14 %; p < 0.01). Of the 688 biological mothers, who completed the fracture questionnaire, 60 (9 %) indicated that they had sustained a fracture before the age of 18 years (white mothers 31 %, mixed ancestry 16 %, black mothers 6 %; W > B, p < 0.001; MA > B, p = 0.01). Unlike the pattern of fracture incidence among the adolescents and their siblings, there was no difference in the prevalence of fractures among the adolescents of mothers who had or did not have a history of fractures. Bivariate logistic regression analyses were initially performed for the whole group to assess if any confounding variables, such as weight, height, ethnicity, gender,

pubertal stage, adolescents’ and mothers’ S63845 datasheet BA and BMC (TB and LS), and sibling history of fracture or maternal history of fracture, were individually associated with adolescent fracture risk. In these analyses, the adolescent’s risk of fracture was higher if a sibling had a history of fracture (OR = 1.6, 95 % CI 1.12–2.32, p = 0.01), but was not associated with maternal history of fracture (OR = 1.09, 95 % CI 0.63–1.86, p = 0.762). Neither adolescent weight nor pubertal stage was associated with fracture risk of the entire www.selleckchem.com/products/Nilotinib.html cohort; however, height was positively associated with

the risk of fracture (OR = 9.85, 95 % CI 2.31–41.83, p < 0.01), and males were at greater risk of fracture compared to females (OR = 1.73, 95 % CI 1.33–2.24, p < 0.001). Adolescent TB BA (OR = 1.0008, 95 % CI 1.0002–1.001; p < 0.05) and TB BMC (OR = 1.0004, 95%CI 1.000002–1.0007, p < 0.05) were both marginally associated with increased fracture risk. Maternal LS BMC was inversely also associated

with fracture risk in their adolescent selleck products offspring (OR = 0.80, 95 % CI 0.7–0.93; p < 0.01). White adolescents had a greater risk of fracture than other ethnic groups (OR = 2.82, 95 % CI 1.82–4.37, p < 0.001). Multivariate logistic regression analyses were performed on the entire group (n = 1099) to determine the risk factors for fractures in the adolescents. The factors which had been found to be significantly associated in simple logistic regression and multiple regression analyses were included in the model, namely gender, ethnicity, sibling history of fracture, adolescent and maternal heights, adolescent TB BA and BMC, and maternal LS BMC. Only the significant risk factors for adolescent fracture risk are shown in Table 4. White ethnicity and male gender remained significant, with a greater risk of adolescent fracture. The adolescent’s risk of fracture was 50 % greater if a sibling had a history of fracture (OR = 1.5, 95 % CI 1.02–2.21, p < 0.05). Maternal LS BMC was protective against the risk of fracture in the adolescent (24 % reduction in fracture risk for every 1 unit increase in maternal BMC Z-score). Table 4 Odds ratios for fractures in 17/18-year-old adolescents Fractures (n = 1,099) Adjusted odds ratio 95 % Confidence interval Whites 3.16* 1.89–5.32 Males 1.94** 1.25–2.99 Sibling history of fracture 1.50*** 1.02–2.