Monday, March 5, 2012

Natural fats do not negatively influence cholesterol

Background: In October 2011, the British Journal of Nutrition published a guest editorial by 13 scientists (Pedersen et al). In this article, they explain the importance of reducing saturated fat intake to limit heart disease risk (1). Because I found that the base of their information was scientifically incorrect, I decided to write a so-called "letter to the editor", which was also published (2). This was followed by a response by Pedersen et al (3) and again, by a response from me (4). All responses got published in the British Journal of Nutrition.

The articles contain a lot of information, so I decided to go for a stepwise analysis of the contents.

Pedersen et al are concerned that saturated fatty acids (SFA) may no longer be considered an important cause of coronary heart disease (CHD):

Uncertainty has recently been expressed as to the role of SFA for the development of atherosclerosis and CHD.
Our main concern, however, is to emphasise the importance of lowering SFA intakes to reduce blood LDL-cholesterol levels at a time when there are tendencies to downplay the importance of SFA.
I was surprised about the 2nd sentence, because the importance of HDL-cholesterol in this association was not mentioned. Two (Katan MB and Mensink RP) of the 13 scientists involved have published an article in the past (5). The conclusions in that article seem completely opposite to their current conclusion. In a meta-analysis of 60 controlled trials they found that replacing carbohydrates by saturated fats will increase both "bad" LDL-cholesterol levels and "good" HDL-cholesterol levels, without changing the ratio total/HDL-cholesterol. Based on this they stated that:
Results suggest that isoenergetic replacement of SFA with carbohydrates does not improve the serum total:HDLcholesterol. All natural fats contain both SFA, which do not  change this ratio, and unsaturated fatty acids, which lower it. As a result, even the replacement of dairy fat and tropical fats with carbohydrates will increase the ratio of total  to HDL-cholesterol.
This can be seen in the following figure they added:


The authors gave us 2 warnings:
Results of prospective observational studies, controlled clinical trials with drugs, mechanistic studies, and genetic 'experiments of nature' all strongly suggest that high concentrations of HDL-cholesterol in the circulation help to prevent coronary artery disease and other CVD. Given these observations, it appears imprudent to ignore the marked effects of diet on HDL-cholesterol.

The effects of dietary fats on total:HDL-cholesterol may differ markedly from their effects on LDL. The effects of fats on these risk markers should not in themselves be considered to reflect changes in risk but should be confirmed by prospective observational studies or clinical trials.
And in 2007, a meta-analysis of 61 prospective studies article was published in the Lancet (6). The authors concluded that including HDL-cholesterol increased the predictive value of non-HDL cholesterol (LDL-cholesterol) for ischemic heart disease (IHD):
Of various simple indices involving HDL cholesterol, the ratio total/HDL cholesterol was the strongest predictor of IHD mortality (40% more informative than non-HDL cholesterol and more than twice as informative as total cholesterol).

Conclusion:  In 2003, Katan MB and Mensink RP concluded that even animal fats will have a positive effect on the ratio total/HDL cholesterol, compared to carbohydrates. They stressed that the effect from dietary fats on HDL-cholesterol should not be ignored and that effects on cholesterol should not in themselves be considered to reflect changes in heart disease risk.
In 2011, the authors completely changed their mind, while they did not reject de results they published earlier. All of a sudden, changes in LDL-cholesterol - and LDL-cholesterol only - are supposed to be the single one predictor of changes in heart disease risk.



References:
1) Pedersen JI et al. (2011) The importance of reducing SFA to limit CHD. Br J Nutr 106, 961-963. http://www.ncbi.nlm.nih.gov/pubmed/21906408
2) Hoenselaar R (2011). The importance of reducing SFA intake to limit CHD risk. Br J Nutr. 2012 Feb;107(3):450-1; author reply 452-4. http://www.ncbi.nlm.nih.gov/pubmed/22136957
3) Pedersen JI et al (2012). Response to Hoenselaar from Pedersen et al. Br J Nutr 107, 452-454. http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=8479188
4) Hoenselaar R (2012). Further response from Hoenselaar. Br J Nutr [Epub ahead of print]
http://www.ncbi.nlm.nih.gov/pubmed/22377374
5) Mensink RP et al (2003). Effects of dietary fatty acids and carbohydrates on the ratio of serum total to HDL cholesterol and on serum lipids and apolipoproteins: a meta-analysis of 60 controlled trials. Am J Clin Nutr. 2003 May;77(5):1146-55. http://www.ajcn.org/content/77/5/1146.long
6) Prospective Studies Collaboration (2007) Blood cholesterol and vascular mortality by age, sex, and blood pressure: a meta-analysis of individual data from 61 prospective studies with 55,000 vascular deaths. Lancet 370, 1829-1839. http://www.ncbi.nlm.nih.gov/pubmed/18061058

Reacties:

2 reacties:

Bog said...

It seems you do not understand the difference between risk predictor vs. causal factor. Poverty and HDL-C are risk predictors for CHD, they are not causally related to the risk of CHD. Giving money to the poor or an attempt to elevate HDL-C does not translate to lower risk of CHD. HDL-C is a warning sign. Low HDL-C at the context of high SFA and dietary cholesterol diets (the typical Western fare) just merely indicates that one is overweight. However, in places where CHD have been exceptionally low, such as rural China, people had very low levels of HDL-C. These people consumed a diet very low in SFA and dietary cholesterol (Campbell et al 1993)

Some fractions in HDL may be causally related to heart disease risk, but not HDL-C itself. People carrying a certain mutation in their HDL cholesterol, ApoA-1 Milano, live very long and have low rates of heart disease, despite they have elevated triglycerides and low HDL-C.
http://en.wikipedia.org/wiki/ApoA-1_Milano

The LDL-C story is ofcourse very different.

A meta-analysis of 108 randomized controlled trials of various medical and dietary based lipid modifying interventions has established that lowering LDL cholesterol significantly decreases the risk of coronary heart disease and all-cause mortality, independent of changes to HDL cholesterol and triglycerides, and non-lipid effects of specific drugs
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2645847/

Recently a meta-analysis of mendelian randomization studies with over 312,000 individuals found that inheriting any of nine studied genetic variants that modify lifelong LDL cholesterol concentrations, but not any other known risk factors predicted a 55% lower risk of coronary heart disease for each mmol/l (38.7 mg/dl) lower LDL cholesterol. If the LDL hypothesis is incorrect this would suggest that all 9 studied genetic variants lower the risk of coronary heart disease by some yet undiscovered mechanism, and that it just happens to be a one in trillion coincidence that all 9 genetic variants lower the risk of coronary heart disease in perfect proportion to the degree in which they lower the concentration of LDL cholesterol.




Zahc said...

Bog says: "It seems you do not understand the difference between risk predictor vs. causal factor."

It seems you don't understand it yourself. LDL-C is also a predictor not necessarily a causal factor. Indeed, just as HDL-C may not be a causal factor, LDL-C also may not be a causal factor.

Bog cites this study - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2645847/. Which by the way was a meta-regression analysis which is observational in nature and cannot establish casualty. Indeed the authors recognized this stating:

"Nevertheless, the relation described by a meta-regression is observational—that is, although the original studies may be randomised trials, a meta-regression across trials does not have the benefit of randomisation to support a causal interpretation and thus risks bias by confounding. "

The phrase "Garbage in, Garbage out" applies here.



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