8.1. Appendix A: Details of Key Variables
Weekly duration of ELC attendance
One of the key measures of ELC use considered in this report is the average number of hours children attend ELC on a weekly basis. Across both cohorts and age points, this measure is based on parent report and includes both funded and unfunded hours. The way in which attendance was reported differed slightly across cohorts and age points.
- In BC1, at both age points, parents were asked to estimate how many hours of pre-school the child attended on a weekly basis. 
- In BC2, cases where ELC data were collected during the age 4 interview and where this took place before 1 st August 2014, parents were asked to indicate how long the child attended pre-school on each day of the week to the nearest half hour.
- In BC2, cases where ELC data were collected during the age 4 interview and where this took place after 1 st August 2014, parents were asked to indicate how long the child attended pre-school on each day of the week to the nearest ten minutes.
- Finally, in BC2, cases where ELC data were collected as part of the age 5 interview, parents were asked how long the child spent at pre-school for each day of the week. Hours and minutes were recorded separately, allowing for reporting of pre-school attendance detailed to the nearest minute.
To enable comparison, all measures of ELC attendance were adapted to a format where .5 denotes half an hour. For BC2 data this was done, first, for each day of the week. The average number of hours was then derived as a total of the time entered for each day of the week. Because the data were collected in different ways, the measures of ELC attendance are not directly comparable across cohorts and age points and results must be interpreted with caution. The analysis uses both continuous and banded measures of ELC attendance.
Equivalised annual household income (quintiles)
In GUS, overall income is measured at household level before tax. At each interview, parents are asked to provide information about the amount of income they receive. This covers all sources of income including earnings, benefits, tax credits and interest from savings. Amounts can be given as either weekly, monthly or annual amounts which are adjusted to produce a single annual figure.
These figures are then 'equivalised' to reflect differences in household size and composition, as these factors affect the income level required to attain a particular living standard. For example, a couple with dependent children will need a higher income than a single person with no children to attain the same material living standards.
The equivalised household income measure enables comparison between households of different size and composition. Furthermore, it also enables comparison over time and, in the case of GUS, between the two cohorts. After equivalisation, the sample is split into five, equally-sized groups - or quintiles - according to income distribution. Each group thus contains around 20% of families.
However, because the income data on GUS is collected in a series of ranges (e.g. £10,400 to £15,599, £15,600 to £20,799 and so on) rather than as a scale of specific, individual values (e.g. £12,457) the split can be slightly imprecise and some groups may contain slightly more or less than 20%. It is also important to note that the groups are split relative to the spread of income for that cohort and sweep of data collection rather than in reference to a fixed cut-off point. As such, the cut-off point denoting the maximum annual income of the poorest 20% of families in BC1 will be different to the cut-off point for the equivalent group in BC2. Nevertheless, in each cohort the lowest and highest quintiles will represent the richest and poorest 20% of families with a child of that particular age.
Highest household level of education
At the first wave of data collection for both cohorts, parents were asked to provide information on the nature and level of any school and post-school qualifications they had obtained. This information was obtained for up to two adults in the household (the main adult respondent and, where applicable, their partner) and was updated at each subsequent contact. Qualifications were grouped according to their equivalent position on the Scottish Credit and Qualifications Framework which ranges from Access 1 to Doctorate. For the purposes of the analysis carried out for this report, these were further banded to create the following categories:
- Degree level qualifications
- Higher standard grades and upper level vocational qualifications
- Upper standard grades and intermediate vocational qualifications
- No qualifications, lower standard grades and vocational and other qualifications
The highest qualification was defined for each parent and a household level variable was calculated. In couple families this corresponds to the highest classification among the respondent and his/her partner.
Area deprivation ( SIMD)
Area deprivation was measured using the Scottish Index of Multiple Deprivation ( SIMD) which identifies small area concentrations of multiple deprivation across Scotland. It is based on 37 indicators in the seven individual domains of Current Income, Employment, Health, Education Skills and Training, Geographic Access to Services (including public transport travel times for the first time), Housing and a new Crime Domain. SIMD is presented at data zone level, enabling small pockets of deprivation to be identified. The data zones, which have a median population size of 769, are ranked from most deprived (1) to least deprived (6,505) on the overall SIMD and on each of the individual domains. The result is a comprehensive picture of relative area deprivation across Scotland.
In this report the data zones have been grouped into quintiles. Quintiles are percentiles which divide a distribution into fifths, i.e., the 20th, 40th, 60th, and 80th percentiles. Those respondents whose postcode falls into the first quintile are said to live in one of the 20% least deprived areas in Scotland. Those whose postcode falls into the fifth quintile are said to live in one of the 20% most deprived areas in Scotland.
Further details on
be found on the Scottish Government Website
The Scottish Government Urban Rural Classification was first released in 2000 and is consistent with the Government's core definition of rurality which defines settlements of 3,000 or less people to be rural. It also classifies areas as remote based on drive times from settlements of 10,000 or more people. The definitions of urban and rural areas underlying the classification are unchanged.
The classification has been designed to be simple and easy to understand and apply. It distinguishes between urban, rural and remote areas within Scotland and includes the following categories:
- 'Large Urban Areas': Settlements of 125,000 people or more
- 'Other Urban Areas': Settlements of 10,000 to 124,999 people
- 'Accessible Small Towns': Settlements of between 3,000 and 9,999 people and within 30 minutes' drive of a settlement of 10,000 or more
- 'Remote Small Towns': Settlements of between 3,000 and 9,999 people and with a drive time of over 30 minutes to a settlement of 10,000 or more
- 'Accessible Rural': Settlements of less than 3,000 people and within 30 minutes' drive of a settlement of 10,000 or more
- 'Remote Rural': Settlements of less than 3,000 people and with a drive time of over 30 minutes to a settlement of 10,000 or more
For further details on the classification see the Scottish
For the purposes of this report, the above were banded into three categories:
- Urban areas (large and other urban areas)
- Towns (accessible and rural small towns)
- Rural areas (accessible and remote rural areas)
Socio-economic classification ( NSSEC) (highest level in household)
This variable draws on the National Statistics Socio-Economic Classification ( NSSEC). It comprises five different occupational classifications:
- Managerial and professional occupations
- Intermediate occupations
- Small employers and own account holders
- Lower supervisory and technical occupations
- Semi routine and routine occupations
- Never worked