Childlessness and union histories: evidence from Finnish population register data

J Biosoc Sci. 2020 Jan;52(1):78-96. doi: 10.1017/S0021932019000257. Epub 2019 Jun 6.

Abstract

From an evolutionary perspective, childlessness may be considered a failure, as it implies that there will be no direct transmission of one's genetic material to later generations. It is also a pressing social issue, because in many contemporary advanced societies, levels of childlessness have increased, and particularly so among men. The absence of a partner is naturally a fundamental determinant of childlessness. Empirical evidence on how childlessness relates to individuals' partnership histories is nevertheless limited. This issue was analysed with Finnish population register data, which allow the complete cohabitation and marriage histories of individuals from age 18 years to be observed. For women and men born between 1969 and 1971, logistic regression models were estimated for childlessness at age 40 by partnership histories in terms of various stages in the process of union formation and dissolution, and accounting for several socioeconomic variables. A strong link between union histories and childlessness was found, with short partnership spells raising the risk of not becoming a parent. Later age when leaving the parental home raised female childlessness, while a short first-union duration related more strongly to male childlessness. These findings may be considered as providing insights into how specific life-history strategies affect reproductive outcomes, and highlight the need to develop new approaches to understand this feature of social inequality.

Keywords: Childlessness; Population registers; Union histories.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Female
  • Fertility
  • Finland
  • Humans
  • Logistic Models
  • Longitudinal Studies
  • Male
  • Marriage / statistics & numerical data*
  • Parents*
  • Registries / statistics & numerical data*
  • Single Person / statistics & numerical data*