糖心Volg

St茅phane Cullati

PhD, Privat Docent - Habilitation

photo

 stephane.cullati@unifr.ch
 +41 26 300 9474
 

Social determinants of health; Biological embedding of social life; Life course; Ageing; Prevention; Health and Social Policies; Quality and security of health care

Senior Researcher
Medicine Section

ARS 02 bu. 286
Rte des Arsenaux 41
1700 Fribourg
Hours of presence
ARS 02, 286
Hours of reception
+41 26 300 9474

Biography

Stéphane Cullati is a sociologist and Senior Lecturer in Epidemiology and Public Health at the 糖心Volg. He trained in sociology and social sciences at the Universities of Lausanne, Geneva and Grenoble, and obtained a doctorate (PhD) in the sociology of health and the life course from the University of Geneva and a habilitation in social epidemiology from the 糖心Volg. He carried out post-doctoral research at University College London Research Department of Epidemiology & Public Health. His research focuses on the relationship between health and society, from the perspective of social inequalities in health, the life course, social policies and reserves. His research has examined the impact of public policy on health inequalities, the (historical) evolution of social inequalities in health, and inequalities in cancer screening.

Research and publications

  • ORCID
    172 publications


    Stefan Sieber, Mengling Cheng, Lore Van Herreweghe, Aswathikutty Gireesh, Kenneth F. Ferraro, St茅phane Cullati, Advances in Life Course Research (2025) | Journal article


    Catherine Sherrington, Frerik Smit, Marcia R Franco, Stephane Cullati, Fiona M Blyth, Anita van Zwieten, Saman Khalatbari-Soltani, St茅phane Cullati, Fiona Blyth, (2025) | Preprint


    Nicolas Rodondi, Frerik Smit, Vladimir Jolidon, Bernadette WA van der Linden, St茅phane Cullati, Arnaud Chiolero, BMC Public Health (2025) | Journal article


    St茅phane Cullati, Julien Fakhoury, Jan-Erik Refle, Liala Consoli, Yves Jackson, Claudine Burton-Jeangros, Scientific Reports (2025) | Journal article


    Anne L眉bbeke, Raffaele Vitiello, St茅phane Cullati, Christophe Bar茅a, Sophie Cole, Gianluca Fabiano, Alan Silman, Nils Gutacker, Thomas Agoritsas, Didier Hannouche, Rafael Pinedo-Villanueva, PLOS ONE (2024) | Journal article


    Patrick Bodenmann, Clement P. Buclin, Moreno Doninelli, Laura Bertini, St茅phane Cullati, Arnaud Chiolero, Adriana Degiorgi, Armin Gemperli, Olivier Hugli, Anne Jachmann, Yves Jackson, Joachim Marti, Kevin Morisod, Katrina A. Obas, Florian R眉ter, Judith Safford, Javier Sanchis-Zozaya, Delphine S. Courvoisier, Matthis Schick, Francesca Giuliani, Swiss Medical Weekly (2024) | Journal article


    Denis Mongin, Adriana Uribe, Stephane Cullati, Delphine S. Courvoisier, Psychological Methods (2024) | Journal article


    A. Chiolero, S. Tancredi, S. Cullati, Public Health (2024) | Journal article


    Arnaud Chiolero, St茅phane Cullati, Cornelia Wagner, Josephine Jackisch, Natalia Ortega, Stephane Cullati, Cristian Carmeli, European Journal of Public Health (2024) | Journal article


    St茅phane Cullati, (2024) | Journal article

  • Research projects

    鈥楶REVENT TOO鈥�. Reducing social and life course inequalities in preventive practices: a comparative study of the effects of health and social policies
    Status: Ongoing

    Start 01.04.2024
    End 31.03.2028
    Funding SNSF 
    Background and rationale: Prevention is key to healthy ageing in middle and early old age but social inequalities in preventive practices, such as cancer screening, have remained persistently stable for decades in high-income countries. Health and social policies can reduce social inequalities, and their intersections, in preventive practices, however little research explored their impact by varying their characteristics (social rights, social expenditure). Furthermore, research has not yet examined how changes in policies (introduction of a policy, change in an existing policy) can modify inequalities in preventive practices. Following an eco-social and institutional approach, we assume that the moderation effect of health and social policies is modified by the history of preventive practices promotion and by the characteristics of the primary healthcare system of the country. Moreover, while research has focused on preventive practices at a given point in time (cross-sectionally) in the lives of individuals, little has been done to study their individual prevention trajectories (e.g., whether the use of preventive practices is stable, declines, or increases), how these trajectories vary according to individuals鈥� past social trajectories (disadvantaged childhood living conditions, non-normative family and employment trajectories), and how policies can modify the influence individuals鈥� past social trajectories on prevention trajectories. Overall objective and specific aims: the overall objective is to better understand how health and social policies can reduce social and life course inequalities in prevention in middle and early old age. Two specific aims will examine (1) the impact of characteristics and change in health and social policies on social inequalities in preventive practices, and if this impact is modified by the history of preventive practices promotion and characteristics of the primary healthcare system of the country; (2) the influences of socio-economic conditions at different moment of the life course, employment and family life trajectories on preventive practices trajectories, and if these life course influences are modified by the country's policies. The project will be divided into 2 Work Packages (WPs), 1 per aim. Methods: WP1 will use (cross-)nationally representative repeated cross-sectional health surveys (EHIS, Belgium, England, Finland, Germany, Sweden, Switzerland, United States), covering a period from several decades (variable baseline depending on surveys) to present. Main outcomes will be use of healthcare services (screening for dyslipidaemia, breast cancer, etc.) to prevent chronic diseases (cancer and cardiometabolic diseases). Countries鈥� policies characteristics and their evolution during the study period will be retrieved from the Comparative Welfare Entitlements Dataset, the Inter-university Consortium for Political and Social Research, and the Social Policy Indicators. The country鈥檚 history of preventive practices promotion will be built using documentations from country鈥檚 health promotion agencies and literature searches in bibliographic databases. Characteristics of the primary healthcare system will be retrieved from the OECD database, the European Primary Care Activity Monitor and a typology of healthcare professionalism. Analyses will include sequence analysis, multilevel regressions, and regression discontinuity. WP2 will use three longitudinal studies of ageing (SHARE, ELSA, HRS) with life history calendars. Countries鈥� policies characteristics will be retrieved from Institutional Rules Explorer of the G2AD, in combination with the SPLASH and the Social Policy Indicators databases. Analyses will include sequence and latent class growth analysis. Expected results: We expect to observe (i) smaller social inequalities in preventive practices among policies with more specified objectives and targeted populations and as a result of improved social policies (aim 1); (ii) smaller negative impact of disadvantaged and non-normative trajectories on preventive trajectories when policies have specified objectives and targeted populations (aim 2). Impact: Provide robust evidence that policies can reduce inequalities in prevention in middle and early old age.

    Social inequalities in the gut microbiome: individual participants meta-analyse of population-level data
    Status: Completed

    Start 01.12.2019
    End 30.11.2020
    Funding SNSF 
    Background: Despite substantial improvement in population health in the past five decades, health inequalities remain stable and consistent across time and space, if not increasing. If the link between social characteristics and health is well-established, the biological pathways between social exposures and health are less clear. Epigenetic factors and the stress model (McEwen 1998) attracted most of the empirical evidence on biological pathways. Recent advances in basic and clinical researches have highlighted the important role of the gut micro-biome for health. We hypothesis that the gut micro-biome could be another biological pathway mediating the social exposures and health link. Objective: To examine the associations between social variables and gut micro-biome biomarkers signatures. Method: individual participants meta-analyse of general population-level gut microbiome. 糖心Volg will be included if 1) participants are healthy patients or from the general population, 2) they collected data on the gut microbiome and 3) social information (social status and socioeconomic) on participants. 糖心Volg will be identified through literature review of studies on healthy participants, repositories of gut microbiome data (Human Microbiome Project Data Portal, European Genome-phenome Archive), and citizen science microbiome projects (e.g., Microsetta Initiative). 糖心Volg鈥� principal investigators (PI) will be contacted and screened for possible inclusion in the meta-analyse. First, analyses will be performed in each study, separately. Association between socioeconomic (primary objective) and social status (secondary objective) variables and gut biomarkers signatures will be estimated by generating odds ratios and 95% confidence intervals estimated with logistic regression analysis. Dichotomisation of biomarkers will be made following clinical guidelines, corrected for sex and age strata when appropriate, and checked by an expert in microbiology collaborating with our team. When appropriate, the analyses will be stratified by sex. When gut biomarkers will be measured repeatedly, the difference between baseline and follow-up will be estimated, and attrition will be included in the estimation. Second, estimates will be pooled in a meta-analysis. Fixed or random effect models will be determined depending on studies heterogeneity. Heterogeneity between studies will be computed with I2 and t2 statistics and 95% prediction intervals for odds ratios will be used to account for t2. Funnel plots will be assessed to identify if biases are operating in the findings. Robustness and sensitivity analyses will be conducted (molecular techniques bias, selection bias). Expected results: we expect cross-sectional associations between socioeconomic status and gut micro-biome signatures, suggesting a social gradient in the gut micro-biome of the general population. Limitations: the gut micro-biome is expected to be a potential, new, biological mediator between social exposures and health, however further researches collecting longitudinally data of gut micro-biome, dietary habits, anthropometrics measures, lifestyles and diseases information, social and life course information, will be needed to confirm this hypothesis.