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Exposome-wide ranking of modifiable risk factors for cardiometabolic disease traits.
Poveda, Alaitz; Pomares-Millan, Hugo; Chen, Yan; Kurbasic, Azra; Patel, Chirag J; Renström, Frida; Hallmans, Göran; Johansson, Ingegerd; Franks, Paul W.
Afiliación
  • Poveda A; Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, 214 28, Malmö, Sweden.
  • Pomares-Millan H; Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, 214 28, Malmö, Sweden.
  • Chen Y; Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, 214 28, Malmö, Sweden.
  • Kurbasic A; Cardiovascular Medicine Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.
  • Patel CJ; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
  • Renström F; Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, 214 28, Malmö, Sweden.
  • Hallmans G; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
  • Johansson I; Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, 214 28, Malmö, Sweden.
  • Franks PW; Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden.
Sci Rep ; 12(1): 4088, 2022 03 08.
Article en En | MEDLINE | ID: mdl-35260745
ABSTRACT
The present study assessed the temporal associations of ~ 300 lifestyle exposures with nine cardiometabolic traits  to identify exposures/exposure groups that might inform lifestyle interventions for the reduction of cardiometabolic disease risk. The analyses were undertaken in a longitudinal sample comprising > 31,000 adults living in northern Sweden. Linear mixed models were used to assess the average associations of lifestyle exposures and linear regression models were used to test associations with 10-year change in the cardiometabolic traits. 'Physical activity' and 'General Health' were the exposure categories containing the highest number of 'tentative signals' in analyses assessing the average association of lifestyle variables, while 'Tobacco use' was the top category for the 10-year change association analyses. Eleven modifiable variables showed a consistent average association among the majority of cardiometabolic traits. These variables belonged to the domains (i) Smoking, (ii) Beverage (filtered coffee), (iii) physical activity, (iv) alcohol intake, and (v) specific variables related to Nordic lifestyle (hunting/fishing during leisure time and boiled coffee consumption). We used an agnostic, data-driven approach to assess a wide range of established and novel risk factors for cardiometabolic disease. Our findings highlight key variables, along with their respective effect estimates, that might be prioritised for subsequent prediction models and lifestyle interventions.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfermedades Cardiovasculares / Exposoma Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Humans Idioma: En Revista: Sci Rep Año: 2022 Tipo del documento: Article País de afiliación: Suecia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfermedades Cardiovasculares / Exposoma Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Humans Idioma: En Revista: Sci Rep Año: 2022 Tipo del documento: Article País de afiliación: Suecia