Scottish Health Survey – telephone survey – August/September 2020: 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

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.

Unlike the face-to-face survey where a considerable proportion of the questions are age specific, this was the case for very few questions in the SHeS 2020 telephone survey with most questions asked of all adults aged 16 and over who took part. The exception to this was a question on pregnancy which was only asked to woman aged 16-49.

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, 2020 and was interviewed on September 1, 2020 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.

Due to sample sizes, the SHeS 2020 report tables are presented using a four age band split rather than the seven category age split used when reporting SHeS data collected via face to face data collection.

1.8.2 Design effects and true standard errors

The SHeS 2020 telephone survey used a stratified 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 shown in tables, and comments on statistical significance throughout the report, have taken the 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 the SHeS 2020 telephone survey 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 shown in Tables 1.6A to 1.13 for selected survey estimates presented in the main report. Tables 1.6A - 1.13