Key Social Norms Take-aways The study emphasizes that addressing adolescent health requires tackling not only individual attitudes but also the broader social norms reinforced by families, peers, schools, and communities. Proxy measures for gender norms—based on patterns of attitudes, behaviors, and their mismatches—offer a powerful tool to identify where social expectations create risks or opportunities for change. Programs aiming to improve adolescent health and gender equality must consider the complex social environments and reference groups that shape norm-related behaviors.

Objectives This article aimed to develop and showcase innovative methods for analyzing how gender norms influence adolescent health outcomes using global health survey data, especially in contexts where direct gender norms measures are often missing.

Methods The authors developed five case studies using diverse datasets from Nigeria, Brazil, South Africa, Zambia, the U.S., and Honduras. They applied various quantitative methods, including intraclass correlation coefficients, regression models, mediation analyses, and social network analysis, to create proxy measures of gender norms drawn from aggregated behaviors, attitudes, and the gap (discordance) between attitudes and behaviors.

Results Across the case studies, the research revealed that gender norms shape adolescent health outcomes such as intimate partner violence, eating disorder risk, HIV status, mental health, social mobility, and adolescent childbirth. For example, adolescent girls in Nigeria working outside the home in communities with restrictive gender norms faced a higher risk of intimate partner violence; in Zambia, adolescent girls were more likely to have HIV in regions with a wide gap between anti-premarital sex attitudes and actual behaviors; and in Honduras, adolescent girls connected to peers who had early pregnancies were more likely to also have adolescent childbirth.

Conclusions Even without direct gender norms questions, researchers can use creative proxy measures from existing datasets to uncover the influence of social norms on health. These methods help identify reference groups and sanctions that maintain or challenge harmful norms, providing critical insights for designing effective health interventions.