Suicide is not only an individual phenomenon, but it is also influenced by social and environmental factors. With the high suicide rate and the abundance of social media data in South Korea, we have studied the potential of this new medium for predicting completed suicide at the population level. We tested two social media variables (suicide-related and dysphoria-related weblog entries) along with classical social, economic and meteorological variables as predictors of suicide over 3 years (2008 through 2010). Both social media variables were powerfully associated with suicide frequency. The suicide variable displayed high variability and was reactive to celebrity suicide events, while the dysphoria variable showed longer secular trends, with lower variability. We interpret these as reflections of social affect and social mood, respectively. In the final multivariate model, the two social media variables, especially the dysphoria variable, displaced two classical economic predictors – consumer price index and unemployment rate. The prediction model developed with the 2-year training data set (2008 through 2009) was validated in the data for 2010 and was robust in a sensitivity analysis controlling for celebrity suicide effects. These results indicate that social media data may be of value in national suicide forecasting and prevention.
Background: Cerebral white matter hyperintensities (WMH) are prevalent incident findings on brain MRI scans among elderly people and have been consistently implicated in cognitive dysfunction. However, differential roles of WMH by region in cognitive function are still unclear. The aim of this study was to ascertain the differential role of regional WMH in predicting progression from mild cognitive impairment (MCI) to different subtypes of dementia. Methods: Participants were recruited from the Clinical Research Center for Dementia of South Korea (CREDOS) study. A total of 622 participants with MCI diagnoses at baseline and follow-up evaluations were included for the analysis. Initial MRI scans were rated for WMH on a visual rating scale developed for the CREDOS. Differential effects of regional WMH in predicting incident dementia were evaluated using the Cox proportional hazards model. Results: Of the 622 participants with MCI at baseline, 139 patients (22.3%) converted to all-cause dementia over a median of 14.3 (range 6.0–36.5) months. Severe periventricular WMH (PWMH) predicted incident all-cause dementia (Hazard ratio (HR) 2.22; 95% confidence interval (CI) 1.43–3.43) and Alzheimer's disease (AD) (HR 1.86; 95% CI 1.12–3.07). Subcortical vascular dementia (SVD) was predicted by both PWMH (HR 16.14; 95% CI 1.97–132.06) and DWMH (HR 8.77; 95% CI 1.77–43.49) in more severe form (≥ 10 mm). Conclusions: WMH differentially predict dementia by region and severity. Our findings suggest that PWMH may play an independent role in the pathogenesis of dementia, especially in AD.
Suggestive associations of suicide with air pollutant concentrations have been reported. Recognizing regional and temporal variability of pollutant concentrations and of suicide, we undertook a detailed meta-analysis of completed suicides in relation to 5 major pollutants over 6 years in the 16 administrative regions of the Republic of Korea, while also controlling for other established influences on suicide rates. Of the 5 major pollutants examined, ozone concentrations had a powerful association with suicide rate, extending back to 4 weeks. Over the range of 2 standard deviations (SD) around the annual mean ozone concentration, the adjusted suicide rate increased by an estimated 7.8% of the annual mean rate. Particulate matter pollution also had a significant effect, strongest with a 4-week lag, equivalent to 3.6% of the annual mean rate over the same 2 SD range that approximated the half of annual observed range. These results strongly suggest deleterious effects of ozone and particulate matter pollution on the major public health problem of suicide.