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\begin{document}

\title{Association of demographic characteristics, aggravating factors,
comorbidities and treatments with atopic dermatitis severity}



\author[1]{Jiahui Zhao}%
\author[1]{Zhixin Zhang}%
\author[2]{Hongguang Chen}%
\author[3]{Xia Dou}%
\author[1]{Zuotao Zhao}%
\author[1]{Lingling Liu}%
\author[1]{Yang Wang}%
\author[1]{Hang Li}%
\affil[1]{Peking University First Hospital}%
\affil[2]{Peking University Sixth Hospital}%
\affil[3]{Peking University Shenzhen Hospital Department of Dermatology}%


\vspace{-1em}



  
  \date{May 27, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
\textbf{Background:} Atopic dermatitis (AD) is one of the most prevalent
chronic inflammatory skin disorders that causes great disease burdens
world-wide. The demographics and clinical characteristics of AD are
different between countries, regions, and age groups yet these
differences were not well characterized in China. To get well guidance
for AD clinicians, we described the demographics, clinical
characteristics, comorbidities, patient-identified aggravating factors
and treatment of AD in all-age patients in China. \textbf{Methods:} This
study included Chinese individuals diagnosed with AD by accredited
clinicians in the department of dermatology of 205 hospitals from 31/34
provincial administrative divisions across China during August, 2021 to
September, 2022. All included patients completed dermatologist-lead
interviews regarding their general medical history, comorbidities,
AD-related aggravating factors and medications. Two-level mixed ordered
logistic regression was used to evaluate factors for aggravation of the
disease. \textbf{Results:} Overall, 16838 respondents were included in
the final analysis with a mean age of 30.94 years (standard deviation, \selectlanguage{ngerman}±
24.08 years). The proportion of patients with severe AD was the highest
in patients with onset of AD at \selectlanguage{english}[?]60 years old (26.73\%). Allergic
rhinitis and hypertension were the most common atopic and non-atopic
comorbidities, respectively. AD severity was significantly associated
with chronic urticaria, food allergy and diabetes. There was a high
proportion of severe AD in patients who had aggravating factors such as
seafood, lamb and beef, chili peppers, alcohol, seasonal changes, and
psychological factors. Cross-sectional survey revealed unmet needs of
severe AD in treatment strategy, in lack of immunosuppressants' and
biological agents' application. \textbf{Conclusion:} Treatment of
comorbidities and control of aggravating factors significantly
contribute to AD management. Improving systemic immunotherapy could
reduce the incidence of severe AD.%
\end{abstract}\selectlanguage{ngerman}%



\sloppy


\textbf{Introduction}

Atopic dermatitis (AD) is one of the most common chronic inflammatory
skin diseases characterized by recurrent pruritic eczematous
lesions.\textsuperscript{1} AD has long been recognized as a disease in
children, with high prevalence rates up to
25\%.\textsuperscript{2}Recently, increasing evidence has suggested that
AD also presents in adults, with prevalence rates estimated at
approximately 2.1\% to 4.9\% worldwide and that both persistent child-
and adult-onset forms have been observed.\textsuperscript{3-5}

The latest epidemiological studies have shown that the prevalence of AD
in industrialized countries has increased since early
2000's.\textsuperscript{3,6-9} This increase prevalence inflicts a
significant disease burden on patients and healthcare systems.
Specifically, the prevalence of AD in China, a country with more than
1.4 billion people, is showing an increasing trend across different age
groups over the past three decades.\textsuperscript{10-13} Nevertheless,
few studies have reported the current state, clinical features, and
treatment of AD in China. A majority of previous studies have focused on
paediatric AD, with a limited number of reports focusing on adults.
Despite the differences in clinical manifestations and demographic
characteristics between children and adults, a thorough analysis of
patients with AD across all age groups is
lacking.\textsuperscript{6,14,15} Therefore, there is a heightened
interest in the comprehensive identification of real-world data on
clinical characteristics, aggravating factors, and comorbidities of AD
in patients from different age groups across China. This study is based
on data extracted from national registry of the China Type II
Inflammatory Skin Disease Clinical Research and Standardized Diagnosis
and Treatment Project. To the best of our knowledge, this is the first
national study with a large sample size on the disease severity, risk
factors, and comorbidity in patients with AD in China. We can utilize
these data to better guide clinicians in designing treatment plans while
actively monitoring changes and trends in clinical characteristics and
patient management of AD. In the future, this study could serve as a
baseline for large-scale control studies.

\textbf{Methods}

\textbf{Study design and populations}

This was a national cross-sectional epidemiological study included
all-aged patients with AD who were diagnosed clinically by ``Williams
diagnostic criteria'' in the department of dermatology in respective
hospitals from 31/34 provincial administrative divisions in China
(Figure S1). Exclusion criteria comprised language or other barriers not
able to follow questions and give answers in a face to face interview.
The cross-sectional entries of patients were screened. Patients were
required to provide written informed consent prior to participation.
This research was registered in a publicly accessible database
(\emph{https://clinicaltrials.gov/}, ClinicalTrials.gov Identifier:
NCT05316805, Cornerstone) and approved by the ethics committees at
country level.

\textbf{Clinical examination and covariates}

The medical history, comorbidities, and aggravating factors were
chosen\emph{a priori} . The general medical history included the
patient's own medical history, family medical history, and life-time
record of incidence of allergies, hay fevers, and asthmas. To determine
the severity of AD, accredited dermatologists evaluated Investigator's
Global Assessment (IGA) and Eczema Area and Severity Index (EASI) scores
of patients. The IGA rating was used to describe the overall appearance
of lesions at a given clinical visit, while the EASI score was used to
measure the extent of affected areas and severity of AD. In this study,
AD severity grouping was classified based on IGA ratings. IGA ratings of
1, 2, 3, and 4 were considered mild, moderate, and severe, respectively.
In terms of comorbidities, we collected patients' information on the
prevalence of common non-atopic and atopic comorbid diseases. Patients
were also asked to identify the aggravating factors of AD from a
predetermined list provided by dermatologists. Additionally, several
health-related measurement scales, such as the weekly average Numeric
Rating Scale Itch Intensity (NRSI), Atopic Dermatitis Control Tool
(ADCT), Dermatology Life Quality Index (DLQI), Hospital Anxiety and
Depression Scale (HADS), and Sleep Disturbance Scores (SDS) were
determined to comprehensively assess the pruritus intensity, AD disease
control, quality of life, and mental health. The patients' treatment
plans for AD were also obtained for analysis.

\textbf{Statistical analysis}

The percentage, mean (standard deviation, SD) and median (interquartile
range, IQR) were used to describe the severity of AD and its population
characteristic distribution. The Kruskal-Wallis rank test was conducted
to examine differences in severity distributions of AD with comorbid
diseases as well as seasonal factors, food-related factors,
environmental factors and psychological factors. Due to regional
differences in the severity of AD, data collected in this study had a
two-level structure: regional level and individual level. Therefore,
two-level mixed ordered logistic regression was used to evaluate each
factor associated with disease aggravation and calculate the 95\%
confidence interval after adjusting for potential confounding factors.
Statistical tests were two-tailed with \emph{P} \textless{} 0.05, and
data were analyzed by STATA 14.0 (StataCorp, College Station, Texas,
USA).

\textbf{Results}

\textbf{Demographic and clinical characteristics}

This study included a total of 16838 patients (mean age 30.94 years, SD
\selectlanguage{ngerman}± 24.08 years) with AD enrolled from 205 hospitals across China from
August, 2021 to September, 2022. The patients' demographic
characteristics are summarized in Table 1. Among all included patients
with AD, the stratification criteria resulted in a high percentage of
moderate (49.51\%) AD patients with smaller proportions of mild
(35.72\%) and severe (14.77\%) AD patients. In terms of gender
distribution, 9156 patients were men (54.91\%) and 3768 patients were
women (45.09\%). Females comprised a lower percentage of severe
(12.14\%) AD patients when compared to males (16.91\%). The majority of
patients included belong to the 18-60 years old age group. The age
distribution of AD according to age was as follows: 0-2 years: 5.13\%;
2-6 years: 12.74\%; 6-12 years: 12.90\%; 12-18 years: 7.91\%; 18-60
years: 44.84\%; and \textgreater{}60 years: 15.32\%; In terms of
severity, the proportion of patients with severe AD within each age
group increased with age: from \textless{}10\% in infants (0--2 years
old) and preschoolers (2--5 years old) to 10--20\% in children (6--11
years old), adolescents (12--17 years old), and adults (18--59 years
old), to 26.56\% in older adults (\textgreater{}60 years old). The
proportion of patients with severe AD was the highest in patients with
onset of AD at \selectlanguage{english}[?]60 years (26.73\%). In terms of gender, the proportion
of severe AD patients increased with the age of AD onset more
drastically in males than females (Figure 1). There was a comparable
proportion of moderate AD patients in males and females. There were less
mild AD patients with older age of AD onset in males than females. In
the entire study population, less AD patients included from rural areas
of habitual residency. There was no significant difference in AD
severity distribution between urban and rural areas of habitual
residency. The proportion of AD severity group was similar across
different levels of education. Overall, there was a higher proportion of
patients with severe AD from northern China (north China 20.75\%,
northeast China 19.94\%), while there was a lower proportion of patients
with severe AD from western China (southwest China 10.72\%, northwest
China 10.93\%) (Table 1). In the total population, the EASI score (mean
6.7, IQR 2.9--15) increased with AD severity; patients with severe AD
had higher EASI scores than patients with mild and moderate AD (Table
1).

\textbf{Patient-reported comorbidities with AD}

In the total population, 9906 patients (60.95\%) did not identify any
comorbid diseases, 4717 patients (29.02\%) identified as having one
comorbid disease, while 1631 patients (10.03\%) identified as having
more than one comorbid diseases. Among patients who have identified as
having at least one atopic comorbidity, allergic rhinitis had the
highest prevalence, followed by food allergy, asthma, chronic urticaria,
and drug allergy (Table 2). Patients having asthma and food allergy
comprised a significantly higher proportion of severe AD, whereas
patients with allergic rhinitis comprised a significantly higher
proportion of moderate AD. Meanwhile, patients comorbid with chronic
urticaria comprised a significantly higher proportion of mild AD.
Remarkably, chronic urticaria (odds ratio {[}OR{]}, 0.74; 95\% CI:
0.63--0.87) might be protective against AD, whereas food allergies (OR,
1.21; 95\% CI: 1.06--1.37, P = 0.003) might be a risk factor for AD.
Among patients who were identified as having at least one non-atopic
comorbidity, hypertension was the highest prevalence, followed by
diabetes and coronary heart disease (Table 2). Patients with
hypertension, diabetes, and coronary heart disease comprised a
significantly higher proportion of severe AD compared to mild and
moderate. The non-atopic comorbidities of hypertension (OR, 1.61,
95\%CI: 1.35-1.93, P\textless{}0.001) and diabetes (OR, 1.64, 95\%CI:
1.27-2.12, P\textless{}0.001) are potential aggravating factors for AD.

\textbf{Patient-reported aggravating factors with AD}

In this study, 14783 patients (87.8\%) did not report any aggravating
factors, whereas 1953 patients (11.6\%) reported 1 or more aggravating
factors. Seasonal aggravating factors including spring, summer, and
winter affected a significant proportion of patients with severe AD.
Freshwater fish and shellfish, ocean fish and shellfish, lamb and beef,
chili peppers, and alcohol were among the aggravating food-related
factors. For environmental risk factors, sunlight, humidity, dryness,
sweat, shower, rub, dust, and pollen are studied, which all contributed
to severe AD. Aggravating psychological factors, including stress,
emotional problems, and sleep disorders, were observed in patients with
severe AD.The above results are presented in Table 3.

The association between AD severity and seasonal aggravating factors was
significant in patients who reported summer as a seasonal risk factor
(OR, 1.23, 95\%CI: 1.04-1.46, P=0.014) (Table 3). The association
between AD severity and food-related aggravating factors was significant
in patients who reported freshwater fish and shellfish (OR, 1.77,
95\%CI: 1.35-2.33, P\textless{}0.001), ocean fish and shellfish (OR:
1.61, 95\%CI: 1.33-1.96, P\textless{}0.001), lamb and beef (OR, 2.01,
95\%CI: 1.59-2.56, P\textless{}0.001), chili peppers (OR, 1.52, 95\%CI:
1.19-1.95, P=0.001), and alcohol (OR, 1.83, 95\%CI: 1.36-2.48,
P\textless{}0.001) as aggravating factors (Table 3). The association
between AD severity and environmental aggravating factors was
significant in patients who reported sunlight (OR: 1.79, 95\%CI:
1.42-2.25, P\selectlanguage{english}<0.001), humidity (OR, 1.61, 95\%CI: 1.23-2.11, P=0.001),
sweat (OR, 1.27, 95\%CI: 1.08-1.48, P=0.004), shower (OR, 1.63, 95\%CI:
1.26-2.11, P\selectlanguage{english}<0.001), rub (OR, 1.84, 95\%CI: 1.37-2.46, P\selectlanguage{english}<0.001), dust
(OR, 1.55, 95\%CI: 1.24-1.92, P\selectlanguage{english}<0.001), and pollen (OR, 2.15, 95\%CI:
1.54-3.00, P\selectlanguage{english}<0.001) as aggravating factors (Table 3). The association
between AD severity and psychological aggravating factors was
significant in patients who reported stress (OR, 1.99, 95\%CI:
1.59-2.50, P\selectlanguage{english}<0.001), emotional problem (OR, 1.80, 95\%CI: 1.44-2.26,
P\selectlanguage{english}<0.001), and sleep disorder (OR, 1.89, 95\%CI: 1.49-2.41, P\selectlanguage{english}<0.001) as
aggravating factors (Table 3).

\textbf{Patient-reported health-related measurements with AD severity}

All patient-reported health-related measurement scores, including weekly
average NRSI, DLQI, HADS, ADCT, and SDS, increased with the severity of
AD (Table 4). The mean weekly NRSI, SDS, DLQI, and ADCT scores were
significantly higher in severe AD patients than moderate and mild AD
patients. Additionally, in terms of the distribution of SDS, a higher
proportion of mild AD patients (28.39\%) reported 0 days of sleep
disturbance per week than moderate (10.06\%) and severe (5.50\%) AD
patients (Figure S2). In contrast, a higher proportion of severe AD
patients (46.47\%) reported 7 days of sleep disturbance per week than
mild (15.13\%) and moderate (22.04\%) AD patients (Figure S2).

\textbf{Treatment plans and AD}

The top six therapies for AD patients were topical glucocorticoids
(32.26\%), oral antihistamines (28.66\%), moisturizers (19.58\%),
topical calcineurin inhibitors (TCI) (5.99\%), glycyrrhizin (5.82\%),
and dupilumab (5.8\%) (Table 5). There was a significantly higher
proportion of severe AD patients who used moisturizer, topical
glucocorticoids, TCI, antibiotic ointments, oral antihistamines, oral
antibiotics, systemic glucocorticoids, cyclosporine, methotrexate,
tripterygium glycosides, glycyrrhizin, thalidomide, NB-UVB phototherapy,
dupilumab, gabapentin, antidepressants, and opioids than that of mild
and moderate AD patients. Common recommended therapies including TCI
(5.99\%), dupilumab (5.8\%), systematic glucocorticoids (4.05\%),
cyclosporine (0.82\%), methotrexate (0.54\%), and NB-UVB (0.76\%) have
low usage rates in the included population (Table 5).

\textbf{Discussion}

This study describes the current demographics, disease characteristics,
comorbidities, and aggravating factors of patients with mild, moderate,
and severe AD in all age groups in China. In moderate to severe group,
the proportion of men was higher relative to the proportion of women
(67.44\% vs 59.78\%, P\selectlanguage{english}<0.001). A cross-sectional study in Europe and
Canada revealed that the proportion of women was higher in the mild AD
group than in the moderate and severe AD groups (61.2\% vs 50.5\%; P
\textless{} 0.001).\textsuperscript{16} Based on the POEM score, a study
in the United States observed that most adult patients with AD had mild
disease (60.1\%, 95\% CI: 56.1, 64.1) followed by moderate disease
(28.9\%, 95\% CI: 25.3, 32.7).\textsuperscript{17} In contrast, our
findings showed that most of the patients with AD in China had moderate
disease severity followed by mild and severe disease. As the results of
previous studies and ours varied, the differences in the results can be
attributed to the varying definitions between the studies. Additionally,
our results suggest that AD in Chinese individuals is poorly controlled
in all age groups. Consistent with findings of previous
studies,\textsuperscript{6} the proportion of AD was generally lower in
rural settings than in urban settings. Meanwhile, marital status and
education level did not have a significant effect on AD severity.

In our study, the issue of relationship between the AD severity and
patient distribution in China was explored. The amount of severe AD in
the northern provinces was dominantly higher than in the western and
central provinces. Additionally, there were more patients with severe AD
in the economically developed southern regions. Aggravating factors, low
temperatures, and an arid climate in northern China may have negative
effects on the skin that may aggravate pruritus in
patients.\textsuperscript{18} Regional specific plants and flowers are
also important components of environmental allergens. South China
belongs to the subtropical and tropical regions, with subtropical grass
pollens being more abundant.\textsuperscript{19} Emerging evidence
showed that exposure to grass pollen induced a significant worsening of
AD.\textsuperscript{20} Our data showed that incidence of severe AD is
very high in Guangdong province. In the future, recognition of
subtropical grass pollen allergens by transcriptomic, proteomic and
bioinformatic approaches is essential for study to increase the efficacy
of allergen-specific immunotherapy for AD.

Early-onset AD usually develop atopic comorbidities such as allergic
rhinitis, asthma, food allergies, and allergic conjunctivitis. The
percentage of infants with AD who complicated with allergic rhinitis,
22.4\%; food allergy, 15.9\%; allergic conjunctivitis 14.1\% in the
study of United Stated.\textsuperscript{21} Allergic rhinitis, food
allergy not asthma or allergic conjunctivitis developed significantly
more often in infants with greater AD severity at baseline. The
relationship of adult-onset AD and atopic comorbidities has been poorly
studied. At all ages of prevalence of allergic rhinitis with AD was
25.88\%; food allergy with AD was 6.2\%, asthma was with AD 4.22\%,
allergic conjunctivitis with AD was 2.2\% in our research. Compared to
the children study above, the prevalence of asthma and food allergy
decreased significantly in the multi-age group, suggesting that asthma
and food allergy are main comorbidities of early-onset AD. In terms of
non-atopic comorbidities, AD patients who have identified as having at
least one non-atopic comorbidity, hypertension had the highest
prevalence, followed by diabetes and coronary heart disease. This is not
uncommon as other studies have also found significant associations
between AD, hypertension, diabetes, and cardiovascular diseases.
Silverberg et al. have found higher odds of diabetes, high blood
pressure, and heart disease in both adults and paediatric patients with
AD compared to healthy control.\textsuperscript{22,23} Additionally, we
found hypertension to be a significant risk factor of AD where patients
with hypertension comprised a significantly higher proportion of severe
AD compared to mild and moderate AD. Similarly, a recent study by
Abdallah \& Vestergaard found that moderate-to-severe AD was
significantly associated with hypertension while mild AD was
not.\textsuperscript{24} This indicate that when managing AD patients,
clinicians have to pay attention to and take care of non-atopic
comorbidities at the same time as performing other AD-specific
interventions. In addition to comorbidities, patient-identified
aggravating factors also contributing to AD development and progression.

Various exogeneous aggravating factors lead to persistence and
recurrence of AD. Our findings revealed that the severity of AD was
associated with exposure to irritants, including fish, shellfish, chili
peppers, dust, pollen, and temperature and humidity changes. Tropomyosin
is the common allergen in fish and
shellfish.\textsuperscript{25}Remarkably, tropomyosin shares a
significant homology to allergens found in house dust
mites.\textsuperscript{25} Therefore, we suppose that house dust mite
immunotherapy could improve seafood tolerance in moderate-to-severe AD.

Aside from comorbidities and exogenous aggravating factors,
psychological factors have also been shown to play a critical role in
increasing the disease burden of AD. In our study, stress, emotional
problems, and sleep disorders have contributed to a significantly higher
proportion of severe AD. In prior studies of adolescent AD, men who
reported with high stress had 46\% higher risk of developing severe AD
than participants who reported with no stress.\textsuperscript{26} Early
studies found that high level of stress may trigger TNF-alpha,
eosinophil, and IgE release, swaying the immune system towards T helper
type 2 (Th2) responses.\textsuperscript{27,28} Patients with AD have
blunted reactivity of the HPA axis and an overactive sympathetic
adrenomedullary system that results in immune imbalance that favors Th2
responses.\textsuperscript{29} Sleep disorders are strongly associated
with AD; they have been reported in 47--80\% of children and in
33--87.1\% of adults with AD.\textsuperscript{30} Specifically, itching
and scratching can cause tissue damage and sleep disturbance, while
pruritus-induced sleep deprivation can further impede immune functions
and exacerbate AD. This suggests that the management of psychological
conditions is a vital part of the management of AD. Recently, the
American Academy of Dermatology (AAD) published guidelines for managing
comorbidities associated with AD. Within these guidelines, the AAD
advised clinicians to assess and treat patients with unaddressed mental
health issues after adequate control of AD in a case-by-case
manner.\textsuperscript{31} In the future, with more evident
associations between psychological aggravating factors and AD,
dermatologists may arrive at a consensus for the management of
psychological aspects of AD.

Furthermore, the treatment and management of AD in China has its own
characteristics and unmet needs. According to several guidelines, the
use of moisturizers, topical glucocorticoids, TCI, and topical
antimicrobials are recommended as topical anti-inflammatory
treatments.\textsuperscript{32-34} For more severe AD, systemic
immunomodulating medications like cyclosporine, azathioprine,
methotrexate, or mycophenolate mofetil, and phototherapy were
recommended.\textsuperscript{32-35} Meanwhile, the use of antihistamines
to reduce pruritus was found to be ineffective, while systemic steroids
are not recommended due to their severe adverse
effects.\textsuperscript{32-38} More recently, the use of biological
agents and JAK inhibitors were also recommended for treatments of severe
AD.\textsuperscript{39-42} However, the therapeutic pattern observed in
our cohort suggested insufficient treatment of patients with AD in
China. For instance, moisturizers containing emollients have been proven
to lessen the symptoms of AD,\textsuperscript{43,44} yet in our cohort,
there was only 19.58\% of AD patients used topical moisturizers.
Additionally, a large proportion of patients used antihistamines
(43.46\%) and systemic steroids (8.51\%) as their primary treatment,
which are not in line with most guidelines. Furthermore, the proportion
of patients using systemic immunomodulatory medications and biological
agents was low in our cohort. Some patients also relied on Chinese
medicine, such as tripterygium and glycyrrhizin, which lack evidence on
their efficacy in treating AD. These patterns of undertreatment may
explained the high proportion of patients with severe AD in this study.
To solve these problems, an increased use of systemic immunomodulating
therapies, promotion of the use of biological agents, and educational
interventions are needed.

In conclusion, our study firstly revealed the severity distribution and
demographic characteristics of patients with AD across all-ages in
China. Effective long-term management of chronic comorbidities is
AD-related challenges faced by dermatologists and allergists.
Undertaking reasonable measures to avoid aggravating factors can
alleviate AD.

\textbf{Funding Information}

This work was supported by PKU-Baidu Fund (grant no. 2020BD012 to Hang
Li) National Natural Science Foundation of China (grant no. 81903213 to
Jiahui Zhao).

\textbf{Authors contributions}

Dr.Hang Li, Dr.Yang Wang, Dr. Jiahui Zhao and Dr. Xia Dou have
contributed substantially to study design. Dr. Hang Li has supervised
all phases of the study. Dr.Yang Wang, Dr. Jiahui Zhao, Dr. Xia Dou and
Dr. Zuotao Zhao acquired data. Dr. Jiahui Zhao, Dr Hongguang Chen and
Zhixin Zhang performed the analysis and interpretation of the data. Dr.
Jiahui Zhao, Zhixin Zhang and Dr. Hongguang Chen drafted the manuscript
and Dr. Hang Li, Dr. Yang Wang revised it critically.

\textbf{Conflicts of Interest}

All the authors have no conflicts of interest to declare.



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\textbf{Table 1. Demographics and Clinical Characteristics of Patients
with AD}\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
& \textbf{Total} & \textbf{AD Severity} & \textbf{AD Severity} &
\textbf{AD Severity} & \textbf{P Value}\tabularnewline
& & \textbf{Mild} & \textbf{Moderate} & \textbf{Severe} &\tabularnewline
\textbf{Number of Participants, n (\%)} & 16838 & 6014 (35.72) & 8337
(49.51) & 2487 (14.77) &\tabularnewline
\textbf{Gender, n (\%)} & & & & & <0.001\tabularnewline
Female & 7,519 & 3024 (40.22) & 3582 (47.64) & 913 (12.14)
&\tabularnewline
Male & 9,156 & 2981 (32.56) & 4627 (50.54) & 1548 (16.91)
&\tabularnewline
\textbf{Age groups, n (\%)} & & & & & <0.001\tabularnewline
<2 & 863 & 421 (48.78) & 363 (42.06) & 79 (9.15) &\tabularnewline
[?]2 \& <6 & 2,145 & 1057 (49.28) & 944 (44.01) & 144 (6.71)
&\tabularnewline
[?]6 \& <12 & 2,172 & 861 (39.64) & 1048 (48.25) & 263 (12.11)
&\tabularnewline
[?]12 \& <18 & 1,332 & 444 (33.33) & 659 (49.47) & 229 (17.19)
&\tabularnewline
[?]18 \& <60 & 7,551 & 2669 (35.35) & 3832 (50.75) & 1050 (13.91)
&\tabularnewline
[?]60 & 2,579 & 548 (21.25) & 1346 (52.19) & 685 (26.56) &\tabularnewline
\textbf{Marital Status, n (\%)} & & & & & <0.001\tabularnewline
Single & 8,995 & 3706 (41.2) & 4236 (47.09) & 1053 (11.71)
&\tabularnewline
Married & 7,530 & 2184 (29) & 3961 (52.6) & 1385 (18.39)
&\tabularnewline
Divorced & 66 & 17 (25.76) & 36 (54.55) & 13 (19.7) &\tabularnewline
\textbf{Age at disease onset, n (\%)} & & & & & <0.001\tabularnewline
0-2 years old & 3,307 & 1399 (42.3) & 1481 (44.78) & 427 (12.91)
&\tabularnewline
2-6 years old & 2,139 & 957 (44.74) & 969 (45.3) & 213 (9.96)
&\tabularnewline
6-12 years old & 1,550 & 601 (38.77) & 760 (49.03) & 189 (12.19)
&\tabularnewline
12-18 years old & 1,186 & 409 (34.49) & 625 (52.7) & 152 (12.82)
&\tabularnewline
18-59 years old & 6,522 & 2172 (33.3) & 3407 (52.24) & 943 (14.46)
&\tabularnewline
60 years and older & 1,904 & 406 (21.32) & 989 (51.94) & 509 (26.73)
&\tabularnewline
\textbf{Habitual residence, n (\%)} & & & & & 0.762\tabularnewline
Urban & 14,753 & 5238 (35.5) & 7366 (49.93) & 2149 (14.57)
&\tabularnewline
Rural & 1,833 & 668 (36.44) & 864 (47.14) & 301 (16.42) &\tabularnewline
\textbf{Level of education, n (\%)} & & & & & <0.001\tabularnewline
\textless{} Elementary school & 6,332 & 2623 (41.42) & 2975 (46.98) &
734 (11.59) &\tabularnewline
Completed middle school & 2,590 & 811 (31.31) & 1286 (49.65) &
493(19.03) &\tabularnewline
Completed high school & 2,217 & 686 (30.94) & 1112(50.16) & 419(18.9)
&\tabularnewline
College diploma & 2,230 & 686 (30.76) & 1225(54.93) & 319(14.3)
&\tabularnewline
Bachelor's degree or higher & 3,221 & 1100 (34.15) & 1635(50.76) &
486(15.09) &\tabularnewline
\textbf{EASI score, mean (IQR)} & 6.7 (2.9-15) & 2.8 (1.3-5.6) & 9.4
(4.65-18.05) & 18.2 (9.6-28.3) & <0.001\tabularnewline
\bottomrule
\end{longtable}

Note: EASI score, Eczema Area and Severity Index Score.

\textbf{Table 2. Comorbidities associated with severity of AD examined
in mixed-effects ordered logistic regression}\selectlanguage{english}
\begin{longtable}[]{@{}lllllllllll@{}}
\toprule
& \textbf{Total} & \textbf{AD severity} & \textbf{AD severity} &
\textbf{AD severity} & \textbf{AD severity} & \textbf{AD severity} &
\textbf{Mixed-effect ordered logistic regression*} &
\textbf{Mixed-effect ordered logistic regression*} &
\textbf{Mixed-effect ordered logistic regression*} &
\textbf{Mixed-effect ordered logistic regression*}\tabularnewline
\midrule
\endhead
& & & & & & & \textbf{Level one} & \textbf{Level one} & & \textbf{Level
two}\tabularnewline
& & \textbf{Mild} & \textbf{Mild} & \textbf{Moderate} & \textbf{Severe}
& \textbf{P Value} & \textbf{OR (95\% CI)} & \textbf{P Value} & &
\textbf{Variance (95\%CI)}\tabularnewline
\textbf{Atopic comorbidity, n (\%)} & & & & & & & & & &\tabularnewline
Asthma & 745 & 272 (4.67) & 272 (4.67) & 338 (4.17) & 135 (5.81) & 0.004
& 1.09 (0.94-1.26) & 0.262 & & 0.08(0.03-0.23)\tabularnewline
Allergic conjunctivitis & 363 & 136 (2.33) & 136 (2.33) & 162 (2.00) &
65 (2.80) & 0.057 & 1.16 (0.95-1.43) & 0.153 & &
0.07(0.03-0.22)\tabularnewline
Chronic urticaria & 639 & 288 (4.94) & 288 (4.94) & 288 (3.55) & 63
(2.71) & \textless{}0.001 & 0.74 (0.63-0.87) & \textless{}0.001 & &
0.07(0.02-0.21)\tabularnewline
Food allergy & 1057 & 387 (6.64) & 387 (6.64) & 495 (6.11) & 175 (7.54)
& 0.041 & 1.21 (1.06-1.37) & 0.003 & & 0.08(0.03-0.22)\tabularnewline
Drug allergy & 303 & 104 (1.79) & 104 (1.79) & 145 (1.79) & 54 (2.33) &
0.208 & 1.18 (0.94-1.48) & 0.149 & & 0.08(0.03-0.22)\tabularnewline
Contact dermatitis & 89 & 29 (0.50) & 29 (0.50) & 40 (0.49) & 20 (0.86)
& 0.086 & 1.41 (0.93-2.13) & 0.11 & & 0.07(0.03-0.22)\tabularnewline
Allergic rhinitis & 4,358 & 1642 (28.18) & 1642 (28.18) & 2044 (25.22) &
672 (28.94) & \textless{}0.001 & 1.02 (0.95-1.10) & 0.556 & &
0.08(0.03-0.23)\tabularnewline
\textbf{Non-atopic comorbidity, n (\%)} & & & & & & & & &
&\tabularnewline
Hypertension & 547 & 113 (1.94) & 113 (1.94) & 274 (3.38) & 160 (6.89) &
\textless{}0.001 & 1.61 (1.35-1.93) & \textless{}0.001 & &
0.08(0.03-0.22)\tabularnewline
Diabetes & 247 & 50 (0.86) & 50 (0.86) & 126 (1.55) & 71 (3.06) &
\textless{}0.001 & 1.64 (1.27-2.12) & \textless{}0.001 & &
0.08(0.03-0.22)\tabularnewline
Coronary heart disease & 137 & 22 (0.38) & 22 (0.38) & 77 (0.95) & 38
(1.64) & \textless{}0.001 & 1.66 (1.19-2.32) & 0.003 & &
0.08(0.03-0.22)\tabularnewline
Inflammatory bowel disease & 12 & 3 (0.05) & 3 (0.05) & 5 (0.06) & 4
(0.17) & 0.271 & 2.23 (0.69-7.15) & 0.178 & &
0.07(0.03-0.22)\tabularnewline
\bottomrule
\end{longtable}

Note: "*"Dependent variable: severity of AD (Mild, Moderate, Severe),
the association between each atopic comorbidity/non-atopic comorbidity
and severity of AD was examined separately by mix-effect two-level
(level one: individual; level two: region) ordered logistic regression
after adjusting for gender, marital status, age on disease set,
educational level and inducing or aggravating factors. An LR test
comparing the model with the one-level model favored the
random-intercept model with \emph{P} \textless{}0.05 for all the
analysis.

\textbf{Table 3. Aggravating factors associated with severity of AD
examined in in mixed-effects ordered logistic regression}\selectlanguage{english}
\begin{longtable}[]{@{}lllllllllll@{}}
\toprule
& \textbf{Total} & \textbf{AD severity} & \textbf{AD severity} &
\textbf{AD severity} & \textbf{AD severity} & \textbf{AD severity} &
\textbf{Mixed ordered logistic regression*} & \textbf{Mixed ordered
logistic regression*} & \textbf{Mixed ordered logistic regression*} &
\textbf{Mixed ordered logistic regression*}\tabularnewline
\midrule
\endhead
& & & & & & & \textbf{Level one} & \textbf{Level one} & & \textbf{Level
two}\tabularnewline
& & \textbf{Mild} & \textbf{Mild} & \textbf{Moderate} & \textbf{Severe}
& \textbf{P Value} & \textbf{OR (95\% CI)} & \textbf{P Value} & &
\textbf{Variance (95\%CI)}\tabularnewline
\textbf{Seasonal factors, n (\%)} & & & & & & & & & &\tabularnewline
Spring & 250 & 100 (1.66) & 100 (1.66) & 102 (1.22) & 48 (1.93) & 0.014
& 0.97 (0.75-1.25) & 0.794 & & 0.08(0.03-0.23)\tabularnewline
Summer & 615 & 211 (3.51) & 211 (3.51) & 280 (3.36) & 124 (4.99) &
<0.001 & 1.23 (1.04-1.46) & 0.014 & & 0.08(0.03-0.23)\tabularnewline
Autumn & 315 & 125 (2.08) & 125 (2.08) & 143 (1.72) & 47 (1.89) & 0.29 &
0.88 (0.70-1.10) & 0.269 & & 0.08(0.03-0.23)\tabularnewline
Winter & 564 & 222 (3.69) & 222 (3.69) & 249 (2.99) & 93 (3.74) & 0.034
& 0.93 (0.78-1.11) & 0.41 & & 0.08(0.03-0.23)\tabularnewline
\textbf{Food-related factors, n (\%)} & & & & & & & & & &\tabularnewline
Milk & 156 & 70 (1.16) & 70 (1.16) & 61 (0.73) & 25 (1.01) & 0.025 &
0.87 (0.63-1.20) & 0.392 & & 0.08(0.03-0.23)\tabularnewline
Egg & 186 & 74 (1.23) & 74 (1.23) & 81 (0.97) & 31 (1.25) & 0.268 & 1.12
(0.83-1.51) & 0.473 & & 0.08(0.03-0.23)\tabularnewline
Freshwater fish and shellfish & 215 & 54 (0.9) & 54 (0.9) & 112 (1.34) &
49 (1.97) & \textless{}0.001 & 1.77 (1.35-2.33) & \textless{}0.001 & &
0.08(0.03-0.23)\tabularnewline
Ocean fish and shellfish & 434 & 120 (2) & 120 (2) & 220 (2.64) & 94
(3.78) & \textless{}0.001 & 1.61 (1.33-1.96) & \textless{}0.001 & &
0.08(0.03-0.23)\tabularnewline
Lamb and beef & 285 & 69 (1.15) & 69 (1.15) & 145 (1.74) & 71 (2.85) &
\textless{}0.001 & 2.01 (1.59-2.56) & \textless{}0.001 & &
0.08(0.03-0.23)\tabularnewline
Chili peppers & 269 & 78 (1.3) & 78 (1.3) & 130 (1.56) & 61 (2.45) &
\textless{}0.001 & 1.52 (1.19-1.95) & 0.001 & &
0.08(0.03-0.23)\tabularnewline
Alcohol & 173 & 38 (0.63) & 38 (0.63) & 91 (1.09) & 44 (1.77) &
\textless{}0.001 & 1.83 (1.36-2.48) & \textless{}0.001 & &
0.08(0.03-0.23)\tabularnewline
\textbf{Environmental factors, n (\%)} & & & & & & & & &
&\tabularnewline
Sunlight & 315 & 88 (1.46) & 88 (1.46) & 147 (1.76) & 80 (3.22) &
\textless{}0.001 & 1.79 (1.42-2.25) & \textless{}0.001 & &
0.08(0.03-0.23)\tabularnewline
Humidity & 225 & 72 (1.2) & 72 (1.2) & 93 (1.12) & 60 (2.41) &
\textless{}0.001 & 1.61 (1.23-2.11) & 0.001 & &
0.08(0.03-0.23)\tabularnewline
Dryness & 561 & 206 (3.43) & 206 (3.43) & 234 (2.81) & 121 (4.87) &
\textless{}0.001 & 1.20 (1.00-1.43) & 0.05 & &
0.08(0.03-0.23)\tabularnewline
Sweat & 710 & 251 (4.17) & 251 (4.17) & 312 (3.74) & 147 (5.91) &
\textless{}0.001 & 1.27 (1.08-1.48) & 0.004 & &
0.08(0.03-0.23)\tabularnewline
Shower & 240 & 66 (1.1) & 66 (1.1) & 121 (1.45) & 53 (2.13) & 0.001 &
1.63 (1.26-2.11) & \textless{}0.001 & & 0.08(0.03-0.23)\tabularnewline
Rub & 189 & 51 (0.85) & 51 (0.85) & 89 (1.07) & 49 (1.97) &
\textless{}0.001 & 1.84 (1.37-2.46) & \textless{}0.001 & &
0.08(0.03-0.23)\tabularnewline
Dust & 364 & 118 (1.96) & 118 (1.96) & 163 (1.96) & 83 (3.34) &
\textless{}0.001 & 1.55 (1.24-1.92) & \textless{}0.001 & &
0.08(0.03-0.23)\tabularnewline
Pollen & 148 & 34 (0.57) & 34 (0.57) & 74 (0.89) & 40 (1.61) &
\textless{}0.001 & 2.15 (1.54-3.00) & \textless{}0.001 & &
0.08(0.03-0.30)\tabularnewline
\textbf{Psychological factors, n (\%)} & & & & & & & & &
&\tabularnewline
Stress & 344 & 89 (1.48) & 89 (1.48) & 158 (1.9) & 97 (3.9) &
\textless{}0.001 & 1.99 (1.59-2.50) & \textless{}0.001 & &
0.08(0.03-0.23)\tabularnewline
Emotional problem & 332 & 94 (1.56) & 94 (1.56) & 151 (1.81) & 87 (3.5)
& \textless{}0.001 & 1.80 (1.44-2.26) & \textless{}0.001 & &
0.08(0.03-0.23)\tabularnewline
Sleep disorder & 288 & 70 (1.16) & 70 (1.16) & 140 (1.68) & 78 (3.14) &
\textless{}0.001 & 1.89 (1.49-2.41) & \textless{}0.001 & &
0.08(0.03-0.23)\tabularnewline
\bottomrule
\end{longtable}

Note: "*"Dependent variable: severity of AD (Mild, Moderate, Severe),
the association between complicated factor and severity of AD was
examined separately by mix-effect two-level (level one: individual;
level two: region) ordered logistic regression after adjusting for
gender, marital status, age on disease set, educational level and
comorbidity. An LR tests comparing the model with the one-level model
favored the random-intercept model with \emph{P} \textless{}0.05 for all
the analysis.

\textbf{Table 4. Impact of severity of atopic dermatitis on
patient-reported pruritus, mental health, health-related quality of
life, sleep distribution, and disease control}\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
& \textbf{Total} & \textbf{AD Severity} & \textbf{AD Severity} &
\textbf{AD Severity} & \textbf{P Value}\tabularnewline
\midrule
\endhead
& & \textbf{Mild} & \textbf{Moderate} & \textbf{Severe} &\tabularnewline
Weekly avg NRSI, mean (IQR) & 5 (3--7) & 3 (2--5) & 6 (4--8) & 7 (5--8)
& \textless{}0.001\tabularnewline
DLQI, mean (IQR) & 6 (0--12) & 2 (0--8) & 7 (0--14) & 11 (0--18) &
0.001\tabularnewline
HADS, mean (IQR) & 8 (3--15) & 7 (3--12) & 8 (3--15) & 14 (7--20) &
0.053\tabularnewline
SD, mean (IQR) & 2 (1--3) & 1 (0--2) & 2 (1--3) & 3 (2--4) &
\textless{}0.001\tabularnewline
ADCT, mean (IQR) & 13 (9--18) & 9 (6--13) & 14 (10--18) & 18 (14--20) &
0.002\tabularnewline
\bottomrule
\end{longtable}

Note: ADCT, atopic dermatitis control tool; avg, average; DLQI,
dermatology life quality index; HADS, hospital anxiety and depression
scale; SD, sleep distribution.



\textbf{Table 5. Therapeutic distribution of Chinese patients with AD at
enrollment.}\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
& \textbf{Total} & \textbf{AD Severity} & \textbf{AD Severity} &
\textbf{AD Severity} & \textbf{P Value}\tabularnewline
\midrule
\endhead
& & \textbf{Mild} & \textbf{Moderate} & \textbf{Severe} &\tabularnewline
\textbf{Number of Participants, n} & 16148 & 5743 & 8098 & 2307
&\tabularnewline
Missing data & 690 & 271 & 239 & 180 &\tabularnewline
\textbf{Topical therapy, n (\%)} & & & & &\tabularnewline
Moisturizer & 3162(19.58) & 1089(18.96) & 1454(17.96) & 619(26.83) &
<0.001\tabularnewline
Glucocorticoids & 5210(32.26) & 1629(28.36) & 2527(31.21) & 1054(45.69)
& <0.001\tabularnewline
Calcineurin inhibitors & 968(5.99) & 298(5.19) & 442(5.46) & 228(9.88) &
<0.001\tabularnewline
Antibiotic ointments & 484(3) & 148(2.58) & 223(2.75) & 113(4.9) &
<0.001\tabularnewline
NSAIDs & 76(0.47) & 26(0.45) & 34(0.42) & 16(0.69) &
0.231\tabularnewline
Crisaborole ointment & 94(0.58) & 32(0.56) & 41(0.51) & 21(0.91) &
0.076\tabularnewline
Others & 879(5.44) & 311(5.42) & 417(5.15) & 151(6.55) &
0.033\tabularnewline
\textbf{Oral therapy, n (\%)} & & & & &\tabularnewline
Antihistamines & 4532(28.66) & 1278(22.85) & 2273(28.55) & 981(43.46) &
<0.001\tabularnewline
Antibiotics & 149(0.94) & 41(0.73) & 67(0.84) & 41(1.82) &
<0.001\tabularnewline
Systemic steroids & 641(4.05) & 174(3.11) & 275(3.45) & 192(8.51) &
<0.001\tabularnewline
Cyclosporine & 130(0.82) & 35(0.63) & 55(0.69) & 40(1.77) &
<0.001\tabularnewline
Methotrexate & 86(0.54) & 15(0.27) & 51(0.64) & 20(0.89) &
0.001\tabularnewline
Tripterygium glycosides & 198(1.25) & 36(0.64) & 97(1.22) & 65(2.88) &
<0.001\tabularnewline
Glycyrrhizin & 921(5.82) & 274(4.9) & 440(5.53) & 207(9.17) &
<0.001\tabularnewline
Thalidomide & 124(0.78) & 21(0.38) & 69(0.87) & 34(1.51) &
<0.001\tabularnewline
\textbf{Phototherapy, n (\%)} & & & & &\tabularnewline
NB-UVB & 120(0.76) & 24(0.43) & 59(0.74) & 37(1.66) &
<0.001\tabularnewline
UVA & 7(0.04) & 2(0.04) & 3(0.04) & 2(0.09) & 0.55\tabularnewline
PUVA & 5(0.03) & 1(0.02) & 4(0.05) & 0(0) & 0.384\tabularnewline
\textbf{Targeted therapy, n (\%)} & & & & &\tabularnewline
Dupilumab & 914(5.8) & 280(5.02) & 468(5.89) & 166(7.4) &
<0.001\tabularnewline
Omalizumab & 10(0.06) & 6(0.11) & 3(0.04) & 1(0.04) &
0.263\tabularnewline
JAK inhibitor & 24(0.15) & 4(0.07) & 14(0.18) & 6(0.27) &
0.099\tabularnewline
\textbf{Anticonvulsant \& CNS depressants, n (\%)} & & & &
&\tabularnewline
Gabapentin & 47(0.3) & 11(0.2) & 19(0.24) & 17(0.76) &
<0.001\tabularnewline
Pregabalin & 28(0.18) & 10(0.18) & 11(0.14) & 7(0.31) &
0.222\tabularnewline
Antidepressants & 40(0.25) & 29(0.52) & 8(0.1) & 3(0.13) &
<0.001\tabularnewline
Opioids & 1(0.01) & 0(0) & 0(0) & 1(0.04) & 0.048\tabularnewline
\bottomrule
\end{longtable}

Note: CNS, central nerve system.



\textbf{Figure and Figure legend}

\textbf{Figure 1.} Percentage of mild, moderate and severe AD onset for
male and female patients with all age groups.\selectlanguage{english}
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\textbf{Hosted file}

\verb`Table1-5.docx`  available at \url{https://authorea.com/users/579851/articles/621162-association-of-demographic-characteristics-aggravating-factors-comorbidities-and-treatments-with-atopic-dermatitis-severity}

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