Clustering and trajectories of key noncommunicable disease risk factors in Norway: the NCDNOR project.
Knut Eirik DaleneSimon LergenmullerErik Reidar SundLaila Arnesdatter HopstockTrude Eid RobsahmYngvar NilssenWenche NystadInger Kristin LarsenInger AriansenPublished in: Scientific reports (2023)
Noncommunicable diseases (NCDs) are a leading cause of premature death globally and have common preventable risk factors. In Norway, the NCDNOR-project aims at establishing new knowledge in the prevention of NCDs by combining information from national registries with data from population-based health studies. In the present study, we aimed to harmonize data on key NCD risk factors from the health studies, describe clustering of risk factors using intersection diagrams and latent class analysis, and identify long-term risk factor trajectories using latent class mixed models. The harmonized study sample consisted of 808,732 individuals (1,197,158 participations). Two-thirds were exposed to ≥ 1 NCD risk factor (daily smoking, physical inactivity, obesity, hypertension, hypercholesterolaemia or hypertriglyceridaemia). In individuals exposed to ≥ 2 risk factors (24%), we identified five distinct clusters, all characterized by fewer years of education and lower income compared to individuals exposed to < 2 risk factors. We identified distinct long-term trajectories of smoking intensity, leisure-time physical activity, body mass index, blood pressure, and blood lipids. Individuals in the trajectories tended to differ across sex, education, and body mass index. This provides important insights into the mechanisms by which NCD risk factors can occur and may help the development of interventions aimed at preventing NCDs.
Keyphrases
- risk factors
- physical activity
- body mass index
- healthcare
- blood pressure
- quality improvement
- mental health
- public health
- depressive symptoms
- type diabetes
- emergency department
- metabolic syndrome
- smoking cessation
- insulin resistance
- weight gain
- health information
- adipose tissue
- weight loss
- machine learning
- heart rate
- electronic health record
- single cell
- skeletal muscle
- deep learning
- fatty acid
- blood glucose
- case control
- sleep quality
- high fat diet induced