Prevention of Metabolic Syndrome by Telephone-Delivered Lifestyle Intervention in a Real-World Setting: Sub-Analysis of a Cluster-Randomized Trial

Abstract

Background:

Evidence of the long-term benefits of telephone-delivered lifestyle interventions is limited. This study investigated the ability of telephone-delivered lifestyle intervention to reduce the incidence of metabolic syndrome (MetS) in subjects diagnosed with impaired fasting glucose (IFG) during health checkups.

Methods:

Our subjects were participants in the Japan Diabetes Outcome Intervention Trial-1 (J-DOIT1), a prospective, cluster-randomized controlled trial designed to investigate whether goal-focused lifestyle coaching over the telephone can effectively reduce the incidence of type 2 diabetes development in high-risk individuals in a primary health care setting. We extracted 753 and 844 J-DOIT1 participants from the intervention and controls arms, respectively, who had IFG but did not meet the MetS criteria at baseline. The intervention arm received goal-focused lifestyle support delivered by health care providers via telephone over a 1-year period. The endpoint was the development of incident MetS, defined based on the Adult Treatment Panel III criteria modified for Japan.

Results:

During the median follow-up period of 4.9 years, 8.0% of the intervention arm and 12.0% of the control arm developed MetS. Overall, the hazard ratio (HR) for the development of MetS was 0.75 [95% confidence interval (CI), 0.52–1.09; P = 0.14] in the intervention arm. However, the HR in overweight or obese [body mass index (BMI) ≥23 kg/m²] individuals was significantly reduced to 0.63 (95% CI, 0.41–0.95; P = 0.029), but not in lean (BMI <23 kg/m²) individuals.

Conclusion:

Telephone-delivered lifestyle intervention effectively reduced the incidence of MetS in overweight and obese subjects in a real-world setting. Clinical trial registration number: UMIN000000662 (registered March 30, 2007; https://upload.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000000798).

Introduction

Metabolic syndrome (MetS) is associated with an increased risk of type 2 diabetes (T2D) and cardiovascular disease.^1
–3 In Japan, the prevalence of MetS was previously reported to be 26.9% and 9.9% in adult men and women, respectively.⁴ To mitigate the recent large increase in medical costs due to an aging society, the Ministry of Health, Labour, and Welfare launched the “Health Checkups and Healthcare Advice with a Particular Focus on Metabolic Syndrome” program (Tokutei Kenshin Hokenshido) in 2008, which aims to contend with the epidemic of MetS and reduce cardiovascular disease and T2D.^5,6

Nowadays, it is mandatory for all adults in Japan aged 40–74 years to undergo this health checkup annually at the workplace or a community center. Those identified as having MetS or being at a high risk of developing it are provided health care advice by professionals. However, it remains to be determined whether the trial launched by the government is effectively lowering the incidence of MetS. Although previous meta-analyses indicated that lifestyle modification interventions are effective in delaying MetS,^7

–10 evidence-based methodologies for lifestyle modifications that can be implemented widely in a public health care setting remain to be identified. Telephone counseling would make it possible to deliver lifestyle intervention broadly and at a low cost while maintaining a personalized interaction. Several studies indicated that telephone-delivered lifestyle interventions promoted significant weight loss in subjects with MetS.^11,12 We previously conducted the Japan Diabetes Outcome Intervention Trial-1 (J-DOIT1), a cluster-randomized controlled trial, to test whether goal-focused lifestyle coaching delivered via telephone can reduce the incidence of T2D in subjects with impaired fasting glucose (IFG) in a real-world setting.¹³ Using the data from the J-DOIT1, the present study was initiated to ascertain the proportion of subjects with IFG who develop MetS, and to determine whether lifestyle intervention delivered via telephone over 1 year can reduce the incidence of MetS in IFG subjects.

Methods

Study design

The J-DOIT is a two-armed cluster randomized-controlled trial with randomization at the level of the health care division and a follow-up period of 5.5 years. The subjects in the intervention arm received 1-year telephone-delivered lifestyle support provided by health care professionals, while the subjects in the control arm did not. This study was approved by the Ethical Committee of the Japan Foundation for the Promotion of International Medical Research Cooperation (Tokyo, Japan). A detailed description of the design has been published elsewhere.¹⁴

Participants

Inclusion criteria were an age of 20–65 years and IFG [defined as a fasting plasma glucose (FPG) concentration of 100–125 mg/dL (5.6–6.9 mmol/L)]. Exclusion criteria included diagnosis with T2D, a history of taking antidiabetic agents, and an HbA1c ≥6.5%.¹⁵ Women with a history of gestational diabetes were eligible. Physical or medical conditions that prevent exercising, pregnancy or possible pregnancy, type 1 diabetes mellitus, liver cirrhosis or chronic viral hepatitis (type B or type C), and the use of a cardiac pacemaker were also among the exclusion criteria.

Procedure

We recruited health care divisions across Japan between April and October 2006. The eligibility criteria for the health care divisions were as follows: (1) health checkups performed according to guidelines set by the Health Promotion Law, (2) 2,000 or more examinees annually, (3) can provide the study group with health checkup data annually starting from 2006, and (4) can conduct lifestyle surveys annually using a questionnaire prepared by the study team.

Randomization

Health care divisions recruited from communities and companies formed groups of cluster randomization units. The groups were then randomly assigned to an intervention or a control arm by independent statisticians according to a computer-generated list. The groups were notified of their allocation status before study subjects were recruited.

Lifestyle support center

As the sample size was large, we outsourced some study-related activities to three existing private companies that are practicing health care services. They participated in this study as lifestyle support centers, and managed the recruitment and enrollment of study participants and lifestyle interventions. We held educational sessions on diabetes and its prevention for health care providers in each support center and training sessions to improve their telephone counselling skills with motivational interviewing. The staff learned about the program including the baseline assessment (lifestyle, motivation for lifestyle modifications, stage of change, health status, and knowledge of diabetes) and setting the personal action plan: (1) list of specific goals in behavioral terms, coaching in realistic and measurable goals to increase self-efficacy, (2) discussion of advantages and disadvantages of healthy behavior changes, (3) identification of barriers to healthy behavior changes, and (4) discussion of problem-solving approaches to improve ability to overcome barriers. Also, we emphasized that they should encourage participants to measure their body weight and count the number of footsteps taken every day. After educational sessions for health care providers, we checked their diabetes prevention knowledge (70 items, total of 70 points), confidence in diabetes prevention support (7 items, 5-point scale, total of 35 points), confidence in diabetes prevention support for participants in precontemplation, completion, or preparation stage (0%–100% scale, total of 100 points), and attitude toward diabetes prevention support (10 items, 7-point scale, total of 70 points). There was no different in the diabetes prevention knowledge score among health care providers of centers A, B, and C (36.3 ± 6.3, 38.4 ± 3.1, and 37.3 ± 4.3 points, respectively). There was no difference in confidence score of diabetes prevention support among three centers (20.8 ± 3.9, 20.2 ± 2.2, and 18.4 ± 2.9 points, respectively). There was no difference in the confidence score for diabetes prevention support for participants in the precontemplation, completion, or preparation stage among the three groups (Precontemplation stage, 37.3 ± 19.5, 51.1 ± 26.2, and 34.3 ± 15.1 points, respectively; Completion stage, 50.0 ± 17.9, 57.8 ± 23.9, and 44.3 ± 12.7 points, respectively; Preparation stage, 74.5 ± 21.2, 74.4 ± 15.9, and 54.3 ± 16.2 points, respectively). There was no difference in the attitude score for diabetes prevention among the three centers (62.3 ± 3.9, 61.0 ± 5.9, and 59.9 ± 6.7 points, respectively). We supervised each lifestyle support center.

Interventions

Intervention arm

Telephone-delivered lifestyle support was provided by lifestyle coaches (nurses, public health nurses, and dieticians) over a 1-year period through a lifestyle support center. The goals for lifestyle change were set for each subject as follows: (1) habitual exercise (10,000 steps or more per day),^16,17 (2) achievement and maintenance of an appropriate body weight (a 5% reduction in body weight in subjects with a body mass index (BMI) of ≥25 kg/m² or a 3% reduction in subjects with a BMI of 23.0–24.9 kg/m²), (3) habitual intake of dietary fiber (five or more dishes of vegetables per day or 350 grams or more of vegetables per day), and (4) restrictions on alcohol intake [1 “go” (180 mL containing 23 grams of alcohol) or less of Japanese sake or its equivalent per day].¹⁸ Each participant was provided with a weight scale (HBF-354 IT-2; Omron Healthcare Co., Ltd.) and pedometer (HJ-710 IT; Omron Healthcare Co., Ltd.) with a storage function. The lifestyle coaches discussed the advantages and disadvantages of health behavior changes with the participants; they identified barriers to health behavior changes and discussed problem-solving approaches to improve the ability to address these barriers. They also listed realistic and measurable personal action plans and encouraged the participants to increase their self-efficacy. The participants were encouraged to measure their body weight and count footsteps daily, and to send the accumulated data to the lifestyle support centers via a transmitter (DC-100; JMS Co., Ltd.). The lifestyle coaches monitored progress toward the participant's goals regularly and provided advice by phone. The average number of phone calls a participant received over 1 year was 5.7, with each call lasting 15–30 min. Participants received lifestyle support calls 3 times from center A, 6 times from center B, and 10 times from center C over 1 year, with the length of each call being between 15 and 30 min. The average number of phone calls that a participant received over 1 year was 5.7 ± 3.2 in all three centers. The average numbers of phone calls that a participant received over 1 year for center A, center B, and center C were 2.8 ± 0.7, 5.2 ± 1.9, and 8.4 ± 3.3 times, respectively). During the intervention period, the participants received periodic newsletters.

Control arm

After setting achievement goals, subjects in the control arm received a weight scale and pedometer. The subjects periodically received newsletters containing health-related information from the lifestyle support center. As such, the control arm was a self-directed arm with self-help devices. The intervention group also received periodic newsletters.

Follow-ups

Participants were followed up over a 3-year period using data from annual health checkups and a questionnaire regarding health and lifestyle.

Assessments

Descriptive measures

Data on the following demographic variables were collected through self-administered questionnaires and health checkups: age, sex, height, weight, and blood pressure.

Primary endpoint measure

The primary endpoint was the development of MetS, which was defined using the modified criteria of the third report of the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Cholesterol in Adults (Adult Treatment Panel III). Individuals with three or more of the following components present were judged to have MetS: (1) serum triglycerides (TG) ≥150 mg/dL (≥1.69 mmol/L), (2) high-density lipoprotein cholesterol (HDL-C) <40 mg/dL (<1.04 mmol/L) for men and <50 mg/dL (<1.29 mmol/L) for women, (3) FPG ≥100 mg/dL (≥5.6 mmol/L), (4) blood pressure ≥130/85 mmHg or taking blood-pressure lowering agents, and (5) BMI ≥25 kg/m².⁸ The waist circumferences were not measured at the majority of health checkup sites in 2006, when the baseline data were obtained; therefore, BMI was used as a substitute. Information regarding the use of TG-lowering medications was unavailable.

Secondary endpoint measures

Secondary endpoints included a change in body weight, achievement of the intervention goals (exercise habits, dietary fiber intake, and restriction of alcohol intake), and a reduction in systolic and diastolic blood pressure, FPG, serum TG, and HDL-C levels. Blood samples were analyzed with standard methods in clinical laboratories under the nationally certified laboratory management system.

Sample size

We initially planned to recruit a total of 2,398 patients from 40 clusters, with ∼60 participants being recruited from each cluster of the J-DOIT1, to examine whether the intervention was effective for reducing the incidence of T2M. Assuming a dropout rate of 30%, we calculated that 3,426 participants would have been required. In the Diabetes Prevention Program (DPP), 3-year cumulative incidences for MetS were 51%, 45%, and 34% in the placebo, metformin, and lifestyle groups, respectively.⁸ Detecting significant change in the development of MetS over 3 years, with a reference rate of 15% in the control arm and a hazard ratio (HR) of 0.5 (α = 0.05, power = 0.8 not allowing for clustering), requires a sample size of 275 subjects in each arm. Using an intra-class correlation (ICC) of 0.05 with 30 subjects in each cluster, the necessary sample size in each arm is 720, representing a total of 1,440 patients for both arms.

Statistical analyses

Values are presented as the mean (standard deviation) or percentage. Student's t-test was used to compare the means (or distribution) of the two study arms for continuous variables. A chi-squared test was used to compare the proportions of categorical variables. Cox regression analysis was used to calculate the HR and 95% confidence interval (CI). We took into account the clustering effect.¹³ The data were analyzed using the Stata/IC 13.1 software. Patients with missing data were omitted from the relevant analysis. P < 0.05 was considered significant.

Results

A total of 2,840 subjects for the J-DOIT1 study who performed health checkups at their workplaces or community centers were recruited. Among them, 1,063 (37.4%) possessed ≥3 elevated metabolic components (BMI, TG, HDL-C, FPG, and blood pressure) at baseline, thus fulfilling the criteria for MetS. Those who did not meet the criteria (753 subjects in the intervention arm and 844 in the control arm) were analyzed in this study. Approximately half of the subjects had one other MetS component in addition to IFG; high blood pressure was the most frequent, followed by a BMI ≥25 kg/m². There were no differences in baseline characteristics between the two arms (Table 1). Characteristically the BMI ranged widely from “underweight” to “obese” levels. There was no difference in BMI between the arms (P = 0.115).

Table 1.

Baseline Characteristics of Study Participants in the Control and Intervention Arms

	Intervention arm (n = 753)	Control arm (n = 844)
Age, years	48.8 (8.1)	48.4 (7.9)
Male, %	78.6	80.9
BMI, kg/m²	23.1 (2.6)	22.9 (2.2)
BMI categories
Underweight (<18.5 kg/m²), %	3.2	3.1
Normal (18.5–22.9 kg/m²), %	45.8	47.0
Overweight (23.0–24.9 kg/m²), %	36.0	37.1
Obesity I (25.0–29.9 kg/m²), %	13.1	12.3
Obesity II, III (≥30.0 kg/m²), %	1.9	0.5
Systolic blood pressure, mmHg	121.4 (14.2)	120.8 (14.4)
Diastolic blood pressure, mmHg	75.6 (9.7)	76.1 (9.9)
HDL-C, mmol/L	1.7 (0.4)	1.7 (0.4)
Triglycerides, mmol/L	1.1 (0.6)	1.1 (0.6)
Fasting plasma glucose, mmol/L	5.9 (0.3)	5.9 (0.3)

Values are the means (standard deviation) or percentages.

BMI, body mass index; HDL-C, high-density lipoprotein cholesterol.

Primary endpoint measures

The drop-out rate was 19.7%, with no differences between the two arms. After being randomized as a cluster randomization unit (health care division), we collected baseline data from annual health checkups and recruited participants. Therefore, a time lag between registration and the start of the intervention occurred (−1.2 years, maximum). Participants received 1-year intervention and were then followed up. We collected the first data of annual health checkups after 1-year intervention (−3.75 years, maximum). Therefore, the median follow-up period was 4.9 years. During the study period (5.5 years, maximum), 8.0% (60 of 753) of the intervention arm and 12.0% (101 of 844) of the control arm developed MetS. The annual incidence of MetS, calculated on the basis of 100 person-years, was 3.3 in the intervention arm and 4.4 in the control arm. The HR for the development of MetS did not differ between the arms (Table 2). We then examined the incidence of MetS and the effects of the interventions among different BMI groups. As shown in Table 3, the annual incidence of MetS in subjects with normal or subnormal BMI (49%) was much lower than in those with BMIs ≥23 kg/m². Intervention significantly reduced the HR in subjects with a BMI ≥23 kg/m² to 0.63 (95% CI, 0.41–0.95; P = 0.029), but not in subjects with a BMI <23 kg/m² (Table 3), suggesting that the intervention was highly effective in reducing the incidence of MetS in overweight and obese subjects with IFG.

Table 2.

Hazard Ratios for the Development of Metabolic Syndrome

	Intervention arm			Control arm			HR (95% CI)	P
	No. of MetS subjects	Person-year at risk	Hazard per 100 person-years at risk	No. of MetS subjects	Person-years at risk	Hazard per 100 person-years at risk	HR (95% CI)	P
All (n = 1,597; 753/844)	60	2,068	2.9	101	2,055	4.9	0.67 (0.45–1.01)	0.056
Obesity categories
BMI ≥23 kg/m² (n = 814; 390/424)	46	941	4.9	84	1,149	7.3	0.63 (0.37–0.84)	0.005
BMI <23 kg/m² (n = 783; 363/420)	14	905	1.6	17	1,155	1.5	1.00 (0.34–3.01)	0.993

Number, intervention arm/control arm. Cox regression analysis was used to calculate the HR and 95% CI.

CI, confidence interval; HR, hazard ratio; MetS, metabolic syndrome.

Table 3.

The Proportions of Subjects Who Achieved Intervention Goals at Baseline, 1 Year After Intervention, and the End of the Trial

Variables	Intervention arm			Control arm
Variables	All (%)	BMI ≥23 kg/m² (%)	BMI <23 kg/m² (%)	All (%)	BMI ≥23 kg/m² (%)	BMI <23 kg/m² (%)
Exercise habits
Baseline	50.9	52.6	49.0	51.8	53.1	50.5
1 Year after intervention	64.1	65.1	63.1	61.0	61.8	60.2
End of trial	61.2	61.3	61.2	59.5	61.8	57.1
Dietary fiber intake
Baseline	0.0	0.0	0.0	0.2	0.0	0.5
1 Year after intervention	40.0	3.8	4.1	0.2	0.0	0.5
End of trial	12.6	10.8	14.6	6.6	6.1	7.1
Restriction of alcohol intake
Baseline	46.1	42.8	49.6	41.8	36.8	46.9
1 Year after intervention	48.1	44.4	52.1	42.8	38.7	46.9
End of trial	52.6	50.3	55.1	48.3	44.1	52.6

Secondary endpoint measures

The decrease in body weight was slightly but significantly greater in the intervention arm than in the control arm after 1 year of intervention (−1.3 ± 3.2 vs. −0.6 ± 3.2 kg; ICC = 0.023, P = 0.007) and at the end of the trial (−0.9 ± 3.2 vs. −0.3 ± 3.2 kg, respectively; ICC = 0.015, P = 0.044). In subjects with BMIs ≥23 kg/m², the decrease in body weight was slightly but significantly greater in the intervention arm than in the control arm after 1 year of intervention (−1.6 ± 3.2 vs. −0.1 ± 3.3 kg; ICC = 0.011, P = 0.034): however, it was nonsignificant at the end of the trial (−1.2 ± 3.2 vs. 0.7 ± 3.6 kg, respectively; ICC = 0.014, P = 0.116). In subjects with BMIs <23 kg/m², the decrease in body weight was slightly but significantly greater in the intervention arm than control arm after 1 year of intervention (−0.9 ± 2.9 vs. 0.2 ± 3.1 kg; ICC = 0.017, P = 0.006) and at the end of the trial (−0.5 ± 3.0 vs. 0.2 ± 3.1 kg; ICC = 0.042, P = 0.049).

The proportions of subjects who achieved dietary fiber intake goals tended to be greater in the intervention arm than in the control arm 1 year after intervention and at the end of the trial (Table 3). However, there were no differences in terms of exercise and alcohol restriction goals. Among the five MetS components (BMI, TG, HDL-C, FPG, and blood pressure), the intervention decreased the proportion of patients with TG ≥150 mg/dL (both at 1 year after intervention and at the end of the trial) and of those with high blood pressure (only at the end of the trial). The proportion of IFG dropped by ∼35% 1 year after commencing intervention; this drop was maintained until the end of the trial in both the intervention and control arms (Table 4).

Table 4.

The Proportion of Metabolic Components at 1 Year After Intervention and at the End of the Trial

Variables	Intervention arm			Control arm
Variables	All, %	BMI ≥23 kg/m², %	BMI <23 kg/m², %	All, %	BMI ≥23 kg/m², %	BMI <23 kg/m², %
(1) Obesity component: BMI ≥25 kg/m²
Baseline	15.0	29.0	0.0	12.8	25.5	0.0
1 Year after intervention	15.0	28.5	0.6	14.1	27.6	0.5
End of trial	17.1	32.8	0.3	15.4	29.5	1.2
(2) High fasting plasma glucose
Baseline	100.0	100.0	100.0	100.0	100.0	100.0
1 Year after intervention	63.6	65.9	61.2	63	67.0	59.0
End of trial	65.7	66.4	65.0	62.1	63.0	61.2
(3) High serum triglycerides
Baseline	7.8	9.7	5.8	9.8	7.5	9.0
1 Year after intervention	10.2^a	11.0	9.4^a	15.4^a,b	20.0^a,b	10.7
End of trial	13.0^a	13.1	12.9^a	17.7^a,b	21.7^a,b	13.6^a
(4) Low HDL-C
Baseline	1.9	2.3	0.9	0.9	0.9	1.0
1 Year after intervention	2.0	2.8	1.1	2.5^a	3.1^a	1.9
End of trial	3.3^a	3.6	3.0	3.4^a	3.3^a	3.6^a
(5) High blood pressure
Baseline	27.1	23.8	30.6	27.0	26.4	27.6
1 Year after intervention	31.2^a	30.0^a	32.5	32.0^a	33.7^a	30.2^a
End of trial	31.9^a	30.3^a	33.6	36.6^a,b	38.9^a,b	34.3^a
No. of metabolic components
One component
Baseline	48.2	35.1	62.4	49.4	36.6	62.3
1 Year after intervention	42.5	39.2	45.5	37.9	30.4	45.5
End of trial	41.4	37.7	45.5	38.4	30.4	46.4
Two components
Baseline	51.8	64.9	37.6	50.6	63.4	37.7
1 Year after intervention	32.4	39.2	26.4	32.0	39.2	24.0
End of trial	32.4	37.7	26.7	34.1	41.7	26.4
Three or more components
Baseline	0.0	0.0	0.0	0.0	0.0	0.0
1 Year after intervention	4.8	6.7	2.8	7.9	13.0	2.8
End of trial	8.0	10.5	5.3	9.0	13.2	4.7

P < 0.05 (vs. baseline).

P < 0.05 (vs. control arm).

Adverse events

There was no difference in the incidence of adverse events between the intervention and control arms (2.3% vs 0.8%; ICC = 0.021, P = 0.103). The numbers of participants who developed cancer, musculoskeletal system problems, ischemic heart disease, stroke, and other adverse events were, 2, 6, 1, 1, and 7 in the intervention arm, and 1, 2, 1, 0, and 3 in the control arm, respectively.

Discussion

Since health checkups became mandatory in Japan, a large number of subjects with IFG are being identified. IFG is one of the components of MetS; therefore, those with IFG could be at a high risk of developing this condition. However, the relationship between IFG and MetS is not fully understood. IFG is defined as an FPG of 100–126 mg/dL, and not all individuals with IFG develop MetS. In terms of health care delivery, it would be helpful to differentiate subjects with IGF who are likely to develop MetS from those who will respond well to lifestyle intervention. Using the data from the J-DOIT1, we therefore aimed to determine whether 1-year telephone-delivered lifestyle interventions in Japanese IFG subjects can reduce the incidence of MetS.

We found that the incidence rate of MetS was low in underweight and normal-weight IFG subjects but rose as the BMI increased. In other words, IFG subjects with BMIs ≥23 kg/m² (overweight and obese) are high-risk groups for MetS, but those with BMIs <23 kg/m² are not. Lifestyle interventions could reduce the incidence of MetS in the former group, as such interventions were found to decrease the proportion of subjects with TG levels ≥150 mg/dL at 1 year and at the end of the trial. Thus, the effect of lifestyle intervention on reducing the incidence of MetS appears to be strongly related to a correction of hypertriglyceridemia. According to the DPP, MetS and some of its components are associated with an increased incidence of diabetes in persons with impaired glucose tolerance, although this incidence rate varied according to the DPP intervention. Baseline hypertriglyceridemia was previously reported to be the second most predictive factor for diabetes after hyperglycemia,¹⁹ and as in our telephone-delivered intervention, face-to-face lifestyle interventions were shown to improve serum TG levels.^20,21

In contrast to hypertriglyceridemia, the proportion of subjects with IFG decreased by ∼35% in both the intervention and control arms at 1 year, with no further changes thereafter. There were no differences in the proportions of IFG between the treatment arms, suggesting that the effect of telephone-delivered lifestyle intervention on FPG was, at most, very small. We provided a weight scale and pedometer to participants in both arms, which may account, at least in part, for the decrease in the proportion of IFG at 1 year among all subjects. Approximately 50% of subjects in our study who had IFG detected during their health checkups had normal or underweight BMI. This suggests that these subjects may not require intervention, since their risk of developing MetS is very low. All health insurers in Japan are mandated to provide Specific Health Checkups and Specific Health Guidance focusing on MetS for all middle-aged adults.⁶ Therefore, this program included not only overweight and obese adults but also normal and underweight adults. It is estimated that ∼50% of men and women aged 40–74 years, corresponding to roughly 27 million people, participate in health checkups annually across Japan. As such, a large number of people who are at high risk of diabetes and cardiovascular diseases are identified every year. Given limited public health resources, it is particularly important to select subjects who are at higher risk and provide them simple, more time-efficient, and effective intervention. Although more work is clearly required, telephone-delivered lifestyle intervention by health professionals could be a useful tool considering that it can deliver lifestyle intervention widely and at a low cost, yet maintain a personalized nature. Telephone counseling is a promising tool to promote a healthy lifestyle.^22,23

The DPP Lifestyle Balance Intervention that involved a 16-session core curriculum in year 1 and 12 sessions of continued telephone contact in year 2, combined with telephone coaching sessions by dietitians, was effective in achieving weight loss for obese people with MetS.¹⁹ Notably, the frequency of calls in our study was lower than in the DPP study.

Diets based on negative-energy-balance, n-3 fatty acids, total antioxidant capacity, and meal frequency have been suggested as effective approaches to treat MetS. Furthermore, the type and percentage of carbohydrates, glycemic index, and dietary fiber content are some of the most import factors associated with insulin resistance, which is an important comorbidity with MetS.²⁴ However, we did not measure dietary factors such as n-3 fatty acids except the dietary fiber intake. A high fiber intake improved insulin resistance and reduced the incidence of T2D.²⁵ In DPP, a high-fiber and low-fat diet with overall calorie reduction led to weight loss, which may reduce the incidence of diabetes in high-risk individuals.²⁶ Although there were no significant differences in exercise habits between the arms, modest but significant weight loss was observed in the intervention group. We consider that weight loss and dietary fiber intake were associated with reducing the incidence of MetS. Further examinations including detailed dietary assessment are required to examine these issues.

Exercise and weight loss lower serum TG levels.²⁷ The consumption of dietary soluble fibers is associated with reduced serum TG levels.²⁸ Dietary fiber is also associated with increased satiety and fullness.²⁹ These factors might explain why the intervention reduced serum TG levels.

This study had several potential limitations. First, we did not have full access to information on the use of drugs; this may have led us to underestimate the prevalence of MetS, even though the study recruited primary subjects with severe disease who did not actively use drugs. In general, patients with hypertriglyceridemia respond to lifestyle modifications, and such patients do not always receive antihyperglycemic drugs such as fibrates in Japan. Second, the study involved volunteer groups with IFG, which may limit the generalizability of our findings.

In conclusion, telephone-delivered lifestyle modification lowered the incidence of MetS in overweight and obese subjects in a real-world setting.

Footnotes

Acknowledgments

This work was supported by a Health and Labor Sciences Research Grant (Strategic Outcomes Research Program for Research on Diabetes and Comprehensive Research on Diabetes/Cardiovascular and Life-Style Related Diseases) from the Ministry of Health, Labour, and Welfare of Japan, and JSPS KAKENHI grant number 18K01988. The authors thank the thousands of participants who contributed to the J-DOIT-1, as well as the numerous investigators involved.

Author Disclosure Statement

No competing financial interests exist.

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