ABSTRACT
Objective To explore the characteristics of distribution on Chinese adult body mass index (BMI) in different age groups and genders and to provide reference related to obesity and related chronic diseases.Methods Data from the China Health and Nutrition Survey in 2009 were used.Sequential sample cluster method was used to analyze the characteristics of BMI distribution in different age groups and genders by SAS.Results Our results showed that the adult BMI in China should be divided into 3 groups according to their age,as 20 to 40 years old,40 to 65 years old,and ＞ 65 years old,in females or in total when grouped by difference of 5 years.For groupings in male,the three groups should be as 20 to 40,40 to 60 years old and ＞60 years old.There were differences on distribution between the male and female groups.When grouped by difference of 10 years,all of the clusters for male,female and total groups as 20-40,40-60 and ＞60 years old,became similar for the three classes,respectively,with no differences of distribution between gender,suggesting that the 5-years grouping was more accurate than the 10-years one,and BMI showing gender differences.Conclusions BMI of the Chinese adults should be divided into 3 categories according to the characteristics of their age.Our results showed that BMI was increasing with age in youths and adolescents,remained unchanged in the middle-aged but decreasing in the elderly.
ABSTRACT
Objective To explore the characteristics of distribution on Chinese adult body mass index (BMI) in different age groups and genders and to provide reference related to obesity and related chronic diseases.Methods Data from the China Health and Nutrition Survey in 2009 were used.Sequential sample cluster method was used to analyze the characteristics of BMI distribution in different age groups and genders by SAS.Results Our results showed that the adult BMI in China should be divided into 3 groups according to their age,as 20 to 40 years old,40 to 65 years old,and ＞ 65 years old,in females or in total when grouped by difference of 5 years.For groupings in male,the three groups should be as 20 to 40,40 to 60 years old and ＞60 years old.There were differences on distribution between the male and female groups.When grouped by difference of 10 years,all of the clusters for male,female and total groups as 20-40,40-60 and ＞60 years old,became similar for the three classes,respectively,with no differences of distribution between gender,suggesting that the 5-years grouping was more accurate than the 10-years one,and BMI showing gender differences.Conclusions BMI of the Chinese adults should be divided into 3 categories according to the characteristics of their age.Our results showed that BMI was increasing with age in youths and adolescents,remained unchanged in the middle-aged but decreasing in the elderly.
ABSTRACT
Objective The aim of this study was to evaluate whether PRDM16 gene polymorphisms were associated with dyslipidemia. Methods The polymorphisms of rs2651899, rs2236518, rs870171, and rs2282198 in PRDM16 gene in 528 participants were genotyped by the method of snapshot or ligase detection reaction. The genotype differences and the allele differences between the case group and the control group were analyzed. Linkage disequilibrium analysis was performed with SHE-sis online software. The interaction between rs2651899, rs2236518, rs870171, rs2282198 and gender, age, BMI were analyzed by MDR software. Results The frequency of allele A in rs2651899 locus was significantly higher in low HDL-C group compared with that in control group[OR(95%CI)=1.32(1.02-1.71), P=0.033]. The frequency of A/C genotype in rs870171 was significantly different between LDL-C abnormal group and control group[OR(95% CI)=1.97(1.01-3.86), P=0.037]. There may be interaction between rs2236518 and sex, which is a risk factor for low HDL-C[Model Ⅱ: OR(95% CI)=1.958(1.366-2.809), P<0.01]. There may be interactions among rs2651899, rs2236518, rs870171, and rs2282198, which seemed to be risk factors for lower HDL-C[Model Ⅳ: OR(95% CI)=3.991(2.707-5.884), P<0.01]. rs870171, rs2282198 may have interaction with age, which is a risk factor for high LDL-C [Model Ⅶ: OR(95%CI)=3.991(2.707-5.884), P<0.01]. Conclusion Allele A of rs2651899 may be a risk factor to low HDL-C. Under the codominant inheritance patterns, genotype A/C of rs870171 may be a risk factor to high LDL-C. In addition, there may be interaction between SNPs with gender and age.