Dietary Diversity, Dietary Quality and Sustainable Dietary Surveillance
MetadataShow full item record
AbstractPoor diets are recognized as the leading risk factor for premature mortality and disease globally. Governments need high quality data on population dietary habits and easy-to-use dietary metrics in order to plan strategies and monitor progress in achieving population dietary goals. Due to high cost of traditional diet surveillance systems, however, many low and middle-income countries (LMICs) lack dietary data. Furthermore, majority of available dietary metrics include complex calculations and require a nutrient database. This research addresses these important gaps. Chapter 1 evaluates the food-based Prime Diet Quality Score (PDQS) in relation to pregnancy complications using data from a large prospective cohort study of U.S. women. In multivariable logistic regression models the PDQS was inversely associated with the risk of gestational diabetes mellitus and marginally inversely associated with the risk of hypertensive disorders in pregnancy. Chapter 2 considers development of sustainable dietary surveillance tools, piloting a dietary survey in the resource-limited Bosnia and Herzegovina (B&H). We demonstrated feasibility of an efficient population-based dietary surveillance model, which can be replicated to bridge a critical data gap in many LMICs. Chapter 3 evaluates nutrient intakes among adults in B&H. Dietary data were collected using two days of 24-hour recall. In this descriptive cross-sectional analysis two thirds of population were overweight or obese, and over half had elevated blood pressure. Dietary intakes of N-3 polyunsaturated fatty acids were low and sodium intakes high across all subgroups. Women had inadequate intakes of a range of micronutrients. Chapter 4 evaluates associations of demographic and socioeconomic factors with dietary quality among adults in B&H. Multivariable regression was used to evaluate homogeneity of means across subgroups. While median PDQS was overall low, it was higher among older individuals, married/cohabitating persons, and those living in central and northern parts of the country. In energy-adjusted models, socioeconomic status and tertiles of household spending were inversely associated with the PDQS. In conclusion, this research bridges a dietary data gap in B&H, and provides important evidence for developing sustainable dietary surveillance models and food-based dietary quality metrics that can serve to evaluate population diets and monitor progress in achieving dietary goals across the globe.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:37925667