The Scottish Health Survey 2024 - Volume 2: Technical Report

1.8   Data analysis and reporting

SHeS is a cross-sectional survey of the population. It examines associations between health status, personal characteristics and behaviour. However, such associations do not necessarily imply causality. In particular, associations between current health status and current behaviour need careful interpretation, as current health may reflect past, rather than present, behaviour. Similarly, current behaviour may be influenced by advice or treatment for particular health conditions.

1.8.1     Reporting age variables

Defining age for data collection

A considerable part of the data collected in SHeS 2024 is age specific, with different questions directed to different age groups. During the interview the participant’s date of birth was ascertained. For data collection purposes, a participant’s age was defined as their age on their last birthday before the interview.

Age as an analysis variable

Age is a continuous variable, and an exact age variable on the data file expresses it as such (so that, for example, someone whose 24th birthday was on January 1, 2024 and was interviewed on October 1, 2024 would be classified as being aged 24.75).

The presentation of tabular data involves classifying the sample into year bands. This can be done in two ways, age at last birthday and ‘rounded age’, that is, rounded to the nearest integer. In this report, all references to age are age at last birthday.

Some of the adult data included in the 2024 report have been age-standardised to allow comparisons between groups after adjusting for the effects of any differences in their age distributions. Further information on age standardisation can be found in chapter 2 of this report.

1.8.2     Standard analysis breakdowns

Scottish Index of Multiple Deprivation (SIMD)

The analysis of 2024 data was based on the most recent version of the Scottish Index of Multiple Deprivation (SIMD), which can be found in the methods section of the Scottish Health Survey dashboard. It is based on 38 indicators in seven individual domains of current income, employment, housing, health, education, skills and training, geographic access to services and crime. SIMD is calculated at data zone level, enabling small pockets of deprivation to be identified. The data zones are ranked from most deprived (1) to least deprived (6,976) on the overall SIMD index. The result is a comprehensive picture of relative area deprivation across Scotland. The index was divided into quintiles for the presentation of analysis within this report. The full index is not available on the archived dataset due to concerns about its potential for identifying individual respondents or households.

1.8.3     Design effects, true standard errors and confidence intervals

SHeS 2024 used a partially clustered, stratified multi-stage sample design. In addition, weights were applied when obtaining survey estimates. One of the effects of using the complex design and weighting is that standard errors for survey estimates are generally higher than the standard errors that would be derived from an unweighted simple random sample of the same size. The calculations of standard errors and confidence intervals shown in tables, and comments on statistical significance throughout the report, have taken the clustering, stratification and weighting into account. The ratio of the standard error of the complex sample to that of a simple random sample of the same size is known as the design factor. Put another way, the design factor (or ‘deft’) is the factor by which the standard error of an estimate from a simple random sample has to be multiplied to give the true standard error of the complex design. The true standard errors and defts for SHeS 2024 have been calculated using a Taylor Series expansion method. The deft values and true standard errors (which are themselves estimates subject to random sampling error) are used to calculated the confidence intervals presented in the survey tables and dashboard.