PubMed

Influence of early-life nutrition on mortality and reproductive success during a subsequent famine in a preindustrial population.

Authors

Hayward AD, Rickard IJ, Lummaa V.

Journal

Proc Natl Acad Sci U S A. 2013 Aug 20;110(34):13886-91. doi: 10.1073/pnas.1301817110. Epub 2013 Aug 5.

Affiliation

Abstract

Individuals with insufficient nutrition during development often experience poorer later-life health and evolutionary fitness. The Predictive Adaptive Response (PAR) hypothesis proposes that poor early-life nutrition induces physiological changes that maximize fitness in similar environments in adulthood and that metabolic diseases result when individuals experiencing poor nutrition during development subsequently encounter good nutrition in adulthood. However, although cohort studies have shown that famine exposure in utero reduces health in favorable later-life conditions, no study on humans has demonstrated the predicted fitness benefit under low later-life nutrition, leaving the evolutionary origins of such plasticity unexplored. Taking advantage of a well-documented famine and unique datasets of individual life histories and crop yields from two preindustrial Finnish populations, we provide a test of key predictions of the PAR hypothesis. Known individuals from fifty cohorts were followed from birth until the famine, where we analyzed their survival and reproductive success in relation to the crop yields around birth. We were also able to test whether the long-term effects of early-life nutrition differed between individuals of varying socioeconomic status. We found that, contrary to predictions of the PAR hypothesis, individuals experiencing low early-life crop yields showed lower survival and fertility during the famine than individuals experiencing high early-life crop yields. These effects were more pronounced among young individuals and those of low socioeconomic status. Our results do not support the hypothesis that PARs should have been favored by natural selection and suggest that alternative models may need to be invoked to explain the epidemiology of metabolic diseases.

PMID

23918366 [PubMed - indexed for MEDLINE]

PMCID

PMC3752237 Free Full Text
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