Global population is expected to rise from 7.7 billion in 2019 to 8.5 billion in 2030, approaching 11 billion by the middle of the 21st century (Department of Economic and Social Affairs, 2019). This increase is a function of fertility, mortality, and migration, the principal determinants of population growth (Sloggett, 2015). While women in many parts of the world have had fewer children over the past few centuries (Lee, 2003), high fertility rates persist in sub-Saharan Africa despite different interventions (Babalola et al., 2019). By 2050, it is projected that up to half of the total population increase globally will be observed in these countries with lifetime fertility to remain well above two births per woman while many countries in sub-Saharan Africa are projected to double their population within the same period (Department of Economic and Social Affairs, 2019). Therefore, the speed of fertility decline in sub-Saharan Africa is a major determinant of global population prospects.

Nigeria is in the top-ten most populated countries globally, and like many sub-Saharan Africa countries is experiencing rapid population growth (Department of Economic and Social Affairs, 2019; Mberu & Reed, 2014). The country is in the early stage of demographic transition where fertility levels decline rather slowly as mortality falls significantly causing rapid population growth (Feyisetan & Bankole, 2009; Ifelunini et al., 2018). Given the established inverse relationship between economic development and fertility (Akpa, Onoja Matthew, & Ikpotokin, 2012; Lee, 2003; Lesthaeghe, 2010), substantial fertility reduction is critical to the subregion's demographic dividend. A low fertility rate is critical for reducing population growth while also improving socioeconomic and health outcomes (Sinding, 2009).

The primary indicator of fertility levels is the total fertility rate (TFR), a value that represents the average number of children a woman would bear in her lifetime based on current age-specific fertility rates. The 2018 Nigeria Demographic and Health Survey (NDHS) estimates Nigeria’s TFR at 5.3 children per woman (National Population Commission & ICF International, 2019). The decline in Nigeria’s TFR has been slow. From a high of 6.0 children per woman in 1990, it stalled at 5.7 in 003 and 2008, and 5.5 in 2013 (Federal Office of Statistics & IRD/Macro International, 1992; National Population Commission & ICF International, 2014; National Population Commission & ICF Macro, 2009; National Population Commission & ORC/Macro, 2000; National Population Commission & ORC Macro, 2004). Cultural and socioeconomic differentials in the TFR trend exist and mean the decline has been uneven. with a larger family size more desired in the north than the south (Adebowale, 2019). A study in Kaduna State reported less than 20% of women wanted less than 5 children and 69% citing 5-14 children as ideal (Adiri et al., 2010). This difference in fertility pattern can be attributed to early marriage prevalent in the Northern part of Nigeria (Goldstone et al., 2018; Solanke, 2015). In addition to the geographical disparity, there are considerable differences in rates among ethnic and socioeconomic groups (Mberu & Reed, 2014). TFR rates are lower among women who live in urban areas, women who have a secondary school education, and women who belong to households in higher or highest wealth quintiles (Wusu & Isiugo-Abanihe, 2019).

Demographically observed fertility or infertility is the result of a well-defined number of factors, collectively termed proximate determinants of fertility (Bongaarts, 1978; Bongaarts & Potter, 1983). These proximate determinants serve to mediate the influence of culture, socioeconomic conditions, and related background determinants on reproductive behaviour. They could be grouped into biological and behavioural factors (Bongaarts, 1993). The biological constraints include pregnancy, period after delivery before fecundity resumes, waiting time to conception, time lost due to naturally occurring intra-uterine mortality, and time lost because of sterility. The behavioural component includes extent of sexual exposure, breastfeeding practice, use of a contraceptive method, and induced abortion. John Bongaarts first designed a quantitative framework for analysis which indicates that variations in four major factors – marriage, contraception, breastfeeding practice, and induced abortion – were the primary proximate causes of differences among populations (Bongaarts, 1978). Revisions of this framework have modified or added to these determinants (Bongaarts, 2015; Stover, 1998).