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Multicenter Study
. 2021 Jul 13;13(7):2398.
doi: 10.3390/nu13072398.

Maternal Nutrition Status Associated with Pregnancy-Related Adverse Outcomes

Maria J Miele  1 , Renato T Souza  1 , Iracema M Calderon  2 , Francisco E Feitosa  3 , Debora F Leite  1   4 , Edilberto A Rocha Filho  4 , Janete Vettorazzi  5 , Jussara Mayrink  1 , Karayna G Fernandes  1   6 , Matias C Vieira  1   7 , Rodolfo C Pacagnella  1 , José G Cecatti  1
Affiliations
Multicenter Study

Maternal Nutrition Status Associated with Pregnancy-Related Adverse Outcomes

Maria J Miele et al. Nutrients. .

Abstract

Although maternal nutrition has an impact on fetal development and gestational outcome, tracking maternal nutrition in outpatient practice is still complex and involves proper technical capacitation in this area. Nevertheless, the association between nutritional variables may broaden the ability to predict the occurrence of gestational disorders and prevention management. We aimed to identify factors that could indicate the probability of adverse outcomes in mid-pregnancy. From a cohort of 1165 nulliparous pregnant women without any previous disease, the nutritional status was assessed by body mass index (BMI) and mid-upper arm circumference (MUAC), associated with dietary patterns and sociodemographic characteristics. Two predictive models with nutritional status for screening the occurrence of adverse outcomes of preterm birth, gestational diabetes mellitus, small-for-gestational-age newborns and preeclampsia were developed. The odds of adverse outcomes were higher in non-white (p < 0.05) obese women and with high protein consumption. There was no significant difference between the models, with an overall accuracy of 63% for both models and a probability of success in predicting adverse outcomes (BMI = 61%, MUAC = 52%). This study of Brazilian pregnant nulliparous women offers two possible options for early tracking of adverse gestational outcomes that should be further externally validated.

Keywords: gestational diabetes mellitus; maternal nutrition; preeclampsia; preterm birth; small-for-gestational-age.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Flow chart of the study sample.
Figure 2
Figure 2
Estimated risks for Preterm-birth and small-for-gestational-age using BMI or MUAC. BMI 1: obese; BMI 2: overweight; BMI 4: underweight. MUAC 1: obese; MUAC 2: overweight; MUAC 4: underweight. PCA 1: Obesogenic; PCA 3: Intermediate; PCA 4: Vegetarian; PCA 5: Protein. Age 1: <20, Age 3: >34 years; Region 1: Northeast. Color 1: Non-white. Preterm-birth AIC = BMI model: 782.8931/MUAC model: 760.9102. Small-for-gestational-age AIC = BMI model: 860.8467/MUAC model: 829.7310. * Values of OR are significant at p < 0.05.
Figure 3
Figure 3
Estimated risks for Gestational diabetes mellitus and preeclampsia using BMI or MUAC. BMI 1: obese; BMI 2: overweight; BMI 4: underweight. MUAC 1: obese; MUAC 2: overweight; MUAC 4: underweight. PCA 1: Obesogenic; PCA 3: Intermediate; PCA 4: Vegetarian; PCA 5: Protein. Age 1: <20, Age 3: >34 years; Region 1: Northeast. Color 1: Non-white. Gestational diabetes mellitus AIC = BMI model: 789.3831/MUAC model: 776.5544. Preeclampsia AIC = BMI model: 589.2154/MUAC model: 574.0860. * Values of OR are significant at p < 0.05. ** Values of OR are significant at p < 0.01.
Figure 4
Figure 4
Estimated risks of adverse pregnancy outcome using BMI or MUAC. BMI 1: obese; BMI 2: overweight; BMI 4: underweight. MUAC 1: obese; MUAC 2: overweight; MUAC 4: underweight. Color 1: Non-white. AIC = BMI model: 1357.881/MUAC model: 1338.214. * Values of OR are significant at p < 0.05. ** Values of OR are significant at p < 0.01. *** Values of OR are significant at p < 0.001.
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References

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