OBJECTIVE: To identify social determinants of @entity102 @entity146 in primary school students in Beijing, China. METHODS: Cross-sectional study was designed and a two-stage (districts and schools) stratified (school type) cluster (classes) sampling method was adopted. Haidian and Fengtai districts were chosen firstly. One state and one private school with more migrant @entity1 were chosen in each district, paired with two state primary schools with more permanent resident @entity1 . Two classes from grades 4, 5 and 6 from each primary school were selected, all students in which and their parents were included as study subjects. A self-designed questionnaire was adopted to collect demographic information, @entity102 @entity146 and knowledge from students and their parents. Overall, a total of 1604 paired samples of students and parents were obtained from eight primary schools. Eleven self-reported behaviors were grouped into three, which were trying smoking, dietary intake frequency (vegetables, fruit, milk, and breakfast intake, salty foods, fatty diets), sedentary life style (reading, watching TV and playing PC continuously more than one hour, and having physical activities both in school and at home). According to the number of risk behaviors, three groups were classified as low (0 - 1), medium (2 - 3), and high (4 + ). ANOVA, Chi-square test and ordinal logistic regression analysis were adopted to find the influence of demographic characteristics, school types, social economic status (SES) , students' health knowledge, and parents' health knowledge and behaviors on students' number of risk behaviors. RESULTS: Ordinal logistic regression analysis showed @entity1 (OR = 1. 26, 95% CI 1. 03 - 1. 53) and older (OR = 1. 25, 95% CI 1. 14 - 1. 37) were risk factors for more risk behaviors. Higher SES scores (OR = 0. 84,95% CI 0. 73 - 0. 95) and higher students' health knowledge scores (OR = 0. 87, 95% CI 0. 83 - 0. 91), and better parents' health behaviors scores (OR = 0. 87, 95% CI 0. 83 - 0. 91) were protective factors for the number of risk behaviors. Household registration status and school types had no significant impact yet. @entity1 (OR = 1. 39, 95% CI 1. 08 -1.79) and lower SES scores (OR =0. 85, 95% CI 0. 73 -1. 00) were significant risk factors for more risk behaviors among migrant students, compared with those in residents students, while other factors had similar impact between two groups. CONCLUSION: Family social and economic status, students' health knowledge and parents' behaviors would have great impact on students' health behaviors cultivation.

[Social determinants of @entity102 XXXX in primary school students in Beijing City].

@entity1 :: ('9606', 'Species') :: ['children', 'Boys', 'boys'] @entity102 :: ('MESH:D002908', 'Disease') :: ['chronic diseases'] @entity146 :: ('MESH:D001523', 'Disease') :: ['related behaviors']
@entity146 :: (MESH:D001523,Disease) :: ['related behaviors']
