Sex and Gender-Related Differences in COVID-19 Diagnoses and SARS-CoV-2 Testing Practices During the First Wave of the Pandemic: The Dutch Lifelines COVID-19 Cohort Study

Background: Although sex differences are described in COVID-19 diagnoses and testing, many studies neglect possible gender-related influences. Additionally, research is often performed in clinical populations, while most COVID-19 patients are not hospitalized. Therefore, we investigated associations between sex and gender-related variables, and COVID-19 diagnoses and testing practices in a large general population cohort during the first wave of the pandemic when testing capacity was limited.
Methods: We used data from the Lifelines COVID-19 Cohort (N=74,722; 60.8% female). We applied bivariate and multiple logistic regression analyses. The outcomes were a COVID-19 diagnosis (confirmed by SARS-CoV-2 PCR testing or physician’s clinical diagnosis) and PCR testing. Independent variables included among others participants’ sex, age, somatic comorbidities, occupation and smoking status. Sex-by-comorbidity and sex-by-occupation interaction terms were included to investigate sex differences in associations between the presence of comorbidities or an occupation with COVID-19 diagnoses or testing practices.
Results: In bivariate analyses female sex was significantly associated with COVID-19 diagnoses and testing, but significance did not persist in multiple logistic regression analyses. However, a gender-related variable, being a healthcare worker, was significantly associated with COVID-19 diagnoses (OR=1.68; 95%CI=1.30-2.17) and testing (OR=12.5; 95%CI=8.55-18.3). Female healthcare workers were less often diagnosed and tested than male healthcare workers 34 (ORinteraction=0.54; 95%CI=0.32-0.92, ORinteraction=0.53; 95%CI=0.29-0.97, respectively).
Conclusion: We found no sex differences in COVID-19 diagnoses and testing in the general population. Among healthcare workers a male preponderance in COVID-19 diagnoses and testing was observed. This could be explained by more pronounced COVID-19 symptoms in males or by institutionalized gender inequities.