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      Economic evaluation of a web-based menu planning intervention to improve childcare service adherence with dietary guidelines

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          Abstract

          Background

          Despite the known benefits of healthy eating in childhood, few Australian childcare services provide food that is consistent with dietary guidelines. The effectiveness of a web-based menu planning intervention to increase childcare service provision of healthy foods and decrease provision of discretionary foods in long day-care services in Australia was assessed in a randomised controlled trial. Here we consider the costs, consequences, cost-effectiveness and budget impact of the intervention using data collected within the trial.

          Methods

          The prospective trial-based economic evaluation involved 54 childcare services across New South Wales (NSW), Australia. Services were randomised to a 12-month intervention or usual care. The intervention involved access to a web-based menu planning and decision support tool and online resources. Effectiveness measures included mean number of food groups, overall menu and individual food group compliance with dietary guidelines, and mean servings of food groups at 12 months. Costs (reported in $AUD, 2017/18) were evaluated from both health sector and societal perspectives. The direct cost to support uptake of the intervention was calculated, as were costs to each childcare service. The incremental cost of the intervention was calculated as the net difference in the cost to undertake menu planning and review plus the direct cost of the intervention. Incremental cost-effectiveness ratios (ICERs) including uncertainty intervals were estimated for differences in costs and effects between intervention and control groups. A relative value index was calculated to determine overall value for money.

          Results

          Over the 12 months of the trial, we calculated a difference in cost between usual practice and intervention groups of − $482 (95% UI − $859, − $56). While the measured increase in menu and food group compliance within the trial did not reach statistical significance, there were significant improvements in mean servings of fruit and discretionary food, represented in the cost-consequence analysis. The calculated relative value index of 1.1 suggests that the intervention returns acceptable value for money for the outcomes generated.

          Conclusion

          Compared to usual practice, web-based programmes may offer an efficient and sustainable alternative for childcare services to improve the provision of healthy foods to children in their care.

          Trial registration

          Australian New Zealand Clinical Trials Registry ACTRN12616000974404

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          Most cited references45

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          Recommendations for Conduct, Methodological Practices, and Reporting of Cost-effectiveness Analyses: Second Panel on Cost-Effectiveness in Health and Medicine.

          Since publication of the report by the Panel on Cost-Effectiveness in Health and Medicine in 1996, researchers have advanced the methods of cost-effectiveness analysis, and policy makers have experimented with its application. The need to deliver health care efficiently and the importance of using analytic techniques to understand the clinical and economic consequences of strategies to improve health have increased in recent years.
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            Tracking of obesity-related behaviours from childhood to adulthood: A systematic review.

            Obesity in childhood carries a wide range of physical, psychological and social disbenefits and also increases the risk of adult obesity with its well-recognised, enhanced risk of several common complex diseases as well as adverse socioeconomic and psychosocial sequelae. Understanding the tracking of the two key modifiable behaviours, food consumption and physical activity, between childhood and adulthood may illuminate the childhood determinants of adult obesity and contribute to the development of effective interventions. We performed a systematic review of the available literature on tracking of both physical activity and of dietary intake between childhood and adulthood by searching MEDLINE, EMBASE, CINAHL, PSYCInfo, Google and Google Scholar. For inclusion, studies had to report baseline measurements when the children were less than, or equal to, 18 years and to report follow-up for at least 5 years to any age over 18 years. After removal of duplicates, 9625 search hits were screened by title and/or abstract and 79 potentially relevant papers were identified and full papers obtained. In total 39 papers were included in this analysis. Of these, 11 papers (from 5 studies) reported data on tracking of diet from childhood to adulthood and 28 papers (from 16 studies) reported data on tracking of physical activity or inactivity. Despite the diversity of study design and measurement methodology, we found evidence of tracking of both physical activity and of diet between childhood and adulthood with estimates of strength of tracking of a similar order for both behaviours. Because of the inherent methodological difficulties in quantifying habitual behaviour, it is likely that the reported estimates of strength of tracking under-estimate the true degree of tracking. The evidence of tracking reported here may give greater impetus to the development of interventions aimed to prevent the persistence of obesity from childhood into adulthood and its attendant adverse socioeconomic, psychosocial and health sequelae. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
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              A Guide to Handling Missing Data in Cost-Effectiveness Analysis Conducted Within Randomised Controlled Trials

              Missing data are a frequent problem in cost-effectiveness analysis (CEA) within a randomised controlled trial. Inappropriate methods to handle missing data can lead to misleading results and ultimately can affect the decision of whether an intervention is good value for money. This article provides practical guidance on how to handle missing data in within-trial CEAs following a principled approach: (i) the analysis should be based on a plausible assumption for the missing data mechanism, i.e. whether the probability that data are missing is independent of or dependent on the observed and/or unobserved values; (ii) the method chosen for the base-case should fit with the assumed mechanism; and (iii) sensitivity analysis should be conducted to explore to what extent the results change with the assumption made. This approach is implemented in three stages, which are described in detail: (1) descriptive analysis to inform the assumption on the missing data mechanism; (2) how to choose between alternative methods given their underlying assumptions; and (3) methods for sensitivity analysis. The case study illustrates how to apply this approach in practice, including software code. The article concludes with recommendations for practice and suggestions for future research. Electronic supplementary material The online version of this article (doi:10.1007/s40273-014-0193-3) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                Penny.reeves@hmri.org.au
                Kim.edmunds@hmri.org.au
                Zoe.Szewczyk@uon.edu.au
                Alice.Grady@hnehealth.nsw.gov.au
                Serene.Yoong@hnehealth.nsw.gov.au
                Luke.Wolfenden@hnehealth.nsw.gov.au
                Rebecca.wyse@hnehealth.nsw.gov.au
                meghan.finch@hnehealth.nsw.gov.au
                Fiona.Stacey@health.nsw.gov.au
                John.Wiggers@hnehealth.nsw.gov.au
                Andrew.searles@hmri.org.au
                Journal
                Implement Sci
                Implement Sci
                Implementation Science : IS
                BioMed Central (London )
                1748-5908
                7 January 2021
                7 January 2021
                2021
                : 16
                : 1
                Affiliations
                [1 ]GRID grid.413648.c, Hunter Medical Research Institute (HMRI), ; New Lambton, New South Wales Australia
                [2 ]GRID grid.266842.c, ISNI 0000 0000 8831 109X, School of Medicine and Public health, , University of Newcastle, ; Callaghan, New South Wales 2308 Australia
                [3 ]Hunter New England Population Health, Wallsend, New South Wales 2287 Australia
                [4 ]GRID grid.266842.c, ISNI 0000 0000 8831 109X, Priority Research Centre for Health Behaviour, , University of Newcastle, ; Callaghan, NSW Australia
                Author information
                http://orcid.org/0000-0001-7335-8765
                Article
                1068
                10.1186/s13012-020-01068-x
                7789335
                33413491
                345a22cd-b64e-4bd5-b15e-20026b9d6512
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 24 June 2020
                : 1 December 2020
                Funding
                Funded by: National Health and Medical Research Fund
                Award ID: APP1102943
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001102, Cancer Council NSW;
                Award ID: PG16-05
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                Medicine
                cost-consequence,economic evaluation,dietary intervention,childhood obesity prevention

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