Statistical analysis
A Chi-square test was used to assess the differences in
socio-demographic and pregnancy characteristics between the exposed and
unexposed groups. A generalized linear model (GLM) was applied to
estimate the associations of Level I lockdown exposure with gestational
length (linear regression) and PTB risk (binary logistic regression),
after adjusting for potential confounders. A multinomial logistic
regression model was used when PTB was further divided into MPTB and
VPTB, with term birth as the reference. An interaction test was
conducted to examine the potential modification effects of infant sex by
comparing the association coefficients between male and female infants
(27).
Similarly, GLM and multinomial logistic regression models were employed
to examine the association of cumulative exposure dose with gestational
length or PTB. The cumulative exposure dose in the exposed group was
divided into four groups by quartiles (Q1, Q2, Q3, and Q4). The
association of each quartile of cumulative exposure (vs unexposed) with
gestational length or PTB were estimated. A trend test was conducted by
assuming the values of quartiles as a continuous variable.
All analyses were performed using R3.6.1 (R Development Core Team 2019,
https://www.r-project.org). All the tests were two-sided and a
P<0.05 was considered to be statistically significant.