|Make your diabetic patients walk: long-term impact of different amounts of physical activity on type 2 diabetes
|Di Loreto C, Fanelli C, Lucidi P, Murdolo G, De Cicco A, Parlanti N, Ranchelli A, Fatone C, Taglioni C, Santeusanio F, De Feo P
This is a critical abstract of an economic evaluation that meets the criteria for inclusion on NHS EED. Each abstract contains a brief summary of the methods, the results and conclusions followed by a detailed critical assessment on the reliability of the study and the conclusions drawn.
The health interventions examined in the study were different levels of intensity of an exercise counselling intervention supporting moderate voluntary aerobic physical activity for patients with type 2 diabetes. The counselling intervention consisted of a first counselling session of at least 30 minutes conducted by a physician and designed to advise on physical activity, followed 1 month later by a telephone call made by the same doctor and then by 15-minute sessions every 3 months in the outpatient clinic for a total of seven maintenance visits. The objective of the counselling was to promote increased energy expenditure, defined in terms of metabolic equivalents (METs) per hour per week. Six different levels of intensity of the aerobic physical activity were considered, based on their increments in METs per hour per week: 0 METs, 1-10 METs, 11-20 METs, 21-30 METs, 31-40 METs, more than 40 METs.
Economic study type
The study population comprised patients who had had type 2 diabetes for at least 2 years and who were over 40 years of age. Patients who had illnesses that could seriously reduce life expectancy or cause cardiac, liver, or renal failure were excluded.
The setting was outpatient diabetes clinic. The economic study was carried out in Italy.
Dates to which data relate
Effectiveness and resource use data were gathered from October 1999 and December 2002. The price year was 2000.
Source of effectiveness data
The effectiveness evidence came from a single study.
Link between effectiveness and cost data
The costing was carried out prospectively on the same sample of patients as that included in the effectiveness study.
Power calculations were not performed. Of all consecutive patients attending the authors' outpatient diabetes clinic over a three-month period (October 1999 - January 2000), 182 patients (mean age: 62 +/- 0.7 years; 88 men; diabetes duration: 7.6 +/- 0.3 years) were allocated to the counselling intervention group. Patients were further divided into six groups based on their increments in METs per hour per week: group 0 (no activity, n = 28), group 1-10 (n = 27), group 11-20 (n = 31), group 21-30 (n = 27), group 31-40 (n = 32), and group >40 (n = 34).
Although the original study was a randomised controlled trial, this sub-study can be considered as a case-control study, which was carried out at a single institution, namely the Department of Internal Medicine of the University of Perugia in Italy. Levels of voluntary physical activity were assessed every 3 months with the Modifiable Activity Questionnaire and calculated as the product of the duration (hours times weeks) of the various activities weighted by an estimate of METs of each activity. All patients were asked to record type, intensity, and duration of performed physical activities every day and their reports were examined and discussed with the physician every 3 months. The length of follow-up was 2 years. Three patients did not complete the study: two died of causes unrelated to physical activity, while one patient dropped out of the follow-up. Thus, the final study sample involved the evaluation of 179 patients.
Analysis of effectiveness
The analysis of the clinical study was restricted to those patients who completed the two-year assessment period. The primary outcome measure was the estimated 10-year coronary heart disease (CHD) risk. Secondary end points were body weight, body mass index (BMI), waist circumference, fasting plasma glucose (FPG), HbA1c, systolic and diastolic blood pressure, heart rate, total cholesterol, low-density lipoprotein (LDL) and high-density lipoprotein (HDL) cholesterol, and triglycerides. At baseline, study groups were comparable with respect to age, diabetes duration, male-to-female ratio, and levels of energy expenditure through voluntary physical activity. The impact of changes in METs on changes in clinical outcomes was calculated using linear regressions according to the least-squares method.
In the whole group, there were significant (p<0.0001) reductions in body weight, BMI, waist circumference, FPG, HbA1c, systolic and diastolic blood pressure, heart rate, total and LDL cholesterol, and triglycerides; a significant reduction in 10-year CHD risk (2.7% +/- 1.1%; p<0.01); and a significant (p<0.0001) increase in HDL cholesterol.
The subgroup analysis showed that in groups 0 and 1-10 there was no significant change in any of the parameters.
In group 11-20, there were significant reductions in HbA1c (baseline: 7.7% +/- 0.2%; change: - 0.4% +/- 0.1%; p<0.0001), systolic (baseline: 143.3 +/- 3 mmHg; change: -6.4 +/- 2.4 mmHg; p=0.0286) and diastolic (baseline: 85 +/- 1 mmHg; change: -2.9 +/- 1.6 mmHg; p<0.003) blood pressure, total cholesterol (baseline: 5.6 +/- 0.2 mmol/l; change: -0.3 +/- 0.1 mmol/l; p<0.0001), triglycerides (baseline: 2.4 +/- 0.1 mmol/l; change: -0.5 +/- 0.1 mmol/l; p<0.0001), and 10-year CHD risk (baseline: 22.5% +/- 1.6%; change: -2.6 % +/- 0.6%; p=0.0003).
In group 21-30, there were significant, (p<0.0001), reductions in body weight, BMI, waist circumference, FPG, HbA1c, systolic, (p=0.048), and diastolic, (p=0.0156), blood pressure, heart rate, total and LDL, (p=0.0229), cholesterol, and triglycerides; a significant reduction (3.7% +/- 0.7%; p<0.01) in 10-year CHD risk; and a significant, (p<0.0001), increase in HDL cholesterol.
In groups 31-40 and >40, there were significant, (p<0.0001), reductions in body weight, BMI, waist circumference, FPG, HbA1c, systolic and diastolic blood pressure, heart rate, total and LDL, (p=0.012), cholesterol, and triglycerides; a 4-5% reduction in 10-year CHD risk, (p<0.01); and a significant, (p<0.0001), increase in HDL cholesterol.
Amounts of energy expenditure (METs per hour per week) were inversely related, (p<0.0001), with changes in body weight (r=0.62), BMI (r=0.62), waist circumference (r=0.77), FPG (r=0.52), HbA1c (r=0.70), systolic (r=0.33) and diastolic (r=0.23; p=0.023) blood pressure, resting heart rate (r=0.76), triglycerides (r=0.56), and percent 10-year CHD risk (r=0.39) and positively related with changes in HDL cholesterol (r=0.39, p<0.0001).
The effectiveness analysis showed that higher levels of intensity of voluntary aerobic exercise led to improvements in terms of reduction of CHD risk and in all clinical endpoints. The higher the intensity as measured in METs per hour per week, the greater the improvements in clinical outcomes. In particular, some benefits were achieved with a target of more than 10 METS per hour per week, while full benefits were achieved with more than 20 METs per hour per week.
Measure of benefits used in the economic analysis
Health outcomes were left disaggregated and no summary benefit measure was used in the economic evaluation. In effect, a cost-consequences analysis was carried out.
The analysis of costs was performed from the societal perspective. The following medical direct costs were included: counselling intervention (physician time), laboratory testing, hospitalisation, and outpatient care. In addition, non-medical direct costs were considered including: items related to physical activity (shoes, fitness equipment, etc.), transportation to exercise places, and admission to health clubs. Unit costs were not presented separately from quantities of resources used. Resource consumption was estimated from the sample of patients included in the effectiveness study. Medical costs came from average rates paid by the Italian National Health Service (NHS). The source of other direct costs was not reported. Discounting was not relevant since costs were incurred within a 2-year time period. The price year was 2000.
Statistical analysis of costs
Costs were presented as means +/- standard deviations. Regression analysis was used to assess the significance of the relationship between change in costs and intensity level of physical exercise.
Indirect costs were included as a societal perspective was taken. The time patients spent in practicing physical activity and the time that participants reported as lost from work or usual activities as a result of counselling visits, illness, or injury were included. Unit costs and quantities of resources used were not presented separately. The source of costs was not reported but costs of time might have been set by the authors. Data on resource use were obtained from the sample of patients included in the clinical study. The price year was 2000. Discounting was not relevant and was not performed.
A sensitivity analysis was performed to assess the impact of a less effective counselling intervention. It was assumed that only 50% or 33% diabetic subjects achieved the target of the intervention (>10 METs per hour per week). The number of subjects not reaching the target in the 50% and 33% simulations were equally distributed between groups 0 and 1-10 and equally subtracted from the other four groups.
Estimated benefits used in the economic analysis
Please refer to the effectiveness results reported above.
In the whole group, significant, (p<0.0001) drops in medical and social costs were estimated, for a total saving of $855 ($1,520 +/- $190) per capita per year after 2 years' follow-up.
There was a significant increase in total costs of $828 (baseline costs: $4,253 +/- $289) in group 0, (p<0.05), and an increase of $224 (baseline: $4,116 +/- $311) in group 1-10; there was a significant decrease, (p<0.05), in total costs in all the other groups: -$386 (baseline: $3,767 +/- $235) in group 11-20; -$1,452 (baseline: $4,001 +/- -$280) in group 21-30, -$1,902 (baseline: $4,169 +/- $228) in group 31-40; and -$2,070 (baseline: $4,214 +/- $247) in group >40.
Cost savings declined with a reduced efficacy of the intervention: the 50% compliance scenario led to cost savings of $207 ($362 +/- $52) in the whole group, while the 33% compliance scenario was cost neutral.
The regression analysis showed that costs were significantly, (p<0.0001) related to energy expenditure. METs per hour per week were inversely related with total costs (r=0.60, -$66). Savings due to reduced insulin use were important.
Synthesis of costs and benefits
A synthesis of costs and benefits was not relevant as a cost-consequences analysis was performed.
The authors concluded that physical activity was an effective and cost-saving approach for the management of patients with type 2 diabetes. Patients who achieved energy expenditures of at least 10 METs per hour per week reduced costs of care and the 10-year CHD risk, and improved all other clinical endpoints. However, significant clinical benefits and significant reductions in costs were obtained for an increase of at least 20 METs per hour per week. The counselling intervention remained cost saving even with lower compliance rates.
CRD COMMENTARY - Selection of comparators
The selection of the comparator in the main clinical trial, namely no intervention, was appropriate as it reflects the current pattern of care in several settings. In the current study, different levels of intensity of physical exercise were compared, which might represent the target of the intervention rather than an intervention itself. You should decide whether they are valid comparators in your own setting.
Validity of estimate of measure of effectiveness
The effectiveness evidence came from a case-control study. In effect, patients were allocated to study groups on the basis of the outcome achieved (level of energy expenditure). This type of study is usually associated with some drawbacks, due mainly to the retrospective design and the possible impact of other factors, which might have affected the results of the clinical analysis. It was noted that changes in body composition might have contributed to the observed effect. However, the authors carried out a statistical analysis to assess the impact of the interventions on the main clinical outcomes. Furthermore, the potential bias associated with differences in caloric intake was controlled. The length of follow-up was appropriate and only a limited number of patients were lost to follow-up assessment. The evidence came from a single institution, thus the study sample may not have been representative of the patient population. No justification for the size of the sample was provided, and due to the small number of patients included in the sub-group analysis, it is unclear whether the results obtained were due to the intervention or to chance. These issues tend to reduce the internal validity of the analysis.
Validity of estimate of measure of benefit
No summary benefit measure was used in the analysis because a cost-consequences analysis was conducted. Please refer to the commentary reported above under 'Validity of estimate of measure of effectiveness'.
Validity of estimate of costs
The perspective adopted in the analysis of costs was appropriate since all relevant categories of costs were considered. However, limited information on costs and resource consumption was provided. In effect, unit costs and quantities of resources used were not given separately (with the exception of a few unit costs), which limits the possibility of replicating the analysis in other settings. The source of data was not reported for all items. The impact of variations in cost estimates was not investigated in the sensitivity analysis. Statistical analyses of costs were performed, which enhances the robustness of the cost comparison. The price year was reported, which means that reflation exercises in other time periods will be possible.
The authors stated that their findings confirmed those reported in other studies, although explicit comparisons were not made. The issue of the generalisability of the study results to other settings was not clearly addressed, and few sensitivity analyses were performed. As a result, the external validity of the study was limited. The authors noted that the physical activity counselling model used in their study is simple and reproducible, but requires physician training in the use of the social cognitive approach, which adds costs that were not included in their calculations. The study referred to patients with type 2 diabetes and this was reflected in the authors' conclusions.
Implications of the study
The study results support the need for, and convenience of, instituting physical activity programmes as an essential part of therapy for type 2 diabetes. The analysis also supports the validity of recommendations made by scientific societies in favour of moderate intensity physical activity. The authors state that future studies should be carried out to establish "if type 2 diabetic subjects have individual differences in metabolic responses to regular exercise and the extent to which genetic heterogeneity might affect the variability in training response".
Di Loreto C, Fanelli C, Lucidi P, Murdolo G, De Cicco A, Parlanti N, Ranchelli A, Fatone C, Taglioni C, Santeusanio F, De Feo P. Make your diabetic patients walk: long-term impact of different amounts of physical activity on type 2 diabetes. Diabetes Care 2005; 28(6): 1295-1302
Other publications of related interest
Di Loreto C, Fanelli C, Lucidi P, et al. Validation of a counseling strategy to promote the adoption and the maintenance of physical activity by type 2 diabetic subjects. Diabetes Care 2003; 26:404-408.
Boule N, Haddad E, Kenny G, et al. Effects of exercise on glycemic control and body mass in type 2 diabetes: a meta-analysis of controlled clinical trials. JAMA 2001;286:1218-1227.
Whelthon SP, Chin A, Xin X, He J. Effect of aerobic exercise on blood pressure: a meta-analysis of randomized, controlled trials. Ann Intern Med 2002;136:493-503.
Subject indexing assigned by NLM
Blood Pressure; Body Mass Index; Coronary Disease /epidemiology; Diabetes Mellitus, Type 2 /physiopathology; Energy Metabolism; Exercise; Heart Rate; Hemoglobin A, Glycosylated /analysis; Humans; Lipids /blood; Physical Fitness; Risk; Walking
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Date abstract record published