Traffic air pollution effects on lung function: a study in outdoor workers with

personal monitors in São Paulo, Brazil

Authors

Ubiratan Paula Santos¹

Maria Lucia Siqueira Bueno Garcia2

Alfésio Luís Ferreira Braga3,4

Paulo Afonso de André5

Claudia Sayuri Furukawa Oshiro2

Diogo Kogiso2

Beatriz Mangueira Saraiva-Romanholo2

Carmen D. Saldiva de André5,6

Julio M. Singer6

Paulo Hilário Nascimento Saldiva5

Affiliation

¹ MD, PhD, Pulmonary Division of Heart Institute (InCor) do Hospital das clínicas da

Faculdade de Medicina da Universidade de São Paulo, Brazil

2Laboratory of Experimental Therapeutics, Faculdade de Medicina da Universidade de

São Paulo, Brazil

3Environmental Epidemiology Study Group, Laboratory of Experimental Air Pollution,

Faculdade de Medicina da Universidade de São Paulo, Brazil

4Environmental Exposure and Risk Assessment Group, Collective Health Post-

graduation Program, Catholic University of Santos, Brazil

5 Laboratory of Experimental Air Pollution, Department of Pathology, Faculdade de

Medicina da Universidade de São Paulo, Brazil

6 Institute of Mathmatics and Statistics, Universidade de São Paulo, Brazil.

Running title : Traffic Air Pollution and Lung Function

Funding: Tecnology Science Ministry National Council of Tecnological and Scientific

Development,(MCTI-CNPq, Edital 18/2006)

Corresponding Author: Ubiratan de Paula Santos

Divisão de Pneumologia do Instituto do Coração (InCor)-HCFMUSP

Av Dr Eneas de Carvalho Aguiar 44, 5 andar, São Paulo, Brazil

Cep: 05403-000

e-mail: pneubiratan@incor.usp.br

All authors declare there are no competing interests

2

Abstract

Background: chronic effects of outdoor air pollution on lung function in adults are still

controversial, although some studies suggest a significant association. Objective:

evaluate the chronic effect of exposure to different levels of traffic-generated PM2.5 on

the lung function of outdoor workers in São Paulo, Brazil. Methods: in order to explore

the effects of a wider range of exposures, three categories of workers were considered:

taxi drivers and traffic controllers, expected to have a greater exposure, and Forest

Institute rangers with an expected lower level of exposure. One hundred and one

participants fulfilled the inclusion criteria. In an initial evaluation, anthropometric and

clinical variables, asthma symptoms prevalence and the intake of fruits and vegetables

per day were assessed. Participants were then scheduled to attend four visits (once a

week for one month) in which they received a 24-hour personal PM2.5 sampler and have

lung function tests, exhaled nitric oxide and exhaled CO measured in the following day.

The volunteers were classified into three exposure groups according the tertiles of all

individual measurements of PM2.5. The association between the spirometry variables

and exposure was assessed by means of multiple robust regression models adjusted for

age, waist circumference, time in job, daily work hours, diabetes or hypertension,

environmental tobacco smoke, former smoking habits and number of fruit and vegetable

servings per day. Results: workers with the highest level of exposure (> 39.6 g/m3)

presented reductions on predicted FVC (-12.2%), FEV1 (9.1%), and increase in FEF25-

75/FVC (14.9%) without changes in FVC/FEV1 when compared to the lowest exposed

group (< 25 g/m3). Conclusions: chronic exposure to vehicular traffic air pollution is

associated with restrictive ventilatory effects.

3

Introduction

Ambient air pollution has been linked to adverse health effects, especially on the

cardiovascular and respiratory systems, with important impact on morbidity and

mortality. A recent report (Lim et al. 2012) estimated that exposure to particulate matter

(PM2.5) led to 3.2 million deaths in 2010. More recently the World Health Organization

(World Health Organization 2014) ascribed 3.7 million deaths (6.7% of the total global

deaths) to environmental pollution in 2012, with 40% attributed to cardiovascular

diseases, 11% to chronic obstructive pulmonary diseases (COPD), 6% to lung cancer,

and 3% to lower respiratory tract infections in children.

In most cities, vehicular emissions represent the main source of atmospheric pollutants.

Studies in different countries have revealed that both short and long-term exposure to

traffic pollution are associated with increased morbidity and mortality from

cardiopulmonary diseases (Brunekreef et al. 2009; Romieu et al. 2012).

Chronic respiratory effects of air pollution have been associated to impairment of lung

development in children and adolescents (Gauderman et al. 2004; Gauderman et al.

2007) and to increased incidence of asthma (McConnell et al. 2006). In adults, several

studies (Andersen et al. 2011, Götschi et al. 2008, Kan et al. 2007) have evidenced lung

function decline associated with chronic exposure, and suggested that the reduction in

air pollution may improve lung function (Boogaard et al. 2013) or attenuate its decline

with age (Downs et al. 2007). However, chronic effects of outdoor air pollution on lung

function in adults is still controversial, although some studies suggest an effect even at

low levels of pollutants (Adam et al. 2015; Schikowski et al. 2014). Acute effects of

ambient levels of traffic pollution were observed in healthy adults (Rice et al. 2013;

4

Zuurbier et al. 2011), but the small number of studies and limitations in their designs

maintains this subject still controversial (Health Effects Institute 2010).

Outdoor workers in urban areas are more exposed to the mix of pollutants generated

from automotive fleet. Indeed, in the urban scenario, there is a gradient of exposure

related to the site where these professionals develop their activities (closer or farther

from high traffic roads). Also, different categories of workers demand different physical

activities and the healthy worker effect cannot be assumed to be present in all of them

(Choudhary and Tarlo 2014).

Our objective is to evaluate the chronic effect of exposure to different levels of traffic-

generated PM2.5 on the lung function of outdoor workers in the city of São Paulo.

Methods

This is an observational study approved by Ethics on Research Committee (CAPPesq)

from Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo,

number 0565/07. All participants signed an informed consent.

Participants

In order to explore the effects of a wider range of exposures, three categories of workers

were selected. Two of them – taxi drivers and traffic controllers – were expected to have

a greater exposure, whereas the third, workers of the Forest Institute rangers, were

presumably submitted to lower levels of exposure, since they spent part of their daily

life in a park in the outskirts of São Paulo. The inclusion criteria were: a) working on

streets and/or avenues (traffic controllers or taxi drivers) or parks (Forest Institute in

São Paulo) for, at least, two years; b) male; c) age between 18 to 65 years and d) non-

smoker or former smoker for over than one year (with air-exhaled carbon monoxide less

than 6 ppm, measured in each of the clinical evaluations).

5

Taxi drivers were informed about the study and invited to a meeting through

advertisements inserted in their union paper. Eighty two workers attended the first

presentation, 64 attended a meeting for clinical evaluation and 57 fulfilled the inclusion

criteria and were admitted to the study.

Three hundred traffic controllers attended 6 meetings in the Traffic Engineering

Company, 149 volunteered, 75 fulfilled the inclusion criteria and 26 remained to the end

of the study. These participants work in the expanded central region of São Paulo.

Forest Institute rangers (working in a park in the outskirts of the city) were recruited

after a project presentation meeting at their institution, responsible for monitoring and

preserving biodiversity in the State of São Paulo. Fifty workers attended the meeting, 23

fulfilled the inclusion criteria and showed up to the clinical evaluation, and 22 remained

in the study.

Study Design

In the period from 2008 to 2012, each participant was followed at specified intervals

within a month, and exposure and effect indicators were measured repeatedly with the

objective of better evaluate the level of exposure and lung function during this short

period.

Participants were submitted to an initial evaluation that included recording of

demographic characteristics, confirmation of the non-smoker condition, occupational,

cardiorespiratory risks and clinical examination. After the initial evaluation, participants

were scheduled, in pairs, to attend four visits (once a week for one month) in the Heart

Institute of Faculdade de Medicina da Universidade de São Paulo. In each visit, they

were submitted to a clinical evaluation to assess the occurrence of complications

between the assessments, to have exhaled CO and exhaled NO measurements as well as

to perform pulmonary function tests.

6

At 7:00 am on the eve of each clinical evaluation, each individual received a portable

lightweight battery operated sampler installed in a shoulder bag to be carried during all

day and kept nearby during sleeping period or baths, in order to record real 24 hours

environmental exposure during. In the following day, before the clinical evaluation and

the pulmonary function test, the monitor was withdrawn.

All participants answered a structured food frequency questionnaire to evaluate the

frequency of usual food consumption (Fisberg et al. 2008). The intake of fruit and

vegetables, sources of antioxidant elements, was recorded as the number of servings per

day.

Anthropometric measures

Weight in light clothes was measured to the nearest 100 g (Tanita scale) and height to

the nearest 0.1 cm was measured barefoot with head in the horizontal Frankfort plane,

using a Seca 208 stadiometer. Waist circumference midway between the lateral lower

ribs and the iliac crest, and hip circumference at the widest part over the greater

trochanters were measured according to standard protocols (World Health Organization

1989).

Respiratory Symptoms and Lung Function

All participants answered a questionnaire on asthma symptoms prevalence in the

preceding 12 months (European Community Respiratory Health Survey 1996; Ribeiro

et al. 2007). Spirometry was performed in the morning, with a KoKo spirometer

(Pulmonary Data Services Instrumentation Inc., Louisville, USA), according to

ATS/ERS recommendations (Miller et al. 2005a; Miller et al. 2005b), during morning

periods. Three manoeuvres were carried out and the best one was chosen and analysed

according to the ATS/ERS criteria (Pellegrino et al. 2005). The predicted values were

7

computed according the reference values recommended for the Brazilian population

(Duarte et al. 2007; Pereira et al. 2007).

Exhaled Nitric Oxide (NOex)

Exhaled nitric oxide (NOex) was collected before each clinical evaluation, according to

ATS standardization. Briefly, exhaled air was trapped in sealed balloons collected by a

Siever Kit (Sievers Instruments Inc., Boulder, CO, USA) with a 0.3 m biologic filter

HEPA (TROX Technik Ltda, SP, Brasil) and measured by chemiluminescence (Sievers

apparatus NOA 280) . Before measurement, the NOex analyzer was tested daily by a

filtering apparatus of ambient air (standardized mixture to transform NO into NO2 in

45ppb, the physiologic pattern, White Martins gases industriais AS, São Paulo SP,

Brasil). The range of NOex among three measurements did not exceed 10% (American

Thoracic Society 1999; American Thoracic Society Workshop 2006).

PM2.5 concentration

The sampler, designed by the Harvard School of Public Health, operates at a flow rate

of 4 lpm through an impaction plate to obtain a PM2.5 cutoff. A silicone catheter

connects the air inlet positioned at the volunteer shoulder to the sampler inflow. A

vacuum pump powered by a rechargeable Li-Ion battery, model WR-5000 Aircheck

from SKC, that incorporates a flow control and a chronometer, provides the necessary

continuous air flow during the 24-hour sampling period. A polycarbonate membrane, a

Whatman filter with a diameter of 37 mm and 0.8 pore size (part number 110809),

installed inside the sampler after the impaction plate retains the particulate matter

sampled. This membrane was weighed before and after the sampling process in an

accurate 1 microgram Mettler Toledo scale, model UMX2, following a laboratorial

protocol developed to control temperature and humidity (Miranda et al. 2012),

estimating the total mass of particulate matter collected. The volume of air sampled is

8

obtained considering the 4 lpm pump flow and the sampling period recorded by the

pump chronometer. The average daily concentration of PM2.5 was obtained dividing

total mass by total air volume sampled.

Statistical Analysis

The tertiles of all individual measurements of PM2.5 were computed and the volunteers

were classified according to them in three exposure groups: low, when all measures

were lower than the first tertile, high, when all measures were higher than the second

tertile and intermediate, otherwise. After defining the exposure groups, the analysis was

based on the averages of the within-individual spirometry variables and baseline

covariates.

The means of the baseline and spirometry variables for the different groups of exposure

were compared by a one-way analysis of variance. When residual diagnostic tools

suggested coarse deviations from the model assumptions, the analysis was

complemented by a Kruskal-Wallis test. To assess the association between passive

smoking, respiratory symptoms, hypertension and/or diabetes and exposure to air

pollution the likelihood ratio tests were considered. The association between spirometry

variables and exposure, adjusted for age, waist circumference, time in job, daily work

hours, diabetes or hypertension, environmental tobacco smoke, previous smoking habits

and number of fruit and vegetable servings per day was assessed by means of multiple

robust regression models based on MM-estimators (Yohai 1987) . The models were

fitted via the lmrob function in the R software package (R Development Core Team

2013).

9

Results

From the 83 traffic-exposed participants (taxi drivers and traffic controllers) four were

excluded due to inconsistencies in the pulmonary function measurements. All 22 Forest

Institute workers were included in the analyses. Participants who attended only one

evaluation session were excluded resulting in a sample size of 101.

345 measures of PM2.5 and 359 pulmonary function tests were completed during the

study period. Figure 1 presents the distribution of individual PM2.5 measurements.

Particulate matter measurements smaller than 25 g/m3 were observed in the group of

traffic controllers and taxi drivers, while some forest rangers were exposed to

concentrations above this value. The observed values of the PM2.5 tertiles were 25 g/m3

and 39.6 g/m3. The mean concentration of PM2.5 was 17.8 g/m3 (standard deviation=

3.5 g/m3) in the low exposure group, 36.6 g/m3 (standard deviation= 10.8 g/m3) in

the medium exposure group and 67.4 g/m3 (standard deviation= 14.1 g/m3) in the

high exposure group.

Table 1 presents demographic and clinical characterization according to exposure

groups. The three groups of exposure are quite similar in terms of age, waist

circumference and body mass index (BMI). On average, participants in the low

exposure group have worked in the same function for a longer period and have less

work shifts than those in the other groups.

Table 2 presents descriptive statistics for symptoms, exhaled nitric oxide (NOex) and

lung function data. Participants in the high exposure group tend to present smaller FEV1

values and higher FEF25-75 when compared to those in the other groups. The prevalence

of respiratory symptoms was higher in the medium exposure group, although

prevalence of wheezing was similar in the three groups. In general, we observed a

decrease of FVC% and FEV1% from the low exposure to the high exposure group,

10

although without statistical significance. On the other hand, a significant increase of

FEF25-75% without a decrease of FEV1/FVC was observed.

In Table 3 we highlight the adverse effects on spirometry parameters observed in the

PM2.5 high and medium exposure groups when compared to the low exposure group. In

order to verify the robustness of the observed findings, we performed a sensitivity

analysis, progressively adding more explanatory variables to check how the estimates

were affected across different model specifications. Because only 86 participants filled

out the food consumption questionnaire and there is no statistical significant differences

among the mean intake of fruit and vegetables in the three exposure groups, this

variable was not included. The estimates for FVC, FEV1, and FEF25-75% remained

reasonably stable for the different sets of explanatory variables considered. In the high

exposure group smaller FVC and FEV1 values were observed. Also, in the same group,

FEF25-75% values were higher with no statistically significant differences detected for

FEV1/FVC.

Discussion

This study suggests that individuals chronically exposed to ambient levels of traffic

pollution present significant alterations in pulmonary function. Moreover, the results

indicate that exposure to ambient traffic pollution vary markedly across individuals,

and, being more evident in individuals with high exposure. The observed findings were

robust and remained reasonably stable for the different sets of explanatory variables

considered. Reductions in FVC and FEV1 were not accompanied by a reduction in

FEV1/FVC, but an increase in FEF25-75% was observed suggesting a restrictive lung

effect. A similar effect, with reduced FVC and FEV1, but no reduction of FEV1/FVC

has been observed after exposure to ozone probably due to change in airways hysteresis

compared with the parenchymal hysteresis (Kjaergaard et al. 2004).

11

A strength of this study is the more precise characterization of the differences in

personal exposure to ambient pollution obtained via personal monitoring (24 hours

PM2.5). Exposure to PM2.5 measured by personal equipment seems to be more

appropriate to assess daily experience of exposure including work shift, time in

commuting and at home. In fact, our results reinforce the concept that urban dwellers

may experience a considerable variation of exposure, depending on their habits and

work characteristics, since the difference between the means of the PM2.5 in the high and

low exposure groups is almost 50 µg/m3.

More than 75% of the participants (classified in the medium level) were exposed to a

mean concentration of 36.6 μg/m3, exceeding the recommended daily concentration of

25 μg/m3 suggested by WHO (World Health Organization 2006). Considering such a

scenario the detection of significant differences among the groups is indeed impressive.

Most probably our results underestimate the effects of air pollution on lung function,

since there is not a group without chronic exposure, since all participants live in São

Paulo, a city known to have high levels of air pollution.

Most of the studies that have focused on chronic (Götschi et al. 2008; Sava and Carlsten

2012; Schikowski et al. 2005) and acute (Sava and Carlsten 2012; Strak et al. 2012)

effects of air pollution on pulmonary function suggest a reduction of this outcome and

most of them reported evidences of obstructive pulmonary disorder (Andersen et al.

2011; Schikowski et al. 2005), although this topic is still controversial (Schikowski et

al. 2014). A recently published study (ESCAPE), designed to evaluate the chronic effect

of air pollution on pulmonary function, suggested an association between exposure to

NO2 and PM10 but not to PM2.5, along with reduced FEV1 and FVC, mainly in obese

individuals (Adam et al. 2015).

12

A longitudinal study carried out in Germany with women living near major roads

detected a significant association between exposure to PM10 and reduction of FVC,

FVE1 and of FEV1/FVC (Schikowski et al. 2005). A study carried out with 1391 non-

smokers followed up by 16 years (Abbey et al. 1998) detected a decrease of 7.2% in

FEV1 among those with higher levels of exposure, as well as a significant decrease in

FEV1/FVC. A similar obstructive effect on children exposed to traffic-generated

pollutants was reported in a study realized in Munich (Wjst et al. 1993).

While the effects of exposure to pollutants generated by burned biomass on lung

function are better established (Eisner et al. 2010; Regalado et al. 2006), this does not

seem to occur with the effects of exposure to urban pollutants. A detailed analysis

(Health Effects Institute 2010) involving studies from different continents concludes

that the evidence is still insufficient, even though it points out that chronic exposure

suggests effects on adolescents and young people, similarly to that suggested by others

authors (Kelly and Fussell 2011). A study conducted in the Netherlands, comparing

transportation modes (bus, car, and bicycle), suggests that exposure to PM10 is

associated with the reduction in PEF and increased resistance of airways. An association

between exposure to soot and increase in FEF25-75% has also been reported (Zuurbier et

al. 2011).

In a statement on risk factors for Chronic Obstructive Pulmonary Diseases (Eisner et al.

2010) The American Thoracic Society considers that there are enough evidences to state

that air pollution reduces lung function.

The results of this study are in agreement with results from other studies (Kalappanavar

et al. 2012; Kan et al. 2007) in the sense that air pollution is associated to a reductions in

FVC and FEV1 without a reduction in FEV1/FVC, suggesting lung volume reduction

13

with restrictive ventilatory disorder, although a possible inflammatory effect of ozone

cannot be ruled out (Goodman et al. 2014; Schelegle et al. 2007).

Few studies also showed increased levels of FEF25-75%. Gupta et al. (2011) considered

two groups of 100 non-smoking policemen, one of them consisting of traffic policemen

and the other consisting of policemen who were never worked exposed to vehicular

pollution, and suggested decreases in lung function as well as higher prevalence of

respiratory symptoms in the exposed group. However, they did not use predicted values

to compare the groups and did not show FEF25-75 and FEV1/FVC values, complicating a

comparison with our results. The lower prevalence of asthma-suggestive respiratory

symptoms in the high exposure group in our study is in agreement with the results of

their lung function test that showed a restrictive functional pattern.

We also detected a significant increase in FEF25-75% without a corresponding reduction

in FEV1/FVC suggesting a restrictive disorder with probable increase in the elastic

recoil. This can be attributed to a characteristic of fine particles which tend to deposit in

the small airways causing wall inflammation, thickening, and remodelling, as suggested

by studies using lungs from autopsies in São Paulo, Brazil (Saieg et al. 2011) and in

Fresno County, California, USA (Pinkerton et al. 2000).

A study carried out in India with 300 children living in an industrial area and 300

children living in a green zone estimated a prevalence of restrictive ventilatory disorders

of 20,3% and 6,0%, respectively, supporting the hypothesis that exposure to air

pollution may be associated with lung function impairment (Kalappanavar et al. 2012).

These findings are also consistent with a study involving 230 children in Mexico city

and 19 in the city of Tlaxcala; the authors detected 60% of interstitial markings in

children of Mexico City in contrast with 0% in city of Tlaxcala, where the PM and

ozone levels are lower(Calderon-Garciduenas et al. 2006). An interesting recently

14

published study, comparing pulmonary function of Indian and UK-Indian children

suggests that children living in rural areas in India have lower values of FVC and FEV1,

without reduction of FEV1/FVC, suggesting an association between nutritional and

environmental effects and restrictive disorders, since exposure to biomass in rural areas

of the country is usual (Sonnappa et al. 2015).

In one of the few studies reporting values of FEF25-75% , a restrictive pattern of lung

function disorder very similar to that observed in our study was observed in traffic

controllers in India (Patil et al. 2013). However, in addition to the methodological

problems of the study, this effect is still controversial given that a previous study

conducted in India three years before, showed reductions in FVC and FEV1 among

nonsmoking participants. When the analysis took only smokers of exposed and

unexposed to traffic groups into account smaller values of FEF25-75% and maximum

voluntary ventilation among the traffic exposed participants was observed, suggesting a

mixed ventilatory disorder (Pal et al. 2010). It is already known that part of the people

exposed to tobacco smoke develop interstitial lung disease (Morse and Rosas 2014;

Vassallo and Ryu 2012), also limiting the interpretation of such results.

Waking up with respiratory symptoms was more frequently present in participants

classified in the medium and high exposed groups. Wheezing, asthma, nasal allergy

were rare and similar among participants of the three groups. Low perception of

respiratory symptoms has been far studied in literature, mainly in asthma patients. Lack

of illness severity perception is associated to worse outcome and prognosis.

Furthermore, the need for education and follow up by symptoms and signs monitoring

by peak flow meter and lung function which present more sensibility and specificity

(Kaptein et al. 2008; Koinis-Mitchell et al. 2009). We conjecture that asthma patients

who may present severe clinical signs during exacerbations may have low perception of

15

their symptoms and it is plausible to assume that exposed individuals may also be less

perceptive of respiratory symptoms due to small fluctuations of ambient air pollution.

This hypothesis supports the need of more specific tools to check adverse effects on

respiratory symptoms secondary to air pollutants.

Although NOex is considered as a good and not invasive method to check for

respiratory inflammation (Choi et al. 2006; Ricciardolo et al. 2004), in our study its

levels were similar among groups independently of the pollutant exposure levels. This

may be caused by the sensibility in detecting low levels of respiratory inflammation.

Accordingly, another study conducted by our group suggested that air pollution was

related to respiratory inflammation in street traffic controllers in São Paulo suggesting

that NOex is a marker of airway inflammation and of decrease the pH of the exhaled

condensate breath (Lima et al. 2013). Differently from this study, the authors compared

indoor and outdoor workers measuring the NO in the condensate breath which may

have improved the sensibility of their results.

In conclusion, this study suggests that adult individuals chronically exposed to higher

concentration of PM2.5 vehicular air pollution showed significant reductions in FVC,

FEV1 and PEF, without a concomitant reduction of FEV1/FVC, as well as an increase of

FEF25-75%, suggesting that the exposure to fine particles is associated, predominantly,

with ventilatory restrictive impairment.

16

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TABLE 1. Baseline characteristics of participants according to exposure groups (N=

101)

  Exposure groups  

Variables Low (N=15)Medium (N=76) High (N=10) p

Age (years) 46.6 (±8.4) 48.4 (±9.0) 49.3 (±12.4) 0.730 (1)

BMI (kg/m2) 26.4 (±3.7) 28.9 (±4.4) 28.4 (±3.7) 0.117 (1)

Waist circumference (cm) 94.9 (±8.8) 102.5 (±12.7) 101.3 (±10.4) 0.098 (1)

Time of work (years) 16.5 (±7.8) 10.3 (±8.2) 11.9 (±11.4) 0.041 (1)

Work shift (hours) 9.3 (±2.4) 11.3 (±3.5) 12.6 (±3.5) 0.040 (1)

Exhaled Carbon Monoxide (ppm) 2.5 (±2.9) 2.6 (±3.1) 1.5 (±2.0) 0.525 (1)

ETS(2) (N (%)) 7 (46.7) 39 (51,3) 4 (40.0) 0.775 (3)

at home (N(%)) 1 (6.7) 5 (6.6) 2 (20.0) 0.430 (4)

at work (N(%)) 6 (40.0) 41 (54.0) 5 (50.0) 0.610 (4)

Hypertension and/or diabetes (N (%)) 5 (33.3%) 24 (31.6%) 3 (30.0%) 0.984 (4)

Haemoglobin (g/dL) 15.3 (±0.9) 15.1 (±0.9) 14.8 (±0.6) 0.463 (1)

Haematocrit (%) 44.4 (±2.9) 44.7 (±2.4) 43.9 (±1.3) 0.587 (1)

White blood cells (N/mm3) 6217 (±1685) 6765 (±1634) 7052 (±2539) 0.469 (1)

Total Colesterol (mg/dL) 200.1 (±39.6) 212.1 (±34.2) 201.8 (±34.9) 0.384 (1)

HDL 47.4 (±8.3) 46.2 (±12.7) 42.9 (±8.3) 0.662 (1)

LDL 130.3 (±37.6) 136.5 (±31.6) 132.8 (±32.2) 0.774 (1)

Albumin (g/dL) 4.7 (±0.2) 4.7 (±0.2) 4.8 (±0.3) 0.623 (1)

Fasting blood glucose (mg/dL) 96.0 (±9.7) 101.4 (±23.4) 106.3 (±21.7) 0.510 (1)

Intake of fruits and vegetables (portions)(5) 5.7 (±3.6) 6.3 (±3.1) 5.7 (±3.3) 0.774 (1)

ANOVA ; (2) Enviromental Tobaco Smoke; (3) Chi-Squared test; (4) Likelihood- Ratio test; (5) Low: N=8, Medium: N=68, High: N=8.Results expressed as mean (± standard deviation) or number (percentage).

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TABLE 2. Prevalence of respiratory symptoms and median (interquartile range) of

exhaled nitric oxide (NOex) and spirometric parameters of participants according to

exposure groups (N=101)

  Exposure groups  

  Low (N=15)Medium (N=76)

High (N=10) p

Respiratory Symptoms Q1. Wheeze 2 (13.3%) 12 (15.8%) 1 (10.0%) 0.867 (1)

Q1.1.Wheeze with breathless 1 (6.7%) 7 (9.2%) 1 (10.0%) 0.940 (1)

Q1.2. Wheeze without a cold 0 (0.0%) 10 (13.2%) 1 (10. 0%) 0.146 (1)

Q2. Waking with tightness in the chest 0 (0.0%) 12 (15.8%) 4 (40.0%) 0.014 (1)

Q3. Waking with breathless 0 (0.0%) 11 (14.5%) 0 (0.0%) 0.035 (1)

Q4. Waking with cough 0 (0.0%) 17 (22.4%) 0 (0.0%) 0.005 (1)

Q5. Attack of asthma 0 (0.0%) 3 (4.0%) 1 (10.0%) 0.388 (1)

Q6. Treatment for asthma 0 (0.0%) 2 (2.6%) 0 (0.0%) 0.562 (1)

Q7. Nasal allergy 2 (13.3%) 21 (27.6%) 3 (30.0%) 0.445 (1)

Q5 or Q6 - Asthma diagnose 0 (0.0%) 5 (6.6%) 1 (10.0%) 0.343 (1)

NOex 19.5 (15.7) 20.7 (10.5) 22.1 (10.1) 0.845 (3)

Lung function parametersFVC (%) (2) 94.0 (13.0) 94.9 (16.4) 83.5 (17.2) 0.076 (3)

FEV1 (%) (2) 91.5 (11.3) 91.2 (13.8) 82.2 (19.2) 0.143 (3)

FEV1/FVC (%) 77.5 (10.9) 79.6 (7.3) 80.3 (6.8) 0.997 (3)

FEF25-75/FVC (%) (2) 102.5 (17.1) 104.8 (18.3)120.2 (22.5) 0.041 (3)

PEF (%) (2) 79.9 (30.0) 74.9 (18.5) 72.6 (26.7) 0.386 (3)

(1) Likelihood- Ratio test; (2) Percentage of predict value; (3) Kruskal-Wallis test.

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Table 3. Effects of PM2.5 on lung function in different stages of the regression model fitting: high exposure – low exposure and medium exposure – low

exposure

    Model 1 Model 2 Model 3 Model 4

 Exposure groups compared effect std error p effect std error p effect std error p effect std error p

FVC (%)(1) Medium -Low -0.13 2.71 0.960 1.01 2.97 0.730 0.81 3.18 0.800 -0.24 3.01 0.938High - Low -12.96 3.88 0.001 -11.01 3.98 0.007 -10.76 4.09 0.010 -12.19 3.98 0.003

FEV1 (%)(1) Medium -Low 0.94 3.35 0.780 1.77 3.47 0.611 1.76 3.50 0.617 1.16 3.33 0.729High - Low -10.12 5.03 0.047 -9.36 4.52 0.041 -8.41 5.04 0.099 -9.10 5.10 0.078

FEV/FVC (%) Medium -Low 1.51 2.39 0.529 1.76 3.02 0.561 1.86 3.29 0.572 1.96 3.31 0.557High - Low 1.42 2.51 0.573 1.46 3.09 0.638 1.97 3.28 0.550 1.97 3.35 0.558

FEF25-75/FVC (%)(1) Medium -Low 1.74 3.09 0.574 -0.83 3.66 0.821 -0.80 3.79 0.833 -0.91 3.86 0.814

High - Low 18.43 5.78 0.002 15.57 5.93 0.010 14.99 5.93 0.013 14.86 6.08 0.017

PEF (%)(1) Medium -Low -4.45 5.53 0.423 -1.48 5.77 0.799 -1.76 5.82 0.763 -1.84 5.66 0.746  High - Low -6.87 7.34 0.351 -3.58 7.43 0.631 -4.34 7.99 0.588 -4.41 7.97 0.581

(1) Percentage of predict valuePredictors included in the modelsModel 1: Exposure groupsModel 2: Exposure groups + age + waist circumference + time of work + work shiftModel 3: Exposure groups + age + waist circumference + time of work + work shift + ETS at home + former smokerModel 4: Exposure groups + age + waist circumference + time of work + work shift + ETS at home + former smoker + DM or HAS

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Figure 1. Distribution of individual personal PM2.5 measurements during the study period in the group of traffic controllers and taxi drivers, and in the group of forest workers

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