Slide 1

Thank you very much and good afternoon everyone. I first would like to thank the organisation. It’s a great honour for me to have been invited to this conference to speak about obesity, one of my favourite topics. I’m a nutritionist and at this moment I’m finishing my PhD about nutritional status in dialysis patients at the Department of Clinical Epidemiology in Leiden.

Slide 2

In the general population it is well known that obesity is an established risk factor for cardiovascular morbidity and mortality, and as Dr Bakker just showed obesity is also a risk factor for CKD, either via diabetes and hypertension or even directly. However, many survival studies in the dialysis population showed opposite associations. Lower values of BMI were associated with an increased risk of mortality, whereas higher values of BMI were shown to be protective resulting in an improved survival.

Slide 3

Now, this obesity-survival paradox in the dialysis population has been referred to as ‘reverse epidemiology’ and it has resulted in the hypothesis that a higher fat mass may provide a survival advantage for dialysis patients. Well, this hypothesis resulted in a large debate and a lot of confusion about the plausibility of the associations, and some researchers even stated that it must be confounding which should be statistically adjusted for.

Slide 4

Now, why such a debate? In many transplantation centres obesity is considered as a contraindication for transplantation because it’s associated with a lot of complications around surgery and eventually also with increased patient mortality.

Slide 5

This is a study of Meier-Kriesche showing that indeed higher values of BMI are associated with increased mortality after transplantation.

Slide 6

As a consequence, the probability for a transplant is lower in obese patients and their time on the waiting list is longer.

Slide 7

So, these contradicting observations lead to the question whether we should advise weight loss in obese dialysis patients who are awaiting a transplantation?

Slide 8

Several mechanisms have been proposed to explain this obesity-survival paradox and I won’t go through them all,

Slide 9

but the first three all relate to disease-related malnutrition, which is referred to as protein energy wasting in the dialysis population. This protein energy wasting is highly prevalent in the dialysis population and may indeed be a plausible explanation: patients who suffer from protein energy wasting may lose weight, may have lower a BMI and this protein energy wasting is related to increased mortality.

Slide 10

In addition, it must be noted that this comparison of the general population with the hemodialysis population, and also the ones we will make in our minds, is based on middle-aged general populations, so middle-aged subjects from the general population that have been followed for a long time of follow up, and they’re being compared with the hemodialysis population which on average is older but also has a lower survival time. So in fact, short-term mortality is being compared to long-term mortality.

Slide 11

Therefore, we hypothesised that age and duration of follow-up may influence the BMI-mortality relation, and made a comparison of a general population and a dialysis population that were strictly comparable for age and duration of follow-up. Well, first, we confirmed that in each BMI category the absolute mortality rates were ten-fold increased in the dialysis population compared with the general population.

Slide 12

However, when we looked at it on a relative scale, we observed that the BMI-mortality relations were similar, and not opposite. So, this study implies that age and duration of follow-up should be taken into account for a valid comparison between populations. However, also in our study the general populations had been followed for a short time. We know that if we follow them for more than 15 or 20 years, that we can detect an increased risk of obesity, whereas our hemodialysis population cannot be followed that long because of the high mortality rate. So it remains a fact that also in our dialysis population the mortality risk associated with a high BMI is lower than the one with the patients with a low BMI.

Slide 13

So we would like to translate these observations in causal interpretations, eventually leading to interventions: after the observation that dialysis patients with a higher fat mass have a better survival we would like to know if increasing fat mass in other patients will also be beneficial.

Slide 14

Now when can we translate association into causation? In the ideal situation, association is causation or can be interpreted as causation if the exposed and unexposed are exchangeable. So there should be no difference between those two groups except for the exposure.

Slide 15

Now randomisation, of course, is our favourite method to achieve this exchangeability. So, if we want to study a treatment effect of a certain pill, we would randomise this study, or the eligible population; so by chance the patients will be assigned to the pill or the placebo, and because of this randomisation the study groups are exchangeable.

Slide 16

So it also would not matter which group we would give the pill or the placebo to, in the end we would find the same effects.

Slide 17

In contrast, if we assigned the pill or the placebo based on a doctor’s prescription, only patients will receive the pill because they need a pill or they will benefit from it, whereas other patients will not receive it. So this association will be biased by confounding by indication. The patient populations will not be comparable because there was an indication for getting assigned a pill or not.
Now if we go back to obesity, the pill is a straightforward exposure, you can give someone a pill or not, but obesity is a far more complex exposure because in fact, we don’t know why someone is obese or not. So the question is: to what extent obese patients are exchangeable with non-obese patients?

Slide 18

Well, in the general population in fact we also don’t know the exact reasons of obesity, but the majority of the persons here on the right side of the scale will have a high BMI because they have eaten too much and exercised too little, resulting in a positive energy balance and if they hadn’t done that, they would be on the more left side of the scale. Thus, in the general population we consider obese patients and non-obese patients exchangeable.

Slide 19

Now in the dialysis population it can be argued whether obese dialysis patients and non-obese dialysis patients are exchangeable and I can think of two arguments: Because the underlying reason for having high BMI or low BMI may be fundamentally different. For example, because of the protein-energy wasting we just discussed. These patients on the left side of the scale may have a lower weight because they suffered from weight loss due to this protein-energy wasting that is associated with increased mortality. So these patients have a higher mortality compared to the ones who don’t suffer from protein-energy wasting.

Slide 20

Another reason may be that also the underlying reason for being an obese dialysis patient may differ, because we do know that obesity in the general population is a risk factor for ESRD. So at least a proportion of these patients may have reached dialysis because they were obese. If they hadn’t been obese, we are not sure whether they are exchangeable with the leaner patients on dialysis but maybe they would have stayed in the general population.

Slide 21

I first would like to show you the study that Dr Bakker also just showed. I think this study by Hsu may provide insight into the effects of obesity. This is large general population that has been followed for a long time of follow-up. Not only was obesity associated with increased risk of ESRD, but in a letter he also added mortality rates and also the mortality rates were increased as a result of obesity. So this study may show that obesity is a risk factor for both ESRD and mortality.

Slide 22

So please note that I’m not saying that the populations are not exchangeable, unfortunately we just don’t know and also no tests exist to test whether they are exchangeable or not. But if they are not exchangeable, the associations may suffer from confounding similar to confounding by indication and this confounding cannot be statistically adjusted for. So I think at this moment on the basis of the observational associations we don’t have sufficient evidence for causal interpretations of beneficial effects of high fat mass.

Slide 23

So, what do we know about the effects of weight change in the dialysis population? Only a few studies examined the effect of weight change on mortality and this is one of them. They all showed that weight loss is associated with an increased mortality risk in a dialysis population. However, also these are observational studies studying weight loss and the problem is that we don’t know if the observed weight loss was intentional or unintentional.

Slide 24

Intentional weight loss by a healthy weight reduction may have opposite health effects than unintentional weight loss as a result of disease.

Slide 25

So I think that the ultimate study that will provide us with final answers whether high fat mass is beneficial in these patients is a randomised controlled trial, with randomisation of increased fat mass in dialysis patients with normal weight. I think we have to study patients with a normal weight to prevent that we study patients with protein-energy wasting, because that would answer a different question. Now, of course, it’s not really feasible to randomise an increase in fat mass to patients or not. So maybe a second trial may be an option; I think it may be feasible to randomise weight reduction in obese dialysis patients. Although not all exercise and controlled diet programmes have been proven successful, it might be the only way to show that a weight reduction is beneficial or not in dialysis patients.

Slide 26

Bariatric surgery may provide a solution because this is something which can easily be randomised to the dialysis patients. A recent study has already shown that gastric bypass before transplantation resulted in weight loss before transplantation so in the end we would like to know whether this result would also improve in the end survival in the patients or not.

Slide 27

In conclusion I think that the phenomenon of reverse epidemiology in dialysis patients leaded to more attention for the relation between nutritional status and survival in dialysis patients, with special attention to improved survival in patients with protein-energy wasting, and I think that’s a good thing. However, on the basis of the observed associations from observational studies at this moment there is no sufficient evidence that increasing fat mass in dialysis patients will improve survival. Randomised controlled trials are needed, randomising weight reduction and interventions with bariatric surgery may be a solution for that.

Slide 28

and I would like to thank you for your attention.