RESUMO
Improving nutritional status during pregnancy is a global interest. Frequently, women either fail to meet or exceed nutrient recommendations. Current strategies to improve maternal nutrition focus on a "one-size-fits-all" approach and fail to consider individual factors that affect the mother's overall nutritional status. The objectives of this review were to determine the importance of key nutrients for optimal maternal and fetal health, to explore to what extent current recommendations consider individual factors, and to explore novel strategies to close the gap between current guidelines and real-world challenges through more personalized approaches. This review intercalated different nutritional guidelines and recent scientific publications and research initiatives related to maternal nutrition. Based on that, an overview of current recommendations, challenges related to present approaches, and perspectives for future directions are described. Current guidelines are not optimally supporting adequate nutrient intake and health of expectant mothers and their offspring. Existing recommendations are not consistent and do not sufficiently take into account how interindividual variation leads to differences in nutrient status. Personalized nutrition offers women the opportunity to improve their health by using strategies that are tailored to their unique nutritional needs. Such strategies can include personalized supplementation, holistic lifestyle interventions, digital and application-based technologies, and dietary assessment through blood biomarker and genetic analysis. However, these approaches warrant further investigation and optimization. More personalized approaches have the potential to optimize mothers' and their offspring's health outcomes more appropriately to their nutritional needs before, during, and after pregnancy. Moving away from a generalized "one-size-fits-all" approach can be achieved through a variety of means. Future aims should be to provide supporting evidence to create customized subpopulation-based or individualized recommendations, improve nutrition education, and develop novel approaches to improve adherence to dietary and lifestyle interventions.
RESUMO
Individual glycemic responses following dietary intake result from complex physiological processes, and can be influenced by physical properties of foods, such as increased resistant starch (RS) from starch retrogradation. Predictive equations are needed to provide personalized dietary recommendations to reduce chronic disease development. Therefore, a precision nutrition model predicting the postprandial glucose response (PPGR) in overweight women following the consumption of potatoes was formulated. Thirty overweight women participated in this randomized crossover trial. Participants consumed 250 g of hot (9.2 g RS) or cold (13.7 g RS) potatoes on two separate occasions. Baseline characteristics included demographics, 10-day dietary records, body composition, and the relative abundance (RA) and α-diversity of gut microbiota. Elastic net regression using 5-fold cross-validation predicted PPGR after potato intake. Most participants (70%) had a favorable PPGR to the cold potato. The model explained 32.2% of the variance in PPGR with the equation: 547.65 × (0 [if cold, high-RS potato], ×1, if hot, low-RS potato]) + (BMI [kg/m2] × 40.66)-(insoluble fiber [g] × 49.35) + (Bacteroides [RA] × 8.69)-(Faecalibacterium [RA] × 73.49)-(Parabacteroides [RA] × 42.08) + (α-diversity × 110.87) + 292.52. This model improves the understanding of baseline characteristics that explain interpersonal variation in PPGR following potato intake and offers a tool to optimize dietary recommendations for a commonly consumed food.