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中国中老年人群体力活动量与全因死亡风险关系及其中介因子分析

Association between physical activity and all-cause mortality risk and related mediators in middle-aged and elderly Chinese population: an analysis of CHARLS data

  • 摘要:
    目的 探讨中国中老年人群体力活动量与全因死亡风险的关系以及影响此种关系的中介变量,为减少我国中老年人群全因死亡风险提供科学依据。
    方法 收集2011 — 2018年中国健康与养老追踪调查(CHARLS)中完成基线调查和3次随访调查的5727名 ≥ 45岁中老年人群的相关数据,采用多因素Cox比例风险回归模型和限制性立方样条模型分析其体力活动量与全因死亡风险之间的关系,并根据随访期间体质指数(BMI)、血压和血生化指标等数据进行中介效应分析。
    结果 中国5727名 ≥ 45岁中老年人群中,体力活动量最低四分位数组(<1720.95 METs-分/周)1 813人(31.66%),第二四分位数组(1720.95 ~ 5543.99 METs-分/周)1082人(18.89%),第三四分位数组(5544.00 ~ 12263.99 METs-分/周)1374人(23.99%),最高四分位数组( ≥ 12264.00METs-分/周)1458人(25.46%)。随访期间发生全因死亡事件者509例,全因死亡率为8.92%,其中体力活动量最低四分位数组、第二四分位数组、第三四分位数组和最高四分位数组中老年人群发生全因死亡事件者分别为271、85、80和73例,全因死亡率分别为14.99%、7.88%、5.89%和5.01%,中国中老年人群全因死亡率随着体力活动量的增加呈下降趋势(χ2趋势= 653.81,P趋势< 0.001)。在调整了性别、年龄、文化程度、婚姻状况、居住地、吸烟情况、饮酒情况、BMI、收缩压(SBP)、舒张压(DBP)、白细胞(WBC)、平均红细胞体积(MCV)、血小板计数(PLT)、血红蛋白(Hb)、红细胞压积(HCT)、C反应蛋白(CRP)、血糖(GLU)、糖化血红蛋白(HbA1c)、总胆固醇(TC)、甘油三酯(TG)、低密度脂蛋白(LDL)、高密度脂蛋白(HDL)、尿素氮(BUN)、肌酐、尿酸(UA)和半胱氨酸蛋白酶抑制物C(CysC)等混杂因素后,多因素Cox比例风险回归模型分析结果显示,体力活动量第二四分位数组、第三四分位数组和最高四分位数组中老年人群全因死亡风险分别为体力活动量最低四分位数组中老年人群的0.62倍(HR = 0.62,95%CI = 0.49~0.80)、0.52倍(HR = 0.52,95%CI = 0.40~0.67)和0.46倍(HR = 0.46,95%CI = 0.35~0.61);限制性立方样条模型分析结果显示,中国中老年人群体力活动量与全因死亡风险存在非线性剂量反应关系,两者呈L形关联,即全因死亡风险随体力活动量的增加逐渐下降,但当体力活动量达到16 000 METs-分/周时,全因死亡风险不再随体力活动量的增加而显著下降。中介效应分析结果显示,BMI和CRP可能介导了体力活动与全因死亡风险之间的关联,体力活动量最高四分位数组中老年人群的中介效应百分比分别为37.22%和39.60%。
    结论 体力活动量的增加可降低中国中老年人群的全因死亡风险,适当的体力活动量可为中老年人群带来更大的健康收益,降低BMI和机体的炎症反应可能是体力活动量与全因死亡风险之间的关联机制。

     

    Abstract:
    Objective To examine the association between physical activity and risk of all-cause mortality and related mediators in middle-aged and elderly people in China to provide evidence for reducing mortality in the population.
    Methods Data were collected from 5 727 individuals aged ≥ 45 years who completed baseline and 3 follow-up surveys in the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2018. We used multivariable Cox proportional hazards regression models and restricted cubic spline models to examine the association between physical activity levels and risk of all-cause mortality. In addition, we conducted a mediation analysis based on body mass index (BMI), blood pressure, and blood biochemical indicators collected during follow-up.
    Results Of all the individuals analyzed, 1 813 (31.66%) were classified as having physical activity (measured in metabolic equivalents METs-min/week) in the lowest quartile (<1 720.95), and the number (proportion) of the individuals with physical activity in the second quartile (1 720.95 – 5 543.99), third quartile (5 544.00 – 12 263.99), and highest quartile (≥ 12 264.00) were 1 082 (18.89%), 1374 (23.99%), and 1458 (25.46%), respectively. During the follow-up, a total of 509 deaths were observed and the all-cause mortality rate was 8.92%, with the number of all-cause deaths (mortality rate) being 271 (14.99%), 85 (7.88%), 80 (5.89%), and 73 (5.01%) among those with physical activity in the lowest, second, third, and the highest quartiles of METs-min/week, respectively. All-cause mortality showed a significant downward trend with increasing levels of physical activity among the individuals (χ2trend = 653.81, P trend < 0.001). After adjustment for sex, age, education level, marital status, place of residence, smoking, alcohol consumption, BMI, systolic blood pressure (SBP), diastolic blood pressure (DBP), white blood cells (WBC), mean corpuscular volume (MCV), platelets (PLT), hemoglobin (Hb), hematocrit (HCT), C-reactive protein (CRP), glucose (GLU), hemoglobin A1c (HbA1c), total cholesterol (TC), triglycerides (TG), low-density lipoprotein (LDL), high-density lipoprotein (HDL), blood urea nitrogen (BUN), creatinine, uric acid (UA), and cystatin C (CysC), multivariate Cox proportional hazards regression analysis showed that the hazard ratio for all-cause mortality for individuals in the second, third, and highest quartiles of METs-min/week was 0.62 (95% confidence interval 95%CI: 0.49 – 0.80), 0.52 (95%CI: 0.40 – 0.67), and 0.46 (95%CI: 0.35 – 0.61) times, respectively, compared with those in the lowest quartile. Furthermore, the results of the restricted cubic spline model showed that there was a non-linear dose-response relationship between physical activity level and risk of all-cause mortality among individuals. This relationship followed an L-shaped curve, indicating that the risk of all-cause mortality gradually decreased with increasing levels of physical activity. However, after a certain threshold of physical activity (16 000 METs-min/week), the risk of all-cause mortality no longer decreased significantly with increasing physical activity. In addition, the mediation analysis suggested that BMI and CRP might play a mediating role in the association between physical activity and risk of all-cause mortality, with the percentage of mediation effects among individuals in the highest quartile of physical activity being 37.22% and 39.60%, respectively.
    Conclusion Increasing physical activity levels may reduce the risk of all-cause mortality among middle-aged and older adults in China, and appropriate physical activity may provide greater health benefits for this population. Reduced BMI and inflammatory responses in the body may be potential mechanisms for the association between physical activity levels and risk of all-cause mortality.

     

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