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
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Abstract 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.
AbstractList 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.
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.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.
Author Weber, Ann M
Meausoone, Valerie
Abdalla, Safa
Gupta, Ribhav
Darmstadt, Gary L
Cislaghi, Beniamino
AuthorAffiliation 5 Stanford Research Computing Center , Stanford University , Stanford , California , USA
1 School of Public Health , University of Nevada Reno , Reno , Nevada , USA
2 Department of Medicine , University of Minnesota School of Medicine , Minneapolis , Minnesota , USA
3 Global Center for Gender Equality, Department of Pediatrics , Stanford University School of Medicine , Stanford , California , USA
4 Department of Global Health and Development , London School of Hygiene and Tropical Medicine , London , UK
AuthorAffiliation_xml – name: 4 Department of Global Health and Development , London School of Hygiene and Tropical Medicine , London , UK
– name: 2 Department of Medicine , University of Minnesota School of Medicine , Minneapolis , Minnesota , USA
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– name: 3 Global Center for Gender Equality, Department of Pediatrics , Stanford University School of Medicine , Stanford , California , USA
– name: 1 School of Public Health , University of Nevada Reno , Reno , Nevada , USA
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Issue 11
Keywords epidemiology
public health
health policy
Language English
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Snippet Global surveys have built-in gender-related biases associated with data missingness across the gender dimensions of people’s lives, imbalanced or incomplete...
Global surveys have built-in gender-related biases associated with data missingness across the gender dimensions of people's lives, imbalanced or incomplete...
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StartPage e007405
SubjectTerms 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
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Title Gender-related data missingness, imbalance and bias in global health surveys
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