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Does a High Sugar High Fat Dietary Pattern Explain the Unequal Burden in Prevalence of Type 2 Diabetes in a Multi-Ethnic Population in The Netherlands? The HELIUS Study.

Merel J HuismanSabita S Soedamah-MuthuEsther VermeulenMirthe MuilwijkMarieke B SnijderMary N NicolaouIrene G M van Valkengoed
Published in: Nutrients (2018)
The risk for type 2 diabetes (T2D) in ethnic minorities in Europe is higher in comparison with their European host populations. The western dietary pattern, characterized by high amounts of sugar and saturated fat (HSHF dietary pattern), has been associated with a higher risk for T2D. Information on this association in minority populations is scarce. Therefore, we aimed to investigate the HSHF dietary pattern and its role in the unequal burden of T2D prevalence in a multi-ethnic population in The Netherlands. We included 4694 participants aged 18-70 years of Dutch, South-Asian Surinamese, African Surinamese, Turkish, and Moroccan origin from the HELIUS study. Dutch participants scored the highest on the HSHF dietary pattern, followed by the Turkish, Moroccan, African Surinamese, and South-Asian Surinamese participants. Prevalence ratios (PR) for T2D were then calculated using multivariate cox regression analyses, adjusted for sociodemographic, anthropometric, and lifestyle factors. Higher adherence to an HSHF diet was not significantly related to T2D prevalence in the total study sample (PR 1.04 high versus low adherence, 95% CI: 0.80-1.35). In line, adjustment for HSHF diet score did not explain the ethnic differences in T2D. For instance, the PR of the South-Asian Surinamese vs. Dutch changed from 2.76 (95% CI: 2.05-3.72) to 2.90 (95% CI: 2.11-3.98) after adjustment for HSHF. To conclude, a western dietary pattern high in sugar and saturated fat was not associated with T2D, and did not explain the unequal burden in prevalence of T2D across the ethnic groups.
Keyphrases
  • risk factors
  • type diabetes
  • physical activity
  • weight loss
  • cardiovascular disease
  • metabolic syndrome
  • south africa
  • healthcare
  • glycemic control
  • body composition
  • insulin resistance
  • data analysis