Study design and participants
We conducted a cross-sectional survey of children aged 3-6 years in Guangzhou between July to October in 2015, which was a part of the National Survey on Physical Growth and Development of Children in nine cities of China (NSPGDC) [15]. The NSPGDC used the identical methodology to collect data from nine cities, thus data collected in each city could be analyzed to produce a general conclusion for the local population. The study design, organization, and implementation of the NSPGDC have been published previously [16]. Briefly, in each study city, a cluster random sampling method based on age groups (there were 22 age groups and 150-200 subjects for each sex-age subgroup) for both urban and rural areas was employed to produce a random sample [17]. Children under 3 years in a community was classified as a minimum cluster unit, and children aged 3 and above in kindergarten regarded as a unit. Exclusion criteria included temporary residents, acute illness within a month, chronic illness (such as cardiopathy, chronic nephrosis, tuberculosis, persistent hepatitis), obviously malnourished and physically handicapped.
The data of 3 to 6 years old children in Guangzhou of the survey was included in this analyze. 5102 participants aged 3 to 6 years were selected from 16 kindergartens in urban administrative districts (Yuexiu, Liwan and Haizhu), and 16 kindergartens in rural administrative districts (Conghua, Huadu, Panyu and Baiyun). We excluded 235 participants after reviewing the completeness of the questionnaire (with missing data >15%). Therefore, the remained 4867participants were included in the final analysis, with an effective response rate of 95.4% (4867/5102). Data was collected by local trained physicians with a structured questionnaire, which include participants’ demographic characteristics, mother’s health conditions during pregnancy, delivery mode, feeding patterns in the first 6 six months, sleep problems and ARDs of the participants. Body weight and height were also measured by calibrated instruments and standard specifications, and body mass index (BMI) was calculated by dividing the weight in kg by the square of length in m. Age and sex specific BMI z-score was calculated according to the Chinese standard[18].
Measurement
Asthma and allergic rhinitis was assessed by the face to face interviewed questions based on the International Study of Asthma and Allergy in Children Questionnaire (ISAACQ) (“Has your baby had wheezing or whistling in the chest during the past 12 months?” “Has your baby had a problem with sneezing, or a runny, or a blocked nose when he/she did not have a cold or the flu during the past 12 months?” [19]. And we asked children’s caregivers whether their children had been diagnosed with asthma/allergic rhinitis by doctors in the past 12 months, and whether their children had taken any aerosol inhalation medicine due to the asthma or wheeze? The pediatricians reviewed the questionnaire and made a judgment that children with symptoms of wheeze or whistling in the chest and had been diagnosed with asthma and use asthma medicine in recent 12 months would be defined as asthma, and the children with symptoms of sneezing, or a runny, or a blocked nose and had been diagnosed with allergic rhinitis would be defined as allergic rhinitis.
We assessed sleep duration, usual bedtime and nocturnal awakening frequency during recent two weeks in the present study, using the questions derived from the Chinese version of The Children’s Sleep Habits Questionnaire (CSHQ) [20]. Sleep duration was assessed based on the questions (“Write in your child’s usual amount of sleep each day (combining nighttime sleep and naps):” According to the National Sleep Foundation’s recommendation, preschoolers (3-6years) who sleep less than 10 hours were defined as short sleep duration [21]. Bedtime was assesses by the question (“write in your child’s usual bedtime”). As the 75 percentiles of bedtime among 3 to 6 aged children in this study was 22:00, the bedtime was classified into 2 groups: at or before 22:00 and after 22:00, and bedtime later than 22:00 was considered as a late bedtime. The nocturnal awakening frequency was assessed by the question (“write in your child’s number of wake up times during the night”), and classified into 2 groups: none or seldom, and once or more per night. According to the previous study by the National Sleep Foundation [19], children who wakened once or more per night among preschoolers (3-6 years) were defined as frequent nocturnal wakening.
Previous studies suggested a broad range of demographic characteristic and environmental factors that are associated with Asthma and allergic rhinitis [9, 10, 22, 23]. Therefore, we adjusted for these potential confounders, which was distributed differently according to the allergic disease in our analysis, including resident area, age, gender, mother’s education, BMI z-score of children, delivery mode, birth weight, maternal tobacco exposure during pregnancy, feeding patterns in the first 6 months.
Ethics declarations
The study was approved by the Ethical Committee for Biomedical Research in Guangzhou Women and Children’s Medical Center, and was conducted in accordance with Helsinki
Declaration and Ethical Guidelines for Research Involving Human Participants. A written informed consent was obtained from all the participants’ parents before starting of the survey.
Statistical analysis
Mean and standard deviation were reported for continuous variables. Frequencies and percentage were reported for categorical variables. T tests and Chi-square tests were used for comparing continuous and categorical variables, respectively. Binary logistic regression models were employed to estimate the odds ratios (OR) and 95% confidence intervals (CI) for asthma and allergic rhinitis according to short sleep duration, late bedtime and frequent nocturnal awaking, respectively. In each logistic regression model, three models were fitted.
In model 1, we estimated the crude ORs. In model 2, we adjusted for demographic characteristics, included region (urban/rural), gender (boys/girls), age, mother’s educational level (college or above/senior high school/junior high school or below) and BMI z-score In model 3, we additionally adjusted for delivery mode (vaginal delivery/cesarean delivery), birth weight (<2500 g/2500-3900g/≥4000 g), maternal tobacco exposure (smoking or passive smoking) during pregnancy, feeding patterns in the first 6 months of the children (breastfeeding/artificial feeding/mixed feeding), passive smoking (yes/no) .We further conducted subgroup analysis to examine whether gender influence the associations of asthma and allergic rhinitis allergic rhinitis with frequent nocturnal awaking where significant associations were found. Missing data of continuous covariates was inputted based on means and categorical covariates was inputted by the median. Significance level was set at P<0.05 and all tests were 2-sided. Statistical analyses were conducted using SPSS Statistics, version 25.0 (IBM Corp).