Background: The prevalence of allergic rhinitis (AR) has been increasing steadily worldwide, especially in countries with increasing industrialization such as China. However, available evidence regarding AR prevalence among Chinese adults is scarce and limited to regional data collected in earlier years. We therefore aimed to provide a more recent and robust estimate of AR prevalence using a nationwide representative cross-sectional study in China.

Methods: Data of 184 326 participants aged 18 years or older were obtained from the China Chronic Disease and Risk Factor Surveillance conducted in 2018-2019. AR was determined by self-reported sneezing, nasal itching, obstruction, or rhinorrhea symptoms for at least 1 h in the absence of a cold or flu within the last 12 months. Multivariable logistic model was used to examine the risk factors of AR, and a possible non-linear relationship was further tested by restricted cubic spline. Potential additive interactions of risk factors with sex, residence, and geographic region were assessed by relative excess risk due to interaction (RERI).

Results: The weighted prevalence of AR was 8.1% (95% confidence interval [CI], 7.4%-8.7%), of whom 23.7% (95% CI, 21.3%-26.0%) were aware of their diagnosis. Increased odds of AR were associated with younger age, men, living in urban area or north region, more education, smoking, underweight, and higher income. Despite the nonsignificant linear trend, the spline regression demonstrated a non-linear association between AR and sleep duration, with higher odds at both ends. Additionally, the observed associations were generally stronger among men and people living in urban area and north region, with significant RERI ranging from 0.07 (95% CI, 0.00-0.14) to 0.40 (95% CI, 0.12-0.67).

Conclusions: AR is prevalent in China and the associated factors and interactions are helpful to design targeted preventive strategies towards certain subpopulations. The low awareness of AR calls for a national effort on AR screening.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10050653PMC
http://dx.doi.org/10.1016/j.waojou.2023.100744DOI Listing

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