Background:

In the United Kingdom in 2010, around three in ten boys and girls (aged 2 to 15) were classed as either overweight or obese. However, overweight and obesity rates are not currently available for the under 2s despite evidence that some infants are larger than desired. Estimates vary but it is thought that between 25% to 33% of infants gain weight rapidly during the first six months of life. Rapid weight gain during infancy is associated with obesity between 6- 8 years of age and later life. There is evidence that weight at 5 years of age is a good indicator of the future health of a child and that obesity during childhood increases the risk of adult obesity. This has a clearly measurable impact on physical and mental health, quality of life, and generates considerable direct and indirect costs. Thus, there is a compelling rationale for identifying those infants at greatest risk.

Previous work:

We have developed a risk score algorithm for overweight in childhood based on a predictor model in infants using the Millenium Cohort Study, a large British birth cohort. Stepwise logistic regression was used to determine a predictor model for childhood overweight at 3 years defined by the IOTF. A risk algorithm was developed by assigning integer values to beta-coefficients based on relative strength. Discrimination was analysed using the receiver operating characteristic (ROC) curve.The strongest predictors of overweight risk at 3 years were rapid weight gain during the first year of life, infant birth weight greater than 3.81 kg, maternal pre-pregnancy BMI from 25 kg/m^2 to 30 kg/m^2 and maternal pre-pregnancy BMI >= 30 kg/m^2. The total risk score ranged from a minimum of 0 to a maximum of 33 corresponding to a predicted risk of overweight from 5.1% to 68.8%. The c-statistic from the ROC was 0.70. While the risk algorithm has been proven to have good internal validity, we have yet to test/validate the algorithm on an external cohort.

Aim of current study:

Therefore, the aim of the current study is to determine the validity of the risk algorithm developed from the MCS using the ALSPAC data set.

Methods:

We have a developed risk equations from the MCS that we will apply to the infants in the ALSPAC cohort. We will compare the predictive risk of overweight at 3 years to the observed risk of overweight at 3 years. Discrimination will be assessed using ROC c-statistics (AUC). This will allow us to calibrate the existing risk equations if neccessary.

Key exposure variables:

Child's gender, household income, infant birth birth, infant weight gain the first year of life, maternal pre-pregnancy BMI, maternal smoking in pregnancy, infant breastfeeding status in the first year, formal childcare arrangements in the first year

Outcome variables: Child's weight at 3 years, Child's height at 3 years, Child exact age at follow-up

Final outcome:

Using those three variables, the primary clinical outcome for childhood overweight at 3 years was defined by the International Obesity Task Force sex and age-specific cut-offs corresponding to an adult BMI >= 25 kg/m^2 (Girls: 18.02 kg/m^2; Boys: 18.41 kg/m^2).

Other confounding variables for the investigation and calibration of the risk equations (We have conducted a systematic review which has informed variable selection):

Child's ethnicity, maternal marital status, maternal education, maternal employment, delivery type, maternal age, maternal alcohol consumption, maternal depression, diabetes, breastfeeding duration, formula feeding, age at introduction of solid food, infant temperment, feeding/eating, sleep, activity, SES