a literature search was performed to identify randomized controlled trials of patient - centered interventions in persons with type 2 diabetes , in which lifestyle issues ( at least nutrition and/or exercise ) were addressed . inclusion criteria were recent publication ( 20032008 ) , large trial ( n > 150 ) , a minimum follow - up of 12 months , mainly caucasian population , risk factor outcomes reported ( weight , bmi , physical activity , smoking , diet , glycemic control , lipids , and/or blood pressure ) , and sufficient information to be able to calculate intervention costs . in addition , we searched for studies that provided quantitative information about long - term maintenance of health benefits achieved through lifestyle interventions . selection criteria for these studies as well as the methods for determining long - term maintenance estimates are described in the supplementary data ( available in an online appendix at http://care.diabetesjournals.org/cgi/content/full/dc09-0363/dc1 ) . intervention effect was defined as a significant change in risk factor outcome for intervention participants compared with control subjects at the latest follow - up . long - term maintenance for each risk factor was defined as the proportion of the intervention effect that could be expected to be sustained over lifetime . for each risk factor , the intervention effect was multiplied with long - term maintenance to estimate the average intervention effect over a lifetime . we assumed that the interventions would be implemented as described , but with a minimum of two patient contacts during the first 2 years ( to enhance long - term maintenance ) . we accounted for additional intervention costs if these requirements were not met in the original intervention . the chronic diseases model ( cdm ) is a markov - type simulation model , developed at the dutch national institute for public health and the environment . the model simulates developments for the dutch diabetic population and is well suited to explore long - term consequences of lifestyle changes . the model combines epidemiological data to quantify the associations between multiple risk factors and chronic diseases , such as cardiovascular diseases and cancers ( supplementary figure a1 and table a1 , available in an online appendix ) . starting from baseline distributions over risk factor classes and diseases , 1-year state transitions determine future developments . state transition probability values depend on a person 's risk level , determined by age , sex , risk factor class , and prevalent disease . estimates of the strengths of the associations between risk factors and diseases are based on international , observational studies . the cdm has previously been used to evaluate long - term outcomes for diabetes prevention and diabetes treatment and to explore the impact of lifestyle risk factors on healthy life expectancy and lifetime medical costs ( 58 ) . we explored the long - term health benefits of the interventions by comparing simulated outcomes for a reference cohort and an intervention cohort . the intervention cohort differed from the reference cohort ( usual care ) by an altered risk factor distribution at the start of the simulation , based upon the trial results . for example , participants in the improving control with activity and nutrition ( ican ) trial lost 2.4 kg baseline weight compared with a weight gain of 0.6 kg in control subjects , a difference of 3 kg or 2.8% of baseline weight ( bmi ) . the long - term maintenance estimate for bmi was 35% ( results ) , and , consequently , ican participants were assumed to have an average 2.8%  35% = 1.0% lower bmi over lifetime , compared with patients receiving usual care . we used a large dutch diabetes database to determine how this difference affected bmi risk factor class distributions at the start of the simulation . once the simulation had started , the same state - specific transition probabilities were applied to both reference and intervention cohorts . cumulative lifetime incidence of cardiovascular disease ( cvd ) ( cvd = acute myocardial infarction + coronary heart disease + congestive heart failure + stroke ) and quality - adjusted life - years ( qalys ) were simulated for these cohorts as well as for 60-year - old participants . the incremental effects on the costs of care were calculated from the model simulations as follows . all model states in the cdm were associated with health care costs , depending on age , sex , and disease state . these costs represent total medical costs , including costs for  unrelated  diseases such as dementia and mental illness ( 9 ) . for each intervention , net present values of incremental costs were calculated by summing the discounted costs over all simulation years and taking the difference with the reference scenario ( usual care ) . cost - effectiveness ratios ( cers ) were calculated as (  intervention costs +  lifetime medical costs)/ qalys for each intervention . in the base - case analyses , clinical benefits and costs were discounted at 1.5 and 4% , respectively , annually , in accordance with dutch guidelines . one - way sensitivity analyses were performed to explore the impact of discount rates , time horizon , and additional long - term intervention costs on the cost - effectiveness of the interventions . probabilistic sensitivity analyses were performed , taking account of uncertainty in intervention effects , long - term maintenance , and intervention costs . for each intervention , 200 random , independent drawings were taken from the distributions for effect , maintenance , and costs . intervention effect and maintenance estimates were multiplied to generate we took into account the possibility that changes in lifestyle risk factors may be correlated . for example , participants with the largest increase in physical activity may also achieve the largest weight loss ( 1012 ) . because quantitative information about all possible combinations of risk factor outcomes is limited ( and sometimes inconsistent ) we assumed , respectively , 0 and 100% correlation between the long - term effect estimates of all risk factors affected . to do so , the long - term effect estimates for each risk factor were ordered , before they were combined . consequently , a low ( high ) effect estimate for one risk factor was combined with low ( high ) estimates for all other risk factors affected . for intervention costs , we considered variation in total contact time of the interventions , and we varied the number of participants in group activities . a literature search was performed to identify randomized controlled trials of patient - centered interventions in persons with type 2 diabetes , in which lifestyle issues ( at least nutrition and/or exercise ) were addressed . inclusion criteria were recent publication ( 20032008 ) , large trial ( n > 150 ) , a minimum follow - up of 12 months , mainly caucasian population , risk factor outcomes reported ( weight , bmi , physical activity , smoking , diet , glycemic control , lipids , and/or blood pressure ) , and sufficient information to be able to calculate intervention costs . in addition , we searched for studies that provided quantitative information about long - term maintenance of health benefits achieved through lifestyle interventions . selection criteria for these studies as well as the methods for determining long - term maintenance estimates are described in the supplementary data ( available in an online appendix at http://care.diabetesjournals.org/cgi/content/full/dc09-0363/dc1 ) . intervention effect was defined as a significant change in risk factor outcome for intervention participants compared with control subjects at the latest follow - up . long - term maintenance for each risk factor was defined as the proportion of the intervention effect that could be expected to be sustained over lifetime . for each risk factor , the intervention effect was multiplied with long - term maintenance to estimate the average intervention effect over a lifetime . we assumed that the interventions would be implemented as described , but with a minimum of two patient contacts during the first 2 years ( to enhance long - term maintenance ) . we accounted for additional intervention costs if these requirements were not met in the original intervention . the chronic diseases model ( cdm ) is a markov - type simulation model , developed at the dutch national institute for public health and the environment . the model simulates developments for the dutch diabetic population and is well suited to explore long - term consequences of lifestyle changes . the model combines epidemiological data to quantify the associations between multiple risk factors and chronic diseases , such as cardiovascular diseases and cancers ( supplementary figure a1 and table a1 , available in an online appendix ) . starting from baseline distributions over risk factor classes and diseases , 1-year state transitions determine future developments . state transition probability values depend on a person 's risk level , determined by age , sex , risk factor class , and prevalent disease . estimates of the strengths of the associations between risk factors and diseases are based on international , observational studies . the cdm has previously been used to evaluate long - term outcomes for diabetes prevention and diabetes treatment and to explore the impact of lifestyle risk factors on healthy life expectancy and lifetime medical costs ( 58 ) . we explored the long - term health benefits of the interventions by comparing simulated outcomes for a reference cohort and an intervention cohort . the intervention cohort differed from the reference cohort ( usual care ) by an altered risk factor distribution at the start of the simulation , based upon the trial results . for example , participants in the improving control with activity and nutrition ( ican ) trial lost 2.4 kg baseline weight compared with a weight gain of 0.6 kg in control subjects , a difference of 3 kg or 2.8% of baseline weight ( bmi ) . the long - term maintenance estimate for bmi was 35% ( results ) , and , consequently , ican participants were assumed to have an average 2.8%  35% = 1.0% lower bmi over lifetime , compared with patients receiving usual care . we used a large dutch diabetes database to determine how this difference affected bmi risk factor class distributions at the start of the simulation . once the simulation had started , the same state - specific transition probabilities were applied to both reference and intervention cohorts . cumulative lifetime incidence of cardiovascular disease ( cvd ) ( cvd = acute myocardial infarction + coronary heart disease + congestive heart failure + stroke ) and quality - adjusted life - years ( qalys ) were simulated for these cohorts as well as for 60-year - old participants . the incremental effects on the costs of care were calculated from the model simulations as follows . all model states in the cdm were associated with health care costs , depending on age , sex , and disease state . these costs represent total medical costs , including costs for  unrelated  diseases such as dementia and mental illness ( 9 ) . for each intervention , net present values of incremental costs were calculated by summing the discounted costs over all simulation years and taking the difference with the reference scenario ( usual care ) . cost - effectiveness ratios ( cers ) were calculated as (  intervention costs +  lifetime medical costs)/ qalys for each intervention . in the base - case analyses , clinical benefits and costs were discounted at 1.5 and 4% , respectively , annually , in accordance with dutch guidelines . one - way sensitivity analyses were performed to explore the impact of discount rates , time horizon , and additional long - term intervention costs on the cost - effectiveness of the interventions . probabilistic sensitivity analyses were performed , taking account of uncertainty in intervention effects , long - term maintenance , and intervention costs . for each intervention , 200 random , independent drawings were taken from the distributions for effect , maintenance , and costs . intervention effect and maintenance estimates were multiplied to generate  long - term effect  estimates . we took into account the possibility that changes in lifestyle risk factors may be correlated . for example , participants with the largest increase in physical activity may also achieve the largest weight loss ( 1012 ) . because quantitative information about all possible combinations of risk factor outcomes is limited ( and sometimes inconsistent ) we assumed , respectively , 0 and 100% correlation between the long - term effect estimates of all risk factors affected . to do so , the long - term effect estimates for each risk factor were ordered , before they were combined . consequently , a low ( high ) effect estimate for one risk factor was combined with low ( high ) estimates for all other risk factors affected . for intervention costs , we considered variation in total contact time of the interventions , and we varied the number of participants in group activities . the interventions differed by scope , focus , content , intensity , and target population . the trials included were the following : 
 diabetes education and self management for ongoing and newly diagnosed ( desmond ) : a 6-h self - management education program for patients with newly diagnosed diabetes ( n = 824 ) evaluated at 12 months ( 13)beyond good intentions ( bgi ) : a 12-week self - management course for patients with screen - detected diabetes ( n = 196 ) evaluated at 12 months ( 14)action for health in diabetes ( look ahead ) : a 1-year intensive lifestyle intervention for overweight patients ( n = 5,145 ) evaluated at 12 months ( 15)mediterranean lifestyle program ( mlp ) : a 6-month lifestyle program for postmenopausal women with diabetes ( n = 279 ) followed by two different maintenance programs , evaluated at 24 months ( 16)x - pert : a 6-week , structured self - management education program for diabetic patients ( n = 314 ) evaluated at 14 months ( 17)improving control with activity and nutrition ( ican ) : a 1-year moderate - intensity lifestyle intervention for overweight patients ( n = 147 ) evaluated at 12 months ( 18)counseling for physical activity ( cpa ) : a 2-year structured counseling intervention to promote physical activity ( n = 340 ) evaluated at 24 months ( 10 ) diabetes education and self management for ongoing and newly diagnosed ( desmond ) : a 6-h self - management education program for patients with newly diagnosed diabetes ( n = 824 ) evaluated at 12 months ( 13 ) beyond good intentions ( bgi ) : a 12-week self - management course for patients with screen - detected diabetes ( n = 196 ) evaluated at 12 months ( 14 ) action for health in diabetes ( look ahead ) : a 1-year intensive lifestyle intervention for overweight patients ( n = 5,145 ) evaluated at 12 months ( 15 ) mediterranean lifestyle program ( mlp ) : a 6-month lifestyle program for postmenopausal women with diabetes ( n = 279 ) followed by two different maintenance programs , evaluated at 24 months ( 16 ) x - pert : a 6-week , structured self - management education program for diabetic patients ( n = 314 ) evaluated at 14 months ( 17 ) improving control with activity and nutrition ( ican ) : a 1-year moderate - intensity lifestyle intervention for overweight patients ( n = 147 ) evaluated at 12 months ( 18 ) counseling for physical activity ( cpa ) : a 2-year structured counseling intervention to promote physical activity ( n = 340 ) evaluated at 24 months ( 10 ) the selected trials , calculations of intervention costs , and characteristics of the simulated cohorts are described in supplementary tables a2a5 ( available in an online appendix ) . significant reductions in risk factors were obtained in all trials ( table 1 ) . based on the long - term results from five other trials ( supplementary data ) , we assumed that on average , respectively , 85 , 55 , and 35% of the initial effects for a1c , physical activity , and bmi ( and all other risk factors ) could be sustained over lifetime . we assumed slightly better maintenance for mlp and cpa , because  initial effects  in these trials were measured at 24 months follow - up . total intervention costs , incurred over 2 years , ranged from  124 to  584 per participant ( table 1 ) . model input : intervention costs and intervention effects * details are provided in supplementary table a2 . this was the only nonsignificant effect that was included in the simulations . the interventions were projected to reduce lifetime cumulative incidence of cardiovascular complications by 154 per 1,000 participants ( table 2 ) . in other words , the number needed to treat to prevent one new cardiovascular complication over lifetime was 191,000 . the relative reduction in expected lifetime cvd incidence ranged from 0.1 to 6.1% . the interventions increased life expectancy by 0.020.34 years and ( discounted ) qalys by 0.010.14 . for 60-year - old participants ( supplementary table a6 , available in an online appendix ) , life expectancy increased by 0.020.42 years and ( discounted ) qalys by 0.010.18 . this intervention increased life expectancy of 60-year - old participants by 0.42 years , whereas average time spent with cvd complications decreased by 0.06 and 0.07 year for stroke and chd , respectively ( data not shown ) . clinical benefits and health care costs for intervention participants compared with usual care * absolute reduction in cumulative lifetime incidence of new cvd complications per 1,000 participants , expected cumulative number of new cvd complications without intervention ( per 1,000 patients in the reference cohort ) , and in parentheses , percent relative reduction achieved through the intervention . , all interventions were projected to increase health care costs over a lifetime , because of increased survival ( table 2 ) . four interventions ( bgi , x - pert , look ahead , and cpa ) had average cers <  20,000/qaly even with equal discounting of costs and effects , a 20-year time - horizon or additional lifetime intervention costs . in the probabilistic sensitivity analyses ( for which details are provided in supplementary tables a7a9 , available in an online appendix ) , these interventions had > 85% probability to remain <  20,000/qaly ( table 3 ) . results for cost - effectiveness (  /qaly ) : base - case and sensitivity analyses * assuming one additional 30-min individual contact (  27 ) per year for the remaining lifetime , starting from year 3 . assuming an average  100 per patient reduction in lifetime health care costs due to reduced medication use . dc , annual discount rates for effects and costs ; na , not available , just one risk factor affected . as expected , assuming 100% correlation between risk factor outcomes increased the variability of the simulated outcomes ( supplementary table a10 , available in an online appendix ) . for example , for look ahead , qalys increased by 0.030.12 if outcomes were assumed to be independent and by 0.010.15 with 100% correlation . similarly , the variability in simulated health care costs and cers was higher if outcomes were assumed to be correlated ( data not shown ) . the cost - effectiveness acceptability curves for the interventions , assuming correlated outcomes , are displayed in fig . 1 . cost - effectiveness acceptability curves for each intervention . in the base - case analyses , immediate cost - savings through reduced medication use ( reported for x - pert , look ahead , and ican ) were not taken into account , and additional analyses were performed to explore the potential impact of these additional intervention benefits ( table 3 ) . although economic outcomes for the three interventions improved , the main results as summarized above were not substantially changed . the interventions differed by scope , focus , content , intensity , and target population . the trials included were the following : 
 diabetes education and self management for ongoing and newly diagnosed ( desmond ) : a 6-h self - management education program for patients with newly diagnosed diabetes ( n = 824 ) evaluated at 12 months ( 13)beyond good intentions ( bgi ) : a 12-week self - management course for patients with screen - detected diabetes ( n = 196 ) evaluated at 12 months ( 14)action for health in diabetes ( look ahead ) : a 1-year intensive lifestyle intervention for overweight patients ( n = 5,145 ) evaluated at 12 months ( 15)mediterranean lifestyle program ( mlp ) : a 6-month lifestyle program for postmenopausal women with diabetes ( n = 279 ) followed by two different maintenance programs , evaluated at 24 months ( 16)x - pert : a 6-week , structured self - management education program for diabetic patients ( n = 314 ) evaluated at 14 months ( 17)improving control with activity and nutrition ( ican ) : a 1-year moderate - intensity lifestyle intervention for overweight patients ( n = 147 ) evaluated at 12 months ( 18)counseling for physical activity ( cpa ) : a 2-year structured counseling intervention to promote physical activity ( n = 340 ) evaluated at 24 months ( 10 ) diabetes education and self management for ongoing and newly diagnosed ( desmond ) : a 6-h self - management education program for patients with newly diagnosed diabetes ( n = 824 ) evaluated at 12 months ( 13 ) beyond good intentions ( bgi ) : a 12-week self - management course for patients with screen - detected diabetes ( n = 196 ) evaluated at 12 months ( 14 ) action for health in diabetes ( look ahead ) : a 1-year intensive lifestyle intervention for overweight patients ( n = 5,145 ) evaluated at 12 months ( 15 ) mediterranean lifestyle program ( mlp ) : a 6-month lifestyle program for postmenopausal women with diabetes ( n = 279 ) followed by two different maintenance programs , evaluated at 24 months ( 16 ) x - pert : a 6-week , structured self - management education program for diabetic patients ( n = 314 ) evaluated at 14 months ( 17 ) improving control with activity and nutrition ( ican ) : a 1-year moderate - intensity lifestyle intervention for overweight patients ( n = 147 ) evaluated at 12 months ( 18 ) counseling for physical activity ( cpa ) : a 2-year structured counseling intervention to promote physical activity ( n = 340 ) evaluated at 24 months ( 10 ) the selected trials , calculations of intervention costs , and characteristics of the simulated cohorts are described in supplementary tables a2a5 ( available in an online appendix ) . significant reductions in risk factors were obtained in all trials ( table 1 ) . based on the long - term results from five other trials ( supplementary data ) , we assumed that on average , respectively , 85 , 55 , and 35% of the initial effects for a1c , physical activity , and bmi ( and all other risk factors ) could be sustained over lifetime . we assumed slightly better maintenance for mlp and cpa , because  initial effects  in these trials were measured at 24 months follow - up . total intervention costs , incurred over 2 years , ranged from  124 to  584 per participant ( table 1 ) . model input : intervention costs and intervention effects * details are provided in supplementary table a2 . the interventions were projected to reduce lifetime cumulative incidence of cardiovascular complications by 154 per 1,000 participants ( table 2 ) . in other words , the number needed to treat to prevent one new cardiovascular complication over lifetime was 191,000 . the relative reduction in expected lifetime cvd incidence ranged from 0.1 to 6.1% . the interventions increased life expectancy by 0.020.34 years and ( discounted ) qalys by 0.010.14 . for 60-year - old participants ( supplementary table a6 , available in an online appendix ) , life expectancy this intervention increased life expectancy of 60-year - old participants by 0.42 years , whereas average time spent with cvd complications decreased by 0.06 and 0.07 year for stroke and chd , respectively ( data not shown ) . clinical benefits and health care costs for intervention participants compared with usual care * absolute reduction in cumulative lifetime incidence of new cvd complications per 1,000 participants , expected cumulative number of new cvd complications without intervention ( per 1,000 patients in the reference cohort ) , and in parentheses , percent relative reduction achieved through the intervention . despite prevented costs for complications , all interventions were projected to increase health care costs over a lifetime , because of increased survival ( table 2 ) . four interventions ( bgi , x - pert , look ahead , and cpa ) had average cers <  20,000/qaly even with equal discounting of costs and effects , a 20-year time - horizon or additional lifetime intervention costs . in the probabilistic sensitivity analyses ( for which details are provided in supplementary tables a7a9 , available in an online appendix ) , these interventions had > 85% probability to remain <  20,000/qaly ( table 3 ) . results for cost - effectiveness (  /qaly ) : base - case and sensitivity analyses * assuming one additional 30-min individual contact (  27 ) per year for the remaining lifetime , starting from year 3 . assuming an average  100 per patient reduction in lifetime health care costs due to reduced medication use . dc , annual discount rates for effects and costs ; na , not available , just one risk factor affected . as expected , assuming 100% correlation between risk factor outcomes increased the variability of the simulated outcomes ( supplementary table a10 , available in an online appendix ) . for example , for look ahead , qalys increased by 0.030.12 if outcomes were assumed to be independent and by 0.010.15 with 100% correlation . similarly , the variability in simulated health care costs and cers was higher if outcomes were assumed to be correlated ( data not shown ) . the cost - effectiveness acceptability curves for the interventions , assuming correlated outcomes , are displayed in fig . 1 . cost - effectiveness acceptability curves for each intervention . in the base - case analyses , immediate cost - savings through reduced medication use ( reported for x - pert , look ahead , and ican ) were not taken into account , and additional analyses were performed to explore the potential impact of these additional intervention benefits ( table 3 ) . although economic outcomes for the three interventions improved , the main results as summarized above were not substantially changed . we showed that it is feasible to simulate long - term outcomes for different kinds of lifestyle interventions for diabetic patients . however , because of limited information about long - term maintenance of health benefits , there was substantial variability ( uncertainty ) in the expected long - term outcomes for each intervention . large differences in health outcomes were also observed between interventions ( 0.010.14 qalys gained ) . however , despite this variability , health gains were generally achieved at reasonable costs ( 50,000/qaly ) . self - management education ( x - pert ) and physical activity counseling ( cpa ) achieved the most promising results with 0.10 qalys gained per person and a very high probability of being cost - effective . overall , the results of the selected trials were consistent with results from several meta - analyses that generally showed 0.30.8% improvements in a1c and modest ( 1.5 kg ) reductions in weight achieved through nonpharmacological diabetes interventions ( 2,19,20 ) . however , we want to highlight some interesting results . this intervention focused on weight loss , mainly through caloric restriction , and included meal replacement products and weight loss medication ( 12 ) . although substantial short - term weight loss with caloric restriction has been reported previously ( 21 ) , the long - term results of look ahead are awaited to see whether these weight losses are sustained . second , the major increase in voluntary physical activity in the cpa trial ( 23 met h / week , corresponding to 1 addition hour of brisk walking per day ) was much larger than the average 2060 min of additional physical activity per week generally seen in other studies ( 22 ) . although the cpa intervention combined multiple evidence - based treatment strategies to enhance physical activity , it remains to be seen whether its findings can be replicated in other settings . finally , three trials reported a decrease in medication use , which is an important , relatively new finding , because health care utilization outcomes were not assessed in any of 21 diabetes self - management trials included in a previous review ( 23 ) . the large number of participants in each of the studies indicates that implementation in regular care is probably feasible . to ensure that health benefits were sustained for a reasonable period of time , we only used intervention effects that were measured at least 12 months after the start of the intervention . in addition , we required interventions to be continued ( with at least two counseling sessions ) in the second year . long - term maintenance estimates were based on the best evidence available , and the impact of uncertainty in these estimates was explored in extensive sensitivity analyses . finally , because changes in various lifestyle habits may go together , we considered the impact of correlated outcomes ( 10,11 ) . our simulations were based on randomized trial results , and it may be difficult to replicate these findings in daily practice . on the other hand , there are some reasons to believe that our health benefits might be underestimated . first , only risk factors included in the model could be used and consequently reported improvements in waist circumference , diastolic blood pressure , lipids , fitness , and psychosocial outcomes were not taken into account . although long - term health outcomes and health care costs are determined mainly by macrovascular diabetes complications , excluding microvascular disease results in an underestimation of health benefits , especially for improved glycemic control . finally , enhanced standard care was provided to control subjects in three trials ( 13,15,17 ) , and for these interventions we may have underestimated the effects in relation to the assumed resources used . on the other hand , large variations also exist in the extent to which lifestyle issues are currently addressed in dutch usual care . because promotion of a healthy lifestyle is already acknowledged as an essential part of diabetes treatment , the question is no longer whether lifestyle issues should be addressed but rather how to find the most ( cost ) effective strategies for specific groups of patients . although look ahead seemed to dominate ican ( larger health benefits and lower cer ) , these trials used different inclusion criteria and outcome measures and , therefore , results could not be properly compared . in addition , favorable efficacy and cost - effectiveness are not sufficient and potential reach , effectiveness , adoption , implementation , and maintenance issues of interventions should also be addressed ( 24 ) . because numerous factors influence the effectiveness of lifestyle interventions , standardized descriptions of intervention components are required to identify successful strategies and to enhance replication and implementation in regular care ( 23,25 ) . we showed that lifestyle interventions can probably improve long - term health of diabetic patients at reasonable costs . future research should be focused on long - term maintenance of health benefits achieved through lifestyle interventions and should directly compare multiple treatment strategies to determine incremental costs and benefits of one over the other . because the potential benefits of successful lifestyle interventions are huge , we should be investing much more in gathering this valuable information .
objectiveto explore the potential long - term health and economic consequences of lifestyle interventions for diabetic patients.research design and methodsa literature search was performed to identify interventions for diabetic patients in which lifestyle issues were addressed . 
 we selected recent ( 20032008 ) , randomized controlled trials with a minimum follow - up of 12 months . 
 the long - term outcomes for these interventions , if implemented in the dutch diabetic population , were simulated with a computer - based model . 
 costs and effects were discounted at , respectively , 4 and 1.5% annually . a lifelong time horizon was applied . 
 probabilistic sensitivity analyses were performed , taking account of variability in intervention costs and ( long - term ) treatment effects.resultsseven trials with 1475,145 participants met our predefined criteria . all interventions improved cardiovascular risk factors at 1 year follow - up and were projected to reduce cardiovascular morbidity over lifetime . 
 the interventions resulted in an average gain of 0.010.14 quality - adjusted life - years ( qalys ) per participant . 
 health benefits were generally achieved at reasonable costs ( 50,000/qaly ) . a self - management education program ( x - pert ) and physical activity counseling achieved the best results with 0.10 qalys gained and 99% probability to be very cost - effective ( 20,000/qaly).conclusionsimplementation of lifestyle interventions would probably yield important health benefits at reasonable costs . however , essential evidence for long - term maintenance of health benefits was limited . 
 future research should be focused on long - term effectiveness and multiple treatment strategies should be compared to determine incremental costs and benefits of one over the other .