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Thursday, 18 May 2017

Fruit and Diabetes - some evidence

It's a commonly discussed paradox of sorts - how can fruit have a negative association with diabetes in epidemiology when it's full of sugar?

Two recent papers from China go some way towards clearing this up in my opinion. One is a prospective study of Type 2 Diabetes risk, in which a difference is seen between different classes of fruit; apples are good, tropical fruits - pineapples, mangos, and bananas are not, but the effect is staggered by gender.[1]

Results: In 494,741 person-years of follow-up, 5207 participants developed T2DM. After adjustment for lifestyle and dietary risk factors, high total fruit consumption was not consistently associated with lower T2DM risk [men: HR of 1.33 (95% CI: 1.04, 1.71) for 3 or more servings/d compared with less than 1 serving/wk (P-trend = 0.17); women: HR of 0.88 (95% CI: 0.71, 1.11) (P-trend = 0.008); P-interaction = 0.003]. The direct association in men was observed for higher–glycemic index (GI) fruit [HR: 1.51 (95% CI: 1.22, 1.86) for 1 or more serving/d compared with rarely consumed; P-trend = 0.001] but not for lower or moderate GI fruit. In women, the consumption of temperate fruit, but not of subtropical or tropical fruit, was associated with lower T2DM risk [HR: 0.79 (95% CI: 0.67, 0.92) for 1 or more serving/d compared with rarely; P-trend = 0.006].

Conclusions: The consumption of temperate fruit, such as apples, was associated with a lower risk of T2DM in women, whereas the consumption of higher-GI fruit, such as bananas, was associated with higher risk in men. The impact of fruit consumption on the risk of diabetes may differ by the type of fruit, which may reflect differences in the glycemic impact or phytochemical content.

A second Chinese paper looked at fruit consumption in the second trimester and risk of gestational diabetes.[2] (This was posted by gestational diabetes expert Lily Nichols @LilyNicholsRDN on her blog)

As epidemiology goes, this paper has signs of class - look at table 1, where they have actually gone to the trouble to check that their respondents are representative of the whole population canvassed by giving the baseline characteristics of the people who didn't want too be in the study, who are well-matched with the people they included. This is textbook stuff, but I can't remember the last time I saw it done. Fruit intake was fairly high - 740g a day in the upper quartile.

An increase in total fruit consumption during the second trimester was associated with an elevated likelihood of GDM (highest vs. lowest quartile: crude OR, 3.20; 95% CI, 1.83 to 5.60). After adjustment for age, education, occupation, income level, pre-pregnancy BMI, gestational weight gain, family history of diabetes, smoking status and alcohol use in Model 1, a significantly higher likelihood of GDM was still observed in the third and fourth quartiles for total fruit consumption (OR 2.81; 95% CI 1.47 to 5.36; OR 3.47; 95% CI 1.78 to 6.36, respectively). After adjustment for potential confounding factors in Model 1 plus the consumption of grain, vegetables, meat and fish, the ORs for the lowest to the highest quartiles of fruit consumption were 1.00 (reference), 1.08 (95% CI 0.50 to 2.34), 3.03 (95% CI 1.54 to 5.94) and 4.82 (95% CI 2.38 to 9.76), respectively.

These are some huge ORs - what about type of fruit?

Comparison of fruit subtypes revealed that a greater consumption of pome fruit was associated with a lower likelihood of GDM (crude OR 0.59; 95% CI 0.37 to 0.96). The OR of GDM in the highest tertile of pome consumption was almost half that in the lowest tertile. However, the association attenuated to null after adjusting for potential confounding factors in Models 1, 2 and 3. Compared with the lowest tertile, the second tertile for consumption of gourd fruit was inversely associated with the likelihood of GDM, but this inverse association was neither observed in the highest tertile nor in the overall trend (P trend = 0.346). The adjusted ORs in Model 3 across the lowest to highest tertiles of fruit consumption were 1.00 (referent), 0.27 (95% CI 0.11 to 0.66) and 0.94 (95% CI 0.45 to 1.95), respectively. In contrast, compared with the corresponding lowest tertiles, the highest tertiles for consumption of citrus and tropical fruit were each related to a higher likelihood of GDM (adjusted OR in Model 3, 2.26; 95% CI 1.29 to 3.99; adjusted OR in Model 3, 3.73; 95% CI 1.74 to 8.01, respectively). Berry consumption was initially positively associated with GDM, but this association was attenuated to null in Model 3 (highest vs. lowest tertile in Model 3: OR, 1.69; 95% CI 0.80 to 3.56).

Ignore the berry association, it's obvious from the CIs that people didn't eat enough berries to give much of a result. But pomes are apples and pears, and again they look good. Why?

They also assessed the results by GI:

The increased consumption of fruit with moderate to high GI values was significantly associated with a higher likelihood of GDM. Compared with the lowest quartile, the highest quartile for consumption of fruits with moderate to high GI was associated with a higher likelihood of GDM (crude OR 3.04; 95% CI 1.80 to 5.06; adjusted OR in Model 3, 2.94; 95% CI 1.47 to 5.88).

High GI fruits were pineapple, mango, citrus. The authors hypothesised about effects of polyphenols, but this didn't really go anywhere.
Here's what I think; apples and pears are the only fruits you can't juice with your bare hands. When you eat an orange, you're swallowing juice and pulp separately. When you eat an apple, you're still swallowing them together, mostly. And this, I think, is what makes the difference. It takes longer for the sugar to appear in your blood, so people with an already impaired phase 1 insulin response are less affected by it, and the slower digestion produces a more satiating and less insulinogenic gut hormone response.
Of course it's possible that people with a sweet tooth ate the sweeter fruit and that a sweet tooth indicates some sort of internal starvation predictive of diabetes, but even so, eating the sweeter, juiceable fruit is not going to help.

The amount of fruit associated with a lower risk of diabetes in meta-analysis, as with pome fruit here ("one or more serving/day") is relatively low and would fit in many low carb diets (the same is true of wholegrains and legumes - the studies that say that these foods are associated with protection don't say that very high intakes are needed at all). Not that this effect, whatever it is, would be important or needed in a low carb diet, but it is available unless your preferred carb intake is under 50g. If people do include sweet or starchy carbs in their diet, the types of carbs are important.
Very important.

Also see Gannon and Nuttall's study comparing a 40% carb diet high in intrinsic sugars (fruit, milk, root veges) with a 60% carb diet high in starch.[3]

[1] Alperet DJ, Butler LM, Koh W-P et al. Influence of temperate, subtropical, and tropical fruit consumption on risk of type 2 diabetes in an Asian population. Am J Clin Nutr. 2017: ajcn147090;ajcn.116.147090v1

[2] Huang W-Q, Lu Y, Xu M, Huang J, Su Y-X, Zhang C-X. Excessive fruit consumption during the second trimester is associated with increased likelihood of gestational diabetes mellitus: a prospective study. Scientific Reports. 2017;7:43620. doi:10.1038/srep43620.

[3] Gannon MC, Nuttall FQ, Westphal SA, Fang S, Ercan-Fang N. Acute metabolic response to high-carbohydrate, high-starch meals compared with moderate-carbohydrate, low-starch meals in subjects with type 2 diabetes. Diabetes Care. 1998 Oct;21(10):1619-26.

Monday, 8 May 2017

A Quick note on the ASCOT-LLA "Nocebo" statin side-effects study

Here's a comment I put on Malcolm Kendrick's post about the "statin side effects minimal" Lancet paper.
For what it's worth, there's evidence that lipid lowering is effective in secondary prevention of CVD, but only in people with lipid markers associated with hyperinsulinaemia.
This is an easy syndrome to correct without drugs. In people without hyperinsulinaemia (shown by high HDL level and low TG/HDL ratio) placebo is just as effective as any lipid lowering meds for secondary prevention of CVD.

The comment:

I tried to understand the ASCOT-LLA Nocebo study. It had an inherently high potential to be unethical and irresponsible, either because its agenda was to discourage side-effect reporting, or if not because its effect will be just that.

So it needed to be clear – it wasn’t clear at all.It needed to be open-access, something its millionaire backers could easily have afforded - it was instead behind a paywall, with only the media reports of its authors statements being free.

(Here it is)
It needed to be representative. To do that, it needed to collect baseline data about people who might have been in the study but weren’t – the people who didn’t respond to the invites, the people who were excluded, and the people who dropped out.
It may be there, but I can’t find it.
What I can find is that a high % of people in all arms of the study had already been on lipid lowering medicines. Other lipid lowering meds actually cause similar side effects to statins, and this probably included prior statin treatment too, so that would have screened out a lot of people who wouldn’t want to repeat the experience.
But also, the % of people who formerly took lipid lowering meds is highest in the arms with most reported side effects. So there can also be an exposure effect, the longer people are exposed to lipid lowering (those with immediate SFX having been screened out) the more likely it is that they will develop SFX. There’s no evidence that this possibility was controlled for, even though it seems perfectly obvious from the study design that the unblinded arm were on statins for longer than the blinded arm. (One of the few things that is obvious).
This is p-hacking a study of a low-dose intervention, for atorvastatin only, over 10 years after the fact to try to discredit people reporting side effects from the entire range of statins and dosage today.
As I said, it’s unethical to propose such a thing unless you’re proposing the perfect trial of it, which this is not.
You'd need a representative sample of drug-naive individuals prescribed a variety of drugs and doses, as in real life, to even begin. And that is the population reporting a high incidence of debilitating (and very specific) side effects; see the comments on the Malcolm Kendrick blog above.
Is it any wonder that people doubt the safety of basic things like vaccines and flouridation today, when this sort of bogus attempt at reassurance, which no-one trusts as far as they can throw it, is being encouraged in the mainstream medical journals?

Tuesday, 2 May 2017

Bradford Hill is rolling in his grave

Austin Bradford Hill was, as should be well known, the father of modern epidemiology, who played a key role in determining a causal relationship between smoking and lung cancer.
His 9 criteria (or viewpoints, as he called them) for evaluating epidemiological evidence were only ever a suggestion, and intended to have adaptable interpretations strongly guided by logic and good sense in any given context, but have stood the test of time despite the best efforts of epidemiologists to abandon and undermine them.
Initially an attempt was made to reduce the criteria to a smaller number of more malleable points with more room for guesswork and consensus, in the name of getting on with the business of identifying risks however small.

More recently, perhaps due to criticism, the full 9 criteria have been revived, and two recent efforts see them ticked off pedantically - in contexts which might well have bemused Bradford Hill.

Firstly, and I will only touch on this briefly, we have the "LDL is causal in CVD" paper.[1] Bradford Hill probably never considered that a class of biological particles present in every human being could be the cause of a common disease that is seen in individuals with widely varying levels of these particles. It's a little bit like finding platelets causal in thrombosis.

But even so, the paper commits a cardinal error.
None of my nine viewpoints can bring indisputable evidence for or against the cause-and-effect hypothesis and none can be required as a sine qua non. What they can do, with greater or less strength, is to help us to make up our minds on the fundamental question – is there any other way of explaining the set of facts before us, is there any other answer equally, or more, likely than cause and effect?

Is there any other explanation? To determine this, you need to also test the likelihood of the known alternatives. This the authors of the LDL paper do not do. Their paper does not mention insulin, ferritin, or the differing atherogenicity of the different classes of LDL particle and other lipoprotein particles such as VLDL or small, dense HDL, nor the oxidation status of the LDL particles. This is as if Hill had looked at a factory where the workers had a high rate of an unusual cancer, had been told that the workers were exposed to three or more novel chemicals, but had only decided to test the associations for one of them (perhaps the chemical that the company paying his wages made an antidote for). They seem to be arguing for the existence of a biological pathway, which few doubt has some relevance, but overlooking much that is also relevant, such as that the risk associated with LDL will not be decreased if the number is lowered by a method that increases the atherogenicity of the particles, that the association with LDL becomes protective as people age, and that lower LDL levels predict decreased survival in hospital after a heart attack, which may be the reason the FOURIER trial found absolutely no benefit in terms of mortality from extreme LDL lowering.

I have no wish, nor the skill, to embark upon philosophical discussion of the meaning of ‘causation’. The ‘cause’ of illness may be immediate and direct; it may be remote and indirect underlying the observed association. But with the aims of occupational, and almost synonymous preventive, medicine in mind the decisive question is where the frequency of the undesirable event B will be influenced by a change in the environmental feature A.With this in mind, we turn to our second new paper, which seems to risk making an opposite set of mistakes.[2] In this paper, in which the causality of foods and nutrients in cardiometabolic diseases is considered using the Bradford Hill criteria, every possible factor is tested, and most of them are found to be causal.
Perhaps if you can use the Bradford Hill criteria to assert causation for 17 different factors in the same disease you have also refuted each of them individually.
But what's interesting is that, even with this drift-netting approach, saturated fat is no longer making an appearance. Unfortunately we seem to lack the analysis that actually shows saturated fat failing the Bradford Hill criteria, the whole thing's a bit hush-hush for some reason.
We also see that the strength of the association is rated weak for PUFA, which is as it should be.
However red meat gets into their sights, which is unfortunate as people don't eat nearly as much red meat as they used to, yet diabetes, one of the conditions attributed to it here, is very much on the rise.

Their interpretation of temporality in general is weak; as well as one thing preceding another, it ought to take into account where possible the effects of duration of exposure on a disease; there are aetiological aspects to temporality (such as latency in cancer diagnosis) that are more complex than a simple longitudinal relationship. Diabetes is a disease of civilisation and red meat is an ancient food, an aspect of temporality which we probably also need to consider.  

The analogies given in Table 2 are not all convincing, many of them seem to refer to other relationships in the table or other associations that are still unproven. Bradford Hill's idea of an analogy was thalidomide and birth defects, an undeniable example of causation.

If we look at the reference list, we see a fair few Mediterranean diet papers and Harvard epidemiology papers featuring cohorts who were told that avoiding red meat was a healthy behaviour; in fact the sole evidence for the "red meat/processed meat and diabetes" claims is the Pan et al paper from 2011.[3] However 3 of the 10 studies in the Pan et al meta-analysis are their own NHS, NHS2 and HPFS studies, which use a cumulative averaging system that may give false results and data from a population of health professionals known to be influenced by advice about healthy behaviours (including advice given publicly by the study authors). If we remove (or combine) these 3 studies (all published together in this one paper) and combine the two Steinbrecher papers for males and females in the same population, we have 2 of 6 (or 7) favourable studies and 4 (or 5) unfavourable, a ratio which no longer meets the authors' test of consistency. In any case meta-analysis is a way of forcing the appearance of strength and consistency where neither may exist; it is probably most useful where exposures in a number of small, underpowered trials are identical (e.g. the same dose of the same drug for the same condition), and much less useful in diet epidemiology, with its already large populations and its data collection uncertainties.

If we turn to table 4 we see something alarming.[2] The recommended intake of PUFA is set at 11% of energy. This necessitates the use of oils. Yet only one country in the world has a PUFA intake this high - Bulgaria, where the age adjusted death rate for CHD is 188.45 per 100,000 of population ranking Bulgaria #21 in the world. Poland, a somewhat comparable country, sets a recommended PUFA intake of 3% (real intakes are higher) and has 136.72 CHD deaths per 100,000, placing at #40. The Tsimane' indians of Bolivia have very low PUFA intakes and experience a very low rate of cardiovascular disease, as do the Kitavans and as did the Tokelauan Islanders; high PUFA intakes are unusual in hunter-gatherers free from cardiometabolic disease. A PUFA intake of 11% is an unproven intervention, even the AHA doesn't recommend more than 10%.
The recommended meat intake of one serving a week is only met in Armenia and Georgia - two countries with very high CHD death rates. This is also a meat intake that will not supply nearly enough iron for women of childbearing age, ffs.
Barbados has the highest fruit consumption, as recommended, but diabetes is a major cause of death there.
This sort of arbitrary decision is not one that the use of Bradford Hill criteria allows anyone to make, especially when it is contradicted by this evidence supplied in the same table.

Such insanity aside, the dietary etiology Bradford Hill paper is probably intended as a well-meaning attempt to justify asking Americans to eat beans, nuts, and fish, which won't do them any harm; its danger is that it polishes up the Bradford Hill criteria into yet another tool that ideologues can use to suppress uncertainty, or justify the use of foods in contexts where they are biologically inappropriate (e.g. wholegrain products in the treatment of diabetes). If you don't respect the uncertainty in diet-health science, and the importance of context, you can't be right.

There's an earlier Bradford Hill dietary paper, by Andrew Mente and colleagues, which makes an interesting contrast with the current one.[4] Although in general agreement, albeit tougher, some associations that satisfy the criteria are for individual nutrients - vitamin E and vitamin C. In fact the vitamin E association is stronger than that for PUFA. Oils and other foods high in PUFA are generally good sources of vitamin E.

It may well be that sourcing expensive (or risky) foods and following exotic dietary patterns can protect us from disease. It may also be that the protective factors in foods are the ones we've always known about - the vitamins and minerals, electrolytes and trace elements, protein, essential fatty acids and so on, and that they do us most good when we find them in foods that won't dump energy into our bloodstreams any faster than the foods our ancestors ate thousands of years ago (which means that sourcing nutrients from fortified foods won't be optimal even if we could get the number of them and their balance right, which is far from being the case today). It may also be that other things in foods act as mild pseudomedicines (the polyphenols and other phytochemicals) or make up for deficiencies in our individual metabolisms (the carnochemicals).

This is what I propose as the null hypothesis of nutrition and health - that simple good feeding will give us most of the protection we need, that wandering away from it first with food refining and depletion, then with food processing (defined as the synthesis of replacements for degraded foods from more and more complex aggregations of equally refined food and non-food ingredients), is the cause of our modern cardiometabolic ills (insofar as these are due to diet and not other genetic and environmental factors) - not the fact that we instinctively cling to eating meat - the last surviving nutritious real food in all too many diets today.


[1] Ference BA, Ginsberg HN, Graham I et al. Low-density lipoproteins cause atherosclerotic cardiovascular disease. 1. Evidence from genetic, epidemiologic, and clinical studies. A consensus statement from the European Atherosclerosis Society Consensus Panel. Eur Heart J. 2017 Apr 24. doi: 10.1093/eurheartj/ehx144

[2] Micha R, Shulkin ML, PeƱalvo JL, et al. Etiologic effects and optimal intakes of foods and nutrients for risk of cardiovascular diseases and diabetes: Systematic reviews and meta-analyses from the Nutrition and Chronic Diseases Expert Group (NutriCoDE). PLOSOne April 27, 2017

[3] Pan A, Sun Q, Bernstein AM, Schulze MB, Manson JE, Willett WC, et al. Red meat consumption and risk of type 2 diabetes: 3 cohorts of US adults and an updated meta-analysis. The American journal of clinical nutrition. 2011;94(4):1088–96. pmid:21831992

[4] Mente A, de Koning L, Shannon HS, Anand SS. A systematic review of the evidence supporting a causal link between dietary factors and coronary heart disease. Arch Intern Med. 2009 Apr 13;169(7):659-69. doi: 10.1001/archinternmed.2009.38.

Monday, 1 May 2017

What I eat 2017

Another in the ever-popular genre of blog posts about what people eat.

No photos though.

I wake up and have an instant coffee with cream and 1/4 spoonful of dark brown sugar.

Maybe I'll have another before breakfast. If I'm out I'll have a long black with cream without sugar, followed by a glass of cold water.

Breakfast is the most important meal of the day, because it decides if and what you'll be eating before dinner. Usually after 10 AM.

My favourite breakfast is 4-5 eggs (depending on size) cooked in a mix of ghee and bacon fat. So I'm eating all the eggs whole, no yolk-only meals, and using less added fat than I did a few years ago.

The virtue of eating more eggs is that I can run further without my joints hurting. I could always run a mile, but the impact on my legs, feet, and ankles meant I couldn't do it the next day. Since increasing my egg intake, I find I can do it day after day (if I want to, sometimes I prefer to relax outside and take things in differently).

I might have leftovers of stir fry with a couple of added eggs, if it's there and I don't want to waste it, or frozen broad beans fried in bacon fat and ghee with a tin of sardine and a couple of eggs, if it's time for some omega 3s.

I'll usually add dried chilli flakes and some curry powder, and always salt.

I don't usually need to eat on days when I'm out of the house, in the city, but if I do it's usually some high-fat deli meat, maybe a piece of fruit.

In the afternoon at home, if I'm not too busy and feel the need, I'll have a small piece of tasty cheddar cheese, or a spoonful of pure peanut butter. If there's any fruit I'll have a couple of pieces. I prefer pears and plums, kiwis and feijoas. Apart from this and the trace element of sugar in coffee, no carbs (and almost always no starch) before dinner.

An hour before dinner on most afternoons I'll have a glass or two (standard serving) of red wine. I like chianti at the moment but whatever's both good and cheap. I started drinking regularly a year or so after I cleared Hep C with the Epclusa trial, and I like the effect, which is interesting because I used to be an alcoholic in the early 90's, but I'm quite sure I'm not anymore.

Dinner could be anything. These days either roast lamb or pork with roast veges, including some starchy carbs cooked in the fat or in beef and lamb dripping, or very spicy stir fry with mince or chicken and lots of veges, eaten with yoghurt and maybe some rice, maybe not. There might be a little sugar in curry pastes or pasta sauces, to be honest this concerns me a lot less than some other common additives like soy or cornstarch. So some days are less than 50g carbohydrate and some are less than 100g, rarely more. I no longer feel any different in my energy levels if I'm in or out of ketosis, expect that higher carbs make me feel overdone after a few days if I'm not exercising much, not that my weight changes, and I adjust back down. My favourite starchy dish is a bean salad, black beans with feta, tomato, vinegar and olive oil.

After dinner I'll have a cup of tea with some dark chocolate. If we don't have any, I'll eat sweet chocolate, but that is the sort of thing that can get away on me. If I need dessert I'll have berries and cream, or a roast apple with cream.

I'll also eat a little bit of cheese close to bedtime. Paradoxically, because I'm a little allergic to dairy and can't drink milk, this seems to stop me from getting hay fever when I'm trying to sleep. And it's good for my teeth - I lost most of these eating carbs, I realise now I could have stopped this at any time just by eating the way I do now. I have some surviving teeth with massive caries where mercury amalgam fillings inserted during childhood fell out due to further decay - these teeth are now hard again, have stayed the same for 6 or more years since going low carb, are still useful, and never hurt. This arrest of dental caries was first noted by Boyd in the teeth of children with diabetes maintained on very low carb diets in the 1920's. I have lived in an area without water fluoridation for the past 11 years.

Exercise is that of someone who has literally never been to a gym in his 59 years. And never been in team sports. In summer I swim in the sea and rivers - my stroke is lousy and slow but I'm finally confident to travel out of my depth for long periods. I climb hills, I run and sprint along the roads and paths, and test myself occasionally with runs up hill or for longer distances, but not every day. I can do 10 pull-ups from a dead hang at the local playground some days - I could never do that before, couldn't even do one a year or so ago. I can do all things I might need to do in my life without exhausting or injuring myself, which is my definition of fitness.

I use some supplements; vitamin D in winter (I average 5,000 IU/day from midwinter; sunlight withdrawal symptoms like psoriasis and optic twitch remind me when it's time to start), magnesium from time to time, grape seed extract at the moment, boron (as borax) which I've trialled for a couple of weeks and I quite like. Vitamin C occasionally.

In spring and summer I try to get enough sunlight exposure to tan early and often, this then allows me to go swimming etc ad lib with minimal use of sunscreen or risk of sunburn.