Impact on the risk of obesity due to interactions between fat mass- and obesity-associated gene rs9939609 variants and behavioral factors, in the Chinese school-aged children
10.3760/cma.j.issn.0254-6450.2010.07.004
- VernacularTitle:体脂和肥胖相关基因多态性与生活行为因素交互作用对学龄儿童肥胖的影响
- Author:
Bo XI
1
;
Mei-Xian ZHANG
;
Yue SHEN
;
Xiao-Yuan ZHAO
;
Xing-Yu WANG
;
Jie MI
Author Information
1. 北京协和医学院
- Keywords:
Obesity;
Fat mass- and obesity-associated geneLife behavior factors;
Interaction
- From:
Chinese Journal of Epidemiology
2010;31(7):737-741
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate how the interactions between fat mass- and obesityassociated (FTO) gene rs9939609 variants and daily-life related behavioral factors would influence the risk of obesity among the Chinese school-aged children. Methods 3503 school-aged children were selected from the Beijing Child and Adolescent Metabolic Syndrome (BCAMS) Study, and divided into obese children (n=1229) and non-obese children (n=2274). Venipuncture blood test,genotyping and questionnaire were performed. Results Five common factors including protein foods, tobacco & alcohol, vegetables & fruits, sedentary behavior and physical exercise in spare time were extracted with factor analysis methodology. Data from logistic regression analysis showed that taking the interaction of rs9939609 variant with protein foods as an example, the risk of interaction accounted for 19.16% when both factors existing simultaneously. Similarly, the interactions of this SNP with vegetables & fruits, sedentary behavior and physical exercise in spare time appeared to be 5.97%, 19.62% and 12.43% respectively; however there might not be interaction between tobacco,alcohol and the SNP in the Chinese children. Conclusion Protein foods, vegetables & fruits,sedentary behavior and physical exercise might modify the effects of FTO rs9939609 variant on the risk of obesity in Chinese school-aged children. However, large-scale, prospective studies with detailed information on related behavioral factors would be ideal models for identifying the interactions between genes and environment.
