Exploring factors influencing COVID-19 severity: a matched case-control study.

Abstract

Objective: COVID-19, first identified in December 2019, quickly became a global pandemic and remains a significant public health concern. Robust data is rare, especially in pregnant women. The symptoms of this disease range from mild to severe respiratory distress syndrome and mortality. The present study aimed to evaluate the factors influencing COVID-19 severity in women to be better prepared in case of a new epidemic.

Patients and methods: This retrospective matched case-control study based on body mass index, smoke, and drug use was conducted on all women hospitalized with COVID-19 at Afzalipour Hospital in Kerman, Iran from the beginning of 2020 to 2021. In this study, 130 female patients with COVID-19 were included, with 65 patients in the case group (moderate and severe cases of COVID-19) and 65 patients in the control group (mild cases of COVID-19). The data were entered into the Stata software, and to determine the effective risk factors for the severity of COVID-19 disease, both univariate and multivariable conditional logistic regression analyses were utilized, assuming individual matching. Finally, the odds ratios (OR), along with 95% confidence intervals (CI), were estimated.

Results: The average age of women in the case group was 36.92 ± 7.07 years, compared to 30.12 ± 6.27 years in the control group. Among all patients, 50% were pregnant, with a mean gestational age of 30.03 weeks. Significant factors affecting disease severity included age, education, employment status, place of residence, insurance coverage, comorbidities, and pregnancy status. The highest adjusted odds ratio for severe COVID-19 was associated with comorbidities (OR = 7.8, 95% CI: 2.3-11.1), while the lowest was associated with urban residence (OR = 2.8, 95% CI: 1.02-4.5). Overall, significant predictors of severe COVID-19 included age over 30, urban residence, lack of insurance, a short duration between diagnosis and hospitalization, comorbidities, and non-pregnancy.

Conclusions: The study identified several significant predictors of severe COVID-19 among women, including age over 30, urban residency, lack of insurance coverage, presence of comorbidities, and non-pregnancy, all of which were associated with a heightened risk of severe illness. Notably, comorbidities emerged as the strongest predictor. These findings underscore the critical need for targeted interventions to protect vulnerable populations.