Data collection and publication - age: guidance

Analysis and presentation of results

Data should be analysed and presented in the way that is most useful to users of that data. Consideration should be given to which types of analysis would most likely reveal any inequalities that require action, which will depend on the subject area to which the data relates. Statistical disclosure issues should always be considered when publishing data.

Age range harmonisation

There are no harmonised age bands or categories for use in Scotland. Scotland's Census 2022 outputs will be primarily disseminated via the Flexible Table Builder^[6] which should allow users to use different age bands to suit their needs. There is a need to maintain comparability with previous Census data so pre-built tables are likely to reflect the classification used in the 2011 outputs. The age bands used in reporting 2011 data were 0-15, 16-24, 25-49, 50-64, and 65+. Those interested in comparing against certain variables should consider reviewing the published 2011 statistics.^[7]

The ONS provides six groupings for outputs of age data, depending on purpose and data quality. While they are not recommended by the Scottish Government, they are linked below for reference.^[8]

Unknown age

Where age is unknown the data should either be presented as 'unknown' or 'missing' or if missing values are unacceptable for your analysis it may be worth imputing the missing values.

Ambiguous terminology

It is recommended that data are presented with age group labels that are unambiguous, such as 'age 65 years and over' or '16 years and under'. Due to changes in the state pension age (specifically the current female state pension age which is changing dynamically to match the male state pension age) the phrases 'pensionable age' and 'pensionable adults' should not be used. Instead, data should be presented clearly stating the age range to which it refers. For the same reason the terms 'working age' and 'working age adults' should not be used. In addition, the term 'child' or 'school age' may mean different things to different people and should, therefore, also be avoided.

Definitions of 'adult' and 'child'

There is some variation regarding who constitutes an adult in Scottish law, depending on the context. The Age of Majority (Scotland) Act 1969^[9] states that:

"a person shall attain majority on attaining the age of eighteen"

Similarly, the Children and Young People (Scotland) Act 2014^[10] references the UN Convention on the Rights of the Child (UNCRC)^[11] which states that:

"a child means every human being below the age of 18 years unless under the law applicable to the child, majority is attained earlier"

Conversely, the Age of Legal Capacity (Scotland) Act 1991^[12] states that:

"a person of or over the age of 16 years shall have legal capacity to enter into any transaction"

As long as the context of a report is one in which 16-17 year olds are considered legally capable, and therefore have the same rights and restrictions as those of or over the age of 18, it is acceptable to refer to a group of people aged 16+ as 'adults'.

Intersectionality

An intersectional analysis gives an insight into how a combination of socio-demographic characteristics might relate to specific forms of disadvantage. For example disadvantage for a young minority ethnic woman may be different to a young white man.

There is an increasing awareness that taking an intersectional approach to hresearch, policy making and operational decisions is important. This is because intersectionality can give insight into the experiences of different groups in society, and how particular characteristics can combine to impact on an individual's experiences. However, there is not always disaggregated data available to support such an approach. This is likely to mean that the information on which important decisions are made is not fully representative of the population it is intending to measure.

For example, data on demographic characteristics may be collected by a public body, but not disaggregated in an intersectional way due to issues around sample size and risk of disclosing an individual's identity. In these cases, organisations should not risk disclosing information about an individual's age.

Where sample size and quality allows, data should be disaggregated, including by sex, gender reassignment, race, religion or belief, age, disability, and sexual orientation, where combinations of these factors can result in discrimination, disadvantage and inequality. Being able to identify cases where combinations of factors are resulting in disadvantage enables policies to be developed and action taken to address these issues.