Childlessness has received attention in the past decades, as it may indicate a new lifestyle and has substantial influences on many aspects of the female life course. An increase in the number of childless people has been observed throughout Europe, North America, and Japan. Accompanying this trend, the mean age at first childbirth has increased. However, whether the phenomenon of remaining childless or that of postponing first childbirth is the main contributor has not been clearly investigated. The aim of this study is to quantify those effects using a decomposition method. We employ the classical life table method to measure changes in first childbirth behavior. Life expectancy is normally used in mortality research to represent the average number of years people live. In childlessness (first childbirth) research, life expectancy signifies the expected number of years without children, as the event of focus is first childbirth. Thus, we define the expected years without children as age 15 to age 50 (EYWC) using the Coale-McNeil model. To avoid the problems of truncation and censoring, only completed cohort fertility data of eight selected countries from the Human Fertility Database are examined. EYWC is decomposed into three factors: remaining childless, postponing first childbirth, and expansion of the standard deviation of mean age at first childbirth. Results of the decomposition show that postponement is mainly occurred in
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.