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Effect of the dietary fat quality on insulin sensitivity

British Journal of Nutrition, ISSN: 0007-1145, Vol: 100, Issue: 3, Page: 471-479
2008
  • 123
    Citations
  • 0
    Usage
  • 129
    Captures
  • 2
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    123
  • Captures
    129
  • Mentions
    2
    • News Mentions
      2
      • News
        2

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Article Description

Recent evidence shows that specific fatty acids affect cell metabolism, modifying the balance between fatty acid oxidation and lipogenesis. These effects may have important implications in addressing the present epidemic of nutrition-related chronic disease. Intake of dietary saturated and n-6 PUFA have increased while n-3 fatty acid intake has decreased. Obesity, type 2 diabetes and insulin resistance are highly prevalent, and both are strongly related to disorders of lipid metabolism characterized by an increased plasma and intracellular fatty acid availability. Thus, it has been hypothesized that change in the quality of dietary fat supply is able to modify the degree of insulin sensitivity. Animal studies provide support for this notion. However, there is limited human data either from normal or diabetic subjects. This review aims to analyse human studies that address this question. To this purpose, the experimental design, dietary compliance, insulin-sensitivity method used and confounding variables are discussed in order to identify the role of dietary fat quality as a risk factor for insulin resistance. Most studies (twelve of fifteen) found no effect relating to fat quality on insulin sensitivity. However, multiple study design flaws limit the validity of this conclusion. In contrast, one of the better designed studies found that consumption of a high-saturated-fat diet decreased insulin sensitivity in comparison to a high-monounsaturated-fat diet. We conclude that the role of dietary fat quality on insulin sensitivity in human subjects should be further studied, using experimental designs that address the limitations of existing data sets. © The Authors 2008.

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