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RESEARCH ARTICLE
Temperature drop and the risk of asthma: a systematic
review and meta-analysis
Xiaowei Cong
1
&Xijin Xu
1,2
&Yuling Zhang
1
&Qihua Wang
1
&Long Xu
1
&Xia Huo
3
Received: 12 May 2017 / Accepted: 3 August 2017
#Springer-Verlag GmbH Germany 2017
Abstract The relationship between asthma and temperature
changes remains controversial. The aim of this study was to
investigate the association between temperature changes and
the risk of asthma. A total of 26 studies (combined total num-
ber of subjects N> 26 million), covering 13 countries and
Costa Rica, were identified by using a series of keywords in
different combinations and searching the papers in PubMed,
EMBSEA, Web of Science, MEDLINE, AIM, LILACS, and
WPRIM before February 2016. Most of the papers were pub-
lished in English. Random-effects meta-analyses were per-
formed to evaluate the effect of temperature drop on risk of
asthma. Several secondary analyses were also calculated
based on stratification for different age, season, latitude, and
region on risk of asthma. The odds ratio (OR) estimate be-
tween temperature drop and asthma was 1.05 (95% CI 1.02,
1.08) in the meta-analysis. For children, the overall OR was
1.09 (95% CI 1.03, 1.15). Dose-effect analyses showed stron-
ger associations in asthma risk for each 1°1 °C decrement in
short-term temperature (OR 1.055, 95% CI 1.00, 1.11).
Further stratifications showed that winter (OR 1.03, 95% CI
1.01, 105) and low latitude (OR 1.72, 95% CI 1.23, 2.41) have
a statistically significant association with the increased risk of
asthma. Exposure of people to short-term temperature drop
(per 1 °C decrement) was significantly associated with the risk
of lower respiratory tract infections (LRTI) with asthma (OR
1.02, 95% CI 1.00, 1.04). Results suggest an adverse effect of
temperature drop on asthma risk, especially in children and
low-latitude areas. It may be opportune to consider the pre-
ventive actions against temperature drop, including simple
face masks, to decrease the risk of asthma.
Keywords Temp erat ure dro p .Asthma .Meta-analysis .
Systematic review
Introduction
Asthma is one of the major chronic non-communicable dis-
eases that affects human health and life quality, and involves
pronounced constriction of airway muscles, lung inflamma-
tion, excessive mucus production, and respiratory distress
(Wasilevich et al. 2012; Shang et al. 2017). Asthma can occur
at any age and has a worldwide prevalence of 5~10% (Eder
et al. 2006), with an estimated 235 million people currently
suffering from asthma (WHO 2013). Although the etiology of
asthma still has not been fully elucidated, some evidence sug-
gests that environment risk factors may trigger asthma (Xu
et al. 2013;Darçın, 2014).
The relationship between global climate changes and their
effects on respiratory health have drawn significant and in-
creasing public attention (Paynter et al. 2010). Among the
numerous climate factors, one of the biggest concerns focused
on the effects of temperature (Lian et al. 2015). Temperature
Responsible editor: Philippe Garrigues
*Xijin Xu
xuxj@stu.edu.cn
*Xia Huo
xhuo@jnu.edu.cn
1
Laboratory of Environmental Medicine and Developmental
Toxicology, and Guangdong Provincial Key Laboratory of Infectious
Diseases and Molecular Immunopathology, Shantou University
Medical College, Shantou, Guangdong 515041, China
2
Department of Cell Biology and Genetics, Shantou University
Medical College, Shantou, Guangdong 515041, China
3
School of Environment, Guangzhou Key Laboratory of
Environmental Exposure and Health, Guangdong Key Laboratory of
Environmental Pollution and Health, Jinan University,
Guangzhou, Guangdong 510632, China
Environ Sci Pollut Res
DOI 10.1007/s11356-017-9914-4
drop have been linked to a number of adverse health endpoints,
including morbidity and mortality of cardiovascular and respi-
ratory diseases (Phung et al. 2016; Beard et al. 2012;WHO
2016). Studies have shown that ambient temperature can affect
inflammation pathways, airway hyper-responsiveness, airway
remodeling, and facilitate bacterial growth in water droplets
and resulting in airway narrowing which are all potential tem-
perature drop triggers of asthma (Buckley and Richardson,
2012; Handley and Webster, 1995;Kaminskyetal.2000).
Although a series of epidemiological studies suggest that
ambient temperature has an effect on asthma, distinct differ-
ences have been showed by different laboratories. For example,
evidence shows that temperature drop may not be a risk factor
for severe respiratory symptoms in children with asthma (Li
et al. 2014), while to the contrary, another study demonstrates
that the relative risk of hospital admissions for asthma was
associated with a lower temperature level (Zhang et al. 2014).
In order to further explore how ambient temperature chang-
es affect risk of asthma, we performed a systemic search to
collect the previously published studies, and extracted and
transformed the data for meta-analysis. A statistical model
was employed for meta-analysis to evaluate the effects of
temperature drops on risk of asthma. In addition, the associa-
tion between the changes in different windows of exposure,
involving age, season, latitude and region, and risk of asthma
were also explored.
Material and methods
We retrieved the published literature available online, up to
February 2016, that reported on the risk of asthma in relation
to temperature changes. All useful data and information
sources were from papers obtained by searching the
PubMed, Embase, Web of Science, Scopus, African Index
Medicus (AIM), Latin American and Caribbean Health
Sciences Information System (LILACS), Index Medicus for
the Eastern Mediterranean Region (IMEMR), Index Medicus
for the South-East Asian Region (IMSEAR), and Western
Pacific Region Index Medicus (WPRIM). The keywords used
in searching for articles were Btemperature drop,^Bambient
temperature,^Btemperature,^Bcold,^Bwarm,^Basthma
incidence,^and Basthma^in different combinations. We also
manually searched the references from the primary studies for
additional publications. Further publications included were
also identified by examining review articles.
Study selection
Inclusion and exclusion criteria
We initially screened studies and abstracts that were related to
the association between asthma and ambient temperature,
especially in regard to temperature drop. If studies did not
address the relationship between asthma and ambient temper-
ature, studies were excluded. Then, we marked and further
evaluated the remaining studies. The criteria for inclusion
were as follows: (a) the study included temperature and asth-
ma; (b) cohort studies and cross-sectional studies were con-
sidered; (c) assumptions of literature focus on risk factor of
asthma; (d) the sample size for study was comprised of more
than 50 cases; (e) the study provided odds ratios (ORs) or
relative risks (RRs) for asthma incidence as well as the 95%
confidence intervals (CI), or information that could be used to
infer these results; and (f) repeated reports, incompleted data,
case study, editorial, and conference proceeding were exclud-
ed. The selection process is described and shown in detail in
Fig.1.
Data extraction
Information regarding publication was extracted as follows:
author, source of publication, exposure period, study design,
data sources, sample size, temperature measurement methods,
OR or RR and 95% CI, and conclusion of publication. If a
study provided association of temperature during different pe-
riods or seasons with asthma incidence, all data was extracted
from full-text articles by author. Several studies assessed the
risk of asthma based on different windows of exposure; we
preferentially chose to evaluate articles with a cohort study,
which could potentially reduce the heterogeneity between
studies included in meta-analysis. In addition, estimates were
extracted based on signal statistical models only if they were
fully adjusted for other multiple covariates. Not all studies
were adjusted for all other variables other than temperature.
However, if the sample was a group that had been selected for
further analysis because of other stronger risk factors for de-
velopment of asthma, data were not eligible due to the inabil-
ity to collect a realistic data set based on temperature drops
(i.e., pollution, tobacco smoke, pet dander, and chemical irri-
tants). Two authors of this study scrutinized extraction criteria
and assessments by using a standard form that included the
characteristics of the articles, and resolved all discrepancies by
discussion.
Meta-analysis and statistical analysis
All study designs for the included studies were divided into
different types based on different windows. Prior to
performing the meta-analysis, we converted all risk estimates
(OR/RR) of ambient temperature from selected studies to a
uniform form of temperature drop increasing the risk of asth-
ma, which allowed us to pool general estimates from different
research studies. The logit transformation was applied in prev-
alence proportions for an appropriate normal distribution, and
estimates of combined logit prevalence were back
Environ Sci Pollut Res
transformed into their original scale for interpretation on the
same basis for all the studies. Then, random-effects meta-anal-
yses were conducted for the assessment of effect of tempera-
ture drops on asthma incidence. We also estimated the pooled
effects of different time, season, latitude, and region on asthma
incidence by using several secondary analyses. These analy-
ses aimed to further explore the impact of temperature drops
on asthma risk and test the impact of heterogeneity.
The varying degree of exposure effects was evaluated by
comparing OR values with 95% CI at a statistical test level of
0.05 between the control and high-exposure group (Onakpoya
et al. 2015). The I-squared (I
2
) value is indicative of a signif-
icantly elevated consistency for the analyzed studies (Chen
et al. 2013). An I
2
value ranging from 25 to 50% based on
odds ratios is indicative that articles included for analysis have
moderate inconsistency. However, if meta-analyses had I
2
values over 50%, then there were large inconsistencies in the
studies. Therefore, I
2
values were determined to meet the re-
quired sensitivity of the meta-analysis by excluding individual
studies of large biases and restricting the analyses to certain
subgroups in a process verified by another study in which a
funnel plot or Egger
’
s graphical test could visually assess the
publication bias (the Egger
’
stestpvalue was < 0.05) (Egger
et al. 1997; Fan et al. 2016). Each statistical test was two-
sided, and a value of p< 0.05 was considered statistically
significant. Data were recorded and analyzed in Excel 2010
(Microsoft Corp) and the Stata software version 12 (Stata
Corp).
Definitions
For the purpose of this review, a temperature drop is defined as
a lower temperature level, compared with a higher or middle
temperature level, at a period of time in the same area, which
is based on prior studies (Zanazzi et al. 2007;Pinoetal.2004;
Wang and Lin, 2014). Risk of asthma is defined as asthma
incidence or pre-existing asthma onset, which comes from
self-reported or hospital/national recorded.
Results
Document search and study characteristics
We selected a total of 132 studies as potentially eligible pub-
lications. After excluding 51 studies (5 studies were reviews,
and 46 studies did not assess temperature and/or asthma), 81
studies were identified for further assessment. We further
Fig. 1 Flow diagram of the
selection of studies for meta-
analysis
Environ Sci Pollut Res
excluded studies due to the absence of risk estimates for the
association between temperature and asthma risk (n=5);or
only the sources of temperature (n= 2); asthma-related symp-
toms (asthma is uncertain) (n= 4); duplicate studies (n=4);
studies on animals (n= 2);, articles that were case studies,
editorials, or conference proceedings (n= 6); and incomplete-
ness of data (n= 32). Finally, 26 studies were included in this
meta-analysis from 1994 to 2014, with a total population of
over 26 million, of which 16 studies assessed temperature
drops and 10 studies assessed temperature raises. More than
350,000 asthma cases were included in these 26 studies that
assessed the association between ambient temperature and
asthma risk (Wasilevich et al. 2012; Beard et al. 2012;
Buckley et al. 2012;Lietal.2014; Zhang et al. 2014;Kim
et al. 2012; Epton et al. 1997;Pinoetal.2004; Lin et al. 2008;
Celenza et al. 1996;Lombardietal.1997; Kiechl-
Kohlendorfer et al. 2007; Gonzalez et al. 2008;Makinen
et al. 2009; Rumchev et al. 2004; Soto-Quiros et al. 1994;
Wang and Lin, 2014; Guo et al. 2012;Mietal.2006;Lee
et al. 2005; Zanolin et al. 2004;Jacobsetal.1997; Yamazaki
et al. 2015; Villeneuve et al. 2015; Khalaj et al. 2010;Gleason
et al. 2014). The included studies were conducted in China
(n= 5), the USA (n= 6), South Korea (n=1),NewZealand
(n=1),Chile(n=1),theUK(n= 1), Austria (n= 1), Brazil
(n=1), Finland (n= 1), Australia (n= 4), Costa Rica (n=1),
Italy (n= 1), Japan (n=1),andCanada(n= 1). An overview
of these publications and the rationale for exclusion in the
present meta-analysis is provided in Table 1and Fig. 1.
Data synthesis
The results of the main extracted data
The results of different meta-analyses and the assessment of
heterogeneity are summarized in Table 2. When the main ex-
tracted data from each study was combined, a statistically
significant association with asthma was observed (OR 1.05,
95% CI 1.02, 1.08). A forest graph of the 21 main studies was
plotted (Fig. 2). Dose-effect analyses showed stronger associ-
ations in asthmarisk for each 1 °C decrement (OR 1.055, 95%
CI 1.00, 1.11) and each 8 °C decrement in ambient tempera-
ture (OR 1.057, 95% CI 1.03, 1.09). The association between
lower respiratory tract infections (LRTI) and temperature
drops (per 1 °C decrement) was statistically significant (OR
1.02, 95% CI 1.00, 1.04) (Fig. 3). Each study did not contrib-
ute more than 8% of the total weight. When pooling the main
data from all studies included, a strong evidence for heteroge-
neity (I
2
of 92.2%) was observed in the meta-analysis, incon-
sistent with the requirement for an overall meta-analysis of the
extracted data. Therefore, further analyses of combined stud-
ies were carried out to explore the sources of heterogeneity by
using different stratification secondary analyses.
The results of different critical windows of exposure
The corresponding pooled estimates of secondary analyses
were calculated after stratification according to different win-
dows: age (children and adult), seasons (spring, summer, fall,
and winter), latitude (low (subtropical), middle latitudes), and
regions (Asian, America, Europe, and Australia). The studies
included in these meta-analyses are shown in Table 2.
Pool estimate of the effect of temperature drop on risk of
asthma in different age groups Heterogeneity was strongly
reduced and the most results for different windows of expo-
sure were consistent. The pooled estimated risk of asthma for
children was significantly increased (OR 1.087; 95% CI 1.03,
1.15) (Table 2). Dose-effect analyses for different stages of
their lives showed statistically significant association between
asthma incidence and temperature drops (per 1 °C decrement)
during the first stages (< 12 years old) (OR 1.070; 95% CI
1.01, 1.12) (Fig. 3). However, there was no increased risk for
adults when the temperature dropped (OR 1.002; 95% CI
0.93, 1.08) (Table 2).
Pool estimate of the effect of temperature drop on risk of
asthma in different seasons Stratification of studies by sea-
son showed that no statistical significance was found for the
increased risk of asthma in spring (OR 1.293; 95% CI 0.63,
2.64), fall (OR 1.373; 95% CI 0.67, 2.81), and summer (OR
1.226; 95% CI 0.71, 2.27). However, winter yielded a statis-
tically significant increase in the risk of asthma (OR 1.030;
95% CI 1.01, 1.05) without evidence of heterogeneity be-
tween studies (I
2
of 3.8%).
Pool estimate of the effect of temperature drop on risk of
asthma in different latitudes Stratification by absolute lati-
tudes showed a markedly increased risk of asthma in all stud-
ies reporting Blow latitude^and Bmiddle latitude^with a low-
level heterogeneity, especially in the low-latitude exposure.
We further explored the risk between asthma and temperature
drop with absolute latitude. BLow latitude^generated the
highest increase of Meta-OR (OR 1.718; 95% CI 1.23, 2.41)
without heterogeneity (I
2
of 46.4%), in contrast to other expo-
sure latitudes. Results were less consistent for additional
substratification. Significant increase of risk of asthma was
observed for lower respiratory tract infections (OR 1.020;
95% CI 1.00, 1.04), but not upper respiratory tract infections
(OR 0.96; 95% CI 0.940, 0.970).
Pool estimate of the effect of temperature drop on risk of
asthma in different regions Stratification by geographical
location showed increased Meta-OR for all groups of studies
in different regions. An increased risk of asthma associated
with temperature drop was observed after combining studies
in Asia (OR 1.004; 95% CI 1.01, 1.16), Europe (OR 1.102;
Environ Sci Pollut Res
Tab l e 1 Characteristics of publications selected for meta-analysis
Author Location Study duration Age No. of
participants
Sex Study design Temperature
measurement method
Type of cases OR/RR (95%CI) Classified
information
Kim et al., 2012 Soonchunhyang, South
Korea (37
。
N)
2005–2009 19–87 2298 Both Case-crossover
study
Monitoring network data Refractory asthma 1.06 (0.89, 1.26) All
Epton et al., 1997 Blenheim, New Zealand
(41
。
S)
1992–1993 17–80 139 Both Prospective
study
Monitoring data at the local
airfield
Asthma 1.03 (0.88, 1.22) All
Pino et al., 2004 Santiago, Chile (33
。
S) 1995–1996 4 months 504 Both Cohort study Monitoring network data Wheezing
bronchitis
0.94 (0.91, 0.97) All
Lin et al., 2008 New York, USA (40
。
N) 1995–1999 Children 1,204,396 Both Retrospective
cohort study
Monitoring sites Asthma 1.06 (1.00, 1.13) All
Celenza et al., 1996 London, UK (51
。
N) 1994 16 or over 148 Both Retrospective
study
Meteorological office Asthma 1.11 (1.05, 1.18) All
Kiechl-Kohlendorfer
et al., 2007
Tyrol, Austria (47
。
N) 1994–1999 6–10 33,808 Both Prospective
study
Temperatures decrease at a
rate of 0.5–1.0 °C/100 m
of altitude
Atopic asthma 1.07 (1.01, 1.12) All
2.05 (1.01, 4.16) Spring
2.22 (1.03, 4.81) Summer
1.87 (1.00, 3.48) Autumn
2.33 (1.03, 5.27) Winter
Gonzalez et al., 2008 Pelotas, Brazil (31
。
S) 1982–2005 Children 5914 Both Birth cohort
study
Monitoring network data Asthma 1.00 January
2.35 (1.11, 4.99) April
0.79 (0.28, 2.28) July
0.78 (0.21, 2.87) October
Makinen et al., 2009 Northern Finland (64
。
N) 2004–2006 19.6
(mean)
892 Men Prospective
study
National meteorological
stations
Asthma 0.96 (0.94, 0.97) URTI
1.02 (1.00, 1.04) LRTI
Li et al., 2014 Sydney, Melbourne,
Brisbane, Adelaide,
Perth, Canberra,
Australia (27
。
S–37
。
S)
2007–2008 7–12 270 Both Cross-sectional
study
Air monitoring station Asthma 1.02 (0.97, 1.02) Lag0 (female)
1.01 (0.97, 1.06) Lag1 (female)
1.01 (0.96, 1.05) Lag2 (female)
1.00 (0.96, 1.04) Lag3 (female)
1.05 (1.01, 1.10) Lag0 (male)
1.06 (1.01, 1.10) Lag1 (male)
1.05 (1.01, 1.09) Lag2 (male)
1.02 (0.98, 1.06) Lag3 (male)
Rumchev et al., 2004 Western Australia (32
。
S) 1997–1999 0.5–3 192 Both Case-control
study
Tinytalk II Data Loggers Asthma 1.07 (1.02, 1.11) All
Soto-Quiros et al.,
1994
CostaRica(10
。
N) 1997–1998 5–17 2682 Both Cross-sectional
study
Meteorological office Asthma 4.27 < 25 °C
3.77 > 25 °C
Zhang et al., 2014 Shanghai, China (31
。
N) 2005–2012 All 23million Both A time-series
analysis
Center for Urban
Environmental
Meteorology
Asthma 1.20 (1.01, 1.41) All
Wan g a n d Lin , 2014 Taipei, China (25
。
N) 2000–2009 All 1 million Both Cohort study Central Weather Bureau Asthma 2.93 (1.26, 6.97) All
Guo et al., 2012 Shanghai, China (31
。
N) 2007–2009 Children 1.99million Both Retrospective
study
Shanghai Meteorological
Bureau
Asthma 1.06 (0.97, 1.17) All
Xu et al., 2013 Brisbane, Australia (27
。
S) 2003–2009 0–14 13,324 Both Retrospective
study
Australian Bureau of
Meteorology
Asthma 1.25 (0.80, 1.95) All
1.06 (0.63, 1.77) 0–4years
1.26 (0.58, 2.73) 5–9years
1.41 (0.77, 3.62) 10–14 years
1.24 (0.73, 2.12) Male
1.29 (0.68, 2.44) Female
Mi et al., 2006 Shanghai, China (31
。
N) 2000 13–14 1414 Both Data logger (Q-track) Asthma 1.15 (0.91, 1.44) All
Environ Sci Pollut Res
Tab l e 1 (continued)
Author Location Study duration Age No. of
participants
Sex Study design Temperature
measurement method
Type of cases OR/RR (95%CI) Classified
information
Cross-sectional
study
Lee et al., 2005 Taiw an, C hin a
(21
。
N–25
。
N)
1995–1996,
2001
12–15 44,104 Both Retrospective
study
Monitoring stations Asthma 1.00 Spring
1.02 Winter
0.99 Summer
Zanolin et al., 2004 Italy (36
。
N–47
。
N) 1998–2000 20–40 27,000 Both Cross-sectional
study
ISAO and ARPA Asthma 1.11 (1.06, 1.14) All
Jacobs et al., 1997 California, USA (36
。
N) 1983–1992 All 3342 Both Retrospective
study
NOAA Asthma 0.99 (0.99, 1.00)
1.00 Summer
1.15 (0.97, 1.37) Winter
1.05 (0.91, 1.20) Spring
1.03 (0.87, 1.22) Fall
Beard et al., 2012 Salt Lake City, USA
(40
。
N)
2003–2008 All 3425 Both Cohort study Monitoring network data Asthma 1.14 (1.02, 1.27) All
Yamazaki et al., 2015 Himeji, Japan (35
。
N) 2010–2013 0–14 1447 Both Case-crossover
study
The Japan Meteorological
Agency
Asthma 1.04 (1.01, 1.07) All
1.12 (1.06, 1.19) Spring
1.07 (0.88, 1.29) Summer
0.99 (0.95, 1.03) Fall
1.01 (0.94, 1.09) Winter
Buckley and
Richardson, 2012
North Carolina, USA
(33
。
N–36
。
N)
2007–2008 > 18 53,156 Both Case-crossover
study
Stata Climate Office Asthma 1.01 (1.00, 1.02) All
1.03 (1.01, 1.05) Winter
0.97 (0.95, 0.99) Spring
1.04 (0.99, 1.09) Summer
1.01 (0.98, 1.03) Fall
Villeneuve et al.,
2005
Ottawa, Canada (45
。
N) 1992–2000 2–15 1 million Both Case-crossover
study
Monitoring network data Asthma 0.97 (0.92, 1.01) All
Khalaj et al., 2010 New South Wales,
Australia (28
。
S–37
。
S)
1998–2006 All 1,497,655 Both Case-only study NSW Bureau of
Meteorology
Asthma 0.92 (0.83, 1.02) Lag0
0.91 (0.82, 1.01) Lag4
0.80 (0.69, 0.92) Average
Wasilevich et al.,
2012
Detroit, USA (42
。
N) 2000–2001 3–18 6659 Both Case-crossover
study
NOAA Asthma 4 h
1.00 (0.99, 1.02) Change
1.01 (0.98, 1.03) Change rate
8h
1.00 (0.99, 1.01) Change
1.01 (0.99, 1.04) Change rate
12 h
0.99 (0.99, 1.01) Change
1.00 (0.98, 1.02) Change rate
24 h
0.99 (0.98, 1.00) Change
0.97 (0.95, 0.99) Change rate
Gleason et al., 2014 New Jersey, USA
(38
。
N–41
。
N)
2004–2007 3–17 21,854 Both Case-crossover
study
New Jersey weather
stations
Asthma 0.89 (0.87, 0.91) All
URTI upper respiratory tract infections, LRTI lower respiratory tract infections, Lag 0 the same day, Lag 1 previous day, Lag 2 day before the previous day, Lag 3 3 days ago, Lag 4 the day after, ISAO
Institute of Atmospheric and Oceanic Sciences, ARPA Regional Agencies for the Protection of the Environment, NOAA National Oceanic and Atmospheric Administration’
Environ Sci Pollut Res
95% CI 1.06, 1.15), and Australia (OR 1.071; 95% CI 1.03,
1.12). Likewise, heterogeneities between the included studies
were not observed (all I
2
< 50%). Data on America revealed
an increased risk of asthma after combining data (OR 1.103;
95% CI 1.04, 1.17) but inconsistency in the study was ob-
served (I
2
of 95.4%).
Sensitivity
Sensitivity analyses in the meta-analysis showed that the
pooled estimate was not significantly changed after the me-
ta-analyses. Exclusion of the studies with more than 7% of the
total weight or less than 1% of the total weight, and the lowest
Tabl e 2 Meta-analysis after stratification of the different windows in the studies
Subgroups No. of studies Summary OR 95% CI x
2
Woo lf I
2
(%) Pfor hypothesis Pfor Egger
’
stest 95%UI
A. The main studies 21 1.050 1.01–1.09 92.1 < 0.001 0.000 0.17–1.03
B. Exposure time windows
(B.1) childhood 11 1.087 1.03–1.15 104.78 90.5 < 0.001 0.416 −0.58–1.27
(B.2) adult 5 1.002 0.93–1.08 55.44 55.4 < 0.001 0.843 −2.27–1.98
C. Exposure season windows
(C.1) spring 2 1.293 0.63–2.64 4.29 4.3 0.038 ––
(C.2) summer 2 1.373 0.67–2.81 3.71 3.7 0.054 ––
(C.3) fall 2 1.226 0.71–2.27 3.74 3.7 0.053 ––
(C.4) winter 2 1.030 1.01–1.05 3.84 3.8 0.050 ––
D. Exposure latitude windows
(D.1) low latitude 3 1.718 1.23–2.41 3.73 46.4 0.155 0.962 −7.43–7.50
(D.2) middle latitude 16 1.063 1.02–1.10 177.67 91.6 < 0.001 0.045 0.02–1.24
(D.3) Circumpolar latitude
URTI 1 0.960 0.95–0.98 ––– – –
LRTI 1 1.020 1.00–1.04 ––– – –
E. Exposure region windows
(E.1) Asian 6 1.004 1.01–1.16 9.33 46.4 0.097 0.039 0.03–0.71
(E.2) America 7 1.103 1.04–1.17 151.37 95.4 < 0.001 0.084 −2.38–2.68
(E.3) Europe 3 1.102 1.06–1.15 2.54 21.2 0.201 0.264 −3.15–2.20
(E.4) Australia 2 1.071 1.03–1.12 0.46 0.0 0.496 ––
Fig. 2 Forest plots of studies for
temperature drops and asthma
Environ Sci Pollut Res
or highest of OR, and deletion of the study reporting com-
bined data for cross-sectional studies on ambient temperature
did not substantially alter the results. Results of the meta-
analyses were all similar when performed with fixed- or
random-effects models.
Funnel plot and asymmetry
A funnel plot for the meta-analysis, containing 21 studies on
temperature drops, was constructed (Fig. 4and Fig. 5). Visual
inspection of the funnel plot did not clearly reveal asymmetry.
The statistical results provided by the linear regression using
the Egger
’
s test showed there was also no significant publica-
tion bias in most of the secondary analyses, except for the
Bmiddle latitude^and BAsian^exposure windows (Table 2).
Discussion
A summary of the evidence
This meta-analysis and systematic review examined the
relevant epidemiological studies reporting an association
between temperature drop and asthma. Overall, temper-
ature drop is associated with asthma. The increased risk
of asthma is also observed and did not alter the
previous result when omitting some extreme values in
the studies. Our conclusion is consistent with the results
of previously narrative reviews (Carlsen, 2012; Kippelen
et al. 2012;Fisher,2011). Furthermore, experimental
studies also showed similar results to our findings. An
increase in temperature from 4 to 25 °C has been
showed to limit disruption of the airway epithelium,
which indicating that exposure to temperature drop
could increase the risk of asthma (Bolger et al. 2011).
Kippelen et al. found a lower temperature level, com-
pared with a higher temperature level, can cause airway
injury, and the repeated injury and repair process of the
epithelium resulted in disorder of airway function and
structure, which could be the underlying mechanism for
the development of asthma (Kippelen and Anderson,
2012). Moreover, asthma exacerbation also shows a sig-
nificant association with temperature drop (Hirabayashi
et al. 2004; May et al. 2011; Abe et al. 2009). These
results support the suggestion that temperature drop may
be a potential causal factor for asthma. However, the
strong evidence of heterogeneity (I
2
of 92.1%) argues
against an overall meta-analysis of the data. Further
analyses were therefore carried out to identify sources
Fig. 3 Polled OR estimates between ambient temperature and asthma
risk, per 1 or 8 °C decrease in temperature, different age ranges, from
below 12 years old (< 12), 13 to 18 years old (13–18), and over 18 years
of age (> 18). LRTI lower respiratory tract infections, URTI upper
respiratory tract infections
Fig. 4 Egger
’
s publication bias plot of studies for temperature drop and
asthma
Fig. 5 Begg
’
s funnel plot of studies for temperature drop and asthma
Environ Sci Pollut Res
of heterogeneity and to improve the analysis of the data
available.
Critical windows of exposure
Age
Stratification by exposure of time windows (childhood and
adult) reduced the heterogeneity and showed a stronger asso-
ciation for exposure during childhood. This result is in agree-
ment with the current evidence suggesting that asthma results
from molecular damage that may be incurred in childhood
(Tenero et al. 2016). Previous reports demonstrated that asth-
ma in children correlates with Clara cell protein CC10 poly-
morphism G + 38A and levels of lower CC10 (Yang et al.
2007). It is noteworthy that Demello et al. observed that tem-
perature drop could inhibit normal cell differentiation similar
to that found for Clara cells in vivo (Demello et al. 2002). To
our knowledge, investigation of cord blood IgE levels could
be a predictive risk factor for asthma (Renkonen et al. 2010);
the IL33-IL1RL1 pathway may play an important role in the
association with persistent asthma (Savenije et al. 2014).
However, the immune system of children is less mature.
Moreover, studies reported that temperature drop can also
suppress the immune system as well as aggravate respiratory
conditions in children (Tod et al. 2016).
Seasons
Only a limited number of studies have reported data for
different seasons of asthma, and the data of two studies
were extracted to calculate the pooled estimates of sec-
ondary analyses. Exposure in winter shows significantly
increased risk of asthma without evidence of heterogene-
ity. It indicates that long-term temperature drop or a lower
temperature level has an impact on asthma. Heir et al.
found that cold air could stimulate the parasympathetic
nervous system, increasing inflammation by generation
of mediators like cysteinyl1 leukotrienes, which increased
contraction of the bronchial smooth muscle and induced
mucus hyperescretion (Heir et al. 1995). Furthermore,
cold air could gate the transient receptor potential
melastain 8 (TRPM8); TRPM8 may provide a mechanistic
link for the manipulation of respiratory sensations such as
dyspnea or mechanisms leading to cold-induced asthma
(Fisher, 2011). These evidences further reveal the adverse
effect of winter. In addition, Nakaji et al. reported that
seasonality affects the incidence of respiratory diseases,
including asthma, pneumonia, and influenza, and the
highest prevalence of these diseases occurs during winter
(Nakaji et al. 2004; Hou et al. 2016).
Latitude
Data show a significant association between temperature drop
at different latitudes and asthma. The risk was the highest
when at low latitude without any heterogeneity. Our results
are consistent with studies that latitude as a possible surrogate
of climate factor could contribute to the prevalence of asthma
in various countries. Areas near the equator display more fre-
quent asthma (Hughes et al. 2011;Soleetal.2006). Although
there are no prior studies to elucidate the association between
temperature drop and asthma at different latitudes, studies
have revealed that latitude has an effect on asthma prevalence
through climate (including temperature change) and its rela-
tion to allergens or viral infections, or vitamin D intake and
ultraviolet radiation (Hughes et al. 2011;Sheaetal.2008;du
Prel et al. 2009; Soebiyanto et al. 2010;Malloletal.2010;Wu
et al. 2008; Arnedo-Pena et al. 2011). These findings suggest
that in a region with higher baseline ambient temperature, a
short-term temperature drop has a higher risk of asthma than
in a region with lower baseline temperature. It could imply
that a potential increased risk of the occurrence of asthma into
the future as the global mean temperature continues to rise,
when a short-term temperature drop occurs. Previous reports
demonstrated that global warming and climate change can
affect and adjust the ability of organisms to adapt to the chang-
ing environment, and reduce offspring fitness (Sears and
Angilletta, 2011; Bartolini et al. 2013).
Regions
We observed an association between increased asthma
risk and temperature drop in all regions, especially in
America and Europe, which is in line with most previous
studies. Currently, 8.4% of individuals in the USA have
asthma contrast to 4.3% of the population worldwide
(Loftus et al. 2016). Adult asthma prevalence is generally
lower in Asia than in Europe (Song et al. 2014). Studies
show that environment factors are more important than
ethnicity in controlling asthma. Meteorological condi-
tions, such as atmospheric pressure, temperature, humidi-
ty, and diurnal amplitude, could be important factors, for
regional differences in risk of asthma (Wang, 2016). In
recent years, we have also found that there is a remarkable
increase in the incidence of asthma in other regions. In
Asia, asthma is a major chronic disease (Thompson et al.
2013;Bramanetal.2006) and the prevalence of child-
hood asthma has continuously increased for decades
(Wong et al. 2013). In Australia, the prevalence of asthma
in children is among the highest (about 1 in 8 children) in
the world, and is continuing to increase (Li et al. 2014).
Studies suggested that global warming and abnormal cli-
mate events, one of the biggest concerns focused on the
effect of temperature, pose an important threat to asthma
Environ Sci Pollut Res
and are set to trigger a surge in numbers of asthma attacks
(Ault, 2004;Costelloetal.2009). However, there is not
still enough evidence to explain the main cause of the
regional difference of asthma attacks.
Limitations
The results of our meta-analysis have some limitations.
Ideally, the highest qualitative evidence available for the asso-
ciation of temperature drops with asthma risk requires lower
heterogeneity in the meta-analysis. However, we found high
or moderate heterogeneity in our meta-analyses. These find-
ings indicate that other factors, such as air pollution and pol-
len, could affect heterogeneity among the included studies.
Air pollution and pollen are regarded as important risk factors
of asthma; pollen transmission is related to temperature. Air
pollution and pollen are not taken into account in this study
due to the limited evidence. Therefore, further meta-analysis is
needed to explore the sources of heterogeneity in the future.
Conclusion
Overall, this meta-analysis observed a clear association be-
tween temperature drop and risk of asthma, and children, win-
ter and low-latitude area might be the critical windows for
adverse effects. Moreover, we also observed an elevated risk
of asthma in America and Europe. These results extend our
understanding of the adverse effect of temperature drop on
asthma, and suggest that the preventive actions against tem-
perature drop would help to decrease the risk of asthma, espe-
cially in critical windows, which is the main conclusion and
purpose of this meta-analysis.
Acknowledgements This study was supported by the National Natural
Science Foundation of China (21377077). We would like to thank Dr.
Stanley Lin for his constructive comments and English language editing.
Compliance with ethical standards
Conflict of interest The authors declare that they have no conflict of
interest.
References
Abe T, Tokuda Y, Ohde S, Ishimatsu S, Nakamura T, Birrer RB (2009)
The relationship of short-term air pollution and weather to ED visits
for asthma in Japan. Am J Emerg Med 27:153–159
Arnedo-Pena A, Garcia-Marcos L, Fernandez-Espinar JF, Bercedo-Sanz
A, Aguinaga-Ontoso I, Gonzalez-Diaz C et al (2011) Sunny hours
and variations in the prevalence of asthma in schoolchildren accord-
ing to the International Study of Asthma and Allergies (ISAAC)
phase III in Spain. Int J Biometeorol 55:423–434
Ault A (2004) Report blames global warming for rising asthma. Lancet
363(363):1532
Beard JD, Beck C, Graham R, Packham SC, Traphagan M, Giles RT et al
(2012) Winter temperature inversions and emergency department
visits for asthma in Salt Lake County, Utah, 2003-2008. Environ
Health Perspect 120:1385–1390
Bolger C, Tufvesson E, Anderson SD, Devereux G, Ayres JG, Bjermer L
et al (2011) Effect of inspired air conditions on exercise-induced
bronchoconstriction and urinary CC16 levels in athletes. J Appl
Physiol 111:1059–1065
Bartolini F, Barausse A, Pörtner HO, Giomi F (2013) Climate change
reduces offspring fitness in littoral spawners: a study integrating
organismic response and long-term time-series. Glob Chang Biol
19:373–386
Braman SS (2006) The global burden of asthma. Chest 130:4–12
Buckley JP, Richardson DB (2012) Seasonal modification of the associ-
ation between temperature and adult emergency department visits
for asthma: a case-crossover study. Environ Health 11:55
Carlsen KH (2012) Sports in extreme conditions: the impact of exercise in
cold temperatures on asthma and bronchial hyper-responsiveness in
athletes. Br J Sports Med 46:796–769
Celenza A, Fothergill J, Kupek E, Shaw RJ (1996) Thunderstorm asso-
ciated asthma: a detailed analysis of environmental factors. BMJ
312:604–607
Chen L, Liu M, Bao J, Xia Y, Zhang J, Zhang L et al (2013) The corre-
lation between apparent diffusion coefficient and tumor cellularity in
patients: a meta-analysis. PLoS One 8:e79008
Costello A, Abbas M, Allen A, Ball S, Bell S, Bellamy R et al (2009)
Managing the health effects of climate change: Lancet and
University College London Institute for Global Health
Commission. Lancet 373:1693–1733
Darçın M (2014) Association between air quality and quality of life.
Environ Sci Pollut Res Int 21:1954–1959
Demello DE, Mahmoud S, Ryerse J, Hoffmann JW (2002) Generation
and characterization of a conditionally immortalized lung clara cell
line from the H-2Kb-tsA58 transgenic mouse. In vitro cellular &
developmental biology Animal 38:154–164
du Prel JB, Puppe W, Grondahl B, Knuf M, Weigl JA, Schaaff F, Schmitt
HJ (2009) Are meteorological parameters associated with acute re-
spiratory tract infections? Clin Infect Dis 49:861–868
Eder W, Ege MJ, von Mutius E (2006) Current concepts: the asthma
epidemic. New Engl J Med 355:2226–2235
Egger M, Davey Smith G, Schneider M, Minder C (1997) Bias in meta-
analysis detected by a simple, graphical test. BMJ 315:629–634
Epton MJ, Martin IR, Graham P, Healy PE, Smith H, Balasubramaniam R
et al (1997) Climate and aeroallergen levels in asthma: a 12 month
prospective study. Thorax 52:528–634
Fan J, Li S, Fan C, Bai Z, Yang K (2016) The impact of PM
2.5
on asthma
emergency department visits: a systematic review and meta-analy-
sis. Environ Sci Pollut Res Int 23:843–850
Fisher JT (2011) TRPM8 and dyspnea: from the frigid and fascinating
past to the cool future? Curr Opin Pharmacol 11:218–223
Gleason JA, Bielory L, Fagliano JA (2014) Associations between ozone,
PM
2.5
, and four pollen types on emergency department pediatric
asthma events during the warm season in New Jersey: a case-
crossover study. Environ Res 132:421–429
Gonzalez DA, Victora CG, Goncalves H (2008) The effects of season at
time of birth on asthma and pneumonia in childhood and adulthood
in a birth cohort in southern Brazil. Cadernos de saude publica 24:
1089–1102
Guo Y, Jiang F, Peng L, Zhang J, Geng F, Xu J et al (2012) The associ-
ation between cold spells and pediatric outpatient visits for asthma in
Shanghai, China. PLoS One 7:e42232
Handley BA, Webster AJ (1995) Some factors affecting the airborne
survival of bacteria outdoors. The Journal of applied bacteriology
79:368–378
Environ Sci Pollut Res
Heir T, Aanestad G, Carlsen KH, Larsen S (1995) Respiratory tract in-
fection and bronchial responsiveness in elite athletes and sedentary
control subjects. Scand J Med Sci Sports 5:94–99
Hirabayashi N, Wada K, Kimura T, Hirabayashi E, Mishima S, Yukioka T
et al (2004) Prevalence of substance abuse among patients with
physical diseases seen in an emergency room in Japan. Am J
Addict 13:398–404
Hou W, Xu X, Lei Y, Cao J, Zhang Y, Chen L et al (2016) The role of the
PM
2.5
-associated metals in pathogenesis of child Mycoplasma
pneumoniae infections: a systematic review. Environ Sci Pollut
Res Int 23:10604–10614
Hughes AM, Lucas RM, Ponsonby AL, Chapman C, Coulthard A, Dear
K et al (2011) The role of latitude, ultraviolet radiation exposure and
vitamin D in childhood asthma and hay fever: an Australian multi-
center study. Pediatr Allergy Immunol 22:327–333
Jacobs J, Kreutzer R, Smith D (1997) Rice burning and asthma hospital-
izations, Butte County, California, 1983-1992. Environ Health
Perspect 105:980–985
Kaminsky DA, Bates JH, Irvin CG (2000) Effects of cool, dry air stim-
ulation on peripheral lung mechanics in asthma. Am J Respir Crit
Care Med 162:179–186
Khalaj B, Lloyd G, Sheppeard V, Dear K (2010) The health impacts of
heat waves in five regions of New South Wales, Australia: a case-
only analysis. Int Arch Occup Environ Health 83:833–842
Kiechl-Kohlendorfer U, Horak E, Mueller W, Strobl R, Haberland C,
Fink FM et al (2007) Living at high altitude and risk of
hospitalisation for atopic asthma in children: results from a large
prospective birth-cohort study. Arch Dis Child 92:339–342
Kim S, Kim Y, Lee MR, Kim J, Jung A, Park JS et al (2012) Winter
season temperature drops and sulfur dioxide levels affect on exac-
erbation ofrefractory asthma in South Korea: a time-trend controlled
case-crossover study using Soonchunhyang Asthma Cohort data. J
Asthma 49:679–687
Kippelen P, Fitch KD, Anderson SD, Bougault V, Boulet LP, Rundell KW
et al (2012) Respiratory health of elite athletes—preventing airway
injury: a critical review. Br J Sports Med 46:471–476
Kippelen P, Anderson SD (2012) Airway injury during high-level exer-
cise. Br J Sports Med 46:385–390
Lee YL, Lin YC, Hwang BF, Guo YL (2005) Changing prevalence of
asthma in Taiwanese adolescents: two surveys 6 years apart. Pediatr
Allergy Immu 16:157–164
Lian H, Ruan Y, Liang R, Liu X, Fan Z (2015) Short-term effect of
ambient temperature and the risk of stroke: a systematic review
and meta-analysis. Int J Environ Res Public Health 12(8):9068–
9088
Lin S, Liu X, Le LH, Hwang SA (2008) Chronic exposure to ambient
ozone and asthma hospital admissions among children. Environ
Health Perspect 116:1725–1730
Li SS, Baker PJ, Jalaludin BB, Guo YM, Marks GB, Denison LS et al
(2014) Are children's asthmatic symptoms related to ambient tem-
perature? A panel study in Australia. Environ Res 133:239–245
Loftus PA, Wise SK (2016) Epidemiology of asthma. Current opinion in
otolaryngology & head and neck surgery 24:245–249
Lombardi E, Morgan WJ, Wright AL, Stein RT, Holberg CJ, Martinez FD
(1997) Cold air challenge at age 6 and subsequent incidence of
asthma. A longitudinal study American journal of respiratory and
critical care medicine 156:1863–1869
Makinen TM, Juvonen R, Jokelainen J, Harju TH, Peitso A, Bloigu A
et al (2009) Cold temperature and low humidity are associated with
increased occurrence of respiratory tract infections. Respir Med 103:
456–462
Mallol J, Sole D, Baeza-Bacab M, Aguirre-Camposano V, Soto-Quiros
M, Baena-Cagnani C et al (2010) Regional variation in asthma
symptom prevalence in Latin American children. J Asthma 47:
644–650
May L, Carim M, Yadav K (2011) Adult asthma exacerbations and envi-
ronmental triggers: a retrospective review of ED visits using an
electronic medical record. Am J Emerg Med 29:1074–1082
Mi YH, Norback D, Tao J, Mi YL, Ferm M (2006) Current asthma and
respiratory symptoms among pupils in Shanghai, China: influence
of building ventilation, nitrogen dioxide, ozone, and formaldehyde
in classrooms. Indoor Air 16:454–464
Nakaji S, Parodi S, Fontana V, Umeda T, Suzuki K, Sakamoto J et al
(2004) Seasonal changes in mortality rates from main causes of
death in Japan (1970-1999). Eur J Epidemiol 19:905–913
Onakpoya IJ, O'Sullivan J, Thompson MJ, Heneghan CJ (2015) The effect
of wind turbine noise on sleep and quality of life: a systematic review
and meta-analysis of observational studies. Environ Int 82:1–9
Paynter S, Ware RS, Weinstein P, Williams G, Sly PD (2010) Childhood
pneumonia: a neglected, climate-sensitive disease? Lancet
376(9755):1804–1805
Phung D, Thai PK, Guo YM, Morawska L, Rutherford S, Chu C (2016)
Ambient temperature and risk of cardiovascular hospitalization: an
updated systematic review and meta-analysis. Sci Total Environ
550:1084–11 02
Pino P, Walter T, Oyarzun M, Villegas R, Romieu I (2004) Fine particu-
late matter and wheezing illnesses in the first year of life.
Epidemiology 15:702–708
Renkonen J, Joenvaara S, Parviainen V, Mattila P, Renkonen R (2010)
Network analysis of single nucleotide polymorphisms in asthma. J
Asthma Allergy 3:177–186
Rumchev K, Spickett J, Bulsara M, Phillips M, Stick S (2004)
Association of domestic exposure to volatile organic compounds
with asthma in young children. Thorax 59:746–751
Sears MW, Angilletta MJ Jr (2011) Introduction to the symposium: re-
sponses of organisms to climate change: a synthetic approach to the
role of thermal adaptation. Integr Comp Biol 51:662–665
Soto-Quiros M, Bustamante M, Gutierrez I, Hanson LA, Strannegard IL,
Karlberg J (1994) The prevalence of childhood asthma in Costa
Rica. Clin Exp Allergy 24:1130–1136
Savenije OE, John JMM, Granell R, Kerkhof M, Dijk FN, de Jongste JC
et al (2014) Association of IL33-IL-1 receptor-like1 (IL1RL1) path-
way polymorphisms with wheezing phenotypes and asthma in
childhood. J Allergy Clin Immun 134:170–177
Shang S, Li J, Zhao Y, Xi Z, Lu Z, Li B et al (2017) Oxidized graphene-
aggravated allergic asthma is antagonized by antioxidant vitamin E
in Balb/c mice. Environ Sci Pollut Res Int 24:1784–1793
Shea KM, Truckner RT, Weber RW, Peden DB (2008) Climate change
and allergic disease. J Allergy Clin Immunol 122:443–453
Soebiyanto RP, Adimi F, Kiang RK (2010) Modeling and predicting
seasonal influenza transmission in warm regions using climatologi-
cal parameters. PLoS One 5:e9450
Sole D, Wandalsen GF, Camelo-Nunes IC, Naspitz CK, Group IB (2006)
Prevalence of symptoms of asthma, rhinitis, and atopic eczema
among Brazilian children and adolescents identified by the
International Study of Asthma and Allergies in Childhood
(ISAAC)-phase 3. J Pediatr 82:341–346
Song WJ, Kang MG, Chang YS, Cho SH (2014) Epidemiology of
adult asthma in Asia: toward a better understanding. Asia Pac
Allergy 4:75–85
Tenero L, Piazza M, Piacentini G (2016) Recurrent wheezing in children.
Translational pediatrics 5:31–36
Thompson PJ, Salvi S, Lin JT, Cho YJ, Eng P, Manap RA et al (2013)
Insights, attitudes and perceptions about asthma and its treatment:
findings from a multinational survey of patients from 8 Asia-Pacific
countries and Hong Kong. Respirology 18:957–967
Tod AM, Nelson P, Cronin de Chavez A, Homer C, Powell-Hoyland V,
Stocks A (2016) Understanding influences and decisions of house-
holds with children with asthma regarding temperature and humidity
in the home in winter: a qualitative study. BMJ Open 6:e009636
Environ Sci Pollut Res
Villeneuve PJ, Leech J, Bourque D (2005) Frequency of emergency room
visits for childhood asthma in Ottawa, Canada: the role of weather.
Int J Biometeorol 50:48–56
Wang W (2016) Progress in the impact of polluted meteorological con-
ditions on the incidence of asthma. J Thorac Dis 8:E57–E61
Wang YC, Lin YK (2014) Association between temperature and
emergency room visits for cardiorespiratory diseases, metabolic
syndrome-related diseases, and accidents in metropolitan
Taipei. PLoS One 9:e99599
Wasilevich EA, Rabito F, Lefante J, Johnson E (2012) Short-term outdoor
temperature change and emergency department visits for asthma
among children: a case-crossover study. Am J Epidemiol 176:123–130
WHO (2013) Asthma http://www.who.int/mediacentre/factsheets/fs307/en/
WHO (2016) Controlled temperature chain (CTC) http://www.who.int/
immunization/programmes_systems/supply_chain/ctc/en/
Wong GW, Leung TF, Ko FW (2013) Changing prevalence of allergic
diseases in the Asia-pacific region. Allergy Asthma Immunol Res 5:
251–257
Wu P, Dupont WD, Griffin MR, Carroll KN, Mitchel EF, Gebretsadik T
et al (2008) Evidence of a causal role of winter virus infection during
infancy in early childhood asthma. Am J Respir Crit Care Med 178:
1123–1129
Xu ZW, Huang CR, Hu WB, Turner LR, Su H, Tong SL (2013) Extreme
temperatures and emergency department admissions for childhood
asthma in Brisbane, Australia. Occup Environ Med 70:730–735
Yamazaki S, Shima M, Yoda Y, Oka K, Kurosaka F, Shimizu S et al
(2015) Exposure to air pollution and meteorological factors associ-
ated with children's primary care visits at night due to asthma attack:
case-crossover design for 3-year pooled patients. BMJ Open 5:
e005736
Yang KD, Ou CY, Chang JC, Chen RF, Liu CA, Liang HM et al (2007)
Infant frequent wheezing correlated to Clara cell protein 10 (CC10)
polymorphism and concentration, but not allergy sensitization, in a
perinatal cohort study. J Allergy Clin Immunol 120:842–848
Zanazzi A, Kohn MJ, MacFadden BJ, Terry DO (2007) Large tempera-
ture drop across the Eocene-Oligocene transition in central North
America. Nature 445:639–642
Zanolin ME, Pattaro C, Corsico A, Bugiani M, Carrozzi L, Casali L et al
(2004) The role of climate on the geographic variability of asthma,
allergic rhinitis and respiratory symptoms: results from the Italian
study of asthma in young adults. Allergy 59:306–314
Zhang Y, Peng L, Kan H, Xu J, Chen R, Liu Y et al (2014) Effects of
meteorological factors on daily hospital admissions for asthma in
adults: a time-series analysis. PLoS One 9:e102475
Environ Sci Pollut Res
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