Wang X, Wen J, Qu Q, Gu S, Zhang L, Li Y, Qi X. Association of weight range with telomere length: A retrospective cohort study.
Front Endocrinol (Lausanne) 2023;
14:1106283. [PMID:
37113487 PMCID:
PMC10126401 DOI:
10.3389/fendo.2023.1106283]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 03/28/2023] [Indexed: 04/29/2023] Open
Abstract
Objective
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.
Methods
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.
Results
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.
Conclusions
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.
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