Paper 117 - Produtronica : : PUCPR

Third International Conference on Production Research – 

Americas’ Region 2006 (ICPR-AM06) 

IFPR – ABEPRO - PUCPR - PPGEPS 

IMPLICATIONS OF THE ENVIRONMENTAL COMFORT 

CONDITIONS, AGE AND TOTAL CUMULATIVE WORKING TIME 

OVER THE WORK ABILITY OF URBAN BUS DRIVERS OF JOÃO 

PESSOA-PB 

Fernanda Diniz de Sá 

Master Program in process. Production Engineering Master Program, Federal 

University of Paraiba (UFPB) - fedinizsa@yahoo.com.br 

Francisco Soares Másculo 

Teacher. Production Engineering Master Program, Federal University of Paraiba 

(UFPB) - masculo@.ct.ufpb.br 

Luiz Bueno da Silva 

Teacher. Production Engineering Master Program, Federal University of Paraiba 

Abstract: 

(UFPB) - bueno@ct.ufpb.br 

Anad Subramanian 

Graduation. Production Engineering, Federal University of Paraiba (UFPB) 

The relationship between work ability and the variables self-perception about thermal 

and noise discomfort environmental, age and total cumulative working time was 

examined in 60 urban bus drivers in the city of João Pessoa, Paraíba State, Brazil. The 

Work Ability Index (WAI), elaborated by Finland’s Institute of Occupational Health 

(FIOSH), assessed the work ability that it considers the physical and mental demands 

of the work, the health condition and individual capacities. Drivers completed a 

questionnaire assessing their self-perception about thermal and noise discomfort 

environmental. A dosimeter and the index WBGT (Wet Bulb Globe Temperature) were 

used to evaluate the thermal and noise environmental conditions inside the buses, 

according to Brazilian norms. The variables involved in this research were: Y - Work 

Ability Index (WAI) and X - Age (I), Cumulative working time (Cwt), Thermal perception 

(Tp) and Noise perception (Np). In the statistical analysis were used χ 2 and Wald tests




(α=0,05) to evaluate the relationship between Y and X and the consistence of your 

parameters. The variable Y was transformed in variable " dummy " for the analysis of 

logistic regression. A dead line was stipulated for Y among WAI good or great, Y = 1 

(WAI>36), and WAI low or moderate (WAI ≤ 36). The analyses revealed strong 

significant associations of the variable age on WAI, classifying it correctly around 78%. 

The work ability for drivers above 40 years old was considered low-moderate, and 

higher self-perception discomfort to the thermal and noise environmental inside the 

buses. The levels of noise and thermal are above of the established by Brazilian 

legislation for salubrious activities, fact that may compromise the drivers’ performance. 

The findings had demonstrated that the process of aging and the environmental 

discomfort self-reported have been determinative in the reduction of the work ability. 

Keywords: Work ability, Noise, Thermal, Age, Bus drivers. 

1 Introduction 

The evaluation of a human being who is in a work context is pertinent to ergonomics, as 

it contains the knowledge about men’s work performance, to apply it to the conception 

of work environment, tasks, tools, machines and production systems (Laville, 1977). In 

other words, it relates to the work adapted to physical and psychological characteristics 

of the human beings, using efficiency and health criterion (Daniellou, 1991). 

Traditionally, the studies involving a worker population search the reasonable 

associations between pathologies and probable risks factors (Cordeiro, 1991). In this 

way, it is notable the production of essays that study associations between the general 

decrease in the workers performance and the occupational exposition to environments 

with high thermal and noise levels. One of the main causes for this interest is 

determined by the characteristics of this exposition like the decrease in the alert state, 

and also the risk of enchaining some other health disturbs for these people (Cordeiro et 

al. (2005); Fleig (2004); Rodrigues and Magalhães (2004); Pimentel-Souza (2000)). 

Recent researches show activities related to transportation as a high risk activity for 

physical and mental health of the worker, due to the occupational exposition factors, 

like noise and thermal (Karazman et al. (2000); Kloimueller et al. (2000); Mello (2000); 

Costa (2003); Fleig (2004)).




For evaluating someone’s performance in work activity, researchers from the Finnish 

Institute of Safety and Occupational Health (FIOSH) developed the Work Ability Index 1 

(Tuomi, 1997). This evaluation has the purpose of supporting the search of ergonomic 

solutions that balance the relation between the work’s demand and the human ability in 

a given context. 

In this way, the objective of this research was to study a fortuitous association between 

the work ability and the variables related to noise-thermal environment perception, age 

and cumulative working time over the urban public bus drivers in João Pessoa – PB. 

2 Methods 

The population was consisted by 60 bus drivers, male, aging between 24 and 57 years 

old, working at least for four years in this function, working for one of the six urban 

public transportation concessionaries in the city of João Pessoa – PB. These companies 

did not allowed their identification, according to the ethic standards for such studies. 

To evaluate the work ability, it was used an auto-applicable questionnaire named Work 

Ability Index (WAI) (Tuomi et al, 1997), used for workers’ health service. It is meant by 

work ability the quality under which a worker is able to do a work. Together with WAI, 

another questionnaire was applied, regarding aspects related to the bus drivers’ 

perception to the thermal and noisy environment, to the work organization, and to the 

population socio-demographic data. 

In a test phase, 20 questionnaires were distributed to bus drivers with at least four 

years of scholarship, chosen in an aleatory way. These questionnaires were not 

included in the data analysis. 

Lately, a non-linear estimating logistic regression, for α=0,05, to verify the association 

between the independent variable (X= age, cumulative working time as urban bus 

driver and perceptions about the thermal and noisy environment) and the depended 

variable (Y= Work Ability Index – WAI) 

For that, the WAI variable was transformed in “dummy” variable for the logistic 

regression analysis. The cutting point was set to the WAI, between the WAI moderate




or good (score >36) and the WAI low or moderate (score =36). 

To elaborate the WAI predictive model, through this estimator, an invariable analysis 

was firstly done, to select the possible predictor variables using the Chi-Square and the 

Wald tests, which evaluate the relation between Y an X and the consistence of the 

parameters model, in that order. 

3 Results 

The sample’s work ability index (WAI) has varied from a 28 minimum score to a 48 as 

maximum score. The WA distributions for age and work time are presented in Chart I. 

CHART 1: Work ability distribution for age and cumulative working time categories. 

Variable Category 

24--| 34 

Age 35--| 44 

45 and more 

Total 

Cumulative 4 ---| 10 

working 11---| 17 

time 18 and more 

Total 

Source: Research data (2006) 

WAI 

Great Good Moderate Low Total 

n° % n° % n° % n° % n° % 

7 11,6 5 8,3 1 1,6 0 0 13 1,6 

7 11,6 3 5 3 5 0 0 13 21,6 

7 11,6 3 5 24 40 0 0 34 56,6 

21 35 11 18,3 28 46,6 0 0 60 100 

14 23,3 7 11,6 3 5 0 0 24 40 

1 1,6 0 0 7 11,6 0 0 8 3,3 

6 10 4 6,6 18 30 0 0 28 6,6 

21 35 11 18,3 28 46,6 0 0 60 100 

The results related to the perception that the bus drivers have about the thermal and 

noisy of their work environment are shown in Chart 2. 

CHART 2: Bus driver perception about the noisy and thermal environment. 

Noise Heat 

Answer % Answer % 

Bad 35 Bad 38,3 

Regular 35 Regular 35 

Good 30 Good 26,6 

Great 0 Great 0 

Total 100 Total 100 

Source: Research data (2006)




The statistic analysis showed that the set of Independent Variables (IVs) – Cumulative 

Working Time (Cwt), Thermal Perception (Tp), Noise Perception (Np) and Age (A) – has 

relation with the Dependent Variable (DV), Work Ability Index (WAI), as observed in 

Table I. This statement is pertinent, as the Chi-square value for the difference between 

the final and the intercept models is highly significant. 

On the other hand, as shown in table 2, the Chi-square values of A, Tp and Np 

significant. The same does not happen with the variable Cwt (sig=0,992>a=0,05). This 

shows a probable relationship between such variables and the WAI. 

TABLE 1: Adjustment model of the data related to the 4 IVs. 

Model 

Intercept 

Only 

Model 

Fitting 

Criteria Likelihood Ratio Tests 

-2 Log 

Likelihood 

80,413 

Chi- 

Square df Sig. 

Final 44,787 35,626 4 ,000 


This affirmation can be confirmed by Wald’s test. Analyzing the consistence of the 

parameters of the logistic regression model, which is presented in Table 3, it is shown 

that only the variable Cwt is not consistent, this means, Sig = 0,992 > 0,05 = α. In 

conclusion, only the A, Tp e Np variables should be in the model, what guides to a re- 

evaluation of the relation between those variables and the WAI.

TABLE 2: Probability test of the relation between each IV and the DV 

Effect 

Model 

Fitting 


-2 Log 

Likelihood 

of Reduced 

Model 

Chi- 


Square Df Sig. 

Intercept 50,928 6,140 1 ,013 

A 55,440 10,653 1 ,001 

Cwt 44,787 ,000 1 ,992 

Tp 49,493 4,706 1 ,030 

Np 50,225 5,438 1 ,020 




However, in spite of the variable Cwt be inconsistent, Table 4 shows that all 

independent variables, together, has classified the WAI variable correctly around 

84,7%, showing that only 15,3% may be related to classification errors, due to other 

variables not evaluated, to the questionnaire elaboration, or even due to the subjective 

perception of each bus driver participant of this research. 

TABLE 3: The significance of the logistic regression model 

WAI 

Intercept 

Age 

Cwt 

Tp 

Np 

B 

-6,117 

,217 

-,001 

-1,027 

-1,011 

Deviation 

2,279 

,077 

,067 

,499 

,461 


Wald 

4,514 

7,874 

,000 

4,233 

4,803 

df 

1 

1 

1 

1 

1 

Sig. 

,034 

,005 

,992 

,040 

,028 

95% Confidence Interval for 

Exp(B) 

Exp(B) Lower Bound Upper Bound 

1,243 

,999 

,358 

,364 

1,068 

,876 

,135 

,147 

1,447 

1,140 

,953 

,899

TABLE 4: Classification of the variable WAI percentages over the four IVs 

Observed Predicted 

0,00 1,00 




Percent 

Correct 

0,00 21 4 84,0% 

1,00 5 29 85,3% 

Overall 

Percentage 


44,1% 55,9% 84,7% 

Being the variable Cwt not consistent, it was taken out of the analysis, and the 

importance of the relation between the A, Tp and Np variables and the dependent 

variable WAI was re-evaluated. Thus, through the Table 5 we can see that the Chi- 

square value (the same as in Table 1) for the difference between the final and intercept 

models is highly significant, because Sig = 0,000

TABLE 6: Probability test of the relation between each IV and the DV 

Effect 

Model 

Fitting 


-2 Log 

Likelihood 

of Reduced 

Model 

Chi- 


Square df Sig. 

Intercept 44,615 6,759 1 ,009 

A 60,538 22,682 1 ,000 

Tp 42,664 4,808 1 ,028 

Np 43,343 5,488 1 ,019 




Wald test affirms the hypothesis that Cumulative Working Time variable (Cwt) is not 

significant for the model. That means, it does not influence the WAI variable. This 

statement can be observed even in Table 7, that highlights the significance of the 

parameters of the A, Tp and Np variables for α = 0,05, as in the Table 8, that shows 

that those variables classified correctly the WAI variable around those 84,7% shown in 

Table 8. This similarity between the results presented in Table 8 and 9 ratify the above 

statement. 

TABLE 7: Significance of the logistic regression model parameters 

WAI 

Intercept 

Age 

Tp 

Np 

B 

-6,111 

,217 

-1,026 

-1,011 

Std. Error 

2,810 

,064 

,494 

,459 


Wald 

4,729 

11,481 

4,306 

4,844 

df 

1 

1 

1 

1 

Sig. 

,030 

,001 

,038 

,028 

95% Confidence Interval for 

Exp(B) 

Exp(B) Lower Bound Lower Bound 

1,242 

,358 

,364 

1,096 

,136 

,148 

1,408 

,945 

,895

TABLE 8: Classification of the WAI variable percentage over the three IVs 


,00 1,00 




Percent 

Correct 

0,00 21 4 84,0% 

1,00 5 29 85,3% 

Overall 

Percentage 


44,1% 55,9% 84,7% 

It was observed in Tables 2, 3, 6 and 7 that among the analyzed independent variables, 

the age (A) is the most significant, what shows a bigger influence in WAI variable. This 

statement can be visualized in the Graphics of the Pictures 1, 2 and 3, and also 

confirmed by its importance over the dependent variable classification, that has 

correctly classified it around 78%, as shown in Table 9. 

TABLE 9: Classification of the WAI percentage over the variable A 


0,00 1,00 

Percent 

Correct 

0,00 20 5 80,0% 

1,00 8 26 76,5% 

Overall 

Percentage 


47,5% 52,5% 78,0% 

It is worth to point out that the older the bus driver is, the worse his classificaion of the 

thermal and noisy environment, showing also a low or moderate work abiity, if 

compared to younger drivers, as shown in the Graphics of Pictures 1 and 2.




Modelo de Regressão Logística 

y=exp(7,64011+(1,03186)*Np+(-0,20897)*A)/(1+exp(7,64011+(1,03186)*Np+(-0,20897)*A) 

Picture 1: Logistic Function 

Modelo de Regressão Logística 

Y=exp(7,36519+(1,04229)*Tp+(-,20244)*A)/1+exp(7,36519+(1,04229)*Pt+(-,20244)*A) 

Picture 2: Logistic Function 

0,8 

0,6 

0,4 

0,2 

0,8 

0,6 

0,4 

0,2

4 Discussion 




According to Carvalho Filho and Papaléo Neto (2000), the thermal-regulation process 

becomes precarious with aging, what harms the efficiency of this mechanism and 

decreases tolerance to heat in elderly people. Like that, the high thermal discomfort 

referred by the older bus drivers can be related to aging process, what can contributes 

to the WA deterioration for those professionals. 

Carvalho Filho and Papaléo Neto (2000) and Kauffman (2001) state that sympathetic 

reflexes of stress, which can be unchained by hearing stimulation like noise, determine 

“escape and fight” systemic reactions in the organism as a whole. Those reactions 

determine the rising of the arterial pressure, cardiac frequency rise, the organism 

energy savings mobilization and an alteration in the alert state. Those are some of the 

stress symptoms. 

When this stimulus does not cause an immediate harm, the organism goes through 

chained adaptations processes and recurrent stress state, what can take the person 

sometimes to a chronic stress state, sometimes to a stronger adaptation. However, with 

the natural decline of the organic functions caused by aging, this humor changes are 

not so supported by the organism (Kauffman, 2001). This determines a fatigue chronic 

state, decreases those people’s tolerance to a noisy environment exposition and can 

contributes for their work ability lost. 

The organic functions deterioration caused by aging, can be another explanation for 

older people to show high levels of discomfort related to noise and heat, and, because 

of that, they have showed spoiled work efficiency. However, as physiological variables 

were not evaluated in this study, those considerations should be deeper analyzed in 

order to get a consistent result about the effects in the environmental perception of 

noise and heat for elderly people. 

The studies done by Bellusci and Fischer (1999) with law court workers, and Boldori 

(2002) with firemen, have found the same relation between WAI and age as the one 

verified in this study. However, they disagree with the result found by Kloimueller et al. 

(2000), who has found a low association between those variables in relation to urban 

bus drivers.




The relation between those variables can be explained as a result of the natural aging 

process, fact that confirms that the WAI is not satisfactory all life long, and that is why it 

is necessary lengthwise studies with frequent workers’ evaluation. 

A significant association between the WAI and cumulative working time was not found 

in this study, confirming the ones of Bellusci and Fischer (1999) and Metzner and 

Fischer (2001) that have found a relationship between them. 

In such a way, age and discomfort related to noise and heat are associated to the loss 

in WA for the urban bus drivers of the population. 

5 Conclusion 

This analysis has shown that elderly people present a larger probability of having a 

moerate or low WAI, expressing the possibility that in old ages, people suffer a work 

ability loss. And also that, the worse the discomfort feeling about noise and heat is, the 

bigger is the bus drivers’ probability of presenting a low or moderate work ability. 

For that, the biggest probability of a bus driver to show a low or moderate WAI was 

presented by the elderly ones, that has presented bigger discomfort about the noise 

and heat variables. The cumulative working time did not show a relation with the work 

ability. Those statements can be explained by the physical changes during aging 

process, which decrease the individual tolerance to the exposition to those environment 

stressors. 

The elderly people’s low tolerance to stress reactions caused by the noise and the 

deterioration of the thermal regulation mechanisms, can be the explanation for elderly 

people having high discomfort levels related to noise and heat, and also low work ability 

levels. 

However, in spite of those signs, physiologic variables were not evaluated in this 

research, what is a limitation. So, an investigation of these variables should be made, in 

order to get consistent results about the thermal and noisy environment perception for 

aging people.

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