Vitamin D deficiency among healthy adolescents in Al Ain, United Arab Emirates

Personal identification numbers were assigned to each participant to maintain anonymity. The identification number was used to confirm consent status and to link students to their respective schools, clinical measurements and blood samples. A questionnaire was developed to obtain relevant information related to age, gender, ethnicity, mother’s education level, dietary habits, and physical activity. The questionnaire was translated in Arabic and validated by a pilot test using 30 volunteers. In the dietary habit section of the questionnaire, milk and milk product consumption data were categorized as less than once per day, once per day and more than once per day. The short version of the International Physical Activity Questionnaire [14] was used to assess the physical activity status in the study participants. Part of the physical activity questionnaire asked information on hours spent watching television, playing video games, and computer use. Combined television, video, and computer hours were categorized as none, ≤2 hours, 3 to 4 hours and >4 hours per day.

A training workshop on standardizing the method of anthropometric and blood pressure measurement was conducted by qualified trainers prior to data collection, and involved nurses of all study schools. All measurements were performed at the same time of the day (i.e. early morning between 8 and 11 am) for all participants. Height was measured in centimeters (cm) using a stadiometer (SECA) with the participant standing in an upright position without wearing shoes. Waist circumference was measured in centimeters (cm) using an un-stretched measuring tape placed around the midpoint between the bottom of the rib cage and above the tip of the iliac crest. Body weight was measured to the nearest 0.2 kilograms (kg) using a digital scale (SECA) with the participant standing in an upright position without shoes and in light clothing. Triplicate readings of height, weight and waist circumference were taken and the average was considered to be the participant’s measurement.

Following at least five minutes of rest in a seated position, blood pressure (BP) was measured on the right arm using a standard mercury sphygmomanometer with an appropriate cuff size. All participants were required to refrain from smoking, consuming caffeine and participating in any moderate- or vigorous-intensity physical activity at least 60 minutes before their blood pressure measurement. Three consecutive measures were obtained at one-minute intervals and the average of the last two readings was considered to be the participant's blood pressure.

A five milliliter venous blood sample was obtained from the subjects by qualified nurses using standardized tubes. Prior to blood sampling, all participants had been instructed to fast for at least eight hours and abstain from smoking. Blood samples were sent to Tawam hospital laboratory within two hours of blood draw where they underwent standardized (quality controlled) analyses. Serum 25 (OH) D concentrations were measured by radioimmunoassay (DiaSorin, Stillwater, MN). The intra-assay and inter-assay for coefficients of variation were 8.3% and 3.2% respectively. The fasting plasma glucose (FBS), high density lipoproteins (HDL) and triglycerides (TG) were analyzed by the DXC 800 Analyzer (Beckman Coulter, Fullerton, CA, USA) using the appropriate conventional laboratory reagents, enzymatic and calorimetric techniques.

Body mass index (BMI) was calculated as body weight in kilograms divided by height in meters squared. BMI was used to classify participants as either healthy/normal weight (BMI 5^th to 75^th percentile), overweight (BMI between the 85^th and 95^th percentiles) or obese (BMI ≥95^th percentile) according to the 2000 Centers for Disease Control and Prevention growth charts using Anthro program in Epi-Info software [15].

Metabolic syndrome (MetS) was defined using the diagnostic criteria proposed by the International Diabetes Federation [16]; namely, waist circumference ≥90^th percentile or ≥94^th percentile (for youth aged 16 years or older), triglycerides concentrations ≥150 mg/dL(1.7 mmol/L), HD-cholesterol <40 mg/dL(1.03 mmol/L) or <50 mg/dL (1.29 mmol/L) for female adolescents aged ≥16 years and older, fasting plasma glucose (FPG) concentrations of >100mg/dL (5.6 mmol/L) and blood pressure (BP) ≥130/80 mmHg.

Elevated blood pressure was defined by using percentiles for systolic and diastolic values on the basis of height percentile, age and gender. Values >95th percentiles were considered elevated [17].

The 25 (OH) levels are the most commonly measured indicator of vitamin D status. We defined vitamin D deficient as having serum 25OHD level ≤15 ng/mL [≤37.5 nmol/L] and vitamin D insufficient as 25OHD level ≤20 ng/mL [≤50 nmol/L], respectively [18, 19].

All data were normally distributed. Descriptive statistics (frequencies, means, standard deviations) were used to estimate serum 25(OH) D concentrations by age group, gender, nationality, mother’s education level, food intake, physical activity, nutritional status and by presence of cardiovascular risk factors such as high blood pressure, high blood glucose, low HDL-cholesterol, high triglycerides and metabolic syndrome. The analyses were conducted using Epi-info, and SPSS (v.19). A one way ANOVA and student t-test was used to analyze the association between serum 25(OH) D concentrations and potentially associated variables. Statistical significance was defined as p-values <0.05. Serum 25 (OH) D concentrations were considered as a continuous outcome variable for multivariate analyses to avoid power loss associated with categorization [20] and stepwise linear regression analysis was used to identify the significant covariates of serum 25 (OH) D concentrations.