The National Child Measurement Programme (NCMP) is a Government scheme established to help improve understanding of obesity prevalence and trends in children. It collects data on the height and weight of school children in Year Reception (aged 4-5 years) and Year 6 (aged 10-11 years) annually. The scheme was set up in 2006 in line with the Government’s strategy to tackle obesity and inform local planning and service delivery for children.
Measurements can be categorised as ‘underweight’, ‘healthy weight’, ‘overweight’, ‘very overweight / obese’. These are based on the child’s body mass index (BMI) which combines both height and weight measurements to give a score indicative of whether or not a child’s weight is healthy, and takes into account their age. Children falling into the overweight, very overweight / obese or severely obese categories are classified as ‘carrying excess weight’.
Wakefield has followed the pattern nationally and regionally in increases for both excess weight and obesity for both Reception Year and Year 6. Excess weight has increased in both genders, but more so in boys, and this is more evident for Year 6. Excess weight and obesity are strongly correlated with deprivation and this is illustrated in the dashboard below, which clearly shows the most deprived areas of the district (deprivation decile 1) have the highest prevalence of excess weight.
The interactive dashboard below shows the breakdown of children in Reception and Year 6 who are overweight or obese. The ‘NCMP Main’ tab shows breakdown categories for deprivation decile, ethnicity and gender. The ‘NCMP – Neighbourhoods’ tab shows the data for all the neighbourhoods across the Wakefield District.
Use the drop down filters to select school year; obese or overweight indicator; whether you wish the breakdown to show deprivation decile / ethnicity / gender / neighbourhood; year. Please note, we have grouped together 3 years’ worth of data for the neighbourhoods, this is due to the small numbers of children measured in each neighbourhood. By combining 3 years data we are able to provide more robust prevalence estimates.