Using food network analysis to understand meal patterns in pregnant women with high and low diet quality

International Journal of Behavioral Nutrition and Physical Activity

Aiyi Liu¹  Myles S. Faith²  Khalid Iqbal³  Grace E. Shearrer⁴  Leah M. Lipsky⁵  Grace M. Betts⁵  Tonja R. Nansel⁵  Carolina Schwedhelm⁶ 

[1] Biostatistics and Bioinformatics Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA;Department of Counseling, School and Educational Psychology, University at Buffalo Graduate School of Education, Buffalo, NY, USA;Department of Human Nutrition, Institute of Basic Medical Sciences, Khyber Medical University, Peshawar, Pakistan;Department of Nutrition, Gillings School of Global Public Health, University of North Carolina Chapel Hill, Chapel Hill, NC, USA;Social and Behavioral Sciences Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA;Social and Behavioral Sciences Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA;Present address: Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association (MDC), Molecular Epidemiology Research Group, Robert-Rössle-Straße 10, 13125, Berlin, Germany;

关键词: Meals;    Breakfast;    Lunch;    Dinner;    Snacks;    Network analysis;    Gaussian graphical models;    Diet quality;    Healthy eating index;    Pregnancy;   

DOI  :  10.1186/s12966-021-01172-1

来源: Springer

【 摘 要 】

BackgroundLittle is known about how meal-specific food intake contributes to overall diet quality during pregnancy, which is related to numerous maternal and child health outcomes. Food networks are probabilistic graphs using partial correlations to identify relationships among food groups in dietary intake data, and can be analyzed at the meal level. This study investigated food networks across meals in pregnant women and explored differences by overall diet quality classification.MethodsWomen were asked to complete three 24-h dietary recalls throughout pregnancy (n = 365) within a prospective cohort study in the US. Pregnancy diet quality was evaluated using the Healthy Eating Index-2015 (HEI, range 0-100), calculated across pregnancy. Networks from 40 food groups were derived for women in the highest and lowest HEI tertiles at each participant-labeled meal (i.e., breakfast, lunch, dinner, snacks) using Gaussian graphical models. Network composition was qualitatively compared across meals and between HEI tertiles.ResultsIn both HEI tertiles, breakfast food combinations comprised ready-to-eat cereals with milk, quick breads with sweets (e.g., pancakes with syrup), and bread with cheese and meat. Vegetables were consumed at breakfast among women in the high HEI tertile only. Combinations at lunch and dinner were more varied, including vegetables with oils (e.g., salads) in the high tertile and sugary foods with nuts, fruits, and milk in the low tertile at lunch; and cooked grains with fats (e.g., pasta with oil) in the high tertile and potatoes with vegetables and meat in the low tertile at dinner. Fried potatoes, sugar-sweetened beverages, and sandwiches were consumed together at all main meals in the low tertile only. Foods were consumed individually at snacks in both tertiles; the most commonly consumed food were fruits in the high HEI tertile and cakes & cookies in the low tertile.ConclusionsIn this cohort of pregnant women, food network analysis indicated that food combinations differed by meal and between HEI tertiles. Meal-specific patterns that differed between diet quality tertiles suggest potential targets to improve food choices at meals; the impact of meal-based dietary modifications on intake of correlated foods and on overall diet quality should be investigated in simulations and intervention studies.Trial registrationPEAS was registered with number NCT02217462 in Clinicaltrials.gov on August 13, 2014.

【 授权许可】

CC BY