The prevalence of obesity is increasing worldwide, and obesity has become a serious epidemic health problem.¹ According to the World Health Organization, the prevalence of obesity has more than doubled worldwide over the past 30 years, and it is estimated that more than half of the world’s population will be overweight or obese by 2030.^2,3 Although the incidence of obesity in South Korea is not as high as that in Western countries, it has increased steadily over the past 20 years. Approximately 35% of Korean adults are classified as obese, with 45% of Korean men classified as obese in 2018.⁴ Obesity is defined as abnormal or excessive fat accumulation, and it increases the risk of mortality, cardiovascular disease, hypertension, type 2 diabetes mellitus, and cancer.^2,3 In a study in the United States, it was reported that obesity can shorten the lifespan of patients by about 15.4 years compared to that of normal-weight individuals.⁵ Therefore, weight-management programs are recommended to reduce the risk of both morbidity and mortality. The U.S. National Institutes of Health reported that a constant multi-dimensional weight-control program that includes diet, exercise, and behavioral therapy is effective.⁶ Since diet therapy is the basis of obesity treatment, simple calorie intake restrictions and eating a well-balanced diet are important. A very-low-calorie diet, while capable of inducing rapid weight loss, is associated with limitations in post-treatment weight maintenance.⁷ Previous studies have instead recommended a daily caloric reduction of 500 to 1,000 kcal and moderate- to high-intensity aerobic exercise for safe weight loss.^8,9 Behavioral therapy, including positive changes in daily behavior and eating habits, showed greater effectiveness when combined with dietary and exercise therapy.¹⁰ The number of weight-management programs and studies with comprehensive designs in South Korea has recently been increasing.¹¹ However, most of these studies have focused on short-term weight reduction rather than on overall lifestyle improvement. Due to the use of simple energy restrictions and exercise programs, their study participants were largely unaware of the importance of lifestyle improvement. As a result, after completing the short-term weight-reduction program, the study participants could not exercise regularly, maintain a healthy diet, or improve their lifestyle.¹²

Based on the limitations of weight-management studies, customized theory-based lifestyle modification is necessary to improve both lifestyle and dietary behaviors for voluntary maintenance over a long time. In theory-based education, the transtheoretical model (TTM) is used to determine the stage of change (SoC) and to implement stage-matched multiple behavior interventions. The model consists of SoC, the process of change, decisional balance, and self-efficacy.¹³ SoC is the core concept of TTM, and it is a stage that shows the intention to change problematic behaviors. It consists of the following five stages: pre-contemplation (PC), contemplation (C), preparation (P), action (A), and maintenance (M).¹³ The behavior of an individual has a cyclical nature, with repeated phases of advancement and regression between the five stages.¹³ Changes in eating behavior occur through a series of processes in the behavioral-change stage of TTM.¹³ It was reported that different methods or strategies should be chosen for each individual according to the stage of behavior change.¹³ Many multidisciplinary obesity programs have been introduced, but weight-control nutrition education that entails TTM in each SoC is insufficient. Most studies on TTM have involved smoking cessation and exercise or are cross-sectional studies that evaluated the relevance and step-by-step characteristics of stages and compositional concepts.^14,15 It was reported that, when planning or conducting nutrition education, education contents and education strategies appropriate for the stage of behavior change are necessary and will make for more effective explanation of the specific mechanism of change.¹⁵

Since long-term weight-reduction maintenance is challenging, weight-management programs should be easy to adopt in everyday life. Compliance with weight-management programs is closely associated with weight reduction¹⁶ and encompasses the program attendance rate, use of medications, lifestyle modification, and fidelity to treatment. In most studies, compliance was measured using frequency of participation, and it was reported that the higher was the attendance rate, the greater were the effects of education and weight reduction.¹⁷ In this study, we investigated the effects of a 12-week customized lifestyle-modification program known as “Change 10 Habits” on body fat composition and the impact of lifestyle habit changes on obesity management among South Korean adults with obesity.

Study design and participants

Between May 2014 and December 2014, a total of 181 participants with obesity (age, 20 to 60 years; body mass index [BMI], 25 to 30 kg/m²) was recruited for this study through a recruitment notice posted on the hospital website. Prior to program initiation, informed written consent was obtained from all participants. Obesity was defined according to the World Health Organization’s guidelines for the Asia-Pacific region.

Individuals with any of the following major diseases were excluded: hypertension, diabetes, heart disease, kidney disease, liver disease, thyroid disease, gout, depression, and mental illness. Other exclusion criteria included the intake of anti-obesity drugs and participation in a commercial obesity program within the last 30 days.

Of the 181 recruited participants, 76 were eventually excluded and 105 were included in the study. Of the 105 included participants, 18 dropped out during the study period, and data from 87 were finally analyzed (Fig. 1). This study included a 12-week customized lifestyle-modification program called “Change 10 Habits,” and was conducted in compliance with the Declaration of Helsinki. The present study was approved by the Institutional Review Board (IRB) of the Kyung Hee University Hospital Ethics Committee (IRB no. KMC IRB 1401-05).

“Change 10 Habits” program

In this study, individual lifestyle-modification education based on the behavior-change stage was delivered four times over 12 weeks throughout the “Change 10 Habits” program. A detailed account of “Change 10 Habits,” encompassing its structure and the content of nutritional education aligned with stages of behavior change, can be found in the study conducted by Kim and Lim.¹⁸ In brief, TTM was used in the program, developed using simple messages for easy recall, and the program was followed in everyday life to improve dietary habits and lifestyle. Regarding program guidelines, we selected 10 behaviors, numbered 1 to 10, for the “Change 10 Habits” program. Education was conducted four times (in weeks 0, 4, 8, and 12) over 12 weeks. The stage of behavior change was evaluated using a TTM questionnaire during individual interviews with a registered dietitian (RD). Participants in the PC and C stages who lacked the intention and plans for behavioral change were grouped into the PC/C stage. Those in the P stage did not enact the behavioral change but had plans to do so, while participants who actively engaged in (A stage) and maintained the behavioral change (M stage) were grouped into the A/M stage. We developed the “Change 10 Habits” lifestyle-modification program based on the stage of TTM and the stage-matched education program.¹⁸ Based on this program, score of RD-conducted education was compared with scores from the previous visit. Participants in the PC/C stage received essential theoretical knowledge from the RD to accurately grasp potential health issues related to each lifestyle habit. Simultaneously, they gained motivation for initiating changes. Individuals in the P stage were provided with realistic goals and action plans by the RD, encouraging immediate behavior modification. Participants in the A/M stage received a diverse range of practical tips from the RD to sustain ongoing positive habits.

Group allocation based on compliance score

Participants were categorized into two groups based on their compliance scores assessed at week 12. A compliance-assessment tool, containing five questions, was developed. Participants self-evaluated by answering two questions (total scores of “Change 10 Habits” and individual goal achievement evaluation), while the RD evaluated participants using three questions (change in stage of behavior change, attitude toward education, and self-efficacy). Compliance was calculated by adding the scores of the five questions asked in week 12, and the total participant average score was 64 points. Participants who scored below this average were designated as showing low compliance (LC), while those who scored above this average were classified as showing high compliance (HC).

Data collection

Measurements of anthropometric characteristics and blood pressure (BP) were performed at baseline and week 12. Height, weight, body fat mass, fat-free mass, total body fat mass, and total body fat percentage were measured using biochemical impedance analysis (Inbody 720; Inbody). BMI was calculated using body weight and height. Waist and hip circumferences were measured, and the waist and hip circumference ratio was calculated. After maintaining a stable status, BP was measured using an automatic electronic sphygmomanometer (BPBIO320S; Inbody).

Body composition was measured using dual-energy X-ray absorptiometry (DEXA) (LUNAR prodigy and iDXA; General Electronics) at baseline and week 12. The following variables were measured: lean body mass (LBM), total body fat mass, total body fat percentage, and the fat percentage of five regions of the body (arms, legs, trunk, abdomen, and thighs).

Venous blood samples were obtained after 12 hours of fasting at baseline and in week 12. The blood samples were used to determine fasting plasma insulin, triglyceride (TG), total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-C), very-low-density lipoprotein cholesterol (VLDL-C), and free fatty acid (FFA) levels. Lipid profile was measured using an enzymatic colorimetric assay with a Roche kit (Roche). Insulin level was measured using electrochemiluminescence immunoassay. FFA level was measured using an NEFA-HR II kit (Wako).

Dietary intake was recorded four times (in weeks 0, 4, 8, and 12) using 3-day records. The records were assessed using a computer-aided nutritional analysis program (CAN Pro, Web version 5.0; The Korean Nutrition Society; 2015).

Statistical analysis

All data were analyzed using SPSS version 22 (IBM Corporation). Continuous variables are expressed as mean±standard deviation, and discrete variables are expressed as frequencies and percentages. Anthropometric data, nutrient intake data, and biochemical data were analyzed using paired t-test, Student’s t-test, and the chi-square test, respectively. Changes in “Change 10 Habits” were evaluated using repeated-measures analysis of variance. Utilizing linear regression analysis, the relationship between compliance and changes in body fat composition was investigated. The beta coefficients, indicating the extent of changes in body fat composition with each one-unit increase in compliance, were assessed. Statistical significance was considered at P<0.05.

Participant characteristics

Of the 87 participants, 57 showed HC and 30 showed LC. There were no significant differences in the general characteristics of age (32.39±11.1 years vs. 30.33±7.61 years, P=0.314), female sex (54.4% vs. 63.3%, P=0.422), marital status (43.9% vs. 40.0%, P=0.729), smoking habit (15.8% vs. 23.3%, P=0.946), consuming alcohol (59.6% vs. 60.0%, P=0.975), and exercise (45.6% vs. 43.3%, P=0.839) between these two groups.

“Change 10 Habits” scores

The behavioral scores of the “Change 10 Habits” program according to participant compliance are shown in Fig. 2. These scores were largely comparable between the two groups at baseline, but the score for “eat three meals regularly, adequate amount” in week 12 was higher in the HC group than in the LC group (7.1±0.3 points vs. 5.6±0.5 points, P<0.05). Similarly, the score of “do not eat after 9:00 PM” was consistently higher in weeks 0, 4, and 12 in the HC group than in the LC group (5.4±0.4 points vs. 4.1±0.5 points, P<0.05; 6.8±0.3 points vs. 5.7±0.5 points, P<0.05; and 6.9±0.3 points vs. 5.5±0.5 points, P<0.05, respectively).

Nutrient intake

Table 1 shows daily nutrient intake by the HC and LC groups before and after the program. No differences in nutrient intake were observed between the two groups at baseline. After the program, both groups experienced a decrease in energy intake. However, in the HC group, the intake of fat, protein, and some micronutrients (vitamin B2, vitamin E, zinc) decreased after the program, whereas in the LC group, overall nutrient intake, including dietary fiber, decreased after the program. The intake of dietary fiber, vitamin B1, vitamin B6, vitamin D, and potassium was lower in the LC group compared to the HC group after the program.

Anthropometric characteristics and biochemical parameters

Data regarding the anthropometric characteristics and biochemical parameters of the HC and LC groups before and after the program are shown in Table 2. No significant differences in BMI at baseline was observed between the two groups. However, after 12 weeks, BMI was significantly lower in the HC group than in the LC group (26.7±1.8 kg/m² vs. 27.7±2.1 kg/m², P<0.05). In the HC group, systolic BP decreased significantly after 12 weeks (117.9±12.2 mmHg vs. 114.3±15.0 mmHg, P<0.05).

In the HC group, TG and VLDL-C levels were significantly higher at baseline than after 12 weeks (121.7±74.9 mg/dL vs. 105.7±60.9 mg/dL, P<0.05; 24.3±15.0 mg/dL vs. 21.1±12.2 mg/dL, P<0.05, respectively). There were no significant differences in other biochemical parameters except the LDL-C level at baseline and after 12 weeks between the two groups.

Body composition

Fig. 3 shows the change in body fat composition measured using DEXA between the HC and LC groups. Both the change in leg fat percentage (LEFAT) and change in total body fat percentage were significantly improved in the HC group than in the LC group (−0.2%±0.3% vs. 0.9%±0.3%, P<0.05; −0.1%±0.3% vs. 1.1%±0.5%, P<0.05, respectively). There were no significant differences in the change in fat composition of the other body parts between the two groups.

We performed a linear regression analysis of compliance and the change in body fat composition (Table 3). The analysis revealed that HC was significantly associated with a reduction in LEFAT (β=−1.09, P=0.04), trunk fat percentage (TRFAT) (β=−1.19, P=0.05), body fat percentage (β=−1.30, P=0.02), and body fat mass (β=−1,000.81, P=0.04) when not adjusting for covariates. This inverse association persisted in model 1, which was adjusted for age and sex (β=−1.17, β=−1.31, β=−1.38, and β=−1,088.77; P<0.05), and model 2, which additionally considered alcohol, smoking, and exercise status (β=−1.23, β=−1.36, β=−1.44, and β=−1,116.84; P<0.05). No significant correlations were observed between compliance and other variables (arm fat percentage [ARFAT], android fat distribution, gynoid fat distribution, and LBM) measured using DEXA.

After implementing the lifestyle-modification program “Change 10 Habits” for 12 weeks, we found that the scores of dietary habits such as “eat three meals regularly, adequate amount” and “do not eat after 9:00 PM” improved in the HC group more than in the LC group. However, “do not eat after 9:00 PM” was the only habit displaying a significant score difference between the two groups from baseline, making it challenging to exclusively attribute the degree of habit change to compliance differences. Moreover, the differences in baseline and final scores between compliance groups were not substantial, indicating similar effects from personalized nutritional education in both groups. Nevertheless, the distribution of the SoC in the “do not eat after 9:00 PM” habit exhibited the largest decrease in the P/C stages and increase in the A/M stages, respectively.¹⁸ Considering that these shifts indicate an overall improvement in the change stages for all participants, it is plausible that the impact based on compliance may have been diluted. We also found that both BMI and percentage of body fat decreased in the HC group more than in the LC group. In addition, in the HC group, the systolic BP, TG level, and VLDL-C level decreased significantly from baseline to after 12 weeks. Our results suggest that HC is associated with low total body fat, LEFAT, and TRFAT.

To manage obesity, behavioral modifications that improve eating habits and physical activity levels are needed.¹⁹ Education focused on diet and exercise is essential in obesity management, but that alone has little effect on weight reduction and maintenance. However, according to behavior-change theory, the behavior of participants is key to weight reduction. Thus, behavior-change theory suggests that participants should implement healthy behaviors and overcome obstacles encountered during behavior implementation to maintain weight reductions. Lifestyle changes are known to influence long-term weight reduction more than short-term changes, and, relative to other treatment methods, lifestyle changes are associated with fewer side effects, a low rate of abandonment, and high levels of effectiveness in the prevention of the “yo-yo” phenomenon that can occur after treatment.²⁰ In a previous weight-reduction study that focused on a TTM-based intervention, positive changes in weight, diet, and blood chemistry profile were observed.²¹ In this study, we designed a TTM-based behavior-change program and implemented it according to the SoC of participants. We then evaluated participant compliance using the total score of five questions that explored achievement, SoC, attitude, and self-efficacy. The “Change 10 Habits” program includes messages that induce a healthy lifestyle and can easily be remembered in daily life. After the program, the behavior scores of all the participants increased, indicating improvements in their behavior. In particular, the behavior “drink eight glasses of water a day” garnered the highest score, while the behavior of performing “1 hour of exercise a day” received the lowest score. In other words, “drink eight glasses of water a day” is the easiest behavior to practice in daily life among those explored in this study. Although the score for performing “1 hour of exercise a day” increased, its score remained <5 points, suggesting that the participants had difficulty with self-monitoring regular exercise. In a previous study, it was reported that high attendance and self-monitoring are essential for successful weight reduction.²² Similarly, in our study, over the 12 weeks of the program, the scores for “eat three meals regularly, adequate amount” and “do not eat after 9:00 PM” were higher in the HC group than in the LC group.

The daily caloric intake of all participants was lower after the 12-week program than at baseline. Despite a reduction in energy intake in both groups, the LC group had lower intakes of dietary fiber and most micronutrients post-intervention compared to the HC group. This was attributed to a decrease in meal quality resulting from the LC group’s lack of practice following the habit of “eat three meals regularly, adequate amount.” There is a general agreement that maintaining regular meal patterns, as opposed to irregular ones, enhances consumers’ dietary habits and nutrition.^23,24 Insufficient intake of micronutrients like calcium and sodium may be associated with the prevalence of obesity.²³ It was reported that poor dietary calcium intake is associated with low blood calcium levels, increased intracellular calcium levels by calcitriol, stimulation of fatty acid synthesis, inhibition of lipolysis, and induction of obesity.²⁴ Although our participants practiced new diet behaviors to reduce body weight, the sodium intake of both study groups exceeded the daily sodium intake recommendation (i.e., 2,300 mg/day).²⁵ Therefore, modifications to sodium intake-related behaviors should be included in the next program. The changes in behavior and dietary habits in this study resulted in changes in BMI and body composition. There were no significant differences in BMI at baseline between the two groups, but, after the program, the BMI of the HC group was significantly lower than the BMI of the LC group. Thus, the proportion of overweight individuals within the HC group decreased after 12 weeks of the program. A remarkable finding of this study was that HC was strongly associated with low LEFAT, low TRFAT, and both low body fat mass and percentage. This finding suggests that participants in the HC group had a high level of practice of the “Change 10 Habits” behaviors in their customized lifestyle-modification program. Further, this finding is consistent with the previous finding of more effective weight reductions with higher compliance.²⁶ Regarding body fat composition, ARFAT, LEFAT, and TRFAT increased in the LC group, while ARFAT, LEFAT, TRFAT, android fat distribution, and total body fat decreased in the HC group. There were significant differences in LEFAT, total body fat percentage, and total body fat mass between the two groups. These differences may correlate with the “Change 10 Habits” score as diet restriction and regular exercise are generally recommended for weight reduction. In this study, the score for practicing “1 hour of exercise a day” did not increase significantly after the program in both groups, remaining <5 in both groups after the program, which implies that exercise is the most difficult of the 10 habits studied to practice. Regarding the score for performing “1 hour of exercise a day” over the 12 weeks of the program, we found that it did not increase in the LC group but did steadily increase in the HC group. We suppose that participants in the HC group exercised steadily but did not perform sufficient exercise. We also found that the higher was the compliance, the lower were the LEFAT, TRFAT, body fat percentage, and body fat mass. Participants in the HC group were more willing to reduce their body weight than participants in the LC group, and the reductions in body weight and body fat were greater in the HC group than in the LC group.

The lipid profile of the HC group improved and the TG and VLDL-C levels of the HC group were also decreased significantly after the program. It was reported in a previous study that visceral fat is induced due to excessive energy intake, a high-fat diet, and reduced physical activity, and that the amount of glucose used in skeletal muscles decreases with increased release of FFAs from visceral fat, resulting in dyslipidemia, hyperglycemia, and insulin resistance.²⁷ Moreover, insulin resistance in the liver degrades the function of insulin, which inhibits the secretion of VLDL-C.²⁸ The results of this study showed that higher compliance in the program is associated with a lower body fat percentage, which may have influenced the improvements in lipid profile.

This study has a great strength because there are few studies that have evaluated TTM-based interventions and their effects on diet, blood chemistry, and body composition based on compliance. On the other hand, this study has some limitations. Although we obtained data on body fat composition, lipid profile, and behavior change, we could not determine a causal relationship between the factors. In addition, the study duration was too short to identify the effects of TTM-based intervention on weight reduction and maintenance. Thus, further research is needed to determine the associations between the above-mentioned factors, and long-term studies on customized lifestyle modifications for body weight reduction are required.

In summary, eating behaviors, anthropometric characteristics, and blood parameters improved more in the HC group than in the LC group, and compliance was significantly associated with changes in body fat composition. The results of this study show that customized lifestyle-modification programs and good compliance (e.g., attendance, attitude, self-efficacy, or goal achievement) can effectively control obesity.

The authors declare no conflict of interest.

Study concept and design: BHK; acquisition of data: BHK; analysis and interpretation of data: BHK; drafting of the manuscript: BHK, DYK, and KS; critical revision of the manuscript: MK, KS, and HL; statistical analysis: BHK; and study supervision: HL.