loader
Home/
Journal of Obesity Treatment and Weight Management

Full Text


Research Article

Frequent Nutritional Intervention to Encourage Consumption of Traditional Vegetables in Japanese with Non-Alcoholic Fatty Liver Disease Greatly Increased Vegetable Intake and Reduced BMI: A Six-Month Trial Study

Yukiko Kobayashi, Yuka Ueda, Yuki Sumi, Hina Tatsumi, Yukiko Sasai, Hiroki Sugiyama, Sayori Wada, Wataru Aoi, Koji Shirota, Michiyo Tani, Yoshiaki Shizukawa, Yuya Seko, Yoshio Sumida, Yuji Naito, Masashi Kuwahata

Correspondence Address :

Yukiko Kobayashi
Laboratory of Nutrition Science
Graduate School of Life and Environmental Sciences
Kyoto Prefectural University
Shimogamo, Sakyo, Kyoto 606-8522, Japan
Tel: +81-75-703-6017
Email: yukicoba@kpu.ac.jp

Received on: February 28, 2018, Accepted on: March 08, 2018, Published on: March 15, 2018

Citation: Yukiko Kobayashi, Yuka Ueda, Yuki Sumi, et al. (2018) Frequent Nutritional Intervention to Encourage Consumption of Traditional Vegetables in Japanese with Non-Alcoholic Fatty Liver Disease Greatly Increased Vegetable Intake and Reduced BMI: A Six-Month Trial Study

Copyright: 2018 Yukiko Kobayashi et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

  • Abstract

  • Fulltext

  • References

  • Tables & Figures

  • Download PDF

Abstract
Background/purpose: In the present study, a method of frequently sending small amounts of vegetables to patients with non-alcoholic fatty liver disease (NAFLD) was selected to encourage continuation of dietary treatment. Furthermore, the hypothesis that frequent receipt of traditional vegetables known to have a high scarcity value would have a strong impact that results in an actual increase in vegetable consumption was tested.
Methods: Twenty NAFLD patients were divided into two groups: Group A, which received seasonal vegetables including traditional vegetables about twice a month to their home, half of the time accompanied by a newsletter containing information about vegetables and a body weight record sheet; and Group B, which did not. All subjects were given nutritional counseling at the start of the intervention (baseline) and during doctors' visits about once every three months. Subjects were asked to submit meal records and photos for two days to evaluate nutrient intakes at baseline and after 3 and 6 months of intervention. Blood tests and BMI were also followed.
Results: The mean age of the subjects was 58.5 +/- 10.3 years. In Group A, total vegetable intake was significantly higher after three months and six months compared to baseline, which led to a body weight reduction.
Conclusion: The effects on NAFLD patients of carrying out a unique nutritional intervention of frequently providing them with vegetables with a high scarcity value that leave a strong impression, in addition to their doctors' visits and nutritional counseling, were assessed, and this method promoted a decrease in body weight

Keywords: NAFLD, Weight loss, Nutritional interventions, Vegetable intake, Traditional vegetables, dietary intakes, Japanese
Fulltext
Introduction
Non-alcoholic fatty liver disease (NAFLD) is one of the most common chronic liver diseases in many advanced nations and has become a serious public health concern worldwide [1-3]. As the obesity rate increases, the number of people with NAFLD has been increasing around the globe, including in Japan [4,5]. According to the Japan Study Group of NAFLD (JSG-NAFLD), 29.7% of people screened had NAFLD [6,7]. The initial manifestation of NAFLD is a fatty liver caused by over-accumulation of triglycerides in hepatocytes.
NAFLD is a multifactorial disease caused by complex interactions among genetics, diet, lifestyle habits, and other factors. Accordingly, many studies have found activities to improve lifestyle habits, reduce weight, and increase physical activity to be effective, and weight reduction has been reported to improve liver function in patients with NAFLD [8-11]. In the clinical guidelines released by the Japanese Society of Gastroenterology, three to twelve months of dieting and exercise therapy to lose weight is recommended for improving liver function and making histological improvements in those with NAFLD (evidence level A) [12]. In a recent study, 31 patients diagnosed histologically with non-alcoholic steatohepatitis (NASH) were randomly divided into groups to undergo 48 weeks of diet and exercise treatment. Their weight decreased a mean of 9.3%, and their NAFLD Activity Score (NAS) improved [13]. However, the Japanese guidelines prioritize proper energy intake, and the only proposal for the rate of nutritional intake is to restrict fat [12]. No concrete clinical nutritional treatment has been established for NAFLD, and there is no agreement on the best approach to diet for people with NAFLD.
Meanwhile, in a previous study we found that people with NAFLD have a lower intake of vitamins, minerals, and dietary fiber than the average Japanese person, and that the reason is a low consumption of vegetables that contain these nutrients [14]. Moreover, we found that people with NAFLD had an excessive energy intake, low vegetable intake, and excessive fruit and snack intake compared to people with diabetes [15]. We therefore hypothesized that, for people with NAFLD, (1) as a result of a decrease in energy density from meals due to an increase in vegetable intake, (2) the total amount of energy at meals would drop, (3) weight would decrease, and (4) the pathological condition would improve. In the present study, a frequent nutritional intervention was performed on NAFLD patients for six months to strongly encourage consumption of vegetables while also providing nutritional counseling, and the changes in vegetable intake, nutritional intake, and physical condition were analyzed in Japanese people with NAFLD. Sending newsletters to specific groups of people is often used as a method to encourage consumption of vegetables in target populations. In the present study, a method of frequently sending small amounts of vegetables to the target population was selected as a nutritional educational tool to strongly evoke continuation of dietetic treatment. In addition, the hypothesis that frequent receipt of traditional vegetables known to have a high scarcity value would have a strong impact that results in an actual increase in vegetable consumption was tested.

Experimental Method

Subjects

This study enrolled NAFLD subjects receiving treatment at the University Hospital, Kyoto Prefectural University of Medicine (Kyoto, Japan). NAFLD was diagnosed on the basis of liver biopsy (performed according to clinical judgment) or transient elastography (FibroScan; Echosens, Paris, France) [16-21] and a patient report of alcohol intake <30 g/day for males and <20 g/day for females [22]. Those diagnosed with NASH stage 4 (cirrhosis) [23] or diabetic nephropathy were excluded. Of the outpatients visiting the department between August 2013 and April 2014, 101 met the requirements. Of those, 81 were excluded from the present study due to transfer to another hospital or participation in another study, leaving a final sample of 20 subjects (8 men and 12 women) who gave consent to participate in the study. Subjects were divided by sex and then randomly allocated to intervention Group A or intervention Group B. Group A had 11 subjects (4 men and 7 women), and Group B had 9 subjects (4 men and 5 women). By the end of the intervention period, two subjects were excluded due to missing data, and two dropped out from the protocol, leaving ten people in Group A (three men and seven women) and six people in Group B (one man and five women) for analysis. The study was approved by the Kyoto Prefectural University Ethics Committee (no. 73) and Kyoto Prefectural University of Medicine Ethics Committee (ERB-C-242).

Nutritional Intervention Protocol

All subjects were given nutritional counseling at the start of the intervention (baseline) and during doctors' visits about once every three months. In addition, subjects in Group A were sent seasonal vegetables including traditional vegetables about twice a month to their home, half of the time accompanied by a newsletter containing information about vegetables and a body weight record sheet. The vegetables used in this study were harvested at the Kyoto Prefectural Agriculture, Forestry and Fisheries Technology Center (Kameoka, Kyoto, Japan), and seasonal vegetables including traditional vegetables were sent in a package weighing about 1 kg. This package was used as a nutritional educational tool aimed at creating frequent opportunities to obtain vegetables to be used in whatever way the subjects desired. Among vegetables grown in Kyoto, there are many varieties of Kyo-yasai (Kyoto vegetables), a traditional vegetable with a distinctive shape that is well-known for having high nutritional value and for being expensive. In the present study, packages sent to subjects contained traditional vegetables of the current season, such as eggplant (kamo-nasu), sweet peppers (manganji-tougarashi), carrots (kintoki-ninjin), daikon radish (shogoin-daikon), and edamame (murasakizukin).

Food Surveys

Subjects were asked to submit meal records and photos for two days. Data from the start of the intervention were used as the baseline values, and subjects were again asked to submit such data after three and six months of intervention. The weight of foods was estimated based on the meal record sheets and photos, and nutrition calculation software (Excel Eiyokun Ver. 6.0, Kenpakusha, Tokyo, Japan) was used to calculate the nutritional value. Daily mean nutritional intake and daily mean intake per food group were calculated. For nutritional intake, 26 items were calculated: energy, energy per standard body weight, protein, fat, saturated fatty acids, cholesterol, carbohydrates, total dietary fiber, retinol equivalent, vitamin D, vitamin B1, vitamin B2, niacin, vitamin B6, vitamin B12, vitamin C, sodium chloride equivalent, potassium, calcium, magnesium, phosphorus, iron, zinc, proteinenergy ratio, fat-energy ratio, and carbohydrate-energy ratio. To calculate intake per food group, foods were categorized into 18 food groups: grains and cereals (including rice and noodles), potatoes, sugar and sweeteners, nuts, green and yellow vegetables, other vegetables, fruits, mushrooms, algae, pulses, fish and shellfish, meat, eggs, milk, oils and fats, confectionery, and beverages.

Nutritional Counseling

All subjects were given nutritional counseling for 30 min per time by the same registered dietitian. Instruction comprised information on correcting the total energy intake and proteinfat- carbohydrate (PFC) ratio according to the dietetic treatment for obesity and diabetes. In addition, subjects were given personalized diet counseling based on the meal records they submitted.

Subjects' Physical Condition

With respect to the subjects' physical condition, the presence of concomitant illnesses, medications, and progress of the disease were determined from electronic health records during the doctors' visits. In addition, subjects' height and weight were measured with measuring equipment. BMI was calculated using the formula body weight (kg)/[height (m)]2.

Biochemical Blood Examinations

Biochemical blood examination results were determined from the electronic health records. Test items were aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyl transpeptidase (γGTP), albumin, and HbA1c.

Statistical Analysis

All analyses were performed with statistical analysis software (IBM SPSS Statistics 22.0, IBM, Armonk, NY, USA.) To compare the results from meal surveys, physical measurements, and biochemical blood examinations at the start of intervention and after three and six months of intervention, data with a normal distribution were analyzed with paired t-tests, and data with a non-normal distribution were analyzed with the Wilcoxon signed rank sum test. To compare the results from meal surveys, physical measurements, and biochemical blood examinations between Group A and Group B, data with a normal distribution were analyzed with non-paired t-tests, and data with a non-normal distribution were analyzed with the Mann-Whitney U test. To examine bivariate correlations, data with a normal distribution were analyzed with Pearson product-moment correlation coefficients, and data with a non-normal distribution were analyzed with Spearman's rank correlation coefficients. The level of significance was 5%.


Results

Characteristics

Table 1 shows the age, sex, BMI, and blood examination data for Group A and Group B at baseline. The mean age of the subjects was 58.5 +/- 10.3 years. No significant differences between groups were observed in BMI or blood test results.
Comparison of Dietary Intake from Before to after Intervention Table 2 shows daily dietary intake for each food group at baseline and after three months of intervention and the change in intake. For intake by food group, no significant differences between Group A and Group B were observed in any values at baseline. Comparing pre- and post-intervention, total vegetable intake and intake of other vegetables increased significantly (p = 0.022, p = 0.020), and intake of confectionery decreased significantly (p = 0.043) in Group A. In contrast, no significant changes were seen in any item in Group B. Comparing Group A and Group B after three months of intervention showed that total vegetable intake and intake of other vegetables were significantly higher for Group A (p = 0.037, p = 0.038). Regarding the amount of change over the three months, intake of other vegetables increased significantly (p = 0.038), and intake of confectionery decreased significantly (p = 0.011) in Group A compared to Group B. For dietary intake, no significant differences between Group A and Group B were observed in any values at baseline. Comparing pre- and post-intervention, intakes of potassium, vitamin B6, and vitamin C increased significantly in Group A (p = 0.037, p < 0.001, p = 0.048). In contrast, no significant changes were seen in any item in Group B. Comparing Group A and Group B after three months of intervention showed that intakes of calcium, phosphorus, vitamin B2, and dietary fiber increased significantly in Group A (p = 0.009, p = 0.003, p = 0.049, p = 0.040). Regarding the amount of change over the three months, intake of vitamin C increased significantly (p = 0.048) in Group A compared to Group B. In Group A, energy intake was slightly lower after three months compared to baseline (p = 0.090).
Table 3 shows daily dietary intake for each food group at baseline and after six months of intervention and the change in intake. Comparing pre- and post-intervention for intake by food group, total vegetable intake increased significantly in Group A (p = 0.039). In contrast, no significant changes were seen in any item in Group B. Comparing Group A and Group B after six months of intervention did not show any significant intergroup differences in any item. For the amount of change during the six months, no significant differences between Group A and Group B were observed. Comparing pre- and post-intervention for nutritional intake, fat intake and the PFC-F ratio increased significantly in Group A (p = 0.039, p = 0.031). Comparing Group A and Group B after six months of intervention did not show any significant intergroup differences in any item (Figure 1).

Relationships between Vegetable Intake, Energy Intake, and BMI

The relationships between vegetable intake, energy intake, and BMI for both groups are shown in Figure 1. After three months of intervention, a significant negative correlation was observed between the amount of change in total vegetable intake and in energy intake (r = -0.692, p = 0.003, Figure 1A). In addition, a significant positive correlation was observed between the amount of change in energy intake and in BMI (r = 0.546, p = 0.029, Figure 1B). In contrast, after six months of intervention, no significant correlations were observed between the amount of change in total vegetable intake and in energy intake (Figure 1C) or between the amount of change in energy intake and in BMI (Figure 1D).


Changes in Vegetable Intake, energy intake, and Body Weight in Both Groups

A comparison of vegetable intake and the amount of change in vegetable intake in both groups is shown in Figure 2. In Group A, total vegetable intake was significantly higher after three months and six months compared to baseline (p = 0.022, p = 0.039). In comparison, it was the same level as baseline after three months and six months in Group B (Figure 2A). When comparing the amount of change in vegetable intake between Group A and Group B, the amount of change was slightly higher in Group A than in Group B after both three months and six months, although these differences were not significant (p = 0.081, p = 0.119, Figure 2B). The rate of energy increase and decrease in subjects is shown in Figure 3A. The rate of subjects whose energy intake decreased was 80% in Group A and 50% in Group B after three months of intervention and 50% in Group A and 33% in Group B after six months of intervention.
The rate of body weight increase and decrease in subjects is shown in Figure 3B. The rate of those who lost at least 1 kg in body weight and maintained their body weight within 1 kg after three months of intervention was 90% in Group A and 83% in Group B. The rate of those who lost at least 1 kg in body weight and maintained their body weight within 1 kg after six months of intervention was 80% in Group A and 66% in Group B.

Discussion

In the present study, the effects on NAFLD patients of performing frequent nutritional intervention in addition to their doctors' visits and nutritional counseling were assessed. An approach of frequently providing seasonal vegetables with a high scarcity value was used. NAFLD patients who received the frequent nutritional intervention showed a significant increase in vegetable intake that led to a body weight reduction. This therefore demonstrates that our unique approach to nutritional intervention strongly helps increase vegetable intake and may greatly improve the pathological condition through a reduction in BMI.
In the present study, both Group A and Group B received nutritional counseling, and the relationships among vegetable intake, energy intake, and body weight change were examined in all subjects. The relationship between amount of change in total vegetable intake and that in energy intake was examined after three months of intervention, and a significant negative correlation was observed between these variables, with a significant positive correlation between the amount of change in energy intake and the amount of change in BMI. This appears to support our hypothesis. In other words, nutritional counseling in patients with NAFLD may lead to a greater decrease in BMI with increasing vegetable intake.
Next, whether frequent nutritional intervention was useful for decreasing body weight was investigated. In Group A, which received frequent nutritional intervention, total vegetable intake increased significantly after three and six months of intervention compared to baseline. Total vegetable intake did not increase in Group B over six months of intervention. The reason for this difference may be the increase in light-colored vegetables in Group A. Not only was the absolute quantity of light-colored vegetables higher in Group A than in Group B, but the amount of change also increased significantly.
Even more detailed investigation showed that total vegetable intake increased in seven of ten subjects in Group A after three months of intervention and increased in two of the remaining three subjects in this group after six months of intervention. This means that frequent nutritional intervention to encourage vegetable consumption led to an increase in vegetable intake, and that this effect was sustained for the duration of the halfyear intervention period. Energy intake in Group A decreased slightly, although not significantly, compared to baseline after three months of intervention. The reason for this may be that the vegetable intake increase in Group A caused a reduction in the energy density of the meals overall. In addition, the absolute quantity of confectionery intake in Group A after three months of intervention and the amount of change from pre- to postintervention were significantly lower compared to Group B, suggesting a decrease in intake of high energy foods. Moreover, the ratio of subjects whose energy intake decreased was 30% higher in Group A than in Group B after three months, indicating that the reduction in energy intake was more pronounced in Group A than in Group B. This indicates that frequent nutritional intervention to encourage vegetable consumption may contribute to weight loss that is useful in improving disease symptoms, and that the effects may be used by combining regular doctor's visits with nutritional counseling.
That said, no correlations were observed among vegetable intake, energy intake, and weight change in subjects overall after six months of intervention. Energy intake did not decrease in either Group A or Group B after six months of intervention. In particular, the mean energy intake in Group A remained about the same as at baseline after six months of intervention, despite a sustained increase in vegetable intake over that period. The reason for this may be that both fat intake and the fat-energy ratio increased significantly. Specifically, the frequency of consumption of confectionery and fried foods decreased after three months of intervention, but it was about the same as baseline or slightly higher after six months of intervention. However, since the ratio of those whose energy intake decreased after six months of intervention was higher in Group A than in Group B, individual differences likely play a large role.
In the present study, nutritional intervention to strongly encourage vegetable consumption may have helped improve the pathological condition and reduce body weight.
However, individual differences manifest slightly after three months of intervention and even more after six months. This may be the result of individual differences in (1) perceptions about fat intake restriction and (2) stage of behavior change. In our previous research, characteristics of eating behavior found in people with NAFLD were low vegetable consumption, high consumption of sweet foods, and a high BMI, i.e. habitual overconsumption of energy [15]. These results suggest that a proper diet did not become a habit for all subjects in the present study, and that some mechanism is needed to cope with the desire for fatty foods. The reason for this is unclear and could be due to a lack of knowledge about nutrition, eating behavior being particularly susceptible to the effects of some factor, or the inability to restrict one's appetite, for example. It should be determined whether this phenomenon is peculiar to NAFLD. Furthermore, understanding of stage of behavior change in patients can lead to success in diet behavior modification [24-27]. It was not possible to examine the stage of behavior change in the present study. Although the approach of providing vegetables to encourage patients has some effect, further investigation is needed to determine a method for supporting modification of eating behavior in NAFLD patients that includes a method for coping with the appetite for fatty foods. Another limitation of this study was the small sample size.
This was a pilot study, and the sample size needs to be increased for further observation. In addition, only the effects on nutrition and physical characteristics were examined, and pathological markers were not compared. The present study was a short-term investigation. Longer term intervention should be carried out in order to monitor the effects up to improvement of the disease. In
the present study, traditional vegetables with a high scarcity value were used as a nutritional educational tool to strongly encourage subjects, and a strong impression was left on the subjects. This is one strength of the present study. Had only vegetables that were available in town been used in the intervention, the same results may not have been obtained.

Conclusion

The effects on NAFLD patients of carrying out a unique nutritional intervention approach of frequently providing patients with vegetables with a high scarcity value that leave a strong impression in addition to their doctors' visits and nutritional counseling were assessed, and this method was found to promote a decrease in body weight. This suggests that this form of nutritional intervention is a useful nutritional treatment method for improving the pathological condition by having NAFLD patients increase their vegetable intake on their own. These research results may contribute to the establishment of dietetic treatment for people with NAFLD as one method for delaying the need for medication.

Acknowledgments

This work was supported by "KPUM-KPU Collaborative Research Program" from Kyoto prefectural Public University corporation. (Kyoto, Japan).

References
1. Williams CD, Stengel J, Asike MI, et al. Prevalence of Nonalcoholic Fatty Liver Disease and Nonalcoholic Steatohepatitis Among a Largely Middle-Aged Population Utilizing Ultrasound and Liver Biopsy: A Prospective Study. Gastroenterology. 2011:140(1):124-131.
2. Radu C, Grigorescu M, Crisan D, et al. Prevalence and associated risk factors of non-alcoholic fatty liver disease in hospitalized patients. J Gastrointestin Liver Dis. 2008;17(3):3255-3260.
3. Vernon G, Baranova A, Younossi ZM. Systematic review: the epidemiology and natural history of non-alcoholic fatty liver disease and non-alcoholic steatohepatitis in adults. Aliment Pharmacol Ther. 2011;34:274-285.
4. Hamaguchi M, Kojima T, Takeda N, et al. The metabolic syndrome as a predictor of nonalcoholic fatty liver disease. Ann Intern Med. 2005;143(10):722-728.
5. Hamabe A, Uto H, Imamura Y, et al. Impact of cigarette smoking on oset of nonalcoholic fatty liver disease over a 10-year period. J Gastroenterol. 2011;46:769-778.
6. Eguchi Y, Hyogo H, Ono M, et al. Prevalence and associated metabolic factors of nonalcoholic fatty liver disease in the general population from 2009 to 2010 in Japan: a multicenter large retrospective study. J Gastroenterol. 2012;47(5):586-595.
7. Sumida Y, Nakajima A, Itoh Y. Limitations of liver biopsy and non-invasive diagnostic tests for the diagnosis of nonalcoholic fatty liver disease/ nonalcoholic steatohepatitis. World J Gastroenterol. 2014;20(2):475-485.
8. Musso G, Gambino R, De Michieli F, et al. Dietary habits and their relations to insulin resistance and postprandial lipemia in nonalcoholic steatohepatitis. Hepatology. 2003;37(4): 909-916.
9. Clark JM. Weight loss as a treatment for nonalcoholic fatty liver disease. J Clin Gastroenterol. 2006 40 Suppl 1:S39-S43.
10. Hollingsworth KG, Abubacker MZ, Joubert I, Allison ME, Lomas DJ. Lowcarbohydrate diet induced reduction of he- patic lipid content observed with a rapid non-invasive MRI technique. Br J Radiol. 2006;79(945):712-715.
11. Nseir W, Hellou E, Assy N. Role of diet and lifestyle changes in nonalcoholic fatty liver disease. World J Gastroenterol. 2014;20(28):9338-9344.
12. Watanabe S, Hashimoto E, Ikejima K, et al. Evidence-based clinical practice guidelines for nonalcoholic fatty liver disease/nonalcoholic steatohepatitis. Hepatology res. 2015;45:363-377.
13. Promrat K, Kleiner DE, Niemeier HM, et al. Randomized con-trolled trial testing the effects of weight loss on nonalcoholic steatohepatitis. Hepatology. 2010;51(1):121-129.
14. Tatsumi H, Kobayashi Y, Wada S, et al. Assessment of dietary factor in Japanese non-alcoholic fatty liver disease patients using Dietary Reference Intake and relationship with blood parameters. Ann Nutr Metab. 2013;63:s301.
15. Kobayashi Y, Tatsumi H, Hattori M, et al. Comparisons of dietary intake in Japanese with non-alcoholic fatty liver disease and type 2 diabetes mellitus. J Clin Biochem Nutr. 2016;59(3):215-219.
16. Berends MA, Snoek J, de Jong EM, et al. Biochemical and biophysical assessment of MTX-induced liver fibrosis in psoriasis patients: Fibrotest predicts presence and Fibroscan predicts the absence of significant liver fibrosis. Liver Int. 2007;27(5):639-645.
17. Lupşor M, Badea R, Ştefănescu H, et al. Analysis of histopatological changes that influence liver stiffness in chronic hepatitis C Results from a cohort of 324 patients. J Gastrointestin Liver Dis. 2008;17(2):155-163.
18. Kim KM, Choi WB, Park SH, et al. Diagnosis of hepatic steatosis and fibrosis by transient elastography in asymptomatic healthy individuals: a prospective study of living related potential liver donors. J Gastroenterol. 2007;42(5):382-388.
19. Yoneda M, Fujita K, Inamori M, et al. Transient elastography in patients with non-alcoholic fatty liver disease (NAFLD). Gut. 2007;56(9):1330-1331.
20. Rockey DC. Noninvasive assessment of liver fibrosis and portal hypertension with transient elastography. Gastroenterology. 2008;134(1):8-14.
21. Ogawa E, Furusyo N, Toyoda K, et al. Transient elastography for patients with chronic hepatitis B and C virus infection: Non-invasive, quantitative assessment of liver fibrosis. Hepatol Res. 2007;37(12):1002-1010.
22. Watanabe S, Hashimoto E, Ikejima K, et al. Japanese Society of Gastroenterology; Japan Society of Hepatology. Evidence-based clinical practice guidelines for nonalcoholic fatty liver disease/nonalcoholic steatohepatitis. J Gastroenterol. 2015;50(4):364-377.
23. Kleiner DE, Brunt EM, Van Natta M, et al. Nonalcoholic Steatohepatitis Clinical Research Network. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology. 2005;41(6):1313-1321.
24. Jones H, Edwards L, Vallis TM, et al. Diabetes Stages of Change (DISC) Study. Changes in diabetes self-care behaviors make a difference in glycemic control: the Diabetes Stages of Change (DISC) study. Diabetes Care. 2003;26(3):732-737.
25. Oldroyd JC, Unwin NC, White M, et al. Randomised controlled trial evaluating the effectiveness of behavioural interventions to modify cardiovascular risk factors in men and women with impaired glucose tolerance: outcomes at 6 months. Diabetes Res Clin Pract. 2001;52(1): 29-43.
26. Siero FW, Broer J, Bemelmans WJ, Meyboom-deJong BM. Impact of group nutrition education and surplus value of Prochaska-based stage-matched information on health-related cognitions and on Mediterranean nutrition behavior. Health Educ Res. 2000;15(5):635-647.
27. Akamatsu R, Takemi Y. Recent trends in application of the transtheoretical model to nutrition education. Jpn J Health educ promot. 2007;15(1):3-18.
Tables & Figures




Figure 1: The relationships among vegetable intake, energy intake, and BMI for all patients. (A) The changes in total vegetable intake and energy intake at 3 months, (B) the changes in BMI and energy intake at 3 months, (C) the changes in total vegetable intake and energy intake at 6 months, and (D) the changes in BMI intake and energy intake at 6 months. Bivariate relationships between changes in total vegetable intake, energy intake, and BMI were assessed using Pearson's correlation coefficient.



Figure 2: The changes in vegetable intakes of group A and B. (A) The changes in total vegetable intakes of group A and B at both 3 and 6 months compared to baseline, (B) the comparison of changes in vegetable intakes between groups A and B at both 3 and 6 months compared to baseline. Values are presented as means + SD. Relationships between baseline and 3 months or between baseline and 6 months for the intake of total vegetables and changes in vegetable intake were assessed using the paired t-test.






Figure 3: The proportions of those whose energy intake and weight increased and/or decreased at both 3 and 6 months compared to baseline. Data are presented as percentages of total subjects.



Values are presented as means +/- SD. Relationships between group A and B were evaluated using the non-paired t-test. *AST, aspartate aminotransferase. **ALT, alanine aminotransferase. ***γGTP, gamma-glutamyl transpeptidase.

Table 1: Characteristics of Patients.




(A).The intakes and changes in food groups (per day)

(B). Intakes and changes in nutrient intake (per day)





(B). Intakes and changes in nutrient intake (per day)

Data are presented as means ± standard deviation for data with a normal distribution, medians (25th, 75th percentile) for data with a non-normal distribution. Relationships between baseline and 3 months were assessed for intakes of food groups and nutrients using the paired t-test for data with a normal distribution or the Wilcoxon rank-sum test for data with a non-normal distribution.

Table 2: Comparisons of dietary intake before and after the intervention (Baseline and 3-month intervention data)




A. The intakes and changes in food groups (per day)





Table 3: Comparisons of dietary intake before and after the intervention (Baseline and 6-month intervention data)

Download PDF