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Journal of Epidemiology logoLink to Journal of Epidemiology
. 2017 Jun 13;27(12):568–573. doi: 10.1016/j.je.2016.12.019

The prevalence and risk factor control associated with noncommunicable diseases in China, Japan, and Korea

Defu Ma a, Hiromichi Sakai b, Chihiro Wakabayashi b, Jong-Sook Kwon c, Yoonna Lee c, Shuo Liu d, Qiaoqin Wan e, Kumiko Sasao b, Kanade Ito b, Ken Nishihara b, Peiyu Wang a,
PMCID: PMC5623033  PMID: 28623056

Abstract

Background

Noncommunicable disease (NCD) has become the leading cause of mortality and disease burden worldwide.

Methods

A cross-sectional survey was carried out to investigate the prevalence of NCDs and risk factor control on dietary behaviors and dietary intake in China, Japan, and Korea.

Results

There were significant differences among the three countries on the prevalence of hypertension (24.5% in China, 17.6% in Korea, and 15.2% in Japan), diabetes (8.9% in China, 5.7% in Korea, and 4.8% in Japan), hyperlipidemia (13.1% in China, 9.2% in Korea, and 6.9% in Japan), and angina pectoris (3.6% in China, 1.7% in Korea, and 1.5% in Japan). The prevalence rate of hypertension, diabetes, hyperlipidemia, and angina pectoris was highest in China and lowest in Japan. However, 82.2%, 48.4%, and 64.4% of Chinese, Koreans, and Japanese presented good dietary behavior, respectively. Multivariable logistic regression analysis found that sex, age, and marital status were predictors of good dietary behavior. In addition, in comparison with subjects without hypertension, diabetes, or hyperlipidemia, subjects with hypertension, diabetes, or hyperlipidemia significantly improved their dietary behaviors and controlled their intake of salt, sugar, and oil.

Conclusions

The prevalence of NCDs and trends in major modifiable risk factor control in China, Korea, and Japan remain troubling. Public efforts to introduce healthy lifestyle changes and systematic NCDs prevention programs are necessary to reduce the epidemic of NCDs in these three Asian countries.

Keywords: Noncommunicable disease, Risk control, Prevalence

Highlights

  • The prevalences of hypertension, diabetes, and hyperlipidemia were highest in China.

  • The prevalences of hypertension, diabetes, and hyperlipidemia were lowest in Japan.

  • Some dietary behaviors improved hypertension, diabetes, and hyperlipidemia.

  • These dietary behaviors differed by sex, age, and marital status.

Introduction

A noncommunicable disease (NCD) is a medical condition that is noninfectious and nontransmissible among people. NCD is one of the leading causes of mortality and disease burden worldwide. A total of 34.5 million deaths (65% of total deaths) globally were caused by NCDs in 2010, which showed a significant increase from 1990.1 The morbidity and mortality rates of NCDs in China, Japan, and Korea have increased because of increasing fat and protein intake and sedentary lifestyle.2, 3 According to the national data, 80% of deaths and 70% of the total disease burden in China in 2005 were caused by NCDs.4 Using the mortality and national health insurance claim data in Korea, researchers found that, of all causes of mortality, the proportion of mortality from the major NCDs was 39.4% in 1983 and increased to 56.0% in 2011.5 In Japan, the leading causes of death are malignant neoplasm, heart disease, and cerebrovascular disease, which accounted for more than 50% of the total deaths in 2009.6

To reduce the burden of NCDs, comprehensive approaches across the entire disease spectrum are needed, from health promotion, primary prevention, high-risk group screening, and early diagnosis to better treatment and rehabilitation. Among these comprehensive approaches, risk factor modification is an efficient and proven strategy in reducing NCD burden.7 According to the World Health Organization (WHO) report, tobacco and alcohol use, physical inactivity, unhealthy dietary behavior, and dietary intake status have been identified as major determinants of NCDs.8 However, “nutrition transition” from traditional vegetable dietary pattern to unhealthy dietary intake, such as processed food, fast food, and fried food, is the decisive factor in the rapid growth of NCD burden for Chinese, Japanese, and Koreans.9 Recently, most public health activities have targeted modifiable risk factors in reducing the burden of NCDs because the prevention and treatment of major modifiable risk factors have been proven to be effective in reducing mortality caused by NCDs. Over the past few decades, we observed some significant achievements in risk factor modifications among Chinese, Japanese, and Koreans, such as improved dietary behaviors and dietary intake status.7

In spite of the many reports on the prevalence of NCDs and risk factor control among Chinese, Japanese, and Koreans, direct comparison of the prevalence and risk factor control between Chinese, Japanese, and Koreans, has never been investigated under the same study protocol. In the present research, the prevalence of NCDs and risk factor control, including dietary behaviors and dietary intake status among Chinese, Japanese, and Koreans, were compared by using similar study protocols.

Methods

Sampling

This study is cooperative research that is performed by Peking University in China, Saitama Prefectural University in Japan, and Shingu College in Korea. In this study, a cross-sectional survey was performed to investigate the prevalence of NCDs and risk factor control on dietary behaviors and dietary intake in four cities, including Beijing in China, with a population of about 20 million; Matsumoto and Koshigaya in Japan, with populations of about 240,000, and 330,000, respectively; and Seongnam in Korea, with a population of about 1 million. Beijing is the capital of China. Matsumoto, Koshigaya, and Seongnam are average cities in Japan and Korea. A multistage stratified random sampling was used in the study. These four cities were selected using purposive sampling in each country, and three communities in different districts were randomly selected in China and Korea. Then, face-to-face interviews were conducted to answer the questionnaire in China and Korea. In Japan, 1500 subjects were randomly selected from the registered permanent residents in Matsumoto and Koshigaya, and self-administered questionnaires were mailed to collect information from registered permanent residents. Participation was noncompulsory, and the respondents were asked to mail back the questionnaires. The study was conducted according to the guidelines in the Declaration of Helsinki. All of the procedures involving human subjects were approved by the Medical Ethics Research Board of Peking University, Saitama Prefectural University, and Shingu College. A written informed consent was obtained in the study.

Questionnaire interviews

The prevalence of four major NCDs, including hypertension, diabetes, hyperlipidemia, and angina pectoris, was investigated in this study. The health outcomes were obtained using a questionnaire. Demographic information, such as age, sex, household composition, education, marital status, and employment status, were obtained. In this study, marital status was stratified to four groups: single, married, divorced, or widowed. The educational status included four levels: less than primary schools, middle school, high school, junior college and technical secondary school, or college and graduate school. In this study, weight and height were self-reported. All subjects were stratified according to the WHO body mass index (BMI) classification: BMI less than 18.5 kg/m2 was classified as underweight, BMI 18.5 kg/m2 to 24.9 kg/m2 was classified as normal weight, BMI 25.0 kg/m2 to 29.9 kg/m2 was classified as overweight, and BMI 30.0 kg/m2 or greater was classified as obese.

Nine questions on dietary behaviors were asked: 1) “Do you control salt intake?”; 2) “Do you control sugar intake?”; 3) “Do you control oil intake?”; 4) “Do you control the intake of food with additives?”; 5) “Do you control the intake of too much energy?”; 6) “Do you eat on time?”; 7) “Do you care about nutrition balance?”; 8) “Do you drink adequate water?”; and 9) “Do you buy food according to the nutrition label?”. Moreover, the dietary behaviors were quantified by marks, and each good dietary behavior was given one mark. A participant who obtained more than five marks was classified as having good dietary behavior. In addition, a food frequency questionnaire was used to investigate the intake status of 12 kinds of food: fruits; vegetables; milk and dairy; beans, tofu and soymilk; seaweed; fish; meat; processed meat; instant noodles; breakfast; eating out; and fast food. The intake frequencies included four classes: never, 1–2 days each week, 3–4 days each week, or 5 or more days each week.

The questionnaire was produced in Japan, and it was translated to Chinese and Korean by Chinese and Korean researchers, respectively. In addition, the questionnaire in Chinese and Korean was back-translated to Japanese to determine its consistency. The validation of each questionnaire version was evaluated using a pilot study in each country.

Data analysis

The differences in the proportion of demographic variables, dietary behaviors, and dietary intake status among three countries were analyzed using the chi-square test. Multivariable logistic regression analysis was used to clarify the predictors for good dietary behavior. The mean score of dietary behavior was analyzed using analysis of variance. Chi-square test was performed to analyze the differences in the prevalence of hypertension, diabetes, hyperlipidemia, and angina pectoris among the three countries. In addition, chi-square test was used to determine the differences on dietary behavior and dietary intake status between subjects with noncommunicable disease and subjects without noncommunicable disease. P values were two-tailed, with P < 0.05 being considered statistically significant. Statistical analyses were performed using SPSS 20.0 (SPSS Inc., Chicago, IL, USA).

Results

In the present research, 1742, 905, and 3000 subjects were investigated and 1742, 905, and 1667 valid questionnaires were obtained in China, Korea, and Japan, respectively. The response rate was 100%, 100%, and 55.6% in China, Korea, and Japan, respectively. There were significant differences in the prevalence of hypertension (24.5% in China, 17.6% in Korea, and 15.2% in Japan, P = 0.001), diabetes (8.9% in China, 5.7% in Korea, and 4.8% in Japan, P = 0.001), hyperlipidemia (13.1% in China, 9.2% in Korea, and 6.9% in Japan, P = 0.001), and angina pectoris (3.6% in China, 1.7% in Korea, and 1.5% in Japan, P = 0.001) among the three countries. The prevalence rate of hypertension, diabetes, hyperlipidemia, and angina pectoris was highest in China and lowest in Japan. Demographic characteristics of the subjects in the three countries are summarized in Table 1. The distributions of sex, age, marital status, education, and BMI were significantly different among the three countries (P = 0.001).

Table 1.

Demographic characteristics of the subjects in China, Korea, and Japan.

Indices China N (%) Korea N (%) Japan N (%) P
Sex
 Male 691 (39.8) 322 (35.6) 761 (45.7) <0.01
 Female 1047 (60.2) 583 (64.4) 906 (54.3)
Age, years
 20–29 287 (16.5) 220 (24.3) 207 (12.5) <0.01
 30–39 307 (17.6) 176 (19.4) 316 (19.0)
 40–49 286 (16.4) 143 (15.8) 346 (20.9)
 50–59 418 (24.0) 189 (20.9) 326 (19.7)
 >60 444 (25.5) 177 (19.6) 464 (28.0)
Marriage
 Single 212 (12.2) 266 (29.4) 327 (19.7) <0.01
 Married 1464 (84.0) 574 (63.5) 1212 (73.0)
 Divorced 29 (1.7) 22 (2.4) 87 (5.2)
 Widowed 37 (2.1) 42 (4.6) 34 (2.0)
Education
 Less than primary schools 177 (10.2) 69 (7.6) 2 (0.1) <0.01
 Middle School 564 (32.5) 96 (10.6) 138 (8.3)
 High School 307 (17.7) 237 (26.2) 631 (38.1)
 Junior College, Technical Secondary School 379 (21.8) 191 (21.2) 451 (27.3)
 College, Graduate School 310 (17.8) 310 (34.3) 432 (26.1)
BMI, kg/m2
 <18.5 74 (4.3) 41 (4.6) 146 (9.0) <0.01
 18.5–24.9 947 (54.4) 659 (73.5) 1151 (70.9)
 25–30 607 (34.9) 170 (19.0) 271 (16.6)
 >30 112 (6.4) 26 (2.9) 58 (3.6)

BMI, body mass index.

P values were calculated using the Chi-square test.

Table 2 shows the dietary behavior control status in China, Korea, and Japan. There were significant differences on the control of salt, sugar, oil, and calories among participants in China, Korea, and Japan. More than 70% of Chinese tried their best to control the intake of salt, sugar, oil, and calories. However, only 35.3% of Koreans tried their best to control the intake of calories. For the dietary behaviors of food additive control, eating on time, paying attention to nutrition balance and labels, and taking adequate amounts of water, significant differences among participants in China, Korea, and Japan were also observed. Most of the subjects tried their best to follow good dietary behaviors. However, most subjects did not pay attention to nutrition labels. Only 44.1% of Chinese, 33% of Koreans, and 28% of Japanese paid attention to nutrition labels. To explore the predictors of good dietary behavior, the dietary behaviors were quantified by marks, and each good dietary behavior was given one mark. Significant differences were observed among the three countries, and the mean scores were 6.74, 4.37, and 5.32 in China, Korea, and Japan, respectively (P = 0.001). Subjects who obtained more than 5 marks were classified as showing good dietary behavior, and the prevalence rates of good dietary behavior were 82.2%, 48.4%, and 64.4% in China, Korea, and Japan, respectively (P = 0.001). Multivariable logistic regression analysis found that sex, age, and marital status were the predictors of good dietary behavior, after adjustment for BMI and education level. Female, married, and old-aged subjects had better dietary behavior than other subjects (Table 3).

Table 2.

The differences of dietary behaviors in China, Korea, and Japan.

China N (%) Korea N (%) Japan N (%) P
Salt-control
 Yes 1304 (74.9) 463 (51.2) 1005 (60.5) <0.01
 No 437 (25.1) 441 (48.8) 656 (39.5)
Sugar-control
 Yes 1261 (72.4) 434 (48.0) 985 (59.4) <0.01
 No 481 (27.6) 470 (52.0) 673 (40.6)
Oil-control
 Yes 1368 (78.6) 524 (57.9) 1085 (65.3) <0.01
 No 373 (21.4) 381 (42.1) 577 (34.7)
Food additives-control
 Yes 1291 (74.3) 461 (51.1) 804 (48.5) <0.01
 No 447 (25.7) 441 (48.9) 854 (51.5)
Eat on time
 Yes 1586 (91.9) 443 (49.0) 1012 (61.0) <0.01
 No 154 (8.9) 461 (51.0) 646 (39.0)
Calorie-control
 Yes 1300 (74.7) 319 (35.3) 1106 (66.7) <0.01
 No 440 (25.3) 585 (64.7) 552 (33.3)
Pay attention to the nutrition balance
 Yes 1327 (76.2) 409 (45.2) 1210 (72.9) <0.01
 No 414 (23.8) 496 (54.8) 449 (27.1)
Drink adequate water
 Yes 1528 (87.8) 602 (66.5) 1169 (70.5) <0.01
 No 214 (12.3) 303 (33.5) 490 (29.5)
Pay attention to the nutrition label
 Yes 767 (44.1) 229 (33.0) 465 (28.0) <0.01
 No 973 (55.9) 606 (67.0) 1194 (72.0)

P values were calculated by Chi-square test.

Table 3.

The predictors for good dietary behavior in China, Korea, and Japan.

OR (95% CI) in China OR (95% CI) in Korea OR (95% CI) in Japan
Sex
 Male Reference Reference Reference
 Female 2.99 (2.28, 3.91) 1.50 (1.09, 2.06) 3.27 (2.55, 4.20)
Age, years
 20–29 Reference Reference Reference
 30–39 0.93 (0.57, 1.53) 1.34 (0.76, 2.37) 1.55 (1.03, 2.33)
 40–49 1.03 (0.6, 1.78) 1.56 (0.82, 2.96) 1.84 (1.19, 2.83)*
 50–59 1.86 (1.06, 3.29)* 2.90 (1.46, 5.77)* 3.0 (1.91, 4.71)*
 >60 2.33 (1.27, 4.28)* 6.11 (2.8, 13.32)* 6.94 (4.27, 11.3)*
Marriage
 Single 0.53 (0.32, 0.87) 0.55 (0.32, 0.94) 0.94 (0.68, 1.30)
 Married Reference Reference Reference
 Divorced 0.52 (0.21, 1.31) 0.53 (0.21, 1.33) 0.81 (0.49, 1.33)
 Widowed 0.72 (0.27, 1.95) 1.01 (0.48, 2.14) 0.77 (0.30, 2.02)
Education
 Less than primary schools Reference Reference Reference
 Middle School 1.29 (0.74, 2.23) 0.90 (0.44, 1.83) 1.29 (0.74, 2.23)
 High School 1.12 (0.62, 2.03) 0.99 (0.51, 1.94) 1.12 (0.62, 2.03)
 Technical Secondary School 1.26 (0.69, 2.29) 1.37 (0.64, 2.89) 1.26 (0.69, 2.29)
 College, Graduate School 1.81 (0.95, 3.42) 1.45 (0.71, 2.99) 1.81 (0.95, 3.42)
BMI. kg/m2
 <18.5 Reference Reference Reference
 18.5–24.9 1.59 (0.89, 2.84) 0.71 (0.36, 1.40) 1.15 (0.77, 1.71)
 25–30 1.37 (0.74, 2.54) 0.62 (0.29, 1.33) 0.71 (0.44, 1.14)
 >30 1.13 (0.51, 2.48) 0.55 (0.18, 1.66) 0.80 (0.40, 1.60)
Hypertension
 Yes Reference Reference Reference
 No 0.75 (0.51, 1.10) 0.88 (0.56, 1.38) 0.64 (0.44, 0.94)
Diabetes
 Yes Reference Reference Reference
 No 0.65 (0.36, 1.18) 1.05 (0.55, 2.01) 1.39 (0.79, 2.43)
Hyperlipidemia
 Yes Reference Reference Reference
 No 1.26 (0.82, 1.95) 1.00 (0.59, 1.71) 0.73 (0.44, 1.20)
Angor pectoris
 Yes Reference Reference Reference
 No 1.76 (0.87, 3.56) 0.81 (0.25, 2.57) 0.90 (0.35, 2.37)

BMI, body mass index; CI, confidence interval; OR, odds ratio.

Adjusted by body mass index and education.

* P < 0.05.

The intake of 12 kinds of food is presented in Table 4. Most of the subjects ate fruit at least once a week, but more than 20% of Japanese never ate fruit. More than 80% of Chinese ate vegetables every day, whereas only 27.9% of Koreans ate vegetables every day. About 29.7% of Chinese never ate dairy food, and 42.4% of Chinese never ate seaweed. For the three countries, about 90% or 80% subjects ate soy food or fish at least once a week. Meat was consumed daily by 24.4%, 6.0%, and 14.1% and processed meat was consumed daily by 2.6%, 3.6%, and 4.7% of Chinese, Korean, and Japanese, respectively. About 50% or 70% of subjects never ate instant noodles or fast food, and only half of Koreans ate breakfast daily. There were 54.7%, 33.2%, and 50.2% of Chinese, Koreans, and Japanese subjects who never ate out, respectively.

Table 4.

The differences of food intake frequency in China, Korea, and Japan.

Foods Frequency China N (%) Korea N (%) Japan N (%) P Foods Frequency China N (%) Korea N (%) Japan N (%) P
Fruit Never 151 (8.7) 74 (8.2) 366 (22.2) <0.01 Meat Never 165 (9.5) 147 (16.2) 60 (3.6) <0.01
1–2 days/week 398 (22.9) 314 (34.7) 614 (37.2) 1–2 days/week 618 (35.8) 511 (56.5) 527 (31.9)
3–4 days/week 458 (26.4) 287 (31.7) 322 (19.5) 3–4 days/week 524 (30.3) 193 (21.3) 831 (50.4)
≥5 days/week 730 (42.0) 230 (25.4) 350 (21.2) ≥5 days/week 421 (24.4) 54 (6.0) 232 (14.1)
Vegetable Never 21 (1.2) 50 (5.5) 21 (1.3) <0.01 Processed meat Never 953 (55.2) 490 (54.4) 308 (18.7) <0.01
1–2 days/week 109 (6.3) 289 (32.0) 167 (10.1) 1–2 days/week 605 (35.0) 308 (34.2) 914 (55.5)
3–4 days/week 153 (8.9) 313 (34.6) 351 (21.2) 3–4 days/week 125 (7.2) 71 (7.9) 347 (21.1)
≥5 days/week 1445 (83.6) 252 (27.9) 1114 (67.4) ≥5 days/week 45 (2.6) 32 (3.6) 77 (4.7)
Milk and dairy Never 513 (29.7) 177 (19.7) 194 (11.8) <0.01 Instant noodle Never 1055 (61.0) 398 (44.2) 986 (59.6) <0.01
1–2 days/week 515 (29.8) 290 (32.3) 352 (21.4) 1–2 days/week 495 (28.6) 346 (38.4) 559 (33.8)
3–4 days/week 274 (15.9) 239 (26.6) 338 (20.5) 3–4 days/week 97 (5.6) 113 (12.5) 92 (5.6)
≥5 days/week 426 (24.7) 191 (21.3) 763 (46.3) ≥5 days/week 82 (4.7) 44 (4.9) 16 (1.0)
Bean tofu, soymilk Never 217 (12.5) 95 (10.5) 112 (6.8) <0.01 Breakfast Never 85 (4.9) 170 (18.9) 188 (11.4) <0.01
1–2 days/week 927 (53.6) 400 (44.4) 595 (36.0) 1–2 days/week 106 (6.2) 110 (12.2) 68 (4.1)
3–4 days/week 373 (21.5) 266 (29.5) 506 (30.6) 3–4 days/week 117 (6.8) 135 (15.0) 86 (5.2)
≥5 days/week 214 (12.4) 140 (15.5) 440 (26.6) ≥5 days/week 1411 (82.1) 485 (53.9) 1313 (79.3)
Seaweed Never 732 (42.4) 182 (20.2) 177 (10.7) <0.01 Outdoor dining Never 946 (54.7) 300 (33.2) 832 (50.2) <0.01
1–2 days/week 823 (47.7) 479 (53.1) 758 (45.9) 1–2 days/week 329 (19.0) 414 (45.8) 608 (36.7)
3–4 days/week 104 (6.0) 181 (20.1) 485 (29.3) 3–4 days/week 171 (9.9) 135 (15.0) 116 (7.0)
≥5 days/week 68 (3.9) 60 (6.7) 233 (14.1) ≥5 days/week 284 (16.4) 54 (6.0) 100 (6.0)
Fish Never 386 (22.4) 215 (23.9) 110 (6.7) <0.01 Fast Food Never 1430 (82.4) 593 (65.6) 1249 (75.3) <0.01
1–2 days/week 1116 (64.7) 512 (56.8) 717 (43.4) 1–2 days/week 220 (12.7) 254 (28.1) 394 (23.8)
3–4 days/week 150 (8.7) 141 (15.6) 652 (39.4) 3–4 days/week 51 (2.9) 35 (3.9) 10 (0.6)
≥5 days/week 72 (4.2) 33 (3.7) 174 (10.5) ≥5 days/week 34 (2.0) 22 (2.4) 5 (0.3)

P values were calculated using the Chi-square test.

The differences on dietary behavior and dietary intake status between subjects with noncommunicable disease and subjects without noncommunicable disease were analyzed. As shown in Table 5, significant differences between subjects with hypertension or diabetes and subjects without hypertension or diabetes on dietary behaviors (except for nutrition balance) were also observed. In comparison with subjects without hyperlipidemia, subjects with hyperlipidemia significantly controlled their intake of salt, sugar, oil, and food additives. Significant differences on food additive-control and eating on time were observed between subjects with angina pectoris and subjects without angina pectoris. Table 6 shows the differences on dietary intake status between subjects with NCDs and subjects without NCDs. Significant differences in vegetable intake were found between subjects with hypertension or diabetes and subjects without hypertension or diabetes. In addition, more subjects with NCDs paid attention to eating breakfast daily. More subjects with hypertension, diabetes, and hyperlipidemia never ate out.

Table 5.

The differences on dietary behavior between subjects with noncommunicable disease and subjects without noncommunicable disease.

Hypertension
P Diabetes
P Hyperlipidemia
P Angor pectoris
P
Yes N (%) No N (%) Yes N (%) No N (%) Yes N (%) No N (%) Yes N (%) No N (%)
Salt-control Yes 646 (77.2) 2126 (61.3) <0.01 204 (71.1) 2568 (63.9) <0.05 310 (73.1) 2462 (63.4) <0.01 74 (71.8) 2698 (64.2) 0.119
No 191 (22.8) 1343 (38.7) 83 (28.9) 1451 (36.1) 114 (26.9) 1420 (36.6) 29 (28.2) 1505 (35.8)
Sugar-control Yes 612 (73.0) 2068 (59.7) <0.01 235 (81.9) 2445 (60.9) <0.01 307 (72.2) 2373 (61.2) <0.01 72 (69.9) 2608 (62.1) 0.122
No 226 (27.0) 1398 (40.3) 52 (18.1) 1572 (39.1) 118 (27.8) 1506 (38.8) 31 (30.1) 1593 (37.9)
Oil-control Yes 650 (77.6) 2327 (67.1) <0.01 216 (75.3) 2761 (68.7) <0.05 331 (77.9) 2646 (68.1) <0.01 79 (76.7) 2898 (68.9) 0.105
No 188 (22.4) 1143 (32.9) 71 (24.7) 1260 (31.3) 94 (22.1) 1237 (31.9) 24 (23.3) 1307 (31.1)
Food additives-control Yes 573 (68.4) 1983 (57.3) <0.01 208 (72.5) 2348 (58.5) <0.01 296 (69.6) 2260 (58.4) <0.01 77 (74.8) 2479 (59.1) <0.01
No 265 (31.6) 1477 (42.7) 79 (27.5) 1663 (41.5) 129 (30.4) 1613 (41.6) 26 (25.2) 1716 (40.9)
Eat on time Yes 683 (81.5) 2358 (68.1) <0.01 240 (83.9) 2801 (69.1) <0.01 340 (80.0) 2701 (69.7) <0.01 86 (83.5) 2955 (70.4) <0.01
No 155 (18.5) 1106 (31.9) 46 (16.1) 1215 (30.3) 85 (20.0) 1176 (30.3) 17 (16.5) 1244 (29.6)
Calorie-control Yes 593 (70.8) 2132 (61.5) <0.01 206 (71.8) 2519 (62.7) <0.01 287 (67.4) 2438 (62.9) 0.072 72 (69.9) 2653 (63.2) 0.179
No 244 (29.2) 1333 (38.5) 81 (28.2) 1496 (37.3) 139 (32.6) 1438 (37.1) 31 (30.1) 1546 (36.8)
Nutrition balance Yes 587 (70.0) 2359 (68.0) 0.282 203 (71.0) 2743 (68.3) 0.357 298 (70.0) 2648 (68.3) 0.510 68 (66.0) 2878 (68.5) 0.593
No 251 (30.0) 1108 (32.9) 83 (29.0) 1276 (31.7) 128 (30.0) 1231 (31.7) 35 (34.0) 1324 (31.5)
Drink adequate water Yes 686 (81.9) 2613 (75.3) <0.01 239 (83.6) 3060 (76.1) <0.01 341 (80.2) 2958 (76.2) 0.070 85 (82.5) 3214 (76.5) 0.159
No 152 (18.1) 855 (24.7) 47 (16.4) 960 (23.9) 84 (19.8) 923 (23.8) 18 (17.5) 989 (23.5)
Refer to the nutrition label Yes 334 (39.9) 1197 (34.5) <0.01 118 (41.1) 1413 (35.2) <0.05 168 (39.4) 1363 (35.1) 0.088 40 (38.8) 1491 (35.5) 0.532
No 504 (60.1) 2269 (65.5) 169 (58.9) 2604 (64.8) 258 (60.6) 2515 (64.9) 63 (61.2) 2710 (64.5)

P values were calculated using the Chi-square test.

Table 6.

The differences on dietary intake status between subjects with noncommunicable disease and subjects without noncommunicable disease.

Hypertension
P Diabetes
P Hyperlipidemia
P Angor Pectoris
P
Yes N (%) No N (%) Yes N (%) No N (%) Yes N (%) No N (%) Yes N (%) No N (%)
Fruit <5 d/w 558 (67.1) 2426 (70.1) 0.111 186 (65.3) 2798 (69.8) 0.110 286 (67.8) 2689 (69.7) 0.436 65 (63.7) 2919 (69.6) 0.231
≥5 d/w 273 (32.9) 1037 (29.8) 99 (34.7) 1211 (30.2) 136 (32.2) 1174 (30.3) 37 (36.3) 1273 (30.4)
Vegetable <5 d/w 242 (29.2) 1232 (35.6) <0.01 80 (28.0) 1394 (34.9) <0.05 126 (30.1) 1348 (34.9) 0.051 27 (26.2) 1447 (34.6) 0.092
≥5 d/w 586 (70.8) 2225 (64.4) 206 (72.0) 2605 (65.1) 293 (69.9) 2518 (65.1) 76 (73.8) 2735 (65.4)
Milk dairy <5 d/w 606 (72.7) 2286 (66.5) <0.01 201 (70.0) 2691 (67.5) 0.396 319 (75.8) 2573 (66.8) <0.01 73 (72.3) 2819 (67.6) 0.335
≥5 d/w 227 (27.3) 1153 (33.5) 86 (30.0) 1294 (32.5) 102 (24.2) 1278 (33.2) 28 (27.7) 1352 (32.4)
Bea, tofu, soymilk <5 d/w 688 (82.8) 2803 (81.2) 0.296 234 (82.4) 3257 (81.4) 0.752 352 (83.4) 3139 (81.3) 0.292 87 (85.3) 3404 (81.4) 0.367
≥5 d/w 143 (17.2) 651 (18.8) 50 (17.6) 744 (18.6) 70 (16.6) 724 (18.7) 15 (14.7) 779 (18.6)
Seaweed <5 d/w 766 (92.1) 3155 (91.4) 0.627 258 (91.5) 3663 (91.6) 0.912 400 (95.2) 4521 (91.2) <0.01 95 (92.2) 3826 (91.6) 1.000
≥5 d/w 66 (7.9) 295 (8.6) 24 (8.5) 337 (8.4) 20 (4.8) 341 (8.8) 8 (7.8) 353 (8.4)
Fish <5 d/w 766 (92.7) 3233 (93.7) 0.346 256 (90.5) 3743 (93.7) <0.05 402 (96.2) 3597 (93.2) <0.05 93 (91.2) 3906 (93.5) 0.310
≥5 d/w 60 (7.3) 219 (6.3) 27 (9.5) 252 (6.3) 16 (3.8) 263 (6.8) 9 (8.8) 270 (6.5)
Meat <5 d/w 688 (82.8) 2888 (83.7) 0.533 228 (80.0) 3348 (83.7) 0.116 347 (82.0) 3229 (83.7) 0.408 85 (82.5) 3491 (83.5) 0.788
≥5 d/w 143 (17.2) 564 (16.3) 57 (20.0) 650 (16.3) 76 (18.0) 631 (16.3) 18 (17.5) 689 (16.5)
Processed meat <5 d/w 809 (97.4) 3312 (96.2) 0.119 280 (98.6) 3841 (96.2) 0.045 412 (97.4) 3709 (96.3) 0.274 102 (99.0) 4019 (96.3) 0.184
≥5 d/w 22 (2.6) 132 (3.8) 4 (1.4) 150 (3.8) 11 (2.6) 143 (3.7) 1 (1.0) 153 (3.7)
Instant noodle <5 d/w 803 (96.7) 3338 (96.7) 1.000 275 (96.5) 3866 (96.7) 0.863 412 (97.2) 3729 (96.6) 0.668 96 (93.2) 4045 (96.8) 0.083
≥5 d/w 27 (3.3) 115 (3.3) 10 (3.5) 132 (3.3) 12 (2.8) 130 (3.4) 7 (6.8) 135 (3.2)
Breakfast <5 d/w 142 (17.1) 923 (26.8) <0.01 40 (14.1) 1025 (25.7) <0.01 70 (16.6) 995 (25.8) <0.01 15 (14.6) 1050 (25.2) <0.05
≥5 d/w 688 (82.9) 2521 (73.2) 244 (85.9) 2965 (74.3) 352 (83.4) 2857 (74.2) 88 (85.4) 3121 (74.8)
Outdoor dining <5 d/w 802 (96.2) 3049 (88.2) <0.01 271 (94.8) 3580 (89.4) <0.01 401 (94.4) 3450 (89.3) <0.01 97 (94.2) 3754 (89.7) 0.185
≥5 d/w 32 (3.8) 406 (11.8) 15 (5.2) 423 (10.6) 24 (5.6) 414 (10.7) 6 (5.8) 432 (10.3)
Fast food <5 d/w 822 (98.7) 3414 (98.6) 0.872 284 (99.0) 3952 (98.6) 0.797 419 (99.1) 3817 (98.5) 0.517 99 (96.1) 4137 (98.6) 0.057
≥5 d/w 11 (1.3) 50 (1.4) 3 (3.0) 58 (1.4) 4 (0.9) 57 (1.5) 4 (3.9) 57 (1.4)

P values were calculated using the Chi-square test.

Discussion

To date, this is the first study on the current prevalence of NCDs and risk factor control in three Asian countries using a single study protocol. The prevalence rates of hypertension, diabetes, hyperlipidemia, and angina pectoris were highest in China and lowest in Japan. However, Chinese subjects presented greater awareness of risk factor control than Korean and Japanese subjects.

The lifestyle and diet of the Chinese, Korean, and Japanese people have changed substantially in recent decades, with increased fat and protein intake and a more sedentary lifestyle.2, 3, 9 A steady increase in NCDs has been observed because of these changes.10, 11 Many important international actions on NCDs have been initiated through international agencies, including the United Nations and WHO, during the past decade. WHO made important steps toward controlling major NCD risk factors by adopting the Framework Convention on Tobacco Control, Global Strategy on Diet, Physical Activity and Health, and Global Strategy to Reduce Harmful Use of Alcohol in 2003, 2004, and 2010, respectively.12 Over the past few decades, some significant achievements in risk factor modifications among Chinese, Koreans, and Japanese have been implemented. In Korea, Korean National Health Insurance Policy has provided most Koreans with medical examinations and health education every other year.13 In Japan, a 10-year national health promotion campaign, called Health Japan 21, was initiated by the Japanese government in 2000 for improving the nation's health.14 In this campaign, 59 indicators, such as diet, smoking, and diabetes, were established to monitor and improve risk factor management.14 In China, the national cancer prevention and control plan (2004–10) and a national chronic disease prevention and control plan have been implemented.4 In this report, about 82%, 48%, and 64% of Chinese, Koreans, and Japanese, respectively, presented good dietary behavior.

Although our dietary behavior quantification method is original to the present research, we discerned that greater attention is needed for modifying risk factors among subgroups of gender, age, and demographic status. We found that males are often less health consciousness compared with females, a finding which was consistent with those of previous studies.13, 15 In the Ansan study of Koreans, a significantly higher rate of awareness, treatment, and control of NCDs was observed in women than those in men.13 In the present research, subjects with hypertension, diabetes, or hyperlipidemia significantly improved their dietary behaviors and controlled salt, sugar, and oil intake compared with subjects without hypertension, diabetes, or hyperlipidemia. However, subjects with angina pectoris did not significantly improve their dietary behaviors compared with subjects without angina pectoris. Thus, health educators should target health education for patients with angina pectoris.

Our study has some limitations. This is a cross-sectional study than can only present the possible risk factors for health consciousness. Although we tried to standardize our surveys in three different regions as uniformly as possible, some procedures had to be modified according to the local research environment. The method of population recruitment and questionnaire survey had to be performed in ways that would best accommodate the local situation. For example, face-to-face interviews were conducted in China and Korea. However, a random sample of registered permanent residence and a mail survey were used in Japan. As a result, the response rate was significantly different among the three countries. The response rate was 55.6% in Japan. This rate is not low for a mail survey in Japan, but we should be careful about the relatively small population of younger respondents or working men. In addition, different understandings of salt, sugar, and oil control among the three countries that are based on cultural background may also introduce bias into the results. However, bias in the comparison of prevalence and risk control status among participants in the three countries is expected to be small because of the large sample size.

In conclusion, the current status of the prevalence of NCDs and trends in major modifiable risk factor control in China, Korea, and Japan reinforce the importance of prevention, detection, and treatment of risk factors in reducing the burden of NCDs on individuals and societies. Public efforts to introduce healthy lifestyle change and systematic NCD prevention programs are necessary to reduce the epidemic of NCDs in these three Asian countries.

Conflicts of interest

None declared.

Acknowledgements

We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work. We thank Dr. Tuohong Zhang of the Peking University for technical assistance.

Footnotes

Peer review under responsibility of the Japan Epidemiological Association.

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