2020 Åkesson Nordsound




Principal Investigator:

Agneta Åkesson


Karolinska Institutet

Start Date:


End Date:


Primary Classification:

30302: Public Health, Global Health, Social Medicine and Epidemiology



  • Castor /proj/nobackup at UPPMAX: 128 GiB
  • Castor /proj at UPPMAX: 128 GiB
  • Cygnus /proj at UPPMAX: 128 GiB
  • Cygnus /proj/nobackup at UPPMAX: 128 GiB
  • Bianca at UPPMAX: 2 x 1000 core-h/month


Background: Exposure to noise in urban environment is unavoidable, and because it has been repeatedly associated with increased risk of several major chronic diseases, including cardiovascular disease, the metabolic syndrome and cancer, it is a rapidly growing public health concern. Yet, only few studies have assessed the association of the joint exposure to noise and air pollution, with these diseases, or explored interactions with other environmental factors such as urban greenness. Hypothesis: Occupational and residential transportation noise increase the risk of cardiovascular disease, obesity, and cancer. This association may be modified by concomitant exposure to air pollution or urban greenness Aim: The overall aim of this project is to prospectively assess the association of air pollution, traffic noise and greenness with cancer in breast and colon, CVD and BMI and survival after cancer diagnosis Method: Residential address history (Uppsala county only) of each study participant 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