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Translation of nutrient recommendations into personalized optimal diets for Chinese urban lactating women by linear programming models.

ABSTRACT: BACKGROUND:Lactating women need to consume a high-quality diet to replete nutrient stores depleted during pregnancy and to ensure sufficient nutrition for breastfeeding. However, several studies reported suboptimal dietary quality and nutrient intake of lactating mothers in China. The objectives of this study was to apply dietary modeling method to develop individualized optimal diets, which meet the nutrient requirements for lactating women in urban China. METHODS:Data were collected from a sample of 576 lactating women from 0 to 240 days postpartum during the Maternal Infant Nutrition Growth study conducted between 2011 and 2012 in three cities including Beijing, Guangzhou, and Suzhou. Dietary intake data were collected with an interviewer-administered 24-h survey. Linear programming was applied to develop dietary plans that meet recommendations for lactation women in the China Dietary Reference Intakes 2013 and the Chinese Dietary Guideline 2016, while with least deviation from the observed dietary intake. RESULTS:Through dietary modeling, individual optimal diets were developed for 576 lactating women. The optimal diets met all the food and nutrient intake constraints set in the linear programming models. The large difference between observed and optimized diets suggests that the nutrient needs of lactating mothers in China may only be met after substantial dietary changes. In addition, the analysis showed that it was difficult to meet the recommended intake for six nutrients: vitamin A, vitamin B1, vitamin B6, calcium, selenium, and dietary fiber. Moreover, four clusters in the optimized diets were identified by K-means cluster analysis. The four clusters confirmed that the optimal diets developed by linear programming could characterize the variety in dietary habits by geographical regions and duration of lactation. CONCLUSION:Linear programming could help translate nutrient recommendations into personal diet advices for a sample of urban lactating mothers from China. The study showed that dietary modeling is helpful to support healthy eating of lactation women by translating dietary guidelines into personalized meal plans. TRIAL REGISTRATION:The Maternal Infant Nutrition Growth study was registered in ClinicalTrials.gov with identifier NCT01971671 . Registration date October 29, 2013.

SUBMITTER: Yu K

PROVIDER: S-EPMC6145120 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Translation of nutrient recommendations into personalized optimal diets for Chinese urban lactating women by linear programming models.

Yu Kai K Xue Yong Y Zhao Wenzhi W Zhao Ai A Li Wenjun W Zhang Yumei Y Wang Peiyu P

BMC pregnancy and childbirth 20180918 1

<h4>Background</h4>Lactating women need to consume a high-quality diet to replete nutrient stores depleted during pregnancy and to ensure sufficient nutrition for breastfeeding. However, several studies reported suboptimal dietary quality and nutrient intake of lactating mothers in China. The objectives of this study was to apply dietary modeling method to develop individualized optimal diets, which meet the nutrient requirements for lactating women in urban China.<h4>Methods</h4>Data were colle ...[more]

PMID: 30227842

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Project description:BackgroundOptimal nutrition during lactation is essential for the well-being of the mother and the infant. Studies have shown that access to nutrient-rich foods during lactation is critical as minimal stores of nutrients can have adverse effects. This study aimed to investigate the diversity, composition, and nutrient adequacy of diets of lactating mothers in Southwest Ethiopia.MethodsA community-based cross-sectional survey was carried out in three districts of Jimma Zone, Southwest Ethiopia, in February 2014. A stratified multistage sampling technique was used to select 558 lactating mothers. Data were collected using a pre-tested and structured interviewer-administered questionnaire. Minimum dietary diversity for women (MDD-W) was computed from a single 24-h recall. A cut off value of 5 was used to classify the dietary diversity into achieving MDD-W or not. The proximate, mineral and anti-nutritional compositions of 12 commonly consumed foods were analysed using standard methods. Nutrient adequacy ratio (NAR) and Mean adequacy ratio (MAR) of these foods were estimated.ResultsThe mean (±SD) dietary diversity score (DDS) of the study participants was 3.73±1.03. Meeting MDD-W was positively associated with agricultural production diversity (P = 0.001) and educational level of the women (P = 0.04). Conversely, district of the study (P = 0.003) and place of residence (P = 0.019) were negatively associated with meeting MDD-W. The proximate composition (g/100g) of the sampled foods ranged between 24.8-65.6 for moisture, 7.6-19.8 for protein, 2.1-23.1 for crude fat, 2.0-27 for crude fibre, 1.0-21.2 for total ash, and 0.9-45.8 for total carbohydrate content. The calorific value ranged between 124.5-299.6 Kcal/100g. The mineral contents (mg/100g) ranged between 9.5-52.5 for iron, 2.2-4.2 for zinc, 42.6-318.2 for calcium, and 150.7-379.9 for phosphorus. The content of anti-nutritional factors (mg/100g) ranged between 11.1-178.9 for phytate and 3.7-315.9 for tannin. All the commonly consumed maternal foods were not sufficient to meet the energy, fat and protein requirements, (NAR<1). However, all diets provided adequate iron and most of the cereal-based foods provided adequate carbohydrate and minerals. The overall nutrient adequacy was below the cut-off point for all food types.ConclusionsThe diets of lactating mothers in Southwest Ethiopia lack diversity and nutrient adequacy. A community-based nutrition education program on the importance of diet diversity and nutrient intake during lactation based on a multi-sectoral approach is needed.

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Translation of nutrient recommendations into personalized optimal diets for Chinese urban lactating women by linear programming models.

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Translation of nutrient recommendations into personalized optimal diets for Chinese urban lactating women by linear programming models.

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