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Grady A, Jackson J, Wolfenden L, Lum M, Yoong SL. Assessing the scalability of healthy eating interventions within the early childhood education and care setting: secondary analysis of a Cochrane systematic review. Public Health Nutr 2023; 26:3211-3229. [PMID: 37990443 PMCID: PMC10755435 DOI: 10.1017/s1368980023002550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 10/05/2023] [Accepted: 11/13/2023] [Indexed: 11/23/2023]
Abstract
OBJECTIVE Early childhood education and care (ECEC) is a recommended setting for the delivery of health eating interventions 'at scale' (i.e. to large numbers of childcare services) to improve child public health nutrition. Appraisal of the 'scalability' (suitability for delivery at scale) of interventions is recommended to guide public health decision-making. This study describes the extent to which factors required to assess scalability are reported among ECEC-based healthy eating interventions. DESIGN Studies from a recent Cochrane systematic review assessing the effectiveness of healthy eating interventions delivered in ECEC for improving child dietary intake were included. The reporting of factors of scalability was assessed against domains outlined within the Intervention Scalability Assessment Tool (ISAT). The tool recommends decision makers consider the problem, the intervention, strategic and political context, effectiveness, costs, fidelity and adaptation, reach and acceptability, delivery setting and workforce, implementation infrastructure and sustainability. Data were extracted by one reviewer and checked by a second reviewer. SETTING ECEC. PARTICIPANTS Children 6 months to 6 years. RESULTS Of thirty-eight included studies, none reported all factors within the ISAT. All studies reported the problem, the intervention, effectiveness and the delivery workforce and setting. The lowest reported domains were intervention costs (13 % of studies) and sustainability (16 % of studies). CONCLUSIONS Findings indicate there is a lack of reporting of some key factors of scalability for ECEC-based healthy eating interventions. Future studies should measure and report such factors to support policy and practice decision makers when selecting interventions to be scaled-up.
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Affiliation(s)
- Alice Grady
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- National Centre of Implementation Science, University of Newcastle, Callaghan, Australia
| | - Jacklyn Jackson
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- National Centre of Implementation Science, University of Newcastle, Callaghan, Australia
| | - Luke Wolfenden
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- National Centre of Implementation Science, University of Newcastle, Callaghan, Australia
| | - Melanie Lum
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- National Centre of Implementation Science, University of Newcastle, Callaghan, Australia
| | - Sze Lin Yoong
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- National Centre of Implementation Science, University of Newcastle, Callaghan, Australia
- Global Centre for Preventive Health and Nutrition, Institute for Health Transformation, Deakin University, Victoria, Australia
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Yoong SL, Lum M, Wolfenden L, Jackson J, Barnes C, Hall AE, McCrabb S, Pearson N, Lane C, Jones JZ, Nolan E, Dinour L, McDonnell T, Booth D, Grady A. Healthy eating interventions delivered in early childhood education and care settings for improving the diet of children aged six months to six years. Cochrane Database Syst Rev 2023; 8:CD013862. [PMID: 37606067 PMCID: PMC10443896 DOI: 10.1002/14651858.cd013862.pub3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/23/2023]
Abstract
BACKGROUND Dietary intake during early childhood can have implications on child health and developmental trajectories. Early childhood education and care (ECEC) services are recommended settings to deliver healthy eating interventions as they provide access to many children during this important period. Healthy eating interventions delivered in ECEC settings can include strategies targeting the curriculum (e.g. nutrition education), ethos and environment (e.g. menu modification) and partnerships (e.g. workshops for families). Despite guidelines supporting the delivery of healthy eating interventions in this setting, little is known about their impact on child health. OBJECTIVES To assess the effectiveness of healthy eating interventions delivered in ECEC settings for improving dietary intake in children aged six months to six years, relative to usual care, no intervention or an alternative, non-dietary intervention. Secondary objectives were to assess the impact of ECEC-based healthy eating interventions on physical outcomes (e.g. child body mass index (BMI), weight, waist circumference), language and cognitive outcomes, social/emotional and quality-of-life outcomes. We also report on cost and adverse consequences of ECEC-based healthy eating interventions. SEARCH METHODS We searched eight electronic databases including CENTRAL, MEDLINE, Embase, CINAHL, PsycINFO, ERIC, Scopus and SportDiscus on 24 February 2022. We searched reference lists of included studies, reference lists of relevant systematic reviews, the World Health Organization International Clinical Trials Registry Platform, ClinicalTrials.gov and Google Scholar, and contacted authors of relevant papers. SELECTION CRITERIA We included randomised controlled trials (RCTs), including cluster-RCTs, stepped-wedge RCTs, factorial RCTs, multiple baseline RCTs and randomised cross-over trials, of healthy eating interventions targeting children aged six months to six years that were conducted within the ECEC setting. ECEC settings included preschools, nurseries, kindergartens, long day care and family day care. To be included, studies had to include at least one intervention component targeting child diet within the ECEC setting and measure child dietary or physical outcomes, or both. DATA COLLECTION AND ANALYSIS Pairs of review authors independently screened titles and abstracts and extracted study data. We assessed risk of bias for all studies against 12 criteria within RoB 1, which allows for consideration of how selection, performance, attrition, publication and reporting biases impact outcomes. We resolved discrepancies via consensus or by consulting a third review author. Where we identified studies with suitable data and homogeneity, we performed meta-analyses using a random-effects model; otherwise, we described findings using vote-counting approaches and via harvest plots. For measures with similar metrics, we calculated mean differences (MDs) for continuous outcomes and risk ratios (RRs) for dichotomous outcomes. We calculated standardised mean differences (SMDs) for primary and secondary outcomes where studies used different measures. We applied GRADE to assess certainty of evidence for dietary, cost and adverse outcomes. MAIN RESULTS We included 52 studies that investigated 58 interventions (described across 96 articles). All studies were cluster-RCTs. Twenty-nine studies were large (≥ 400 participants) and 23 were small (< 400 participants). Of the 58 interventions, 43 targeted curriculum, 56 targeted ethos and environment, and 50 targeted partnerships. Thirty-eight interventions incorporated all three components. For the primary outcomes (dietary outcomes), we assessed 19 studies as overall high risk of bias, with performance and detection bias being most commonly judged as high risk of bias. ECEC-based healthy eating interventions versus usual practice or no intervention may have a positive effect on child diet quality (SMD 0.34, 95% confidence interval (CI) 0.04 to 0.65; P = 0.03, I2 = 91%; 6 studies, 1973 children) but the evidence is very uncertain. There is moderate-certainty evidence that ECEC-based healthy eating interventions likely increase children's consumption of fruit (SMD 0.11, 95% CI 0.04 to 0.18; P < 0.01, I2 = 0%; 11 studies, 2901 children). The evidence is very uncertain about the effect of ECEC-based healthy eating interventions on children's consumption of vegetables (SMD 0.12, 95% CI -0.01 to 0.25; P =0.08, I2 = 70%; 13 studies, 3335 children). There is moderate-certainty evidence that ECEC-based healthy eating interventions likely result in little to no difference in children's consumption of non-core (i.e. less healthy/discretionary) foods (SMD -0.05, 95% CI -0.17 to 0.08; P = 0.48, I2 = 16%; 7 studies, 1369 children) or consumption of sugar-sweetened beverages (SMD -0.10, 95% CI -0.34 to 0.14; P = 0.41, I2 = 45%; 3 studies, 522 children). Thirty-six studies measured BMI, BMI z-score, weight, overweight and obesity, or waist circumference, or a combination of some or all of these. ECEC-based healthy eating interventions may result in little to no difference in child BMI (MD -0.08, 95% CI -0.23 to 0.07; P = 0.30, I2 = 65%; 15 studies, 3932 children) or in child BMI z-score (MD -0.03, 95% CI -0.09 to 0.03; P = 0.36, I2 = 0%; 17 studies; 4766 children). ECEC-based healthy eating interventions may decrease child weight (MD -0.23, 95% CI -0.49 to 0.03; P = 0.09, I2 = 0%; 9 studies, 2071 children) and risk of overweight and obesity (RR 0.81, 95% CI 0.65 to 1.01; P = 0.07, I2 = 0%; 5 studies, 1070 children). ECEC-based healthy eating interventions may be cost-effective but the evidence is very uncertain (6 studies). ECEC-based healthy eating interventions may have little to no effect on adverse consequences but the evidence is very uncertain (3 studies). Few studies measured language and cognitive skills (n = 2), social/emotional outcomes (n = 2) and quality of life (n = 3). AUTHORS' CONCLUSIONS ECEC-based healthy eating interventions may improve child diet quality slightly, but the evidence is very uncertain, and likely increase child fruit consumption slightly. There is uncertainty about the effect of ECEC-based healthy eating interventions on vegetable consumption. ECEC-based healthy eating interventions may result in little to no difference in child consumption of non-core foods and sugar-sweetened beverages. Healthy eating interventions could have favourable effects on child weight and risk of overweight and obesity, although there was little to no difference in BMI and BMI z-scores. Future studies exploring the impact of specific intervention components, and describing cost-effectiveness and adverse outcomes are needed to better understand how to maximise the impact of ECEC-based healthy eating interventions.
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Affiliation(s)
- Sze Lin Yoong
- Global Centre for Preventive Health and Nutrition, Institute for Health Transformation, School of Health and Social Development, Faculty of Health, Deakin University, Victoria, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Melanie Lum
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Luke Wolfenden
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Jacklyn Jackson
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Courtney Barnes
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Alix E Hall
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Sam McCrabb
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Nicole Pearson
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Cassandra Lane
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Jannah Z Jones
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Erin Nolan
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Lauren Dinour
- College of Education and Human Services, Montclair State University, Montclair, New Jersey, USA
| | - Therese McDonnell
- School of Nursing, Midwifery and Health Systems, University College Dublin, Dublin, Ireland
| | - Debbie Booth
- Auchmuty Library, University of Newcastle, Callaghan, Australia
| | - Alice Grady
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
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Yoong SL, Lum M, Wolfenden L, Jackson J, Barnes C, Hall AE, McCrabb S, Pearson N, Lane C, Jones JZ, Dinour L, McDonnell T, Booth D, Grady A. Healthy eating interventions delivered in early childhood education and care settings for improving the diet of children aged six months to six years. Cochrane Database Syst Rev 2023; 6:CD013862. [PMID: 37306513 PMCID: PMC10259732 DOI: 10.1002/14651858.cd013862.pub2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
BACKGROUND Dietary intake during early childhood can have implications on child health and developmental trajectories. Early childhood education and care (ECEC) services are recommended settings to deliver healthy eating interventions as they provide access to many children during this important period. Healthy eating interventions delivered in ECEC settings can include strategies targeting the curriculum (e.g. nutrition education), ethos and environment (e.g. menu modification) and partnerships (e.g. workshops for families). Despite guidelines supporting the delivery of healthy eating interventions in this setting, little is known about their impact on child health. OBJECTIVES To assess the effectiveness of healthy eating interventions delivered in ECEC settings for improving dietary intake in children aged six months to six years, relative to usual care, no intervention or an alternative, non-dietary intervention. Secondary objectives were to assess the impact of ECEC-based healthy eating interventions on physical outcomes (e.g. child body mass index (BMI), weight, waist circumference), language and cognitive outcomes, social/emotional and quality-of-life outcomes. We also report on cost and adverse consequences of ECEC-based healthy eating interventions. SEARCH METHODS We searched eight electronic databases including CENTRAL, MEDLINE, Embase, CINAHL, PsycINFO, ERIC, Scopus and SportDiscus on 24 February 2022. We searched reference lists of included studies, reference lists of relevant systematic reviews, the World Health Organization International Clinical Trials Registry Platform, ClinicalTrials.gov and Google Scholar, and contacted authors of relevant papers. SELECTION CRITERIA We included randomised controlled trials (RCTs), including cluster-RCTs, stepped-wedge RCTs, factorial RCTs, multiple baseline RCTs and randomised cross-over trials, of healthy eating interventions targeting children aged six months to six years that were conducted within the ECEC setting. ECEC settings included preschools, nurseries, kindergartens, long day care and family day care. To be included, studies had to include at least one intervention component targeting child diet within the ECEC setting and measure child dietary or physical outcomes, or both. DATA COLLECTION AND ANALYSIS Pairs of review authors independently screened titles and abstracts and extracted study data. We assessed risk of bias for all studies against 12 criteria within RoB 1, which allows for consideration of how selection, performance, attrition, publication and reporting biases impact outcomes. We resolved discrepancies via consensus or by consulting a third review author. Where we identified studies with suitable data and homogeneity, we performed meta-analyses using a random-effects model; otherwise, we described findings using vote-counting approaches and via harvest plots. For measures with similar metrics, we calculated mean differences (MDs) for continuous outcomes and risk ratios (RRs) for dichotomous outcomes. We calculated standardised mean differences (SMDs) for primary and secondary outcomes where studies used different measures. We applied GRADE to assess certainty of evidence for dietary, cost and adverse outcomes. MAIN RESULTS: We included 52 studies that investigated 58 interventions (described across 96 articles). All studies were cluster-RCTs. Twenty-nine studies were large (≥ 400 participants) and 23 were small (< 400 participants). Of the 58 interventions, 43 targeted curriculum, 56 targeted ethos and environment, and 50 targeted partnerships. Thirty-eight interventions incorporated all three components. For the primary outcomes (dietary outcomes), we assessed 19 studies as overall high risk of bias, with performance and detection bias being most commonly judged as high risk of bias. ECEC-based healthy eating interventions versus usual practice or no intervention may have a positive effect on child diet quality (SMD 0.34, 95% confidence interval (CI) 0.04 to 0.65; P = 0.03, I2 = 91%; 6 studies, 1973 children) but the evidence is very uncertain. There is moderate-certainty evidence that ECEC-based healthy eating interventions likely increase children's consumption of fruit (SMD 0.11, 95% CI 0.04 to 0.18; P < 0.01, I2 = 0%; 11 studies, 2901 children). The evidence is very uncertain about the effect of ECEC-based healthy eating interventions on children's consumption of vegetables (SMD 0.12, 95% CI -0.01 to 0.25; P =0.08, I2 = 70%; 13 studies, 3335 children). There is moderate-certainty evidence that ECEC-based healthy eating interventions likely result in little to no difference in children's consumption of non-core (i.e. less healthy/discretionary) foods (SMD -0.05, 95% CI -0.17 to 0.08; P = 0.48, I2 = 16%; 7 studies, 1369 children) or consumption of sugar-sweetened beverages (SMD -0.10, 95% CI -0.34 to 0.14; P = 0.41, I2 = 45%; 3 studies, 522 children). Thirty-six studies measured BMI, BMI z-score, weight, overweight and obesity, or waist circumference, or a combination of some or all of these. ECEC-based healthy eating interventions may result in little to no difference in child BMI (MD -0.08, 95% CI -0.23 to 0.07; P = 0.30, I2 = 65%; 15 studies, 3932 children) or in child BMI z-score (MD -0.03, 95% CI -0.09 to 0.03; P = 0.36, I2 = 0%; 17 studies; 4766 children). ECEC-based healthy eating interventions may decrease child weight (MD -0.23, 95% CI -0.49 to 0.03; P = 0.09, I2 = 0%; 9 studies, 2071 children) and risk of overweight and obesity (RR 0.81, 95% CI 0.65 to 1.01; P = 0.07, I2 = 0%; 5 studies, 1070 children). ECEC-based healthy eating interventions may be cost-effective but the evidence is very uncertain (6 studies). ECEC-based healthy eating interventions may have little to no effect on adverse consequences but the evidence is very uncertain (3 studies). Few studies measured language and cognitive skills (n = 2), social/emotional outcomes (n = 2) and quality of life (n = 3). AUTHORS' CONCLUSIONS ECEC-based healthy eating interventions may improve child diet quality slightly, but the evidence is very uncertain, and likely increase child fruit consumption slightly. There is uncertainty about the effect of ECEC-based healthy eating interventions on vegetable consumption. ECEC-based healthy eating interventions may result in little to no difference in child consumption of non-core foods and sugar-sweetened beverages. Healthy eating interventions could have favourable effects on child weight and risk of overweight and obesity, although there was little to no difference in BMI and BMI z-scores. Future studies exploring the impact of specific intervention components, and describing cost-effectiveness and adverse outcomes are needed to better understand how to maximise the impact of ECEC-based healthy eating interventions.
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Affiliation(s)
- Sze Lin Yoong
- Global Centre for Preventive Health and Nutrition, Institute for Health Transformation, School of Health and Social Development, Faculty of Health, Deakin University, Victoria, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Melanie Lum
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Luke Wolfenden
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Jacklyn Jackson
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Courtney Barnes
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Alix E Hall
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Sam McCrabb
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Nicole Pearson
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Cassandra Lane
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Jannah Z Jones
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Lauren Dinour
- College of Education and Human Services, Montclair State University, Montclair, New Jersey, USA
| | - Therese McDonnell
- School of Nursing, Midwifery and Health Systems, University College Dublin, Dublin, Ireland
| | - Debbie Booth
- Auchmuty Library, University of Newcastle, Callaghan, Australia
| | - Alice Grady
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
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Lee C, Kim S, Kim J, Lim C, Jung M. Challenges of diet planning for children using artificial intelligence. Nutr Res Pract 2022; 16:801-812. [PMID: 36467765 PMCID: PMC9702545 DOI: 10.4162/nrp.2022.16.6.801] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 02/13/2022] [Accepted: 03/23/2022] [Indexed: 10/28/2023] Open
Abstract
BACKGROUND/OBJECTIVES Diet planning in childcare centers is difficult because of the required knowledge of nutrition and development as well as the high design complexity associated with large numbers of food items. Artificial intelligence (AI) is expected to provide diet-planning solutions via automatic and effective application of professional knowledge, addressing the complexity of optimal diet design. This study presents the results of the evaluation of the utility of AI-generated diets for children and provides related implications. MATERIALS/METHODS We developed 2 AI solutions for children aged 3-5 yrs using a generative adversarial network (GAN) model and a reinforcement learning (RL) framework. After training these solutions to produce daily diet plans, experts evaluated the human- and AI-generated diets in 2 steps. RESULTS In the evaluation of adequacy of nutrition, where experts were provided only with nutrient information and no food names, the proportion of strong positive responses to RL-generated diets was higher than that of the human- and GAN-generated diets (P < 0.001). In contrast, in terms of diet composition, the experts' responses to human-designed diets were more positive when experts were provided with food name information (i.e., composition information). CONCLUSIONS To the best of our knowledge, this is the first study to demonstrate the development and evaluation of AI to support dietary planning for children. This study demonstrates the possibility of developing AI-assisted diet planning methods for children and highlights the importance of composition compliance in diet planning. Further integrative cooperation in the fields of nutrition, engineering, and medicine is needed to improve the suitability of our proposed AI solutions and benefit children's well-being by providing high-quality diet planning in terms of both compositional and nutritional criteria.
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Affiliation(s)
- Changhun Lee
- Department of Industrial Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Korea
| | - Soohyeok Kim
- Department of Industrial Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Korea
| | - Jayun Kim
- Kosin Innovative Smart Healthcare Research Center, Kosin University Gospel Hospital, Busan 49267, Korea
| | - Chiehyeon Lim
- Department of Industrial Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Korea
- Graduate School of Artificial Intelligence, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Korea
| | - Minyoung Jung
- Kosin Innovative Smart Healthcare Research Center, Kosin University Gospel Hospital, Busan 49267, Korea
- Department of Pediatrics, Kosin University Gospel Hospital, Kosin University College of Medicine, Busan 49267, Korea
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