Maternal micronutrient status and its association with sociodemographic, maternal, and dietary factors in a cross-sectional study.

AIM: Maternal serum micronutrient status can have a significant impact on short- and long-term outcomes for mother and offspring. The aim of this study was to examine the associations of maternal serum folate, ferritin, and vitamin B12 status with maternal and dietary factors. METHODS: This observational cross-sectional study was carried out with 165 healthy pregnant women at least 18 years of age with a singleton pregnancy. Maternal nutrient intake was determined by 24-hour dietary recall method and supplement records. Multivariable analyses using stepwise linear regression models were performed to associations of dietary intakes and maternal serum status. RESULTS: There was a difference between the lowest and highest quartile of maternal serum folate, ferritin, and vitamin B12 status and maternal characteristics and dietary, and total intakes of nutrients (p < 0.05). Multivariable stepwise linear regression analysis showed the predictors of serum folate status were dietary folate equivalent, dietary folate, total vitamin B6 and iron intake. Primer predictors of serum ferritin and vitamin B12 status were dietary protein intake (p < 0.05). CONCLUSION: Our findings support existing recommendations that folic acid supplementation should be prescribed to achieve optimal serum folate status during pregnancy. However, dietary protein intake is important to provide optimal maternal serum vitamin B12 and ferritin status.

Associations of maternal characteristics and dietary factors with anemia and iron-deficiency in pregnancy.

OBJECTIVE: Anemia and iron deficiency during pregnancy influence maternal and fetal health, birth outcomes, and the risk of chronic disease in offspring. This study aimed to examine the association with sociodemographic, maternal factors, supplement use and dietary intakes, and anemia and iron deficiency in pregnancy. METHODS: A cross-sectional study was conducted on 165 pregnant women aged between 19 and 45 years who were interviewed, and dietary intake was assessed by 24-hours dietary recall, supplement records and food frequency questionnaire. Learning Vector Quantization feature selection method which is one of the machine learning techniques was used to extract important variables from sociodemographic, maternal, and dietary factors. RESULTS: The prevalence of anemia was 15.2% and prevalence of iron deficiency was 65.5%. Total intake of iron, phosphorus, vitamin B1 and B2 were importance factors for iron deficiency while age, number of births, use of folic acid supplement, dietary folate equivalent and total iron intake were importance factors for anemia. CONCLUSIONS: Maternal and dietary characteristics were the most crucial risk factors for anemia while dietary factors were the most important risk factor for iron deficiency in pregnancy. The development of anemia and iron deficiency is associated with the coexistence of many nutrient deficiencies.