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Posts Tagged New Zealand

Randomness and Clustering: Is the Number of Twins in Timaru a Mystery? Darcy Cowan Aug 04

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If you saw 3 News last night you might have caught the story about the bumper crop of twins born this year. The prologue to the story gave the impression of a mystery with words to the effect of  “Experts are at a loss to explain it”, I personally think this was a sloppy attempt to generate some “Experts are baffled” buzz around an essential pointless story that just filled up a slow news day.

Stuff also covered the story but without the mystery aspect, good thing because the stats given at the end of the piece kind of belie that approach.

“The previous year was another big year for twins with ten sets born out of 620 babies. In 2005 and 2006 there were 542 babies born, including six sets of twins. In 2004 and 2005 only two sets of twins were found among the 571 babies born and in the 2003 and 2004 year, there were sevens sets of twins and one set of triplets in the 557 babies born.”

So in other words the number goes up and down every year and this year just happened to be a cluster of births higher than average. Boring.

What’s the deal with randomness though and why are we so poor at recognising it? We tend to think of random events or locations as those that are approximately evenly distributed in time or space. This view of randomness however gives a false impression of what it means to be truly random.

Randomness is more a measure of unpredictability than it is of aesthetic impression. There are different ways of defining this property but one approach is to apply the criteria of an algorithm. An algorithm is essentially a series of instructions, the more instructions, the more complicated the algorithm. One such might be “1. from an initial number add 5, 2. repeat step 1.”. This would be an algorithmic representation of a sequence of numbers at regular increments of 5 eg 1,6,11,16,21.

Nothing random about that, the key here though would be that a sequence of really random numbers wouldn’t be able to be represented by an algorithm that was less complicated than the sequence itself, ie it would be it’s own algorithm and would not be able to be compressed any further.

What has this got to do with groups of twins? Well, if events such as the birth of twins are actually random (simplifying the world somewhat) then we would expect to see variations in the number of births in any one place. Based on this assumption we can look back at previous numbers to see whether this year is within the range we would expect.

Using the figures from the story and removing this year’s number and the year that only 2 twins were born as a possible outlier I get a range of between 0.5% and 2% of births being twins, with a high probability that normal variation will fall in this range. The percentage of twin births this year is 1.8%, high but apparently normal.

Now the sample size here is very small so I wouldn’t put too much trust in it but it is indicative that there is nothing really out of the ordinary going on here. According to the NZ Multiple Birth Association there were 900 multiple births last year in NZ (incl. triplets) this is about 1.4% of the 63,000 live births in NZ last year. So rough and ready these numbers may be but they aren’t too far off the mark, some places will be higher than average and others lower.

So when several rare(ish) events happen at the same time or place, consider; is this really unusual? What would we expect if it was just random?

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Filed under: Psychological, Sciblogs, Science, skepticism, Uncategorized Tagged: Multiple birth, New Zealand, Probability, randomness, Science

Smoking Bans and the Effect of Health Warnings Darcy Cowan Jan 21

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In the world today there is an increasing focus on the negative aspects of smoking and a concerted attempt to reduce the presence of smoking in society. Given the harmful effects of this addiction on not only the active smoker but those around them this seems like a prudent move. Two of the approaches with the goal of minimising public exposure to cigarette smoke are the banning of smoking in businesses and public places and the addition of more strenuous warning labels on the cigarettes themselves.

Both of these tactics have been used in New Zealand with varying levels of acceptance (and success). Smoking bans draw the criticism that individual freedoms are being curtailed. This may be a legitimate point but conceptually it is no different than government enforcement of wearing seatbelts while driving on public roads. The aim is to reduce the risk of harm to the public. The real question in each case is whether the intervention is effective in it’s goals.

Addressing this question two studies last year looked at each of these methods, the first I will look at is a meta-analysis (with the concomitant problems those have, that’s another story) of the effect of smoking bans on the hospital admissions of acute myocardial infarction (that’s a heart attack to you and me). The analysis found that smoking bans were associated with an average reduction of heart attacks by 17%.

For each year a ban was in place it was accompanied by a reduction of the incidence rate ratio (the number of new cases per unit of population eg 10 cases per 100,000 people) of 26%. This indicates that the longer a ban is in force the fewer people who will be affected by heart attacks. Looks like an effective strategy to me, 17% is nothing to be sneezed at when it is individual lives you are considering. Depending on individual risk factors the chance of death in the 30 days after a heart attack can be up to 16%.

An editorial discussing these findings in more depth (in the Journal of the American College of Cardiology, the journal this study was published in) can be found Here and is a good read.

The second study focused on the how well explicit (i.e. emphasising death) cigarette pack warnings encouraged smokers to quit. Specifically it looked at smokers for whom the act of smoking formed part of the basis for their self-esteem. Subjects undertook a questionnaire that evaluated whether smoking was tied to their self esteem using statements like ‘‘Smoking allows me to feel valued by others,” and ‘‘Smoking allows me to feel worthy.” (as well as negative versions). The subjects rated how much they agreed with the statements and this was used to determine the smoking-based self esteem for each subject.

Participants were then shown pictures of cigarette packs that either had mortality related warnings (e.g. ‘‘Smoking leads to deadly lung cancer.”) or more moral or self esteem related warnings (e.g. ‘‘Smoking brings you and the people around you severe damage” and ‘‘Smoking makes you unattractive”). After a delay to allow the warnings to be filtered out of conscious awareness the subjects were asked a further series of questions to assess the effect of the warnings (e.g. ‘‘Do you intend to smoke more or less in the future?” ‘‘Do you intend to quit smoking in the future?”).

Subjects for whom smoking formed part of the basis for their self esteem actually increased their likelihood of smoking in response to warnings emphasising mortality. For these people it was the self image warnings that were most effective. Unfortunately is seems that the opposite is true for individuals that do not consider smoking to be an important factor of their self esteem so a one size fits all approach would probably not be effective. The study authors suggest that specific populations could have warnings tailored to be most effective depending on the relevance smoking has to the group identity (e.g. “young smokers who want to impress their peers.”).

This result may be applicable to other areas where minimising harm is the goal, such as drink driving campaigns.

In summary, despite any reservations regarding the form that inducements to stop smoking take it seems that the benefits are indeed worth the attempt. Also, as I often point out, the real world is more nuanced and complicated than we would generally like it to be, more effort may be required to identify sub-groups that respond most to different strategies but this also looks to be worth trying.

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Posted in Medicine, Psychological, Sciblogs, Science Tagged: American College of Cardiology, Cigarette, health, Health and Medicine, Lung cancer, Myocardial infarction, New Zealand, Review, Science, Science and Society, smoking, Smoking ban, Tobacco smoking

Measles Outbreak Darcy Cowan Aug 07

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There was a story in the NZ Herald this week regarding a Measles outbreak in Auckland and the response to this event by the Powers That Be. Whether or not the action taken (keeping unvaccinated children at home following possible contact with carriers)  is correct, either practically or ethically is a question that will be endlessly discussed by others. I would like to focus on a point made in the article about vaccination coverage in New Zealand children. It was implied that approximately 25% of NZ children are unvaccinated, at the moment data is collected at childhood “milestones” 6,12,18 and 24 months of age. At 24 months the coverage is 77%, after this age no information (currently available) is collected but it is reasonable to expect that the numbers do not climb appreciably after this age.

I found it interesting that the article did not mention that compared with other developed countries this coverage is practically dismal. The coverage in the USA is >95%, though school attendance is predicated upon receiving vaccinations exemptions are available. In the UK where recently there have been concerns over vaccination rates dropping encouraging outbreaks over there, the coverage is still >80%. Even Australia has 82% coverage at age 5. The target coverage for NZ is >95%. Why do we lag behind?

According to the National Childhood Immunisation Survey conducted in 2005, 25% of those whose children do not receive the vaccinations have made this choice due to fears of vaccine safety (another 5% had concerns over a particular vaccine). 3% of respondents reported that they did not believe vaccines work at all. More mundane reasons were also quite prominent: child was on a different schedule or immunisation was done overseas – 19%, medical reasons – 11%, thought the child was vaccinated/not sure if vaccinated ~10%. A laundry list of other reasons each had <3%. Compared with the US where the reasons mostly cited were “Philosophical or Religious beliefs against vaccination” ~66%. Considering that in many states exemption due to religious reasons are about the only ones the law will accept (barring medical reasons) this is likely to cover a wider array of actual reasons.

How should NZ tackle the vaccination issue?

See also:

Evidence Based Thought: What’s wrong with catching the Measles?

Posted in Medicine, Psychological, Sciblogs, Science, skepticism Tagged: Children, epidemic, fears, measles, New Zealand, outbreak, survey, Vaccination