Background: Chronic pain, usually defined as pain lasting longer than 3 months, has an increasing global prevalence and imposes a significant socioeconomic burden on health care systems worldwide. In fact, chronic pain are among the top 5 underlying causes of years lived with disability in the world affecting 20 to 30 % of the adult population. Patients with chronic pain have an excess risk of mortality, but the underlying pathophysiology is incompletely understood. We hypothesize that chronic pain is a clinically relevant contributor to the development of cardiovascular disease and mortality. Therefore, we aim to investigate novel aspects of this detrimental interplay using multiple large study cohorts with unique data on pain phenotypes, psychosocial factors, and a large number of cardiovascular events as well as other diseases and mortality events during a long follow-up time. We are furthermore interested in detailed characterization of people with chronic pain / using pain medication with regards to circulating proteins and metabolites and the microbiome. We expect that our findings will lead to important new insights of the interplay between chronic pain and disease that may have implications for the routine care of chronic pain patients in primary care. Aims and Statistical Analysis Plan: 1) Investigate associations between chronic pain and mortality and CVD events using survival analyses and investigate potential mediation by other lifestyle factors and medication using mediation analysis. 2) Investigate associations between chronic pain / pain medication and omics (microbiome, metabolome and proteins) using logistic regression models as well as machine learning approaches such as LASSO regression and random forest. 3) Investigate how omics data may mediate associations between chronic pain / pain medications and mortality/CVD outcomes.