4.5 Article

How do short-term associations between diet quality and metabolic risk vary with age?

期刊

EUROPEAN JOURNAL OF NUTRITION
卷 60, 期 1, 页码 517-527

出版社

SPRINGER HEIDELBERG
DOI: 10.1007/s00394-020-02266-5

关键词

DASH; Adolescent; Early adulthood; Diet quality; Metabolic syndrome; Cardiovascular risk

资金

  1. Centre for Diet and Activity Research (CEDAR), a UKCRC Public Health Research Centre of Excellence [RES-590-28-0002]
  2. British Heart Foundation
  3. Wellcome Trust
  4. Department of Health
  5. Economic and Social Research Council
  6. Medical Research Council
  7. UK Clinical Research Collaboration
  8. Medical Research Council [MC_UU_12015/7]
  9. MRC [MC_ UU_12015/5]
  10. NIHR Biomedical Research Centre Cambridge: Nutrition, Diet, and Lifestyle Research Theme [IS-BRC-1215-20014]
  11. MRC [MC_UU_00006/3, MR/K023187/1, MC_UU_00006/5, MC_UU_12015/5, MC_UU_12015/7] Funding Source: UKRI

向作者/读者索取更多资源

The study found differences in the associations between diet quality and metabolic risk across different age groups, especially showing significant attenuation in adolescents and young adults. This suggests that the mechanisms by which diet impacts metabolic risk may vary with age.
Purpose Poor diet quality is one of the key contributors to poor cardiovascular health and associated morbidity and mortality. This study aimed to assess how the short-term associations between diet quality and metabolic risk factors change with age. Methods This longitudinal, observational study used data from the National Diet and Nutrition Survey (2008-2016) (n = 2024). Diet quality was measured using the Dietary Approaches to Stop Hypertension (DASH) index, fruit and vegetable (F&V) intake, and a F&V biomarker score. We assessed associations between measures of diet quality and a metabolic risk z score (generated from five metabolic risk factors) among those aged 11-60 years, and then tested effect modification by age group (adolescents 11-18 years, young adults 19-35 years, mid-aged adults 36-60 years). Results Analysis across all age groups showed inverse associations between standardised DASH index and metabolic risk z score of - 0.19 (95% CI - 0.26, - 0.11). These associations were moderated by age group, with strong associations seen in mid-aged adults: - 0.27 (95% CI - 0.39, - 0.16), but associations were significantly attenuated in young adults [- 0.10 (95% CI - 0.22, 0.01)] and adolescents [0.03 (95% CI - 0.05, 0.11)]. Similar results were found for F&V intake and F&V biomarker score. Conclusions Short-term associations between diet quality and metabolic risk are not consistent across adolescent and young adult age groups, suggesting that mechanisms by which diet impacts on metabolic risk may be acting differently in younger age groups compared to adults. Further research is warranted using longitudinal study designs and replication in different populations to understand changes in determinants of cardiometabolic health with age.

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