In multivariable adjusted model, we adjusted for age, sex, body mass index (BMI), smoking status, race, and tumour stage.
In addition to computing an age-adjusted model, we adjusted for a priori potential confounders of the association between GDM and hypertension.
In the first model we adjusted for age (years) and sex and in the multivariable model we additionally adjusted for categories of education, cigarette smoking, alcohol consumption, diabetes mellitus, and BMI (kg/m).
In the logistic regression analyses as well as the GLM model, we adjusted for age (categorized 18 25, 26 35, 36 45, 46 55, 56 65 years), gender, annual household consumption (categorized ≤950, 950 1200, >1200 USD/year), habitat (urban versus rural), altitude (<2000 versus ≥2000 m) and the use of alcohol or marijuana (no versus yes).
For each model, we adjusted Δ to set the Ψ V) functions of the QIF and EIF models to have the same radius of curvature at their minimum (see Methods).
To alter the formation of images in our model, we adjusted the medium-wavelength cone sensitivity function to have a different peak sensitivity, without changing the overall shape of the function.
In the first model, we adjusted for age only.
In each model we adjusted for serum cholesterol and triglycerides, education, exercise, and smoking.
Furthermore, in a third model, we adjusted also for all other available potential confounders.
In the first model, we adjusted for age, gender and pubertal stage.
In the primary model, we adjusted the analyses for sex and year of birth.
