“Aging is not lost youth but a new stage of opportunity and strength.” (Betty Friedan)
In the previous article, I introduced this health longevity series discussing the well-known and debated topic concerning the “underpopulation threat,” in which the global population growth is estimated to peak by9.73 billion by 2064, followed by a sharp decline to 8.79 billion by 2100. Besides female emancipation, the covid-10 pandemic, or the socio-economic instabilities, the overall decreased fertility rate will profoundly impact shifting the demographic toward the aging population. Thus, an effect on the economy, politics, and healthcare needs should be considered. However, transforming the concept of aging from being a disease into an opportunity to increase a healthy lifespan is the way to cope with this unavoidable event.
Hence, in this article, I will describe aging and how it differs from longevity. Moreover, factors implicated in longevity will also be reported, and recently developed methods concerning how to measure health longevity.
What is aging?
Aging has been defined as the progressive, event-dependent decline in maintaining biochemical and physiological functions. Indeed, this process is characterized by the progressive accumulation of damage at the molecular and cellular level, disrupting tissues and organs. However, this structural and physical damage is also accompanied by functional deterioration, causing cognitive dysfunctions and decreased capabilities. Aging is also one of the main risk factors leading to disease development (e.g., dementia, cancer, diabetes, cardiovascular disorders) and death [1]. Even though this process is an unavoidable life event, its path is neither linear nor consistent and sometimes not associated with an individual’s biological age. Thus, the possibility to distinguish a healthy path from a pathological path is relevant concerning an individual’s wellbeing. Although the focus is usually on extending lifespan (i.e., the number of years that a person or animal can live), it would be more worth focusing on increasing a healthy lifespan instead (i.e., the number of years that a person can live in good health). Indeed, several factors may influence the development of a healthy pattern such as physical and social context (e.g., community, neighborhoods, home, and physical exercise), as well as genetic, personal, and social characteristics (e.g., sex, ethnicity, and socioeconomic status) [1].
Nevertheless, defining health longevity is quite complex, and science has already tried to detect specific biomarkers able to quantify the healthspan. However, the variety of markers that were found, such as metabolites (e.g., fasting glucose, cholesterol, other inflammatory signals), or related to physiological health (e.g., cognitive functions, cardiovascular activity, vision, and auditory functions), raised the need of determining a universal measure of healthspan that can differentiate biological from chronological aging.
What is longevity?
The term “longevity” origins from the Latin word “longaevitās,” and this term is a combination of two words longus (= long) and aevum (= age), which combined give rise to the meaning of having a “long life” when compared to the average person lifespan, and under “ideal” conditions. Indeed, longevity is simply the length of a lifespan.
The last century saw an increased lifespan due to advances in medicine, technologies, socio-economic and demographic changes, lifestyles, but mostly the great reduction of infectious diseases. Indeed, whether the average person born in 1900 would have had a lifespan of 50 years, today’s life expectancy is much longer. Life expectancy is about 81 years for women and 76 for men in the USA. Based on a statistic in 2019, women tend to live 5.5 years longer than men in EU countries, with a similar pattern across countries. However, the gap between genders tends to decrease when considering health longevity, particularly after the age of 65. Indeed, women showed again to have a healthier and longer life (years free from disabilities), although this factor also depends on the country of residence. In Germany, women aged 65 would expect to live 1.3 years longer and healthier than men. However, in the Netherlands, men are shown to live 0.6 years longer and free from disability than women, and 1.0 years compared to Cyprus and Portugal.
What characterizes and determines longevity?
A few factors would be considered when thinking of increasing life span, and these factors begin from our behavior, attitudes, nutrition, habits, genetics, and environment.
Here are a few suggestions that have been proposed to promote longevity:
Exercise regularly: it can positively affect our DNA by reversing our biological clock;
Eat fruits and vegetables: a diet based on vegetables and fruits consumption can increase lifespan, although disagreement concerns which is the best diet for longer life;
Intermittent fasting or fasting: since the 1930s, studies demonstrated that food restrictions have proved to extend life in mice and other species;
Restricted diet (caloric deficit): a study published in 2018 in Cell Metabolisms demonstrated that when compared to a control group, a group that underwent a caloric deficit (by 15%) over two years did show lower oxidative stress;
Enough time to sleep: from 7 to 9 hours are beneficial for longer life;
Stress management: is fundamental because stress can negatively affect our body and mind leading to unhealthy behaviors and habits (e.g., overeating, smoking, drinking);
No smoke or alcohol consumption;
Relationships: spending time with beloved people helps in reducing risky behaviors, thus also reducing mortality rates.
Nevertheless, a strong focus has been made on genetics and nutrition to promote longevity and health. Indeed, longevity responds to decreased mortality rates among the older ages, particularly in those developed countries. Indeed, from the last 50 years of the past century, the mortality rate of women over the age of 80 years decreased by 50%. A few factors have been identified responsible for increasing lifespan, such as better hygiene conditions, social welfare, advances in medicine, and healthcare services. However, an improved social and economic environment also affected changing diet habits. A study based on laboratory animals [2] from Gertrude H. Sergievsky Center, the Taub Institute on Alzheimer’s Disease and the Aging Brain, at the Columbia University Medical Center (NY) found that diet restriction, particularly caloric deficit by the consumption of antioxidants, as well as genetic variations, can positively impact longevity. Even though these promising findings, still doubtful, the processes behind this outcome and their effect on humans. In addition, as described by Singh and Watson (2014) [3], it was found that a few behaviors as smoking cessation, caloric deficit, genetics, and environmental variables can influence longevity and omega-3 fatty acids. Thus, increasing the consumption of fish oil while reducing dysfunctional lifestyle behaviors was found to correlate with increased lifespan. Building healthy behaviors can even reduce developing cancer and cardiovascular disease.
How does aging differ from longevity?
As previously discussed, living longer and free of age-related diseases differs from just increasing years to life. While life expectancy increased over centuries, the older populations have had more years of life affected by chronic diseases. With rapid advances in sequencing technologies and analytical algorithms, it is now possible to distinguish between aging and longevity processes. Thus, investing more resources in increasing healthspan is necessary to promote healthy aging.
Given the definitions of aging, lifespan, healthspan, and longevity, the concepts should be considered interconnected. Accordingly, aging can hardly be differentiated from longevity because the rate of aging can influence lifespan, although researchers debate on the fact that lifespan and longevity are two processes that occur independently of aging and healthspan [4]. So, which mechanisms drive aging and longevity? Whether longevity is determined by our evolution where those genes with greater reproductive advantage have been selected, longevity would be the product of a genetic process, optimized, evolved, and selected throughout the years to guarantee the next generation. On the opposite, aging is a process characterized by damage and repair, in which environmental and genetic variabilities play a significant role, and where the activity of repairing forces would determine the impact of damage. Indeed, a lack of damage repair would lead to cell death, inflammatory processes, and age-related diseases [4].
Nevertheless, is there a limit when it’s about longevity? Longevity is one of the most significant achievements in human history. However, although a few argue that human longevity will tend to increase over the coming years, others debate that there are biological limits, and we are already close to it. A study by Olshansky and Carnes (2019) [5] did show that although the rate of life expectancy dramatically improved from 1990, this rate was gradually reduced over the years. Indeed, whether this rate was 0.142 from 1990 to 2000 with a life expectancy of 75.4 years, from 2010 and 2016, it was just 0.017 and with a life expectancy of 78.91.
Whether the future of technologies would give us more insight into DNA sequencing and gene regulation to detect individual differences in genetic variations, the possibility to gain information concerning aging will allow the identification of those mechanisms responsible for slowing this process while promoting healthy longevity [4].
Aging and the biological clock
Having seen how the aging rate is highly individual, and thus differing among people, in contrast to the view that aging is a disease, the hope that this process can be delayed or even reversed is becoming the goal of science.
The investigation of aging brought to the establishment of four methods proposed to ”diagnose” the age:
● Transcriptomics
● Metabolomics
● Proteomics
● Epigenomics
Transcriptomics
It examines the part of DNA that would be translated into RNA, and eventually protein. With this method, the idea was to use part of the genome to identify the biological age. Indeed, “transcripts” of the DNA were used to classify younger from older individuals and in which several markers (e.g., blood urea, albumin, or IL-6) were indicators of the age difference between the two aging groups. Nevertheless, other markers did not show strong correlations, thus misleading these findings [6].
Metabolomics
It aims to profile small molecules (or metabolites) to give an accurate and complete overview of the biological process. Indeed, they represent the intermediate and final stage of metabolisms in organs and tissues. A few examples of age-related biomarkers were the tripeptide CGT, associated with dysfunctional lung functioning and mineral density of bone hips, or urine samples related to kidney functions and hyperglycemia. However, due to the difficulty in differentiating metabolic diseases from aging and the reduced number of comparable and reproducible findings, even this method showed limitations [6].
Proteomics
It measures proteins in the blood. Hence, proteins circulate in the blood for different periods depending on their function. They tend to undergo chemical changes (i.e., glycosylation) that respond to inflammatory processes and increase with aging. In this regard, a proteomics study from the Stanford School of Medicine, involving massive participation of individuals between 18 and 95 years old, demonstrated that a biological clock exists and that can be used to predict the chronological age based on the collected blood samples. Moreover, this proteomic clock was able to predict the age of a new sample of individuals based on a few protein information. In addition, while proteins tend to change with gender, the clock could even predict differences in age based on sexes. Hence, these findings would stimulate the possibility of creating proteomic clocks to define the biological age, thus implemented in personalized medicine [6].
Epigenomics
It is the latest discovery in the context of DNA methylation. Hence, aging is influenced by this process in which methyl groups build on DNA molecules due to environmental, natural, and stress-related events. Thus, DNA methylation is a great biomarker to measure epigenetic biological age. One example is the first finding by Steve Horvath. He forged the name “Horvath Clock”; a clock able to predict with high accuracy several causes of mortality and independently of major risk factors (e.g., a 6% increased risk of developing cancer over the years was related to a one-year increase in the epigenetic clock, and 17% increased risk of dying from cancer in five years). Besides, the Horvath clock was found to establish high correlations between age and the development of age-related diseases (e.g., the acceleration of this epigenetic clock was found to correlate with increased structural and functional changes occurring with Alzheimer’s disease). Lastly, epigenomics has also demonstrated how treatments and behaviors can influence the epigenetic age, and how these habits and treatments might reverse and delay the process of aging; a great hope when it is about promoting health longevity [6].
Women’s health and reproductive longevity
A relevant field of research, although mostly underestimated, regards women’s reproductive longevity. Indeed, ovaries reflect the process of aging in humans, able to detect signs of decline decades before other tissues. Thus understanding the ovarian aging process would offer insights into how humans age, particularly about women’s health, reproduction, and their impact on lifespan [7].
Although the new generations are expected to live even beyond 100 years, females spend more than half of this lifespan after menopause. However, it is well known how menopause negatively affects health affecting bone density, cognition, cardiovascular, and immune system functionality. Nevertheless, the biggest concern is that reproductive longevity is closely related to mortality risk. This process accompanies women across their life, influencing their career, family, and well-being. Indeed, most of the time, women’s choices depend on reproduction, and this biological clock greatly differs from men.
Furthermore, social and economic circumstances also impacted most developed countries. Whether before the 60s, women gave birth already at the age of 21, nowadays women have their first child after the age of 30. For this reason, the importance of recognizing the link between women’s reproductive clock and lifespan and how this relationship would help gain insight into the aging process should not be underestimated. Indeed, reproductive longevity might be another promising field of research to understand how to tackle aging and how to delay its progression, while improving women’s health and life quality [7].
Can health longevity be measured?
Having seen that an epigenetic clock was found to predict biological age and the development of age-related diseases while paving the way toward innovative treatments [6], can health longevity be measured?
Indeed, in aging individuals health longevity is a measure of life quality, and it reflects the relationship between age and the status of health. Moreover, health longevity refers to the transition between stages of health across ages. Because this transition might be influenced by a variability of factors (e.g., lifestyle, women’s reproductive cycle, socio-economic status, health service accessibility, genetics, environment), this concept can have different definitions. Thus, investigating those variances and components influencing this measure would be the key to identifying novel treatments and healthcare services. Nevertheless, most studies were based on incidence-based (cf. prevalence-based models that rely on age-specific prevalences) models estimating health longevity by giving a measure of mean “health expectancy,” ignoring those variances influencing these stage transitions.
Hence, the study of Caswell and van Daalen (2021) [8] proposed a comprehensive theory and methodology to measure health longevity. The proposed method was aimed to be flexible, efficient, and without any simulation requirement. In addition, this method can compute the mean, variance, skewness, and higher moments of health years as a measure of variation across individuals. Indeed, this method was proposed to investigate those variabilities influencing the transitions between age and health stages, and proposed to address a few questions [8]:
How to measure the life spent at each health stage for a specific range of ages?
How to define and measure the value (e.g., medical costs, life quality, workforces) of longevity at each health stage?
How often do the transitions between ages and health status occur (at the individual level)?
How to define and measure the value (e.g., stress-related factors, socio-economic status, healthcare services) of these transitions?
Furthermore, a multi-state Markov model was developed to measure each moment of health longevity and where individuals were classified based on their age and health status. This model was built based on a simple algorithm to create a multi-state matrix including occupancy, transitions, or values associated with either occupancy or transitions. Results showed how this model can measure all moments of health longevity while analyzing any number of health stages, variances in transitions, or any type of value related to each stage. Thus, the proposed model becomes an effective solution in contrast to inhomogeneity issues brought by previous models [8].
Gaining health to your years: science tells you how to live longer and healthier
A novel branch of medicine, called “longevity medicine” will be discussed in the next article. I will also discuss how this field is evolving toward the investigation of health longevity based on advanced methods to detect early signs of age-related (communicable or non-communicable) disease development through advanced medical technologies. Moreover, the latest scientific findings will present a focus on variables, behaviors, and habits needed to increase healthy longevity will be presented about the latest scientific findings. Lastly, tips from Peter Diamandis to develop a longevity mindset are discussed to evolve a positive and proactive mindset.
“Age is inevitable. Aging isn't.” (Marv Levy)
References:
World Health Organization, WHO (2018). Aging and health. Available at: https://www.who.int/news-room/fact-sheets/detail/ageing-and-health [Accessed July 09, 2021].
Yian Gu, Nicole Schupf, Richard Mayeux, Chapter 46 - Genetic and Dietary Influences on Lifespan, Editor(s): Roger N. Rosenberg, Juan M. Pascual, Rosenberg's Molecular and Genetic Basis of Neurological and Psychiatric Disease (Fifth Edition), Academic Press, 2015, Pages 509-520, ISBN 9780124105294, https://doi.org/10.1016/B978-0-12-410529-4.00046-2.
Vijay Karam Singh, Ronald Ross Watson, Chapter 1 - Enhanced Longevity and Role of Omega-3 Fatty Acids, Editor(s): Ronald Ross Watson, Fabien De Meester, Omega-3 Fatty Acids in Brain and Neurological Health, Academic Press, 2014, Pages 1-7, ISBN 9780124105270, https://doi.org/10.1016/B978-0-12-410527-0.00001-6.
Grinstein, J. D. (2021). What’s the Difference Between Aging and Longevity? NMN.com. Available at: https://www.nmn.com/news/difference-between-aging-longevity [Accessed on December 27, 2021]
Olshansky SJ, Carnes BA. Inconvenient Truths About Human Longevity. J Gerontol A Biol Sci Med Sci. 2019 Nov 13;74(Suppl_1):S7-S12. DOI: 10.1093/gerona/glz098. PMID: 31001621.
Diamandis, P.H. (2021). What is Your True Biological Age? Available at: https://www.diamandis.com/blog/what-is-your-true-biological-age [Accessed on December 27, 2021]
Diamandis, P.H. (2021). Reproductive Longevity & Your Lifespan. Available at: https://www.diamandis.com/blog/reproductive-longevity [Accessed on December 27, 2021]
Caswell, H. and van Daalen, S. (2021). Healthy longevity from incidence-based models: More kinds of health than stars in the sky. Demographic Research, 45, 13, 397-452. DOI: 10.4054/DemRes.2021.45.13
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