- Email: [email protected]
Effect of a continuous diabetes lifestyle intervention program on male workers in Korea
diabetes research and clinical practice 90 (2010) 26–33
Contents lists available at ScienceDirect
Diabetes Research and Clinical Practice jou rna l hom ep ag e: w ww.e lse v ier .com/ loca te /d iab res
Effect of a continuous diabetes lifestyle intervention program on male workers in Korea Ji Yeon Kang a, Sang Woon Cho a, Sook Hee Sung a, Yoo Kyoung Park b,c, Yun Mi Paek a,*, Tae In Choi a a
Radiation Health Research Institute, Korea Hydro & Nuclear Power Co., Ltd, Seoul, Republic of Korea Department of Medical Nutrition, Kyung Hee University, Yongin, Republic of Korea c Research Institute of Clinical Nutrition, Kyung Hee University, Seoul, Republic of Korea b
article info
abstract
Article history:
Aims: This study was conducted to compare the effects of two years of lifestyle intervention
Received 23 January 2010
to no intervention or one year of intervention on diabetes risk factors in male workers with
Received in revised form
impaired fasting glucose (IFG) or diabetes.
3 June 2010
Methods: We conducted a randomized lifestyle intervention trial designed to alter personal
Accepted 7 June 2010
lifestyles among 123 industrial male workers (CG; control group, n = 75; OIG; one-year intervention group, n = 23; TIG; two-year intervention group, n = 25). The intervention consisted of two parts, the main program (face-to-face counseling five times/12 weeks)
Keywords:
and a follow-up program (e-mail counseling ten times/30 weeks). Assessments included
Diabetes
biochemical characteristics, anthropometry and nutrient intake at baseline and after two
Lifestyle intervention
years.
Long term
Results: After two years, systolic blood pressure, HOMA-IR, HDL cholesterol and total energy
Worker
intake ( p < 0.05) were reduced in the OIG group, while weight, body mass index, waist circumference, blood pressure, fasting plasma glucose (FPG), HbA1c and nutrient intake (total energy, carbohydrate, protein and sodium) were significantly decreased ( p < 0.05, respectively) in the TIG group. When compared to the CG, subjects in OIG and TIG showed significant improvements in the level of FPG and HbA1c ( p < 0.05). Conclusions: Continuous lifestyle intervention for two years is more effective at improving diabetes risk factors than OIG. # 2010 Elsevier Ireland Ltd. All rights reserved.
1.
Introduction
Subjects with diabetes and pre-diabetes (including impaired fasting glucose (IFG) and impaired glucose tolerance (IGT)) face a greater risk for the development of cardiovascular disease (CVD), particularly coronary heart disease, peripheral vascular disease and stroke [1–5]. Previous studies have investigated the feasibility and efficacy of intervention for the prevention and management of diabetes. Additionally, it has recently
been demonstrated that multicomponent lifestyle intervention can prevent or at least postpone type 2 diabetes [6–11]. Moreover, lifestyle interventions that focus on body weight control, physical activity and dietary change have been shown to be much more effective at reducing the incidence of diabetes than pharmacological intervention (metformin) [10]. In the China Da Qing Diabetes Prevention Study (CDQDPS), subjects with IGT who underwent long-term diet and/or were subject to exercise interventions showed a significant de-
* Corresponding author at: Radiation Health Research Institute, Korea Hydro & Nuclear Power Co., Ltd, 388-1 Ssangmoon-dong, Dobong-gu, Seoul 132-703, Republic of Korea. Tel.: +82 2 3499 6651; fax: +82 2 3499 6622. E-mail address: [email protected] (Y.M. Paek). 0168-8227/$ – see front matter # 2010 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.diabres.2010.06.006
diabetes research and clinical practice 90 (2010) 26–33
crease in the incidence of diabetes over a 6-year period [12]. Additionally, a longitudinal follow-up of CDQDPS participants over 20 years (up to 14 years after the active intervention) revealed that combined intervention (diet + exercise) effectively prevented or delayed diabetes [13]. Similarly, a Finnish Diabetes Prevention Study (DPS) [14] revealed significantly greater improvements in clinical and metabolic characteristics and nutrient intake in the intervention group after three years when compared with the control group. The results of an extended follow-up of the DPS revealed that the effect of lifestyle intervention on diabetes risk remained after active lifestyle counseling was stopped [15]. Similar study was performed in the U.S. for over a decade (Diabetes Prevention Program and the following Diabetes Prevention Program Outcomes Study) and the results were quite similar to that of the DPS. After 10 years (treatment period: about 3 years, extended follow-up period: about 7 years), a reduction in diabetes incidence by either lifestyle (34%) or metformin (18%) therapy persisted for at least 10 years [16]. The results hold strong, however, only with an extended length of intervention. Short-term intervention studies have been found to have limited effects. For example, Chan et al. [17] reported that waist circumference and diastolic blood pressure improved, [(Fig._1)TD$IG]but that hemoglobin A1c (HbA1c) and HDL levels worsened at
27
the end of 6 months. Moreover, Jacobs-van der Bruggen et al. [18] suggested that interventions be continued (with at least two counseling sessions) during the second year to sustain the potential long-term health and economic consequences of lifestyle interventions. These results indicate that sustainability of lifestyle intervention is required to achieve the desired long-term effects of lifestyle intervention. The present study was conducted to determine if a continuous lifestyle intervention program reduced the number of diabetes-related factors and improved nutrient intake among male office workers with IFG and diabetes. The lifestyle intervention effect was analyzed by a comparison among three intervention programs (no intervention, one-year and two-year intervention).
2.
Subjects, materials and methods
2.1.
Subjects and study design
Written informed consent was obtained from all subjects, and the research protocol was approved by the Institutional Review Board of the Asan Medical Center (Seoul, Korea, 2007). Fig. 1 shows a flowchart of this study. The subjects were
Fig. 1 – Flowchart of the study.
28
diabetes research and clinical practice 90 (2010) 26–33
recruited from industrial male workers by screening members of the diabetes risk group who participated in annual regular health check-ups. Type 2 diabetes and IFG were defined according to the American Diabetes Association (ADA) criteria based on the fasting plasma glucose (FPG) levels. Type 2 diabetes was defined as a FPG 7.0 mmol/l while IFG was defined as a FPG level of 5.6–6.9 mmol/l [19]. Harati et al. [20] reported that a 5.6 mmol/l cut-off value of IFG combined with other diabetes risk factors performed better than the 6.1 mmol/l value for prediction of future type 2 diabetes. Subjects taking glucose-lowering drugs, lipid-lowering therapy or anti-hypertensive medication, manifesting cardiovascular disease and chronic alcohol and/or drug abuse were excluded from basal screening. Subjects who satisfied the inclusion criteria (n = 285) were called and invited to participate in the intervention, and 125 individuals accepted. The subjects were then randomly assigned to either the control group (CG), one-year intervention group (OIG) or two-year intervention group (TIG) after stratification for age, FPG and HbA1c levels. Specifically, the subjects were assigned in a 1.5:1 ratio to either the CG or a lifestyle intervention group. Two subjects in the OIG were excluded because they were unable to receive the intervention due to job relocation; however, no one was excluded from the CG or TIG. Overall, 123 men (CG: 75, OIG: 23, TIG: 25) were included in the final analyses. The lifestyle intervention program consisted of two parts, a main program and a follow-up program. The main program consisted of 5 times of 20–30 min of face-to-face counseling based on the participant’s health profiles (5 times during 12 weeks). Four weeks after the main program was finished a follow-up program was started. During the follow-up program period, e-mail nutrition education was provided every three weeks, a total of 10 times. Each e-mail included information regarding healthy eating habits and lifestyle such as examples of foods or dietary pattern that leads to diabetes, dietary tips when eating out, and easy guide to increase physical activity. After baseline examination, subjects of the OIG were instructed to continue their usual lifestyle for one year and then underwent lifestyle intervention. At the second year, the members of the group received the same lifestyle intervention as the TIG. The subjects in control group received general information on health at baseline but were offered no further information for the duration of the study. At baseline and after two years all study subjects were subject to anthropometric examination, blood sampling and dietary recording.
2.2.
Lifestyle intervention program
The intervention program consisted of motivating each participant to correct imbalances in their lifestyle voluntarily by providing practical advice. Lifestyle intervention program were made based on the key components of Comprehensive Lifestyle Modification Program (CLMP) [21] to focus on improving self-confidence for exchange of usual lifestyle. In each session, experienced staff and each participant developed one or two specific and achievable goals such as ‘‘Use stairs instead of elevators to and from work’’, ‘‘Eat fruits or milk instead of high-calorie food (bread, pizza, etc.), ‘‘March in place during watching TV’’ and ‘‘Eat breakfast every morning’’ to work on until the next session. During each session, the
experienced staff checked whether the personal goals had been achieved. If so, the participant was advised to continue to maintain the goals and, if possible, set additional goals. Moreover, if the participant had any problems or concerns, they were instructed to call a staff member for specific and practical advice and coping strategies. All participants in the intervention group also received health-related materials to view at home and in the workplace (e.g. pamphlets and brochures). Dietary recommendations were consisted of: calorie goal of 1400–2200 per day with 55–70% carbohydrate intake, 7–20% protein and 15–25% fat followed by recommendation from Korean Diabetic Association; daily salt intake of less than 5 g; and daily alcohol intake of less than about 50 g [22]. Professional dietitian used motivational counseling skill and developed an action plan for individualized problem solving and behavior-change support. Counseling session consisted of a theoretical portion with a presentation on dietary advice and its background, after which examples of recommendable foods were introduced. Participants were encouraged to keep regular meal time, eat more fruits and vegetables and avoid high-risk foods containing high levels of saturated fat, cholesterol, simple sugar, alcohol and sodium and limit nighttime snacking. All sessions included extra time for questions and a discussion about food choice and additional topics. Participants with a body mass index (BMI) of less than 25 kg/m2 were advised to maintain their present weight, but, those who are overweight were advised to reduce their weight to a desirable level at a rate of 1.0–2.0 kg/month. Weight reduction, however, was not the primary goal of the intervention, rather a possible outcome of changes in lifestyle. All subjects in the lifestyle intervention were individually guided to increase their physical activity to burn up about 200– 300 kcal/day such as brisk walking can be accumulated in sessions of at least 10 min to reach the total of 30 min a day. And, moderate intensity and endurance exercise (walking, jogging, mountaineering, cycling) was recommended to increase aerobic capacity and lean body mass.
2.3.
Measurements
Anthropometric measurements of subjects were conducted by experienced research staff. Height and weight were recorded with participants wearing lightweight clothing and no shoes using a body composition analyzer (Inbody 720; Biospace Co., Seoul, Korea). BMI was calculated as the body weight (kg)/height squared (m2). Waist circumference (WC) was measured at the midpoint between the iliac crest and the lower ribs [23]. Blood pressure was measured twice using a standard manometer (FT-700R; Jawon Medical Co., Seoul, Korea), with the average of two measurements taken as the final result. Blood samples were collected from each subject after overnight fasting for more than 10 h. FPG, HbA1c, total cholesterol, high-density lipoprotein cholesterol (HDL) and low-density lipoprotein cholesterol (LDL) were analyzed by enzymatic methods using commercially available kits and an automatic analyzer (Cobas Integra 800; Roche Diagnostics, Mannheim, Germany). And, homeostasis model of insulin
29
diabetes research and clinical practice 90 (2010) 26–33
Table 1 – Effects of lifestyle intervention program on anthropometrics and biochemical characteristics. Control group (n = 75) Baseline Age (years)
After
47.47 5.79
Proportion of IFG to Diabetes IFG 63 (84.0) Diabetes 12 (16.0)
75.17 9.11 25.60 2.58 a 85.43 7.35 a 132.41 14.05 87.64 11.03 6.37 0.86 5.95 0.81 2.23 1.47 204.04 32.10 a 49.87 13.80 135.72 31.39
Baseline
After
45.61 6.06
57 (76.0) 18 (24.0)
Annual income (U.S. dollar) ** >90,000 25 (33.3) 90,000 50 (66.7) Weight (kg) BMI (kg/m2) WC (cm) SBP (mmHg) DBP (mmHg) FPG (mmol/1) HbAlc (%) HOMA-IR Total cholesterol (mg/dl) HDL (mg/dl) LDL (mg/dl)
One year intervention group (n = 23)
Baseline
After
45.84 5.17
22 (95.7) 1 (4.3)
23 (100.0) 0 (0.0)
17 (73.9) 6 (26.1) 74.91 8.87 25.57 7.58 88.61 6.44 * 131.61 15.75 86.59 11.82 6.20 1.26 6.23 1.21 * 2.20 1.87 209.79 34.71 50.53 13.46 124.31 33.18 *
Two years intervention group (n = 25)
22 (88.0) 3 (12.0)
23 (92.0) 2 (8.0)
8 (32.0) 17 (68.0)
72.42 9.67 24.44 3.1 l ab 83.20 5.43 ab 131.70 12.21 84.65 9.66 5.99 0.41 5.58 0.52 1.73 1.23 195.48 31.12 a 45.65 13.37 121.70 34.62
72.10 9.35 24.33 3.06 84.30 6.34 125.17 12.49 * 83.00 9.52 5.14 0.77 * 5.44 0.89 1.25 0.82 * 195.39 33.11 42.87 13.14 * 115.04 31.66
77.48 11.65 26.77 3.68 b 89.06 9.19 b 135.96 11.91 83.28 7.87 6.24 0.67 5.88 0.64 2.12 1.93 222.32 31.59 b 44.64 13.66 135.20 31.91
76.62 10.54 * 26.47 3.27 * 87.30 7.30 * 125.04 9.52 * 79.68 9.26 * 5.41 1.34 * 5.73 0.96 * 1.62 1.21 211.20 34.81 41.36 10.31 129.88 39.90
Data are means S.D. or n(%). IFG: impaired fasting glucose, BMI: body mass index, WC: waist circumference, SBP: systolic blood pressure, DBP: diastolic blood pressure, FPG: fasting plasma glucose, HbAlc: hemoglobin Alc, HOMA-IR: homeostasis model of insulin resistance, HDL: high-density lipoprotein, LDL: low-density lipoprotein. * : Significantly different within group between baseline and after by paired t-test ( p < 0.05). ** : significantly different among three group at baseline by Fisher’s exact test. a,b : Means with different superscript letter are significantly among three group at baseline by Turkey’s post hoc test.
resistance (HOMA-IR) was calculated as FPG (mmol/l) fasting serum insulin (mU/mL)/22.5. Dietary intakes were analyzed using a computerized food frequency questionnaire (FFQ) originally developed by the Korea Centers for Disease Control and Prevention [24] and modified by our institution for industrial workers. The FFQ was designed to collect information regarding the usual intake of food over the past year.
2.4.
Statistical analyses
2.4.1.
Sample size calculation
Given approximately 95% power to detect an effect size of 0.5 standard deviations (SD) among three groups in a fixedeffects ANOVA model with a two-sided a level of 0.05, the estimated target sample size was 66 individuals (22 subjects in each group) [25]. Assuming a drop-out rate of up to 10%, we determined a sample size for the analysis of 75 for the CG, 25 for OIG and 25 for TIG, for a total of n = 125 subjects.
2.4.2.
Data analysis
Statistical analyses were conducted using the SPSS program (SPSS 15.0 KO for Windows; SPSS Inc., Chicago). Variables with skewed distribution were log-transformed prior to statistical analysis. Chi-square test of was used to test the homogeneity of the proportion of IFG and diabetes, and annual income. Paired t-tests were used to analyze the differences between baseline and after intervention values. One-way analysis of variance (ANOVA) with Tukey’s post hoc test was used to
compare groups. A P < 0.05 was considered to be statistically significant.
3.
Results
The baseline characteristics of the three groups are shown in Table 1 and Table 2. There were no differences among groups in terms of age and proportion of IFG and diabetes (data not shown). Annual income was higher in OIG than CG and TIG ( p < 0.05). Additionally, the baseline characteristics were similar across the groups except for the BMI, WC and total cholesterol, which was higher in the TIG than in the other groups. When the effects of the lifestyle intervention program on anthropometry and biochemical characteristics were evaluated, WC and HbA1c were increased while LDL cholesterol was significantly decreased ( p < 0.05) in the CG. In the OIG, systolic blood pressure (SBP), FPG, HOMA-IR and HDL cholesterol were significantly reduced ( p < 0.05). Conversely, we observed a reduction in weight, BMI, WC, SBP, diastolic blood pressure (DBP), FPG and HbA1c in the TIG ( p < 0.05). The efficacy of the lifestyle intervention program on nutrient intake is shown in Table 2. In the CG, there were no differences in nutrient intake at baseline and after lifestyle intervention. However, we observed a reduction in total energy intake in the OIG ( p < 0.05) after intervention. Additionally, the total energy, carbohydrate, protein and sodium levels decreased significantly in the TIG after the intervention ( p < 0.05, respectively).
30
After
7338.81 2705.37 * 17.25 5.30 262.64 69.95 * 52.26 20.69 * 1835.46 660.19 * 160.07 126.59 9.72 6.29 9.91 6.50 4.03 2.33 240.72 240.61
Baseline
9459.47 3083.87 19.08 8.44 320.44 101.74 83.90 35.05 b 4192.41 2428.33 b 153.00 112.21 12.59 10.37 12.92 10.83 5.39 3.83 283.37 207.76
Table 3 shows the magnitude of this effect. The decreases in weight and BMI were similar among the three groups. Follow-up Turkey’s tests showed that changes in WC, SBP and total cholesterol in TIG were greater than changes in the CG and OIG ( p < 0.05). The OIG and the CG showed similar changes in WC, SBP and total cholesterol. The changes in FPG and HbA1c were significantly higher in the TIG than in the other groups ( p < 0.05), but these values did not differ significantly between the OIG and TIG. Finally, the change in the intake of protein and sodium ( p < 0.05) differed among groups, with the TIG having a larger decrease than the CG and OIG.
4.
*
Data are means S.D. MUFA: Monounsaturated fatty acid, PUFA: Polyunsaturated fatty acid. : Significantly different within group between baseline and after by paired t-test ( p < 0.05). a,b: Means with different superscript letter are significantly among three group at baseline by Turkey’s post hoc test.
7863.62 1994.73 15.32 4.79 280.70 73.59 56.17 77.06 1813.11 854.98 165.46 103.19 8.33 4.15 8.52 4.34 4.17 7.31 266.25 264.75 8543.23 2131.97 14.82 4.82 320.24 88.52 59.30 21.57 a 1951.57 979.50 a 165.36 88.85 9.67 4.85 9.57 4.74 4.24 1.83 232.27 224.31 7532.56 2129.98 15.56 6.44 274.09 78.66 52.55 20.19 1743.95 843.91 163.95 116.34 9.02 6.86 9.35 7.38 4.15 2.88 228.96 266.26 8124.19 2975.18 15.14 5.16 302.46 103.72 56.55 28.59 a 2047.61 1295.04 a 154.64 106.42 10.01 7.63 10.25 8.27 4.66 3.81 215.96 225.71 Total energy (kJ) Total fat (E%) Carbohydrate (g) Protein (g) Sodium (mg) Cholesterol (mg) Saturated fatty acid (g) MUFA (g) PUFA (g) Alcohol (kcal)
After Baseline After Baseline
Control group (n = 75)
Table 2 – Effect of lifestyle intervention program on nutrient intakes.
One year intervention group (n = 23)
*
Two years intervention group (n = 25)
diabetes research and clinical practice 90 (2010) 26–33
Discussion
The results of this study indicate that continuous lifestyle intervention can be beneficial for reducing diabetes risk factors. The effects of the intervention program were most intensive in the TIG, especially with respect to glycemic control and nutrient intake. Glycemic control is an important predictor of chronic complications of diabetes. Menzin et al. [26] demonstrated that improved glycemic characteristics led to cost savings. In this study, the FPG levels were significantly decreased in both the OIG ( 0.84 mmol/l) and the TIG ( 0.83 mmol/l). Brekke et al. [27] reported a reduction in FPG of 0.43 mmol/l after one year and 0.34 mmol/l after two years in a diet and exercise group. Lindstrom et al. [14] also showed a reduction in FPG of 0.2 mmol/l one year after intervention, but found that the FPG level was not decreased when compared to that of baseline after three years, suggesting difficulties in changing and maintaining dietary or lifestyle habits. Eriksson et al. [28] showed that after one year of lifestyle intervention, no change in FPG was observed in a group with IGT. Despite IFG being defined as 5.6 mmol/l in this study, intensive lifestyle intervention was more effective at glycemic control when compared with previous lifestyle intervention studies. The homeostatic model assessment (HOMA-IR) was used to approximate insulin resistance. The level of HOMA-IR was significantly reduced in the subjects in OIG, however, no reduction was found in the other groups. While there is still substantial debate in regard to the appropriate diagnostic approach to the insulin resistance, reduced HOMA-IR by lifestyle intervention implies the possibility of improving insulin resistance in the subjects. In addition to improving glycemic control, other studies have also identified changes in nutrient intake after intervention. Mayer-Davis et al. [29] found that the significant differences in the changes of dietary intake of total energy and fat (E%) in the lifestyle intervention group was greater than those of Metformin and Placebo groups at 1-year post intervention. Moreover, Swinburn et al. [30] showed that reduced-fat diet intervention in individuals with glucose intolerance led to significant decreases in energy, fat, fat (E%), carbohydrate (E%) and protein (E%). Roumen et al. [31] reported that total fat (E%) intake was significantly decreased and carbohydrate and fiber intake increased in an intervention group when compared with a control group after three years. Dietary carbohydrate is the primary macronutrient that
31
diabetes research and clinical practice 90 (2010) 26–33
Table 3 – Comparison of changes between baseline and after lifestyle intervention program among three group. Control group (n = 75) DWeight DBMI DWC * DSBP * DDBP DFPG * DHbAlc * DHOMA-IR DTotal cholesterol DHDL DLDL DTotal energy DTotal fat (E%) DCarbohydrate DProtein DSodium DCholesterol DSaturated fatty acid DMUFA DPUFA DAlcohol
One year intervention group (n = 23)
Two years intervention group (n-25)
0.27 2.13 0.08 0.72 3.19 8.85 a 0.80 13.59 a 1.05 10.00
0.32 1.36 0.10 0.46 1.11 5.53 ab 6.52 11.91 ab 1.65 9.14
0.86 1.92 0.30 0.65 1.76 2.95 b 10.92 12.21 b 3.60 7.16
0.17 1.12 a 0.27 0.65 a 0.03 1.29 5.75 25.61 a 0.67 8.25 11.41 26.90
0.84 0.75 b 0.13 0.71 b 0.47 1.01 0.09 27.42 ab 2.78 5.79 6.65 21.99
0.83 0.91 b 0.15 0.69 b 0.50 1.29 11.12 19.56 b 3.28 10.08 5.32 26.64
591.77 3322.74 0.42 5.31 28.37 123.42 3.99 31.10 a 303.66 1419.46 a 9.31 111.89 1.06 9.01 0.90 9.83 0.51 4.17 13.86 204.41
679.61 1849.81 0.50 4.91 39.53 94.51 3.13 20.42 a 138.47 935.73 a 0.10 101.95 1.35 4.59 1.04 4.49 0.12 1.99 33.97 139.47
1951.33 2182.56 1.83 8.90 57.80 89.11 31.63 28.50 b 2356.95 2266.49 b 7.07 135.67 2.87 9.32 3.01 10.11 1.36 3.47 42.66 134.82
D: After - Baseline, BMI: body mass index, WC: waist circumference, SBP: systolic blood pressure, DBP: diastolic blood pressure, FPG: fasting plasma glucose, HbAlc: hemoglobin Alc, HOMA-IR: homeostasis model of insulin resistance, HDL: high-density lipoprotein, LDL: low-density lipoprotein, MUFA: monounsaturated fatty acid, PUFA: polyunsaturated fatty acid. * : Significantly different among group between by ANOVA ( p < 0.05). a,b: Means with different superscript letter are significantly among three group.
affects postprandial glucose levels. In addition, the National Cholesterol Education Program and the American Heart Association recommend lowering the dietary intake of total fat (<30% energy), saturated fat (<10% energy) and cholesterol (<300 mg/dl) to improve lipid levels and reduce the risk of cardiovascular disease [32,33]. Recently, it has been suggested that carbohydrate and fat restricted diets have greater effectiveness in weight loss and metabolic improvement in obese or diabetic patients [34–38]. In our study, the difference in the intake of protein and sodium among groups was striking. Although not significant, total fat (E%) and alcohol intake were reduced in the TIG when compared to the other groups. Moreover, the intake of total energy, carbohydrate, saturated fatty acid, MUFA and PUFA tended to decrease more in the TIG. Although the actual changes in dietary intake levels in this study were trivial when compared with other studies [27,29,30], our lifestyle intervention program with setting individualized simple, but, achievable dietary goal led successful implementation of program. Recently, the WHO recommended that a lower BMI cut-off point for Asians for public health action should be added to the present WHO classifications of BMI based on the difference in the effects of obesity on type 2 diabetes or cardiovascular diseases in Asians [39]. As a result, a BMI of 25 kg/m2 is the recommended cut-off point for obesity for Korean and other Asian populations. Obesity is associated with diabetes [40]; therefore, many intervention studies have targeted weight loss or attainment of a BMI of less than 25 kg/m2 [8,12,28,41]. We found that the weight and BMI reduction that occurred during the study was small but substantial in the TIG. Other
studies on subjects with IGT [8,42] or diabetes risk groups [27,28,43] have found greater weight loss, but this may have occurred because weight reduction was not a primary goal of this study. However, as lifestyle intervention continued, the weight and BMI tended to decrease. Lifestyles are difficult to change. It has been shown that the effects of interventions decrease as the drop out rate increases because of strong restrictions or impediments of the willing participants [31,32,34]. Our study may be more applicable to decreasing diabetes through steady and constant lifestyle change. It should be noted that this study has several limitations. First, the size of the study population was small. We attempted to enroll more participants, but this was difficult due to the unpredictable work schedules of the target population. Second, we evaluated IFG at baseline according to the ADA criteria, which made it difficult to compare the results of our study with those of other studies that employed the WHO criteria [3,17,41,44]. Third, in this study, the effect of change in the level of exercise was not taken into account; therefore, we were not able to distinguish the additive effects of changes in eating behavior and increased levels of exercise on the improvement of glycemic control. Fourth, we conducted random sampling, but baseline data of BMI, WC, total cholesterol, HDL, and intake of protein and sodium was significantly higher in TIG compared to the CG and OIG. It may have influenced the outcomes of intervention. For that reason, we have done a comparative analysis of change between baseline and after lifestyle intervention program among three groups.
32
diabetes research and clinical practice 90 (2010) 26–33
In conclusion, the results of this study showed that, in male Korean industrial workers with IFG or diabetes, continuous lifestyle intervention over two years targeting lifestyle changes had favorable effects on diabetes markers when compared with short-term intervention. This utility of this intervention should be evaluated in a longer term demonstration with a larger population, to better understand the potential sustainability and long-term effectiveness for the prevention and management diabetes.
[11]
[12]
[13]
Acknowledgement The study was supported by grant from the Korea Hydro & Nuclear Power project (E08NJ22).
Conflict of interest
[14]
[15]
The authors declare that they have no conflict of interest.
references [16]
[1] Juutilainen A, Lehto S, Ronnemaa T, Pyorala K, Laakso M. Type 2 diabetes as a ‘‘Coronary Heart Disease Equivalent’’: an 18-year prospective population-based study in Finnish subjects. Diabetes Care 2005;28:2901–7. [2] Stratton IM, Adler AI, Neil HA, Matthews DR, Manley SE, Cull CA, et al. Association of glycaemia with macrovascular and microvascular complications of type 2 diabetes (UKPDS 35): prospective observational study. BMJ 2000;321:405–12. [3] Chakarova N, Tankova T, Atanassova I, Dakovska L. Serum lipid and hsCRP levels in prediabetes-impaired fasting glucose (IFG) and impaired glucose tolerance (IGT), Diabetes. Res Clin Pract 2009;86:56–60. [4] Faeh D, William J, Yerly P, Paccaud F, Bovet P. Diabetes, prediabetes are associated with cardiovascular risk factors and carotid/femoral intima-media thickness independently of markers of insulin resistance and adiposity. Cardiovasc Diabetol 2007;6:32. [5] Meigs JB, Nathan DM, D’Agostino Sr RB, Wilson PW. Fasting and postchallenge glycemia and cardiovascular disease risk: the Framingham Offspring Study. Diabetes Care 2002;25:1845–50. [6] Ramachandran A, Snehalatha C, Mary S, Mukesh B, Bhaskar AD, Vijay V. The Indian Diabetes Prevention Programme shows that lifestyle modification and metformin prevent type 2 diabetes in Asian Indian subjects with impaired glucose tolerance (IDPP-1). Diabetologia 2006;49:289–97. [7] Mensink M, Feskens EJ, Saris WH, de Bruin TW, Blaak EE. Study on lifestyle intervention and Impaired glucose tolerance maastricht (SLIM): preliminary results after one year. Int J Obes Relat Metab Disord 2003;27:377–84. [8] Kosaka K, Noda M, Kuzuya T. Prevention of type 2 diabetes by lifestyle intervention: a Japanese trial in IGT males. Diabetes Res Clin Pract 2005;67:152–62. [9] Tuomilehto J, Lindstrom J, Eriksson JG, Valle TT, Hamalainen H, Ilanne-Parikka P, et al. Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med 2001;344:1343–50. [10] The Diabetes Prevention Program Research Group. Reduction in the incidence of type 2 diabetes with
[17]
[18]
[19]
[20]
[21]
[22] [23]
[24]
[25]
[26]
lifestyle intervention or metformin. N Engl J Med 2002;346:393–403. Li G, Hu Y, Yang W, Jiang Y, Wang J, Xiao J, et al. Effects of insulin resistance and insulin secretion on the efficacy of interventions to retard development of type 2 diabetes mellitus: the DA Qing IGT and Diabetes Study. Diabetes Res Clin Pract 2002;58:193–200. Pan XR, Li GW, Hu YH, Wang JX, Yang WY, An ZX, et al. Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance. The Da Qing IGT and Diabetes Study. Diabetes Care 1997;20:537–44. Li G, Zhang P, Wang J, Gregg EW, Yang W, Gong Q, et al. The long-term effect of lifestyle intervention to prevent diabetes in the China Da Qing Diabetes Prevention Study: a 20-year follow-up study. Lancet 2008;371:1783–9. Lindstrom J, Louheranta A, Mannelin M, Rastas M, Salminen V, Eriksson J, et al. The Finnish Diabetes Prevention Study (DPS): lifestyle intervention and 3-year results on diet and physical activity. Diabetes Care 2003;26:3230–6. Lindstrom J, Ilanne-Parikka P, Peltonen M, Aunola S, Eriksson JG, Hemio K, et al. Sustained reduction in the incidence of type 2 diabetes by lifestyle intervention: follow-up of the Finnish Diabetes Prevention Study. Lancet 2006;368:1673–9. Diabetes Prevention Program Research Group. 10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study. Lancet 2009;374:1677–86. Chan LC, Ware R, Kesting J, Marczak M, Good D, Shaw JT. Short term efficacy of a lifestyle intervention programme on cardiovascular health outcome in overweight Indigenous Australians with and without type 2 diabetes mellitus The healthy lifestyle programme (HELP). Diabetes Res Clin Pract 2007;75:65–71. Jacobs-van der Bruggen MA, van Baal PH, Hoogenveen RT, Feenstra TL, Briggs AH, Lawson K, et al. Cost-effectiveness of lifestyle modification in diabetic patients. Diabetes Care 2009;32:1453–8. The expert Committe on the Diagnosis Classification of Diabetes Mellitus. Follow-up report on the diagnosis of diabetes mellitus. Diabetes Care 2003;26:3160–7. Harati H, Hadaegh F, Tohidi M, Azizi F. Impaired fasting glucose cutoff value of 5.6 mmol/l combined with other cardiovascular risk markers is a better predictor for incident Type 2 diabetes than the 6.1 mmol/l value: Tehran lipid and glucose study. Diabetes Res Clin Pract 2009;85: 90–5. Yoo JS, Lee SJ, Lee HC, Kim MJ. The effect of a comprehensive lifestyle modification program on glycemic control and body composition in patients with type 2 diabetes. Asian Nurs Res 2007;1:106–15. Korean Diabetic Association. Dietary guideline for diabetics. Seoul: Korean Diabetic Association; 2010. World Health Organisation. Physical status: the use and interpretation of anthropometry. Geneva: WHO; 1985. pp. 430–431. Ahn YJ, Lee JE, Paik HY, Lee HK, Jo IH, Kim KC. Development of a semi-quantitative food frequency questionnaire based on dietary data from the Korea National Health and Nutrition Examination Survey. Nutr Sci 2003;6: 173–84. Cohen J. Statistical power analysis for the behavioral science, 2nd ed., Hillsdale, NJ: Lawrence Erlbaum Associates; 1988. Menzin J, Langley-Hawthorne C, Friedman M, Boulanger L, Cavanaugh R. Potential short-term economic benefits of improved glycemic control: a managed care perspective. Diabetes Care 2001;24:51–5.
diabetes research and clinical practice 90 (2010) 26–33
[27] Brekke HK, Jansson PA, Lenner RA. Long-term (1- and 2-year) effects of lifestyle intervention in type 2 diabetes relatives. Diabetes Res Clin Pract 2005;70:225–34. [28] Eriksson J, Lindstrom J, Valle T, Aunola S, Hamalainen H, Ilanne-Parikka P, et al. Prevention of type II diabetes in subjects with impaired glucose tolerance: the Diabetes Prevention Study (DPS) in Finland. Diabetologia 1999;42:793–801. [29] Mayer-Davis EJ, Sparks KC, Hirst K, Costacou T, Lovejoy JC, Regensteiner JG, et al. Dietary intake in the Diabetes Prevention Program Cohort: baseline and 1-year postrandomization. Ann Epidemiol 2004;14:763–72. [30] Swinburn BA, Metcalf PA, Ley SJ. Long-term (5-year) effects of a reduced-fat diet intervention in individuals with glucose intolerance. Diabetes Care 2001;24: 619–24. [31] Roumen C, Corpeleijn E, Feskens EJM, Mensink M, Saris WHM, Blaak EE. Impact of 3-year lifestyle intervention on postprandial glucose metabolism: the SLIM study. Diabet Med 2008;25:597–605. [32] Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive Summary of the Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). JAMA 2001;285:2486–97. [33] Krauss RM, Eckel RH, Howard B, Appel LJ, Daniels SR, Deckelbaum RJ, et al. AHA Dietary Guidelines. Revision 2000: a statement for healthcare professionals from the Nutrition Committee of the American Heart Association. Circulation 2000;102:2284–99. [34] Haimoto H, Iwata M, Wakai K, Umegaki H. Long-term effects of a diet loosely restricting carbohydrates on HbA1c levels, BMI and tapering of sulfonylureas in type 2 diabetes: a 2-year follow-up study. Diabetes Res Clin Pract 2008;79:350–6. [35] Noakes M, Foster PR, Keogh JB, James AP, Mamo JC, Clifton PM. Comparison of isocaloric very low carbohydrate/high saturated fat and high carbohydrate/low saturated fat diets
[36]
[37]
[38]
[39]
[40]
[41]
[42]
[43]
[44]
33
on body composition and cardiovascular risk. Nutr Metab (Lond) 2006;3:7. Kirk E, Reeds DN, Finck BN, Mayurranjan MS, Patterson BW, Klein S. Dietary fat and carbohydrates differentially alter insulin sensitivity during caloric restriction. Gastroenterology 2009;136:1552–60. Ratliff J, Mutungi G, Puglisi MJ, Volek JS, Fernandez ML. Carbohydrate restriction (with or without additional dietary cholesterol provided by eggs) reduces insulin resistance and plasma leptin with out modifying appetite hormones in adult men. Nutr Res 2009;29:262–8. Ley SJ, Metcalf PA, Scragg RKR, Swinburn BA. Long-term effects of a reduced fat diet intervention on cardiovascular disease risk factors in individuals with flucose intolerance. Diabetes Res Clin Pract 2004;63:103–12. WHO expert consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004;363:157–63. Bermudez OI, Tucker KL. Total and central obesity among elderly Hispanics and the association with type 2 diabetes. Obes Res 2001;9:443–51. Watanabe M, Okayama A, Shimamoto K, Ueshima H. Shortterm effectiveness of an individual counseling program for impaired fasting glucose and mild type 2 diabetes in Japan: multi-center randomized control trial. Asia Pac J Clin Nutr 2007;16:489–97. Oldroyd JC, Unwin NC, White M, Mathers JC, Alberti KG. Randomised controlled trial evaluating lifestyle interventions in people with impaired glucose tolerance. Diabetes Res Clin Pract 2006;72:117–27. Brekke HK, Lenner RA, Taskinen MR, Ma˚nsson JE, Funahashi T, Matsuzawa Y, et al. Lifestyle modification improves risk factors in type 2 diabetes relatives. Diabetes Res Clin Pract 2005;68:18–28. Coppell KJ, Tipene-Leach DC, Pahau HL, Williams SM, Abel S, Iles M, et al. Two-year results from a community-wide diabetes prevention intervention in a high risk indigenous community: the Ngati and Healthy projects. Diabetes Res Clin Pract 2009;85:220–7.
Contents lists available at ScienceDirect
Diabetes Research and Clinical Practice jou rna l hom ep ag e: w ww.e lse v ier .com/ loca te /d iab res
Effect of a continuous diabetes lifestyle intervention program on male workers in Korea Ji Yeon Kang a, Sang Woon Cho a, Sook Hee Sung a, Yoo Kyoung Park b,c, Yun Mi Paek a,*, Tae In Choi a a
Radiation Health Research Institute, Korea Hydro & Nuclear Power Co., Ltd, Seoul, Republic of Korea Department of Medical Nutrition, Kyung Hee University, Yongin, Republic of Korea c Research Institute of Clinical Nutrition, Kyung Hee University, Seoul, Republic of Korea b
article info
abstract
Article history:
Aims: This study was conducted to compare the effects of two years of lifestyle intervention
Received 23 January 2010
to no intervention or one year of intervention on diabetes risk factors in male workers with
Received in revised form
impaired fasting glucose (IFG) or diabetes.
3 June 2010
Methods: We conducted a randomized lifestyle intervention trial designed to alter personal
Accepted 7 June 2010
lifestyles among 123 industrial male workers (CG; control group, n = 75; OIG; one-year intervention group, n = 23; TIG; two-year intervention group, n = 25). The intervention consisted of two parts, the main program (face-to-face counseling five times/12 weeks)
Keywords:
and a follow-up program (e-mail counseling ten times/30 weeks). Assessments included
Diabetes
biochemical characteristics, anthropometry and nutrient intake at baseline and after two
Lifestyle intervention
years.
Long term
Results: After two years, systolic blood pressure, HOMA-IR, HDL cholesterol and total energy
Worker
intake ( p < 0.05) were reduced in the OIG group, while weight, body mass index, waist circumference, blood pressure, fasting plasma glucose (FPG), HbA1c and nutrient intake (total energy, carbohydrate, protein and sodium) were significantly decreased ( p < 0.05, respectively) in the TIG group. When compared to the CG, subjects in OIG and TIG showed significant improvements in the level of FPG and HbA1c ( p < 0.05). Conclusions: Continuous lifestyle intervention for two years is more effective at improving diabetes risk factors than OIG. # 2010 Elsevier Ireland Ltd. All rights reserved.
1.
Introduction
Subjects with diabetes and pre-diabetes (including impaired fasting glucose (IFG) and impaired glucose tolerance (IGT)) face a greater risk for the development of cardiovascular disease (CVD), particularly coronary heart disease, peripheral vascular disease and stroke [1–5]. Previous studies have investigated the feasibility and efficacy of intervention for the prevention and management of diabetes. Additionally, it has recently
been demonstrated that multicomponent lifestyle intervention can prevent or at least postpone type 2 diabetes [6–11]. Moreover, lifestyle interventions that focus on body weight control, physical activity and dietary change have been shown to be much more effective at reducing the incidence of diabetes than pharmacological intervention (metformin) [10]. In the China Da Qing Diabetes Prevention Study (CDQDPS), subjects with IGT who underwent long-term diet and/or were subject to exercise interventions showed a significant de-
* Corresponding author at: Radiation Health Research Institute, Korea Hydro & Nuclear Power Co., Ltd, 388-1 Ssangmoon-dong, Dobong-gu, Seoul 132-703, Republic of Korea. Tel.: +82 2 3499 6651; fax: +82 2 3499 6622. E-mail address: [email protected] (Y.M. Paek). 0168-8227/$ – see front matter # 2010 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.diabres.2010.06.006
diabetes research and clinical practice 90 (2010) 26–33
crease in the incidence of diabetes over a 6-year period [12]. Additionally, a longitudinal follow-up of CDQDPS participants over 20 years (up to 14 years after the active intervention) revealed that combined intervention (diet + exercise) effectively prevented or delayed diabetes [13]. Similarly, a Finnish Diabetes Prevention Study (DPS) [14] revealed significantly greater improvements in clinical and metabolic characteristics and nutrient intake in the intervention group after three years when compared with the control group. The results of an extended follow-up of the DPS revealed that the effect of lifestyle intervention on diabetes risk remained after active lifestyle counseling was stopped [15]. Similar study was performed in the U.S. for over a decade (Diabetes Prevention Program and the following Diabetes Prevention Program Outcomes Study) and the results were quite similar to that of the DPS. After 10 years (treatment period: about 3 years, extended follow-up period: about 7 years), a reduction in diabetes incidence by either lifestyle (34%) or metformin (18%) therapy persisted for at least 10 years [16]. The results hold strong, however, only with an extended length of intervention. Short-term intervention studies have been found to have limited effects. For example, Chan et al. [17] reported that waist circumference and diastolic blood pressure improved, [(Fig._1)TD$IG]but that hemoglobin A1c (HbA1c) and HDL levels worsened at
27
the end of 6 months. Moreover, Jacobs-van der Bruggen et al. [18] suggested that interventions be continued (with at least two counseling sessions) during the second year to sustain the potential long-term health and economic consequences of lifestyle interventions. These results indicate that sustainability of lifestyle intervention is required to achieve the desired long-term effects of lifestyle intervention. The present study was conducted to determine if a continuous lifestyle intervention program reduced the number of diabetes-related factors and improved nutrient intake among male office workers with IFG and diabetes. The lifestyle intervention effect was analyzed by a comparison among three intervention programs (no intervention, one-year and two-year intervention).
2.
Subjects, materials and methods
2.1.
Subjects and study design
Written informed consent was obtained from all subjects, and the research protocol was approved by the Institutional Review Board of the Asan Medical Center (Seoul, Korea, 2007). Fig. 1 shows a flowchart of this study. The subjects were
Fig. 1 – Flowchart of the study.
28
diabetes research and clinical practice 90 (2010) 26–33
recruited from industrial male workers by screening members of the diabetes risk group who participated in annual regular health check-ups. Type 2 diabetes and IFG were defined according to the American Diabetes Association (ADA) criteria based on the fasting plasma glucose (FPG) levels. Type 2 diabetes was defined as a FPG 7.0 mmol/l while IFG was defined as a FPG level of 5.6–6.9 mmol/l [19]. Harati et al. [20] reported that a 5.6 mmol/l cut-off value of IFG combined with other diabetes risk factors performed better than the 6.1 mmol/l value for prediction of future type 2 diabetes. Subjects taking glucose-lowering drugs, lipid-lowering therapy or anti-hypertensive medication, manifesting cardiovascular disease and chronic alcohol and/or drug abuse were excluded from basal screening. Subjects who satisfied the inclusion criteria (n = 285) were called and invited to participate in the intervention, and 125 individuals accepted. The subjects were then randomly assigned to either the control group (CG), one-year intervention group (OIG) or two-year intervention group (TIG) after stratification for age, FPG and HbA1c levels. Specifically, the subjects were assigned in a 1.5:1 ratio to either the CG or a lifestyle intervention group. Two subjects in the OIG were excluded because they were unable to receive the intervention due to job relocation; however, no one was excluded from the CG or TIG. Overall, 123 men (CG: 75, OIG: 23, TIG: 25) were included in the final analyses. The lifestyle intervention program consisted of two parts, a main program and a follow-up program. The main program consisted of 5 times of 20–30 min of face-to-face counseling based on the participant’s health profiles (5 times during 12 weeks). Four weeks after the main program was finished a follow-up program was started. During the follow-up program period, e-mail nutrition education was provided every three weeks, a total of 10 times. Each e-mail included information regarding healthy eating habits and lifestyle such as examples of foods or dietary pattern that leads to diabetes, dietary tips when eating out, and easy guide to increase physical activity. After baseline examination, subjects of the OIG were instructed to continue their usual lifestyle for one year and then underwent lifestyle intervention. At the second year, the members of the group received the same lifestyle intervention as the TIG. The subjects in control group received general information on health at baseline but were offered no further information for the duration of the study. At baseline and after two years all study subjects were subject to anthropometric examination, blood sampling and dietary recording.
2.2.
Lifestyle intervention program
The intervention program consisted of motivating each participant to correct imbalances in their lifestyle voluntarily by providing practical advice. Lifestyle intervention program were made based on the key components of Comprehensive Lifestyle Modification Program (CLMP) [21] to focus on improving self-confidence for exchange of usual lifestyle. In each session, experienced staff and each participant developed one or two specific and achievable goals such as ‘‘Use stairs instead of elevators to and from work’’, ‘‘Eat fruits or milk instead of high-calorie food (bread, pizza, etc.), ‘‘March in place during watching TV’’ and ‘‘Eat breakfast every morning’’ to work on until the next session. During each session, the
experienced staff checked whether the personal goals had been achieved. If so, the participant was advised to continue to maintain the goals and, if possible, set additional goals. Moreover, if the participant had any problems or concerns, they were instructed to call a staff member for specific and practical advice and coping strategies. All participants in the intervention group also received health-related materials to view at home and in the workplace (e.g. pamphlets and brochures). Dietary recommendations were consisted of: calorie goal of 1400–2200 per day with 55–70% carbohydrate intake, 7–20% protein and 15–25% fat followed by recommendation from Korean Diabetic Association; daily salt intake of less than 5 g; and daily alcohol intake of less than about 50 g [22]. Professional dietitian used motivational counseling skill and developed an action plan for individualized problem solving and behavior-change support. Counseling session consisted of a theoretical portion with a presentation on dietary advice and its background, after which examples of recommendable foods were introduced. Participants were encouraged to keep regular meal time, eat more fruits and vegetables and avoid high-risk foods containing high levels of saturated fat, cholesterol, simple sugar, alcohol and sodium and limit nighttime snacking. All sessions included extra time for questions and a discussion about food choice and additional topics. Participants with a body mass index (BMI) of less than 25 kg/m2 were advised to maintain their present weight, but, those who are overweight were advised to reduce their weight to a desirable level at a rate of 1.0–2.0 kg/month. Weight reduction, however, was not the primary goal of the intervention, rather a possible outcome of changes in lifestyle. All subjects in the lifestyle intervention were individually guided to increase their physical activity to burn up about 200– 300 kcal/day such as brisk walking can be accumulated in sessions of at least 10 min to reach the total of 30 min a day. And, moderate intensity and endurance exercise (walking, jogging, mountaineering, cycling) was recommended to increase aerobic capacity and lean body mass.
2.3.
Measurements
Anthropometric measurements of subjects were conducted by experienced research staff. Height and weight were recorded with participants wearing lightweight clothing and no shoes using a body composition analyzer (Inbody 720; Biospace Co., Seoul, Korea). BMI was calculated as the body weight (kg)/height squared (m2). Waist circumference (WC) was measured at the midpoint between the iliac crest and the lower ribs [23]. Blood pressure was measured twice using a standard manometer (FT-700R; Jawon Medical Co., Seoul, Korea), with the average of two measurements taken as the final result. Blood samples were collected from each subject after overnight fasting for more than 10 h. FPG, HbA1c, total cholesterol, high-density lipoprotein cholesterol (HDL) and low-density lipoprotein cholesterol (LDL) were analyzed by enzymatic methods using commercially available kits and an automatic analyzer (Cobas Integra 800; Roche Diagnostics, Mannheim, Germany). And, homeostasis model of insulin
29
diabetes research and clinical practice 90 (2010) 26–33
Table 1 – Effects of lifestyle intervention program on anthropometrics and biochemical characteristics. Control group (n = 75) Baseline Age (years)
After
47.47 5.79
Proportion of IFG to Diabetes IFG 63 (84.0) Diabetes 12 (16.0)
75.17 9.11 25.60 2.58 a 85.43 7.35 a 132.41 14.05 87.64 11.03 6.37 0.86 5.95 0.81 2.23 1.47 204.04 32.10 a 49.87 13.80 135.72 31.39
Baseline
After
45.61 6.06
57 (76.0) 18 (24.0)
Annual income (U.S. dollar) ** >90,000 25 (33.3) 90,000 50 (66.7) Weight (kg) BMI (kg/m2) WC (cm) SBP (mmHg) DBP (mmHg) FPG (mmol/1) HbAlc (%) HOMA-IR Total cholesterol (mg/dl) HDL (mg/dl) LDL (mg/dl)
One year intervention group (n = 23)
Baseline
After
45.84 5.17
22 (95.7) 1 (4.3)
23 (100.0) 0 (0.0)
17 (73.9) 6 (26.1) 74.91 8.87 25.57 7.58 88.61 6.44 * 131.61 15.75 86.59 11.82 6.20 1.26 6.23 1.21 * 2.20 1.87 209.79 34.71 50.53 13.46 124.31 33.18 *
Two years intervention group (n = 25)
22 (88.0) 3 (12.0)
23 (92.0) 2 (8.0)
8 (32.0) 17 (68.0)
72.42 9.67 24.44 3.1 l ab 83.20 5.43 ab 131.70 12.21 84.65 9.66 5.99 0.41 5.58 0.52 1.73 1.23 195.48 31.12 a 45.65 13.37 121.70 34.62
72.10 9.35 24.33 3.06 84.30 6.34 125.17 12.49 * 83.00 9.52 5.14 0.77 * 5.44 0.89 1.25 0.82 * 195.39 33.11 42.87 13.14 * 115.04 31.66
77.48 11.65 26.77 3.68 b 89.06 9.19 b 135.96 11.91 83.28 7.87 6.24 0.67 5.88 0.64 2.12 1.93 222.32 31.59 b 44.64 13.66 135.20 31.91
76.62 10.54 * 26.47 3.27 * 87.30 7.30 * 125.04 9.52 * 79.68 9.26 * 5.41 1.34 * 5.73 0.96 * 1.62 1.21 211.20 34.81 41.36 10.31 129.88 39.90
Data are means S.D. or n(%). IFG: impaired fasting glucose, BMI: body mass index, WC: waist circumference, SBP: systolic blood pressure, DBP: diastolic blood pressure, FPG: fasting plasma glucose, HbAlc: hemoglobin Alc, HOMA-IR: homeostasis model of insulin resistance, HDL: high-density lipoprotein, LDL: low-density lipoprotein. * : Significantly different within group between baseline and after by paired t-test ( p < 0.05). ** : significantly different among three group at baseline by Fisher’s exact test. a,b : Means with different superscript letter are significantly among three group at baseline by Turkey’s post hoc test.
resistance (HOMA-IR) was calculated as FPG (mmol/l) fasting serum insulin (mU/mL)/22.5. Dietary intakes were analyzed using a computerized food frequency questionnaire (FFQ) originally developed by the Korea Centers for Disease Control and Prevention [24] and modified by our institution for industrial workers. The FFQ was designed to collect information regarding the usual intake of food over the past year.
2.4.
Statistical analyses
2.4.1.
Sample size calculation
Given approximately 95% power to detect an effect size of 0.5 standard deviations (SD) among three groups in a fixedeffects ANOVA model with a two-sided a level of 0.05, the estimated target sample size was 66 individuals (22 subjects in each group) [25]. Assuming a drop-out rate of up to 10%, we determined a sample size for the analysis of 75 for the CG, 25 for OIG and 25 for TIG, for a total of n = 125 subjects.
2.4.2.
Data analysis
Statistical analyses were conducted using the SPSS program (SPSS 15.0 KO for Windows; SPSS Inc., Chicago). Variables with skewed distribution were log-transformed prior to statistical analysis. Chi-square test of was used to test the homogeneity of the proportion of IFG and diabetes, and annual income. Paired t-tests were used to analyze the differences between baseline and after intervention values. One-way analysis of variance (ANOVA) with Tukey’s post hoc test was used to
compare groups. A P < 0.05 was considered to be statistically significant.
3.
Results
The baseline characteristics of the three groups are shown in Table 1 and Table 2. There were no differences among groups in terms of age and proportion of IFG and diabetes (data not shown). Annual income was higher in OIG than CG and TIG ( p < 0.05). Additionally, the baseline characteristics were similar across the groups except for the BMI, WC and total cholesterol, which was higher in the TIG than in the other groups. When the effects of the lifestyle intervention program on anthropometry and biochemical characteristics were evaluated, WC and HbA1c were increased while LDL cholesterol was significantly decreased ( p < 0.05) in the CG. In the OIG, systolic blood pressure (SBP), FPG, HOMA-IR and HDL cholesterol were significantly reduced ( p < 0.05). Conversely, we observed a reduction in weight, BMI, WC, SBP, diastolic blood pressure (DBP), FPG and HbA1c in the TIG ( p < 0.05). The efficacy of the lifestyle intervention program on nutrient intake is shown in Table 2. In the CG, there were no differences in nutrient intake at baseline and after lifestyle intervention. However, we observed a reduction in total energy intake in the OIG ( p < 0.05) after intervention. Additionally, the total energy, carbohydrate, protein and sodium levels decreased significantly in the TIG after the intervention ( p < 0.05, respectively).
30
After
7338.81 2705.37 * 17.25 5.30 262.64 69.95 * 52.26 20.69 * 1835.46 660.19 * 160.07 126.59 9.72 6.29 9.91 6.50 4.03 2.33 240.72 240.61
Baseline
9459.47 3083.87 19.08 8.44 320.44 101.74 83.90 35.05 b 4192.41 2428.33 b 153.00 112.21 12.59 10.37 12.92 10.83 5.39 3.83 283.37 207.76
Table 3 shows the magnitude of this effect. The decreases in weight and BMI were similar among the three groups. Follow-up Turkey’s tests showed that changes in WC, SBP and total cholesterol in TIG were greater than changes in the CG and OIG ( p < 0.05). The OIG and the CG showed similar changes in WC, SBP and total cholesterol. The changes in FPG and HbA1c were significantly higher in the TIG than in the other groups ( p < 0.05), but these values did not differ significantly between the OIG and TIG. Finally, the change in the intake of protein and sodium ( p < 0.05) differed among groups, with the TIG having a larger decrease than the CG and OIG.
4.
*
Data are means S.D. MUFA: Monounsaturated fatty acid, PUFA: Polyunsaturated fatty acid. : Significantly different within group between baseline and after by paired t-test ( p < 0.05). a,b: Means with different superscript letter are significantly among three group at baseline by Turkey’s post hoc test.
7863.62 1994.73 15.32 4.79 280.70 73.59 56.17 77.06 1813.11 854.98 165.46 103.19 8.33 4.15 8.52 4.34 4.17 7.31 266.25 264.75 8543.23 2131.97 14.82 4.82 320.24 88.52 59.30 21.57 a 1951.57 979.50 a 165.36 88.85 9.67 4.85 9.57 4.74 4.24 1.83 232.27 224.31 7532.56 2129.98 15.56 6.44 274.09 78.66 52.55 20.19 1743.95 843.91 163.95 116.34 9.02 6.86 9.35 7.38 4.15 2.88 228.96 266.26 8124.19 2975.18 15.14 5.16 302.46 103.72 56.55 28.59 a 2047.61 1295.04 a 154.64 106.42 10.01 7.63 10.25 8.27 4.66 3.81 215.96 225.71 Total energy (kJ) Total fat (E%) Carbohydrate (g) Protein (g) Sodium (mg) Cholesterol (mg) Saturated fatty acid (g) MUFA (g) PUFA (g) Alcohol (kcal)
After Baseline After Baseline
Control group (n = 75)
Table 2 – Effect of lifestyle intervention program on nutrient intakes.
One year intervention group (n = 23)
*
Two years intervention group (n = 25)
diabetes research and clinical practice 90 (2010) 26–33
Discussion
The results of this study indicate that continuous lifestyle intervention can be beneficial for reducing diabetes risk factors. The effects of the intervention program were most intensive in the TIG, especially with respect to glycemic control and nutrient intake. Glycemic control is an important predictor of chronic complications of diabetes. Menzin et al. [26] demonstrated that improved glycemic characteristics led to cost savings. In this study, the FPG levels were significantly decreased in both the OIG ( 0.84 mmol/l) and the TIG ( 0.83 mmol/l). Brekke et al. [27] reported a reduction in FPG of 0.43 mmol/l after one year and 0.34 mmol/l after two years in a diet and exercise group. Lindstrom et al. [14] also showed a reduction in FPG of 0.2 mmol/l one year after intervention, but found that the FPG level was not decreased when compared to that of baseline after three years, suggesting difficulties in changing and maintaining dietary or lifestyle habits. Eriksson et al. [28] showed that after one year of lifestyle intervention, no change in FPG was observed in a group with IGT. Despite IFG being defined as 5.6 mmol/l in this study, intensive lifestyle intervention was more effective at glycemic control when compared with previous lifestyle intervention studies. The homeostatic model assessment (HOMA-IR) was used to approximate insulin resistance. The level of HOMA-IR was significantly reduced in the subjects in OIG, however, no reduction was found in the other groups. While there is still substantial debate in regard to the appropriate diagnostic approach to the insulin resistance, reduced HOMA-IR by lifestyle intervention implies the possibility of improving insulin resistance in the subjects. In addition to improving glycemic control, other studies have also identified changes in nutrient intake after intervention. Mayer-Davis et al. [29] found that the significant differences in the changes of dietary intake of total energy and fat (E%) in the lifestyle intervention group was greater than those of Metformin and Placebo groups at 1-year post intervention. Moreover, Swinburn et al. [30] showed that reduced-fat diet intervention in individuals with glucose intolerance led to significant decreases in energy, fat, fat (E%), carbohydrate (E%) and protein (E%). Roumen et al. [31] reported that total fat (E%) intake was significantly decreased and carbohydrate and fiber intake increased in an intervention group when compared with a control group after three years. Dietary carbohydrate is the primary macronutrient that
31
diabetes research and clinical practice 90 (2010) 26–33
Table 3 – Comparison of changes between baseline and after lifestyle intervention program among three group. Control group (n = 75) DWeight DBMI DWC * DSBP * DDBP DFPG * DHbAlc * DHOMA-IR DTotal cholesterol DHDL DLDL DTotal energy DTotal fat (E%) DCarbohydrate DProtein DSodium DCholesterol DSaturated fatty acid DMUFA DPUFA DAlcohol
One year intervention group (n = 23)
Two years intervention group (n-25)
0.27 2.13 0.08 0.72 3.19 8.85 a 0.80 13.59 a 1.05 10.00
0.32 1.36 0.10 0.46 1.11 5.53 ab 6.52 11.91 ab 1.65 9.14
0.86 1.92 0.30 0.65 1.76 2.95 b 10.92 12.21 b 3.60 7.16
0.17 1.12 a 0.27 0.65 a 0.03 1.29 5.75 25.61 a 0.67 8.25 11.41 26.90
0.84 0.75 b 0.13 0.71 b 0.47 1.01 0.09 27.42 ab 2.78 5.79 6.65 21.99
0.83 0.91 b 0.15 0.69 b 0.50 1.29 11.12 19.56 b 3.28 10.08 5.32 26.64
591.77 3322.74 0.42 5.31 28.37 123.42 3.99 31.10 a 303.66 1419.46 a 9.31 111.89 1.06 9.01 0.90 9.83 0.51 4.17 13.86 204.41
679.61 1849.81 0.50 4.91 39.53 94.51 3.13 20.42 a 138.47 935.73 a 0.10 101.95 1.35 4.59 1.04 4.49 0.12 1.99 33.97 139.47
1951.33 2182.56 1.83 8.90 57.80 89.11 31.63 28.50 b 2356.95 2266.49 b 7.07 135.67 2.87 9.32 3.01 10.11 1.36 3.47 42.66 134.82
D: After - Baseline, BMI: body mass index, WC: waist circumference, SBP: systolic blood pressure, DBP: diastolic blood pressure, FPG: fasting plasma glucose, HbAlc: hemoglobin Alc, HOMA-IR: homeostasis model of insulin resistance, HDL: high-density lipoprotein, LDL: low-density lipoprotein, MUFA: monounsaturated fatty acid, PUFA: polyunsaturated fatty acid. * : Significantly different among group between by ANOVA ( p < 0.05). a,b: Means with different superscript letter are significantly among three group.
affects postprandial glucose levels. In addition, the National Cholesterol Education Program and the American Heart Association recommend lowering the dietary intake of total fat (<30% energy), saturated fat (<10% energy) and cholesterol (<300 mg/dl) to improve lipid levels and reduce the risk of cardiovascular disease [32,33]. Recently, it has been suggested that carbohydrate and fat restricted diets have greater effectiveness in weight loss and metabolic improvement in obese or diabetic patients [34–38]. In our study, the difference in the intake of protein and sodium among groups was striking. Although not significant, total fat (E%) and alcohol intake were reduced in the TIG when compared to the other groups. Moreover, the intake of total energy, carbohydrate, saturated fatty acid, MUFA and PUFA tended to decrease more in the TIG. Although the actual changes in dietary intake levels in this study were trivial when compared with other studies [27,29,30], our lifestyle intervention program with setting individualized simple, but, achievable dietary goal led successful implementation of program. Recently, the WHO recommended that a lower BMI cut-off point for Asians for public health action should be added to the present WHO classifications of BMI based on the difference in the effects of obesity on type 2 diabetes or cardiovascular diseases in Asians [39]. As a result, a BMI of 25 kg/m2 is the recommended cut-off point for obesity for Korean and other Asian populations. Obesity is associated with diabetes [40]; therefore, many intervention studies have targeted weight loss or attainment of a BMI of less than 25 kg/m2 [8,12,28,41]. We found that the weight and BMI reduction that occurred during the study was small but substantial in the TIG. Other
studies on subjects with IGT [8,42] or diabetes risk groups [27,28,43] have found greater weight loss, but this may have occurred because weight reduction was not a primary goal of this study. However, as lifestyle intervention continued, the weight and BMI tended to decrease. Lifestyles are difficult to change. It has been shown that the effects of interventions decrease as the drop out rate increases because of strong restrictions or impediments of the willing participants [31,32,34]. Our study may be more applicable to decreasing diabetes through steady and constant lifestyle change. It should be noted that this study has several limitations. First, the size of the study population was small. We attempted to enroll more participants, but this was difficult due to the unpredictable work schedules of the target population. Second, we evaluated IFG at baseline according to the ADA criteria, which made it difficult to compare the results of our study with those of other studies that employed the WHO criteria [3,17,41,44]. Third, in this study, the effect of change in the level of exercise was not taken into account; therefore, we were not able to distinguish the additive effects of changes in eating behavior and increased levels of exercise on the improvement of glycemic control. Fourth, we conducted random sampling, but baseline data of BMI, WC, total cholesterol, HDL, and intake of protein and sodium was significantly higher in TIG compared to the CG and OIG. It may have influenced the outcomes of intervention. For that reason, we have done a comparative analysis of change between baseline and after lifestyle intervention program among three groups.
32
diabetes research and clinical practice 90 (2010) 26–33
In conclusion, the results of this study showed that, in male Korean industrial workers with IFG or diabetes, continuous lifestyle intervention over two years targeting lifestyle changes had favorable effects on diabetes markers when compared with short-term intervention. This utility of this intervention should be evaluated in a longer term demonstration with a larger population, to better understand the potential sustainability and long-term effectiveness for the prevention and management diabetes.
[11]
[12]
[13]
Acknowledgement The study was supported by grant from the Korea Hydro & Nuclear Power project (E08NJ22).
Conflict of interest
[14]
[15]
The authors declare that they have no conflict of interest.
references [16]
[1] Juutilainen A, Lehto S, Ronnemaa T, Pyorala K, Laakso M. Type 2 diabetes as a ‘‘Coronary Heart Disease Equivalent’’: an 18-year prospective population-based study in Finnish subjects. Diabetes Care 2005;28:2901–7. [2] Stratton IM, Adler AI, Neil HA, Matthews DR, Manley SE, Cull CA, et al. Association of glycaemia with macrovascular and microvascular complications of type 2 diabetes (UKPDS 35): prospective observational study. BMJ 2000;321:405–12. [3] Chakarova N, Tankova T, Atanassova I, Dakovska L. Serum lipid and hsCRP levels in prediabetes-impaired fasting glucose (IFG) and impaired glucose tolerance (IGT), Diabetes. Res Clin Pract 2009;86:56–60. [4] Faeh D, William J, Yerly P, Paccaud F, Bovet P. Diabetes, prediabetes are associated with cardiovascular risk factors and carotid/femoral intima-media thickness independently of markers of insulin resistance and adiposity. Cardiovasc Diabetol 2007;6:32. [5] Meigs JB, Nathan DM, D’Agostino Sr RB, Wilson PW. Fasting and postchallenge glycemia and cardiovascular disease risk: the Framingham Offspring Study. Diabetes Care 2002;25:1845–50. [6] Ramachandran A, Snehalatha C, Mary S, Mukesh B, Bhaskar AD, Vijay V. The Indian Diabetes Prevention Programme shows that lifestyle modification and metformin prevent type 2 diabetes in Asian Indian subjects with impaired glucose tolerance (IDPP-1). Diabetologia 2006;49:289–97. [7] Mensink M, Feskens EJ, Saris WH, de Bruin TW, Blaak EE. Study on lifestyle intervention and Impaired glucose tolerance maastricht (SLIM): preliminary results after one year. Int J Obes Relat Metab Disord 2003;27:377–84. [8] Kosaka K, Noda M, Kuzuya T. Prevention of type 2 diabetes by lifestyle intervention: a Japanese trial in IGT males. Diabetes Res Clin Pract 2005;67:152–62. [9] Tuomilehto J, Lindstrom J, Eriksson JG, Valle TT, Hamalainen H, Ilanne-Parikka P, et al. Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med 2001;344:1343–50. [10] The Diabetes Prevention Program Research Group. Reduction in the incidence of type 2 diabetes with
[17]
[18]
[19]
[20]
[21]
[22] [23]
[24]
[25]
[26]
lifestyle intervention or metformin. N Engl J Med 2002;346:393–403. Li G, Hu Y, Yang W, Jiang Y, Wang J, Xiao J, et al. Effects of insulin resistance and insulin secretion on the efficacy of interventions to retard development of type 2 diabetes mellitus: the DA Qing IGT and Diabetes Study. Diabetes Res Clin Pract 2002;58:193–200. Pan XR, Li GW, Hu YH, Wang JX, Yang WY, An ZX, et al. Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance. The Da Qing IGT and Diabetes Study. Diabetes Care 1997;20:537–44. Li G, Zhang P, Wang J, Gregg EW, Yang W, Gong Q, et al. The long-term effect of lifestyle intervention to prevent diabetes in the China Da Qing Diabetes Prevention Study: a 20-year follow-up study. Lancet 2008;371:1783–9. Lindstrom J, Louheranta A, Mannelin M, Rastas M, Salminen V, Eriksson J, et al. The Finnish Diabetes Prevention Study (DPS): lifestyle intervention and 3-year results on diet and physical activity. Diabetes Care 2003;26:3230–6. Lindstrom J, Ilanne-Parikka P, Peltonen M, Aunola S, Eriksson JG, Hemio K, et al. Sustained reduction in the incidence of type 2 diabetes by lifestyle intervention: follow-up of the Finnish Diabetes Prevention Study. Lancet 2006;368:1673–9. Diabetes Prevention Program Research Group. 10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study. Lancet 2009;374:1677–86. Chan LC, Ware R, Kesting J, Marczak M, Good D, Shaw JT. Short term efficacy of a lifestyle intervention programme on cardiovascular health outcome in overweight Indigenous Australians with and without type 2 diabetes mellitus The healthy lifestyle programme (HELP). Diabetes Res Clin Pract 2007;75:65–71. Jacobs-van der Bruggen MA, van Baal PH, Hoogenveen RT, Feenstra TL, Briggs AH, Lawson K, et al. Cost-effectiveness of lifestyle modification in diabetic patients. Diabetes Care 2009;32:1453–8. The expert Committe on the Diagnosis Classification of Diabetes Mellitus. Follow-up report on the diagnosis of diabetes mellitus. Diabetes Care 2003;26:3160–7. Harati H, Hadaegh F, Tohidi M, Azizi F. Impaired fasting glucose cutoff value of 5.6 mmol/l combined with other cardiovascular risk markers is a better predictor for incident Type 2 diabetes than the 6.1 mmol/l value: Tehran lipid and glucose study. Diabetes Res Clin Pract 2009;85: 90–5. Yoo JS, Lee SJ, Lee HC, Kim MJ. The effect of a comprehensive lifestyle modification program on glycemic control and body composition in patients with type 2 diabetes. Asian Nurs Res 2007;1:106–15. Korean Diabetic Association. Dietary guideline for diabetics. Seoul: Korean Diabetic Association; 2010. World Health Organisation. Physical status: the use and interpretation of anthropometry. Geneva: WHO; 1985. pp. 430–431. Ahn YJ, Lee JE, Paik HY, Lee HK, Jo IH, Kim KC. Development of a semi-quantitative food frequency questionnaire based on dietary data from the Korea National Health and Nutrition Examination Survey. Nutr Sci 2003;6: 173–84. Cohen J. Statistical power analysis for the behavioral science, 2nd ed., Hillsdale, NJ: Lawrence Erlbaum Associates; 1988. Menzin J, Langley-Hawthorne C, Friedman M, Boulanger L, Cavanaugh R. Potential short-term economic benefits of improved glycemic control: a managed care perspective. Diabetes Care 2001;24:51–5.
diabetes research and clinical practice 90 (2010) 26–33
[27] Brekke HK, Jansson PA, Lenner RA. Long-term (1- and 2-year) effects of lifestyle intervention in type 2 diabetes relatives. Diabetes Res Clin Pract 2005;70:225–34. [28] Eriksson J, Lindstrom J, Valle T, Aunola S, Hamalainen H, Ilanne-Parikka P, et al. Prevention of type II diabetes in subjects with impaired glucose tolerance: the Diabetes Prevention Study (DPS) in Finland. Diabetologia 1999;42:793–801. [29] Mayer-Davis EJ, Sparks KC, Hirst K, Costacou T, Lovejoy JC, Regensteiner JG, et al. Dietary intake in the Diabetes Prevention Program Cohort: baseline and 1-year postrandomization. Ann Epidemiol 2004;14:763–72. [30] Swinburn BA, Metcalf PA, Ley SJ. Long-term (5-year) effects of a reduced-fat diet intervention in individuals with glucose intolerance. Diabetes Care 2001;24: 619–24. [31] Roumen C, Corpeleijn E, Feskens EJM, Mensink M, Saris WHM, Blaak EE. Impact of 3-year lifestyle intervention on postprandial glucose metabolism: the SLIM study. Diabet Med 2008;25:597–605. [32] Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive Summary of the Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). JAMA 2001;285:2486–97. [33] Krauss RM, Eckel RH, Howard B, Appel LJ, Daniels SR, Deckelbaum RJ, et al. AHA Dietary Guidelines. Revision 2000: a statement for healthcare professionals from the Nutrition Committee of the American Heart Association. Circulation 2000;102:2284–99. [34] Haimoto H, Iwata M, Wakai K, Umegaki H. Long-term effects of a diet loosely restricting carbohydrates on HbA1c levels, BMI and tapering of sulfonylureas in type 2 diabetes: a 2-year follow-up study. Diabetes Res Clin Pract 2008;79:350–6. [35] Noakes M, Foster PR, Keogh JB, James AP, Mamo JC, Clifton PM. Comparison of isocaloric very low carbohydrate/high saturated fat and high carbohydrate/low saturated fat diets
[36]
[37]
[38]
[39]
[40]
[41]
[42]
[43]
[44]
33
on body composition and cardiovascular risk. Nutr Metab (Lond) 2006;3:7. Kirk E, Reeds DN, Finck BN, Mayurranjan MS, Patterson BW, Klein S. Dietary fat and carbohydrates differentially alter insulin sensitivity during caloric restriction. Gastroenterology 2009;136:1552–60. Ratliff J, Mutungi G, Puglisi MJ, Volek JS, Fernandez ML. Carbohydrate restriction (with or without additional dietary cholesterol provided by eggs) reduces insulin resistance and plasma leptin with out modifying appetite hormones in adult men. Nutr Res 2009;29:262–8. Ley SJ, Metcalf PA, Scragg RKR, Swinburn BA. Long-term effects of a reduced fat diet intervention on cardiovascular disease risk factors in individuals with flucose intolerance. Diabetes Res Clin Pract 2004;63:103–12. WHO expert consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004;363:157–63. Bermudez OI, Tucker KL. Total and central obesity among elderly Hispanics and the association with type 2 diabetes. Obes Res 2001;9:443–51. Watanabe M, Okayama A, Shimamoto K, Ueshima H. Shortterm effectiveness of an individual counseling program for impaired fasting glucose and mild type 2 diabetes in Japan: multi-center randomized control trial. Asia Pac J Clin Nutr 2007;16:489–97. Oldroyd JC, Unwin NC, White M, Mathers JC, Alberti KG. Randomised controlled trial evaluating lifestyle interventions in people with impaired glucose tolerance. Diabetes Res Clin Pract 2006;72:117–27. Brekke HK, Lenner RA, Taskinen MR, Ma˚nsson JE, Funahashi T, Matsuzawa Y, et al. Lifestyle modification improves risk factors in type 2 diabetes relatives. Diabetes Res Clin Pract 2005;68:18–28. Coppell KJ, Tipene-Leach DC, Pahau HL, Williams SM, Abel S, Iles M, et al. Two-year results from a community-wide diabetes prevention intervention in a high risk indigenous community: the Ngati and Healthy projects. Diabetes Res Clin Pract 2009;85:220–7.