스웨덴 등록 자료: 성별 불쾌감을 진단받은 사람의 사망률이 일치 대조군의 거의 두 배

2001~2023년 스웨덴 성별 불쾌감 개인의 전체 원인 및 원인별 사망률 전국 추정: 등록 자료 기반 코호트 연구

Authors: Kristen D. Clark, Richard A. White, Sarah S. Jackson, Alkistis Skalkidou, Thomas Frisell, Fotios C. Papadopoulos
Journal: EClinicalMedicine
Year: 2026
Source: https://doi.org/10.1016/j.eclinm.2026.104088

Summary

Swedish researchers found everyone diagnosed with gender dysphoria in national health records between 2001 and 2023, about 9,000 people who were about 25 on average when diagnosed. They compared deaths with men and women of the same age and county. Over about seven years, 211 people with gender dysphoria died, almost twice the death rate of the comparison groups after allowing for age. Extra deaths came from accidents, violence and suicide (suicide was not counted on its own), from unclear causes, from mental and brain conditions such as drug or alcohol problems, and from cancer in people born female. The authors call for public health action but say the records cannot explain why. Nothing beyond age and county was taken into account, and many causes had very few deaths. So the study shows a gap in deaths but not what causes it.

Key findings

연구는 2001~2023년 스웨덴에서 성별 불쾌감 진단을 받은 9,038명(출생 시 남성 4,181명, 여성 4,857명)을 나이와 지역이 같은 179,816명과 비교했습니다.
사망은 211건이었고, 나이를 고려한 뒤 사망률은 연간 1만 명당 183명 대 96명으로 약 두 배 높았습니다.
출생 시 남성에서 사망률은 여성의 2.3배, 남성의 1.6배였으며, 사고, 폭력, 자살(3.2배와 2.5배), 불분명한 원인(약 5배), 정신 또는 뇌 질환(3.6배와 2.6배)으로 인한 사망이 더 많았습니다.
출생 시 여성에서 사망률은 여성의 2.1배, 남성의 1.7배였으며, 사고, 폭력, 자살(2.2배와 1.5배)과 암(2.4배와 1.8배)으로 인한 사망이 더 많았습니다.
자살, 살인, 사고가 함께 211건의 사망 중 76건(36%)을 차지했지만, 자살은 따로 보고되지 않았습니다.
평균적으로 각 사망은 출생 시 남성에서는 (남성과 비교해) 6년, 출생 시 여성에서는 (여성과 비교해) 9년 일찍 일어났습니다.
저자들은 이 결과가 사망을 추적하기 위한 출발점일 뿐, 원인이나 치료의 효과에 대한 증거가 아니라고 말합니다.

Abstract

BACKGROUND: Transgender and gender-diverse (TGD) people experience elevated mortality risk, yet population-based estimates of cause-specific mortality remain limited. Prior studies have focused on narrow subgroups or outdated cohorts, leaving gaps in understanding current mortality disparities. Therefore, the purpose of this study is to quantify all-cause and cause-specific mortality among all TGD adults with a diagnosis of gender dysphoria in Sweden. METHODS: This cohort study provides national cause-specific mortality estimates among TGD adults in Sweden using registry data (2001-2023). TGD people were identified using ICD-10 codes for "gender dysphoria" and matched to approximately 10 cisgender controls of each sex by age and county. Age-standardized mortality rates, absolute mortality risk differences, mortality rate ratios (MRR), and years of potential life lost (YPLL) were calculated overall and stratified by sex assigned at birth. FINDINGS: A total of 9038 TGD people were identified, among them, 211 deaths were observed. All-cause mortality risk was almost twice that of the cisgender comparison group (MRR = 1.9, 95% confidence interval [CI] 1.7, 2.2). Stratified analyses showed distinct mortality patterns for transfeminine (assigned male sex at birth) and transmasculine (assigned female sex at birth) people, with higher risk from ill-defined diseases among transfeminine people (cisgender women as reference: MRR = 4.9, 95% CI 2.3, 10.3; cisgender men: MRR = 5.5, 95% CI 2.6, 11.4) and transmasculine people from neoplasms (cisgender women: MRR = 2.4, 95% CI 1.4, 4.1; cisgender men: MRR = 1.8, 95% CI 1.1, 3.1). These disparities resulted in a mean of 6.3 YPLL for transfeminine people compared to cisgender men and 9.0 YPLL for transmasculine people compared to cisgender women. INTERPRETATION: These findings highlight persistent health inequities and underscore the need for targeted public health interventions and an evaluation of data collection processes to improve health monitoring and support TGD populations in Sweden. FUNDING: The present study was funded by a Starting Grant (2023-01397) and a project grant (2021-01968) from the Swedish Research Council for Health, Working Life and Welfare (FORTE).

Conclusion

These findings highlight persistent health inequities and underscore the need for targeted public health interventions and an evaluation of data collection processes to improve health monitoring and support TGD populations in Sweden. The authors note that registry data cannot distinguish whether excess deaths result from biological factors, behavioural risks, systemic barriers or administrative biases. They state that future research linking clinical treatment records to mortality is required, and that the findings serve primarily as a baseline for monitoring mortality trends rather than evidence of specific causal pathways.

Methodological limitations

Almost nothing taken into account: People were only matched on age and county. The study did not account for mental illness, drug use, smoking, income or past self-harm, all of which strongly predict the kinds of deaths behind much of the gap.
No treatment information: There is no data on hormones or surgery, so the study cannot say whether medical transition is linked to more or fewer deaths, as the authors note.
Suicide not counted on its own: Suicide was lumped in with accidents and violence, so the study gives no suicide figure despite how important it is.
Very few deaths for many causes: Many cause-of-death figures rest on fewer than 5 to 10 deaths, so they are very uncertain. For example, deaths from nutrition-related conditions were 22 times higher, but the true figure could be anywhere from 2 to 243 times. Some results look implausible, such as almost no mental or brain-related deaths among people born female.
Age adjustment skews the numbers: Rates were adjusted to match Sweden's whole 2023 population, although the people studied were about 25 on average. This gives a few deaths at older ages a lot of weight, such as a high cancer rate in people born female based on 15 deaths.
Many comparisons, some likely chance: About 15 causes of death were compared against two groups for each sex without correcting for the number of tests, so some "significant" findings may be chance.
Unclear causes on death records: The extra deaths with unclear causes may come from paperwork problems (such as ID numbers changing after a legal gender change) or from accidents and violence not properly recorded, which the authors admit.
Only people with a diagnosis: Only people with a recorded diagnosis were included, which over-represents those in contact with specialist care and leaves out those on waiting lists. Diagnoses from age 10 were counted, although the group is described as adults.
Errors in the tables: The first table has apparent mistakes, such as 411,146 comparison people born outside the Nordic countries in a group of only 179,816, and text calling 18.5% "slightly higher" than 19.5–20.4%. Reported figures should be treated with care.
Explanation not tested: The discussion mainly blames stress from being a minority and barriers to healthcare, but the data did not measure either.

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Summary

Key findings

Abstract

Conclusion