Characterising the impact of COVID-19 environment on mental health, gender affirming services and socioeconomic loss in a global sample of transgender and non-binary people: a structural equation modelling

BackgroundWe characterised the impact of COVID-19 on the socioeconomic conditions, access to gender affirmation services and mental health outcomes in a sample of global transgender (trans) and non-binary populations.MethodsBetween 16 April 2020 and 3 August 2020, we conducted a cross-sectional surv...

Full description

Saved in:
Bibliographic Details
Published in:BMJ global health 2021-03, Vol.6 (3), p.e004424
Main Authors: Restar, Arjee Javellana, Jin, Harry, Jarrett, Brooke, Adamson, Tyler, Baral, Stefan David, Howell, Sean, Beckham, S Wilson
Format: Article
Language:English
Subjects:
Adult
Anxiety
Bias
Coronaviruses
COVID-19
COVID-19 - economics
COVID-19 - psychology
Cross-Sectional Studies
Environmental factors
Epidemiology
Female
Gender identity
Gender-affirming care
Global health
Health disparities
Humans
Hypotheses
Latent Class Analysis
Low income groups
Male
Medical research
Mental depression
Mental disorders
Mental Disorders - epidemiology
Mental health
Middle Aged
Non-binary gender
Original Research
Pandemics
Pandemics - economics
Pneumonia, Viral - economics
Pneumonia, Viral - psychology
Pneumonia, Viral - virology
Prevalence
Public health
SARS-CoV-2
Social Media
Socioeconomic Factors
Socioeconomics
Statistical methods
Structural equation modeling
Transgender persons
Transgender Persons - psychology
Variables
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:BackgroundWe characterised the impact of COVID-19 on the socioeconomic conditions, access to gender affirmation services and mental health outcomes in a sample of global transgender (trans) and non-binary populations.MethodsBetween 16 April 2020 and 3 August 2020, we conducted a cross-sectional survey with a global sample of trans and non-binary people (n=849) through an online social networking app. We conducted structural equational modelling procedures to determine direct, indirect and overall effects between poor mental health (ie, depression and anxiety) and latent variables across socioecological levels: social (ie, reduction in gender affirming services, socioeconomic loss impact) and environmental factors (ie, COVID-19 pandemic environment).ResultsAnxiety (45.82%) and depression (50.88%) in this sample were prevalent and directly linked to COVID-19 pandemic environment. Adjusted for gender identity, age, migrant status, region, education and level of socioeconomic status, our final model showed significant positive associations between relationships of (1) COVID-19 pandemic environment and socioeconomic loss impact (β=0.62, p
ISSN:2059-7908
2059-7908
DOI:10.1136/bmjgh-2020-004424