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Seasonal Variations in Temperature–Suicide Associations Across South Korea

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Seasonal Variations in Temperature–Suicide Associations Across South Korea OCTOBER 2019 K A L K S T E I N E T A L . 731 Seasonal Variations in Temperature–Suicide Associations across South Korea a ADAM J. KALKSTEIN Department of Earth and Planetary Sciences, Weizmann Institute of Science, Rehovot, Israel MILOSLAV BELORID Applied Meteorology Research Division, National Institute of Meteorological Sciences, Seogwipo, Jeju, South Korea P. GRADY DIXON Department of Geosciences, Fort Hays State University, Hays, Kansas KYU RANG KIM Applied Meteorology Research Division, National Institute of Meteorological Sciences, Seogwipo, Jeju, South Korea KEITH A. BREMER Department of Geosciences, Fort Hays State University, Hays, Kansas (Manuscript received 31 January 2019, in final form 14 June 2019) ABSTRACT South Korea has among the highest rates of suicide in the world, and previous research suggests that suicide frequency increases with anomalously high temperatures, possibly as a result of increased sunshine. However, it is unclear whether this temperature–suicide association exists throughout the entire year. Using distrib- uted lag nonlinear modeling, which effectively controls for nonlinear and delayed effects, we examine temperature–suicide associations for both a warm season (April–September) and a cool season (October– March) for three cities across South Korea: Seoul, Daegu, and Busan. We find consistent, statistically sig- nificant, mostly linear relationships between relative risk of suicide and daily temperature in the cool season but few associations in the warm season. This seasonal signal of statistically significant temperature–suicide asso- ciations only in the cool season exists among all age segments, but especially for those 35 and older, along with both males and females. We further use distributed lag nonlinear modeling to examine cloud cover–suicide associations and find few significant relationships. This result suggests that that high daily temperatures in the cool season, and not exposure to sun, are responsible for the strong temperature–suicide associationsfoundinSouthKorea. 1. Introduction suicide in South Korea has risen dramatically in recent years, with suicide rates increasing by approximately 400% Suicide is the fourth-leading cause of death in South since the early 1990s (J. W. Kim et al. 2017). The observed Korea, which has among the highest rates of suicide in increase has been especially pronounced among males and the world (B. Kim et al. 2015). Further, the prevalence of the elderly (Jeon et al. 2016), although explanations behind the rise in suicides vary and include changes in economic Supplemental information related to this paper is available at the conditions and employment (Chan et al. 2014; Min et al. Journals Online website: https://doi.org/10.1175/WCAS-D-19-0019.s1. 2015), the prevalence and media coverage of celebrity suicide (Lee et al. 2014; Kim and Woo 2016; Park et al. a Additional affiliation: United States Military Academy, West 2016), improvements in data classification of suicide (Chan Point, New York. et al. 2015), and beyond (K. Kim et al. 2017). Like many other midlatitude locations, South Korea Corresponding author: Adam J. Kalkstein, adam.kalkstein@ displays a seasonal pattern in suicide, with suicides peaking westpoint.edu in the late spring and early summer (Kim et al. 2011; DOI: 10.1175/WCAS-D-19-0019.1 Ó 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses). Unauthenticated | Downloaded 10/06/21 03:16 PM UTC 732 WEATHER, CLIMATE, AND SOCIETY VOLUME 11 TABLE 1. Average maximum temperature (MaxT; 8C), minimum temperature (MinT; 8C), and cloud cover (in tenths) for Seoul, Daegu, and Busan across the entire year, the warm season (April–September), and the cool season (October–March). Standard deviations are given in parentheses. Seoul Daegu Busan Annual Warm Cool Annual Warm Cool Warm Cool avg season season avg season season Annual avg season season MaxT 17.41 (10.65) 25.76 (5.26) 9.04 (7.71) 19.73 (9.65) 27.23 (5.20) 12.20 (6.82) 19.16 (7.78) 24.74 (4.61) 13.56 (6.11) MinT 9.10 (10.49) 17.39 (5.66) 0.78 (7.07) 10.16 (9.63) 17.79 (5.57) 2.51 (6.14) 11.80 (8.64) 18.21 (5.07) 5.36 (6.40) Cloud cover 4.85 (3.16) 5.79 (3.06) 3.91 (2.97) 4.83 (3.17) 5.86 (2.99) 3.76 (2.99) 4.74 (3.33) 5.80 (3.16) 3.68 (3.15) Y. Kim et al. 2015). Further, there is increasing evidence 10 million, and it sits in the far northwestern portion of that environmental factors mightplayaroleincontribut- South Korea adjacent to the Yellow Sea. Daegu, located ing to the likelihood of suicide across South Korea. For in the more mountainous south-central portion of South example, previous research suggests suicide across the Korea, is the fourth-largest city, with a population over country increases during periods of higher surface tem- 2.5 million. Busan, a coastal city in the southeast portion peratures (Kim et al. 2011), and Y. Kim et al. (2015) link of the country, is South Korea’s second-largest, with a increases in suicide to elevated levels of surface ozone. Jee population exceeding 3.5 million. Among South Korea’s et al. (2017) conclude suicide frequency rises in association four largest cities, only Incheon was excluded because with periods of additional solar radiation, although Kim of its proximity to Seoul. Further, current analytical et al. (2016) disagree and find no relationship between methods do not allow us to analyze smaller cities across sunlight and suicide. South Korea properly because of reduced sample sizes The comprehensive study by Kim et al. (2016) high- that are inadequate for a comprehensive study of lights weather–suicide associations prevalent across temperature–suicide associations. several East Asian countries, including South Korea, Daily suicide counts for each city were obtained from even after controlling for natural seasonal and day-of- Statistics Korea (http://kosis.kr) and include 19 years of week cycles using a time-stratified case-crossover design data, spanning from 1998 through 2016; The data include (Janes et al. 2005). Consistent with Kim et al. (2011), only those who have committed suicide. Suicides were Kim et al. (2016) uncover strong temperature–suicide determined from the International Classification of associations across South Korea with elevated temper- Diseases (ICD) codes E950-E959 (ICD-9; suicide and atures associated with increases in suicide. However, self-inflicted injury) and X60-X84 (ICD-10; intentional Kim et al. (2016) examine these relationships only self-harm). Suicide data were further broken down by throughout the entire year, and as a result, it remains unclear whether these associations are always evident or occur only in certain seasons. Thus, the goal of this re- search is to examine whether temperature–suicide as- sociations across South Korea remain valid during distinct ‘‘warm’’ and ‘‘cool’’ seasons by examining three major cities with different climates: Seoul, Daegu, and Busan. An examination of temperature–suicide associ- ations on a seasonal level will not only be a valuable tool for health practitioners, but also has the potential to shed light on the causal mechanisms responsible for any observed temperature–suicide relationships, a topic on which many questions remain. 2. Data and methods Three major cities across South Korea were selected on the basis of size, climate, and geography, with each city representing a unique climate and geographical lo- cation (Table 1; Fig. 1). Seoul, the capital of South Korea, is the largest city in the country, with a population over FIG. 1. Locations of Seoul, Daegu, and Busan in South Korea. Unauthenticated | Downloaded 10/06/21 03:16 PM UTC OCTOBER 2019 K A L K S T E I N E T A L . 733 TABLE 2. Average daily suicides in Seoul, Daegu, and Busan across the entire year, the warm season (April–September), and the cool season (October–March), broken out by gender and age. Standard deviations are given in parentheses. Seoul Daegu Busan Annual avg Warm season Cool season Annual avg Warm season Cool season Annual avg Warm season Cool season Male 3.62 (2.29) 3.86 (2.33) 3.39 (2.22) 1.00 (1.04) 1.05 (1.04) 0.96 (1.04) 1.68 (1.40) 1.81 (1.44) 1.56 (1.35) Female 1.80 (1.54) 1.87 (1.52) 1.73 (1.56) 0.50 (0.73) 0.53 (0.75) 0.47 (0.71) 0.74 (0.88) 0.78 (0.90) 0.70 (0.86) 0–34 1.36 (1.26) 1.40 (1.26) 1.31 (1.25) 0.34 (0.59) 0.35 (0.60) 0.32 (0.58) 0.51 (0.74) 0.53 (0.75) 0.48 (0.72) 35–64 2.84 (1.97) 2.99 (1.97) 2.69 (1.96) 0.84 (0.95) 0.87 (0.95) 0.81 (0.94) 1.36 (1.23) 1.44 (1.27) 1.29 (1.19) 651 1.22 (1.22) 1.33 (1.26) 1.11 (1.17) 0.32 (0.59) 0.35 (0.61) 0.30 (0.57) 0.55 (0.78) 0.62 (0.82) 0.48 (0.74) Total 5.42 (3.02) 5.72 (3.03) 5.11 (2.98) 1.50 (1.33) 1.58 (1.33) 1.42 (1.31) 2.42 (1.72) 2.58 (1.77) 2.26 (1.67) gender, along with three distinct age segments (0–34, categorical ‘‘day of week’’ variable to account for 35–64, and 651), and then were plotted over time to weekly cycles/patterns. Informed by previous research reveal both seasonal and long-term trends in the data.
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