Since the second half of the 19th century most Western and Asian societies have gone through the fertility transition, the shift from high to low fertility. A longstanding, unresolved debate has developed about whether this decline was caused by ‘spacing’ (increasing the time between births) or by ‘stopping’ (terminating childbearing ...
(Show more)Since the second half of the 19th century most Western and Asian societies have gone through the fertility transition, the shift from high to low fertility. A longstanding, unresolved debate has developed about whether this decline was caused by ‘spacing’ (increasing the time between births) or by ‘stopping’ (terminating childbearing at younger ages). Recently, the same debate has re-emerged concerning the fertility transition in sub-Saharan Africa, which has been described as ‘a new type of transition’ characterized by the use of modern contraceptives by women who still want large families and by ‘postponement’ of childbearing as a response to uncertain external conditions, such as housing shortages, income drops, and marriage problems. By now, the debate has reached a dead-end because of disagreement about the methods to detect fertility control. While most prior studies have focused on single markers of fertility control, such as spacing and stopping, we use an empirical approach based on the life course perspective that allows us to understand (changes in) fertility behaviour over women’s entire reproductive lifespans (age 15-45). ‘Holistic’ reproductive trajectories not only capture reproductive dynamics taking place over more extended periods of (life) time but also ensure a better examination of the endogenous causality of reproductive events and of the actual practiced reproductive control. Using sequence and cluster analysis we identify different types of reproductive trajectories incorporating, besides fertility, also marriage behaviour, and other forms of reproductive management, such as abortions. Trajectories are explained by exploiting multilevel logistic models capturing structural, ideational/cultural, and social-interactional variables. We base our analysis on longitudinal micro data from a health and demographic surveillance system in Niakhar region, Senegal that has been in place since the early 1960s.
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