lead and Lead exposure increases the risk of high these studied variables in the exposed group.blood pressure (ATSDR, 1989). Massive dosesof lead can cause cardiac abnormalities. Lead cancause serious, permanent kidney and braindamage at high enough levels. Low levels may 49
  10. 10. Methodology after work was considered as the lead concentration that the respondents were exposedWorkers demographic background to. This was a cross-sectional study carried Blood Lead and Blood Pressureout at an electronics factory in Petaling Jaya,Selangor. The plant produces various types of The respondent’s venous blood sampleselectronic parts and the employees comprise were collected and preserved (Sinclair andproduction operators who are mostly women. Dohnt, 1984) . The lead analysis carried out withFrom the name list of all the employees, all the the wavelength of 283.3nm according to Hitachi50 lead soldering operators were selected as Method (Hitachi Ltd., 1997) using Hitachi Z-exposed group. Questionnaire interviews were 5000 Series Polarized Zeeman Atomicconducted on the exposed worker to obtain their Absorption Spectrometer. Blood pressurebackground information and from these readings were taken using a digital bloodinformation, the unexposed group were selected pressure monitor (MARS Digital Blood Pressureand matched according to the background of the Monitor) before blood collection.exposed group. From these, 36 non leadsoldering operators were selected purposively as Quality Controlunexposed group and matching was carried outin terms of age, gender, smoking and health Quality control and assurance arestatus. These workers had also given a written procedures that are taken to ensure the quality ofconsent to participate in the study. the data produced in this study. The quality control procedures that were used for this studyAir Lead include pretest of questionnaire, calibration maintenance of all instruments, Standard The workers breathing area was Operating Procedure (SOP) on sampling,sampled for 8 work hours with Escord Elf air- analytical methods and materials.sampling pumps and mixed cellulose ester(MCE) filters with 0.8 µm pore size, 37 mm Ethicsdiameter. The pump was calibrated at a flow rateof 1.7 L/min. A cyclone was attached to the All respondents were briefed about thepump so that only the respirable lead from the study and were asked to participate in the studyincoming air was sampled. The filter papers on a voluntary basis. Consent forms were givenplaced on the cassette holders attached to the to be read and signed. All respondents werecyclone were digested and analyzed to determine given a choice to continue participating in thethe concentration of lead by using Graphite study or to pull out at any time they choose to doFurnace Atomic Absorption (Hitachi Z-5000 so. In following specifications for an ethicalSeries Polarized Zeeman). Method of air lead research, a certified and experienced doctor wassampling was adapted from Method No. 7105 – asked to draw blood from the respondents.Lead by GFAAS (NIOSH, 1994). Finally all the information about the respondents and the company that was involved in thisDust Lead research remains confidential. The study had the approval of the Faculty of Medicine and Health For dust lead sampling, 19 respondents Sciences Ethics Committee.from the 50 exposed group were randomlysampled. Dust lead from the workstation surface Resultswas collected by taking wipe samples. The tissuepaper used as wipes were first weighed. Two sets Background informationof wipe samples which consist of the left andright side surface area were taken before they The respondents who took part in thisstart work and at the end of the shift before they study consisted of mainly Malay and a minorityclean up the table. The samples were collected, Indian ethnic groups. The total number ofweighed and digested according to Method No. respondents was 83, whereby 50 were in the9100: Lead in Surface Wipe Samples (NIOSH, exposed group and the remaining 33 were from1994). The difference between the lead the unexposed group (Table 1). As can be seen inconcentrations in the wipe samples before and Table 1, there are 22 exposed respondents and 33 50
  11. 11. unexposed respondents living in the Klang the systolic blood pressure (p= 0.955) and theValley. diastolic blood pressure (p = 0.554 ) between the two groups.Table 1 : Background information of workers Study Groups; Comparisons in Air Lead Variables Frequency (%) The mean personal air lead Exposed Unexposed Total concentration was 0.5723 g/m³ and 0.0067 (n=50) (n=33) (N=83) g/m³ for the exposed and the unexposed group Ethnic groups respectively (Table 3). The distribution of air 45 (90.0) 24 (72.7) 69 (83.1) lead concentration is significantly different from -Malay 4 (8.0) 9 (27.3) 13 (15.7) -Indian 1 (2.0) - 1 (1.2) a normal distribution curve, therefore non -Others parametric statistical test was used to determineResidential areas the difference between the groups. There is a -Klang Valley 22 (44.0) 19 (57.6) 41 (49.4) significant difference in air lead concentration -Non-Klang 58 (56.0) 14 (42.4) 42 (50.6) between the two groups in which the exposed ValleyN = 83 group have higher air lead concentrations than the unexposed group (t = 5.307, p < 0.001).Comparisons of Age and Blood Pressure Table 3 : Lead exposure variables The mean age of the exposed group was Study groups31.08 years and the unexposed group mean ± std.dev. Z prespondents were slightly older with a mean age Variables value valueof 33.78 years. There is no significant difference Exposed Unexposedin age between the exposed and unexposed group (n=50) (n=33)as shown in Table 2. Air lead 0.57 ± 0.0067 ± -5.10 < 0.001** concentrations 0.93 0.0045Table 2 : Biological profile of workers (µg/m3) Study groups Blood lead 5.10 ± 5.09 ± -1.18 0.239Variables mean ± std.dev. t/Z p concentrations 1.41 0.88 value value (µg/dl) Exposed Unexposed (n=50) (n=33) N = 83 Statistic Mann Whitney U test ** Significant at p ≤ 0.01Age 31 ± 6.3 34 ± 6.8 -1.820 0.073(years)∇ Comparison in Dust LeadSystolicblood 121.18 ± 117.58 ± -0.591 0.554pressure 18.59 20.00 The distribution of dust lead(mmHg)≠ concentration was significantly different from a normal distribution curve. Therefore, non parametric statistical test was used. For the leftDiastolicblood 72.16 ± 72.27 ± -0.056 0.955 side surface area, the mean lead concentration ispressure 12.81 11.83 8.45 g/cm² and the right side surface area has a(mmHg)≠ mean of 49.10 g/cm² (Table 4). There is a significant difference in the mean dust leadN = 83∇ statistic test concentration between the left and right side in≠ statistic Mann Whitney U test which the right side surface area has higher dust lead concentration than the left side surface area For the exposed group, the mean (t = -7.231, p < 0.001).systolic blood pressure measurements were121.18 mmHg and for the unexposed group was Comparison of Blood Lead Concentrations117.58 mmHg. The diastolic blood pressure ofthe exposed group had a mean of 72.16 mmHg The distribution of blood leadand for the unexposed group was 72.27 mmHg concentration is also significantly different from(Table 2). There is no significant difference in a normal distribution curve, therefore, non 51
  12. 12. parametric test was again used. The mean blood was found between blood lead concentrationslead concentration of the exposed group is 5.10 with air lead concentrations and blood g/dl and for the unexposed group is 5.09 g/dl concentrations for each separate group as well as(Table 3). There is no significant difference in when both groups are combined (Table 5).mean blood lead concentration between the The same test was carried out toexposed and unexposed group. (t = – 0.273, p = evaluate the correlation between blood lead0.786. concentrations and dust lead concentrations for the 19 exposed workers. There is also noTable 4 : Lead dust levels between right and left significant correlation between the two variables hand for the right side surface area as well as for the left side (Table 5). Exposed group mean ± std.dev. Variables Z P value Discussions Right Left value side side From the results it is clear that the (n=19) (n=19) respondents are exposed to very low concentrations of air lead. Through observations,Dust lead 49.10 ± 8.45 ± -3.823 <0.001** the use of central and individual exhaust filterconcentrations 34.19 9.04 systems may have contributed to the low air lead(µg/cm2) concentrations. Each workstation has an exhaustN = 19 suction fan with filter placed directly towardsStatistics Mann Whitney U test where the workers do their soldering work.** Significant at p ≤ 0.01 Therefore, all the fumes from the soldering work will be sucked to the central exhaust fan throughCorrelation between Blood Lead the individual exhaust fan almost immediately.Concentrations with Studied Variables There is very little chance for the fumes to escape unless the workers attempt to solder far The Spearman’s Rho test for correlation away from the suction range of the exhaust.was carried out since most of the data is notnormally distributed. No significant correlationTable 5 : Relationship between blood lead and selected variables Blood lead concentrations (µg/dl) Variables Exposed Unexposed All r P value r P value r P valueAir lead concentration (µg/m3) 0.021 0.887 -0.036 0.844 -0.023 0.840Right hand dust lead level (µg/cm2)# 0.255 0.291 - - - -Left hand dust lead level (µg/cm2) # 0.019 0.937 - - - -Systolic blood pressure (mmHg) -0.078 0.588 -0.146 0.419 -0.142 0.201Diastolic blood pressure (mmHg) -0.025 0.864 -0.085 0.638 -0.078 0.485N = 83# n = 19Statistic Spearman rho test 52
  13. 13. Other factors could also be that the this study were higher. This is obvious due to theproduction rates were quite slow at the time of area sampled and the nature of the work that thissampling. Due to the current economic study had focused on. Not only were the workersdownturn, most electronic companies were working with soldering alloy made up of 40%producing at rates far below their normal rates. lead, the area sampled was directly where theAs such, the respondents were working less work was being done and would naturally havebecause there was not much production targeted an extremely high concentrations of lead.and working hours were limited to a maximum The WHO has proposed 40 g/dl asof 6 hours a day. Therefore, the air lead maximal tolerable individual blood leadproduced was probably be lower than it would concentrations for adult male workers and 30have been if production is at maximum capacity. g/dl for women of childbearing age. The The findings of this study were respondents blood lead which did not exceed 10consistent with a study (Sinclair and Dohnt, µg/dl, indicates that lead does not pose any1984) on a group of crafts workers who produce hazard in their workplace and no significantstained glass. Their air sampling indicated air difference found in the mean blood lead betweenlead concentrations ranging between 0.88 to 15 the 2 groups.µg/m³ with a mean of 6.0 µg/m³. This value is Although the soldering workers arehigher than that obtained from this study. The exposed to lead during their work, this exposurePEL for air lead concentration set by the United does not seem to have any effect on their bloodStates Occupational Safety and Health lead concentrations. Therefore, this suggests thatAdministration is 50 µg/m³ whereas Malaysian whatever blood lead concentrations that thestandards set by the Factories and Machinery Act respondents have are not from their workplace(FMA) is 150 µg/m³. All these workers were but from the general environment such asexposed to less than 5 µg/m³ air lead. Therefore, ambient air, food, water, dust from the streets oralthough there was a difference in concentration paints and perhaps emission from nearbyof personal air lead between the exposed and industries. Since the blood concentrations areunexposed groups, their low blood lead very low, no adverse health effects are seen inconcentrations indicates that inhalation was not the respondents.the main route of exposure. One of the reasons why correlation From the statistical results, the lead dust between air lead concentration and blood leadconcentrations for the right side surface area are concentration is often very poor is because evensignificantly higher than the left. This is due to though the respiratory tract is the main route ofthe fact that the workers hold the soldering iron exposure, intake by the oral route such ason their right side surface area of their work area consumption of lead contaminated food andand clean the tip of the iron rod on the right side drinking water may be overwhelming that it willsurface area of the work table. These caused a increase total uptake and therefore, sway a directlot of dust and pebbles of melted solder wire to correlation between air lead and blood leadscatter around the right side of the work table. concentrations (Stellman, 1998). Some other studies have found varying Although there is a significant amountlevels of dust lead depending on the area in of contamination of dust lead at the work station,which they were collected. A study (Kaliamal, this contamination has no effect on blood lead2001) reported dust lead levels in homes to have concentrations. This could mean that althougha mean of 0.07 ng/g/m². Whereas another study the dust lead was present, the workers are(Johnson et al., 2000) among workers working protected from either inhalation or skinon a bridge found that although airborne lead absorption. This could be explained by the factexposure was low, surface contamination was that all the workers use facemasks and glovevery high especially on their clothing 4766 when entering the soldering department. Theyµg/m²) and vehicles (3600 µg/m²). The American must also use finger cots when doing solderingConference of Governmental Industrial work as well as practice good hygiene such asHygienists (ACGIH) has set a Housing and hand washing before and after work.Urban Development (HUD) guideline of 200 Although the mean blood pressure ofµg/ft² for construction work surface lead both systolic and diastolic blood pressure for theconcentration. exposed workers was slightly higher than the When compared to the above studies as unexposed workers, this difference was notwell as to the guideline, the values obtained in significant. The mean blood pressure of the exposed workers was 121.18 / 72.16 mmHg 53
  14. 14. whereas the unexposed workers had a mean finally, blood lead at a level of below 10 µg/dl,blood pressure of 117.58 / 72.27 mmHg. This does not cause an increase in blood pressure. Inresult is quite close to the findings in a study of conclusion, the lead soldering workers in thislead battery manufacturing workers (Wu et al., electronic factory are not at high risk of exposure1996) which showed a mean blood pressure of to lead from their workplace.121.7 / 77.9 for the female workers. There is no correlation between bloodlead concentration and blood pressure since the Referencesblood lead was found to be very low. Nodifference in blood pressure was found between Proctor, N.H., Hughes J.P., Fischman M.L.the 2 groups. Hypertension may begin to occur at Chemical Hazards of the Workplace, 2nd ed.,blood lead concentrations of 10 µg/dl and above 1989. Van Nostrand Reinhold, Philadelphia.(Kovala et al., 1997). As such, the results of this Nurunniza Z.A. Comparisons of Blood Leadstudy is consistent with (Kovala et al., 1997) that Concentrations and Neurobehavioralsince the workers’ blood lead concentrations are Scores between Two Groups of Workers inbelow 10 µg/dl, the average blood pressure was Selangor, Malaysia. Final Year Project,normal and not elevated. Occupational lead B.Sc. (Environmental and Occupationalexposure and blood pressure which stated that Health) 2001. Universiti Putra Malaysia.blood lead does not adversely affect blood Mazrura, S. Neurobehavioral Performancepressure unless at very high exposure. A similar Among Worker Exposed To Lead. Master ofstudy (Korrick et al., 1999) also concludes that (Public Health) Thesis,1996. Universitithere was no association between hypertension Kebangsaan Malaysia.and either blood or tibia lead concentrations. Megat, A.M.M. The Association of Blood Lead There are many standards and Concentrations on the Neurobehavioralregulations set by various government and non- among Women Production Workers in angovernmental bodies that are meant to be used as Electronic Factory. Final Year Project,guidelines for both environmental and (B.Sc. Environmental and Occupationaloccupational settings. The Occupational Safety Health) 2000. Universiti Putra Malaysia.and Health Administration (OSHA) of United Kovala T., Matikainen, E., Mannelin, T., Erkkila,States have regulated a Permissible Exposure J., Riihimaki, V., Hanninen, H., Aitio, A.Limit (PEL) for air lead levels at 50 g/m3. It Effects of low level exposure to lead onalso regulates the removal of a worker from neurophysical functions among lead batteryexposure if his/her blood lead level reaches workers. Occup. and Environ. Med.1997.60 g/dl or higher. The American Conference of 54: 487-493.Governmental Industrial Hygienists (ACGIH) ATSDR – American Toxic Substance and Drugrecommends a TWA of 150 g/ m3 for air lead Registry. Lead Toxicity. 1989. USand 30 g/dl for blood lead concentration. The Department of Health and Human Services.Centers for Disease Control (CDC) have Cooper, A.K. Cooper’s Toxic Exposures Deskrecommended that the level of concern for blood Reference. 1996:pp.1286-1296. Croomlead for the general population to be 10 g/dl. Helm Ltd, LondonFrom this study, the blood lead concentrations of NIOSH Lead by GFAAS, (Method No. 7105,these workers conformed to all the regulations Issue 2). NIOSH Manual of Analyticalstated above. Methods, 4th Edition. DHHS NIOSH Publication. 1994.Conclusion www.cdc.gov/niosh/nmam/nmammenu.html NIOSH Lead in Surface Wipe Samples (Method There is a significant difference in air No. 9100, Issue 1). NIOSH Manual oflead concentrations between exposed and Analytical Methods, 4th Edition. DHHSunexposed respondents. Dust lead concentrations NIOSH Publication 1994.on the right side surface area were significantly www.cdc.gov/niosh/nmam/nmammenu.htmlhigher than the left side surface area. However, Sinclair D.F. and Dohnt B.R. Sampling andthere is no significant difference in blood lead analysis techniques used in a blood leadconcentrations and blood pressure between survey of 1241 children in Port Pirie, Southexposed and unexposed respondents. Air as well Australia. Clin. Chem.1984. 10:1616-9.as dust lead concentrations does not directly HITACHI, (1997). Sample Analysis Methods.contribute to blood lead concentrations and GFAA Guide For Polarized Zeeman Atomic 54
  15. 15. Absorption Spectrometry (7): pg 48. Japan: bridge:comparisons of trades, work tasks. HITACHI Ltd. Am. Ind. Hygiene Assoc. J. 2000. 61, 815-Pant B.C., Harrison J.R., Long G.W., Gupta S. 819. Exposure to lead in stained glass work. An Stellman, J.M. (Ed). Encyclopedia of environmental evaluation. The Sci. of Tot. Occupational Health and Safety (4th edition). Environ. 1994. 141: 11-15. 1998. International Labour Office, Geneva.Kaliammal M. Relationship between indoor dust Wu, T.N., Shen, C.Y., Ko, K.N., Guu, C.F., Gau, lead level and children’s blood lead H.J., Lai, J.S., Chen, C.J., Chang, P.Y. concentration in Seri Serdang, Selangor. Occupational lead exposure and blood B.Sc. (Environmental and Occupational pressure. Int J. of Epid. 1996. 25: 791-796. Health) 2001. Universiti Putra Malaysia. Korrick S.A., Hunter D.J., Rotnitzky A., Hu H.,Johnson J.C., Reynolds S.J., Fuortes L.J., Clarke Speizer F.E. Lead and hypertension in a W.R. Lead exposure among workers sample of middle aged women. Am. J. of renovating a previously deleaded Pub Health. 1999. 89: 330-335. 55
  16. 16. Occupational Heat Stress Of Workers In A Plastic Industry, Selangor Goh See Bena , Zailina Hashimb , Rosnan Hamzahb a Seremban Health Office, Seremban District, Negeri Sembilan b Environmental & Occupational Health Unit, Department of Community Health, Faculty of Medical & Health Sciences, Universiti Putra MalaysiaAbstract A cross sectional study to determine the exposure of heat and its biological effects on the workers in aplastic factory located in the Shah Alam Industrial Estate, Selangor, Malaysia. Forty five respondents from thepolymer section in the factory were selected as the respondents. Variables measured were the environmentaltemperature (WBGTin), air velocity, relative humidity, body temperature, average heart and recovery heart rate.QUESTEMP°34 Area Heat Stress Monitor was used to measure the environmental temperature in °C (WBGTin) andrelative humidity (%). Velocicheck Model TSI 8830 was used to measure the air velocity in meter per second (m/s)while the OMRON Blood Pressure Monitor Model T3, was used to measure average heart rate and recovery heartrate. Body temperature (°C) was measured by the Instant Ear Thermometer-OMRON Gentle Temperature ModelMC509. Interviews using questionnaires were used to determine respondents’ socioeconomic background, previousrisk factors on heat exposure and other information related to heat stress. Results showed that the meanenvironmental temperature for the exposed group was 28.75°C, the mean air velocity was 0.15 m/s and the meanrelative humidity was 58.1%. These production workers were exposed occasionally to heat when loading plasticpowder into the molds as well as demolding the finished plastic products from the molds. The average time ofmonitoring was 2 hours for intermittent exposure and 8 hours duration for overall exposure. Maximum demand forwork load was measured 1 minute after work activities were stopped at the demolding section. There was asignificant difference between body temperature and average heart rate before work, after 2 hours of work and after 8hours of work ( p < 0.001). The mean recovery heart rate after 1 min was 88.0 ± 12.0 beat per min. (bpm), indicatingthat there is no excessive physiological demand. Body temperature (36.8 ± 0.40°C) and average heart rate after 8hours (78 ± 12 bpm) indicated a good body control of heat exposure. Five out of six workplaces monitored hadtemperatures of greater than 28°C (ACGIH TLV). The workers were exposed to moderate heat stress during thestudy period, however, body temperature and average heart rate measurement did not reach unacceptable level ofphysiologic strain.Key words: occupational heat stress, heart rate measurements, blood pressures, plastic industry and physiologic strain.Introduction One of the most overlooked hazards Temperature range from relatively at low 150oCthat encountered in workplaces is heat. Previous to extreme cases of 250oC. Crockford et al.research has found that excessive exposure to (1981) said the hot environment in theseheat at the workplace will develop heat stress industries has a profound effect on workers’(NWOSU, 2000; Cullen and Nadel, 1994). Heat comfort, productivity, safety and health.stress is the aggregate of environmental and This study aims at examining the heatphysical work factors that constitute the total strain and heat stress experienced by workers inheat load imposed on the body (Alpaugh and a plastic industry.Hogan, 1992).The bodily response to total heatstress is called the heat strain (NIOSH, 1986). In Methodologyterms of heat-related illnesses, the mildest formof heat stress are those which cause workers to This is a cross sectional study conductedfeel uncomfortably warm. Further exposure to in a factory at the Shah Alam Industrial Estate,hot workplace may result in heat cramps, heat Selangor. Forty five workers from the polymerexhaustion, heat syncope and heat stroke section were selected as the respondents. This(Kroemer, 1994). In plastic industries, many of study involved six measurements such as the Wetthe processes generate heat to the workplace. Bulb Globe Indoor Temperature (WBGTin), air 56
  17. 17. velocity, relative humidity, body temperature, The molding operations are continuousaverage heart rate and recovery heart rate. process which is carried out by two personnel The plastic industry is divided into three with a 12 hours work shift which are made up ofdistinct sectors. The first sector comprises the raw the machine operators and supervisors. Thematerial suppliers, which are used to manufacture highest overall exposure to heat stress waspolymers and molding compounds. The second machine operators. The study population wassector is made up of manufacturers, which made up of all the male production lines workers.convert raw materials into finished products. The Purposive sampling method was carried based onthird sector comprises machinery suppliers, which the inclusion criteria such as: male workers; agesupply equipment to the manufacturers. Many of between 20-55 years; work duration of more thanthe plastics processing machines operate at very 3 months and healthy (non-alcoholic, withouthigh temperature of above 200oC. hypertension and not using drugs). To evaluate the heat stress experienced A workplace with temperature of moreby the workers at the workplace, the than 37oC can influence the body heat exchangeenvironmental parameters at selected work with the environment (Alpaugh and Hogan,locations were measured; metabolic rate for 1992). It was concluded that repeat heat exposuredifferent activities were estimated and mapping for 9-10 consecutive days, can alter bodywere made on the amount of time spent at temperature. Therapeutic drugs interfere withdifferent work locations in the factory (Logan and thermoregulation and affect heat toleranceBernard, 1999). The American Conference of (Deberairdim, 1999). A hypertension patient canGovernmental Industrial Hygienists method for reduce heat transport from the body to skin andestimating metabolic rate was used. The WBGT increases the risk of overheating (Havenith,has proved to be very successful in monitoring 1995).heat stress (ACGIH, 1999). QUESTEMP°34 Area Heat Stress Measurements of body temperature and Monitor was used to measure the WBGTinheart rate were carried out before work, after 2- environmental temperature (°C) and relativehours and after 8-hours of work. Intermittent humidity (%) (Quest Technologies, 1997)exposure should be averaged over 2-hours (US Velocicheck model TSI 8830 measured the airdept. of Labour, 1999). For overall exposure, the velocity (m/s) while the OMRON model T3, waswork period of about 3 to 5-hour could be taken used to measure average heart rate and recoveryas a representative (Logan and Bernard, 1999) but heart rate. Body temperatures (°C) werean 8-hour work period would definitely give a measured by the Instant Ear Thermometer-Omroncomprehensive picture. NIOSH (1986) model MC509. Closed ended self-administeredrecommended the recovery heart rate of 1 minute questionnaires were used to determine(HR@1) as the second criteria of indicator for respondents’ socioeconomic background, theirwork demand and work strain. Heart rate history of risk factor in heat exposure and otherrecovery after 1-minute at the end of removing information related to heat stress. For qualityfinished products from molds was recorded. control, all instruments were calibrated before Four environmental parameters were use.also measured which included the ambienttemperature, radiant temperature, air velocity and Resultsrelative humidity. Environmental parameters wererecorded for 8 hours daily. Background information of respondents The factory was divided into 6workplaces namely Rotational (RS) 160, RS 220, More than half of the respondents wereRock and roll (RR) 1000, RR 2000, metal foreign workers from Bangladesh and Indonesia.fabrication and general site, to facilitate Majority had gone through secondary education.environmental measurement. The four basic steps The age range was between 20 to 50 years oldof molding processes were loading, heating (170 and the majority of the respondents were betweento 370oC), cooling and demolding (10). Time for a 20-30 years old. Sixty percent had a normal BMIwhole cycle takes 60 minutes and average time of 18.5 –24.9. Sixty percent had normal Bodyfor demolding range from 7 to 15 minutes. The Mass Index. All of them had worked for moreheat ejected from machines and molding than 3 months. Majority of them were machineprocesses can contribute to a heat stress that operators (Table 1).requires evaluation (Burges, 1995). The respondents’ health complaints obtained through questionnaire interview are 57
  18. 18. tabulated in Table 2. Most frequent health Comparison of body temperature and heartsymptoms experienced were dizziness due to the rate, before and after work.radiant heat produced by the machines. Comparisons of body temperature beforeTable 1 : Background Information of work, after 2 hours and after 8 hours of work are Respondents. as shown in Table 3. The mean body temperature before work was 36.3 ± 0.55oC, after 2 hours of Variables Male Percentage work was 36.7 ± 0.36oC and after 8 hours of work Race was 36.8 ± 0.40oC. Paired t-test gave a significant 14 31.1 difference of mean body temperatures before Malay 2 4.4 Chinese work with after 2 hours work (t = 6.51, p<0.001) 2 4.4 Indian 16 35.7 and before work with after 8 hours of work Bangladesh 11 24.4 (t=5.93, p<0.001) respectively. The means and Indonesia range of the measured body temperatures are Job Classifications shown as box plots in Figure 1. Operator 30 66.7 Comparisons of heart rate before work, Metal Fabricator 5 11.1 after 2 hours, after 8 hour of work and recovery Foreman 5 11.1 heart rate at 1 min after loading plastic powder Quality Controller 2 4.4 and removing finished product from the plastic Supervisor 3 6.7 molds are tabulated in Table 3. The mean heart Age group rate before work was 71 ± 10 bpm, after 2 hours 20 – 30 years 29 64.4 of work was 76 ± 11 bpm and after 8 hours of 31 – 40 years 9 20.0 work was 78 ± 12 bpm. Paired t-test results 41 – 50 years 7 15.6 showed a significant difference before work, after >50 years 0 0 Body Mass Index Table 3 : Comparison of Body Temperature and <18.5 (Underweight) 6 13.4 Heart Rate of Respondents According 18.5 – 24.9 (Normal) 27 60.0 to Work Duration 25 – 29.9 (Overweight) 11 24.4 30 – 34.9 (Obese) 0 0 Main Comparative Variables t p 35 – 39.9 Very obese 1 2.2 Variables >40 Extremely obese 0 0 Education Body temperature °C Primary 2 4.4 Mean ± std. dev. Secondary 38 84.5 Before After 2 hrs work 6.51 <0.001 Tertiary 5 11.1 36.3 ± 0.55 36.7 ± 0.36 Duration of work Before After 8 hrs work 5.93 <0.001 3 – 12 months 10 22.2 36.3 ± 0.55 36.8 ± 0.40 13 – 24 months 9 20.0 After 2 hrs After 8 hrs work 1.68 0.98 > 25 months 26 57.8 36.7 ± 0.36 36.8 ± 0.40 N = 45 Heart rate (bpm) Mean ± std. dev.Table 2: Health Complaints of Respondents Before After 2 hrs work 5.41 <0.001 Health complaints Percentage 71 ± 10 76 ± 11 Before After 8 hrs work 6.38 <0.001 Dizziness 37.8 71 ± 10 78 ± 12 Fatigue 22.2 After 2 hrs After 8 hrs work 2.18 0.034 Nausea 11.1 76 ± 11 78 ± 12 Muscles spasm 11.1 Before At 1 min 5.71 <0.001 Uncoordinated movement 8.9 71 ± 10 88 ± 12 Fainting 2.2 (Recovery Rate) N = 45 58
  19. 19. 2 hours work and after 8 hours of work difference with the mean heart rate before work (trespectively (t = 5.41; p<0.001; t = 6.38; = 5.71; p<0.001). The means and range ofp<0.001). The mean recovery heart rate after 8 measured heart rate are showed as box plot inhours of work also showed a significant Figure 2. 3 8 .0 3 7 .5 3 7 .0 3 6 .5 3 6 .0 3 5 .5 44 3 5 .0 N = 45 45 45 T e m p b e fo re w o rk te m p a fte r 2 h r te m p a fte r 8 h r Note : ------- = _____ = Threshold for body temperature Figure 1 : Box plots of respondents’ body temperature ° 110 100 90 80 70 60 50 40 N = 45 45 45 H R b efo re w o rk H R a fte r 2 h r H R a fte r 8 h r Note : ------ = Threshold for heart rate for moderate heat stress (110 bpm) HR : Heart rate (beat per minute) Figure 2 : Box plots of respondents’ heart rate (bpm) 59
  20. 20. Assessment of heat stress 26.50 – 30.40 oC. As shown in Table 4, a one way ANOVA test results showed a significant The assessment of heat stress difference in the WBGTin at the 6 studiedis based on the Wet Bulb Globe Temperature workplaces (F=4.090, p=0.004).(WBGT), which is adjusted to work demand Table 5 shows estimated metabolic ratereflected in metabolic rate (NIOSH, 1986). for respondents range from (250 – 300 kcal/hrMeasured Wet Bulb Temperature range from with work/rest regimen of 75% work, 25% rest,(25.5 – 29.3oC); Globe Temperature (28.4 – each hour. Five out six workplaces were above36.1oC); Relative Humidity (44 – 77%) and Air the heat exposure threshold of 28oC (ACGIHVelocity (0.01 – 0.28m/s) at various workplaces TLV). The areas were RS 220, RR 1000, RRin the production lines. One way ANOVA test 2000, Metal Fabrication site and General site.gave a significant value for Natural Wet Bulb However, statistics did not show any significantTemperature and Globe temperature at these correlation between workplaces with bodywork places (F=8,005, p<0.001; F=2.701, temperature or heart rate after 8 hours of workp=0.03). Measurements of Wet Bulb Globe respectively (Table 6).Indoor Temperature (WBGTin) at theseworkplace showed a range of temperature fromTable 4 : The Comparisons In Means For Natural Wet Bulb Temperature, Globe Temperature And Wet Bulb Globe Temperature Indoor Between The 6 Workplaces. *Variable / Areas Range Mean ± std. dev. F pNatural Wet BulbTemperatures (°C) 25.5 – 27.6 27.0 ± 0.52Machine RS 160 25.5 – 26.8 26.2 ± 0.46 8.005 0.001Machine RS 220 27.4 – 29.3 28.0 ± 0.59Machine RR 1000 26.0 – 28.0Machine RR 2000 27.3 ± 0.73 25.9 – 28.7 27.8 ± 0.98Metal Fabrications 26.5 – 28.3General site 27.6 ± 0.57Globe Temperatures (°C) 28.3 – 33.0 31.2 ± 1.40Machine RS 160 29.1 – 33.8 31.4 ± 1.50 2.701 0.03Machine RS 220 31.2 – 33.8 32.6 ± 0.90Machine RR 1000 29.7 – 36.1Machine RR 2000 33.9 ± 2.14 28.4 – 34.5 32.8 ± 2.15Metal Fabrications 28.9 –33.9General site 32.0 ± 1.82WBGTin 26.5 – 28.5 27.7 ± 0.70Machine RS 160 26.8 – 29.0 28.2 ± 0.73 4.090 0.004Machine RS 220Machine RR 1000 28.5 – 30.0 29.2 ± 0.50 27.1 – 30.4 29.3 ± 1.10Machine RR 2000 26.6 – 30.3Metal Fabrications 29.2 ± 1.33 27.2 – 29.9 28.9 ± 0.88General siteNote : N = 8 ( Eight hourly monitoring for each workplace) 60
  21. 21. for accumulated effects on heat stress. (Nag et Table 5 : Heat Stress At Various Workplaces al., 1999). with Moderate Work Task The box plots represented the body temperature data collected during the study Workplaces Measured Work period (Kinnear and Gray. 1999). The highest WBGTi regime value of body temperature measured was 37.3°C Machine RS 160 27.7 and 37.4°C after 2 hours and after 8 hours of Machine RS 220 28.2* work respectively. There was a significant 75% work, difference for body temperature measured at Machine RR 1000 29.2* 25% rest, Machine RR 2000 29.3* different work durations. However, body each hour Metal fabrication 29.2* temperature of below 38.0°C as a threshold General sites 28.9* value is considered a safe exposure for the respondents (ACGIH, 1999). *Measured WBGTi is above the recommended Logan et al., (1999) found in his study ACGIH TLV of 28.0. on 31 aluminum smelters who were exposed to heat, that 95% of the subjects had oralTable 6 : Correlation between WBGTin with body temperature below 38.0°C. Azwan and Rampal temperature and heart rate of (2001) also recorded 96.2% out of 164 respondents. respondents selected for a heat stress study at Main Co-related two major steel plants was 37.5°C (below the Variable Variables r p body temperature threshold for a safe exposure). Heart rate is a measurement of both WBGTin Body temperature 0.143 0.348 work demands and heat stress. Heart rate is a (after 8 hrs work) valuable guide in accessing hazards to health workers exposed to heat stress (Mirnard, 1973) . Heart rate 0.150 0.325 There was a significantly difference for (after 8 hrs work) body heart rate at different intervals of work durations. The highest value of average heart Discussions rate measured was 100 bpm and 103 bpm for work after 2 hours and work after 8 hours. Zenz This study involved only male et al., (1994) that daily average heart rate should respondents. Exposure to excessive heat is be less than 110 bpm for moderate work-load, associated with nephrolithiasis (Borghi, 1993) could probably result in a significant rise on testicular cancer (Zhang, 1995) and poor semen body heart rate. Recovery heart rate (HR@1) was quality (Bonde, 1992). A high incidence of uric based on the heart rate at 1 minute after work acid stones was present in the workers who were stop. As interpreted, if was greater than 120 exposed to heat stress (Borghi, 1993). Majority bpm, then work task and heat stress is of the respondents were foreign workers. All the considered high (NIOSH, 1986). respondents were in the age group of 20 to 50 Measurements of Natural Wet Bulb years. The overall height of the study Temperatures (NWBT) showed a range of 25.5 to respondents range from 156 – 179 cm, whereas 29.3oC, the Globe Temperature (GT) had a range weight of the respondents range from 43.8 – of 28.3 to 36.1oC and the Wet Bulb Globe 121.1 kg. Sixty percent of them had a normal Temperature indoor ( WBGTin) was in the range Body Mass Index (BMI). Age and BMI are of 26.5 to 30.4oC. There was a significant confounders and can influence heat stress. The difference for NWBT, GT and WBGTin in the 6 length of employment in the factory range from workplaces. However, there was no significant 3 months to 15 years. correlation between WBGTin with body Beside rectal temperature as a measure temperature or heart rate after 8 hours of work of body temperature, ear canal temperature can was found. These could be due to several factors. also be used. It was carried out by inserting a The short periods of time required for loading sensor in the ear canal (NIOSH, 1986). At highly plastic powder and removing product from the heated workplace, body temperature would start mould under the intense heat may not affect the to rise depending on the environmental heat. For workers as much as that would be predicted from this reason, body temperature is good indicator the WBGTin values (Havenith et al., 1997). The factory is semi-auto with most of the manual task handled by hoists and forklifts. These had greatly 61
  22. 22. reduced the manual lifting activities and Referencestherefore, reduce the heat load on the workers(Helander, 1991). Majority of the workers in the NWOSU (2000). Heat Related Injuries. Healthpolymer section had worked for more than 3 and safety department. NWOSU homepage.months and thus had acclimatized themselves http://nwosu.edu/well with the environment (Shido et al., 1999). Cullen, MR. and Nadel, E. (1994). ThermalWhen exposure to heat takes place over an stressors in Cullen, M. R. Textbook Ofextended period in workplace, a process of Clinical Occupational Environmentalphysiological adaptation called acclimatization Medicine. USA:W.B. Saunders Publisher.occurs. It is manifested as a reduction in the heart pp. 658-666rate and internal body temperature at the expense Alpaugh, EL. and Hogan, TJ. (1992).of increased sweating. Worker acclimatizes to a Temperature extremes in Barbara. A. P. (Ed)specific dry or humid atmosphere and to a Fundamentals of Industrial Hygiene 3rdspecific workload. Any increase in this load or in edition pp. 265-280. USA: National Safetythe thermal burden may result in health damage Council.(Havenith, 1995). NIOSH- National Institute for Occupational Sixty percent of workers had normal Safety and Health. (1986). Criteria For ABMI of 18.5-24.9, giving a better heat tolerance Recommended Standard Occupational(Donohue and Bates, 2000) and all of the foreign Exposure To Hot Environments. Departmentworkers come from tropical countries with hot of Health and Human Services, Washington.climate. Majority of the workers were also young pp.1-107.and about 64% are between the age group of 20- Kroemer. KHE., Kroemer, HB. and Kromer-30 years old. Havenith et al., (1997) showed in Ekbert, KE. (1994). Ergonomics-How Tohis study on factory workers that older workers Design For Ease And Efficiency. Prenticehave less efficient sweat glands. The respondents Hall Publisher. pp. 244-263.are also considered healthy because they have Crockford, GW. (1981) The thermal environmentfew health complaints. It was also observed that in Schilling, RSF., Occupational Healththe workers have short hourly break in between Practice 2nd Edition. London: Butterworthsthe work tasks whereby they were able to drink Publisher. pp. 453-490.water. This also reduced their body dehydration Logan, WP. and Bernard, ET. (1999). Heat stresswhen their bodily fluid are balance and thus cause and strain in an aluminum smelter. Am Ind.less heat stress. Hyg Assoc. J. 60:659-665. ACGIH - American Conference of GovernmentalConclusion Industrial Hygienists. (1999). 1992-1993 Threshold Limit Values for Chemical In summary the findings of this study Substances and Physical Agents andsuggest that workers in this plastic industry were Biological Exposure Indices. Cincinnati:exposed to moderate heat stress during the study ACGIH pp.89-96.period. Even though the measured WBGTi at OSHA (1999). Heat Stress. Technical Manualvarious workplaces were slightly above the Section III. Chapter 4. US Dept. of Labour.recommended ACGIH threshold level, the body Kearns, MP. and Corrigan, N. (1999). Opentemperature and average heart rate measured did flame heating methods for the rotationalnot reach unacceptable level of physiologic moulding of plastics. Rotation Nov : 34-38strain. Furthermore, no significant correlation Burges, WA. (1995) Recognition Of Healthwas found between the WBGTi with the body Hazards In Industry. A Review Of Materialstemperature as well as the heart beat. However, And Processes, 2nd edition. Canada: Johnpreventive measures to excessive heat exposures Wiley & Sons. Inc.which can cause physiological strain and Deberairdim, LJ. (1999). Handbook ofeventually lead to poor health outcome of the Occupational Safety And Health. 2nd Edition.workers must be addressed by the management USA: John Willey and Sons Publisher.in order to sustain productive and healthy Havenith, G. (1995) Individual Heat Stressworkers. Response. Physiological Research Center, University Park, PA, USA. pp. 67-77. Quest Technologies. (1997). Questemp34° Thermal Environment Monitor, Operator’s 62
  23. 23. Manual. Wisconsin, USA: Quest Havenith, G. Coenen, J., Kistemaker, L. and Technologies. Kenney WL., (1997) The Relevance OfBorghi, L. (1993). Hot occupation and Individual Characteristics For Human Heat nephrolothiasis. J. Urol. 150(6):1757-1760. Stress Response Is Dependent On WorkZhang, ZF. (1995) Occupational exposure to Intensity and Climate Type. Physiological extreme temperature and risk of testicular Research Center, University Park, cancer. Arch. Env. Health. 50(1):13-17. Pennsylvania, USA.Bonde, JP. (1992). Semen quality in welders Helander, M. (1991) A Guide To The Ergonomics exposed to radiant heat. Brit. J. Ind. Med. Of Manufacturing. USA: Taylor & Francis 49:5-10. Publisher.Nag, A. Kothari, D. and Desai, H. (1999). Shido, O. Sugimoto, N. Tanabe, M. and Exposure limits of women in hot Sakurada, S. (1999). Core temperature and environment. Ind J. Med. Res. 138:110. sweating onset in humans acclimated to heatKinnear, PR. and Gray, CD. (1999) SPSS For given at a fixed daily time. J. Appl. Physiol. Windows Made Simple 3rd Edition. UK: 276 (4):1095-1101. Psychology Press Ltd. Donoghue. AM. and Bates GP. (2000). The riskAzwan A. and KG Rampal. (2001). Heat stress of heat exhaustion at a deep underground among workers in two steel plants in metalliferous mine in relation to body-mass Peninsular Malaysia. Paper presented at the index and predicted VO2max. Occup Med. 2nd National Public Health Medicine 50 (4): 259-263. Conference at the Summit Hotel, Subang Jaya. 17 -19th April 2001. AcknowledgementMirnard D. (1973). Industrial Environment-Its Evaluation and Control. Physiology of Heat Acknowledgement to the Management of the Stress. (NIOSH) Department of Health and Plastic Industry and the workers who Human Services, Washington . volunteered in the study. Research funded by theZenz. C., Dickerson, OB. and Horvath, E. (1994). faculty of Medicine and Health Sciences, Occupational Medicine 3rd Edition. Ohio, Universiti Putra Malaysia. USA: Mosby Publications, pp. 305-331. 63

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