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Journal of Occupational Health Psychology2001, Vol. 6, No. 3, 182-195

Copyright 2001 by the Educational Publishing Foundation1076-8998/01/$5.00 DOI: 10.1037//1076-8998.6.3.182

The Interactive Effect of Chronic Exposure to Noise and JobComplexity on Changes in Blood Pressure and Job Satisfaction:

A Longitudinal Study of Industrial Employees

Samuel MelamedNational Institute of Occupational and

Environmental Health

Yitzhak FriedWayne State University

Paul FroomNational Institute of Occupational and Environmental Health

The hypothesis of this study was that noise exposure level and job complexity interact to affectchanges in blood pressure (BP) levels and job satisfaction over 2-4 years of follow-up. Resultsshowed that among workers exposed to high noise, those with complex jobs showed increases inBP that were more than double shown by those with simple jobs. Under low noise exposure, therewas a small increase in BP for workers with complex jobs but about a 3-fold increase in workerswith simple jobs. The prevalence of elevated BP showed a similar trend. Job satisfactionincreased among workers with complex jobs but was much less in those exposed to high noise.It was concluded that exposure to occupational noise has a greater negative impact on changes inBP and job satisfaction over time among those performing complex jobs. In contrast, jobcomplexity had a clear beneficial effect for workers exposed to low noise.

In recent years, considerable effort has been di-rected toward investigating the possible effects ofchronic exposure to noise on the cardiovascular sys-tem, especially on the risk of hypertension. Interest inthe effects of chronic exposure to noise has twomajor sources. First, it is recognized that high ambi-ent noise is one of the most prevalent environmentalstressors in the workplace. North American researchhas shown that the percentage of workers exposeddaily to harmful noise of over 85 dB(A) rangesbetween 30% and 60% across industries (Deguise,1988; Franks, 1990). In certain industries, the per-centage may reach as high as 70%-95%. Second,laboratory studies have fairly consistently shown thatacute noise exposure, even at moderate levels ofaround 80 dB(A), has cardiovascular and autonomic

Samuel Melamed, Department of Occupational HealthPsychology, National Institute of Occupational and Envi-ronmental Health (NIOEH), Ra'anana, Israel; YitzhakFried, Department of Management, School of Business Ad-ministration, Wayne State University; Paul Froom, Depart-ment of Epidemiology, NIOEH.

This study was supported by the Committee for Researchand Prevention in Occupational Safety and Health, the Is-raeli Ministry of Labour and Social Affairs.

Correspondence concerning this article should be ad-dressed to Samuel Melamed, Department of OccupationalHealth Psychology, National Institute of Occupational andEnvironmental Health, P. O. Box 3, Ra'anana, Israel 43100.Electronic mail may be sent to [email protected].

effects that are manifested by increased vascular re-sistance (Andren, Hansson, Bjorkman, Jonsson, &Borg, 1979; Sawada, 1993), heart rate (Andren et al.,1979; Sawada, 1993), blood pressure (Andren et al.,1979; Harrison & Kelly, 1989; Sawada, 1993), andstress hormones (Miki, Kawamorita, Araga, Musha,& Sudo, 1998).

However, in contrast to the laboratory findings,field studies have found no consistent associationbetween occupational noise exposure and risk forhypertension and other cardiovascular diseases(Babisch, 1998; Kristensen, 1989; A. Smith, 1991).Weak correlations, no correlations, and even negativecorrelations between noise exposure and these end-points have been found in over 50% of these studies(Kristensen, 1989).

These inconsistent findings may be explained bythree reasons, two methodological and one concep-tual. First, the inconsistent results reflect the generaldifficulty in generalizing from the effects of labora-tory stressors on blood pressure to the effects ofchronic stressors on long-term elevation of bloodpressure (Harshfield et al., 1988; Pickering & Gerin,1988; Van Engeren & Sparrow, 1989). Factors thatcause acute changes in blood pressure may be differ-ent from those that contribute to chronic changes(Schwartz, Pickering, & Landsbergis, 1996).

Second, deficiencies in research design have beennoted in a high proportion of studies of occupational

182

NOISE, JOB COMPLEXITY, AND BLOOD PRESSURE 183

noise and its effects (e.g., Babisch, 1998; Kristensen,1989; Thompson, 1993). Most of the studies werecross-sectional or retrospective in nature, usuallywith no record of exposure history and of hearingprotector use. No control was made in many studiesfor other negative work and environmental condi-tions. Furthermore, in many studies, no direct mea-sure of noise was available, and the evidence ofhearing loss among the study's participants inferredthe existence of such exposure. The more method-ologically rigorous studies (e.g., those that controlledfor possible confounding variables) have reportedlower associations between noise exposure and bloodpressure levels (Thompson, 1993).

Third, it is conceivable that the inconsistent asso-ciations between noise and blood pressure are due tothe effect of moderators. One such moderator is jobcomplexity. Jobs higher in complexity typically re-quire the use of greater cognitive capacity comparedwith jobs lower in complexity. The information over-load model argues that individuals' capacity for in-formation processing is limited (e.g., S. Cohen,1980). Stressors such as noise increase cognitive loadbecause they require a share of cognitive capacity inaddition to that allocated to job requirements. Forsimple jobs (i.e., jobs of low complexity), the cogni-tive demands are low, so that the effect of noise onjob performance is likely to be relatively small. Incontrast, high ambient noise is likely to producecognitive overload on complex jobs that impose highcognitive demands and thus decrease performance onsuch jobs (e.g., Baron, 1994; S. Cohen, Gary, Evans,Stokols, & Krantz, 1986; Kryter, 1994). Moreover,increased cognitive overload is likely to lead to ad-verse psychological (e.g., lower job satisfaction) andphysiological (e.g., higher blood pressure) reactions.This association between increased cognitive loadand physiological responses has been demonstratedin numerous laboratory studies (e.g., Callister, Su-warno, & Seals, 1992; Fournier, Wilson, & Swain,1999; Svebak, 1982; Veltman & Gaillard, 1993,1996, 1998).

The literature has also provided more direct sup-port for the expected joint effect of noise and cogni-tive difficulty on physiological reactions. Specifi-cally, in a series of experiments, exposure to recordednoise (factory, aircraft, or traffic) in combination withmental task performance (binary-choice test) resultedin increased blood pressure compared with exposureto recorded noise alone (Mosskov & Ettema, 1977a,1977b). Similar results were obtained in other studies(Carter & Beh, 1989; Ray, Brady, & Emurian, 1984)but not in all (Wu, Huang, Chou, & Chang, 1988).

The combination of noise and cognitive task perfor-mance was also associated with increased muscletension (Hanson, Schellekens, Veldman, & Mulder,1993) and increased heart rate, norepinephrine, andcortisol levels (Tafalla & Evans, 1997). The proposedexplanation of these and other noise effects invokedthe information overload model mentioned above.Furthermore, these findings further corroborate thegeneral association between increased cognitiveoverload and physiological responses.

It is difficult, however, to extrapolate from theselaboratory studies to occupational situations involv-ing long-term exposure to ambient noise. Most of thestudies cited were conducted on small groups ofparticipants, and the experimental manipulations typ-ically lasted less than 0.5 hr. To our knowledge,besides one (not well described) Russian study (citedin Welch, 1979), no other field studies, either longi-tudinal or cross-sectional, have examined the effectof chronic exposure to occupational noise on physi-ological outcomes among employees with cogni-tively demanding versus nondemanding jobs. Thus, itremains unknown whether chronic noise exposurewould have a negative effect on the cardiovascularsystem of employees, particularly those holding com-plex (cognitively demanding) jobs.

We hypothesized that chronic exposure to ambientnoise would interact with job complexity to affectblood pressure levels over time. We expected thatincreased blood pressure would occur primarilyamong workers performing complex jobs under highambient noise exposure.

In addition, we tested the hypothesis, also derivedfrom the information overload model, that the com-bination of high ambient noise exposure and high jobcomplexity would also have a negative effect on jobsatisfaction over time. We focused on job satisfactionbecause it is conceived to be a job-related affect.Previous research has shown that the proportion ofvariance in this variable that is explained by adversejob characteristics is much higher than that explainedfor more general affects such as anxiety, depression,or irritation (French, Caplan, & Harrison, 1982). Jobsatisfaction was found to be negatively associatedwith occupational noise exposure in several cross-sectional studies (Melamed, Luz, & Green, 1992;Verbeek, van Dijk, & de Vries, 1986). In line withthis reasoning, we hypothesized that exposure tonoise would mainly affect the job satisfaction ofthose performing complex jobs. No study has exam-ined the long-term interactive effect of noise expo-sure and job complexity on this outcome. We tested

184 MELAMED, FRIED, AND FROOM

the two hypotheses in a longitudinal study of indus-trial employees, followed up between 2 and 4 years.

The present study was designed to overcome someof the methodological deficiencies mentioned earlier.Its particular strength, besides its longitudinal design,was in focusing on workers who were likely to havefairly stable work environment conditions throughoutthe follow-up period. These were workers who re-mained at the same work station during the wholestudy period (see Method section). This best controlsfor the possible confounding effect of third variablesand permits a claim of causal effect. According toZapf, Dormann, and Frese (1996, p. 148), for longi-tudinal research the stability of third variables overtime is crucial. Of particular importance here was ourconfirmation of the stability of noise exposure at theindividual level over time (see Method section),which ensures chronicity of the noise exposure.

Method

Study Population

The study participants were 1,831 workers, ages 20-60years, who participated in the two waves of the CORDIS(Cardiovascular Occupational Risk Factors Determinationin Israel) follow-up study (see Green & Harari, 1995),conducted in 21 industrial plants 2—4 years apart (M = 2.6years). A detailed description of the types of plants thatwere sampled is presented elsewhere (Melamed et al.,1992). Excluded from this sample were 42 workers withchronic diseases (diabetes, myocardial infarction, anginapectoris, and stroke) that might affect blood pressure levelsand other cardiovascular endpoints. Of these workers, 282had missing values on one or more of the study variables.Thus, the sample was reduced to 1,507 workers distributedacross 161 work stations. Work station was defined as agroup of workers employed in similar physical work andenvironmental conditions (e.g., control room operators, of-fice workers, or workers employed in a given work process).Of these, 700 changed their work station during the fol-low-up period. Because by doing so, they are likely to havealso changed their noise exposure levels and other work andenvironmental conditions, they were not included in thestudy sample. Thus, the final sample consisted of 807 work-ers (451 men and 356 women) who remained in the samework station throughout the follow-up period. Their meanage was 44.00 years (range = 22—62 years), their meantenure was 9.97 years (range = 0-36 years), and their meanlevel of education was 10.50 years (range = 4-15 years).Sixty-seven percent were blue-collar and 33% were white-collar workers.

Measures

Noise exposure level. Multiple noise measurementswere taken. At Time 1 (Tl), ambient noise levels at eachwork station were measured using a Quest sound level

meter Type SL-215 (area sampling; Quest Electronics,Oconomovoc, WI), tripod-mounted and adjusted to a heightof 150 cm from the floor. Noise levels were sampled twicea day (morning and afternoon) in winter and in summer.Each sampling period lasted 0.5 hr, during which 5 to 10readings were taken (depending on noise fluctuations). Re-sults were noted in dB(A) and were averaged for eachworker across four sampling periods. The average intercor-relation between noise levels in the four sampling periods atTl was >.90. Noise exposure level was defined by thegeometric mean exposure across the four samplings. AtTime 2 (T2), 2-4 years later, we returned to 115 workstations and again measured the ambient noise level. Noiseexposure levels were measured during 1 day in summer andin winter, using a Quest M-27 noise-logging dosimeter. Thecorrelation between the noise levels sampled twice duringT2 was .89. Results were noted in Leq and were averagedfor each worker for the two sampling periods at T2.

Stability of exposure levels over time. The noise expo-sure level was found to be highly stable; the correlationbetween noise levels measured twice (2 to 4 years apart) atthe same work stations was .86. Therefore, in all analyseswe used the noise levels measured at Tl.

Ambient temperature. Hourly outdoor dry temperaturereadings (°C) for each day of the year for the regions of thestudy were obtained from the National Meteorological In-stitute, Beit Dagan, Israel.

Job complexity. Job complexity was assessed by aver-aging an expert's ratings of two items. The first item, taskcomplexity, provided an overall assessment of the number ofelements, decisions, skill level, independence, and sophis-tication of the employee's job. Rating ranged from 1, rep-resenting a very simple job, to 4, representing a very com-plex job. The second item, task variety, assessed thediversity of tasks in a given job. Ratings on this item alsoranged from 1, representing no diversity, to 4, representinghigh diversity. These items, which correlated .87, were partof the job analysis conducted on the 480 jobs held by theemployees in the 21 plants sampled. Other work character-istics included in the job analysis were type of work (repet-itive work or work underload), pay system, type of service/production processes, and other general characteristics (e.g.,rotation or team work). Job analyses were performed by anexperienced rater who observed workers in the same jobsfor 1 day. The reliability of the ratings was evaluated in apilot study that focused on 48 jobs in two plants from twodifferent industries. Ratings were made by three indepen-dent raters who observed workers in the same job on 2separate days. Interrater agreement assessed by kappa sta-tistic (J. Cohen, 1977) had a median value of .91.

Inspection of the job complexity scores revealed a bi-modal distribution with two distinct clusters of high and lowscores. On the basis of this finding and given that the studyhypotheses were specifically formulated in terms of low andhigh job complexity, we dichotomized job complexity intolow and high on the basis of median split of the scoredistribution (scores 2-4 and 5-8, respectively).

Physical examination. Workers were examined in anonfasting state between 7:00 a.m. and 4:00 p.m. in a quiet,air-conditioned room at the factory site. Blood pressure wasmeasured three times following a 5-min rest using a stan-dard mercury sphygmomanometer (Baummanometer), thecuff of which was placed on the workers' right arm. Systolicblood pressure corresponded to the first Korotkoff sound


and diastolic blood pressure to the fifth. The participant wassupine during the first measurement and sitting upright forthe next two measurements. The average of the second andthird measurements was used in the analysis. This measure-ment procedure should produce a valid assessment of bloodpressure (see, e.g., Fried, 1988; Fried, Rowland, & Ferris,1984).

Job satisfaction. Job satisfaction was measured by theSatisfaction With Work subscale of the Job DescriptionIndex (JDI; P. C. Smith, Kendall, & Hulin, 1969). Thissubscale had the highest correlation with other measures ofwell-being (Meir & Melamed, 1986) and with withdrawalbehavior (Muchinsky, 1977). The scale consisted of 18items, with a response scale of yes = 3, ? = 1, or no = 0.Two hundred forty-one workers did not complete the JDI atTl, mainly because of language difficulties or because theywere absent at the time of administration. An additional 221workers did not complete the JDI at T2, because of specificrequests of some factories to shorten the questionnaire bat-tery. In these factories, only the medical questionnaireswere administrated.

Confounding variables. The major potential confound-ing variables are age, sex, body mass index (weight inkilograms/[height in meters]2), and a family history of hy-pertension, which is known to be associated with increasedrisk for hypertension (Schwartz et al., 1996). Other possibleconfounding variables included tenure at the department,which might reflect history of exposure to environmentaland job stress but also acquired coping strategies (Zapf etal., 1996); use of hearing protection devices (HPDs) toattenuate noise exposure; and ambient temperature (Kristal-Boneh, Harari, Green, & Ribak, 1995). These variableswere controlled for in the subsequent tests of the linkbetween noise exposure, job complexity, and blood pressureelevation over time. Finally, an additional potent confound-ing variable is the presence of workers in white-collar andblue-collar jobs in our study sample. White- and blue-collarworkers might differ not only in the complexity of their jobsbut also in the exposure to noise and to other adverse workand environmental conditions (as indicated in recent anal-ysis of CORDIS data; see Melamed, Yekutieli, Froom,Kristal-Boneh, & Ribak, 1999). Thus, we also controlled forthis variable in the data analysis. Detailed descriptions ofwhite-collar and blue-collar jobs have been presented else-where (Melamed, Ben-Avi, Luz, & Green, 1995; Melamedet al., 1992; Melamed et al., 1999).

Results

The intercorrelations among the key study vari-ables are presented in Table 1. The main finding hereis a significant association between the predictor vari-ables and the outcomes. Noise exposure levels cor-related positively with systolic blood pressure levelsat T2 and negatively with job satisfaction at Tl andT2. Job complexity correlated positively with jobsatisfaction at Tl and T2. Another noteworthy find-ing is the negative correlation between noise and jobcomplexity. This suggests that those employed innoisy environments tend to also have more simplejobs. Furthermore, as expected, the white/blue-collar

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Table 2Moderated Multiple Regressions of Blood Pressure (BP) Percentage Change [(Time 2 — Time 1) *100/Time 1] on Time 1 Blood Pressure Value, Control Variables, Noise Exposure Level, and JobComplexity (N = 787)

Systolic BP change

Step and variable

Step 1: ControlsTime 1 BP (mmHg)Age (years)GenderBody mass index (kg/m2)HPD use (yes/no)Family history of hypertensionAmbient temperature (°C)Job tenure (years)White/blue collar

Step 2: Main effectsNoise [dB(A)]Job complexity (low/high)

Step 3: InteractionsNoise X Job Complexity

B

-0.28*0.21*0.910.34*1.410.17

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1.40

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SEB

0.020.040.720.761.160.710.340.050.75

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Diastolic BP change

\K B

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0.12*-1.11

0.50*-1.61

0.92-1.39*-0.04

1.43.00

0.04-0.44

.01*0.19*

SEB

0.040.040.820.081.320.810.400.050.86

0.040.83

0.07

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0.11-0.05

0.190.040.04

-0.13-0.03

0.06.00

-0.04-0.02

.01*0.57

Note. For systolic blood pressure change, final model F(\2, 774) = 17.96, p < .001, total R2 = .20, adjusted R2 = .19.For diastolic blood pressure change, final model F(12, 775) = 21.78, p < .001, R2 = .25, adjusted R2 = .24. B indicatesunstandardized regression coefficients; /3 indicates standardized regression coefficients. HPD = hearing protection device.*p < .05.

variable correlated positively with both the predictorand the outcome variables. On the one hand, it cor-related negatively with job complexity and positivelywith noise exposure levels. On the other hand, itcorrelated positively with systolic blood pressure atT2 and negatively with job satisfaction at both Tland T2. Thus, this variable may be a possible con-founder in this study. Finally, inspection of the meanscores presented in this table reveals that both sys-tolic and diastolic blood pressure increased by 2mmHg at T2, which is consistent with the expectedincrease in blood pressure with age. Job satisfaction,however, decreased over time.

To directly test the major hypothesis that the in-teraction between chronic noise exposure and jobcomplexity predicts blood pressure change over time,we used percentage change from the baseline becauseit is a more stringent measure from the physiologicalpoint of view. This is because at the start of realhypertension disease, the vessel lumen becomes nar-rowed and a proportionally high blood pressure riseis needed to keep the blood flow constant. Thus,percentage pressure change [(blood pressure Tl -blood pressure T2)/blood pressure Tl] served as anoutcome variable. This hypothesis was tested throughmoderated hierarchical multiple regression models inwhich possible confounding variables were con-

trolled. A review by Aguinis, Peterson, and Pierce(1999) supported the use of moderated multiple re-gression as the method of choice for estimating mod-erating effects in applied psychology. Entered in Step1 were all possible confounding variables: age, gen-der, body mass index, job tenure, family history ofhypertension, HPD use, ambient temperature, andwhite/blue-collar category. Also entered in this stepwas Tl (baseline) blood pressure value. To test themain effect of noise (continuous variable) and jobcomplexity (low/high),1 we entered these variables inStep 2 in addition to all variables in Step 1. Finally,the interactive effect of noise exposure and job com-plexity on blood pressure change was tested in Step3. In this step, the interaction term was entered, alongwith all the variables in the previous step. The resultsof this analysis are presented in Table 2.

The results show no main effect of either noise orjob complexity on systolic or diastolic blood pressurepercentage change (Step 2). However, a significantinteractive effect of noise by job complexity on both

1 We have tried, in a preliminary analysis, to enter jobcomplexity as a continuous variable, but this yielded lessfavorable results, probably because of the true bimodaldistribution of the job complexity scores.


systolic and diastolic measures of blood pressure wasfound even after adjusting for several control vari-ables. Entering this interaction term in Step 3 resultedin a significant, albeit low (1%), increment in R2.Thus, the results supported the first hypothesis. Itshould be added, however, that a small amount ofexplained variance in stressor-outcome relationshipis to be expected in longitudinal studies. For anextensive discussion of this issue, see Zapf et al.(1996).

The interactive effect of noise by job complexityon the adjusted percentage change in systolic anddiastolic blood pressure is presented in Figure 1. Aspredicted, among workers exposed to high noise lev-els, systolic blood pressure increased by a muchhigher percentage (6%) in those with high job com-plexity compared with those with lower job complex-ity (2%). The opposite trend was evident amongworkers exposed to low noise levels. There was nochange in systolic blood pressure for workers withhigh job complexity. However, a relatively large in-crease (4%) was observed in workers with low jobcomplexity.

A somewhat unexpected result was the beneficialeffect of noise on workers with low job complexity.The percentage of increase in systolic blood pressurewas much lower among those exposed to high noiselevels (2%) than those exposed to low noise levels(4%). Possible reasons for this occurrence are dis-cussed later. A similar trend was observed for dia-stolic blood pressure. All results are in the samedirection. However, the beneficial effect of noise forworkers in low complex jobs was even more pro-nounced here (see Figure 1, right).

Moderated hierarchical multiple regression analy-sis, similar to that described above, was used to testthe hypothesis concerning percentage change in jobsatisfaction. Three irrelevant control variables—fam-ily history of hypertension, body mass index, and theambient temperature—were excluded. The results arepresented in Table 3. Significant main effects of jobcomplexity, in the expected direction, were observedeven after controlling for possible confounding vari-ables (Step 2). Also significant was the Noise X JobComplexity interaction (Step 3: incremental R2 of2%). Thus, the second hypothesis was also sup-ported.

The interaction for percentage change (adjustedscores) in job complexity is depicted in Figure 2. Thistime, the main effect of job complexity is clearlyevident. Job satisfaction increased over time amongworkers with high job complexity. However, jobsatisfaction decreased over time in workers with low

job complexity. The increase in job satisfaction in theformer group was much lower (3%) among the sub-group of workers exposed to high noise levels com-pared with workers exposed to low noise levels (9%).A large reduction in job satisfaction (-34%) wasobserved among workers with low complexity jobswho were exposed to low noise levels. A muchsmaller reduction (-13%) was observed among thoseexposed to high noise levels.

The final analysis focused on the prevalence ofelevated blood pressure in the study sample. Elevatedblood pressure was defined as either systolic bloodpressure >140 mmHg or diastolic blood pressure£90 mmHg and/or antihypertension medication use.The purpose of this analysis was to test whether theinteraction of noise exposure levels (low/high) andjob complexity can predict the prevalence2 of ele-vated blood pressure. A cutoff point of 80 dB(A) wasused to dichotomize noise exposure levels into highand low. The selection of this cutoff point was basedon previous findings that this was the threshold fordetecting the effect of noise on blood pressure levels(e.g., Fogari, Zoppi, Vanasia, Marasi, & Villa, 1994).The effect of the interaction between noise exposureand job complexity on risk for elevated blood pres-sure was tested through logistic regression analysisthat controlled for the same possible confoundersmentioned earlier. The results are presented in Table4. Noise exposure level was found to interact with jobcomplexity in predicting risk for elevated blood pres-sure (odds ratio [OR] = 2.66, 95% confidence inter-val [CI] = 1.11-6.35).

To understand the meaning of this interaction, weexamined the percent prevalence of elevated bloodpressure in four groups of workers defined by noiseexposure levels and job complexity. The results, pre-sented in Table 5, were consistent with the trendobserved for the blood pressure percentage changesshown in Figure 1. The highest prevalence of ele-vated blood pressure was observed among workers incomplex jobs who were exposed to high noise levels.Workers exposed to high noise levels but performingsimple jobs had a lower prevalence of elevated bloodpressure. The reverse was observed among workersexposed to low ambient noise. Among these workers,

2 In a preliminary analysis, we examined whether thisinteraction would predict the incidence (new cases) of ele-vated blood pressure during the follow-up period. However,the small number of new cases (n = 65) during a follow-upperiod of 2-4 years did not provide enough statistical powerto test the above possibility.


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Table 3Moderated Multiple Regression of Job Satisfaction Percentage Change [{Time 2— Time 1) * lOOfTime 1] on Control Variables, Noise Exposure Levels,and Job Complexity (N = 246,)

Step and variable

Step 1: ControlsTime 1 job satisfactionAge (years)GenderHPD use (yes/no)Job tenure (years)White/blue collar

Step 2: Main effectsNoise, in dB(A)Job complexity (low/high)

Step 3: InteractionNoise X Job Complexity

B

-2.26*-0.11-9.83*-2.59

0.50-20.60*

-0.0422.72*

-1.30*

Job satisfaction

SEB

0.260.295.508.850.395.20

0.326.23

0.63

change

P

-.50-.02-.11-.02

.09-.23

-.01.25

-0.96

A*2

.25*

.04*

.02*

Note. Final model F(9, 236) = 13.87, p < .001, total R2 = .31, adjusted R2 = .30. Bindicates unadjusted regression coefficients; /3 indicates standardized regression coefficients.HPD = hearing protection device.*p< .05.

the lowest prevalence of elevated blood pressure wasobserved in those having complex jobs.

Discussion

To our knowledge, this is one of the few longitu-dinal studies on the effect of chronic exposure toindustrial noise on blood pressure levels. This is alsothe only study that examined in a natural field settingthe interactive effect of ambient noise and job com-plexity on changes in blood pressure and job satis-faction. Regression analysis results revealed that afterseveral potent confounding variables were controlledfor, neither noise exposure levels nor job complexitywas associated with blood pressure change over time.This finding concerning noise replicates the negativeresults obtained in most retrospective longitudinalstudies (e.g., Hessel & Sluis-Cremer, 1994; Hirai etal., 1991). Yet, there are a few retrospective longitu-dinal studies with positive findings (e.g., Deyanov,Mincheva, Hadjiolova, & Ivanovich, 1995; Talbott,Gibson, Burks, Engberg, & McHugh, 1999). To ourknowledge, there are no field studies of the long-termeffect of job complexity on blood pressure levels;hence we cannot tell whether our finding concerningjob complexity can be generalized. Nevertheless, theresults of this controlled study suggest that noiseexposure levels or job complexity alone are poorpredictors of blood pressure change over time.

However, as hypothesized, the complexity of theworkers' jobs turned out to have a significant mod-erating effect on the association between chronicnoise and blood pressure. The results show a signif-icant interactive effect of noise exposure levels andjob complexity on both systolic and diastolic bloodpressure changes over time. This significant interac-tive effect was evident even after controlling for ninepossible confounding variables: baseline systolicblood pressure values, age, sex, body mass index,tenure, family history of hypertension, HPD use, theambient temperature, and white/blue-collar category.As mentioned previously, our recent analysis of theCORDIS data has shown that compared with white-collar workers, blue-collar workers are exposed to awider range and magnitude of adverse work andenvironmental conditions, namely, safety hazards,overcrowding, cognitive and physical demands, andenvironmental stressors (Melamed et al., 1999).Thus, the fact that the results remained significanteven after controlling for white/blue-collar categoryfurther reinforces the significance of our findings.

Plotting these interactions revealed that amongworkers exposed to high ambient noise levels, athreefold adjusted increase in systolic blood pressurewas observed in those performing complex jobs com-pared with those performing simple jobs. A corre-sponding twofold increase was observed for the ad-justed percentage changes in diastolic Mood pressure.


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-20

-30

-40

High JobComplexity

Low JobComplexity

LowNoise Exposure Level

High

Figure 2. The interaction between noise exposure levels and job complexity in the predic-tion of percentage change in job satisfaction (after adjusting for several possible confoundingvariables).

Thus, the present work showed for the first time in acontrolled field study that the adverse interactiveeffect of noise exposure and task complexity onphysiological outcomes, observed in laboratory stud-ies (see introduction), generalizes to the work envi-ronment. This finding may partly explain the reasonfor the inconsistent results of previous studies on theeffect of chronic noise exposure on blood pressurelevels. As mentioned earlier, because these studiesfailed to consider the type of jobs the exposed work-ers were performing, the degree of job complexitymay have influenced the results. Further follow-upstudies are needed to confirm the findings of thepresent study and to determine whether the adverseeffects of noise on the cardiovascular system will bemore pronounced in workers performing cognitivelydemanding jobs.

At the same time, the present findings also showedthe existence of a beneficial effect of job complexityin blood pressure change in workers exposed to lowlevels of ambient noise. There was a minor adjusted

change in systolic and diastolic blood pressureamong workers with high job complexity but about athreefold increase in the percentage change in bothsystolic and diastolic blood pressure in workers withlow job complexity. Complementary results wereobserved when we examined the prevalence of ele-vated blood pressure in the worker sample. Logisticregression results indicated that the interaction ofnoise exposure levels (high/low) and job complexity(high/low) was associated with increased risk forelevated blood pressure (adjusted OR = 2.66, 95%CI = 1.11-6.15), even after controlling for severalpossible confounding variables. The highest preva-lence of elevated blood pressure was observed amongworkers in complex jobs exposed to high ambientnoise (31%). This compares with the prevalence of22% in workers in noncomplex jobs. Among workersexposed to low noise levels, however, those em-ployed in complex jobs had the lowest prevalence ofelevated blood pressure (20%), whereas among thosewith simple jobs the prevalence was 23%.


Table 4Logistic Regression for Predicting Blood Pressure Elevation by Noise ExposureLevel and Job Complexity and Their Interaction

Variable

Noise (low/high)Job complexity (low/high)Noise X Job ComplexityAge (years)GenderBody mass index (kg/m2)HPD use (yes/no)Ambient temperature (°C)White/blue collarFamily history of hypertension

Odds ratio

0.220.312.661.090.851.142.130.831.071.40

95% CI

0.05-0.820.09-1.061.11-6.351.07-1.110.55-1.321.09-1.191.11 .020.67-1.020.65-1.750.93-2.08

P.025.061.027.0001.48.0001.02.089.78.09

Note. CI = confidence interval; HPD = hearing protection device.

Taken together, the findings lead to two conclu-sions. First, exposure to occupational noise has agreater effect on changes in blood pressure over timeamong those performing complex jobs. These work-ers also showed the highest prevalence of elevatedblood pressure. Second, job complexity, in contrast,had a clear beneficial effect for workers exposed tolow noise levels. This was manifested in no change ofsystolic blood pressure and in a small percentagechange in diastolic blood pressure over time (whichlikely reflected the typical rise of blood pressure withage) and in the lowest prevalence of elevated bloodpressure.

This latter finding is rather novel. Job complexityis considered by industrial/organizational psycholo-gists to be a positive job characteristic. Higher jobcomplexity is associated with greater job challengeand stimulation, and it is typically expected to affectemployees' psychological well-being and motivation(e.g., Fried & Ferris, 1987; Hackman & Oldham,1976). Previous studies have demonstrated the ben-eficial effect of this job characteristic on attitudinaland behavioral outcomes, such as job performance

Table 5Percentage Prevalence of Elevated Blood PressureAmong Workers Classified by Noise ExposureLevels and Job Complexity

Low noiseexposure

Job complexity

LowHigh

N

246337

%

22.819.6

High noiseexposure

N

12085

%

21.730.6

and productivity, creativity, and intention to leave(e.g., Fried & Ferris, 1987; Oldham & Cummings,1996; Oldham, Kulik, Ambrose, Stepina, & Brand,1986; Sparrow & Davies, 1988). The present findingsshow for the first time that among those with favor-able environmental conditions, such as low ambientnoise levels, job complexity may be a protectivefactor associated with reduced risk for cardiovasculardisease.

These findings are particularly revealing becauseof the general failure of prior studies to demonstratea clear association between work stress and healthindicators (e.g., Briner & Reynolds, 1999; S. Cohen& Williamson, 1992; Lazarus & Folkman, 1984;Pollock, 1988). Several researchers have pointed outthat this failure is due to the profound methodologicalshortcomings of studies in the area of organizationalstress, particularly the reliance on cross-sectional de-signs and self-report data (e.g., Briner & Reynolds,1999; Frese & Zapf, 1988; Jex & Beehr, 1991). Thepresent study overcomes these methodological weak-nesses and thus contributes to the current literature.

Other important findings of this study are con-cerned with the attitudinal outcome of job satisfac-tion. Noise exposure was found to negatively corre-late with job satisfaction at both Tl and T2. This isconsistent with the findings of other studies (Mel-amed et al., 1992; Verbeek et al., 1986). Job com-plexity, as expected, was positively correlated withthis outcome as found in other studies (Ganzach,1998; Hackman & Oldham, 1976). Plotting the inter-action of noise exposure by job complexity on jobsatisfaction change over time revealed that exposureto high noise levels offsets the positive effects of jobcomplexity on job satisfaction. This finding is con-


gruent with the trend observed for blood pressurechange, namely, higher elevation of both systolic anddiastolic blood pressure, compared with those ex-posed to low noise levels. However, among workersexposed to low noise levels, those with complex jobsnot only showed increased job satisfaction over timebut also had minor changes in blood pressure at T2.Those with simple jobs manifested a decrease in jobsatisfaction over time and had higher percentagechange in blood pressure. This similarity in findingsfor the psychological and physiological outcomes isimportant, as it has not often been found in otherstudies (Frese & Zapf, 1988; Fried, 1988; Kasl,1996). It can serve as mutual validation of bothoutcomes.

Integration of all the findings suggests that theanticipated positive role of job complexity, suggestedby organizational behavior and organizational psy-chology scholars, is manifested only under favorableenvironmental conditions, such as low ambient noise.One other study making a similar suggestion wasconducted by Oldham, Kulik, and Stepina (1991).This study showed that the combination of job com-plexity and overcrowding was associated with re-duced job satisfaction. Additional studies are neededto determine whether the present findings can bereplicated and extended to other negative environ-mental conditions, such as high ambient temperatureor bad lighting. At the same time, the findings heresupport the assertion that performance of complexjobs under high ambient noise levels may imposehigh attentional demands and may be stressful(Baron, 1994; S. Cohen et al., 1986; Kryter, 1994).The stressfulness of such a combination was mani-fested here by less improvement of job satisfactionover time, increased blood pressure levels, and higherprevalence of elevated blood pressure beyond thatattributable to increased age. Further research isneeded to cross-validate this finding and to determineif it generalizes to other stress indicators, both be-havioral (e.g., impaired performance and high ab-sence rate) and physiological (e.g., elevated levels ofstress hormones, increased ambulatory blood pres-sure levels, and reduced heart rate variability).

Yet another important finding of this study is thatthe effects of noise exposure on employee physiolog-ical and attitudinal outcomes were obtained at mod-erate noise exposure levels. In our sample, 30% wereexposed to noise levels &80 dB(A). Further inspec-tion of the data revealed that of these, only 46% wereexposed to noise levels s85 dB(A). Thus, our find-ings are consistent with those of others (e.g., Fogariet al., 1994) in indicating that the adverse effects of

noise on employees can be observed at levels lowerthan those [S85 dB(A)] considered to be harmfulaccording to the noise regulations.

A somewhat unexpected finding here for workersin simple jobs was the beneficial effect of beingexposed to moderate levels of ambient noise. Com-pared with their counterparts who were exposed tolow ambient noise, they showed much lower bloodpressure change over time (in particular diastolicblood pressure) and considerably less reduction injob satisfaction. One possible explanation for thebenefits of noise for low complexity jobs, whichoften may be monotonous and boring, is the arousaltheory (Broadbent, 1971; Kryter, 1994; Loeb, 1986).Exposure to moderate noise levels may be arousingand offset the understimulation associated with theboredom and monotony likely to be experienced insimple jobs. We should emphasize, however, thatmost of the beneficial effects of noise were obtainedin laboratory conditions and focused on task perfor-mance. Positive effects were obtained either with"white" (broadband random) noise or music. Thebeneficial effect of moderate industrial noise expo-sure observed here with physiological and attitudinaloutcomes is rather novel, and it is unclear whether itcan be accounted for by the arousal theory. Anotherviable explanation for the above finding is self-selec-tion of jobs. Those in simple jobs who selected towork in noisy environments may have been healthierand more resilient to stressfulness of simple jobs.However, this self-selection cannot be explained interms of the control variables examined here (such asinitial Tl blood pressure values, family history ofhypertension, body mass index, blue vs. white collar,etc.). The above results were obtained after control-ling for all these possible confounders. Thus, if self-selection was operating here, it may be manifested invariables other than those examined by us. At anyrate, the above finding is certainly interesting anddeserves further exploration and validation in futurestudies.

The strength of this study is in its longitudinaldesign, in the examination of workers who remainedin the same work station throughout the follow-upperiod, and in the use of objective measures of noiseexposure levels, job complexity, and blood pressure.The only subjective measure was job satisfaction. Wetherefore have minimized cognitive biases (for elab-oration, see Frese & Zapf, 1988). However, it isappropriate to note some limitations of our study.First, the assessment of noise exposure could havebeen improved if we had used personal dosimeters atTl as we did at T2 and sampled the exposure to noise


four times a year rather than twice. Second, it wouldhave been desirable to record job changes, if therewere any, to assess changes in job complexity. Thiswould have allowed us to obtain more precise results.Third, our follow-up period was too short to have asufficient number of new cases of elevated bloodpressure to be able to test if our predictor variablesand their combination would predict incidence of theabove endpoint. Finally, because we obtained jobsatisfaction data for only a third of the workers, wedo not know if our results can be generalized to theentire sample.

In conclusion, despite the limitations noted above,this field study contributes to the literature in severalways. It highlights the significance of taking intoaccount the complexity of the jobs performed whenstudying the effect of chronic noise exposure onemployees' outcomes. It demonstrates that job com-plexity may be beneficial or detrimental to workers'well-being, depending on the conjunction of favor-able versus unfavorable environmental conditions. Itshows that, given favorable environmental condi-tions, the beneficial effects of job complexity mayextend to health outcomes. Finally, the findings sug-gest that workers in simple jobs may benefit fromexposure to moderate noise levels.

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the interactiv effece otf chronic exposur to noise e and ...simple jobs (i.e., jobs of low...

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