Gender-related data missingness, imbalance and bias in global health surveys

Global surveys have built-in gender-related biases associated with data missingness across the gender dimensions of people's lives, imbalanced or incomplete representation of population groups, and biased ways in which gender information is elicited and used. While increasing focus is being placed on the integration of sex-disaggregated statistics into national programmes and on understanding effects of gender-based disparities on the health of all people, the data necessary for elucidating underlying causes of gender disparities and designing effective intervention programmes continue to be lacking. Approaches exist, however, that can reasonably address some shortcomings, such as separating questions of gender identification from biological sex. Qualitative research can elucidate ways to rephrase questions and translate gendered terms to avoid perpetuating historical gender biases and prompting biased responses. Non-health disciplines may offer lessons in collecting gender-related data. Ultimately, multidisciplinary global collaborations are needed to advance this evolving field and to set standards for how we measure gender in all its forms.

Automated summary

Global surveys have gender-related biases due to missing data, incomplete representation of population groups, and biased ways of using gender information. While efforts are being made to integrate sex-disaggregated statistics into national programs, there is still a lack of data to understand gender disparities and design effective intervention programs. Approaches such as separating gender identification from biological sex, using qualitative research to rephrase questions, and learning from non-health disciplines can help address these challenges. Collaboration across disciplines is essential to advance the field and establish standards for measuring gender in all its forms.