The present epidemiological investigation aims to clarify the role of air pollution in creating and exacer-bating asthma symptoms. Its specific objectives are:
• to quantify the prevalence of childhood respiratory disorders among the paediatric population resid-ing in the Milazzo–Valle del Mela area;
• to characterize the air pollution level in the area; and
• to evaluate respiratory function among resident children affected by obstructive pulmonary diseases and evaluate its relationship to air pollution levels.
The investigation consisted of cross-sectional and panel studies and a monitoring campaign. The first study was a cross-sectional survey of the prevalence of respiratory disorders among all children
(6–10 years old) who attended the primary schools in the area. It surveyed 2506 children. The study took place from April to May 2007, and a questionnaire was administered to the parents of the children.
Two panel studies – PANEL 120 and PANEL 50 – were then conducted on a subsample of children. The first panel study, PANEL 120, enrolled 154 children that scored positive for any asthmatic symptoms on the questionnaire completed by their parents. The panel was followed up from November 2007 to April 2008. Every two weeks, respiratory function and bronchial inflammation were assessed, while parents recorded (in a diary) symptoms and drugs taken by their children during the follow-up.
The second panel study, PANEL 50, enrolled 50 children. The subjects were followed up for a week with daily measurements of health status, respiratory function, bronchial inflammation and air pollutant level, performed with personal monitors. Epigenetic markers – that is, the study of pathways that develop heritable patterns of gene expression without changing the underlying DNA – were evaluated twice using samples of nasal cells. The 50 children were divided into small groups of 5 children each. Each group was followed up for a week; after that another group was followed up, and so on from December 2007 to April 2008. Groups were matched by residence and the school the children attended. Within each group, a so-called witness was chosen to wear the personal monitoring device. During the day, parents compiled an hourly diary of the children’s activities.
Ambient air quality was assessed by monitoring campaigns. Dosimeters measured gaseous pollutants, and a gravimetric device measured PM2.5.
A communication plan was developed, and the parents of the children attending the schools enrolled in the study participated in all investigatory phases through a series of public meetings and initiatives. The dates of release of the results of each study were communicated to the parents.
The epidemiological investigation was launched on 27 March 2007. The first study results were presented during a meeting on 6 October 2007. From November 2007 to February 2008, several meetings with the parents of the population groups accompanied the subsequent studies. The data on air quality recorded by the monitoring campaign were presented on 30 May 2008. Final results were reported during a scientific meeting at the University of Messina on 28 February 2009 and at public meetings in the Municipality of Milazzo on 30 April 2009, in the Municipality of San Filippo del Mela on 24 April 2010 and in the Munici-pality of Santa Lucia del Mela on 5 June 2010.
Material and methods
Exposure assessment
Ambient air quality was assessed by monitoring campaigns. Passive dosimeters were located at 21 sites in each schoolyard, measuring continuously for a week each month during the study period, from Novem-ber 2007 to April 2008. These dosimeters measured gaseous pollutants (sulfur dioxide, nitrogen dioxide, and benzene, toluene and xylene).17 Also, a gravimetric device located at the secondary school of Pace del Mela measured PM2.5, and ARPA Tuscany analysed the particle filters collected. From December 2007 to April 2008, we obtained a series of daily PM2.5 averages.18 Personal passive dosimeters were also used for personal monitoring of exposure to gaseous air pollutants. Personal monitoring was completed with PM2.5 laser-based personal monitors.19 Every day, at the witness’s home, at 18:00, a nurse collected and replaced the daily personal passive dosimeters and checked the PM2.5 instrument.
17 The sampling was in accordance with European Committee for Standardization practices. The analysis was performed by Passam AG Labo-ratory for Environmental Analysis (technical standards EN 45001 1996 and ISO/IEC 17025 2001).
18 The sampler used was AirFlow HS Avantech (technical standards UNI–EN 12341:2001 and UNI EN 14907:2005).
19 Personal monitoring of exposure to PM2.5 was done using a laser-based Sidepack AM510 (technical standards: EN61326-1:1997 A11998 Clause 6 and EN61326:1997 + A1:1998; and ATEX Equipment Directive 94/9/EC). Calibration with gravimetric standards was done by ARPA Tuscany.
Outcome evaluation
For the first panel study, PANEL 120, a team of two nurses and one or two pneumologists examined (every two weeks) the children enrolled, at each primary school of the study area. They performed a spirometric examination, collecting:
• forced vital capacity (FVC), which determines the vital capacity from a maximally forced expiratory effort;
• forced expiratory volume in 1 second (FEV1);
• the ratio of FEV1 to FVC;
• forced expiratory flow between 25% and 75% of vital capacity (FEF25–75); and
• measurements of fractional exhaled nitric oxide (FeNO), a reproducible marker of airway inflamma-tion.
Children enrolled in the PANEL 50 study performed self-administered FEV1 measurements at home, using a pocket-size pulmonary function electronic monitoring device (Piko-1) twice a day – in the morn-ing, when they got up for school, and in the evening (at 18:00), under the supervision of a nurse; on that occasion, the nurse measured the child’s FeNO. On Tuesday and Friday afternoons, each child went to a dedicated outpatient clinic to undergo nasal brushing, to collect nasal cells for DNA methylation analy-sis. Nasal brushing was performed on Tuesdays in the right nostril and on Fridays in the left nostril by a trained nurse. The highly quantitative polymerase chain reaction–pyrosequencing analysis on bisulfite-treated DNA was used to measure DNA methylation in the promoter regions of interleukin-6 and nitric oxide synthase gene promoters and of Alu and LINE-1 repetitive elements (Baccarelli et al., 2012).20 The studies were conducted in accordance with the Declaration of Helsinki and a Ministry of Health Cir-cular from 2 September 2002 (Ministry of Health, 2002). The Ethics Committee of Local Health Service Unit No. 7, Cagliari, Italy, and the Research Ethics Committee of the University of Milan approved the study; the parents of the study participants gave their informed written consent. The local health authority was informed, and general practitioners and paediatricians with practices in the study area were informed and worked with the study researchers.
Statistical methods
Standard descriptive statistics were used to summarize data. To evaluate the association of FEV1, FeNO and DNA methylation with pollutant concentration, we fitted the data with a generalized estimating equation population average model, specifying a gamma family with a log link and a robust estimator of standard error. We chose a gamma-distributed response because one of the dependent variables (FEV1) had a slightly asymmetrical distribution. The association of wheezing symptoms (yes/no) with pollut-ants concentration was quantified by fitting the data with a multivariable generalized estimating equation regression model for binary data. The generalized estimating equation models were used to take into ac-count the presence of correlated data in the panel studies – that is, repeated measurements for each child during the follow-up period.
All observations of FeNO levels below the limit of detection of 6.25 µg/m3 (5 ppb; 5 measurements) were excluded from the analysis. In addition, to avoid ambient nitric oxide interfering with FeNO readings, readings taken when the ambient nitric oxide level was greater than 6.25 µg/m3 (5 ppb) were excluded.
20 DNA methylation, performed by enzymes called DNA methyltransferases, is an epigenetic mechanism that regulates gene expression. DNA methylation is established in utero or during early life and subsequently varies in response to environmental stressors. There is growing evidence that several inflammatory mediators are programmed through epigenetic mechanisms, such as DNA methylation. Among those mediators relevant to asthma are: fractional exhaled nitric oxide production – which is predominantly due to overexpression in the airway epithelium of the inducible nitric oxide synthase (iNOS) associated with lower DNA methylation in its specific gene promoter – and also interleukin-6, the overexpression of which is associated with reduced DNA methylation in its specific gene promoter. However, a large part of DNA methylation in the human genome is located in intergenic DNA – that is, DNA sequences located between gene clusters. In particu-lar, Alu and LINE-1 repetitive elements, which are sequences of intergenic DNA repeated in up to one million copies per haploid genome, represent about 30% of the human genome and are heavily methylated. Alu and LINE-1 methylation has been shown to correlate with the global amount of DNA methylation and has been shown to decrease in response to inflammation and oxidative stress.
Multivariate models for statistical analysis of FEV1, FeNO and DNA methylation data were used as con-tinuous variables, and results were expressed as a per cent variation for a 10 μg/m3 increase in pollutant concentration. These models included independent variables for: age; gender; subject’s height and weight;
day of the week; parental education; exposure to environmental tobacco smoke and to mould or damp-ness in the child’s room; symptoms of rhinoconjunctivitis (as a proxy for atopy); traffic intensity in the street of residence; recent respiratory infections; use of a steroid inhalator for asthma; outdoor tempera-ture; and relative humidity.
Results
Cross-sectional study
The target population consisted of 2506 children who attended the primary schools of the municipalities of Condrò, Gualtieri Sicaminò, Milazzo, Pace del Mela, San Filippo del Mela, San Pier Niceto and Santa Lucia del Mela. Parents were asked to fill out the Italian version of the International Study of Asthma and Allergies in Childhood questionnaire (Galassi, Battista & Forastiere, 2005), and 2242 valid questionnaires (89.5% of those completed) were analysed.
The number (and prevalence) of respiratory disorders among children participating in the Milazzo–
Valle del Mela area 2007 cross-sectional study included: 168 (7.5%) with lifetime asthma; 239 (10.7%) with wheezing during the last 12 months; 84 (3.7%) with persistent cough or phlegm during the last 12 months; and 193 and 133 (19.6% and 15.6%) with allergic rhinitis or eczema, respectively (Table 69).
Table 69. Respiratory disorders and allergic symptoms in primary school children
Respiratory disorder or
allergic symptom Gender Children 6–7 years old Children older than 8 years
Number Per cent Number Per cent
Wheezing ever Boys 117 29�1 204 27�3
Girls 85 21�7 154 21�9
Wheezing last 12 months Boys 47 11�7 94 12�6
Girls 38 9�7 60 8�5
Asthma ever Boys 33 8�2 81 10�9
Girls 11 2�8 43 6�1
Allergic rhinitis ever Boys 86 21�4 168 22�5
Girls 58 14�8 127 18�1
Allergic rhinitis last 12 months Boys 103 25�6 205 27�5
Girls 65 16�6 139 19�8
Rhinoconjunctivitis last 12 months Boys 43 10�7 106 14�2
Girls 32 8�2 73 10�4
Eczema ever Boys 51 12�7 121 16�2
Girls 59 15�1 120 17�1
Eczema last 12 months Boys 46 11�4 90 12�1
Girls 49 12�5 72 10�2
Persistent cough or phlegm last 12 months Boys 19 4�7 28 3�8
Girls 15 3�8 22 3�1
The socioeconomic characteristics for education and employment of the parents and other characteristics are described in Table 70.
Table 70. Prevalence of risk factors and predictors of childhood respiratory disorders
Mother Education ≥ 14years 488 61�5 806 55�6
Employed 325 41�0 582 40�2
Housewife 324 40�9 607 41�9
Father Education ≥ 14 years 422 53�2 716 49�4
Employed 700 88�3 1278 88�2
Mean age of mother at
delivery (years) – 29�8 – 29�3 –
Child’s current weight (kg) – 26�1 – 36�1 –
Child’s habits Sedentary 61 7�7 137 9�5
Intense physical activity more than
once a week 338 42�6 688 47�5
Parents’ and others’ habits Mother current smoker 149 18�8 295 20�4
Mother smoker during pregnancy 55 6�9 76 5�2
Father current smoker 244 30�8 440 30�4
Mother and father current smokers 92 11�6 176 12�1
At least one parent current smoker 301 38�0 559 38�6
At least one smoker at home 205 25�9 438 30�2
At least one smoker at home or one
parent smoker 322 40�6 621 42�9
During the first year of life 121 9�6 217 17�2
Mould or dampness in
child’s room Current 127 10�1 240 19�0
Both 39 3�1 77 6�1
Tables 71–77 show the data on prevalence and their corresponding ORs for the 2007 Milazzo–Valle del Mela cross-sectional study. The estimated effects (prevalence ORs) of the main risk factors showed that, in children exposed to passive smoke, the prevalence of asthmatic symptoms and persistent cough or phlegm increased consistently (Table 71). For example, having mother as a current smoker versus never smoker showed an OR for wheezing during the last 12 months of 1.4 (95% CI: 1.0–2.0); for current asthma, it was 1.6 (95% CI: 1.0–2.5); and for persistent cough or phlegm, it was 2.1 (95% CI: 1.3–3.6(Table 71). Exposure to intense car traffic or living in areas with the highly frequent passage of trucks increases the prevalence of inflammatory symptoms (Table 72). For example, for children exposed to intense car traffic, in contrast to its absence, the OR for wheezing during the last 12 months was 0.8 (95% CI: 0.5–1.4); for asthma ever, it was 1.5 (95% CI: 1.0–2.2); and for persistent cough or phlegm, it was 2.3 (95% CI: 1.0–5.3). Exposure to mould or dampness (currently and in the first year of life), versus never being exposed, increases the risk of asthmatic symptoms (Table 73). The OR for wheezing during the last 12 months was 1.8 (95% CI: 1.1–3.0); for current asthma, it was 1.5 (95% CI: 1.0–2.2); and for persistent cough or phlegm, it was 0.2 (95% CI: 0.0–1.5).
Table 71. Prevalence and OR of childhood respiratory disorders: passive smoking
Respiratory disorders and passive smoking Number of children Per cent a OR 95% CI Wheezing last 12 months
Parents smoking
Non-smokers 62 8�0 1�0 –
Ex-smokers 12 11�2 1�4 0�7–2�7
At least one smoker 87 10�6 1�4 1�0–1�9
Mother smoking
Non-smoker 109 8�1 1�0 –
Ex-smoker 32 11�0 1�4 0�9–2�1
Current smoker 45 10�8 1�4 1�0–2�0
Father smoking
Non-smoker 78 8�5 1�0 –
Ex-smoker 39 7�9 0�9 0�6–1�3
Current smoker 74 11�3 1�4 1�0–1�9
Current asthma Parents smoking
Non-smokers 36 4�6 1�0 –
Ex-smokers 3 2�8 0�6 0�2–2�0
At-least one smoker 39 4�7 1�1 0�7–1�8
Mother smoking
Non-smoker 55 4�1 1�0 –
Ex-smoker 11 3�8 0�8 0�4–1�7
Current smoker 27 6�5 1�6 1�0–2�5
Father smoking
Non-smoker 40 4�4 1�0 –
Ex-smoker 25 5�1 1�3 0�8–2�1
Current smoker 32 4�9 1�2 0�7–1�9
Persistent cough or phlegm Parents smoking
Non-smokers 26 3�3 1�0 –
Ex-smokers 5 4�7 1�4 0�5–3�7
At least one smoker 36 4�4 1�3 0�8–2�2
Mother smoking
Non-smoker 38 2�8 1�0 –
Ex-smoker 13 4�5 1�7 0�9–3�2
Current smoker 24 5�8 2�1 1�3–3�6
Father smoking
Non-smoker 31 3�4 1�0 –
Ex-smoker 15 3�1 0�9 0�5–1�6
Current smoker 28 4�3 1�2 0�7–2�1
a Per cent of children with respiratory disorders (by disorder indicated), which indicates prevalence�
Table 72. Prevalence and OR of childhood respiratory disorders: traffic pollution
Respiratory disorders and traffic Number of children Per cent a OR 95% CI Wheezing last 12 months
Traffic intensity
Absent 34 11�3 1�0 –
Low 92 10�5 0�9 0�6–1�4
Moderate 86 11�1 1�0 0�7–1�6
Intense 27 9�9 0�8 0�5–1�4
Regularity of trucks
Never 73 10�2 1�0 –
Seldom 113 11�1 1�1 0�8–1�5
Frequently 45 11�4 1�1 0�8–1�7
Continuously 8 8�9 0�9 0�4–1�9
Asthma ever Traffic intensity
Absent 25 8�3 1�0 –
Low 68 7�8 0�9 0�6–1�5
Moderate 55 7�1 0�9 0�5–1�4
Intense 19 6�9 0�8 0�4–1�6
Regularity of trucks
Never 59 8�3 1�00 –
Seldom 73 7�2 0�9 0�6–1�2
Frequently 27 6�8 0�8 0�5–1�3
Continuously 8 8�9 1�1 0�5–2�4
Persistent cough or phlegm Traffic intensity
Absent 9 3�0 1�0 –
Low 36 4�1 1�5 0�7–3�1
Moderate 18 2�3 0�9 0�4–2�0
Intense 17 6�2 2�3 1�0–5�3
Regularity of trucks
Never 27 3�8 1�0 –
Seldom 34 3�3 0�8 0�5–1�4
Frequently 11 2�8 0�8 0�4–1�6
Continuously 10 11�1 3�1 1�4–6�7
a Per cent of children with respiratory disorders (by disorder indicated), which indicates prevalence�
Table 73. Prevalence and OR of childhood respiratory disorders: mould or dampness
Respiratory disorders and mould or dampness Number of children Per cent a OR 95% CI Wheezing last 12 months
Never 160 9�9 1�0 –
Only current 36 14�3 1�5 1�0–2�3
In the first year of life 23 10�4 1�0 0�6–1�6
Always 19 11�4 1�8 1�1–3�0
Current asthma
Never 465 28�8 1�0 –
Only current 111 44�2 1�9 1�4–2�5
In the first year of life 72 32�4 1�2 0�8–1�6
Always 44 26�5 1�5 1�0–2�2
Persistent cough or phlegm
Never 56 3�5 1�0 –
Only current 14 5�6 1�5 0�8–2�9
In the first year of life 12 5�4 1�5 0�8–3�0
Always 1 0�6 0�2 0�0–1�5
a Per cent of children with respiratory disorders (by disorder indicated), which indicates prevalence�
Social inequalities clearly emerged from the survey. The prevalence of persistent cough or phlegm was higher among children whose parents were blue collar workers or had a lower level of education (Tables 74 and 75). The percentage of asthma hospital admissions for children with a father who was a blue collar worker was 3.5%, in contrast to 1.9% among children with no blue collar father. This did not correspond to a greater severity of the disease: 74% of asthmatic children with their father classified as executive for his job were diagnosed as having severe asthma, in contrast to 50% among other asthmatic children.
Table 74. Prevalence and OR of childhood respiratory disorders: parents’ work
Respiratory disorders and parents’ occupational category Number of parents Per cent a OR 95% CI Wheezing last 12 months
Executive 35 13�6 1�0 –
High-ranking white collar 50 9�6 0�7 0�4–1�1
Low-ranking white collar 11 7�9 0�6 0�3–1�1
Blue collar 90 11�2 0�8 0�5–1�2
Asthma ever
Executive 19 7�4 1�0 –
High-ranking white collar 38 7�3 1�0 0�6–1�9
Low-ranking white collar 9 6�4 0�9 0�4–2�0
Blue collar 75 9�4 1�3 0�8–2�2
Persistent cough or phlegm
Executive 5 1�9 1�00 –
High-ranking white collar 14 2�7 1�4 0�5–3�9
Low-ranking white collar 5 3�6 1�8 0�5–6�5
Blue collar 40 5�0 2�6 1�0–6�7
a Per cent of children with respiratory disorders (by disorder indicated), which indicates prevalence�
Table 75. Prevalence and OR of childhood respiratory disorders: parents’ education
Respiratory disorders and number of years of parents’
education Number of
parents Per cent a OR 95% CI
Wheezing last 12 months
>14 52 13�3 1�0 –
14 120 10�2 0�7 0�5–1�0
9 62 10�3 0�8 0�5–1�1
6 5 9�3 0�8 0�3–2�0
Asthma ever
>14 31 7�9 1�0 –
14 91 7�8 0�9 0�6–1�4
9 42 7�0 0�8 0�5–1�3
6 3 5�6 0�7 0�2–2�5
Persistent cough or phlegm
>14 7 1�8 1�0 –
14 47 4�0 2�3 1�0–5�0
9 27 4�5 2�4 1�0–5�6
6 2 3�7 2�2 0�4–11�2
a Per cent of children with respiratory disorders (by disorder indicated), which indicates prevalence�
Minor findings include the observation of a higher prevalence of wheezing during the last 12 months and persistent cough or phlegm among children participating in physical activities more than three times a week, in contrast to no such activity (Table 76). Also, a high body mass index (BMI) was associated with a higher prevalence of respiratory symptoms. Children with a BMI above the 80th percentile (BMI of 20.9 in this population) showed a higher prevalence of wheezing during the last 12 months (OR: 1.4; 95% CI: 0.9–2.2); a higher prevalence of asthma ever (OR: 1.8; 95% CI: 1.0–3.1); and a higher prevalence of persistent cough or phlegm (OR: 2.1; 95% CI: 0.9–4.6), all in contrast to children in the lowest quintile of BMI (Table 77).
Table 76. Prevalence and OR of childhood respiratory disorders: activity level
Respiratory disorders and level of physical activity Number of children Per cent a OR 95% CI Wheezing last 12 months
Never 41 9�6 1�0 –
Occasionally 72 10�3 1�1 0�7–1�7
1–2 times per week 76 11�0 1�2 0�8–1�8
More than 3 times a week 37 11�1 1�2 0�8–2�0
Asthma ever
Never 28 6�6 1�0 –
Occasionally 56 8�0 1�2 0�7–1�9
1–2 times per week 56 8�1 1�2 0�7–1�9
More than 3 times a week 22 6�6 1�0 0�5–1�7
Persistent cough or phlegm
Never 13 3�1 1�0 –
Occasionally 21 3�0 1�3 0�6–2�7
1–2 times per week 33 4�8 2�2 1�1–4�3
More than 3 times a week 16 4�8 2�2 1�0–4�7
a Per cent of children with respiratory disorders (by disorder indicated), which indicates prevalence�
Table 77. Prevalence and OR of childhood respiratory disorders: child’s BMI
Respiratory disorders and BMI (quintiles) Quintile Number of children Per cent a OR 95% CI Wheezing last 12 months
≤15�3 1st 41 10�5 1�0 –
>15�3–16�6 2nd 43 11�1 1�0 0�6–1�6
>16�6–18�4 3rd 38 9�7 0�9 0�6–1�4
>18�4–20�8 4th 32 8�2 0�8 0�5–1�3
>20�8 5th 51 13�0 1�4 0�9–2�2
Asthma ever
≤15�3 1st 22 5�6 1�0 –
>15�3–16�6 2nd 28 7�3 1�2 0�6–2�1
>16�6–18�4 3rd 28 7�1 1�1 0�6–2�0
>18�4–20�8 4th 26 6�7 1�0 0�6–1�9
>20�8 5th 42 10�7 1�8 1�0–3�1
Persistent cough or phlegm
≤15�3 1st 10 2�6 1�0 –
>15�3–16�6 2nd 16 4�1 1�6 0�7–3�6
>16�6–18�4 3rd 14 3�6 1�5 0�6–3�4
>18�4–20�8 4th 11 2�8 1�1 0�5–2�8
>20�8 5th 19 4�8 2�1 0�9–4�6
a Per cent of children with respiratory disorders (by disorder indicated), which indicates prevalence�
Discussion: the cross-sectional study
We compared the results of the cross-sectional study with those of the SIDRIA-2 project (Galassi, Battista
& Forastiere, 2005) (Table 78). The comparison can be done only by considering children 6–7 years old.
The prevalence of wheezing in the last 12 months was higher than that recorded in the SIDRIA-2 project in 2002: on average 11% versus 8%. The prevalence of known risk factors was somewhat similar to that re-corded in the SIDRIA-2 project (Table 79). In the Milazzo–Valle del Mela study, the distribution of the oc-cupations of parents was different, and the number of housewives was particularly high. It is worth noting that the prevalence of children exposed to indoor (passive) smoking and outdoor (traffic) pollutants in the Milazzo–Valle del Mela study was lower; housing conditions (mould and dampness), however, appeared similar for children 6–7 years old, but worse for children 8 years or older (Table 70). The prevalence of chil-dren with BMI above the 95th percentile of the reference distribution (SIDRIA-2) was greater than 13%.
Table 78. Prevalence of childhood respiratory disorders: study comparison
Respiratory disorders and
gender Children 6–7 years of age
Milazzo–Valle del Mela study SIDRIA-2 study
Number Per cent a Per cent a 95% CI
Wheezing last 12 months
Boys 47 11�7 9�5 8�7–10�2
Girls 38 9�7 7�2 6�4– 7�9
Asthma ever
Boys 33 8�2 11�1 10�1–12�2
Girls 11 2�8 7�3 6�6–8�1
a Per cent of children with respiratory disorders (by disorder indicated), which indicates the prevalence�
Table 79. Prevalence of childhood respiratory disorder risk factors: study comparison
Risk factor and category Children 6–7 years of age
Milazzo–Valle del Mela study SIDRIA-2 study
Number Per cent a Per cent a 95% CI
Mother
Education: 14 years or more 488 61�5 61�8 59�3–64�4
Employed 325 41�0 62�9 60�2–65�7
Housewife 324 40�9 26�1 23�9–28�3
Father
Education: 14 years or more 422 53�2 56�1 53�0–59�1
Employed 700 88�3 91�1 89�8–92�3
Physical activity
Sedentary 61 7�7 7�0 6�4–7�6
Intense physical activity more than once a week 338 42�6 42�5 40�8–44�2
Smoking
Mother current smoker 149 18�8 27�4 26�3–28�4
Mother smoker during pregnancy – 6�9 12�5 11�8–13�2
Father current smoker 244 30�8 35�7 34�7–36�6
Mother and father current smokers – 11�6 16�1 15�4–16�8
At least one parent current smoker – 38�0 46�9 45�7–48�2
Traffic intensity
Absent 115 14�5 13�8 11�9–15�6
Small to moderate 569 71�8 64�3 62�1–66�5
Intense 99 12�5 20�2 16�9–23�5
High regularity of:
Cars 489 38�8 59�0 55�8–62�1
Trucks 154 12�2 20�0 18�1–22�0
Mould or dampness in child’s room
During the first year of life 121 9�6 12�6 –
Current 127 10�1 10�5 –
Both 39 3�1 – –
a Per cent of children with respiratory disorders (by risk factor), which indicates the prevalence�
In comparison with the SIDRIA-2 study, the Milazzo–Valle del Mela study reported evidence of under-diagnosis: the higher prevalence of wheezing was associated with a lower prevalence of diagnosed asthma (Table 78). We also observed a higher hospitalization rate among children of lower social classes, which is not explained by the greater severity of the disease. Moreover, the prevalence of bronchitis symptoms (persistent cough or phlegm) was higher among children of lower social classes (parents education less than 6 years compared with more than 14 years: OR = 3.6 versus 1.8 in the SIDRIA-2 study) and among children with greater exposure to the outdoor environment, through physical activity (more than three times a week, in contrast to no such activity: OR = 2.2. versus 0.9 in the SIDRIA-2 study), traffic intensity (high versus low: OR = 2.3 versus 1.2 in the SIDRIA-2 study) and regularity of trucks (intense versus not (intense): OR = 3.1 versus 1.8 in the SIDRIA-2 study) (Table 80). The prevalence ORs for other known risk factors were almost identical to those documented in the SIDRIA-2 project (Table 80).
Table 80. Prevalence and ORs of childhood respiratory disorders: comparative study – selected risk factors
Table 80. Prevalence and ORs of childhood respiratory disorders: comparative study – selected risk factors