Development of a gender score in a representative German population sample and its association with diverse social positions.

gender analysis intersectionality measurement relational theory secondary data analysis social epidemiology

Journal

Frontiers in epidemiology
ISSN: 2674-1199
Titre abrégé: Front Epidemiol
Pays: Switzerland
ID NLM: 9918419158106676

Informations de publication

Date de publication:
2022
Historique:
received: 07 04 2022
accepted: 02 08 2022
medline: 24 8 2022
pubmed: 24 8 2022
entrez: 8 3 2024
Statut: epublish

Résumé

Gender as a relational concept is rarely considered in epidemiology. However, an in-depth reflection on gender conceptualisation and operationalisation can advance gender analysis in quantitative health research, allowing for more valid evidence to support public health interventions. We constructed a context-specific gender score to assess how its discriminatory power differed in sub-groups defined by social positions relevant to intersectional analyses, i.e., sex/gender, race, class, age and sexual attraction. We created a gender score with the help of multivariable logistic regression models and conditional probabilities based on gendered social practices and expressed on a masculinity-femininity continuum, using data of the German Socioeconomic Panel. With density plots, we exploratively compared distributions of gendered social practices and their variation across social groups. We included 13 gender-related variables to define a gender score in our sample ( The distribution of gendered social practices differs among social groups, which empirically backs up the theoretical notion of gender being a context-specific construct. Economic participation and household structures remain essential drivers of heterogeneity in practices among women and men in most social positions. The gender score can be used in epidemiology to support concerted efforts to overcome these gender (in)equalities-which are important determinants of health inequalities.

Sections du résumé

Background UNASSIGNED
Gender as a relational concept is rarely considered in epidemiology. However, an in-depth reflection on gender conceptualisation and operationalisation can advance gender analysis in quantitative health research, allowing for more valid evidence to support public health interventions. We constructed a context-specific gender score to assess how its discriminatory power differed in sub-groups defined by social positions relevant to intersectional analyses, i.e., sex/gender, race, class, age and sexual attraction.
Methods UNASSIGNED
We created a gender score with the help of multivariable logistic regression models and conditional probabilities based on gendered social practices and expressed on a masculinity-femininity continuum, using data of the German Socioeconomic Panel. With density plots, we exploratively compared distributions of gendered social practices and their variation across social groups.
Results UNASSIGNED
We included 13 gender-related variables to define a gender score in our sample (
Conclusions UNASSIGNED
The distribution of gendered social practices differs among social groups, which empirically backs up the theoretical notion of gender being a context-specific construct. Economic participation and household structures remain essential drivers of heterogeneity in practices among women and men in most social positions. The gender score can be used in epidemiology to support concerted efforts to overcome these gender (in)equalities-which are important determinants of health inequalities.

Identifiants

pubmed: 38455329
doi: 10.3389/fepid.2022.914819
pmc: PMC10910995
doi:

Types de publication

Journal Article

Langues

eng

Pagination

914819

Informations de copyright

Copyright © 2022 Wandschneider, Sauzet, Razum and Miani.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Auteurs

Lisa Wandschneider (L)

Department of Epidemiology and International Public Health, School of Public Health, Bielefeld University, Bielefeld, Germany.

Odile Sauzet (O)

Department of Epidemiology and International Public Health, School of Public Health, Bielefeld University, Bielefeld, Germany.
Center for Statistics, Bielefeld University, Bielefeld, Germany.

Oliver Razum (O)

Department of Epidemiology and International Public Health, School of Public Health, Bielefeld University, Bielefeld, Germany.
Research Institute Social Cohesion (RISC), Bielefeld University, Bielefeld, Germany.

Céline Miani (C)

Department of Epidemiology and International Public Health, School of Public Health, Bielefeld University, Bielefeld, Germany.

Classifications MeSH