Effects of age, gender, and environmental exposures on exhaled nitric oxide level in healthy 12 to 18 years Qatari children

年龄、性别和环境暴露对12至18岁健康卡塔尔儿童呼出气一氧化氮水平的影响

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Abstract

CONTEXT: Fractional exhaled nitric oxide (FENO) is a useful noninvasive diagnostic tool for asthma and some other pediatric respiratory diseases. Factors affecting FENO level are variable in different populations and studies. AIMS: To estimate the normal values of exhaled nitric oxide for Qataris 12 to 18 years of age. Other objectives were to measure the correlation of anthropometric and other potential factors with FENO levels. SETTINGS AND DESIGN: Community-based, cross-sectional study. METHODS: A total of 438 Qatari national school children from both genders were randomly recruited in cross-sectional study. Of them, 203 were non-atopic and hence included in the statistical analysis. Questionnaires including personal data, demographic data, and other factors that may affect FENO level were distributed. STATISTICAL ANALYSIS USED: Comparison of means done using t-test. We performed Spearman's rho test to measure correlations. Data analysis was done using PASW 18.0 Release 18.0.0, 2009. RESULTS: The geometric mean of FENO levels for all subjects was 14.1 ppb (upper level CI 95% - 36.3 ppb). FENO was significantly higher in males (R(2) = -0.254, P<0.0001) and was negatively correlated with increasing age for the whole study population (P=0.036). This decline was interrupted by a significant upraise at the age of 15 years (P=0.0462) which seems to be driven by the males (P=0.0244). FENO levels were lower in subjects exposed to cats (P=0.019). We could not find significant correlation between FENO and other factors studied. CONCLUSIONS: Estimated FENO level with 95% CI in Qatari children, which is probably close to those in other Gulf countries, will be helpful clinically. The lower level of FENO with female gender, increasing age, and exposure to cats needs to be further studied to establish the association and to understand the underlying mechanisms.

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