Risk factors for allergic rhinitis in children residing in five different regions of the Central Federal District: Observational study

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Aim. To detect known risk factors for allergic rhinitis and determine the associated risks in five regions of the Central Federal District of the Russian Federation for 2017–2021 in different age groups.

Materials and methods. The study was conducted at the Odintsovo Regional Hospital (Odintsovo), the Regional Children's Clinical Hospital (Yaroslavl), the City Children's Clinical Hospital (Tver), the Regional Children's Clinical Hospital (Vladimir), and the Vologda Children's City Polyclinic (Vologda). The homogeneity of the studied populations for the time criterion was assessed; the risk factors for allergic rhinitis (AR) recorded by the pediatrician in patients with an established diagnosis with ICD-10 codes J30.1, J30.2, J30.3, and J30.4 were analyzed. The total children population was 361,281 in the fourth quarter of 2021, and the number of children diagnosed with AR was 6,757. The study included children aged from 0 to 17 years. When assessing the evidence base, the data analysis and synthesis for each study site in each time range was performed in 100% of patients with AR.

Results. The analysis results showed that in 2017–2021, in all studied regions, there was a steady increase in the total children's population and an increase in AR patients from birth to 17 years, and in some regions, such as Odintsovo and Tver, the prevalence of AR is growing exponentially. All risk factors were divided into three groups according to the feasibility of controlling their effect: uncontrollable (6 factors), partially controlled (10 factors) and controlled (12 factors). Most controlled risk factors were socio-biological and medical, and partially controlled ones were medical and socio-economic.

Conclusion. The breakdown of risk factors into groups according to control feasibility will enable the reformatting of therapeutic and preventive measures aimed at reducing the prevalence of AR, which is a predictor of bronchial asthma occurrence.

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About the authors

Pavel V. Berezhanskiy

Morozov Children's City Clinical Hospital; Research Clinical Institute of Childhood; People’s Friendship University of Russia (RUDN University); Sechenov First Moscow State Medical University (Sechenov University)

Author for correspondence.
Email: berezhanskiy-pv@rudn.ru
ORCID iD: 0000-0001-5235-5303
SPIN-code: 1480-9900

Cand. Sci. (Med.)

Russian Federation, Moscow; Moscow; Moscow; Moscow

Alexander B. Malakhov

Morozov Children's City Clinical Hospital; Research Clinical Institute of Childhood; Sechenov First Moscow State Medical University (Sechenov University)

Email: alexis4591m@mail.ru
ORCID iD: 0000-0002-2686-8284
SPIN-code: 1749-0503

D. Sci. (Med.), Prof.

Russian Federation, Moscow; Moscow; Moscow

Nataly S. Tataurshchikova

People’s Friendship University of Russia (RUDN University)

Email: berezhanskiy-pv@rudn.ru
ORCID iD: 0000-0002-3486-8188

D. Sci. (Med.)

Russian Federation, Moscow

Tatiana A. Gutyrchik

Morozov Children's City Clinical Hospital; Research Clinical Institute of Childhood

Email: tanya_2904@list.ru
ORCID iD: 0000-0002-8421-1694

Graduate Student

Russian Federation, Moscow; Moscow

Tatiana I. Iushina

Morozov Children's City Clinical Hospital

Email: berezhanskiy-pv@rudn.ru


Russian Federation, Moscow


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Supplementary files

Supplementary Files
1. Fig. 1. Population attributable fractions in the group of uncontrollable risk factors.

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2. Fig. 2. Population attributable fractions in the group of partially managed risk factors.

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3. Fig. 3. Population attributable fractions in the group of partially managed risk factors.

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