Page 99 - IJPS-11-3

International Journal of
Population Studies Male fertility in Uganda

1.1. Study conceptual framework fertility levels through variables such as contraceptive use

This research was conceptualized based on both Bongaarts’ and the duration of cohabitation and marriage.
proximate determinants framework and the supply- In addition, the supply-demand economic framework
demand Easterlin’s economic framework as modified for fertility by Richard Easterlin, as modified by Bongaarts
by (Bongaarts, 1993; 2015). Figure 1 illustrates the (1993), was used in this study to explain the supply and
conceptual framework designed for this study, visualizing demand for children, accounting for both economic and
male fertility determinants based on the proximate sociological approaches to fertility analysis. According
determinants frameworks. These frameworks can be used to this evidence, the motivation to limit fertility arises
to explain the determinants of fertility of any population only when the supply of children exceeds demand and
and are crucial in the determination of fertility levels and is influenced by the economic and psychological costs
differences among populations. For instance, background associated with various birth control methods. Thus,
factors such as education level may influence exposure to in view of this framework, fertility levels are majorly
sexual activities and unions, indirectly impacting fertility. influenced by changes in demand for children (desired
Changes in sexual activities and unions directly alter fertility) and the implementation of fertility decisions
fertility levels. A unique feature of the Bongaarts model based on either the need to regulate childbearing or the
is the assumption that changes in fertility levels are a costs of unwanted childbearing (Bongaarts, 1993). This
direct result of changes in proximate determinants. For study examined the association between the number of
example, a change in proximate factors, such as the sexual current wives and fertility levels. The model assumes that an
exposure index, directly impacts fertility levels for a given individual’s decision to marry or have another child largely
population (Bongaarts, 2015). Furthermore, Bongaarts depends on the labor market conditions experienced
(2015) demonstrates that fertility differences among during the reproductive period. Therefore, the proximate
populations at any given time or during trend analysis determinants included in the conceptual framework for
are entirely dependent on the proximate determinants, this study to examine the factors directly associated with
through their inhibitory effects. Thus, proximate male fertility in Uganda included reported contraceptive
determinants, such as sexual exposure through marriage, use, the number of current wives, and the duration
contraception, postpartum infecundability, and abortion, of cohabitation and marriage. The regression model
are sufficient and important in explaining fertility examined the determinants of male fertility by considering
variations comprehensively. Based on this evidence, this the number of CEB to men as the primary study outcome
study examined the association of sexual exposure with variable. Therefore, this study aimed to examine the socio-

Indirect Determinants Proximate Determinants Outcome Variable

Demographic factors
• Age of a man
• Place of residence
• Partner age difference
Proximate Determinants
• Number of current wives Male fertility
• Duration of cohabitation (Children
and marriage ever born)
Socio-economic and behavioral • Contraceptive use
factors
• Education
• Wealth status
• Occupation
• Religion
• Access to traditional mass media
platforms (radio, television and
newspapers or magazines
• Number of women fathered with
children
• Timing of first child’s birth
• Number of lifetime sexual partners
Figure 1. A conceptual framework for determinants of male fertility

Volume 11 Issue 3 (2025) 93 https://doi.org/10.36922/ijps.461