Page 107 - IJPS-11-3

International Journal of
Population Studies Male fertility in Uganda

and knowledge that their spouse(s) are using contraception improves significantly if the data analyzed includes
(Namasivayam et al., 2019; Ochako et al., 2017). Therefore, respondents who have already completed their lifetime
interventions should focus on men engaging in discussions fertility span. However, the UDHS Individual Man’s
on contraceptive use with both health workers and their Recode data file is limited to respondents below 54 years.
spouses to demystify myths about contraception, promote Thus, this study did not analyze the causes of changes in
male involvement, and advocate for improved partner the mean number of CEB over the entire lifetime of men
contraceptive use among couples (Asiimwe et al., 2014; in Uganda.
Kabagenyi et al., 2014; Ochako et al., 2017).
Furthermore, this study could not infer causality given
To wrap up this discussion, this study addressed the the cross-sectional study design of the UDHS. The authors
direct and indirect factors responsible for the changes also acknowledge the possibility of an endogeneity effect
in CEB among men aged 15 – 54 years in Uganda, using in the regression model, possibly due to the inclusion
data from the 2006 – 2016 survey rounds. However, more of variables such as contraceptive use and age at first
research should investigate the dynamics of lifetime male childbirth. During the interpretation of the decomposition
fertility projections and their drivers, especially if men regression results, it is worth noting that the distinction
aged 55 years and older are included. Research to further between differences due to compositional changes in
improve understanding of male fertility and its effects characteristics and behavior is not without limitations.
on sustainable development outcomes in Uganda is also Reproductive behavior in this study includes independent
needed, as current knowledge is very limited. variables that could also be viewed as indicators of fertility
This study was constrained by several limitations. It behavior, such as age at first childbirth.
used secondary data from cross-sectional surveys, and
the analysis was limited to the data available in the UDHS 5. Conclusion
household, woman, and man individual recode data files. The findings of this research are critical for redirecting
The results of this study should be interpreted with caution policies and programs to prioritize men as key
due to potential data quality inconsistencies associated beneficiaries in achieving family and national Sustainable
with demographic health survey data and the limitations Development Goals. The slow male fertility transition
of data analysis, which are explained as follows: Essential observed between 2006 and 2016 was fundamentally
variables with missing records (such as the age at first attributed to changes in the composition of characteristics
childbirth and the number of current wives) were included among men aged 15 – 54 years, rather than changes in
in the analysis only after assigning pseudo or imputed behavioral responses toward lower CEB. Key factors
data to the missing values and recoding them; otherwise, negatively associated with CEB included an increase in
variables with missing data were avoided and excluded the proportion of men who delayed the onset of first
during data analysis to reduce bias. childbirth until age 25 or older, attained secondary or
Reconstruction of the ASFRm and TFRm for preceding higher education, and resided in urban areas. In addition,
years of the survey rounds included in this research was a decline in the proportion of men who were in polygamous
important, but this was not undertaken by the authors. unions and those engaged in agricultural occupations
Instead, this study focused on the application of the was associated with a reduction in CEB. Therefore,
own-children method, as described by Schoumaker, to government interventions and policies in Uganda
understand prevailing male fertility trends and to support should focus on interventions that delay the formation
contextualization of the Poisson decomposition regression of cohabitation and marriage unions and the onset of
model for this study (Schoumaker, 2017). Furthermore, this childbirth or fatherhood among adolescents and young
research did not analyze the determinants of male fertility men below the age of 25 years. Furthermore, prioritizing
using the own-children method, which was considered a the elimination of low educational levels among boys
limitation. Instead of using the ASFRm and TFRm as the and men is essential for enhancing the achievement of
dependent variables in the regression model, CEB for men Sustainable Development Goal 4 on quality education.
aged 15 – 54 years was used as a proxy. This, in turn, can significantly contribute to a more rapid
Another limitation was the inability of this study to male fertility transition in Uganda.
analyze completed lifetime fertility using the CEB variable. Acknowledgments
All data for survey respondents aged 15 – 54 years were
included in the analysis; yet, these respondents had Sincere gratitude is extended to Professor Bruno
not completed their lifetime fertility. In this regard, the Schoumaker at the Université Catholique de Louvain,
authors assume that the quality of CEB fertility analysis Belgium, for his valuable guidance on the estimation of

Volume 11 Issue 3 (2025) 101 https://doi.org/10.36922/ijps.461