Validity of Scottish predictors of child obesity (age 12) for risk screening in mid-childhood: a secondary analysis of prospective cohort study data-with sensitivity analyses for settings without various routinely collected predictor variables

Objective To analyse the Growing Up in Scotland cohort for predictors of obesity at age 12, present at school entry (age 5-6). Methods The initial model included literature-based risk factors likely to be routinely collected in high-income countries (HICs), as well as Adverse/Protective Childhood Experiences (ACEs/PCEs). Missing data were handled by Multiple Chained Equations. Variable-reduction was performed using multivariable logistic regression with backwards and forwards stepwise elimination, followed by internal validation by bootstrapping. Optimal sensitivity/specificity cut-offs for the most parsimonious and accurate models in two situations (optimum available data, and routinely available data in Scotland) were examined for their referral burden, and Positive and Negative Predictive Values. Results Data for 2787 children with full outcome data (obesity prevalence 18.3% at age 12) were used to develop the models. The final Optimum Data model included six predictors of obesity: maternal body mass index, indoor smoking, equivalized income quintile, child's sex, child's BMI at age 5-6, and ACEs. After internal validation, the area under the receiver operating characteristic curve was 0.855 (95% CI 0.852-0.859). A cut-off based on Youden's J statistic for the Optimum Data model yielded a specificity of 77.6% and sensitivity of 76.3%. 37.0% of screened children were Total Screen Positives (and thus would constitute the referral burden.) A Scottish Data model, without equivalized income quintile and ACEs as a predictor, and instead using Scottish Index of Multiple Deprivation quintile and age at introduction of solid foods, was slightly less sensitive (76.2%) but slightly more specific (79.2%), leading to a smaller referral burden (30.8%). Conclusion Universally collected, machine readable and linkable data at age 5-6 predict reasonably well children who will be obese by age 12. However, the Scottish treatment system is unable to cope with the resultant referral burden and other criteria for screening would have to be met.

Automated summary

The study analyzed data from the Growing Up in Scotland cohort to predict obesity at age 12 based on information collected at age 5-6. Six predictors of obesity were identified: maternal body mass index, indoor smoking, equivalized income quintile, child's sex, child's BMI at age 5-6, and ACEs. The models showed good predictive accuracy but highlighted challenges in managing the referral burden in the Scottish treatment system.