Suggestions for a gender-sensitive and intersectional practice of health monitoring and reporting. (30th September 2020) - Mena, E; Jaehn, P; Merz, S; Pöge, K; Strasser, S; Saß, A C; Rommel, A; Holmberg, C; Bolte, G
Abstract: Background: Health reports summarize the evidence basis on disease burden and its causes and are intended to inform decisions of policy makers. By focusing on health needs of social groupings according to sex/gender or race/ethnicity, PHMR crucially contributes to achieving health equity. In order to realise its aims, PHMR relies on the availability of high-quality data, appropriate analysis methods and intuitive presentation of results. Methods: The joint project AdvanceGender used mixed methods to translate principles of intersectionality into new methods for recruitment, data analysis and health reporting. A review of descriptions of representativeness in epidemiological studies was conducted to investigate how an intersectional perspective can inform recruitment. To evaluate intersectional and gender-sensitive data analysis, we reviewed and applied recently developed methods such as classification and regression tree analysis (CART) and multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA). Findings: An intersectional perspective on representativeness unravelled that study participation of women and men might be differential according to further social categories such as civil status or educational level. CART analysis might help to identify intersectional groupings differing in health behaviours or outcomes by exploring a multitude of social dimensions without facing the risk of stereotyping with predefined categories. MAIHDA depicts an alternative method that is suited for descriptive analyses of health-related outcomes among intersectional strata. In contrast to analysing supposedly static features such as sex, a focus on solution-linked variables like social support might be a fertile ground to identify areas for public health action. Discussion: Principles of intersectionality open up new perspectives for recruitment and data analysis that might be fruitful for population health research and ultimately for PHMR. : Greta Bauer Schulich School of Medicine & Dentistry, Western University, London, Canada Contact: gbauer@uwo.ca Olena Hankivsky University of Melbourne, Centre for Health Equity, Melbourne, Australia Institute for Intersectionality Research, School of Public Policy, Simon Fraser University, Burnaby, Canada Contact: o.hankivsky@unimelb.edu.au Nicole Rosenkötter NRW Centre for Health, Division of Health Reporting, Bielefeld, Germany Contact: Nicole.Rosenkoetter@lzg.nrw.de