Population Institute

ABSTRACT

The fertility preferences of young people are crucial in shaping future population dynamics. Yet, research on male fertility preferences and the influence of community-level factors on these fertility desires remains limited, particularly in the Philippines. Utilizing data from the 2021 Young Adult Fertility and Sexuality Study (YAFS), the study addresses this research gap by examining the fertility preferences of Filipino youth aged 15 to 24. Multilevel analysis or hierarchical linear modeling was employed to explore associations between the youth’s preferred number of children and individual- and community-level factors among a sample of 5,312 male and 5,637 female youth.

Findings reveal significant gender differences in fertility preferences of the youth and the factors associated with these fertility desires. Males generally prefer a higher number of children than females. All three community-level characteristics examined are significantly associated with fertility preferences. For both male and female youth, peer fertility is positively associated with the desired number of children. The youth’s perception of low community acceptance of non-traditional norms is associated with a preference for larger family sizes among both sexes. Rural residence, however, is associated with a higher preferred number of children exclusively among male youth. At the individual level, older age, not working, and having more siblings are linked to a higher preferred number of children for both males and females. Additional factors, such as marriage among females, low economic status, and having female friends with early pregnancy experience among males, are also associated with a higher preferred number of children.

The results underscore the need for gender-sensitive, culturally-informed, and location-specific interventions to support Filipino youth in achieving their desired family sizes.

Keywords: Fertility preferences, Community factors, Individual factors, Filipino youth, Multilevel analysis, Hierarchical linear modeling