ORIGINAL PAPER

Influence of outdoor temperature and humidityon the methacholine challenge test

Bruno Sposato • Marco Scalese •

Andrea Pammolli • Carlo Pareo • Raffaele Scala

Received: 21 February 2012 / Accepted: 18 July 2012 / Published online: 1 August 2012

� Springer Science+Business Media B.V. 2012

Abstract Objective of this study was to evaluate

whether outdoor temperature and humidity can influ-

ence methacholine test results in outpatients living in

temperate areas. 4,723 subjects (2,391 males; age:

35.1 ± 16.15; FEV1 = 100.36 % [relative interquar-

tile range (IQR):92.34–108.8]) that performed metha-

choline tests for suspected asthma between 2000 and

2010 were considered. Outdoor minimum, mean, and

maximum temperature values (�C), relative humidity

(%), and dew point (Tdp), registered when performing

the tests, were examined. Airways hyperresponsive

patients, with PD20 (provocative dose to obtain a 20 %

fall in FEV1) \3,200 lg were 2,889 (61.2 %) and

median PD20 was 359 lg [IQR:160-967]. On receiving

operating curve (ROC) analysis, temperature, humidity,

and Tdp did not significantly predict airways hyperre-

sponsiveness (AHR), even using a 200, 800, and

3,200 lg cutoffs to identify AHR. When subjects were

subdivided into subgroups, according to different levels

of temperature, humidity, and dew point, no differences

in PD20 and prevalence were found. Only a higher

number of hyperresponsive subjects was detected in

smokers when they were tested in hot and humid

conditions. A weak but significantly positive relation-

ship between PD20 and mean, maximum, and minimum

temperatures was detected in severe hyperresponsive

subjects (PD20 \ 200 lg) (r = 0.100, 0.112, 0.110,

respectively; p = 0.001). The regression logistic model

showed that maximum temperature was a significantly

protective factor for AHR (OR:0.995, 95 % CI:

0.982–0.998; p = 0.012) especially in severe hyperre-

sponsive subjects (OR:0.988, 95 % CI: 0.977–0.999;

p = 0.035). In conclusion, weather conditions do not

seem to influence PD20 values obtained with metha-

choline tests in real life. Hot and humid environments

may increase the prevalence of AHR in smokers while a

temperature increase may reduce the AHR risk espe-

cially in severe hyperresponsive subjects.

This article was presented at Amsterdam 2011 Congress of

European Respiratory Society as Poster presentation (number

P4049) in Thematic Poster Session on 09/27/2011 and

published only as an Abstract in Abstract book: Eur Respir J

2011; 38: Suppl. 55, 739 s. However, this manuscript has never

been submitted in this form for publication elsewhere. The

authors alone are responsible for the contents and writing of the

paper.

B. Sposato (&)

Unit of Pneumology, ‘‘Misericordia’’ Hospital,

Via Senese 161, 58100 Grosseto, Italy

e-mail: bsposat@tin.it

M. Scalese

Institute of Clinical Physiology, National Research

Council (CNR), Pisa, Italy

A. Pammolli

Department of Physiopathology, Experimental Medicine

and Public Health University of Siena, Siena, Italy

C. Pareo

Unit of Pneumology, ‘‘Carlo Urbani’’ Hospital, Jesi, Italy

R. Scala

Unit of Pneumology and UTIP, ‘‘S.Donato’’ Hospital,

Arezzo, Italy

123

Aerobiologia (2013) 29:187–200

DOI 10.1007/s10453-012-9272-0

Keywords Airway hyperresponsiveness �Temperature �Humidity �Methacholine test �Asthma �Environment

1 Introduction

Asthma is a chronic inflammatory disease of the

airways characterized by bronchial obstruction, often

reversible either spontaneously or with treatment. It is

also characterized by airways hyperresponsiveness

(AHR) that can be defined as an exaggerated airways

obstructive response to a variety of pharmacological,

chemical, and physical stimuli (histamine, methacho-

line, cold air, etc.) (ATS 2000). In subjects with

suspected symptoms of asthma and a normal baseline

spirometry without a significant increase in lung

function after inhaling bronchodilators, it is often

necessary to perform a methacholine challenge test to

detect AHR and therefore to confirm a diagnosis of

asthma. In case the provocative dose or concentration

(PD20 or PC20) of methacholine required to obtain a

20 % fall in forced expiratory volume in one second

(FEV1) is lower after the test, the possibility that the

suggestive symptoms may be due to asthma is high,

whereas this probability is low if PD20 or PC20 values

are higher (ATS 2000). AHR seems to be character-

ized by seasonal variations according to the changes in

seasonal exposition to various allergens (pollens and

house dust mites) (Tilles and Bardana 1997). In fact, a

higher exposure to house dust mites in autumn, when

they increase in number, or to a greater quantity of

pollens in spring, seems to increase AHR in subjects

with rhinitis or asthma (Riccioni et al. 2001; van der

Heide et al. 1997; Beier et al. 2003). Also, respiratory

infections, especially in cold seasons, might increase

hyperresponsiveness in asthmatics (Busse 1990), thus

influencing AHR variability.

On the contrary, it is not clear whether temperature

and humidity may have a direct influence on AHR.

Extreme values of temperature and humidity and a

prolonged exposure to them may determine AHR

variations (Helenius et al. 1996; Langdeau et al. 2000;

Bougalt et al. 2010). In fact, some studies highlighted

how AHR prevalence, induced by methacholine, was

higher in athletes that inhaled cold and humid air during

training in comparison with those that performed

training in environments with either dry air or a mixture

of dry and humid air (Hemingson et al. 2004; Langdeau

et al. 2000; Bougalt et al. 2010). Furthermore, very high

and very low values of humidity (95 %) and temper-

ature (-18 �C), respectively, can increase exercise-

induced bronchoconstriction (Stensrud et al. 2006,

2007). However, these conclusions were drawn after

studying athletes and not common people; furthermore,

these subjects were often studied only in extreme

environmental conditions, and sometimes, results were

obtained in artificial indoor environments and only with

exercise challenge testing. On the other hand, a non-

extreme temperature and humidity seem to influence

weakly exercise-induced AHR (Koh and Choi 2002)

but not methacholine- or histamine-induced AHR (Koh

and Choi 2002; Schmidt and Bundgaard 1986; Tessier

et al. 1988) in subjects with asthma who are not athletes.

However, these studies were carried out on few patients

and therefore there are still doubts whether exposure to

normal range of outdoor temperature and humidity,

which alternate during the seasons, may influence

AHR. Especially, we do not know if a methacholine

challenge test results may be differently influenced by a

higher or lower value of environmental outdoor tem-

perature and/or humidity to which a subject is exposed

before the test. Therefore, the aim of this study was to

evaluate whether the results of a methacholine chal-

lenge test can be influenced by different daily outdoor

temperature and humidity values when the test is

performed on a large number of outpatients living in

temperate climates where temperature and humidity

never reach extreme values.

2 Materials and methods

2.1 Study design and subjects

For this retrospective study, we took out from the

spirometer data files of our pneumology departments

of Grosseto and Arezzo (Tuscany, Italy) and analyzed

the results of 5,023 consecutive methacholine chal-

lenge tests performed between 2000 and 2010. All

tests were carried out to confirm or exclude an asthma

diagnosis. In fact, all patients had suspected asthma

symptoms (unexplained episodes of cough and/or

wheezing and/or dyspnea) with a normal spirometry

and therefore, for this reason, they were subjected to a

methacholine challenge test. For every test, FEV1,

FEV1/FVC, forced vital capacity (FVC), PD20FEV1,

smoking habits, and body mass index (BMI) were

188 Aerobiologia (2013) 29:187–200

123

considered. Also, minimum, medium, and maximum

values of temperature (T), relative humidity (H), and

temperature dew point (Tdp), measured on the days

when the tests were performed, were also taken into

account. The purpose was to relate T, H, and Tdp with

the results of the methacholine tests measured on the

same date.

Only 4,723 consecutive subjects (2,391 M; mean

age 35.1 ± 16.17; median FEV1 % 100.36 [IQR:92.24–

108.75] and FEV1/FVC 86.33 [IQR:81.5–90.88])

were suitable for the study. Three hundred subjects

were excluded. Most of them had not completed the

challenge: some were intolerant to testing and others

had interrupted the test because they had shown a fall

in FEV1 [ 10 % with buffer solution. One hundred

and three subjects were not considered because the

temperature and humidity on the day when the test was

carried out were not known. Only the first challenge of

those few who had repeated the test several times was

taken into consideration.

These subjects were subdivided into subgroups on

the basis of the PD20 value, sex, age, smoking habits,

and BMI, in order to evaluate possible effects of

temperature and humidity on the above said catego-

ries. Unfortunately, allergic sensitizations in the

subjects recruited for this study were not recorded

and therefore these were not available. BMI value of

25 was used as a cutoff to subdivide subjects with

normal weight or underweight (BMI \ 25) from

overweight or obese subjects (BMI [ 25). Interna-

tional cutoff points for BMI, to assess overweight and

obese children, were used to subdivide subjects with

age\18 years into underweight normal or overweight

obese (Cole et al. 2000).

The methacholine test was put off for at least 4 weeks

when subjects had shown an exacerbation of symptoms

or an airway infection. B2-agonist bronchodilators were

not taken 24 h before the test, whereas inhaled or

systemic corticosteroids were suspended 3 weeks

before performing it. Antihistamines were also sus-

pended at least 10 days before the challenge test. The

use of the data recorded in each spirometer, which were

necessary for this study and its protocol, was approved

by the local ethical committees.

2.2 Methacholine challenge testing

The challenge test was performed by using a dosimeter

method (Chai et al. 1975). The same kind of

instrument and method was used in Grosseto and

Arezzo from 2000 to 2010. Methacholine sulfate was

provided by Lofarma (Milan, Italy) and administered

in aerosol form using an MEFAR MB3 dosimeter

(output: 9 ll/puff; MEFAR Elettromedicali Brescia,

Italy) with an MB2 ampoule model. Buffer and

methacholine were diluted with distilled water and

then two different progressive methacholine solutions

were prepared for the test: an ampoule with a

methacholine concentration of 4 mg/ml (40 lg inha-

lation dose) and another with a concentration of

40 mg/ml (400 lg inhalation dose). The buffer solu-

tion was administered first, followed by 40 lg of

methacholine, increasing the doses step by step until

PD20FEV1 was obtained or until the maximum dose of

muscarinic agonist was reached. FEV1 was measured

after administering 40, 80, 120, 240, 400, 800, 1,600,

2,400, and 3,200 lg of cumulative methacholine

doses. At the end of exhalation during tidal breathing,

patients inhaled methacholine slowly and deeply from

the nebulizer in 5 s and then held their breaths for 5

more seconds. The test was interrupted if a fall in

FEV1 [ 10 % was obtained with the buffer solution.

The time interval between the two steps was 2 min,

calculated from the start of one step to the next. FEV1

was measured at 30 and 90 s after nebulization. An

acceptable quality FEV1 was obtained at each step. No

more than two maneuvers after each dose were

performed and the highest FEV1 value was taken into

account. AHR was defined by a 20 % fall in FEV1

following a challenge test with a cumulative metha-

choline dose\3,200 lg. Subjects who did not achieve

a 20 % fall in FEV1 with a methacholine dose of

3,200 lg were considered normal.

All AHR subjects with PD20 B 200, 200 \ PD20 B

800, and PD20 [ 800 were arbitrarily considered

affected by severe, moderate, and mild AHR with

the purpose of evaluating the effects of temperature

and humidity on the different levels of AHR.

FEV1 was measured before and during the chal-

lenge test using a spirometer HP 47120E Pulmonary

System Desk (Hewlett Packard, Waltham, Massachu-

setts, USA). PD20 FEV1 was calculated by linear

interpolation of the dose–response curves. The FEV1

measured before inhaling the buffer solution was

considered as the baseline value, whereas the FEV1

measured after the buffer solution was used as the

referral to calculate FEV1 decrease and thus the PD20

value. FEV1 and FVC were expressed as percentages of

Aerobiologia (2013) 29:187–200 189

123

the predicted value, whereas FEV1/FVC was reported

only as a ratio (reference equation: CECA, 1971).

2.3 Assessing temperature and humidity values

Data concerning daily temperature, relative humidity,

and Tdp observed between 2000 and 2010 were

measured in the Italian Air Force meteorological

stations of Grosseto (coordinate: WMO 16206; ICAO

LIRS; LAT 42.75; LON 11.07; H 7m) and Arezzo

(coordinate: WMO 16172; ICAO LIQB; LAT 43.47;

LON 11.85; H 249m) airports. All data were kindly

provided by the Meteorology National Centre of the

Italian Air Force where they were recorded (Airport

‘‘M. DE BERNARDI’’, Pratica di Mare, Pomezia,

ROME; http//www.meteoam.it). Temperature and Tdp

were considered in �C, whereas relative humidity was

in percentage. Data concerning temperature, humidity,

and Tdp, recorded on that particular day, were associ-

ated to the methacholine test results performed on the

same date. We considered the daily average, minimum

and maximum temperatures, relative humidity, and Tdp

values on each day the test was performed. With the

purpose of evaluating the combined effects of tem-

perature and relative humidity on hyperresponsiveness

prevalence and PD20, different arbitrary mean levels of

temperature and humidity (T B 10 �C, T [ 10 �C and

B20 �C, T [ 20 �C; H B 60 %, H [ 60 % and

B80 %, H [ 80 %) were used to subdivide subjects

into subgroups. Also, for Tdp, different arbitrary cutoff

values were used to assess a probable influence on the

prevalence of AHR and PD20 (Tdp B 5 �C, Tdp [ 5

and B12 �C and Tdp [ 12 �C).

2.4 Statistical analysis

Categorical variables are expressed as percentages.

Continuous variables that had a normal distribution

are expressed as mean values, accompanied by their

standard deviations. All continuous variables that had

a non-normal distribution are expressed as median

values, accompanied by their relative interquartile

range (IQR—25� and 75� quartiles). Comparisons

between groups were made with the chi-square and

Kruskal–Wallis tests, where appropriate. Associations

between continuous variables are expressed as Pear-

son correlations.

The influence of temperature, humidity, and Tdp

was assessed by the receiving operating curve (ROC),

being the area under the curve equal to the probability

to discriminate from the risk of being or not being

hyperresponsive, identified by three different cutoffs

(\ or [3200, \ or [800, \ or [200 lg).

Logistic binary regression models were performed

to evaluate whether minimum, medium, and maxi-

mum values of temperature, relative humidity, and

Tdp, corrected for age, sex, smoking habits, BMI, and

FEV1, can be independent risk factors for AHR

(transformed into dichotomic variables with

3,200 lg as cutoff of normality status). Odd ratios of

temperature, humidity, and Tdp in the different AHR

levels (severe, moderate, and mild) compared with

normal subjects were also calculated. Logistic regres-

sion models were used only for those subjects whose

smoking history was known (4,169 subjects). p values

less than 0.05 were considered statistically significant.

Statistical analyses were performed using an SPSS v13

(SPSS Inc, Chicago, USA) software.

3 Results

The subjects’ characteristics are shown in Table 1.

The monthly averages of temperature, relative humid-

ity, and Tdp measured between 2000 and 2010 are

shown in Fig. 1.

Receiving operating curve (ROC) analysis high-

lighted that minimum, mean, and maximum values of

temperature, humidity, and Tdp were similar in hyper-

responsive and in non-hyperresponsive subjects (AUC

between 0.46 and 0.52) using three different cutoffs of

normality to identify AHR: 3,200, 800, and 200 lg

(data not shown in tables or figures for absence of any

statistical significance).

No meaningful relationships (Pearson correlation)

between PD20, temperature, and humidity were found

when the subjects were considered as a whole. No

relationships were also found in males, females,

smokers, non-smokers, normal weight/underweight

and overweight/obese subjects, and in those aged B20

and between 20 and 35 years. In subjects aged from 36

to 51, a weak positive but significant relationship was

found between PD20 and minimum, maximum, and

mean temperatures (r = 0.072, 0.081, and 0.079,

respectively; p \ 0.05), whereas in subjects aged

[52 years a significant relationship was found only

with maximum temperature (r = 0.093; p \ 0.05).

When we considered separately subjects with mild,

190 Aerobiologia (2013) 29:187–200

123

moderate, and severe AHR, only the latter (with a

PD20 \ 200 lg) showed significant relationships

between PD20 and Tmin, Tmax, Tmean, Hmin,

Tdpmax, and Tdpmean (r = 0.100, 0.112, 0.110,

0.066, 0.068, 0.081, and 0.095, respectively;

p \ 0.001 for the first three and p \ 0.05 for the

others) (data not shown in tables or figures).

AHR prevalence (defined by a PD20 \ 3,200 lg)

was similar in subjects that performed the tests in

different combined levels of temperature/humidity

and Tdp when subjects were considered as a whole

(Figs. 2, 3). On the contrary, when subjects were

divided into different categories, a higher prevalence

of AHR was found in smokers that performed the tests

when mean temperature was [20 �C and humidity

[80 % rather than when the levels of temperature and

humidity were lower. No other differences in AHR

prevalence for other subgroups were found in the

different combinations of temperature and humidity

and Tdp (Figs. 2, 3). In addition, no differences in PD20

were found in different conditions of temperature/

humidity and Tdp when the test was performed

(Tables 2, 3), except for subjects aged between 35

and 51 and in those with mild AHR, where PD20 was

higher when the tests were performed in weather

conditions with dew point values [12 �C (Table 3;

Fig. 4).

Although 3 logistic regression models were applied

(one for Tmin, Tmax, and Tmean, one for Hmin,

Hmax, and Hmean, and one for Tdpmin, Tdpmax, and

Tdpmean), the odd ratio was the same for age, sex,

FEV1, smoking habits, and BMI (Table 4). The

logistic regression model (Table 4) showed a signif-

icantly higher AHR risk in females (OR: 1.567;

p = 0.0001), smokers (OR: 1.249; p = 0.008), and

overweight or obese subjects (OR: 1.220; p = 0.006),

whereas age and FEV1 % were protective factors. In

fact, increasing their values, the risk of being hyper-

responsive decreased. The logistic regression models

showed that maximum temperature was a protection

factor for AHR (OR: 0.990, 95 %CI: 0.982–0.998;

p = 0.012). When the logistic regression model was

applied to mild, moderate, and severe hyperrespon-

sive subjects (compared with normal subjects), only in

Table 1 Subjects’ characteristics

No of subjects (M/F) 4723 (2,391/2,332)

Age 35.1 [±16.15]

*Smokers 820 (20.2 %)

*Ex-smokers 282 (7.0 %)

Subjects with PD20 [ 3200 lg 1834 (38.8 %)

PD20(lg) 359.0 [160.0–967.0]

Patients with PD20 \ 3200 lg 2889 (61.2 %)

FVC % 98.90 [90.87–107.48]

FEV1 % 100.36 [92.34–108.80]

FEV1/FVC % 86.34 [81.48–90.89]

BMI 24.67 (±4.74)

The continuous variables are median with relative interquartile

range [IQR] or mean with standard deviation (±SD) and

categorical values are expressed as number of cases

(percentage)

BMI body mass index; FEV1 forced expiratory volume in one

second; FVC forced vital capacity; FEF25–75 forced expiratory

flow between 25 and 75 % of vital capacity; PD20 provocative

dose to obtain a 20 % fall in FEV1

* Valuated on 4,053 patients

Fig. 1 Monthly average of minimum, maximum, and mean temperature (a), humidity (b), and dew point (c) measured from 2000 to

2010. T temperature (�C); H humidity (%); Tdp dew point (�C); min minimum; max maximum; �C degrees centigrade

Aerobiologia (2013) 29:187–200 191

123

Fig. 2 Prevalence of subjects (%) with AHR (identified with a

normality cutoff of 3,200 lg) that performed the test in the

different levels of temperature and humidity taken into account

(T B 10 �C, T [ 10 �C and B 20 �C, T [ 20 �C; H B 60 %,

H [ 60 % and B 80 %, H [ 80 %). AHR airway hyperrespon-

siveness; T temperature (�C); H humidity (%); �C degrees

centigrade

192 Aerobiologia (2013) 29:187–200

123

Fig. 3 Prevalence of subjects (%) with AHR (identified with a

normal 3,200 lg cutoff) that performed the test in the different

levels of dew points (Tdp) taken into account (Tdp B 5 �C,

Tdp [ 5 and B12 �C and Tdp [ 12 �C). AHR airway hyperre-

sponsiveness; Tdp dew point (�C); �C degrees centigrade

Aerobiologia (2013) 29:187–200 193

123

Table 2 Median [IQR] values of PD20 in different conditions of outdoor temperature and humidity in the various categories of

subjects taken into consideration

H B 60 % H [ 60 %

and B 80 %

H [ 80 % p

Total n. 2,889 Mean

T �C

B10 341.5 [114–776] 370 [165–973] 357 [157–1,050] 0.903

[10

and B 20

340.5 [156–922] 367 [164–987] 390 [160–934]

[20 330 [173–963] 357 [161–941] 263.5 [82–874.5]

Males n. 1,404 Mean

T �C

B10 327 [114–921] 318.5 [163–836] 367 [148–1,060] 0.482

[10

and B 20

327 [178–928] 357 [167–897] 409 [161–985]

[20 340 [174–1,015] 332.5 [133–770] 64 [60–168]

Females n. 1,485 Mean

T �C

B10 350 [115–767] 433 [165–1,011] 347.5 [157–1,029] 0.710

[10

and B 20

347 [143–890] 408 [160–1,072] 384 [159–916]

[20 317 [173–886] 389 [197–1,115] 419 [117–1,695]

Non-smokers n. 1,909 Mean

T �C

B10 316.5 [110–821] 364 [158–851] 355.5 [149–1,041] 0.684

[10

and B 20

403 [166–1,063] 360 [164–986] 405 [160–985]

[20 320 [164–1,051] 382.5 [184–943] 238 [67–1,274]

Smokers n. 539 Mean

T �C

\10 513 [252–921] 383 [198–1,011] 449 [218–1,060] 0.779

10–20 336.5 [170–846] 491 [171–1,041] 407 [141–735]

[20 333.5 [187–671] 493 [197–1,111] 404 [132–769]

Underweight/normal weight n.

1,676

Mean

T �C

\10 373.5 [138–891] 436 [175–1,046] 330 [175–1,016] 0.976

10–20 349 [180–930] 426 [155–987] 437 [142–945]

[20 344 [142–1,123] 346.5 [148–840] 640 [117–1,905]

Overweight/obese n. 1,213 Mean

T �C

\10 299 [106–714] 327 [151–729] 372 [133–1,121] 0.241

10–20 280 [149–823] 350.5 [170–987] 354 [172–934]

[20 315 [187–628] 382 [178–943] 153 [64–359]

Age B20 years n. 671 Mean

T �C

\10 396 [190–769] 378 [198–882] 336 [189–943] 0.316

10–20 216 [136–616] 317 [115–722] 562 [198–1,032]

[20 321 [130–1,020] 310 [128–816] 153 [60–419]

Age [20 and B35 years n. 984 Mean

T �C

\10 348 [87–1,030] 366 [158–981] 470.5 [144–1,175] 0.423

10–20 352 [177–957] 429.5 [160–1,003] 312 [117–652]

[20 293 [159–894] 327 [143–917] 640 [168–897]

Age [36 and B51 years n. 742 Mean

T �C

\10 306 [100–646] 298 [131–1,007] 320 [190–672] 0.196

10–20 582 [191–922] 369 [189–1,083] 364 [141–1,183]

[20 487 [194–1,255] 517 [192–1,115] 359 [117–852]

Age [51 years n. 552 Mean

T �C

\10 336 [166–1,014] 447.5 [277–762] 577 [130–1,258] 0.296

10–20 473.5 [156–1,348] 434 [197–1,163] 594 [320–1,248]

[20 340 [187–621] 361.5 [198–694] 95 [95–95]

Severe AHR n. 905 Mean

T �C

\10 80 [52–114] 97 [46–151] 88 [55–140] 0.065

10–20 115 [56–156] 100 [62–150] 98 [56–155]

[20 119.5 [67–165] 105 [70–148] 82 [62–135]

Moderate AHR n. 1145 Mean

T �C

\10 363 [288–570] 378 [298–551] 347.5 [264–522] 0.085

10–20 349 [280–553] 367 [302–557] 437 [311–621]

[20 349.5 [250–532] 377 [291–626] 419 [359–640]

194 Aerobiologia (2013) 29:187–200

123

the latter maximum temperature was a protection

factor for AHR (OR: 0.988, 95 %CI: 0.977–0.999;

p = 0.035) (Table 4).

4 Discussion

According to our study, performing the test in different

conditions of temperature and humidity does not seem

to significantly influence results in PD20 values in the

various categories of the subjects considered. A higher

temperature associated to an elevated level of humid-

ity may promote a greater prevalence of AHR in

smokers. On the whole, however, the temperature

increase may be a protective factor for AHR.

Similarly, also other studies, although carried out on

a lower number of subjects, did not find any differences

in airway responsiveness, detected by histamine or

methacholine challenge tests, with different conditions

of temperature and humidity (Koh and Choi 2002;

Arantes-Costa et al. 2002; Schmidt and Bundgaard

1986). This poor direct outdoor environmental influ-

ence of temperature and humidity on PD20 may be

simply due to the fact that seasonal alternation of

‘‘normal’’ range of temperature and humidity does not

significantly influence airway hyperresponsiveness. In

fact, temperature levels rarely reach extreme values in

our temperate climate where the study was carried out

and where people are accustomed to ‘‘normal’’

humidity and temperature ranges. Only prolonged

exposures to extreme values of temperature and

humidity (as in the case of swimmers and winter sport

athletes during their training) can increase the possi-

bility to find methacholine-induced airway hyperre-

sponsiveness (Hemingson et al. 2004; Helenius et al.

1996; Langdeau et al. 2000; Bougalt et al. 2010). There

are probably other factors that influence bronchial

hyperresponsiveness in common people who are not

Table 3 Median [IQR] values of PD20 obtained with different conditions of dew point (Tdp) in the various categories of subjects

taken into consideration

Tdp B 5 Tdp [ 5 and B 12 Tdp [ 12 p

Total 372 [157–981] 356 [165–942] 366 [159–1,007] 0.580

Males 343.5 [169–941] 350 [161–897] 350 [156–938] 0.864

Females 396 [149–986] 363 [166–984] 385 [169–1,115] 0.628

Non-smoking 352 [154–959] 357 [169–954] 376 [164–1,024] 0.407

Smoking 414.5 [198–973] 375 [171–986] 493 [180–1,132] 0.449

Underweight/normal weight 410 [170–986] 375.5 [158–983] 377 [148–1,060] 0.776

Overweight/obese 345.5 [151–943] 337 [170–930] 359 [172–942] 0.388

Age B20 years 336.5 [153–728] 319.5 [149–799] 335 [153–943] 0.684

Age [20 and B35 years 372 [157–981] 374 [160–977] 337.5 [137–897] 0.504

Age [35 and B51 years 335 [148–999] 327 [170–986] 517 [208–1,231] 0.012

Age [51 years 500 [217–1,267] 384 [195–1,040] 367 [175–891] 0.236

Severe AHR 92 [52–150] 97 [59–150] 110 [64–156] 0.065

Moderate AHR 374 [297–559] 360 [275–548] 382 [302–590] 0.052

Mild AHR 1,441 [1,055–2,015] 1,342 [1,070–1,962] 1,522.5 [1,153–2,188] 0.020

See legend of Tables 1 and 2 for the meaning of abbreviations

Statistically significant values are in bold

Table 2 continued

H B 60 % H [ 60 %

and B 80 %

H [ 80 % p

Mild AHR n. 839 Mean T �C \10 1,484 [1,101–2,113] 1,451 [1,057–1,994] 1,318 [1,058–1,877] 0.896

10–20 1,542.5 [1,020–1,979] 1,414.5 [1,060–2,101] 1,526 [1,172–2,086]

[20 1,370 [1,103–2,038] 1,446 [1,115–2,210] 1,695 [897–1,905]

T temperature; H humidity; AHR airway hyperresponsiveness; �C degrees centigrade; see Table 1 for other abbreviations

Aerobiologia (2013) 29:187–200 195

123

exposed to extreme environmental conditions like

athletes, that is, allergens and airways infections (Tilles

and Bardana 1997; Busse 1990) and not the normal

range of the temperature and the humidity.

This poor influence of normal range of temperature

and humidity on PD20 may be also due to some

limitations of this study. In fact, this may be due to the

fact that our patients are usually people who spend

most of their time in closed environments (home,

workplace, etc.) and, therefore, are not highly exposed

to outdoor temperature and humidity, especially in

cold seasons. Furthermore, they had enough time,

during their 10–30-min wait before the test was carried

out, to get used to the waiting room temperature and

humidity, which were always constant. This might

have hidden a more significant effect of temperature

and/or humidity on AHR. It should be also added that

the methacholine challenge test is probably not the

most suitable method to highlight the effects of

climate. In fact, different levels of temperature and

humidity did not influence the position of the dose–

response curve to methacholine in rats (Arantes-Costa

Fig. 4 Prevalence of subjects (%) with mild PD20 [ 800,

moderate (200 \ PD20 B 800), and severe (PD20 B 200) AHR

that performed the test in the different levels of temperature/

humidity (T B 10 �C, T [ 10 �C and B 20 �C, T [ 20 �C;

H B 60 %, H [ 60 % and B 80 %, H [ 80 %) and dew point

(Tdp) taken into account (Tdp B 5 �C, Tdp [ 5 and B 12 �C and

Tdp [ 12 �C). AHR airway hyperresponsiveness; T temperature

(�C); H humidity (%); Tdp dew point (�C); �C degrees

centigrade

196 Aerobiologia (2013) 29:187–200

123

Ta

ble

4A

dju

sted

od

dra

tio

s(l

og

isti

cre

gre

ssio

n)

for

risk

fact

ors

and

95

%C

Ias

soci

ated

toth

ep

rese

nce

of

bro

nch

ial

hy

per

resp

on

siv

enes

s(e

stab

lish

edb

yusi

ng

a3

,20

0lg

PD

20

cuto

ff)

and

inth

ev

ario

us

lev

els

of

hy

per

resp

on

siv

enes

s(m

ild

,m

od

erat

e,an

dse

ver

e)in

com

par

iso

nw

ith

no

rmal

sub

ject

s

All

AH

Rv

ersu

sn

orm

alM

ild

AH

Rv

ersu

sn

orm

alM

od

erat

eA

HR

ver

sus

no

rmal

Sev

ere

AH

Rv

ersu

sn

orm

al

OR

95

%C

Ip

OR

95

%C

Ip

OR

95

%C

Ip

OR

95

%C

Ip

Fem

ales

1.5

67

1.3

64

–1

.80

00

.00

01

1.5

33

1.2

70

–1

.85

00

.00

01

1.4

95

1.2

56

–1

.77

90

.00

01

1.6

71

.37

4–

2.0

29

0.0

00

1

Ag

e0

.98

40

.97

9–

0.9

88

0.0

00

10

.99

10

.98

5–

0.9

98

0.0

07

0.9

83

0.9

78

–0

.98

90

.00

01

0.9

97

0.9

70

–0

.98

30

.00

01

FE

V1

%0

.97

10

.96

6–

0.9

76

0.0

00

10

.98

40

.97

7–

0.9

91

0.0

00

10

.97

70

.97

0–

0.9

83

0.0

00

10

.94

80

.94

0–

0.9

56

0.0

00

1

Sm

ok

ing

1.2

49

1.0

60

–1

.47

30

.00

81

.30

31

.04

4–

1.6

26

0.0

19

1.3

47

1.1

01

–1

.64

80

.00

41

.07

70

.85

3–

1.3

60

.53

1

Ov

erw

eig

ht

or

ob

ese

1.2

20

1.0

60

–1

.40

50

.00

61

.01

50

.83

5–

1.2

34

0.8

78

1.2

91

1.0

80

–1

.54

20

.00

51

.39

71

.14

4–

1.7

06

0.0

01

Mea

nT

0.9

92

0.9

82

–1

.00

10

.09

70

.99

40

.98

1–

1.0

08

0.3

86

0.9

91

0.9

79

–1

.00

30

.14

60

.99

30

.98

0–

1.0

07

0.3

19

Mea

nH

1.0

03

0.9

97

–1

.00

90

.38

31

.00

50

.99

6–

1.0

14

0.2

45

1.0

00

0.9

92

–1

.00

80

.99

61

.00

30

.99

4–

1.0

12

0.4

56

Mea

nT

dp

0.9

94

0.9

84

–1

.00

40

.25

00

.99

30

.97

9–

1.0

07

0.3

60

0.9

94

0.9

81

–1

.00

60

.36

80

.99

50

.98

1–

1.0

09

0.5

89

Min

T0

.99

50

.98

4–

1.0

05

0.3

04

0.9

96

0.9

82

–1

.01

10

.60

30

.99

20

.97

9–

1.0

05

0.2

13

1.0

01

0.9

86

–1

.01

50

.94

1

Min

H1

.00

31

.00

0–

1.0

07

0.0

65

1.0

04

1.0

00

–1

.00

90

.72

01

.00

20

.99

7–

1.0

06

0.5

19

1.0

05

1.0

00

–1

.01

00

.07

8

Min

Tdp

0.9

92

0.9

83

–1

.00

20

.15

00

.99

20

.97

9–

1.0

05

0.2

73

0.9

94

0.9

82

–1

.00

60

.33

00

.99

30

.98

0–

1.0

06

0.3

51

Max

T0

.99

00

.98

2–

0.9

98

0.0

12

0.9

91

0.9

80

–1

.00

20

.09

40

.99

20

.98

2–

1.0

02

0.1

11

0.9

88

0.9

77

–0

.99

90

.03

5

Max

H0

.99

60

.98

8–

1.0

05

0.4

25

0.9

98

0.9

86

–1

.01

00

.76

60

.99

60

.98

6–

1.0

07

0.4

89

0.9

92

0.9

80

–1

.00

40

.20

3

Max

Tdp

0.9

96

0.9

87

–1

.00

60

.53

60

.99

60

.98

2–

1.0

10

0.6

39

0.9

96

0.9

84

–1

.00

90

.61

30

.99

70

.98

4–

1.0

11

0.7

65

Fem

ales

,sm

ok

ers,

and

ov

erw

eig

ht/

ob

ese

sub

ject

sw

ere

com

par

edw

ith

mal

es,

no

n-s

mo

ker

s,an

du

nd

erw

eig

ht/

no

rmal

wei

gh

tsu

bje

cts,

resp

ecti

vel

y.

Th

islo

gis

tic

reg

ress

ion

asse

ssed

on

ly4

,08

6su

bje

cts,

wh

ose

smo

kin

gh

isto

ryw

ask

no

wn

OR

od

dra

tio

s;C

Ico

nfi

den

cein

terv

al;

AH

Rai

rway

hy

per

resp

on

siv

enes

s;T

tem

per

atu

re;

Hh

um

idit

y;

Tdp

dew

po

int;

min

min

imu

m;

ma

xm

axim

um

Sta

tist

ical

lysi

gn

ifica

nt

val

ues

are

inb

old

Aerobiologia (2013) 29:187–200 197

123

et al. 2002) and AHR in asthmatics (Koh and Choi

2002) whereas, if airway reactivity is detected by

exercise, the induced bronchospasm can be more or

less severe according to whether the test is carried out

with different levels of temperature/humidity (Hele-

nius et al. 1996; Koh and Choi 2002; Stensrud et al.

2006, 2007). In fact, the percentage of asthmatic

subjects positive to exercise-induced bronchospasm

was lower in summer than in autumn, winter, and

spring, whereas the responsiveness measured with

methacholine was the same in the four seasons (Koh

and Choi 2002). Methacholine induces bronchospasm

through a muscarinic receptor stimulation, while the

rapid breathing during exercise may cause evaporation

of the mucosal surface water and an increase in

osmolarity, which then favor mast cell degranulation

and constriction of the airway smooth muscle (Koh

and Choi 2002; ATS 2000; Anderson et al. 1982). This

exercise-induced process might be highly influenced

by temperature/humidity.

However, our study shows also some interesting

perspectives. A higher prevalence of AHR was found

in smokers when the methacholine challenge test was

carried out on days in which temperature and humidity

reached higher values in comparison with what

obtained with lower levels. This study also highlights

that smoking can be an AHR risk factor (?25 %) in

subjects with typical asthma respiratory symptoms.

Other studies had already observed that an increased

airway responsiveness could be found in asymptom-

atic smokers if compared with non-smokers (Jensen

et al. 1998; Jogi et al. 2004). Furthermore, allergic

rhinitis (±asthma) hyperresponsive subjects showed

an improvement in methacholine-induced AHR

12 months after they had stopped smoking, thus

confirming the importance of such habit in hyperre-

sponsiveness (Piccillo et al. 2008). Smoking can cause

chronic airway neutrophilic inflammation and oxida-

tive epithelium damage, thus leading to the develop-

ment of airway hyperresponsiveness (Chalmers et al.

2001); in fact, a dose-dependent relationship between

the number of cigarettes smoked and the degree of

hyperresponsiveness has been demonstrated (Gerrard

et al. 1980). Likely, higher levels of temperature and

humidity may increase these effects of smoking on the

airway mucosa. This is confirmed by the fact that

during extreme heat events in summer (very high

temperature and humidity) there is an increase in the

risk of hospitalization for COPD, just involving

subjects with a smoking history (Michelozzi et al.

2009).

The results of our study seem also to indicate that

there is a very weak but significantly positive

relationship between temperature and PD20 in hyper-

responsive subjects aged between 35 and 51 and

especially in those with severe AHR. Also, a logistic

regression model showed a weak but significant

protection factor of the maximum temperature for

bronchial hyperresponsiveness, in particular in sub-

jects with severe AHR, where bronchial sensitivity to

temperature is probably higher. These results seem to

indicate that an increase of temperature could corre-

spond to an improvement in AHR, at least in subjects

with severe hyperresponsiveness whose probability of

being asthmatic is higher. In fact, in the presence of

suggestive symptoms, according to guidelines, the

lower the PD20 value, the higher the probability to

have an asthma diagnosis (ATS 2000). Subjects with

severe AHR, rather than those with mild AHR or

normal reactivity, may have a greater sensitivity to

variations in temperature. Also, elite endurance ath-

letes, whose stress caused by environmental condi-

tions is higher, experience seasonal fluctuations in

airway responsiveness with a worsening during the

cold season, which is then reversed during warm

months (Hemingson et al. 2004; Langdeau et al. 2000).

Cold air in winter, probably, stresses the airways

because of the required warming and humidifying of

the air, which can lead to possible bronchial mucosal

inflammation (Karjalainen et al. 2000; Larsson et al.

1998) with a consequent increase in AHR which is

then reversed when the air gets warmer. Another study

observed that heavy exercise at temperatures below

zero causes bronchospasm in high number of elite

runners with atopy; on the contrary, non-atopic

runners do not seem to be affected (Helenius et al.

1996). Therefore, the seasonal change in AHR may be

related to allergic status. Unfortunately, the atopic

status of our subjects was unknown and therefore we

could not establish whether the protective effect of

temperature on AHR and the higher prevalence of

AHR in smokers concerns only atopic subjects or not.

However, this protective effect of temperature may be

due to a general improvement of the climate condi-

tions when passing from cold seasons to warmer ones

and not only just to a direct influence of temperature

increase (on AHR). In fact, in summer rather than in

other seasons, airborne pollen concentrations of most

198 Aerobiologia (2013) 29:187–200

123

plants and the risk of airways infection diseases are

lower (at least in areas with a Mediterranean climate)

and therefore a reduced AHR may be found (Tilles and

Bardana 1997; Busse 1990). Thus, it seems less

probable to find subjects with airways hyperrespon-

siveness (especially with severe AHR) in summer

when the temperature is higher. This is in line with

another study of ours (Sposato et al. 2012) where a

lower risk of bronchial hyperresponsiveness was

found in summer compared with spring and autumn

and confirmed also by Fruchter and Yigla (2009) who

found a lower number of positive methacholine tests in

summer compared with winter and spring. Also, other

studies gave value to this result and showed that in

asthmatic adults and children, asthma hospitalizations

were significantly and negatively correlated with

temperature reaching a lowest peak of admissions in

June–July (Chen et al. 2006; Xrasagar et al. 2006).

Another study found a significant relationship between

temperature, humidity, seasons, and acute asthmatic

visits (Ivey et al. 2003), confirming that various

climatic factors (temperature, wind speed, humidity,

thunderstorms, etc.) can influence asthma status.

When the test was performed in hot and humid

conditions (Tdp [ 12 �C), the subjects with mild

hyperresponsiveness showed a higher PD20 in com-

parison with what observed with lower levels of

temperature and humidity. It seems that hot and humid

weather may improve airway reactivity in subjects

with mild hyperresponsiveness. An improvement of

lung function after exercise has been found in normal

subjects in hot and humid environmental conditions,

whereas in the same weather environments pulmonary

function worsened in asthmatics (Eschenbacher et al.

1992). We have to take into account that many

subjects categorized as mild AHR could actually be

normal subjects and not asthmatics. In fact, according

to guidelines (ATS 2000), as we have already said, the

probability to diagnose asthma is reduced when PD20

values are high.

5 Conclusion

Different weather conditions do not seem to influence

the PD20 values obtained with the methacholine

challenge test in real life. Hot and humid conditions

may increase the prevalence of AHR in smokers. The

increase in temperature seems to reduce the risk of

detecting AHR especially in subjects with severe AHR

where a diagnosis of asthma is more probable.

Acknowledgments We acknowledge Prof. Piero Angelo

Lenzi for his professional and linguistic editing.

Conflict of interest All authors declare to have no conflicts of

interest, including specific financial interests and relationships

and affiliations relevant to the subject of the manuscript.

References

Anderson, S. D., Schoeffel, R. E., Follet, R., Perry, C. P., Da-

viskas, E., & Kendall, M. (1982). Sensitivity to heat and

water loss at rest and during exercise in asthmatic patients.

European Journal of Respiratory Diseases, 63, 459–471.

Arantes-Costa, F. M., Zoriki, S., Santos, M. H. C., Kobata, C.

H. P., Vieira, J. E., & Martins, M. A. (2002). Effects of

ventilation, humidity and temperature on airway respon-

siveness to methacholine in rats. European RespiratoryJournal, 19, 1008–1014.

ATS (American Thoracic Society). (2000). Guidelines for me-

tacholine and exercise challenge testing-1999. AmericanJournal of Respiratory and Critical Care Medicine, 161,

309–329.

Beier, J., Beeh, K. M., Kornmann, O., Morankic, E., Ritter, N.,

& Buhl, R. (2003). Dissimilarity between seasonal changes

in airway responsiveness to adenosine-50-monophosphate

and methacholine in patients with grass pollen allergic

rhinitis: Relation to induced sputum. InternationalArchives of Allergy and Immunology, 132, 76–81.

Bougalt, V., Turmel, J., & Boulet, L. P. (2010). Bronchial

challenges and respiratory symptoms in elite swimmers

and winter sport athletes. Airway hyperresponsiveness in

asthma: Its measurement and clinical significance. Chest,138(2 Suppl), 31S–37S.

Busse, W. W. (1990). Respiratory infections: Their role in air-

way responsiveness and the pathogenesis of asthma. TheJournal of Allergy and Clinical Immunology, 85, 671–683.

Chai, H., Farr, R. S., Froehlich, L. A., Mathison, D. A., Ma-

cLean, J. A., Rosenthal, R. R., et al. (1975). Standardiza-

tion of bronchial inhalation challenge procedure. TheJournal of Allergy and Clinical Immunology, 56, 323–327.

Chalmers, G. W., MacLeod, K. J., Thomson, L., Little, S. A.,

McSharry, C., & Thomson, N. C. (2001). Smoking and

airway inflammation in patients with mild asthma. Chest,120, 1917–1922.

Chen, C. H., Xirasagar, S., & Lin, H. C. (2006). Seasonality in

adult asthma admission, air pollutant levels, and climate: A

population-based study. Journal of Asthma, 43, 287–292.

Cole, T. J., Bellizzi, M. C., Flegal, K. M., & Dietz, W. H. (2000).

Establishing a standard definition for child overweight and

obesity worldwide: International survey. BMJ, 320, 1–6.

Eschenbacher, W. L., Moore, T. B., Lorenzen, T. J., Weg, J. G.,

& Gross, K. B. (1992). Pulmonary responses of asthmatic

and normal subjects to different temperature and humidity

conditions in an environmental chamber. Lung, 170,

51–62.

Aerobiologia (2013) 29:187–200 199

123

Fruchter, O., & Yigla, M. (2009). Seasonal variability of the

methacholine challenge test. Journal of Asthma, 46,

951–954.

Gerrard, J. W., Cockcroft, D. W., Mink, J. T., Cotton, D. J.,

Poonawala, R., & Dosman, J. A. (1980). Increased non-

specific bronchial reactivity in cigarette smokers with

normal lung function. The American Review of RespiratoryDisease, 122, 577–581.

Helenius, I. J., Tikkanen, H. O., & Haahtela, T. (1996). Exer-

cise-induced bronchospasm at low temperature in elite

runners. Thorax, 51, 628–629.

Hemingson, H. B., Davis, B. E., & Cockcroft, D. W. (2004).

Seasonal fluctuations in airway responsiveness in elite

endurance athletes. Canadian Respiratory Journal, 11,

399–401.

Ivey, M. A., Simeon, D. T., & Monteil, M. A. (2003). Climatic

variables are associated with seasonal acute asthma

admissions to accident and emergency room facilities in

Trinidad, West Indies. Clinical and Experimental Allergy,33, 1526–1530.

Jensen, E. J., Dahl, R., & Steffensen, F. (1998). Bronchial

reactivity to cigarette smoke in smokers: Repeatability,

relationship to methacholine reactivity, smoking and

atopy. European Respiratory Journal, 11, 670–676.

Jogi, R., Janson, C., Boman, G., & Bjorksten, B. (2004).

Bronchial hyperresponsiveness in two populations with

different prevalences of atopy. The International Journalof Tuberculosis and Lung Disease, 8, 1180–1185.

Karjalainen, E. M., Laitinen, A., Sue-Chu, M., Altraja, A.,

Bjermer, L., & Laitinen, L. A. (2000). Evidence of airway

inflammation and remodeling in ski athletes with and

without bronchial hyperresponsiveness to methacholine.

American Journal of Respiratory and Critical Care Med-icine, 161, 2086–2091.

Koh, Y. I., & Choi, I. S. (2002). Seasonal difference in the

occurrence of exercise-induced bronchospasm in asth-

matic: Dependence on humidity. Respiration, 69, 38–45.

Langdeau, J. B., Turcotte, H., Bowie, D. M., Jobin, J., Desgagne,

P., & Boulet, L. P. (2000). Airway hyperresponsiveness in

elite athletes. American Journal of Respiratory and Criti-cal Care Medicine, 161, 1479–1484.

Larsson, K., Tornling, G., Gavhed, D., Muller-Suur, C., &

Palmberg, L. (1998). Inhalation of cold air increases the

number of inflammatory cells in the lung in healthy sub-

jects. European Respiratory Journal, 12, 825–830.

Michelozzi, P., Accetta, G., De Sario, M., D’Ippoliti, D., Mar-

ino, C., Baccini, M., et al. (2009). High temperature and

hospitalizations for cardiovascular and respiratory causes

in 12 European cities. American Journal of Respiratoryand Critical Care Medicine, 179, 383–389.

Piccillo, G., Caponnetto, P., Barton, S., Russo, C., Origlio, A.,

Bonaccorsi, A., et al. (2008). Changes in airway hyperre-

sponsiveness following smoking cessation: Comparisons

between Mch and AMP. Respiratory Medicine, 102,

256–265.

Riccioni, G., Di Stefano, F., De Benedictis, M., Verna, N.,

Cavalluci, E., Paolini, F., et al. (2001). Seasonal variability

of non-specific hyper-responsiveness in asthmatic patients

with allergy to house dust mites. Allergy and AsthmaProceedings, 22, 5–9.

Schmidt, A., & Bundgaard, A. (1986). Lung function and

bronchial hyperreactivity following exposure to four dif-

ferent temperatures and relative humidities. EuropeanJournal of Respiratory Diseases Supplement, 143, 67–73.

Sposato, B., Scala, R., Pammolli, A., Scala, R., & Naldi, M.

(2012). Seasons can influence the results of the metha-

choline challenge test. Annals of Thoracic Medicine, 7,

61–68.

Stensrud, T., Berntsen, S., & Carlsen, K. H. (2006). Humidity

influences exercise capacity in subjects with exercise-

induced bronchoconstriction (EIB). Respiratory Medicine,100, 1633–1641.

Stensrud, T., Berntsen, S., & Carlsen, K. H. (2007). Exercise

capacity and exercise-induced bronchoconstriction (EIB)

in a cold environment. Respiratory Medicine, 101,

1529–1536.

Tessier, P., Cartier, A., Ghezzo, H., Martin, R. R., & Malo, J. L.

(1988). Bronchoconstriction due to exercise combined

with cold air inhalation does not generally influence

bronchial responsiveness to inhaled histamine in asthmatic

subjects. European Respiratory Journal, 1, 133–138.

Tilles, S. A., & Bardana, E. J. (1997). Seasonal variation in

bronchial hyper-responsiveness in allergic patients. Clini-cal Reviews in Allergy and Immunology, 15, 169–185.

van der Heide, S., De Monchy, J. G., De Vries, K., Dubois, A. E.,

& Kauffman, H. F. (1997). Seasonal differences in airway

hyperresponsiveness in asthmatic patients: Relationship

with allergen exposure and sensitization to house dust

mites. Clinical and Experimental Allergy, 27, 627–633.

Xrasagar, S., Lin, H. C., & Liu, T. C. (2006). Seasonality in

pediatric asthma admission: The role of climate and envi-

ronmental factors. European Journal of Pediatrics, 165,

747–752.

200 Aerobiologia (2013) 29:187–200

123