The happiest countries and happiest U.S. states tend to have the highest suicide rates, according to research from the UK’s University of Warwick, Hamilton College in New York and the Federal Reserve Bank of San Francisco.
The new research paper titled Dark Contrasts: The Paradox of High Rates of Suicide in Happy Places has been accepted for publication in the Journal of Economic Behavior & Organization. It uses U.S. and international data, which included first-time comparisons of a newly available random sample of 1.3 million Americans, and another on suicide decisions among an independent random sample of approximately 1 million Americans.
The research confirmed a little known and seemingly puzzling fact: many happy countries have unusually high rates of suicide.
This observation has been made from time to time about individual nations, especially in the case of Denmark. This new research found that a range of nations – including: Canada, the United States, Iceland, Ireland and Switzerland, display relatively high happiness levels and yet also have high suicide rates. Nevertheless the researchers note that, because of variation in cultures and suicide-reporting conventions, such cross-country scatter plots are only suggestive. To confirm the relationship between levels of happiness and rates of suicide within a geographical area, the researchers turned to two very large data sets covering a single country, the United States.
The scientific advantage of comparing happiness and suicide rates across U.S. states is that cultural background, national institutions, language and religion are relatively constant across a single country. While still not absolutely perfect, as the States are not identical, comparing the different areas of the country gave a much more homogeneous population to examine rather than a global sample of nations.
Comparing U.S. states in this way produced the same result. States with people who are generally more satisfied with their lives tended to have higher suicide rates than those with lower average levels of life satisfaction. For example, the raw data showed that Utah is ranked first in life-satisfaction, but has the 9th highest suicide rate. Meanwhile, New York was ranked 45th in life satisfaction, yet had the lowest suicide rate in the country.
The researchers then also tried to make their comparison between States even fairer and yet more homogeneous by adjusting for clear population differences between the states including age, gender, race, education, income, marital status and employment status. Even with these adjustments. This still produced a very strong correlation between happiness levels and suicide rates although some states shifted their positions slightly. Hawaii then ranks second in adjusted average life satisfaction but has the fifth highest suicide rate in the country. At the other end of the spectrum, for example, New Jersey ranked near the bottom in adjusted life satisfaction (47th) and had one of the lowest adjusted suicide risks (coincidentally, also the 47th highest rate).
The researchers (Professor Andrew Oswald from the University of Warwick, Associate Professor of Economics Stephen Wu of Hamilton College and Mary C. Daly and Daniel Wilson both from the Federal Reserve Bank of San Francisco) believe the key explanation that may explain this counterintuitive link between happiness and suicide rates draws on ideas about the way that human beings rely on relative comparisons between each other.
University of Warwick researcher Professor Andrew Oswald said, “Discontented people in a happy place may feel particularly harshly treated by life. Those dark contrasts may in turn increase the risk of suicide. If humans are subject to mood swings, the lows of life may thus be most tolerable in an environment in which other humans are unhappy.”
Professor Stephen Wu of Hamilton College said, “This result is consistent with other research that shows that people judge their well-being in comparison to others around them. These types of comparison effects have also been shown with regards to income, unemployment, crime, and obesity.”