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Importance of sex and gender factors for COVID-19 infection and hospitalisation: a sex-stratified analysis using machine learning in UK Biobank data.
Azizi, Zahra; Shiba, Yumika; Alipour, Pouria; Maleki, Farhad; Raparelli, Valeria; Norris, Colleen; Forghani, Reza; Pilote, Louise; El Emam, Khaled.
Afiliación
  • Azizi Z; Centre for Outcomes Research and Evaluation, McGill University Health Centre, Montreal, Québec, Canada.
  • Shiba Y; Department of Biology, McGill University, Montreal, Québec, Canada.
  • Alipour P; Centre for Outcomes Research and Evaluation, McGill University Health Centre, Montreal, Québec, Canada.
  • Maleki F; Faculty of Medicine and Health Sciences, McGill University, Montreal, Québec, Canada.
  • Raparelli V; Augmented Intelligence & Precision Health Laboratory (AIPHL), Department of Radiology, McGill University Health Centre, Montreal, Québec, Canada.
  • Norris C; Department of Translational Medicine, University of Ferrara, Ferrara, Italy.
  • Forghani R; Faculty of Nursing, University of Alberta, Edmonton, Alberta, Canada.
  • Pilote L; Faculty of Nursing, University of Alberta, Edmonton, Alberta, Canada.
  • El Emam K; Heart and Stroke Strategic Clinical Networks, Alberta Health Services, Edmonton, Alberta, Canada.
BMJ Open ; 12(5): e050450, 2022 05 18.
Article en En | MEDLINE | ID: mdl-35584867
OBJECTIVE: To examine sex and gender roles in COVID-19 test positivity and hospitalisation in sex-stratified predictive models using machine learning. DESIGN: Cross-sectional study. SETTING: UK Biobank prospective cohort. PARTICIPANTS: Participants tested between 16 March 2020 and 18 May 2020 were analysed. MAIN OUTCOME MEASURES: The endpoints of the study were COVID-19 test positivity and hospitalisation. Forty-two individuals' demographics, psychosocial factors and comorbidities were used as likely determinants of outcomes. Gradient boosting machine was used for building prediction models. RESULTS: Of 4510 individuals tested (51.2% female, mean age=68.5±8.9 years), 29.4% tested positive. Males were more likely to be positive than females (31.6% vs 27.3%, p=0.001). In females, living in more deprived areas, lower income, increased low-density lipoprotein (LDL) to high-density lipoprotein (HDL) ratio, working night shifts and living with a greater number of family members were associated with a higher likelihood of COVID-19 positive test. While in males, greater body mass index and LDL to HDL ratio were the factors associated with a positive test. Older age and adverse cardiometabolic characteristics were the most prominent variables associated with hospitalisation of test-positive patients in both overall and sex-stratified models. CONCLUSION: High-risk jobs, crowded living arrangements and living in deprived areas were associated with increased COVID-19 infection in females, while high-risk cardiometabolic characteristics were more influential in males. Gender-related factors have a greater impact on females; hence, they should be considered in identifying priority groups for COVID-19 infection vaccination campaigns.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedades Cardiovasculares / COVID-19 Tipo de estudio: Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Aspecto: Determinantes_sociais_saude Límite: Aged / Female / Humans / Male / Middle aged País/Región como asunto: Europa Idioma: En Revista: BMJ Open Año: 2022 Tipo del documento: Article País de afiliación: Canadá Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedades Cardiovasculares / COVID-19 Tipo de estudio: Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Aspecto: Determinantes_sociais_saude Límite: Aged / Female / Humans / Male / Middle aged País/Región como asunto: Europa Idioma: En Revista: BMJ Open Año: 2022 Tipo del documento: Article País de afiliación: Canadá Pais de publicación: Reino Unido