Previously submitted to: JMIR Medical Informatics (no longer under consideration since May 21, 2026)
Date Submitted: May 11, 2026
Open Peer Review Period: May 21, 2026 - May 21, 2026
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Effect Size and Variance Interpretation in Epigenetic Studies of Women Reproductive History
ABSTRACT
Background:
Modern epigenetics increasingly employs biological clocks to quantify the impact of life choices on aging. Recent high-impact studies have claimed that childbearing significantly accelerates biological aging in women. This article critically re-examines these claims, challenging the growing trend of biological determinism imposed on reproductive choices through large-scale genomic datasets
Objective:
The goal of this study was to establish an upper-bound estimate for the actual predictive power of reproductive history on female lifespan and biological destiny. Based on a secondary analysis of current epigenetic findings, the study aims to quantify this contribution relative to the dominant influence of stochastic and genetic factors
Methods:
A rigorous secondary upper bounded analysis was performed on demographic and epigenetic data from recent influential research. The study utilizes Fisher’s Analysis of Variance (ANOVA) to partition variance and Cohen’s d to calculate standardized effect sizes. The goal was to quantify the actual predictive power of reproductive history on female lifespan and biological destiny compared to stochastic and genetic factors
Results:
The analysis reveals that a reported 1-year acceleration in biological aging, while statistically significant in large cohorts, possesses negligible explanatory power. When evaluated against the standard deviation of high-longevity populations (SD = 9.1 years), this 1-year shift accounts for only 1.2% of the variance in female lifespan, leaving 98.8% governed by stochastic noise and genetics. With a standardized effect size near zero (d = 0.11) and a survival distribution overlap of 95.6% between groups, the epigenetic signals attributed to childbearing are shown to be biologically and practically irrelevant for individual life expectancy
Conclusions:
Microscopic p-values in massive datasets may distort scientific reality and create unjustified societal anxiety. This work demonstrates that current epigenetic signals still do not provide a reliable basis for life-altering labels or reproductive penalties. The study calls for a return to scientific realism, distinguishing between molecular non sequiturs and tangible health outcomes, ultimately defending the stochastic freedom of human life Clinical Trial: Not Applicable
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