Cuypers et al. BMC Public Health 2012, 12:820 http://www.biomedcentral.com/1471-2458/12/820 frequency (Not once (1), Once (2), 2–3 times (3), 4 times or more (4) in the last 7 days) and constructed a variable by adding the scores for cultural and social activities separately (range 4–16). Both results of earlier research [10,16,17] and statistical analyses [18] support our choice of the components in the definition of cultural and social activities. In the multivariable analyses this variable was assumed to be continuous. In the stratified analyses we dichotomised and converted the cultural variable into high culturally active corresponding to two or more cultural activities a day (1). High participation (1) in social activities was defined as corresponding to doing more than one social activity a day. Self-reported pubertal development status was assessed based on the Pubertal Development Scale (PDS) [19]. Measures at follow-up, HUNT 3 (2006–08) According to the WHO recommendations overweight was defined as BMI ≥ 25 kg/m2 [20]. Central overweight was defined as WC ≥ 80 cm for females and WC ≥ 94 cm for men [21]. Body fat distribution was measured by WHR. Overweight was defined as WHR > 0.80 in women and > 0.90 in men [22]. Z-scores were calculated to be able to adjust for age and sex and to pool all body fat estimates data of the adoles- cents and young adults, accounting for the natural devel- opment of the body measures over age in a longitudinal life perspective. The z-scores of the respective adiposity measures (at baseline sex-and-age specific and at follow- up sex-specific) were used as continuous variables. The physical activity level was assessed by self-report as described previously for adolescents and adults, and four categories of physical activity change over time were defined (stable active, stable inactive, from inactiv- ity to activity and from activity to inactivity [23]. We chose to use this “pattern”-physical activity variable be- cause there is indication that changes in physical activity may be more predictive in concordance to Kettaneh et al. [24]. Socio-economic status (SES) was measured in HUNT 3 (2006–08) reclassifying the Norwegian occupation clas- sification (STYRK) into an approximation to the Erikson Goldthorpe Portocarero social class scheme [14]. Genotypes In all, 12 SNPs representing 12 susceptibility loci asso- ciated with body fat estimates in GWA studies [25-29] and recently replicated in adolescent [30-33] were geno- typed: rs6265 in BDNF, rs545854 near MRSA, rs571312 near MC4R, rs987237 near TFAP2B, rs1121980 in FTO, rs2815752 near NEGR1, rs6548238 near TMEM18, rs10195252, near GRB14, rs10838738 in MTCH2, rs10938397 near GNPDA2, rs7566605 near INSIG2, and Page 3 of 10 rs11084753 near KCTD15. Genotyping was carried out by Centre for Integrative Genetics (CIGENE), Norwe- gian University of Life Sciences, Norway. All variants passed quality-control criteria with a call-rate ≥ 95% and were in Hardy-Weinberg equilibrium (p > 0.05), assessed by the genetic analysis program PLINK (Additional file 1: Table S1). Because a genetic predisposition score GPS might re- flect larger effects than each single variant separately [34] a GPS across the 12 SNPs was calculated by sum- ming the BMI-increasing alleles [35] defined by the results reported by recent GWA studies [25-31,36]. Individuals with missing genotypes for more than three SNPs were excluded (0.6% of the sample). For the purpose of calculating the genetic predispos- ition score in individuals with missing genotypes for three SNPs or less, missing genotype data were replaced with the average allele count of the respective SNP. The GPS was normally distributed (n = 1450, mean: 11.4, SD: 2.2) and inserted in the analyses as a continuous variable. Ethics Participation in the HUNT and the Young HUNT study was voluntary and approved by the Norwegian Data In- spectorate, The Directorate of Health, and by the Re- gional Committee for Medical and Health Research Ethics. All participants and the guardians of adolescents younger than 16 years signed an informed consent. Statistics Social or cultural activities in adolescence were divided into quartiles where first quartile indicated lowest par- ticipation rate and fourth quartile highest participation rate. In each group the prevalence of the weight status (normal weight and overweight) in young adulthood was recorded. Separate Generalized Estimating Equation (GEE) type linear models were employed to study the independent relationships between participation in cultural activities and social activities at baseline and z-scores of BMI, WC, and WHR respectively at follow-up. Because the effect of environmental influences seems to be larger in indivi- duals with phenotypic extremes during adolescence [37] and BMI at baseline may affect both participation in leis- ure time activities and tracking of BMI into adulthood, we chose to present the analyses including only the 1123 adolescents with normal weight at baseline [38]. GEE adjusts for the correlation between repeated observations taken in the same individual. In all these analyses, an exchangeable correlation structure was assumed. We adjusted for pubertal development at base- line, physical activity change, and SES at follow-up simultaneously.