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The association between early life circumstances and multi-system biological aging: A systematic review and
Zhuoqi Luo1, Haiyan Ren1, Wali Lukman Ahmed1
1School of Nursing, Xuzhou Medical University, Jiangsu, China.
Objective:
To systematically investigate the relationship between early life circumstances and multi-system biological aging and to synthesize evidence on mediating and moderating factors.
Methods:
Studies from PubMed, EMBASE, Web of Science, Scopus, PsycInfo, CNKI, and SinoMed were searched from inception to February 2025. We included observational studies examining the relationship between early life circumstances (including adverse childhood experiences, childhood socio-economic status, perinatal factors, and childhood personal traits) and multi-system biological aging (composite algorithms based on multi-system clinical biomarkers, such as phenotypic age, Klemera-Doubal method biological age, homeostatic dysregulation, and Pace of Aging). A multi-level random-effects meta-analysis was employed for data synthesis. Sensitivity, moderator, and subgroup analyses were conducted to explore sources of heterogeneity and test robustness.
Results:
A total of 23 studies containing 344,852 participants were included. 16 of these were included in a meta-analysis, which showed a statistically significant correlation between early life circumstances and multi-system biological aging (Cohen's d = 0.18, 95 %CI: 0.12-0.24, p < 0.0001). Moderator analysis and subgroup analysis indicated that the type, period, and assessment method of early life circumstances, the multi-system biological aging indicators, age, geographic location, study quality, and covariate adjustment significantly influenced the association. The neighbourhood and living environment was a mediator, while age and sex served as moderators. Socioeconomic status, psychosocial factors, and healthy lifestyles exhibited both mediating and moderating effects.
Conclusions:
Adverse early life circumstances are associated with accelerated multi-system biological aging. These findings provide a foundation for identifying at-risk populations and formulating targeted interventions to decelerate biological aging.
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