Abstract and Introduction
Extant analyses of the relation between economic conditions and population health were often based on annualized data and were susceptible to confounding by nonlinear time trends. In the present study, the authors used generalized additive models with nonparametric smoothing splines to examine the association between economic conditions, including levels of economic activity in New York State and the degree of volatility in the New York Stock Exchange, and monthly rates of death by suicide in New York City. The rate of suicide declined linearly from 8.1 per 100,000 people in 1990 to 4.8 per 100,000 people in 1999 and then remained stable from 1999 to 2006. In a generalized additive model in which the authors accounted for long-term and seasonal time trends, there was a negative association between monthly levels of economic activity and rates of suicide; the predicted rate of suicide was 0.12 per 100,000 persons lower when economic activity was at its peak compared with when it was at its nadir. The relation between economic activity and suicide differed by race/ethnicity and sex. Stock market volatility was not associated with suicide rates. Further work is needed to elucidate pathways that link economic conditions and suicide.
Globally, approximately 1 million people per year commit suicide. A recent review in which risk factors for suicide were summarized showed a focus on studies assessing proximal characteristics, including psychiatric morbidity and history of self-harm, which are present in approximately 90% and 40% of individuals who commit suicide, respectively. Genetic factors, exposure to childhood adversities and stressful life events, access to means of committing suicide (e.g., access to firearms or prescription drugs), and poorer physical health are also associated with suicide.
Rates of suicide death exhibit substantial variability, both within places over time and across geographic regions, at different scales. Although proximal risk factors contribute to our understanding of the factors that predict individual-level vulnerability to suicide, they are unlikely to explain observed spatiotemporal variability in rates of suicide. As noted by Emile Durkheim in his seminal work Suicide, the determinants of individual cases of suicide might be distinct from the determinants of the suicide rate, a social attribute that Durkheim considered a new fact sui generis. From a population-health perspective, variability in the rate of suicide might reflect changes in exposure to intermittent stressors that occur within populations, including instability in the economic cycle.
A growing body of empirical work has considered how economic conditions are associated with mortality. Although some research has indicated that economic downturns and rapid economic change adversely affect health, recent econometric analyses showed that economic expansions are associated with increased mortality rates and shorter life expectancies at the population level, resulting in the counterintuitive conclusion that recessions are "good for your health". A notable exception is suicide. Work investigating the relation between economic conditions and suicide generally shows that rates of suicide tend to fluctuate countercyclically with economic activity, increasing during recessions and economic downturns. However, findings have been inconsistent; for example, suicide rates fluctuated countercyclically in some countries during the Asian financial crisis of the late 1990s but remained stable or declined during a recession in Finland in the early 1990s. Alternative methodological approaches for handling challenges to internal validity may contribute to mixed findings.
One of the primary challenges to research concerning economic conditions and health is confounding. Most studies are based on parametric modeling of annualized data and may not adequately account for measured and unmeasured time-varying confounders, potentially resulting in biased estimates of the association between economic conditions and suicide. For example, seasonal and long-term secular trends, such as levels of spending on mental health services, may confound the association between economic conditions and suicide rates. The application of nonparametric alternatives such as generalized additive models (GAMs), which account for potential time-varying confounding using smoothing functions, to data of finer temporal resolution offers a flexible alternative to the traditional approach. A second threat is measurement error. Economic conditions are generally measured using gross domestic product, an important economic indicator that nonetheless may be removed from the everyday experience of individuals. Alternative measures, such as levels of employment, hours worked, consumer confidence, and stock market volatility, might more adequately capture the economic insecurity experienced by populations during times of economic crisis.
In light of these challenges, we explored the use of GAMs applied to historical economic and suicide data from New York City (NYC) to estimate the relation between economic conditions, measured by economic activity and volatility in the stock market, and monthly rates of suicide. Furthermore, as data from recent studies have suggested that the method of death and demographic characteristics, including sex and age, may moderate the relation between levels of economic activity and suicide, we assessed whether the relation between economic conditions and suicide rates varied according to the type of suicide (i.e., violent vs. nonviolent) and individual-level demographic characteristics (i.e., age, sex, or race/ethnicity).