MPH Master pieces

NRT in pregnancy

Here is a good randomised controlled trial on an important topic. I remember discussing the need for this trial in some committee or other a few years ago so it's nice to see it in print.

One of the key issues with any medication during pregnancy is whether any damage is being done to the foetus. With (hopefully) such a rare event, it requires enormous numbers to be sure that a drug really is safe. But actually, all drugs confer both benefit and risk of harm: in this case the trial is ethical because as the authors say:

"There is a general consensus that nicotine-replacement therapy is probably less harmful than smoking."

 

 

Smoking laws

Laws which restrict certain actions provoke controversy so it's up to us to know the evidence. (Notice I said 'restrict certain actions' not 'curtail certain freedoms' - words matter. As scientists we should try to remain as objective as possible and 'freedom' is one of the least objective words in the dictionary.)

This is low grade evidence but it's an important question. England and Ireland have passed strong smoke-free laws; in the Netherlands the laws are weaker. So that sets up a natural experiment to compare comprehensive versus partial legislation. The data in this paper are from annual surveys of a cohort which (if I have read the report correctly) maintains response rates over 75%.

The statistical handling is complex, with 'generalised estimating equations' to handle the problem of repeat analysis on the same set of people, and also as the authors point out, of the central question:

Of key interest in this study is the period by country interaction, as it allows for formal testing of whether quit attempts and/or success evolved over the two time periods differently in each of the three countries.

Comprehensive legislation also seems to create more support among smokers than partial bans. 

 

Smoking - the social context

Here is an interesting use of data from a national survey. Must admit I hadn't heard of the British Household Panel Survey before, but the 'Panel' in the title indicates that it is longitudinal - the sample people are interviewed in successive years. Hence behaviour change - in this case smoking quitting and smoking initiation - can be studied.

The questions on social capital are pretty basic - one question on whether you can trust other people, and one on membership of groups and clubs - but that is typical for items in omnibus surveys. Nevertheless the results are interesting.

Not quite sure why it took two authors in Sweden to analyse this British dataset! but it reminds us that often with these large datasets contain a wealth of knowledge waiting to be revealed by creative ideas for analysis.

The BHPS is now part of the new 'Understanding Society' survey, which also incorporates health measurements such as blood pressure, BMI, SF12 and much else.

Smoking bans - cars and children

Surveys like this are important to build the case for legislation. Politicians like to do good, and they like it even more if doing good doesn't lose them votes. So it is up to us to create and demonstrate popular support. That's pretty much how it happened for seat belt legislation in the 1970s.

These surveys show that even smokers think smoking should be banned in cars when children are in them.

Also note that some jurisdictions have already enacted this legislation, and when you do so support increases. 

Smoking bans

In 2006, Scotland banned smoking in public places - pubs, workplaces etc.

You might think that this doesn't do much for children because (1) they aren't in pubs and (2) they aren't at work. Not so, as this paper shows. It's a time series analysis, so not proof beyond all doubt. But it's hard to think of anything else to explain the picture. Notice that the the paper shows data from 2000, and a good data run after the legislation. This is important - beware a time series which doesn't give you a good long data run before the period of interest.

Hospital admissions could in theory go down if children are dying more before reaching hospital - but there's no reason to think that's what is happening here. 

The tobacco industry argued that a ban on smoking in pubs would mean people going home to smoke and so making things worse for children. They were wrong.

 

Smoking - mums and kids

Last week's blog was about a large scale social social network.  Here it is up close and personal: the target group were 6th and 7th grade pupils (aged about 12) and their mothers.

The intervention was added on to a standard smoking intervention ,

"The central component of the Linking Lives intervention was a written manual that focused on effective communication and parental monitoring strategies for preventing adolescent tobacco use. The manual consisted of 9 short modules written at a fourth-grade reading level and 2 tobacco-related homework activities for parents to use at home with their adolescent."

There is some good process measurement of the intended mechanism (e.g. intervention children more likely to see their mothers as trustworthy) with a primary outcome of 'ever smoked'. This was assessed by self report. On this measure the trial was very successful with a 42% reduction in 'ever smoked'. At baseline about 5% had ever smoked; at follow up 10% of the intervention group and 15% of the comparison group had ever smoked. Follow up was for 15 months, so this reports the situation in 14 year-olds. I guess the numbers will rise as they get older.

The intervention was directed at Latino and African American groups. I wonder whether mother-child relationships in those communities are stronger / weaker / different from mother-child relationships in other communities.

 

Passive smoking laws

Did the laws against smoking in public places work? We need to know because sooner or later (maybe right now, infact) someone will try to get them repealed. 

So here is an analysis. You can't do a randomised trial with laws, so the analysis is before-and-after. Sometmes it's easy to see an abrupt change as a law is introduced, but not here. The graph is seesawing all over the place with random variation but to my eye there is a general downward drift from about 2003 onwards. Trouble is, it isn't an abrupt change on the day the law came in on 2 July 2007.

Thinking about it, you wouldn't really expect that. Laws of this type (unlike tax changes...) take time to become introduced and embedded; in general social laws lag, not lead, public opinion. You can't pass a law like this unless most people already agree with it. The same was true of seat belt laws.

The statisticians have used Poisson regression because the data are counts (whole numbers).

We should also congratulate the authors for presenting the raw data as a graph. If all they had given us was the statistics, we might have fored a very different opinion. Always look for some unmodified data in a paper! - it's suprising how often all you get is odds ratios / adjusted rates etc etc/

Smoking trajectories

There are now some good programmes you can run in schools to delay the initiation of smoking. But the million dollar question is - does delay equal success? Or do kids smoke as much in the end?

 Here is an analysis from California which gives hope. It seems that cohorts which start smoking later end up with fewer smokers - at least in a place which has run well funded, statewide programmes for many, many years. Probably not much use running programmes in schools and then sending children out into an unreformed community.

Tobacco control - harm reduction or zero tolerance?

Here is an interesting exchange of views on tobacco control. Note that with questions like this there is little evidence and plenty of assertion!

A heavyweight team from the UK argue that we need to treat smoking like other addictions and go for harm reduction with 'MN' - medicinal nicotine. Commentators from Australia, India and Hong Kong are not convinced.

What do you think?

Smokefree Scotland

 Here is an evaluation of the effect of the smoke-free laws in Scotland. This is one of those things we absolutely need to know about if we are in public health but the paper, particularly the methods section, is not an easy read. The basic design is a questionnaire survey.

There are two difficult bits in the methods section. Firstly the survey respondents were recruited in several different survey waves with top-up samples for drop out. All this will give plenty of material for the tobacco companies to rubbish the research. Our task is to form a balanced judgement about whether the resulting sample is likely to give us truth or not - and to accept that we may have to conclude with regret that it does not. Important to be alert to flaws, particularly when research appears to say what we want it to say. 

The other difficult bit in the methods section is the statistical methodology. There is a lot of weighting to make the samples representative of the base populations. But more tricky for the non-statistician is the use of generalised estimating equations (GEE). The main benefit of using GEE is to get right (or as right as possible) the confidence intervals on all the results. But it also permits analysis of interactions between variables. As the authors point out, the key question is whether the various measures changed more in Scotland than in the rest of the UK. They have before-and-after measures (i.e two waves of results) in two areas, so technically speaking they are looking for a wave-by-area interaction.