J Obes Metab Syndr 2022; 31(1): 70-80
Published online March 30, 2022 https://doi.org/10.7570/jomes21074
Copyright © Korean Society for the Study of Obesity.
1Department of Food Science and Nutrition, Dong-A University, Busan; 2Department of Health Science, Graduate School, Dong-A University, Busan; 3Center for Food and Bio Innovation, Dong-A University, Busan; 4Center for Silver-targeted Biomaterials, Brain Busan 21 Plus Program, Busan; 5Department of Dietetics, Kangbuk Samsung Hospital, Seoul, Korea
Oh Yoen Kim
Department of Food Science and Nutrition, Dong-A University, 37 Nakdong-daero 550beon-gil, Saha-gu, Busan 49315, Korea
Eun Mi Kim
Department of Dietetics, Kangbuk Samsung Hospital, 29 Saemunan-ro, Jongno-gu, Seoul 03181, Korea
The first two authors contributed equally to this study.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background: We investigated whether eating behavior modification improves metabolic syndrome (MetS)-related risks in overweight/obese Korean adults, and identified dietary factors that improve metabolic status.
Methods: Among 159 volunteers, 71 with a body mass index ≥23 kg/m2 and without other chronic diseases participated in the 8-week intervention, among which 54 participants who completed the intervention were included in the analyses. At baseline, patients were categorized either metabolically healthy obese (MHO; <3 MetS risk factors, n=42) or metabolically unhealthy obese (MUHO; ≥3 MetS risk factors, n=12), and then educated regarding how to choose healthy foods and meals.
Results: Lipid profiles and anthropometric and glycemic parameters were significantly improved among all participants after the intervention. Changes in waist circumference (P= 0.025), and glycemic parameters (glucose, P=0.046, insulin, P=0.005, C-peptide, P=0.041) were positively correlated with changes in calorie intake from snacks. Changes in visceral fat area were negatively correlated with changes in total calorie intake (P=0.046), and positively correlated with those in calorie intake from dietary fats (P=0.039). In addition, changes in insulin (P=0.013) and C-peptide (P=0.008) concentrations were negatively correlated with changes in dietary fiber intake at dinner. After the intervention, 83.3% of initially MUHO participants became MHO and 16.7% of MHO participants became MUHO.
Conclusion: Eating behavior modification may be an important strategy to improve metabolic factors in overweight/obese people.
Keywords: Eating, Behavior, Overweight, Obesity, Metabolic syndrome
Obesity, a global health issue, is a problematic metabolic disorder1 that may increase the risks of hypertension, dyslipidemia, metabolic syndrome (MetS), type 2 diabetes, and cardiovascular disease (CVD).2,3 The World Health Organization (WHO; 2018) reported that 39% of adults aged 18 years and older were overweight (body mass index [BMI] ≥25 kg/m²) and 13% were obese (BMI≥30 kg/m²) in 2016 and 39 million children under the age of 5 were overweight or obese in 2020.4 The WHO report also estimated that more than one billion people will be obese by 2030.5 In contrast, Korean obesity guidelines define obesity as a BMI ≥25 kg/m², and overweight as a BMI ≥23 and <25.0 kg/m² (Korean Society for the Study of Obesity, Seoul, Korea). The Korean National Health Examination and Nutrition Survey (KNHANES) has reported that 43.1% of male adults and 27.4% of female adults were obese (BMI ≥25 kg/m²) in 2020.6 However, it has been suggested that the obesity criteria for Koreans need revision, although consensus on revised criteria has not been established; the current obesity criteria for Koreans have therefore remain unchanged for the time being. Nonetheless, obesity-related disease continues to increase among Korean people with BMI ≥23 kg/m² (public hearing, the Korean Society for the Study of Obesity, Seoul, Korea; September 1, 2016). However, not all overweight and obese people have cardiometabolic risk factors (i.e., increased waist circumference [WC]), blood pressure, serum triglyceride [TG]) and fasting glucose concentrations, and reduced serum high-density lipoprotein cholesterol [HDL-C] concentrations).7-10 Overweight and obese people can be classified according to both BMI and metabolic health status.9 Metabolically healthy obese (MHO) individuals have a BMI ≥25 kg/m² while maintaining acceptable insulin sensitivity, lipid profiles, inflammatory response and/or blood pressure, such that they have less than two of five MetS risk factors.7-11 Metabolically unhealthy obese (MUHO) individuals have a BMI ≥25 kg/m² and three or more MetS risk factors.12 According to Rasaei et al.,11 MHO individuals are more likely to have cardiometabolic risk factors than those who are considered metabolically healthy normal weight (MHNW);12 interestingly, the cardiometabolic risks observed in MHO people are likely to be much lower than those shown in MUHO ones.7 Therefore, MHO may be considered an intermediate status that may progress to cardiometabolic disease. This novel approach to identify individuals with MHO and MUHO highlights the need for optimal and individualized treatment of overweight and obesity.8,9 According to Stelmach-Mardas and Walkowiak,10 the traditional lifestyle intervention for MHO and MUHO aims to reduce body weight by limiting daily calorie intake and increasing physical exercise. Most of the dietary interventions suggest energy restriction by reducing the usual calorie intake by approximately 500 kcal per day or lowering the proportion of carbohydrates less than 50% in daily calorie intake.10,13 Many weight loss interventions to improve metabolic profiles of people with MHO and MUHO have been assessed, but few studies have analyzed factors other than losing weight that may improve metabolic status.8,10
This study aimed to investigate whether eating behavior modification improves MetS-related risk factors in overweight and obese Korean adults according to Korean guidelines, and to identify the specific factors that improve metabolic status, including eating habits and dietary factors (e.g., calorie intake, and macronutrient composition. etc.).
Study participants (≥21 years) were recruited through public advertisement. Initially, 159 Korean adults participated in the baseline screening, of which 88 were excluded (51 were categorized as MHNW; 37 either had a diagnosis of another chronic disease, such as diabetes, dyslipidemia, CVD, coronary heart disease, stroke, and cancer, or were taking medications). After screening, 71 participants were enrolled in the eating behavior modification intervention for 8 weeks. During the intervention, 17 participants dropped out due to personal reasons (i.e., relocation, leg fracture, or work conflicts), such that 54 participants were included in the analyses. The study goal was explained to them and written informed consent was obtained. The study protocol was approved by the Institutional Review Board of Dong-A University (IRB No. 2-104709-AB-N-01-201603-BR-001-10).
The participants undertook the eating behavior modification for overweight and obese adults (BMI ≥23 kg/m² or WC ≥90 cm in men, WC ≥85 cm in women) in accordance with Korean obesity guidelines for 8 weeks.6,14 Each participant visited our clinic twice, at week 0 (baseline) and week 8 (after), for measurement of their anthropometric parameters and collection of basic information, fasting blood samples, and food records. Basic information included demographics, medical history, and family history. Based on the data obtained at week 0, participants were categorized into two groups:MHO (none or 1−2 MetS risk factors) and MUHO (≥3 MetS risk factors). Education regarding eating behavior modification was provided to the participants at their first visit. In addition, cell phone text messages were sent to the participants every 2 weeks during the intervention period to motivate them to follow the program.
Eating behavior education was provided by a registered clinical dietitian, with the content having been developed by the research team based on the guidelines of Korean Dietetic Association and Dietary Reference Intakes for Koreans (KDRIs) 2015. At the first visit, subgroups of participants received education together, and then also had individualized counseling for 1 hour. The content of the education materials included materials addressing, “What is metabolic syndrome?” and “Recommendation for eating behavior modification.” An example of the latter is as follows: (1) regular and healthy eating patterns by using the food exchange table, food model, and calorie table for restaurant foods eaten outside the home; (2) healthy food choice method (appropriate amounts of mixed grains, rice, beans, vegetables, and dairy foods, and reduced amounts of simple sugars and alcohol); (3) smart tips for eating out; and (4) cooking strategies to reduce the intake of sodium and saturated fats. In personalized counseling, the optimal total calorie intake (TCI) for a healthy body weight was calculated based on the estimated individual basal metabolic rate and ideal body weight. After that, each participant was encouraged to make a basic 1-day meal plan for a day based on the calculated TCI using the food exchange table with guidance from the dietitian. Participants were able to easily contact the dietitian during the education and intervention period if they had questions about the modification.
A registered clinical dietitian provided the participants with written and verbal instructions as to how to record their dietary intake and lifestyle. Information on each participant’s usual diet was obtained using a 24-hour recall survey. To assess the dietary intake during the intervention period, dietary records for three days (2 weekdays and 1 weekend day) were recorded by each participant and confirmed by a dietitian at the week 8 visit. Nutrient content from the diet records of each individual was analyzed using the Computer Aided Nutritional analysis program (CAN-pro 4.0; Korean Nutrition Society, Seoul, Korea).
Anthropometric measurements and basic parameters were measured while the participants wore light clothes and had removed their shoes. Height, weight, body fat percentage, and skeletal muscle mass and visceral fat area (VFA) were measured using an automatic body composition analyzer (N20; AIIA Communication Inc., Seongnam, Korea) without metallic materials. BMI was computed as body weight in kilograms divided by the square of the height in meters (kg/m2). The WC was measured using a measuring tape. Blood pressure was measured at the arm while seated after a period of rest using an automatic blood pressure monitor (HEM- 7220; Omron, Matsusaka, Japan).
Blood samples were collected in plain tubes and ethylenediaminetetraacetic acid (EDTA)-treated tubes in the morning after an 8-hour fast. Blood samples were separated into serum or plasma by a centrifuge, aliquoted and stored at −80°C before analyses. Serum TG concentrations and total cholesterol were measured using kits on a Hitachi 7150 autoanalyzer (Hitachi, Tokyo, Japan). After precipitation of serum chylomicrons with dextran sulfate magnesium, the concentrations of low-density lipoprotein cholesterol (LDL-C) and HDL-C in the supernatant were analyzed enzymatically. The serum glucose concentration was measured using a glucose oxidase method with a Beckman glucose analyzer (Beckman Instruments, Irvine, CA, USA). The glycosylated hemoglobin (HbA1c) concentration was measured using a glycated hemoglobin analyzer (SD A1cCare; SD Biosensor Inc., Suwon, Korea). The serum insulin and C-peptide concentrations were assessed using radioimmunoassay methods. The homeostasis model assessment insulin resistance (HOMA-IR) was calculated using HOMA method developed by Matthews et al.15
All statistical analyses were performed using IBM SPSS version 24.0 (IBM Corp., Armonk, NY, USA). Proportions were tested using the chi-square method; differences in within-group means before and after the intervention were assessed using a general linear model with adjustment for confounding factors (i.e., age and sex); differences between the baseline values and those obtained after the intervention between the MHO and MUHO group were assessed using Student t-test. Spearman’s correlation test was used to describe associations between eating behavior modification and MetS-related parameters. Results were described as mean±standard error, percentages, or correlation coefficient. A two-tailed
Table 1 presents the baseline characteristics of all of the participants and each gender group. The mean age and percentages of current cigarette smokers and current alcohol drinkers among the total participants were 42.6±1.77 years, 9.3%, and 74.1%, respectively. The men were slightly younger than the women (
Table 2 presents the anthropometric parameters at baseline and after 8 weeks of the eating behavior modification intervention. The BMI (
Table 4 presents the participants’ daily TCI and proportion of calorie intake derived from macronutrients at baseline and after the intervention. There were no statistically significant differences between the MHO and MUHO groups at baseline. The proportion of the TCI derived from dietary fat tended to decrease after the intervention in both groups. In addition, the TCI and proportions of the TCI derived from carbohydrate or protein were not significantly different in the MHO and MUHO groups during the intervention. In addition, the amount of daily macronutrient intakes ingested as carbohydrates (
Fig. 1 shows the proportion and amount of calorie intake according to meal distribution before and after the intervention. During the intervention, the proportion of calorie intake derived from breakfast consumption increased significantly in all participants (
Fig. 2 shows the relationship between changes in VFA and in daily calorie intake from TCI and macronutrients. Changes in VFA were negatively correlated with those in TCI (r=–0.296,
Among the MUHO participants (n=12) at baseline, 10 were categorized as MHO (83.3%) after the intervention, and only two remained MUHO (16.7%). Among the MHO participants (n=42) at baseline, 36 remained MHO (85.7%), and six were categorized as MUHO (14.3%) after the intervention. The results may be explained by the MUHO group having relatively better adherence to eating behavior modification. Specifically, six participants who had been categorized as MHO at baseline were categorized as MUHO due deterioration of their metabolic status.
This study aimed to investigate if eating behavior modification improves MetS-related risk factors in overweight, obese Korean adults, and to identify the dietary factors that improve metabolic status. Improvements in the participants’ body weight, BMI, body fat, skeletal muscle mass, HbA1c, HOMA-IR, total cholesterol, and kidney functions were measured in all participants after the intervention. Both eating behavior and dietary factors, such as breakfast consumption, decreased TCI, decreased calorie intake from snacks, and increased dietary fiber intake contributed to the improvements in metabolic parameters.
With regard to the participants’ baseline characteristics, the percentage of current alcohol drinkers was 74.1%. It was considerably higher compared with that reported by the KNHANES study 2008–2013 (about 10%).16 In this study, the majority of overweight and obese participants frequently engaged in unfavorable lifestyle and eating behaviors, such as drinking alcohol, irregular timing of meals, skipping breakfast, and overeating. Nevertheless, in this study, the participants’ body weight and BMI both decreased significantly. The eating behavior modification undertaken by participants in this study did not suggest strict energy restriction, which was different from other studies.13,17,18 Our results are partly supported by several previous studies that have reported that unfavorable eating patterns and dietary factors influenced MetS and cardiometabolic health.19,20
The eating behavior education program included a recommendation that the participants eat breakfast, and the proportion of breakfast calorie intake increased in both groups. In addition, the proportion of calories ingested during dinner intake in the MUHO group tended to decrease. Daily nutrient intake from macronutrients, carbohydrate, vegetable fat, and vegetable protein intakes increased significantly only in the MUHO group (
Many previous studies have reported metabolic improvements after implementing an energy-restricted dietary intervention rather than through an understanding of eating behavior and dietary factors.10,21,22 Arab et al.23 reported that VFA decreased along with the reduction of TCI in overweight and obese patients with nonalcoholic fatty liver disease. However, this study showed that changes in VFA were negatively correlated with those in TCI (
As mentioned above, 10 of the MUHO participants (n=12) at baseline were classified as MHO (83.3%) after the intervention and only two remained MUHO (16.7%). Among the MHO participants (n=42), 36 remained MHO (85.7%) after the intervention, but six became classified as MUHO (14.3%) due to deterioration of their metabolic status The results may be explained as the MUHO group having had relatively greater adherence to the eating behavior modification. In addition, some studies have reported that MHO status is unstable and may worsen to metabolic unhealthy status.27-29
This study has several limitations. First, the number of participants in the MUHO group was relatively small. For example, some of metabolic and dietary changes observed in the MUHO group were numerically greater than the MHO group, but it did not reach the statistical significance due to the small number of subjects in the MUHO group. Second, the 8-week intervention period was relatively short. Future studies with a larger number of participants and longer study period must be performed to improve the statistical power. In addition, this study did not emphasize the participants doing exercise, because it focused on eating behavior modification.
However, physical exercise is one of several important factors that may improve body composition and MetS risk.10 In follow-up studies, exercise needs to be considered together with eating behavior modification. Despite these limitations, eating behavior modifications (rather than strict energy-restriction) increased adherence to a weight loss program among obese participants, such that metabolic status improved to a greater degree with eating behavior intervention than when strictly restricting energy intake, even though the improvement in adiposity is not particularly great. The key finding from this study is that obesity treatment did not depend on strict calorie restriction alone, but rather eating behavior modification, such as breakfast consumption, decreased TCI, and decreased calorie intake from snack, and increased dietary fiber intake.
In conclusion, this study demonstrated that changes in the eating behavior may be important for metabolic improvement in overweight and obese people, thereby preventing type 2 diabetes and CVD.
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea, funded by the Ministry of Education NRF-2016R1A2B4013627.
Study concept and design: OYK and EMK; acquisition of data: HK, EY, and OYK; analysis and interpretation of data: HK, EY, OYK, and EMK; drafting of the manuscript: HK and OYK; critical revision of the manuscript: EY, OYK, and EMK; statistical analysis: EY and OYK; obtained funding: OYK; administrative, technical, or material support: OYK and EMK; and study supervision: OYK and EMK.
Baseline characteristics of study participants
|Variable||Total (n = 54)||Women (n = 34)||Men (n = 20)|
|Age (yr)||42.6 ± 1.77||47.2 ± 2.16||35.0 ± 2.22*|
|Current cigarette smoker||5 (9.3)||2 (5.9)||3 (15.0)|
|Current alcohol drinker||40 (74.1)||21 (61.8)||19 (95.0)|
|Meal frequency per day|
|3||21 (38.9)||16 (47.1)||5 (25.0)|
|2||30 (55.6)||16 (47.1)||14 (70.0)|
|Irregular||3 (5.6)||3 (5.9)||1 (5.0)|
|Breakfast skipping per week|
|0–1||18 (33.3)||14 (41.2)||4 (20.0)|
|2–3||15 (27.8)||10 (29.4)||5 (25.0)|
|≥4||21 (38.9)||10 (29.4)||11 (55.0)|
|Overeating per week|
|0–1||10 (18.5)||6 (17.6)||4 (20.0)|
|2–3||34 (63.0)||23 (67.6)||11 (55.0)|
|≥4||10 (18.5)||5 (14.7)||5 (25.0)|
|Eating out per week|
|0–1||9 (16.7)||7 (20.6)||2 (10.0)|
|2–3||30 (55.6)||22 (64.7)||8 (40.0)|
|≥4||15 (27.8)||5 (14.7)||10 (50.0)|
|MetS RF number|
|0||9 (16.7)||7 (20.6)||2 (10.0)|
|1–2||33 (61.1)||27 (64.7)||11 (55.0)|
|≥3||12 (22.2)||5 (14.7)||7 (35.0)|
Values are presented as mean± standard error or number (%); tested by Student t-test or chi-square test.
MetS, metabolic syndrome; RF, risk factor.
Anthropometric parameters at baseline and after the intervention
|Variable||MHO (n= 42)||MUHO (n= 12)|
|Weight (kg)||70.9 ± 1.61||70.6 ± 1.65||0.189||76.6 ± 3.70||75.5 ± 3.42||0.033||0.050||0.151|
|BMI (kg/m2)||26.2 ± 0.39||26.0 ± 0.39||0.087||27.4 ± 0.54||27.0 ± 0.51||0.044||0.047||0.428|
|Waist (cm)||89.4 ± 1.22||89.1 ± 1.15||0.519||94.1 ± 1.44||94.0 ± 1.39||0.874||0.019||0.873|
|SBP (mmHg)||120.4 ± 2.54||119.4 ± 2.19||0.444||138.6 ± 3.09||139.9 ± 3.82||0.693||0.001||0.437|
|DBP (mmHg)||77.2 ± 1.65||77.7 ± 1.66||0.673||89.0 ± 2.58||88.4 ± 2.89||0.763||0.001||0.651|
|Body fat (kg)||23.4 ± 0.81||22.8 ± 0.85||0.069||23.5 ± 1.32||22.9 ± 1.25||0.124||0.915||0.859|
|SMM (kg)||26.0 ± 0.85||27.3 ± 1.14||0.098||29.4 ± 2.14||34.0 ± 3.36||0.104||0.044||0.092|
|VFA (cm2)||105.2 ± 4.05||105.3 ± 4.46||0.439||127.4 ± 8.03||124.1 ± 8.28||0.303||0.049||0.085|
Values are presented as mean± standard error.
MHO, metabolically healthy obese; MUHO, metabolically unhealthy obese; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; SMM, skeletal muscle mass; VFA, visceral fat area.
Biochemical markers at baseline and after the intervention
|Variable||MHO (n= 42)||MUHO (n= 12)|
|HbA1c (%)||5.45 ± 0.06||5.38 ± 0.05||0.029||5.90 ± 0.16||5.69 ± 0.17||0.076||0.008||0.110|
|HOMA-IR||3.07 ± 0.70||2.83 ± 0.48||0.049||8.94 ± 2.59||7.56 ± 1.86||0.237||0.024||0.075|
|Glucose (mg/dL)||93.9 ± 3.20||95.1 ± 1.63||0.648||109.7 ± 6.36||106.8 ± 6.74||0.702||0.026||0.508|
|Insulin (μIU/mL)||11.6 ± 1.65||10.3 ± 0.94||0.455||31.6 ± 8.85||19.0 ± 5.72||0.305||0.047||0.110|
|C-Pep (ng/dL)||2.35 ± 0.22||2.29 ± 0.13||0.791||4.69 ± 0.76||3.56 ± 0.50||0.326||0.011||0.150|
|TG (mg/dL)||96.4 ± 6.41||109.3 ± 8.42||0.072||256.0 ± 82.4||197.3 ± 42.1||0.216||0.001||0.010|
|HDL-C (mg/dL)||59.7 ± 1.83||57.4 ± 1.50||0.052||49.0 ± 5.93||49.9 ± 5.87||0.631||0.025||0.181|
|LDL-C (mg/dL)||129.5 ± 4.70||122.3 ± 4.68||0.037||124.3 ± 14.3||118.1 ± 10.6||0.577||0.049||0.906|
|Total-C (mg/dL)||199.6 ± 5.20||192.8 ± 4.69||0.050||208.1 ± 12.5||196.1 ± 10.5||0.250||0.045||0.526|
Values are presented as mean± standard error.
MHO, metabolically healthy obese; MUHO, metabolically unhealthy obese; HbA1c, glycosylated hemoglobin; HOMA-IR, homeostatic model assessment for insulin resistance; CPep, C-peptide; TG, triglyceride; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; Total-C, total cholesterol.
Daily calorie and macronutrient intakes at baseline and after intervention
|Per day||MHO (n= 42)||MUHO (n= 12)|
|TCI (kcal)||1,839 ± 97.7||1,752 ± 85.3||0.290||1,723 ± 120.4||2,049 ± 243.9||0.234||0.555||0.089|
|Carbohydrate (%)||53.7 ± 1.70||56.8 ± 1.11||0.116||53.0 ± 4.20||58.0 ± 3.04||0.324||0.655||0.602|
|Fat (%)||29.2 ± 1.30||26.8 ± 0.89||0.097||28.6 ± 3.43||25.2 ± 2.43||0.098||0.551||0.651|
|Protein (%)||17.1 ± 0.67||16.4 ± 0.45||0.392||18.5 ± 1.83||16.8 ± 0.88||0.471||0.162||0.640|
|Carbohydrate (g)||239.0 ± 11.5||243.7 ± 11.0||0.998||211.8 ± 21.1||285.3 ± 24.8||0.024||0.268||0.016|
|Fat (g)||60.4 ± 4.57||52.7 ± 3.83||0.115||53.8 ± 8.55||60.8 ± 11.40||0.567||0.498||0.217|
|Vegetable fat (g)||26.7 ± 1.53||25.3 ± 1.90||0.566||20.8 ± 4.86||31.3 ± 4.88||0.030||0.128||0.027|
|Animal fat (g)||33.7 ± 4.23||27.4 ± 3.06||0.133||33.0 ± 8.03||29.5 ± 7.70||0.527||0.939||0.809|
|Protein (g)||78.9 ± 5.61||70.7 ± 4.08||0.153||76.7 ± 12.2||85.9 ± 10.6||0.606||0.860||0.081|
|Vegetable protein (g)||31.8 ± 1.64||30.1 ± 1.57||0.401||30.4 ± 3.41||40.8 ± 3.51||0.030||0.691||0.006|
|Animal protein (g)||47.1 ± 5.15||40.5 ± 3.62||0.186||46.3 ± 12.20||45.1 ± 8.76||0.891||0.948||0.676|
|Dietary fiber (g)||18.3 ± 1.10||18.6 ± 1.10||0.945||19.0 ± 1.95||23.9 ± 2.50||0.093||0.736||0.078|
|Cholesterol (mg)||350.2 ± 34.0||371.7 ± 27.3||0.684||348.2 ± 62.5||400.2 ± 74.5||0.718||0.977||0.803|
Values are presented as mean± standard error.
MHO, metabolically healthy obese; MUHO, metabolically unhealthy obese; TCI, total calorie intake.