|Individual and community factors associated with lifetime fertility in Eswatini: an application of the Easterlin–Crimmins model
|Garikayi Bernard Chemhaka, and Clifford Odimegwu
|Journal of Population Research, 37, 291–322; DOI: 10.1007/s12546-020-09244-y
|Understanding fertility variation among women helps identify individuals and communities with high reproductive performance that slows fertility transition especially for African countries. The aim of this study was to investigate individual and community factors influencing lifetime fertility/children ever born (CEB) in Eswatini (formerly Swaziland). Using data from a onetime national representative demographic and health survey conducted in 2006–2007, this study goes beyond previous efforts by considering a broad range of individual and community factors that influences lifetime fertility and applying a supply–demand Easterlin–Crimmins model allowing for a multilevel framework. The results of a sequential multilevel (random intercept) Poisson regression suggest that the model was appropriate to account for overdispersed CEB data. All multilevel models found significant, but small, lifetime fertility variation across communities/clusters. While lifetime fertility variation decreased significantly from the empty model to the final model after controlling for a range of individual and community, it does not entirely disappear indicating the local community may have some bearing on CEB. Further, this suggests compositional (individual demographic and socioeconomic) factors explained substantial, but not all of the variation. At individual-level, the results suggest a significant negative association of household wealth index, level of education, age at sexual debut and age at first birth with CEB. On the other hand, the incident of childbearing among women increased significantly with child loss, having high fertility norms (5 or more children), being married, particularly in polygyny than monogamy unions, being employed and empowered. The compatibility of the latter two variables with childbearing contends with theory and warrants attention for future research. The results confirm the Easterlin–Crimmins model explain fertility behaviour reliably and demand (fertility norms) and supply (child loss) variables have good predictive value. At community level, women from rural communities had higher fertility than from urban ones. Overall, lifetime fertility in Eswatini is strongly related to individual (compositional) characteristics and is unique for urban–rural communities.