目的:验证人类年龄,一种新的生物年龄指标(BA),用于预测全因死亡率和年龄相关结局,并使用多国纵向队列描述特定人群的衰老模式。
方法:我们分析了来自全球老龄化门户的协调跨国数据,包括来自美国的研究,英格兰,墨西哥,哥斯达黎加,和中国。我们使用体重指数和腰围与身高的比率来估计50-90岁参与者的人类年龄和AnthometerAgeAccel作为BA和年龄加速度的代表,分别。我们使用Cox模型比较了人类年龄和实际年龄(CA)的全因死亡率的预测能力,描述了所有国家的老龄化趋势,并探讨了使用广义估计方程(GEE)对AnthomerAgeAccel进行纵向评估以预测新发功能下降和与年龄有关的疾病的实用性。
结果:使用来自55,628名参与者的数据,我们发现,在预测死亡率方面,与合并症无关,人类年龄(c统计0.772)优于CA(0.76),性别,种族/民族,教育,和生活方式;这一结果在除墨西哥以外的大多数国家都得到了复制。加速衰老的个体死亡风险高出39%,人类年龄也确定了每年生物衰老更快的趋势。在纵向分析中,较高的AnthroperAgeAccel值可独立预测自我报告的健康恶化和日常生活的基本/工具活动(ADL/IADL)的新发病缺陷,糖尿病,高血压,癌症,慢性肺病,心肌梗塞,和中风。
结论:人类年龄是与年龄相关结局相关的稳健且可重复的BA指标。它的实施可以促进不同人群生物衰老加速趋势的建模,尽管重新校准可能会增强其在代表性不足的人群中的效用,例如来自拉丁美洲的个人。
OBJECTIVE: To validate AnthropoAge, a new metric of biological age (BA), for prediction of all-cause mortality and age-related outcomes and characterize population-specific aging patterns using multinational longitudinal cohorts.
METHODS: We analyzed harmonized multinational data from the Gateway to Global Aging, including studies from the US, England, Mexico, Costa Rica, and China. We used body mass index and waist-to-height ratio to estimate AnthropoAge and AnthropoAgeAccel in participants aged 50-90 years old as proxies of BA and age acceleration, respectively. We compared the predictive capacity for all-cause mortality of AnthropoAge and chronological age (CA) using Cox models, described aging trends in all countries and explored the utility of longitudinal assessments of AnthropoAgeAccel to predict new-onset functional decline and age-related diseases using generalized estimating equations (GEE).
RESULTS: Using data from 55,628 participants, we found AnthropoAge (c-statistic 0.772) outperformed CA (0.76) for prediction of mortality independently of comorbidities, sex, race/ethnicity, education, and lifestyle; this result was replicated in most countries individually except for Mexico. Individuals with accelerated aging had a ~39% higher risk of death, and AnthropoAge also identified trends of faster biological aging per year. In longitudinal analyses, higher AnthropoAgeAccel values were independently predictive of self-reported health deterioration and new-onset deficits in basic/instrumental activities of daily living (ADL/IADL), diabetes, hypertension, cancer, chronic lung disease, myocardial infarction, and stroke.
CONCLUSIONS: AnthropoAge is a robust and reproducible BA metric associated with age-related outcomes. Its implementation could facilitate modeling trends of biological aging acceleration in different populations, although recalibration may enhance its utility in underrepresented populations such as individuals from Latin America.