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Original Investigation |

Quality of Life and Cost-effectiveness of a 3-Year Trial of Lifestyle Intervention in Primary Health Care FREE

Margareta K. Eriksson, PhD; Lars Hagberg, PhD; Lars Lindholm, PhD; Eva-Britt Malmgren-Olsson, PhD; Jonas Österlind, MD; Mats Eliasson, MD, PhD
[+] Author Affiliations

Author Affiliations: Björknäs Health Care Center, Boden, Sweden (Dr Eriksson); Departments of Community Medicine and Rehabilitation (Drs Eriksson and Malmgren-Olsson) and Public Health and Clinical Medicine (Drs Lindholm and Eliasson), Umeå University, Umeå, Sweden; Department of Social Medicine and Public Health, and Centre for Health Care Science, Örebro County Council, Örebro, Sweden (Dr Hagberg); and Department of Medicine, Sunderby Hospital, Luleå, Sweden (Drs Österlind and Eliasson).


Arch Intern Med. 2010;170(16):1470-1479. doi:10.1001/archinternmed.2010.301.
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Published online

Background  Lifestyle interventions reduce cardiovascular risk and risk of diabetes mellitus, but reports on long-term effects on quality of life (QOL) and health care utilization are rare. We investigated the impact of a primary health care–based lifestyle intervention program on QOL and cost-effectiveness over 3 years.

Methods  A total of 151 men and women, aged 18 to 65 years, at moderate to high risk for cardiovascular disease, were randomly assigned to either lifestyle intervention with standard care or standard care alone. Intervention consisted of supervised exercise sessions and diet counseling for 3 months, followed by regular group meetings over a 3-year period. Change in QOL was measured with EuroQol (5-dimensional EuroQol-5D [EQ-5D] and EuroQol-VAS [EQ-VAS]), the 36-Item Short-Form Health Survey (SF-36), and the 6-dimensional Short-Form 6D (SF-6D). The health economic evaluation was performed from a societal view and a treatment perspective. In a cost-utility analysis, the costs, gained quality-adjusted life-years (QALYs), and savings in health care were considered. Cost-effectiveness was also described using the net monetary benefit method.

Results  Significant differences between the groups over the 3-year period were shown in the EQ-VAS ( = .002), SF-6D ( = .01), and SF-36 ( = .04) physical component summary but not in the EQ-5D ( = .24) or SF-36 ( = .37) mental component summary. The net savings were $47 per participant. Costs per gained QALY, savings not counted, were $1668 to $4813. Probabilities of cost-effectiveness were 89% to 100% when the amount of $50 000 was used as stakeholder's threshold of willingness to pay for a gained QALY.

Conclusion  Lifestyle intervention in primary care improves QOL and is highly cost-effective in relation to standard care.

Trial Registration  clinicaltrials.gov Identifier: NCT00486941

Figures in this Article

People who are sedentary have a higher relative risk of mortality than the physically active, and unfit people have a higher risk than fit people.13 Most people in developed countries do not reach the recommended level of physical activity (PA),4 thereby contributing to public health problems.5 Extensive and intensive lifestyle intervention programs delay the onset of diabetes mellitus (DM) and reduce cardiovascular risk by increasing PA, reducing overweight, and making changes in dietary habits.6

Health-related quality of life (QOL) is a patient-centered outcome and incorporates the patient's perspective of physical, mental, and social well-being. Individuals with obesity, DM, and other cardiovascular risk factors, such as hypertension and hyperlipidemia, report diminished well-being and QOL,7,8 whereas being active is associated with a higher QOL.9,10

For a comprehensive assessment of an intervention program it is essential to incorporate the individual's broader perspective of well-being, not only the conventional medical outcomes.11 One recent randomized controlled trial (RCT)12 showed a dose-response effect of PA on both physical and mental aspects of QOL. Otherwise, reports on the long-term effect of programs for increased PA on QOL are rare, inconsistent, and very seldom performed in primary health care.1318 Despite the evidence that health care can promote PA and that it is an effective treatment method, its promotion is rarely used as standard care.

An important factor in the selection of interventions in health care should be the cost-effectiveness compared with competing methods. A systematic review19 found no report concerning cost-effectiveness of PA promotion in primary health care used as a treatment method alongside standard care.

We recently reported a 3-year follow-up on an RCT with lifestyle intervention performed in a primary health care setting.20 It involved a population at moderate-to-high risk for cardiovascular disease and favorably reduced several risk factors. Our hypothesis was that the program improved QOL and was cost-effective.

STUDY DESIGN

A complete description of the Swedish Björknäs study has been published.20 In brief, the study was a 3-year RCT with a control group, which received standard care, and an intervention group, which also received a lifestyle-modification program. All individuals were followed up at 3 months and at 1, 2, and 3 years (Figure 1).

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Figure 1.

Flowchart of participants.

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PARTICIPANTS, RANDOMIZATION, AND BLINDING

The study population was recruited from a primary care center in northern Sweden. Individuals 18 to 65 years old with hypertension, dyslipidemia, type 2 DM, obesity, or any combination thereof, were identified. Individuals with a diagnosis of coronary heart disease, stroke, severe hypertension, and severe psychiatric morbidity were excluded. The 340 eligible individuals were invited by letter, and 177 (52%) agreed to participate. Of those, 18 withdrew before randomization, and an additional 8 met the study's exclusion criteria. A total of 151 enrolled participants were randomly allocated to the intervention group (n = 75) or the control group (n = 76), using a computer-generated random numbers sequence. The allocation was concealed until after the baseline examinations were completed. There was no blinding.

INTERVENTION

The intervention consisted of supervised progressive exercise training 3 times a week and diet counseling on 5 occasions during the first 3 months, followed by regular group meetings. All activities were performed in small groups (n = 10-13). The exercise sessions were led by physiotherapists and consisted of Nordic walking, aqua-aerobics, and interval training on a bicycle ergometer combined with circuit-type resistance training. Each training group was offered 1 session of each activity every week. The diet counseling was in accordance with the Nordic nutrition recommendations and was given both verbal and written by a trained dietician.

After the 3-month active intervention period, participants were invited to attend group meetings on 6 occasions during the first year, on 4 occasions during the second year, and on 2 occasions during the third year. Participants were encouraged to maintain at least 30 minutes/d of PA. The focus was on self-regulatory strategies, such as goal-setting, action planning, and relapse avoidance. Participants were asked to reflect on benefits, barriers, and costs of adherence to a healthier lifestyle.

The control group was given both verbal and written information about exercise and diet at 1 group meeting. Both groups were requested to complete activity logs and continued with their routine care.

OUTCOMES

Primary outcomes were change in QOL measured as the 5-dimensional EuroQol 5D (EQ-5D), the EuroQol visual analog scale (EQ-VAS), and the 6-dimensional Short-Form 6D (SF-6D) based on the self-administrated generic questionnaires EuroQol (EQ) and the 36-Item Short-Form-Health Survey (SF-36); gained QALYs; and change in resource use.

The EQ includes the EQ-5D self-classifier,21 a descriptive system that measures 5 dimensions of health status: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. We computed a single score based on the value tariff from a British population.22 The EQ-VAS records the respondent's perception of overall health status on a 20-cm line graduated from 0 (indicating worst imaginable health) to 100 (indicating best imaginable health). We transformed the EQ-VAS to a 0 to 1 scale by dividing the actual score by 100.

The SF-36 consists of 36 items grouped into 8 domains: physical functioning, limitations in physical role functioning, bodily pain, general health, vitality, social functioning, limitations in emotional role functioning, and mental health.23 Each domain is scored from 0 (worst imaginable health) to 100 (best imaginable health) obtained from the patient's raw scales. Changes greater than 3 to 5 scale points may be clinically relevant.24 The SF-36 physical component summary score and mental component summary score were calculated using the Swedish manual.23 The SF-6D is a utility score derived from responses to 11 questions in the SF-36 questionnaire and consists of 6 dimensions of health.25,26

HEALTH ECONOMIC ANALYSIS METHOD

The analysis in this study was a cost-utility analysis with a societal perspective. Cost-effectiveness ratios were based on gained QALYs and net costs for the intervention group compared with the control group. In the analysis, costs for stakeholder of intervention, patients' costs, treatment effect, and savings in health care use were considered, but not the cost for the participants' exercise time or changes in production.

Health care utilization data were extracted from electronic patient records from all health care centers and hospitals in the county, and were followed from 6 months before the start of the intervention to 3 years after the intervention was started.

Measurements made at baseline and at the follow-ups that were used in the calculation are given in Table 1. All costs were transformed from Swedish currency to US dollars using the exchange rate of 1 US dollar = 7.5 Swedish krona. Costs were recalculated to the price level of 2009 using the Swedish consumer price index. Research costs and costs relating to the development of the method were not included. All changes in effect and costs were discounted 3% per year.

Table Graphic Jump LocationTable 1. Measurement Methods for Variables in the Health Economic Analysis

The uncertainty from the underlying trial was handled with the net monetary benefit (NMB) method,29 which is based on replacing health effects (QALYs) with the amount of money decision makers are willing to pay for a gained quality-adjusted life-year (QALY). When both effects and resource use are expressed in monetary units, it is possible to calculate a 95% confidence interval for cost-effectiveness and the probability that an intervention is cost-effective in relation to a competing intervention.

A gained QALY is calculated from the difference in QOL between the intervention and control groups at the follow-up times. Differences were assumed to develop linearly between follow-up times. For instance, if QOL had increased 0.04 more at 3 months and 0.08 more at 1 year in the intervention group than in the control group, the mean change during the first 3 months would be 0.02 [(0.00 + 0.04)/2] and for the following 9 months it would be 0.06 [(0.04 + 0.08)/2]. Gained QALY for this year would be 0.05 {[(0.02 × 3)/12] + [(0.06 × 9)/12]}.

A scatterplot of 5000 bootstrapped incremental cost-effectiveness ratios was created by repeatedly drawing a random sample with replacement using parameters estimated from the RCT. Individual values were used for savings in health care costs and gained QALY, and mean values were used for costs in intervention and control groups. This produced estimates of the probability that the intervention was cost-effective using several thresholds of willingness to pay for a QALY. Results are presented in a cost-effectiveness acceptability curve.30 Furthermore, mean NMB and 95% confidence intervals of NMB were estimated for these different threshold values.

STATISTICAL ANALYSES

Differences between groups in changes in outcome variables over 3 years were analyzed on an intention-to-treat (ITT) basis. If data were missing, the last observation was carried forward. The general linear model with repeated measures of variance was used to investigate mean changes in QOL over time and overall main effects, testing also for the effects of time and the interaction between group and time. For exploratory reasons, all outcomes were also analyzed per-protocol using only available data and were also adjusted for age and sex. These results did not differ substantially from the unadjusted ITT analysis, which therefore is presented. We used t tests, with Bonferroni correction when needed, for comparison at singular time points.

We calculated a statistical index of responsiveness, effect size, as standardized response mean according to Cohen.31 A change in effect size of 0.2 to 0.5 should be regarded as “small,” greater than 0.5 to 0.8 as “moderate,” and greater than 0.8 as “large.”

A total of 151 individuals were randomized, with the greatest attrition occurring during the first year. The number lost to follow-up did not differ substantially between the groups: 17 in the intervention group and 14 in the control group. Six individuals were excluded: 4 did not start the intervention, and 2 from the control group had incomplete baseline data (Figure 1). Finally, 71 intervention and 74 control participants were included, and the 3-year follow-up was completed by 120 participants (83%).

OUTCOMES AND ESTIMATIONS

The mean age of the study population was 54.4 years, and 57% were female (Table 2). Overweight or obesity was present in 86.8%, and most had 1 or more additional risk factors. An inactive lifestyle was common; 54.5% were sedentary or minimally active, and 84.2% reported no exercise or less than 30 minutes of exercise per day. Smoking, DM, and treatment with lipid-lowering drugs were more common in the intervention group, while hypertensive medication was less common. The intervention groups tended to be less physically active and reported lower mean scores in all QOL questions at baseline.

Table Graphic Jump LocationTable 2. Patient Characteristics at Baselinea

The EQ-5D score and the mental dimensions of the SF-36 were similar to those in the general Swedish population,23,32 whereas the scores for the EQ-VAS and the physical dimensions of the SF-36 were lower (Figure 2). Problems in the pain/discomfort dimension were more common and problems in the anxiety/depression dimension were less common than in the general population of Stockholm32 (Figure 2C).

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Figure 2.

Baseline quality of life in the Björknäs Study Group and Swedish Norm Data.23,32 A, 36-Item Short-Form (SF-36) instrument dimensions. B, EuroQol (EQ) dimensions. C, Proportion problem in EQ dimensions. Error bars represent standard deviations.

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QUALITY OF LIFE

The EQ-5D scores did not change significantly during the 3-year period (see Table 3 for P values). However, the EQ-VAS scores differed significantly between the groups over the 3-year period (P = .002), with greater improvement in the intervention group. The improvement in the SF-6D mean score was higher in the intervention group than in the control group (P = .01).

Table Graphic Jump LocationTable 3. Mean Changes in Quality of Life (QOL) Scores From Baseline to 3 Years in the Swedish Björknäs Studya (Δ Intervention Group − Control Group)

Mean changes in scores and summaries in the SF-36 dimensions are shown in Table 3. Over 3 years an improved physical functioning (P = .02) and less bodily pain (P = .01) were found in the intervention group. The physical component summary improved to a higher degree in the intervention group (P = .04) but not the mental component summary or its subscales.

There were no significant main time effects or interaction effects between time and group for most QOL variables. But in the SF-36 bodily pain dimension, groups were changing in different directions over time, increasing in the intervention group and decreasing in the control group (Table 3). In addition, vitality and social functioning scores showed a significant interaction over time: the intervention group improving and the control group decreasing slightly. The main time effect was significant only for social functioning (P = .005). Calculations of the effect size at the 3-year follow-up showed moderate effects on the EQ-VAS, SF-6D, bodily pain, and physical component summary, and small-to-moderate effects on physical functioning (Table 3).

COSTS

Costs were $337 higher for the intervention group than for the control group: $197 of those costs were financed by health care, and the remaining $140 were costs imposed on the participants owing to increased PA (Table 4). Costs for medical testing, such as serum lipids, glucose, and hemoglobin A1c levels, were $185 per patient and year for both intervention and control groups. (Costs are given in US dollars except where indicated.)

Table Graphic Jump LocationTable 4. Costs per Participant and Changes in Health Care Use 6 Months Before Baseline and During the 3 Years After Starta
GAINED QALY

Gained QALY per participant in the intervention group compared with the control group during the 3 years was 0.08 (P = .24) using the EQ-5D, 0.20 (P < .01) using the EQ-VAS, and 0.07 (P = .03) using the SF-6D (discounted 3% per year).

SAVINGS

The mean number of visits to the family physician in the intervention group decreased by 0.28 per half-year compared with baseline, and increased by 0.10 in the control group (P = .04). For other health care use there were no notable changes between the groups. Savings in family physician visits was $493 for the 3-year period, and savings for all health care use was $384 (P = .44) (Table 4).

COST-EFFECTIVENESS

There were net savings of $47 per participant in the intervention group compared with the control group. Gross costs per gained QALY were $1668 to $4813 using the 3 different QOL scales (Table 5). Using $50 000 as the threshold of willingness to pay for a QALY, the probability of cost-effectiveness is 0.985 using the SF-6D, 0.886 using the EQ-5D, and 0.999 using the EQ-VAS (Figure 3).

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Figure 3.

Probability of cost-effectiveness using the 5-dimensional EuroQol-5D (EQ-5D), EuroQol visual analog scale (EQ-VAS), and 6-dimensional Short-Form 6D (SF-6D) instruments presented in a cost-effectiveness acceptability curve with $0, $10 000, $30 000, $50 000, and $100 000 as value of a quality-adjusted life-year (QALY).

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Table Graphic Jump LocationTable 5. Costs per Gained Quality-Adjusted Life-Year (QALY), Probability of Cost-effectiveness, and Net Monetary Benefit (NMB), Intervention vs Controla

To our knowledge, the Björknäs study demonstrates for the first time that a lifestyle intervention over 3 years, targeted to a population at moderate-to-high risk for CVD, performed in “real life” primary health care, improves QOL and is highly cost-effective. The intervention used the core features of the American Diabetes Prevention Program13 and the Finnish Diabetes Prevention Study33 but was delivered at a conventional primary care setting in northern Sweden, without additional resources. These results should be viewed in the context of the previously reported favorable impact on PA, fitness, waist circumference, waist-to-hip ratio, blood pressure, and smoking cessation over the 3-year period.20 We have not been able to find any previous reports on the effect on QOL or cost-effectiveness of group-based lifestyle interventions in primary health care, focusing on PA with a follow-up over many years.

PA AND QOL

People with obesity and other cardiovascular risk factors have lower QOL,7,8 and obese patients have more problems regarding mobility and pain7 in concordance with our comparison with the Swedish population. Women with higher levels of exercise report higher QOL.34 The causality between higher level of PA and improved QOL was recently confirmed in an RCT with sedentary postmenopausal women, which demonstrated a strong and graded effect of 3 different doses of supervised exercise on QOL over a 6-month period.12 Even a small increase in exercise was associated with improvements in some SF-36 dimensions. The magnitude of improvements in QOL was similar to the results in our study, with better physical and mental health after the initial supervised exercise period. We noted that the mental improvement waned over a longer period, in accordance with other lifestyle interventions.17,18

The effects of PA on QOL in clinical trials are inconsistent, the methods to promote it differ,1316 some studies include only women12 or have short follow-up. “Physical activity on prescription” involves a health professional's written advice to a patient to be more physically active. Some RCTs in primary care, using PA on prescription but not supervised exercise sessions, report no effect on QOL or fitness at a 6-month follow-up,14 or some improvements in QOL after 2 years.16

The ProActive study15 targeted a sedentary population at risk of DM and investigated the effects of a theory-based behavioral intervention. The program taught behavior change and was delivered regularly for 1 year by health professionals by telephone or in participants' homes. The intervention was not more effective than written advice to promote PA or improve fitness but improved some SF-36 scales.

PA AND COST-EFFECTIVENESS

Costs per gained QALY were low ($1668-$4813). When savings in health care were also considered, there were $47 in net savings. The probability for cost-effectiveness using $50 000 per QALY as the threshold for cost-effectiveness was 88.8% to 99.9%. Net monetary benefits for the intervention group were higher than for the control group using the EQ-VAS and SF-6D but not when the EQ-5D was used.

There is no official level of willingness to pay for a gained QALY in the United States, but $50 000 and $100 000 USD are often used. In Great Britain also there is no official level, but the National Institute for Health and Clinical Excellence applies $32 000 to $50 000 as acceptable values, and in Sweden a threshold of $37 500 has been used to guide decisions about subsidized medicine. Thus, the cost-effectiveness of the intervention was good in relation to what Western countries are willing to pay for a QALY, and the probability for cost-effectiveness was very high in this study. Most important for the low cost-effectiveness ratio is the increase in patients' QOL. Higher QOL may also have had an impact on reducing the number of family physician visits, which enhanced good cost-effectiveness.

The main reasons for cost-effectiveness were the sustainable increases in exercise level and QOL compared with the control group. An important aspect in the performance of the intervention method was probably the long-time contact with the participants. Another important aspect was that the group activities generated rather low costs per participant.

STRENGTHS AND WEAKNESSES

The Björknäs study was performed in an ordinary primary care setting, typical of Northern and Western European health care systems, with limited resources. The intervention continued for the whole 3-year period, albeit with tapering of intensity, and attrition was rather low. More than half of those eligible were randomized, in contrast to most major intervention studies,35 which strengthens the internal and external validity. The study population and the number of dropouts did not differ, nor did the size of the group of individuals who declined to participate.20 All data were analyzed conservatively on an ITT basis.

Clinically relevant effect sizes were noted for many, but not all, outcomes, and the use of 2 valid and reliable QOL instruments provided similar results. The study was initially powered for anthropometric measurements, not for QOL, and may thus be too small to detect significant improvements in less responsive scales.

A strength of the health economic analysis is that it is completely based on data from the trial, and only the 3-year follow-up time was considered in the analysis. Hence, no assumptions are needed, except for expenses for PA. The assumed costs represent a common yearly fee at exercise centers in Sweden. If the fee is doubled (from $140 to $280), the costs per gained QALY were still very low: $456 to $1317, instead of $47 in net savings. The main uncertainty is from the underlying trial. This uncertainty is managed according to recommendation from Drummond et al29 when patient-level data are used. The NMB concept is an improvement in dealing with uncertainty compared with using sensitive analysis, especially when insignificant changes between groups are used in the calculation of cost-effectiveness ratios.

The costs for the participants' exercise time were not considered in this analysis. It is a topic concerning loss of enjoyment when exercising. For some individuals, PA may represent a loss of enjoyment, but those who frequently perform PA do not seem to lose enjoyment when spending time on exercise.36 Neither were savings in production considered. In a situation with full employment, such savings may be important, but with significant unemployment, the savings will be restricted to costs of replacing a sick worker with a new one and will be of restricted magnitude.

The actual program and the Diabetes Prevention Program (DPP)13 are 2 of few interventions lasting for 3 years. The DPP was an intense lifestyle program and showed a treatment effect compared with placebo of 0.07 QALY in 3 years, very similar to the findings of the Björknäs study. That program was very costly ($2780 for program holder year 2000), with mostly individual meetings. Costs were more than 10 times higher than for the actual project, which mainly used group meetings, but despite the high costs, the DPP was cost-effective.

Most important for cost-effectiveness is the effect in QALY, but there is no gold standard for a method to estimate QALY. We have used tariffs based on all 3 standard techniques29 (time trade-off, standard gamble, and rating scale), and the valuation of QOL is made by both patients and a general population. We think the result is more convincing when acceptable cost-effective ratios are achieved with different methods.

Probably the cost-effectiveness is even better. Gains in QOL may remain after the 3-year period. The actual analysis had only a treatment perspective, but there were also preventive effects against cardiovascular diseases and type 2 DM.20 Several lifestyle interventions have shown good cost-effectiveness from only a preventive perspective for similar patient groups.19 Furthermore, the results are likely to be an underestimate because the control group received more promotion of healthy lifestyle than is generally common in primary health care.

Thus, high-intensity and long-lasting interventions can produce sustainable improvements in QOL and can obviously be cost-effective. Such programs may be a wise use of resources in primary health care for patients with diseases to which inactivity strongly contributes.

Correspondence: Margareta K. Eriksson, PhD, Björknäs Health Care Center, Idrottsgatan 3, 961 64 Boden, Sweden (Margareta.eriksson@nll.se).

Accepted for Publication: March 17, 2010.

Author Contributions: Dr Eliasson had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Eriksson, Lindholm, Malmgren-Olsson, and Eliasson. Acquisition of data: Eriksson and Österlind. Analysis and interpretation of data: Eriksson, Hagberg, Lindholm, Malmgren-Olsson, and Eliasson. Drafting of the manuscript: Eriksson, Malmgren-Olsson, and Eliasson. Critical revision of the manuscript for important intellectual content: Eriksson, Hagberg, Lindholm, Malmgren-Olsson, Österlind, and Eliasson. Statistical analysis: Eriksson, Hagberg, and Malmgren-Olsson. Obtained funding: Eriksson, Malmgren-Olsson, and Eliasson. Administrative, technical, and material support: Eriksson and Malmgren-Olsson. Study supervision: Hagberg, Lindholm, Malmgren-Olsson, and Eliasson.

Financial Disclosure: None reported.

Funding/Support: This study was supported by the Norrbotten Local County Council, Division of Primary Health Care, Luleå, Sweden; Visare Norr, Northern County Councils, Sweden; and the Heart Foundation of Northern Sweden.

Role of the Sponsor: The sponsors had no role in the design or conduct of the study; the collection, management, analysis, or interpretation of the data; or the preparation, review, or approval of the manuscript.

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Sullivan  MKarlsson  JWare  JE  Jr The Swedish SF-36 Health Survey, I: evaluation of data quality, scaling assumptions, reliability and construct validity across general populations in Sweden. Soc Sci Med 1995;41 (10) 1349- 1358
PubMed Link to Article
Samsa  GEdelman  DRothman  MLWilliams  GRLipscomb  JMatchar  D Determining clinically important differences in health status measures: a general approach with illustration to the Health Utilities Index Mark II. Pharmacoeconomics 1999;15 (2) 141- 155
PubMed Link to Article
Brazier  JRoberts  JDeverill  M The estimation of a preference-based measure of health from the SF-36. J Health Econ 2002;21 (2) 271- 292
PubMed Link to Article
Kharroubi  SBrazier  JEO'Hagan  A Modelling covariates for the SF-6D standard gamble health state preference data using a nonparametric Bayesian method. Soc Sci Med 2007;64 (6) 1242- 1252
PubMed Link to Article
EuroQol Group, EuroQol: a new facility for the measurement of health-related quality of life. Health Policy 1990;16 (3) 199- 208
PubMed Link to Article
Dolan  PGudex  CKind  PWilliams  A A social tariff for EuroQol: results from a UK general population survey. Discussion Paper No. 138 York, England Centre for Health Economics, University of York1995;1- 24
Drummond  MFSchulper  MJTorrance  GW Methods for the Economic Evaluation of Health Care Programmes. 3rd ed. Oxford, England Oxford University Press2005;
van Hout  BAAl  MJGordon  GSRutten  FF Costs, effects and C/E-ratios alongside a clinical trial. Health Econ 1994;3 (5) 309- 319
PubMed Link to Article
Cohen  J Statistical Power Analysis for the Behavioural Sciences. 2nd ed. Mahwah, NJ Lawrence Erlbaum Associates1988;
Burström  KJohannesson  MDiderichsen  F Health-related quality of life by disease and socio-economic group in the general population in Sweden. Health Policy 2001;55 (1) 51- 69
PubMed Link to Article
Lindgren  PLindstrom  JTuomilehto  J  et al. DPS Study Group, Lifestyle intervention to prevent diabetes in men and women with impaired glucose tolerance is cost-effective. Int J Technol Assess Health Care 2007;23 (2) 177- 183
PubMed Link to Article
Fine  JTColditz  GACoakley  EH  et al.  A prospective study of weight change and health-related quality of life in women. JAMA 1999;282 (22) 2136- 2142
PubMed Link to Article
Ruge  TNystrom  LLindahl  B  et al.  Recruiting high-risk individuals to a diabetes prevention program: how hard can it be? Diabetes Care 2007;30 (7) e61
PubMed Link to Article
Hagberg  L Cost-effectiveness of the promotion of physical activity in health care [medical dissertation].  Umeå, Sweden Umeå Universitet2007;

Figures

Place holder to copy figure label and caption
Figure 1.

Flowchart of participants.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.

Baseline quality of life in the Björknäs Study Group and Swedish Norm Data.23,32 A, 36-Item Short-Form (SF-36) instrument dimensions. B, EuroQol (EQ) dimensions. C, Proportion problem in EQ dimensions. Error bars represent standard deviations.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 3.

Probability of cost-effectiveness using the 5-dimensional EuroQol-5D (EQ-5D), EuroQol visual analog scale (EQ-VAS), and 6-dimensional Short-Form 6D (SF-6D) instruments presented in a cost-effectiveness acceptability curve with $0, $10 000, $30 000, $50 000, and $100 000 as value of a quality-adjusted life-year (QALY).

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Measurement Methods for Variables in the Health Economic Analysis
Table Graphic Jump LocationTable 2. Patient Characteristics at Baselinea
Table Graphic Jump LocationTable 3. Mean Changes in Quality of Life (QOL) Scores From Baseline to 3 Years in the Swedish Björknäs Studya (Δ Intervention Group − Control Group)
Table Graphic Jump LocationTable 4. Costs per Participant and Changes in Health Care Use 6 Months Before Baseline and During the 3 Years After Starta
Table Graphic Jump LocationTable 5. Costs per Gained Quality-Adjusted Life-Year (QALY), Probability of Cost-effectiveness, and Net Monetary Benefit (NMB), Intervention vs Controla

References

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Haskell  WLLee  IMPate  RR  et al. American College of Sports Medicine; American Heart Association, Physical activity and public health: updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Circulation 2007;116 (9) 1081- 1093
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Martínez-González  MAVaro  JJSantos  JL  et al.  Prevalence of physical activity during leisure time in the European Union. Med Sci Sports Exerc 2001;33 (7) 1142- 1146
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Sach  THBarton  GRDoherty  MMuir  KRJenkinson  CAvery  AJ The relationship between body mass index and health-related quality of life: comparing the EQ-5D, EuroQol VAS, and SF-6D. Int J Obes (Lond) 2007;31 (1) 189- 196
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Wolin  KYGlynn  RJColditz  GALee  IMKawachi  I Long-term physical activity patterns and health-related quality of life in U.S. women. Am J Prev Med 2007;32 (6) 490- 499
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Garratt  ASchmidt  LMackintosh  AFitzpatrick  R Quality of life measurement: bibliographic study of patient assessed health outcome measures. BMJ 2002;324 (7351) 1417
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Diabetes Prevention Program Research Group, Within-trial cost-effectiveness of lifestyle intervention or metformin for the primary prevention of type 2 diabetes. Diabetes Care 2003;26 (9) 2518- 2523
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Grandes  GSanchez  ASanchez-Pinilla  RO  et al. PEPAF Group, Effectiveness of physical activity advice and prescription by physicians in routine primary care: a cluster randomized trial. Arch Intern Med 2009;169 (7) 694- 701
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Kinmonth  ALWareham  NJHardeman  W  et al.  Efficacy of a theory-based behavioural intervention to increase physical activity in an at-risk group in primary care (ProActive UK): a randomised trial. Lancet 2008;371 (9606) 41- 48
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Lawton  BARose  SBElley  CRDowell  ACFenton  AMoyes  SA Exercise on prescription for women aged 40-74 recruited through primary care: two year randomised controlled trial. BMJ 2008;337a2509
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Ackermann  RTEdelstein  SLNarayan  KM  et al. Diabetes Prevention Program Research Group, Changes in health state utilities with changes in body mass in the Diabetes Prevention Program. Obesity (Silver Spring) 2009;17 (12) 2176- 2181
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Williamson  DARejeski  JLang  WVan Dorsten  BFabricatore  ANToledo  KLook AHEAD Research Group, Impact of a weight management program on health-related quality of life in overweight adults with type 2 diabetes. Arch Intern Med 2009;169 (2) 163- 171
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Hagberg  LALindholm  L Cost-effectiveness of healthcare-based interventions aimed at improving physical activity. Scand J Public Health 2006;34 (6) 641- 653
PubMed Link to Article
Eriksson  MKFranks  PWEliasson  M A 3-year randomized trial of lifestyle intervention for cardiovascular risk reduction in the primary care setting: the Swedish Björknäs study. PLoS One 2009;4 (4) e5195
PubMed Link to Article
Rabin  Rde Charro  F EQ-5D: a measure of health status from the EuroQol Group. Ann Med 2001;33 (5) 337- 343
PubMed Link to Article
Dolan  P Modeling valuations for EuroQol health states. Med Care 1997;35 (11) 1095- 1108
PubMed Link to Article
Sullivan  MKarlsson  JWare  JE  Jr The Swedish SF-36 Health Survey, I: evaluation of data quality, scaling assumptions, reliability and construct validity across general populations in Sweden. Soc Sci Med 1995;41 (10) 1349- 1358
PubMed Link to Article
Samsa  GEdelman  DRothman  MLWilliams  GRLipscomb  JMatchar  D Determining clinically important differences in health status measures: a general approach with illustration to the Health Utilities Index Mark II. Pharmacoeconomics 1999;15 (2) 141- 155
PubMed Link to Article
Brazier  JRoberts  JDeverill  M The estimation of a preference-based measure of health from the SF-36. J Health Econ 2002;21 (2) 271- 292
PubMed Link to Article
Kharroubi  SBrazier  JEO'Hagan  A Modelling covariates for the SF-6D standard gamble health state preference data using a nonparametric Bayesian method. Soc Sci Med 2007;64 (6) 1242- 1252
PubMed Link to Article
EuroQol Group, EuroQol: a new facility for the measurement of health-related quality of life. Health Policy 1990;16 (3) 199- 208
PubMed Link to Article
Dolan  PGudex  CKind  PWilliams  A A social tariff for EuroQol: results from a UK general population survey. Discussion Paper No. 138 York, England Centre for Health Economics, University of York1995;1- 24
Drummond  MFSchulper  MJTorrance  GW Methods for the Economic Evaluation of Health Care Programmes. 3rd ed. Oxford, England Oxford University Press2005;
van Hout  BAAl  MJGordon  GSRutten  FF Costs, effects and C/E-ratios alongside a clinical trial. Health Econ 1994;3 (5) 309- 319
PubMed Link to Article
Cohen  J Statistical Power Analysis for the Behavioural Sciences. 2nd ed. Mahwah, NJ Lawrence Erlbaum Associates1988;
Burström  KJohannesson  MDiderichsen  F Health-related quality of life by disease and socio-economic group in the general population in Sweden. Health Policy 2001;55 (1) 51- 69
PubMed Link to Article
Lindgren  PLindstrom  JTuomilehto  J  et al. DPS Study Group, Lifestyle intervention to prevent diabetes in men and women with impaired glucose tolerance is cost-effective. Int J Technol Assess Health Care 2007;23 (2) 177- 183
PubMed Link to Article
Fine  JTColditz  GACoakley  EH  et al.  A prospective study of weight change and health-related quality of life in women. JAMA 1999;282 (22) 2136- 2142
PubMed Link to Article
Ruge  TNystrom  LLindahl  B  et al.  Recruiting high-risk individuals to a diabetes prevention program: how hard can it be? Diabetes Care 2007;30 (7) e61
PubMed Link to Article
Hagberg  L Cost-effectiveness of the promotion of physical activity in health care [medical dissertation].  Umeå, Sweden Umeå Universitet2007;

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