SINCE Donald Trump’s surprising victory in America’s presidential election on November 8th, polling enthusiasts have been poring over the data to try to understand precisely how he won. The single factor that best predicted the amount of votes that Republican’s gained compared to 2012 is the share of voting-age citizens who are both white and do not have a college degree. This variable alone can explain 41% of the county-level swing to Mr Trump. For many that statistic might provide closure on what was a bitter and forgettable election. But Patrick Ruffini, a pollster, called on "data nerds" to find another variable that matches the explanatory power of this pale pedagogic predictor.

Fighting fit for such a challenge, The Economist has crunched the numbers and discovered a coherent set of variables that beat it: an index of health metrics. Together these variables can explain 43% of the Republican party’s gains over the Democrats. Even when controlling for a battery of other indicators—race, education, age, gender, income, marital status, immigration and employment—these health metrics remain significant and predictive.

The data suggest that the ill may have been particularly susceptible to Mr Trump’s message. According to our model, if diabetes were just 7% less prevalent in Michigan, Mr Trump would have gained 0.3 fewer percentage points there, enough to swing the state back to the Democrats. Similarly, if an additional 8% of people in Pennsylvania had engaged in regular physical activity, and the rate of heavy drinking in Wisconsin were 5% lower, Hillary Clinton would have won the electoral college vote and be set to enter the White House. But such counter-factual predictions are always impossible to test. Unfortunately, there is no way to re-run the election with healthier voters and compare the results. But the evidence suggests that Mr Trump performed well in communities that are literally dying.

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