He Huiyu, Wei Mengling, Zhong Jiao, Wang Juan, Huang Lei, Lan Yajia, Zhang Yang
/ ( 610041) Department of Environmental and Occupational Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China.
/ ( 610041) Department of Osteoporosis, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China.
Sichuan Da Xue Xue Bao Yi Xue Ban. 2025 Mar 20;56(2):470-477. doi: 10.12182/20250360203.
To investigate the relationship between biological aging and the rate of cognitive decline in middle-aged and elderly populations.
Longitudinal tracking data of cognitive function were obtained from the China Health and Retirement Longitudinal Study (CHARLS). We employed the Klemera and Doubal method (KDM) to estimate biological age (BA), and calculate the biological aging index (BAI) and biological aging type (BAT). A multivariate linear regression model was employed to analyze the relationships between baseline BAI, BAT, and cognitive function scores. Based on the baseline analysis, a mixed-effects model was used to examine the longitudinal associations between baseline BAI, BAT, and cognitive function during follow-up.
A total of 5897 participants were included in the study. BAI was found to be negatively associated with baseline cognitive function scores, with the partial regression coefficient () (95% CI) being -0.185 (-0.231, -0.139) ( < 0.001). Compared with the lagged aging group, the premature aging group had lower cognitive function scores ( [95% CI]: -0.741 [-0.966, -0.516]). For age and sex, for each additional year of baseline BAI, cognitive function scores declined by an average of 0.012 (95% CI: -0.019, -0.005) points per year after adjusting for age and sex, and declined by 0.011 (95% CI: -0.018, -0.004) points per year after adjusting for other covariates. Compared with participants with lagged aging, those with premature aging experienced, on average, an additional decline of 0.042 (95% CI: -0.075, 0.009) points per year in cognitive function scores after adjusting for age and sex alone, and by 0.039 (95% CI: -0.072, -0.007) points per year after adjusting for other covariates.
Biological aging affects the rate of cognitive decline in middle-aged and elderly populations. A higher BAI is associated with a faster decline in cognitive function. Compared with those with lagged aging, individuals with premature aging exhibit a more rapid rate of cognitive decline.
探讨中老年人群生物衰老与认知衰退速率之间的关系。
认知功能的纵向跟踪数据来自中国健康与养老追踪调查(CHARLS)。我们采用克莱梅拉和杜巴尔方法(KDM)来估计生物年龄(BA),并计算生物衰老指数(BAI)和生物衰老类型(BAT)。采用多元线性回归模型分析基线BAI、BAT与认知功能得分之间的关系。基于基线分析,使用混合效应模型来检验随访期间基线BAI、BAT与认知功能之间的纵向关联。
本研究共纳入5897名参与者。发现BAI与基线认知功能得分呈负相关,偏回归系数()(95%置信区间)为-0.185(-0.231,-0.139)(<0.001)。与滞后衰老组相比,早衰组的认知功能得分较低([95%置信区间]:-0.741[-0.966,-0.516])。对于年龄和性别,在调整年龄和性别后,基线BAI每增加一岁,认知功能得分平均每年下降0.012(95%置信区间:-0.019,-0.005)分;在调整其他协变量后,平均每年下降0.011(95%置信区间:-0.018,-0.004)分。与滞后衰老的参与者相比,仅调整年龄和性别后,早衰者的认知功能得分平均每年额外下降0.042(95%置信区间:-0.075,0.009)分;在调整其他协变量后,平均每年下降0.039(95%置信区间:-0.072,-0.007)分。
生物衰老影响中老年人群的认知衰退速率。较高的BAI与认知功能更快衰退相关。与滞后衰老者相比,早衰个体的认知衰退速率更快。