Identification of Socio-demographic and Psychological Factors Affecting Women's Propensity to Breastfeed: An Italian Cohort

Abstract

Background: Exclusive breastfeeding until 6 months postpartum is a World Health Organization objective and benefits have been demonstrated for both mother and infant. It is important to clarify which factors influence breastfeeding intentions. Our objective was to assess and identify socio-demographic and psychological factors associated with breastfeeding intention in a sample of pregnant Italian women. Materials and Methods: This prospective study included 160 pregnant women. The following psychological constructs were measured using standardized questionnaires: anxiety, prenatal attachment, adult attachment, personality traits, and intention to breastfeed. Socio-demographic data were also collected using a self-report questionnaire. Assessment took place after the 20th gestational week. Results: Self-employment, age and feeding received as an infant were significantly related to breastfeeding intention. Regarding psychological factors, we also found that Neuroticism was negatively associated with mother's breastfeeding intentions. Relationships between psychological constructs and breastfeeding attitude were examined and represented within a graphical modeling framework. Conclusion: It may be possible to identify women that are less inclined to breastfeed early on in pregnancy. This may aid healthcare staff to pay particular attention to women who show certain socio-demographic and psychological characteristics, so as to fulfill more focused programs.

Keywords: Italy; breastfeeding; breastfeeding intention; neuroticism; psychological factors.

FIGURE 1

Graphical model showing underlying relationships between IIFAS and psychometric scales. Different shades of gray have been used to highlight groupings of psychometric scales derived from the same questionnaire (from light gray for the PAI scales to dark gray for the ASQ scales). For the outcome variable a white ellipse with a thicker border has been chosen. Lines indicate dependencies and associations, among variables identified by the “data driven” approach.]