Background: Most studies assessing the associations between environmental, occupational or lifestyle factors and cardiovascular diseases (CVD) are limited to single exposures and rarely considered a more complex exposure panorama. Consequently, there is limited knowledge on their separate and combined contribution to health and disease. This PhD-project is designated to bringing all this information on important exposures together for an assessment of the so called exposome. Aim: The overall aim of this project is to prospectively assess the impact on CVD by air pollution, traffic noise and greenness, and to explore the interaction between these environmental factors and diet and lifestyle, occupational exposure to air pollution and noise, and by socioeconomic status. Specific research questions include: • Are there inequalities in the exposure to air pollution, traffic noise and greenness depending on socioeconomic determinants? • Does exposure to air pollution and traffic noise increase the risk of MI and stroke? • Does exposure to residential greenness reduce the risk of MI and stroke? • To what extent do the environmental exposures contribute to CVDs considering other risk factors, including diet and lifestyle, occupational exposure to air pollution and noise and socioeconomic determinants? Method: Participants’ residential address history (Uppsala county) will be assigned a geographic coordinate. Yearly averaged concentrations (1990-2015) of air pollutants related to traffic, heating and shipping, including NOx, PM10, PM2,5, and Black Carbon, is modeled using a Gaussian dispersion modeling technique, using the Nordic Prediction Method. Greenness exposure is based on satellite images and the Normalized Difference Vegetation Index (NDVI). Socio-economic factors as well as exposure to occupational noise and air pollution will be based on occupational codes (SSYK and NYK) from SCB. The codes will be linked to the exposure using Job Exposure Matrices for air pollution and noise, respectively. Data will be complemented by questionnaire data.