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: [email protected]
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
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Fem
ales
1.5
67
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1.2
70
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.85
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1.4
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.37
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29
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00
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Ag
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40
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97
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.97
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83
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00
10
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80
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0.9
56
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00
1
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49
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30
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81
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.04
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1.3
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.00
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60
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1
Ov
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or
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ese
1.2
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50
.00
61
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5–
1.2
34
0.8
78
1.2
91
1.0
80
–1
.54
20
.00
51
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71
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nT
0.9
92
0.9
82
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.00
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nT
dp
0.9
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.00
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80
.99
50
.98
1–
1.0
09
0.5
89
Min
T0
.99
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4–
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05
0.3
04
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96
0.9
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–1
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10
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30
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9–
1.0
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01
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86
–1
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50
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1
Min
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.00
31
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1.0
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65
1.0
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7–
1.0
06
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19
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8
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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
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90
.03
5
Max
H0
.99
60
.98
8–
1.0
05
0.4
25
0.9
98
0.9
86
–1
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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
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ales
,sm
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and
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ject
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ere
com
par
edw
ith
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es,
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ker
s,an
du
nd
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ht/
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ly4
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tem
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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