Early-Life Intelligence Predicts Midlife Biological Age

Jonathan D. Schaefer, Avshalom Caspi, Daniel W. Belsky, Honalee Harrington, Renate Houts, Salomon Israel, Morgan E. Levine, Karen Sugden, Benjamin Williams, Richie Poulton, Terrie E. Moffitt

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


Objectives: Early-life intelligence has been shown to predict multiple causes of death in populations around the world. This finding suggests that intelligence might influence mortality through its effects on a general process of physiological deterioration (i.e., individual variation in "biological age"). We examined whether intelligence could predict measures of aging at midlife before the onset of most age-related disease. Methods: We tested whether intelligence assessed in early childhood, middle childhood, and midlife predicted midlife biological age in members of the Dunedin Study, a population-representative birth cohort. Results: Lower intelligence predicted more advanced biological age at midlife as captured by perceived facial age, a 10-biomarker algorithm based on data from the National Health and Nutrition Examination Survey (NHANES), and Framingham heart age (r = 0.1-0.2). Correlations between intelligence and telomere length were less consistent. The associations between intelligence and biological age were not explained by differences in childhood health or parental socioeconomic status, and intelligence remained a significant predictor of biological age even when intelligence was assessed before Study members began their formal schooling. Discussion: These results suggest that accelerated aging may serve as one of the factors linking low early-life intelligence to increased rates of morbidity and mortality.

Original languageEnglish (US)
Pages (from-to)968-977
Number of pages10
JournalJournals of Gerontology - Series B Psychological Sciences and Social Sciences
Issue number6
StatePublished - Nov 1 2016

Bibliographical note

Funding Information:
The Dunedin Multidisciplinary Health and Development Research Unit is supported by the New Zealand Health Research Council. This work was supported by the National Institute on Aging (AG032282, AG048895), the Medical Research Council (MR/K00381X), the Economic and Social Research Council (ES/M010309/1), and the Jacobs Foundation. J. D. S. and D. W. B. were supported by the NIA (T32-AG000139-25, T-32AG000029), and (P30-AG028716-08).


  • Aging
  • Biomarkers
  • Cognition
  • IQ
  • Intelligence

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