An analysis of data from the China Health and Retirement Longitudinal Study (CHARLS) of people older than 45 reported that psychological factors such as being lonely or feeling unhappy add up to 1.65 years to one’s biological age. This effect was found to be stronger than those of biological sex, living area, marital status, and smoking status. The study was published in Aging.

Studies of biological aging indicate that people do not age at the same rate. A slower biological aging rate is associated with better health compared to peers with the same chronological age, age determined by one’s date of birth.

To study the pace of aging, scientists have been developing so-called “aging clocks” — mathematical models that allow the measurement of biological age. These clocks combine data on various health parameters and medical conditions to produce predictions of biological age. In recent times, scientists started developing aging clocks aided by AI algorithms and this technology shows promise in opening new venues in drug development.

Aside from diseases and medical conditions, studies using aging clocks have so far explored ways to influence biological aging through exercise, diet, and dietary supplements. There are also certain chemical compounds showing great promise in this area. In contrast, the impact of psychological factors on aging has not been studied much, in spite of there being several psychological theories claiming effects of various psychological factors on aging.

“Our company is studying the ways a regular consumer can slow down their pace of aging and delay the onset of aging-related diseases. But to find these ways you first need to quantify the aging rate on an individual level,” explained study author Fedor Galkin, the research director at Deep Longevity.

“We do that using a proprietary ‘aging clock’ technology that recognizes the footprints of aging in biological data, e.g. clinical blood tests. At some point, we discovered that one’s emotional state is a strong confounder in measuring the pace of aging and thus needs to be accounted for.”

“Thus, we started exploring more in the direction of mental aging. And now we are trying to build a unified model of body and soul that would help people not only physically rejuvenate, but also get the motivation to enjoy and remain productive throughout their increased lifespan.”

Galkin and his colleagues used their aging clock to examine data from CHARLS participants. CHARLS is a nationwide study of Chinese population older than 45 years of age that collects information on social and economic status of the respondents, their health history, biometrics and blood sample data.

It’s particular importance for China comes from the fact that, of East Asian countries, China has the lowest proportion of people over 65 years of age with no major disabilities and with normal cognitive functions – 15.7%. This starkly contrasts countries like Japan and South Korea where these percentages are 29.2% and 25.5%, respectively.

This particular study used data from 4451 CHARLS participants and it included responses to 8 markers of psychological state of the person, questions asking about how often the person is bothered by things, lacking focus, depressed, hopeful, fearful, prone to restless sleep, happy and lonely.

The aging clock the study authors constructed used a combination of 16 blood biomarkers, seven biometric parameters, and the biological sex of the person to create a deep neural network that predicts biological age. The pieces of data this aging clock relies most on are systolic and diastolic blood pressure, cystatin C (a biomarker of kidney function), body mass index, and spirometry results.

Results showed that the age clock is accurate down to 5-6 years (mean absolute error was 5.68 years) and that it correctly classifies persons with aging-associated diseases as older than healthy people of the same chronological age.

When associations between aging clock predictions of age, social, and psychological factors were examined, results showed that the aging clock classified people who smoke and those suffering from restless sleep as older (1.25 years for smoking, .44 for restless sleep) and those that were currently married as a bit younger (-.59 years). “However, if the eight psychological variables are considered as a scale representing psychological well-being, being on its lower end has an effect of accelerating aging by 1.65 years,” the researchers wrote.

The findings indicate that “one’s mental health is an essential part of longevity,” Galkin told PsyPost. “If you do not take care of your psychological comfort, you are cutting away from your lifespan just as much or even more if you took up smoking.”

He added that “our study can be seen as a verification of an ancient adage in reverse: ‘Corpore sano in mens sana.‘ We’ve just been able to put this in concrete mathematical terms within the context of aging. There is no big surprise.”

“The surprising parts will probably come when we start integrating the findings of this study with our recently published AI recommendation engine that can direct people toward higher mental well-being with simple exercises,” Galkin said. “The ultimate goal is to learn how to improve the physical health of a person via their psychology and scale it to a national or global level to push the human lifespan even further.”

The study highlights how psychological factors need to be studied in the context of aging. However, it should be noted that the design of the study does not allow for cause-and-effect conclusions.

“It was a cross-sectional study, and now, we are looking for a more controlled setting in which we will be able to check the shift in the physical pace of aging in response to a known set of psychological factors,” Galkin said. “This should also let us gain a better resolution on the aging-accelerating effects of certain attitudes or emotions and learn more about the cross-dependence of the factors we presented in this article.”

The paper, “Psychological factors substantially contribute to biological aging: evidence from the aging rate in Chinese older adults”, was authored by Fedor Galkin, Kirill Kochetov, Diana Koldasbayeva, Manuel Faria, Helene H. Fung, Amber X. Chen, and Alex Zhavoronkov.


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