Tea drinking vs. beer drinking, and mortality in pre-industrial England

When I introduce the difference between causation and correlation in my ECONS101 class, I talk about how, even when there is a good story to tell about why a change in one variable causes a change in the other, that doesn't necessarily mean that an observed relationship is causal. It appears that I am just a susceptible to a good story as anyone else. When a research paper has a good story, and the data and methods seem credible, I'm willing to update my priors by a lot (unless the results also contradict a lot of the prior research). I guess that's a form of confirmation bias.

So, I was willing to accept at face value the results of the article on tea drinking and mortality in England that I blogged about earlier this week. To recap, that research found that the increase in tea drinking in 18th Century England, by promoting the boiling of water, reduced mortality. However, now I'm not so sure. What has caused me to re-evaluate my position is this other paper by Francisca Antman and James Flynn (both University of Colorado, Boulder), on the effect of beer drinking on mortality in pre-industrial England.

Antman is the author of the tea-drinking article, so it should be no surprise to expect that the methods and data sources are similar, given the similarity of the two papers in terms of research question and setting. However, there are some key differences between the two papers (which I will come to in a minute). First, why study beer? Antman and Flynn explain that:

Although beer in the present day is regarded primarily as a beverage that would be worse for health than water, several features of both beer and water available during this historical period suggest the opposite was likely to be true. First, brewing beer would have required boiling the water, which would kill many of the dangerous pathogens that could be found in contaminated drinking water. As Bamforth (2004) puts it, ‘the boiling and the hopping were inadvertently water purification techniques’ which made beer safer than water in 17th century Great Britain. Second, the fermentation process which resulted in alcohol may have added antiseptic qualities to the beverage as well...

Notice that the first mechanism here is basically the same as for tea. Boiling water makes water safer to drink, even when it is being used in brewing. Also:

...beer in this period, which sometimes referred to as ”small beer,” was generally much weaker than it is today, and thus would have been closer to purified water. Accum (1820) found that small beer in late 18th and early 19th century England averaged just 0.75% alcohol by volume, a tiny fraction of the content of even the ‘light’ beers of today.

The data sources are very similar to those used for the tea drinking paper, and the methods are substantially similar as well. Antman and Flynn compare parish-level summer deaths (which are more likely to be associated with water-borne disease than summer deaths) between areas with high water quality and low water quality, before and after a substantial increase in the malt tax in 1780. Using this difference-in-differences approach, they find that:

...the summer death rate in low water quality parishes increases by 22.2% relative to high water quality parishes, with a p-value on the equality of the two coefficients of .001.

Antman and Flynn then use a second identification strategy, which is to compare summer deaths between parishes that have gley soil (suitable for growing barley, which is then malted and used to make beer) and parishes without gley soil, before and after the change in the malt tax. In this analysis, they find that:

...parishes with gley soil had summer death rates which increased by approximately 18% after the malt tax was implemented relative to parishes without gley soil.

Not satisfied with only two identification strategies, Antman and Flynn then use a third, which is rainfall. Their data is limited to the counties around London (because that is where they have the rainfall data from). In this analysis, they find that:

...the effect of rainier barley growing seasons on parishes with few nearby water sources is positive and significant, indicating that summer deaths rise following particularly rainy barley growing seasons... [and] ...rainy barley-growing seasons lead to more summer deaths in areas where beer is most abundant, even controlling for the number of deaths occurring in the winter months.

So, the evidence seems consistent with beer drinking being associated with lower mortality, because in areas where beer drinking decreased (because of the increase in the malt tax) by a greater amount, mortality increased by more.

But not so fast. There are two problems here, when you compare across the tea drinking and beer drinking research. First, the data that they use is not consistent. The tea drinking paper uses all deaths in each parish. The beer drinking paper uses only summer deaths, arguing that summer deaths are more likely to be from water-borne causes. If that is the case, why use all deaths in the tea drinking paper? What happens to the results from each paper when you use the same mortality data specification?

Second, the increase in the Malt Tax was in 1780. The decrease in the tea tax (which the tea drinking paper relies on) was in 1784. The two tax changes are awfully close together timewise, and disentangling their effects would be difficult. However, neither paper seems to account for the other properly. The beer drinking paper includes tea imports as a control variable, but in the tea drinking paper it wasn't tea imports, but tea imports interacted with water quality that was the key explanatory variable (and the timing of the tea tax change interacted with the water quality variable). The tea drinking paper doesn't really control for changes in beer drinking at all.

That second problem is the bigger issue, and creates a potentially problematic omitted variable problem in both papers. If you don't include changes in tea drinking in the beer drinking paper, and the two tax changes happened around the same time, how can you be sure that the change in mortality was due to tea drinking, and not beer drinking? And vice versa for failing to include changes in beer drinking in the tea drinking paper.

However, maybe things are not all bad here. Remember that the two effects are going in opposite directions. It is possible that the decrease in the tea tax increased tea drinking, and mortality reduced, while the increase in the malt tax decreased beer drinking, and mortality increased. However, then we come back to the first problem. Why use a measure of overall mortality in the tea drinking paper, and a measure of only summer mortality in the beer drinking paper, when both papers are supposed to be looking at changes in mortality stemming from water-borne diseases?

Hopefully now you can see why I have my doubts about the tea drinking paper, as well as the beer drinking paper. Both are telling an interesting story, but the inconsistencies in data and approach across the two papers should make use extra cautious about the results, and leave us pondering the question of whether the results are causal or simply correlation.

[HT for the beer paper: The Dangerous Economist]

Read more:

• Tea drinking and mortality in pre-industrial England

Tea drinking and mortality in pre-industrial England

[Update: I now have some doubts about this paper - see this follow-up post]

The importance of clean water for public health is thoroughly uncontroversial in modern times. In the temporary absence of a safe water source, one recommendation is to boil water for drinking, which will kill off most bacteria and other pathogens. However, prior to the acceptance of the germ theory of disease, the importance of clean water was relatively unknown. Water-borne diseases such as dysentery and cholera were relatively common (at least, compared with modern times).

In the late 17th Century, the English began drinking tea in large numbers (more on that in a moment). One of the important aspects of tea drinking is that it requires boiling of water. Did that lead to a reduction in mortality, especially from water-borne disease? That is the research question addressed in this forthcoming article by Francisca Antman (University of Colorado, Boulder), to be published in the journal Review of Economics and Statistics (ungated earlier version here, and relatively non-technical summary by the author here). Why investigate this? Antman notes that:

...several historians have suggested that the custom of tea drinking was instrumental in curbing deaths from water-borne diseases and thus sowing the seeds for economic growth.

Antman's research is the first to quantitatively attempt to assess these claims. She uses data on mortality rates at the parish level for 404 parishes from the mid-16th Century to the mid-19th Century, and a couple of different proxies for water quality:

The primary water quality measure used in the analysis is the number of water sources within 3 km of the parish, as calculated using data from the United Kingdom Environment Agency Statutory Main River Map of England overlaid on a map of historical parish boundaries... It is expected that parishes with a higher number of rivers proximate to the parish would have benefited from greater availability of running water, and thus would have benefited from relatively cleaner water compared with those parishes which were limited to only a few sources and thus suffered from a greater likelihood of contamination...

An alternative water quality proxy, the average elevation within a parish, is also offered to show that the relationship between tea and mortality is robust to alternative measures of water quality... Elevation is believed to be positively correlated with water quality because parishes at higher elevation would have been less likely to be subjected to water contamination from surrounding areas.

Antman applies two different strategies to identify the effect of tea drinking on mortality. In the first, she compares the decline in mortality between high (above the median) water quality parishes and low (below the median) water quality parishes over time. She particularly compares the difference between before and after the widespread adoption of tea drinking, which she dates as:

...the Tea and Windows Act of 1784 which reduced the tea tax from 119 to 12.5 percent at one stroke...

The second strategy uses lagged national-level tea imports as an indicator of when tea drinking increased in prevalence, but is otherwise similar. The results from the first strategy are nicely summarised in panel A1 of Figure 1 from the paper:

Notice that mortality declines in both high-water-quality parishes (dashed line with diamonds) and low-water-quality parishes (solid line with circles) after 1784, but that the decline was larger in low-water-quality parishes. And even though there is an up-tick in mortality towards the end of the time period (probably due to urbanisation, as urban areas had higher mortality than rural areas), the difference between high-water-quality and low-water-quality parishes continued to increase. Antman notes that:

With regard to the magnitudes of the impact of tea drinking on mortality, the estimates suggest that areas with worse water quality saw yearly mortality rates drops by about 18% by the end of the period, relative to parishes with better water quality...

The results are similar using the second strategy, although the size of the effect was smaller. Antman also shows that her results are robust to controlling for smallpox mortality, and to controlling for wages, as well as robust to including different proxies for parish-level population. So, it does seems that tea drinking, by promoting the boiling of water, did reduce mortality in pre-industrial England.

[HT: The Dangerous Economist, last year]

The procyclical relationship between mortality and economy

Since the beginning of the pandemic, I've gotten more than a little tired of the whole economy vs. public health debate. Especially when lockdowns were new, the media seemed to have this lazy public-health-experts-favour-lockdowns vs. economists-argue-against-lockdowns theme going on. But what if both sides were wrong? Lockdowns may save lives from coronavirus, but reduce preventive healthcare and diagnosis of medical problems like cancer, which might result in more deaths overall. Not having lockdowns may reduce the economic impact from business closures, but what about the economic impact of increased death and illness from coronavirus? I think it will take us a while to disentangle everything, and hopefully we'll know better for next time.

In the meantime, here's something else to think about. In this discussion paper from late last year, Kadir Atalay, Rebecca Edwards, Stefanie Schurer, David Ubilava (all University of Sydney) looked at the relationship between the business cycle and mortality, using annual state-level data from Australia over the period from 1979 to 2017 (see also the non-technical summary on The Conversation). Interestingly, past research has shown that there is a negative relationship between unemployment (a measure of the business cycle) and mortality - that is, mortality is higher when the economy is doing better and unemployment is lower. That might seem surprising at first, but Atalay are able to confirm this relationship with their Australian data, but only for a subset of age groups:

Overall, we find no effect of unemployment on all-cause mortality... A 1 p.p. increase in the unemployment rate is associated with a zero impact on mortality (-0.02 percent and statistically insignificant). The effect is likewise statistically insignificant when estimated separately for men and women...

We observe that mortality is procyclical for the youngest age group (0-24 years) in the pooled sample (-1.8 percent, p-value<0.05) and for men (-1.9 percent, p<0.10) and women (-1.5, p-value<0.10) separately. Hence, there are fewer deaths in times of economic growth for the young. For those 25-64 years and 65 years of age and older, we do not observe any significant relationship.

Drilling down further into the five-year age groups, they find that it's essentially a result of men aged 20-39 years, as shown in their Figure 4, Panel A:

Notice that the only statistically significant bars are among the age groups 20-39 years. The corresponding figure for women shows no statistically significant effects. So, what is going on here? Atalay et al. next look at cause-specific mortality, and find that:

...higher unemployment is associated with fewer vehicle accident (road) deaths. An increase in the unemployment rate by 1 p.p. is significantly associated with a 6 percent decrease in transport accidents (p-value<0.05)... The number of lives saved are five time [sic] larger for men (73 fewer deaths) than for women (15 fewer deaths).

In other words, mortality is positively associated with the business cycle, that effect is concentrated among young men, and is driven by changes in the number of motor vehicle accidents. The mechanism seems clear - when the economy is doing better, people drive more, and that increases the risks of accidents, injuries and deaths. That is both interesting and plausible. However, Atalay et al. then probably over-reach in their conclusion:

Our findings allow us to propose an estimate for the likely impact of the recession associated with the pandemic and the Great Lockdown on mortality. If unemployment rates rise from the February 2020 rate of 5.1 percent to 10 percent as predicted by the Reserve Bank of Australia, we would expect almost 425 fewer deaths due to vehicle transport accidents. This reduction in the number of deaths is equivalent to approximately 30 percent of all transport accidents in 2017.

Although lockdowns did create a snap recession in Australia, and people drove less because they were confined to home, there is no reason to believe that the relationship observed over the period 1979 to 2017 would continue to hold. The pandemic period really is an out-of-sample event. However, we should take this as suggestive evidence in favour of lockdowns reducing mortality, and through a mechanism that isn't directly related to coronavirus.