Our network
PRIME Health maintains a close collaboration with the Centre for Epidemiology and Community Medicine (CES) in Region Stockholm, as well as the recently established Swedish Center for Impacts of Climate Extremes. Our international network encompasses scholars from various countries, including the United States, the United Kingdom, and Spain.
Our methods
We use a range of methods and data sources to forge interdisciplinary approaches to public health research. PRIME hosts the total population record-linkage “The Developmental Origins of Health and Disease-study” and are lead investigators of cohorts run by CES: , , the , along with .
Our Projects
Climate Extremes:
We investigate vulnerability and adaptation to climate extremes to inform sustainable transformation and future scenarios. This encompasses analyzing a broad spectrum of climate extremes, including temperature fluctuations, floods, droughts, and storms. We utilize individual and aggregated level data at the national level from multiple countries and employ interdisciplinary approaches such as storylines and system dynamics models.
Funding: Formas, Forte, VR
Physical Activity, Obesity, and Cardiometabolic Diseases:
Following precision public health principles, we utilize biological samples and accelerometers alongside survey and health data registers for research within this domain. Our work includes observational and experimental studies examining the impact of outdoor school environments, risk stratification for cardiometabolic diseases, and the effectiveness of healthcare interventions.
Funding: Region Stockholm, Formas, Cancerfonden, Forte
Maternal and Child Health:
This theme focuses on uncovering the developmental origins of health and evaluating the performance of maternal and child health systems. We investigate the perinatal health effects of infections, smokeless nicotine, drug use, and other healthcare interventions during pregnancy. Additionally, we assess the longer-term impacts of reproductive and child health care and early life conditions on population health and welfare. Our methodology involves employing a variety of quantitative methods for causal inference, such as target trial emulation and genetically informative study designs.
Funding: NIH, VR