■先前的研究表明,体重与端粒长度之间存在显着关联,但没有考虑重量范围。该研究旨在研究体重范围与端粒长度的关系。
■分析了来自1999-2000年国家健康和营养调查(NHANES)的2918名年龄在25-84岁之间的合格参与者的数据。有关人口统计变量的信息,生活方式因素,人体测量变量,并包括医疗合并症。采用调整潜在混杂因素的单变量和多变量线性回归模型来确定体重范围和端粒长度之间的关联。使用非参数限制的三次样条模型来说明可能的非线性关系。
■在单变量线性回归中,BMImax,BMI范围,和体重范围均显示与端粒长度呈显著负相关。然而,BMI/体重范围的年增长率与端粒长度呈显著正相关.端粒长度和BMImin之间没有显着关联。在调整了潜在的混杂因素后,在BMImax中仍然存在逆关联(β=-0.003,P<0.001),BMI范围(β=-0.002,P=0.003),和体重范围(β=-0.001,P=0.001)。此外,BMI范围(β=-0.026,P=0.009)和体重范围(β=-0.010,P=0.007)的年比率与端粒长度呈负相关,在模型2-4中调整协变量后。在多元线性回归模型中,BMImin(β=-0.002,P=0.237)与端粒长度的相关性仍未达到统计学意义。约束三次样条分析的结果表明,BMImax(非线性P=0.026),BMI范围(非线性的P=0.022),重量范围(非线性的P=0.035),BMI范围的年率(非线性的P=0.030),和重量范围的年比率(非线性P=0.027)都与端粒长度具有非线性逆关联。
■该研究表明,在美国成年人中,体重范围与端粒长度呈负相关。较大的体重波动可能会加速端粒缩短和老化。
Previous research has shown a significant association between weight and telomere length, but did not take into consideration weight range. The study was to investigate the association of weight range with telomere length.
Data of 2918 eligible participants aged 25-84 years from the National Health and Nutrition Examination Survey (NHANES) 1999-2000 cycle were analyzed. Information about demographic variables, lifestyle factors, anthropometric variables, and medical comorbidities were included. Univariate and multivariate linear regression model with adjustments for potential confounders were employed to determine the association between weight range and telomere length. A non-parametrically restricted cubic spline model was used to illustrate the possible non-linear relationship.
In univariate linear regression, BMImax, BMI range, and weight range all revealed significant negative associations with telomere length. However, annual rate of BMI/weight range showed a significant positive associations with telomere length. There was no significant association between telomere length and BMImin. After adjusting for potential confounders, the inverse associations persisted in BMImax (β=-0.003, P<0.001), BMI range (β=-0.002, P=0.003), and weight range (β=-0.001, P=0.001). Furthermore, annual rate of BMI range (β=-0.026, P=0.009) and weight range (β=-0.010, P=0.007) presented negative associations with telomere length, after adjusting for covariates in Model 2-4. The association between BMImin (β =-0.002, P=0.237) and telomere length still could not reach statistical significance in multivariate linear regression model. The results of restricted cubic spline analysis showed that BMImax (P for nonlinear =0.026), BMI range (P for nonlinear =0.022), weight range (P for nonlinear =0.035), annual rate of BMI range (P for nonlinear =0.030), and annual rate of weight range (P for nonlinear =0.027) all had nonlinear inverse associations with telomere length.
The study suggests that weight range is inversely associated with telomere length in U.S. adults. Larger weight fluctuation may accelerate telomere shortening and aging.