Discrimination based on gender identity against transgender women and travestis in Brazil: a latent class analysis and associated factors (Q30011): Difference between revisions
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Discrimination based on gender identity against transgender women and travestis in Brazil | |||
Revision as of 17:43, 8 November 2024
No description defined
- Discrimination based on gender identity against transgender women and travestis in Brazil: a latent class analysis and associated factors.
- Discrimination based on gender identity against transgender women and travestis in Brazil
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Discrimination based on gender identity against transgender women and travestis in Brazil: a latent class analysis and associated factors |
No description defined |
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Statements
To identify groups of transgender women and travestis (TGW) with specific patterns of gender-based discrimination (GBD) and analyze the factors associated with GBD. (English)
A cross-sectional study was conducted with TGW recruited through respondent-driven sampling in five Brazilian cities (2019-2021). (English)
Latent class analysis was used to characterize GBD (low, medium, and high) using 14 observable variables. (English)
Descriptive analysis was performed, and associations between predictor variables and GBD were estimated by adjusted odds ratios (aOR) using ordinal logistic regression. (English)
Out of a total of 1,317 TGW, 906 (68.8%) answered questions about GBD. (English)
Most were under 34 years old, single, and had a Brown race/skin color. (English)
GBD was classified as "low," "medium," and "high," with estimates of 41.7, 44.5, and 13.8%, respectively. (English)
Variables positively associated with higher intensity of GBD included living in Manaus compared to São Paulo, being ≤34 years old compared to >34, being homeless compared to living in one's own house or rented apartment, not having legally changed one's name compared to those who had, and reporting physical or sexual violence compared to those who did not report. (English)
Variables negatively associated with higher intensity of GBD included having a Brown or Asian race/skin color compared to White and a monthly income ≥1 minimum wage compared to ³1. (English)
A high proportion of GBD was observed in Brazilian TGW, with this outcome associated with more vulnerable sociodemographic characteristics and a history of violence. (English)
Identificar grupos de mulheres trans e travestis (MTT) com padrões específicos de discriminação por identidade de gênero (DIG) e analisar os fatores associados à DIG. (Portuguese)
Estudo transversal com MTT recrutadas por <i>respondent-driven sampling</i> em cinco capitais brasileiras (2019-2021). (Portuguese)
Análise de classes latentes foi usada para caracterizar a DIG (em baixa, média e alta) usando 14 variáveis observáveis. (Portuguese)
Análise descritiva foi realizada e as associações entre variáveis preditoras e DIG foram estimadas por <i>odds ratio</i> ajustados (ORaj), usando regressão logística ordinal. (Portuguese)
Do total de 1.317 MTT, 906 (68,8%) responderam perguntas sobre DIG. (Portuguese)
A maioria apresentava idade ≤34 anos, solteiras e com raça/cor de pele parda. (Portuguese)
DIG foi classificada em “baixa”, “média” e “alta”, com estimativas de 41,7, 44,5, 13,8%, respectivamente. (Portuguese)
As variáveis positivamente associadas à maior intensidade de DIG foram: morar em Manaus em comparação com São Paulo; possuir idade £34 anos em comparação com idade >34; estar em situação de rua em comparação com quem mora em casa ou apartamento próprio ou alugado; não ter retificado o nome em documento em comparação com quem retificou; e relato de violência física ou sexual em comparação com [...] (Portuguese)
As variáveis negativamente associadas à maior intensidade de DIG foram: raça/cor de pele parda ou amarela em comparação com branca; e renda média mensal <1 salário mínimo em comparação com ≥1 salários. (Portuguese)
Observaram-se alta proporção de DIG em MTT brasileiras e associação desse desfecho com características sociodemográficas mais vulneráveis e histórico de violência. (Portuguese)
Laio (English)
Magno (English)
L
Beo Oliveira (English)
Leite (English)
BO
Sandro (English)
Sperandei (English)
S
Marcos (English)
Pereira (English)
M
Daniela Riva (English)
Knauth (English)
DR
Andréa Fachel (English)
Leal (English)
AF
Maria Amélia de Sousa Mascena (English)
Veras (English)
MASM
Inês (English)
Dourado (English)
I
23 August 2024
21 August 2024
<b>Conflict of interests:</b> nothing to declare. (English)