Study design and participants
This cross-sectional study was conducted in Khorasan Razavi, northeastern Iran in January 2015. All the participants (n= 988) were girl students girls aged 12-18 years. The study population was recruited using a random cluster sampling method from several schools in different areas of city. We excluded those with autoimmune disease, cancer, metabolic bone disease, hepatic or renal failure, cardiovascular disorders, malabsorption or thyroid, parathyroid, adrenal diseases and anorexia nervosa or bulimia. In addition, girls taking anti-inflammatory, anti-depressant, anti-diabetic, or anti-obesity drugs, vitamin D or calcium supplement use and hormone therapy within the previous 6 months were not included. The ethical committee of Mashhad University of Medical Sciences, Mashhad, Iran, approved the study and all participants and their parents completed informed written consent.
Demographic and anthropometric assessments
General Demographic information was collected by face-to-face interview, using a standard questionnaire. Physical activity was assessed through validated Modifiable Activity questionnaire [18] and provided as metabolic equivalentsmets in hours per day. To estimate energy intake, the reported portion size in FFQ were converted to grams using household measures and then were entered to the Nutritionist IV software. Body weight, height and waist circumference were measured by a trained technician using standard protocols. Body Mass Index was calculated as weight in kilograms divided by height in meters squared. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured by an experienced nurse using standard protocol.
Biochemical assessments
Fasting blood samples were obtained between 8 and 10 a.m after an overnight fast. A electrochemi-luminescence method (ECL, Roche, Basel, Switzerland) was used for the measurement of serum 25-OH vitamin D. Fasting blood glucose (FBG), triglyceride (TG), total cholesterol (TC), high density lipoprotein-cholesterol (HDL-C), high-sensitive C-reactive protein (hs-CRP), calcium and phosphorus concentrations were measured by enzymatically method with the use of commercial kits (Pars Azmun, Karaj, Iran) and the BT-3000 auto-analyzer machine (Biotechnica, Rome, Italy). Low density lipoprotein-cholestrol (LDL-C) was calculated by using Friedewald formula if serum TGs concentrations were lower than 4.52 mmol/L[19].
Dietary behaviors assessment
Data on diet-related practices including frequency of main meal (1, 2 or 3 times) and snack (never, 1-2 or ≥3 times) intake, regular meal consumption (never, sometimes, almost or always), breakfast consumption (never or 1 day, 2-4 day, 5-6 day or every day), rate of food chewing (low, moderate or high), intra-meal fluid intake (never, sometimes, almost or always), frequency of fried (never, 1-3 in week, 4-6 in week or every day) and spicy (never, 1-3 in week, 4-6 in week or every day) food consumption were evaluated using a standard questionnaire.
Assessment of sleep disorders
A Persian translation of the Epworth Sleepiness Scale (ESS) was used for the assessment of daytime sleepiness [20], and its reliability and validity has been published previously [21]. This questionnaire asks respondents to rate their sleepiness in eight daily situations from 0 to 3 giving a total score of 0 (no daytime sleepiness) to 24 (the most excessive daytime sleepiness). EDS was defined as an ESS ≥10 [22].
Statistical analyses
Kolmogrov-Smirnow test was applied to assess the distribution of variables. Independent sample t-test was used detect differences in general characteristics (age, physical activity, energy intake, SBP and DBP) and biochemical assessments between individuals with and without EDS. Chi-square test was used to compare the categorical characteristics (menstruation, passive smoker, general and abdominal obesity) of the study population. To determine the association between diet-related practices and EDS, we used logistic regression in different models. Firstly, using an crude model, and then adjusted for age, physical activity, menstruation and passive smoking. Further adjustments were performed for general obesity. P-value <0.05 was considered statistically significant. All statistical analyses were performed using statistical Package for Social Sciences version 17 (SPSS Inc., Chicago, Illinois, USA).