Lori A J Scott-Sheldon1,2, Larry V Hedges3, Chris Cyr4, Deborah Young-Hyman5, Laura Kettel Khan6, Mackenzie Magnus4, Heather King4, Sonia Arteaga7, John Cawley8,9, Christina D Economos10, Debra Haire-Joshu11, Christine M Hunter5, Bruce Y Lee12, Shiriki K Kumanyika13, Lorrene D Ritchie14, Thomas N Robinson15, Marlene B Schwartz16. 1. Centers for Behavioral and Preventive Medicine, The Miriam Hospital, Providence, RI, USA. 2. Department of Psychiatry and Human Behavior, Alpert School of Medicine, Brown University, Providence, RI, USA. 3. Department of Statistics, Northwestern University, Evanston, IL, USA. 4. Impact Genome Project, Mission Measurement, Chicago, IL, USA. 5. Office of Behavioral and Social Sciences, Office of the Director, National Institutes of Health, Bethesda, MD, USA. 6. Division of Nutrition, Physical Activity, and Obesity, Centers for Disease Control and Prevention, Atlanta, GA, USA. 7. Office of the Director, National Institutes of Health, National Institutes of Health, Bethesda, MD, USA. 8. Department of Policy Analysis and Management, Cornell University, Ithaca, NY, USA. 9. Department of Economics, Cornell University, Ithaca, NY, USA. 10. Division of Nutrition Interventions, Communication, and Behavior Change, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA. 11. Center for Obesity Prevention and Policy Research, Brown School, Washington University, Saint Louis, MO, USA. 12. CUNY Graduate School of Public Health and Policy, New York, NY, USA. 13. Department of Community Health and Prevention, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA. 14. Nutrition Policy Institute, University of California, Division of Agriculture and Natural Resources, Berkeley, CA, USA. 15. Departments of Pediatrics and Medicine, Stanford Solutions Science Lab, Stanford University, Stanford, CA, USA. 16. Department of Human Development and Family Studies, University of Connecticut, Hartford, CT, USA.
Abstract
Objective: To evaluate the efficacy of childhood obesity interventions and conduct a taxonomy of intervention components that are most effective in changing obesity-related health outcomes in children 2-5 years of age. Methods: Comprehensive searches located 51 studies from 18,335 unique records. Eligible studies: (1) assessed children aged 2-5, living in the United States; (2) evaluated an intervention to improve weight status; (3) identified a same-aged comparison group; (4) measured BMI; and (5) were available between January 2005 and August 2019. Coders extracted study, sample, and intervention characteristics. Effect sizes [ESs; and 95% confidence intervals (CIs)] were calculated by using random-effects models. Meta-regression was used to determine which intervention components explain variability in ESs. Results: Included were 51 studies evaluating 58 interventions (N = 29,085; mean age = 4 years; 50% girls). Relative to controls, children receiving an intervention had a lower BMI at the end of the intervention (g = 0.10, 95% CI = 0.02-0.18; k = 55) and at the last follow-up (g = 0.17, 95% CI = 0.04-0.30; k = 14; range = 18-143 weeks). Three intervention components moderated efficacy: engage caregivers in praise/encouragement for positive health-related behavior; provide education about the importance of screen time reduction to caregivers; and engage pediatricians/health care providers. Conclusions: Early childhood obesity interventions are effective in reducing BMI in preschool children. Our findings suggest that facilitating caregiver education about the importance of screen time reduction may be an important strategy in reducing early childhood obesity.
Objective: To evaluate the efficacy of childhood obesity interventions and conduct a taxonomy of intervention components that are most effective in changing obesity-related health outcomes in children 2-5 years of age. Methods: Comprehensive searches located 51 studies from 18,335 unique records. Eligible studies: (1) assessed children aged 2-5, living in the United States; (2) evaluated an intervention to improve weight status; (3) identified a same-aged comparison group; (4) measured BMI; and (5) were available between January 2005 and August 2019. Coders extracted study, sample, and intervention characteristics. Effect sizes [ESs; and 95% confidence intervals (CIs)] were calculated by using random-effects models. Meta-regression was used to determine which intervention components explain variability in ESs. Results: Included were 51 studies evaluating 58 interventions (N = 29,085; mean age = 4 years; 50% girls). Relative to controls, children receiving an intervention had a lower BMI at the end of the intervention (g = 0.10, 95% CI = 0.02-0.18; k = 55) and at the last follow-up (g = 0.17, 95% CI = 0.04-0.30; k = 14; range = 18-143 weeks). Three intervention components moderated efficacy: engage caregivers in praise/encouragement for positive health-related behavior; provide education about the importance of screen time reduction to caregivers; and engage pediatricians/health care providers. Conclusions: Early childhood obesity interventions are effective in reducing BMI in preschool children. Our findings suggest that facilitating caregiver education about the importance of screen time reduction may be an important strategy in reducing early childhood obesity.
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