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
