Metabolic Health

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Paper - Meta-analysis of prospective cohort studies evaluating the association of saturated fat with cardiovascular disease - 2010 (doi.org)

submitted 4 days ago* (last edited 3 days ago) by jet@hackertalks.com to c/metabolic_health@lemm.ee

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Conclusions: A meta-analysis of prospective epidemiologic studies showed that there is no significant evidence for concluding that dietary saturated fat is associated with an increased risk of CHD or CVD. More data are needed to elucidate whether CVD risks are likely to be influenced by the specific nutrients used to replace saturated fat.

General Paper Analysis - This is a meta-analysis of epidemiology. While the meta aspect gives great confidence in the results, we have to be mindful that epidemiology is the weakest of scientific data. A pyramid built on sand - as it were.

But as the paper itself says

such studies have caveats, including a reliance on nutritional assessment methods whose validity and reliability may vary (25), the assumption that diets remain similar over the long term (26) and variable adjustment for covariates by different investigators. Nonetheless, a summary evaluation of the epidemiologic evidence to date provides important information as to the basis for relating dietary saturated fat to CVD risk.

Full paper at the link.

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[–] jet@hackertalks.com 1 points 4 days ago* (last edited 3 days ago)

Y Axis is log plot of Relative Risk, closer to zero is less risk (top)

I love the footnote on figure 3:

This indicates publication bias favoring studies with significant results.

[–] jet@hackertalks.com 1 points 4 days ago

Although the Strong Heart Study reported a positive association between saturated fat and CVD in younger than in older individuals (ie, RR = 5.17; 95% CI: 1.6, 16.4), the fully adjusted model that included adjustment for polyunsaturated fatty acids, trans fats, and monounsaturated fatty acids was not statistically significant (RR = 2.98; 95% CI: 0.66, 13.6).

This touches upon the theme of yesterday's paper https://hackertalks.com/post/5676721 , that with large data sets the variables and the groupings of correlation are nearly as important as the data itself.