Lower Life Expectancy in a State is Correlated with a Higher Share Voting for Trump

A lower life expectancy in a state is associated with a higher share in the state voting for Trump.  The chart above shows the simple correlation, using state-wide averages, between the life expectancy in a state and Trump’s share of the vote in that state in the 2020 presidential election.  States where life expectancy is relatively low saw, on average, a higher share of their population voting for Trump.  Life expectancy was especially low in a set of mostly Southern states that also had a high share voting for Trump (the bottom right corner of the chart).

The figures on life expectancy come from a recently issued set of estimates produced by the CDC.  The CDC estimates are geographically highly detailed, providing estimates down to the census tract level, but I have only used here the overall state-wide averages.  Due to their fine level of geographic detail, the CDC estimates are averaged over several years (2010 to 2015) to smooth out year-to-year statistical noise.  But life expectancy figures generally change only slowly over time (2020 was an exception, due to Covid-19), so figures for 2010-15 will provide a good estimate of what should be considered normal for life expectancy currently (i.e. with the exception of the Covid-19 impact).  The presidential election results are from Wikipedia, where the Trump share is his share in the overall vote in each state (including third party and other minor candidates).

The correlation is a strong one.  The regression equation (shown in the chart) for the relationship has an R-squared of 0.45.  This means that if one simply knew the life expectancy in a state, one could predict 45% of the variation in the share across the states that would vote for Trump.  This is high for such a simple cross-section relationship.  The negative slope of the equation (-0.11) means that every percentage point increase in the share of the vote for Trump is associated with a 0.11 year lower life expectancy.  Or put another way, a state with a life expectancy that is one year less than in another is associated with an expected 9 percentage point higher share of those voting for Trump (where 9 is roughly equal to 1 / 0.11).

Why this correlation?  Note that it is not saying that a high or low life expectancy in itself would necessarily be driving a tendency to vote for Trump or not.  Rather, a number of factors that enter into the determination of life expectancy are quite possibly also factors in common with the views of Trump supporters.  Life expectancy depends on personal factors and decisions (smoking, diet and exercise, obesity, vaccinations, whether to wear a mask to protect oneself and others to reduce the spread of a deadly disease), as well as on decisions made by state and local governments chosen by that electorate   (such as on access to health care, e.g. whether Medicaid should be available for the poor).  Life expectancy also depends on income levels and for any given average income level on income inequality.

And it will depend on the social norms of the region, such as car driving habits (speeding) and access to guns.  Of the factors reducing life expectancy in the US between 2014 and 2017 (mostly offsetting factors that would have, by themselves, led to a higher life expectancy) unintentional injuries accounted for just over half (50.6%) while suicides and homicides accounted for a further 15% (suicide 7.8% and homicide 7.5%).  That is, these non-medical factors accounted for two-thirds of the factors that had a negative impact on life expectancy in this period.

Few would question that better health is better than poorer health.  The high correlation seen here between life expectancy and the degree of Trump support suggests that there are significant commonalities in the various states between behaviors (both personal and social) that lead to poorer health outcomes and support for Trump.

Trump’s Mismanagement of the Covid-19 Crisis: South Korea Shows What Would Have Been Possible

Source:  David Leonhardt, Newsletter of April 13, 2020, The New York Times

I normally only include charts I have developed myself in this blog, but the chart above, from David Leonhardt of the New York Times, is particularly striking.  It comes from his newsletter of April 13, and shows the daily number of deaths (on a seven-day moving average) per 10 million people, from February 19 to now in the US and in South Korea.

It shows what the US could have achieved had the Trump administration managed this crisis as well as South Korea has.  And one cannot argue that South Korea is a rich country with resources that the US does not have – GDP per capita in the US is double that of South Korea.  Nor is it because of travel bans.  Trump repeatedly asserts that the crisis would have been far greater in the US had he not had the singular wisdom to impose a ban on travel (by non-US citizens) from China on February 2 (and from Europe and other countries later).  But the only travel ban South Korea has imposed has been travel from Hubei Province in China.  And South Korea has far more contact with China, from both business and personal travel and trade in goods, than the US has.  Yet despite this, the deaths from Covid-19 have been far fewer in South Korea than in the US even after scaling for population.

And it is not only South Korea that has demonstrated competence in the management of the Covid-19 virus.  Death rates in other countries of East Asia, all similarly heavily exposed to China, have been even lower than that of South Korea.  In terms of the cumulative number of deaths from Covid-19 since the crisis began (as of April 13), there have been 4 deaths per million of population in South Korea, but just 2 per million in Singapore, 1 per million in Japan, 0.5 per million in Hong Kong, and 0.3 per million in Taiwan.  For the US, in contrast, the total is 71 per million.  (Reminder:  The chart above tracks deaths per day, not the cumulative total, and shows the figures per 10 million of population.)

This also shows that Trump’s repeated assertion that the deaths suffered in the US were inevitable – that nothing more could have been done – is simply nonsense.  Sadly, it is deadly nonsense.  South Korea shows what could have been done.  Travel bans were not important.  Rather, it was the basic public health measures of large-scale testing, identifying those with the virus or who may have been exposed to the virus, quarantining or isolating those exposed (including self-isolating, along with self-monitoring and regular reporting), and then treating in hospitals those who developed severe symptoms.

None of this is new to public health professionals.  And the US has excellent public health professionals.  What was different in the US was Trump, who refused to listen to them and indeed treated many of those in government as enemies to be attacked (as those with expertise were seen as members of the “deep state”).

The US had prepared plans on what to do should an infectious disease such as Covid-19 threaten.  There was, for example, a major effort to develop such plans in 2006/2007, towards the end of the Bush administration.  The work included running exercises similar to war-games of various scenarios (“table-top” exercises), to see how officials would respond and what the likely outcomes then would be.  These plans were further developed during Obama’s two terms in office.  But the Trump administration then ignored this previous preparation, and indeed took pride in dismantling important elements of it.

Dr. James Lawler, now an infectious disease doctor at the University of Nebraska but then serving in the Bush White House, participated in the 2006/2007 task force.  Over the weekend, the New York Times released a trove of over 80 pages of emails (obtained through a Freedom of Information Act request) of late-January to mid-March from Dr. Lawler and other experts, in and out of government, discussing how to address the crisis.  Particularly telling is a March 12 email from Dr. Lawler in which he said:

“We are making every misstep initially made in the table-tops at the outset of pandemic planning in 2006.  We had systematically addressed all of these and had a plan that would work – and has worked in Hong Kong/Singapore.  We have thrown 15 years of institutional learning out the window …”

Throwing those 15 years of institutional learning out the window has had deadly consequences.

The Rapid Growth in Deaths from Covid-19: The Role of Politics

Deaths from Covid-19 have been growing at an extremely rapid rate.  The chart above shows what those rates have been in the month of March, averaged over seven day periods to smooth out day-to-day fluctuations.  The figures are for the daily rate of growth over the seven day period ending on the date indicated.  The curves start in the first period when there were at least 10 cases, which was on March 3 for the US as a whole.  Hence the first growth rate shown is for the one week period of March 3 to 10.  As I will discuss below, the chart has not only the growth rates for the US as a whole but also for the set of states that Trump won in 2016 and for the set that Clinton won.  They show an obvious pattern.

The data come from the set assembled by The New York Times, based on a compilation of state and local reports.  The Times updates these figures daily, and has made them available through the GitHub site.  And it provides a summary report on these figures, with a map, at least daily.

I emphasize that the figures are of daily growth rates, even though they are calculated over one week periods.  And they are huge.  For the US as a whole, that rate was just over 28% a day for the seven day period ending March 30.  It is difficult to get one’s head around such a rapid rate of growth, but a few figures can be illustrative.  In the New York Times database, 3,066 Americans had died of Covid-19 as of March 30.  If the 28% rate of growth were maintained, then the entire population of the US (330 million) would be dead by May 16.  For many reasons, that will not happen.  The entire population would have been infected well before (if there was nothing to limit the spread) and it is fatal for perhaps 1% of those infected.  And the 99% infected who do not die develop an immunity, where once they recover they cannot spread the virus to others.  For this reason as well, 100% of those not previously exposed will not catch the virus.  Rather, it will be some lower share, as the spread becomes less and less likely as an increasing share of the population develops an immunity.  This is also the reason why mass vaccination programs are effective in stopping the spread of a virus (including to those not able to receive a vaccination, such as very young children or those with compromised immune systems).

So that 28% daily rate of growth has to come down, preferably by policy rather than by running out of people to infect.  And there has been a small reduction in the last two days (the seven day periods ending March 29 and March 30), with the rate falling modestly to 28% from a 30% rate that had ruled since the seven day period ending March 22.  But it has much farther to go to get to zero.

The recent modest dip might be an initial sign that the social distancing measures that began to be put in place around parts of the nation by March 16 are having a positive effect (and where many individuals, including myself, started social distancing some time before).  It is believed that it takes about 4 to 7 days after being infected before one shows any symptoms, and then, in those cases where the symptoms are severe and require hospitalization (about 20% of the total), another several days to two weeks before it becomes critical for those where it will prove fatal.  Hence one might be starting to see the impacts of the policies about now.

But the social distancing measures implemented varied widely across the US.  They were strict and early in some locales, and advisory only and relatively late in other locales.  Sadly, Trump injected a political element into this.  Trump belittled the seriousness of Covid-19 until well into March, even calling Covid-19 a “hoax” conjured up by the Democrats while insisting the virus soon would go away.  And even since mid-March Trump has been inconsistent, saying on some days that it needs to be taken seriously and on others that it was not a big deal.  Fox News and radio hosts of the extreme right such as Rush Limbaugh also belittled the seriousness of the virus.

It is therefore understandable that Trump supporters and those who follow such outlets for what they consider the news, have not shown as much of a willingness to implement the social distancing measures that are at this point the only way to reduce the spread of the virus.  And it shows in the death figures.  The red curve in the chart at the top of this post shows the daily growth rates of fatalities from this virus in those states that voted for Trump in the 2016 election.  While the spread of the virus in these states, many of which are relatively rural, started later than in the states that voted for Clinton, their fatalities from the virus have since grown at a substantially faster pace.

The pace of growth in the states that voted for Clinton has also been heavily influenced by the rapid spread of the virus in New York.  As of March 30, more than half (57%) of the fatalities in the Clinton states was due to the fatalities in New York alone.  And New York is a special case.  With its dense population in New York City, where a high proportion use a crowded subway system or buses to commute to work, with the work then often in tall office buildings requiring long rides in what are often crowded elevators, it should not be surprising that a virus that goes person to person could spread rapidly.

Excluding New York, the rate of increase in the other states that voted for Clinton (the curve in green in the chart above) is more modest.  The rates are also then even more substantially lower than those in the Trump-voting states.

But any of these growth rates are still incredibly high, and must be brought down to zero quickly.  That will require clear, sustained, and scientifically sound policy, from the top.  But Trump has not been providing this.