Evidence map›Paper›PMID 36170009›Full record

ArticleAging2022

Psychological factors substantially contribute to biological aging: evidence from the aging rate in Chinese older adults.

Fedor Galkin, Kirill Kochetov, Diana Koldasbayeva, Manuel Faria, Helene H Fung, Amber X Chen, Alex Zhavoronkov

Abstract read
In one paragraph

Article in Aging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed.

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  10. Impact of early-life food deprivation on health-related quality of life among older people in China: evidence from CHARLS.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025
    Article
  11. Article
  12. Review
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  15. Article
  16. Promising benefits of six-monthFrontiers in aging · 2025
    Article
  17. Article
  18. Article
  19. Review
  20. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Fedor GalkinDeep Longevity Limited, Hong Kong, People's Republic of China.
Kirill KochetovDeep Longevity Limited, Hong Kong, People's Republic of China.
Diana KoldasbayevaDeep Longevity Limited, Hong Kong, People's Republic of China.
Manuel FariaDepartment of Psychology, Stanford University, Stanford, CA 94305, USA.
Helene H FungDepartment of Psychology, The Chinese University of Hong Kong, Hong Kong, People's Republic of China.
Amber X ChenDepartment of Psychology, The Chinese University of Hong Kong, Hong Kong, People's Republic of China.
Alex ZhavoronkovDeep Longevity Limited, Hong Kong, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We have developed a deep learning aging clock using blood test data from the China Health and Retirement Longitudinal Study, which has a mean absolute error of 5.68 years. We used the aging clock to demonstrate the connection between the physical and psychological aspects of aging. The clock detects accelerated aging in people with heart, liver, and lung conditions. We demonstrate that psychological factors, such as feeling unhappy or being lonely, add up to 1.65 years to one's biological age, and the aggregate effect exceeds the effects of biological sex, living area, marital status, and smoking status. We conclude that the psychological component should not be ignored in aging studies due to its significant impact on biological age.

Indexed as

AgingRetirementAgedChinaHumansLongitudinal StudiesMarital Statusaging clockslifespan psychologylongevitypsychological aging

Identifiers

PMID36170009
PMCPMC9550255

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.