ORIGINAL ARTICLE https://doi.org/10.3346/jkms.2016.31.S2.S121 • J Korean Med Sci 2016; 31: S121-128

Application of a Modified Garbage Code Algorithm to Estimate Cause-Specific Mortality and Years of Life Lost in Korea Ye-Rin Lee,1 Young Ae Kim,2 So-Youn Park,3 Chang-Mo Oh,4 Young-eun Kim,1 and In-Hwan Oh1 1

Department of Preventive Medicine, School of Medicine, Kyung Hee University, Seoul, Korea; 2 Cancer Policy Branch, National Cancer Control Institute, National Cancer Center, Goyang, Korea; 3 Department of Medical Education and Humanities, School of Medicine, Kyung Hee University, Seoul, Korea; 4Cancer Registration and Statistic Branch, National Cancer Control Institute, National Cancer Center, Goyang, Korea Received: 15 December 2015 Accepted: 19 May 2016 Address for Correspondence: In-Hwan Oh, MD Department of Preventive Medicine, School of Medicine, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Korea E-mail: [email protected] Funding: This study was supported by a grant from the Korean Health Technology R&D Project, Ministry of Health and Welfare, Republic of Korea (Grant No. HI13C0729).

Years of life lost (YLLs) are estimated based on mortality and cause of death (CoD); therefore, it is necessary to accurately calculate CoD to estimate the burden of disease. The garbage code algorithm was developed by the Global Burden of Disease (GBD) Study to redistribute inaccurate CoD and enhance the validity of CoD estimation. This study aimed to estimate cause-specific mortality rates and YLLs in Korea by applying a modified garbage code algorithm. CoD data for 2010-2012 were used to calculate the number of deaths. The garbage code algorithm was then applied to calculate target cause (i.e. , valid CoD) and adjusted CoD using the garbage code redistribution. The results showed that garbage code deaths accounted for approximately 25% of all CoD during 2010-2012. In 2012, lung cancer contributed the most to cause-specific death according to the Statistics Korea. However, when CoD was adjusted using the garbage code redistribution, ischemic heart disease was the most common CoD. Furthermore, before garbage code redistribution, selfharm contributed the most YLLs followed by lung cancer and liver cancer; however, after application of the garbage code redistribution, though self-harm was the most common leading cause of YLL, it is followed by ischemic heart disease and lung cancer. Our results showed that garbage code deaths accounted for a substantial amount of mortality and YLLs. The results may enhance our knowledge of burden of disease and help prioritize intervention settings by changing the relative importance of burden of disease. Keywords:  Cause of Death; Garbage Code; Years of Life Lost; Mortality; Korea

INTRODUCTION Measuring the burden of disease allows for determination of the overall health status of a population and the rational allocation of limited health care resources (1). An indicator of burden of disease, disability-adjusted life years (DALYs), is a combination of years of life lost (YLLs), which indicates loss of life years due to premature death, and years lived with disability (YLDs), which indicates loss of healthy years due to disability (2). In 1990, YLLs accounted for 76.7% of DALYs worldwide, showing a higher proportion than YLDs; in 2010, YLLs represented 68.8% of DALYs measured worldwide by the Global Burden of Diseases (GBD) Study. When compared by region, YLLs comprised approximately half of the DALYs in developed countries with a high income, such as Asia Pacific, Western Europe, and North America, and over 80% of the DALYs in developing countries, such as SubSaharan Africa (3). Therefore, measuring YLLs is considered an important factor for determining burden of disease.   Given that YLLs are measured using the mortality rate and cause of death (CoD), accurate measurement of the cause-specific mortality rate is important. In Korea, CoD data collected by the Statistics Korea are utilized to estimate the cause-specific

mortality rate. CoD is collected from death certificates using the Korean Standard Classification of Diseases (4). However, death certificates contain errors owing to incorrect entries and are thus limited. For example, some entries, such as senility or cardiac arrest, may not reflect the real CoD. Therefore, correcting CoD codes is necessary to estimate the burden of disease.   In order to increase the accuracy of CoD, Statistics Korea supplements data on infant deaths, which is frequently omitted from the Mother and Child Health Law registry data, as well as uncertain CoD using data from the National Cancer Center, National Health Insurance Service, National Police Agency, Ministry of National Defense, and Korean Coast Guard actually (5). The death certificate data is highly credible and easily accessible compared to other secondary sources; therefore, it is used in a variety of studies (6,7). However, problems regarding estimation of cause-specific mortality rates have been continuously raised despite the supplementation (7-10). For example, mortality due to senility, which is not valid CoD, accounted for 5% of CoD in Korea in 2012 (11). Therefore, accurately estimating the CoD will enhance the validity of cause-specific mortality rates still.   The GBD Study researchers have tried to improve the accu-

© 2016 The Korean Academy of Medical Sciences. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

pISSN 1011-8934 eISSN 1598-6357

Lee Y-R, et al.  •  Cause of Mortality and YLL in Korea racy of CoD by categorizing disease groups in accordance with GBD 2010 CoD. For example, in 1996, Murray and Lopez, investigators for Target cause the GBD Study, used the term “garbage codes” to describe causes GBD 2013 that cannot serve as an underlying CoD (12). Naghavi et al. (13) further characterized these garbage codes into four categories Number of deaths* GBD 2010 as follows: (i) causes that cannot or should not be considered as an underlying CoD (e.g. R54: senility); (ii) intermediate causes GBD 2013/Expert (e.g. I50: heart failure); (iii) immediate causes that are the final Garbage code judgement MATERIALS AND METHODS steps in a disease pathway leading to death (e.g. I46: cardiac arrest); and (iv) unspecified causes within a larger cause groupingData source and methodology for garbage code redistribution New Zealand BOD (e.g. B99: other and unspecified infectious diseases). The GBD The algorithm for garbage code redistribution was developed based on the GBD 2010 and 2010 Study added to this by drafting a list of 59 garbage codes 2013 Study (8,16),code the New Zealand Burden of Disease report (9), and the Fig. 1.methodologies Simplified garbage redistribution algorithm for useStudy in Korea. that have a wider application than the 26 garbage codes used GBD, Global Burden of Diseases; BOD, Burden of Diseases. Korean Standard Classification of Disease-6 (Fig. 1) (17). Furthermore, expert opinions were by the World Health Organization (WHO) in 2013 (8,14). To es- *According to Statistics Korea based on Korean Standard Classification of Disease (KCD-6). for a few diseases. The specialists of each disease examined the appropriateness of the timate the burden of disease accurately, garbage code deathsconsidered should be redistributed to other valid target disease groups todistribution rate, and as a result, the final garbage code list included 84 items. The 2010–2012 data on avoid underestimating the burden of disease. Therefore, theCoD statistics used tofrom calculate theKorea standard life expectancy (4).ofCoD was the Statistics were used to calculate the number deaths, and clasan ageGBD Study researchers developed a redistributed algorithm forspecific sified into target cause, which is target of redistributed garbage life table from Statistics Korea was used to calculate the standard life expectancy (4). CoD the GBD 2010 Study, which, with appropriate application, may code, and garbage code deaths (8,11). was classified into target cause, which is target of redistributed garbage code, and garbage code deaths help to estimate the YLLs accurately.   To apply the developed algorithm, the 2010-2012 CoD data   However, the disease classification system used in the Kore-(8,11).from the Statistics Korea were utilized to calculate age- and sexan Burden of Disease Study is different from the systems used specific ratesalgorithm, for eachthedisease inCoD a certain of time. To applydeath the developed 2010–2012 data fromperiod the Statistics Korea were by the GBD 2010 and 2013 studies. Furthermore, given that theutilizedThen the number of deaths within each of thein84 garbage to calculate age- and sex-specific death rates for each disease a certain periodcodes of time. Then methodologies of the GBD 2010 and 2013 studies were devel- was determined. Each garbage code death was then distributed the number of deaths within each of the 84 garbage codes was determined. Each garbage code death oped for worldwide use, they do not reflect the reality in each to a relevant target cause based on each garbage code proporwas then distributed to a relevant target cause based on each garbage code proportion. The distributed country. For example, among the garbage code list, 3.31% of tion. The distributed garbage code deaths were then redistribcodeagain deaths were then on redistributed again based on the sex- andrates age-specific rates tarof each deaths coded as cardiac arrest (ICD: I46) were redistributed togarbage uted based the sexand age-specific of each CoD.CoD. The total number of target cause death is the sum of original death target cause Chagas disease. However, Chagas disease has been shown totargetget The total number of target cause death isdue theto sum of and occur almost entirely in Latin America (15). Therefore, this par-sum oforiginal death due to target cause and sum of redistributed garredistributed garbage code death. ticular algorithm would not work in Korea, where Chagas dis- bage code death. ease almost does not exist. YLLs   Therefore, in order to resolve these discrepancies, this studyCalculating Calculating YLLs applied a modified garbage code redistribution algorithm based The used to estimate is (10). as follows (10). Theequation equation used to estimate YLL is asYLL follows on the GBD 2010 Study methodology to increase the validity of ��� �� ����������� ���� � ���� � �� � 1� � � ������� ���r � ��� � 1�� CoD estimation as well as to estimate age-, sex-, and cause-spe- ��� � �� � ��� �� cific mortality rates and YLLs in Korea.   �

1�� �1 � � ��� � �

r = discount rate; β = age-specific weight parameter, K = use of age-specific weight (when used age-weight, applied 1; when r = discount rate; β = age-specific weight parameter, K = use of age-specific weight (when used ageData source and methodology for garbage code did not0);use, = at constant; = age at death; weight, applied 1; when did not use, applied C = applied constant; 0); a =C age death; L =alife expectancy at L = life redistribution expectancy at death. death. The algorithm for garbage code redistribution was developed   For the purpose of this calculation, age-weight was estabbased on the GBD 2010 and 2013 Study methodologies (8,16), lished age-weight as 4% andwas theestablished discount as rate was For the purpose of this calculation, 4%(r) and the applied discount as rate3% (r) (1,11). the New Zealand Burden of Disease Study report (9), and the The results were then used to calculate the standard expected was applied as 3% (1,11). The results were then used to calculate the standard expected years of life Korean Standard Classification of Disease-6 (Fig. 1) (17). Fur- years of life lost (SEYLL), which is an indicator calculated by thermore, expert opinions were considered for which a fewisdiseases. setting the standard life expectancy for each age and lost (SEYLL), an indicator calculated by setting the standard life expectancy for each age multiplyThe specialists of each disease examined the appropriateness ing the standard life expectancy by the death rate for each age and multiplying the standard life expectancy by the death rate for each age as follows (10). of the distribution rate, and as a result, the final garbage code as follows (10). � list included 84 items. The 2010-2012 data on CoD statistics ����� � � �� ��∗ from the Statistics Korea were used to calculate the number of ��� deaths, and an age-specific life table from Statistics Korea was

MATERIALS AND METHODS

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age of x.

Here, ��∗ is life expectancy at the age of x, l is age at death, and �� is the death rate at the https://doi.org/10.3346/jkms.2016.31.S2.S121

Meanwhile, because of using the 2010 prevalence data to calculate YLDs of injury in this

Lee Y-R, et al.  •  Cause of Mortality and YLL in Korea  Here, ex* is life expectancy at the age of x, l is age at death, and dx is the death rate at the age of x.   Meanwhile, because of using the 2010 prevalence data to calculate YLDs of injury in this study, YLLs of injury were calculated using 2010 mortality data to ensure consistency and YLLs for all other diseases were calculated using 2012 data. Ethics statement This study was approved by the institutional review board of Korea University (IRB No. 1040548-KU-IRB-13-164-A-1).  

RESULTS The number of deaths To compare the number of deaths by year, cause of specific mortality was calculated for each year from 2010 to 2012. After ap-

The number of death (thousands)

300

plying the modified garbage code algorithm, the total number of deaths was approximately 257,000 in 2010, 259,000 in 2011, and 268,000 in 2012. The proportion of garbage code deaths was 24.6% in 2010, 24.8% in 2011, and 25.2% in 2012 and was higher in women (29.6%) than in men (21.6%) (Fig. 2).   Of the 84 items on the garbage code list, the top 15 items comprised 80% of all garbage code deaths, and senility ranked the highest at 15,054 cases, representing 22% of garbage code deaths and 5% of all deaths (Table 1). According to the Statistics Korea CoD data, in 2012, lung cancer was the most frequent CoD, followed by ischemic stroke, ischemic heart disease, self-harm, and liver cancer; however, after application of the garbage code redistribution algorithm, ischemic heart disease was the most frequent CoD, followed by ischemic stroke, lung cancer, selfharm, and hemorrhagic stroke (Table 2).   Among disease groups, the proportion of garbage code deaths

The number of target cause deaths (%)

The number of garbage code deaths (%)

250

25.2 24.6

24.8

200 74.8

75.2

150

75.4

21.0

100 79.0



Male

29.6 78.4

78.6

70.8

Female

21.6 29.2

29.2

50 0

21.4

70.4

70.8

Total



Male

2010

Female

Total



2011

Male

Female

Total

2012

Fig. 2. The number of target cause deaths compared to garbage code deaths from Statistics Korea during 2010-2012. Table 1. Ranking of garbage codes by number of deaths in 2012 Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Garbage code Senility Pneumonitis Heart failure Renal failure Disseminated intravascular coagulation, cardiac arrest, acute respiratory failure, and coma Hypertension Undetermined intentional or unintentional Cerebrovascular disease Septicemia Unintentional exposure to unspecified factors Malignant neoplasm without specification of site Unspecified heart disease Gastrointestinal hemorrhage All disorders of electrolyte and fluid balance Cardiac conduction disorders

https://doi.org/10.3346/jkms.2016.31.S2.S121

No. of deaths Male

Female

Total

4,938 5,496 1,441 2,196 2,182 780 1,495 1,070 922 691 500 466 332 258 186

10,116 5,274 2,849 2,000 1,530 1,567 806 1,225 1,233 1,196 433 336 327 184 231

15,054 10,770 4,290 4,196 3,712 2,347 2,301 2,295 2,155 1,887 933 802 659 442 417

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Lee Y-R, et al.  •  Cause of Mortality and YLL in Korea was the lowest among psychological diseases (8.4%), followed by cancer (8.5%) and musculoskeletal diseases (10.6%). On the contrary, disease groups with the highest proportion of garbage code deaths were diarrhea, lower respiratory, and other communicable disease (60.7%), followed by unintentional injuries other than transport injuries (53.7%) and neglected tropical diseases and malaria (41.5%) (Fig. 3). However, 39.4% of garbage code deaths were redistributed to cardiovascular and circulatory diseases, followed by neoplasms (10.4%) and uninten-

tional injuries other than transport injuries (9.6%) (Fig. 4).   When comparing the rates of age-specific garbage code deaths, 39.4% we found that as age increased, the proportion of garbage code

39.4% 39.4% 39.4% 39.4% 39.4% 39.4%

24.6% 24.6% 24.6% 24.6% 24.6% 39.4% 24.6%

1 1 1 1 9.6% 11 24.6% 7.8% 24.6% 9.6% 7.8% 8.2% 10.4% 9.6% 7.8% 8.2% Table 2. Ranking of cause of death in 2012 with and without garbage code redistri9.6% 7.8% bution 8.2% Cardiovascular and circulatory diseases 10.4% 9.6%(3 9.6% 7.8% 8.2% 7.8% No. of deaths Cardiovascular and circulatory diseases 9.6%(3 7.8% 8.2% 8.2% diseases Cardiovascular and circulatory (3 Rank Cause of death without garNeoplasms (10.4%) Cause of death with gar8.2% No. No. Cardiovascular and circulatory diseases (3 Neoplasms (10.4%) bage code redistribution* bage code redistribution* Cardiovascular and circulatory (3 Neoplasms (10.4%) Unintentional injuries other thandiseases transpor 1 Lung cancer 16,782 Ischemic heart disease 25,836 Cardiovascular and circulatory diseases (39.4%) Cardiovascular and circulatory diseases (3 9.6% 7.8% Neoplasms (10.4%) Unintentional injuries other than transpor 2 Ischemic stroke 15,164 Ischemic stroke 20,253 Neoplasms (10.4%) 8.2% Neoplasms (10.4%) Unintentional injuries other than transpor Diabetes, urogenital, blood, and endocrine 3 Ischemic heart disease 14,640 Lung cancer 17,869 Neoplasms (10.4%) Unintentional injuries other thaninjuries transport injuries (9.6%) Unintentional otherand thanendocrine transpor Diabetes, urogenital, blood, 4 Self-harm 14,094 Self-harm 15,170 Unintentional other than transpor Diabetes, urogenital, blood, and injuries endocrine diseases (8.2%) and Diabetes, urogenital, blood, endocrine 5 Liver cancer 11,413 Hemorrhagic and other 12,936 Chronic repiratory diseases (7.8%) Cardiovascular and circulatory diseases (39.4%) Unintentional injuries other than transpor Diabetes, urogenital, blood, and endocrine Chronic repiratory diseases (7.8%) nonischemic stroke Chronic repiratory diseases (7.8%) Diabetes, urogenital, blood, and endocrine Chronic repiratory diseases (7.8%) Others (24.6%) (24.6%) Others *Derived from the Statistics Korea Database; Including tracheal andNeoplasms bronchial can(10.4%) Diabetes, urogenital,diseases blood, and endocrine Chronic repiratory (7.8%) Others (24.6%) cer; The mortality data from 2010 were applied because prevalence data from 2010 repiratory Others Fig. 4. ProportionChronic of redistributed(24.6%) garbage code deaths bydiseases target causes. (7.8%) were used to calculate the disability-adjusted life years. Chronic repiratory diseases (7.8%) Unintentional injuries than transport injuries (9.6 Othersother (24.6%) Others (24.6%) 0% 20% 40% 60% 80% 100% 0 20 40 60 80 100 (%) Others (24.6%) Diabetes, urogenital, blood, and endocrine diseases (8.2% †

†

‡

†

Communicable diseases Communicable diseases

‡

Fig. 4. Proportion of redistributed garbage code deaths by tar 74.1 25.9 Fig. 4. Proportion of redistributed garbage code deaths by tar 39.3 60.7 Diarrhea, LRI, meningitis, and common infectious diseases Diarrhea, LRI, meningitis, and common infectious diseases Fig. 4. Proportion of redistributed garbage code deaths by tar Chronic repiratory diseases (7.8%) Fig. 4.andProportion of redistributed garbage code deaths by tar 58.5 41.5 Neglected tropical diseases and malaria Neglected tropical diseases malaria Fig. 4. Proportion of redistributed code deaths by tar 82.8 17.2 Maternal and neonatal disorders Maternal and Neonatal disorders Others (24.6%)of redistributed garbage Fig. 4. Proportion garbage code deaths by tar HIV/AIDS tuberculosis HIV/AIDS and and tuberculosis

Nutritional deficiencies Nutritional deficiencies

Other communicable disorders Other communicable disorders

59.9

46.1

40.1

53.9

Non-communicable diseases Non-communicable diseases

Neoplasms Neoplasms

91.5 8.5

62.7 37.3 Cardiovascular and circulatory diseases Cardiovascular and circulatory diseases Fig. 4. Proportion of redistributed garbage code deaths by target causes 73.4 26.6 Chronic repiratory diseases Chronic repiratory diseases

Digestive diseases Digestive diseases

67.8

Neurological disorders Neurological disorders

80.6

19.4

Mental Mental and behavioral disorders and behavioral disorders

91.6

Diabetes, urogenital, blood, blood, and endocrine diseases Diabetes, urogenital, and endocrine diseases

72.3

89.4 10.6 70.3

Transport injuries Transport injuries Unintentional other transport than transport injuries Unintentional injuries injuries other than injuries

46.3

18.1

53.7 83.4 16.6

nature, war,legal and legal intervention Forces of Forces nature,of war, and intervention Garbage codecode deathsdeaths (%) Garbage

29.7 81.9

Self-harm and interpersonal violence Self-harm and interpersonal violence

Target cause deaths (%) Target cause deaths (%)

8.4

27.7

Musculosketal disorders Musculosketal disorders Other non-communicable diseases Other non-communicable diseases

Injury* Injury*

32.2

87.7

12.3

(%)

Fig. 3. Proportion of deaths in 2012 assigned a garbage code according to disease groups. LRI, lower respiratory infections. *The mortality data from 2010 were applied because prevalence data from 2010 were used to calculate the disability-adjusted life years, which is a parent study of this study.

Fig. 3. Proportion of deaths in 2012 assigned a garbage code according to disease groups *

The mortality data from 2010 were applied because prevalence data from 2010 were used to calculate the disabilityS124   http://jkms.org https://doi.org/10.3346/jkms.2016.31.S2.S121 adjusted life years, which is a parent study of this study

LRI, Lower respiratory infections.

0-9 10-19 20-29 Lee Y-R, et al.  •  Cause of Mortality and YLL in Korea

30-39

40-49

50-59

60-69

70-79

Total

Male

Female

Total

Female

Male

Total

Male

Female

Total

Female

Male

Total

Female

Male

Total

Female

Male

Total

Female

Male

Total

Female

Male

Total

Female

Male

0%

80+

Age group Target cause deaths (%) Target cause deaths (%)

Garbage codecode deathsdeaths (%) Garbage (%)

100% 100 90% 90

11.8 12.0 11.8 11.1 11.2 11.1 13.1 11.4 12.5 14.6 10.1 13.0 17.3 11.0 15.5 16.5 12.4 15.5 16.1 15.6 16.0 20.2 22.5 21.2 33.4 39.9 37.5

88.0 88.2 88.9of 88.8 88.9 86.9in 88.6 87.5 assigned 89.9 87.0 a garbage code by sex and age group Fig. 5. 88.2 Proportion deaths 2012 89.0 85.4 87.6 80% 80 84.5 83.9 84.4 84.0

84.5 83.5

82.7

79.8

77.5 78.8

70% 70

66.6

(%)

60% 60

60.1 62.5

50% 50 40% 40 30% 30 20% 20

0-9

10-19 10-19

20-29 20-29

30-39 30-39

40-49 40-49

50-59 50-59

60-69 60-69

70-79 70-79

Total Total

Female Female

Male Male

Total Total

Female Female

Male Male

Total Total

Female Female

Male Male

Total Total

Female Female

Male Male

Total Total

Female Female

Male Male

Total Total

Female Female

Male Male

Total Total

Female Female

Male Male

Total Total

Female Female

Male Male

Total Total

Female Female

0%0

Male Male

10% 10

80+ 80+

Age Age group group (%) Fig. 5. Proportion of deaths in 2012 assigned a garbageTarget code bycause sex anddeaths age group.

450

350 a garbage code by sex and age group 129 300

5

308

109 243

250 200 150 100 50

39 45

19 35

49 75

70 125

117 241

180 218

135 71

0-9 10-19 20-29 30-39 40-49 50-59 60-69 70-79 ≥ 80

Age group

YLLs Premature death contributed 2,208 thousand YLLs in Korea in 2012, including 1,361 thousand among men and 847 thousand among women (a difference of 1.6 times). The number of YLLs was highest among those aged 50-59 years (308 thousand), and YLLs for men aged 50-59 accounted for 23% of the total YLLs. The number of YLLs was highest among women aged 70-79 years (180 thousand) (Fig. 6).   In terms of disease-specific YLLs, we found that self-harm was the most frequent cause of YLLs (573 YLLs per 100,000 individuals), followed by ischemic heart disease (YLLs = 308 per 100,000 individuals), lung cancer (YLLs = 250 per 100,000 individuals), and liver cancer (YLLs = 234 per 100,000 individuals). Differences by gender were also found. For example, among both men and women, self-harm contributed the most YLLs per 100,000 individuals (729 for men, 417 for women), followed by ischemic heart disease (374 for men, 241 for women). However, among men, liver cancer (YLLs = 362 per 100,000 individuals) was the third leading cause of YLLs, followed by lung canhttps://doi.org/10.3346/jkms.2016.31.S2.S121

Male Female

400

YLLs (thousands)

deaths also tended to increase. The proportion of age-specific garbage code deaths according to sex was relatively higher in Fig.20-60 5. Proportion deaths assigned men aged years than inof women of in the2012 same age group; however, the proportion was found to be higher in women aged ≥ 60 years than in men of the same age group. In addition, the proportion of garbage code deaths was the highest in women aged ≥ 80 years when compared to all other age groups, accounting for approximately 40% of cases (Fig. 5).

Garbage code deaths (%)

Fig. 6. Years of life lost in 2012 by sex and age group after garbage code redistribution. YLLs, years of life lost.

cer (YLLs = 351 per 100,000 individuals), and cirrhosis of the liver (YLLs = 320 per 100,000 individuals), whereas hemorrha­ gic stroke (YLLs = 202 per 100,000 individuals) was the third leading cause of YLL for women, followed by ischemic stroke (YLLs = 177 per 100,000 individuals), and lung cancer (YLLs = 149 per 100,000 individuals) (Table 3).   Among the total YLLs in 2012, self-harm contributed the most YLLs followed by ischemic heart disease, lung cancer, liver cancer, and hemorrhagic stroke after applying the garbage code redistribution algorithm; however, when calculating the YLLs without the garbage code redistribution, self-harm contributed the most YLLs followed by lung cancer, liver cancer, cirrhosis of the liver, and ischemic heart disease. In particular, ischemic heart disease rose from the 5th place to the 2nd place after application of the garbage code redistribution, and hemorrhagic

5

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Lee Y-R, et al.  •  Cause of Mortality and YLL in Korea Table 3. Top 5 causes of death by YLLs per 100,000 individuals according to sex* Male Rank 1 2 3 4 5

Female

Disease

YLLs/per 100,000

Self-harm† Ischemic heart disease Liver cancer Lung cancer‡ Cirrhosis of the liver

729 374 362 351 320

Total

Disease

YLLs/per 100,000

Disease

YLLs/per 100,000

Self-harm† Ischemic heart disease Hemorrhagic and other non-ischemic stroke Ischemic stroke Lung cancer‡

417 241 202 177 149

Self-harm† Ischemic heart disease Lung cancer‡ Liver cancer Hemorrhagic and other non-ischemic stroke

573 308 250 234 228

YLLs, years of life lost. *Garbage code deaths redistributed; †The mortality data from 2010 were applied because prevalence data from 2010 were used to calculate the disability-adjusted life years; ‡ Including tracheal and bronchial cancer. Table 4. Top 5 causes of death by YLLs in 2012 with and without garbage code death redistribution Rank 1 2 3 4 5

YLLs without garbage YLLs/per code death redistribution 100,000 Self-harm* Lung cancer† Liver cancer Cirrhosis of the liver Ischemic heart disease

536 235 223 181 179

YLLs with garbage code death redistribution

YLLs/per 100,000

Self-harm* Ischemic heart disease Lung cancer† Liver cancer Hemorrhagic and other non-ischemic stroke

573 308 250 234 228

30.3%

23.7%

5.8%

19.0%

5.9% 15.3%

YLLs, years of life lost. *The mortality data from 2010 were applied because prevalence data from 2010 were used to calculate the disability-adjusted life years; †Including tracheal and bronchial cancer.

Neoplasms (30.3%) Neoplasms Neoplasms (30.3%) (30.3%) Neoplasms (30.3%) Neoplasms (30.3%) Cardiovascular and circulatory diseases (19.0%) Neoplasms (30.3%) Neoplasms (30.3%) Neoplasms (30.3%) Cardiovascular and circulatory diseases (19.0%) Cardiovascular and circulatory diseases Cardiovascular anddiseases circulatory diseases (19.0%) (19.0%) Cardiovascular and circulatory diseases(19.0%) (19.0%)diseases Cardiovascular and circulatory Cardiovascular and circulatory (19.0%) Self-harm and interpersonal violence (15.3%) Cardiovascular and circulatory diseases (19.0%) Self-harm and interpersonal violence (15.3%) Self-harm and interpersonal violence (15.3%) Self-harm and interpersonal violence (15.3%) Self-harm and interpersonal violence (15.3%) Self-harm and and interpersonal interpersonal violence violence (15.3%) (15.3%) Self-harm Unintentional injuries other than transport injuries Self-harm andother interpersonal violence (15.3%) Table 5. Most common diseases and related YLLs by age group* Unintentional injuries thantransport transport injuries (5.9%) Unintentional injuries other than transport injuries (5.9%) (5.9%) Unintentional injuriesother than (5.9%) Unintentional injuries other than transport Unintentional injuries otherinjuries than transport injuries injuries (5.9%) (5.9%) Unintentional injuries other than transport injuries Transport injuries (5.8%) Transport injuries (5.8%) Age groups, yr Disease YLLs/100,000 Unintentional injuries other than transport injuries (5.9%) (5.9%) Transport injuriesinjuries (5.8%) Transport (5.8%) Transport injuries (5.8%) Transport injuries (5.8%) (5.8%) Others (23.7%) Transport injuries 0-9 Preterm birth complications 384 Others (23.7%) Others (23.7%) Transport injuries (5.8%) Others (23.7%) Others 10-19 Self-harm† 201 Others (23.7%) (23.7%) Others (23.7%) Fig. 7. Proportion of years of life lost by disease group in Korea in 2012 after garbage co † 20-29 Self-harm 840 Fig. 7. ProportionOthers of years (23.7%) of life lost by disease group in Korea in 2012 after gar30-39 40-49 50-59 60-69 70-79 ≥ 80

Self-harm† Self-harm† Self-harm† Lung cancer‡ Ischemic heart disease Ischemic heart disease

843 738 632 866 1,465 2,637

Fig. 7. of years of bageProportion code redistribution. Fig. 7. Proportion of years of Fig. 7. Proportion of years of redistribution Fig. 7. Proportion of years of Fig. 7. Proportion of years Fig. 7. Proportion of years of of redistribution redistribution redistribution ed the most YLLs (Table 5). redistribution redistribution redistribution

YLLs, years of life lost. *Garbage code deaths were redistributed; †The mortality data from 2010 were applied because prevalence data from 2010 were used to calculate the disability-adjusted life years; ‡Including tracheal and bronchial cancer.

stroke rose from the 7th place to the 5th place (Table 4).   After redistributing all diseases into 21 sub-classifications, neoplasms represented 30.3% of the total YLLs, whereas cardiovascular and circulatory diseases accounted for 19.0%, and self-harm and interpersonal violence for 15.3%. These three disease groups comprised 64.6% of the total YLLs (Fig. 7).   For age-specific YLLs, preterm birth complications contributed the most YLLs (384 per 100,000 individuals aged 0-9 years), while self-harm contributed the most among those aged 10-59 years. Among individuals aged 60-69 years, lung cancer contri­ buted the most YLLs (866 per 100,000 individuals), while among individuals aged ≥ 70 years, ischemic heart disease contribut-

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disease disease disease disease disease disease

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DISCUSSION In this study, we measured the YLLs in Korea during 2010-2012 after applying a garbage code redistribution algorithm. The total YLL were 2,208 thousand in 2012. In addition, self-harm contributed the most YLLs (573 per 100,000 individuals), followed by ischemic heart disease and lung cancer. The annual proportion of garbage codes was approximately 25% from 2010 to 2012.   According to the GBD 2010 Study, ischemic heart disease, ischemic stroke, hemorrhage stroke, chronic obstructive pulmonary disease, and lower respiratory infections were the most common CoD worldwide. In Korea, ischemic stroke, ischemic heart disease, lung cancer, hemorrhage stroke, and self-harm were the most common CoD by GBD7 2010 study (3). However, in this study, ischemic heart disease, ischemic stroke, lung cancer, self-harm, and hemorrhagic stroke were the most common CoD; these results are quite different from the GBD 2010 Study https://doi.org/10.3346/jkms.2016.31.S2.S121

7

Korea Korea Korea Korea Korea Korea

in in in in in in

Lee Y-R, et al.  •  Cause of Mortality and YLL in Korea results. This may be due to differences in the data source or the garbage code algorithm. Actually, the original CoD data from the Statistics Korea showed that the most common CoD was lung cancer followed by ischemic stroke, ischemic heart disease, self-harm, and liver cancer. This change in order was also presented in YLLs. The rank of YLLs with and without garbage code death redistribution was different except self-harm. This indicates that using raw data to estimate CoD is not sufficient for estimating the burden of disease. Therefore, additional consideration is required when ranking diseases for health care policymaking, and health care policy measures for cardiovascular disease prevention are warranted.   In 2012, the total YLLs were 2,208 thousand, showing a slight increase from 2007 (2,188 thousand YLLs) (1). In 2012, the total YLL for men were 1,361 thousand, which was 1.6 times higher than that for women (847 thousand). Among men, the number of YLLs was the highest among those aged 50-59 years (308 thousand), while among women, the number of YLLs was the highest for those aged 70-79 years (180 thousand). The results for men are consistent with those from a previous study (1). Furthermore, unlike the age-specific mortality rate, which increases with age, the YLLs remained the highest among men aged 50-59 years. In particular, the YLL for those aged 30-59 years were 676 thousand in 2012, comprising 50% of the YLL for men and 30% of the total YLL. The premature death of individuals in the productive age group who support their household economy signifies a huge loss for the country (1). Therefore, measures to prevent loss due to premature deaths in the productive age group are urgently needed.   In addition, while ischemic heart disease contributed the most to the number of deaths, self-harm contributed the most to YLLs. This may be explained by the relatively high number of deaths at young ages due to self-harm. Diseases with high rates of YLLs signify a great burden on society, and hence, policy measures to reduce YLLs are required. In particular, self-harm, which is categorized as a preventable mortality but is the leading CoD among those in the productive age group, requires further attention (18).   Furthermore, among disease groups, cancer showed a tendency to rank lower in both the number of deaths and YLLs after applying the garbage code redistribution algorithm. On the contrary, cardiovascular diseases tended to rank higher, which may be because 47% of senility deaths, which comprise the highest proportion of all garbage code deaths, were redistributed to cardiovascular disease. Furthermore, 87% of heart failure deaths and 98% of high blood pressure deaths were redistributed to cardiovascular disease, which may also contribute to the high ranking.   Per the GBD 2010 Study, the proportion of garbage code deaths was the lowest in Finland at 5.5% and the highest in Sri Lanka at 69.6% (8). In New Zealand, the proportion of garbage codes https://doi.org/10.3346/jkms.2016.31.S2.S121

was 10.4% for all deaths (9), while in United Kingdom, this value was 17.5% (19). On the other hand, according to a WHO report, the value in Haiti was estimated to be 32%-52% and in Thailand, the value was estimated to be 39%-54% (14). Thus, although the proportion of garbage code deaths in Korea is relatively low when compared to that in other developing countries, it is still higher than the proportion in other developed countries. This implies a need to redistribute CoD to increase the validity of the cause-specific mortality rates.   The proportion of garbage code deaths tended to increase with age. For example, in individuals aged 0-9 years, the proportion of garbage code was 11.8%. On the other hands, in case of ≥ 80 years, the proportion was 37.5%. It seems that accurate diagnosis of CoD becomes more difficult with age as the number of comorbidities increases (7,20). Also, the total number of deaths was 1.23 times higher for men than that for women, but the number of garbage code deaths was 1.11 times higher in women (29%) than in men (21%). This may be explained by the longer life expectancy for women as well as differences in CoD between men and women. For example, the leading cause of death for women is ischemic heart disease, for which garbage code deaths were most frequently redistributed. However, further research regarding the cause of gender differences is necessary.   This study has some limitations. For example, we used a modified garbage code redistribution algorithm based on the GBD 2010 Study, and although garbage code algorithms, like those in New Zealand and the United Kingdom, are widely used, these algorithms need to be further validated among different populations, including Korean populations. Therefore, studies examining the real cause of death in Korea are needed in the future.   Accurate estimation of YLLs is important for epidemiological research and policymaking, and estimation of CoD and YLLs should be enhanced. The results of this study showed that selfharm contributed the most to YLLs, followed by ischemic heart disease and lung cancer. In addition, the results showed that garbage code deaths that were inaccurate or did not represent the underlying CoD for 25% of all deaths every year from 2010 to 2012. Thus, the applied algorithm and results of this study may help to estimate the burden of disease more accurately by identifying the specific cause of mortality. Furthermore, these results may be used to prioritize diseases when allocating limited health care resources and establishing related policies.

DISCLOSURE The authors declare that they have no competing interests.

AUTHOR CONTRIBUTION Study conception and design: Oh IH, Lee YR. Acquisition of http://jkms.org  S127

Lee Y-R, et al.  •  Cause of Mortality and YLL in Korea data: Kim YA, Park SY. Analysis and interpretation of data: Kim YA, Lee YR, Oh CM. Manuscript preparation: Lee YR, Oh IH. Critical revision of manuscript: Kim Y, Oh CM, Park SY, Oh IH. Approval of manuscript: all authors.

ORCID Ye-Rin Lee  http://orcid.org/0000-0002-4507-4877 Young Ae Kim  http://orcid.org/0000-0002-3819-0028 So-Youn Park  http://orcid.org/0000-0003-0553-5381 Chang-Mo Oh  http://orcid.org/0000-0002-5709-9350 Young-eun Kim  http://orcid.org/0000-0003-0694-6844 In-Hwan Oh  http://orcid.org/0000-0002-5450-9887

2095-128. 9. Ministry of Health (NZ). Ways and means: a report of methodology from the New Zealand burden of diseases, injuries and risk factor study, 20062016 [Internet]. Available at http://www.health.govt.nz/publication/waysand-means-report-methodology-new-zealand-burden-disease-injuryand-risk-study-2006-2016 [accessed on 8 July 2015]. 10. Chang H, Myoung JI, Shin Y. Burden of disease in Korea: years of life lost due to premature deaths. Korean J Prev Med 2001; 34: 354-62. 11. Yoon SJ, Jo MW, Park HS, Oh IH, Kim BS, Kim DW, Yoon JH, Ko SK, Kong YH, Jung JH, et al. A Study on Measuring and Forecasting the Burden of Disease in Korea. Cheongju: Ministry of Health and Welfare, 2015. 12. Murray CJ, Lopez AD. The Global Burden of Disease: a Comprehensive Assessment of Mortality and Disability from Diseases, Injuries and Risk Factors in 1990 and Projected to 2020 (Global Burden of Disease and Injury Series Vol. 1). Cambridge, MA: Harvard University Press, 1996.

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