寿命学概述（四）

(四)寿命评估1寿命学发展的瓶颈寿命评估就是用特异的生物学指标测定生命质量,推算机体的生物学年龄,是衰老的生物学鉴定或衰老生物指标测定的延伸与发展。 人口老龄化推动了老年学中的衰老生物学的发展,形成了日益深化和扩大的衰老与抗衰老研究领域,应运而生的衰老生物学是时代的产物。衰老的检测与量化评估一直是衰老研究中被关注的焦点,最经典的方法是用寿命评估衰老;     

一种人体衰老生物学标志的"可干预性"分析

衰老生物学标志是根据日历年龄来测定一定功能年龄的手段,是确定衰老速度的方法,是延缓衰老药物疗效的标准,是论证健在型衰老的依据[1]。增龄变化、多元组合以及流行病学意义并不能说明指标系作为衰老生物标志的成立,它还必须具有可变性。1　材料与方法1.1　受试者自愿受?..     

铝作业工人生物学年龄的评估

目的：为评估职业性铝接触对作业人群衰老过程的影响，寻找反映机体衰老的敏感生物学指标。方法：选择１０５名年龄２５～６０岁的铝作业工人为研究对象，以舒张压、收缩压、肺活量、Ｇｕｎｔｈｅｒ指数、手握力、视简单反应时、数字译码、视觉记忆、血清胆固醇和血糖作为评价生物学年龄的指标。结果：铝作业工人的生物学年龄明显高于其时序年龄，平均高３．６岁。结论：提示职业性铝接触可以加速机体正常的衰老进程     

生物学年龄及其影响因素研究进展

衰老与人体功能损伤、多种重大慢性疾病和死亡风险密切相关。在不同个体中,衰老的速率并不一致。生物学年龄是根据机体的生物学数据计算出来的一种年龄指标,相比于实足年龄,更能反映机体的衰老状态。近年来,越来越多的流行病学研究对其与各种健康相关结局的相关性进行了探究和验证。本研究对生物学年龄相关指标和预测模型及其影响因素的研究进展进行综述。     

寿命学概述(四)

(四)寿命评估 1 寿命学发展的瓶颈 寿命评估就是用特异的生物学指标测定生命质量,推算机体的生物学年龄,是衰老的生物学鉴定或衰老生物指标测定的延伸与发展.     

逆转炎症年龄,抗御免疫衰老

国际学术期刊《自然-衰老》发表的斯坦福医学院、巴克老龄化研究所等团队联合完成的研究成果指出,免疫系统衰老是衰老的一个主要标志,它与年龄和非传染性疾病的很多方面息息相关。他们还研究出了一个检测系统性慢性炎症的可靠指标,可量化读取免疫系统的年龄,并确定其与衰老及健康之间的关系。     

生物学年龄评价方法进展

利用生物学年龄衡量个体的衰老进程,可以弥补实足年龄难以解释同龄个体间健康水平差异的缺陷。近年来,涌现出多种基于临床或表型、分子生物学指标或复合型指标的生物学年龄测量方法。本文对一些常见的生物学年龄评价指标进行概述,并比较这些评价指标的效度。     

算算自己的生理学年龄

生理学年龄,也叫生物学年龄,或简称为生理年龄。它是根据正常人个体生理学和解剖学上发育状态推算出来的年龄,用以表示人体组织结构和生理功能的实际衰老程度。在曰常生活中,人们可以经常看到,有的人虽已七八十岁,但仍耳聪目明,行动灵活,思维敏捷,好像只有四五十岁;而有的人虽然只有三四十岁,却已满面皱纹,头发稀疏,弓腰驼背,犹如六七十岁,一副未老先衰的模样。而这种差异是时序年龄所不能表达的。 生理年龄试图客观地反映人在生理学上的个体差异,但是如何“量化”却仍待解决。有人根据影响     

人体衰老与延缓衰老研究进展--人体老化的特征和表现

本文介绍衰老生物学的基本理论和人体衰老研究的新进展,也涉及长寿研究的现状以及延缓衰老的理论依据和抗衰老途径.衰老生物学(biology of senescence)或老化生物学(biology of aging)是研究生物衰老现象、过程与规律的科学.其任务是揭示衰老现象的特征,在不同水平(分子、细胞、组织、器官及整体水平)上的衰老变化,探讨导致衰老变化的原因和机制,以寻求延缓衰老的途径和方法.根本目的在于认识衰老的本质,增强老年健康意识,延长人的寿命,提高老年人的生命质量.     

年老并不意味衰老

年龄增长并不意味着衰老,甚至有可能出现这样的情况:年龄上变老,这用生物学的观点看,是一种可度量的生物现象.人们有可能减缓衰老,某些情况下还可逆转衰老的进程. 60岁可以比20岁更健康 我们希望活到100岁时还能享有最佳的健康状况,然后寿终正寝——这并非不可实现的奢望.但是为了实现这个愿望,我们必须为之付出努力.     

Early vascular aging (EVA): consequences and prevention

It has often been recognized that a discrepancy exists during the clinical consultation between the chronological age of a patient on the one hand with the signs and symptoms of biological age that can be recorded on the other hand. In cardiovascular medicine this is obvious when a heavy smoker presents with features of early biological aging, for example skin appearance and impaired lung function. This could also be extrapolated to vascular function as the target for numerous cardiovascular risk factors, thereby increasing the risk of early cardiovascular disease (CVD). Both new and old treatment modalities can play a role for the prevention of early vascular aging, first of all smoking cessation and improved lifestyle in general, but later on also the use of drugs such as statins or agents that block the renin-angiotensin system (RAS). New classes of drugs are currently being tested for CVD prevention, including glitazones and rimonabant, even if adverse effects (heart failure and depression) might restrict their usefulness. Results from ongoing intervention studies will eventually cast new light on possibilities to prevent the development of vascular aging.     

From quantified to qualculated age: the health pragmatics of biological age measurement

There is growing interest, within the social sciences, in understanding self-quantification and how it affects health practices in contemporary society. There is, however, less research on how ageing and health measurement relate, even though this relationship has become more pertinent with the growing availability of services and devices offering biological, personalised age measurements, from simple online questionnaires to telomere length quantification. Little is known about who uses these devices, why they use them and the socio-technical implications of such uses. To explore these issues, we conducted semi-structured interviews and focus groups with users of measurements of biological age (BA) in Denmark. We found that participants engage with the measurements with a degree of scepticism regarding their technical validity, reliability and sensitivity. Rather than seeking an exact biological quantification, participants use measurements as a pragmatic, rough indication of individual health. We develop a conceptual model to understand participants’ engagement with BA measurements, which suggests that, instead of a substitution of chronological age for BA, users gauge the difference between the two to qualify their present and future individual trajectory in a lay model of the relationship between functional capacity and age.     

Dietary Polyphenol Intake Is Associated with Biological Aging,a Novel Predictor of Cardiovascular Disease: Cross-Sectional Findings from the Moli-Sani Study

Biological aging, or the discrepancy between biological and chronological age of a subject (Δage), has been associated with a polyphenol-rich Mediterranean diet and represents a new, robust indicator of cardiovascular disease risk. We aimed to disentangle the relationship of dietary polyphenols and total antioxidant capacity with Δage in a cohort of Italians. A cross-sectional analysis was performed on a sub-cohort of 4592 subjects (aged ≥ 35 y; 51.8% women) from the Moli-sani Study (2005–2010). Food intake was recorded by a 188-item food-frequency questionnaire. The polyphenol antioxidant content (PAC)-score was constructed to assess the total dietary content of polyphenols. Total antioxidant capacity was measured in foods by these assays: trolox equivalent antioxidant capacity (TEAC), total radical-trapping antioxidant parameter (TRAP) and ferric reducing-antioxidant power (FRAP). A deep neural network, based on 36 circulating biomarkers, was used to compute biological age and the resulting Δage, which was tested as outcome in multivariable-adjusted linear regressions. Δage was inversely associated with the PAC-score (β = −0.31; 95%CI −0.39, −0.24) but not with total antioxidant capacity of the diet. A diet rich in polyphenols, by positively contributing to deceleration of the biological aging process, may exert beneficial effects on the long-term risk of cardiovascular disease and possibly of bone health.     

An empirical examination of subjective age in older adults

ABSTRACT

It has been observed that subjective age (SA) often trails chronological age, especially in older adults. In a previously published article, we argued that differences in individual’s SA is a function of their level of activity on biological, mental, and social dimensions. This article empirically tests this proposition using a newly created Subjective Aging Index (SAI). The SAI is related to SA above the effect of age with differences existing across age groups and sex. The findings contribute to the literature on successful aging strategies with important implications for health care practitioners, marketers, and individuals heading towards older adult years.     

Determination of the rate of biological aging in vibration disease

Examining 80 males with vibration disease has shown a significant increase in their biological age (particularly in patients with vibration disease due to exposure to second-degree general vibration) as compared with that in the control group, which is indicative of the role of these factors in the acceleration of the body's aging processes.     

The molecular biology of aging--therapeutic interventions?

Aging is a complex mechanism of progressive and irreversible processes occurring to molecules, to cells and to the whole organism and ending with death. Genetic - so called "programmed" - factors and the combination of environmental interactions play the most important role in its development. Changes in macromolecules caused by free radicals, non-enzymatic glycosylation and apoptosis have a special role in the pathomechanism of aging. Endocrine and immune systems have also an important influence and control on the process. Those environmental effects, as for example irradiation, toxic chemicals, metal ions, free radicals play a determinant role in the development of aging. Diseases of old age should be distinguished from aging per se, although changes in old age increase the frequency of diseases. Those aging changes, which are associated with a generalized increase in mortality (but not with specific disease) would qualify as biomarkers of aging and would distinguish biological age from chronological age (passage of time). Because of increased average lifetime of people in the "western world", basic and clinical research in connection with aging and geriatrics has special importance in medicine. Better understanding of molecular and cellular mechanisms of aging could improve not only medical care of the elderly but could hold out also some hope in finding feasible solutions to slow down the aging process as well.     

Is this environment making you older? Molecular biomarkers and new approaches to investigate the influences of environmental chemicals through aging

Aging is characterized by a gradual and progressive decline in system integrity that occurs with advancing chronological age. Although it is a physiological process, aging is associated with a myriad of age-related diseases (ARDs), including frailty, sarcopenia, chronic obstructive pulmonary disease, cardiovascular disease, cancer, and neurodegenerative diseases. While not exclusively ARDs, many of these diseases lead to death, a lesser quality of life, and increased healthcare costs for individuals and systems. ARDs share several underlying molecular mechanisms, such as cellular damage, inflammation, DNA methylation changes, stem cells exhaustion, and DNA mutations, which have been outlined as hallmarks of aging. Evidence suggests that environmental exposures, including but not limited to metals, air pollution, endocrine-disrupting chemicals, and noise, may accelerate biological aging. Over the past few years, aging research has identified new molecular biomarkers of the aging process. When applied to investigate environmental influences, these biomarkers can help identify individuals who are particularly susceptible to the influences of environmental exposures on aging processes and therefore guide in implementing possible preventive measures.     

Biological function,activity and dependency among elderly Sherpa in the Nepal Himalayas

This paper considers a model contrasting the aging experience of Western and non-Western populations through consideration of the hypothesized interrelationships among four factors (biological change with age, dependency, family structure and the aging experience) in a non-Western setting. Western views of the contrast in the aging process in Western industrial and traditional pre-industrial societies include the notion that traditional societies manifest relatively slow rates of biological aging, and have extended family structures which accommodate the elderly resulting in few aging problems. On the basis of data deriving from a case study of Sherpas in Helambu, Nepal, the model appears to be an oversimplification and suggestions for revision are offered.     

Time Benders: A Model of Subjective Aging in Aging Adults

This article develops a new model for understanding the aging experience. Drawing upon aging literature from the chronological, biological, mental, and social aging perspectives, the model offered is an integrated perspective that provides better understanding of the relationship between chronological age and an individual's perceived age. The article provides evidence of ways that consumers are trying to “time bend” and change today's perceived reality of aging. The article concludes with a discussion of implications for the health care industry and provides examples of how some businesses seem to already be looking at aging and health related issues through this lens.     

基于机器学习的宁夏地区老年人生物学年龄研究

目的 生物学年龄(Biological age, BA)可以更有效的判断个体真正的衰老状态，精准预测BA有助于为老年个体早期制定有针对性的预防措施，目前关于老年人分亚群对生物学年龄与生化指标相关性研究较少。利用机器学习算法计算宁夏地区老年人的生物学年龄，并识别相关生物化学指标分亚群进行分析。方法 纳入2020年宁夏地区老年人健康体检者共4 060名作为研究对象，采集空腹静脉血、尿液检测生物化学指标，利用随机森林(Random Forest, RF)算法筛选与BA相关的生物学指标，计算生物学年龄，并对RF算法的预测精度进行评估。结果 在老年人的不同亚群(低龄、中龄、高龄)中，各年龄段生物学指标在生物学年龄的重要性各有不。研究采用平均绝对误差(Mean Absolute Error,MAE)、均方根误差(Root Mean Square Error,RMSE)、相关系数(Coefficient of association,R²)进行模型的效能评估。结论 利用随机森林计算老年人生物学年龄并分析相关指标，可以更加精准定位老年人中高危人群及对健康老龄化有一定的指导。