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Paul Franks

Paul Franks

Principal investigator

Paul Franks

Generalizability of a Diabetes-Associated Country-Specific Exploratory Dietary Pattern Is Feasible Across European Populations

Author

  • Franziska Jannasch
  • Janine Kröger
  • Claudia Agnoli
  • Aurelio Barricarte
  • Heiner Boeing
  • Valerie Cayssials
  • Sandra Colorado-Yohar
  • Christina C. Dahm
  • Courtney Dow
  • Guy Fagherazzi
  • Paul W. Franks
  • Heinz Freisling
  • Marc J. Gunter
  • Nicola D. Kerrison
  • Timothy J. Key
  • Kay Tee Khaw
  • Tilman Kühn
  • Cecilie Kyro
  • Francesca Romana Mancini
  • Olatz Mokoroa
  • Peter Nilsson
  • Kim Overvad
  • Domenico Palli
  • Salvatore Panico
  • Jose Ramón Quirós García
  • Olov Rolandsson
  • Carlotta Sacerdote
  • Mariá José Sánchez
  • Mohammad Sediq Sahrai
  • Ruth Schübel
  • Ivonne Sluijs
  • Annemieke M.W. Spijkerman
  • Anne Tjonneland
  • Tammy Y.N. Tong
  • Rosario Tumino
  • Elio Riboli
  • Claudia Langenberg
  • Stephen J. Sharp
  • Nita G. Forouhi
  • Matthias B. Schulze
  • Nicholas J. Wareham

Summary, in English

BACKGROUND: Population-specificity of exploratory dietary patterns limits their generalizability in investigations with type 2 diabetes incidence. OBJECTIVE: The aim of this study was to derive country-specific exploratory dietary patterns, investigate their association with type 2 diabetes incidence, and replicate diabetes-associated dietary patterns in other countries. METHODS: Dietary intake data were used, assessed by country-specific questionnaires at baseline of 11,183 incident diabetes cases and 14,694 subcohort members (mean age 52.9 y) from 8 countries, nested within the European Prospective Investigation into Cancer and Nutrition study (mean follow-up time 6.9 y). Exploratory dietary patterns were derived by principal component analysis. HRs for incident type 2 diabetes were calculated by Prentice-weighted Cox proportional hazard regression models. Diabetes-associated dietary patterns were simplified or replicated to be applicable in other countries. A meta-analysis across all countries evaluated the generalizability of the diabetes-association. RESULTS: Two dietary patterns per country/UK-center, of which overall 3 dietary patterns were diabetes-associated, were identified. A risk-lowering French dietary pattern was not confirmed across other countries: pooled HRFrance per 1 SD: 1.00; 95% CI: 0.90, 1.10. Risk-increasing dietary patterns, derived in Spain and UK-Norfolk, were confirmed, but only the latter statistically significantly: HRSpain: 1.09; 95% CI: 0.97, 1.22 and HRUK-Norfolk: 1.12; 95% CI: 1.04, 1.20. Respectively, this dietary pattern was characterized by relatively high intakes of potatoes, processed meat, vegetable oils, sugar, cake and cookies, and tea. CONCLUSIONS: Only few country/center-specific dietary patterns (3 of 18) were statistically significantly associated with diabetes incidence in this multicountry European study population. One pattern, whose association with diabetes was confirmed across other countries, showed overlaps in the food groups potatoes and processed meat with identified diabetes-associated dietary patterns from other studies. The study demonstrates that replication of associations of exploratory patterns with health outcomes is feasible and a necessary step to overcome population-specificity in associations from such analyses.

Department/s

  • Genetic and Molecular Epidemiology
  • EpiHealth: Epidemiology for Health
  • EXODIAB: Excellence in Diabetes Research in Sweden
  • Internal Medicine - Epidemiology

Publishing year

2019

Language

English

Pages

1047-1055

Publication/Series

The Journal of nutrition

Volume

149

Issue

6

Document type

Journal article

Publisher

Oxford University Press

Topic

  • Nutrition and Dietetics
  • Public Health, Global Health, Social Medicine and Epidemiology
  • Endocrinology and Diabetes

Keywords

  • diet-disease association
  • dietary patterns
  • meta-analysis
  • principal component analysis
  • replication
  • type 2 diabetes mellitus

Status

Published

Research group

  • Genetic and Molecular Epidemiology
  • Internal Medicine - Epidemiology

ISBN/ISSN/Other

  • ISSN: 1541-6100