Zhang Liming, Yu Jiening, Jia Xueqing, Su Zichang, Hu Yingying, Zhang Jingyun, Yang Wei, Chen Xi, Hoogendijk Emiel O, Huang Huiqian, Liu Zuyun
Second Affiliated Hospital, School of Public Health, Zhejiang Key Laboratory of Intelligent Preventive Medicine, Zhejiang University School of Medicine, Hangzhou, China.
Zhejiang University School of Medicine, Hangzhou, China.
J Cachexia Sarcopenia Muscle. 2025 Jun;16(3):e13862. doi: 10.1002/jcsm.13862.
Ageing is a complex and multi-dimensional process that manifests heterogeneities across different organs/systems, individuals and countries. We aimed to delineate the life-course percentile curves and establish the normative values of multi-systemic (e.g., muscle-skeletal, brain, cardiovascular and pulmonary) ageing metrics for people under distinct sociodemographic contexts (i.e., sex, income and education).
Three national datasets, the UKB (the United Kingdom), the NHANES (the United States) and the CHARLS (China) were utilized for the analyses. We selected 14 ageing metrics (e.g., body mass index, grip strength, fat-free mass index, bone mineral content [BMC], bone mineral density [BMD], diastolic blood pressure, cognitive function and frailty index_Lab) that represent the functions of different organs/systems and plotted their sex-, educational- and income-specific percentile curves utilizing the GMALSS model. We also estimated the age-specific normative values for each ageing metric in distinct sociodemographic contexts.
The functions of all metrics, except for cognitive function, manifested a progressive decline or maintained stability after adulthood (20s), especially after middle age (40s-50s). The cognitive function showed an evident decline in old age (70s-75s) (e.g., in the CHARLS: the median [IQR] cognitive function scores were 11.6 [9.1, 13.8], 10.3 [7.5, 12.9], 8.3 [5.5, 11.0] at the ages of 60, 70 and 80 for males, respectively). In the stratified analyses, males and females manifested disparities in percentile curves of ageing metrics involving the muscle-skeletal and cardiovascular systems. For instance, BMC and BMD manifested an evident decline after middle age in females, whereas they showed a slow decline after adulthood in males. Notably, we observed substantial income and educational disparities in percentile curves of several ageing metrics within Chinese participants: the 'low-income' and 'low-education' subgroups manifested an evident decline in ageing metrics (e.g., grip strength and frailty index_Lab) representative of multiple systems. By contrast, these income or educational disparities were not observed in the British and American participants.
Our investigation delineated the potential heterogeneities and socioeconomic disparities in percentile curves of multi-systemic ageing metrics and provided their age-specific normative values tailored to different sexes and socioeconomic contexts based on three national datasets. This study may serve as a proof-of-concept for understanding the multi-dimensional signature of systemic ageing and calls for policies to promote health equity across nations when facing dramatic global ageing.
衰老 是一个复杂的多维度过程，在不同器官/系统、个体和国家中表现出异质性。我们旨在描绘生命历程百分位数曲线，并为处于不同社会人口背景（即性别、收入和教育程度）下的人群建立多系统（如肌肉骨骼、大脑、心血管和肺部）衰老指标的规范值。
分析使用了三个国家数据集，即英国生物银行（UKB）、美国国家健康与营养检查调查（NHANES）和中国健康与养老追踪调查（CHARLS）。我们选择了14个衰老指标（如体重指数、握力、去脂体重指数、骨矿物质含量[BMC]、骨矿物质密度[BMD]、舒张压、认知功能和衰弱指数_Lab），这些指标代表不同器官/系统的功能，并利用广义加性混合模型（GMALSS）绘制其按性别、教育程度和收入划分的百分位数曲线。我们还估计了不同社会人口背景下每个衰老指标的年龄特异性规范值。
除认知功能外，所有指标的功能在成年期（20多岁）后均呈逐渐下降或保持稳定，尤其是在中年期（40多岁至50多岁）之后。认知功能在老年期（70多岁至75岁）出现明显下降（例如，在CHARLS中：男性在60岁、70岁和80岁时的认知功能得分中位数[四分位间距]分别为11.6[9.1，13.8]、10.3[7.5，12.9]、8.3[5.5，11.0]）。在分层分析中，男性和女性在涉及肌肉骨骼和心血管系统的衰老指标百分位数曲线上表现出差异。例如，BMC和BMD在中年后女性中明显下降，而在成年后男性中下降缓慢。值得注意的是，我们在中国参与者的几个衰老指标百分位数曲线中观察到了显著的收入和教育差异：“低收入”和“低教育”亚组在代表多个系统的衰老指标（如握力和衰弱指数_Lab）上明显下降。相比之下，在英国和美国参与者中未观察到这些收入或教育差异。
我们的研究描绘了多系统衰老指标百分位数曲线中的潜在异质性和社会经济差异，并基于三个国家数据集提供了针对不同性别和社会经济背景的年龄特异性规范值。这项研究可作为理解系统衰老多维特征的概念验证，并呼吁在面对全球急剧老龄化时制定促进各国健康公平的政策。
