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<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="1.3" xml:lang="en" article-type="research-article"><?properties manuscript?><processing-meta base-tagset="archiving" mathml-version="3.0" table-model="xhtml" tagset-family="jats"><restricted-by>pmc</restricted-by></processing-meta><front><journal-meta><journal-id journal-id-type="nlm-journal-id">0376027</journal-id><journal-id journal-id-type="pubmed-jr-id">412</journal-id><journal-id journal-id-type="nlm-ta">Am J Clin Nutr</journal-id><journal-id journal-id-type="iso-abbrev">Am J Clin Nutr</journal-id><journal-title-group><journal-title>The American journal of clinical nutrition</journal-title></journal-title-group><issn pub-type="ppub">0002-9165</issn><issn pub-type="epub">1938-3207</issn></journal-meta><article-meta><article-id pub-id-type="pmid">39537027</article-id><article-id pub-id-type="pmc">11701942</article-id><article-id pub-id-type="doi">10.1016/j.ajcnut.2024.11.006</article-id><article-id pub-id-type="manuscript">NIHMS2039140</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>School-based nutrition education programs alone are not cost-effective for preventing childhood obesity: A microsimulation study</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Kenney</surname><given-names>Erica L.</given-names></name><xref rid="A1" ref-type="aff">1</xref><xref rid="A2" ref-type="aff">2</xref></contrib><contrib contrib-type="author"><name><surname>Poole</surname><given-names>Mary Kathryn</given-names></name><xref rid="A1" ref-type="aff">1</xref></contrib><contrib contrib-type="author"><name><surname>McCulloch</surname><given-names>Stephanie M.</given-names></name><xref rid="A2" ref-type="aff">2</xref></contrib><contrib contrib-type="author"><name><surname>Barrett</surname><given-names>Jessica L.</given-names></name><xref rid="A2" ref-type="aff">2</xref></contrib><contrib contrib-type="author"><name><surname>Tucker</surname><given-names>Kyla</given-names></name><xref rid="A3" ref-type="aff">3</xref></contrib><contrib contrib-type="author"><name><surname>Ward</surname><given-names>Zachary J.</given-names></name><xref rid="A4" ref-type="aff">4</xref></contrib><contrib contrib-type="author"><name><surname>Gortmaker</surname><given-names>Steven L.</given-names></name><xref rid="A2" ref-type="aff">2</xref></contrib></contrib-group><aff id="A1"><label>1</label>Department of Nutrition, Harvard T.H. Chan School of Public Health</aff><aff id="A2"><label>2</label>Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health</aff><aff id="A3"><label>3</label>Office of Student Wellbeing, Massachusetts Institute of Technology</aff><aff id="A4"><label>4</label>Center for Health Decision Science, Harvard T.H. Chan School of Public Health</aff><author-notes><fn fn-type="con" id="FN1"><p id="P1">Authorship Contributions.</p><p id="P2">EK, MKP, JLB, ZW, and SG designed the research. EK, MKP, and KT conducted the research. JLB and SM analyzed the data. EK, MKP, JLB, and SG wrote the paper. EK had primary responsibility for final content. All authors have read and approved the final manuscript.</p></fn><corresp id="CR1"><bold>Address correspondence to:</bold> Erica L. Kenney, Department of Nutrition, Harvard T.H. Chan School of Public Health, 667 Huntington Ave., Boston, MA 02115, <email>ekenney@hsph.harvard.edu</email>.</corresp></author-notes><pub-date pub-type="nihms-submitted"><day>22</day><month>12</month><year>2024</year></pub-date><pub-date pub-type="ppub"><month>1</month><year>2025</year></pub-date><pub-date pub-type="epub"><day>12</day><month>11</month><year>2024</year></pub-date><pub-date pub-type="pmc-release"><day>01</day><month>1</month><year>2026</year></pub-date><volume>121</volume><issue>1</issue><fpage>167</fpage><lpage>173</lpage><abstract id="ABS1"><sec id="S1"><title>Background.</title><p id="P3">Although interventions to change nutrition policies, systems, and environments (PSE) for children are generally cost-effective for preventing childhood obesity, existing evidence suggests that nutrition education curricula, without accompanying PSE changes, are more commonly implemented.</p></sec><sec id="S2"><title>Objective.</title><p id="P4">Estimate the societal costs and potential for cost-effectiveness of three nutrition education curricula frequently implemented in U.S. public schools for childhood obesity prevention.</p></sec><sec id="S3"><title>Methods.</title><p id="P5">In 2021, we searched for nutrition education curricula in the SNAP-Ed Toolkit, a catalogue of interventions for obesity prevention coordinated by the federal government. Standard costing methodologies estimated the societal costs from 2023&#x02013;2032 of nationwide implementation of each identified curriculum. Using the Childhood Obesity Intervention Cost-Effectiveness Study (CHOICES) microsimulation model, which projects the costs, healthcare costs saved, and cases of obesity prevented for childhood obesity prevention interventions, we conducted threshold analyses for each curriculum, estimating the cost per quality-adjusted life year (QALY) for a range of hypothetical effects on child body mass index (BMI) to determine how large of an effect each curriculum would need to have to meet a cost-effectiveness threshold of $150,000 per QALY.</p></sec><sec id="S4"><title>Results.</title><p id="P6">Three nutrition education curricula without PSE were identified from SNAP-Ed; none had evidence of an impact on obesity risk. From 2023 to 2032, the estimated implementation costs of the curricula nationwide ranged from $1.80 billion (95% UI: $1.79-$1.82 billion) to $3.48 billion (95% UI: $3.44-$3.51 billion). Each curriculum would have to reduce average child BMI by 0.10 kg/m<sup>2</sup> or more&#x02014;an effect size that has not been reported by any of the three curricula, or by more comprehensive existing prevention programs&#x02014;to be considered cost-effective at this threshold.</p></sec><sec id="S5"><title>Conclusions.</title><p id="P7">SNAP-Ed-endorsed nutrition education curricula alone are unlikely to be cost-effective for preventing childhood obesity. Continued efforts to implement interventions with strong evidence for effectiveness, including PSE approaches, are needed.</p></sec></abstract><kwd-group><kwd>Childhood obesity</kwd><kwd>Nutrition Education</kwd><kwd>schools</kwd><kwd>prevention</kwd><kwd>cost-effectiveness analysis</kwd><kwd>threshold analysis</kwd></kwd-group></article-meta></front><body><sec id="S6"><title>Introduction</title><p id="P8">Nutrition education, especially for children, has been frequently implemented as a chronic disease prevention strategy, especially as a strategy for preventing obesity by modifying individual behaviors.(<xref rid="R1" ref-type="bibr">1</xref>) As the prevalence of childhood obesity has grown, so too have calls to implement more robust nutrition education curricula in K-12 school settings.(<xref rid="R2" ref-type="bibr">2</xref>&#x02013;<xref rid="R4" ref-type="bibr">4</xref>) The Centers for Disease Control and Prevention promotes nutrition education as a chronic disease prevention strategy,(<xref rid="R5" ref-type="bibr">5</xref>) and $464 million of funding for the Supplemental Nutrition Assistance Program (SNAP), the largest social safety net program in the U.S., was set aside in 2022 for SNAP-Ed,(<xref rid="R6" ref-type="bibr">6</xref>) a program that promotes nutrition education for SNAP recipients and obesity prevention.(<xref rid="R7" ref-type="bibr">7</xref>) Yet education is typically much less effective at producing clinically meaningful and lasting change than public health interventions that modify contexts and environments using policy or systems changes.(<xref rid="R8" ref-type="bibr">8</xref>) While SNAP-Ed has, in recent years, also adopted &#x0201c;policies, systems and environment,&#x0201d; or PSE, strategies per requirements of the Healthy, Hunger-Free Kids Act of 2010,(<xref rid="R7" ref-type="bibr">7</xref>) its primary activity remains delivering direct nutrition education.(<xref rid="R9" ref-type="bibr">9</xref>,<xref rid="R10" ref-type="bibr">10</xref>)</p><p id="P9">It is unknown, however, whether direct nutrition education is a cost-effective strategy for population health. Although nutrition education may be a more palatable public health intervention for policymakers and politicians,(<xref rid="R1" ref-type="bibr">1</xref>) existing evidence suggests that, consistent with theoretical models proposing that education-only has limited impact compared to more robust, structural public health interventions,(<xref rid="R8" ref-type="bibr">8</xref>) nutrition education alone may have limited impact in supporting sustained behavior change with regards to eating and physical activity.(<xref rid="R11" ref-type="bibr">11</xref>&#x02013;<xref rid="R13" ref-type="bibr">13</xref>) Meanwhile, school-based PSE strategies have been found to reduce childhood obesity risk (such as changes to school nutrition standards,(<xref rid="R14" ref-type="bibr">14</xref>) eliminating the sale of sugary beverages and other unhealthy snacks,(<xref rid="R15" ref-type="bibr">15</xref>) providing water on school lunch lines,(<xref rid="R16" ref-type="bibr">16</xref>) and incorporating more robust physical activity programs(<xref rid="R17" ref-type="bibr">17</xref>)). With the lack of evidence for effectiveness at reducing excess weight gain in children, it is not possible to directly estimate the cost-effectiveness of nutrition education curricula for childhood obesity prevention. Yet, given that nutrition education is widely promoted and adopted in U.S. schools as an obesity prevention strategy, it is important to understand its potential for cost-effectiveness, and whether the current widespread adoption of this strategy is a prudent use of existing school and public health funds.</p><p id="P10">The first aim of this study was to identify evidence-based nutrition education curricula that are currently promoted for youth obesity prevention in U.S. school settings and to estimate the implementation costs of these nutrition education curricula if they were scaled to reach students nationally. The second aim was to assess the potential for the nutrition education curricula to be cost-effective for childhood obesity prevention, by estimating how large of an average effect on children&#x02019;s body mass index (BMI) each curriculum would need to have in order for it to meet a standard cost-effectiveness threshold.</p></sec><sec id="S7"><title>Methods</title><sec id="S8"><title>Intervention Selection</title><p id="P11">This analysis was conducted after engaging a group of advisory partners, consisting of federal, state, and local public health practitioners, policymakers and researchers with expertise in childhood obesity prevention, as part of the Childhood Obesity Intervention Cost-Effectiveness Study (CHOICES). The advisory group requested that CHOICES explore the cost-effectiveness of strategies that are frequently implemented, and specifically cited a need for evidence of the cost-effectiveness of school-based nutrition education. To identify specific nutrition education curricula for modeling, between May and June 2021, we searched the online SNAP-Ed Toolkit(<xref rid="R18" ref-type="bibr">18</xref>) for school-based interventions (see <xref rid="SD1" ref-type="supplementary-material">Supplementary Figure 1</xref> for flow diagram). The toolkit, a catalogue maintained by the federal government, features obesity prevention interventions developed by practitioners and/or researchers that meet criteria of the SNAP-Ed Evaluation Framework. We chose to select interventions from SNAP-Ed given its wide reach and given that the included interventions undergo a quality review. Fifty-one (96%) of the 53 interventions from our search had a nutrition education component. From this list, we eliminated 29 interventions with multiple intervention components beyond nutrition education (such as modifying school meals or increasing physical activity opportunities), as these would not allow us to isolate the impact of nutrition education alone. Additionally, we excluded four interventions that were not designed to be implemented at school, and one intervention for changing teachers&#x02019; nutrition knowledge only. For the remaining 17 SNAP-Ed Toolkit interventions, we then conducted targeted literature searches using PubMed, Google Scholar, the SNAP-Ed Toolkit, program sites when available, and the Google search engine to locate research studies evaluating their effectiveness at changing behaviors and/or weight outcomes. Thirteen of these interventions (72%) had at least one relevant peer-reviewed publication or publicly-available evaluation report with <italic toggle="yes">any</italic> outcome (not necessarily nutrition- or weight-related). For these 13 interventions, we searched available literature to determine whether they have actually been implemented outside of a research or pilot evaluation context; most (10 of the 13) showed no evidence of being in use, but three were found to have been implemented across multiple states. We thus arrived at three nutrition education interventions:(<xref rid="R18" ref-type="bibr">18</xref>)</p><list list-type="order" id="L2"><list-item><p id="P12"><bold>Pick a Better Snack:</bold> Eight lessons delivered by a nutrition educator for grades Kindergarten to 3, eight supplemental lessons led by classroom teachers, and take-home family newsletters;(<xref rid="R19" ref-type="bibr">19</xref>)</p></list-item><list-item><p id="P13"><bold>Harvest of the Month:</bold> Six nutrition lessons featuring a fruit or vegetable with taste tests for grades 4 to 6, plus take-home resources for families;(<xref rid="R20" ref-type="bibr">20</xref>) and</p></list-item><list-item><p id="P14"><bold>Choose Health: Food, Fun and Fitness:</bold> Six nutrition lessons for grades 3 to 6 with take-home family newsletters and activities.(<xref rid="R21" ref-type="bibr">21</xref>)</p></list-item></list><p id="P15">Because schools could use a wide variety of different programs, with different activities, costs and outcomes, we chose to include all three of the interventions in our study to reflect the variation in programs implemented rather than selecting a single program.</p></sec><sec id="S9"><title>Intervention Reach</title><p id="P16">We assumed that 70.6% of students in the grade levels targeted by each intervention would participate in the interventions in public schools across 50 states plus the District of Columbia (<xref rid="SD1" ref-type="supplementary-material">Supplementary Tables 1</xref>&#x02013;<xref rid="SD1" ref-type="supplementary-material">3</xref>). This assumption mirrors a similar estimate from the School Health Policies and Practices Study of 2016 which estimated the percentage of school districts with a policy requiring schools to deliver nutrition education to students.(<xref rid="R22" ref-type="bibr">22</xref>)</p></sec><sec id="S10"><title>Intervention costs</title><p id="P17">We collected information on costs needed to implement each nutrition education program using a standard cost-estimation protocol with a modified societal perspective.(<xref rid="R23" ref-type="bibr">23</xref>,<xref rid="R24" ref-type="bibr">24</xref>) We enumerated implementation costs including labor (including both paid and unpaid labor) and materials (i.e., brochure printing costs, food costs), as well as payers, using estimates from peer-reviewed articles of the interventions, implementation manuals when available or from personal communications with intervention developers. Hours of labor were converted to costs using estimates for hourly wages for various job roles from the Bureau of Labor Statistics.(<xref rid="R25" ref-type="bibr">25</xref>) Costs are discounted at 3% annually, adjusted for inflation, and reported in 2019 U.S. dollars; 3% is the standard reference case for discounting in the U.S.(<xref rid="R26" ref-type="bibr">26</xref>,<xref rid="R27" ref-type="bibr">27</xref>) More detailed information on cost estimation can be found in <xref rid="SD1" ref-type="supplementary-material">Supplementary Tables 1</xref>&#x02013;<xref rid="SD1" ref-type="supplementary-material">3</xref>.</p></sec><sec id="S11"><title>Intervention effects</title><p id="P18">To estimate the potential impact on childhood obesity from implementing the three nutrition education programs in schools, we reviewed the evidence identified from our targeted literature search of scientific journals and grey literature described above including 3 studies for Pick a Better Snack,(<xref rid="R19" ref-type="bibr">19</xref>,<xref rid="R28" ref-type="bibr">28</xref>,<xref rid="R29" ref-type="bibr">29</xref>) 6 studies or evaluation reports for Harvest of the Month,(<xref rid="R20" ref-type="bibr">20</xref>,<xref rid="R30" ref-type="bibr">30</xref>&#x02013;<xref rid="R34" ref-type="bibr">34</xref>) and 2 studies for Choose Health, Food, Fun, and Fitness.(<xref rid="R21" ref-type="bibr">21</xref>,<xref rid="R35" ref-type="bibr">35</xref>) No studies reported associations with body weight (i.e., BMI) or behavioral outcomes for which there is evidence of impact on child weight (i.e., calorie intake, intake of sugary drinks, minutes of physical activity, or hours of television watched). Therefore, in the absence of evidence of the effects of the three selected nutrition education curricula on body weight or BMI, we modeled one-way sensitivity analyses for each curriculum using five hypothetical BMI effects: &#x02212;0.01, &#x02212;0.05, &#x02212;0.1, &#x02212;0.2, and &#x02212;0.3 kg/m<sup>2</sup>. These effect sizes were chosen based on the range of BMI effects previously estimated through the CHOICES study for effective childhood obesity prevention interventions in school, early care and education, and community and government settings.(<xref rid="R17" ref-type="bibr">17</xref>,<xref rid="R24" ref-type="bibr">24</xref>,<xref rid="R36" ref-type="bibr">36</xref>&#x02013;<xref rid="R38" ref-type="bibr">38</xref>) These effect sizes were estimated based on implementation of policy, systems, and environmental strategies, including school-based physical activity promotion (e.g., active physical education &#x02212;0.01 kg/m<sup>2</sup> BMI effect), state sugary drink excise taxes of 1 cent per ounce (&#x02212;0.13 kg/m<sup>2</sup> BMI effect), improved early care and education policies and practices (&#x02212;0.21 kg/m<sup>2</sup> BMI effect), and healthy afterschool programs (&#x02212;0.29 kg/m<sup>2</sup> BMI effect).</p><p id="P19">This study was approved as non-human subjects research by the Harvard T.H. Chan School of Public Health Institutional Review Board.</p></sec><sec id="S12"><title>Statistical Analyses</title><p id="P20">With these estimates of reach, cost, and effect gathered above, we then used the CHOICES microsimulation model(<xref rid="R23" ref-type="bibr">23</xref>,<xref rid="R24" ref-type="bibr">24</xref>) (<xref rid="F1" ref-type="fig">Figure 1</xref>) to estimate both the total costs to implement each of the three nutrition education curricula from 2023&#x02013;2032 as well as the potential net costs per quality adjusted life year (QALY) gained associated with each curriculum under the range of hypothetical effects on child BMI, compared with projections with no intervention. The microsimulation model leverages detailed data from multiple nationally representative datasets to simulate the experiences of individuals in the U.S. population related to height/weight trajectories and health, accounting for demographic characteristics and projected population growth. The model estimates healthcare costs associated with increasing BMI using age- and sex-specific estimates derived from the Medical Expenditure Panel Survey.(<xref rid="R39" ref-type="bibr">39</xref>) The healthcare cost savings associated with implementing a strategy that reduces excess weight gain are combined with the strategy&#x02019;s implementation costs to estimate net costs of the strategy. QALYs gained from implementing a strategy were estimated using health-related quality of life weights associated with three BMI categories (under/normal weight, overweight, obesity) by sex and age group.(<xref rid="R23" ref-type="bibr">23</xref>,<xref rid="R40" ref-type="bibr">40</xref>,<xref rid="R41" ref-type="bibr">41</xref>) A 10-year period was used to align with budget planning timelines for policymakers.(<xref rid="R42" ref-type="bibr">42</xref>) The model allows for the estimation of various outcomes, including: the <italic toggle="yes">number of people reached</italic> by the intervention over 10 years; the <italic toggle="yes">annual intervention cost</italic> in U.S. dollars (including private and government expenses); the <italic toggle="yes">intervention cost per person; healthcare costs related to excess weight gain</italic> saved over 10 years; the projected <italic toggle="yes">number of childhood obesity cases prevented</italic> in thousands in the year 2032; and the intervention&#x02019;s costs per QALY. To account for uncertainty in model inputs, we calculated 95% uncertainty intervals (UI), using 1,000 Monte Carlo iterations for a simulated nationally representative population of one million individuals. The model is programmed in Java (v1.8.0, Oracle Corporation, Redwood Shores, CA, USA), and R (v4.1.1, R Foundation for Statistical Computing, Vienna, Austria) was used to summarize results. Further details on the CHOICES microsimulation model are available elsewhere.(<xref rid="R23" ref-type="bibr">23</xref>,<xref rid="R24" ref-type="bibr">24</xref>)</p><p id="P21">Using the five hypothetical effects on child BMI, we conducted a threshold analysis to identify how large of an effect each curriculum would need to have on children&#x02019;s weight to meet a threshold for cost-effectiveness. For each curriculum, we calculated the incremental cost-effectiveness ratio in terms of cost per QALY gained, given the curriculum&#x02019;s reach and costs, for the five hypothetical BMI effects specified above. We identified the magnitude of the BMI effect at which the cost per QALY fell below a willingness-to-pay threshold of $150,000, a threshold commonly and increasingly used in economic evaluation to reflect the value of health improvements.(<xref rid="R43" ref-type="bibr">43</xref>,<xref rid="R44" ref-type="bibr">44</xref>) We then compared the estimated effect needed to similar childhood obesity prevention interventions to assess whether that impact would be plausible. To gauge the plausibility of the BMI effects, we then qualitatively compared estimated effects needed to similar and more intensive childhood obesity prevention interventions we could identify that had evaluated impacts on BMI.</p></sec></sec><sec id="S13"><title>Results</title><p id="P22">The three direct nutrition education interventions included in this study&#x02013;Pick a Better Snack, Harvest of the Month, and Choose Health: Food, Fun and Fitness&#x02013; were projected to reach a large number of children. Over ten years, implementation of such nutrition education curricula would be estimated to reach between 31.7 million (95% UI: 31.0 million to 32.2 million) young children for Harvest of the Month to 34.0 million (95% UI: 33.5 million to 34.7 million) for Choose Health: Food, Fun, and Fitness (<xref rid="T1" ref-type="table">Table 1</xref>). Variations in projected reach were largely due to some interventions pertaining to smaller ranges of grade levels than others.</p><p id="P23">The interventions ranged widely in estimated total implementation costs. Harvest of the Month was estimated to cost $1.80 billion (95% UI: $1.79 billion to $1.82 billion) over ten years if implemented nationwide, with an annual cost per child of $18.70 ($18.50 to $18.90), while Choose Health, Fun, Food, and Fitness would cost $1.92 billion total (95% UI: $1.92 billion to $1.92 billion), with an annual cost per child of $15.90 ($15.60 to $16.20). Meanwhile, Pick a Better Snack, which involved more materials for more frequent lessons and more labor time for nutrition educators and school teachers(<xref rid="R45" ref-type="bibr">45</xref>) was estimated to have the highest implementation costs, at $3.48 billion (95% UI: $3.44 billion to $3.51 billion) over ten years and an annual cost per child of $30.50 ($30.20 to $30.90) (<xref rid="T1" ref-type="table">Table 1</xref>). Most of these implementation costs would be borne by state government agencies, with smaller costs borne by schools themselves, if the interventions were implemented with the same structures described in available evidence (<xref rid="T2" ref-type="table">Table 2</xref>).</p><p id="P24">When the curricula were assumed to have a BMI effect of &#x02212;0.01 kg/m<sup>2</sup>, the costs per QALY gained for each were well above a cost-effectiveness threshold of $150,000 per QALY ($1,430,000 per QALY for Pick a Better Snack, $1,060,000 per QALY for Harvest of the Month, and $950,000 per QALY for Choose Health, Fun, Food, and Fitness). Costs per QALY gained were still estimated to be higher than $150,000 for all curricula when a larger BMI effect of &#x02212;0.05 kg/m<sup>2</sup> was assumed, and only met this threshold when a BMI effect of &#x02212;0.1 kg/m<sup>2</sup> was used (<xref rid="F2" ref-type="fig">Figure 2</xref>).</p></sec><sec id="S14"><title>Discussion</title><p id="P25">In this cost-effectiveness analysis of nutrition education curricula without any accompanying changes to policies, systems, or environments that were selected from the SNAP-Ed Toolkit for obesity prevention, we found that such curricula are unlikely to be cost-effective for preventing childhood obesity at a cost-effectiveness threshold of $150,000 per QALY. In order to be considered cost-effective, these interventions, which currently lack published evidence of having an effect on weight status, would need to have implausibly large effects on children&#x02019;s BMI. We estimated that the effects of the curricula on students&#x02019; BMI would have to be greater than &#x02212;0.05 kg/m<sup>2</sup>, and at least &#x02212;0.1 kg/m<sup>2</sup> for Pick a Better Snack, the curriculum with the highest estimated per person implementation cost, for the curricula to be cost-effective at $150,000 per QALY gained. In comparison, the Texas Sprouts intervention, which involved both school-based nutrition education and gardening, was associated with a nonsignificant BMI change of &#x02212;0.02 kg/m<sup>2</sup>.(<xref rid="R46" ref-type="bibr">46</xref>) Achieving a BMI effect two and a half to five times larger than that found by the Texas Sprouts intervention by implementing nutrition education alone is not likely to be plausible. While school-based nutrition education curricula may appear to be more feasible or politically palatable compared to more effective obesity prevention interventions that directly influence nutrition environments for children, and while nutrition education curricula may improve knowledge, the results of this study suggest that only implementing such curricula without accompanying PSE changes is likely not an efficient use of resources if obesity prevention is the goal.(<xref rid="R8" ref-type="bibr">8</xref>)</p><p id="P26">These findings highlight an area of public health nutrition practice that needs refinement. Public health agencies have scarce resources, experiencing regular budget cuts(<xref rid="R47" ref-type="bibr">47</xref>) and limited funds at state and local levels,(<xref rid="R48" ref-type="bibr">48</xref>) and local health departments across the US, for example, spend an average of roughly $50 per capita per year across all public health initiatives.(<xref rid="R48" ref-type="bibr">48</xref>) State public health departments and schools, which would likely bear a substantial portion of implementation costs, are also chronically under-resourced. In this context, it is even more essential for these entities to spend such limited resources wisely if the goal is measurable impacts in improving child weight status and reducing chronic disease burden. Cost-effectiveness analyses of school-based or afterschool-based obesity prevention programs that do involve the implementation of other components, such as Planet Health,(<xref rid="R49" ref-type="bibr">49</xref>) the Coordinated Approach to Child Health,(<xref rid="R50" ref-type="bibr">50</xref>) and the FitKid Project,(<xref rid="R51" ref-type="bibr">51</xref>) as well as analyses of school-based programs that solely focus on policy and environmental changes and do not incorporate nutrition education, like stronger standards for school meals,(<xref rid="R24" ref-type="bibr">24</xref>) and the provision of water dispensers on school lunch lines,(<xref rid="R37" ref-type="bibr">37</xref>) suggest that these approaches are simply more cost-effective. Nutrition professionals involved in supporting school-based efforts to promote healthy weight should consider selecting programs that focus on policy, systems, and environmental changes.</p><p id="P27">Of note, the modeled programs were identified via the SNAP-Ed toolkit, which serves as a mechanism for disseminating obesity prevention interventions to low income communities. In 2022, the federal government allocated $464 million to deliver SNAP-Ed in income-eligible communities nationwide,(<xref rid="R6" ref-type="bibr">6</xref>) much of which occurs in educational settings.(<xref rid="R9" ref-type="bibr">9</xref>) Prior evidence suggests more states are partnering with schools for PSE interventions(<xref rid="R9" ref-type="bibr">9</xref>) though barriers to implementation remain.(<xref rid="R10" ref-type="bibr">10</xref>,<xref rid="R52" ref-type="bibr">52</xref>&#x02013;<xref rid="R54" ref-type="bibr">54</xref>) Our results suggest that if these school-based lessons involved the utilization of direct nutrition education-only programs, and do not make continued progress on PSE interventions, this approach may not be an investment with good value for money if childhood obesity prevention is the goal. This is of particular concern given that SNAP-Ed is meant to focus on low income communities; spending scarce financial resources on programs that are unlikely to impact obesity may inadvertently contribute to health inequities by diverting needed resources away from potentially effective programs instead. While school-based nutrition education alone may be helpful for improving students&#x02019; nutrition knowledge,(<xref rid="R55" ref-type="bibr">55</xref>) especially when multi-component interventions are implemented,(<xref rid="R56" ref-type="bibr">56</xref>,<xref rid="R57" ref-type="bibr">57</xref>) and for contributing to students&#x02019; development of general knowledge more broadly, such increases in knowledge may not be sufficient to translate to sustained behavioral change, particularly enough to bring about the significant dietary changes that may be necessary to prevent obesity in childhood.(<xref rid="R58" ref-type="bibr">58</xref>,<xref rid="R59" ref-type="bibr">59</xref>)</p><p id="P28">These results also further highlight the inadequacy of current efforts to translate the evidence base for childhood obesity into effective practice. Effective interventions have been identified,(<xref rid="R60" ref-type="bibr">60</xref>) and the cost-effectiveness of several school-based interventions in the U.S. has also been evaluated;(<xref rid="R37" ref-type="bibr">37</xref>,<xref rid="R49" ref-type="bibr">49</xref>&#x02013;<xref rid="R51" ref-type="bibr">51</xref>) in other words, evidence does exist that could be used to help inform strategic choices that maximize the utilization of limited public health and educational expenditures for the most population health impact. Yet existing data suggests that such evidence is not being widely accessed in school settings.(<xref rid="R61" ref-type="bibr">61</xref>) More work to effectively disseminate research findings to practitioners in a usable, practical format is needed, as is work to help train practitioners in the skills needed for utilizing evidence-based interventions specific to their targeted health outcomes. Resources like the SNAP-Ed Toolkit Literature Review Database released in 2022(<xref rid="R18" ref-type="bibr">18</xref>) (now available in the SNAP-Ed Library(<xref rid="R62" ref-type="bibr">62</xref>)) may further assist practitioners with accessing evidence for dietary and obesity outcomes. More work may also be needed to ensure the implementation of multiple evidence-based interventions in schools as no single strategy or intervention will adequately prevent childhood obesity&#x02014;careful consideration of cost-effectiveness is key to maximizing impact with available resources.</p><p id="P29">This study has several limitations. First, we were not able to directly estimate the cost-effectiveness of each of the curricula, since there were no published studies evaluating their effects on children&#x02019;s weight status. Our threshold analysis assesses the plausibility of the interventions being cost-effective, but it is possible that the true, unstudied effect of the interventions are unexpectedly higher than what has been seen in similar interventions with larger doses and more intervention activities. Second, the nutrition education curricula assessed here have demonstrated effects on other behavioral outcomes (e.g. fruit and vegetable intake) for which there is no evidence of impact for childhood obesity/weight outcomes but may have other benefits for population health. Additionally, there are likely a multitude of other nutrition education curricula in use nationwide&#x02014;some evidence-based, and some developed ad hoc&#x02014;so the three curricula modeled here may not be representative of all programs in place at the moment. However, given that the three curricula modeled here were rigorously and carefully developed by experts in the field, and promoted by SNAP-Ed, it is unlikely that curricula developed ad hoc or with a less rigorous process would be more effective at preventing obesity than what was modeled.</p></sec><sec id="S15"><title>Conclusions</title><p id="P30">By themselves, nutrition education curricula&#x02014;even those endorsed by SNAP-Ed&#x02014;are not likely to be cost-effective strategies for preventing childhood obesity. To be considered cost-effective at standard thresholds, each of these evidence-based nutrition education curricula would have to have implausibly large impacts on child BMI. While nutrition education can support improved knowledge and skills, it cannot be thought of as a stand-alone solution for addressing cardiometabolic disease risk in children. Efforts to better translate research findings on effective and cost-effective programs for childhood obesity prevention into public health practice are needed.</p></sec><sec sec-type="supplementary-material" id="SM1"><title>Supplementary Material</title><supplementary-material id="SD1" position="float" content-type="local-data"><label>1</label><media xlink:href="NIHMS2039140-supplement-1.docx" id="d67e561" position="anchor"/></supplementary-material></sec></body><back><ack id="S18"><title>Funding/support:</title><p id="P32">This study was supported by Healthy Eating Research, a national program of the Robert Wood Johnson Foundation (2833590), The JPB Foundation, the National Heart, Lung, and Blood Institute (NHLBI) (5T32HL098048, R01HL146625, and 1F31HL162250), the National Institute of Diabetes and Digestive and Kidney Diseases (K01DK125278), and the Centers for Disease Control and Prevention (U48DP006376). The content is solely the responsibility of the authors and does not necessarily represent the official views of these agencies.</p></ack><fn-group><fn id="FN2"><p id="P33" content-type="publisher-disclaimer">This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.</p></fn><fn fn-type="COI-statement" id="FN3"><p id="P34"><bold>Conflict of interest disclosures:</bold> The authors have no conflicts to disclose.</p></fn><fn id="FN4"><p id="P35">Declaration of interests</p><p id="P36">The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.</p></fn></fn-group><sec sec-type="data-availability" id="S17"><title>Data Share Statement:</title><p id="P31">Data used in the model are available from published literature and publicly available data sources cited in the manuscript.</p></sec><glossary><title>Abbreviations:</title><def-list><def-item><term>PSE</term><def><p id="P37">Policy, Systems, and Environment</p></def></def-item><def-item><term>CHOICES</term><def><p id="P38">Childhood Obesity Intervention Cost-Effectiveness Study</p></def></def-item><def-item><term>QALY</term><def><p id="P39">Quality-adjusted Life Year</p></def></def-item><def-item><term>SNAP</term><def><p id="P40">Supplemental Nutrition Assistance Program</p></def></def-item><def-item><term>BMI</term><def><p id="P41">body mass index</p></def></def-item></def-list></glossary><ref-list><title>References</title><ref id="R1"><label>1.</label><mixed-citation publication-type="journal"><name><surname>Chrisman</surname><given-names>M</given-names></name>, <name><surname>Hampton</surname><given-names>N</given-names></name>. <article-title>Preferred child obesity message frames and their perceived strength among state policymakers</article-title>. <source>Child Obes</source>. <year>2021</year>
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M = million. UI = uncertainty interval.</p></fn><fn id="TFN2"><p id="P46">Projections from the CHOICES microsimulation model.</p></fn><fn id="TFN3"><p id="P47">The 95% uncertainty interval is a central range in which 95 percent of model results fell when the model was run 1,000 times, taking into account uncertainty from data sources and population projections</p></fn></table-wrap-foot></table-wrap><table-wrap position="float" id="T2"><label>Table 2.</label><caption><p id="P48">Summary of estimated 10-year implementation costs of three nutrition education curricula if implemented in U.S. public schools nationwide for obesity prevention by category and payer (2023&#x02013;2032)</p></caption><table frame="box" rules="groups"><colgroup span="1"><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/></colgroup><thead><tr><th align="left" valign="top" rowspan="1" colspan="1">Intervention</th><th align="center" valign="top" rowspan="1" colspan="1">Estimated amount in U.S. dollars $<break/>(% of total implementation costs)</th><th align="center" valign="top" rowspan="1" colspan="1">Payer<sup><xref rid="TFN5" ref-type="table-fn">1</xref></sup></th></tr></thead><tbody><tr><td align="left" valign="top" rowspan="1" colspan="1">Pick a Better Snack</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x02003;Labor</td><td align="left" valign="top" rowspan="1" colspan="1">$230 M (6%)</td><td align="left" valign="top" rowspan="1" colspan="1">State government</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1">$1.33 B (38%)</td><td align="left" valign="top" rowspan="1" colspan="1">Schools</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x02003;Materials</td><td align="left" valign="top" rowspan="1" colspan="1">$1.95 B (56%)</td><td align="left" valign="top" rowspan="1" colspan="1">State government</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Harvest of the Month</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x02003;Labor</td><td align="left" valign="top" rowspan="1" colspan="1">$10,000 (&#x0003c;1%)</td><td align="left" valign="top" rowspan="1" colspan="1">State government</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1">$930 M (51%)</td><td align="left" valign="top" rowspan="1" colspan="1">School</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x02003;Materials</td><td align="left" valign="top" rowspan="1" colspan="1">$880 M (49%)</td><td align="left" valign="top" rowspan="1" colspan="1">School</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Choose Health: Food, Fun and Fitness</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x02003;Labor</td><td align="left" valign="top" rowspan="1" colspan="1">$850 M (44%)</td><td align="left" valign="top" rowspan="1" colspan="1">State government</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x02003;Materials</td><td align="left" valign="top" rowspan="1" colspan="1">$1.06 B (55%)</td><td align="left" valign="top" rowspan="1" colspan="1">State government</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x02003;Equipment</td><td align="left" valign="top" rowspan="1" colspan="1">$11.5 M (1%)</td><td align="left" valign="top" rowspan="1" colspan="1">State government</td></tr></tbody></table><table-wrap-foot><fn id="TFN4"><p id="P49">Notes: Projections from the CHOICES microsimulation model(<xref rid="R23" ref-type="bibr">23</xref>,<xref rid="R24" ref-type="bibr">24</xref>).</p></fn><fn id="TFN5"><label>1</label><p id="P50">Payers were estimated based on available peer-reviewed evidence and program reports. B = billion. M = million.</p></fn></table-wrap-foot></table-wrap></floats-group></article>