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This project focuses on health of young individuals transitioning from adolescence to young adulthood within the STARS cohort, a unique study monitoring both mental and physical health on 2283 individuals since the age of 13. Besides that they experienced the COVID-19 pandemic-related stressors, many of them are now also expressing worries related to gang crime, terrorism, war, economic hardships and/or the climate crisis.The main objective of this project is to explore the evolving health status among individuals transitioning from adolescence to young adulthood. The research aims to investigate the complex interplay between physiological and psychosocial dynamics, accentuated by the current turbulent times.By conducting a fourth follow-up (wave 4) of STARS participants now entering young adulthood, and utilizing data from waves 1-3 at ages 13, 15, and 18 years, we seek to answer these questions:1a.  What is the prevalence of mental illness and cardiometabolic risks among young adults? How do factors like motivation, life purpose, and maintaining hope amidst challenges impact health? Data: online surveys, physiological examinations, registers at wave 4. Method: Regression analysis.1b. What challenges do young adults perceive, and how do they navigate the turbulent times marked by polycrisis? Data: qualitative semi-structured interviews at wave 4. Method: qualitative thematic analysis.2. Is it possible to discern unique trajectories of mental health issues, personal and social resources (including coping strategies), health behaviours, and educational achievement throughout adolescence? Data: waves 1-3. Method: group-based trajectory modelling.3. How do socioeconomic and personal adversities in early life shape these paths? Data: registers and from wave 1. Method: Multinominal regression4. Do these trajectories function as mediators/moderators in the associations between early life socioeconomic factors, personal adversities, and the likelihood of mental illness and cardiovascular risks among young adults? Method: regression, mediation, moderation analysis.Recognizing the heightened vulnerability of young adults facing polycrisis, the project contributes not only to the understanding of young adult health but also to providing insights into future health risks and trajectories.The budget prioritizes staff salaries due to their extensive involvement in organizing the fourth follow-up, and costs including laboratory analysis of blood/hair samples.

Research problem and specific questions: Strong evidence links high outdoor temperatures to increased population morbidity, but little is known about the relationship between heat exposure indoors and its impact on health. Presently, no empirically supported recommendations regarding an upper indoor temperature threshold for health exist. Defining such a threshold is important as without this it will be difficult to establish any regulatory requirements that ensure that future buildings are sufficiently resilient to warmer summers. As the frequency of heat waves increases, understanding the sensitivity of different dwellings to outdoor temperature, especially in homes occupied by the elderly, is critical. This collaboration programme between six Swedish Universities aims to establish an evidence-based upper indoor temperature threshold for wellbeing

identify dwelling-specific characteristics that are most likely to increase the risk of heat-related illness, develop a temperature sensitivity regression model for indoor temperature prediction, and visualise area-level heat-vulnerability of the buildings on interactive maps, made available for a wide variety of endusers.Data and method: We aim to collect indoor temperature and humidity data, self-reported information about sleep quality, mental and physical health, as well as dwelling-specific characteristics from 4,000 adults across Sockholm, Malmö, Göteborg and Umeå during summer months, 2024-2027, by using temperature loggers, automatic text messages and electronic questionnaires. Physiological health data will be collected from 400 senior citizens by using Actiheart-5, activity, heart rate and sleep monitors. The associations between indoor temperatures and physical and mental health outcomes will be examined by multiple regression models. A model for prediction of indoor temperatures in different types of buildings will be developed by fitting the collected indoor temperature data to a modified energy balance model.Relevance and utilisation: The sustainability of housing policy includes ensuring access to a healthy indoor environment for all socio-economic groups. Being able to predict how different buildings are likely to respond to high outdoor temperatures is important for mitigating their potentially harmful impact. The present programme aims to fill the gaps in knowledge regarding the role that different building characteristics play in personal temperature exposure and visualise these problems on interactive maps for wider public, which is important for improving heat epidemiology, preparing prevention programmes.Plan for programme realisation: The data will be collected during four summers, after which model development and data analyse will be conducted. Regular research group and stakeholder meetings will be held. Programme costs include salaries for a research assistant and statistician, costs for technical devices, as well as postal costs for the distribution of temperature loggers.

Research problem and specific questions: Strong evidence links high outdoor temperatures to increased population morbidity, but little is known about the relationship between heat exposure indoors and its impact on health. Presently, no empirically supported recommendations regarding an upper indoor temperature threshold for health exist. Defining such a threshold is important as without this it will be difficult to establish any regulatory requirements that ensure that future buildings are sufficiently resilient to warmer summers. As the frequency of heat waves increases, understanding the sensitivity of different dwellings to outdoor temperature, especially in homes occupied by the elderly, is critical. This collaboration programme between six Swedish Universities aims to establish an evidence-based upper indoor temperature threshold for wellbeing

identify dwelling-specific characteristics that are most likely to increase the risk of heat-related illness, develop a temperature sensitivity regression model for indoor temperature prediction, and visualise area-level heat-vulnerability of the buildings on interactive maps, made available for a wide variety of endusers. Data and method: We aim to collect indoor temperature and humidity data, self-reported information about sleep quality, mental and physical health, as well as dwelling-specific characteristics from 4,000 adults across Sockholm, Malmö, Göteborg and Umeå during summer months, 2024-2027, by using temperature loggers, automatic text messages and electronic questionnaires. Physiological health data will be collected from 400 senior citizens by using Actiheart-5, activity, heart rate and sleep monitors. The associations between indoor temperatures and physical and mental health outcomes will be examined by multiple regression models. A model for prediction of indoor temperatures in different types of buildings will be developed by fitting the collected indoor temperature data to a modified energy balance model. Relevance and utilisation: The sustainability of housing policy includes ensuring access to a healthy indoor environment for all socio-economic groups. Being able to predict how different buildings are likely to respond to high outdoor temperatures is important for mitigating their potentially harmful impact. The present programme aims to fill the gaps in knowledge regarding the role that different building characteristics play in personal temperature exposure and visualise these problems on interactive maps for wider public, which is important for improving heat epidemiology, preparing prevention programmes. Plan for programme realisation: The data will be collected during four summers, after which model development and data analyse will be conducted. Regular research group and stakeholder meetings will be held. Programme costs include salaries for a research assistant and statistician, costs for technical devices, as well as postal costs for the distribution of temperature loggers.