Development of a Concise Healthy Diet Score for Cardiovascular Disease among Japanese; The Japan Collaborative Cohort Study

Abstract

Aims: Several diet quality indicators have been developed primarily for cardiovascular disease (CVD) prevention in Western countries. However, those previous indicators are complicated and less feasible in clinical and health-promoting settings. Therefore, we aimed to develop a concise dietary risk score for CVD prevention in Japanese.

Methods: Using the self-administered food frequency questionnaire with 35 food items, we developed a concise healthy diet score (cHDS) ranging from 0 to 5 points. We examined the association of cHDS with risks of all-cause and cause-specific mortality among 23,115 men and 35,557 women who were free of CVD and cancer.

Results: During 19.2 years of median follow-up, 6,291 men and 5,365 women died. In men, the multivariable hazard ratios (95% confidence intervals) for the highest cHDS (5 points) compared to the lowest (0-1 points) were 0.74 (0.60–0.91, P-trend=0.008) for CVD and 0.86 (0.77-0.95, P-trend=0.05) for all causes. No significant associations were found for stroke, coronary heart disease, and other causes in men. The corresponding hazard ratio in women was 0.65 (0.52–0.81, P-trend＜0.001) for CVD, 0.63 (0.45–0.88, P-trend＜0.001) for stroke, 0.48 (0.30–0.78, P-trend=0.008) for coronary heart disease, 0.67 (0.54-0.84, P-trend＜0.001) for other causes, and 0.75 (0.66–0.85, P-trend＜0.001) for all causes.

Conclusion: We developed a concise diet quality score named cHDS in the Japanese population and found the inverse association of cHDS with mortality from CVD and all causes for both men and women.

Introduction

Healthy diets have an important role in cardiovascular disease (CVD)¹⁾. Overall diet quality has been assessed with several indicators developed in Western countries as an evidence-based healthy diet for CVD prevention (e.g. Dietary Approach to Stop Hypertension (DASH) diet^{2, 3)} and alternate Healthy Eating Index (aHEI)^{4, 5)}) and as a traditional diet in the heart-healthy region (e.g. Mediterranean diet⁶⁾). Also, diet quality indices have been developed among Japanese such as the Japanese Diet Index^{7, 8)} and Japanese Food Guide Spinning Top (JFGST)^{9, 10)}, relating to lower CVD mortality. However, all diet quality indices require measuring the dietary intake of many food items and calculating relative levels such as upper or lower median in target populations. Therefore, most diet quality indices are unlikely useful for a brief intervention in clinical and health-promoting settings when time and human resources are generally limited. Then, the development of brief dietary assessment tools has been in an effort^{11, 12)}.

To improve the utility of a brief dietary assessment tool, several theories for effective behavior changes could be useful¹³⁾. The goal-setting theory suggests that unclear goals like “Eat more vegetables” have less power to change behavior^{14, 15)}. Then, setting a clear goal like “5 A Day” is key to increasing the effectiveness of the intervention^{16, 17)}. In addition, the setting of clear goals would encourage people to determine the priority of their behavior change. We considered that the multiple ‘yes-no’ question-based diet quality score could be feasible and effective for promoting healthy eating behaviors through brief intervention in a short meeting, but few useful scores for CVD prevention exists to date.

To provide a dietary assessment tool for brief intervention to promote dietary behavior change¹⁸⁾, especially for Japanese, we aimed to develop a concise healthy diet score for CVD prevention using the data from the Japan Collaborative Cohort Study for Evaluation of Cancer Risk (JACC Study), and we examined the association of the developed dietary score with all-cause and cause-specific mortality.

Subjects and Methods

Study Cohort

The JACC Study sponsored by the Ministry of Education, Culture, Sports, Science and Technology of Japan is an ongoing cohort study that comprised a nationwide community-based sample of 46,395 men and 64,190 women aged 40–79 years in 1988–1990, from 45 communities across Japan, as described elsewhere in detail¹⁹⁾. Participants completed self-administered questionnaires about their lifestyles, dietary intake, and medical histories. The participants were followed up until the end of 2009 in 35 areas, 2008 in two areas, 2003 in four areas, and 1999 in four areas.

We excluded participants from 11 communities where the complete version of the food frequency questionnaire (FFQ) was not distributed (n=48,915: 22,082 men and 26,833 women), those who had a medical history of cancer or CVD (n=2,998: 1,198 men and 1,800 women), and those with a total energy intake of less than 500 kcal/day or more than 3500 kcal/day. Finally, we included 23,115 men and 35,557 women in the current analysis.

Informed consent was obtained from individuals in 36 communities (written in 35 and oral in one) and from community leaders as group consent in nine communities. The institutional review boards of Hokkaido University and Osaka University Graduate School of Medicine approved the JACC Study protocol.

Dietary Assessment

The self-administered FFQ contained the following 35 food items which were classified into the major sources of food groups assessed by the weighed food record in the National Nutrition Survey 1990 in Japan²⁰⁾: beef, pork (excluding ham or sausage), ham or sausage, chicken, liver, eggs, milk, yogurt, cheese, butter, margarine, deep-fried foods or tempura, fried vegetables, fresh fish, kamaboko (fish paste), dried or salted fishes, spinach or garland chrysanthemum, carrot or pumpkin, tomatoes, cabbage or head lettuce, Chinese cabbage, edible wild plants, fungi (enokidake, shiitake mushroom), potatoes, algae (seaweeds), pickles, tsukudani (preserved foods using soy sauce), boiled beans, tofu (soybean curd), citrus fruits, other fruits (excluding citrus variety), fresh fruit juice (in summer), sweets, rice, and miso soup (Fig.1). Participants were asked about their consumption of 33 food items other than rice and miso soup during the past year and responded with five possible choices: ‘rarely’, ‘1-2 times/month’, ‘1-2 times/week’, ‘3-4 times/week’, and ‘almost every day’. To use those responses as a continuous variable, we assigned daily intake levels of 0, 0.05, 0.214, 0.5, and 1.0, respectively. To minimize the impact of selection bias and unmeasured dietary environmental factors such as dietary culture, and food availability, we combined the lowest two intake frequency categories ‘rarely’, and ‘1-2 times/month’ as ‘＜1 time/week’. Rice intake was asked for the average number of standard-sized bowls of rice consumed a day and answered with an integer. Miso soup intake was asked for that frequency first with four possible choices: ‘rarely’, ‘several times a month’, ‘every other day’, and ‘almost every day’. Then, for the participants having miso soup almost every day, we asked them the daily number of cups of miso soup consumed as an integer. High reproducibility and low-to-moderate accuracy were reported on our FFQ²¹⁾.

Fig.1.

Development of concise healthy diet score (cHDS)

In addition to the food item intake, participants were asked about their salt preference with five possible choices: ‘love’, ‘like’, ‘neutral’, ‘don’t like’, and ‘dislike’.

Development of the Concise Healthy Diet Score (cHDS)

We randomly divided each imputed dataset by two-thirds for the derivation data and by one-third for validation data. There are no significant differences in the characteristics of participants between those datasets (Supplementary Table 1). As shown in Fig.1, we developed a concise healthy diet score (cHDS) using the derivation data. First, to simplify the assessment of salt intake, the salt intake score was calculated from 7 salt-rich foods (miso soup, hams or sausages, cheese, kamaboko, dried or salted fish, pickles, and tsukudani) as the total number of those consumed two cups a day or more for miso soup, and three times a week or more for the others. The salt intake score was significantly correlated with the preference for salty foods, an indicator of salt intake²²⁾, in the deprived data (Spearman’s correlation coefficient=0.15, p-value ＜0.001).

Supplementary Table 1.Characteristics of study participants in the derivation and validation dataset

	Overall	Derivation dataset	Validation dataset
No. at risk	58,672	39,115	19,557
Age, years	56.1 (9.9)	56.2 (9.9)	56.1 (9.9)
BMI, kg/m2	22.8 (3.0)	22.8 (3.0)	22.8 (3.0)
Current smoking, %	23.9	23.8	24.1
Education: College or higher, %	13.7	13.7	13.7
Exercise: 5+ hrs/wk, %	5.3	5.3	5.2
Walking 1+ hr/d, %	48.8	48.8	48.9
History of hypertension, %	20.3	20.3	20.2
History of diabetes mellitus, %	4.3	4.3	4.4
Current drinking alcohol, %	39.0	39.0	39.1
Energy intake, kcal/day	1557 (441)	1557 (440)	1558 (441)
Rice, bowls/day	3.2 (1.4)	3.2 (1.4)	3.2 (1.4)
Miso soup, cups/day	1.9 (1.6)	1.9 (1.6)	1.9 (1.6)
Meats, time/week	0.6 (0.4)	0.6 (0.4)	0.6 (0.4)
Egg, time /week	0.6 (0.4)	0.6 (0.4)	0.6 (0.4)
Dairy products, time /week	0.7 (0.6)	0.7 (0.6)	0.7 (0.6)
Fresh fish, time/week	0.5 (0.3)	0.5 (0.3)	0.5 (0.3)
Processed foods, time/week	0.3 (0.3)	0.3 (0.3)	0.3 (0.3)
Vegetable, time/week	2.2 (1.1)	2.2 (1.1)	2.2 (1.1)
Mushroom, time/week	0.3 (0.3)	0.3 (0.3)	0.3 (0.3)
Potatoes, time/week	0.4 (0.3)	0.4 (0.3)	0.4 (0.3)
Seaweeds, time/week	0.5 (0.4)	0.5 (0.4)	0.5 (0.4)
Beans, time/week	0.7 (0.4)	0.7 (0.4)	0.7 (0.4)
Fruits, time/week	1.1 (0.6)	1.1 (0.6)	1.1 (0.6)
Fruit juice, time/week	0.3 (0.3)	0.3 (0.3)	0.3 (0.3)

Next, we excluded 6 food items as follows: deep-fried foods or tempura, and fried vegetables due to dishes which could overlap with other individual food items; liver and edible wild plants due to food items consumed less than once a week in around four-fifths of our population; and butter and margarine due to condiments. Then, we combined 22 food items into 13 food groups: rice, egg, potatoes, algae, fungi, fresh fish, fresh fruit juices, sweets, such as meats (beef, pork and chicken), dairy products (milk and yogurt), vegetables (spinach or garland chrysanthemum, carrots and pumpkins, tomatoes, cabbage, and lettuce and Chinese cabbage), beans (boiled beans and tofu), and fruits (citrus fruits and other fruits).

Then, as components of cHDS, we chose intakes of fresh fish, fruits, vegetables, and salt which have been strongly recommended in the Japanese and US guidelines for the primary prevention of CVD^{23, 24)}, our prior studies reported a significant association between these intakes and risk of CVD mortality^25-28), the score was inversely associated with risk of CVD mortality.

In the derivation data, we examined the associations of intakes of four definite components (fresh fish, vegetables, fruits, and salt intake score) and the 10 food items/groups with the risk of CVD mortality after adjusting for lifestyles, medical history, total energy intake, and four definite components using the Cox proportional hazard model (Table 1). The cHDS components were determined when the multivariable hazard ratios (HRs) at the highest category were ＜0.90 or ＞1.10 compared with the lowest category (reference), resulting in beans as well as fresh fish, vegetables, fruits, and salt intake score as the component. We excluded nine food groups (rice, egg, potatoes, algae, fungi, fresh fruit juices, sweets, meats, dairy products), because of not meeting the above inclusion criteria. Then, the cut-point category for each of the five components was determined when the category of the multivariable HR of ＜0.90 started to include the median number of the participants or when the category of the multivariable HR of ＞1.10 appeared (Table 2). The cHDS ranged from 0 to 5 points.

Table 1.Hazard ratios of cardiovascular mortality according to the 5 components selected and the 9 candidate excluded

	No. of participants	Person-years	CVD deaths	Age, sex-adjusted HR	Multivariable HR
Selected 5 items
Fresh fish
＜1 time/week	3,240	51,880	245	1.00	1.00
1-2 times/week	12,854	209,028	752	0.85 (0.72-1.01)	0.90 (0.76-1.07)
3-4 times/week	12,533	206,089	673	0.79 (0.67-0.93)	0.86 (0.73-1.02)
Almost every day	10,488	177,737	600	0.74 (0.62-0.87)	0.81 (0.67-0.97)
Fruits
＜1 time/week	2,792	44,692	211	1.00	1.00
1-2 times/week	3,451	56,817	213	0.78 (0.62-0.97)	0.86 (0.68-1.08)
3-4 times/week	5,698	94,698	358	0.82 (0.68-1.01)	0.92 (0.76-1.12)
Almost every day	27,174	448,528	1,489	0.71 (0.60-0.83)	0.86 (0.72-1.02)
Vegetables
＜1 time/day	2,814	45,064	189	1.00	1.00
1 time/day	10,134	165,773	601	0.83 (0.69-1.00)	0.92 (0.76-1.13)
2 times/day	12,144	200,233	627	0.70 (0.58-0.84)	0.81 (0.67-0.99)
3+ times/day	14,024	233,665	853	0.70 (0.58-0.84)	0.85 (0.69-1.05)
Beans
＜1 time/week	1,992	31,708	129	1.00	1.00
1-2 times/week	7,968	130,917	418	0.80 (0.63-1.02)	0.87 (0.68-1.12)
3-4 times/week	10,375	171,600	568	0.77 (0.61-0.96)	0.87 (0.69-1.09)
Almost every day	18,781	310,509	1,155	0.73 (0.58-0.91)	0.88 (0.69-1.12)
Salt intake score
0-1 point	16,896	271,181	839	1.00	1.00
2 points	11,921	199,646	732	0.96 (0.85-1.08)	1.04 (0.92-1.18)
3 points	6,476	109,204	444	1.05 (0.92-1.20)	1.19 (1.03-1.37)
4-7 points	3,822	64,704	255	1.01 (0.86-1.18)	1.22 (1.02-1.44)
Excluded 9 items
Meats
＜1 time/week	3,671	58,939	304	1.00	1.00
1-2 times/week	9,341	151,361	596	0.85 (0.72-1.00)	0.90 (0.76-1.07)
3-4 times/week	14,818	244,756	798	0.81 (0.69-0.94)	0.90 (0.77-1.06)
Almost every day	11,284	189,679	572	0.81 (0.69-0.96)	0.93 (0.78-1.11)
Egg
＜1 time/week	2,862	45,534	194	1.00	1.00
1-2 times/week	9,190	149,552	557	0.99 (0.81-1.21)	1.05 (0.86-1.28)
3-4 times/week	10,340	170,505	556	0.91 (0.75-1.12)	1.01 (0.82-1.24)
Almost every day	16,723	279,143	962	0.90 (0.74-1.10)	1.06 (0.86-1.30)
Dairy products
＜1 time/week	9,048	146,464	631	1.00	1.00
1-2 times/week	5,193	86,839	290	0.91 (0.77-1.07)	0.94 (0.80-1.11)
3-4 times/week	4,921	82,718	264	0.91 (0.77-1.07)	0.99 (0.84-1.17)
Almost every day	19,953	328,714	1,085	0.81 (0.72-0.91)	0.94 (0.83-1.06)
Fungi
＜1 time/week	13,548	223,968	854	1.00	1.00
1-2 times/week	14,972	246,433	838	0.95 (0.84-1.08)	1.01 (0.89-1.14)
3-4 times/week	7,664	126,227	405	0.85 (0.74-0.98)	0.94 (0.81-1.10)
Almost every day	2,931	48,107	173	0.92 (0.76-1.12)	1.01 (0.83-1.24)
Potatoes
＜1 time/week	6,795	109,862	389	1.00	1.00
1-2 times/week	14,491	235,108	776	0.87 (0.74-1.02)	0.95 (0.81-1.12)
3-4 times/week	10,580	174,971	609	0.86 (0.74-1.01)	0.99 (0.84-1.18)
Almost every day	7,249	124,793	497	0.82 (0.69-0.96)	0.98 (0.81-1.18)
Algae (seaweeds)
＜1 time/week	4,190	67,369	264	1.00	1.00
1-2 times/week	11,415	187,829	661	0.93 (0.79-1.09)	1.03 (0.87-1.21)
3-4 times/week	11,139	184,747	634	0.90 (0.76-1.06)	1.04 (0.87-1.25)
Almost every day	12,371	204,790	711	0.82 (0.71-0.95)	1.00 (0.84-1.19)
Fresh fruit juice
＜1 time/week	16,326	266,555	1,108	1.00	1.00
1-2 times/week	9,743	161,485	504	0.91 (0.80-1.03)	0.95 (0.84-1.08)
3-4 times/week	6,753	112,112	343	0.91 (0.79-1.05)	0.99 (0.86-1.15)
Almost every day	6,293	104,583	314	0.89 (0.77-1.02)	0.98 (0.84-1.13)
Sweets
＜1 time/week	13,714	223,994	833	1.00	1.00
1-2 times/week	11,924	197,089	628	0.81 (0.72-0.92)	0.89 (0.79-1.01)
3-4 times/week	7,538	124,674	447	0.87 (0.76-1.00)	0.98 (0.85-1.14)
Almost every day	5,940	98,978	362	0.81 (0.71-0.94)	0.93 (0.80-1.08)
Rice intake
＜2 bowl/day	3,343	52,945	209	1.03 (0.86-1.24)	1.04 (0.83-1.29)
2 bowls/day	7,708	121,005	390	0.97 (0.84-1.11)	0.98 (0.84-1.15)
3 bowls/day	16,186	270,493	1,077	1.00	1.00
4 bowls/day	4,521	76,227	216	0.88 (0.74-1.05)	0.91 (0.75-1.09)
5 bowls/day	3,783	64,080	176	0.86 (0.71-1.05)	0.90 (0.71-1.15)
6+ bowls/day	3,574	59,985	202	0.97 (0.80-1.16)	0.98 (0.75-1.29)

Multivariable model was further adjusted for BMI (fifths), smoking (never, former, current smoking ＜20, and 20+ cigs/day), alcohol intake (never, former, current drinker ＜23, 23-45, 46-68, and 69+ g ethanol/day), walking (＜0.5, 0.5, 0.6-0.9, and 1+ hour/day), sports (＜1, 1-2, 3-4, and 5+ hours/week), education (＜12, 13-15, 16-18, and 19+ years), history of hypertension and diabetes (no, and yes, for each), total energy intake (continuous), salt intake score, and intakes of fresh fish, vegetables, and fruits (four categories each).

Table 2.The recommended amount for each food item/group/score

	Recommended intake level
Fresh fish	3 times/week or more
Fruits	1 time/day or more
Vegetables	2 times/day or more
Beans	3 times/week or more
Salt intake score	2 points or less

We examined the internal validity of cHDS to the risk of CVD mortality by comparing the associations between the derivation and validation data sets. We confirmed the similarity of the inverse association between the cHDS and the risk of CVD death in the two datasets (Supplementary Table 2).

Supplementary Table 2.Hazard ratios of cardiovascular mortality in the derivation and validation datasets according to the concise healthy diet score

	Concise healthy diet score					P value for trend
	0-1	2	3	4	5
Derivation datasets
No. at risk	2,670	5,857	9,890	13,086	7,612
Person-years	43,617	95,803	161,719	217,029	126,567
No. of CVD deaths	184	381	604	720	382
Age-adjusted HR＊	1.00	0.89 (0.72-1.10)	0.81 (0.66-0.99)	0.70 (0.57-0.85)	0.64 (0.52-0.78)	＜0.001
Adjusted HR#	1.00	0.92 (0.74-1.14)	0.85 (0.70-1.04)	0.77 (0.63-0.95)	0.70 (0.57-0.87)	＜0.001
Validation datasets
No. at risk	1,347	2,931	4,935	6,527	3,817
Person-years	21,947	47,829	80,789	108,285	63,625
No. of CVD deaths	94	182	300	358	190
Age-adjusted HR＊	1.00	0.81 (0.57-1.15)	0.79 (0.57-1.10)	0.68 (0.50-0.94)	0.62 (0.45-0.86)	0.001
Adjusted HR#	1.00	0.83 (0.58-1.19)	0.83 (0.60-1.15)	0.75 (0.53-1.05)	0.68 (0.48-0.96)	0.02

^＊Model 1: adjusted for age and sex.

^#Model 2: adjusted for BMI (fifths), energy intake (continuous), smoking (never, former, current smoking ＜20, and 20+ cigs/day), alcohol intake (never, former, current drinker ＜23, 23-45, 46-68, and 69+ g ethanol/day), walking (＜0.5, 0.5, 0.6-0.9, and 1+ hour/day), sports (＜1, 1-2, 3-4, and 5+ hours/week), education (＜12, 13-15, 16-18, and 19+ years), history of hypertension and diabetes (no, and yes, for each).

Mortality Surveillance

In each community, investigators systematically reviewed death certificates to identify the participant’s underlying cause of death. The registration of death is legally required and followed across Japan. Thus, all deaths that occurred in the cohort were ascertained by reviewing death certificates at a public health center unless participants died after moving out from their original community.

We used the underlying cause of death coded with the International Statistical Classification of Diseases and Related Health Problems–10^th Revision (ICD-10) to identify mortality endpoints: total stroke (I60-I69), coronary heart disease (CHD) (I20-I25), total CVD (I00-I99), cancer (C00-C97), and non-cancer and non-CVD deaths (neither C00-C97 nor I00-I99). The date of moving out from the community was verified by population register sheets. We treated 2,472 participants (4.2%) who moved out from their original communities during follow-up as censored cases.

Statistical Analysis

Person-years of follow-up were calculated from the baseline in 1988–1990 to their first endpoint in the follow-up as follows: death, moving out, or the end of follow-up. To minimize loss of sample size and non-responding bias, we conducted multiple imputation for missing values of dietary intakes and potential confounding factors. The percentage of missing data is shown in Supplementary Table 3. Since a large number of datasets is expected to achieve stable estimates and to improve the validity of the significance tests²⁹⁾, we created 20 imputed datasets using the PROC MI procedure and obtained a single estimate using the PROC MIANALYZE procedure.

Supplementary Table 3.The proportion of missing data for diet and potential confounding factors in the overall dataset

	Missing data (%)
No. at risk	58,672
Height	1,914 (3.3)
Weight	1,335 (2.3)
Smoking	3,567 (6.1)
Education	4,966 (8.5)
Exercise	1,899 (3.2)
Walking	3,823 (6.5)
History of hypertension	3,008 (5.1)
History of diabetes mellitus	3,761 (6.4)
Drinking alcohol	4,110 (7.0)
Miso soup	2,907 (5.0)
Beef	3,149 (5.4)
Pork	730 (1.2)
Ham and sausage	1,543 (2.6)
Chicken	1,419 (2.4)
Liver	3,678 (6.3)
Egg	244 (0.4)
Milk	349 (0.6)
Yogurt	4,574 (7.8)
Cheese	753 (1.3)
Butter	1,247 (2.1)
Margarine	1,475 (2.5)
Fries	733 (1.2)
Fried vegetables	921 (1.6)
Fresh fish	281 (0.5)
Kamaboko (fish paste)	4,429 (7.5)
Dried or salted fish	714 (1.2)
Spinach or garland chrysanthemum	354 (0.6)
Carrot or pumpkin	410 (0.7)
Tomatoes	1,041 (1.8)
Cabbage or head lettuce	343 (0.6)
Chinese cabbage	1,142 (1.9)
Edible wild plants	1,105 (1.9)
Fungi (enokidake, shiitake mushroom)	502 (0.9)
Potatoes	428 (0.7)
Algae (seaweeds)	440 (0.7)
Pickles	524 (0.9)
Tsukudani (preserved foods using soy sauce)	987 (1.7)
Boiled beans	637 (1.1)
Tofu (soybean curd)	173 (0.3)
Citrus fruits	567 (1.0)
Fresh fruits juice (in summer)	1,480 (2.5)
Fruits (excluding citrus variety)	1,893 (3.2)
Sweets	258 (0.4)
Salt preference	3,377 (5.8)

We examined the sex-specific association of the cHDS with all-cause and cause-specific mortality in the overall population. According to the cHDS, mean values and proportions of baseline characteristics were calculated. Their linear trend was tested using the linear regression model for mean values and the logistic regression model for proportions. HRs and 95% confidence intervals (CIs) for the risk of all-cause and cause-specific mortality were calculated using the Cox proportional hazards model, compared to the lowest score group.

We also examined the association of modified aHEI revision in 2010 (aHEI2010)⁵⁾ and JFGST¹⁰⁾ with CVD mortality to compare the strength of their associations. Calculation methods of modified aHEI2010 and JFGST were written in detail in Supplementary Methods. Model 1 was adjusted for age (continuous). Model 2 was further adjusted for body mass index (BMI) (fifths), energy intake (continuous), smoking (never, former, current smoking ＜20, and 20+ cigs/day), alcohol intake (never, former, current drinker ＜23, 23-45, 46-68, and 69+ g ethanol/day), walking (＜0.5, 0.5, 0.6-0.9, and 1+ hour/day), sports (＜1, 1-2, 3-4, and 5+ hours/week), education (＜12, 13-15, 16-18, and 19+ years), history of hypertension and diabetes (no, and yes, for each).

All analyses were performed using SAS version 9.4 (SAS Institute Inc., Cary, NC). All statistical tests were two-tailed, and P value ＜0.05 was considered significant.

Results

During 19.2 years of median follow-up, 6,291 men and 5,365 women died: 1,665 and 1,728 from CVD; 733 and 784 from stroke; 395 and 308 from CHD; 2,487 and 1,754 from cancer; and 2,139 and 1,883 from other cause deaths, respectively. Male and female participants with a higher cHDS had older age, and lower BMI, and were more likely to have regular exercise, high education, and a history of hypertension and diabetes, and less likely to have smoking and alcohol drinking habits (Table 3).

Table 3.Characteristics of study participants according to the concise healthy diet score (cHDS)

concise healthy diet score	Men					Women
	0-1	2	3	4	5	0-1	2	3	4	5
No. at risk	2,349	4,390	6,339	6,726	3,311	1,668	4,398	8,486	12,887	8,118
Age, years	53.9 (9.9)	55.5 (10.0)	55.9 (9.9)	56.7 (9.7)	57.3 (9.9)	55.8 (10.4)	55.9 (10.2)	56.2 (10.0)	56.3 (9.7)	56.5 (9.6)
BMI, kg/m2	22.6 (2.8)	22.7 (2.8)	22.7 (2.8)	22.7 (2.8)	22.7 (2.7)	22.8 (3.3)	23.0 (3.3)	22.9 (3.1)	23.0 (3.0)	22.8 (3.0)
Current smoking, %	60.9	57.6	55.3	51.1	47.2	8.4	6.1	4.9	3.8	3.1
Education: College or higher, %	14.9	17.5	17.7	19.4	22.6	5.7	8.1	9.4	11.0	13.2
Exercise: 5+ hrs/wk, %	5.1	6.0	7.1	7.5	7.4	4.0	3.5	4.4	4.3	4.5
Walking 1+ hr/d, %	43.8	47.6	48.3	50.1	46.5	46.9	49.0	49.4	50.4	48.2
History of hypertension, %	16.8	18.6	18.8	20.1	21.5	20.1	20.9	20.8	21.2	20.7
History of diabetes mellitus, %	4.5	5.5	6.1	6.4	7.2	3.2	3.3	3.0	3.1	3.7
Current drinking alcohol, %	75.5	76.4	75.9	75.0	71.9	16.7	16.6	15.9	15.0	15.6
Energy intake, kcal/day	1501 (476)	1626 (469)	1752 (482)	1854 (484)	1808 (430)	1211 (369)	1293 (358)	1406 (364)	1512 (365)	1480 (303)
Rice, bowls/day	3.6 (1.6)	3.7 (1.6)	3.8 (1.7)	3.7 (1.6)	3.5 (1.5)	3.2 (1.4)	3.0 (1.3)	3.0 (1.3)	2.9 (1.2)	2.8 (1.1)
Miso soup, cups/day	1.9 (1.7)	2.0 (1.7)	2.2 (1.7)	2.3 (1.7)	2.1 (1.6)	1.6 (1.6)	1.6 (1.5)	1.8 (1.5)	1.9 (1.4)	1.6 (1.2)
Meats, serving/week	0.4 (0.3)	0.5 (0.3)	0.5 (0.4)	0.6 (0.4)	0.6 (0.4)	0.4 (0.3)	0.5 (0.4)	0.6 (0.4)	0.6 (0.4)	0.6 (0.4)
Egg, serving/week	0.5 (0.4)	0.5 (0.4)	0.6 (0.4)	0.7 (0.3)	0.7 (0.3)	0.4 (0.3)	0.5 (0.4)	0.6 (0.4)	0.7 (0.4)	0.7 (0.3)
Dairy products, serving/week	0.5 (0.5)	0.5 (0.5)	0.6 (0.6)	0.7 (0.6)	0.8 (0.5)	0.5 (0.5)	0.6 (0.5)	0.7 (0.6)	0.8 (0.6)	0.9 (0.6)
Fresh fish, serving/week	0.2 (0.2)	0.3 (0.3)	0.5 (0.3)	0.6 (0.3)	0.7 (0.2)	0.2 (0.1)	0.3 (0.2)	0.4 (0.3)	0.6 (0.3)	0.7 (0.2)
Processed foods, serving/week	0.2 (0.3)	0.3 (0.3)	0.3 (0.3)	0.4 (0.3)	0.2 (0.2)	0.3 (0.3)	0.3 (0.3)	0.3 (0.3)	0.4 (0.3)	0.3 (0.2)
Vegetables, serving/week	0.9 (0.5)	1.3 (0.8)	1.8 (1.0)	2.5 (1.0)	2.8 (0.9)	1.0 (0.5)	1.4 (0.8)	2.0 (1.0)	2.6 (1.0)	2.9 (0.9)
Fungi, serving/week	0.1 (0.1)	0.2 (0.2)	0.2 (0.2)	0.3 (0.3)	0.3 (0.3)	0.1 (0.2)	0.2 (0.2)	0.2 (0.2)	0.3 (0.3)	0.4 (0.3)
Potatoes, serving/week	0.2 (0.2)	0.2 (0.2)	0.3 (0.3)	0.4 (0.3)	0.5 (0.3)	0.2 (0.2)	0.3 (0.3)	0.4 (0.3)	0.5 (0.3)	0.5 (0.3)
Algae, serving/week	0.2 (0.3)	0.3 (0.3)	0.5 (0.3)	0.6 (0.3)	0.6 (0.3)	0.3 (0.3)	0.4 (0.3)	0.5 (0.3)	0.6 (0.3)	0.7 (0.3)
Beans, serving/week	0.2 (0.2)	0.4 (0.3)	0.6 (0.4)	0.8 (0.4)	0.9 (0.4)	0.2 (0.3)	0.4 (0.3)	0.7 (0.4)	0.9 (0.4)	0.9 (0.4)
Fruits, serving/week	0.3 (0.2)	0.5 (0.5)	0.8 (0.6)	1.2 (0.6)	1.4 (0.5)	0.3 (0.3)	0.8 (0.6)	1.1 (0.6)	1.3 (0.6)	1.5 (0.5)
Fresh fruit juices, serving/week	0.2 (0.2)	0.2 (0.3)	0.3 (0.3)	0.4 (0.4)	0.3 (0.3)	0.2 (0.3)	0.2 (0.3)	0.3 (0.4)	0.4 (0.4)	0.3 (0.4)
Sweets, serving/week	0.2 (0.2)	0.2 (0.3)	0.3 (0.3)	0.3 (0.3)	0.3 (0.3)	0.2 (0.3)	0.3 (0.3)	0.4 (0.3)	0.4 (0.3)	0.4 (0.3)

Table 4 shows the association between groups by the cHDS and risks of mortality from all-cause, CVD, stroke, CHD, cancer, and other causes, along with HRs and 95% CIs. The cHDS was inversely associated with risks of mortality from all causes, and CVD in men and women, and further with stroke, CHD, and other causes in women. The multivariable HRs (95% CIs) comparing the lowest (0-1 points) and the highest (5 points) cHDS were 0.74 (0.60–0.91, P-trend=0.008) for CVD, 0.70 (0.52-0.96, P-trend=0.07), 0.81 (0.67-0.97, P-trend=0.12), and 0.86 (0.77-0.95, P-trend=0.05) for all causes in men. In women, those figures were 0.65 (0.52–0.81, P-trend＜0.001) for CVD, 0.63 (0.45–0.88, P-trend＜0.001) for stroke, 0.48 (0.30–0.78, P-trend=0.008) for CHD, 0.67 (0.54-0.84, P-trend＜0.001) for other causes, and 0.75 (0.66–0.85, P-trend＜0.001) for all causes.

Table 4.Hazard ratios of all-cause and cause-specific mortality according to the concise healthy diet score (cHDS)

	concise healthy diet score					P value for trend
	0-1	2	3	4	5
Men
No. at risk	2,349	4,390	6,339	6,726	3,311
Person-years	37,789	70,540	102,555	108,347	53,521
CVD (No. of deaths)	164	320	438	514	229
Model 1	1.00	0.90 (0.75-1.09)	0.80 (0.66-0.95)	0.81 (0.68-0.96)	0.67 (0.55-0.82)	＜0.001
Model 2	1.00	0.93 (0.77-1.13)	0.85 (0.71-1.03)	0.90 (0.75-1.08)	0.74 (0.60-0.91)	0.008
Stroke (No. of deaths)	73	131	207	223	99
Model 1	1.00	0.82 (0.62-1.10)	0.84 (0.64-1.09)	0.78 (0.60-1.02)	0.65 (0.48-0.88)	0.007
Model 2	1.00	0.84 (0.63-1.12)	0.89 (0.68-1.16)	0.85 (0.65-1.12)	0.70 (0.52-0.96)	0.07
CHD (No. of deaths)	34	84	106	117	53
Model 1	1.00	1.15 (0.77-1.72)	0.94 (0.64-1.38)	0.90 (0.62-1.33)	0.77 (0.50-1.18)	0.03
Model 2	1.00	1.23 (0.82-1.84)	1.06 (0.72-1.57)	1.09 (0.73-1.61)	0.91 (0.58-1.41)	0.29
Cancer (No. of deaths)	223	453	666	778	366
Model 1	1.00	0.99 (0.84-1.16)	0.94 (0.81-1.10)	0.98 (0.84-1.14)	0.89 (0.75-1.05)	0.22
Model 2	1.00	1.01 (0.86-1.18)	0.98 (0.84-1.15)	1.07 (0.91-1.24)	0.99 (0.83-1.17)	0.64
Other causes (No. of deaths)	205	384	590	658	302
Model 1	1.00	0.88 (0.74-1.04)	0.87 (0.74-1.02)	0.84 (0.72-0.98)	0.72 (0.60-0.86)	＜0.001
Model 2	1.00	0.91 (0.77-1.08)	0.94 (0.80-1.10)	0.95 (0.81-1.12)	0.81 (0.67-0.97)	0.12
Total deaths (No. of deaths)	592	1,158	1,694	1,951	897
Model 1	1.00	0.93 (0.84-1.02)	0.88 (0.80-0.96)	0.88 (0.80-0.97)	0.77 (0.69-0.85)	＜0.001
Model 2	1.00	0.95 (0.86-1.05)	0.93 (0.85-1.02)	0.98 (0.89-1.08)	0.86 (0.77-0.95)	0.05
Women
No. at risk	1,668	4,398	8,486	12,887	8,118
Person-years	27,775	73,093	139,954	216,967	136,671
CVD (No. of deaths)	114	242	465	564	343
Model 1	1.00	0.82 (0.65-1.03)	0.81 (0.66-0.99)	0.61 (0.50-0.74)	0.60 (0.49-0.75)	＜0.001
Model 2	1.00	0.85 (0.68-1.06)	0.82 (0.67-1.02)	0.65 (0.53-0.81)	0.65 (0.52-0.81)	＜0.001
Stroke (No. of deaths)	51	110	200	269	154
Model 1	1.00	0.82 (0.58-1.14)	0.76 (0.56-1.04)	0.64 (0.47-0.87)	0.60 (0.43-0.82)	＜0.001
Model 2	1.00	0.85 (0.61-1.19)	0.77 (0.56-1.06)	0.67 (0.49-0.92)	0.63 (0.45-0.88)	＜0.001
CHD (No. of deaths)	28	42	82	99	57
Model 1	1.00	0.57 (0.36-0.93)	0.58 (0.37-0.88)	0.43 (0.28-0.65)	0.40 (0.26-0.63)	＜0.001
Model 2	1.00	0.60 (0.37-0.97)	0.63 (0.41-0.98)	0.52 (0.34-0.82)	0.48 (0.30-0.78)	0.008
Cancer (No. of deaths)	84	202	424	640	404
Model 1	1.00	0.91 (0.71-1.18)	0.98 (0.78-1.24)	0.93 (0.74-1.17)	0.94 (0.74-1.19)	0.67
Model 2	1.00	0.92 (0.71-1.19)	1.00 (0.79-1.27)	0.96 (0.76-1.21)	0.97 (0.76-1.24)	0.99
Other causes (No. of deaths)	115	273	463	660	372
Model 1	1.00	0.91 (0.73-1.14)	0.79 (0.64-0.97)	0.69 (0.57-0.84)	0.64 (0.51-0.79)	＜0.001
Model 2	1.00	0.93 (0.75-1.16)	0.81 (0.66-1.00)	0.74 (0.61-0.92)	0.67 (0.54-0.84)	＜0.001
Total deaths (No. of deaths)	313	717	1,352	1,864	1,119
Model 1	1.00	0.88 (0.77-1.00)	0.84 (0.74-0.95)	0.72 (0.64-0.81)	0.70 (0.62-0.80)	＜0.001
Model 2	1.00	0.90 (0.78-1.03)	0.87 (0.77-0.99)	0.77 (0.68-0.87)	0.75 (0.66-0.85)	＜0.001

Model 1: adjusted for age and sex.

Model 2: adjusted for BMI (fifths), energy intake (continuous), smoking (never, former, current smoking ＜20, and 20+ cigs/day), alcohol intake (never, former, current drinker ＜23, 23-45, 46-68, and 69+ g ethanol/day), walking (＜0.5, 0.5, 0.6-0.9, and 1+ hour/day), sports (＜1, 1-2, 3-4, and 5+ hours/week), education (＜12, 13-15, 16-18, and 19+ years), history of hypertension and diabetes (no, and yes, for each).

To compare the associations for diet quality indices, we examined the sex-specific association with all-cause and cause-specific mortality in the overall population for the aHEI2010 and JFGST as well as the cHDS. The cHDS was inversely associated with CVD mortality in men and women (Table 5). The HRs of CVD mortality were lower with higher JFGST in women, but not in men. The aHEI2010 had no association in both men and women.

Table 5.Comparison of association for CVD mortality risk among cHDS, JFGST, and aHEI2010

	Q1	Q2	Q3	Q4	Q5	P value for trend
Men
cHDS, median (range)	1 (0-1)	2 (2)	3 (3)	4 (4)	5 (5)
No. at risk	2,349	4,390	6,339	6,726	3,311
Person-years	37,789	70,540	102,555	108,347	53,521
No. at risk of CVD deaths	164	320	438	514	229
Adjusted HR	1.00	0.93 (0.77-1.13)	0.85 (0.71-1.03)	0.90 (0.75-1.08)	0.74 (0.60-0.91)	0.008
JFGST, median (range)	37.4 (10.8-43.4)	46.7 (43.4-50.0)	52.5 (50.0-55.4)	57.9 (55.4-61.2)	64.4 (61.2-77.7)
No. at risk	8,182	5,703	4,155	3,007	2,068
Person-years	131,868	92,256	67,408	48,013	33,206
No. at risk of CVD deaths	504	409	327	251	174
Adjusted HR	1.00	1.00 (0.86-1.15)	0.99 (0.84-1.17)	0.97 (0.81-1.17)	0.88 (0.71-1.09)	0.31
aHEI2010, median (range)	40.8 (20.4-44.0)	46.4 (44.0-48.5)	50.5 (48.5-52.5)	54.7 (52.5-57.2)	61.4 (57.2-83.9)
No. at risk	3,593	3,784	4,260	4,894	6,584
Person-years	59,690	61,024	69,452	77,943	104,641
No. at risk of CVD deaths	233	244	297	387	504
Adjusted HR	1.00	0.94 (0.79-1.13)	0.92 (0.78-1.10)	1.05 (0.88-1.25)	0.96 (0.81-1.14)	0.86
Women
cHDS, median (range)	3.0 (0-3.0)	4.0 (4.0)	5.0 (5.0)	6.0 (6.0)	7.0 (7.0)
No. at risk	1,668	4,398	8,486	12,887	8,118
Person-years	27,775	73,093	139,954	216,967	136,671
No. at risk of CVD deaths	114	242	465	564	343
Adjusted HR	1.00	0.85 (0.68-1.06)	0.82 (0.67-1.02)	0.65 (0.53-0.81)	0.65 (0.52-0.81)	＜0.001
JFGST, median (range)	39.7 (17.7-43.4)	47.2 (43.4-50.0)	52.9 (50.0-55.4)	58.3 (55.4-61.2)	65.1 (61.2-79.2)
No. at risk	3,553	6,032	7,579	8,727	9,666
Person-years	57,033	99,383	126,035	146,616	165,391
No. at risk of CVD deaths	197	281	378	417	455
Adjusted HR	1.00	0.78 (0.64-0.95)	0.83 (0.68-1.00)	0.75 (0.62-0.90)	0.65 (0.53-0.80)	＜0.001
aHEI2010, median (range)	40.6 (21.6-44.0)	46.4 (44.0-48.5)	50.4 (48.5-52.5)	54.6 (52.5-57.2)	60.2 (57.2-84.9)
No. at risk	8,141	7,951	7,475	6,840	5,150
Person-years	138,481	133,589	125,300	113,664	83,424
No. at risk of CVD deaths	299	347	380	380	322
Adjusted HR	1.00	0.94 (0.81-1.11)	1.02 (0.87-1.19)	0.98 (0.84-1.15)	0.97 (0.83-1.15)	0.99

Adjusted for BMI (fifths), energy intake (continuous), smoking (never, former, current smoking ＜20, and 20+ cigs/day), alcohol intake (never, former, current drinker ＜23, 23-45, 46-68, and 69+ g ethanol/day), walking (＜0.5, 0.5, 0.6-0.9, and 1+ hour/day), sports (＜1, 1-2, 3-4, and 5+ hours/week), education (＜12, 13-15, 16-18, and 19+ years), history of hypertension and diabetes (no, and yes, for each).

Discussion

We developed a concise diet quality score named ‘concise Healthy Diet Score’ in the Japanese population and confirmed the inverse association of the cHDS with risks of mortality from total CVD, and all causes in men, and with mortality from stroke, CHD, total CVD, other causes, and all causes in women. This is the first study to develop a concise diet quality score which was useful for the prediction of CVD and all-cause mortality in Japanese.

Numerous dietary indices and their modifications have been proposed to assess overall diet quality representing nutrient recommendations, healthy dietary habits, and dietary variety³⁰⁾. The Healthy Eating Index (HEI) score was developed as an indicator of adherence to the Dietary Guidelines for Americans by the US Department of Agriculture in 1995 ³¹⁾ and revised in 2005 and every five years thereafter^32-34). The aHEI was developed based on epidemiological evidence for chronic disease by Harvard researchers in 2002 ⁴⁾ and revised in 2010 ⁵⁾. In Japan, the JFGST was developed in 2005 as an educational tool of the Dietary Reference Intakes for Japanese⁹⁾. Regarding CVD, the highest level of diet quality was associated with 19 (95%CI: 16-23) % lower risk for HEI³⁵⁾, 23 (20-26) % lower risk for aHEI³⁵⁾, and 16 (4-27) % lower risk for the JFGST¹⁰⁾, compared with the lowest level of diet quality. Similar to the previous indices, the presently developed score was associated with 33 (17-45) % lower CVD risk in men, and 29 (14-41) % lower risk in women, suggesting that the present score may have sufficient performance assessing diet quality similar to the previous indices.

There were several differences between the previous indices and the present score. First, we did not use alcohol intake as a component of our developed healthy diet score similar to most dietary indices. Because alcohol intake is known to have a J- or U-shaped association with CVD mortality^{36, 37)}. Second, intakes of whole grains and red meats were emphasized in the Western-origin diet quality indices, but not in the Japanese indices since intake levels of whole grains and red meats were much lower in Japan than in the Western countries. In 1990 when our cohort study started, the per capita consumptions in Japan were as low as a third of the US level for red meat (24.3 kg/year in Japan, and 72.5 kg/year in the US) and milk (78.0 kg/year, and 256.7 kg/year), and three-fold higher than the US level for fish consumption as a major source of n-3 fatty acid (47.5 kg/year, and 15.2 kg/year)³⁸⁾. In 2019, such a discrepancy between the US and Japan has been slightly smaller, but still not ignorable: the per capita consumptions were 32.1 kg/year in Japan, and 68.1 kg/year in the US for red meat; 64.8 kg/year, and 227.9 kg/year for milk; and 30.0 kg/year, and 13.0 kg/year for fish, respectively³⁹⁾. Therefore, we examined whether diet quality indices from different origins and CVD risk. Finally, we found the inverse association for the JFGST and present score, but not for modified aHEI2010. The differences in food availability or dietary background may explain no association for modified aHEI2010 in our population. On the other hand, our FFQ had only 35 food items and may be too concise to compare the association with CVD risk among three diet quality indices.

In the Japan Atherosclerosis Society Guidelines for Prevention of Atherosclerotic Cardiovascular Diseases 2022, daily intakes (80 g of fish, 80 g of beans, 225 g of fruits, and 400 g of vegetables) were recommended for individuals with high low-density lipoprotein cholesterol²³⁾. The serving size in our FFQ was 63 g of fresh fish, 50 g of beans, 80 g of fruits, and 47 g of vegetables, and the recommendation in cHDS was 3 times or more per week for fish and beans, once a day or more for fruits, and twice a day or more for vegetables. Therefore, compared with the Japan Atherosclerosis Society recommendation for high-risk individuals, the cHDS recommendation for primary prevention was aiming around one-third of the daily amount for fish, beans, and fruits, and a quarter of the daily amount for vegetables. Consuming the four foods more than the amounts in the cHDS recommendation should be encouraged for high-risk individuals.

Strength and Limitations

Our study had several strengths. A prospective cohort study design could control recall bias, and a large sample size could minimize the probability of alpha and beta errors.

Our study also had several limitations. First, measurement errors in dietary assessment were inevitable due to self-reporting and a limited number of food items in our FFQ. While our FFQ covered the major food items reported in the Japan National Nutrition Survey 1990 in Japan²⁰⁾ and had high reproducibility and low-to-moderate accuracy (the Spearman correlation coefficients were 0.20 (energy) to 0.46 (animal protein, potassium) compared with dietary records in 12 days (3 days in each season)²¹⁾. Second, the dietary intake and other lifestyle information were assessed only once at baseline. Dietary habits can alter over time, and these would result in misclassification. Finally, we developed a dietary score partially by the data-driven approach which could cause the over-fitting issue. Although we found a similar association between the developed dietary score and CVD mortality in derivation and validation data, the current dietary score may not fit with another population. In addition, some food groups in our FFQ contained a few food items. For example, grain contained only rice in the current population although other sources of carbohydrates were not ignorable: rice accounted for 197.9 g (70.0%) and wheat products such as bread and noodles for 84.8 g (30.0%) according to the Japan National Nutrition Survey in 1990 ²⁰⁾. The present dietary score will be used with some modifications such as replacing the rice score with the refined grain score in other populations. Furthermore, since the impact of each food item/group can change in the future, some food items/groups omitted from our dietary score would be added in the future.

Conclusion

In this study, we developed a concise dietary score for CVD prevention in the Japanese population. A higher cHDS was associated with a lower risk of mortality from total CVD, and all causes in men and with a lower risk of mortality from stroke, CHD, total CVD, other causes, and all causes in women. Future studies are needed to examine the association between the cHDS and the risk of chronic disease in other populations and the usefulness of that score in dietary modification.

Acknowledgement

The authors thank all staff members who were involved in this study for their valuable help in conducting the baseline survey and follow-up. This article was supported by the Clinical Investigator’s Research Project at the Osaka University Graduate School of Medicine.

The members of the JACC Study Group are as described below: The members of the JACC Study Group are as described below: Dr Akiko Tamakoshi (present chairperson of the study group), Hokkaido University Graduate School of Medicine; Dr. Mitsuru Mori, Hokkaido Chitose College of Rehabilitation; Dr. Kiyomi Sakata, Iwate Preventive Medical Association; Dr. Hiroyasu Iso, Institute for Global Health Medicine, Bureau of International Health Cooperation; Dr. Shogo Kikuchi, Aichi Medical University School of Medicine; Dr. Koji Suzuki, Fujita Health University School of Medical Sciences; Dr. Yoshihisa Fujino, University of Occupational and Environmental Health, Japan; Dr. Kenji Wakai, Nagoya University Graduate School of Medicine; Dr. Hiroki Amano, Tottori University Faculty of Medicine; Dr. Masahiko Ando, Nagoya University Hospital; Dr. Hironori Imano, Kindai University Faculty of Medicine; Dr. Satoshiue Okabayashi, Kyoto University Occupational Welfare Division; Dr. Kotaro Kosasa, Kyoto Prefectural University of Medicine; Dr. Kahiro Kaneko, National Center for Spiritual and Neurological Medicine Research; Dr. Michiko Kurosawa, Juntendo University Faculty of Medicine; Dr. Akira Shibata, Kyushu University; Dr. Kokoro Shirai, Osaka University Graduate School of Medicine; Dr. Sadao Suzuki, Nagoya City University Graduate School of Medicine; Dr. Naohito Tanabe, University of Niigata Prefecture Faculty of Human Life Studies; Dr. Koji Tamakoshi, Nagoya University Faculty of Health Sciences; Dr. Ichiro Tsuji, Tohoku University Graduate School of Medicine; Dr. Mariko Naito, Hiroshima University Graduate School of Biomedical & Health Sciences; Dr. Yosikazu Nakamura, Jichi Medical School; Dr. Yoshiharu Hoshiyama, Studies of Japan Child and Family Research Institute; Dr. Kazuya Mikami, Japanese Red Cross Kyoto Daiichi Hospital; Dr. Isao Muraki, Osaka University Graduate School of Medicine; Dr. Hiroshi Yatsuya, Fujita Health University School of Medicine; Dr. Kazumasa Yamagishi, Faculty of Medicine, University of Tsukuba; and Dr. Yasuhiko Wada, University of Kochi Faculty of Nutrition.

Conflict of Interest

The Authors declare that there is no conflict of interest.

Funding

This work was supported by Grants-in-Aid for Scientific Research from the Ministry of Education, Culture, Sports, Science and Technology of Japan (MEXT) (Monbu Kagaku-sho); Grants-in-Aid for Scientific Research on Priority Areas of Cancer; and Grants-in-Aid for Scientific Research on Priority Areas of Cancer Epidemiology from MEXT (Nos. 61010076, 62010074, 63010074, 1010068, 2151065, 3151064, 4151063, 5151069, 6279102, 11181101, 17015022, 18014011, 20014026, 20390156, and 26293138), and JSPS KAKENHI No. 16H06277 (CoBiA) and 22H04923. It was also supported by Grant-in-Aid from the Ministry of Health, Labour and Welfare, Health and Labor Sciences research grants, Japan (Research on Health Services: H17–Kenkou–007; Comprehensive Research on Cardiovascular Disease and Life-Style Related Diseases: H20-Junkankitou [Seishuu]-Ippan-013; H23-Junkankitou [Seishuu]-Ippan-005; H26-Junkankitou [Seisaku]-Ippan-001; H29-Junkankitou [Seishuu]-Ippan-003; 20FA1002; and 23FA1006); an Intramural Research Fund (22-4-5) for Cardiovascular Diseases of National Cerebral and Cardiovascular Center. The sponsors have no role in the study design, data collection, analysis or interpretation of data, writing the manuscript, or submission of the manuscript for publication.

Author Contribution

JN, IM, and HI designed the research. JN and IM conducted data analysis. JN drafted the initial manuscript. All authors made a critical revision and approved the final manuscript.

Supplementary Methods

Calculation of Diet Quality Indices

To compare the association of diet quality indices in the same population, we calculated the alternate Healthy Eating Index revision in 2010 (aHEI2010)¹⁾ and the Japan Food Guide Spinning Top (JFGST) score²⁾ in our population.

The modified aHEI2010 was calculated by summing 10 component scores. We excluded the whole grain component from the original AHEI2010 because of non-availability in our FFQ. Intakes of vegetables, fruit, nuts and legumes, long chain omega-3 fats (docosahexaenoic acid and eicosapentaenoic acid), and polyunsaturated fatty acids are positive components (higher the better). Intakes of sugar-sweetened drinks and fruit juice, red and processed meat, trans fat, and sodium are inverse components (lower the better). The ideal alcohol intake is a small amount. Each component scored from 0 to 10 linearly according to their intake levels. Supplementary Table 4 showed intake levels for scores 0 and 10 and food items used for each component.

Supplementary Table 4.Included food items and intake levels for minimum and maximum scores according to AHEI2010 components in the current study

Components	Score 0	Score 10	Food items used in the current study
Vegetables, servings/d	0	≥ 5	Spinach or garland chrysanthemum, carrot or pumpkin, tomatoes, cabbage or head lettuce, Chinese cabbage, edible wild plants, fungi (enokidake, shiitake mushroom), potatoes, algae (seaweeds), pickles, tsukudani (preserved foods using soy sauce)
Fruits, servings/d	0	≥ 4	Citrus fruits, other fruits (excluding citrus variety)
Sugar-sweetened beverage and fruit juice, servings/d	≥ 1	0	Fresh fruit juice
Nuts and legumes, servings/d	0	≥ 1	Boiled beans, tofu (soybean curd)
Red and processed meats, servings/d	≥ 1.5	0	Beef, pork (excluding ham or sausage), ham or sausage, liver
trans fat, % of energy	≥ 4	≤ 0.5	Palmitoleic acid, oleic acid, linoleic acid, icosenoic acid, alpha-linolenic acid
Long-chain (n-3) fats, mg/d	0	250
Poly-unsaturated fatty acid, % of energy	≤ 2	≥ 10
Sodium, mg/d	Highest decile	Lowest decile
Alcohol, drinks/d
Women	≥ 2.5	0.5-1.5
Men	≥ 3.5	0.5-2.0

The JFGST score was calculated according to the previous publication from the JPHC study²⁾. The JFGST score was adherence to a Japanese food guide calculated from eight components: total energy, grain dishes, vegetable dishes, fish and meat dishes, dairy products, fruits, sweets and alcoholic beverages, and the white-to-red meat ratio. The recommended intake levels were determined by sex, age, and physical activity level for components other than sweets and alcoholic beverages. The recommended intake levels and the serving sizes were listed in Supplementary Table 5. Physical activity levels are divided into moderately physically active, and sedentary. Moderately physically active is determined when individuals engage in manual labour or walk one hour a day or longer. Sedentary means not moderately physically active. The component score increases linearly from no intake (score 0) to the recommended intake level (score 10) and decreases linearly over that level up to a two-fold recommended intake level (score 0). Each component score is rounded off to the nearest integer. Grain dishes included rice. Vegetable dishes included spinach and garland chrysanthemum, carrot and pumpkin, tomatoes, cabbage and head lettuce, Chinese cabbage, edible wild plants, fungi (enokidake, shiitake mushroom), potatoes, algae (seaweeds), pickles, and tsukudani (preserved foods using soy sauce). Fish and meat dishes included beef, pork (excluding ham and sausage), ham and sausage, chicken, liver, eggs, fresh fish, kamaboko (fish paste), dried or salted fish, boiled beans, and tofu (soybean curd). Dairy products included milk, yogurt, cheese, and milk in tea and coffee. Fruits included citrus fruits, other fruits (excluding citrus variety), and fresh fruit juice (in summer). Sweets and alcoholic beverages included sweets, sugar in tea and coffee, and alcoholic beverages. White meat included chicken, fresh fish, kamaboko (fish paste), and dried or salted fish. Red meat included beef, pork (excluding ham and sausage), ham and sausage, and liver.

Supplementary Table 5.Included food items and intake levels for minimum and maximum scores according to JFGST components in the current study

Components	Serving size	Persons aged ≥ 70; sedentary women1		Sedentary men1; moderately active women1		Moderately active men1
		Score 0	Score 10	Score 0	Score 10	Score 0	Score 10
Total energy, kcal/d	-	≥ 4000	1600-2000	≥ 4800	2000-2400	≥ 5600	2400-2800
Grain dishes,2 servings/d	40 g carbohydrate	0 or ≥ 10	4-5	0 or ≥ 14	5-7	0 or ≥ 16	7-8
Vegetable dishes,3 servings/d	70 g wet weight of vegetables	0	≥ 5	0	≥ 5	0	≥ 6
Fish and meat dishes,4 servings/d	6 g protein	0 or ≥ 8	3-4	0 or ≥ 10	3-5	0 or ≥ 8	4-6
Dairy products,5 servings/d	100 mg calcium	0 or ≥ 4	2	0 or ≥ 4	2	0 or ≥ 6	2-3
Fruits,6 servings/d	100 g wet weight of fruits	0	≥ 2	0	≥ 2	0	≥ 2
Snacks and alcoholic beverages,7 kcal/d	-	≥ 400	≤ 200	≥ 400	≤ 200	≥ 400	≤ 200
White-to-red meat ratio8	-	0	≥ 4	0	≥ 4	0	≥ 4

1 Aged 18- 69. 2 Calculated from rice. 3 Calculated from spinach and garland chrysanthemum, carrot and pumpkin, tomatoes, cabbage and head lettuce, Chinese cabbage, edible wild plants, fungi (enokidake, shiitake mushroom), potatoes, algae (seaweeds), pickles, and tsukudani (preserved foods using soy sauce). 4 Calculated from beef, pork (excluding ham and sausage), ham and sausage, chicken, liver, eggs, fresh fish, kamaboko (fish paste), dried or salted fishes, boiled beans, and tofu (soybean curd). 5 Calculated from milk, yogurt, cheese, and milk in tea and coffee. 6 Calculated from citrus fruits, other fruits (excluding citrus variety), and fresh fruit juice (in summer). 7 Calculated from sweets, sugar in tea and coffee, and alcoholic beverages. 8 Calculated based on wet weight grams.

Supplementary References

1)Chiuve SE, Fung TT, Rimm EB, Hu FB, McCullough ML, Wang M, Stampfer MJ, Willett WC: Alternative dietary indices both strongly predict risk of chronic disease. J Nutr, 2012; 142: 1009-1018

2)Kurotani K, Akter S, Kashino I, Goto A, Mizoue T, Noda M, Sasazuki S, Sawada N, Tsugane S, Japan Public Health Center based Prospective Study G: Quality of diet and mortality among Japanese men and women: Japan Public Health Center based prospective study. BMJ, 2016; 352: i1209

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