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\begin{document}

\title{The Influence of Constipation on Asthma: A Real-world, Population-based
Cohort Study}



\author[1]{Yen Chu Huang}%
\author[1]{Meng Che Wu}%
\author[2]{Yu-Hsun  Wang}%
\author[3]{James Cheng-Chung Wei}%
\affil[1]{Taichung Veterans General Hospital}%
\affil[2]{Chung Shan Medical University, Taichung,}%
\affil[3]{Chung Shan Medical University}%


\vspace{-1em}



  
  \date{May 07, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
Background Among respiratory diseases, asthma is one of the most
burdensome disorder worldwide. Growing evidence disclose gut dysbiosis
may contribute to asthma via the gut-lung axis. Constipation can lead to
alteration of the gut microflora. The clinical impact of constipation on
asthma has not been researched. Therefore, we aim to assess the risk of
asthma in constipated patients by a nationwide population-based cohort
study. Methods We analyzed 82421 constipated patients and 82421
individuals without constipation between 1999 and 2013 from the
Taiwanese National Health Insurance Research Database. Analysis of
propensity score was utilized to match age, gender, comorbidities, and
medications at a ratio of 1:1. Besides, multiple Cox regression analysis
was performed to evaluate the adjusted hazard ratio of asthma.
Furthermore, sensitivity tests and a stratified analysis were conducted.
Results The incidence of asthma was 10.8 per 1,000 person-years in the
constipation group, which was higher than the rate of 5.6 per 1,000
person-years observed in the non-constipation group. After adjustment
for age, gender, comorbidities, and medications, constipated patients
had a 1.91-fold greater risk of asthma compared to those without
constipation (adjusted hazard ratio {[}aHR{]}: 1.91 (95\% C.I.
1.84-1.99). In subgroup analyses, patients aged 20-39 years had a
2.04-fold highest risk of asthma in the constipation cohort (aHR:2.04,
95\% CI, 1.84-2.26). Besides, the severity of constipation is associated
with an increased risk of asthma; the aHR was 1.76 (1.69-1.85),
2.15(2.03-2.27), and 2.29(2.10-2.49) for \textless{} 3 times, 3-12
times, and [?]12 times of laxatives prescription within one year,
respectively. (p\textless{}0.001) Moreover, constipated patients had a
higher likelihood of asthma, regardless of gender, comorbidities, and
medications. Conclusion Constipation relates to a significantly
increased risk of asthma. Physicians should be aware of the possibility
of asthma in constipated people. Further research is warranted to
investigate the possible pathological mechanisms of this association.%
\end{abstract}%



\sloppy


\textbf{The Influence of Constipation on Asthma: A Real-world,
Population-based Cohort Study}

\textbf{Yen-Chu HUANG,\textsuperscript{1,}}
\textsuperscript{++}\textbf{Meng-Che WU,\textsuperscript{1,}}
\textsuperscript{++}\textbf{, Yu-Hsun WANG,\textsuperscript{2} James
Cheng-Chung WEI\textsuperscript{3,4}}

\textsuperscript{1}\emph{Division of Pediatric Gastroenterology,
Children's Medical Center, Taichung Veterans General
Hospital,}\textsuperscript{2}\emph{Department of Medical Research, Chung
Shan Medical University Hospital} ,

\emph{\textsuperscript{3}Division of Allergy, Immunology and
Rheumatology, Chung Shan Medical University Hospital; Institute of
Medicine, College of Medicine, Chung Shan Medical
University,\textsuperscript{4}Graduate Institute of Integrated Medicine,
China Medical University}

\textbf{Short running title: Constipation and asthma}

Correspondence: James Cheng-Chung Wei, Institute of Medicine, Chung Shan
Medical University, No. 110, Sec 1, Jianguo N. Road, Taichung City,
40201, Taiwan. Email: jccwei@gmail.com

\textbf{Disclosures relevant to this paper: None}

++ Yen-Chu Huang and Meng-Che Wu are co-first authors

\textbf{ABSTRACT}

\textbf{Background}

Among respiratory diseases, asthma is one of the most burdensome
disorder worldwide. Growing evidence disclose gut dysbiosis may
contribute to asthma via the gut-lung axis. Constipation can lead to
alteration of the gut microflora. The clinical impact of constipation on
asthma has not been researched. Therefore, we aim to assess the risk of
asthma in constipated patients by a nationwide population-based cohort
study.

\textbf{Methods}

We analyzed 82421 constipated patients and 82421 individuals without
constipation between 1999 and 2013 from the Taiwanese National Health
Insurance Research Database. Analysis of propensity score was utilized
to match age, gender, comorbidities, and medications at a ratio of 1:1.
Besides, multiple Cox regression analysis was performed to evaluate the
adjusted hazard ratio of asthma. Furthermore, sensitivity tests and a
stratified analysis were conducted.

\textbf{Results}

The incidence of asthma was 10.8 per 1,000 person-years in the
constipation group, which was higher than the rate of 5.6 per 1,000
person-years observed in the non-constipation group. After adjustment
for age, gender, comorbidities, and medications, constipated patients
had a 1.91-fold greater risk of asthma compared to those without
constipation (adjusted hazard ratio {[}aHR{]}: 1.91 (95\% C.I.
1.84-1.99). In subgroup analyses, patients aged 20-39 years had a
2.04-fold highest risk of asthma in the constipation cohort (aHR:2.04,
95\% CI, 1.84-2.26). Besides, the severity of constipation is associated
with an increased risk of asthma; the aHR was 1.76 (1.69-1.85),
2.15(2.03-2.27), and 2.29(2.10-2.49) for \textless{} 3 times, 3-12
times, and [?]12 times of laxatives prescription within one year,
respectively. (p\textless{}0.001) Moreover, constipated patients had a
higher likelihood of asthma, regardless of gender, comorbidities, and
medications.

\textbf{Conclusion}

Constipation relates to a significantly increased risk of asthma.
Physicians should be aware of the possibility of asthma in constipated
people. Further research is warranted to investigate the possible
pathological mechanisms of this association.

\textbf{Key words: constipation, asthma,} \textbf{Longitudinal Health
Insurance Database, gut microflora, dysbiosis}

\textbf{What's Known?}

Recent studies showed that intestinal dysbiosis contributes to asthma
via the gut-lung axis.

Constipation can lead to alteration of the gut microflora.

\textbf{What's New?}

Constipated people had a 1.91-fold greater risk for asthma compared with
those without constipation. Furthermore, patients with constipation had
a higher likelihood of asthma, regardless of gender, comorbidities, as
well as the usage of corticosteroids and antihistamines.

Constipation relates to a significantly risk factor of asthma. Physician
should take care of the possibility of developing asthma in constipated
patients.

\textbf{INTRODUCTION}

Among respiratory diseases, asthma is one of the most burdensome
disorder both affects in childhood and adulthood. The prevalence was
estimated that there were more than 272 million people had asthma
worldwide in 2017.{[}1{]} Asthma not only increases financial, social,
and psychological burdens, but also makes a harmful impact on quality of
life, and is connected with comorbidities.{[}2{]} Interestingly, there
is increasing evidence presenting an connection between asthma and
constipation{[}3{]}, a common condition affecting adults and children
globally and a frequent reason for visits to physicians. The mean global
prevalence of constipation in children is 12\% and that in adult is
16\%. {[}4{]} Even though constipation has few complications of
life-threatening, it can make physical and mental distress for patients
and their families, eventually impairing quality of life. Complications
of constipation included hemorrhoids, rectal prolapse, and fecal or
urine incontinence, which usually increases the frequency of
hospitalizations or outpatient department visits, leading to increased
burdens of health insurance.

Nowadays, constipation is seemed to be a causative factor in intestinal
dysbiosis{[}5{]} and therapeutic managements are increasingly
incorporating prebiotics, probiotics{[}6{]}, or synbiotics with a view
to regulating the intestinal microflora{[}7, 8{]}. Moreover, recent
research has demonstrated that the gut microbiota would exert important
regulatory effects via the gut-lung axis.{[}9-11{]} For instance, gut
dysbiosis{[}12{]} and lower concentration of short-chain fatty acids
(SCFAs) in the bowel are found in patients with asthma. This condition
decreases the production of butyrate and propionate, leading to the
dysregulation of gut inflammation and the defect of the intestinal
epithelial barriers, resulting in leaky gut and allow penetration of
microorganisms and toxins into systemic circulation, thereby activating
Th2 immune responses, eventually contributing to airway inflammation.
Some research have suggested that allergic diseases might be associated
with constipation.{[}13, 14{]} Furthermore, previous study has
demonstrated that stool stasis in the long time could influence the
microbiota and environment of gut, resulting in deleterious effects on
mucosal immunity and intestinal motility.{[}15{]} Whether if
constipation predisposes susceptible people to asthma is unknown. At
present, there are still scanty data on the connection between
constipation and asthma in the literature. In addition, this association
has never been investigated using a large-scale national longitudinal
database. We hypothesized that constipation might influence the risk of
asthma and assessed this hypothesis by analyzing a real-world,
population-based retrospective cohort from National Health Insurance
Research Database (NHIRD) in Taiwan.

\textbf{METHODS}

\textbf{Data source}

This study analyzed the National Health Insurance Research Database
(NHIRD) that contains the healthcare data of almost 99\% of Taiwan's
entire population, approximately 23 million NHI beneficiaries. The
database includes all insurance claims data, including outpatient
visits, emergency visits, and hospitalizations. The Longitudinal Health
Insurance Database, (LHID) is a subset of the NHIRD comprising one
million individuals randomly sampled from the 23 million NHI
beneficiaries for the period from 1999 to 2013.{[}16{]} The data of
patients were de-identified prior to release to the users, in accordance
with privacy protocols, and this study was approved by the Institutional
Review Board of Chung Shan Medical University Hospital (IRB no.
CS15134).

\textbf{Study group and outcome measurement}

The population was composed of patients with newly diagnosed
constipation (ICD-9-CM codes=564.0) from 2000 to 2012. To ensure
accuracy of diagnoses, we excluded any diagnosis of constipation before
2000 and only patients with at least three outpatient visits or one
hospitalization were selected for inclusion in the final analysis. The
index date of this cohort was set as the first date of diagnosis of
constipation. Furthermore, to ensure that all individuals had new-onset
asthma, we ruled out any diagnosis of asthma (ICD-9-CM=493) happening
before the index date. The non-constipation group constituted subjects
who had never been diagnosed with constipation for the period 1999 to
2013.

The outcome variable was defined as a diagnosis of asthma with at least
three outpatient visits or once hospitalization. The patients were
followed up until the occurrence of atopic dermatitis, 31 December 2013,
or withdrawal from the National Health Insurance system, whichever
occurred first.

\textbf{Covariates and matching}

The baseline characteristics were age, gender, hypertension
(ICD-9-CM=401-405), hyperlipidemia (ICD-9-CM=272.0-272.4), chronic
kidney disease (ICD-9-CM=585), chronic liver disease (ICD-9-CM=571),
chronic obstructive pulmonary disease (COPD) (ICD-9-CM =491, 492, 496),
cancer (ICD-9-CM=140-208), diabetes (ICD-9-CM=250), cardiovascular
disease (ICD-9-CM=410-414), stroke (ICD-9-CM=430-438), and autoimmune
disease (ICD-9-CM=710.0, 720.0, 714.0). The comorbidities were defined
as occurring within one year prior to the index date with at least three
outpatient visits or once hospitalization. Besides, corticosteroids and
antihistamines during the study period were included and defined as
usage for at least [?]30 days. To assess the severity of constipation, we
collected additional information on the total numbers of laxatives
prescription (anatomical therapeutic chemical {[}ATC{]} classification
system code A06A), which occurred within one year after the index date.

Moreover, propensity score matching based on age, gender, hypertension,
hyperlipidemia, chronic kidney disease, chronic liver disease, COPD,
cancer, diabetes, cardiovascular disease, stroke, autoimmune disease,
corticosteroids, and antihistamines was applied to balance the
heterogeneity of the two groups. The propensity score was a probability
that was estimated through logistic regression. The binary variable was
the constipation and non-constipation group.

\textbf{Statistical analysis}

Comparisons between the constipation group and non-constipation group
were using absolute standardized differences (ASD). Whenever the ASD
were less than 0.1, the characteristics of the two groups were deemed to
be similar. On the other hand, Kaplan-Meier analysis was applied to
calculate the cumulative incidence of asthma and then log-rank test was
used to test the significance. Cox proportional hazard model was applied
to estimate the hazard ratio of asthma between the constipation and
non-constipation groups.

\textbf{RESULTS}

The flowchart is presented in Fig. 1. We identified 82421 patients with
constipation and 82421 matched controls between 1999 and 2013 from the
LHID. Demographic characteristics of this study participants are shown
in Table 1. The constipated patients and non-constipation cohort were
similar in age and gender distribution. After propensity score matching,
there were no statistically significant differences between the
constipation and non-constipation groups.

As shown in Table 2, the incidence of asthma was 10.8 per 1,000
person-years in the constipation group, which was higher than the rate
of 5.6 per 1,000 person-years observed in the non-constipation group.
After adjustment, patients with constipation had a significantly higher
risk of asthma than those without constipation (aHR:1.91, 95\% C.I.
1.84-1.99, p\textless{}0.001). Compared with women, men had a
significantly higher risk of asthma (aHR:1.17; 95\% CI, 1.12-1.22;
p\textless{}0.001). In term of comorbidities, we observed that people
with hypertension, COPD, or autoimmune disease had a relatively higher
risk of asthma. (hypertension:1.22, 95\% C.I. 1.15-1.29,
p\textless{}0.001; COPD:3.21, 95\% C.I. 2.94-3.50, p\textless{}0.001;
autoimmune disease:1.42, 95\% C.I. 1.17-1.73, p\textless{}0.001). By
contrast, patients using corticosteroids or antihistamines during the
study for period at least 30 days had a lower risk of asthma.
(corticosteroids: 0.80, 95\% C.I. 0.76-0.84, p\textless{}0.001;
antihistamines: 0.61, 95\% C.I. 0.59-0.64, p\textless{}0.001)

Table 3 showed that subgroup analyses were performed to assess the
association between constipation and asthma based on demographic
characteristics. Patients in the constipation group aged 20-39 years,
had a 2.04-fold greater risk of asthma compared with the same age group
in the non-constipation group (aHR; 95\% CI,1.84-2.26, P \textless{}
0.001). Patients aged \textless{}20, 40-64, and [?]65 years in the
constipation group had a 1.85, 1.70, and 2.02-fold greater risk of
asthma.(aHR; 95\% CI, 1.69-2.01, 1.57-1.83 and 1.89-2.16; P \textless{}
0.001), respectively. Among females, compared with those without
constipation, there was a 1.86-fold higher risk of asthma in patients
with constipation (aHR; 95\% CI, 1.77-1.96; P \textless{} 0.001). Among
males, there was 1.92-fold higher risk of asthma in patients with
constipation (aHR; 95\% CI, 1.80-2.04; P \textless{} 0.001).
Furthermore, constipated patients had a higher likelihood of asthma,
regardless of comorbidities and medications.

In addition, Table 4 presents that analysis for risk of asthma in
constipated patients with laxatives prescription. Compared to
participants without constipation, the adjusted hazard ratio was 1.76
(95\% CI, 1.69-1.85; P \textless{} 0.001), 2.15(95\% CI, 2.03-2.27; P
\textless{} 0.001), and 2.29(95\% CI, 2.10-2.49; P \textless{} 0.001)
for \textless{} 3 times, 3-12 times, and [?]12 times of laxatives
prescription within one year, respectively. There appeared to be a
dose-effect relationship between constipation severity and risk of
asthma.The Kaplan--Meier curves are shown in Fig. 2. The cumulative
incidence of asthma was significantly higher in constipated patients
than in non-constipated patients, and the log-rank test for the
comparison of cumulative incidence curves resulted in a P-value of
\textless{}0.001

\textbf{DISCUSSION}

In this study, people with constipation had a 1.91-fold higher risk for
developing asthma than non-constipated individuals, regardless of age,
gender, comorbidities or medications. As far as we know, this is the
largest epidemiological research by using a nationwide longitudinal
population-based dataset to expound the association between constipation
and asthma. This relationship might be of pathophysiological and
clinical importance. Our findings emphasize the considerably higher risk
of asthma in individuals with constipation. Constipation might be
influential in the development of asthma. Physicians should take care
about the possibility of asthma in patients with constipation.
Correspondingly, constipated patients should be informed of the probable
risk of asthma and be offered with applicable management for asthma as
required. Our findings further highlight the importance of maintaining
fair bowel habits in order to avoid constipation, which could in turn
mitigate risk of asthma.

We also observed that the risk of developing asthma was significantly
increased in patients with hypertension, chronic obstructive pulmonary
disease (COPD), chronic liver disease, and autoimmune disease. Most of
these comorbidities, such as COPD or autoimmune disease, were connected
to chronic inflammation, which could contribute to release of serum
cytokines and activate T-cell response. In addition, we further extended
to suggest that constipation severity is associated with the risk of
asthma. There seemed to be a dose-dependent relationship between
constipation and subsequent risk of asthma, which strengthened our
hypothesis.

The pathophysiological mechanisms underlying the association between
constipation and asthma remain ambiguous. Currently, there has been
considerable studies conducted between intestinal microbiota and
asthma.{[}17-21{]} The extended ``'hygiene hypothesis'' discloses that
the initial composition of the infant gut microflora plays a vital role
in the development of atopic diseases.{[}22-24{]} Another research in
United Kingdom, which analyzed the gut microbiome of the people with
asthma, showed that there were abundant with Clostridiums spp. whereas
Faecalibacterium prausnitzii and Bacteroides stercoris were depleted in
individuals with asthma.{[}25{]} Similarly, some researches have
suggested that alterations in the intestinal microflora would lead to
constipation and constipation-related symptoms.{[}5, 7{]} In contrast to
the healthy individuals, constipated patients had relatively higher
amount of potentially pathogenic microbes, such as Clostridiums spp. and
Pseudomonas aeruginosa, and relatively lower amount of Bacteroides spp.,
Bifidobacterium, and Lactobacillus.{[}26{]} These alternates in the
intestinal surroundings could affect bowel motility by the active
materials. Some studies exhibited that microbial-derived metabolites,
mainly short-chain fatty acids (SCFAs), acted as pivotal drivers of
T-cell subset activity and proliferation.{[}27{]} Furthermore, it has
been disclosed that production of bowel microbial SCFAs could
down-regulate proinflammatory reactions at the area of allergen
insult.{[}28{]} Moreover, SCFAs might influence bowel motility via
stimulating the contraction of colonic smooth muscles, thereby assisting
to present or relieve constipation.{[}29, 30{]} By contrast, immune
homeostasis would be devastated by proinflammatory dietary type, or
''Westernized dietary style'', which might be described as being low in
fiber and high in fat, changing the intestinal microbiota, and leading
to decrease SCFAs production. Hence, less fiber intake, such as fewer
fresh fruits, in patients with constipation might be also pivotal role
in developing atopy.{[}31, 32{]} Organizing the presently available
corroboration suggests that the gut microbiota might be a key
mechanistic part linking asthma and constipation. It is not known how
constipation influence the configuration of the intestinal microflora
and how applicable this condition is to asthma. Nevertheless,
constipation appears to be the predisposing point for asthma. Further
comprehensive metabolomic and metagenomic analyses of the gut microbiome
in constipated individuals are warranted to clarify the potential
mechanisms underlying these connections.

The major advantages of this study were the relatively large sample size
and long follow-up period. An integrated past history of used medical
services was accessible for all cases. Therefore, there was slightest
selection, information, and recall bias. As such, it was feasible to
properly examine our hypothesis. However, there some potential
limitations existed in our study. First, the NHIRD does not include data
on covariates, such as social adversity, personal lifestyle, family
history, laboratory data and environmental factors. Although we adjusted
for several comorbidities and matched propensity scores, these
unmeasured confounding factors could have influenced our results.
Second, the diagnoses of asthma and constipation were totally dependent
on the ICD-9 codes in the administrative dataset. We did not undergo a
review of the patients' medical documents so that it was not probable to
check the accuracy of diagnoses, and thus there might have some
misclassifications existed. It is worth noting, however, that any
misclassifications were more probably to be random, and connections were
often underestimated rather than overestimated. Besides, clinical
judgment might be different among clinicians, and so diagnoses would not
have been consistent, which might have affected the validity. However,
Taiwan's National Health Insurance administration monitors the accuracy
of the claims data to prevent violations. Finally, it keeps unclear as
to if the findings of our study may be extrapolated to other ethnic
groups, as the majority of our subjects were Taiwanese. Further clinical
research should include other nationalities and ethnicities to define
the generalizability of the relationship observed herein.

\textbf{CONCLUSION}

In conclusion, constipated people had a 1.91-fold greater risk for
asthma compared with those without constipation. Individuals with
constipation should be alert to the elevated risk of developing asthma.
Moreover, physicians should define the intestinal condition, including
the gut microbiome, in patients with asthma. The precise
pathophysiological association between constipation and asthma still
needs further research.

\textbf{ACKNOWLEDGMENTS:}

None.

\textbf{CONFLICT OF INTEREST:}

There is no conflict of interest in this study.

\textbf{FUNDING:}

The authors have not declared a specific grant for this study from any
funding agency in the public, commercial or not-for-profit sectors.

\textbf{AVAILABILITY OF DATA AND MATERIALS:}

The LHID is a subset of the NHIRD, a database of all medical claims in
Taiwan's NHI system. The usage of NHIRD is limited to research purposes
only. Only Taiwanese citizens who fulfill the requirements for
conducting research projects are eligible to apply for access to the
National Health Insurance Research Database (NHIRD). Applicants must
follow the Personal Data Protection Act
(\emph{https://law.moj.gov.tw/ENG/LawClass/LawAll.aspx?pcode=I0050021})
and related regulations of the National Health Insurance Administration
and NHRI (National Health Research Institutes), and an agreement must be
signed by the applicant and his/her supervisor upon application
submission. The datasets generated and analyzed during the current study
are available from the authors on reasonable request.

\textbf{ETHICS APPROVAL AND CONSENT TO PARTICIPATE:}

This study was approved by the Institutional Review Board of Chung Shan
Medical University Hospital (Approval number CS15134) in Taiwan. The
requirement for written consent from study subjects was waived by the
Institutional Review Board, as the LHID consists of de-identified
secondary data.

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Table 1. Demographic characteristics of constipation group and
non-constipation group\selectlanguage{english}
\begin{longtable}[]{@{}lllllll@{}}
\toprule
& Before propensity score matched & Before propensity score matched & &
After propensity score matched & After propensity score matched
&\tabularnewline
\midrule
\endhead
& Constipation (N =102467) & Non-constipation (N =102467) & ASD &
Constipation (N =82421) & Non-constipation (N =82421) &
ASD\tabularnewline
Age & & & \textless{}0.001 & & & 0.048\tabularnewline
\textless{}20 & 15501 (15.1) & 15501 (15.1) & & 13276 (16.1) & 13395
(16.3) &\tabularnewline
20-39 & 31798 (31.0) & 31798 (31.0) & & 25192 (30.6) & 25115 (30.5)
&\tabularnewline
40-64 & 30822 (30.1) & 30822 (30.1) & & 24699 (30.0) & 24207 (29.4)
&\tabularnewline
[?]65 & 24346 (23.8) & 24346 (23.8) & & 19254 (23.4) & 19704 (23.9)
&\tabularnewline
Mean \selectlanguage{ngerman}± SD & 44.1 \selectlanguage{ngerman}± 22.7 & 44.1 \selectlanguage{ngerman}± 22.7 & \textless{}0.001 & 43.6 \selectlanguage{ngerman}± 22.8 &
43.7 \selectlanguage{ngerman}± 23.0 & 0.008\tabularnewline
Gender & & & \textless{}0.001 & & & 0.001\tabularnewline
Female & 68983 (67.3) & 68983 (67.3) & & 56360 (68.4) & 56405 (68.4)
&\tabularnewline
Male & 33484 (32.7) & 33484 (32.7) & & 26061 (31.6) & 26016 (31.6)
&\tabularnewline
Hypertension & 18188 (17.8) & 12651 (12.3) & 0.152 & 12212 (14.8) &
12289 (14.9) & 0.003\tabularnewline
Hyperlipidemia & 5500 (5.4) & 3728 (3.6) & 0.083 & 3684 (4.5) & 3663
(4.4) & 0.001\tabularnewline
Chronic liver disease & 3829 (3.7) & 2060 (2.0) & 0.103 & 2109 (2.6) &
2044 (2.5) & 0.005\tabularnewline
Chronic kidney disease & 1042 (1.0) & 638 (0.6) & 0.044 & 558 (0.7) &
624 (0.8) & 0.009\tabularnewline
Diabetes & 9368 (9.1) & 5495 (5.4) & 0.146 & 5556 (6.7) & 5442 (6.6) &
0.006\tabularnewline
COPD & 2622 (2.6) & 1337 (1.3) & 0.091 & 1374 (1.7) & 1337 (1.6) &
0.004\tabularnewline
Autoimmune disease & 966 (0.9) & 584 (0.6) & 0.043 & 571 (0.7) & 569
(100.0) & \textless{}0.001\tabularnewline
Corticosteroids & 25401 (24.8) & 14964 (14.6) & 0.258 & 14855 (18.0) &
14796 (18.0) & 0.002\tabularnewline
Antihistamines & 71110 (69.4) & 51862 (50.6) & 0.391 & 51741 (62.8) &
51862 (62.9) & 0.003\tabularnewline
\bottomrule
\end{longtable}

ASD: Absolute standardized differences.

COPD: Chronic obstructive pulmonary disease.

Table 2. Cox proportional hazard model analysis for risk of asthma\selectlanguage{english}
\begin{longtable}[]{@{}llllllll@{}}
\toprule
& No. of asthma & PY & ID & Univariate & & Multivariate &\tabularnewline
\midrule
\endhead
& & & & HR (95\% C.I.) & p value & HR (95\% C.I.) & p
value\tabularnewline
Group & & & & & & &\tabularnewline
Non-constipation & 3740 & 662847 & 5.6 & 1 & & 1 &\tabularnewline
Constipation & 6622 & 610672 & 10.8 & 1.88 (1.81-1.96) &
\textless{}0.001 & 1.91 (1.84-1.99) & \textless{}0.001\tabularnewline
Age & & & & & & &\tabularnewline
\textless{}20 & 2250 & 249050 & 9.0 & 1 & & 1 &\tabularnewline
20-39 & 1551 & 410253 & 3.8 & 0.40 (0.37-0.42) & \textless{}0.001 & 0.37
(0.35-0.40) & \textless{}0.001\tabularnewline
40-64 & 2721 & 377274 & 7.2 & 0.75 (0.71-0.80) & \textless{}0.001 & 0.68
(0.64-0.72) & \textless{}0.001\tabularnewline
[?]65 & 3840 & 236941 & 16.2 & 1.60 (1.52-1.69) & \textless{}0.001 & 1.31
(1.23-1.39) & \textless{}0.001\tabularnewline
Gender & & & & & & &\tabularnewline
Female & 6252 & 903955 & 6.9 & 1 & & 1 &\tabularnewline
Male & 4110 & 369563 & 11.1 & 1.57 (1.51-1.63) & \textless{}0.001 & 1.17
(1.12-1.22) & \textless{}0.001\tabularnewline
Hypertension & 2243 & 145764 & 15.4 & 1.98 (1.89-2.07) &
\textless{}0.001 & 1.22 (1.15-1.29) & \textless{}0.001\tabularnewline
Hyperlipidemia & 517 & 43009 & 12.0 & 1.37 (1.25-1.50) &
\textless{}0.001 & 0.91 (0.82-0.99) & 0.037\tabularnewline
Chronic liver disease & 334 & 26518 & 12.6 & 1.50 (1.35-1.68) &
\textless{}0.001 & 1.21 (1.09-1.36) & \textless{}0.001\tabularnewline
Chronic kidney disease & 79 & 5131 & 15.4 & 1.65 (1.32-2.06) &
\textless{}0.001 & 1.06 (0.85-1.32) & 0.624\tabularnewline
Diabetes & 836 & 61790 & 13.5 & 1.57 (1.46-1.69) & \textless{}0.001 &
0.96 (0.89-1.03) & 0.273\tabularnewline
COPD & 568 & 12955 & 43.8 & 5.16 (4.74-5.61) & \textless{}0.001 & 3.21
(2.94-3.50) & \textless{}0.001\tabularnewline
Autoimmune disease & 104 & 7533 & 13.8 & 1.63 (1.35-1.98) &
\textless{}0.001 & 1.42 (1.17-1.73) & \textless{}0.001\tabularnewline
Corticosteroids & 1876 & 250654 & 7.5 & 0.93 (0.89-0.98) & 0.007 & 0.80
(0.76-0.84) & \textless{}0.001\tabularnewline
Antihistamines & 6212 & 915347 & 6.8 & 0.65 (0.62-0.68) &
\textless{}0.001 & 0.61 (0.59-0.64) & \textless{}0.001\tabularnewline
\bottomrule
\end{longtable}

ID: Incidence density (per 1000 person-years).

PY: person-years.

COPD: Chronic obstructive pulmonary disease.

Table 3. Subgroup analysis of the association between constipation and
asthma development\selectlanguage{english}
\begin{longtable}[]{@{}llllllll@{}}
\toprule
& Constipation & Constipation & & Non-constipation & Non-constipation &
&\tabularnewline
\midrule
\endhead
& N & No. of asthma & & N & No. of asthma & HR (95\% C.I.) & p
value\tabularnewline
Age & & & & & & &\tabularnewline
\textless{}20 & 13276 & 1429 & & 13395 & 821 & 1.85 (1.69-2.01) &
\textless{}0.001\tabularnewline
20-39 & 25192 & 1019 & & 25115 & 532 & 2.04 (1.84-2.26) &
\textless{}0.001\tabularnewline
40-64 & 24699 & 1668 & & 24207 & 1053 & 1.70 (1.57-1.83) &
\textless{}0.001\tabularnewline
[?]65 & 19254 & 2506 & & 19704 & 1334 & 2.02 (1.89-2.16) &
\textless{}0.001\tabularnewline
Gender & & & & & & &\tabularnewline
Female & 56360 & 3980 & & 56405 & 2272 & 1.86 (1.77-1.96) &
\textless{}0.001\tabularnewline
Male & 26061 & 2642 & & 26016 & 1468 & 1.92 (1.80-2.04) &
\textless{}0.001\tabularnewline
Hypertension & & & & & & &\tabularnewline
No & 70209 & 5193 & & 70132 & 2926 & 1.89 (1.81-1.98) &
\textless{}0.001\tabularnewline
Yes & 12212 & 1429 & & 12289 & 814 & 1.84 (1.69-2.01) &
\textless{}0.001\tabularnewline
Hyperlipidemia & & & & & & &\tabularnewline
No & 78737 & 6308 & & 78758 & 3537 & 1.90 (1.82-1.98) &
\textless{}0.001\tabularnewline
Yes & 3684 & 314 & & 3663 & 203 & 1.61 (1.35-1.92) &
\textless{}0.001\tabularnewline
Chronic liver disease & Chronic liver disease & & & & & &\tabularnewline
No & 80312 & 6401 & & 80377 & 3627 & 1.88 (1.80-1.96) &
\textless{}0.001\tabularnewline
Yes & 2109 & 221 & & 2044 & 113 & 1.95 (1.55-2.44) &
\textless{}0.001\tabularnewline
Chronic kidney disease & Chronic kidney disease & & & & &
&\tabularnewline
No & 81863 & 6571 & & 81797 & 3712 & 1.88 (1.81-1.96) &
\textless{}0.001\tabularnewline
Yes & 558 & 51 & & 624 & 28 & 1.94 (1.23-3.08) & 0.005\tabularnewline
Diabetes & & & & & & &\tabularnewline
No & 76865 & 6084 & & 76979 & 3442 & 1.89 (1.81-1.97) &
\textless{}0.001\tabularnewline
Yes & 5556 & 538 & & 5442 & 298 & 1.80 (1.56-2.07) &
\textless{}0.001\tabularnewline
Chronic obstructive pulmonary disease & Chronic obstructive pulmonary
disease & Chronic obstructive pulmonary disease & Chronic obstructive
pulmonary disease & Chronic obstructive pulmonary disease & Chronic
obstructive pulmonary disease & Chronic obstructive pulmonary disease &
Chronic obstructive pulmonary disease\tabularnewline
No & 81047 & 6261 & & 81084 & 3533 & 1.89 (1.81-1.97) &
\textless{}0.001\tabularnewline
Yes & 1374 & 361 & & 1337 & 207 & 1.76 (1.48-2.08) &
\textless{}0.001\tabularnewline
Autoimmune disease & Autoimmune disease & & & & & &\tabularnewline
No & 81850 & 6554 & & 81852 & 3704 & 1.88 (1.81-1.96) &
\textless{}0.001\tabularnewline
Yes & 571 & 68 & & 569 & 36 & 1.99 (1.33-2.98) &
\textless{}0.001\tabularnewline
Corticosteroids & & & & & & &\tabularnewline
No & 67566 & 5547 & & 67625 & 2939 & 2.01 (1.92-2.10) &
\textless{}0.001\tabularnewline
Yes & 14855 & 1075 & & 14796 & 801 & 1.39 (1.26-1.52) &
\textless{}0.001\tabularnewline
Antihistamines & & & & & & &\tabularnewline
No & 30680 & 2836 & & 30559 & 1314 & 2.33 (2.19-2.49) &
\textless{}0.001\tabularnewline
Yes & 51741 & 3786 & & 51862 & 2426 & 1.63 (1.55-1.72) &
\textless{}0.001\tabularnewline
\bottomrule
\end{longtable}

Table 4. Cox proportional hazard model analysis for risk of asthma in
constipated patients with laxatives\selectlanguage{english}
\begin{longtable}[]{@{}lllllll@{}}
\toprule
& N & No. of asthma & Univariate & & Multivariate &\tabularnewline
\midrule
\endhead
& & & HR (95\% C.I.) & p value & HR (95\% C.I.) & p value\tabularnewline
Group & & & & & &\tabularnewline
Non-constipation & 82421 & 3740 & 1 & & 1 &\tabularnewline
Constipation with Laxatives prescription \textless{}3 times & 55070 &
3929 & 1.59 (1.52-1.66) & \textless{}0.001 & 1.76 (1.69-1.85) &
\textless{}0.001\tabularnewline
Constipation with Laxatives prescription =3-12 times & 21332 & 2000 &
2.37 (2.24-2.50) & \textless{}0.001 & 2.15 (2.03-2.27) &
\textless{}0.001\tabularnewline
Constipation with Laxatives prescription [?]12 times & 6019 & 693 & 3.39
(3.13-3.68) & \textless{}0.001 & 2.29 (2.10-2.49) &
\textless{}0.001\tabularnewline
\bottomrule
\end{longtable}

+Adjusted for age, gender, hypertension, hyperlipidemia, chronic liver
disease, chronic kidney disease, diabetes, COPD, autoimmune disease,
corticosteroids, and antihistamines.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{Figure 1.} Flowchart of enrolment of constipation and
non-constipation groups.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

\textbf{Figure 2.} Kaplan--Meier curve of cumulative incidence
proportion of asthma in constipation and non-constipation groups.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-1/Figure-1}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-2/Figure-2}

\end{center}
\end{figure}

\selectlanguage{english}
\FloatBarrier
\end{document}

