Statistical analysis
We used modified Poisson regression to estimate RRs with 95% CIs
between exposure groups before gestational day 238 and late-onset
preeclampsia.32 Cox proportional hazard models with
time since gestational day 238 were used to estimate hazard ratios (HR)
for exposure after gestational day 237. We used robust standard errors
to account for correlation within women who participated with
>1 pregnancy in the PRIDE Study.33,34
The models were weighted using inverse probability of censoring weights
and adjusted for a sufficient set of confounders. We used inverse
probability of censoring weights to account for potential selection bias
resulting from differential loss-to-follow-up,35 by
fitting logistic regression models to predict not being lost-to-follow
up using determinants of attrition. We used the models’ predicted
probabilities to calculate inverse weights for loss-to-follow-up. Under
the assumption that data were missing at random, we imputed missing data
on confounders through multiple imputation (25 imputations; Text S1).
We conducted a number of sensitivity analyses to assess the robustness
of the primary analysis. Firstly, we selected gestational hypertension
as secondary outcome measure, distinguishing between exposure in
gestational weeks 0-19 and after gestational week 20, as some studies
indicate a protective effect of calcium supplements on this outcome as
well.6 Women with chronic hypertension (N=85) were
excluded from these analyses. Secondly, we used an externally validated
prediction model to select women at high risk of developing
preeclampsia, with a risk threshold of 3%,36,37 and
replicated the main analyses in this population. Finally, we restricted
the analyses to women who did not use calcium-containing supplements
during pregnancy. All statistical analyses were performed using Stata/SE
16.0.