ArticleEvolutionary human sciences2020
Using sequence analysis to test if human life histories are coherent strategies.
Article in Evolutionary human sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Older health and social care workers' labour market patterns: a 16-year longitudinal study from ages 61-65 to 76-80.BMC health services research · 2025Article
- Borderline Personality Disorder in a "Life History Theory" Perspective: Evidence for a Fast "Pace-of-Life-Syndrome".Frontiers in psychology · 2021Article
- How evolutionary behavioural sciences can help us understand behaviour in a pandemic.Evolution, medicine, and public health · 2020Review
- The evolutionary ecology of age at natural menopause: implications for public health.Evolutionary human sciences · 2020Article
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2 authors.
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Abstract
Life history theory, a prominent ecological model in biology, is widely used in the human sciences to make predictions about human behaviour. However, its principal assumptions have not been empirically tested. We address this gap with three research questions: (1) do humans exhibit coherent life history strategies; (2) do individuals adopt strategies along a slow-fast continuum; and (3) are socioeconomic circumstances during childhood associated with the pace of the life history strategy that an individual adopts? Data from the Wisconsin Longitudinal Study is used to reconstruct the life histories of US women including information on puberty, fertility, menopause and death. We introduce a novel methodological approach to evolutionary anthropology, sequence analysis, to assess if human life histories are coherent strategies and how these strategies are patterned. In subsequent analyses we used multinomial logistic regressions to test whether childhood socioeconomic status predicts the life history patterns women follow. Results provide little evidence that humans follow coherent life-history strategies; Wisconsin women are clustered by the number of children they have but not by ages at life events. Socioeconomic status does not predict which cluster women fall into, suggesting that less well-off women do not have higher fertility, as predicted.
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