Monday, February 23, 2015

Nutrients, Food and Eating Patterns

Nutrients vs. Food

A response to the meta-analysis by Harcombe, et al is that we should focus on foods rather than nutrients, sometimes implying that modern conventional dietary advice successfully does this.  This type of response is couched as a sort of acceptance of the paper (in so far as not directly arguing against the results), but serves to shift the topic elsewhere.

I agree that research and recommendations should be based on food rather than nutrients.  It’s difficult to translate the effects of nutrients to foods, and it’s very reductionist and illogical to generalise the proposed effect of a nutrient on disease to foods high in that nutrient, as doing so ignores the other nutrients in food or other factors of the disease, yet alone any nutrient interactions.

The recommendation to reduce intake of dietary cholesterol is a good example of the issues of making dietary recommendations based on nutrients rather than food.  Eggs, offal and certain seafoods are among the most nutrient dense foods*, but also happen to be rich sources of dietary cholesterol, resulting in previous dietary recommendations to limit their consumption.  So it’s good news that the USDA dietary guidelines are planning to catch up to the rest of the world** by no longer considering dietary cholesterol ‘a nutrient of concern’.  Hopefully it doesn’t take too long before this information becomes widespread.

The problem is that most conventional dietary advice is still largely about single nutrients such as SFA and salt*** (both of which has poor evidence against them), rather than food.  The advice to reduce SFA is perhaps the single most influential recommendation in conventional dietary advice.  It provides the basis to recommend low fat dairy and lean meats over full fat dairy and fattier cuts of meat; to recommend margarine and vegetable oils instead of butter and animal fats; and to emphasise plant foods over animal foods.  So it should hardly be surprising that meta-analyses continue to be written that focus on single nutrients, especially SFA.

* These foods also comprise most of the very short list of foods that are rich in choline, a nutrient only ~6% of adult Americans exceed the recommendation for [1].  It could easily be argued that the advice to reduce dietary cholesterol is largely responsible for widespread insufficient intakes of choline

** For example, this seems to be all the Australian Dietary Guidelines (2013) has to say on dietary cholesterol is this: “Eating cholesterol does not necessarily increase cholesterol in human blood plasma because when it is absorbed the liver tends to reduce its own endogenous cholesterol synthesis” and “There do not appear to be any increased health risks associated with consumption of eggs. There is recent evidence to suggest that consumption of eggs every day is not associated with increased risk of coronary heart disease” [2]

*** Not to mention widespread assumptions based on the lipid hypothesis.  Sometimes it seems like half the Australian Dietary Guidelines is about whether a food or some component in food influences some measure of blood lipids.

Eating Patterns

Unfortunately this type of response really just moves on to discuss ‘eating patterns’, such as the Mediterranean diet, which isn’t the answer either

When discussing eating patterns, many people simply recite a list of foods, which are no doubt healthier than the SAD/SWD, but with very little discussion of why certain foods are on or off the list, except for being a part of, or not a part of, the diet of a healthy population.  As such, eating patterns can often be quite susceptible to dogma and be poorly defined, varying from person to person based on each their individual biases, and may not even be a completely accurate representation of the population’s diet they are trying to convey (e.g. the politically correct ‘Mediterranean diet’)

Eating patterns are also quite susceptible to confounding variables, such as lifestyle, environmental and genetic factors.  Due to many dietary differences, research on various eating patterns makes it difficult to determine what foods in a specific eating pattern are good, bad and ok, and therefore how they can be improved.

* The eating pattern approach is one of the basic arguments for Paleo: HGs ate A,B,C, didn’t eat X,Y,Z and had near population wide freedom of disease.  This Paleo argument also suffers from the same issues associated with other eating patterns and vice versa (so no double standards), but has the advantage over other eating patterns as we are more likely to be better adapted to eat a Paleo diet than a Mediterranean/Asian/etc diet (the evolutionary argument).

Brazil’s Dietary Guidelines

This is as good a place as any to mention Brazil’s Dietary Guidelines (2014).  Unlike other national dietary guidelines, Brazil’s dietary guidelines are refreshingly almost free of proposed effects of nutrient/food on disease/blood lipids, although fat, SFA and red meat, are mentioned a little.  The guidelines are written for the average person and are mainly a collection of common sense approaches to eat well, which are outlined in its ‘ten steps to healthy diets’:

1.      Make natural or minimally processed foods the basis of your diet
2.      Use oils, fats, salt, and sugar in small amounts when seasoning and cooking natural or minimally processed foods and to create culinary preparations
3.      Limit consumption of processed foods
4.      Avoid consumption of ultra-processed foods
5.      Eat regularly and carefully in appropriate environments and, whenever possible, in company
6.      Shop in places that offer a variety of natural or minimally processed foods
7.      Develop, exercise and share cooking skills
8.      Plan your time to make food and eating important in your life
9.      Out of home, prefer places that serve freshly made meals
10.  Be wary of food advertising and marketing 

Forget about all the low fat/low carb/gluten free/sugar free/Paleo/etc cupcake binges in your 80:20 rule.  Following these guidelines will most likely get you at least 80% of the benefit of any diet/way of eating/healthy eating pattern.  Brazil’s dietary guidelines are really needed in other countries to simplify food for the average consumer and get them to focus on the things that matter most

Thursday, February 19, 2015

The Harcombe Meta-Analysis

The Meta-Analysis

A new meta-analysis regarding fat and coronary heart disease (CHD) was recently published by Harcombe, et al, titled: ‘Evidence from randomised controlled trials did not support the introduction of dietary fat guidelines in 1977 and 1983: a systematic review and meta-analysis’.  The title pretty much says it all.  This meta-analysis pooled the results from clinical trials that investigated the effects of reduced and/or modified fat* consumption on CHD, but which were also available at the time when the first US and UK dietary guidelines were introduced (1977 and 1983 respectively).  They concluded “…that dietary advice not merely needs review; it should not have been introduced”

The results for total mortality (RR=0.996) and CHD mortality (RR=0.989) can be seen in figure 2 and figure 3 respectively.  For those familiar with the trials/other meta-analyses (or who just read my previous blog post), the results of this meta-analysis shouldn’t be much of a surprise as previous meta-analyses have consistently reported no significant benefit for CHD mortality and total mortality*.  The meta-analysis also raises many good points regarding the limited evidence at the time of the US and UK dietary guidelines: only 2467 men, no women, no pure primary prevention studies and not testing the proposed guidelines.

* The meta-analysis included 5 fat modification trials (RCOT, LAVAT, MRCT, ODHS, SDHS) and only 1 low fat trial (Ball, et al).  They excluded the Finnish Mental Hospital Study (FMHS) and the Anti-Coronary Club for not being randomised)

** Except Mozaffarian, et al for CHD mortality due to their inclusion of FMHS and Skeaff & Miller for total mortality due to their incorrect interpretation of FMHS.

The Responses

As expected many people raised objections to the meta-analysis, most of which trivialised the results of the RCTs and took the position of arguing from the ‘totality of the evidence’, turning their attention to specific observational studies and the lipid hypothesis to support their position on SFA.

Unfortunately, many of the experts discussed the relationship between SFA, cholesterol and CHD as if anything that raises/lowers cholesterol will increase/decrease CHD.  While this assumption is correct some of the time, there are certainly exceptions:

  • CETP increases the total-C:HDL-C ratio, but torcetrapib, a CETP inhibitor, significantly increased CHD events and total mortality in clinical trials [8]
  • Replacing SFA with MUFA reduces the total-C:HDL-C ratio, but the Jakobsen meta-analysis of cohort studies found that doing so is associated with an increased risk of CHD events [5] (you can use the Jakobsen meta-analysis to support PUFA consumption, but not to vilify SFA)
  • With the exception of DART, in all of the main diet heart trials the experimental group lowered their cholesterol, but this didn’t translate into reduced CHD in the better controlled trials: near significant (P = 0.05-0.10) increase in major CHD events in RCOT; no difference in major CHD events and CHD mortality in MRCT; significant increase in CHD mortality in SDHS; and a 31% increase in CHD events among women in MCS 

Most of the evidence from observational studies they provided comes from ecological studies (both geographical and temporal), which is a poorer quality type of observational study that’s more susceptible to confounding variables.  However, the evidence from recent meta-analyses of observational studies (usually cohort studies) find that: (1) SFA intake is not associated with CHD [1] [2] [3] [4]; (2) PUFA may or may [5] [6] not be [1] [3] [4] inversely associated with CHD; and (3) meta-analyses that find PUFA is inversely associated with CHD do so regardless of whether SFA, carbohydrate, and probably also MUFA, is replaced with PUFA [5] [6].  The observational evidence of non-specific benefit for PUFA may be due to nuts (or at least what nuts replace) rather than vegetable oils [7] and is not that relevant to SFA consumption, particularly because Jakobsen found a minor increased risk in CHD when SFA was replaced with MUFA or carbohydrate [5].

Some of the objections related to dietary adherence, arguing essentially that (1) we don’t know what the participants were eating and (2) that it’s difficult to get people to eat differently.  The first point equally applies to observational studies, which are notorious for their inaccuracies.  The second point is true of most trials, but not these ones where compliance was really good (see table below), suggesting the ‘experts’ and other people commenting haven’t actually read the original papers.


Target
Average Reported Intake
RCOT
80g of olive/corn oil
58g olive oil and 64g corn oil
LAVAT
40% fat with 2/3 from vegetable oils
Adherence was approximately 80%
MRCT
85g soybean oil
80g soybean oil
ODHS
High soybean oil
28% of calories from soybean oil
SDHS
SFA intake 10%, PUFA intake ≥15% of total calories
SFA intake 8.9%, PUFA intake 15.1%
Low Fat (Ball, et al)
40g fat
45g fat (control group was 110-130g)

Saturday, February 14, 2015

Intro to the Diet Heart Trials

The lipid hypothesis led to the development of cholesterol lowering drugs and cholesterol lowering diets as a means to try and reduce the incidence of coronary heart disease (CHD).  The efficacy of cholesterol lowering diets (low SFA, high PUFA, low dietary cholesterol) were tested in several clinical trials, many of which took place approximately 50 years ago.  Five main meta-analyses have pooled the results of these clinical trials, but have come to different conclusions (see table below).


CHD Events
CHD Mortality
Total Mortality
0.83 (0.69-1.00)
P = 0.073
0.84 (0.62-1.12)
P = 0.335
0.88 (0.76-1.02)
P = 0.005
0.81 (0.70-0.95)
P = 0.008
0.80 (0.65-0.98)
P = ???
0.98 (0.89-1.08)
P = ???
1.13 (0.84-1.53)
P = 0.43
1.17 (0.82-1.68)
P = 0.38
1.16 (0.95-1.42)
P = 0.15
0.78 (0.65-0.93)
P = 0.005
0.81 (0.64-1.03)
P = 0.08
0.92 (0.80-1.06)
P = 0.25
0.82 (0.66-1.02)
P = 0.073
0.92 (0.73-1.15)
P = 0.46
1.02 (0.88-1.18)
P = 0.81
0.77 (0.57-1.03)
P = 0.077
0.98 (0.76-1.27)
P = 0.88
0.97 (0.76-1.23)
P = 0.78
0.86 (0.69-1.07)
P = ???
-
-
* Ramsden, et al categorised trials as replacing SFA with either just omega 6 PUFA (n-6) or both omega 6 and omega 3 PUFA (n-6+3) and performed a separate analysis for each category
** Hooper, et al categorised trials modified fat (replacing SFA with MUFA and/or PUFA) or both modified fat and reduced fat and performed a separate analysis for each category.  The primary outcome measures in Hooper, et al were cardiovascular events, cardiovascular mortality and total mortality (rather than CHD events and CHD mortality)
*** Chowdhury, et al did not analyse CHD mortality or total mortality

All the meta-analyses, except Ramsden, et al (n-6), found a significant (P < 0.05) or near significant (P < 0.10) reduction in CHD events in the order of approximately 20%.  Only Mozaffarian, et al and Ramsden, et al (n-6+3) found a significant or near significant reduction in CHD mortality.  And only Skeaff & Miller found a significant reduction in total mortality, with the hazard ratios in other meta-analyses being very close to 1.0 on average.

The different results between the meta-analyses is partially due to differences in the trials each of them included.  There are nine trials that have been included in at least two of the meta-analyses and only five of the nine trials were included by all of them.  In addition Ramsden, et al and Hooper, et al performed separate analyses based on their categorisation of the trials.  The trials, their inclusion in meta-analyses and how they are categorised in Ramsden, et al and Hooper, et al is shown in the table below.

* Categorised as an omega 6 (6) or omega 6+3 trial (6+3)
** Categorised as a fat modification (M) or fat modification and reduced fat trial (M,R)
*** Hooper, et al was the only meta-analyses that included other trials not listed in this table.  They included four small trials, a feasibility study (The National Diet Heart Study), two trials testing the effect of a Mediterranean diet (The MeDiet and one by Sondergaard, et al), and one which tested the effect of linoleic acid on complications of diabetes (Houtsmuller, et al)

Sunday, February 1, 2015

Do Nuts Explain the Inverse Association Between PUFA and CHD?

After looking at the observational studies regarding saturated fat (SFA) and coronary heart disease (CHD) two things stuck out: (1) SFA wasn’t associated with CHD; and (2) PUFA was sometimes inversely associated with CHD (which may depend somewhat on whether the Harvard School of Public Health is writing the meta-analysis).

One could dismiss the results by taking the approach of correlation ≠ causation, observational studies have confounding variables, etc [1].  But the inverse association could also be real (not due to confounding variables) and then if so, what is the effect caused by?  The observational studies look at PUFA, SFA, etc, but we don’t eat nutrients, we eat food.  What does replacing PUFA with SFA or CHO translate to when we think about foods consumed in a population?

Vegetable oils are a major source of PUFA, but this inverse association between PUFA and CHD (assuming it’s real) is probably not due to vegetable oils.  The clinical trials that tested replacing SFA with vegetable oils show that it takes a multifactorial diet (ODHS, STARS), a higher intake of trans fats and higher use of cardiotoxic drugs in the control group (FMHS) or a vitamin E deficient control diet (LA Vets) for there to be any benefit regarding CHD events/mortality (total mortality is another story).  When these things are absent, or near absent (RCOT, MRC, SDHS, MCS, DART), there is no difference on average.

Another major source of PUFA could be nuts as they are very dense sources of PUFA by weight and have a relative high proportion of their calories come from PUFA.  So it’s easy to see how even a ‘small’ quantity of nuts by weight can strongly influence PUFA intake.  (Remember that high PUFA intake is 10% of total calories, which is 22g of PUFA in a 2,000 calorie diet)


PUFA per 100g
PUFA % of Energy
Calories per 100g
Almonds
12.8
24.4
598
Walnuts
49.6
75.0
694
Cashew
7.8
15.9
635
Pistachio
15.8
32.7
571
* Data from NUTTAB (post)

Observational studies have generally shown nuts to be fairly strongly inversely associated with CHD, often having one of the strongest inverse associations among all foods tested [2] [3].  The strong inverse association between nuts and CHD may then be diluted by other things high in PUFA like vegetable oils, resulting in the weaker association between PUFA and CHD


Comparison
RR (CI)
Mente, et al (2009) [2]
High vs. low
0.70 (0.57-0.82)
Kelly & Sabate (2006) [3]
High vs. low
0·63 (0.51-0.83)
Kelly & Sabate (2006) [3]
Unit* per week
-8.3%
* Probably an ounce (28.3g)

Assuming this association is also not due to confounders, why are nuts inversely associated with CHD?  On paper nuts don’t have much going for them.  Compared to other whole foods they are low in protein and have the lowest nutrient density per calorie [4] [5], a really high omega 6:3 ratio and a very high energy density.

There are some proposed mechanisms for how nuts may be cardioprotective, which are outlined in these papers* [6] [7].  One of the most commonly mentioned mechanism is that nuts (and seeds) are high in arginine, which is a precursor of nitric oxide, which promotes endothelial function.

However, the effects of supplemental arginine are often minor and/or inconsistent [8] and while nuts (and seeds) have a very high proportion of arginine relative to total amino acids (~13-14% vs. ~6-8% in other whole foods) they aren’t good sources of protein so total arginine is average (although the ratio may be more important).  Also, many of the other mechanisms (such as inflammation) probably also apply to other whole foods.  It could simply be that as most of time, most people eat nuts as a snack, which could mean displacing other snack foods**, which are often highly processed, very low in nutrients and may contain questionable ingredients

In summary:

  • Nuts may reduce the risk of CHD, as there’s certainly a strong inverse association in observational studies, but this may depend on what they replace
  • The strong inverse association between nuts and CHD may explain the weaker inverse association between PUFA and CHD in observational studies 

* The authors of these papers have been funded by industry 

** This is similar to observational studies showing a benefit of whole grains probably because they replaced refined grains