Sleep disorders and risk of hospitalization in patients with mood disorders: Analysis of the National Sample Cohort over 10 years

Psychiatry Research 245 (2016) 259–266

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Sleep disorders and risk of hospitalization in patients with mood disorders: Analysis of the National Sample Cohort over 10 years Kyu-Tae Han a,b, Woorim Kim a,b, Seung Ju Kim a,b, Suk-Yong Jang a,b,d, Yeong Jun Ju a,b, Sung Youn Chun a,b, Sang Gyu Lee b,c, Eun-Cheol Park a,b,d,n a

Department of Public Health, Graduate School, Yonsei University, Seoul, Republic of Korea Institute of Health Services Research, Yonsei University College of Medicine, Seoul, Republic of Korea c Department of Hospital Management, Graduate School of Public Health, Yonsei University, Seoul, Republic of Korea d Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea b

art ic l e i nf o

a b s t r a c t

Article history: Received 4 January 2016 Received in revised form 30 June 2016 Accepted 14 August 2016 Available online 17 August 2016

Medical utilization due to organic sleep disorders has increased remarkably in South Korea, which may contribute to the deterioration of mental health in the population. We analyzed the relationship between organic sleep disorders and risk of hospitalization due to mood disorder. We used data from the National Health Insurance Service (NHIS) National Sample Cohort 2002–2013, which included medical claims filed for the 15,537 patients who were newly diagnosed with a mood disorder in a metropolitan region, and employed Poisson regression analysis using generalized estimating equation (GEE) models. By the results, there was a 0.53% hospital admission rate among 244,257 patients with outpatient care visits. Patients previously diagnosed with an organic sleep disorder before specific outpatient care had a higher risk for hospitalization. Such associations were significant in females, patients with a longer duration of disease, or those who lived in the largest cities. In conclusion, considering that experiencing a sleep disorder by a patient with an existing mood disorder was associated with deterioration of their status, health policy makers need to consider insurance coverage for all types of sleep disorders in patients with psychological conditions. & 2016 Elsevier Ireland Ltd. All rights reserved.

Keywords: Admission of outpatient Metropolitan Mood disorder Outpatient care Sleep disorder

1. Introduction Sleep is a substantial part of a person's life, constituting approximately one-third of their lifetime. Therefore, sleep is intimately related to many aspects of an individual's life (Kuppermann et al., 1995; Taheri et al., 2004). In South Korea, sleep issues have become increasingly common. According to the 2009 Society at a Glance in the Organization for Economic Cooperation and Development (OECD), South Korea scored lowest among the 18 OECD countries regarding average sleep time (South Korea: 469 min per day, OECD-18: 502 min per day) (Co-operation and Development, 2008). In addition, the National Health Insurance Service (NHIS) of South Korea reported that utilization of health resources due to organic sleep disorder (International Classification of Diseases [ICD]-10: G47) has gradually increased in South Korea (number of patients [inpatient and outpatient]: 358,062 in 2012, 380,876 in 2013, and 414,524 in 2014) (National Health n Correspondence to: Department of Preventive Medicine and Institute of Health Services Research, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 120-752, Republic of Korea. E-mail address: [email protected] (E.-C. Park).

http://dx.doi.org/10.1016/j.psychres.2016.08.047 0165-1781/& 2016 Elsevier Ireland Ltd. All rights reserved.

Insurance Service, 2015). In solving the problems about increasing sleep disorder, many professionals have studied how duration and quality of sleep affect an individual's life and health. They found that those with sufficient duration and quality of sleep had improved physical and mental health, as well as daily activity, than those who did not have sufficient sleep (Maquet, 2001; Walker, 2009; Barber et al., 2010). A deficiency in sleep duration or quality may contribute to both physical and mental problems such as depression, diabetes mellitus, and cardiovascular diseases (Wolfson and Carskadon, 1998; Knutson et al., 2006; Hoevenaar-Blom et al., 2014). Meanwhile, some studies suggested that breathing-related sleep disorder such as sleep apnea have an association with the worsening status of patients with psychiatric diseases (Benca, 1992; Ohayon, 2003). Considering these remarkable increases over the last few years in problems related to sleep and the fact that issues about sleep disorder recently emerged in South Korea, it is essential to investigate the impact of such increases. Thus, we hypothesized that there are some associations between increases in sleep disorders and the worsening status of mental health in South Korea. South Korea has faced many problems related to issues of

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mental health in the 21st century (Cho et al., 2007), and has focused on patients with mood disorders. Mood disorders, which are psychological condition characterized by dramatic changes in or extremes of mood, are classified as follows: manic episode, bipolar disorder, depressive episode, recurrent depressive disorder, persistent mood disorder, and other mood disorder (World Health Organization, 1992). Health Insurance Review and Assessment (HIRA) statistics indicate that patients and healthcare expenditures for mood disorders (ICD-10: F3) have rapidly increased in South Korea (2010: 688,303 patients, 241 thousand US Dollars [USD], 2015: 774,223 patients, 288 thousand USD) (Health Insurance Review and Assessment Service, 2010–15). Given that severe cases of mood disorders can progress to suicidal ideation or suicide attempts, this increase may result in higher levels of suicide rates in South Korea (South Korea¼ 29.1 per 100,000 population, Average of OECD ¼ 12.0 per 100,000 population in 2012) (Nordström et al., 1995; Rihmer, 2007; Organization for Economic Cooperation and Development, 2015). Developing effective management tools for addressing mood disorders can, over time, contribute to resolving problems related to deteriorating mental health, specifically suicide, as well as to the increasing medical expenditures in South Korea. Although there are several studies that address the management of mental health problems, including suicide, as well as studies regarding the association between mental health and sleep, there are few studies that focus on the impact of organic sleep disorders on patients with mood disorders in South Korea (Lee et al., 2012; Kim et al., 2013a, 2013b). Therefore, it is worthwhile to investigate how organic sleep disorders not caused by psychological condition affect the deterioration of an existing mood disorder. Thus, we analyzed the relationship between organic sleep disorders and risk of hospitalization due to mood disorder among individuals who had received outpatient treatment for a mood disorder in metropolitan areas using nationwide data.

2. Methods 2.1. Study population We used data from the NHIS National Sample Cohort 2002–2013, which were released by the NHIS in 2014. The data comprise a nationally representative random sample of 1,025,340 individuals, approximately 2.2% of the entire population of the NHIS in 2002. The data were produced by the NHIS using a systematic sampling method to generate a representative sample of 46,605,433 Korean residents recorded in 2002. The database includes all medical claims filed from January 2002 to December 2013. In order to investigate the association between sleep disorders and risk of hospitalization in patients with a diagnosed mood disorder, we excluded the first year of each patient as wash-out period, and followed these individuals from then on. Therefore, we included only patients who were newly diagnosed with a mood disorder (ICD-10: F3) during outpatient care after 2003 (50,160 patients). We then excluded patients diagnosed with an organic sleep disorder (ICD-10: G47) prior to diagnosis of a mood disorder in order to limit our investigation to the effect of sleep disorders on patients who had already experienced a mood disorder. In addition, we selected for patients residing in a metropolitan region to examine the outcome variable, assuming substantial access to medical resources. This was done because South Koreans are disinclined to visit a medical institution for issues related to mental health and sleep disorders, even when they have high accessibility to health care resources compared to other countries (Kim et al., 2012; Shim et al., 2013).

Fig. 1. Sampling method for data used in this study.

Finally, the data used in this study were from 15,537 patients newly diagnosed with a mood disorder in a metropolitan region during 2003–2013. Regional characteristics were determined from the “e-provincial indicators” published by Statistics Korea, which contained the regional demographic structures for the 253 basic administrative Si-Gun-Gu (city-county-ward) districts of South Korea. We classified the data based on the Si-Gun-Gu information to take into account the regional characteristics of the community in which each patient resided (Statistics Korea, 2016). The unit of analysis in this study was 244,257 outpatient cases for 15,537 patients, rather than patients during 2003–2013, to analyze the risk of hospitalization in patients with a mood disorder (Fig. 1). 2.2. Variables 2.2.1. Outcome variable The outcome variable used in this study was hospitalization due to mood disorder (major diagnosis ¼ICD-10: F3) of patients who had made previous outpatient visits due to a mood disorder. We assumed that hospitalization due to mood disorder of an outpatient was caused by a deterioration in the mood disorder status of the patient (Han et al., 2016). We identified the date of each patient's first outpatient visit during the study period, and we followed each patient after the date of the first outpatient visit. If an outpatient subject with a mood disorder was hospitalized due to mood disorder after specific outpatient care, we considered the hospitalization due to the reason for outpatient care. 2.2.2. Primary variable of interest The primary variable of interest in this study was whether patients had been diagnosed with an organic sleep disorder (ICD-10: G47) not due to a psychiatric disorder. This included several types of sleep disorders as follows: insomnias (G47.0), hypersomnias (G47.1), disorders of the sleep-wake schedule (G47.2), sleep apnea (G47.3), narcolepsy/cataplexy (G47.4), other

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sleep disorders (G47.8), and unspecified sleep disorder (G47.9). If a patient with a mood disorder was diagnosed with an organic sleep disorder prior to the specific outpatient care, we assumed that the patient had an organic sleep disorder. 2.2.3. Covariates We adjusted both patient and regional variables when analyzing the effect of sleep disorders on patients with mood disorders. The patient variables included in the analyses were: sex, age, income, type of insurance coverage, year of outpatient visit, period from first diagnosis for mood disorder, mental disability, pre-hospitalization during 1 year, and days of medication for mood or sleep disorder. Age was categorized as o39 years, 40–59 years, and 4 60 years. In data used in this study, the income level of each individual was collected based on mean household income as follows: r10%, 11–20%, 21–30%, 31–40%, 41–50%, 51–60%, 61– 70%, 71–80%, 81–90%, and Z91%. This was categorized into three groups based on frequencies of each level (group 1: o40%, group 2: 40–79%, group 3: Z80%). Types of insurance coverage were categorized as beneficiaries of National Health Insurance (NHI) (regionally insured), NHI (workplace insured), or Medical Aid. The majority of the general population was covered by the NHI after paying the insurance fee charged based on economic status evaluation, whereas a few low-income, disabled, and elderly populations were covered by Medical Aid, and offered free insurance by the government. In cases of NHI beneficiaries, the types of insurance coverage were divided as regionally or workplace-insured based on the job status of each beneficiary. The period from first diagnosis for mood disorder was defined as the time between the first diagnosis of a mood disorder (ICD10: F3) to the time of specific outpatient care, to reflect the severity of patient. Individuals with severe mental health problems lasting more than 1 year were considered to have a mental disability, even if they were provided optimal treatment by doctors through the prequalification system. We also included pre-hospitalization and days of drug prescription (for mood and sleep disorders) per each outpatient care to reflect the severity of disease in each patient. Pre-hospitalization was defined as hospitalization during the previous 1 year from specific outpatient care. Days of drug treatment per year were defined as the days of prescription drug administered for treatment of mood or sleep disorder in each outpatient care. The regional variables were the region, population size, elderly proportion of the population, number of cultural/welfare per 100,000 people, number of medical facilities per 1000 people, and gross regional domestic product per population (GRDP). The regions included were Seoul, Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan. The population size was defined as the total number of residents in each community, and the elderly proportion of the population was defined as the number of elderly individuals among the total population of the community. The GRDP value added on the production side was used as an indicator of how much value was added to the economic activities in each region. 2.3. Statistical analyses We first examined the frequencies and percentages of each categorical variable at the baseline of each patient and performed χ2 tests for the distribution of outpatient cases by each variable during the study period. Next, to compare the average values and standard deviations of the continuous variables, we examined the mean and standard deviation of each continuous variable at baseline, and performed an analysis of variance (ANOVA) for each variable during the study period. Analyses were performed for both patient- and regional-level variables. Finally, to examine the

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associations between sleep disorder and risk of hospitalization due to mood disorder in patient who had experience for diagnosis of mood disorder, we performed multiple Poisson regression analysis using the generalized estimating equation (GEE) model with a link logit including both inpatient- and regional-level variables were analyzed as the data used in this study was hierarchically structured and had binary outcome variables. This GEE model assumed proper distributions for each case while taking into account the correlation among cases within the regions. In this study, the correlation structure was modeled as an exchangeable correlation structure (Hanley et al., 2003). In this model, the goodness of fit for the GEE model was assessed using the quasi-likelihood under the independence criterion (QIC) (Barnhart and Williamson, 1998). The lower value for QIC indicated that it has a better model fitting. Additionally, subgroup analyses were performed according to sex, age, income, period from first diagnosis, and region. In these analyses, we grouped the period from first diagnosis and region as two categories to determine differences more clearly. All statistical analyses were performed using SAS statistical software version 9.2. Cary, NC. 2.4. Ethics statement The data used in our study consisted of details regarding patient utilization of healthcare and was approved by the Institutional Review Board, Yonsei University Graduate School of Public Health (2014-239). This study did not include informed consent from the patients as the patient information was anonymized and unidentified prior to analysis.

3. Results The data used in analysis included 15,537 patients at baseline and 244,257 outpatient cases during the period 2003–2013. Table 1 shows the general characteristics, including patient and regional variables, of the study population at baseline. There were more females than males (females: 67.40%), more individuals in the 40–59 age group than in the other age groups, and more individuals in income group 1 (low income) than in the other income groups. Workplace insurance was the most common type of insurance coverage (Medical Aid¼0.94%; NHI, regionally insured ¼ 39.33%; NHI, workplace insured ¼ 59.73%). Patients with mental disabilities made up 0.31% of the total patients with mood disorders. The average prescription for days of treatment for mood disorders at baseline was 0.96 days. The average number of followup outpatient visits was 15.40 during the study period. Finally, the highest baseline percentage of patients lived in Seoul (47.29%) compared to any other region (Table 1). Table 2 shows the associations between the patient and regional variables, and the hospitalization of outpatients who were diagnosed with mood disorders during the study period. Among a total of 244,257 outpatient cases, 0.53% involved hospitalization following outpatient care. Those in the younger age groups were more frequently hospitalized after outpatient care than those in the older age groups (r39 years: 0.71%, 40–59 years: 0.53%, Z 60 years: 0.38%, P-value o0.0001). By income level, the lower income group had more hospitalizations following outpatient care due to mood disorder (group 1: 0.60%, group 2: 0.53%, group 3: 0.49%, P-value ¼0.0217). Beneficiaries of Medical Aid were more frequently hospitalized than individuals with other types of insurance (Medical Aid: 1.79%; NHI, regionally insured: 0.55%; NHI, workplace insured: 0.51%, P-value o0.0001). Patients with mental disabilities or pre-hospitalization were more frequently hospitalized after outpatient care than patients without these factors (with mental disability: 4.73%, without

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Table 1 Characteristics of study population at baseline.

Table 2 Characteristics of study population by hospitalization during study period. N/Mean %/SD

Individual variables Sex Male Female Age (years) r39 40–59 Z60 Income Group 1 Group 2 Group 3 Type of insurance coverage Medical Aid NHI (regionally insured) NHI (workplace insured) Year of first diagnosis 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Mental disability Yes No Medication days for mood disorder

Regional variables Region Seoul Busan Daegu Incheon Gwangju Daejeon Ulsan Population (100,000 people) Elderly proportion of population Number of cultural facilities per 100,000 people Number of welfare facilities per 100,000 people Number of medical facilities per 1,000 people Gross regional domestic product per population (million KRW) Average follow-up time Total

5065 10,472

32.60 67.40

4299 5714 5524

27.67 36.78 35.55

6102 5480 3955

39.27 35.27 25.46

146 6111 9280

0.94 39.33 59.73

1331 1572 1537 1395 1537 1411 1398 1399 1264 1510 1183

8.57 10.12 9.89 8.98 9.89 9.08 9.00 9.00 8.14 9.72 7.61

48 15,489 0.96

0.31 99.69 7 4.63

7348 2373 1528 1734 774 1199 581 3.93 11.23 3.01 4.21 8.80 27.36

47.29 15.27 9.83 11.16 4.98 7.72 3.74 7 1.40 7 2.55 7 3.47 7 2.39 7 4.58 7 8.71

15.40 15,537

7 26.98 100.0

SD, standard deviation; NHI, National Health Insurance; KRW, Korea Won.

mental disability: 0.50%, P-value o 0.0001; pre-hospitalization: 3.48%, no pre-hospitalization: 0.44%, P-value o 0.0001). The average period from first diagnosis for mood disorder was lower in cases with hospitalization after outpatient care. Patients hospitalized after outpatient care had on average fewer prescription days for treatment of mood disorder per outpatient care than patients without hospitalization after outpatient care (with hospitalization: mean ¼0.60 and standard deviation [SD]¼ 7 4.00, without hospitalization: mean ¼1.14 and SD ¼ 76.14, P-value ¼0.0018). With respect to regional characteristics, patients who lived in Gwangju were more frequently hospitalized after outpatient care than patients living in other regions (Table 2). Table 3 shows the results of the multiple Poisson regression analysis, adjusting for patient and hospital variables, that was used to examine the association between sleep disorders and risk for

Variables

Individual variables Sex Male Female Age (years) r 39 40–59 Z 60 Income Group 1 Group 2 Group 3 Type of insurance coverage Medical Aid NHI (regionally insured) NHI (workplace insured) Year of outpatient visit 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Sleep disorder Yes No Mental disability Yes No Pre-hospitalization during 1 year Yes No Period from first diagnosis Medication days for mood disorder Medication days for sleep disorder

Regional variables Region Seoul Busan Daegu Incheon Gwangju Daejeon Ulsan Population (100,000 people) Elderly proportion of population Number of cultural facilities per 100,000 people Number of welfare facilities per 100,000 people Number of medical facilities per 1000 people Gross regional domestic product per population (million KRW) Total

Hospitalization (N¼ 244,257) Yes

No

P-value

N/Mean %/SD

N/Mean %/SD

413 893

0.53 0.54

77,252 165,699

99.47 99.46

0.8928

516 490 300

0.71 0.53 0.38

72,469 91,762 78,720

99.29 99.47 99.62

o 0.0001

404 458 444

0.60 0.53 0.49

67,437 85,942 89,572

99.40 99.47 99.51

0.0217

29 504 773

1.79 0.55 0.51

1587 90,509 150,855

98.21 99.45 99.49

o 0.0001

76 89 95 101 158 145 150 140 141 118 93

1.63 0.93 0.75 0.73 0.75 0.57 0.53 0.48 0.45 0.33 0.28

4573 9522 12,552 13,710 20,983 25,095 27,894 29,079 31,005 35,583 32,955

98.37 99.07 99.25 99.27 99.25 99.43 99.47 99.52 99.55 99.67 99.72

o 0.0001

198 1108

0.51 0.54

38,390 99.49 204,561 99.46

0.5266

93 1213

4.73 0.50

1875 241,076

o 0.0001

275 1031 2.17 0.60

3.48 0.44 7 2.67 7 4.00

7616 96.52 235,335 99.56 2.55 7 2.62 1.14 7 6.14

2.07

7 6.58

2.21

7 6.39

0.4322

580 231 137 130 91 83 54 3.91 11.34

0.49 0.59 0.64 0.49 0.83 0.43 0.65 7 1.32 7 2.46

118,372 38,782 21,234 26,374 10,821 19,121 8247 3.94 11.28

99.51 99.41 99.36 99.51 99.17 99.57 99.35 7 1.38 7 2.49

o 0.0001

0.4849 0.3871

3.08

7 3.67

3.04

7 3.52

0.7160

6.31

7 4.24

6.30

7 4.53

0.9473

8.97

7 4.57

8.74

7 4.49

0.0634

27.19

7 9.05

27.50

7 8.43

0.1859

1306

0.53

242,951

99.47

95.27 99.50

o 0.0001 o 0.0001 0.0018

The results of chi-square test or ANOVA for each variable. SD, standard deviation; NHI, National Health Insurance; KRW, Korea Won.

K.-T. Han et al. / Psychiatry Research 245 (2016) 259–266

Table 3 Association between sleep disorders and hospitalization due to mood disorders. Variables

Hospitalization RR

Individual variables Sex Male Female Age (years) r 39 40–59 Z 60 Income Group 1 Group 2 Group 3 Type of insurance coverage Medical Aid NHI (regionally insured) NHI (workplace insured) Year of outpatient visit Sleep disorder Yes No Mental disability Yes No Pre-hospitalization during 1 year Yes No Period from first diagnosis Medication days for mood disorder (per increase 1 day) Medication days for sleep disorder (per increase 1 day)

Regional variables Region Seoul Busan Daegu Incheon Gwangju Daejeon Ulsan Population (per increase 100,000 people) Elderly proportion of population (per increase 10%) Number of cultural facilities per 100,000 people (per increase 5 facilities) Number of medical facilities per 1000 people (per increase 5 facilities) Gross regional domestic product per population (per million KRW)

95% CI

P-value

0.95 0.80 1.14 1.00 – –

0.6037 –

1.57 1.29 1.00

1.28 1.05 –

o0.0001 0.0160 –

1.11 1.03 1.00

0.91 1.35 0.86 1.22 – –

0.3156 0.7720 –

1.97 1.02 1.00 0.88

1.16 0.87 – 0.85

3.32 1.19 – 0.90

0.0116 0.8353

1.35 1.00

1.01 –

1.80 –

0.0418 –

1.93 1.59 –

o0.0001

5.54 3.32 9.23 1.00 – –

o0.0001 –

2.64 1.00 0.97 0.98

1.81 – 0.93 0.96

o0.0001 – 0.2544 0.0129

1.00

0.98 1.01

0.7488

0.39 0.44 0.41 0.43 0.58 0.30 1.00 1.04 1.12

0.05 0.03 0.02 0.03 0.03 0.02 – 0.95 0.73

0.3687 0.5810 0.5661 0.5399 0.7125 0.4099 – 0.3992 0.6093

1.01

0.99 1.03

0.2675

1.00

0.98 1.02

0.8385

0.99 0.92 1.06

0.7349

3.85 – 1.02 1.00

3.06 7.90 8.65 6.30 10.63 5.18 – 1.13 1.70

The results of multiple Poisson regression analysis using the GEE model including both inpatient- and regional-level variables. QIC values by models were as follows ¼null model: 20121.43, individual model: 18552.80, full model: 18460.50. RR, relative risk; CI, confidence interval; NHI, National Health Insurance; KRW, Korea Won

hospitalization after outpatient care. The age of a patient at the outpatient visit was inversely associated with risk for hospitalization after outpatient care (r39 years: relative risk [RR] ¼1.57, 95% confidence interval [CI] ¼1.28–1.93, P-value o0.0001; 40–59 years: RR ¼1.29, 95% CI ¼1.05–1.59, P-value ¼0.0160; Z 60 years: reference). The income level inversely trended with the risk for hospitalization, but there were no significant relationships. By type of insurance coverage, patients who applied for Medical Aid had a higher risk of hospitalization after outpatient care than those with other insurance types, while years of outpatient visits were inversely associated with risk for hospitalization. Patients previously diagnosed with organic sleep disorders before specific

263

outpatient care had a higher risk for hospitalization after outpatient care (RR: 1.35, 95% CI: 1.01–1.80, P-value: 0.0418) than those who were not. In addition, patients with mental disabilities or pre-hospitalization had a higher risk for hospitalization after outpatient care than those without these factors (with mental disability: RR ¼5.54, 95% CI ¼3.32–9.23, P-value o0.0001; without mental disability: reference; pre-hospitalization: RR ¼2.64, 95% CI ¼1.81–3.85, P-value o0.0001; without pre-hospitalization: reference). Medication days for treatment of mood disorders were also inversely associated with the risk for hospitalization. However, there was no significant relationship with prescription days for sleep disorders. Regarding regional characteristics, there were no significant relationships with risk of hospitalization (Table 3). Finally, we performed sub-group analysis to compare differences in the relationship between sleep disorders and risk of hospitalization after stratifying sex, age, income, period from first diagnosis, and region. In the sub-group analysis by sex, sleep disorders were positively associated with risk for hospitalization in females, but not in males (males þsleep disorder: RR ¼1.06, 95% CI ¼0.72–1.55; females þsleep disorder: RR ¼1.46, 95% CI ¼1.02– 2.10). However, in the sub-group analysis for age or income, there were no significant relationships. Sub-group analysis for the period from first diagnosis revealed that having a sleep disorder was positively associated with risk of hospitalization after outpatient care in those in the 43 years group, but this association was not significant in those in the o2 years group ( o2 years þsleep disorder: RR ¼1.13, 95% CI ¼0.79–1.61; 43 years þsleep disorder: RR¼ 1.66, 95% CI ¼ 1.17–2.35). In addition, in the sub-group analysis for region, which was categorized as “Seoul and Busan” and others, sleep disorder was positively associated with the risk of hospitalization only for the “Seoul and Busan” group (“Seoul and Busan”þsleep disorder: RR ¼1.46, 95% CI ¼ 1.07–2.00; othersþsleep disorder: RR¼ 1.09, 95% CI ¼0.63–1.87) (Fig. 2).

4. Discussion In the 21st century, South Korea has faced problems related to mental health in the arena of health care. Although the overall health status of the South Korean population has improved substantially due to the development of medical techniques and improvement in nutrition, new health problems related to mental health have rapidly increased (Cho et al., 2007; Uutela, 2010). Over the past several years, many professionals and health policy experts have endeavored to mitigate this increase in mental health problems in South Korea. Nevertheless, mental health-related issues remain, and medial expenditures and cost-burdens for patients have gradually increased due to these issues. Therefore, we found it necessary to access data and attempt to solve such problems with a different perspective than that of previous studies. We found that, among other problems, those related to sleep have recently and gradually increased, and South Korea has been labeled as vulnerable compared to other OECD countries (Co-operation and Development, 2008). In order to explore a possible association between sleep disorders and mental health issues, we analyzed the impact of organic sleep disorders on the deterioration of mood disorders in patients residing in the metropolitan areas. Our results indicated that sleep disorders were positively associated with the risk of hospitalization due to mood disorders following outpatient care in patients with mood disorders. This finding was similar to those of previous studies regarding mental health and sleep, which found that the duration and quality of sleep is related to a decrease in mental and physical health or quality of life. Here, we analyzed such associations focusing on the impact of organic sleep disorders on patients previously diagnosed

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Fig. 2. Relative risk for sleep disorders associated with the risk of hospitalization after outpatient care stratified by sex, age, period from first diagnosis, and region. The results of multiple Poisson regression analysis using the GEE model including both inpatient- and regional-level variables. Patients without sleep disorders were used as the reference group. Results were considered statistically significant if each bar, as marked for standard deviation, did not reach the cutoff line (1.00). CI, confidence interval; RR, relative risk.

with a mood disorder. These findings may assist in creating alternatives for effective management of patients suffering from mental health problems. The South Korean government has included treatment for sleep disorders in insurance coverage since 2008. Based on the criteria for insurance coverage of sleep disorders, coverage was only applied to patients with organic sleep apnea after a test for respiratory disturbance index (RDI) or to patients with non-organic sleep disorders due to a psychological condition (Choi et al., 2006; Jin et al., 2012). However, other sleep disorders in addition to sleep apnea are not covered by insurance, compelling many patients to either assume large medical costs or cease their sleep disorder treatment due to the cost burden (Goodridge et al., 2012). Given the negative effect of sleep disturbance on mental health and quality of life, as found by previous studies, it follows that insurance should cover all types of sleep disorders. However, there are some economic limitations to overcome. Our results suggest that, at a minimum, health policy makers and government decision makers should consider insurance coverage for all types of sleep disorders in patients with a psychological condition. In addition, on the clinical perspective, physicians needed to refrain from assuming that sleep disorder was caused by psychological conditions for patient with both symptoms at time of diagnosis. If physicians treat a patient with mood disorder, they have to check the comorbid condition about sleep disorder and consider the complex treatment for both mood disorder and sleep disorder. Also, the beneficiaries of Medical Aid had higher risk in hospitalization due to mood disorder in this study. This result was similar with previous studies, because they had lower accessibility for healthcare and were relatively vulnerable related to economic issues (Lee et al., 1998; Kim et al., 2015). Therefore, these issues are also one of the urgent problems in South Korea. In addition, our sub-group analyses found some differences in the association between sleep disorders and the risk for hospitalization after outpatient care in patients with a mood disorder. Sleep disorder had statistically significant positive associations with the risk of hospitalization in the following sub-groups:

females, patients with o2 years from the first diagnosis of a mood disorder, and patients who lived in “Seoul and Busan”. Our results by sex were similar to the previous studies that evaluated mental health, although these previous studies reported a more negative association in females than in males, as compared to our study (Gater et al., 1998; Jeon et al., 2007). With respect to our results by period from the first diagnosis of a mood disorder, they may be caused by the severity due to the duration of disease. Previous studies have also demonstrated that longer duration of the disease was strongly associated with the risk of a decrease in mental health status or quality of life (Lehrner et al., 1999; Spijker et al., 2002), suggesting that patients with a prolonged mood disorder require more attention. Our results of sub-group analysis by region found a statistically significant association with the risk of hospitalization only in the “Seoul and Busan” region. This result was due to Seoul and Busan being the first-and second-largest densely populated cities in South Korea. Patients with mood disorders in those regions are more frequently exposed to the risk factors for sleep disturbance. Therefore, based upon our results and the studies of others, the overall mental health condition of people residing in large cities could be said to be worse than those residing in small cities or rural areas (Laird, 1973; Srole and Fischer, 1978). Our study has several strengths compared with previous studies. First, we used the national sampling cohort data to identify the relationship between organic sleep disorders and the risk for hospitalization after outpatient care in patients with a mood disorder. These data are particularly helpful for establishing evidence-based policies for mental healthcare and sleep medicine. Next, to the best of our knowledge, this study is the first to investigate the impact of sleep disorders on the risk for hospitalization after outpatient care of patients with mood disorders in South Korea. Many previous studies demonstrate that the decreased duration or quality of sleep was negatively associated with mental health or quality of life. However, the results of our study suggest alternatives for the effective management of psychological conditions and sleep disorders by taking another point of view. In addition, the recent NHIS report described rapid increases in the

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utilization of health care resources due to organic sleep disorders (average increase in the number of patients with sleep disorders: 7.60% per year) (Health Insurance Review and Assessment Service, 2010–15). As mood disorders and sleep disorders are gradually increasing and are expected to become more prevalent in South Korea in the future, our results can be used to improve the management of these patients. Finally, we adjusted the data for days of drug treatment for mood disorders or sleep disorders and prehospitalization to provide more detail, allowing for the analysis of the severity of mood disorders experienced by patients (Padgett et al., 1990; Curyto et al., 2001). Our study also has some limitations. First, in previous studies, many factors were considered and associated with the risk of patients suffering from mental health problems. However, our study could not consider factors such as job status, marital status, family history of psychological conditions, and other factors that have been associated with mental health, because this study was performed using a NHI sampling cohort, which was collected based on the medical utilization of each patient (French, 1963; Zahner and Daskalakis, 1997; Wu et al., 2001). Next, we could not identify detailed information regarding the income level, because the data used in this study were collected based on NHIS criteria for the economic status of a population, not detailed income described in monetary units. Thus, we could not reflect detailed differences that might have been caused by income. Third, in this study, we assumed that hospitalization due to mood disorder (major diagnosis ¼ICD-10: F3) was caused by the last outpatient care resulting from mood disorder prior to hospitalization. Hence we could not consider other types of treatment, excluding medication that might have been provided to patients with mood disorders. Also, many previous studies raised questions about using ICD coding, because inaccuracy related to consensus between coding at patient visit and at discharge could easily occur in the real world (O'malley et al., 2005; Stausberg et al., 2008). Although the claim data like the one used in this study was collected by aggregating patient's information from first visit to discharge for insurance claim the medical cost by NHI, there still remains concern about inaccuracy of ICD coding. Therefore, further studies using more detailed data and design will be needed. Fourth, we could not consider the types of organic sleep disorder such as insomnias or hypersomnias, because the frequencies of these disorders was relatively low in the data used in this study and had converging issues. Thus, identifying the differences in each type of sleep disorder through further studies using a larger data is needed. In addition, we only included organic sleep disorder in this study rather than both types of sleep disorders which include nonorganic sleep disorder to avoid concerns about causal relationship. Organic sleep disorder was originally defined as sleep disorder which not be resulted by psychological condition in contrast with nonorganic sleep disorder. Nevertheless, it could causes the causal relationship issues related to ICD coding and limitations of secondary data. Fifth, in this study, although it would have been more detailed if the symptom measures could be repeatedly assessed over time, we used hospitalization due to mood disorder as indirect indicators of worsening status due to limitation of data. Finally, we only selected for patients residing in the metropolitan regions, in order to examine the outcome variable, assuming substantial accessibility to medical resources. Therefore, our findings had some limitations that might prevent generalization to all of South Korea. Despite the limitations, our findings suggest that organic sleep disorders are negatively associated with the status of patients with mood disorders. These associations were particularly significant in females, patients with longer duration of diseases, or patients who resided in the “Seoul and Busan” regions. Although further study using more detailed data will be needed in the future, health

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policy makers and decision makers in mental healthcare or sleep medicine should consider effective alternatives such as reduce copayment by the strengthening insurance coverage for the optimal management of sleep disorders in patients with psychological conditions.

5. Conclusions Sleep disorders in patients with mood disorders were positively associated with the deterioration of patient status. Such associations were more significant in females, patients with longterm mood disorders, or patients living in large cities. Therefore, based on our results, health policy makers and government decision makers need to consider insurance coverage for all types of sleep disorders in patients with psychological conditions.

Authors' contributions K.T.H. designed the study, researched data, performed statistical analyses and wrote the manuscript. S.J.K., Y.J.J., S.Y.C., S.G.L., and E.C.P. contributed to the discussion and reviewed and edited the manuscript. E.C.P. is the guarantor of this work and as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. The English in this document has been checked by at least two professional editors, both native speakers of English. In addition, W.K. provided re-editing services for our manuscript to improve quality of scientific writing.

Conflict of interest The authors declare no conflicts of interest.

Acknowledgements None.

References Barber, L.K., Munz, D.C., Bagsby, P.G., Powell, E.D., 2010. Sleep consistency and sufficiency: are both necessary for less psychological strain? Stress Health 26, 186–193. Barnhart, H.X., Williamson, J.M., 1998. Goodness-of-fit tests for GEE modeling with binary responses. Biometrics, 720–729. Benca, R.M., 1992. Sleep in psychiatric disorders. ACCP 2008 Sleep Medicine Board Review Syllabus Book, p. 71. Cho, M.J., Kim, J.-K., Jeon, H.J., Suh, T., Chung, I.-W., Hong, J.P., Bae, J.-N., Lee, D.-W., Park, J.-I., Cho, S.-J., 2007. Lifetime and 12-month prevalence of DSM-IV psychiatric disorders among Korean adults. J. Nerv. Ment. Dis. 195, 203–210. Choi, J.B., Nelesen, R., Loredo, J.S., Mills, P.J., Ancoli-Israel, S., Ziegler, M.G., Dimsdale, J.E., 2006. Sleepiness in obstructive sleep apnea: a harbinger of impaired cardiac function? Sleep 29, 1531–1536. OECD, 2009. Society at a Glance 2009, OECD Social Indicators. OECD Publishing, Paris. Curyto, K.J., Johnson, J., TenHave, T., Mossey, J., Knott, K., Katz, I.R., 2001. Survival of hospitalized elderly patients with delirium: a prospective study. Am. J. Geriatr. Psychiatry 9, 141–147. French, J.R., 1963. The social environment and mental health. J. Social Issues, 39–56. Gater, R., Tansella, M., Korten, A., Tiemens, B.G., Mavreas, V.G., Olatawura, M.O., 1998. Sex differences in the prevalence and detection of depressive and anxiety disorders in general health care settings: report from the World Health Organization Collaborative Study on Psychological Problems in General Health Care. Arch. Gen. Psychiatry 55, 405–413. Goodridge, D., Hawranik, P., Duncan, V., Turner, H., 2012. Socioeconomic disparities in home health care service access and utilization: a scoping review. Int. J. Nurs. Stud. 49, 1310–1319. Han, K.-T., Jang, S.Y., Park, S., Cho, K.H., Yoo, K.-B., Choi, Y., Park, E.-C., 2016. Social

266

K.-T. Han et al. / Psychiatry Research 245 (2016) 259–266

welfare centers protect outpatients with mood disorders from risk of hospital admission. PLoS One, 11. Hanley, J.A., Negassa, A., Forrester, J.E., 2003. Statistical analysis of correlated data using generalized estimating equations: an orientation. Am. J. Epidemiol. 157, 364–375. Health Insurance Review & Assessment Service, 2010–15. Statistics for Diseases. Hoevenaar-Blom, M.P., Spijkerman, A.M., Kromhout, D., Verschuren, W.M., 2014. Sufficient sleep duration contributes to lower cardiovascular disease risk in addition to four traditional lifestyle factors: the MORGEN study. Eur. J. Prev. Cardiol. 21, 1367–1375. Jeon, G.-S., Jang, S.-N., Rhee, S.-J., Kawachi, I., Cho, S.-I., 2007. Gender differences in correlates of mental health among elderly Koreans. J. Gerontol. Ser. B: Psychol. Sci. Soc. Sci. 62, S323–S329. Jin, S.-M., Lee, H.-S., Ryu, H.-H., Ryu, S.-H., Shin, D.-Y., Kim, C.-H., Kim, M.S., Chung, I.-K., 2012. Retrospective study on the airway obstruction aspects of computed tomography and lateral cephalometry and the correlation of polysomnography in obstructive sleep apnea patients. J. Korean Assoc. Oral. Maxillofac. Surg. 38, 295–304. Kim, J.-H., Kim, K.R., Cho, K.H., Yoo, K.-B., Kwon, J.A., Park, E.-C., 2013a. The association between sleep duration and self-rated health in the Korean general population. J. Clin. Sleep. Med.: JCSM: Off. Publ. Am. Acad. Sleep. Med. 9, 1057. Kim, J.-H., Lee, K.-S., Yoo, K.-B., Park, E.-C., 2015. The differences in health care utilization between Medical Aid and health insurance: a longitudinal study using propensity score matching. PLoS One 10, e0119939. Kim, J.-H., Park, E.-C., Cho, W.-H., Park, J.-Y., Choi, W.-J., Chang, H.-S., 2013b. Association between total sleep duration and suicidal ideation among the Korean general adult population. Sleep 36, 1563. Kim, S.-W., Jang, J.-E., Kim, J.-M., Shin, I.-S., Ban, D.H., Choi, B., Chung, S.-A., Yoon, J.S., 2012. Comparison of stigma according to the term used for schizophrenia: split-mind disorder vs. attunement disorder. J. Korean Neuropsychiatr. Assoc. 51, 210–217. Knutson, K.L., Ryden, A.M., Mander, B.A., Van Cauter, E., 2006. Role of sleep duration and quality in the risk and severity of type 2 diabetes mellitus. Arch. Intern. Med. 166, 1768–1774. Kuppermann, M., Lubeck, D.P., Mazonson, P.D., Patrick, D.L., Stewart, A.L., Buesching, D.P., Filer, S.K., 1995. Sleep problems and their correlates in a working population. J. Gen. Intern. Med. 10, 25–32. Laird, J.T., 1973. Mental health and population density. J. Psychol. 85, 171–177. Lee, Y.J., Cho, S.-J., Cho, I.H., Kim, S.J., 2012. Insufficient sleep and suicidality in adolescents. Sleep 35, 455. Lee, Y.M., Kim, J.H., Lee, H.Y., Jeong, Y.K., Lim, K.Y., Lee, J.H., Rhee, C.S., 1998. Length of stay in the mental health facilities in Korea. J. Korean Neuropsychiatr. Assoc. 37, 83–94. Lehrner, J., Kalchmayr, R., Serles, W., Olbrich, A., Pataraia, E., Aull, S., Bacher, J., Leutmezer, F., Gröppel, G., Deecke, L., 1999. Health-related quality of life (HRQOL), activity of daily living (ADL) and depressive mood disorder in temporal lobe epilepsy patients. Seizure 8, 88–92.

Maquet, P., 2001. The role of sleep in learning and memory. Science 294, 1048–1052. National Health Insurance Service, 2015. Statistics for Diseases: Sleeping Disorder. In. Nordström, P., Åsberg, M., Åberg-Wistedt, A., Nordin, C., 1995. Attempted suicide predicts suicide risk in mood disorders. Acta Psychiatr. Scand. 92, 345–350. O'malley, K.J., Cook, K.F., Price, M.D., Wildes, K.R., Hurdle, J.F., Ashton, C.M., 2005. Measuring diagnoses: ICD code accuracy. Health Serv. Res. 40, 1620–1639. Ohayon, M.M., 2003. The effects of breathing-related sleep disorders on mood disturbances in the general population. J. Clin. Psychiatry. 64, 1195–1200. Organization for Economic Cooperation and Development, 2015. Health at a Glance 2015: OECD Indicators. In. Padgett, D., Struening, E.L., Andrews, H., 1990. Factors affecting the use of medical, mental health, alcohol, and drug treatment services by homeless adults. Med. Care, 805–821. Rihmer, Z., 2007. Suicide risk in mood disorders. Curr. Opin. Psychiatry 20, 17–22. Shim, J.W., Kim, M.J., Kim, E.K., Park, H.K., Song, E.S., Lee, S.M., Lee, J.H., Jin, H.S., Kim, E.S., Chang, Y.S., 2013. The impact of neonatal care resources on regional variation in neonatal mortality among very low birthweight infants in Korea. Paediatr. Perinat. Epidemiol. 27, 216–225. Spijker, J., De Graaf, R., Bijl, R.V., Beekman, A.T., Ormel, J., Nolen, W.A., 2002. Duration of major depressive episodes in the general population: results from The Netherlands Mental Health Survey and Incidence Study (NEMESIS). Br. J. Psychiatry 181, 208–213. Srole, L.E., Fischer, A.K., 1978. Mental health in the Metropolis: The midtown Manhattan Study (Rev ed). New York U Press. Statistics Korea, 2016. E-provincial Indicators. In. Stausberg, J., Lehmann, N., Kaczmarek, D., Stein, M., 2008. Reliability of diagnoses coding with ICD-10. Int. J. Med. Inform. 77, 50–57. Taheri, S., Lin, L., Austin, D., Young, T., Mignot, E., 2004. Short sleep duration is associated with reduced leptin, elevated ghrelin, and increased body mass index. PLoS Med. 1, 210. Uutela, A., 2010. Economic crisis and mental health. Curr. Opin. Psychiatry 23, 127–130. Walker, M.P., 2009. The role of sleep in cognition and emotion. Ann. NY Acad. Sci. 1156, 168–197. Wolfson, A.R., Carskadon, M.A., 1998. Sleep schedules and daytime functioning in adolescents. Child Dev., 875–887. World Health Organization, 1992. The ICD-10 Classification of Mental and Behavioural Disorders: Clinical Descriptions and Diagnostic Guidelines. World Health Organization, Geneva. Wu, P., Hoven, C.W., Cohen, P., Liu, X., Moore, R.E., Tiet, Q., Okezie, N., Wicks, J., Bird, H.R., 2001. Factors associated with use of mental health services for depression by children and adolescents. Psychiatr. Serv. 52, 189–195. Zahner, G.E., Daskalakis, C., 1997. Factors associated with mental health, general health, and school-based service use for child psychopathology. Am. J. Public Health 87, 1440–1448.