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Blog entry date

26 Mar 2025

Working with census data - sexual orientation and trans status

In March 2025 we added a range of new data to our Flexible Table Builder. We’ve gone further than ever before in letting users define the small area, multivariate data they need. The table builder now includes data at data zone level for most variables. And for the first time users can build tables with the sexual orientation and trans status variables (though only at Scotland level).

We’ve now provided access to more than a billion statistics and in this blog we wanted to remind users of the supporting information available. We also wanted to highlight the practical tips we published when the table builder first went live.

When publishing census statistics, we’ve provided practical guidance on ‘working with census statistics’. For example, where population estimates show a change since the previous census smaller than +/-1%, this should be interpreted as minimal change rather than as an increase or decrease. This more practical approach was developed with reference to guidance from the Office for Statistical Regulation (OSR) on approaches to presenting uncertainty in the statistical system. We made a wide range of other supporting information available too, including topic based quality reports, imputation rates and confidence intervals.

The Flexible Table Builder enables users to access millions of statistics. So we were keen to provide some further practical guidance on using the data. This included a discussion about taking care when making comparisons between population groups, with explicit reference to the UK Armed Forces veterans population.

The veterans population is typically older than the general population. And we know that disability, for example, is closely related to age. So we might expect UK Armed Forces veterans to have a different disability profile compared to the wider population. The Scottish Government have published a report which discusses the issue of comparing the veteran and non-veteran populations in more detail.

With the inclusion of sexual orientation and trans status in the table builder it is important to reiterate the importance of age structure when working with census data. In contrast to the veteran population, the LGBTQ+ population has a younger age profile than the general population.

Figures 1 and 2 are taken from the sexual orientation and trans status or history topic report. Users should consider this younger age profile when comparing the characteristics of these groups to the wider population if there are likely to be age-related associations. And as with any set of statistics, associations do not necessarily imply causation.

We also want to remind users of the practical tips for working with detailed census data we published in 2024.

When making comparisons between population groups you should ask yourself:

 

  • what makes the group(s) I’m interested in unique/different?
  • are there any differences in the age, sex, or geographic distributions?
  • what about other characteristics?
  • are any of these differences likely to have an impact on the thing I’m measuring/comparing?

 

If the answer to these questions is yes (or maybe) then you should consider:

 

  • highlighting known differences in characteristics that might impact the comparison when presenting your analysis
  • breaking down the data to try to account for differences and compare like with like e.g. comparing older veterans with older non-veterans
  • applying a weighting to comparator groups, or standardising the data in some way e.g. age standardisation