Background Men, particularly those belonging to gender minority groups, often experience poorer physical health outcomes. This study examined global health and quality of life (QoL) across diverse male gender subgroups in Switzerland. While emphasising male gender diversity, we aimed to identify key sociodemographic risk factors associated with reduced global health and QoL. Methods We analysed a subset of the Swiss Health Survey 2022, a cross-sectional nationally representative health-related dataset from the general Swiss population. Our sample included individuals falling into one of the three groups: cisgender men, transgender men (assigned female at birth with male gender identity) and men with ‘other’ gender identities (assigned male at birth but identifying as non-binary or non-specified gender identity). Global health and QoL were assessed using the Minimum European Health Module (MEHM) and the global QoL item of the WHOQOL-Bref. Four binary logistic regression models examined the association between male gender identities, sociodemographic data and MEHM and QoL outcomes. Results Our study comprised 3 505 801 male cases after weighting. Of these, 12.9% reported fair to very poor health. Key risk factors included being unemployed, migration background and being a transgender man. The strongest protective factor was higher education. Chronic conditions were reported by 33.3% men, with unemployment again being the most relevant risk factor. Identifying as a man with ‘other’ gender identities emerged as a protective factor. Regarding QoL, 8% stated impaired QoL, while the male gender identity ‘other’ was the strongest risk factor and tertiary school education the most relevant protective factor. Discussion Risk and protective factors vary across different global health outcomes and QoL in men. These findings highlight the importance of disaggregating male gender categories beyond the binary to better understand the complexity of health disparities. A differentiated, gender-inclusive approach is essential for accurately identifying vulnerable groups and tailoring public health interventions accordingly.
Lieb et al. (Wed,) studied this question.