Taking on non-sense about exercise

I lost my cool today when I opened the newspaper in the morning. Predictably there was an ignorant nonsensical article published in the T2 by a fitness expert. Normally I would not have bothered but this one touched a nerve.

“Strength coach Charles Poliquin had coined the term ‘chunky aerobics instructor’ (CAIS) to describe women aerobics and step-class instructors who spend almost two to three hours every day on aerobic exercise, yet carry 22-24 per cent body fat. Compare these figures to female sprinters who carry only 12-13 per cent body fat and the punchline is clear: stay away from aerobic exercise!”

Comparing apples to oranges are we? Normal women compared with sprinters? Even then this is a pathetic comparison. He seems to imply that 22 -24% body fat is bad for women. On the contrary 21-24% body fat is considered to be fitness level for women and 25 to 31% body fat is acceptable for women (Diabetes India). So he is wrong there. May be he should have Googled properly before shooting his mouth off.

“Forget what doctors tell you about aerobic exercise based on research done on treadmill running of rats. Humans are not rats.”

Oh! Slandering doctors are we? Perhaps he should have read up a bit more. Isn’t there any human study showing the effect of aerobic exercise? Of course there is, the fitness expert is too lazy to even use Google. What a shame! So here are two studies (on humans m'Lord, not on rats, I swear) that show aerobic exercise is indeed good for you –

1. Effect of Exercise on Total and Intra-abdominal Body Fat in Postmenopausal Women: A Randomized Controlled Trial
– Whoa, an RCT! I can barely control my glee. Qouting the results –

“Exercisers showed statistically significant differences from controls in baseline to 12-month changes in body weight (–1.4 kg; 95% confidence interval [CI], –2.5 to –0.3 kg), total body fat (–1.0%; 95% CI, –1.6% to –0.4%), intra-abdominal fat (–8.6 g/cm2; 95% CI, –17.8 to 0.9 g/cm2), and subcutaneous abdominal fat (–28.8 g/cm2; 95% CI, –47.5 to –10.0 g/cm2). A significant dose response for greater body fat loss was observed with increasing duration of exercise.”

                    And the conclusion –

“Regular exercise such as brisk walking results in reduced body weight and body fat among overweight and obese postmenopausal women.”

    2 .Effect of Aerobic Training on Percentage of Body Fat,Total Cholesterol and HDL-C among Obese Women (PDF) – Quoting from the abstract –

“The results showed that there were significant changes in Percentage of Body Fat, TC and HDL-C.”

So Mr. Fruitness expert, you are demonstrably wrong. Maybe you should think again before slandering doctors and sprouting non-sense?

Edit - Can't believe I missed this nugget -

"Cortisol leads to adrenal fatigue, yo-yo-like fluctuations in blood sugar and completely throws your digestive system off gear."

Our fruitness expert is a total woo monger, peddling a fake disease!! From the brilliant people of Science based Medicine -

“Adrenal fatigue” is not a real medical condition. There are no scientific facts to support the theory that long-term mental, emotional, or physical stress drains the adrenal glands and causes many common symptoms."

Irwin, M. (2003). Effect of Exercise on Total and Intra-abdominal Body Fat in Postmenopausal Women: A Randomized Controlled Trial JAMA: The Journal of the American Medical Association, 289 (3), 323-330 DOI: 10.1001/jama.289.3.323

Writing at the doc2doc clinical blog

I have written a post on numbers needed to treat over at the doc2doc clinical blog of BMJ. Here is an excerpt, go ahead and have a read –

“The NNT or number needed to treat is a useful way to report binary outcomes of RCTs. NNT gives us an easy to understand statistic. It can also be used to present results of continuous variables by converting them to dichotomous variables. NNT can be defined as the reciprocal of the absolute risk reduction (ARR) or NNT=1/ARR. ARR is the difference between the absolute risk of the control group (AR_C) and the absolute risk of the treatment group (AR_T) or NNT=1/ (AR_C - AR_T). The value of NNT can lie between 1 to +∞ for a beneficial effect and -1 to -∞ for harmful effect.” Read more.

Novartis vs. Government of India

From 6^th September onwards, a very important case is being heard in the Supreme Court. It concerns two parties, the drug manufacturing giant Novartis and the government of India but the outcome of this case has huge implications for the people of India and of other low income countries.

Imatinib mesylate. From wikimedia

What is the case about?

Novartis wants to obtain a patent on imatinib mesylate, a salt of the drug imatinib used for the treatment of cancers like chronic myeloid leukaemia. Previously, Novartis appealed in the Chennai High Court and the Indian Patent Appelleate Board but the decision was not in their favour. In both the cases, section 3(d) of the Indian Patent Act was cited to show that imatinib mesylate did not show any significant efficacy than that of the original compound although Novartis claimed that it increased the bioavailability of the drug by 30%. Now Novartis is challenging the decision in Supreme Court to obtain a patent.

Why should you be bothered?

If Novartis does not have a patent on the drug, it allows generic manufacturers to produce the drug. Competition in the generic market drives the price of the drug down and you and I can afford to buy the drug should we need it. If Novartis succeeds in getting a patent, it gains a monopoly on the drug and no other company can produce it unless authorized by Novartis. This is a common tactic used by pharmaceutical companies to maximize their profit, called evergreening. If Novartis is successful in getting a patent, this will set a precedent, all the other companies too will file for patents and will ultimately drive up the cost of life saving medicines.

Médecins Sans Frontières, an international humanitarian organization has already spoken up against this, saying that this will drive up the cost of medicine in low income countries to whom they supply drugs which they buy from generic Indian manufacturers. 

Who is more corrupt? Correlating politicians and corruption using Google

This post was inspired by a post on The Madura Beats.

Let me start off by saying that this should not be taken seriously. It’s a quick and dirty work of half hour and not a rigorous study. If you want a rigorous study then probably a journal on political science would be a good starting place. That being said let me begin the post.

There is a nifty tool powered by Google called Google Insights for Search that lets you see the interest in particular search items overtime. You can also compare different search items and see how they vary over time. So I began my experiment. I searched for the search terms “lalu prasad yadav” and “corrupt” originating from India from 2004 till date. The graph shows the Google output.

I then downloaded the data and fired up R (a very powerful free statistical software). If you notice carefully you will see that the interest in “corrupt” went up sharply towards the end, that’s probably because of the recent interest in anticorruption movement. Hence I removed the outliers from the data using the rm.outlier() function of outliers package in R. Then I calculated Pearson’s correlation coefficient to see if the searches of Lalu Prasad Yadav and corrupt are correlated and plotted a scatter graph. The results are below.

Lalu Prasad Yadav and Corrupt
Pearson's product-moment correlation
data:  lpydata$lalu.prasad.yadav and lpydata$corrupt 
t = -6.4745, df = 398, p-value = 2.806e-10
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval: -0.3947899 -0.2172100 
sample estimates: cor = -0.3086874 

Scatter gram of interest in LaluPrasad Yadav and Corrupt

I did the same using the search terms “manmohan singh” and “corrupt”. The results are below –

Manmohan Singh and Corrupt

Pearson's product-moment correlation

data:  newdata1$manmohan.singh and newdata1$corrupt 

t = 7.7384, df = 398, p-value = 8.371e-14

alternative hypothesis: true correlation is not equal to 0 

95 percent confidence interval: 0.2732764 0.4439476 

sample estimates:cor= 0.361638

Scatter gram of Manmohan Singh and Corrupt

The findings are counterintuitive. Though searches of both Manmohan Singh and Lalu Prasad Yadav are weakly correlated with the search of coruupt, they are correlated in the opposite way. Manmohan Singh has a positive correlation with corrupt while Lalu Prasad Yadav has a negative correlation with corruption. This means more the interest in the search term “corrupt”, more the interest in search term “Manmohan Singh” while more the interest in search term “corrupt”, less the interest in search term “Lalu Prasad Yadav”. Not what you expect, eh?

What does this mean? This means correlation doesn’t equal to causation and that my model is too simple to model the actual reality! Of interest, in the beginning of the tine series, there was almost no interest in the search term “Lalu Prasad Yadav” but there was a high interest in “corrupt”. Probably this screwed up the results.

Edited to Add -
Spurred on by the comment of confused yuppie, I did a bit more calculation, now comparing "lalu prasad yadav" and "manmohan singh" wit the search term "honest". The results -

Lalu Prasad Yadav and Honest

Pearson's product-moment correlation
data:  lpynew$lalu.prasad.yadav and lpynew$honest 
t = 0.1226, df = 59, p-value = 0.9028
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval: -0.2368133  0.2667080 
sample estimates: cor = 0.01595912 

Lalu Prasad Yadav and honest

Manmohan Singh and Honest -

And then I run into problems. Somehow on downloading the .CSV file the data for honest is not there. So I can't test for correlation. I anyone is able to find the data for honest then please let me know.

At least the interest for Lalu Prasad Yadav is not correlated with honest.

Taking on Yoga

My routine after getting up in the morning comprises of going through the newspaper. Imagine my irritation when I flipped open t2, the supplement that comes with The Telegraph. The article was titled “Yoga for immunity” and I quote the first paragraph of the article –

“The onset of monsoon brings along with it a number of ailments such as asthma, allergies, common cough and cold, abdominal disorders, typhoid, malaria, swine-flu, jaundice, diarrhoea and eye disorders. And to beat such disorders during the season, the best treatment one can resort to is yoga.”

What? Consider being hit by such load of non-sense, at a time when I wasn’t still fully out of the clutches of Hypnos, it is not pleasant I tell you. But it did drove out the last remnants of any sleep from my eyes. I generally don’t pay much attention to articles like this but this is different. One rarely comes across this much non-sense compressed in two sentences. Published in a leading daily this is potentially dangerous. About 2,00,000 people below the age of 70 years die every year in India due to malaria (source). It is a very serious disease and can easily take your life unless treated properly. Enteric fever or typhoid is a similar dangerous disease. Jaundice can occur due to many causes form infection to cancer and needs medical evaluation. Certainly they can’t be cured by Yoga, leave alone the claim that yoga is the best treatment for these conditions. This is a fact. And there it was, a leading newspaper telling yoga is the best treatment for all these diseases with any evidence whatsoever

I did search Pubmed (a database of biomedical literature with over 20 million citations) to be sure that Yoga didn’t work. No surprise there. On searching with the limits clinical trials, meta-analysis and randomized controlled trial – the results showed zilch. There is not a single trial done to test whether yoga works for malaria, jaundice or enteric fever, leave alone testing if it’s the best. So where from the author is getting her information? It doesn’t matter, whatever her source is, it's not reliable as there has not been a single trial of yoga for these diseases.

I did send a complaint to the newspaper asking to give evidence in support of the claims in the form of randomized controlled trials or to retract the claims. I urge you do the same. It will only take a moment of your time to send an e-mail at t2@abp.in but it may stop the spread of misinformation.

Sunday Book Club: Intensive and Critical Care Medicine – Chapter I

I have been reading this book titled “Intensive and CriticalCare Medicine: World Federation of Societies of Intensive and Critical CareMedicine” by A. Gullo, J. Besso, P.D. Lumb, G.F. Williams (Eds) published by Springer and thought about writing a review of it. 

Intensive and CriticalCare Medicine: World Federation of Societies of Intensive and Critical CareMedicine

First things first, the book is divided into 12 sections, beginning with section I – Introduction and Mission. I will talk about the rest of the sections as I work through the book. 75 authors have contributed to the book and it is of 573 pages including the index. The book is hard bound which is rather nice.

Moving on, the first chapter “History of Critical Care Medicine: The Past, the Present and the Future” is written by G. Ristagno and M.H Weil. Now Dr. M.H Weil was a pioneer in the field of Critical Care Medicine, infact he can be attributed with coining the term “Critical Care”. He was right there when it all began and it is fascinating to learn about the birth of a specialty from him. Unfortunately, Dr. Weil passed away on July 29 this year.

The chapter gives a concise overview of the history of Critical care Medicine as a specialty, how it evolved from “Shock Ward” to the modern day Intensive Care Unit. It’s very interesting to learn about the introduction of real time patient monitoring devices and their evolution into today’s point of care devices, the setting up Society of Critical Care Medicine and how the first three presidents of the Society set up an impromptu meeting in the Boardwalk of Atlantic City.

All in all, the chapter is quite nice. There are some pictures depicting how the ICUs looked back then. Such nuggets are rarely present in textbooks. It provides a good commentary from someone who actually shaped the field.

Measuring corruption in India

Let’s have a look at the level of corruption in India in the past few years.

Fig. 1 Global Integrity Index

Fig. 1 is the data from the Global Integrity report which measures legal framework of a country and the actual implementation of the framework associated with all things related to corruption. More the value less is the corruption. The data for 2005 and 2008 are missing. The integrity index should be interpreted as -

• Very strong (90+)
• Strong (80+)
• Moderate (70+)
• Weak (60+)
• Very Weak (< 60)

Hence India is fluctuating between weak and moderate integrity.

Fig. 2 Percentage paying bribes

Fig. 2 is prepared with data from the Global CorruptionBarometer which shows what percentage of the survey respondents gave a bribe. Data for 2007 is missing. It is interesting to see that the percentage shot up suddenly in 2009. Wonder why?

Fig. 3 Corruption Perception index of India

Fig. 3 shows the Corruption perception index of Transparency International. More value indicates less corruption.

There has been gradual decrease in the level of corruption across the years but some may say it’s not enough. Will the anti-corruption movement change the scene. We have to wait and see.