2.5 Statistical analyses
Categorical variables were compared by using the Chi-square test. For
continuous variables, normality
was tested by the
Kolmogorov-Smirnov test. The independent sample t -test was used
for normal data, the Wilcoxon-Mann-Whitney test was used for nonnormal
data. To assess the relationship between
exercise during pregnancy and PTB
risk, Multiple logistic regression was used to calculate odds ratios
(ORs ) and 95% of the corresponding confidence intervals (95%CIs ). Variable selection
for the multiple models was guided by the directed acyclic graph (DAG).
The DAG was plotted to recognize potential causality, mediation, or
confounding factors[17]. Furthermore, women’s
exercise activity during pregnancy was grouped by time spent and energy
expenditure, and the none and low group was used as a reference.
The effect of each trimester was
observed separately. For subgroup analysis, the subjects were stratified
by whether they had pregnancy complications or not.
The median effect was analyzed by
sequential test.
Statistical analyses were performed using the statistical computing
environment R 4.0.5. P-value of <0.05 was considered
statistically significant.