The association of mean telomere length with all-cause, cerebrovascular and cardiovascular mortality
Author(s) -
Yuqing Huang,
Kenneth Lo,
Yingqing Feng,
Bin Zhang
Publication year - 2019
Publication title -
bioscience reports
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.938
H-Index - 77
eISSN - 1573-4935
pISSN - 0144-8463
DOI - 10.1042/bsr20192306
Subject(s) - hazard ratio , national health and nutrition examination survey , medicine , confounding , proportional hazards model , confidence interval , demography , multivariate analysis , bayesian multivariate linear regression , linear regression , population , environmental health , machine learning , sociology , computer science
Mean telomere length (MLT) is a marker of cell aging and may associate with age-related diseases. However, the relationship between MLT and mortality risk remains unclear. We aimed to investigate the relationship between MLT and all-cause, cerebrovascular and cardiovascular mortality among adults in United States. We analyzed data were from National Health and Nutrition Examination Survey (NHANES, 1999-2002) with follow-up data through 31 December 2015. Based on MLT, participants were categorized into low, middle and high groups. Multivariate Cox proportional hazards regression, subgroup analysis and generalized additive model (GAM) were performed by using hazard ratios (HRs) and 95% confidence intervals (CIs). A total of 7827 participants were included in analysis (48.18% male). After 158.26 months of follow-up on average, there were 1876 (23.97%), 87 (1.11%) and 243 (3.10%) onset of all-cause, cerebrovascular and cardiovascular mortality. After adjustment for potential confounders, using the low group as the reference, HRs for all-cause (0.87 and 0.86), cerebrovascular (0.75 and 0.75) and cardiovascular mortality (1.01 and 0.69) for the middle to high groups were not statistically significant (all P>0.05 for trend). MLT was non-linearly related to all-cause mortality but not to cerebrovascular and cardiovascular mortality. It was the first study to demonstrate the non-linear relationship between MLT and all-cause mortality.
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