Digital screening tool may identify inadequate calcium intake in pregnant women: Study
Managing adequate intakes of calcium during pregnancy is
important in several physiological processes, and reduces the risk of perinatal
adverse events such as hypertensive disorders and preterm birth. The
recommended daily intake (RDI) of calcium is 1000 mg/day for all women of
childbearing age. Calcium demands increase substantially during pregnancy, but
are met by an increased intestinal absorption, renal reabsorption and
mobilization from the maternal skeleton, mediated mostly by an increase in PTH
and IGF-I over the course of pregnancy. However, these measures are
insufficient to compensate for an inadequate intake.
Women of childbearing age have remarkably low intakes of
calcium. Calcium supplementation starting from the second or third trimester in
women with chronically low intakes reduces risks of gestational hypertension
and preeclampsia. The WHO and Dutch guidelines for pregnancy consultation
therefore recommend daily calcium supplementation starting from the 20th week
of gestation in women with an inadequate intake. Due to tight regulation of
serum calcium levels, there is poor association between dietary and total calcium
serum levels. Hence, nutritional screening is the only appropriate method to
assess calcium intake. During regular maternal outpatient clinic visits there
is neither time nor expertise for elaborate dietary assessments. A simple
screening tool for calcium intake could offer a solution, and contribute to
better care and prevention through early detection and intervention in women at
risk of having an inadequate intake
The aim of this study was to develop an effective and simple
digital screening tool based on a prediction model for calcium intake in pregnancy
that is suitable for making accurate individual predictions with a minimal
number of predictors to be used by both clinicians and patients.
Authors extracted all data from the Rotterdam Periconceptional
cohort (PREDICT study) conducted at the Erasmus MC, University Medical Centre
in Rotterdam, the Netherlands, between November 2014 and December 2020. Data
was extracted from food frequency questionnaires. The estimated average
requirement of 750 m/day was defined as the lower limit for an adequate calcium
intake. They created a prediction model, using multivariable binary logistic
regression with backward stepwise selection, predicting the probability of
adequate calcium intake developing a simple screening tool based on the
prediction model.
694 participants are included, of which 201 (29 %) had an
adequate calcium intake. Total daily or weekly intakes of cheese, milk, and
yogurt or curd were selected as predictors for the prediction model. The model
had excellent discrimination (AUC 0.858), a good fit (Brier score 0.136, HL
statistic p = 0.499) and satisfactory calibration. The test accuracy measures
were: sensitivity 80.9 %, specificity 77.1 %, PPV 89.7 %, NPV 62.2 %. A colour
coded digital screening tool was developed for use in clinical practice.
This prediction model accurately detects inadequate intakes
of calcium in a tertiary hospital based cohort of women in the periconceptional
period. The model has low error rates, with a high sensitivity and specificity.
The screening tool based on this model enables clinicians to make a quick
estimate of the adequacy of calcium intake in pregnancy.
This study demonstrated the possibility of accurately
estimating calcium intake based on a limited number of food items. The
screening tool presented in this study is an efficient and reliable instrument
to accurately estimate calcium intake in pregnant women practicing a
Western-style diet. It can be used in clinical practice to detect women at risk
of having an inadequate calcium intake and as such contribute to better
periconceptional and pregnancy care for mother and offspring
Source: I.L. Vanwersch et al.; European Journal of
Obstetrics & Gynecology and Reproductive Biology 305 (2025) 31–36