Factors influencing male fertility in Uganda

Henry Nsobya, Elizabeth Nansubuga, C. Misinde
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Abstract

Male fertility is an important component of population research. Against this backdrop, this paper aims to examine the factors explaining male fertility changes in Uganda. The authors applied the own-children method, as described by Schoumaker, to understand the prevailing male total fertility rate trends and to select datasets for inclusion during the multivariate analysis, using the Uganda demographic health surveys conducted from 2006 to 2016. A multivariable Poisson decomposition regression model was used to examine factors associated with male fertility changes. This model analyzed data from the 2006 and 2016 surveys only and included a total sample size of 7839 male respondents. The outcome variable for the regression model was children ever born (CEB). The regression model showed that differences related to changes in the proportional composition of characteristics contributed 113% to the change in CEB, compared with the differences due to reproductive behavior, with other factors being kept constant. The most important proportional changes that led to meaningful variability in CEB were observed among the following characteristics: occupation, number of current wives, total number of lifetime partners, type of residence, education, and age at first childbirth. Thus, interventions to delay the formation of cohabitation and marriage unions and the onset of childbirth or fatherhood among adolescents and young men below the age of 25 should be prioritized as potent fertility regulation measures. In addition, the focus on eliminating the lack of education and primary education as the highest levels attained among boys and men should be prioritized to boost a rapid male fertility transition in Uganda.
影响乌干达男性生育率的因素
男性生育率是人口研究的一个重要组成部分。在此背景下,本文旨在研究解释乌干达男性生育率变化的因素。作者采用了 Schoumaker 所描述的自有子女法,以了解当前男性总和生育率的趋势,并利用 2006 年至 2016 年进行的乌干达人口健康调查,选择数据集纳入多变量分析。多变量泊松分解回归模型用于研究与男性生育率变化相关的因素。该模型仅分析了 2006 年和 2016 年的调查数据,共包括 7839 个男性受访者样本。回归模型的结果变量是曾经出生的子女(CEB)。回归模型显示,在其他因素保持不变的情况下,与生育行为造成的差异相比,与特征构成比例变化有关的差异对 CEB 变化的贡献率为 113%。在以下特征中,最重要的比例变化导致了 CEB 的显著变化:职业、现任妻子人数、一生伴侣总数、居住地类型、教育程度和初次生育年龄。因此,应优先采取干预措施,推迟同居和婚姻结合的形成,推迟 25 岁以下青少年和年轻男子开始生育或成为父亲的时间,以此作为有效的生育调节措施。此外,应将重点放在消除男童和男子缺乏教育和小学教育这一最高水平上,以促进乌干达男性生育率的快速转变。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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