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Open AcceResearch articleCost-utility of a walking programme for moderately depressed, obese, or overweight elderly women in primary care: a randomised controlled trialNarcis Gusi*1, Maria C Reyes1, Jose L Gonzalez-Guerrero2, Emilio Herrera3 and Jose M Garcia3
Address: 1Faculty of Sports Sciences, University of Extremadura, Cáceres, Spain, 2Geriatric Unite, Hospital of Cáceres, Cáceres, Spain and 3Health System of Extremadura, Junta de Extremadura, Mérida, Spain

Email: Narcis Gusi* - [email protected]; Maria C Reyes - [email protected]; Jose L Gonzalez-Guerrero - [email protected]; Emilio Herrera - [email protected]; Jose M Garcia - [email protected]

* Corresponding author

AbstractBackground: There is a considerable public health burden due to physical inactivity, because it isa major independent risk factor for several diseases (e.g., type 2 diabetes, cardiovascular disease,moderate mood disorders neurotic diseases such as depression, etc.). This study assesses the costutility of the adding a supervised walking programme to the standard "best primary care" foroverweight, moderately obese, or moderately depressed elderly women.

Methods: One-hundred six participants were randomly assigned to an interventional group (n =55) or a control group (n = 51). The intervention consisted of an invitation, from a generalpractitioner, to participate in a 6-month walking-based, supervised exercise program with three 50-minute sessions per week. The main outcome measures were the healthcare costs from the HealthSystem perspective and quality adjusted life years (QALYs) using EuroQol (EQ-5D.)

Results: Of the patients invited to participate in the program, 79% were successfully recruited, and86% of the participants in the exercise group completed the programme. Over 6 months, the meantreatment cost per patient in the exercise group was €41 more than "best care". The meanincremental QALY of intervention was 0.132 (95% CI: 0.104–0.286). Each extra QALY gained bythe exercise programme relative to best care cost €311 (95% CI, €143–€394). The costeffectiveness acceptability curves showed a 90% probability that the addition of the walkingprogramme is the best strategy if the ceiling of inversion is €350/QALY.

Conclusion: The invitation strategy and exercise programme resulted in a high rate ofparticipation and is a feasible and cost-effective addition to best care. The programme is a cost-effective resource for helping patients to increase their physical activity, according to therecommendations of general practitioners. Moreover, the present study could help decisionmakers enhance the preventive role of primary care and optimize health care resources.

Trial Registration: [ISRCTN98931797]

Published: 8 July 2008

BMC Public Health 2008, 8:231 doi:10.1186/1471-2458-8-231

Received: 30 October 2007Accepted: 8 July 2008

This article is available from: http://www.biomedcentral.com/1471-2458/8/231

© 2008 Gusi et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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BackgroundPhysical inactivity is a considerable public health burden,because it is a major independent risk factor for severaldiseases (e.g., type 2 diabetes, cardiovascular disease,moderate mood disorders neurotic diseases such asdepression, etc.) [1,2]. It is also associated with a highprevalence of musculoskeletal disorders [3]. Moderatedepression and being overweight are among the mostcommon and expensive public health problems and lead-ing reasons for consultation in primary care [4,5]. A largeproportion of health care resources – including office vis-its, hospitalisation, and medication – are required by theelderly.

General practitioners usually recommend increasingphysical activity because even such moderate increaseshave been shown to improve the quality of life in olderadults [6,7] and elderly are interested in sports, walkingand health [8]. However, rates of physical inactivity aresubstantial in elderly women [9-12]. Therefore, physicalactivity should be promoted, especially in elderly popula-tions. The National Institute for Health and Clinical Excel-lence (NICE) of the United Kingdom established the needto study the clinical- and cost-effectiveness of pedometersand exercise referrals because there is limited evidence torecommend these interventions based on studies of walk-ing and cycling, especially in trials longer than 12 weeks[13]. Bjorgaas et al. recently reported that the use of a ped-ometer with weekly monitoring by nurses is effective inphysically active patients with diabetes mellitus, but thisactivity was not sustained in relatively inactive patientswith diabetes mellitus type 2 [14].

Traditional community-based exercise referral schemesinvolve referral from a primary care practitioner to a 10–12 week exercise programme run by local leisure services.These programmes succeed in the short-term [15,16] butare limited in terms of sustainability and impact on healthoutcomes [15]. From a health economics perspective, justthe assessment and advice from an exercise specialist maybe appropriate to initiate action. However, the mainte-nance of increased activity requires further support (tech-nical or societal support by phone or peers). This needwas demonstrated in a study that showed that the propor-tion of participants who maintained an active lifestylethree months after the cessation of 10-week programmesranged between 7.5% in the advice-only group and 11–14% in the leisure centre group or walking group [17].Walking appears to be as effective as leisure centre classesand is less expensive [17] but there is a lack of knowledgeabout walking programmes, especially those that addstrengthening and stretching exercises. Wormald et al.[18] indicated that the success of the service was highlydependent upon the exercise advisor and that traditionalschemes should be broadened to encompass everyday

lifestyle activities. However, as health system resources arelimited, the decision-maker frequently selects the strate-gies adopted based on the lowest cost per quality-adjustedlife-years (QALY). Cost utility is the ratio of incrementaleffectiveness of one strategy compared to another (e.g.,standard medical practice) measured in QALYs divided bythe incremental cost.

The cost and effectiveness of the patient recruitment strat-egy are among the most relevant determinants of the costutility of physical activity promotion. However, furtherresearch on recruitment from practice-based populationsis required [19,20]. In addition, among the few cost-utilityanalyses of exercise interventions in primary care, mostinvolved patients younger than 60 years of age who suf-fered heart disease or back pain. Thus, the effectiveness ofexercise programmes with overweight or moderatelydepressed, elderly females remains largely unknown.

The purpose of this study was to assess the cost utility ofadding to the standard "best care" a supervised walkingprogramme that also included strengthening and stretch-ing exercises The patients involved were elderly femaleswho were overweight or moderately depressed.

MethodsRecruitmentFour general practices in Cáceres (Spain) were recruited toparticipate in the study. Practices were selected at random,from those with two to five partners, and these practiceswere not previously conducting an exercise programme orexercise prescription scheme. Of five general practicesapproached, four agreed to participate. The distancesbetween practices allowed the grouping of participantsinto two exercise groups.

The population of the catchment area comprised elderlywomen who consulted one of the family physicians whopracticed in one of four public primary care centres partic-ipating in this study. Eligible women were aged 60 yearsand older, suffered from either moderate depression orwere overweight, and were capable of walking for morethan 25 minutes. Women who scored 6 to 9 points in the15-item Geriatric Depression Scale were considered mod-erately depressed [21]. Women who had a body massindex (BMI) of 25 to 39.9 kg/m2 were considered over-weight (overweight or obese type I or II). Patients wereexcluded if they had poor health (severe obesity or majordepression), a debilitating medical condition or a knownunstable cardiac condition, attention or comprehensionproblems (e.g., Alzheimer's, apraxia, global aphasia, andother types of dementia or psychopathology), or theintention of leaving the region. No patients were excludedfollowing enrolment.



Physicians advised eligible women on the walking pro-gramme, called "Exercise Looks After You", as part of acomplete health, fitness and nutritional assessment. Infact, the participating physicians previously included gen-eral advice in their routine so the additional time andeffort required was kept to a minimum because of thepractitioners' busy schedules. All participants providedinformed consent in writing, and the study was approvedby the Bioethics Committee of the University according tothe Declaration of Helsinki.

Study designMedical practitioners spent 2 weeks at each practice refer-ring patients to researchers. A research assistant, who didnot participate in the current investigation, randomisedparticipants to either an intervention group or controlgroup, according to a random numbers table. The flow-chart of participants is presented in Figure 1. Consistently,

medical practitioners did not know which group patientswere randomised to prior to their exercise referral, andthey did not interact with the research team throughoutthe trial. Researchers evaluated participants at baselineand after the 6-month programme.

InterventionsTwo alternatives: best care in general practice and theaddition of a walking programme were compared. Theresearch group educated practice teams in "active manage-ment" by identifying eligible patients and giving exerciseadvice.

Exercise programmeThis intervention was a walking programme that con-sisted of supervised walks with a group in a public park orforest tracks. The qualified exercise leaders had expertisein fitness testing and the supervision of physical activity ingroups, and had been graduated from university programsin sport sciences. These leaders instructed and trained theintervention group for 50 minutes, three times per weekover a 6-month period. Each session consisted of walkingalternating with specific exercises, as follows: 5 minutes ofjoint mobility (8–12 easy rotations at the neck, shoulder,hip and ankle and 8–12 easy flexion-extensions of theknee, wrist and elbow); 15 minutes of brisk-walking; 5minutes of strengthening (8–12 flexion-extension of armsagainst a wall, 8–12 spine flexion with elevation of alter-nating knees, in a standing position) and stretching (ham-strings and shoulders [trying to touch the fingers on theupper-back]); 20 minutes of brisk-walking including 20foot-steps and 50 hand-claps to provide additionalmechanical impact. In addition, simple nutritional advicewas provided. The technicians' schedule included 10hours per week from Monday to Friday. This programmewas designed without reference to any explicit behav-ioural model or theory; rather, it was intended as a prag-matic intervention that could be easily organised for alarge population by a public health agency. The leaderneither recommended nor advised against practicebetween sessions. Socialising within the group wasencouraged.

Control groupPatients in the control group received the best care in gen-eral practice, which consisted of routine care and a recom-mendation of physical activity. These participants in thecontrol group underwent fitness testing by the researchteam.

Data collectionParticipants completed questionnaires, including the EQ-5D health status instrument [22] at the beginning of theprogramme and after the 6-month programme. Over thesame period, health care was recorded, including hospitalstays, drug usage, secondary care, primary care and physi-cal therapist visits; health care from private resources andwithin the National Health System was recorded.

Unit costsParticipants were retired and living close to practices, andwere recruited in a previously arranged consultation with-out considering the current project; thus, we decided toperform an economic analysis from the health service per-spective. This decision was based on the assumption thatmarginal societal costs were negligible (there were noadditional costs of displacement, and participants did notlose work-hours). In fact, this analysis were recommended

Flow-chart of participants throughout trialFigure 1Flow-chart of participants throughout trial.

Assessed for eligibility (N=160); Addressed by General Practitioners

Allocated to exercise group, n=64Received exercise program, n=64

Allocated to control group, n=63Received control program, n=63

Lost to follow n=9Low attendance:-Care of relative=7-Lack of interest=2

Excluded, n=32- Lost =20- Refused to participate=12

127 randomized

Completed the program, n=55Included in analysis, n=55

Completed the program, n=51Included in analysis, n=51

Lost to follow n=12-Lack of interest=12

Allocation

Follow-up

Analysis

Enrollment



by NICE to contribute to health policy for an expensivecondition. The unit costs are expressed in Euros at 2005prices. Participants' follow-up periods were between Janu-ary and July of the same year. Costs were not adjusted ordiscounted, as we solely focused on effects over a 6-monthperiod. The cost of the programme was based on the sal-ary of a graduate in sports science in health promotion;this salary was published in the official 2005 bulletin ofthe regional government. The cost of the programme didnot include other possible costs because the clinical anal-ysis did not show statistically significant changes in theuse of the National Health System (medication, consulta-tion, etc.) and there was no difference between groupsregarding assessment and advice from a physician. Inaddition, we did not hire any facility (but used publicparks or forest tracks), and the recruitment did not requireany additional time by the practitioner.

Health outcomesThe EQ-5D [22] was used to assess five dimensions ofhealth related quality of life (HRQOL): (1) mobility; (2)self-care; (3) daily activities; (4) pain and discomfort; and(5) anxiety or depression. The scale of dimensions is from1 to 3 (no problems, some problems, or extreme prob-lems). Using a combination of these dimensions, a totalof 243 possible health states exist. Each health state hasbeen previously defined using the time trade-off methodof utility analysis based on the response of a sample of theSpanish population [23]. This total score of utility wasscaled from 1 = a fully functional quality of life to 0 =death. The QALYs that the participants experienced overthe 6-month period was estimated by calculating "areasunder (health utility) curves" [24]. To avoid bias, datawere adjusted for differences in baseline EQ-5D scores byregression analysis [25]. The State-Trait Anxiety Inventory(STAI) [26], was used to evaluate anxiety by using 20items with a scale of 0 to 3. The Trait Anxiety index is thesum of these 20 scores expressed as a percentage. The fifthquestionnaire, the Geriatric Depression Scale [27],includes 15 questions to evaluate the level of depressionfrom 0 (no depression) to 15 (the worst level of depres-sion). A score of 5 or higher indicates the presence ofdepression.

Sample sizeThe primary outcome was the EQ-5D utility. The requiredsample size was calculated with the Spanish EQ-5D dataset for a hypothetical study comparing two groups with asignificance level alpha (0.05) and 80% of the powerneeded for a minimal clinically relevant difference of 0.1[28]. The required sample ranges between 60 participantsextracted from general population and 100 extracted fromcritically ill participants. We selected at least 120 partici-pants to exceed the higher number by 20%, thus allowingfor potential drop-outs.

Statistical analysisThe statistical analysis was performed by researchers whohad not participated in the data collection or implemen-tation of the exercise programme. Normality of data wasinitially tested using the Kolgomorov-Smirnov test usingthe correction of Lillifors. The effects of programme onanxiety, depression and Body Mass Index were testedusing analyses of variance (ANOVA) for continuous vari-ables. Age-adjusted analyses of covariance were used tocompare, between the groups, the changes in measuredvariables over time (from the beginning of the pro-gramme to 6 months). For all tests the significance levelwas set at p < .05. The analyses were done using SPSS 15.0(SPSS Inc. Chicago, USA).

Cost utility analysisMost of the participants who dropped out declined to betested after the period of intervention, so the researchteam performed a non-intent-to-treat analysis. We firstestimated the incremental mean costs of the programmeand the mean QALYs gained by the two treatment alterna-tives. Secondly, the incremental cost effectiveness ratio forthe intervention was calculated by dividing the incremen-tal costs by incremental QALYs.

To report the uncertainty due to sampling variation, wecalculated the 95% confidence interval (CI) using thenon-parametric bootstrapping technique (1000 replicatesre-sampled with replacement from treatment and controlpopulations) and plotted a cost effectiveness acceptabilitycurve [29,30]. This curve estimates the probability that theintervention is cost effective compared with the alterna-tive, across the range of values that decision makers pay toachieve an additional QALY. The "investment ceiling" isthe level of spending that should not be exceeded, evenassuming unlimited funding. For the health care system inSpain, the 2005 adjusted investment ceiling was set at34729/QALY [31]. Decision makers should compare this

upper limit of acceptable payment with estimated incre-mental cost effectiveness ratios to determine whether agiven treatment is cost effective relative to the alternatives.

In addition, two cost effectiveness acceptability curveswere plotted to compare the following three differentalternatives or scenarios with certain variables manipu-lated: (A) best care, followed by exercise plus fitness andhealth assessment at the Physical Activity Unit; (B) bestcare followed by the worst case scenario (in terms of sal-ary, rate of participation, and efficacy); (C) the walkingprogramme.

Four sensitivity analyses were performed to explore therobustness of estimations and how dependent the resultswere on estimates of unit costs per participant and effi-cacy. The first analysis examined the influence of the rate



of participation in the programme since this could influ-ence the technician's "productivity" based on the numberof participants per unit of time provided by the techni-cian. The second analysis estimated the cost of adding apermanent timetable of consultation, assessment orrecruitment provided by the technician. To randomise allparticipants, the present trial only recruited participantsprior to the beginning of the exercise programme; how-ever, the widespread implementation of the programmewould probably require permanent consultation. We esti-mated that exercise advisor schedule should increase 5hours per week to attend the participants and new candi-dates to join the programme.

A third analysis explored the variations due to the salarychanges of the technician since such changes are a majorsource of variability in economic studies [32].

Finally, the robustness of cost effectiveness was examinedby exploring scenarios combining the influence of the var-iations in salary, rate of participation, and effectivenessfrom the lowest to the highest limit of the 95% CI.

ResultsResponseSeventy-nine percent (127/160) of patients identified bygeneral practitioners were recruited, but 20 of referredpatients did not follow this referral; they were lost to fol-low-up or did not come to the research laboratory (Fig. 1).Eighty-six percent (55 of 64) of the participants in thewalking group completed the programme. Fifteen to 22patients attended each exercise group. At baseline, theintervention group was slightly less depressed, less over-weight and younger than the control group, but these dif-

ferences were not statistically significant (p > .05) (Table1). The participants who were lost to follow-up (mainlybecause they had to care for a relative) were similar tothose who completed the trial but a slightly higher per-centage of them were moderately depressed. The partici-pants in the control group who dropped out were similarto those who followed the trial but they were mainly liv-ing in an urban area. The social network in the rural areawas stronger. Anxiety and depression, as measured by theEQ-5D, STAI and Geriatric Depression Scale, improved inthe intervention group and mean BMI decreased (BMImean change 1.2%; p = .003); these measures in the con-trol group remained unaltered for the most part (Table 2).

CostsThe incremental cost of adding the exercise programme(Table 3), 2250, was related to the salary of the techni-cian (10 hours per week; 25% of the total salary) over a 6-month period. Therefore, the mean incremental cost perparticipant, integrated in a group smaller than 30 partici-pants, who attended three of the five available sessionsper week, was 41.

Health outcome and cost utility analysisThe interventional group improved more QALYs than thecontrol group (Table 4) being adequate to perform a costutility analysis. Each additional QALY gained by the exer-cise group cost less than 400. The cost effectivenessacceptability curves (Fig. 2) showed a 99.9% probabilitythat the addition of the walking programme is an accept-able strategy if the ceiling of inversion is 600/QALY.

Table 1: Baseline characteristics of patients allocated exercise programme or best care.

Characteristics ExerciseCompletedFollow up

Best CareCompletedFollow up

ExerciseLost to

Follow up

Best CareLost to

Follow up

N 55 51 9 12Age (years) 71(5) 74 (6)Living in rural areas (%) 67 65 67 33Living alone (%) 24 18 22 17Education, primary school or higher (%) 40 37 44 33Income (€/month), (%):

less than 360 4 3 11 0360 to 600 89 91 89 92more than 600 7 6 0 8

Daily smoking (1 or more cigarette/day) 1 0 0 0Daily alcohol consumption (%) 11 4Physical activity standardised (%) 0 0 0 0Overweight (%) 80 86 78 83BMI 29.7 (4.2) 30.6 (4.3)Diabetes mellitus type II (%) 40 39 33 25Moderate depressed (%) 33 39 44 33



Sensitivity analysisThe sensitivity analyses are presented in Table 5. The firstanalysis manipulated the number of participants andtheir distribution in groups attended by the technician.This analysis showed a variation of cost-utility ratio from311 to 462/QALY. In the second analysis, the predicted

cost-utility of adding 5 hours per week, to assess andrecruit new participants, was 462/QALY. The third sensi-tivity analysis focused on salary since this is a majorsource of cost variation related to location. If the salarywas doubled the cost utility ratio was 621/QALY. Thefourth analysis presented the best scenario or combina-tion of the previously cited variables and the worst sce-nario. The estimated cost utility ratio ranged between 94/QALY of the best scenario and 871/QALY of the worstscenario.

DiscussionPrincipal findingsThe present study demonstrated that practitioners' exer-cise advice and the walking-programme efficientlyenhanced the health-related quality of life in a high riskpopulation, overweight or moderately depressed elderlywomen. This efficiency was based upon low-cost; how-ever, a high recruitment rate was obtained by combiningthe medical advice of practitioners with the supervision ofan exercise monitor.

Strengths and weaknessTo our knowledge, the current study is the first cost utilityanalysis of a walking exercise intervention with elderlyfemales in primary care. It differed from traditional exer-cise referral schemes in that the physical activity advisorswere specifically trained and employed for this pro-gramme [18]. In addition, walking, as well as strengthen-ing and stretching exercises were used to enhance thefeasibility of the programme in different environments.The most comparable study, by Munro et al. [33], ana-lysed the cost utility of a strategy based on a letter from theresearch team inviting physically untrained persons olderthan 65 years of age to attend locally organised, free, twiceweekly, exercise classes for 2 years. That study was con-ducted in Great Britain and the authors reported an incre-mental cost of 17174/QALY gained, using the utilityindex from the SF-36 and a mean cost per attendee per ses-sion of 9.1. In the present study we calculated an incre-mental cost of 311/QALY and 0.5/attendee per session.The differences between the study by Munro et al. and ourstudy may be partly explained by: (a) the lower initialQALY in our population; (b) the gender of participants,who were predominantly female in the Munro study butexclusively female in our study; (c) the lengths of the pro-grammes (2 years in the Munro study and 6 months in ourstudy); and (d) the greater expense of the recruitmentstrategy of Munro et al. However, the impact of differencesin programme length may (c, above) may have been min-imized because most of the QALY increments in the

Table 3: Incremental cost of the exercise programme compared to usual care.

Concept unit* over 6 months (€) Total (€)

Health system costsPersonnel†

sport technician (25 weeks) 9 €/hour 2250Facilities (renting) 0 €/hour 0Medication (no mean change were observed) Drug price 0Consultation (no mean change were observed) Official price 0Total health system perspective 2250

. *Public cost in Euro in 2005.† There is no marginal cost of adding or dropping-out participants in groups up to 30 persons.

Table 2: Health outcomes of the exercise programme compared to usual care

Health outcome Group Baseline Six months p*

Body Mass Index (kg·m-2) exercise 29.7 (4.2) 29.4 (4.2) .003Control 30.6 (4.3) 30.8 (4.3)

Depression by Geriatric Depression Scale Exercise 2.3 (2.5) 1.8 (2.3) .001Control 2.6 (2.5) 2.9 (2.5)

Anxiety by State Trait Anxiety Inventory exercise 19.2 (11.2) 14.1 (9.0) <.001Control 21.2 (10.4) 22.2 (9.8)

Anxiety/Depression by EQ-5D Exercise 1.4 (0.6) 1.2 (0.4) .009Control 1.4 (0.6) 1.5 (0.7)

*p of F by Analysis of Variance.



Munro study were achieved in the first part of the 2-yearperiod.

Previous studies have shown that recruiting elderly peoplein the general population to participate in exercise provesdifficult, even when using different strategies [34,35]. Inthe framework of practice-based recruitment, Margitic etal. [19] reported that patient self-administered, office-based questionnaires were cheaper ($14/randomized par-ticipant) than patient mailings ($58) and direct telephonecontact. Direct medical invitations to an exercise unit oroffice are easier to administer and less expensive; how-ever, the rate of recruitment varies. Tully et al. [36]reported poor recruitment following contact by the gen-eral practitioner who invited patients to participate in anunsupervised home-based walking programme. Stevens et

al. [20] achieved higher recruitment rates by invitingpatients (45–74 years of age) to a consultation with anexercise development officer and offering a personalisedcombination of leisure-centre and home-based activities.However, our sensitivity analysis suggests that unit costscould be halved with a more effective recruitment strategy.Bell-Syer and Moffet [37] reported a 73% response rate togeneral practitioner reiterative invitations (an average ofseven invitations) to participate in an exercise program forprimary care patients with low-back pain. A recent reviewof exercise referrals in the United Kingdom [17] reportedsimilar rates of recruitment by mail (50–60%) and lowrates of maintenance without the continuous support of atechnician. The strategy in the current study resulted in arecruitment rate of 79%; this strategy consisted of a spe-cific targeted invitation from general practitioners to eld-erly women who were overweight or moderatelydepressed, offering a consultation with an exercise moni-tor and a supervised exercise programme. This highrecruitment rate could be partially explained by the specif-icity of the invitation to older, overweight patients, whoare usually more willing to participate than the generalpopulation [38], the active-management of general practi-tioners [39], and the offer of supervision in the exerciseprogramme. Richert et al. [40] also demonstrated benefitsof partnership and natural peer support in low-costrecruiting for enhancing physical activity. While recruit-ment rates were high in our programme, the retention rateof 86% was similar to previous supervised, group-basedcommunity strategies to promote exercise in the elderlypopulation (80–90%) [6].

The NICE of the United Kingdom has recommended tele-phone support as an inexpensive alternative for maintain-ing the physically active lifestyle acquired by exercisereferrals. However, more research is required to assess thecomparative sustainability, retention, effectiveness andcost-effectiveness of exercise programmes (walking,cycling, advising or pedometer) that are longer than 10weeks [14]. Benett et al. [41] has recently reported that the

Cost effectiveness acceptability curvesFigure 2Cost effectiveness acceptability curves. * Worst sce-nario described as 30% higher salary, 30% lower participation rating and the effectiveness of lower limit of 95% confidence interval. – The efficiency threshold was set at 34729 €/QALY.

0102030405060708090

100

0 200 400 600 800 1000 1200

Ceiling (€)

Pro

bab

ility

that

giv

en tr

eatm

ent

is b

est (

%)

Exercise available

Manipulation followed by Exercise+assessment

Manipulation followed by worst scenario*

Table 4: The EQ-5D utilities of the exercise programme compared to usual care

Alternatives Best care in generalPractice (n = 51)

Best care plusExercise (n = 55)

EQ-5D utility at baseline 0.542 (0.334) 0.688 (0.304)EQ-5D utility at 6 months* 0.510 (0.196) 0.890 (0.178)QALY over 6 months* 0.263 (0.132) 0.395 (0.121)QALY difference versus best care† 0.132 (0.104 to 0.286)Incremental cost per person (€) 41Cost-utility (€/QALY) † 311 (143 to 394)

Expressed as mean (SD)QALY = quality adjusted life year*Mean (SD) estimated by analysis of covariance with adjustment for baseline EQ-5D score and then rounded to three significant figures.† Mean (95% confidence interval estimated by bootstrapping).



combination of a pedometer-based exercise program withmonthly telephone support did not increase the level ofphysical activity in physically inactive persons. However,evidence suggests that the pedometer-based programmeworks well with more physically active persons [14,42].

Unanswered questionsExercise programmes targeted towards patients with par-ticular diseases result in a demonstrable reduction in theuse of health care services (frequentation, medication,etc.) [17,43,44]; however, exercise programmes targetedtowards the general population have not been found tomake any difference in the use of health care services inprimary care [33]. The current study also failed to findchanges in the use of primary health care services. Thesample size was adequate to test the primary outcome, theutility of EQ-5D, but the sample size may have been insuf-ficient to detect significant changes in the use of healthservices and medication. This relative reduction in thesample size was partially due to the selection criteria,which excluded patients with co-morbidities to allow usto focus the study on women with obesity and depression.The effects of the current programme on health systemresources in a more wide-spread service could vary. How-ever, the lack of change in frequency of consultations(consultation/month) in the short-term may be partiallyexplained by the limits of supply and the management of"free" appointments in the general practices of theNational Health System. Therefore, one should be cau-tious in generalizing these results to private care or morewide-spread services. In addition, this study may havebeen limited by a selection bias that favoured patientswith low educational levels and low income, and wholived in medium sized cities and rural areas. As a result,

more research is required to assess the efficiency of thecurrent strategy in a more general population, with alonger programme, in different age or socioeconomicgroups. The largest effect using the EQ-5D was detected inthe dimension of anxiety/depression, so one could expectbetter cost-utility ratios in groups that include higher per-centages of participants with problems in anxiety/depres-sion.

ConclusionThe current study presented a pragmatic and cost-effectivestrategy to enhance the level of physical activity in over-weight or moderately depressed elderly women. The pro-gramme could be a cost-effective resource for helpingpatients increase physical activity, as recommended bygeneral practitioners. Moreover, the present study couldhelp decision makers enhance the preventive role of pri-mary care and optimize health resources.

List of abbreviationsBMI, body mass index; NICE, National Institute forHealth and Clinical Excellence; QALY, quality-adjustedlife years

Competing interestsThe authors declare that they have no competing interests.

Authors' contributionsNG was involved in the conception, planning and designof this study, as well as the acquisition of data (but not thefitness testing), analysis and interpretation of data, andwriting the manuscript. MCR was involved in organisingthis research, the acquisition of data and analysis andinterpretation of data. JLG and JMG were involved in

Table 5: Sensitivity analyses by treatment group

Manipulation of variables Incremental cost versusbest care per person (€)

Cost utility ratio(€/QALY)

Number of participants:- 30% lower 58 439- 30% higher* 47 356- 50% lower or higher 41 311- Distributed in 3 groups* 61 462

Including 5 h/week for assessment 61 462Salary of technician:

- 30% lower 29 220- 30% higher 54 409

Best scenario of salary,participation and effectiveness†

27 94

Worst scenario of salary, participation and effectiveness‡

115 871

* Requires 5 additional hours of the technician†Salary 30% lower + Participation 30 persons per group + QALY differential at higher limit of 95% confidence interval + distributed in two groups‡Salary 30% higher + Participation 30% lower + QALY differential at lower limit of 95% confidence interval + distributed in three groups.



planning and organising the research and interpretationof data. EH assisted in the writing of the manuscript. Allthe authors read and approved the final manuscript.

AcknowledgementsThanks to Angeles Duran and Yolanda Garcia for their technical support. The study was supported by European Social Funds and the Government of Extremadura, Spain (2PR02B017).

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