Health Promotion International Advance Access originally published online on October 4, 2007
Health Promotion International 2007 22(4):271-283; doi:10.1093/heapro/dam027
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Time to give nutrition interventions a higher profile: cost-effectiveness of 10 nutrition interventions
Health Economics, Division of Health Sciences, University of South Australia, Adelaide, South Australia, Australia
* Corresponding author. E-mail: kim.dalziel{at}unisa.edu.au
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SUMMARY |
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The aim of this study was to evaluate the economic performance of 10 nutrition interventions. The interventions included Mediterranean Diet, Intensive Lifestyle Change (nutrition and physical activity) to Prevent Diabetes, Reduced Fat Diet for persons with IGT, Nutritional Counselling in GP (GP, general practice/primary care), Nurse Counselling in GP, Oxcheck Nurse Health Checks in GP, Gutbusters Workplace (for men), Talking Computer, Multi Media 2 fruit 5 veg Campaign and the FFFF (Fighting Fit, Fighting Fat) Media Campaign. Markov models were constructed in order to estimate economic performance expressed as cost per QALY (quality adjusted life year) gained. Data from original clinical trial reports were used to populate the models, supplemented by the wider literature where required. Performance of the Mediterranean Diet and Intensive Lifestyle Change to Prevent Diabetes interventions could be estimated with most certainty and both were highly cost-effective interventions, at AU $1020 (US $760, £410) and AU $1880 (US $1410, £750) per QALY gained, respectively. The media campaign interventions appear highly cost-effective at AU $46 (US $34, £18) for ‘2 fruit 5 veg’ and AU $5600 (US $4200, £2200) per QALY gained for FFFF, but are associated with considerable uncertainty, and may be dominated under certain assumptions. Several interventions were cost-saving under plausible sets of assumptions, whereas a small number were potentially dominated. All interventions subject to economic evaluation appeared cost-effective relative to societal norms. Nutrition interventions can constitute a highly efficient component of a strategy to reduce the growing disease burden linked to over/poor nutrition. There is an urgent need for high-quality trial data from which economic performance of nutrition interventions can be modelled.
Key words: nutrition; risk factors; economic analysis; cost-effectiveness
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INTRODUCTION |
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TOPSUMMARYINTRODUCTIONMETHODRESULTSDISCUSSIONFUNDINGREFERENCES |
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Dietary trends across the world are of increasing concern, with rates of obesity and overweight rising to epidemic proportions, with alarming increases in developing countries (WHO, 2006a
). Poor diet is a key risk factor contributing to a large portion of the world's disease burden. There has been a significant change in dietary habits and physical activity levels worldwide as a result of industrialization, urbanization, economic development and food market globalization (WHO, 2006a). Diseases and conditions linked to poor diet include cardiovascular disease (29.2% of global deaths), diabetes (171 million people worldwide), cancers (12.5% of global deaths; WHO, 2006a). Obesity has reached alarming proportions and is still increasing with 1 billion adults overweight worldwide and at least 300 million of them clinically obese (WHO, 2006a). Nutrition and physical activity in combination determine the bodies' energy balance and thus rates of obesity.
The health care costs attributable to diseases and conditions related to nutrition are large, with estimates of medical expenses for overweight/obesity alone in the US of $78.5 billion in 1998, or 9.1% of total medical expenditure (US Department of Health and Human Services, 2006). This compares, for instance, with the direct medical costs attributed to smoking of US $50 billion, or 7% of total US medical expenditure (Centres for Disease Control and Prevention, 1994).
Nutrition is undoubtedly a major modifiable determinant of disease. The WHO has estimated that up to 2.7 million lives could be saved each year if fruit and vegetable consumption were sufficiently increased (WHO, 2006b). Lifestyle changes related to diet have the potential to modify disease outcomes and costs of management.
Economic evaluation can be used to ensure scarce resources are allocated more efficiently to reduce the burden of harm from poor diet. However, there are to date relatively few published cost-effectiveness analyses of nutrition interventions. A review by Pavlovich et al. in 2004 (Pavlovich et al., 2004) identified 13 published cost-effectiveness analyses of nutrition interventions, with none reporting a cost per QALY, although since then a small number of cost–utility analyses of nutrition interventions have been published (see Discussion). It is possible that medical and pharmaceutical interventions aimed at treating the effects of poor nutrition receive priority funding over nutrition interventions, partly due to the widespread availability of cost-effectiveness studies for these types of interventions (Ebrahim et al., 1999; Foxcroft, 2005; Pignone et al., 2006).
Cost–utility analysis which uses cost per QALY as the primary measure of economic performance is especially important for comparisons across interventions, modalities and disciplines, as they allow for direct comparisons.
The aim of our study was to assess the economic performance using cost per QALY (cost utility) of a range of nutrition interventions designed to improve the risk profile for chronic disease in order to support the decisions of policy-makers, health care managers and clinicians.
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METHOD |
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TOPSUMMARYINTRODUCTIONMETHODRESULTSDISCUSSIONFUNDINGREFERENCES |
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This economic evaluation exercise involved three main research tasks:
- identification of potential interventions through a literature review and selection of a subset for inclusion in the economic evaluation exercise;
- assessment of the quality of seminal studies used to inform economic evaluation of interventions;
- comparison of the economic performance of the interventions through
- the conduct of cost-effectiveness analysis based purely on trial results, with performance expressed as cost/natural unit, such as cost per additional serve of fruit and vegetables per person per day; and where possible
- modelled cost–utility analysis expressed as cost per QALY.
- the conduct of cost-effectiveness analysis based purely on trial results, with performance expressed as cost/natural unit, such as cost per additional serve of fruit and vegetables per person per day; and where possible
Selection of interventions
Standard databases including Medline, CINAHL and the Cochrane Database were searched to identify potential interventions. Bibliographies were hand-searched to identify further relevant studies. An advisory group with professionals in nutrition and disease burden was used to guide the selection process. Selection of interventions for evaluation was made using the following broad criteria: clear description of the intervention, objective outcome measures, good scientific rigour (ideally RCTs), health as the primary objective, length of follow-up and not primarily to address economic market failure. The aim was to include a range of interventions designed to modify diet as a risk factor for disease, covering diverse delivery settings—including primary care, population targets and mode of intervention. Table 1 summarizes the 10 interventions chosen and seminal study details.
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A seminal study was used as the primary source of effectiveness and cost data for the economic evaluation of each intervention. This approach was necessitated by the highly individualized nature of each intervention.
Quality assessment of seminal studies
The quality of the seminal studies used to inform the economic evaluation of each intervention was critically appraised using the framework from the Centre for Reviews and Dissemination (CRD, 2001). This framework covered, for instance, assessment items such as selection bias, sample size calculation, randomization, blinding, equal treatment of study groups, similar baseline characteristics, loss to follow-up/intention to treat analyses and objectivity of outcome measures. Applying these criteria, three trials were identified as high quality: the ‘Mediterranean Diet’ (de Lorgeril et al., 1999), ‘Intensive Lifestyle Change to Prevent Diabetes’ (Eriksson et al., 1999) and ‘Oxcheck Nurse Checks in GP’ (GP, general practice/primary care) [Imperial Cancer Research Fund (ICRF), 1995]. Four trials were of poor quality with considerable potential for bias: ‘Nutritional Counselling in GP’ (Pritchard et al., 1999), ‘Gutbusters Workplace’ (Egger et al., 1996), ‘Multi Media 2 fruit 5 veg Campaign’ (Dixon et al., 1998) and ‘FFFF Media Campaign’ (Wardle et al., 2001). The remaining three studies were of intermediate quality.
Two trials had to be excluded from economic analysis owing to data problems/data gaps: ‘Nutritional Counselling in GP’ (Pritchard et al., 1999), owing to major flaws in the effectiveness data, including double counting of study participants, high risk of contamination from the same doctors caring for patients in the ‘usual care’ and intervention groups, large loss to follow-up and lack of intention to treat analysis. The ‘Talking Computer’ intervention (Delichatsios et al., 2001) was also excluded owing to the highly idiosyncratic nature of the intervention and an inability to obtain data on costs. More details about trial quality are available elsewhere (Segal et al., 2005). This meant we completed economic evaluations for eights studies.
Economic evaluation
A cost-effectiveness analysis and cost–utility analysis were completed for each intervention, where data quality allowed. Variation across studies in the behavioural and clinical outcome descriptors used restricted the direct comparison of economic performance in terms of cost-effectiveness. Cost–utility analysis was thus employed as the primary measure of performance, with diverse trial outcomes translated into a single metric, the QALY, allowing the direct comparison of economic performance across all the interventions studied.
Cost-effectiveness analysis
Costs
Incremental costs of each intervention (Table 2) were measured by the differential resource use for intervention compared with control participants, where costs were calculated as the product of (i) programme inputs for the intervention and control protocols described in the clinical trial reports and (ii) Australian published unit costs (taken, for instance, from the Medicare Benefits Schedule and standard ‘charge-out’ rates for pertinent health professional groups).
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Effectiveness
A range of outcomes are reported for each intervention. These include behavioural change variables such as fruit and vegetable intake, clinical risk parameters such as weight, and BMI and final outcomes of clinical events, disease rates and mortality. Key estimates of effectiveness are summarized in Table 2 (column 4).
Two interventions reported final outcomes and are particularly interesting. The Mediterranean Diet intervention reported a large and significant reduction in all primary and secondary health endpoints at 4-year-follow-up, including all-cause and cardiac morality. For instance, the odds ratio of a cardiac death or non-fatal AMI was 0.28 for the Mediterranean Diet group relative to the control group (p < 0.0001; de Lorgeril et al., 1999). For the Intensive Lifestyle Change to Prevent Diabetes intervention, the estimated cumulative incidence of diabetes, the primary study end-point, was 58% lower in the intervention group compared with the control group at 5-year-follow-up (hazard ratio = 0.42, p < 0.001; Eriksson et al., 1999).
The net differential costs and key outcomes for each intervention (except for the Talking Computer) were used to calculate incremental cost-effectiveness ratios (incremental costs divided by incremental benefits, Table 2).
Economic modelling for cost utility
Costs
Costs of the intervention were as derived for the cost-effectiveness analysis. Future costs incurred were discounted at 5% p.a. (Commonwealth Department of Health and Ageing, 2002). Australian costs (2003) were converted into US$ and Euros using published exchange rates (as of June 2006).
Changes in health service costs consequential to the intervention were included in the base case where ‘downstream’ health service use data were reported in the clinical trial. In that case, reported incidence or event data were used to a model the pattern of health service use. Differential ‘downstream’ health service costs between control and intervention groups were estimated by applying appropriate unit costs derived from Australian AN DRG hospital cost-weights and other pertinent data sources to event data (Australian Institute of Health and Welfare, 2005). The Mediterranean Diet intervention was the only study to fit these criteria. For this study, the following event costs were used: minor event AU $1304 (US $976, £523), AMI AU $4851 (US $3632, £1946), major event AU $2981 (US $2232, £1196; 28), stroke (new event) AU $18 956 (US $14 194, £7603), stroke (annual cost of ongoing management) AU $1777 (US $1331, £713; 29). For further explanation, see Dalziel et al. (2005).
Where interventions targeted a specific disease (such as diabetes), but ‘consequential’ outcomes/health service use was not reported in the clinical trial data, estimated downstream cost savings were incorporated via sensitivity analysis, but were not included in the base case analysis. For the three diabetes models, the sensitivity analysis included mean annual cost savings of AU $2508 (US $1878, £1006) per diabetes-year avoided.
In the absence of any direct data on downstream health service use, or an obvious ‘disease model’ to apply, estimation of downstream health and cost impact of nutrition interventions are highly uncertain and have conservatively been excluded.
Effectiveness
Mortality was reported only in the Mediterranean Diet study (de Lorgeril et al., 1999), and quality of life was not reported by any of the selected seminal studies. Estimates of QALY gains were therefore derived through economic modelling. Model parameters were informed by the intermediate outcome measures reported in the seminal studies and other pertinent data sources as described in what follows. Key behavioural and clinical outcomes reported in the trials are summarized in Table 2.
Modelling
We modelled the relationship between (i) reported changes in behaviour and/or clinical parameters and (ii) mortality and quality of life. The model parameters were informed by the reported clinical trial results and published relationships between dietary behaviour and/or clinical parameters and health (mortality and quality of life). Four economic models were constructed to cover the range of outcomes reported for the eight nutrition interventions that were able to be modelled.
Each model was a state transition Markov model and was developed in TreeAge Pro (2004). We developed two disease models (cardiac and diabetes) and two behavioural models (fruit and vegetable consumption and BMI). The models were run for 20 years except for the Reduced Fat Diet for IGT intervention, where the model time frame was restricted to 5 years, given the lack of any significant difference in clinical outcomes between control and intervention groups at the 5-year follow-up.
Assumptions common to all models were 1-year cycle length, a societal perspective and costs and outcomes discounted at 5%, consistent with current Australian guidelines (Commonwealth Department of Health and Ageing, 2002). Modelling assumptions unique to each model are described in Table 3. Markov health states for the disease models were chosen to reflect natural disease progression, in addition to incorporating the outcomes reported by the seminal trials. Health states for the behavioural models were defined according to the outcomes reported, including behaviour change. Transition probabilities described in Table 3 were derived from the seminal trials, with rates transferred into annual transition probabilities using the commonly accepted approach (Miller and Homan, 1994). Other model parameters, especially to link surrogate to long-term and final health outcomes, were based on pertinent literature, such as life tables, long-term observational studies and epidemiological studies obtained through literature searches.
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Quality-of-life weights are also summarized in Table 3. For the BMI model, population estimates measured by the AqoL, obtained from the SA Health Omnibus Survey (McNeil and Segal, 1999
), were used. For the fruit and vegetable model, utility estimates were derived by using the Brazier transformation (Brazier et al., 2002) on SF-36 scores reported in the National Nutrition survey [Australian Bureau of Statistics (ABS), 2001]. For the other two disease models, the published literature was consulted, with TTO (time trade-off) estimates (Derdeyn and Powers, 1996; Kuntz et al., 1996; Lee et al., 1997) available for the cardiac model and EQ-5D estimates (Colagiuri et al., 2003) utilized for the diabetes model.
Discounted estimated costs, utilities and life years for the intervention and control cohorts were summed over the model period and compared. Extensive univariate sensitivity analyses were performed varying estimates of effect size, cost, utility, time horizon and discount rate (Segal et al., 2005; Dalziel et al., 2006a).
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RESULTS |
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Cost-effectiveness based on trial results in natural units
Cost-effectiveness estimates based on trial results, without any extrapolation of costs or outcomes, are presented in Table 2. The incremental cost-effectiveness ratios are presented in natural units on the basis of outcomes presented in the original studies.
In relation to promoting fruit and vegetable consumption, we estimated that the cost-per-percentage-point increase in people consuming the recommended serves of fruit and vegetables per day ranged from AU $12 (US $9, £5) for the Victorian Multi Media 2 fruit 5 veg Campaign and AU $5800 (US $4300, £2300) for Nurse Counselling in GP to a high of AU $7500 (US $5600, £3000) for the UK FFFF Media Campaign. We note, however, that the behavioural outcome data for both media campaigns are highly uncertain.
For interventions reporting weight loss, cost-effectiveness ranged from a low AU $13 per additional kilogram weight loss (US $10, £5) for Nutrition Counselling in General Practice by a dietitian plus general practitioner (primary care physician) to AU $60 (US $40, £20) for the Gutbusters Workplace intervention and AU $300 (US $220, £120) for the Intensive Lifestyle Change to Prevent Diabetes programme. In relation to weight loss, the Reduced Fat Diet for IGT was dominant (less effective and more costly). Where outcome was reported in terms of persons who are obese (BMI 
30), the cost was AU $4100 (US $3000, £1600) for the Oxcheck Nurse Checks in GP intervention per person who changed from being obese and AU $16 300 (US $12 200, £6500) for the FFFF Media Campaign.
In relation to major disease outcomes, the Mediterranean Diet had cost-effectiveness ratios of AU $3300 (US $2500, £1300) per non-fatal AMI averted and AU $5300 (US $4000, £2100) per death averted. The Intensive Lifestyle Change to Prevent Diabetes intervention had a cost-effectiveness ratio of AU $9500 (US $7100, £3800) per incident case of diabetes prevented.
Modelled cost–utility analysis
Cost–utility analysis results are presented in Table 4. Point estimates (derived by applying ‘base–case’ assumptions) and the range from sensitivity analysis are reported. Both the Mediterranean Diet intervention for persons after AMI and Intensive Lifestyle Change to Prevent Diabetes perform exceptionally well—AU $1020 (US $760, £410) and AU $1880 (US $1410, £750) per QALY gained, respectively. Performance is also highly certain, with a narrow range of values suggested by the sensitivity analysis, reflecting the high quality of evidence derived from the clinical trials. The Reduced Fat Diet for IGT intervention for persons with IGT is a less cost-effective diabetes prevention intervention, reflecting less successful clinical trial results.
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The Multi Media campaigns, in contrast, performed well in terms of point estimates—AU $46 (US$34, £18) per QALY gained per person for the 2 fruit 5 veg intervention and AU $5600 (US $4200, £2300) for the UK FFFF campaigns, but these estimates were associated with great uncertainty, with possible performance varying from less than AU $25 (US $18, £10) to intervention dominated, reflecting the poorer quality and thus great uncertainty in the clinical trial results.
The performance of the two interventions set in the GP appears similar at AU $10 600 (US $7900, £4200) and AU $12 600 (US $9400, £5100). Although when certainty of results and absolute size of benefit are also considered, the Oxcheck Nurse Checks in GP intervention looks less favourable.
The Gutbusters Workplace group programme for men conservatively cost AU $19 800 (US $14 800, £7900) per QALY gained, but under a range of assumptions, such as benefits extending beyond 5 years and realization of cost offsets from the predicted reduction in incidence of type 2 diabetes, the intervention would be dominant. For more details, the readers may refer to Segal et al. (Segal et al., 2005).
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DISCUSSION |
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TOPSUMMARYINTRODUCTIONMETHODRESULTSDISCUSSIONFUNDINGREFERENCES |
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Key findings
All eight nutrition interventions subject to economic modelling are estimated to be highly cost-effective relative to suggested societal norms. All interventions meet the WHO definition (WHO, 2006c
) of ‘cost effective’ as 1–3 times GDP/head equal to AU $11 427 to AU $33 786 in June 2005 (ABS, 2005). The majority of interventions are also favourable relative to the WHO definition of ‘very cost-effective’ of less than GDP/head (AU $11 427, June 2005). Some interventions, notably the Mediterranean Diet and the two interventions to prevent type 2 diabetes as well as Gutbusters Workplace, are cost-saving under plausible sets of assumptions. The Mediterranean Diet and Intensive Lifestyle Change to Prevent Diabetes are the most certain and cost-effective interventions based on good quality trials. Our analysis did not show that population-wide interventions will necessarily provide better value for money than interventions targeted at high-risk groups. Although both types of interventions are potentially cost-effective, the more targeted interventions in this exercise were associated with more certain benefits.
The estimates for the two media campaigns while potentially very cost-effective are also the least certain, with the range in sensitivity analysis extending to intervention dominated (more expensive and less effective) due to the uncertainty regarding effectiveness estimates.
Relation to previous research
This is the first economic evaluation to assess multiple lifestyle interventions in the area of nutrition, with a focus on reducing risk factors for chronic disease. It adds to what is only a small number of cost–utility studies of nutrition interventions in the literature. A search of English language MEDLINE June 2006 using keywords for cost–utility/QALY and diet/nutrition identified just six cost–utility analyses of nutrition interventions: three diabetes prevention interventions [all relating specifically to the Diabetes Prevention Program (DPP) multi-centre diabetes prevention programme], a low carbohydrate versus standard diet for persons who are obese, and the author's evaluation of the Mediterranean diet compared with American Heart Association diet for persons post-AMI (also included as one of the 10 nutrition interventions reported on in this paper). The very small number of reported economic studies is concerning, given the importance of nutrition as a risk factor for the incidence and progression of common chronic diseases.
The results of the previously published studies are summarized in Table 5. Our results are consistent with previous economic evaluations of nutrition interventions. For instance, we report for the Intensive Lifestyle Change to Prevent Diabetes intervention a cost per QALY gained of AU $1880, very similar to the results of Ackerman et al. (Ackerman et al., 2006) or Herman et al. (Herman et al., 2005).
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The nutrition interventions evaluated in this paper compare very favourably with other options, such as pharmacotherapies, to manage risk factors related to the diseases associated with poor nutrition. A review of interventions to prevent CHD risk found that nutrition interventions had the most favourable cost-effectiveness of £290 (AU $724, US $542) to £780 (AU $1949, US $1458) per life-year gained compared with antihypertensive medications at £1510 (AU $3772, US $2822) and the cholesterol-lowering medication simvastatin at £8240 (AU $20 585, US $15 397; Ebrahim et al., 1999
). The statins are the predominant drug class used for cholesterol-lowering and typically constitute the single largest cause of expenditure on pharmaceuticals. (In Australia, in 2004–05, AU $1063 million was spent on statins, representing 9.7% of the total expenditure on pharmaceuticals.) More recent studies highlight the poor economic performance of statins unless well targeted for those at high risk, with estimated cost-effectiveness ratios of up to US $56 200 (AU $75 134, £30 076) for primary prevention in men compared with aspirin therapy alone (Pignone et al., 2006). Similarly, Orlistat, an ‘obesity drug’, has a reported cost–utility estimate of £19 005 (AU $47 477, US $35 513) to £24 431 per QALY gained (AU $75 134, US $30 076; Foxcroft, 2005). A performance substantially worse than the nutrition interventions is reported here.
The cost–utility estimates for the eight nutrition interventions also compare favourably with physical activity interventions, another means to potentially reduce lifestyle attributable disease burden (Hatziandreu et al., 1988; Munro et al., 2004; Dalziel et al., 2006b).
Limitations and future research
The main limitations of this work relate to the quality of the available clinical trial evidence and other data that support modelling of the relationships between intermediate outcomes and health. The quality of the key effectiveness data was mixed. The wide range of possible values estimated through sensitivity analysis for the media-based interventions highlight the difficulties of conducting economic analysis for community/population-based interventions. The primary challenge is devising and funding community intervention studies of sound experimental design. There are published standards for clinical trials, and potentials for bias are well documented (e.g. CRD and the Cochrane Collaboration). The performance of clinical-based interventions is readily amenable to randomized control trial methods, and the relative dearth of high-quality nutrition intervention studies is disappointing.
Measurement of quality of life in clinical trials is still uncommon and is an important outcome. Its application should be expanded using summary measures such as one of the several published multi-attribute utility instruments. It may also be valuable to explore whether there are other less tangible benefits (or costs) relating to alternative diets that can be incorporated and measured.
There is potential to widen the scope of some clinical trials in order to better inform economic evaluation. It is desirable that interventions are compared with all other likely options for care in order to assess the true opportunity cost of the intervention. For example, pharmacotherapy trials are likely to compare the intervention drug to another drug or placebo and are unlikely to compare to a nutrition intervention alternative. As nutrition interventions lack the negative side effects that accompany some medical interventions, determining their relative efficacy is of considerable public health significance.
Trials with longer follow-up periods are important to provide information on maintenance of behaviour change beyond the intervention period. In addition, there is a need for quality epidemiological data to inform longer term relationships. Our research has highlighted the need for risk equations that incorporate nutrition variables that can be used to model the relationship between observed changes in nutrition and health over the longer term.
While we wait for an extension of the evidence base on nutrition interventions, which will require a funding commitment from government agencies, in the absence of drug company funding, the available evidence suggests that considerable benefits are obtainable by allocating additional resources to a range of cost-effective nutrition interventions.
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FUNDING |
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This work has been supported by a publication grant from the Faculty of Business and Economics, Monash University. Some of this work was performed as part of a research contract for the Australian Government, Department of Health and Ageing, Division of Population Health.
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ACKNOWLEDGEMENTS |
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The authors would like to acknowledge Susan Day (research fellow), Andrew Dalton and Rachelle Katz (research assistant), who assisted with the identification of model parameters including costs, and Duncan Mortimer (senior research fellow), who provided advice regarding the economic modelling.
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