New research reveals over 2.8 million trans individuals in the United States
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A study from the Williams Institute at UCLA School of Law has revealed that more than 2.8 million people aged 13 and older in the United States identify as trans, representing approximately 1% of the population in that age group.
The research, based on data collected between 2021 and 2023 from federal surveys and state health agencies, offers one of the most comprehensive portraits of the trans population in the US to date. It found that 724,000 youth aged 13 to 17 identify as transgender, accounting for 3.3% of that age group, while 2.1 million adults (0.8%) also identify as trans.
The demographic breakdown shows that trans individuals tend to be significantly younger than the general population. A striking 76% of trans people are under the age of 35, compared to just 34% of the overall US population.
Among young adults aged 18 to 24, 2.72% identify as trans, while the percentage drops to 0.42% among those aged 35 to 64, and 0.26% for those 65 and older.
The study also highlighted gender diversity within the trans community: 32.7% identify as trans women, 34.2% as trans men, and the remainder as non-binary or gender diverse.
Dr Jody Herman, senior scholar of public policy at the Williams Institute and co-author of the report, emphasised the importance of recognising the unique needs of this population: “This is a substantial population that has unique concerns and barriers to getting their needs met, and lawmakers need to keep that in mind,” she said.
The release of this data comes amid significant political controversy. President Donald Trump signed an executive order declaring that the US government will officially recognise only two genders - male and female - prompting concerns about the erasure of trans individuals from federal surveys and public policy.
Researchers warn that this may be the last opportunity for a comprehensive analysis of the transgender population for years to come, as federal agencies begin removing references to gender diversity from critical datasets.
