Evaluating the Accuracy and Quality of Breastfeeding-Related Information on Instagram

<b><i>Background:</i></b> Social media platforms, particularly Instagram, are increasingly used by new and expecting parents to seek health-related information, including guidance on breastfeeding. While this offers opportunities for accessible support, concerns persist regarding the accuracy and quality of content shared online. <b><i>Objective:</i></b> This study aimed to evaluate the accuracy and general quality of breastfeeding-related information shared on Instagram and to examine how these attributes vary by post characteristics, including format, content topic, and account type. <b><i>Methods:</i></b> A cross-sectional observational study was conducted using 80 top-performing Instagram posts identified through four popular breastfeeding-related hashtags. Posts were manually screened and assessed for eligibility. Accuracy was evaluated against official guidelines from the Centers for Disease Control and Prevention, World Health Organization, and American Academy of Pediatrics using a 4-point scale. General quality was assessed using the Global Quality Scale (GQS), a validated 5-point tool. Ordered logistic regression was used to assess associations between post characteristics and outcomes. <b><i>Results:</i></b> Overall, 38.8% of posts were completely accurate, while 36.3% were either mostly or completely inaccurate. The mean accuracy score was 3.7 (SD = 1.41), and the mean GQS was 4.0 (SD = 1.03). Image-based posts were significantly more accurate than videos (odds ratio [OR] = 2.52; 95% CI: 1.11-5.74), and posts by health care professionals had significantly higher quality scores (OR = 5.23; 95% CI: 1.66-16.54). Accuracy and quality scores were strongly correlated (ρ = 0.68, <i>p</i> < 0.001). <b><i>Conclusion:</i></b> While Instagram can serve as a valuable platform for breastfeeding education, content quality and accuracy vary widely. Posts by health care professionals tend to be more reliable. Public health efforts should focus on amplifying evidence-based content and mitigating misinformation to better support maternal and child health online.