Wilma Nusselder, PhD, is an Assistant Professor in Medical Demography at the Department of Public Health, Erasmus University Medical Center. She specializes in the intersection of public health and demography, investigating how risk factors and chronic diseases influence health, functioning, and mortality. Her research highlights variations across subgroups defined by gender, socioeconomic position, and ethnicity.

Her work frequently employs summary measures of population health, such as health expectancies, which consider both the length and quality of life. She focuses on describing, explaining, and projecting health and mortality trends, as well as assessing the impact of interventions and policies on these outcomes. Her research encompasses data collection, analysis, method development, modeling, scenario analysis, and projections.

As the coordinator of ERAINHE, a collaborative data and research framework at Erasmus MC, she oversees the collection and harmonization of mortality data by socioeconomic position across European countries. This initiative supports collaborative research in close cooperation with national data sources.

She teaches both medical and PhD students and collaborates with multidisciplinary international teams, connecting experts in public health, demography, sociology, and econometrics.

Research Interests:

• Socioeconomic differences in health and mortality
• Gender differences in health and mortality
• Summary measures of population health, with a focus on health expectancy
• Impact of risk factors, interventions, and policy changes on health and mortality inequalities
• Societal impacts of health and mortality inequalities and policies affecting these

Research Methods:

• Extensive experience in quantitative data analysis using ERAINHE data, register data, and cross-sectional and longitudinal surveys, employing statistical techniques and life table analysis
• Development of methods such as decomposition and attribution to better understand changes and disparities in aggregated health outcomes
• Co-development of modeling approaches to estimate the contribution of risk factors to health inequalities and assess the effects of interventions and policies on health outcomes
• Co-development of the health impact assessment model DYNAMO-HIA, coordinating the estimation of detailed input data by combining various public data sources, tailored survey data analyses, and literature evidence
• Co-development of projections for life expectancy, disability, and health expectancy by gender and educational attainment