Academic journal article Seoul Journal of Economics

Income, Health, and Suicide: Evidence from Individual Panel Data in Korea

Academic journal article Seoul Journal of Economics

Income, Health, and Suicide: Evidence from Individual Panel Data in Korea

Article excerpt

(ProQuest: ... denotes formulae omitted.)

I.Introduction

Suicide is a major public health concern worldwide and a particularly serious social issue in South Korea. Suicide rates in South Korea experienced a sharp rise during the last 15 years, especially among the elderly. The number of suicidal deaths per 100,000 increased from 7.3 in 1991 to 31.9 in 2011 before it fell slightly to 25.5 in 2016. Particularly, the suicide rate for the population 60 and older jumped from 13.3 in 1991 to 71.1 in 2010 and is currently 47.2.

Numerous studies from multiple disciplines have attempted to investigate the determining factors of suicide.1 However, research on the issue has been seriously restricted by lack of individual-level data on suicide. Previous studies based on micro data primarily investigated suicide attempts or suicidal thoughts (Goodwin et al. 2003; Kim et al. 2010; Lee et al. 2010; Chen et al. 2012). Although the effects of local or national economic conditions measured by unemployment and poverty rates have been examined (Noh 2006; Chang et al. 2009; Classen, and Dunn 2012; Phillips 2013; Lee, and Kang 2014), how individual economic status affects the risk of committing suicide is largely unknown.2

Limited evidence regarding the effects of individual health problems on suicide for the general population has also been presented although past studies have shown a positive relationship between poor health and suicide (Harris et al. 1994; Grabbe et al. 1997; Stenager, and Stenager 1998; Stenager et al. 1998; Palmier-Claus et al. 2012). These studies contained selection bias due to the use of small, clinic-based, selected, or non-representative samples; thus, they could not be applied to the general population.

In addition, although previous studies using a representative database pointed to chronic disease or disability as a determining factor for suicide, little is known about the combined effects of disease and disability in population-based samples. Erlangen and colleagues (2015) examined the association between 39 physical diseases and suicidal deaths in older adults and found that multiple physical diseases increased the risk of suicide. Lee and colleagues (2017) assessed the risk of suicide in relation to disability. Particularly, they examined variations in the risk of suicide for different sexes, ages, and income levels. The results showed that the risk of suicide is higher for people with disability than those without (Lee et al. 2017). A gap in the literature lies on the failure of these studies to consider the combined effects of functional limitations and diseases. Kaplan and colleagues (2007) analyzed how suicide risk differentials vary among people with diseases and functional impairments. The drawbacks are as follows: (1) they were unable to examine the effects specific to each disease and (2) their data relied on self-reported surveys.

We fill this gap in the literature by investigating how individual economic status and health affect the probability of suicidal death of Koreans aged 40 and older. This study is based on the analysis of the National Health Insurance Service National Sample Cohort (NHISNSC) data, which comprise individual panel data that looked into a sample of approximately one million individuals from 2002 to 2013. These sources provide information on the type of employment (wage earners vs. self-employed workers), income class, type and severity of disability, classifications of diseases, and basic personal characteristics. We can identify the individuals who committed suicide because the deceased in the sample are linked to the Cause of Death Statistics. Given that almost everyone in Korea is covered by the NHIS, the sample is representative of the entire population. The suicide rates by gender, age, and year estimated from the sample are similar to those obtained from the entire population. Using the data, we estimated logit models of the correlates of suicide. …

Search by... Author
Show... All Results Primary Sources Peer-reviewed

Oops!

An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.