STUDY OBJECTIVES: Sex differences are related to both biological factors and the gendered environment. We constructed measures to model sex-related differences beyond binary sex.

METHODS: Data came from the baseline visit of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). We applied the least absolute shrinkage and selection operator penalized logistic regression of male versus female sex over sociodemographic, acculturation, and psychological factors jointly. Two "gendered indices," the gendered index of sociodemographic environment (GISE) and gendered index of psychological and sociodemographic environment, summarizing the sociodemographic environment (GISE) and psychosocial and sociodemographic environment (GIPSE) associated with sex, were calculated by summing these variables, weighted by their regression coefficients. We examined the association of these indices with insomnia, a phenotype with strong sex differences, in sex-adjusted and sex-stratified analyses.

RESULTS: The distribution of GISE and GIPSE differed by sex with higher values in male individuals. In an association model with insomnia, male sex was associated with a lower likelihood of insomnia (odds ratio [OR] = 0.60, 95% CI [0.53, 0.67]). Including GISE in the model, the association was slightly weaker (OR = 0.63, 95% CI [0.56, 0.70]), and weaker when including instead GIPSE in the association model (OR = 0.78, 95% CI [0.69, 0.88]). Higher values of GISE and of GIPSE, more common in the male sex, were associated with a lower likelihood of insomnia, in analyses adjusted for sex (per 1 standard deviation of the index, GISE OR = 0.92, 95% CI [0.87, 0.99], GIPSE OR = 0.65, 95% CI [0.61, 0.70]).

CONCLUSIONS: New measures such as GISE and GIPSE capture sex-related differences beyond binary sex and have the potential to better model and inform research studies of sleep health.