Weight loss: all gone wrong?

weight 22 augustSo, I go on holiday, hire a bike and cycle a lot for the fortnight I am away: regularly burning (according to online assessments) over one thousand calories a day.

And then I come back and find (see the graph) that my weight has risen by five pounds. Too much drinking, fatty foods and so on? I don’t think so, though plainly something is up.

(In the graph the green line is the 90 day moving average, the blue the 30 day and the red the 14 day – I smoothed the weight gain over the two weeks I was away across that period – as I didn’t have access to scales then).

Weight gain and loss continues to be a mystery to me – I am “training” as hard as ever but weight has gone up even though I don’t think I have changed my diet.

I am going to go for heavier weights (necessarily with lower repetitions) now to see if that makes any difference (this is generally combined with a fair amount of cardio too).

My aim is to get to 168 pounds by the end of the year – still overweight incidentally – but that looks quite remote now.

Two things I can be certain about though, given the difficulties I have had with running since coming back from holiday are: cycling is a poor way to train to run – very different muscles used (and not just in the legs – I never realised ho important my arms were in running for instance) and I really ought to invest in a runner’s watch.

How can I lose that final stone?

The graph on this page shows the moving fortnightly average of my weight (in pounds – human weight will be one of the last things to go metric in Britain) since the middle of February.My weight

I think the graph shows I am still losing weight from my gym-five-times-a-week approach, but it has become much harder than before (in fact the rate of decrease in February was still a fair bit lower than in 2012).

So, how can I fix this? Serious, evidence-backed replies only please!

I am not particularly interested in hearing about diets either.

The February weight loss started when I changed my routine in the gym – essentially doing a much higher number of repetitions on the machines (with a lower weight) – I usually do 45 – 60 minutes of cardio followed by 15 – 30 of strength.

I have kept that (newer) regime but, as you can see, it has been of limited effectiveness.

How many kilowatt hours have I burnt losing weight? Not that many

English: inner workings of the magnetic resist...
English: inner workings of the magnetic resistance bicycle (Photo credit: Wikipedia)

Here’s a slightly sobering calculation – both in terms of what it tells us about human energy use and human frailty.

Since I started working in the gym, about 18 months ago, I think I have lost about 40 lbs of fat (weight loss is a bit more than that, but I am concentrating on fat).

If human fat has a calorific value of about 4000 kilocalories per pound, this all works out at about 44 kilowatt hours – around £5 ($7 or so) worth of electric power. (Or, judging by the winter gas bill I have just received this is around a day’s worth of gas usage).

Thinking of it another way – 100 watts on the exercise bike is fairly easy to maintain for a sustained period (I would not normally do more than half an hour on this but I am sure I could do this for several hours if all else fails) – this 444 hours.

Of course I have used far more than this to sustain this weight loss – but it puts our routine energy use into perspective to think that all that effort is just a day’s worth of hot water, hobs and central heating.

Some questions about the science of magic chocolate

This image was selected as a picture of the we...
 (Photo credit: Wikipedia)

I have to be careful here, as it’s not unknown for bloggers to be sued in the English courts for the things they write about science. So I will begin by saying I am not, and have no intention of, casting aspersions on the integrity of any of the authors of the paper I am about to discuss. Indeed, my main aim is to ask a few questions.

The paper is “Effects of Intentionally Enhanced Chocolate on Mood“, published in 2007 in issue 5 of volume 3 of “Explore: The Journal of Science and Healing” by Dean Radin and Gail Hayssen, both of the Institute of Noetic Sciences in California, and James Walsh of Hawaiian Vintage Chocolate.

The reason it came to my attention today is because it was mentioned in the “Feedback” diary column of the current issue of the New Scientist:

the authors insist that in “future efforts to replicate this finding… persons holding explicitly negative expectations should not be allowed to participate for the same reason that dirty test tubes are not allowed in biology experiments”. [Correspondent] asks whether this may be “the most comprehensive pre-emptive strike ever” against any attempt to replicate the results.

But I want to ask a few questions about the findings of the report which are, in summary, that casting a spell over chocolate makes it a more effective mood improver.

In their introduction to the paper the authors state:

Cumulatively, the empirical evidence supports the plausibility that MMI [mind-matter interaction] phenomena do exist.

Unfortunately, the source quoted for this is a book –Entangled Minds – so I cannot check if this is based on peer reviewed science. But you can read this review (as well as those on Amazon) – and make your own mind up.

Again, not doubting their sincerity, I do have to question their understanding of physics when they state:

Similarities between ancient beliefs about contact magic and the modern phenomenon of quantum entanglement raise the possibility that, like other ethnohistorical medical therapies once dismissed as superstition – eg, the use of leeches and maggots in medicine – some practices such as blessing food may reflect more than magical thinking or an expression of gratitude.

The study measured the mood of the eaters of chocolate over a week. Three groups ate chocolate “blessed” in various ways and one ate unblessed chocolate.

The first thing that is not clear (at least to me) is the size of each group. The experiment is described as having been designed for 60 participants, but then states that 75 signed informed consents before reporting that 62 “completed all phases of the study”. Does that mean that 13 dropped out during it? As readers of Bad Pharma will know it is an error to simply ignore drop outs (if they are there – as I say it is not clear.)

The researchers base their conclusion that –

This experiment supports the ethnohistorical lore suggesting that the act of blessing food, with good intentions, may go beyond mere superstitious ritual – it may also have measurable consequences

– substantially on the changes in mood on one day – day 5 of the 7.

The researchers say that the p-value for their finding on that day is 0.0001 – ie there is a 1 in 10000 chance this is the result of chance alone.

I have to say I just not convinced (not by their statistics which I am sure are sound) but by the argument. Too small a sample, too short a period, too many variables being measured (ie days, different groups), a lack of clarity about participation and so on. But I would really appreciate it if someone who had a stronger background in statistics than me had a look.

Bad Pharma by @bengoldacre: the review

English: Ben Goldacre speaking at TAM London O...
English: Ben Goldacre speaking at TAM London October 2009 (Photo credit: Wikipedia)

In one sense Bad Pharma: How drug companies mislead doctors and harm patients is the perfect book: this week I could read it, in two chunks over the exact time (to the minute) it took to me to fly to Eastern Europe and back.

Of course that alone would be a poor reason to recommend it, and there are plenty of others.

The sheer level of duplicity by the pharma companies and the scientific publishing companies is deeply depressing. The supine (or worse) attitude of the regulators just as bad.

Drug companies love to tell us how much it costs to develop a drug (though it turns out they fiddle the figures – adding in the opportunity cost of capital while, of course, ignoring any return – not so much the “double counting” that Ben Goldacre describes it as single entry book-keeping) – but how many of us know they spend more, much more, on marketing? That is their biggest cost and as Goldacre points out, most of that spend would be pointless if we had the information we needed – and could have – about which drug was more effective and which was not.

There remain annoyances in style – talking about “going forward”, writing of an an organisation “curating” data and a general tone which suggests he’s the clever scientist and we’ll all struggle with a bit of maths. But overall these are minor quibbles.

Overall, though, this is a polemic and so it would be good to see the response from the industry. Are they really the liars and frauds this book suggests they might be? Surely they cannot all be? Time for the industry to get its act together and issue a convincing reply if they want to rescue their reputation.

But Goldacre does deal with a few of the points that concerned me after the first chunk (the second half was better, as it goes).

On “me too” drugs he makes a reasonable case that companies could make a good return if regulators insisted on “better” and not just “the same”. The economics of that would be interesting to see, but I think I’d give that to Goldacre on points. More seriously even that the waste of money that many of these “me too” dugs represents is the fact that they may actually be less effective than the off-patent molecules they are replacing – the complete lack of rigour in the drug testing regime means that “me too” is essentially only validated against a placebo or a deliberately broken dose of a rival.

The book makes me worry about science in general. Much of the trickery, knavish and foolish behaviour by manufacturers, medics and scientific publishers could have direct analogues in other scientific fields, especially where a financial return is at stake (and for academics under pressure to make an “impact” that could mean everywhere). Medicine seems to be particularly broken, but the book has given me cause for concern about science in general.

One thing that is missing from Goldacre’s various lists of actions to be taken is a serious examination of how to influence public policy via politics. This is where his innate hostility to politicians seems to obscure his vision. Few politicians are likely to read this book from cover to cover – but some might, as I know some British MPs have already expressed concerns about “medicalisation” and “disease mongering” and the impact this is having on some of the most vulnerable. But there is surely no reason why MPs and eventually ministers should not take action on many of the points raised.

Of course, big pharma has many resources and big lobbying to fall back on (declaration of  – former – interest: in a past life I have been, indirectly, part of this) but  there are a few points to bear in mind in constructing a case to convince politicians: (1) no one serious is trying to close big pharma down, this is about reform not destruction, (2) big pharma will threaten to shift resources elsewhere – but what state wants to pay over the odds for duff medicines? Their bluff can be called (as, in his way, President Obama has already done over ACA) and (3) state medical services are amongst the most expensive public enterprises, only defence costs come close – that is a powerful, popular and populous answer to any threatening sabre rattling by recalcitrant drugs companies.

In the end, though, my gut feeling is that pharma will co-operate with a setting of the house in order. And as medicine in most developed countries is a monopsony they will have little choice in any case.