| Home | E-Submission | Sitemap | Contact Us |  
top_img
Cancer Research and Treatment > Volume 55(2); 2023 > Article
Jung and Yoon: Trends and Patterns of Cancer Burdens by Region and Income Level in Korea: A National Representative Big Data Analysis

Abstract

Purpose

This study aimed to elucidate the trends and characteristics of the cancer burden in Korea by cancer site, region, and income level.

Materials and Methods

Korean National Burden of Disease research methodology was applied to measure the cancer burden in Korea from 2008 to 2018. The cause of death and National Health Insurance claims data were obtained from Statistics Korea and the National Health Insurance Service, respectively. An incidence-based approach was applied to calculate the disability-adjusted life-years, which is a summary measure of population health.

Results

In the past decade, the cancer burden in Korea increased from 2,088 to 2,457 person-years per 100,000 population. Among the cancer burden, the years of life lost decreased, and the years lived with disabilities increased. Cancers of the trachea, bronchus, and lung had the highest disease burden, followed by those of the stomach, colon and rectum, liver, and breast.

Conclusion

The findings of this study can provide valuable quantitative data for prioritizing and evaluating cancer prevention strategies and implementing cancer policies. Estimating the difference in cancer burden according to region and income level within a country can yield useful data to understand the nature of the cancer burden and scale of the problem. In addition, the results of this study provide a better understanding of the causes of cancer patterns, thereby generating new hypotheses regarding its pathogenesis.

Introduction

Cancer has been the leading cause of death worldwide over the past few decades, and it remains a major barrier to increasing the life expectancy [1]. The incidence and mortality due to cancer is rapidly increasing worldwide, and the International Agency for Research on Cancer reported 19.3 million new cancer cases and 10 million deaths due to cancer worldwide in 2020 [2]. In Korea, the number of new cancer cases in 2018 was 243,837 (128,757 male, 115,080 female), and has been increasing every year since 2015 [3]. The increase in disease burden due to cancer reflects not only the aging and growth of the population, but also the increase in the prevalence of major cancer risk factors.
The Korea Central Cancer Registry (KCCR) has collected cancer incidence data nationwide since 1999 [4], presenting an opportunity to identify trends in cancer incidence and causes by periodically providing nationwide cancer statistics. However, few studies have measured the cancer burden by year using a comprehensive measure that combines morbidity and mortality, while providing information on the national cancer status for individual indicators, such as cancer incidence, prevalence, and survival. Additionally, differences in cancer morbidity and mortality exist according to region and country, mainly due to differences in population risk factors deriving from socioeconomic differences [5]. In the Global Burden of Disease (GBD) study, the disease burden was classified according to the socio-demographic index (SDI), a composite index that reflects the national income level and educational background [6]. However, to the best of our knowledge, no studies to date have calculated the differences in cancer disease burden according to individual socioeconomic factors within a country. A comprehensive assessment of the disease burden in population groups at the national level can aid in various decision-making processes, such as the prioritization of healthcare services and research, and resource allocation. Furthermore, clarifying the disease burden can provide insights to organizations and individuals committed to health policy and can be used as an evaluation tool of national cancer control programs undertaken by the Korean government.
Therefore, this study was conducted to identify trends in the cancer burden among Koreans according to cancer site, sex, region and income level using big data, including claims data from the National Health Insurance Service (NHIS).

Materials and Methods

1. Study design and data sources

Based on the classification system of the Korean National Burden of Diseases (KNBD), we selected 30 cancers to analyze. Among these, 25 were solid tumors, including cancers of the (1) esophagus, (2) stomach, (3) liver, (4) larynx, (5) trachea, bronchus, or lung (TBL), (6) breast, (7) cervical, (8) uterine, (9) prostate, (10) colon and rectum, (11) mouth, (12) nasopharynx, (13) other parts of the pharynx and oropharynx, (14) gallbladder and biliary tract, (15) pancreas, (16) ovary, (17) testicular, (18) kidney, (19) other urinary organs, (20) bladder, (21) brain and nervous system, (22) thyroid, (23) bone and connective tissue, (24) malignant melanoma of the skin, and (25) non-melanoma skin cancer. In addition, there were four blood cancers, including (26) Hodgkin’s disease, (27) non-Hodgkin’s lymphoma, (28) multiple myeloma, and (29) leukemia. Finally, (30) benign neoplasms of the brain and other parts of the central nervous system, which are benign neoplasms of other specific sites, were also included in this study.
We estimated the 2008–2018 national cancer burden in terms of years of life lost (YLL), years lived with disabilities (YLD), and disability-adjusted life years (DALYs). In this study, the GBD-based measurement methodology was modified to suit the Korean situation, and an incidence-based approach was applied to the calculation [7]. In the KNBD study, the national disease burden was measured as the DALY. The DALY is an index of the level of health measured by expressing illness and death as a single scale, along with the quality-adjusted life years (QALY). For the QALY, the individual level is the subject of analysis, and the preference for the health state is determined by weights selected by individuals. In contrast, for the DALY, preference for the health state is determined by weights according to the severity of each disease as deter-mined by experts. Additionally, since the DALY is applied to a population group, it is more useful in measuring the national level of health [8].
For YLL measurement, we calculated the mortality rate by age, sex, and disease using the data on the cause of death by year (for 2008–2018) from Statistics Korea; for indicated causes that could not be the cause of death, garbage codes were applied and redistributed [9]. The standard expected YLLs were used to calculate the number of years lost due to premature death. The standard life expectancy was based on the 2008–2018 life table by year, sex, and age provided by Statistics Korea [10].
To calculate the prevalence and incidence rates for YLD measurement, we used health insurance claims data by year (for 2008–2018). In a previous KNBD study, cancer registration data was used to calculate the cancer burden; however, as with other diseases, the data source has been changed to health insurance claims data. This is because the KCCR publishes data from the two previous years [11], while the NHIS database is updated every year, enabling the prevalence and incidence rates according to region and income levels to be calculated every year. Korea has a mandatory universal health coverage system. As of the end of 2020, a total of 52,870,968 people receive health security benefits in Korea; of these, the National Health Insurance (NHI) covers 97.1% and the remaining 2.9% comprise Medical Aid beneficiaries. The Medical Aid program is a form of public assistance [12]. The NHIS claims database contains information, such as the diagnosis name, treatment start and end dates, prescription history, and whether surgery was performed as medical treatment, with the exception of non-insured items [13]. To prevent overestimation of the incidence and prevalence rates from claims data, the prevalence was defined as ≥ 1 hospitalization or three outpatient visits, and a 5-year washout period was applied to calculate the number of occurrences.

2. Statistical analyses

YLL by cancer site was calculated by multiplying the number of deaths by sex and year by the standard life expectancy in each age group. To calculate the YLD, the incidence rate of each cancer was multiplied by the average duration and the assigned disability weight. We applied disability weights for specific causes, measured using a domestic self-report questionnaire [14]. The disease duration and average age of onset were estimated using the DisMod-II program. We measured the YLD using an incidence-based approach, with consideration of the disease prevalence, incidence, mortality, case fatality, and disability weight. In this study, when calculating the YLL and YLD, an age-weighting rate of 4% and a time discount of 3% were applied [7]. Finally, the YLL and YLD were summed to calculate cancer-site DALYs. We calculated the YLL, YLD, and DALY rates per 100,000 population by cancer type and sex, and then ranked the leading causes of disease burden.
For the regional classification, 250 municipal-level administrative districts were selected, comprising 67 cities (“Si”), 114 counties (“Gun”), and 69 districts (“Gu”). Because the NHIS calculates insurance premiums based on the wage and income of beneficiaries, insurance premiums were used as a proxy for classifying the income level of the population. Therefore, we used equivalized annual household income based on insurance premiums, divided into quintiles by sex. Additionally, insurance premiums for Medical Aid beneficiaries (who do not pay insurance premiums) were calculated as 0. Income levels were equally divided into five groups for all populations, including NHI beneficiaries and Medical Aid beneficiaries. The equivalized annual household income was derived as follows:
Equivalisedannualhouseholdincome=AnnualhouseholdincomeNo.ofhouseholdmember0.5
Because it is impossible to confirm the income level from the data on the cause of death in Statistics Korea, we obtained the death rate distribution by income level from the claims data. By applying this to the YLL calculation result, YLL was distributed according to income level. We present all results in units per 100,000 population, as the YLL, YLD, and DALY rates. SAS ver. 9.4 (SAS Institute Inc., Cary, NC) was used for statistical analysis.

Results

From 2008 to 2018, the DALY rate increased approximately 17.7% (from 2,088 to 2,457, respectively). In 2018, 52.4% of the Korean cancer DALY rates stemmed from the YLL (1,288) and 47.6% from the YLD (1,169). Between 2008 and 2018, the YLL rate decreased by 2.6% (from 1,322 to 1,288), whereas the YLD rate increased by 52.6% (from 766 to 1,169) (Fig. 1).
The leading causes of cancer DALYs for both sexes in 2018 were TBL cancers (n=349), stomach cancer (n=289), colon and rectum cancers (n=277), liver cancer (n=277), and breast cancer (n=241), which accounted for 58.3% of the total cancer burden in Korea. The proportion of the YLL in the DALY was the highest (≥ 70%) in pancreatic cancer, gallbladder and biliary tract cancer, brain and nervous system cancers, liver cancer, and TBL cancers, and the lowest in thyroid cancer and benign neoplasms of the brain and other parts of the central nervous system (< 10%) (Fig. 2). There was a difference in the cancer ranking between males and females: in males, the DALY rate was the highest for TBL cancers (n=482), liver cancer (n=426), stomach cancer (n=381), colon and rectum cancers (n=328), and prostate cancer (n=183); in females, it was the highest for breast cancer (n=474), colon and rectum cancers (n=226), TBL cancers (n=218), stomach cancer (n=198), and thyroid cancer (n=162). The five major cancers accounted for 66.2% and 58.2% of the total cancer burden in males and females, respectively (Table 1).
Trends over the past decade varied by cancer type. Between 2008 and 2018, the DALY rates for prostate cancer, multiple myeloma, testicular cancer, other urinary organ cancers, uterine cancer, and breast cancer significantly increased by more than 60%. Prostate cancer remained in the top 15 in 2008 but rose to the top eight in 2018. In contrast, the DALY rates of laryngeal, cervical, stomach, liver, and nasopharyngeal cancers decreased. Both the YLL and YLD rates decreased in cervical and laryngeal cancers. However, for stomach, liver, and nasopharyngeal cancers, the YLL rate decreased while the YLD rate increased, revealing that a decrease in the YLL rate contributed to a decrease in the DALY rate. As shown in Fig. 3, the rankings of TBL cancers and colorectal cancer have risen over the past 10 years, while those of stomach and liver cancers have declined slightly.
The distribution and difference in cancer burden by region were examined. The region with the highest DALY rate was Gunwi-gun, Gyeongsangbuk-do (n=4,312), which had a rate 2.61 times higher than that in the lowest region, Yeongtong-gu, Suwon-si, Gyeonggi-do (n=1,650). Further, the highest regional YLL rate (Gunwi-gun, Gyeongsangbuk-do; n=2,702) was 3.65 times higher than the lowest regional YLL rate (Yeongtong-gu, Suwon-si, Gyeonggi-do; n=740). Additionally, the highest regional YLD rate (Goesan-gun, Chungcheongbuk-do; n=1,787) was 1.96 times higher than the lowest regional YLD rate (Yeongtong-gu, Suwon-si, Gyeonggi-do; n=910). Regions with an overall low disease burden tended to be distributed in Seoul and the Gyeonggi Province. Furthermore, the gap in the burden of cancer death was larger than that of the cancer incidence (Fig. 4).
The gap in the DALY rate according to income level decreased from 2008 to 2012 and then increased. In 2008, the cancer DALY rate was 1.71 times higher in the Q1 group (lowest income level) than in the Q5 group (highest income level). This decreased to 1.60 times in 2012, but then increased again to 1.81 times in 2018. However, the difference in disease burden between the Q1 and Q2 groups was in the range of 1.38 to 1.47, indicating a significant difference between Q1 and the other groups. In addition, in terms of the rate of DALY rate increase over the past 10 years, the Q3–Q5 group showed an increase rate of around 15%, whereas the Q1 and Q2 groups showed relatively higher increase rates of 21.3% and 20.5%, respectively (Fig. 5).
TBL cancers had the highest DALY rate among groups Q1 to Q5. In addition, the types of cancer ranked in the top five were the same. However, cancers with the second highest disease burden were stomach cancer in the Q2–Q4 groups, liver cancer in the Q1 group, and breast cancer in the Q5 group. Overall, the disease burden tended to decrease with increasing income level. Conversely, there were cases where the disease burden was greater in the high-income group than in the low-income group. For thyroid cancer, the DALY rate gradually increased as the income level increased, and the gap between Q1 and Q5 was 32 (Q1: 87, Q5: 119). In the case of prostate cancer, there was no constant increase according to income level, but among the groups, the DALY rate (107) was the highest in the Q5 group (S1 Table).

Discussion

This study was conducted to quantify the burden of premature death and disability according to cancer site, sex, region, and income level by applying the GBD methodology to the situation in Korea. The cancer burden among Koreans has increased as a whole over the past decade. Further, the cancer burden due to death has decreased and the cancer burden due to disability has increased. Key findings from this study may help in understanding cancer patterns in Korea.
In 2008, the importance of preventing premature death was emphasized, as the YLL accounted for approximately 63% of the total DALY; since then, the YLD has steadily increased and YLL has decreased, resulting in a YLL:YLD ratio of 52:48 in 2018. This appears to reflect a situation in which advances in early detection, diagnosis, and treatment technologies for various cancers and improvements in cancer management have been effective in reducing the YLL. However, a reduction in the YLD rate due to primary prevention has not been adequately achieved, and as cancer survival rate is increasing, the overall cancer burden is still inevitably increasing. Continuous efforts are needed to reduce cancer mortality through early diagnosis, treatment, and prevention, with minimal sequelae. However, primary prevention efforts also need to be emphasized to reduce the cancer incidence through a reduction in cancer risk factors. In Korea, as interest and demand for specialized cancer treatment have increased, large cancer hospitals have been established and cancer treatments have diversified. Although treating cancer is naturally of importance, active investment in multidisciplinary research on the nature of cancer is essential. Furthermore, research focused on identifying cancer risk factors and understanding preventive effects should be actively pursued. It is necessary to develop cancer prevention practice guidelines that reflect such research results and strengthen publicity so that they can be put into practice in daily life. Above all else, there is a need for more specialized primary care services that can lead to overall lifestyle changes, such as appropriate physical activity and nutrition for cancer survivors and healthy people before the onset of cancer. The establishment and generalization of these primary medical services is very important for reducing the cancer incidence.
A decrease in the age-standardized mortality rate for many cancers in Korea over the past several decades can be observed from the main information annually published in the National Cancer Registry. Nevertheless, when examined by cancer site, the share of the YLL for pancreatic cancer, gallbladder and biliary tract cancer, brain and nervous system cancers, liver cancer, and TBL cancers was over 70%, suggesting that these cases reflect a poor prognosis after cancer diagnosis.
Regarding the cancer burden ranking results, the DALY rate was highest in the order of TBL cancers, stomach, colorectal, liver, and breast cancers, which was slightly different from the 2019 GBD order of lung, liver, stomach, colorectal, and pancreatic cancers [6]. This seems to be due to differences in methodologies. In the GBD study, the burden of disease was calculated through an estimation based on published papers and the numerical values extracted therefrom. Epidemiological indicators collected by the Institute for Health Metrics and Evaluation, which served as data input in the GBD study, may not be the most useful and up-to-date information at the national level. In addition, multiple assumptions and methodological choices, often compromises, are required to integrate different types of information. Most importantly, there is a difference in the DALY measurement perspective. In the GBD study, a prevalence-based approach was applied. In contrast, in the present study, disease burden was measured using epidemiological indicators extracted from NHIS claims data, with information on the actual medical use of Koreans. In addition, the KNBD study, which is the basis of the present study, adopted an incidence-based approach that is useful for cohort-based data [7].
TBL cancers in men and breast cancer in women were found to be major causes of the cancer burden, which is consistent with the ranking of cancer burden by sex published in the 2019 GBD study [6]. Furthermore, a research team from the Alberta Department of Health in Canada analyzed premenopausal and postmenopausal breast cancer cases from 44 populations in 41 countries, including Asia, Europe, and the United States, and found that Korean women had the highest average annual growth rate of breast cancer [15]. However, the breast cancer incidence rate is higher at a younger age in Korea than in Western countries. Contrary to the epidemiology of female breast cancer in the West, where the incidence rapidly increases in women in their 60s and 70s, the breast cancer incidence rate in Korean women is highest in women aged 45–50 years [16]. The reasons for this increase in breast cancer incidence in young women are presumed to be early menarche, decreased breastfeeding, obesity, late marriage, and low fertility [1719]. Although it is impossible to completely avoid situational factors with long-term exposure in women, such as the active entry of women into society and delays in marriage and childbirth, it is necessary to try to improve the prognosis by promoting self-examinations and managing individually controllable factors. On the other hand, TBL cancers have the highest cancer burden among all people and men, and the importance of management has been emphasized, as TBL cancers have ranked first in the country’s cancer mortality rate for the past 10 years. As can be seen from the results of the present study, with an YLL as high as 70%, TBL cancers are deadly, with a low survival rate. This is also supported by the 2018 National Cancer Registry statistics [20], which reported the 5-year relative survival rate of lung cancer as 32.4%, representing the second poorest prognosis, after gallbladder and other biliary tract and pancreatic cancers. The increased recognition of the need for early TBL cancer screening was reflected by its addition to the national health screening list in July 2019 [21]. The introduction and implementation of this TBL cancer screening program is expected to yield significantly improved survival rates.
The cancer burden trend over the past 10 years differed according to cancer site, and both the YLL and YLD decreased in laryngeal and cervical cancers. Laryngeal cancer, along with nasopharyngeal cancer, is a representative disease caused by smoking, and as the smoking rate of adults has continuously decreased over the last decade [22], it can be inferred that reductions in the burden of laryngeal and nasopharyngeal cancers are an effect of the reduction in the smoking rate. In addition, the incidence of cervical cancer has gradually decreased since the human papillomavirus vaccine was introduced in Korea in 2006 [23], and this effect may have reduced the burden of cervical cancer. In addition, cervical cancer screening is expected to further reduce the burden of cervical cancer through continuous efforts to improve screening rates, as this not only reduces mortality, but also lowers the incidence of cancer itself [24] by detecting factors of cancer.
The decreases in the DALY rate for stomach and liver cancers were confirmed to be due to decreases in the YLL. For stomach cancer, the National Cancer Screening Program seems to be effective in reducing the death rate. A study by Jun et al. [25] demonstrated that regular gastroscopy could reduce the risk of stomach cancer death by 81%. The effect of early screening for stomach cancer in reducing the risk of death was also reflected in the results of the present study. On the other hand, mortality rates in stomach and liver cancers are almost entirely attributable to modifiable risk factors [26]. Thus, the decreases in the DALY rate for stomach and liver cancers may be attributed to improvements in the smoking rate [22], which is a modifiable risk factor.
In contrast, in cancers for which the cause has not yet been clearly identified, such as prostate cancer, multiple myeloma, testicular cancer, other urinary organ cancers (including renal pelvic and ureteric orifice cancers), uterine cancer, and kidney cancer, the rate of increase in disease burden tended to exceed 50%. Although chemical substances and genetic factors have been mentioned as causes of these diseases, the causal relationship between these factors and disease onset has not been clearly identified. Therefore, research that can improve the understanding of the causes of these diseases, as well as the causes of this increase in disease burden, is needed.
Because NHIS claims data were used as the main data source in the present study, the health insurance premium variables and regional variables in the Qualification and Premium Database were used to identify differences in income level and regional cancer burden and its characteristics. According to the regional results, there were many regions with relatively low disease burden in Seoul and Gyeonggi-do, the metropolitan areas, which may reflect the differences in medical access and imbalances. Health disparities generally arise from a complex combination of socioeconomic, biological, behavioral, and structural barriers [27], with lower socioeconomic groups more likely to engage, and persist, in unhealthy behaviors [28]. In addition, these groups may have relatively fewer opportunities for early detection and timely treatment, and have a higher risk of serious comorbidities, than high socioeconomic groups [29].
As revealed by the GBD study [30], the cancer burden was high in the low-income group within the country, with a higher rate of increase over the past 10 years. In contrast, the burden of most cancers decreased as income level increased, with the exception of thyroid and prostate cancers, which had a higher disease burden in higher income groups. This is similar to the results of a previous study in which the screening prevalence, incidence rate, and postoperative complication rate of thyroid cancer were higher in the high-income group than in other groups [31]. Controversy over the overdiagnosis of thyroid cancer has been growing in Korea since around 2014, and the claim that overdiagnosis is the cause of the rapid increase in thyroid cancer, based on the research published by Ahn et al. [32], has spread throughout the world. Proponents of this claim have publicly pointed out problems with thyroid cancer screening and argued that the Korean government and medical community should refrain from overdiagnosis and take preventive measures. In other words, because thyroid cancer screening is an opportunistic health checkup, it may be affected by the financial ability of service users [31]. On the other hand, other studies indicate that the risk of developing prostate cancer is increased in high socioeconomic groups [33]. In Korea, as with thyroid cancer, it is presumed that this is the result of active participation by the high-income group in screening rather than an actual difference in cancer risk. However, since there are few studies that have identified a consistent cause in this regard, additional research is needed to determine the relationship between prostate cancer and income level. Finally, although the top five cancer types remained the same among all income groups, there were slight differences in the rankings. Thus, it is necessary to consider these results when setting cancer management priorities.
Combining the above results, there was a gap in the cancer burden according to sex, region, and income level. Additionally, there was a difference in the ranking of the cancer types accounting for the most cancer burden according to sex and income level. The findings from the present study can be used as a basis for establishing cancer management programs tailored to the characteristics of cancer burden by region or income level in the future. Most importantly, since the top five cancers (such as TBL and breast cancers) accounted for more than 50% of the cancer burden for both men and women, cancer management policies and health resource allocation that prioritize these cancers are required. In addition, it is necessary to identify rapidly increasing cancer types or specific issues by continuously monitoring the cancer burden, and efforts are needed to identify the causes and prepare countermeasures.
The present study has several limitations. Although the cancer burden was examined at various levels, its association with risk factors was not confirmed. It is necessary to quantify the attributable burden of risk factors such as smoking, drinking, and obesity, which are generally identified as being related to cancer. Because the frequency and level of exposure and the dangerousness of a risk factor may differ by age group, income level, etc., future studies should evaluate the attributable burden by various subgroups to provide useful evidence for cancer management. Another limitation is the uncertainty of the duration of each cancer. Although we used DisMod-II to estimate the duration of each cancer, it does not reflect differences in the duration of the disease according to the healthcare environment and the country’s level of development. In the future, it is necessary to develop and establish a methodology that can directly estimate the duration of each disease using real-world data, including information on actual medical use in Korea. Finally, although the NHIS claims data is useful for examining the overall distribution and long-term trend of the cancer burden, it does not reflect non-used medical services, unmet needs for medical services, and misdiagnoses because it only covers cases diagnosed at medical institutions.
Our findings on the cancer burden provide valuable and quantitative data for the prioritization and evaluation of prevention strategies and implementation of cancer policies with a focus on cancer prevention and early diagnosis. Estimating the difference in cancer burden according to region and income level within a country can help elucidate the nature of the cancer burden and scale of the problem. In addition, the results of this study provide clues to understand the patterns in cause of cancer. Such understanding helps generating new hypothesis about its pathogenesis. However, in the case of carcinoma, the cause of which remains unknown despite its large cancer burden, it is necessary to continuously conduct research to determine its etiology and lay the foundation for prevention.

Electronic Supplementary Material

Supplementary materials are available at Cancer Research and Treatment website (https://www.e-crt.org).

Notes

Ethical Statement

This study was approved by the Institutional Review Board (IRB) of Korea University (IRB No. KUIRB-2018-0024-01). Due to the study’s retrospective nature, informed consent was not required.

Author Contributions

Conceived and designed the analysis: Jung YS, Yoon SJ.

Collected the data: Jung YS, Yoon SJ.

Contributed data or analysis tools: Jung YS, Yoon SJ.

Performed the analysis: Jung YS, Yoon SJ.

Wrote the paper: Jung YS, Yoon SJ.

Conflicts of Interest

Conflict of interest relevant to this article was not reported.

Acknowledgments

This study was supported by a grant from the National R&D Program for Cancer Control, Ministry of Health and Welfare, Republic of Korea (grant number: HA21C0206). This study was administratively supported by the National Health Insurance Service of Korea (NHIS-2019-1-182).

Fig. 1
Trend of burden of cancer in Korea, from 2008 to 2018. DALY, disability-adjusted life year; YLD, year lived with disability; YLL, year of life lost.
crt-2022-126f1.jpg
Fig. 2
DALYs by cancer site in Korea, 2018. DALY, disability-adjusted life year; YLD, year lived with disability; YLL, year of life lost.
crt-2022-126f2.jpg
Fig. 3
Cancer rankings by DALYs in 2018 and percentage change from 2008 to 2018 (unit: DALY rate per 100,000 population). Cancers are ordered by rank in 2018 and are linked to their ranking in 2008. Color refers to the change in DALY rate from 2008 to 2018: red signifies an increase of more than 60%, gray signifies an increase of less than 60%, and blue signifies a decrease. DALY, disability-adjusted life year; YLD, year lived with disability; YLL, year of life lost. Rankings are by DALY rate.
crt-2022-126f3.jpg
Fig. 4
Cancer burden by region, 2018. (A) DALY rate per 100,000 population by region. (B) YLL rate per 100,000 population by region. (C) YLD rate per 100,000 population by region. DALY, disability-adjusted life year; YLD, year lived with disability; YLL, year of life lost.
crt-2022-126f4.jpg
Fig. 5
Difference in cancer burden according to income level, 2018. DALY, disability-adjusted life year.
crt-2022-126f5.jpg
Table 1
DALYs (unit: DALY rate per 100,000 population) by cancer site and sex in Korea, 2018
Rank Men Women
% of total DALY rates No. of DALYs DALY rate Cancer site Cancer site DALY rate No. of DALYs % of total DALY rates
1 17.7 121,300 482 TBL cancers Breast cancer 474 120,427 21.6
2 15.7 107,332 426 Liver cancer Colon and rectum cancers 226 57,548 10.3
3 14.0 96,022 381 Stomach cancer TBL cancers 218 55,505 9.9
4 12.1 82,668 328 Colon and rectum cancers Stomach cancer 198 50,214 9.0
5 6.7 46,031 183 Prostate cancer Thyroid cancer 162 41,072 7.4
6 4.8 32,548 129 Pancreatic cancer Liver cancer 129 32,692 5.9
7 3.5 23,781 94 Gallbladder and biliary tract cancer Pancreatic cancer 103 26,103 4.7
8 3.2 22,030 87 Leukemia Ovarian cancer 102 25,898 4.6
9 3.0 20,478 81 Bladder cancer Cervical cancer 90 22,926 4.1
10 2.8 19,106 76 Non-Hodgkin’s lymphoma Gallbladder and biliary tract cancer 81 20,662 3.7
11 2.5 17,085 68 Esophageal cancer Leukemia 64 16,301 2.9
12 2.4 16,251 65 Kidney cancer Brain and nervous system cancers 56 14,279 2.6
13 2.3 15,926 63 Brain and nervous system cancers Uterine cancer 55 13,939 2.5
14 1.7 11,741 47 Thyroid cancer Non-Hodgkin’s lymphoma 53 13,509 2.4
15 1.2 8,016 32 Multiple myeloma Kidney cancer 29 7,414 1.3
16 1.1 7,313 29 Mouth cancer Multiple myeloma 28 7,188 1.3
17 1.0 6,846 27 Bone and connective tissue cancer Bone and connective tissue cancer 20 5,148 0.9
18 0.9 6,029 24 Cancer of other part of pharynx and oropharynx Bladder cancer 20 5,065 0.9
19 0.7 4,945 20 Laryngeal cancer Mouth cancer 19 4,804 0.9
20 0.6 3,957 16 Other urinary organ cancers Non-melanoma skin cancer 14 3,447 0.6
21 0.5 3,417 14 Non-melanoma skin cancer Benign neoplasm of brain and other parts of central nervous system 13 3,304 0.6
22 0.4 2,808 11 Nasopharyngeal cancer Esophageal cancer 12 3,029 0.5
23 0.4 2,530 10 Malignant melanoma of the skin Malignant melanoma of the skin 10 2,478 0.4
24 0.3 2,329 9 Benign neoplasm of brain and other parts of central nervous system Other urinary organ cancers 8 2,053 0.4
25 0.3 1,713 7 Testicular cancer Cancer of other part of pharynx and oropharynx 4 1,049 0.2
26 0.2 1,610 6 Breast cancer Nasopharyngeal cancer 4 992 0.2
27 0.2 1,058 4 Hodgkin’s disease Hodgkin’s disease 3 645 0.1
28 0.0 - - Cervical cancer Laryngeal cancer 2 570 0.1
29 0.0 - - Uterine cancer Prostate cancer - - 0.0
30 0.0 - - Ovarian cancer Testicular cancer - - 0.0

DALY, disability-adjusted life year; TBL, trachea, bronchus, and lung.

References

1. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68:394–424.
crossref pmid pdf
2. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71:209–49.
crossref pmid pdf
3. Korea Central Cancer Registry, National Cancer Center. Annual report of cancer statistics in Korea in 2018. Sejong: Ministry of Health and Welfare; 2020.

4. Jung KW, Won YJ, Kong HJ, Lee ES. Cancer statistics in Korea: incidence, mortality, survival, and prevalence in 2016. Cancer Res Treat. 2019;51:417–30.
crossref pmid pmc pdf
5. Lin L, Li Z, Yan L, Liu Y, Yang H, Li H. Global, regional, and national cancer incidence and death for 29 cancer groups in 2019 and trends analysis of the global cancer burden, 1990–2019. J Hematol Oncol. 2021;14:197.
crossref pmid pmc pdf
6. GBD Diseases Injuries Collaborators. Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2020;396:1204–22.
pmid pmc
7. Jung YS, Kim YE, Park H, Oh IH, Jo MW, Ock M, et al. Measuring the burden of disease in Korea, 2008–2018. J Prev Med Public Health. 2021;54:293–300.
crossref pmid pmc pdf
8. Shin YS, Yoon SJ, Park HJ. The method for burden of disease: for evidence based health policy making. Seoul: Kyungmunsa; 2004.

9. Lee YR, Kim YA, Park SY, Oh CM, Kim YE, Oh IH. Application of a modified garbage code algorithm to estimate cause-specific mortality and years of life lost in Korea. J Korean Med Sci. 2016;31(Suppl 2):S121–8.
crossref pmid pmc pdf
10. Statistics Korea. Life tables [Internet]. Daejeon: Statistics Korea; 2022. [cited 2022 Feb 18]. Available from: http://kosis.kr/statHtml/statHtml.do?orgId=101&tblId=DT_1B42&conn_path=I3

11. Yang MS, Park M, Back JH, Lee GH, Shin JH, Kim K, et al. Validation of cancer diagnosis based on the National Health Insurance Service Database versus the National Cancer Registry Database in Korea. Cancer Res Treat. 2022;54:352–61.
crossref pmid pmc pdf
12. National Health Insurance Service. National Health Insurance statistical yearbook, 2020. Wonju: National Health Insurance Service; 2021.

13. National Health Insurance Sharing Service. Data provision guide [Internet]. Wonju: National Health Insurance Sharing Service; c2019. [cited 2022 Feb 18]. Available from: https://nhiss.nhis.or.kr/bd/ay/bdaya001iv.do

14. Kim YE, Jo MW, Park H, Oh IH, Yoon SJ, Pyo J, et al. Updating disability weights for measurement of healthy life expectancy and disability-adjusted life year in Korea. J Korean Med Sci. 2020;35:e219.
crossref pmid pmc pdf
15. Heer E, Harper A, Escandor N, Sung H, McCormack V, Fidler-Benaoudia MM. Global burden and trends in premenopausal and postmenopausal breast cancer: a population-based study. Lancet Glob Health. 2020;8:e1027–37.
crossref pmid
16. Kang SY, Kim YS, Kim Z, Kim HY, Kim HJ, Park S, et al. Breast cancer statistics in Korea in 2017: data from a breast cancer registry. J Breast Cancer. 2020;23:115–28.
crossref pmid pmc pdf
17. Norsa’adah B, Rusli BN, Imran AK, Naing I, Winn T. Risk factors of breast cancer in women in Kelantan, Malaysia. Singapore Med J. 2005;46:698–705.
pmid
18. Tolessa L, Sendo EG, Dinegde NG, Desalew A. Risk factors associated with breast cancer among women in Addis Ababa, Ethiopia: unmatched case-control study. Int J Womens Health. 2021;13:101–10.
crossref pmid pmc pdf
19. Ghiasvand R, Bahmanyar S, Zendehdel K, Tahmasebi S, Talei A, Adami HO, et al. Postmenopausal breast cancer in Iran: risk factors and their population attributable fractions. BMC Cancer. 2012;12:414.
crossref pmid pmc pdf
20. Hong S, Won YJ, Lee JJ, Jung KW, Kong HJ, Im JS, et al. Cancer statistics in Korea: incidence, mortality, survival, and prevalence in 2018. Cancer Res Treat. 2021;53:301–15.
crossref pmid pmc pdf
21. National Cancer Center. National Cancer Screening Program [Internet]. Goyang: National Cancer Center; 2022. [cited 2022 Feb 18]. Available from: https://www.ncc.re.kr/main.ncc?uri=eng-lish/sub04_ControlPrograms03

22. Ministry of Health and Welfare of Korea, Korea Disease Control and Prevention Agency. Korea health statistics 2020. Cheongju: Korea Disease Control and Prevention Agency; 2022.

23. Min KJ, Suh DH, Baba T, Chen X, Kim JW, Kobayashi Y, et al. Time for enhancing government-led primary prevention of cervical cancer. J Gynecol Oncol. 2021;32:e12.
crossref pmid pdf
24. Landy R, Pesola F, Castanon A, Sasieni P. Impact of cervical screening on cervical cancer mortality: estimation using stage-specific results from a nested case-control study. Br J Cancer. 2016;115:1140–6.
crossref pmid pmc pdf
25. Jun JK, Choi KS, Lee HY, Suh M, Park B, Song SH, et al. Effectiveness of the Korean National Cancer Screening Program in reducing gastric cancer mortality. Gastroenterology. 2017;152:1319–28.
crossref pmid
26. Hashim D, Boffetta P, La Vecchia C, Rota M, Bertuccio P, Malvezzi M, et al. The global decrease in cancer mortality: trends and disparities. Ann Oncol. 2016;27:926–33.
crossref pmid
27. Lortet-Tieulent J, Soerjomataram I, Lin CC, Coebergh JW, Jemal A. U.S. burden of cancer by race and ethnicity according to disability-adjusted life years. Am J Prev Med. 2016;51:673–81.
crossref pmid
28. Pampel FC, Krueger PM, Denney JT. Socioeconomic disparities in health behaviors. Annu Rev Sociol. 2010;36:349–70.
crossref pmid pmc
29. Louwman WJ, Aarts MJ, Houterman S, van Lenthe FJ, Coebergh JW, Janssen-Heijnen ML. A 50% higher prevalence of life-shortening chronic conditions among cancer patients with low socioeconomic status. Br J Cancer. 2010;103:1742–8.
crossref pmid pmc pdf
30. Institute for Health Metrics and Evaluation. Findings from the global burden of disease study 2017. Seattle, WA: Institute for Health Metrics and Evaluation; 2018.

31. Kang HY, Kim I, Kim YY, Bahk J, Khang YH. Income differences in screening, incidence, postoperative complications, and mortality of thyroid cancer in South Korea: a national population-based time trend study. BMC Cancer. 2020;20:1096.
crossref pmid pmc pdf
32. Ahn HS, Kim HJ, Welch HG. Korea’s thyroid-cancer “epidemic”: screening and overdiagnosis. N Engl J Med. 2014;371:1765–7.
crossref pmid
33. Cheng I, Witte JS, McClure LA, Shema SJ, Cockburn MG, John EM, et al. Socioeconomic status and prostate cancer incidence and mortality rates among the diverse population of California. Cancer Causes Control. 2009;20:1431–40.
crossref pmid pmc
TOOLS
PDF Links  PDF Links
PubReader  PubReader
ePub Link  ePub Link
XML Download  XML Download
Full text via DOI  Full text via DOI
Download Citation  Download Citation
Supplement  Supplement
  Print
Share:      
METRICS
3
Web of Science
3
Crossref
3
Scopus
2,933
View
161
Download
Related article
Editorial Office
Korean Cancer Association
Room 1824, Gwanghwamun Officia
92 Saemunan-ro, Jongno-gu, Seoul 03186, Korea
TEL: +82-2-3276-2410   FAX: +82-2-792-1410   E-mail: journal@cancer.or.kr
About |  Browse Articles |  Current Issue |  For Authors and Reviewers
Copyright © Korean Cancer Association.                 Developed in M2PI