| Title: | Importance of sex and gender factors for COVID-19 infection and hospitalisation: a sex-stratified analysis using machine learning in UK Biobank data |
| Journal: | BMJ Open |
| Published: | 18 May 2022 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/35584867/ |
| DOI: | https://doi.org/10.1136/bmjopen-2021-050450 |
| URL: | https://bmjopen.bmj.com/content/bmjopen/12/5/e050450.full.pdf |
Publication 13929
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Abstract
OBJECTIVE: To examine sex and gender roles in COVID-19 test positivity and hospitalisation in sex-stratified predictive models using machine learning.</p>
DESIGN: Cross-sectional study.</p>
SETTING: UK Biobank prospective cohort.</p>
PARTICIPANTS: Participants tested between 16 March 2020 and 18 May 2020 were analysed.</p>
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.</p>
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.</p>
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.</p>
13 Keywords
- Aged
- Biological Specimen Banks
- COVID-19
- Cardiovascular Diseases
- Cross-Sectional Studies
- Female
- Hospitalization
- Humans
- Machine Learning
- Male
- Middle Aged
- Prospective Studies
- United Kingdom
12 Authors
- Zahra Azizi
- Yumika Shiba
- Pouria Alipour
- Farhad Maleki
- Valeria Raparelli
- Colleen Norris
- Reza Forghani
- Louise Pilote
- Khaled El Emam
- Alexandra Kautzky-Willer
- Karolina Kublickiene
- Maria Trinidad Herrero
1 Application
| Application ID | Title |
|---|---|
| 45551 | Mechanistic modelling of neurodevelopment, neuroplasticity, and neurodegeneration |
Enabling scientific discoveries that improve human health