Dietary pattern classifications with nutrient intake and health-risk factors in Korean men

Nutrition 27 (2011) 26–33

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Nutrition journal homepage: www.nutritionjrnl.com

Applied nutritional investigation

Dietary pattern classifications with nutrient intake and health-risk factors in Korean men Ji Eun Lee Ph.D. a,1, Jung-Hyun Kim Ph.D. a,1, Say Jin Son M.S. a, Younjhin Ahn Ph.D. b, Juyoung Lee Ph.D. b, Chan Park Ph.D. b, Lilha Lee Ph.D. a, Kent L. Erickson Ph.D. c, In-Kyung Jung Ph.D. a,1, * a b c

Department of Home Economics Education, Chung-Ang University, Seoul, Korea National Genome Research Institute, Korea Centers for Disease Control and Prevention, Seoul, Korea Department of Cell Biology and Human Anatomy, University of California, Davis, California, USA

a r t i c l e i n f o

a b s t r a c t

Article history: Received 22 April 2009 Accepted 24 October 2009

Objective: This study was performed to identify dietary patterns in Korean men and to determine the associations among dietary patterns, nutrient intake, and health-risk factors. Methods: Using baseline data from the Korean Health and Genome Study, dietary patterns were identified using factor analysis of data from a validated food-frequency questionnaire, and associations between these dietary patterns and health-risk factors were analyzed. Results: Three dietary patterns were identified: 1) the ‘‘animal-food’’ pattern (greater intake of meats, fish, and dairy products), 2) the ‘‘rice–vegetable’’ pattern (greater intake of rice, tofu, kimchi, soybean paste, vegetables, and seaweed), and 3) the ‘‘noodle–bread’’ pattern (greater intake of instant noodles, Chinese noodles, and bread). The animal-food pattern (preferred by younger people with higher income and education levels) had a positive correlation with obesity and hypercholesterolemia, whereas the rice–vegetable pattern (preferred by older people with lower income and educational levels) was positively associated with hypertension. The noodle–bread pattern (also preferred by younger people with higher income and education levels) had a positive association with abdominal obesity and hypercholesterolemia. Conclusion: This study identifies three unique dietary patterns in Korean men, which are independently associated with certain health-risk factors. The rice–vegetable dietary pattern, modified for a low sodium intake, might be a healthy dietary pattern for Korean men. Ó 2011 Elsevier Inc. All rights reserved.

Keywords: Factor analysis Obesity Hypertension Blood lipid profile

Introduction Most nutritional epidemiologic studies have identified associations among one or more selected nutrients, foods or energy intake, and the incidence of chronic disease. However, ‘‘food’’ does not contain a single nutrient but is a combination of nutrients and non-nutrients that interact, implying that more complex relations exist between food intake and chronic diseases [1–3]. In this regard, several nutritional epidemiologists have investigated the correlations between overall diet quality or dietary pattern and chronic diseases in an effort to overcome the limitations of traditional single-nutrient studies and to evaluate these complex relations [1,2]. This research was supported by Chung-Ang University Research Scholarship Grants in 2007. 1 These authors contributed equally to this work. * Corresponding author. Tel.: þ82-2-820-5380; fax: þ82-2-817-7304. E-mail address: [email protected] (I.-K. Jung). 0899-9007/$ - see front matter Ó 2011 Elsevier Inc. All rights reserved. doi:10.1016/j.nut.2009.10.011

Dietary patterns have been analyzed by factor analysis or cluster analysis to simplify the nutrient intake or food consumption of individuals into one of several dietary groups. This method has been used to determine unique, and healthy dietary patterns in various countries and populations [3–6]. In addition, the World Health Organization (WHO) has suggested that each country determine its own healthy dietary patterns, because the differences in cultures and populations can have an impact on dietary patterns [7,8]. Within several populations, researchers have identified different dietary patterns that are attributable to varying social and cultural backgrounds [9,10]. Furthermore, dietary patterns may have altered over time due to food availability and preference changes [11]. Since 1980, researchers have elucidated relations between dietary patterns and chronic diseases such as cancer, hypertension, and diabetes [1,3]. In the Nurses’ Health Study and Health Professionals Follow-up Study, two dietary patterns were identified: the ‘‘prudent dietary pattern’’ (characterized by a higher

J. E. Lee et al. / Nutrition 27 (2011) 26–33

27

Table 1 Food groups for dietary pattern analysis No.

Foods or food groups

Food items

1 2 3 4 5 6

steamed rice roasted grain powder ramen noodles Chinese noodles other noodles

steamed rice (well milled), steamed rice with barley, steamed rice with other cereals, soybean roasted grain powder ramen noodle soup chajangmyun (noodle with black bean paste) buckwheat vermicelli /buckwheat noodle, dumpling, rice-cake soup (prepared with slices of rice cake, beef, and eggs) loaf bread, breakfast cereals, butter/margarine, pizza/hamburger bread with small red bean, other breads, rice cake cakes, snacks, candy/chocolate potatoes, sweet potatoes sweet potato noodle tofu starch jelly nuts kimchi (napa cabbage kimchi), kkakduki (cubed radish kimchi)/small radish kimchi, nabak kimchi (watery kimchi with sliced vegetable), other kimchi soybean paste pot stew salt-fermented fish green pepper, lettuce, perilla leaf, leek/water dropwort, cucumber, red pepper leaves, spinach, green yellow vegetables, cabbage, radish/salted radish, vegetable juice, carrot doraji/deoduck (kinds of white root), bean sprouts, pumpkin gruel/pumpkin juice, bracken/sweet potato stalk, onion, squash, oyster mushroom, other mushroom pickles hard persimmon/dried persimmon, citrus fruit, muskmelon/melon, banana, pear, apple/apple juice, orange/orange juice, watermelon, peach/plum, strawberry, grape/grape juice, tomato/ tomato juice chicken, pan-roasted pork, pork belly, braised pork, dog meat pan-roasted beef ribs, thick-beef soup/hard boiled beef ribs, edible viscera egg/quail eggs sushi, hair tail, eel, yellow croaker, Alaska pollack mackerel/Pacific saury/Spanish mackerel dried anchovy ham/sausage, tuna (canned), fish paste/crab flavored cuttlefish/octopus, crab, clam, oyster, shrimp laver (dried), kelp/sea mustard whole milk, yogurt, ice cream, cheese carbonated drinks, coffee, coffee cream, coffee sugar green tea soybean milk, other drinks

7 8 9 10 11 12 13 14 15

loaf bread, breakfast cereals, pizza/hamburger other breads snacks potatoes and sweet potatoes sweet potato noodle tofu starch jelly nuts kimchi

16 17 18

soybean paste salt-fermented fish yellow-green vegetables

19

other vegetables

20 21

pickles fruits

22 23 24 25 26 27 28 29 30 31 32 33 34

low-fat meats high-fat meats eggs lean fish fatty fish dried anchovy processed meats and fishes shellfish seaweeds milk and dairy products coffee and carbonated drinks tea other drinks

intake of fruit, vegetables, legumes, whole grains, and fish) and the ‘‘Western dietary pattern’’ (characterized by a higher consumption of processed meat, red meat, butter, high-fat dairy products, eggs, and refined grains) [12–15]. Researchers have suggested that the prudent dietary pattern might reduce the risk of coronary heart disease, chronic obstructive pulmonary disease, and gestational diabetes mellitus [12–15]. In addition, researchers in East Asian countries, such as China and Japan, have tried to identify connections between their countries’ dietary patterns, characterized by a high intake of rice and vegetables and a low intake of animal food, and local culture. In the Shanghai Men’s Health Study, three dietary patterns were classified as ‘‘fruit-based,’’ ‘‘vegetable-based,’’ and ‘‘meat-based’’ [16]. It showed that elderly men with chronic diseases preferred a vegetable-based diet and not fruit- or meat-based diets [16]. The Self-Defense Forces Health Study in Japan also identified three dietary patterns: the ‘‘Japanese pattern’’ (highly correlated with soybean products, fish, seaweed, vegetables, fruit, and green tea), the ‘‘animal-food’’ pattern, and the ‘‘high-dairy, highfruit and -vegetable, high-starch, low-alcohol’’ pattern [17,18]. They reported that the high-dairy, high-fruit and -vegetable, high-starch, low-alcohol pattern had a negative association with glucose tolerance abnormality and colorectal adenomas [17,18]. Many countries have tried to identify their own dietary patterns to determine the relation between dietary patterns and

chronic disease, because dietary culture and unique dietary patterns are factors that can influence the incidence of chronic disease [4–6,19–26]. Before the mid-20th century, a unique dietary pattern and dietary culture existed in Korea. The dietary pattern of Koreans has changed, along with the incidence of chronic disease, since the introduction of Western dietary culture. However, no previous study has directly examined the effects of dietary patterns and health-risk factors on Korean men after the introduction of a Western diet, even though in other countries, the Western pattern has been reported to increase the incidence of chronic disease [12,15,17,18]. Therefore, in this study, we define current dietary patterns for Korean men and identify associations among Korean dietary patterns, socioeconomic factors, lifestyle factors, and health-risk factors. Based on this information, we will suggest a healthy dietary pattern for Korean men.

Materials and methods Study population The Korea Health and Genome Study is a population-based prospective cohort study, begun in 2001, for the purpose of describing the frequency and determinants of chronic disease in Korea. Biennially, participant’s dietary intake, health information, and disease status are assessed by intensive interviews and health examinations. Participants were randomly selected within an age range of 40–69 y, as described in previous studies [27,28]. The procedures used were in

28

J. E. Lee et al. / Nutrition 27 (2011) 26–33

accordance with institutional guidelines and approved by the institutional review committee. Informed consent was obtained from all study participants. In the present study, the baseline data were collected from 4762 Korean men from May 2001 to February 2003. Three participants, whose weight or height was not measured, were excluded from the data sample. We also excluded 967 men who were diagnosed with and were being treated for cancer, hypertension, or diabetes. In addition, 211 men were excluded because they failed to fully complete the semiquantitative food-frequency questionnaire or had dietary intakes of more than 4000 kcal or less than 500 kcal [29]. Therefore, a total of 3581 subjects were analyzed. Dietary assessment method and food grouping Dietary intake information was collected by administering a validated semiquantitative food-frequency questionnaire to each participant [30]. This questionnaire requested information regarding the participant’s consumption of 103 food items (Table 1). The participant’s food intake frequency was quantified using nine categories: ‘‘never or seldom,’’ ‘‘once a month,’’ ‘‘two to three times a month,’’ ‘‘one to two times a week,’’ ‘‘three to four times a week,’’ ‘‘five to six times a week,’’ ‘‘once a day,’’ ‘‘twice a day,’’ and ‘‘three times or more every day.’’ The portion size was classified depending on the average size of each selected food item. Each portion size was then categorized as one of three amounts: small, medium, or large. To analyze the data using factor analysis, nine scaled frequencies of food intake, created from the food intake data, were recalculated to measure food intake frequency within 1 mo. For example, if a participant ate rice three times per day, his rice intake frequency was 90 times per month (30 d). Personal nutritional intake per day was calculated by multiplying frequency of food intake by the amount of food intake for each period. Daily nutrient intake was calculated using the Korean Food Composition Table [31]. The 103 food items in the semiquantitative food-frequency questionnaire were grouped into 34 predefined food groups, based on similarities in ingredients, nutrient profile, and/or culinary usage (Table 1). Assessment of other variables Sociodemographic characteristics used in the analysis were age at the time of recruitment, family income per month, and education level. Lifestyle-related factors were examined, including alcohol consumption, smoking status, regular exercise activity, and nutrition-supplement intake during the 4 wk preceding recruitment. For anthropometric purposes, the following was measured: height (centimeters), weight (kilograms), and waist circumference (WC; centimeters). Height and weight were measured to the nearest 0.1 cm and 0.1 kg, respectively, and WC was measured to the nearest 0.1 cm three times and an average was taken. Body mass index (BMI) was calculated as weight (kilograms) divided by the square of height (meters). Obesity parameters were defined underweight (BMI <18.5), normal (BMI 18.5 to <25), overweight (BMI 25 to <30), and obese (BMI  30.0). Abdominal obesity was defined as a WC larger than 90 cm [32]. Blood pressure was measured according to the WHO–International Society of Hypertension guidelines by a trained technician using a mercury sphygmomanometer. The blood pressure result presented in this study was the average of three measurements. We classified the hypertensive group as those participants whose systolic blood pressure (SBP) was over 140 mmHg or diastolic blood pressure was over 90 mmHg [32]. Levels of total cholesterol (TC), triacylglycerols, and high-density lipoprotein (HDL) and low-density lipoprotein (LDL) cholesterol were measured after 10 h of fasting. TC and triacylglycerols were measured enzymatically with the AVIDA 1650 (Bayer, Tarrytown, NY, USA), and HDL cholesterol levels were measured, after precipitation of the other lipoproteins, by the same method [33]. LDL cholesterol levels were calculated by the Friedewald equation [34]. Statistical methods Factor analysis is a statistical data reduction technique used to explain variability among observed random variables in terms of aggregated unobserved random variables called factors [35]. Principal component factor analysis was used to identify dietary patterns, with the factors rotated by orthogonal transformation. The weight of the factors, in conjunction with an eigenvalue >1.25, determined whether a factor should be retained [36]. Factor names reflected the food groups having the highest loadings of that factor. Food groups having a positive loading contributed directly to that dietary pattern, and food groups with negative loadings were inversely associated with a given dietary pattern. When a food group loaded on more than one dietary pattern, only the pattern with high loading was considered for factor naming. Factor scores were calculated for each study participant and were computed by weighting each factor loading by the eigenvalue of each factor, multiplying these weights with the corresponding standardized food-group intake of the subjects, to create a sum of

Table 2 Factor-loading matrix for dietary patterns* Food group

Steamed rice Roasted grain powder Ramen Noodles Chinese noodles Other noodles Loaf bread, breakfast cereals, pizza/hamburger Other breads Snacks Potatoes and sweet potatoes Sweet potato noodles Tofu Starch jelly Nuts Kimchi Soybean paste Salt-fermented fish Yellow-green vegetables Other vegetables Pickles Fruits Low-fat meats High-fat meats Eggs Lean fish Fatty fish Dried anchovy Processed meats and fishes Shellfish Seaweeds Milk and dairy products Coffee and carbonated drinks Tea Other drinks Eigen value Percentage of variability explained

Dietary pattern Animal– food

Rice– vegetable

Noodle– bread

0.17

0.39

0.15

0.17

0.15 0.15 0.49 0.54 0.58 0.61 0.42

0.25 0.19

0.19 0.19

0.15 0.22 0.26 0.29

0.41 0.58 0.19 0.63 0.54 0.23 0.59 0.65 0.35 0.33 0.22 0.37 0.36 3.12 14.5

0.45 0.15 0.52 0.19 0.50 0.62 0.32 0.59 0.60 0.33 0.35 0.24 0.24 0.22 0.16 0.42

0.37 0.25 0.19 0.30 0.15 0.26 0.22

0.18 0.16

0.22 0.15 0.19

0.19 0.21 0.44 0.24

3.06 5.7

2.24 4.6

* Factor loadings are equivalent to simple correlations between the food items and the dietary patterns. Factor loadings less than 0.15 are not shown for simplicity.

these products. The scores represent standardized variables with a mean ¼ 0 and a standard deviation ¼ 1. A high factor score for a given dietary pattern indicated a high intake of the food groups constituting that food pattern, and a low score indicated a low intake of those food groups. All analyses were performed with a ¼ 0.05 significance level with SAS 9.1 (SAS Institute, Cary, NC, USA). Dietary patterns were identified with a principal components analysis (eigenvalue >1.25, Varimax rotation) using the PROC FACTOR procedure. Relations among dietary patterns, sociodemographic variables, and lifestyle variables were analyzed using the Mantel-Haenszel chisquare test. Pearson’s correlation coefficients were calculated between these factors and energy-adjusted nutrient intake. Nutrient intake is highly correlated to energy intake, so energy-adjusted nutrient intakes were calculated using the regression residual method [29]. Associations between dietary patterns and health-related factors were analyzed using general linear regression analyses, controlled by sociodemographic factors, lifestyle factors, and energy intake. To determine the associations between dietary patterns and health-risk factors, we calculated the odds ratios and 95% confidence intervals from unconditional logistic regression models, which were controlled for age, occupation, family income, and education level.

Results Classification of dietary patterns We first classified the dietary patterns of Korean men through factor analysis, identifying three dietary patterns: the ‘‘animalfood’’ (greater intake of raw and processed meats, fish, and dairy

J. E. Lee et al. / Nutrition 27 (2011) 26–33

products), the ‘‘rice–vegetable’’ (greater intake of steamed rice, tofu, kimchi, soybean paste, yellow-green vegetables, vegetables, potatoes, sweet potatoes, salted-fermented fish, pickles, dried anchovies, and seaweed), and the ‘‘noodle–bread’’ (greater intake of instant noodles, noodles, Chinese noodles, and bread; Table 2). These three dietary patterns explained 24.8% of the overall variation in food intake.

Relation between nutrient intake and dietary pattern To characterize the identified dietary patterns by factor analysis of the nutrient intake data, we determined the relation between the factor score of each dietary pattern and nutrient intake (Table 3). After energy adjustment, the men who had a higher animal-food dietary pattern score had a positive association with most of the nutrients, except for carbohydrates and fiber intake. Similarly, the rice–vegetable dietary pattern had a highly positive association with calcium, phosphorus, iron, sodium, potassium, vitamin A, and folate, which are abundant in vegetable sources. However, individuals who had a higher noodle–bread dietary pattern score had a negative association with most nutrient intakes except for fat, due to the relatively high amounts of fat found in instant noodles, fried noodles, and bread compared with other staple foods in the Korean diet.

Associations between sociodemographic characteristics and lifestyle factors and dietary patterns We investigated how sociodemographic characteristics and lifestyle factors related to each of the dietary patterns (Table 4). Participants with higher animal-food and noodle–bread dietary pattern scores were generally younger and had higher education levels and incomes. In addition, participants with higher animalfood dietary pattern scores generally exercised regularly, took more nutritional supplements, and had lower rates of smoking. Participants with higher rice–vegetable dietary pattern scores were generally older, had lower educational levels, had lower incomes, and took more nutritional supplements. There was no association between dietary patterns and alcohol consumption.

Table 3 Relations between nutrient intake and dietary pattern score* Dietary pattern Animal–food

Rice–vegetable

Noodle–bread

Absolute Energy Absolute Energy Absolute Energy adjusted adjusted adjusted Energy Protein Fat Carbohydrate Fiber Calcium Phosphorus Iron Sodium Potassium Vitamin A Thiamin Riboflavin Folate Niacin Vitamin C * y

0.35y 0.58y 0.53y 0.13y 0.17y 0.48y 0.53y 0.47y 0.17y 0.45y 0.34y 0.38y 0.56y 0.35y 0.62y 0.29y

0.61y 0.45y 0.53y 0.07y 0.35y 0.47y 0.32y 0.00 0.31y 0.19y 0.18y 0.49y 0.16y 0.63y 0.11y

0.41y 0.49y 0.29y 0.37y 0.67y 0.58y 0.56y 0.65y 0.56y 0.63y 0.53y 0.50y 0.48y 0.63y 0.46y 0.57y

0.29y 0.00 0.02 0.59y 0.42y 0.43y 0.53y 0.45y 0.52y 0.38y 0.31y 0.27y 0.47y 0.23y 0.39y

0.48y 0.40y 0.51y 0.41y 0.17y 0.28y 0.34y 0.33y 0.20y 0.27y 0.22y 0.39y 0.40y 0.23y 0.32y 0.14y

0.04z 0.26y 0.16y 0.20y 0.04z 0.18y 0.07y 0.05z 0.16y 0.02 0.01 0.04z 0.11y 0.15y 0.17y

All nutrients were adjusted with regard to energy by the residual method. P < 0.0001, z P < 0.05.

29

Relation between health-related factors and dietary patterns This study further analyzed the data to examine the relations between dietary patterns and health-related factors (Table 5). The animal-food dietary pattern had a positive association with BMI and WC, which were related to obesity and abdominal obesity. In addition, this dietary pattern showed a positive association with LDL cholesterol levels but a negative association with HDL cholesterol levels. As a result, the animal-food dietary pattern showed a positive association with TC. This pattern also had a negative association with systolic blood pressure. Unlike the animal-food dietary pattern, the rice–vegetable dietary pattern was positively associated with systolic blood pressure and negatively associated with TC and LDL cholesterol. The noodle–bread dietary pattern was positively associated with TC. Relation between dietary patterns and health-risk factors This study showed that, in Korean men, different dietary patterns were associated with different profiles of health-related factors. Because these factors may increase the risks of chronic diseases, we investigated whether each dietary pattern was related to diseases such as obesity, hypertension, hypercholesterolemia, and hypertriglyceridemia (Table 6). After adjusting for sociodemographic factors, the odds ratios from the lowest to the highest quintiles of the animal-food dietary pattern score were 1.0 to 1.59 for obesity and 1.0 to 1.92 for hypercholesterolemia. The odds ratios across increasing quintiles of the rice–vegetable dietary pattern score were 1.0 to 1.47 for hypertension. In addition, the risk of abdominal obesity and hypercholesterolemia across the quintiles of the noodle–bread dietary pattern ranged from 1.0 to 1.38 and 1.0 to 1.48, respectively. These results showed that the animalfood and noodle–bread dietary patterns were associated with increased risks of obesity and abdominal obesity, respectively, and hypercholesterolemia and that the rice–vegetable dietary pattern was associated with increased risk of hypertension. Discussion Lifestyles, dietary patterns, and the prevalence of chronic diseases changed drastically after the industrialization of Korea. Before industrialization, only a few food sources were available to the general population, and malnutrition was a leading public health problem. However, after industrialization, the general population acquired access to diverse food sources, which improved the quantity and quality of the diet [37,38]. Recently, the intake of fast food and Western food has increased along with the prevalence of obesity [39]. Other research has shown that fast food–induced obesity can increase the risk of several chronic diseases [40]. Several studies have shown a strong relation between diet and chronic diseases such as diabetes, cardiovascular diseases, and cancer [4,17,21,36,41]. The WHO has suggested that each country identify its own dietary patterns to prevent chronic diseases [7]. Other Western countries have attempted to identify local dietary patterns to suggest a healthy dietary pattern for citizens [12,14,17,23]. However, very few studies have sought to identify the Korean dietary pattern or to recommend a healthy Korean diet. This is the first study to identify the dietary patterns of Korean men. In it, we sought to determine the relations between these dietary patterns and health-risk factors in Korean men. From the results, we could suggest a healthy dietary pattern for Korean men. This study identified three dietary patterns among Korean men: animal-food, rice–vegetable, and noodle–bread. Traditional

30

Table 4 Sociodemographic and lifestyle characteristics by quintiles for each dietary pattern score Dietary pattern Animal–food

* y z

Noodle–bread

2

3

4

5 (high)

1 (low)

2

3

4

5 (high)

1 (low)

2

3

4

5 (high)

56.1 (9.0)

51.9 (8.7)

50.0 (8.1)

48.5 (7.4)

47.6z (6.8)

48.9 (8.0)

49.3 (7.7)

50.8 (8.5)

52.2 (9.0)

53.0z (9.0)

53.5 (8.8)

51.2 (8.6)

50.1 (8.6)

49.3 (8.1)

50.0z (8.2)

41.4 26.7 25.6 6.3

24.8 28.0 31.8 15.5

13.5 22.9 42.9 20.8

9.4 20.1 41.7 28.9

7.7z 15.1 42.0 35.2

13.2 20.3 39.4 27.2

17.7 20.3 37.6 24.4

19.1 22.9 38.1 19.9

21.4 24.0 35.2 19.4

25.3z 25.1 33.8 15.9

27.3 25.6 31.6 15.6

22.6 22.0 37.3 18.2

15.9 23.8 38.7 21.6

14.4 22.6 35.9 27.1

16.6z 18.7 40.5 24.3

52.8 30.0 11.2 6.0

36.2 34.6 17.2 12.0

19.6 35.2 22.8 22.4

12.5 31.1 28.1 28.3

11.6z 26.9 26.1 35.5

23.0 33.0 23.6 20.4

23.1 29.8 22.5 24.5

25.7 31.6 20.2 22.5

27.6 31.8 19.9 20.8

34.1z 31.8 18.9 15.3

35.4 30.1 17.0 17.4

27.5 33.1 21.5 17.9

25.3 32.0 22.8 19.9

22.6 30.3 22.6 24.5

22.6z 32.5 21.2 23.8

12.0

13.7

15.3

16.4

16.5x

12.9

13.6

14.9

16.6

16.0jj

14.1

13.9

13.8

13.9

18.2

19.6 69.1 11.3

18.9 71.2 9.9

19.6 71.2 9.2

17.2 75.7 7.1

18.2 74.6 7.3

18.3 72.1 9.6

15.5 75.4 9.1

23.4 69.0 7.7

18.5 71.9 9.7

17.8 73.4 8.8

19.1 72.0 9.0

18.8 72.6 8.7

19.2 71.1 9.8

21.7 71.4 7.0

14.8 74.7 10.5

18.5 25.0 5.9 50.6

17.8 28.7 5.3 48.3

20.7 31.8 4.6 42.9

22.0 29.1 4.3 44.6

17.3jj 31.6 4.3 46.7

18.7 27.0 5.7 48.5

19.2 32.5 4.3 44.1

20.9 30.7 4.6 43.8

20.3 28.7 4.6 46.4

17.2 27.4 5.2 50.2

19.4 28.8 4.6 47.2

19.5 29.4 4.8 46.4

19.9 29.8 4.1 46.2

22.4 27.4 4.8 45.5

15.1 30.8 6.3 47.8

9.6

22.8

27.8

27.8

27.6z

23.3

24.2

22.8

24.2

21.2

20.5

26.7

24.4

22.5

21.5

Mean (SD), tested by general linear regression. Percentage, tested by the Mantel-Haenszel chi-square test. P for trend <0.0001, x P for trend <0.01, jj P for trend <0.05.

J. E. Lee et al. / Nutrition 27 (2011) 26–33

Age(y)* Educationy Elementary school Middle school High school College Family incomey <1 000 000 Won 1 000 000–1 990 000 Won 2 000 000–2 990 000 Won >3 000 000 Won Nutritional supplementy Yes Alcohol consumptiony No Quit Current Smokingy Never Past Sometimes Current Regular exercisey Yes

Rice–vegetable

1 (low)

24.2 (2.9) 83.5 (7.5) 114.8 (15.4) 75.1 (11.0) 201.4y (38.4) 174.6 (131.3) 120.9 (36.0) 48.4 (12.2) 24.2 (2.9) 83.2 (7.2) 113.7 (14.5) 74.6 (10.3) 199.0 (34.6) 167.2 (130.8) 119.8 (31.0) 47.9 (11.4) 162.3 (124.3)

106.5 (34.6)

50.6 (13.1)

Triacylglycerol (mg/dL)

LDL cholesterol (mg/dL)

HDL cholesterol (mg/dL)

BMI, body mass index; DBP, diastolic blood pressure; HDL, high-density lipoprotein; LDL, low-density lipoprotein; SBP, systolic blood pressure; WC, waist circumference * Values were analyzed by general linear regression, which were adjusted for age (y). Values are presented as mean (SD). y P for trend <0.0001, z P for trend <0.01, x P for trend <0.05.

187.5 (37.4)

76.7 (9.9) DBP (mmHg)

Total cholesterol (mg/dL)

119.3 (16.2) SBP (mmHg)

82.2 (7.7) WC (cm)

4 3

24.1 (2.8) 82.8 (7.5) 114.0 (15.0) 74.5 (10.6) 198.4 (35.6) 159.0 (108.0) 120.3 (33.1) 48.0 (11.2) 24.0 (3.0) 82.9 (7.9) 115.2 (15.1) 75.4 (10.8) 196.3 (36.1) 164.7 (113.9) 117.3 (34.3) 47.8 (12.2)

2 1 (low)

23.8 (2.9) 82.6 (7.5) 117.1 (16.1) 76.0 (10.8) 194.5 (36.5) 159.9 (108.8) 114.9 (33.5) 48.7 (11.3) 23.9 (3.0) 83.3 (7.6) 117.8y (16.1) 75.9 (10.7) 195.1x (35.8) 169.1 (132.0) 114.1y (32.8) 49.6 (12.6)

5 (high) 4

23.8 (2.8) 82.7 (7.4) 114.9 (15.3) 74.8 (10.6) 195.1 (37.2) 162.5 (118.2) 115.9 (34.7) 48.3 (11.7) 24.2 (2.9) 83.2 (7.6) 114.9 (15.4) 75.9 (10.8) 199.4 (36.0) 165.4 (106.0) 120.0 (34.3) 47.8 (11.5)

3 2

24.3 (2.8) 83.0 (7.3) 114.0 (15.1) 74.8 (11.0) 199.3 (36.6) 159.1 (109.9) 121.5 (33.8) 47.6 (11.3) 24.1 (3.0) 82.9 (7.8) 113.2 (14.0) 74.2 (10.4) 200.8 (35.7) 169.4 (127.3) 121.7 (32.1) 47.6 (11.0)

1 (low)

24.7x (2.8) 84.2x (6.9) 112.6z (13.9) 74.6 (10.9) 205.1y (35.8) 169.3 (125.9) 127.5y (33.0) 46.1z (10.0)

5 (high) 4

24.4 (2.8) 83.2 (7.3) 113.4 (14.6) 74.9 (11.1) 203.7 (35.1) 167.8 (108.3) 124.2 (32.7) 47.8 (11.2) 24.2 (2.8) 83.2 (7.5) 114.0 (14.8) 74.6 (10.6) 199.2 (34.9) 162.4 (108.6) 119.8 (31.8) 47.7 (11.4)

3 2

23.8 (3.0) 82.2 (8.1) 115.5 (15.8) 74.8 (10.9) 194.2 (35.4) 163.7 (127.0) 115.0 (32.2) 48.7 (11.9)

1 (low)

23.2 (2.9)

Noodle–bread Rice–vegetable Animal–food

Quintile of dietary pattern score

Table 5 Health-related characteristics by quintile of dietary pattern score*

BMI (kg/m2)

5 (high)

J. E. Lee et al. / Nutrition 27 (2011) 26–33

31

Korean foods include mainly steamed rice (refined, whole, or mixed), noodles, or gruels as staple foods, with diverse side dishes, such as kimchi, pot stews, soups, tofu, fish, meats, and vegetables [37,38]. Therefore, dietary patterns were determined based on the types of staple foods and/or side dishes. Among the three dietary patterns defined, the rice–vegetable dietary pattern was the closest to the Korean traditional dietary pattern, namely steamed rice with vegetable-based side dishes. The animal-food dietary pattern consisted of steamed rice with side dishes containing larger portions of meat and fish instead of vegetables. The noodle–bread dietary pattern consisted mainly of noodles or bread as a staple food, with few side dishes. In addition, a higher intake of fast foods was found in this dietary pattern. In determining associations among the dietary patterns and health-risk factors, we found the animal-food dietary pattern was highly associated with obesity and hypercholesterolemia. This pattern was characterized by a high intake of animal-based foods, which contain relatively high amounts of fat. Even though the average amount of meat intake in Korea is lower than in Western countries, the meat intake has increased about 1.5 times in the past decade [42]. The Korea National Health and Nutrition Examination Survey (KNHANES) showed that animal-origin foods were one of the main sources of fat in the Korean diet [42]. Several investigations have shown that the Western dietary pattern, based on animal-origin foods, is highly correlated with obesity, hypertension, and cardiovascular disease [16,21,36,43,44]. In addition, other studies have reported that the Western dietary pattern (which contains large amounts of fat) is positively associated with C-reactive protein, homocysteine, fasting glucose, and insulin and negatively associated with blood carotenoid and HDL cholesterol [36,45,46]. It may therefore be prudent to reduce the amount of animal food intake to prevent obesity and cardiovascular disease in Korea. The rice–vegetable dietary pattern is very similar to the traditional Korean diet. Other investigations have suggested that a vegetable-based diet with a low energy density is considered a healthy diet [47]. Still other studies have reported that a vegetable or fiber-rich dietary pattern is negatively correlated to high blood lipid profiles and positively correlated to HDL cholesterol [36,48,49]. In addition, the Dietary Approach to Stop Hypertension and the MyPyramid (published by the US Department of Agriculture) have shown that a vegetable-based dietary pattern decreases the risk of hypertension, cancer, and myocardial infarction [50,51]. However, even though our participants were Korean men who appeared healthy and had not been diagnosed with, or treated for, chronic disease, the rice–vegetable dietary pattern was still associated with an increased risk of hypertension. The increased risk persisted even after adjustment for age. Such an increase in risk might be associated with high sodium intake. The WHO has reported that a high salt intake is associated with an increased risk of high blood pressure and has presented evidence for a causal relation between salt intake and cardiovascular disease [52]. Another study has shown that the ‘‘Japanese dietary pattern,’’ having a higher intake of soybean, fish, seaweed, vegetables, fruit, and green tea, has a positive correlation to the prevalence of hypertension in Japan because of the high sodium intake [21]. In addition, the KNHANES in 2005 showed that a Korean’s typical salt intake per day was 13.4 g, which is three times higher than the WHO recommendation of less than 5 g/d [42,52]. The KNHANES also reported that kimchi, soybean paste, salted seafood, and pot stews contained relatively high amounts of salt. Therefore, the association between the

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J. E. Lee et al. / Nutrition 27 (2011) 26–33

Table 6 Association between dietary patterns and health-risk factors* Quintile of each dietary pattern score

Animal-food Obesity Abdominal obesity Hypertension Hypercholesterolemia Hypertriglyceridemia Rice–vegetable Obesity Abdominal obesity Hypertension Hypercholesterolemia Hypertriglyceridemia Noodle–bread Obesity Abdominal obesity Hypertension Hypercholesterolemia Hypertriglyceridemia * y

1 (low)

2

3

4

5 (high)

1.00 1.00 1.00 1.00 1.00

1.33 0.94 0.80 1.08 0.88

(1.05–1.68) (0.71–1.24) (0.58–1.09) (0.74–1.57) (0.68–1.13)

1.38 0.98 0.74 1.46 0.94

(1.09–1.75) (0.73–1.30) (0.53–1.03) (1.02–2.10) (0.72–1.21)

1.46 0.87 0.84 1.62 1.01

(1.15–1.86) (0.65–1.17) (0.60–1.17) (1.13–2.33) (0.78–1.31)

1.59 1.06 0.69 1.92 1.00

(1.24–2.04)y (0.78–1.42) (0.48–1.00) (1.33–2.78)y (0.76–1.31)

1.00 1.00 1.00 1.00 1.00

1.05 0.95 1.38 1.21 0.78

(0.85–1.30) (0.72–1.24) (0.98–1.95) (0.89–1.63) (0.61–1.00)

1.14 1.01 1.34 1.18 0.99

(0.91–1.41) (0.77–1.32) (0.95–1.89) (0.87–1.61) (0.78–1.26)

0.86 0.85 1.20 0.95 0.92

(0.69–1.07) (0.64–1.12) (0.85–1.71) (0.69–1.32) (0.72–1.17)

1.06 1.07 1.47 0.90 1.08

(0.85–1.33) (0.81–1.40) (1.05–2.07)x (0.64–1.25) (0.84–1.37)

1.00 1.00 1.00 1.00 1.00

1.18 1.19 0.76 1.22 1.13

(0.94–1.47) (0.91–1.57) (0.56–1.03) (0.87–1.70) (0.89–1.44)

1.08 0.88 0.66 1.13 0.86

(0.86–1.36) (0.66–1.18) (0.48–0.91) (0.80–1.58) (0.66–1.11)

1.19 1.09 0.68 1.20 1.03

(0.95–1.49) (0.83–1.45) (0.49–0.94) (0.86–1.68) (0.80–1.32)

1.20 1.38 0.82 1.48 1.26

(0.96–1.50) (1.05–1.81)x (0.60–1.12) (1.07–2.05)z (0.99–1.61)

Odds ratio (95% confidence interval) was controlled for age, occupation, family income, and education level. P for trend <0.0001, z P for trend <0.01, x P for trend <0.05.

rice–vegetable dietary pattern and hypertension might be a result of the high salt intake [42]. The noodle–bread dietary pattern was characterized by greater intake of instant noodles, noodles, Chinese noodles, and bread, which mainly consists of carbohydrates, fat, seasoning, and sugar, so this dietary pattern was negatively related to most nutrients. Noodle soup and instant noodles contain large amounts of carbohydrate and fat and are usually served with a few side dishes, such as kimchi. In addition, this dietary pattern showed a higher intake of fast foods, such as hamburgers and pizza, which usually contain a high energy but few nutrients. This is likely the reason the noodle–bread dietary pattern was strongly associated with an increased risk of abdominal obesity and hypercholesterolemia. This study contains several strengths. It was populationbased and used a validated food-frequency questionnaire. In addition, it is the first to identify dietary patterns among Korean men. However, it has some limitations. First, although factor analysis is a widely used technique in nutritional epidemiology, this method as applied within this study arises from arbitrary decisions involved in selecting and grouping foods for analysis derived from the questionnaire. However, the derived dietary patterns accounted for 24.8% of the total variance, which is comparable to findings in other studies [17,18]. Other investigators have also established the validity of such a dietary pattern approach by testing internal validity [53,54]. Second, because this study analyzed baseline data, it was inconclusive regarding identified dietary patterns that increase health-risk factors, such as obesity, abdominal obesity, hypercholesterolemia, and hypertension. It covered only a single period, so it is possible dietary patterns have changed. Therefore, a prospective study or trial should be undertaken to confirm ongoing associations between dietary patterns and health-risk factors. Third, alcohol consumption and exercise were only roughly assessed, even though these factors have been shown to be associated with health-risk factors. It may be relevant to note for future studies that alcohol intake was found to be higher than 10 g/d in Korean men [55]. Our study showed that the animal-food and noodle–bread dietary patterns were positively associated with obesity,

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