Diabetes Research and Clinical Practice 106S2 (2014) S282–S287
Contents available at ScienceDirect
Diabetes Research and Clinical Practice journ al h ome pa ge : www .elsevier.co m/lo cate/diabres
Diabetes burden and prevention in Korea and the Western Pacific Region Nam H. Cho* Department of Preventive Medicine, Ajou University School of Medicine, Suwon, Korea
ARTICLE INFO
ABSTRACT
Keywords: Diabetes mellitus Diabetes burden Diabetes management Diabetes prevention
Diabetes burden in the Western Pacific Region (WPR) is more problematic than in any other part of the world. In 2013, the International Diabetes Federation reported > 382 million people are living with diabetes around the world. About 36%, approximately 138 million people with diabetes, are living in the WPR. In addition, in the WPR, from 2012 to 2013, 6 million diabetes mellitus cases were newly diagnosed, accounting for 54.5% of all type 2 diabetes mellitus (T2DM) cases diagnosed in the world during the same period. South Korea is no exception, and the prevalence of diabetes is estimated to be as high as 5 million people. The prevalence of T2DM in Korea increased from < 1% in 1960 to > 10% by early 2000. According to the Ansung–Ansan Cohort study, from 2001 to 2011, T2DM increased 54% and 60% in the 50th and 60th age groups, respectively. The main reason for the rapid increase in the prevalence of diabetes in Korea was the sudden growth in the economy, resulting in rapid urbanization. Moreover, scientific evidence suggests the dramatic increase in T2DM incidence and prevalence in Korea is related to the influence of economic development, health policy, urbanization, westernized diet, decreased physical activity, as well as an individual’s health behavior changes. However, diabetes management response rate was low in the newly onset groups with < 20%, but gradually increased up to around 90%, then declined to < 80% after 16–20 year of developing T2DM, showing an “M” management pattern. The study results revealed that despite the successful implementation of the universal health insurance system in Korea beginning in 1987, people diagnosed with T2DM were not properly managing T2DM. Most developing countries in the WPR are emulating the Korean experiences. There is clear evidence that utilization of BED (Behavioral change, Exercise, and proper Diet) could be the best vector to fight against the diabetes tsunami in the WPR. From the Korean experiences the WPR, at high risk for T2DM, could learn to prevent, intervene, and properly manage T2DM in order to reduce diabetes-related morbidity and mortality. © 2014 Elsevier Ireland Ltd. All rights reserved.
exception, and the prevalence of diabetes is estimated to
1. Introduction The burden of diabetes in the Western Pacific Region (WPR) is more problematic than in any other part of the world. In 2013, the International Diabetes Federation reported more than 382 million people are living with diabetes around the world [1]. About 36%, which is approximately 138 million people with diabetes, are living in the WPR [2]. Korea is no
be as high as 5 million people [3]. The prevalence of T2DM in Korea increased from less than 1% in 1960 to 6–9% by the end of the 1990s [4,5]. The rapid rise in the prevalence of diabetes in Korea and the WPR may be related to rapid urbanization which introduced a westernized diet. A decrease in physical activity and an increasing obese population may also be contributions [6].
* Corresponding author at: Department of Preventive Medicine, Ajou University School of Medicine, 206, World-cup-ro, Yeongtong-gu, Suwon, 443–749, Korea. E-mail address: Email: [email protected] (N.H. Cho). 0168-8227© 2014 Elsevier Ireland Ltd. All rights reserved.
N.H. Cho / Diabetes Research and Clinical Practice 106S2 (2014) S282–S287
The putative risk factors for T2DM in the Korean population include (but are not limited to) increasing age, urban living, female gender, obesity, smoking, family history of diabetes, impaired liver function, metabolic syndrome, elevated blood pressure, and increased triglycerides. All these risk factors are also revealed as the risk factors in countries located in the WPR.
2. Subjects and methods 2.1. Study population The design and methods used in the Ansung–Ansan Cohort Study have been described previously [7]. Briefly, it is an ongoing prospective, community-based, large cohort study, that investigates the trends in diabetes and associated risk factors. The baseline examinations were performed in 2001– 2002, and biennial follow-up examinations will continue through 2022. The eligibility criteria included an age of 40–69 years, residence within the borders of the survey area for at least six months before testing, and sufficient mental and physical capacity to participate. This study, the Korean Genome and Epidemiologic Study (KoGES), is based on two communities in South Korea: the Ansung cohort for a rural community (n = 5018) and the Ansan cohort for an urban community (n = 5020).
2.2. Anthropometric and laboratory measurements All participants responded to an interviewer-administered questionnaire and underwent a comprehensive physical examination. Socio-demographic characteristics included age, gender, occupation, education, marital status, and income. Lifestyle characteristics were also assessed; cigarette smoking and alcohol drinking status were categorized as never, former, and current. Levels of exercise were categorized as never, lightly (< 3 times/week, 30 minutes per session), or regular (3 times/week, 30 minutes per session) during the previous month. The presence of diseases including diabetes, hypertension, dyslipidemia, and cardiovascular disease were noted as well as medications prescribed to the patients. Diabetes was defined as per the American Diabetes Association (ADA) criteria using a 75 g oral glucose tolerance test (OGTT) and individual previous medical history [8]. For subjects without diabetes, glucose tolerance status was assessed as per the ADA criteria; impaired fasting glucose (IFG) only (5.6 FPG < 7.0 mmol/L and 2hPG < 7.8 mmol/L), impaired glucose tolerance (IGT) only (FPG < 5.6 mmol/L and 7.8 2hPG < 11.1 mmol/L), and IFG+IGT (5.6 FPG < 7.0 mmol/L and 7.8 2hPG < 11.1 mmol/L). Blood pressure was measured in a standardized manner with a mercury sphygmomanometer by a trained research assistant. Measurement of sitting blood pressure was taken after a 5 min period of rest. At least two blood pressure readings were recorded with a 30-second interval and the average value was used as a measure of systolic and diastolic blood pressure. Height and body weight were measured to the nearest 0.1 cm and 0.1 kg, respectively. Body Mass Index was calculated as weight in kilograms divided by height in meters squared. Waist circumference (WC) was measured at the midpoint between the lower rib margin and the iliac crest in the standing position. Blood was drawn for biochemical analysis
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after an overnight fast. Plasma glucose, serum triglycerides, HDL-cholesterol, and LDL-cholesterol levels were measured using an autoanalyzer (ADVIA1650; Siemens, NY, USA). Insulin was measured with an immunoradiometric assay kit (INSIRMA kit; Biosource, Nivelles, Belgium) using a gamma counter system (Packard, USA). Insulin resistance was estimated using the homeostasis model of assessment (HOMA-IR), calculated as fasting glucose (mmol/L) × fasting insulin (uU/mL)/22.5 [9]. All participants participated in the study voluntarily and informed consent was obtained in all cases. The study protocol was approved by the Ethics Committee of the Ajou University School of Medicine, and Korean Health and Genomic Study at the Korean National Institute of Health.
3. Results Of 5018 subjects in the Ansung cohort, 332 individuals (6.7%) were previously diagnosed with DM, 305 (6.1%) with unidentified DM, 899 (18.1%) with IGT, and 56 missing OGTT. In the Ansan cohort, 240 individuals (4.8%) were previously diagnosed with DM, 330 (6.6%) with unidentified DM, 1196 (24%) with IGT, and 35 missing OGTT. The prevalence of T2DM was higher in the rural area mainly due to the higher number of older participants; however, when age-stratified the prevalence was significantly higher in the urban cohort (Table 1). During the 10-year follow-up and 49,532 personyears at risk, 1,291 new T2DM cases were identified with an overall incidence rate of 26.0 per 1000 person-year. An upward trend of crude incidence density was shown in groups of urban residents, men and the aged. In the men of the rural area (Ansung), there were 20.5, 24.5 and 31.5 per 1,000 person-years each in their 40s, 50s and 60s respectively. By comparison, incidence densities of men in the urban area were 28.3, 42.3 and 55.9 per 1,000 person-years, respectively. The incident density of T2DM was lower in women than in men, but took on similar aspects: 13.8, 20.1 and 27.1 for rural women and 18.3, 33.4 and 52.9 per 1,000 person-years for urban women in their 40s, 50s and 60s, respectively. This study further revealed the age, gender, and residentspecific annual incidences of T2DM were 1.33%, 1.55%, 1.68%, and 2.35% in 40-year-old rural females, urban females, rural males, and urban males respectively. In the 50-year-old group, the rate increased to 1.48% in rural females, 1.65% in rural males, 2.3% in urban females, and 3.18% in urban males, and in the 60-year-old group, 1.85% in rural males, 2.05% in rural females, 4.1% in urban females, and 4.55% in urban males. In the 70-year-old group, the rate increased to 3.08% in rural females, 3.93% in rural males, 5% in urban females, and 5% in urban males. The incidence rates stratified by age and gender in rural subjects show a “J”-shaped pattern, but linear patterns were observed in urban subjects. Furthermore, in this cohort we observed a 54% increase of T2DM in the 50th , and 60% in 60th age groups within the 10-year period. A stepwise discriminative analysis was performed taking the outcome variables as the presence and absence of diabetes in subjects. Predictor variables were age, HbA1c , HOMA index of insulin resistance and b-cell function, total protein, WBC, metabolic syndrome, ALT, presence of familial history of diabetes, living area (urban), and smoking status (Table 2). Significant independent relationships were observed
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Table 1 Prevalence of T2DM by gender, place of residence, and age groups Age group
Gender
Rural cohort 40th Male Female Total
Total
DM status Normal
IGT
Unknown DM
Known DM
562 (81.1%) 679 (78.7%) 1241 (79.8%)
79 (11.4%) 137 (15.9%) 216 (13.9%)
30 (4.3%) 23 (2.7%) 53 (3.4%)
22 (3.2%) 24 (2.8%) 46 (3.0%)
693 (44.5%) 863 (55.5%) 1556 (100%)
50th
Male Female Total
453 (68.9%) 510 (64.7%) 963 (66.6%)
106 (16.1%) 172 (21.8%) 278 (19.2%)
50 (7.6%) 57 (7.2%) 107 (7.4%)
48 (7.3%) 49 (6.2%) 97 (6.7%)
657 (45.5%) 788 (54.5%) 1445 (100%)
60th
Male Female Total
550 (63.8%) 672 (61.1%) 1222 (62.3%)
170 (19.7%) 235 (21.4%) 405 (20.7%)
62 (7.2%) 83 (7.6%) 145 (7.4%)
80 (9.3%) 109 (9.9%) 189 (9.6%)
862 (44.0%) 1099 (56.0%) 1961 (100%)
Total
Male Female Total
1565 (70.8%) 1861 (67.7%) 3426 (69.0%)
355 (16.0%) 544 (19.8%) 899 (18.1%)
142 (6.4%) 163 (5.9%) 305 (6.1%)
150 (6.8%) 182 (6.6%) 332 (6.7%)
2212 (44.6%) 2750 (55.4%) 4962 (100%)
Urban cohort 40th Male Female Total
1191 (72.3%) 1048 (70.5%) 2239 (71.5%)
291 (17.7%) 361 (24.3%) 652 (20.8%)
115 (7.0%) 51 (3.4%) 166 (5.3%)
50 (3.0%) 26 (1.7%) 76 (2.4%)
1647 (52.6%) 1486 (47.4%) 3133 (100%)
50th
Male Female Total
332 (58.9%) 338 (58.4%) 670 (58.6%)
139 (24.6%) 178 (30.7%) 317 (27.7%)
41 (7.3%) 32 (5.5%) 73 (6.4%)
52 (9.2%) 31 (5.4%) 83 (7.3%)
564 (49.3%) 579 (50.7%) 1143 (100%)
60th
Male Female Total
138 (47.6%) 172 (41.1%) 310 (43.7%)
80 (27.6%) 147 (35.1%) 227 (32.0%)
26 (9.0%) 65 (15.5%) 91 (12.8%)
46 (15.9%) 35 (8.4%) 81 (11.4%)
290 (40.9%) 419 (59.1%) 709 (100%)
Total
Male Female Total
1661 (66.4%) 1558 (62.7%) 3219 (64.6%)
510 (20.4%) 686 (27.6%) 1196 (24.0%)
182 (7.3%) 148 (6.0%) 330 (6.6%)
148 (5.9%) 92 (3.7%) 240 (4.8%)
2501 (50.2%) 2484 (49.8%) 4985 (100%)
Table 2 Cox proportional hazard analysis for T2DM Variable
b
p-value
ALT Age b-cell function HOMA-IR Total protein WBC Normal IFG IGT IFG+IGT MetS Family history of DM City dweller HbA1c 5.6% Non-smoker Ex-smoker Current smoker
0.005 0.023 −0.002 0.096 −0.083 0.047
< 0.001 < 0.001 < 0.001 0.005 < 0.001 0.003
1.042 1.316 1.734 0.433 0.368 0.455 0.892
< 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001
0.211 0.413
0.007 < 0.001
RR (95% CI)
1 2.84 (2.15–3.73) 3.73 (3.28–4.24) 5.66 (4.55–7.04) 1.54 (1.36–1.75) 1.44 (1.23–1.70) 1.58 (1.39–1.79) 2.44 (2.16–2.75) 1 1.23 (1.06–1.44) 1.51 (1.31–1.74)
ALT, Alanine transaminase; IFG, Impaired fasting glucose; IGT, Impaired glucose tolerance; MetS, Metabolic syndrome; WBC, White blood cell.
N.H. Cho / Diabetes Research and Clinical Practice 106S2 (2014) S282–S287
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100 80
%
60 40 20 0
New
20 yrs
Duration of Diabetes Fig. 1 – The pattern of T2DM management in Korea. Solid line indicates mean value, dotted line indicates female, dashed–dotted line indicates male.
Fig. 2 – Trend of T2DM in Korea, economy vs. prevalence. Dotted line indicates the prevalence of type 2 diabetes mellitus, solid line indicates gross national income (GNI). for all the predictors on the dependent variables (all p < 0.01). However, diabetes management response rate was low in the newly onset groups with less than 20%, but gradually increased up to around 90%, then declined to less than 80% after 16–20 years of developing T2DM, showing an “M” management pattern (Fig. 1). The study results from Korea revealed that the T2DM management pattern is inappropriate; the pattern should be an inverse “L” pattern. In other words, the rate should gradually increase from the time of T2DM diagnosis and stay at a high level. However, the rate was observed to decline around 16–20 years after disease onset, then to increase upon diagnosis of diabetes complications,
then to decline again about 5 years after diagnosis of complications. As shown in Fig. 2, Korea has experienced both a steady economic growth and an increasing prevalence of diabetes. In the early 1970s, epidemiologic studies from Korea reported a T2DM prevalence of less than 2%; however, a log linear increase in prevalence was observed starting in 1987. This is an unusual pattern, as one would expect a gradual linear increase if the prevalence is related to risk exposure. The Korean government implemented a universal health insurance system in 1987 and the prevalence of diabetes clearly reflects a “seeking of disease” concept. This hypothesis is further supported by
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the fact that the Korean gross national income is curtailing the prevalence pattern of diabetes (Fig. 2). Diabetes awareness campaigns, individuals’ health-care attitudes and interests, screening programs, and national health-care coverage all relate to the higher prevalence of diagnosed diabetes and contribute to the logarithmic prevalence pattern. The most recent study from the National Health Insurance Corporation and the Bureau of National Statistics indicated a total of 2 million people with diabetes in Korea [10]. However, this report did not include asymptomatic cases, which are present in about the same amount as known cases. If we include asymptomatic cases, as well as impaired glucose tolerance cases, we would estimate somewhere around 4–5 million people have T2DM or are at high risk for T2DM in Korea [11].
4. Discussion Korea has experienced a dramatic increase in the prevalence of diabetes since the early 1990s; however, the rapid increase in the prevalence of this chronic disease could be the result of various artifacts, rather than being the consequence of risk factors. The artifacts responsible for dramatic changes of the prevalence and incidence of the chronic disease in Korea include: 1. Changes in diagnostic methods and criteria. 2. Changes in national health policy and the health insurance system. 3. Promotion of disease awareness. However, it is almost impossible for exposure to key risk factors in a large population to result in such a dramatic increase of patterns in chronic diseases. For example, chronic diseases, such as diabetes, are the consequence of exposure to multiple risk factors over a long period of time. In other words, exposure to multiple risk factors from environment, lifestyle, and habitual factors result in the progression of a disease at different rates among individuals and in a gradual pattern. Therefore, the onset of diabetes occurs based on the individual’s susceptibility, immunity, and exposure amount, as well as on the duration of the risk factors and incubation period. Thus, the dramatic change in the patterns of incidence and prevalence of diabetes are related to economic changes of individual nations, as well as an individuals’ health behavior. This ongoing community-based prospective cohort study in the residents of two Korean communities – Ansung , and Ansan – revealed the putative risk factors identified in Korean studies are very similar to the risk factors identified from other countries, including genetic backgrounds [12–14]. The high incidence and prevalence of T2DM in Korea is related to economic development, which has a direct influence on health policy as well as an individuals’ health behavior and which is associated with a high rate of T2DM [15]. Therefore, we expect to observe the current diabetes rates until key risk factors incubate long enough in our society. At which point we would expect to start observing a more gradual increase in both the incidence and prevalence of T2DM in Korea. Thus, the best approach to the battle against T2DM in Korea is to identify the hidden cases by early screening through primary prevention and education. Furthermore, in this study, we also investigated the putative risk factors that are associated with the quality of life (QoL).
First, the duration of diabetes was negatively associated with quality of life, specifically physical and psychological items. Second, the HbA1c was also significantly associated with physical and psychological items. This study clearly revealed that improving the QoL in diabetes patients is closely associated with the blood glucose control and which could be done by adopting a tailored care program for individual patients. Environmental and genetic factors very likely contribute to some degree to the high rate of diabetes in Korea. Although genetic factors are independently associated with the onset of T2DM, the strength of this association is less than that of the environmental risk factors that have been reported [16,17]. Similar to the findings from the Korean study, many countries in the WPR follow the diabetes pattern of Korea such as rapid socio-economic changes and modernization, a high rate of metabolic syndrome, adoption of a westernized life style, high rates of smoking (the prevalence of smoking in the WPR is among the highest in the world), increases of child obesity, an increasing older population, sarcopenia obesity, and high rates of gestational diabetes mellitus in the Asian population. Thus, a better understanding of the risk factors from Korea could also lead to a better understanding of T2DM in the WPR, as well as a possible and successful prevention of the disease. In conclusion, T2DM is one of the fastest growing noncommunicable diseases in both Korea and the WPR. The prevalence and incidence of T2DM are at an epidemic stage in both Korea and the WPR, mainly due to economic growth. Most of the developing countries in the WPR are emulating Korean experiences. There is clear evidence that utilization of BED (Behavioral change, Exercise, and proper Diet) could be the best vector to fight the diabetes tsunami in the WPR. From Korean experiences, the WPR, at high risk for T2DM, could learn to prevent, intervene, and properly manage T2DM in order to reduce diabetes-related morbidity and mortality.
Conflicts of interest The author declares that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.
References 1. Linnenkamp U, Guariguata L, Beagley J, Whiting DR, Cho NH. The IDF Diabetes Atlas methodology for estimating global prevalence of hyperglycaemia in pregnancy. Diabetes Res Clin Pract 2014;103:186–96. 2. Chan JC, Cho NH, Tajima N, Shaw J. Diabetes in the Western Pacific Region – past, present and future. Diabetes Res Clin Pract 2014;103:244–55. 3. Kwon HS, Kim KW, Kim DJ, Kim SR, Min KW, Park KS, et al. Diabetes mellitus epidemiologic study in Kyunggi province 2003. Diabetes Metab J 2005;29:97–102. 4. Park Y, Lee H, Koh CS, Min H, Yoo K, Kim Y, et al. Prevalence of diabetes and IGF in Yonchon County, South Korea. Diabetes Care 1995;18:545–8. 5. Kim YI, Choi CS, Kim SW, Lee JS, Kim HH, Lee MS, et al. Prevalence of diabetes mellitus and impaired glucose
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tolerance in Korean adults living in the Jungup district, South Korea. J Kor Diabetes 1998;22:36–71. Cho NH. Longitudinal epidemiology study of diabetes mellitus: community cohort based genome project. Seoul: Korean Diabetes Association; 2004. Choi SH, Kim TH, Lim S, Park KS, Jang HC, Cho NH. Hemoglobin A1c as a diagnostic tool for diabetes screening and new-onset diabetes prediction: a 6-year communitybased prospective study. Diabetes Care 2011;34:944–9. Genuth S, Alberti KG, Bennett P, Buse J, Defronzo R, Kahn R, et al. Follow-up report on the diagnosis of diabetes mellitus. Diabetes Care 2003;26:3160–7. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985;28:412–9. 2001 Annals of health insurance statistics on National Health Insurance Corporation. National Health Insurance Corporation, Seoul, 2002. Kang SK, Kim KW, Cho NH, Hur CW, Kim HK, Choi RY, et al. Nationwide Diabetes Epidemiology Study. Korean Diabetes Association Monograph; 2003.
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12. Wannamethee SG, Shaper AG, Perry IJ; British Regional Heart Study. Smoking as a modifiable risk factor for type 2 diabetes in middle-aged men. Diabetes Care 2001; 24:1590–5. 13. Rimm EB, Chan J, Stampfer MJ, Colditz GA, Willett WC. Prospective study of cigarette smoking, alcohol use, and the risk of diabetes in men. BMJ 1995;310:555–9. 14. Ng MC, Park KS, Oh B, Tam CH, Cho YM, Shin HD, et al. Diabetes. Implication of genetic variants near TCF7L2, SLC30A8, HHEX, CDKAL1, CDKN2A/B, IGF2BP2, and FTO in type 2 diabetes and obesity in 6,719 Asians. Diabetes 2008;57:2226–33. 15. Cho NH. The epidemiology of diabetes in Korea: from the economics to genetics. Korean Diabetes J 2010;34:10–5. 16. Sladek R, Rocheleau G, Rung J, Dina C, Shen L, Serre D, et al. A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature 2007;445:881–5. 17. Cho YS, Chen CH, Hu C, Long J, Ong RT, Sim X, et al. Metaanalysis of genome-wide association studies identifies eight new loci for type 2 diabetes in east Asians. Nat Genet 2011;44:67–72.
Contents available at ScienceDirect
Diabetes Research and Clinical Practice journ al h ome pa ge : www .elsevier.co m/lo cate/diabres
Diabetes burden and prevention in Korea and the Western Pacific Region Nam H. Cho* Department of Preventive Medicine, Ajou University School of Medicine, Suwon, Korea
ARTICLE INFO
ABSTRACT
Keywords: Diabetes mellitus Diabetes burden Diabetes management Diabetes prevention
Diabetes burden in the Western Pacific Region (WPR) is more problematic than in any other part of the world. In 2013, the International Diabetes Federation reported > 382 million people are living with diabetes around the world. About 36%, approximately 138 million people with diabetes, are living in the WPR. In addition, in the WPR, from 2012 to 2013, 6 million diabetes mellitus cases were newly diagnosed, accounting for 54.5% of all type 2 diabetes mellitus (T2DM) cases diagnosed in the world during the same period. South Korea is no exception, and the prevalence of diabetes is estimated to be as high as 5 million people. The prevalence of T2DM in Korea increased from < 1% in 1960 to > 10% by early 2000. According to the Ansung–Ansan Cohort study, from 2001 to 2011, T2DM increased 54% and 60% in the 50th and 60th age groups, respectively. The main reason for the rapid increase in the prevalence of diabetes in Korea was the sudden growth in the economy, resulting in rapid urbanization. Moreover, scientific evidence suggests the dramatic increase in T2DM incidence and prevalence in Korea is related to the influence of economic development, health policy, urbanization, westernized diet, decreased physical activity, as well as an individual’s health behavior changes. However, diabetes management response rate was low in the newly onset groups with < 20%, but gradually increased up to around 90%, then declined to < 80% after 16–20 year of developing T2DM, showing an “M” management pattern. The study results revealed that despite the successful implementation of the universal health insurance system in Korea beginning in 1987, people diagnosed with T2DM were not properly managing T2DM. Most developing countries in the WPR are emulating the Korean experiences. There is clear evidence that utilization of BED (Behavioral change, Exercise, and proper Diet) could be the best vector to fight against the diabetes tsunami in the WPR. From the Korean experiences the WPR, at high risk for T2DM, could learn to prevent, intervene, and properly manage T2DM in order to reduce diabetes-related morbidity and mortality. © 2014 Elsevier Ireland Ltd. All rights reserved.
exception, and the prevalence of diabetes is estimated to
1. Introduction The burden of diabetes in the Western Pacific Region (WPR) is more problematic than in any other part of the world. In 2013, the International Diabetes Federation reported more than 382 million people are living with diabetes around the world [1]. About 36%, which is approximately 138 million people with diabetes, are living in the WPR [2]. Korea is no
be as high as 5 million people [3]. The prevalence of T2DM in Korea increased from less than 1% in 1960 to 6–9% by the end of the 1990s [4,5]. The rapid rise in the prevalence of diabetes in Korea and the WPR may be related to rapid urbanization which introduced a westernized diet. A decrease in physical activity and an increasing obese population may also be contributions [6].
* Corresponding author at: Department of Preventive Medicine, Ajou University School of Medicine, 206, World-cup-ro, Yeongtong-gu, Suwon, 443–749, Korea. E-mail address: Email: [email protected] (N.H. Cho). 0168-8227© 2014 Elsevier Ireland Ltd. All rights reserved.
N.H. Cho / Diabetes Research and Clinical Practice 106S2 (2014) S282–S287
The putative risk factors for T2DM in the Korean population include (but are not limited to) increasing age, urban living, female gender, obesity, smoking, family history of diabetes, impaired liver function, metabolic syndrome, elevated blood pressure, and increased triglycerides. All these risk factors are also revealed as the risk factors in countries located in the WPR.
2. Subjects and methods 2.1. Study population The design and methods used in the Ansung–Ansan Cohort Study have been described previously [7]. Briefly, it is an ongoing prospective, community-based, large cohort study, that investigates the trends in diabetes and associated risk factors. The baseline examinations were performed in 2001– 2002, and biennial follow-up examinations will continue through 2022. The eligibility criteria included an age of 40–69 years, residence within the borders of the survey area for at least six months before testing, and sufficient mental and physical capacity to participate. This study, the Korean Genome and Epidemiologic Study (KoGES), is based on two communities in South Korea: the Ansung cohort for a rural community (n = 5018) and the Ansan cohort for an urban community (n = 5020).
2.2. Anthropometric and laboratory measurements All participants responded to an interviewer-administered questionnaire and underwent a comprehensive physical examination. Socio-demographic characteristics included age, gender, occupation, education, marital status, and income. Lifestyle characteristics were also assessed; cigarette smoking and alcohol drinking status were categorized as never, former, and current. Levels of exercise were categorized as never, lightly (< 3 times/week, 30 minutes per session), or regular (3 times/week, 30 minutes per session) during the previous month. The presence of diseases including diabetes, hypertension, dyslipidemia, and cardiovascular disease were noted as well as medications prescribed to the patients. Diabetes was defined as per the American Diabetes Association (ADA) criteria using a 75 g oral glucose tolerance test (OGTT) and individual previous medical history [8]. For subjects without diabetes, glucose tolerance status was assessed as per the ADA criteria; impaired fasting glucose (IFG) only (5.6 FPG < 7.0 mmol/L and 2hPG < 7.8 mmol/L), impaired glucose tolerance (IGT) only (FPG < 5.6 mmol/L and 7.8 2hPG < 11.1 mmol/L), and IFG+IGT (5.6 FPG < 7.0 mmol/L and 7.8 2hPG < 11.1 mmol/L). Blood pressure was measured in a standardized manner with a mercury sphygmomanometer by a trained research assistant. Measurement of sitting blood pressure was taken after a 5 min period of rest. At least two blood pressure readings were recorded with a 30-second interval and the average value was used as a measure of systolic and diastolic blood pressure. Height and body weight were measured to the nearest 0.1 cm and 0.1 kg, respectively. Body Mass Index was calculated as weight in kilograms divided by height in meters squared. Waist circumference (WC) was measured at the midpoint between the lower rib margin and the iliac crest in the standing position. Blood was drawn for biochemical analysis
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after an overnight fast. Plasma glucose, serum triglycerides, HDL-cholesterol, and LDL-cholesterol levels were measured using an autoanalyzer (ADVIA1650; Siemens, NY, USA). Insulin was measured with an immunoradiometric assay kit (INSIRMA kit; Biosource, Nivelles, Belgium) using a gamma counter system (Packard, USA). Insulin resistance was estimated using the homeostasis model of assessment (HOMA-IR), calculated as fasting glucose (mmol/L) × fasting insulin (uU/mL)/22.5 [9]. All participants participated in the study voluntarily and informed consent was obtained in all cases. The study protocol was approved by the Ethics Committee of the Ajou University School of Medicine, and Korean Health and Genomic Study at the Korean National Institute of Health.
3. Results Of 5018 subjects in the Ansung cohort, 332 individuals (6.7%) were previously diagnosed with DM, 305 (6.1%) with unidentified DM, 899 (18.1%) with IGT, and 56 missing OGTT. In the Ansan cohort, 240 individuals (4.8%) were previously diagnosed with DM, 330 (6.6%) with unidentified DM, 1196 (24%) with IGT, and 35 missing OGTT. The prevalence of T2DM was higher in the rural area mainly due to the higher number of older participants; however, when age-stratified the prevalence was significantly higher in the urban cohort (Table 1). During the 10-year follow-up and 49,532 personyears at risk, 1,291 new T2DM cases were identified with an overall incidence rate of 26.0 per 1000 person-year. An upward trend of crude incidence density was shown in groups of urban residents, men and the aged. In the men of the rural area (Ansung), there were 20.5, 24.5 and 31.5 per 1,000 person-years each in their 40s, 50s and 60s respectively. By comparison, incidence densities of men in the urban area were 28.3, 42.3 and 55.9 per 1,000 person-years, respectively. The incident density of T2DM was lower in women than in men, but took on similar aspects: 13.8, 20.1 and 27.1 for rural women and 18.3, 33.4 and 52.9 per 1,000 person-years for urban women in their 40s, 50s and 60s, respectively. This study further revealed the age, gender, and residentspecific annual incidences of T2DM were 1.33%, 1.55%, 1.68%, and 2.35% in 40-year-old rural females, urban females, rural males, and urban males respectively. In the 50-year-old group, the rate increased to 1.48% in rural females, 1.65% in rural males, 2.3% in urban females, and 3.18% in urban males, and in the 60-year-old group, 1.85% in rural males, 2.05% in rural females, 4.1% in urban females, and 4.55% in urban males. In the 70-year-old group, the rate increased to 3.08% in rural females, 3.93% in rural males, 5% in urban females, and 5% in urban males. The incidence rates stratified by age and gender in rural subjects show a “J”-shaped pattern, but linear patterns were observed in urban subjects. Furthermore, in this cohort we observed a 54% increase of T2DM in the 50th , and 60% in 60th age groups within the 10-year period. A stepwise discriminative analysis was performed taking the outcome variables as the presence and absence of diabetes in subjects. Predictor variables were age, HbA1c , HOMA index of insulin resistance and b-cell function, total protein, WBC, metabolic syndrome, ALT, presence of familial history of diabetes, living area (urban), and smoking status (Table 2). Significant independent relationships were observed
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Table 1 Prevalence of T2DM by gender, place of residence, and age groups Age group
Gender
Rural cohort 40th Male Female Total
Total
DM status Normal
IGT
Unknown DM
Known DM
562 (81.1%) 679 (78.7%) 1241 (79.8%)
79 (11.4%) 137 (15.9%) 216 (13.9%)
30 (4.3%) 23 (2.7%) 53 (3.4%)
22 (3.2%) 24 (2.8%) 46 (3.0%)
693 (44.5%) 863 (55.5%) 1556 (100%)
50th
Male Female Total
453 (68.9%) 510 (64.7%) 963 (66.6%)
106 (16.1%) 172 (21.8%) 278 (19.2%)
50 (7.6%) 57 (7.2%) 107 (7.4%)
48 (7.3%) 49 (6.2%) 97 (6.7%)
657 (45.5%) 788 (54.5%) 1445 (100%)
60th
Male Female Total
550 (63.8%) 672 (61.1%) 1222 (62.3%)
170 (19.7%) 235 (21.4%) 405 (20.7%)
62 (7.2%) 83 (7.6%) 145 (7.4%)
80 (9.3%) 109 (9.9%) 189 (9.6%)
862 (44.0%) 1099 (56.0%) 1961 (100%)
Total
Male Female Total
1565 (70.8%) 1861 (67.7%) 3426 (69.0%)
355 (16.0%) 544 (19.8%) 899 (18.1%)
142 (6.4%) 163 (5.9%) 305 (6.1%)
150 (6.8%) 182 (6.6%) 332 (6.7%)
2212 (44.6%) 2750 (55.4%) 4962 (100%)
Urban cohort 40th Male Female Total
1191 (72.3%) 1048 (70.5%) 2239 (71.5%)
291 (17.7%) 361 (24.3%) 652 (20.8%)
115 (7.0%) 51 (3.4%) 166 (5.3%)
50 (3.0%) 26 (1.7%) 76 (2.4%)
1647 (52.6%) 1486 (47.4%) 3133 (100%)
50th
Male Female Total
332 (58.9%) 338 (58.4%) 670 (58.6%)
139 (24.6%) 178 (30.7%) 317 (27.7%)
41 (7.3%) 32 (5.5%) 73 (6.4%)
52 (9.2%) 31 (5.4%) 83 (7.3%)
564 (49.3%) 579 (50.7%) 1143 (100%)
60th
Male Female Total
138 (47.6%) 172 (41.1%) 310 (43.7%)
80 (27.6%) 147 (35.1%) 227 (32.0%)
26 (9.0%) 65 (15.5%) 91 (12.8%)
46 (15.9%) 35 (8.4%) 81 (11.4%)
290 (40.9%) 419 (59.1%) 709 (100%)
Total
Male Female Total
1661 (66.4%) 1558 (62.7%) 3219 (64.6%)
510 (20.4%) 686 (27.6%) 1196 (24.0%)
182 (7.3%) 148 (6.0%) 330 (6.6%)
148 (5.9%) 92 (3.7%) 240 (4.8%)
2501 (50.2%) 2484 (49.8%) 4985 (100%)
Table 2 Cox proportional hazard analysis for T2DM Variable
b
p-value
ALT Age b-cell function HOMA-IR Total protein WBC Normal IFG IGT IFG+IGT MetS Family history of DM City dweller HbA1c 5.6% Non-smoker Ex-smoker Current smoker
0.005 0.023 −0.002 0.096 −0.083 0.047
< 0.001 < 0.001 < 0.001 0.005 < 0.001 0.003
1.042 1.316 1.734 0.433 0.368 0.455 0.892
< 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001
0.211 0.413
0.007 < 0.001
RR (95% CI)
1 2.84 (2.15–3.73) 3.73 (3.28–4.24) 5.66 (4.55–7.04) 1.54 (1.36–1.75) 1.44 (1.23–1.70) 1.58 (1.39–1.79) 2.44 (2.16–2.75) 1 1.23 (1.06–1.44) 1.51 (1.31–1.74)
ALT, Alanine transaminase; IFG, Impaired fasting glucose; IGT, Impaired glucose tolerance; MetS, Metabolic syndrome; WBC, White blood cell.
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100 80
%
60 40 20 0
New
20 yrs
Duration of Diabetes Fig. 1 – The pattern of T2DM management in Korea. Solid line indicates mean value, dotted line indicates female, dashed–dotted line indicates male.
Fig. 2 – Trend of T2DM in Korea, economy vs. prevalence. Dotted line indicates the prevalence of type 2 diabetes mellitus, solid line indicates gross national income (GNI). for all the predictors on the dependent variables (all p < 0.01). However, diabetes management response rate was low in the newly onset groups with less than 20%, but gradually increased up to around 90%, then declined to less than 80% after 16–20 years of developing T2DM, showing an “M” management pattern (Fig. 1). The study results from Korea revealed that the T2DM management pattern is inappropriate; the pattern should be an inverse “L” pattern. In other words, the rate should gradually increase from the time of T2DM diagnosis and stay at a high level. However, the rate was observed to decline around 16–20 years after disease onset, then to increase upon diagnosis of diabetes complications,
then to decline again about 5 years after diagnosis of complications. As shown in Fig. 2, Korea has experienced both a steady economic growth and an increasing prevalence of diabetes. In the early 1970s, epidemiologic studies from Korea reported a T2DM prevalence of less than 2%; however, a log linear increase in prevalence was observed starting in 1987. This is an unusual pattern, as one would expect a gradual linear increase if the prevalence is related to risk exposure. The Korean government implemented a universal health insurance system in 1987 and the prevalence of diabetes clearly reflects a “seeking of disease” concept. This hypothesis is further supported by
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the fact that the Korean gross national income is curtailing the prevalence pattern of diabetes (Fig. 2). Diabetes awareness campaigns, individuals’ health-care attitudes and interests, screening programs, and national health-care coverage all relate to the higher prevalence of diagnosed diabetes and contribute to the logarithmic prevalence pattern. The most recent study from the National Health Insurance Corporation and the Bureau of National Statistics indicated a total of 2 million people with diabetes in Korea [10]. However, this report did not include asymptomatic cases, which are present in about the same amount as known cases. If we include asymptomatic cases, as well as impaired glucose tolerance cases, we would estimate somewhere around 4–5 million people have T2DM or are at high risk for T2DM in Korea [11].
4. Discussion Korea has experienced a dramatic increase in the prevalence of diabetes since the early 1990s; however, the rapid increase in the prevalence of this chronic disease could be the result of various artifacts, rather than being the consequence of risk factors. The artifacts responsible for dramatic changes of the prevalence and incidence of the chronic disease in Korea include: 1. Changes in diagnostic methods and criteria. 2. Changes in national health policy and the health insurance system. 3. Promotion of disease awareness. However, it is almost impossible for exposure to key risk factors in a large population to result in such a dramatic increase of patterns in chronic diseases. For example, chronic diseases, such as diabetes, are the consequence of exposure to multiple risk factors over a long period of time. In other words, exposure to multiple risk factors from environment, lifestyle, and habitual factors result in the progression of a disease at different rates among individuals and in a gradual pattern. Therefore, the onset of diabetes occurs based on the individual’s susceptibility, immunity, and exposure amount, as well as on the duration of the risk factors and incubation period. Thus, the dramatic change in the patterns of incidence and prevalence of diabetes are related to economic changes of individual nations, as well as an individuals’ health behavior. This ongoing community-based prospective cohort study in the residents of two Korean communities – Ansung , and Ansan – revealed the putative risk factors identified in Korean studies are very similar to the risk factors identified from other countries, including genetic backgrounds [12–14]. The high incidence and prevalence of T2DM in Korea is related to economic development, which has a direct influence on health policy as well as an individuals’ health behavior and which is associated with a high rate of T2DM [15]. Therefore, we expect to observe the current diabetes rates until key risk factors incubate long enough in our society. At which point we would expect to start observing a more gradual increase in both the incidence and prevalence of T2DM in Korea. Thus, the best approach to the battle against T2DM in Korea is to identify the hidden cases by early screening through primary prevention and education. Furthermore, in this study, we also investigated the putative risk factors that are associated with the quality of life (QoL).
First, the duration of diabetes was negatively associated with quality of life, specifically physical and psychological items. Second, the HbA1c was also significantly associated with physical and psychological items. This study clearly revealed that improving the QoL in diabetes patients is closely associated with the blood glucose control and which could be done by adopting a tailored care program for individual patients. Environmental and genetic factors very likely contribute to some degree to the high rate of diabetes in Korea. Although genetic factors are independently associated with the onset of T2DM, the strength of this association is less than that of the environmental risk factors that have been reported [16,17]. Similar to the findings from the Korean study, many countries in the WPR follow the diabetes pattern of Korea such as rapid socio-economic changes and modernization, a high rate of metabolic syndrome, adoption of a westernized life style, high rates of smoking (the prevalence of smoking in the WPR is among the highest in the world), increases of child obesity, an increasing older population, sarcopenia obesity, and high rates of gestational diabetes mellitus in the Asian population. Thus, a better understanding of the risk factors from Korea could also lead to a better understanding of T2DM in the WPR, as well as a possible and successful prevention of the disease. In conclusion, T2DM is one of the fastest growing noncommunicable diseases in both Korea and the WPR. The prevalence and incidence of T2DM are at an epidemic stage in both Korea and the WPR, mainly due to economic growth. Most of the developing countries in the WPR are emulating Korean experiences. There is clear evidence that utilization of BED (Behavioral change, Exercise, and proper Diet) could be the best vector to fight the diabetes tsunami in the WPR. From Korean experiences, the WPR, at high risk for T2DM, could learn to prevent, intervene, and properly manage T2DM in order to reduce diabetes-related morbidity and mortality.
Conflicts of interest The author declares that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.
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