Sociodemographic characteristics of pregnant women tested positive for COVID-19 admitted to a referral center in Northern Italy during lockdown period.

2021 
INTRODUCTION: We investigated association between sociodemographic characteristics and COVID-19 disease among pregnant women admitted to our unit, the largest high-risk maternity unit in the Milan metropolitan area. METHODS: Between March 1, 2020 and April 30, 2020, 896 pregnant women were admitted to our Institution and tested for COVID-19. We collected information regarding their sociodemographic characteristics. Additional information on geographical area of residence, number of family members, number of family members tested positive for COVID-19, and clinical data was collected for women tested positive for COVID-19. Odds ratios (ORs) and 95% confidence intervals (CIs) for the risk of developing COVID-19 according to sociodemographic characteristics were estimated by unconditional logistic regression models. RESULTS: Among the 896 women enrolled, 50 resulted positive for COVID-19. Pregnant women aged ≥35 years had a significantly lower risk of developing the infection (crude OR = 0.29; 95% CI:0.16-0.55). Conversely, foreign women (crude OR = 3.32; 95% CI:1.89-5.81), unemployed women (crude OR = 3.09; 95% CI: 1.77-5.40), and women with an unemployed partner (crude OR = 3.16; 95% CI: 1.48-6.79) showed a significantly higher risk of infection. Ethnicity was positively associated with the risk of developing COVID-19 (mutually adjusted OR = 2.15; 95% CI:1.12-4.11) in the multivariate analysis. Foreign women with COVID-19 were more likely to have a lower education level (p < 0.01), to be unemployed (p < 0.01), and to live in larger families (p < 0.01) compared to Italian pregnant women. CONCLUSIONS: The socioeconomic conditions described are characteristic of immigration patterns in our metropolitan area. These factors may increase the risk of viral transmission, reducing the effectiveness of lockdown and social distancing.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    18
    References
    1
    Citations
    NaN
    KQI
    []