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 o...

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Veröffentlicht in:BMJ global health Jg. 6; H. 11; S. e007405
Hauptverfasser: Weber, Ann M, Gupta, Ribhav, Abdalla, Safa, Cislaghi, Beniamino, Meausoone, Valerie, Darmstadt, Gary L
Format: Journal Article
Sprache:Englisch
Veröffentlicht: England BMJ Publishing Group Ltd 01.11.2021
BMJ Publishing Group LTD
BMJ Publishing Group
Schlagworte:
Bias
epidemiology
Gender
Gender identity
Global Health
Health disparities
health policy
Health Surveys
Households
Humans
Non-binary gender
Practice
Public health
Qualitative research
Sexism
Surveys and Questionnaires
Women
Nigeria
Sierra Leone
India
epidemiology
public health
health policy
ISSN:2059-7908, 2059-7908
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Zusammenfassung: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.
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ISSN:2059-7908
2059-7908
DOI:10.1136/bmjgh-2021-007405