Republican presidents are bad for our health?

Infant mortality in the US fluctuates with the political party of the President.  A paper published in the  June 4 issue of the widely respected International Journal of Epidemiology ("Us Infant Morality and the President's Party," Rodriguez et al.) reports that between 1965-2010, infant mortality rates were 3% higher when a Republican was president than when the president was a Democrat.

Rodriguez et al. write that previous "political epidemiology" has been cross-national, and has attempted to determine the effect of policy on public health; welfare states, national health systems vs not, higher social expenditures or medical expenditures per capita vs lower, etc. Income inequality was found to be correlated with public health until the data were re-analyzed and additional variables controlled (Avendano, 2012), leading Avendano to question whether income inequality was in fact causal, as opposed to either spurious or real but only correlation with some unmeasured variable(s).  Further studies have attempted to determine which social factors are actually causal; some have suggested social expenditure and the generosity of family policies may be. In this way, political policies may affect public health, but actual causality, rather than just correlation, is difficult to determine.

Rodriguez et al. posed the question, ‘Is the political party of the president of the USA associated with an important, objective and sensitive measure of population health, infant mortality?’ The idea is that the party in power drives macroeconomic policy, and macroeconomic policy influences the socioeconomic milieu, affecting variables that affect health and mortality.

Infant mortality has fallen dramatically since 1965, from a total of 24.7 per 1000 births to 6.1 in 2010.  In the graph below, the authors have removed the trend, and show total infant mortality, neonatal and post-neonatal mortality, by president, for blacks and whites.  During Democratic administrations, all rates are lower, across the board, on average 3% lower.

Logged IMR, NMR, and PMR residual trends and presidential partisan regimes, 1965–2010; Source, Rodriguez et al., 2014

The statistical effects are essentially the same for Blacks and Whites, but infant mortality among Black infants is about two times higher than it is among Whites, so the absolute effect is larger.  The percentages may be small -- very small, in fact -- but their consistency does lend them credibility.

Several things stand out about these results.  First, as the authors point out, the implementation of policies that might have had a direct effect on infant mortality -- Johnson's Great Society and Medicaid in the 1960's, or expansion of Medicaid eligibility between 1979 and 1992 don't correlate with these periodic dips in IMRs.  That would be the easy explanation.  But this means that the correlation with political party may have little or nothing to do with policy differences.

Or, Rodriguez et al. suggest, the correlation could reflect real, cyclical changes in socioeconomic conditions for mothers and infants, depending on national policy.  Or, differential availability of abortion, since high risk fetuses may be more likely to be aborted than fetuses at lower risk.  Or, it might reflect differing attitudes toward health disparities, with Democrats more likely than Republicans to use government to address them -- but what actual governmental policy is implemented, or eliminated, and thus responsible for the fluctuations is anybody's guess.

But there's something curious about these findings.  Neonatal mortality, death before 28 days of life, is generally considered to be due to conditions of pregnancy or congenital abnormalities, while post-neonatal infant mortality, death between 29 days and 1 year, includes sudden infant death syndrome, which isn't correlated with socioeconomic status, but PMR is also considered to be a reflection of socioeconomic conditions.  If that's so, then neonatal mortality should look quite different from post-neonatal mortality in this study, but it doesn't.  It shouldn't be fluctuating with policy differences or income inequality or whatever political or economic factors, if any, might be responsible for the trend reported here.  And, one would expect there to be a more marked difference between Black neonatal and post-neonatal mortality, since health disparities are most reflected in Black infant deaths.

Equally problematic is that one might expect that presidential terms are short relative to the lag time between implementing a new policy and its effects.  The study did allow for a one year lag time, but still, most health policies don't have immediate impact. So the incumbent's party may be irrelevant to what happens during his term, or it would at least be the successor's (sometimes the same sometimes different) party.  Do people's expectations, based on the current President's outlook, change their behavior in subtle ways? Sounds plausible, and would have nothing to do with the policy change itself, but so many people are uninvolved, uninterested in, or skeptical of the political system that this might not be much of an explanation. And the pattern goes back before CNN and FOX imitation news organizations had much intentionally motivating influence on what people thought or were aware of.

Still, social and political epidemiology are interesting approaches to understanding the underlying causes of ill health and mortality.  The fields look at risk factors several steps removed from those generally considered as causes of disease, so that AIDS, or malaria, e.g., might be attributed to poverty rather than HIV infection or being bitten by a parsite-carrying mosquito, and legitimately so.  That is, the idea is that poverty increases one's risk of exposure to diseases, and if you eliminate poverty you eliminate risk.  The difficulty, of course, is that enacting public health policy that calls for eliminating poverty is a lot more difficult than distributing bed nets or clean needles.

And, the problem of identifying cause from correlation is huge with such metadata.  It can be pretty much pure guess work to pull causal factors from the social or political hat, as this paper suggests -- in fact, if something like, to make something up, differences in completeness of registration of vital statistics in Republican and Democratic years were responsible for this cyclical dip, it would look just the same as if the cause were changing policy. The point is, that we just don't know.  In addition, it's hard to avoid interpreting results from one's particular political point of view -- maybe there's something interesting in this paper, maybe there's not, but it's very hard to know.