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1.
AIDS Behav ; 23(Suppl 2): 172-182, 2019 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-31350712

RESUMO

Supporting resilience among people living with HIV (PLHIV) is crucial to their sustained uptake of HIV services as well as psychological and social wellbeing. However, no measures exist to assess resilience specifically in relation to living with HIV. We developed the PLHIV Resilience Scale and evaluated its performance in surveys with 1207 PLHIV in Cameroon, Senegal and Uganda as part of the PLHIV Stigma Index-the most widely used tool to track stigma and discrimination among PLHIV worldwide. Factor analyses demonstrated satisfactory psychometric properties and reliability (alphas = 0.81-0.92). Levels of resilience (e.g., whether one's self-respect has been positively, negatively, or not affected by one's HIV status) varied substantially within and across countries. Higher resilience was associated with less depression in each country (all p < 0.001), and, in Cameroon and Uganda, better self-rated health and less experience of stigma/discrimination (all p < 0.001). The final 10-item PLHIV Resilience Scale can help inform interventions and policies.


Assuntos
Infecções por HIV/psicologia , Psicometria/estatística & dados numéricos , Resiliência Psicológica , Estigma Social , Inquéritos e Questionários/normas , Adulto , Camarões , Análise Fatorial , Feminino , Infecções por HIV/diagnóstico , Humanos , Masculino , Reprodutibilidade dos Testes , Senegal , Discriminação Social/psicologia , Uganda
2.
S Afr Med J ; 111(11): 1084-1091, 2021 11 05.
Artigo em Inglês | MEDLINE | ID: mdl-34949274

RESUMO

BACKGROUND: There are limited in-depth analyses of COVID-19 differential impacts, especially in resource-limited settings such as South Africa (SA). OBJECTIVES: To explore context-specific sociodemographic heterogeneities in order to understand the differential impacts of COVID-19. METHODS: Descriptive epidemiological COVID-19 hospitalisation and mortality data were drawn from daily hospital surveillance data, National Institute for Communicable Diseases (NICD) update reports (6 March 2020 - 24 January 2021) and the Eastern Cape Daily Epidemiological Report (as of 24 March 2021). We examined hospitalisations and mortality by sociodemographics (age using 10-year age bands, sex and race) using absolute numbers, proportions and ratios. The data are presented using tables received from the NICD, and charts were created to show trends and patterns. Mortality rates (per 100 000 population) were calculated using population estimates as a denominator for standardisation. Associations were determined through relative risks (RRs), 95% confidence intervals (CIs) and p-values <0.001. RESULTS: Black African females had a significantly higher rate of hospitalisation (8.7% (95% CI 8.5 - 8.9)) compared with coloureds, Indians and whites (6.7% (95% CI 6.0 - 7.4), 6.3% (95% CI 5.5 - 7.2) and 4% (95% CI 3.5 - 4.5), respectively). Similarly, black African females had the highest hospitalisation rates at a younger age category of 30 - 39 years (16.1%) compared with other race groups. Whites were hospitalised at older ages than other races, with a median age of 63 years. Black Africans were hospitalised at younger ages than other race groups, with a median age of 52 years. Whites were significantly more likely to die at older ages compared with black Africans (RR 1.07; 95% CI 1.06 - 1.08) or coloureds (RR 1.44; 95% CI 1.33 - 1.54); a similar pattern was found between Indians and whites (RR 1.59; 95% CI 1.47 - 1.73). Women died at older ages than men, although they were admitted to hospital at younger ages. Among black Africans and coloureds, females (50.9 deaths per 100 000 and 37 per 100 000, respectively) had a higher COVID-19 death rate than males (41.2 per 100 000 and 41.5 per 100 000, respectively). However, among Indians and whites, males had higher rates of deaths than females. The ratio of deaths to hospitalisations by race and gender increased with increasing age. In each age group, this ratio was highest among black Africans and lowest among whites. CONCLUSIONS: The study revealed the heterogeneous nature of COVID-19 impacts in SA. Existing socioeconomic inequalities appear to shape COVID-19 impacts, with a disproportionate effect on black Africans and marginalised and low socioeconomic groups. These differential impacts call for considered attention to mitigating the health disparities among black Africans.


Assuntos
COVID-19/epidemiologia , Disparidades nos Níveis de Saúde , Hospitalização/estatística & dados numéricos , Grupos Raciais/estatística & dados numéricos , Adolescente , Adulto , Distribuição por Idade , Idoso , Idoso de 80 Anos ou mais , COVID-19/mortalidade , Criança , Pré-Escolar , Feminino , Humanos , Lactente , Recém-Nascido , Masculino , Pessoa de Meia-Idade , Fatores de Risco , Distribuição por Sexo , Fatores Socioeconômicos , África do Sul/epidemiologia , Adulto Jovem
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