Validation, Optimal Threshold Determination, and Clinical Utility of the Infant Risk of Overweight Checklist for Early Prevention of Child Overweight

• Published in: Childhood obesity 2016-06, Vol.12 (3), p.202-209
• Main Authors: Redsell, Sarah A, Weng, Stephen, Swift, Judy A, Nathan, Dilip, Glazebrook, Cris
• Format: Article
• Language: English
• Subjects: Algorithms; Checklist - standards; Child, Preschool; Female; Humans; Infant; Longitudinal Studies; Male; Original; Parents; Pediatric Obesity - prevention & control; Reference Values; Risk Assessment; Risk Factors; United Kingdom - epidemiology
• ISSN: 2153-2168; 2153-2176
• DOI: 10.1089/chi.2015.0246

Previous research has demonstrated the predictive validity of the Infant Risk of Overweight Checklist (IROC). This study further establishes the predictive accuracy of the IROC using data from the Avon Longitudinal Study of Parents and Children (ALSPAC) and examines the optimal threshold for determining high risk of childhood overweight. Using the IROC algorithm, we calculated the risk of being overweight, based on International Obesity Task Force criteria, in the first year of life for 980 children in the ALSPAC cohort at 5 years. Discrimination was assessed by the area under the receiver operating curve (AUC c-statistic). Net reclassification index (NRI) was calculated for risk thresholds ranging from 2.5% to 30%, which determine cutoffs for identifying infants at risk of becoming overweight. At 5 years of age, 12.3% of boys and 19.6% of girls were categorized overweight. Discrimination (AUC c-statistic) ranged from 0.67 (95% confidence interval [CI], 0.62-0.72) when risk scores were calculated directly to 0.93 (95% CI, 0.88-0.98) when the algorithm was recalibrated and missing values of the risk factor algorithm were imputed. The NRI showed that there were positive gains in reclassification using risk thresholds from 5% to 20%, with the maximum NRI being at 10%. This study confirms that the IROC has moderately good validity for assessing overweight risk in infants and offers an optimal threshold for determining high risk. The IROC algorithm has been imbedded into a computer program for Proactive Assessment of Obesity Risk during Infancy, which facilitates early overweight prevention through communication of risk to parents.