Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, 70 El Venizelou Ave, 176 71 Kallithea, Athens, Greece.
Department of Dietetics, Nutrition and Sport, School of Allied Health, Human Services and Sport, La Trobe University, Melbourne, 3086, Australia.
Eur J Pediatr. 2021 Aug;180(8):2549-2561. doi: 10.1007/s00431-021-04090-3. Epub 2021 May 14.
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.
本研究旨在开发并检验一种基于围产期因素和产妇社会人口学特征预测儿童肥胖风险的指数的预测准确性。分析采用了横断面和回顾性数据,这些数据来自于参加 Feel4Diabetes 研究的 2775 名学龄儿童及其家庭的欧洲队列。该队列使用三分之二的样本进行指数开发,其余三分之一用于评估其预测准确性。逻辑回归分析确定了儿童肥胖的预测模型。计算了接收者操作特征曲线下的面积 (AUC-ROC)、敏感性、特异性以及阳性和阴性预测值 (PPV、NPV)。进行了截断分析以确定指数得分的最佳值,该最佳值可预测肥胖的最高敏感性和特异性。有 8 个因素与肥胖显著相关,被纳入欧洲“儿童肥胖风险评估”(CORE)指数的组成部分:居住地区、产妇教育程度、产妇孕前体重状况、妊娠期体重增加、孕期吸烟、出生体重与胎龄、婴儿生长速度以及前 6 个月的纯母乳喂养。风险评分范围为 0 至 22,对应风险为 0.9 至 54.6%。AUC-ROC 为 0.725,最佳截断值≥9(敏感性=74.1%,特异性=61.0%,PPV=11.3%,NPV=97.2%)。结论:欧洲 CORE 指数可作为识别 6-9 岁肥胖高风险婴儿的筛查工具。该工具可以帮助医疗保健专业人员在生命早期开始预防措施。试验注册:Feel4Diabetes 干预措施在 https://clinicaltrials.gov/ 注册;编号 CT02393872;日期 2015 年 3 月 20 日。已知:• 由于预防肥胖应在生命早期开始,因此迫切需要早期识别高风险儿童,以促进有针对性的干预。新发现:• 本研究开发并评估了一种用于儿童肥胖风险评估(CORE)的指数的预测准确性,该指数结合了某些围产期因素和产妇社会人口学特征,用于一个大型的欧洲队列。• 欧洲 CORE 指数可作为识别 6-9 岁肥胖高风险婴儿的筛查工具,并帮助卫生专业人员启动早期预防策略。