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Food intake patterns and cardiovascular risk factors in Japanese adults: analyses from the 2012 National Health and nutrition survey, Japan

  • Nay Chi Htun1,
  • Hitomi Suga1,
  • Shino Imai1,
  • Wakana Shimizu1 and
  • Hidemi Takimoto1Email author
Nutrition Journal201716:61

https://doi.org/10.1186/s12937-017-0284-z

Received: 19 June 2017

Accepted: 12 September 2017

Published: 19 September 2017

Abstract

Background

There is an increasing global interest in the role of Japanese diet as a possible explanation for the nation’s healthy diet, which contributes to the world’s highest life-expectancy enjoyed in Japan. However, nationwide studies on current food intake status among general Japanese population have not been established yet. This study examined the association between food intake patterns and cardiovascular risk factors (CVRF) such as waist circumference (WC), body mass index (BMI), blood pressure (SBP, DBP), HbA1c and blood lipid profiles among general Japanese adults.

Methods

De-identified data on the Japan National Health and Nutrition Survey (NHNS) 2012 with a total of 11,365 subjects aged 20–84 years were applied. Food intake patterns were derived by principal component analysis (PCA) based on 98 food groups. Generalized linear regression analysis was used to assess the relation between the food intake patterns and CVRF.

Results

We identified three food intake patterns: traditional Japanese, Westernized, and meat and fat patterns. Traditional Japanese pattern was significantly related to high WC and BMI in men, and high DBP in women. Westernized pattern was associated with lower SBP, but high total cholesterol and LDL cholesterol in both men and women. Meat and fat pattern was associated with high WC, high BMI, high blood pressure and blood lipid profiles in both men and women (trend P < 0.001).

Conclusion

The significant association between cardiovascular disease risks and three food intake patterns derived from the NHNS, showed a similar tendency to other dietary survey methods.

Keywords

Food intake patternCardiovascular risk factorsBlood pressureBlood lipid profilesJapaneseNational Health and nutrition survey (NHNS)

Background

Cardiovascular disease (CVD) is one of the major contributors to the global burden of disease, and is the leading cause of premature mortality [1]. The vast majority of cardiovascular disease is explained by conventional risk factors such as cigarette smoking, hypertension, obesity, diabetes, dyslipidemia, and unhealthy lifestyle behaviors including poor dietary habits, excessive caloric intake, physical inactivity, and psychosocial stressors [2, 3]. Along with lifestyle factors such as physical activity, diet is one of the most important modifiable risk factors [47], providing effective means to achieve healthy and nutritious diets are essential for cardiovascular disease prevention [8].

Japan is unique among developed countries because the prevalence of cardiovascular disease morbidity and mortality remain substantially lower despite having the same trend in cardiovascular risk factors (CVRF) (such as rise in serum cholesterol, etc.) as other developed countries [9, 10]. The world’s highest healthy life expectancy enjoyed in Japan may be partly explained by the Japanese diet. For example, a very recent cohort study found that the food intake patterns of Japanese adults who followed the government recommended food guide for the nation (the Japanese Spinning Top Food Guide 2005) at the baseline, had lower rates of mortality than those who didn’t [11]. And, another nationwide study in elderly Japanese has observed that improvement in dietary habits, such as yearly increase in vegetables and meat intake, may contribute to decreasing prevalence of anemia [12].

As dietary habits are influenced by lifestyle, socioeconomic and environmental factors such as family income, food prices, individual preferences, cultural beliefs, traditional single food- or nutrient-based approach may fail to take into consideration the complicated interaction and cumulative effects among nutrients. Therefore, overall assessment of food intake patterns, taking into account of the interactions, inter-correlations between nutrients and foods and their cumulative effects, has gained attention in the studies of the association between health and diseases [13].

Many epidemiologic cohort studies have been implemented to explain the correlation between food intake patterns and cardiovascular risk factors such as hypertension, obesity and blood lipid profiles [14, 15]. The scientific evidences have consistently shown that the food intake pattern rich in fruits, vegetables, fish and whole grains (known as healthy or prudent pattern) [1618], DASH diet (Dietary Approaches to Stop Hypertension) [19] and Mediterranean diet [2023] are favorable for reducing cardiovascular disease risks, whereas food intake patterns characterized by high fat and sugar or a meat-based diet have deleterious effects and have been associated with increased risks of obesity, type 2 diabetes, and cardiovascular disease [15, 24]. To date, only one cross-sectional study in Japanese reported that vegetable-rich diet pattern was significantly associated with favorable blood lipid profiles in women [25]. Most of the above mentioned cohort studies identified food intake pattern using intake data from semi-quantified food frequency questionnaires (FFQs), on limited populations. Because FFQs are developed to assess the habitual intakes of the specific population of research subjects, the food lists (5 to 350, median number 79) applied may not be able to reflect the intakes of the general population [26]. On the other hand, weighed dietary records are able to provide more details on actual intakes and provide more precise estimates of portion sizes than FFQs. The Japan National Health and Nutrition Survey (J-NHNS) is unique, as it is based on a single day dietary survey in which the survey participants are requested to weigh and record all foods consumed. Currently 2116 food items are available for use in the J-NHNS. Of these, 1789 food items are the same as those listed in the Standard Tables of Food Composition 2010 [27], and 50 food items are original for the survey. The foods are then grouped into 98 food groups, which has been consistently used since 2005 [28].

This study aimed to explore the food intake patterns and examine their association with cardiovascular risk factors such as waist circumference, body mass index (BMI), blood pressure, HbA1c level and blood lipid profiles among 11,365 Japanese aged 20–84 years, using the nationally representative data from J-NHNS conducted in year 2012, while controlling for a wide range of potential confounding factors.

Methods

Survey outlines of the 2012 J-NHNS

Out of the 2010 national census areas units, 475 areas stratified by prefecture were randomly extracted for the 2012 J-NHNS, consisting of 10 areas per prefecture (Tokyo: 15 areas). Approximately 50 households were included in each area. Participants were household members (aged 1 year and over) of all households residing in the selected area. Total number of households and family members aged 1 year and over in the 475 areas were approximately 23,750 and 61,000, respectively. Of the selected census areas, four alternative areas were re-selected to replace those unable to conduct this survey due to the influence of the Great East Japan Earthquake [28].

De-identified records on the 2012 J-NHNS with the permission of secondary use of data from Ministry of Health, Labor and Welfare were applied. A total of 11,365 subjects, 4686 men and 6679 women (pregnant and lactating mothers were excluded) aged 20–84 years who had a complete data on dietary intake, lifestyle factors, anthropological and blood pressure measurements, HbA1c measured in National Glyco-hemoglobin Standardization Program (NGSP) units (%), fasting blood lipid profiles [total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C)] were selected.

The dietary survey was conducted by semi-weighing of all foods consumed in the one-day dietary records of the household, with proportional distribution within the household members [29]. Information regarding the cooking status (boiled, roasted, etc.) of each food was recorded, and post-cooked nutrient values in the Standard Food Composition Tables 2010 were applied for estimating nutrient intakes. For foods categorized as “cereals” except bread, post-cooked weight of the food was applied as the intake food weight. Participants aged 20 years and above were asked to record the number of daily step counts measured with a pedometer as part of the physical examination. BMI was calculated by weight in kilograms divided by height in meters squared.

Definition of hypertension, diabetes, hypercholesterolemia and elevated LDL cholesterol

Hypertension was defined as either having a systolic blood pressure (SBP) of ≥140 mmHg or diastolic blood pressure (DBP) of ≥90 mmHg, currently under anti-hypertensive treatment, or previously diagnosed for hypertension. We defined diabetes based on HbA1c ≥6.5% or currently under anti-diabetic treatment, or previously diagnosed for diabetes. Subjects with hypercholesterolemia were defined as having serum total cholesterol level ≥ 240 mg/dL and subjects with elevated LDL cholesterol were defined as having serum LDL cholesterol level ≥ 140 mg/dL or subjects having lipid lowering medication for both. In the present study, anti-hyperlipidemia medication included both cholesterol-lowering medication and triglyceride-lowering medication.

Statistical analysis

The original 2116 food items used in the J-NHNS are categorized into 98 food groups [28]. Then food intake patterns were identified using principal component analysis (PCA) based on the 34 food groups reorganized from the original 98 food groups (Table 1). Analyses were done after excluding the subjects with total energy intake (kcal) under the 5th percentile (n = 1281, 1124 kcal) or above the 95th percentile (n = 1281, 2792 kcal). Eigen values > 1.5 were used to determine whether a factor should be considered as major food intake pattern. Varimax rotation was applied to review the correlations between variables and factors. Food groups with positive loadings in each pattern indicate the direct relationship and food groups with negative loadings shows the inverse relationship with that pattern. For each subject, the factor scores for each food intake pattern were calculated by summing the intakes of food items weighted by their factor loading [13]. Factor scores were then categorized into four groups based on the quartiles of factor scores. Spearman’s correlation coefficients were calculated between the factor scores of each pattern and energy-adjusted nutrient intakes so that the correlation between food intake patterns and specific nutrient intakes could be studied.
Table 1

Factor loadings and explained variation in food groups

Food groups

Factor1

Factor2

Factor3

34 Food groups used in dietary pattern anaylsis

Original 98 food items from J-NHNS [food group number]

Traditional Japanese

Westernized

Meat and fat

Rice

Rice [1]

0.149

−0.667

−0.021

Rice products

Rice products [2]

−0.003

0.061

−0.030

Flour and wheat products

Flour and wheat [3], other wheat products [4]

−0.064

−0.038

0.399

Bread and danish

bread [4], danish [5]

−0.207

0.638

0.006

Noodles (includes soba)

Udon, chinese noodles [6] instant chinese noodles [7] pasta [8] soba (buckwheat noodles) [10]

−0.063

0.224

0.282

Corn products and other grains

Corn products [11] other grains [12]

0.022

0.058

−0.022

Potatoes

Sweet potatoes [13], potatoes [14], other starchy roots and tubers [15], processed starch [16]

0.323

−0.042

0.051

Sugars and sweeteners

Sugars and sweeteners [17]

0.394

0.203

0.098

Beans

Soy beans and soybean products [18], Tofu [19], soy bean curd [20], Natto [21], other soy bean products [22], other beans [23]

0.381

−0.043

−0.097

Seeds and nuts

seeds and nuts [24]

0.163

0.115

−0.035

Fresh vegetables

tomato [25] carrot [26] spanich [27] green pepper [28] other brightly colored vegetables [29] cabbage [30] cucumber [31] radish [32] onion [33] Chinese cabbage [34] other light-colored vegetables [35]

0.577

0.049

0.162

Vegetable juice

vegetable juice [36]

0.006

0.116

−0.010

Salted or pickled vegetables

leafy vegetables pickles [37] pickled radish and other salted or pickled vegetables [38]

0.261

−0.148

−0.177

Fresh fruit

Strawberry [39], citrus fruits [40], banana [41], apples [42], other fruits [43]

0.389

0.333

−0.288

Jam

Jam [44]

0.057

0.356

−0.041

Fruit juice

Fruit juice [45]

−0.055

0.036

0.050

Mushrooms

Mushrooms [46]

0.372

0.085

0.117

Seaweeds

Seaweeds [47]

0.262

−0.033

−0.049

Fish and shellfish

Mackerel, sardines [48], salmon and trout [49], red snapper, flounder and flatfishes [50], tuna, swordfishs [51], other raw fishes [52], shellfishes [53], squid and cuttlefish [54], prawns and crabs [55], processed fishes and seafood (salted, dried) [56], canned fish and seafoods [57] tsukudani [58] fish paste [59], fish ham and sausages [60]

0.389

−0.144

−0.189

Meat

Beef [61], pork [62], ham and sausages [63], other meats [64], chicken [65], other poultry [66], innards [67], whale [68], other processed meat and meat products [69]

−0.055

−0.114

0.623

Eggs

Eggs [70]

0.095

−0.114

0.238

Milk, cheese, and yogurt

Milk [71], cheese [72], and yogurt [73]

0.144

0.420

−0.160

Other milk products

Other dairy products [74], other milks [75]

−0.076

0.045

0.034

Butter and margarine

Butter [76], margarine [77]

−0.160

0.484

0.164

Other fats

Vegetable oils [78], animal fats [79], other fats [80]

−0.032

−0.162

0.573

Confectionaries

Japanese confectioneries (Wagashi) [81], cakes and pastries [82], biscuits [83], candies [84], other confectioneries [85]

−0.019

0.203

−0.139

Alcohol drinks

Japanese sake [86], beer [87], whiskey, wine and other alcoholic beverages [88]

0.028

−0.169

0.247

Tea

Tea [89]

0.269

−0.003

−0.232

Coffee and cocoa

Coffee and cocoa [90]

−0.052

0.282

0.141

Other beverages

Other beverages [91]

−0.091

−0.018

0.192

Sauce, mayonnaise

Sauce [92], salt [94], mayonnaise [95], other seasonings [97]

0.161

0.146

0.389

Soy sauce

Soy sauce [93]

0.554

−0.014

0.242

Miso

Miso [96]

0.397

−0.309

−0.139

Spices

Spices [98]

0.137

0.019

0.149

Explained variation in food groups (%)

2.080

2.007

1.729

Factor loadings (absolute values) > 0.3 were shown in bold characters

A detailed description of food groups used in NHNS were shown on page 57–63 (Table 1) of reference [28]

Generalized linear models was used to assess the association of adherence to three major food intake patterns with waist circumference, body mass index (BMI), systolic and diastolic blood pressure, HbA1c and blood lipid profiles (TC, LDL-C and HDL-C) after adjustment with other potential confounding variables; such as age in years, BMI, step counts/day (as continuous variables), smoking habit (1: current smoker, 2: past smoker, 3: non smoker), drinking habit (1: Yes, 2: No), and, medication status (hypertension, diabetes, and dyslipidemia, 1:Yes, 2: No). Trend association across quartile categories of each food intake pattern was assessed by using Cochrane-Armitage trend test for categorical variables and generalized linear regression analysis for continuous variables. Logistic regression analysis was used to determine the association of dietary patterns with the risk of hypertension, hypercholesterolemia and elevated LDL cholesterol. The odds ratios (OR) were estimated for each quartile compared with the lowest quartile of each food intake pattern as the reference. The association analyses were performed separately in men and women. Two-sided P values <0.05 were regarded as statistically significant. All statistical analyses were performed using Statistical Analysis System 9.3 (SAS Institute, Cary, NC, USA).

Results

Food intake pattern analysis

We identified three food intake patterns by principal component analysis: (a) “traditional Japanese” (greater intake of miso, soy sauce, fresh vegetables and fruits, beans and potatoes), (b) “Westernized” (greater intake of bread, dairy, butter and margarine, jam, low intake of rice and miso), (c) “Meat and fat” (high intake of meat, fat, sauce and mayonnaise, wheat and wheat products). These three food intake patterns accounted for 2.1%, 2.0% and 1.7%, respectively, explained 5.8% of the total variance in food intake (Table 1).

Spearman’s correlation coefficients showed positive correlations between nutrients and traditional Japanese pattern, while Westernized pattern showed positive correlation with total fat intake, micronutrients except vitamin D, vitamin B12, sodium and iron, and negative correlation with carbohydrate, ω-3 fatty acid. Meat and fat patterns showed positive correlation with total energy, protein and fat intake, ω-6 fatty acids, vitamin B1, sodium and iron, and negative correlation with other micronutrients (Table 2).
Table 2

Correlation coefficients abetween subject characteristics, dietary energy and nutrient intakes and each factor

 

Men

Women

Traditional Japanese

Westernized

Meat and fat

Traditional Japanese

Westernized

Meat and fat

 Age at survey (yrs)

0.321

0.108

−0.378

0.354

0.024

−0.316

 Height (cm)

−0.133

−0.011b

0.253

−0.162

0.063

0.209

 Body weight (kg)

−0.007b

−0.019b

0.152

−0.008b

−0.004b

0.080

 Abdominal circumference (cm)

0.095

0.003b

−0.025

0.127

−0.032

−0.078

 BMI

0.071

−0.020b

0.016b

0.086

−0.047

−0.039

 Steps per day

0.022b

−0.008b

0.125

0.003b

0.063

0.123

 Systolic blood pressure (mmHg)

0.112

−0.028

−0.091

0.207

−0.038

−0.135

 Diastolic blood pressure (mmHg)

−0.017b

−0.042

0.056

0.107

−0.001b

−0.027

 Serum total cholesterol (mg/dL)

−0.027

0.023b

0.129

0.094

0.123

−0.009b

 Serum HDLcholesterol (mg/dL)

−0.003b

−0.004b

0.092

−0.048

0.100

0.093

 Serum LDL cholesterol (mg/dL)

−0.063

0.051

0.094

0.056

0.093

−0.011b

 HbA1c (%)

0.156

0.049

−0.142

0.193

0.009b

−0.120

Energy and nutrient intakes

 Energy (kcal)

0.357

−0.065

0.313

0.405

0.102

0.234

 Protein (g)

0.534

0.011

0.212

0.534

0.076

0.156

 Fat (%energy)

0.090

0.138

0.469

0.105

0.209

0.429

 ω-3 fatty acids (g)

0.338

−0.117

0.008b

0.348

−0.091

0.008b

 ω-6 fatty acids (g)

0.153

0.016b

0.448

0.194

0.046

0.397

 Carbohydrates (%energy)

0.331

−0.083

0.008b

0.416

0.037

−0.047

 Dietary fiber (g)

0.680

0.226

−0.008b

0.715

0.239

−0.013b

 Vitamin A (μgRAE)

0.393

0.141

0.026

0.417

0.149

0.015b

 Vitamin D (μg)

0.392

−0.072

−0.207

0.374

−0.053

−0.168

 Vitamin B1 (mg)

0.322

0.150

0.239

0.393

0.182

0.213

 VitaminB2 (mg)

0.449

0.165

−0.002b

0.475

0.195

−0.043

 Vitamin B6 (mg)

0.600

0.030

0.068

0.631

0.088

0.024

 Vitamin B12 (μg)

0.353

−0.074

−0.157

0.351

−0.051

−0.149

 Folate (μg)

0.678

0.097

−0.075

0.708

0.119

−0.105

 VitaminC (mg)

0.522

0.174

−0.154

0.552

0.180

−0.176

 Sodium (mg)

0.519

0.025

0.184

0.555

0.029

0.152

 Potassium (mg)

0.751

0.205

−0.020b

0.768

0.240

−0.057

 Calcium (mg)

0.514

0.307

−0.107

0.531

0.322

−0.120

 Iron (mg)

0.692

0.018b

0.038

0.708

0.044

0.009b

aSpearman’s correrlation analysis

bnot significant

General characteristics of the subjects by food intake patterns

Table 3 shows the general characteristics of the study subjects according to quartile categories of each food intake pattern score. Subjects with a higher score for the traditional Japanese pattern were older, had higher BMI and waist circumference, higher SBP, lower LDL-C, higher proportion of having anti-hypertensive, anti-diabetic, anti-lipid medication and were likely to be past smoker in men and less likely to have smoking and drinking habits in women. Subjects with a higher score for the Westernized pattern were older, had lower BMI and waist circumference, higher LDL-C, were likely to have anti-hypertensive and anti-lipid medications, and were likely to have drinking habit than the group with lower Westernized pattern score. Participants with higher meat and fat pattern score were younger, had higher step counts, less likely to take anti-hypertensive, anti-diabetic and anti-lipid medications, but more likely to have smoking and drinking habits.
Table 3

Subject charcterisics by gender, according to quartiles of the three food intake pattern scores

 

Traditional Japanese

Westernized

Meat and fat

Q1

Q2

Q3

Q4

 

Q1

Q2

Q3

Q4

 

Q1

Q2

Q3

Q4

Mean

S.D.

Mean

S.D.

Mean

S.D.

Mean

S.D.

p for trend

Mean

S.D.

Mean

S.D.

Mean

S.D.

Mean

S.D.

p for trend

Mean

S.D.

Mean

S.D.

Mean

S.D.

Mean

S.D.

p for trend

Men (N)

894

 

1059

 

1224

 

1509

  

1696

 

1125

 

908

 

957

  

947

 

1015

 

1185

 

1539

  

 Age at survey (yrs)

50.0

16.4

55.9

15.9

60.3

14.9

63.3

13.4

<0.001

56.4

15.9

57.7

16.1

59.8

15.7

60.9

14.6

<0.001

66.7

13.6

61.1

15.0

57.3

15.1

52.1

15.2

<0.001

 Height (cm)

167.5

6.5

166.7

7.0

166.0

6.7

165.3

6.8

<0.001

166.3

7.1

166.2

6.8

166.1

6.7

166.1

6.3

0.900

163.7

6.7

165.6

6.8

166.6

6.7

167.9

6.5

<0.001

 Body weight (kg)

66.8

11.5

65.5

10.5

65.2

10.4

65.7

10.1

0.006

66.1

11.1

65.5

10.5

65.5

9.8

65.6

10.3

0.370

63.3

10.0

65.2

10.3

65.8

10.6

67.4

10.7

<0.001

 Waist circumference (cm)

85.5

9.4

85.2

9.2

85.7

8.7

86.7

8.2

<0.001

85.9

8.9

85.5

9.0

86.1

8.6

86.0

8.7

0.479

85.9

8.7

86.1

8.7

85.5

8.9

85.9

8.9

0.457

 BMI

23.8

3.5

23.5

3.3

23.6

3.1

24.0

3.0

0.004

23.8

3.3

23.7

3.2

23.7

3.1

23.7

3.2

0.483

23.6

3.1

23.8

3.1

23.7

3.3

23.9

3.3

0.120

 Steps per day

6958

4514

7092

4328

7065

5208

6954

4082

0.834

7051

4915

6994

4264

6919

4227

7061

4428

0.890

6276

4262

6839

5236

7193

4236

7448

4360

<0.001

 Systolic blood pressure

132.6

18.0

133.6

17.6

136.6

17.5

136.9

17.1

<0.001

135.9

18.1

134.9

17.3

134.4

17.2

135.3

17.5

0.171

137.2

16.8

136.0

17.6

135.1

17.7

133.7

17.8

<0.001

 Diastolic blood pressure

82.5

11.5

81.9

11.4

82.0

10.8

81.6

10.7

0.324

82.5

11.3

81.8

10.9

81.4

11.2

81.8

10.5

0.098

81.0

10.8

81.4

10.7

82.2

11.0

82.8

11.4

0.000

 Serum total cholesterol

196.4

34.4

197.5

33.3

194.3

34.5

194.7

33.6

0.083

194.9

34.2

195.3

33.7

195.8

33.4

196.8

34.2

0.576

188.1

33.4

194.3

33.7

196.2

33.6

200.5

33.8

<0.001

 Serum HDLcholesterol

54.4

14.2

55.0

15.1

54.9

14.4

54.7

15.7

0.819

54.9

15.4

55.1

14.7

54.4

15.0

54.5

14.2

0.627

53.2

14.4

53.8

14.1

55.0

15.1

56.2

15.5

<0.001

 Serum LDL cholesterol

117.5

31.4

116.6

30.3

113.5

31.2

112.8

29.6

<0.001

113.2

31.1

114.5

30.5

115.3

30.3

117.2

30.0

0.011

109.2

30.0

114.7

30.1

114.9

30.0

118.0

31.3

<0.001

 HbA1C

5.7

0.8

5.7

0.8

5.8

0.8

5.8

0.7

<0.001

5.8

0.8

5.8

0.8

5.8

0.7

5.8

0.9

0.107

5.9

0.8

5.9

0.8

5.8

0.8

5.7

0.8

<0.001

 Anti-hypertensive medication (%)

21.3

 

26.7

 

33.2

 

35.4

 

<0.001

28.0

 

30.3

 

32.7

 

31.3

 

0.011

42.1

 

33.4

 

28.0

 

22.3

 

<0.001

 Anti-diabetic medication (%)

5.6

 

8.4

 

9.3

 

9.5

 

0.001

6.9

 

8.5

 

9.1

 

10.4

 

0.001

11.9

 

10.2

 

7.8

 

5.7

 

<0.001

 Anti-lipid medication (%)

8.4

 

11.0

 

12.9

 

14.9

 

<0.001

9.2

 

11.7

 

14.6

 

16.0

 

<0.001

14.8

 

15.0

 

11.9

 

9.2

 

<0.001

 Current smoking (%)

42.2

 

32.8

 

28.3

 

21.5

 

<0.001

34.2

 

29.7

 

25.3

 

26.2

 

<0.001

21.8

 

25.1

 

32.7

 

35.5

 

<0.001

 Past smoking (%)

30.3

 

37.8

 

43.1

 

48.6

 

<0.001

37.4

 

40.9

 

45.2

 

44.5

 

<0.001

48.5

 

43.0

 

40.6

 

36.1

 

<0.001

 Current drinking (%)

37.1

 

33.8

 

36.6

 

34.8

 

0.271

43.2

 

36.5

 

32.5

 

23.4

 

<0.001

24.7

 

31.6

 

37.8

 

42.9

 

<0.001

Women (N)

1589

 

1715

 

1747

 

1628

  

999

 

1715

 

1932

 

2033

  

2116

 

1923

 

1595

 

1045

  

 Age at survey (yrs)

49.2

15.3

56.4

15.8

59.9

14.1

64.1

11.9

<0.001

57.2

16.3

56.6

16.0

57.6

15.4

58.2

14.2

0.011

63.0

14.2

57.6

14.9

53.9

15.2

51.5

14.7

<0.001

 Height (cm)

154.9

6.3

153.7

6.7

153.3

6.7

152.1

6.2

<0.001

152.8

7.1

153.2

6.8

153.5

6.5

154.0

6.1

<0.001

151.7

6.7

153.6

6.5

154.5

6.3

155.2

6.0

<0.001

 Body weight (kg)

53.7

8.9

53.2

8.8

53.1

8.8

53.1

8.3

0.102

53.8

9.6

53.4

8.6

53.3

8.7

52.9

8.2

0.091

52.2

8.5

53.4

8.4

53.9

8.9

54.3

9.0

<0.001

 Waist circumference (cm)

80.5

10.3

81.3

10.2

81.8

9.8

82.8

9.7

<0.001

82.1

10.6

81.9

10.1

81.7

10.1

81.0

9.7

0.013

82.0

10.0

81.7

9.9

81.3

10.4

81.0

10.1

0.026

 BMI

22.4

3.7

22.6

3.6

22.6

3.5

23.0

3.4

<0.001

23.1

4.0

22.8

3.5

22.6

3.6

22.3

3.4

<0.001

22.7

3.5

22.6

3.5

22.6

3.7

22.6

3.6

0.837

 Steps per day

6450

3696

6101

3383

6366

3609

6465

3958

0.014

6096

4125

6242

3663

6233

3476

6651

3582

<0.001

5824

3706

6398

3559

6637

3588

6837

3766

<0.001

 Systolic blood pressure

122.8

18.7

127.8

19.1

130.1

18.7

133.3

18.4

<0.001

130.5

19.9

128.6

19.1

127.8

18.8

128.3

19.0

0.003

131.6

19.1

128.7

19.1

126.1

19.1

125.8

18.1

<0.001

 Diastolic blood pressure

75.3

10.9

77.1

10.7

78.0

10.7

78.3

10.3

<0.001

77.6

10.7

77.0

10.7

76.8

10.5

77.4

10.9

0.174

77.7

10.7

77.2

10.8

76.6

10.7

77.1

10.6

0.026

 Serum total cholesterol

200.3

34.9

203.5

34.5

207.2

34.3

206.9

34.0

<0.001

198.7

34.5

200.6

33.2

205.8

35.1

209.5

34.3

<0.001

204.3

34.7

206.1

33.8

204.1

34.6

203.0

35.2

0.096

 Serum HDLcholesterol

64.4

15.0

63.8

14.9

64.1

15.9

62.8

15.2

0.018

62.0

15.4

62.5

15.1

64.2

15.5

65.4

14.9

<0.001

62.2

15.0

63.6

15.3

64.7

15.2

66.0

15.7

<0.001

 Serum LDL cholesterol

116.2

31.1

118.2

30.7

119.7

30.0

119.5

30.2

0.004

114.0

30.0

115.8

29.4

119.6

31.0

121.7

30.9

<0.001

118.5

30.8

119.6

30.0

118.3

30.9

116.4

30.4

0.064

 HbA1C

5.6

0.6

5.7

0.7

5.7

0.6

5.8

0.7

<0.001

5.7

0.7

5.7

0.6

5.7

0.6

5.7

0.6

0.529

5.8

0.6

5.7

0.6

5.6

0.6

5.6

0.7

<0.001

 Anti-hypertensive medication (%)

15.7

 

26.3

 

26.4

 

32.7

 

<0.001

30.2

 

27.4

 

24.4

 

22.2

 

<0.001

33.9

 

25.4

 

19.5

 

16.9

 

<0.001

 Anti-diabetic medication (%)

3.2

 

4.0

 

4.2

 

5.3

 

0.002

4.1

 

4.4

 

3.8

 

4.3

 

0.496

5.1

 

5.0

 

2.8

 

2.8

 

<0.001

 Anti-lipid medication (%)

11.1

 

16.3

 

18.5

 

22.4

 

<0.001

15.1

 

17.1

 

16.9

 

18.3

 

0.021

21.2

 

18.5

 

13.7

 

11.6

 

<0.001

 Current smoking (%)

12.4

 

7.0

 

5.3

 

3.1

 

<0.001

7.0

 

7.3

 

6.4

 

6.9

 

0.351

4.9

 

5.6

 

8.2

 

11.3

 

<0.001

 Past smoking (%)

11.4

 

8.2

 

6.3

 

4.4

 

<0.001

7.5

 

7.1

 

7.6

 

7.9

 

0.229

4.8

 

7.5

 

9.3

 

10.5

 

<0.001

 Current drinking (%)

9.1

 

6.6

 

5.4

 

3.9

 

<0.001

8.6

 

8.2

 

5.7

 

3.8

 

<0.001

2.6

 

5.9

 

7.7

 

11.9

 

<0.001

For continuous variables, the general linear model was applied

For categorical variables, the Cochrane-Armitage trend test was applied

Significant P values <0.05 were shown in bold characters

Energy and nutrients intake across the quartiles of food intake patterns

We explored the relationship between nutrients intake and the food intake pattern scores by generalized linear model analysis (Table 4). For all three food intake pattern scores, higher scores were associated with higher total energy intake in both men and women. A higher traditional Japanese pattern score was significantly associated with higher intakes of protein, ω-3, ω-6 fatty acids, dietary fiber, vitamin A, D, B1, B2, B6, B12, C, folate, sodium, potassium, calcium and iron in both men and women. Higher Westernized pattern score was associated with higher intake of protein, fat, ω-6 fatty acids, dietary fiber, vitamin A, B1, B2, B6, C, folate, sodium, potassium, calcium, and lower intake of ω-3 fatty acids, carbohydrates, vitamin D and vitamin B12. Higher meat and fat pattern score was associated with higher intakes of protein, fat, ω-6 fatty acids, dietary fiber, vitamin B1, B2, B6, sodium, iron and lower intakes of ω-3 fatty acids, vitamin B12, C, folate, potassium and calcium in both men and women.
Table 4

Energy and nutrient intakes by gender, according to quartiles of the three food intake pattern scores

 

Traditional Japanese

 

Westernized

 

Meat and fat

 

Men

Q1

 

Q2

 

Q3

 

Q4

  

Q1

 

Q2

 

Q3

 

Q4

  

Q1

 

Q2

 

Q3

 

Q4

  

N

894

 

1059

 

1224

 

1509

  

1696

 

1125

 

908

 

957

  

947

 

1015

 

1185

 

1539

  

/day

Mean

S.D.

Mean

S.D.

Mean

S.D.

Mean

S.D.

p for trend

Mean

S.D.

Mean

S.D.

Mean

S.D.

Mean

S.D.

p for trend

Mean

S.D.

Mean

S.D.

Mean

S.D.

Mean

S.D.

p for trend

Energy (kcal)

1954

411

2039

409

2117

403

2333

381

<0.001

2189

425

2080

427

2082

414

2166

416

<0.001

2000

393

2042

400

2109

401

2308

422

<0.001

Protein (g)

62.2

16.8

70.5

16.5

76.9

18.0

89.6

20.1

<0.001

77.6

22.1

75.3

20.8

75.3

19.8

78.2

18.9

0.001

73.4

21.5

73.2

19.6

75.3

20.3

82.2

20.3

<0.001

Fat (%energy)

24.9

7.6

23.8

6.9

23.2

6.8

22.6

6.6

<0.001

21.9

6.8

23.3

6.9

24.3

6.8

25.7

6.6

<0.001

19.6

6.3

22.0

6.3

23.9

6.2

26.5

6.9

<0.001

ω-3 fatty acids (g)

1.8

1.1

2.2

1.3

2.6

1.6

3.1

1.7

<0.001

2.7

1.7

2.5

1.6

2.3

1.5

2.3

1.4

<0.001

2.7

1.8

2.5

1.6

2.3

1.5

2.5

1.4

<0.001

ω-6 fatty acids (g)

9.2

4.3

9.5

4.2

9.8

4.3

10.9

4.7

<0.001

10.0

4.5

9.7

4.4

9.8

4.2

10.4

4.7

0.003

7.6

3.8

8.6

3.4

9.8

3.8

12.3

4.8

<0.001

Carbohydrates (%energy)

62.3

8.5

62.2

8.0

62.1

7.9

62.0

7.6

0.782

63.9

8.0

62.2

7.9

61.2

7.7

59.8

7.3

<0.001

65.7

7.8

63.6

7.4

61.8

7.2

59.2

7.8

<0.001

Dietary fiber (g)

10.5

3.7

13.3

4.1

15.8

4.6

21.7

7.0

<0.001

14.5

5.9

15.8

6.5

16.9

6.7

18.6

7.6

<0.001

16.7

7.6

15.8

6.3

16.0

6.7

16.0

6.5

0.019

Vitamin A (μgRAE)

386

520

485

638

540

633

730

832

<0.001

502

708

582

705

575

682

621

682

0.000

513

425

549

557

594

800

569

821

0.055

Vitamin D (μg)

4.8

6.6

7.0

7.8

9.2

9.0

12.1

11.1

<0.001

9.7

10.3

8.8

9.6

8.4

9.2

7.5

7.9

<0.001

11.5

10.9

9.8

10.1

8.3

9.1

6.8

7.8

<0.001

Vitamin B1 (mg)

0.9

1.0

0.9

0.7

1.0

0.6

1.1

0.7

<0.001

0.9

0.8

1.0

0.7

1.0

0.6

1.1

0.8

<0.001

0.9

0.7

1.0

0.8

1.0

0.8

1.1

0.7

<0.001

VitaminB2 (mg)

1.1

0.9

1.2

0.8

1.3

0.6

1.6

0.7

<0.001

1.2

0.8

1.3

0.7

1.3

0.6

1.5

0.8

<0.001

1.4

0.7

1.3

0.8

1.3

0.8

1.3

0.8

0.165

Vitamin B6 (mg)

1.0

0.9

1.2

1.0

1.4

0.7

1.8

1.1

<0.001

1.4

1.0

1.4

0.9

1.3

0.9

1.5

1.0

0.071

1.4

0.9

1.4

0.9

1.3

0.8

1.5

1.2

0.011

Vitamin B12 (μg)

4.6

5.3

6.4

7.9

7.6

7.3

9.8

8.9

<0.001

8.1

8.7

7.4

7.3

7.1

7.7

6.8

7.2

0.000

9.3

8.5

7.9

7.5

6.9

7.1

6.5

8.2

<0.001

Folate (μg)

208

91

275

138

325

117

438

165

<0.001

317

176

322

149

334

152

348

148

<0.001

350

171

325

140

320

144

322

176

<0.001

VitaminC (mg)

58.9

56.7

82.9

56.4

106.0

63.5

154.6

99.4

<0.001

91.2

63.6

102.5

74.1

116.2

83.0

133.7

110.6

<0.001

130.0

102.6

110.0

77.8

103.1

79.5

95.2

71.4

<0.001

Sodium (mg)

3482

1319

4021

1304

4553

1377

5568

1693

<0.001

4579

1677

4496

1687

4467

1560

4668

1674

0.032

4257

1618

4389

1602

4471

1535

4914

1746

<0.001

Potassium (mg)

1689

519

2124

495

2494

543

3303

837

<0.001

2338

810

2460

830

2615

912

2811

934

<0.001

2639

1012

2465

846

2476

859

2509

822

<0.001

Calcium (mg)

363

191

460

217

535

213

664

248

<0.001

450

213

512

229

571

249

638

273

<0.001

574

275

538

242

516

249

499

227

<0.001

Iron (mg)

5.9

1.9

7.4

2.1

8.5

2.1

10.9

3.0

<0.001

8.5

3.0

8.5

3.0

8.5

3.1

8.7

3.0

0.511

8.7

3.1

8.3

3.1

8.4

3.0

8.7

2.9

0.004

Women

                           

N

1589

 

1715

 

1747

 

1628

  

999

 

1715

 

1932

 

2033

  

2116

 

1923

 

1595

 

1045

  

Energy (kcal)

1542

320

1640

316

1744

309

1905

298

<0.001

1724

342

1661

339

1685

340

1764

325

<0.001

1637

335

1673

325

1738

328

1875

319

<0.001

Protein (g)

52.7

13.8

60.3

14.4

66.8

15.0

76.8

16.2

<0.001

63.7

17.3

63.1

18.1

63.8

17.0

65.9

16.6

<0.001

62.2

17.8

62.5

16.5

65.2

16.6

70.0

17.1

<0.001

Fat (%energy)

27.1

7.5

25.8

7.2

25.1

6.9

24.3

6.6

<0.001

23.1

6.9

24.5

7.1

26.1

7.1

27.2

6.9

<0.001

22.2

6.6

25.2

6.4

27.6

6.6

29.7

6.9

<0.001

ω-3 fatty acids (g)

1.5

1.0

1.9

1.2

2.2

1.3

2.6

1.4

<0.001

2.3

1.3

2.1

1.3

2.1

1.3

2.0

1.3

<0.001

2.2

1.4

2.0

1.3

2.0

1.2

2.1

1.2

<0.001

ω-6 fatty acids (g)

7.7

3.5

8.0

3.6

8.8

3.9

9.7

4.2

<0.001

8.7

3.9

8.2

3.8

8.5

4.0

8.8

3.9

<0.001

7.1

3.5

8.1

3.4

9.3

3.7

11.3

4.2

<0.001

Carbohydrates (%energy)

59.2

8.4

59.4

8.1

59.4

7.9

59.5

7.6

0.706

62.1

8.1

60.3

8.2

58.8

7.9

57.9

7.5

<0.001

62.6

7.8

59.8

7.4

57.3

7.5

55.3

7.7

<0.001

Dietary fiber (g)

10.3

3.3

13.4

3.9

16.4

4.3

21.7

6.2

<0.001

13.3

5.2

14.8

6.1

15.6

6.1

17.1

6.2

<0.001

15.7

6.4

15.2

6.0

15.3

5.9

15.7

6.3

0.025

Vitamin A (μgRAE)

362

335

472

396

586

686

714

596

<0.001

471

773

521

533

537

430

575

501

<0.001

513

417

543

528

548

579

542

705

0.165

Vitamin D (μg)

4.5

6.2

6.8

7.7

8.2

8.1

10.6

9.4

<0.001

7.8

8.3

8.0

8.7

7.6

8.2

7.0

7.8

0.001

9.0

8.9

7.5

8.1

7.0

8.0

5.7

6.7

<0.001

Vitamin B1 (mg)

0.7

0.5

0.8

0.5

0.9

0.5

1.0

0.5

<0.001

0.7

0.4

0.8

0.6

0.8

0.5

0.9

0.5

<0.001

0.8

0.6

0.8

0.4

0.9

0.5

1.0

0.6

<0.001

VitaminB2 (mg)

0.9

0.5

1.1

0.6

1.2

0.5

1.4

0.5

<0.001

1.0

0.5

1.1

0.6

1.2

0.6

1.2

0.6

<0.001

1.2

0.6

1.1

0.5

1.1

0.5

1.2

0.6

<0.001

Vitamin B6 (mg)

0.8

0.6

1.1

0.7

1.2

0.6

1.5

0.6

<0.001

1.1

0.7

1.2

0.7

1.2

0.7

1.2

0.6

0.012

1.2

0.7

1.1

0.7

1.1

0.5

1.2

0.7

<0.001

Vitamin B12 (μg)

3.8

4.3

5.5

5.7

6.4

6.2

7.9

6.5

<0.001

6.5

7.1

6.2

6.2

5.7

5.5

5.6

5.5

<0.001

7.1

6.7

5.7

5.7

5.3

5.2

4.9

5.5

<0.001

Folate (μg)

200

70

273

89

331

109

431

130

<0.001

288

129

302

134

311

128

324

133

<0.001

327

136

302

126

301

129

299

134

<0.001

VitaminC (mg)

64.3

50.0

95.9

58.6

121.9

69.2

167.6

90.3

<0.001

89.6

58.2

105.6

73.1

113.2

77.4

129.5

87.1

<0.001

131.6

89.5

109.2

74.1

100.4

66.1

99.4

69.9

<0.001

Sodium (mg)

2949

1016

3512

1072

4076

1144

4978

1413

<0.001

3967

1420

3824

1389

3816

1372

3955

1367

0.001

3653

1327

3810

1372

3957

1348

4372

1441

<0.001

Potassium (mg)

1596

450

2080

487

2493

531

3204

756

<0.001

2054

687

2241

794

2375

811

2554

826

<0.001

2425

854

2300

797

2300

769

2349

805

<0.001

Calcium (mg)

359

177

462

203

556

212

672

238

<0.001

401

180

466

230

529

232

594

245

<0.001

552

257

507

229

495

230

473

215

<0.001

Iron (mg)

5.4

1.5

6.9

2.1

8.2

2.0

10.2

2.7

<0.001

7.5

2.5

7.7

2.9

7.7

2.7

7.8

2.7

0.115

7.8

3.0

7.5

2.6

7.7

2.7

7.9

2.6

0.001

For continuous variables, the general linear model was applied

Association of each food intake pattern with waist circumference, BMI, blood pressure and blood lipid profiles

Table 5 shows mean waist circumference, BMI, blood pressure, HbA1c and blood lipid profiles according to the quartiles for each food intake pattern. The multivariable adjusted geometric means for waist circumference (P for trend = 0.008) and BMI (P for trend = 0.001) in men, and mean DBP (P for trend = 0.019) in women were significantly increased according to the lowest to the highest quartile of traditional Japanese pattern. Men in the highest quartile of Westernized pattern had lower SBP (P for trend = 0.003), higher TC (P for trend = 0.047) and higher LDL-C (P for trend = 0.006), while women in the highest quartile of Westernized pattern had lower waist circumference (P for trend = 0.039), lower BMI (P for trend <0.001), lower SBP (P for trend = 0.001) and higher TC, HDL-C and LDL-C (P for trend <0.001 for all). Compared with the lowest quartile of the meat and fat pattern, those in the highest quartile had higher waist circumference (P for trend = 0.016), SBP (P for trend = 0.013), DBP (P for trend = 0.003), TC (P for trend <0.001) and LDL-C (P for trend <0.001) in men and higher waist circumference (P for trend <0.001), BMI (P for trend <0.001), TC (P for trend = 0.001) and LDL-C (P for trend = 0.013) in women. No association between HbA1c and food intake patterns was observed in both men and women.
Table 5

Subject characteristics adjusted for age, medication status, smoking status, drinking, and steps count, according to quartiles of the three food intake pattern scores

 

Traditional Japanese

Westernized

Meat and fat

 

Q1

Q2

Q3

Q4

 

Q1

Q2

Q3

Q4

 

Q1

Q2

Q3

Q4

 
 

Mean

S.E.

Mean

S.E.

Mean

S.E.

Mean

S.E.

p for trend

Mean

S.E.

Mean

S.E.

Mean

S.E.

Mean

S.E.

p for trend

Mean

S.D.

Mean

S.D.

Mean

S.D.

Mean

S.D.

p for trend

Men (N)

895

1061

1228

1509

 

1698

1127

909

959

 

947

1015

1185

1539

 

Waist circumference (cm)

85.8

0.3

85.3

0.3

85.6

0.2

86.4

0.2

0.008

86.0

0.2

85.5

0.3

85.9

0.3

85.9

0.3

0.516

85.2

0.3

85.9

0.3

85.6

0.2

86.4

0.2

0.016

BMI (kg/m2)

23.7

0.1

23.5

0.1

23.7

0.1

24.0

0.1

0.001

23.9

0.1

23.7

0.1

23.7

0.1

23.7

0.1

0.333

23.6

0.1

23.7

0.1

23.7

0.1

23.9

0.1

0.081

Systolic blood pressure

136.1

0.5

134.7

0.5

135.6

0.5

134.8

0.4

0.182

136.3

0.4

135.0

0.5

133.9

0.5

134.9

0.5

0.003

133.8

0.5

135.1

0.5

135.4

0.5

136.1

0.4

0.013

Diastolic blood pressure

82.7

0.4

82.1

0.3

81.9

0.3

81.5

0.3

0.128

82.2

0.3

81.8

0.3

81.5

0.4

82.2

0.4

0.338

81.0

0.4

81.5

0.3

82.1

0.3

82.7

0.3

0.003

Serum total cholesterol

195.1

1.1

197.2

1.0

194.7

1.0

195.4

0.9

0.305

194.1

0.8

195.2

1.0

196.4

1.1

197.8

1.1

0.047

189.5

1.1

194.8

1.0

195.9

1.0

199.6

0.9

<0.001

Serum HDLcholesterol

54.3

0.5

55.1

0.4

54.8

0.4

54.7

0.4

0.691

54.3

0.3

55.0

0.4

54.6

0.5

55.5

0.5

0.170

54.5

0.5

54.1

0.4

54.8

0.4

55.4

0.4

0.199

Serum LDL cholesterol

115.9

1.0

115.9

0.9

114.0

0.9

113.8

0.8

0.191

113.0

0.7

114.5

0.9

115.6

1.0

117.1

1.0

0.006

110.0

1.0

115.1

0.9

114.7

0.9

117.4

0.8

<0.001

HbA1C

5.78

0.02

5.77

0.02

5.79

0.02

5.78

0.02

0.902

5.81

0.02

5.77

0.02

5.75

0.02

5.77

0.02

0.158

5.74

0.02

5.79

0.02

5.77

0.02

5.80

0.02

0.125

Women (N)

1589

1716

1748

1628

 

999

1715

1932

2033

 

2116

1923

1595

1045

 

Waist circumference (cm)

82.0

0.2

81.3

0.2

81.4

0.2

81.7

0.2

0.170

81.9

0.3

81.8

0.2

81.7

0.2

81.1

0.2

0.039

80.7

0.2

81.7

0.2

82.1

0.2

82.4

0.3

<0.001

BMI (kg/m2)

22.7

0.1

22.5

0.1

22.5

0.1

22.7

0.1

0.138

23.0

0.1

22.7

0.1

22.6

0.1

22.4

0.1

<0.001

22.4

0.1

22.6

0.1

22.8

0.1

22.9

0.1

<0.001

Systolic blood pressure

128.1

0.4

128.4

0.4

128.7

0.4

129.1

0.4

0.321

130.3

0.5

128.9

0.4

127.8

0.4

128.1

0.4

0.001

127.9

0.4

128.6

0.4

128.6

0.4

129.6

0.5

0.062

Diastolic blood pressure

76.5

0.3

77.2

0.3

77.6

0.2

77.3

0.3

0.019

77.5

0.3

77.1

0.3

76.8

0.2

77.4

0.2

0.229

76.9

0.2

77.2

0.2

77.1

0.3

77.9

0.3

0.115

Serum total cholesterol

204.1

0.9

204.4

0.8

205.8

0.8

203.7

0.8

0.287

199.3

1.0

201.4

0.8

205.6

0.7

208.7

0.7

<0.001

202.1

0.7

206.1

0.8

205.3

0.8

205.3

1.0

0.001

Serum HDLcholesterol

63.5

0.4

63.8

0.4

64.3

0.4

63.5

0.4

0.338

62.0

0.5

62.3

0.4

64.3

0.3

65.4

0.3

<0.001

63.3

0.3

63.5

0.3

64.0

0.4

64.8

0.5

0.070

Serum LDL cholesterol

118.8

0.8

118.7

0.7

118.7

0.7

117.5

0.7

0.531

114.5

0.9

116.6

0.7

119.4

0.7

121.0

0.7

<0.001

116.8

0.7

119.7

0.7

119.1

0.7

118.3

0.9

0.013

HbA1C

5.68

0.01

5.70

0.01

5.69

0.01

5.72

0.01

0.173

5.73

0.02

5.69

0.01

5.69

0.01

5.69

0.01

0.295

5.68

0.01

5.70

0.01

5.70

0.01

5.73

0.02

0.063

The general linear model adjusted for participant age, steps count, medication status (hypertension, diabetes, and dyslipidemia), smoking and drinking status was applied

Significant P values <0.05 were shown in bold characters

Association of each food intake pattern with hypertension, diabetes, hypercholesterolemia and elevated LDL cholesterol

Table 6 showed the logistic regression analysis for the association of each food intake pattern with cardiovascular disease risk. Traditional Japanese pattern was related to a lower prevalence of hypertension in men and not in women. The multivariate-adjusted ORs (95% CI) for the lowest through highest quartiles of the traditional Japanese pattern were 1.00 (reference), 0.75 (0.59–0.95), 0.83 (0.65–1.04) and 0.67 (0.53–0.84), respectively (trend P = 0.003). Westernized pattern was associated with higher prevalence of hypercholesterolemia and elevated LDL cholesterol in women, but not in men. The multivariate-adjusted ORs (95% CI) comparing the highest quartile to the lowest were Q2: 1.13 (0.87–1.46), Q3: 1.33 (1.04–1.71) and Q4: 1.80 (1.41–2.29) for hypercholesterolemia (trend P < 0.001), and Q2: 1.19 (0.86–1.62), Q3: 1.43 (1.06–1.93) and Q4: 1.75 (1.30–2.35) for elevated LDL cholesterol (trend P < 0.001). Also, higher meat-fat pattern score was positively associated with hypertension, diabetes and hypercholesterolemia in men, but not in women (Table 6).
Table 6

Association of each food intake pattern with hypertension, diabetes, hypercholesterolemia and elevated LDL cholesterol

 

Traditional Japanese

Westernized

Meat and fat

 

Q1

Q2

Q3

Q4

p for trend

Q1

Q2

Q3

Q4

p for trend

Q1

Q2

Q3

Q4

p for trend

Men (N)

895

1061

1228

1509

 

1698

1127

909

959

 

947

1015

1185

1539

 

Hypertension

 Prevalence: n (%)

445 (49.8)

546 (51.6)

738 (60.3)

918 (60.8)

 

959 (56.5)

633 (56.3)

517 (56.9)

538 (56.2)

 

611 (64.5)

596 (58.7)

650 (54.9)

790 (51.3)

 

 ORa (95% CI)

1 (ref)

0.75 (0.59–0.95)

0.83 (0.65–1.04)

0.67 (0.53–0.84)

0.003

1 (ref)

0.93 (0.76–1.14)

0.86 (0.69–1.06)

0.84 (0.68–1.05)

0.169

1 (ref)

1.13 (0.88–1.45)

1.20 (0.94–1.53)

1.41 (1.11–1.79)

0.008

Diabetes

 Prevalence: n (%)

110 (12.3)

148 (14.0)

214 (17.5)

271 (18.0)

 

245 (14.4)

176 (15.6)

149 (16.4)

173 (18.1)

 

179 (18.9)

199 (19.6)

184 (15.5)

181 (11.8)

 

 ORa (95% CI)

1 (ref)

0.69 (0.48–1.00)

0.90 (0.64–1.27)

0.80 (0.57–1.11)

0.300

1 (ref)

0.92 (0.69–1.23)

0.87 (0.64–1.19)

0.92 (0.68–1.25)

0.839

1 (ref)

1.62 (1.17–2.25)

1.52 (1.09–2.12)

1.38 (0.98–1.95)

0.021

Hypercholesterolemia

 Prevalence: n (%)

170 (19.0)

219 (20.7)

266 (21.7)

355 (23.5)

 

315 (18.6)

231 (20.5)

220 (24.2)

244 (25.5)

 

197 (20.8)

243 (23.9)

250 (21.1)

320 (20.8)

 

 ORa (95% CI)

1 (ref)

1.01 (0.75–1.38)

0.94 (0.69–1.27)

0.94 (0.70–1.27)

0.853

1 (ref)

1.04 (0.79–1.36)

1.20 (0.90–1.60)

1.22 (0.92–1.62)

0.415

1 (ref)

1.45 (1.02–2.07)

1.34 (0.94–1.89)

1.64 (1.17–2.29)

0.036

Elevated LDL cholesterol

 Prevalence: n (%)

161 (18.0)

200 (18.9)

234 (19.1)

314 (20.8)

 

270 (15.9)

213 (18.9)

206 (22.7)

220 (23.0)

 

190 (20.1)

217 (21.4)

223 (18.8)

279 (18.1)

 

 ORa (95% CI)

1 (ref)

0.94 (0.67–1.30)

0.78 (0.56–1.10)

0.78 (0.56–1.09)

0.281

1 (ref)

1.19 (0.88–1.62)

1.40 (1.02–1.92)

1.18 (0.85–1.64)

0.228

1 (ref)

1.11 (0.75–1.64)

1.07 (0.73–1.57)

1.28 (0.89–1.85)

0.462

Women (N)

1589

1716

1748

1628

 

999

1715

1932

2033

 

2116

1923

1595

1045

 

Hypertension

 Prevalence: n (%)

439 (27.6)

697 (40.6)

778 (44.5)

835 (51.3)

 

461 (46.1)

727 (42.4)

782 (40.5)

779 (38.3)

 

1073 (50.7)

798 (41.5)

547 (34.3)

331 (31.7)

 

 ORa (95% CI)

1 (ref)

1.05 (0.83–1.32)

1.13 (0.91–1.42)

1.03 (0.82–1.30)

0.507

1 (ref)

0.96 (0.75–1.23)

0.90 (0.70–1.14)

0.88 (0.69–1.11)

0.142

1 (ref)

1.05 (0.86–1.27)

1.00 (0.81–1.22)

1.03 (0.81–1.31)

0.840

Diabetes

 Prevalence: n (%)

100 (6.3)

141 (8.2)

141 (8.1)

171 (10.5)

 

97 (9.7)

146 (8.5)

146 (7.6)

164 (8.1)

 

207 (9.8)

177 (9.2)

102 (6.4)

67 (6.4)

 

 ORa (95% CI)

1 (ref)

1.02 (0.70–1.48)

0.86 (0.59–1.26)

0.95 (0.66–1.38)

0.521

1 (ref)

0.78 (0.54–1.13)

0.71 (0.49–1.02)

0.75 (0.52–1.08)

0.061

1 (ref)

1.14 (0.85–1.55)

1.09 (0.77–1.53)

1.31 (0.88–1.96)

0.231

Hypercholesterolemia

 Prevalence: n (%)

375 (23.6)

497 (29.0)

588 (33.7)

585 (35.9)

 

255 (25.5)

482 (28.1)

586 (30.3)

722 (35.5)

 

721 (34.1)

617 (32.1)

443 (27.8)

264 (25.3)

 

 ORa (95% CI)

1 (ref)

0.92 (0.74–1.14)

1.02 (0.83–1.26)

0.84 (0.67–1.06)

0.237

1 (ref)

1.13 (0.87–1.46)

1.33 (1.04–1.71)

1.80 (1.41–2.29)

<0.001

1 (ref)

1.14 (0.94–1.38)

1.21 (0.99–1.48)

1.21 (0.96–1.53)

0.567

Elevated LDL cholesterol

 Prevalence: n (%)

302 (19.0)

426 (24.8)

491 (28.1)

514 (31.6)

 

218 (21.8)

418 (24.4)

505 (26.1)

592 (29.1)

 

631 (29.8)

516 (26.8)

373 (23.4)

213 (20.4)

 

 ORa (95% CI)

1 (ref)

1.06 (0.82–1.37)

1.12 (0.87–1.45)

1.05 (0.80–1.38)

0.755

1 (ref)

1.19 (0.86–1.62)

1.43 (1.06–1.93)

1.75 (1.30–2.35)

<0.001

1 (ref)

0.99 (0.78–1.24)

1.15 (0.91–1.46)

1.06 (0.80–1.40)

0.333

a The logistic regression analysis adjusted for participant age, waist circumference, BMI, steps count, medication status (hypertension, diabetes, and dyslipidemia), smoking and drinking status was applied

OR (95% CI): Adjusted odds ratio (95% Confidence Interval)

Significant P values <0.05 were shown in bold characters

Discussion

In this cross-sectional analysis of the Japan NHNS 2012 data, we identified three food intake patterns derived by principal component analysis: the traditional Japanese pattern, Westernized pattern, meat and fat pattern. Food intake patterns showed differences in associations between CVRFs among men and women. The traditional Japanese pattern was significantly associated with increased BMI and waist circumference, but significantly lower prevalence of hypertension in men. This association may be partly explained by higher energy intake, but with higher vegetable as well as potatoes consumption, which are rich in potassium [30] and contributed to lower blood pressure [31]. However, the traditional Japanese pattern for women was found to have a positive association with diastolic blood pressure. High salt intake (such as from miso soup and Japanese pickles intake) in the highest quartile of traditional Japanese pattern in women may have contributed to raised diastolic blood pressure [32, 33].

Westernized pattern was inversely associated with SBP in men, waist circumference in both men and women, and BMI (in women). The Westernized pattern identified in our study is somewhat similar to previously reported ‘bread-dairy pattern’ or ‘Westernized breakfast pattern’, mainly comprising bread and danish, butter and margarine, milk, cheese and yogurt, fresh fruits but low intakes of rice, which was inversely related with abdominal obesity, BMI and blood pressure [3437]. In our study population, subjects in the highest quartile of the Westernized pattern consumed greater amount of potassium intake than those in the lowest quartile. Because high potassium intake is a known protective factor for hypertension [31], the higher potassium intake from fresh fruits in the high Westernized pattern score group may have contributed to lower blood pressure. Additionally, foods or nutrients contributed to westernized breakfast pattern such as milk and yogurt, which are rich source of calcium, have also been shown to decrease blood pressure [38]. On the other hand, the Westernized pattern was positively associated with HDL-C (in women), TC and LDL-C in both men and women, and positively associated with hypercholesterolemia and elevated LDL cholesterol in women. This may be due to high fat intake among the highest quartile of Westernized pattern (Table 4) [39].

Interestingly, a simultaneous increase in both HDL and LDL cholesterol was observed with the higher Westernized pattern score in women, consistent with the finding reported by JY Shin et al., 2013 [35]. It has been reported that the average HDL-C levels are indeed high among Japanese people in general, due to genetic deficiency of cholesteryl ester transfer protein (CETP) [40]. In spite of high HDL-C levels, we speculate that these certain number of subjects with CETP deficiency had increased risk of dyslipidemia. Furthermore, this direct association of increased HDL cholesterol with the Westernized pattern might be mediated by lower carbohydrates [41] and higher saturated fat intake [42] and butter [43] among those in the highest quartile of the Westernized pattern.

As expected, meat and fat pattern identified in our study was positively associated with waist circumference, BMI, blood pressure, TC and LDL-C in both men and women, and higher prevalence of hypertension, diabetes and hypercholesterolemia in men after additional adjustment for waist circumference and BMI [4447]. These positive associations may partly be attributable to the unhealthy cardiovascular risk constituents in meat and fat pattern (such as red meat and saturated fats and cholesterol) [48]. Our result is comparable to a cohort study in Japan that reported a pattern with high meat intakes was closely related to an increased risk of cardiovascular diseases [49].

However, the present study has some limitations. First, as the association was derived from the cross-sectional study, the causal relationship between food intake patterns and the cardiovascular risk factors could not be determined, and may have possibility of reverse causality. Awareness of previously diagnosed hypertension or dyslipidemia can alter their food intake patterns, such as an increase in the consumption of vegetables in hypertensive subjects [50]. However, the significant association persisted after adjusting for medication for hypertension, diabetes and hyperlipidemia. Second, as the Japan NHNS is usually conducted in November, the observed food intake patterns may not accurately reflect seasonal variations in food intake and availability. Third, although the food intake was estimated through a self-reported dietary record data and checking of the records were conducted by trained dieticians, under or over reporting of intake is inevitable. Last, because food intake patterns were derived from the one-day dietary record with a diverse variables of food items, explained variation in food groups of the principal component analysis was low compared to previous studies using FFQs. Because FFQs are developed to assess the habitual food intakes of the specific population of research subjects, the possible food intake patterns may have been pre-defined by their habitual intake which give rise to higher explained variance of each pattern compared to one-day dietary record. Previous study of dietary patterns by Hamer M et al. using weighed food record also showed a similar trend of low percentage of explained variance [51]. Moreover, a study of dietary patterns by McCann SE et al. using FFQs, also observed that the explained variance increased as the number of food groups decreased [52]. Despite these limitations, our study was based on a large-scale, nationally representative health and nutrition survey data, which was highly standardized in obtaining socio demographic and lifestyle characteristics as well as biological cardiovascular risk factors.

Conclusion

In summary, three major food intake patterns identified in this cross-sectional analysis, were found to have significant associations with cardiovascular risk factors. The traditional Japanese pattern showed protective effect against hypertension in men, Westernized pattern was positively associated with dyslipidemia in women, while meat-fat pattern was related to all cardiovascular risk factors in men. The association between cardiovascular disease risk factors and food intake patterns derived from one-day dietary records of the National Health and Nutrition Survey was similar to previous cohort studies examining habitual intake through FFQs.

Abbreviations

BMI: 

Body mass index

CETP: 

Cholesteryl ester transfer protein

CVD: 

Cardiovascular disease

CVRF: 

Cardiovascular risk factors

DASH: 

Dietary approaches to stop hypertension

DBP: 

Diastolic blood pressure

FFQs: 

Food frequency questionnaires

HbA1c: 

Hemoglobin A1c

HDL-C: 

High density lipoprotein cholesterol

J-NHNS: 

The Japan National Health and Nutrition Survey

LDL-C: 

low density lipoprotein cholesterol

NGSP: 

National Glyco-hemoglobin Standardization Program

OR: 

Odds ratio

PCA: 

Principal component analysis

SBP: 

Systolic blood pressure

TC: 

Total cholesterol

WC: 

Waist circumference

Declarations

Acknowledgements

We would like to thank Dr. Suminori Kono, the Principal Investigator, who designed and planned the research project and made this work possible.

Funding

This work was supported by Health and Labor Sciences Research Grants (Special Research Project H26-tokubetsu-shitei-033) from the Ministry of Health, Labor and Welfare of Japan.

Availability of data and materials

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

Authors’ contributions

HT substantially contributed to the conception and design, and the acquisition of the data. HT and NCH contributed to the analysis and interpretation of the data and NCH drafted the manuscript. HS, SI and WS took part in the interpretation of the data and provided critical revisions of the manuscript for important intellectual content. HT made a final revision and approval of the manuscript. All authors read and approved the final manuscript.

Ethics approval and consent to participate

We obtained the consent of the secondary use of the 2012 NHNS data from Ministry of Health, Labor and Welfare. This study was approved by the institutional review board of the National Institute of Health and Nutrition.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Nutritional Epidemiology and Shokuiku, National Institutes of Biomedical Innovation, Health and Nutrition

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© The Author(s). 2017

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