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J. Lindström1, A. 3, K. Sheppard4, A. Gilis-Januszewska5, C. Greaves4, U. Handke6, P. Pajunen1, S. Puhl7, A. Pölönen8, A. Rissanen9, M. Roden10, T. Stemper14, V. Telle-Hjellset11, J. Tuomilehto12, D. Velickiene13, P. Schwarz2, T. Acosta, M. Adler, A. Alkerwi, N. Barengo, R. Barengo, J. Boavida, K. Charlesworth, V. Christov, B. Claussen, X. Cos, E. Cosson, S. Deceukelier, V. Dimitrijevic-Sreckovic, P. Djordjević, P. Evans, A. Felton, M. Fischer, R. Gabriel-Sánchez, A. Gilis-Januszewska, M. Goldfracht, J. Gomez, C. Greaves, M. Hall, U. Handke, H. Hauner, J. Herbst, N. Hermanns, L. Herrebrugh, C. Huber, U. Hühmer, J. Huttunen, A. Jotic, Z. Kamenov, Ş. Karadeniz, N. Katsilambros, M. Khalangot, K. Kissimova-Skarbek, D. Köhler, V. Kopp, P. Kronsbein, B. Kulzer, D. Kyne‐Grzebalski, K. Lalić, N. Lalic, R. Landgraf, Y. Lee-Barkey, S. Liatis, J. Lindström, K. Makrilakis, C. McIntosh, M. McKee, A. Mesquita, D. Misiņa, F. Muylle, A. Neumann, A. Paiva, P. Pajunen, B. Paulweber, M. Peltonen, L. Perrenoud, A. Pfeiffer, A. Pölönen, S. Puhl, F. Raposo, T. Reinehr, A. Rissanen, C. Robinson, M. Roden, U. Rothe, T. Saaristo, J. Scholl, P. Schwarz, K. Sheppard, S. Spiers, T. Stemper, B. Stratmann, J. Szendroedi, Z. Szybinski, T. Tankova, V. Telle-Hjellset, G. Terry, D. Tolks, F. Toti, J. Tuomilehto, A. Undeutsch, C. Valadas, P. Valensi, D. Veličkienę, P. Vermunt, R. Weiss, J. Wens, T. Yılmaz (2010)
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It has been shown that real-life implementation studies for the prevention of type 2 diabetes (DM2) performed in different settings and populations can be effective. However, not enough information is available on factors influencing the reach of DM2 prevention programmes. This study examines the predictors of completing an intervention programme targeted at people at high risk of DM2 in Krakow, Poland as part of the DE-PLAN project. A total of 262 middle-aged people, everyday patients of 9 general practitioners’ (GP) practices, at high risk of DM2 (Finnish Diabetes Risk Score (FINDRISK)>14) agreed to participate in the lifestyle intervention to prevent DM2. Intervention consisted of 11 lifestyle counseling sessions, organized physical activity sessions followed by motivational phone calls and letters. Measurements were performed at baseline and 1 year after the initiation of the intervention. Seventy percent of the study participants enrolled completed the core curriculum (n=184), 22% were men. When compared to noncompleters, completers had a healthier baseline diabetes risk profile (P<.05). People who completed the intervention were less frequently employed versus noncompleters (P=.037), less often had hypertension (P=.043), and more frequently consumed vegetables and fruit daily (P=.055). In multiple logistic regression model, employment reduced the likelihood of completing the intervention 2 times (odds ratio [OR] 0.45, 95% confidence interval [CI] 0.25–0.81). Higher glucose 2 hours after glucose load and hypertension were the independent factors decreasing the chance to participate in the intervention (OR 0.79, 95% 0.69–0.92 and OR 0.52, 95% CI 0.27–0.99, respectively). Daily consumption of vegetables and fruits increased the likelihood of completing the intervention (OR 1.86, 95% 1.01–3.41). In conclusion, people with healthier behavior and risk profile are more predisposed to complete diabetes prevention interventions. Male, those who work and those with a worse health profile, are less likely to participate and complete interventions. Targeted strategies are needed in real-life diabetes prevention interventions to improve male participation and to reach those who are working as well as people with a higher risk profile. Abbreviations: BMI = body mass index, CVD = cardiovascular disease, DE-PLAN = Diabetes in Europe: Prevention Using Lifestyle, Physical Activity and Nutritional Intervention, DM2 = type 2 diabetes, DPS = Diabetes Prevention Study, FINDRISK = Finnish Diabetes Risk Score, GP = general practitioner, HIPS = the Health Improvement and Prevention Study, IFG = impaired fasting glucose, IGT = impaired glucose tolerance, OGTT = oral glucose tolerance test, RCT = randomized controlled trial, Sydney DPP = Sydney Diabetes Prevention Program. Keywords: completion the intervention, diabetes type 2, high diabetes risk, lifestyle prevention Editor: Jongwha Chang. The authors have no conflicts of interest to disclose. a b Department of Endocrinology, Jagiellonian University, Medical College, Kopernika, Krakow, Poland, Chronic Disease Prevention Unit, National Institute for Health and Welfare (THL), Helsinki, Finland, Department of Medical and Population Health Science, Herbert Wertheim College of Medicine, Florida International University, Miami, d e f USA, Dasman Diabetes Institute, Dasman, Kuwait, Centre for Vascular Prevention, Danube-University Krems, Krems, Austria, Department of Chronic Disease g h Prevention, National Institute for Health and Welfare, Department of Public Health, University of Helsinki, Helsinki, Finland, Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia, Department for Prevention & Care of Diabetes, Medical Clinic Unit III, University Clinic, Carl Gustav Carus at Technical University Dresden, Paul Langerhans Institute Dresden of the Helmholtz Center Munich at University Hospital and Faculty of Medicine, Technical University Dresden, Dresden, k l m German Center for Diabetes Research, Neuherberg, Germany, Department of Endocrinology, Department of Family Medicine, Chair of Medicine and Gerontology, Jagiellonian University, Medical College, Krakow, Poland. Correspondence: Aleksandra Gilis-Januszewska, Department of Endocrinology, Jagiellonian University, Medical College, Kopernika 17 Str., 31-501 Krakow, Poland (e-mail: myjanusz@cyfronet.pl). Copyright © 2018 the Author(s). Published by Wolters Kluwer Health, Inc. This is an open access article distributed under the Creative Commons Attribution-NoDerivatives License 4.0, which allows for redistribution, commercial and non- commercial, as long as it is passed along unchanged and in whole, with credit to the author. Medicine (2018) 97:5(e9790) Received: 4 July 2017 / Received in final form: 23 December 2017 / Accepted: 14 January 2018 http://dx.doi.org/10.1097/MD.0000000000009790 1 Gilis-Januszewska et al. Medicine (2018) 97:5 Medicine 1. Introduction 800 FINDRISC distributed The vivid increase of type 2 diabetes (DM2) prevalence and its 566 FINDRISC completed complications observed worldwide call for an intensified search for strategies aimed at reducing the disease burden. Lifestyle 368 168 interventions through dietary and physical changes have proved FINDRISC >14 FINDRISC ≤14 to be very effective in DM2 prevention and, as demonstrated in 275 93 several randomized controlled trials (RCTs), they reduce DM2 signed consent not signed consent [1–3] incidence up to 60%. There are also very promising results of and agreed for OGTT real-life implementation studies performed in different settings 262 13 and populations, which have proved that less-intensive, lower invited to parcipate newly screened budget lifestyle interventions can also be effective and can result 3 in the intervenon DM2 [4–16] in long-term beneficial outcomes. Nevertheless, there are still many challenges in the field of DM2 completed baseline prevention. As the main focus is to achieve health benefits at the measurements population level, improvement of the reach and efficacy of the 184 74 programmes are one of the most important public health burdens. completed not completed Recruitment rates in RCTs are known to be very low, but this intervenon intervenon highly controlled clinical situation cannot be compared with real- [2] 1 2 3 Finnish Diabetes Risk Score, Oral glucose tolerance test; Diabetes mellitus type 2 life setting. However, among randomized patients, completion of the programme was high, which suggests that people Figure 1. The flow chart: study participants, completers, and noncompleters. participating in RCTs are a very selective, highly motivated [2] group. The data on participation rates and completion of interventions in implementation studies are very scarce. Also, very Subsequently, 275 people signed informed consent and agreed little is known about the factors affecting completion of to undergo oral glucose tolerance test (OGTT) examination. Out intervention and attendance. In some studies, age, education, of these, 262 (258 with all measurements done) were invited to health, and economic status as well as the level of psychological participate in the intervention. A total 184 participants distress were related to the participation in the pro- completed the intervention (completers). Among completers, [6,7,11,17,18] grammes. There are also very important practical the number of completed counseling sessions was from 8 to 11 (9 external obstacles like work commitments, accessibility, afford- participants completed all sessions but not the final examination ability, and practicality of the interventions, as well as factors after 1 year). Around 74 of eligible participants who completed relatedto the quality of intervention provided, which may influence all baseline examination and agreed to participate in the study did [17–19] the uptake of the prevention programmes. The DE-PLAN not eventually participate in the intervention (noncompleters). project (Diabetes in Europe: Prevention Using Lifestyle, Physical Among noncompleters, the number of completed counseling Activity and Nutritional Intervention) was an EU-initiated and sessions was from 0 to 3. sponsored real-life implementation study aiming to assess the This study followed the Good Clinical Practice guidelines and reach, adoption, and implementation of the programme in diverse the guidelines of the Helsinki Declaration. The study protocol real-life settings in 17 countries in Europe, but also to create a was approved by the Jagiellonian University Ethics Committee. network of trained and experienced professionals to continue The committee’s reference number is KBET/43/L/2006. All study [4,5,10,11,20] DM2 prevention across Europe. participants gave their written informed consent before the The aim of this study was to investigate the predictors of participation in the study. completing an intervention programme within primary health- Two nurses in each of the participating practices have been care targeted at people at high risk of DM2 in Krakow, Poland trained to act as diabetes prevention managers and deliver within the framework of the DE-PLAN project. intervention. The intervention consisted of reinforced behavior modification with a special focus on the following lifestyle goals: weight loss of initial body mass, reduced intake of total fat, 2. Materials and methods reduced intake of saturated fat, increased consumption of fiber The DE-PLAN project was based on the principles of the Diabetes (from fruit, vegetables, and cereal), and increased physical [1] [1,4,5,20] Prevention Study (DPS) and examined the intervention activity. implementation in real-life settings and hence the design of the The intervention lasted 10 months and consisted of 1 study was not randomized. individual session and 10 group sessions (10–14 people) followed A detailed description of the programme has been published by 6 motivational telephone calls and 2 motivational let- [7,8] [1,4,5,20] previously. The study was performed in 9 independent ters. From week 4 of the initiation of the intervention, primary healthcare general practitioners’ (GP) practices in patients were offered free of charge physical activity sessions 2 Krakow and entailed city inhabitants aged >25 years who met times a week. In case of a patient’s cancellation or no-show for a inclusion criterion of high diabetes risk assessed with the Finnish scheduled appointment, the staff called the patient to reschedule Diabetes Risk Score (FINDRISK) >14) (33% chance of and provide motivation to continue the study. In case of logistic developing DM2 within 10 years). Information about the study problems to continue counseling with the initial group, the and the leaflets with FINDRISK questionnaire were distributed in patient was offered participation in another group (with more co-operating practices. Patients with known risk factors were convenient location and timetable of sessions). In the course of directly approached by nurses and medical staff. Out of 800 the intervention, 6 meetings were organized for prevention FINDRISK questionnaires distributed, 566 were completed, 368 managers to discuss the problems and share their experience, as respondents scored FINDRISK >14 (Fig. 1) well as to allow them to consult any issues concerning physical 2 Gilis-Januszewska et al. Medicine (2018) 97:5 www.md-journal.com activity, diet, and motivation techniques. In case of nonpartici- Baseline data of completers and noncompleters are presented pation, the nurses were asked to provide the reasons explaining in Table 1. Noncompleters had higher 120 OGTT glucose and the patients’ decision. Prevention managers could also consult a triglycerides (P=.046, P=.004) in comparison with completers. [4,5] dietitian and physical activity specialist over the telephone. IFG or IGT was more frequent among noncompleters versus completers (36% vs 25%, P=.069). Those who did not complete the intervention were more frequently employed versus com- 2.1. Measurements and predictors pleters (P=.037), more often had a family history of diabetes The baseline examination procedure included: questionnaires (P=.066) and hypertension (P=.043). There were no differences (FINDRISK, baseline, clinical, and lifestyle and quality of life) in education, marital status, smoking, and frequency of and biochemical tests such as: fasting and 120 OGTT glucose, depression between completers and noncompleters. As far as serum triglycerides, high-density lipoprotein, and total choles- lifestyle factors are concerned, completers more frequently terol. Impaired fasting glucose (IFG) was defined as fasting consumed vegetables and fruit every day versus noncompleters plasma glucose concentration of 6.1 to 7.0mmol/L. Impaired (41% versus 30%, P=.055). There were no other baseline glucose tolerance (IGT) was defined as glucose plasma differences between completers and noncompleters. concentration of 7.80 to 11.0mmol/L after oral administration In multiple logistic regression model the status of being of 75g of glucose (OGTT). Diabetes mellitus was defined as employed decreased the likelihood of completing the intervention fasting glucose concentration of >7.0mmol/L or glucose 2 times (OR 0.45, 95% CI 0.25–0.81). Patients with higher 120 concentration of >11.1mmol/L at 2 hours of OGTT (120 OGTT glucose and hypertension were found to have lower [4,5] OGTT). Body mass index (BMI) was calculated as weight (in completion rate (OR 0.79, 95% 0.69–0.92 and OR 0.52, 95% CI light indoor clothes, kg) divided by height squared (m ); waist 0.27–0.99, respectively). Daily consumption of vegetables and circumference was measured midway between the lowest rib and fruits increased the likelihood of completing the intervention (OR iliac crest; diastolic and systolic blood pressures were taken while 1.86, 95% CI 1.01–3.41) (Table 2). Thirty percent of non- sitting after 10-minute rest. completers gave the reason of nonparticipation in the interven- Data on education, marital status, employment status, history tion, the most commonly declared reasons were: “shortage of of increased blood glucose, family history of diabetes, Finnish time” and “inability to continue time-consuming programme,” Diabetes Risk Score (FINDRISK), smoking status, history of “working commitments,” and other commitments like “taking hypertension, history of cardiovascular disease, and depression care of children, grandchildren, or elderly parents.” were taken with the of self-reported questionnaire. Lifestyle was explored with the use of simple self-reported 4. Discussion questions on physical activity and consumption of vegetables and fruit. The following questions were asked: “Do you perform at Results of real-life implementation studies performed in different least 30 minutes of physical activity at work and/or during leisure settings and populations proved that lifestyle DM2 prevention time (including normal daily activity each day)” or “Do you eat interventions, however less-intensive and less costly than RCTs, fruit or vegetables daily?” Measurements were performed at can be effective, and that beneficial outcomes can last for a longer [7–19] baseline and then repeated after 1 and after 3 years from the time. However, in order to achieve health benefits at [5] initiation of the intervention. population level, the reach and efficacy of the programmes should be improved. Therefore, the present study investigates the factors influencing the completion of the DE-PLAN programme designed 2.2. Statistical analyses as a real-life, real-setting, lifestyle DM2 prevention intervention. The descriptive analyses are given as percentages (for categorical In our study, 30% of those who completed all baseline variables) and means with standard deviations (for continuous examinations and initially agreed to participate did not variables). Chi-square tests for categorical variables and t tests for eventually complete the intervention. Noncompleters had worse continuous ones were applied to compare the distribution health profile versus completers. People who did not complete the between the potential predictors according to whether the intervention were more frequently employed as compared to participants completed the intervention or not. Stepwise logistic completers and more often had hypertension. Completers more regression models were used to assess the association between the frequently consumed vegetables and fruit on a daily basis when different predictors and outcome variable. The odds ratios (ORs) compared to noncompleters. Employment was an independent and the respective 95% confidence interval (CI) were calculated. noncompletion factor and it decreased the probability to A P-value of<.05 was considered statistically significant. complete the intervention 2 times. Also, hypertension was an The data were analyzed using STATISTICA version 12 independent factor decreasing the chance to complete the study 2 (StatSoft, Inc, 2014, www.statsoft.com). times, while daily consumption of vegetables and fruit was increasing the chance to complete the study. In the similar prevention study performed in occupational 3. Results setting in Finland, out of 657 people (airline employees) with Outof368 respondents eligible to participate in the study baseline increased DM2 risk invited to the intervention, 53% [6] (FINDRISK > 14), 275 (75%) agreed to undergo OGTT agreed to participate. Unlike in our study where only 22% of examination and subsequently 262 (71%) agreed to participate in participants were men, in Finland men and women attended the the study (258 with complete baseline examination). A total of 184 intervention equally. FINDRISK score, waist circumference, BMI, (70% of all who agreed) completed the core curriculum while 74 sedentary lifestyle, depression, sleeping problems, and stress [6] (30% of all who agreed) did not eventually complete the intervention. affecting work ability increased participation in both sexes. In Out of those who agreed to participate in the study, 24% were another DE-PLAN study run in Greece, where patients were recruited through primary healthcare centers and workplace, out men, while the percentage of men among completers was 22% of 620 high-risk individuals, 191 agreed to participate in the study and among noncompleters was 30% (ns). 3 Gilis-Januszewska et al. Medicine (2018) 97:5 Medicine Table 1 Baseline characteristic of people enrolled in the study according to participation in the intervention. Completed interventions (n= 184) Did not complete interventions (n= 74) Variable Mean SD Mean SD P value Age 55.9 11.1 54.9 12.2 .386 Body mass index, kg/m 31.8 4.9 32.6 4.6 .157 Waist circumference, cm 98.8 11.8 100.9 9.2 .062 Systolic blood pressure, mm Hg 131.9 14.3 134.5 14.1 .798 Diastolic blood pressure, mm Hg 81.9 8.4 83.6 10.3 .446 Fasting glucose, mmol/L 5.3 0.7 5.4 0.7 .686 2-H OGTT glucose, mmol/L 5.8 1.8 6.6 2.1 .046 TC, mmol/L 5.5 1.0 5.8 1.3 .098 HDL cholesterol, mmol/L 1.4 0.4 1.4 0.4 .906 TG, mmol/L 1.7 1.2 2.4 2.6 .004 FINDRISK 18.3 2.8 18.7 2.9 .629 %% Men 22 30 .136 Education Basic/medium 79 72 .193 High 21 28 Married/having a partner/cohabiting (yes vs no) 70 72 .468 Employed (yes vs no) 39 54 .037 Current smoking (yes vs no) 20 26 .179 History of hyperglycaemia (yes vs no) 60 55 .487 History of hypertension (yes vs no) 65 77 .043 History of depression (yes vs no) 16 16 .574 Family history of diabetes (yes vs no) 58 70 .066 >30-minute daily physical activity (yes vs no) 16 19 .368 Daily consumption of vegetables and fruit (yes vs no) 41 30 .055 FINDRISK= Finnish Diabetes Risk Score, HDL= high-density lipoprotein, IFG= impaired fasting glucose, IGT= impaired glucose tolerance, OGTT= oral glucose tolerance test, SD= standard deviation, TC= total cholesterol, TG= triglyceride. [11] and 125 fully completed the programme. In this study, glucose despite undergoing the initial screening process. In this study, intolerance and the site of recruitment was independently people with family history of diabetes and history of high blood [11] associated with participation in the programme. glucose, physically inactive were significantly more likely to [18] In the Sydney Diabetes Prevention Program (Sydney DPP), enroll in the study, while high-risk individuals who smoked, were one-third of eligible patients did not participate in the programme born in a high diabetes risk region, took blood pressure-lowering Table 2 Multivariate analysis of predictors of completing the lifestyle interventions programme in primary healthcare in Krakow, Poland. Full model Reduced model Variable OR 95% CI OR 95% CI Age 0.99 0.95–1.03 Sex (man vs woman) 0.90 0.39–2.07 BMI, kg/m 1.02 0.92–1.12 FINDRISK 0.95 0.81–1.12 WC 0.98 0.94–1.03 120 OGTT 0.83 0.70–0.97 0.79 0.69–0.92 TC 0.93 0.69–1.26 TG 0.89 0.73–1.09 Education (basic/medium vs high) 1.67 0.81–3.45 ∗∗ Employment (yes vs no) 0.45 0.21–0.96 0.45 0.25–0.81 Family history of diabetes (yes vs no) 0.54 0.25–1.19 Current smoking (yes vs no) 0.66 0.32–1.36 ∗∗∗ History of hypertension (yes vs no) 0.63 0.29–1.34 0.52 0.27–0.99 >30-minute daily physical activity (yes vs no) 0.88 0.37–2.07 ∗∗∗∗ Daily consumption of vegetable and fruit (yes vs no) 1.98 1.01–3.85 1.86 1.01–3.41 History of hyperglycemia (yes vs no) 1.17 0.51–2.68 BMI= body mass index, CI= confidence interval, FINDRISK= Finnish Diabetes Risk Score, OGTT= oral glucose tolerance test, OR= odds ratio, SD= standard deviation, TC= total cholesterol, TG= triglyceride, WC= waist circumference. P= .002. ∗∗ P= .007. ∗∗∗ P= .048. ∗∗∗∗ P= .046. Participating in >8 sessions. 4 Gilis-Januszewska et al. Medicine (2018) 97:5 www.md-journal.com medications and consumed little fruit and vegetables were high-risk individuals. The lack of association between age and [18] significantly less likely to take up the programme. Low completion of the intervention might result from the narrow age participation in the prevention programmes is observed even range for this study and small sample size. among patients with much higher DM2 risk like, for example, in Some strengths and limitations of our study need to be the DM2 prevention trial among women with gestational discussed. This is one of the first real-life, real-setting studies [19] diabetes. In this study, recruitment was more challenging investigating factors influencing completion of diabetes preven- than anticipated with only 89 out of 410 (22%) women agreeing tion lifestyle intervention among high diabetes risk individuals [19] to participate in the programme. In our study, employment without diabetes. The participants in our study were volunteers, was an independent factor decreasing the likelihood of and, similarly to many other studies, this one predominantly participation 2 times. This is in concordance with the Health attracted women. Around 22% out of those who completed the Improvement and Prevention Study (HIPS), where mixed and study were men, while among noncompleters the percentage of complex method to assess the factors influencing attendance was men was 30%. Very low uptake of the intervention by men [17] used. In this study, people who were older, did not work, and suggests that the results of the study might not be generalized to had higher levels of psychological distress were significantly more both sexes and implies the need for further studies on sex-specific likely to attend. Working commitments and problems with mechanism of completion of real-life lifestyle interventions. There accessing the programme were described as important are also important psychological factors influencing completion [17] obstacles. Attendance was promoted by providing sessions and attrition rates in lifestyle prevention programmes which were outside working hours. Similarly to our study, in the HIPS, the not studied in our project which further implies the need for [9,31,32] lifestyle modification programme was taken up mainly by continued investigation separately for both sexes. We [17] nonworking participants. Also, as reported by Gucciardi should also interpret lifestyle data with caution as the measure of et al, conflict with working hours schedule could be the main vegetables and fruit consumption frequency and physical activity [21] obstacle in an uptake of DM2 education services. In Finland, was very crude. in the prevention study among airline company employees, the Furthermore, there are very important practical barriers like uptake of the group intervention was so low that group work commitments, accessibility, affordability, and practicality [6] [17–19] intervention was discontinued. Instead, a diabetes prevention of the interventions as well as factors related to the quality website was created, with good uptake measured as the number of intervention given by GPs and prevention officers which were [6] of visits per year. In another DPS implementation study run in not investigated in our study and, as indicated by other research, Finland—FIN-D2D—project with similar uptake of the pro- might be very important in diabetes prevention programme [17,18] gramme being unemployed and undereducated was related to uptake. In our study, some of noncompleters reported also [9] active participation in the intervention but only in men. In the other than working commitments like “taking care of children,” Greek DE-PLAN study, recruitment through workplace was the “taking care of grandchildren,” or “taking care of elderly most successful strategy in identifying high-risk individuals, parents” as the reason of the drop out. However, the total [11] enrolling, and maintaining them in the study. Therefore, to number of people who gave any reason of nonparticipation in the improve the reach and attendance of working people it seems intervention was low. essential to develop strategies targeted towards providing These observations highlight the need to develop lifestyle convenient and accessible services. In fact, several new strategies interventions further in order to increase completion of the are being investigated like for instance internet-based interven- programmes by males, particularly those who are working and tions, telephone counseling, mobile apps, or workplace-run those at high risk. Results and experience of the DE-PLAN [22–28] interventions. programme were used in the preparation of the European In our study, similarly to the Sydney DPP healthier behaviors like guidelines and the toolkit for the Diabetes Prevention in Europe more frequent consumption of vegetables and fruit was observed where some strategies for the reach of focus population have [33,34] among completers. In baseline characteristics people who been described. The study is being continued in the city of participated in the study also had a better health profile; higher Krakow as a self-government-sponsored initiative. 120 OGTT glucose was an independent factor decreasing the In conclusion, further insight into the determinants of chance to participate in the intervention. These findings might completion of real-life diabetes type 2 prevention interventions point out to a higher awareness and motivation among people is needed to learn about the barriers as well as to improve the participating in lifestyle intervention studies and are concordant reach and attendance of target population. with previous studies where people participating in epidemiologi- [7,8,29,30] cal studies had a healthier profile than general population. Acknowledgments This is also in line with some other studies, where participation in the RCTs was high, which suggests that people participating in The authors would like to thank all the nurses—diabetes intervention studies are a very selective and highly motivated prevention managers, dietitian, physical activity specialist, and [2] group. In our study also people with hypertension were less likely psychologist without whom this work would not have been possible. They are very grateful for the time and expertise they to complete the intervention. This association, also present in the devoted to the performance of the DE-PLAN study. Sydney DPP, is not clear but might be in line with observations that people with a worse health profile are less likely to participate in [18] prevention initiatives. References In our study, there were no particular socioeconomic differ- [1] Tuomilehto J, Lindström J, Eriksson JG, et al. Prevention of type 2 ences between completers and noncompleters but in previously diabetes mellitus by changes in lifestyle among subjects with impaired published research low socioeconomic status was related to less glucose tolerance. N Engl J Med 2001;344:1343–50. frequent use of health care services despite poorer health [2] Knowler WC, Barrett-Connor E, Fowler SE, et al. Reduction in the [30,31] status. Our findings underline the need of further research incidence of type 2 diabetes with lifestyle intervention or metformin. 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Medicine – Wolters Kluwer Health
Published: Feb 1, 2018
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