Wednesday, April 15, 2015

Looking Back on the Latest AHSNZ Conference, and Moving Forward to the Next One

Surviving the Urban Jungle

A couple of weeks ago I had the pleasure of attending a conference in Wellington organised by the Ancestral Health Society of New Zealand (AHSNZ) called ‘Surviving the Urban Jungle’.  See the programme below:

Survival of the Fittest: Lessons from the Christchurch Earthquakes
Jamie Scott, Health Researcher, Synergy Health, Christchurch

Whakapapa or fatness? Assessing physical health and performance with measures that matter
Dr Isaac Warbrick, PhD, Auckland University of Technology, Auckland

Our love affair with speed: Why it really isn’t sexy
Lulu Loya Wu, Health Coach, Wellington

Fertility vs Famine – A delicate balance of survival
Kate Callaghan, Nutritionist, Wanaka

Surviving modernity’s ‘fadism': Exploring the ethics of ancestral health
Andrew Dickson, PhD, Massey University, Palmerston North

Weight loss: The pot of gold at the end of the rainbow
Dr Anastasia Boulais, Medical Practitioner, Christchurch

ANCESTRAL MOVEMENT WORKSHOP
Max Bell
Shelley Bell
Jason Young

In particular, Jamie’s and Andrew’s talks really struck a chord with me.  Jamie’s talk was powerful and his message of being physically and mentally prepared for a natural disaster (or similar situations) is one that is quite unique.  Andrew’s talk offered insights on the pillars of modern faddism and methods to resist faddism, which is particularly relevant given the current state of Paleo

The movement workshop was fun and featured some basic parkour and mobility (don't be put off by the dramatic youtube videos of parkour, it's actually very scalable)

* The society has also previously organised two other conferences: the first in Christchurch called ‘Ancient Genes vs. Modern World’; and the second in Wanaka called ‘Health of the Land, Health of the People

Looking Back, Moving Forward

The society is also holding an international symposium in October at Queenstown called “Looking Back, Moving Forward”.  Among the impressive speakers list, made up a large number of professionals and academics, you’ll find many well-known people in the Paleo/Ancestral Health community, but also many people who aren’t.  A broad range of topics will be covered, such as diet, physical activity, urban design, indigenous health, sustainability and climate change.  This quote from the Whole 9 South Pacific facebook page sums up my thoughts about the event as well:

“Far from choir-preaching, this event has the ability to bring together many professionals whose work has never been appreciated by the ancestral community before. And, of course, there will be some of the very well known names. Check out the speaker line up”

Jamie was kind enough to invite me (a relative nobody) to be one of the speakers.  My talk will be based on my research on saturated fat and coronary heart disease (which I’m planning to publish as a meta-analysis around the middle of the year). 

You can register here.  There’s also information on how to get there, where to stay and what else you can do around Queenstown (if you can, turn the trip into a holiday, Queenstown is a great place for that)

Sunday, April 5, 2015

Paleolithic Diet Trials: Masharani, et al (2015)


Participants and Diets

25 adults aged 50-69, with type 2 diabetes, were randomised to follow a Paleo diet or the American Diabetes Association diet.  Three meals and three snacks were provided.  An attempt to avoid weight loss was made by calculating maintenance energy needs and then adjusting calorie intake if 3lb (~1.35kg) of weight loss occurred.

“The Paleo diet consisted of meat, fish, poultry, eggs, fruit, vegetables, tree nuts, canola oil, mayonnaise and honey. We excluded dairy products, legumes, cereals, grains, potatoes and products containing potassium chloride. Some foods, such as mayonnaise, carrot juice and domestic meat, were not consumed by hunter gatherers but contain the general nutritional characteristics of pre-agricultural foods.”

In addition, there were 3 ramp up diets for 7 days for those in the Paleo group to “allow for adaptation of the subjects’ intestinal tract and potassium handling systems to adjust to the markedly higher dietary content of the fiber and potassium in the Paleo diet”

The ADA diet is not defined in the paper except for “…containing moderate salt intake, low-fat dairy, whole grains and legumes”, as opposed to the exclusion of these foods in the Paleo diet (excluding added salt, not all salt).  There is also no measurement of what the participants ate, except for macronutrients and some micronutrients.  Calorie intake was identical and macronutrient ratios were fairly similar although the Paleo group had slightly lower protein, fat and SFA; and slightly higher carbohydrate and MUFA.


ADA
Paleo
Energy (kcal)
3000.5
3001.5
Pro:Fat:Carb (%)
20.3:28.8:54.4
18.5:27.0:58.2
SFA:MUFA:PUFA (%)
6.4:13.8:6.1
3.6:14.8:6.3
Sodium (mg)*
4112
1580
Potassium (mg)*
6337
12246
Calcium (mg)
1998
932
Fibre (g)**
15g
42g
* The figures for sodium and potassium intake in the Paleo group are in mmol (the unit they reported), while those for the ADA group seem to be in mg
** The fibre intake in the Paleo group is what you would expect with 3000 calories, a high carbohydrate diet and most of the carbohydrates coming from fruit and vegetables.  The fibre intake in the ADA group is very low and if it’s correct, then the ADA group were probably eating a lot of refined grains rather than whole grains

Results

Glucose control: fasting glucose significantly decreased in the Paleo group, with no change in the ADA group, although the difference between the groups was only P=0.3.  Consequently, fructosamine, a short term marker of glycemic control, significantly decreased in the Paleo group, with no change in the ADA group and a near significant difference between the groups (P=0.06).  HbA1c significantly decreased in both groups, despite no improvement in fasting glucose and fructosamine in the ADA group.  Both groups had minor improvements in insulin sensitivity (P = 0.1 and 0.09 respectively), although among the most insulin resistant participants, those in the Paleo group, but not the ADA group, had a significant improvement in insulin sensitivity (see figure below)

Blood lipids: both groups had decreases in HDL-C, probably due to lower fat intake.  The Paleo group, but not the ADA group, had significant decreases in total-C and LDL-C probably due to both the very low SFA intake and high fibre intake.  Triglycerides almost significantly decreased in the Paleo group, but not the ADA group, despite higher carbohydrate intake and no difference in weight loss and baseline triglycerides, which may be due to high fibre intake.


ADA Diet
Paleo Diet
P Value Between Groups
Difference
P Value
Difference
P Value
Weight (kg)
-2.1±1.9
0.004
-2.4±0.7
<0.001
0.7
Systolic blood pressure
-2±13
0.7
-4±12
0.2
0.6
Diastolic blood pressure
0±12
0.9
-1±6
0.4
0.6
Mean arterial pressure
-1±7
0.8
-2±7
0.3
0.6
HbA1c
-0.18±0.24
0.04
-0.30±0.49
0.04
0.5
Fasting glucose (mmol/l)
+0.6±1.8
0.4
-1.3±1.4
0.008
0.3
Fructosamine (mg/dl)
-3±28
0.7
-34±41
0.009
0.06
Insulin sensitivity
+1.0±1.9
0.1
+1.3±2.6
0.09
0.8
Total-C (mg/dl)
-9±25
0.2
-26±27
0.003
0.2
Trigs (mg/dl)
-5±63
0.8
-23±46
0.08
0.5
HDL-C (mg/dl)
-6±8
0.03
-8±7
0.001
0.5
LDL-C (mg/dl)
-7±17
0.2
-15±22
0.02
0.4
Creatinine clearance
-16±29
0.1
-3±29
0.9
0.2
Urine K/Na**
+0.6±0.3
 <0.0001
+2.0±0.8
<0.0001
0.001
Urine pH
+0.1±0.3
0.7
+0.8±0.5
<0.0001
<0.001
Urine Ca/Creatinine
-2±33
0.9
-45±43
0.002
0.008
* Bold = p < 0.05.  Underline = p < 0.10

** The urinary potassium:sodium ratio reflects dietary intake, and therefore can be used as a marker of compliance.  “Calculation of potassium to sodium ratio confirmed that all the patients, except for one, on the Paleo diet were compliant with the diet”

Lastly, after the trial was over the participants seemed to revert back to their old diets (based on urine sodium and potassium) and consequently the reductions in cholesterol and HbA1c were also reverting back to the usual level. 

Tuesday, March 31, 2015

Emphasising 'Randomised' and 'Controlled' in a Meta-Analysis of Randomised Controlled Trials regarding Saturated Fat and Coronary Heart Disease

A key feature of randomised controlled trials is that the groups in the trial are treated identically except for the experimental treatment.  With dietary interventions this is near impossible, although at the very least, clinical trials with a multifactorial diet intervention such as ODHS and STARS should not be considered adequately controlled for the purposes of drawing conclusions regarding the effects of replacing SFA with PUFA.  Arguably none of the trials should be considered well controlled for this purpose due to dietary advice to reduce TFA which only given to the experimental group.  That being said, it is still worthwhile to pool the results of these trials together and categorise them based on how well controlled they were, while acknowledging the issue of unequal advice to reduce TFA intake.

In this post the trials are categorised as ‘adequately controlled’ or ‘inadequately controlled’.   Clinical trials that are categorised as ‘adequately controlled’ are those that most closely approximate a true test of replacing SFA with PUFA, while the clinical trials categorised as ‘inadequately controlled’ have too many dietary and non-dietary differences between the groups to be considered close to a valid test of replacing SFA with PUFA.  Due to the uncertainty regarding TFA intake in SDHS, I’ll have a separate set of results that excludes it.

Below is a summary of the dietary and non-dietary differences between the groups, whether these differences are favourable or unfavourable to the experimental group and whether the clinical trial is assessed as adequately controlled


Dietary and non-dietary differences between the groups
Direction
Adequately Controlled
RCOT
Advice to reduce TFA in experimental group
Favourable
Yes
LAVAT
Higher TFA intake in control group
Lower and insufficient α-tocopherol intake in control group
Favourable
Favourable
No
MRCT
Advice to reduce TFA in experimental group
Favourable
Yes
ODHS
Highly multifactorial diet intervention
Very Favourable
No
SDHS
Advice to reduce TFA in experimental group
High intake of high TFA margarine in experimental group
Favourable
Unfavourable
Unknown
FMHS
Higher intake TFA intake in control group
Higher use of cardiotoxic medication in control group
Favourable
Favourable
No
MCS
Advice to reduce TFA in experimental group
Favourable
Yes
DART
Modestly multifactorial diet intervention
Advice to reduce TFA in experimental group
Slightly Favourable
Favourable
Yes
STARS
Highly multifactorial diet intervention
Very Favourable
No

A few things to note:

  • The results in this post came from the Review Manager V.5.1 software (RevMan), provided by the Cochrane Collaboration
  • E = number of CHD events (multiple events in one participant is counted each time)
  • P = number of participants who have had CHD events (multiple events in one participant is counted once)
  • I included data on CHD mortality from SDHS as CHD events (after all, a death from CHD is a CHD event)
  • For FMHS and MCS I’m using person years to calculate the RR and I’m using the same approach I discussed previously to enter the data from those trials into RevMan
  • I’ve only included the basic 6 forest plots in this blog post.  The ones excluding SDHS and FMHS are in a separate powerpoint

 Major CHD Events (E)

Major CHD Events (P)
 

Total CHD Events (E)

Total CHD Events (P)

CHD Mortality
 

Total Mortality

For a summary of the results see the table below.  Simply pooling the trials together suggests a ~10% reduction in CHD events and CHD mortality which doesn’t reach significance, with no effect on total mortality.  However, differentiating the trials based on whether they are adequately controlled or not tells a different story.  Pooling the results from the trials that are considered adequately controlled results in an RR that is consistently very slightly above 1.0 (not significant) and excluding SDHS from this category lowers the RR to approximately 1.0.  Meanwhile the pooling the results of the inadequately controlled trials results in a highly significant reduction in CHD events and CHD mortality of about 30%, but total mortality isn’t affected, even in this category, which is quite surprising.  Altogether this suggests that it’s extremely unlikely that replacing SFA with PUFA was responsible for the reduction in CHD in the inadequately controlled trials and that it was most likely due to the other differences that are summarised in the table above.

I didn’t do a separate analysis for both groups combined when excluding SDHS because that represents a very biased interpretation of these trials, one that criticises and excludes SDHS based on potential differences in TFA intake, while ignoring all the cases of higher TFA intake in the control group and other differences between the groups.  Unfortunately this is a common approach among those who promote conventional dietary advice.  A comment by Zahc sums up this attitude well “It seems that you are assuming that fat modification is beneficial, and therefore negative results must mean that the trial is flawed”


Adequately Controlled Trials
Inadequately Controlled Trials
Total
Adequately Controlled Trials – SDHS
Major CHD Events (E)
1.07 (0.87-1.32)
P = 0.53
0.68 (0.52-0.88)
P = 0.004
0.90 (0.74-1.10)
P = 0.31
0.99 (0.82-1.20)
P = 0.96
Major CHD Events (P)
1.07 (0.87-1.32)
P = 0.53
0.67 (0.49-0.92)
P = 0.01
0.92 (0.75-1.11)
P = 0.38
0.99 (0.82-1.20)
P = 0.96
Total CHD Events (E)
1.03 (0.85-1.25)
P = 0.75
0.69 (0.58-0.82)
P < 0.0001
0.86 (0.73-1.03)
P = 0.10
0.96 (0.81-1.13)
P = 0.62
Total CHD Events (P)
1.03 (0.85-1.25)
P = 0.75
0.71 (0.59-0.86)
P = 0.0004
0.88 (0.74-1.04)
P = 0.12
0.96 (0.81-1.13)
P = 0.62
CHD
Mortality
1.11 (0.92-1.33)
P = 0.28
0.66 (0.54-0.80)
P < 0.0001
0.88 (0.70-1.10)
P = 0.25
1.04 (0.85-1.26)
P = 0.72
Total
Mortality
1.06 (0.92-1.23)
P = 0.41
0.96 (0.85-1.08)
P = 0.46
1.00 (0.91-1.09)
P = 0.96
1.02 (0.90-1.17)
P = 0.72

Next, I wanted to see the effect of only including adequately randomised trials, thereby excluding FMHS.  I mentioned previously that FMHS strongly influences the result for CHD mortality, being both a large study and quite an outlier, and that excluding FMHS removes the favourable result for CHD mortality.  However, I underestimated its effect on CHD events as removing FMHS increased the RR by ~0.05-0.06 and removed any hint of significance for total CHD events 


Inadequately Controlled Trials
Inadequately Controlled Trials – FMHS
Total
Total - FMHS
Major CHD Events (E)
0.68 (0.52-0.88)
P = 0.004
0.76 (0.63-0.92)
P = 0.005
0.90 (0.74-1.10)
P = 0.31
0.96 (0.80-1.14)
P = 0.61
Major CHD Events (P)
0.67 (0.49-0.92)
P = 0.01
0.79 (0.63-0.98)
P = 0.03
0.92 (0.75-1.11)
P = 0.38
0.97 (0.82-1.15)
P = 0.72
Total CHD Events (E)
0.69 (0.58-0.82)
P < 0.0001
0.72 (0.56-0.92)
P = 0.009
0.86 (0.73-1.03)
P = 0.10
0.92 (0.77-1.11)
P = 0.38
Total CHD Events (P)
0.71 (0.59-0.86)
P = 0.0004
0.76 (0.59-0.98)
P = 0.03
0.88 (0.74-1.04)
P = 0.12
0.94 (0.79-1.11)
P = 0.45
CHD
Mortality
0.66 (0.54-0.80)
P < 0.0001
0.77 (0.59-1.00)
P = 0.05
0.88 (0.70-1.10)
P = 0.25
0.99 (0.83-1.20)
P = 0.95
Total
Mortality
0.96 (0.85-1.08)
P = 0.46
0.89 (0.71-1.12)
P = 0.33
1.00 (0.91-1.09)
P = 0.96
1.00 (0.89-1.13)
P = 0.96