HIGHLIGHTS
SUMMARY
The reliance on global health datasets ill-equipped for research at the gender-health nexus may be a central factor impeding progress, with interventions derived from datasets built on gender bias and restrictive gender norms perpetuating a cycle of gender inequalities and inadequate data collection. The authors extend this analysis to gain insights into the effects of gender- and age-imbalanced and missing covariate data on gender-health outcomes. The authors hypothesised that the analytic models are sensitive to gender-age sampling imbalance and data missingness, and defined gender-age-imbalance as gender-age . . .
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