Christina Mavrogianni1, George Moschonis2, Eva Karaglani1, Greet Cardon3, Violeta Iotova4, Pilar De Miguel-Etayo5,6, Esther M González-Gil5,6,7, Κaloyan Tsochev4, Tsvetalina Tankova8, Imre Rurik9,10, Patrick Timpel11, Emese Antal10, Stavros Liatis12, Konstantinos Makrilakis12, George P Chrousos13, Yannis Manios14. 1. Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, 70 El Venizelou Ave, 176 71 Kallithea, Athens, Greece. 2. Department of Dietetics, Nutrition and Sport, School of Allied Health, Human Services and Sport, La Trobe University, Melbourne, 3086, Australia. 3. Department of Movement and Sports Sciences, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium. 4. Department of Paediatrics, Medical University of Varna, Varna, Bulgaria. 5. Growth, Exercise, Nutrition and Development (GENUD) Research Group, Instituto Agroalimentario de Aragón (IA2), Universidad de Zaragoza Instituto de Investigación Sanitaria de Aragón (IIS Aragón), 50009, Zaragoza, Spain. 6. Centro de Investigación Biomédica em Red de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28020, Madrid, Spain. 7. Department of Biochemistry and Molecular Biology II, Center of Biomedical Research (CIBM), Instituto de Nutrición y Tecnología de los Alimentos, Universidad de Granada, Granada, Spain. 8. Department of Diabetology, Clinical Center of Endocrinology, Medical University of Sofia, Sofia, Bulgaria. 9. Department of Family and Occupational Medicine, University of Debrecen, Debrecen, Hungary. 10. Hungarian Society of Nutrition, Budapest, Hungary. 11. Department for Prevention and Care of Diabetes, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Deutschland, Dresden, Germany. 12. University of Athens Medical School, National and Kapodistrian University of Athens, Athens, Greece. 13. University Research Institute of Maternal and Child Health & Precision Medicine, National and Kapodistrian University of Athens, 'Aghia Sophia' Children's Hospital, Athens, Greece. 14. Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, 70 El Venizelou Ave, 176 71 Kallithea, Athens, Greece. manios@hua.gr.
Abstract
The aim of this study was to develop and examine the predictive accuracy of an index that estimates obesity risk in childhood based on perinatal factors and maternal sociodemographic characteristics. Analysis was conducted by using cross-sectional and retrospective data collected from a European cohort of 2775 schoolchildren and their families participating in the Feel4Diabetes-study. The cohort was randomly divided by using two-thirds of the sample for the development of the index and the remaining one third for assessing its predictive accuracy. Logistic regression analyses determined a prediction model for childhood obesity. The area under the receiver operating characteristic curve (AUC-ROC), sensitivity, specificity, and positive and negative predictive values (PPV, NPV) were calculated. Cut-off analysis was applied to identify the optimal value of the index score that predicts obesity with the highest possible sensitivity and specificity. Eight factors were found to be significantly associated with obesity and were included as components in the European "Childhood Obesity Risk Evaluation" (CORE) index: region of residence, maternal education, maternal pre-pregnancy weight status, gestational weight gain, maternal smoking during pregnancy, birth weight for gestational age, infant growth velocity, and exclusive breastfeeding during the first 6 months. Risk score ranged from 0 to 22 corresponding to a risk from 0.9 to 54.6%. The AUC-ROC was 0.725 with optimal cut-off ≥9 (sensitivity = 74.1%, specificity = 61.0%, PPV = 11.3%, NPV = 97.2%). Conclusion: The European CORE index can be used as a screening tool for the identification of infants at high-risk for becoming obese at 6-9 years. This tool could assist healthcare professionals in initiating preventive measures from the early life.Trial registration: The Feel4Diabetes-intervention is registered at https://clinicaltrials.gov/ ; number, CT02393872; date, March 20, 2015. What is Known: • As prevention of obesity should start early in life, there is a compelling rationale for the early identification of high-risk children to facilitate targeted intervention. What is New: • This study developed and assessed the predictive accuracy of an index for the Childhood Obesity Risk Evaluation (CORE), combining certain perinatal factors and maternal sociodemographic characteristics in a large European cohort. • The European CORE index can be used as a screening tool for identifying infants at high-risk for becoming obese at 6-9 years and assist health professionals in initiating early prevention strategies.
The aim of this study was to develop and examine the predictive accuracy of an index that estimates obesity risk in childhood based on perinatal factors and maternal sociodemographic characteristics. Analysis was conducted by using cross-sectional and retrospective data collected from a European cohort of 2775 schoolchildren and their families participating in the Feel4Diabetes-study. The cohort was randomly divided by using two-thirds of the sample for the development of the index and the remaining one third for assessing its predictive accuracy. Logistic regression analyses determined a prediction model for childhood obesity. The area under the receiver operating characteristic curve (AUC-ROC), sensitivity, specificity, and positive and negative predictive values (PPV, NPV) were calculated. Cut-off analysis was applied to identify the optimal value of the index score that predicts obesity with the highest possible sensitivity and specificity. Eight factors were found to be significantly associated with obesity and were included as components in the European "Childhood Obesity Risk Evaluation" (CORE) index: region of residence, maternal education, maternal pre-pregnancy weight status, gestational weight gain, maternal smoking during pregnancy, birth weight for gestational age, infant growth velocity, and exclusive breastfeeding during the first 6 months. Risk score ranged from 0 to 22 corresponding to a risk from 0.9 to 54.6%. The AUC-ROC was 0.725 with optimal cut-off ≥9 (sensitivity = 74.1%, specificity = 61.0%, PPV = 11.3%, NPV = 97.2%). Conclusion: The European CORE index can be used as a screening tool for the identification of infants at high-risk for becoming obese at 6-9 years. This tool could assist healthcare professionals in initiating preventive measures from the early life.Trial registration: The Feel4Diabetes-intervention is registered at https://clinicaltrials.gov/ ; number, CT02393872; date, March 20, 2015. What is Known: • As prevention of obesity should start early in life, there is a compelling rationale for the early identification of high-risk children to facilitate targeted intervention. What is New: • This study developed and assessed the predictive accuracy of an index for the Childhood Obesity Risk Evaluation (CORE), combining certain perinatal factors and maternal sociodemographic characteristics in a large European cohort. • The European CORE index can be used as a screening tool for identifying infants at high-risk for becoming obese at 6-9 years and assist health professionals in initiating early prevention strategies.
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