Posts from January 2017 (25)

If you’d like to comment on or debate any of this week’s Stat of the Week nominations, please do so below!

There’s a story on Stuff, with more detail at either Nature News or Scientific American, that turmeric doesn’t work. The original paper in the Journal of Medicinal Chemistry isn’t open access (actually, is), but its abstract is. It’s not new chemical research; it’s a review of what’s known about curcumin, the allegedly-active ingredient of turmeric, and why they don’t believe it.  In the opposite of the academic cliche, the point of the paper is to argue that less research is needed on curcumin and similar compounds.

StatsChat isn’t MedChemChat, but the paper is relevant for two reasons. First, turmeric is one of the foods that attracts low-quality, over-publicised research, which does end up on StatsChat. Second, the reason they don’t believe in turmeric is relevant.

Turmeric, if you believe the stories, appears to have pretty much every interesting biochemical effect anyone’s ever looked for.  That phenomenon has been seen before in medicinal chemistry, and the experience is that compounds which pass a huge range of screening tests tend to do it by cheating.

In 2010, two Australian chemists wrote a paper about “Pan-Assay INterference compounds” (PAINs) (abstract, story, blog post by another chemist). Most biologically interesting properties a compound might have aren’t visible to the naked eye. A lot of work goes into devising subtle and precise assays to measure them. A compound can mess up the assay and appear to pass the test without having the specific effect you’re looking for.  One important reason for PAIN is a compound that reacts with a wide range of proteins.

Turmeric, as you will no doubt have guessed, looks like a PAIN.  This nicely explains its excellent test-tube performance with its generally disappointing performance given as food to whole animals or people.  The researchers are arguing that turmeric seems to work in the lab because it cheats, and that it seems safe but less useful than hoped in people and animals mostly because it’s not absorbed well.

As the stories are careful to note, none of this definitively implies that curcumin (or some other tumeric ingredient) couldn’t have a beneficial effect, just that most of the evidence isn’t credible.   The same argument applies to some other trendy antioxidants.

It’s a recurrent theme on StatsChat that most data aren’t the real thing you care about. The speedometer needle position isn’t the same as speed; saliva THC concentration isn’t the same as impairment; methamphetamine traces on a wall aren’t the same as use — or manufacture– by a tenant; having a Chinese name isn’t the same as being an overseas housing speculator.  The map isn’t the territory.

Photo by Flickr user saptarshikar

From the Herald

Nationwide 63.2 per cent of people today live in their own home – the lowest rate since the 61.2 per cent recorded at the 1951 Census – whereas 33 per cent live in a rental.

From Newstalk ZB

A shade over 63 percent of people today are living in their own home. 

That’s the lowest rate since 1951 when it was 61 percent.

From Newshub

Dwelling and household estimates data released on Tuesday shows that as of December 2016, 63.2 percent of people live in their own home.

One News don’t have text up yet, but their story has the same claim.

As David Welch points out in a stat-of-the-week nomination, that’s not what the number means: 63.2% is the percentage of homes occupied by at least one of their owners.  It’s the home ownership rate if you’re a house, rather than if you’re a person.

The proportion of people living in those households isn’t easy to work out — on one hand, single-person households tend to be renters; on the other hand, overcrowded households are often renters too.  StatsNZ does provide the proportion of individuals who own their home, which is rather lower, at about 50%. But that’s not the number the news stories want, either.  That’s the proportion of people 20 and older who, personally, own or part-own their homes. Living in a home owned by your parents, or your partner, or your child, doesn’t count.

That last sentence also illustrates why ‘home ownership’ is harder to define than you might think, just like unemployment.  Should a 22-year-old living with parents count towards home ownership? If not, should they count in the denominator as not home ownership, or should we just be looking at owning vs renting? How about an elderly person living with one of their children?

It would be helpful if the proportion of people living in owner-occupied households was published regularly, but it wouldn’t answer all the questions.  As an easier step, it would also be useful if the media accurately described the number they used.

We have a headline today in the Herald “New Zealand’s most monogamous town revealed“.

At first sight you might be worried this is something new that can be worked out from your phone’s sensor data, but no. It’s the result of a survey, and not even a survey of whether people are monogamous, but of whether they say they agree with the statement “I believe that monogamy is essential in a relationship” as part of the user data for a dating site that emphasises lasting relationships.

To make matters worse, this particular dating site’s marketing focuses on how different its members are from the general population.  It’s not going to be a good basis for generalising to “Kiwis are strongly in favour of monogamy”

You can find the press release here (including the embedded map) and the dating site’s “in-depth article” here.

It’s not even that nothing else is happening in the world this week.

Last year, we had a bunch of early-stage Alzheimer’s trials in the news. I thought I’d look at what’s due out in the clinical trial world this year.

Perhaps most importantly, in March we should see the first real results on a new set of cholesterol-lowering drugs.  The ‘PCSK9’ inhibitors are one of the first drugs outside the cancer world to come from large-scale genetic studies without a particular hypothesis in mind. As the gene name ‘PCSK9’ indicates to those in the know, the gene was originally named just as the ninth in a series of genes that looked similar in structure.  It turned out that mutations in PCSK9 had big effects on LDL (‘bad’) cholesterol levels. Also, importantly, there is at least one person walking around alive and healthy with disabling mutations in both her copies of the gene — so there was a good chance that inhibiting the protein would be safe.  At least three companies have drugs (monoclonal antibodies) that target PCSK9 and reduce cholesterol by a lot; though the drugs need to be given by intravenous injection.

Although the drugs have been shown to reduce cholesterol, and have been approved for sale in the US for people with very high cholesterol not otherwise treatable, they haven’t been shown to prevent heart attacks (which is the point of lowering your cholesterol). The first trial looking at that sort of real outcome has finished, and there’s a good chance the results will be presented at the American College of Cardiology meeting in March.  For people in NZ the main interest isn’t in the new treatments — it’s hard to see them being cost-effective initially — but in the impact on understanding cholesterol.  If these drugs do prevent heart attacks, they will increase our confidence that LDL cholesterol really is a cause of disease; if they don’t, they will give aid and comfort to the people who think cholesterol is missing the whole point.

What else? There are some interesting migraine trials due out: both using a new approach to prevention and using a new approach to giving the current treatments.  The prevention approach is based on inhibiting something called CGRP in the brain, which appears to be a key trigger; the drug is injected, but only every few months.  The treatment approach is based on a new sort of skin patch to try to deliver the ‘triptan’ drugs, which they hope will be as fast as inhaling or injecting them and less unpleasant.

Also, there’s an earlier-stage New Zealand biotech product that will have results early in the year: using cells from specially bred pigs, coated so the immune system doesn’t notice them, to treat Parkinson’s Disease.

Each week, we would like to invite readers of Stats Chat to submit nominations for our Stat of the Week competition and be in with the chance to win an iTunes voucher.

Here’s how it works:

• Anyone may add a comment on this post to nominate their Stat of the Week candidate before midday Friday January 13 2017.
• Statistics can be bad, exemplary or fascinating.
• The statistic must be in the NZ media during the period of January 7 – 13 2017 inclusive.
• Quote the statistic, when and where it was published and tell us why it should be our Stat of the Week.

Next Monday at midday we’ll announce the winner of this week’s Stat of the Week competition, and start a new one.

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If you’d like to comment on or debate any of this week’s Stat of the Week nominations, please do so below!

The AA are campaigning again for random drug tests of drivers. I’m happy to stipulate that in NZ lots of people smoke cannabis, and some of these people drive when stoned, and sometimes when drunk as well, and this is bad. As the ads say.

On the other hand, science has not yet provided us with a good biochemical roadside test for impairment from cannabis. For alcohol, yes. For THC, no. That’s even more of an issue in the US states where recreational marijuana use is legal, since the option of just taking away driving licences for anyone with detectable levels isn’t even there.

This isn’t just a point about natural justice. There’s empirical reason (though not conclusive) to believe that many people who might fail a biochemical test are reasonably careful about driving while high.

First, there hasn’t been any evidence of an increase in road deaths in the US states where medical or recreational marijuana use is legal, even though there has been an increase in people driving with detectable levels of the drug.

Second, if you look at the 2010 ESR report (PDF) that the AA are relying on, you find (p20)

The culpability of the drivers using cannabis by itself was determined and odds ratios have been calculated as described in the alcohol section and in Appendix two. The results are given in Table seven. The odds ratio calculated for cannabis only use is only slightly greater than one, implying that cannabis does not significantly impact on the likelihood of having a crash.

Now, the report says, correctly, that this disagrees with other evidence and that we shouldn’t assume driving while stoned is safe. But they tried quite hard to do alternative analyses showing cannabis was bad, and were unsuccessful.

In 2012, there was another AA campaign, and a story in the Herald

But Associate Minister of Transport Simon Bridges said the Government would wait for saliva testing technology to improve before using it.

A government review of the drug testing regime in May concluded the testing devices were not reliable or fast enough to be effective.

It ruled the saliva screening takes at least five minutes, is unlikely to detect half of cannabis users, and results are not reliable enough for criminal prosecution.

“The real factor is reliability … we can’t have innocent people accused of drug driving if they haven’t been.

“But as the technology improves, I’m sure in the future we will have a randomised roadside drug test.”

That seems like a sensible policy.

• Graphics, overquantified life: Andrew Elliott’s graph of his baby’s first six months of sleep
• Graphics: Bird migrations in the Americas (click for animation)
• Public policy: Graeme Edgeler has better numbers on the three-strikes law, and a new post
• Graphics: Weather forecast around the British Isles,
  from the people who tweet the Shipping Forecast
• From the Washington Post: more people die between Christmas and New Year than you’d expect. It’s true in NZ, so it’s not the weather.
• The alt-right movement finds more dumb things to do with genetic testing: the Atlantic
• A (moderately technical) short course on Fairness and Transparency in Machine Learning.
• “Missing Datasets”: a partial list of useful and important public datasets that don’t (and won’t) exist.
• Surash Venkat explains why modern data-based ‘algorithms’ aren’t at all like recipes — which is why they need to be studied statistically, not just by looking at the code or asking if the developers were pure of heart.
• “The Great AI Awakening”. From the NY Times, on Google, the revolution in machine translation, and big data.
• “Companies Ponder a Rating of Workers’ Health”. From the Wall St Journal.  One one hand, having big companies report summaries of their employees’ health might give them better incentives.  On the other hand, they’d need to get the data, and if you think about what else they might do with it…

Over the holidays, problems began emerging with the new data-based approach to detecting benefit overpayments in Australia. I learned about this from @Asher_Wolf, an Australian privacy advocate.  In a significant number of cases the computer system was  inaccurate as to whether people owed money.  Documentation to correct the errors is the sort of thing a lot of people don’t have lying around (though perhaps technically they should) and in at least some cases the computer system didn’t allow the correct information to be submitted.   The Sydney Morning Herald has a piece (warning: autoplaying audio ads) referencing Cathy O’Neil’s book Weapons of Math Destruction.

Australian regulations on government data-matching systems call for the development of a ‘program protocol’, including “description of the data to be provided and the methods used to ensure it is of sufficient quality for use in the program” and “a statement of the costs and benefits of the program.” However, in Appendix C describing the cost-benefit statement it’s made clear than only cash costs and benefits to the Commonwealth count. Monetary compliance costs to individuals don’t count, and non-monetary costs don’t count. Sending out more letters seems to counts as beneficial as long as it raises more money than you spend doing it — whether or not that money is legally owed.

The ‘technical standards’ report is supposed to cover data integrity and risks “including, but not limited to, risks to the privacy of individuals, reputational risks, and risks relating to incorrect matches.”  In particular, it’s supposed to describe “the sampling techniques used to verify the validity/accuracy of matches”.  That would be interesting to see, given that it seems to take a lot of work to prove that a match is incorrect.

In principle this might all  be worked out in the appeals process, by real humans — or, at least, the amounts of repayments might be. The stress inflicted on the recipients of the letters and the harm done to the reputation of Australia’s government data systems are harder to fix.  In the short term, the former is (rightly) getting more attention; in the long term it might be the latter that does the greater damage.