Life-history theory, chronic childhood illness and the timing of first reproduction in a British birth cohort

Research output: Contribution to journalArticleResearchpeer-review

39 Citations (Scopus)

Abstract

Life-history theoretical models show that a typical evolutionarily optimal response of a juvenile organism to high mortality risk is to reach reproductive maturity earlier. Experimental studies in a range of species suggest the existence of adaptive flexibility in reproductive scheduling to maximize fitness just as life-history theory predicts. In humans, supportive evidence has come from studies comparing neighbourhoods with different mortality rates, historical and cross-cultural data. Here, the prediction is tested in a novel way in a large (n = 9099), longitudinal sample using data comparing age at first reproduction in individuals with and without life-expectancy-reducing chronic disease diagnosed during childhood. Diseases selected for inclusion as chronic illnesses were those unlikely to be significantly affected by shifting allocation of effort away from reproduction towards survival; those which have comparatively large effects on mortality and life expectancy; and those which are not profoundly disabling. The results confirmed the prediction that chronic disease would associate with early age at first reproduction: individuals growing up with a serious chronic disease were 1.6 times more likely to have had a first child by age 30. Analysis of control variables also confirmed past research findings on links between being raised father-absent and early pubertal development and reproduction.

Original languageEnglish
Pages (from-to)2998-3002
Number of pages5
JournalProceedings of the Royal Society B: Biological Sciences
Volume279
Issue number1740
DOIs
Publication statusPublished - 7 Aug 2012
Externally publishedYes

Fingerprint

Dive into the research topics of 'Life-history theory, chronic childhood illness and the timing of first reproduction in a British birth cohort'. Together they form a unique fingerprint.

Cite this