This nationwide study was conducted in urban and rural areas of Iran in 2015 as the fifth national survey of a school-based surveillance program entitled the Childhood and Adolescence Surveillance and Prevention of Adult Non-communicable disease (CASPIAN-V) study. Data was checked at the district level by academic supervisors (expert of school health) and controlled by national supervisors and operators. Detailed description of the sampling and data collection methods are published previously (11). Briefly, here we explain the methodology of the CASPIAN-V study.
Study population and sampling framework
The study population consisted of students aged 7–18 years in primary and secondary schools in urban and rural areas across the country. Students were selected by multistage, stratified cluster sampling method from 30 provinces of the country (48 clusters of 10 students in each province). Stratification was performed in each province according to the residence area (urban/rural) and level of education (primary/ secondary). The sampling size was proportional to population in each urban or rural area with equal sex ratio. Cluster sampling with equal clusters was used in each province to reach the necessary sample size. Clusters were determined at the level of schools, including 10 statistical units (students and their parents) in each cluster.
Procedure and measurements
Questionnaires
Two sets of the questionnaires were used for students and their parents. The questionnaires were obtained from Global School Student Health Survey (GSHS) that translated to Persian (12). The reliability and validity of the Persian version of questionnaire was approved in the previous studies (13, 14).
The student questionnaire included questions regarding body image, psychosocial environment of school, dietary habits, life‑style habits, and violence behavior. Trained personnel completed questionnaires in a calm atmosphere inside the schools; the whole process was supervised and controlled by a team of health care professionals.
Issues such as family composition, economic and socio-demographic factors, genetic determinants (family history of hypertension, diabetes, and obesity), past history of student (birth weight, breastfeeding, and type of complementary food), and family dietary habits were included in the parent’s questionnaire.
Measuring tools
The questionnaire of the World Health Organization- Global School-based Student Health Survey (WHO-GSHS) was used to assess aggressive behaviors, LS, SRH and counseling with family members. Demographic information on age, gender, residence area, family based characteristics, living with parents, parental level of education, possessing a family private car and type of home gathered through interview with students.
Life satisfaction (LS) was assessed through a single item. Students were asked to indicate their degree of life satisfaction by using a tenth-point scale from 1= very dissatisfied to 10 = very satisfied. Fewer than 6 responses were aligned to dissatisfaction and responses of equal and upper 6 were defined as satisfaction.
Self-rated health (SRH) was assessed through a single item, "how would you describe your general state of health?"; the categories of response were “perfect”, “good”, “bad,” and “very bad”. For statistical analysis, "perfect and good" responses were considered as "good SRH". Moreover, the preference of participant in consulting with father, mother, and sister/brother and friends were asked for further analyses.
Physical activity was assessed through a validated questionnaire including weekly frequency of leisure time physical activity outside the school during the past week, and having sufficient physical activity was defined as at least 30 min of exercise per day that led to sweating and large increases in breathing or heart rate (15).
Sedentary time was considered as the average number of hours per day spent watching television or using computer assessed with a validated questionnaire (12).
Socioeconomic status (SES) was calculated through a questionnaire included questions about the following socioeconomic indicators: (a) parental level of education (illiterate: score 1, less than high school: score 2, high school graduate: score 3, academic education: score 4); (b) parental occupational status (unemployed: score 1, worker/farmer: score 2, governmental employee: score 3, self-employed: score 4); (c) number of inhabitants in home, and (d) possessing a family private car (yes/no). It should be noted that for questions (a) and (b) (i.e. parental occupational status and level of education) data from the parent with a higher occupational status/education was considered.
School satisfaction was assessed through a validated questionnaire regarding the overall satisfaction with school life experience including interest in learning tasks, attitude to homework, school environment, relationships with teachers and classmates.
Social contact was assessed through a validated questionnaire regarding social relationship, the number of friends and time spend with them.
Well-being was considered as the overall satisfaction with relationships with family members and friends and current life conditions.
Ethical concerns
The protocols of the present study were assessed and approved by the Research and Ethics Council of Isfahan University of Medical Sciences (Project Number: 194049). Written informed consent and verbal consent was obtained from the parents and students, respectively (11).
Statistical analysis
All variables were checked for normality and expressed as means (standard deviation, SD). Student’s two-tailed t test was used to compare the mean differences of characteristics between boys and girls. Pearson correlation was applied to examine the relationships between the study variables and to implement the subsequent structural modeling. Path analysis was applied to examine the causal framework. Path analysis includes causal modeling, analysis of covariance structures, and latent variable models. This model is a generalization of multivariate multiple regression that allows one to estimate the strength and sign of direction and indirection association for complicated causal schemes with multiple dependent and independent variables (16,17). Path standardized coefficients (β) as the effect sizes of associations were calculated. Goodness of fit (GOF) indices (e.g. The Root Mean Square Error of Approximation (RMSEA), the goodness of fit index (GFI), the adjusted GFI) were applied for assessing of fitness of the model (18). All of the statistical analysis was performed using IBM, AMOS and STATA 11.0 (STATA Corp, College Station, TX). P-value less than 0.05 was considered as statistically significant.