Background Although maternal smoking during pregnancy has been reported to have an effect on childhood overweight/obesity, the impact of maternal smoking around the trajectory of the body mass of their offspring is not very clear. modeled BMI trajectory using 3604-87-3 supplier a 2-level random intercept and slope regression. Results The participating mothers delivered 1619 babies during the study period. For male children, there was very strong evidence that the effect of age in months around the increase in BMI z-score was enhanced by maternal smoking during pregnancy (< 0.0001). In contrast, for female children, there was 3604-87-3 supplier only weak evidence for an conversation between age in months and maternal smoking during pregnancy (= 0.054), which suggests that the effect of maternal smoking during pregnancy around the early-life BMI trajectory of offspring differed by gender. Conclusions These results may be useful for exploring the mechanism of fetal programming and might therefore be clinically important. < 0.0001). However, there was no evidence of a relationship between BMI z-score trajectory and maternal smoking during pregnancy (= 0.7). Regarding the conversation term between age in months and maternal smoking, there was very strong evidence that maternal smoking during pregnancy enhanced the effect of age in months around the increase in BMI z-scores (< 0.0001; Table, Figure). Figure. Childhood body mass index (BMI) z-score trajectories calculated by individual growth analysis based on random intercept and random slope models, as shown, 3604-87-3 supplier 3604-87-3 supplier for smoking and nonsmoking mothers Table. Solution for fixed effects in the random intercept and random slope model for months of age of the children (MOA), smoking status of their mother, and conversation between MOA and smoking status of their mother in the Koshu Project, 1991C2008 For girls, there was very strong evidence that BMI z-score also increased as age in months increased (< 0.0001). In addition, there was very strong evidence for a relationship between BMI z-score trajectory and maternal smoking during pregnancy (= 0.0006). However, there was only a weak conversation between age in months and maternal smoking during pregnancy (Table, Figure). DISCUSSION The present study confirmed our previous findings (ie, that the effect of maternal smoking during pregnancy around the early-life BMI trajectory of offspring differed by gender) but used an analytic method with greater validity and precision. As boys grew up, they were more likely than girls to be affected by maternal smoking during pregnancy. Among boys, although BMI z-score significantly increased as age in months increased, the effect of maternal smoking during pregnancy was not significant, which could enhance the effect of age in months around the increase in BMI z-score. In contrast, among girls, the coefficients of both age in months and the conversation term between age in months and maternal smoking were smaller than those in males. Consequently, the effect of maternal smoking on BMI z-score in girls was smaller than that in males. These results were consistent with those of our previous study, which used a fixed effect model.13 Some studies have suggested that girls are less vulnerable to adverse environmental factors such as exposure to smoking.18 Moreover, Smith et al have shown that prenatal nicotine exposure results in higher testosterone levels in rat fetuses,19 and Blouin et al have suggested that androgens play an important role in regulating body fat distribution.20 Our results appear to be consistent with these biological explanations. In contrast, Wisniewski and Chernausek have suggested that girls are more susceptible to environmental factors associated with obesity.21 However, they did not include a Japanese population in their study. Thus, it may be necessary to conduct further studies of the effects of ethnic differences. In conclusion, smoking by pregnant mothers increases childhood weight gain, especially in boys. This result may be valuable for exploring the mechanism of fetal programming and might thus be clinically important. For example, it is important to conduct further studies on gender differences in fetal programming to clarify the mechanism of obesity-related diseases such as type 2 diabetes. ACKNOWLEDGMENTS We thank the study participants for the use of their personal data. We also thank the staff of the Administrative Office of Koshu City. This work was supported by a Grant-in-Aid for Scientific Research (KAKENHI 20590639) from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan. Conflicts of interest: The authors have Rabbit polyclonal to LRRC8A no financial or other conflicts of interest. Recommendations 1. Nguyen DM, El-Serag HB. The epidemiology of obesity. Gastroenterol Clin North Am. 2010;39:1C7 10.1016/j.gtc.2009.12.014 [PMC free article] [PubMed] [Cross Ref] 2. World Health Organization. A World Health Business Consultation on Obesity. ObesityPreventing and Managing the Global Epidemic. Geneva, Switzerland: World Health Business; 1998. 3. Popkin BM, Doak CM. The obesity epidemic is a worldwide phenomenon. Nutr Rev. 1998;56:106C14 10.1111/j.1753-4887.1998.tb01722.x [PubMed] [Cross Ref] 4. Matsushita Y, Takahashi Y, Mizoue T, Inoue M, Noda M, Tsugane S; JPHC Study Group . Overweight and obesity trends among Japanese.