Ian Pool, 1936-2022

I was very saddened to hear of the passing of Ian Pool at the end of last month. I have held off on posting about this, waiting for a good obituary to show up online. I was not to be disappointed - Stuff published a beautiful obituary by Brian Easton earlier today. For those who don't know, Ian Pool is widely regarded as the founding father of New Zealand demography. He set up the Population Studies Centre (PSC) at the University of Waikato, which remains a national centre of excellence in demography and population studies (in its latest incarnation, renamed as Te Ngira - Institute for Population Research). Ian was well known for his work on African demography, as well as Māori demography, among many other contributions to the field.

I had many interactions with Ian over the years, including as a co-author and a co-researcher. When I first met him, sometime in the mid-2000s, I was working as a research assistant for Jacques Poot at the PSC, and completing my PhD in economics. Ian initially struck me as one of those infuriating people who have the habit of constantly name-dropping famous people they have met. However, Ian's name-dropping wasn't merely a cynical attempt to big-note himself - he really did know and had closely interacted with Joseph Stiglitz, Thomas Piketty, and others. And I have to admit feeling a bit of a warm glow some years later when Ian name-checked me in a seminar or presentation (more than once) for my work on stochastic population projections.

My interactions with Ian also resulted in what is possibly one of the big missed opportunities of my career. Ian was very keen to have me work on a new research idea, distributional national accounts. I was mildly interested, but didn't have the time to devote to it immediately. I also had other priorities, especially in trying to establish a longitudinal ageing study based at Waikato (an initiative that eventually proved to be a dead end, as despite a lot of positive end-user engagement, we couldn't secure sufficient funding to make the study feasible). Anyway, I hadn't realised at the time just how important the idea of distributional national accounts was to become, as well as its centrality to the work of Piketty, Emmanuel Saez, and others. Distributional national accounts were also a key contribution to the work of the High-Level Expert Group on the Measurement of Economic Performance and Social Progress, co-chaired by Stiglitz, Fitoussi, and Durand, as noted in the book Measuring What Counts (which I reviewed here). Ian was at the cutting edge, but sadly, I don't believe that he did find someone to work on New Zealand's distributional national accounts.

I was never a student of Ian's, but I did sit in on a workshop that he gave some years ago, on how to derive and interpret life tables. He was an excellent communicator, and clearly would have been a great teacher and mentor to students at all levels. I have had the pleasure of working with a number of his excellent former PhD and graduate students, including Natalie Jackson and Tahu Kukutai. I'm sure that a more complete roll call of Ian's students would reveal just how much of an impact he has had, and continues to have, on population studies and demography both in New Zealand and internationally.

Aside from his research contributions, Ian was just a lovely, generous, and sincere man. He was patient and kind to colleagues and students alike, and a fountain of knowledge on many things. He will be greatly missed.

The problem with studies on the relationship between alcohol outlets and sexually transmitted diseases

I've done a fair amount of research on the impacts of alcohol outlets on various measures of alcohol-related harm. That work has focused predominantly on violence, property damage, and crime generally. One thing I haven't looked at is the relationship with sexually transmitted diseases. That is for good reason. Crime is an acute outcome associated with drinking, and is measurable almost immediately. That distinguished crime from longer-term negative consequences of drinking such as liver cirrhosis, for example.

However, in-between those two extremes are some alcohol-related harms that we could refer to as medium-term harms. For example, the theoretical link between alcohol consumption and risky behaviour, including risky sex, seems clear. So, if having more alcohol outlets in a particular area is associated with greater alcohol consumption (following availability theory, as I discussed in this post earlier this week), then alcohol outlets should be positively associated with greater prevalence of sexually transmitted diseases. Sexually transmitted diseases do not become immediately apparent in the way that violence or property damage does, but they don't take years to manifest in the way that cirrhosis does.

There have only been a few studies on the relationship between alcohol outlets and sexually transmitted diseases. So, I was interested to read two studies recently related to this topic, which had been sitting on my to-be-read pile for some time. The first study was reported in this 2015 article by Molly Rosenberg (Harvard School of Public Health) and co-authors, published in the journal Sexually Transmitted Diseases (ungated NLM version here). They look at the relationship between alcohol outlets and Herpes Simplex Virus Type 2 (HSV-2) prevalence among young women (aged 13-21 years) in the Agincourt Health and Demographic Surveillance System site in South Africa. The Agincourt sample has predominantly been used as an HIV surveillance site, and there are dozens of studies based on this sample. However, they didn't look at HIV as an outcome in this study:

...because of the small number of prevalent infections at baseline and the likelihood that at least some of the cases were a result of perinatal, as opposed to sexual, transmission.

Fair enough. Perinatal transmission of HIV (transmission at or around the time of birth) has been a serious problem, but I guess it must be less of a problem for HSV-2. In their analysis, Rosenberg et al. essentially counted the number of alcohol outlets (both on-licence and off-licence combined) in each village, and related that number to HSV-2 prevalence for the 2533 young women in their sample. They found that:

Treating the alcohol outlet exposure numerically, for every 1-unit increase in number of alcohol outlets per village, the odds of prevalent HSV-2 infection increased 8% (odds ratio [OR; 95% CI], 1.08 (1.01–1.15]). The point estimate changed minimally after adjustment for village- and individual-level covariates (OR [95% CI], 1.11 (0.98–1.25]); however, this adjusted estimate was less precise.

Not only was it less precise, but it becomes statistically insignificant (barely), which they don't note. So, this doesn't provide strong evidence of a link between alcohol outlets and sexually transmitted diseases, although the evidence is suggestive. The problem is that the analysis essentially assumes that all young women in the same village have the same exposure to alcohol. This marks the number of outlets as an imperfect proxy for the real exposure variable, and suggests that the real effect might be larger. Again, this is suggestive evidence at best.

The second study was reported in this 2015 article by Matthew Rossheim (George Mason University), Dennis Thombs, and Sumihiro Suzuki (both University of North Texas), published in the journal Drug and Alcohol Dependence (sorry, I don't see an ungated version of this one online). This study did look at HIV as an outcome, relating zip-code-level HIV prevalence to the number of alcohol outlets (of different types) across 350 cities in the US. Perinatal transmission of HIV is not much of a problem in the US (certainly not compared to South Africa at the time that the Agincourt sample were born). Based on their data for a little over 1000 zip codes, Rossheim et al. found that:

...the presence of one additional on-premise alcohol outlet in a ZIP code was associated with an increase in HIV prevalence by 1.5% (rate ratio [RR] = 1.015). In contrast, more beer, wine, and liquor stores and gas stations with convenience stores were associated with lower HIV rates (RR = 0.981 and 0.990, respectively). Number of pharmacies and drug stores was not associated with HIV prevalence (p = 0.355).

On-premise outlets (predominantly bars and nightclubs) were associated with higher HIV prevalence, while liquor stores and gas stations were associated with lower HIV prevalence. Rossheim et al. don't have a good explanation for why, although they note a number of obvious limitations with their study. The literature on the impacts of alcohol outlets is littered with these sorts of inconsistent findings.

The real problem with a study like this is the time lapse between the alcohol consumption and the measured outcome variable. As I noted at the start of this post, with acute harm (like violence or property damage), the effect is immediately seen and can be measured, and likely occurred close to the location of alcohol consumption. With HIV prevalence, there is only a small chance that HIV was contracted as a result of activity within the local area. People move about over time, they 'interact' with people in many locations, and they can migrate from city to city. So, all we can say with this study is that people living with HIV tend to live in areas that have lots of bars and night clubs, and tend to live in areas that have fewer liquor stores and gas stations. Call this the gay-men-live-near-night-clubs effect, if you want to evoke a bunch of stereotypes. This effect is correlation, and it is difficult to say with any certainty if there is any causal relationship here.

Now, the Agincourt study has this problem as well, but the young women there probably still live in the same village they grew up in, so in that case the exposure to alcohol can be (imperfectly, as I noted above) proxied by the number of outlets in the village. And the symptoms of HSV-2 appear within a week, rather than weeks or months later as can be the case for HIV. So, moving about is less of an issue, although not eliminated entirely.

Anyway, these two studies are interesting, but they mainly highlight the problems with this broader literature. When we move beyond measuring acute harms associated with alcohol outlets, it isn't clear that the associations that are being measured are anything more than spurious correlation.

Stephen Hickson on the fight against woolly words

I'm loving Stephen Hickson's work lately. In addition to writing about the stupidity of removing GST from food last week (which I posted about here), and co-authoring a piece in The Conversation with myself and others on our 'quick takes' on Budget 2022, he wrote the most hilarious post on LinkedIn yesterday:

Woolly words...

I came across this article today (not sure if you need a subscription to read it or not but the gist of it is in the first paragraph "FIRE-FIGHTING FOAM starves the flames of oxygen. A handful of overused words have the same deadening effect on people’s ability to think. These are words like “innovation”, “collaboration”, “flexibility”, “purpose” and “sustainability”. They coat consultants’ websites, blanket candidates’ CVs and spray from managers’ mouths. They are anodyne to the point of being useless. These words are ubiquitous in part because they are so hard to argue against."

https://lnkd.in/dGmNY_ub

Imagine if the government becomes aware of the damage that the excessive use of these words is causing… there's a good chance that the Government will sign up to an international accord to limit the use of Woolly Words. In an attempt to make good on that commitment they will introduce a Woolly Words Trading Scheme (WWTS). In order to get political buy-in some sectors will initially be exempt despite being the biggest users of Woolly Words, e.g. Marketing companies. Additionally the cap on Woolly Words won’t initially be binding and so everyone will agree that the WWTS is pretty weak. Eventually this will get fixed though it will take a while. But a WWTS isn’t very sexy and doesn’t look like the government is really doing anything. So they’ll start doing things that make little sense and are expensive but look a lot sexier. For example they’ll offer to subsidise at great expense the use of better words in mission statements and annual reports of some arbitrarily favoured organisations in return for them reducing their own use of Woolly Words. Or they’ll simply ban the use of Woolly Words in some sectors such as health. While this makes these organisations and sectors less woolly it doesn’t reduce the overall quantity of Woolly Words available when the WWTS is binding. It couldn't possibly happen could it?

It's not hard to see that this is a satirical take on the emissions trading scheme, including the exclusion of agriculture, and the various tinkering the government undertakes to try and solve problems that would more easily be solved if the scheme were comprehensive. In my ECONS102 class, we characterise an efficient property rights system as one that has four key features:

1. Universal - all resources are privately, publicly, or communally owned and all entitlements are completely specified;
2. Exclusive - all benefits and costs accrued as a result of owning and using the resources should accrue to the owner whether directly or indirectly;
3. Transferable - all property rights should be transferable from one owner to another in a voluntary exchange; and
4. Enforceable - property rights should be secure from involuntary seizure or encroachment by others.

The emissions trading scheme (and the woolly words trading scheme) creates a property right - the right to emit carbon (or the right to use woolly words). The scheme will only be efficient if it is universal - that is, all emissions (or woolly words) must be covered by the scheme. When agriculture (or marketing) is excluded, they can generate as many emissions (or woolly words) as they like, essentially without consequence. If the government is concerned about their emissions (or woolly words), then the government has to create all sort of other regulations to keep them in line. Which is completely unnecessary, since including them within the trading scheme would be much more efficient (lower cost, and simpler all around).

If we really are concerned about carbon emissions (or woolly words), we have the means to limit them. Excluding favoured sectors from the trading scheme is pure politics, combined with a fair amount of fingers-in-the-ears-I'm-not-listening-to-you, and that is going to cost us far more in the long term.

Fast food outlets, obesity, and why we do meta-analysis

Some time back, someone (I forget who) pointed me to this report by Christopher Snowdon (Institute of Economic Affairs) on the relationship between the density of fast food outlets and obesity. It was of interest to me because the underlying theory linking fast food outlets to obesity is substantively the same as one of the key theories linking alcohol outlets and various measures of alcohol-related harm. That theory is known as availability theory, and posits that more outlets (fast food, or alcohol) in a particular area reduces the 'full cost' of the good (fast food, or alcohol), and therefore increases consumption (the straightforward consequence of a downward-sloping demand curve). The 'full cost' includes the price, as well as the cost of travelling to obtain the good. Both of those components of the full cost may be lower when there are more outlets. Price may be lower due to greater local competition, while travel cost may be lower because each consumer will likely live closer to the nearest outlet. The last component of availability theory is that because there is more consumption (fast food, or alcohol), there are more problems (obesity, or alcohol-related harms). This last component is essentially taken on faith.

Anyway, Snowdon summarises the literature analysing the relationship between fast food outlets and obesity, which is made up of 74 studies published between 2004 and 2017. I say summarise, rather than review, for good reason. Snowdon's report doesn't provide a critical appraisal of the quality of the included studies, nor does it attempt to synthesise from this literature, other than to conclude that:

Of the 74 studies identified, only fifteen (20%) found a positive association between the proximity and/or density of fast food outlets and obesity/BMI. Forty-four (60%) found no positive association, of which eleven (15%) found a negative (inverse) association. Fifteen (20%) produced a mix of positive, negative and (mostly) null results, which, taken together, point to no particular conclusion.

Of the 39 studies that looked specifically at children, only six (15%) found a positive association while twenty-six (67%) found no association and seven (18%) produced mixed results. Of the studies that found no association, five (13%) found an inverse relationship between fast food outlet density/proximity and childhood obesity/overweight...

Overall, the weight of evidence suggests that there is no association between obesity and either the proximity or density of fast food outlets to schools, homes and workplaces.

When Snowdon refers to the 'weight of the evidence', you can almost take him literally. He has effectively counted the number of studies on each side of the debate, and concluded that the side with more studies is correct. That is not how literature should be reviewed, as it takes no account of the quality of the methods or data in each study, nor the diversity (or lack thereof) in study contexts (most of the studies were conducted in the US).

To be fair to Snowdon, he does say that:

Science is not decided by sheer weight of numbers, but the fact that most studies in the literature have found no association between obesity/BMI and fast food outlet density/proximity strongly suggests that no such relationship exists. This conclusion is not based on an absence of evidence. There is plenty of evidence.

However, the second part of that quote seems to contradict the first part. Anyway, how could we do better? A quick and dirty assessment of the journals in which these 74 studies were published suggests to me that we might put more weight on those that found positive associations between fast food outlets and obesity, as they were published in high-quality journals like the American Economic Journal: Economic Policy, Health Economics, and Social Science and Medicine. Studies that found mixed or null results were published in (among others) Social Science and Medicine, Economics and Human Biology, American Journal of Public Health, and Journal of Urban Health. Maybe that's only a slight difference in the quality of journals though, and you might argue that there is greater publication bias towards statistically significant results in higher-quality journals. On the other hand, you'd expect the better journals to take a harder line on quality of analysis. A second alternative is to expect that more recently published articles are likely to have built on the learnings of earlier articles, and therefore should have more weight. In that case, we would tend more towards the mixed and null findings, as those that found positive associations tend to be older.

Both of those approaches are admittedly crude. A much better approach is to actually synthesise the literature properly. You could do this narratively, or you could apply meta-analysis, where the coefficient estimates are combined quantitatively to arrive at an overall measure of the relationship between variables (in this case, the relationship between fast food outlets and obesity). Meta-analysis is much more credible than simply listing the papers and counting them. It doesn't apply a crude statistically-significant-or-not approach, since both the coefficient estimates and the standard errors are included in the overall estimate. That way, we aren't ignoring or potentially misclassifying studies with large, but imprecisely measured, coefficients.

It seems to me that this literature on fast food outlets and obesity is ripe for a meta-analysis (although, here is one that focuses on childhood obesity). That might make a nice project for a suitably motivated and interested Honours or Masters student.