Appendix 2: Glossary

Body mass index (BMI) is a measure of weight adjusted for height. In this report, BMI was derived from both self-reported and interviewer-measured values. BMI is calculated by dividing weight in kilograms by the square of height in metres (kg/m²). BMI in this report is classified into five categories:

• underweight (BMI less than 18.5kg/m²)
• normal or healthy weight (BMI 18.5 to 24.9kg/m²)
• overweight (BMI 25.0 to 29.9kg/m²)
• obese grades I and II (BMI 30.0 to 39.9kg/m²)
• obese grade III (BMI 40+kg/m²)

The Frankfort Plane is an imaginary line passing through the external ear canal and across the top of the lower bone of the eye socket, immediately under the eye. A participant’s head is positioned so that the Frankfort Plane is horizontal. In this position the headplate of the stadiometer will rest on the crown of the head. This measures maximal height.

The English Index of Multiple Deprivation (IMD) is a measure of area deprivation based on 37 indicators, across seven domains of deprivation. IMD is a measure of the overall deprivation experienced by people living in a neighbourhood, although not everyone who lives in a deprived neighbourhood will be deprived themselves. To enable comparisons, areas are classified into quintiles (fifths).

A p-value is the probability of the observed result occurring due to chance alone. A p-value of less than 5% is conventionally taken to indicate a statistically significant result (p<0.05). It should be noted that the p-value is dependent on the sample size, so that with large samples differences or associations which are very small may still be statistically significant. Results should therefore be assessed for their importance on the magnitude of the differences or associations as well as on the p-value itself.

In a linear regression model, the value of R² represents the percentage of variance in the outcome variable which is explained by the predictor variables in the model.

Regions are based on the nine former Government Office Regions: North East, North West, Yorkshire and the Humber, East Midlands, West Midlands, East of England, London, South East and South West.

The bias associated with using self-reported data for height and weight (and BMI derived from these) was estimated by calculating the difference between self-reported and interviewer-measured values. A positive difference indicates overestimation (for example over-reporting of height), and a negative difference, underestimation (for example under-reporting of weight).

The degree of misclassification that resulted from using BMI derived from self-reported height and weight to estimate the prevalence of the various BMI categories was assessed by calculating sensitivity and specificity. Sensitivity is the percent of true positives, and specificity, the percent of true negatives. For example, for obesity (BMI 30kg/m² or more), sensitivity is the percentage of participants classified as obese based on self-reported data among those classified as obese based on measured data; in other words, the percentage of obese participants (according to measured BMI) who reported themselves as such. Specificity is the percentage of participants classified as not obese (BMI less than 30kg/m²) based on self-reported values among those who were not obese based on measured values; that is, the percentage of participants who reported that they were not obese among those classified by measured data as being non-obese.

The statistical significance of an estimate is based on the probability of its occurring due to chance alone. Within this report, estimates are assumed to be statistically significant if they have a p-value of less than 0.05 or less, that is a probability of occurring by chance below 5%. Statistical significance does not imply substantive importance; differences that are statistically significant are not necessarily meaningful or relevant.

See also P-value