Predictors of Major Dietary Patterns Among Pregnant Women Attending Public Health Facilities in Eastern Ethiopia: A New Epidemiological Approach - Oumer, Abdu; Abraham, Mihret; Nuri, Aliya (Frontiers in Nutrition, 2022)
Background: dietary pattern analysis is a robust statistical procedure that efficiently characterize the dietary intakes of individuals. However, there is a lack of robust dietary intake evidence beyond nutrient intake in Ethiopia. This study was to answer, what are the major dietary consumption patterns and its predictors among pregnant women in Ethiopia. Methods: A facility-based survey among 380 randomly selected pregnant women using a contextualized food frequency questionnaire over one month recall was used. The frequency of food consumption was standardized to daily frequency equivalents, and a sequential exploratory factor analysis was used to derive major dietary patterns. A multivariable ordinary logistic regression model was fitted with all its assumptions. Results: Three major dietary patterns ("fruits and animal-source foods," "cereals, tubers, and sweet foods", "legumes and vegetables"), explaining 65% of the total variation were identified. Women snacks (AOR = 1.93; 1.23-2.75), without food aversion (AOR = 1.59; 1.08-2.35), non-fasting (AOR = 0.75;1.12-2.12), and receiving nutritional counseling (AOR = 1.96; 1.25-3.07) were significantly positively associated with a higher tercile of fruits and animal-source food consumption. Non-working mothers (AOR = 1.8;1.23-2.76), chronic disease (AOR = 1.88; 1.14-3.09), or received nutritional counseling (AOR = 1.33; 0.88-2.01), were fasting (AOR = 1.33;0.88-2.01), and no food cravings (AOR = 4.27;2.67-6.84), and aversion (AOR = 1.60;1.04-2.44) had significantly higher odds of consuming cereals, tubers, and sweet foods. Literacy (AOR = 1.87; 1.14-3.09), urban residence (AOR = 2.10; 1.10-3.93), low socioeconomic class (AOR = 2.68;1.30-5.23), and skipping meals (AOR = 1.73; 1.15-2.62) were associated with higher odds of legume and vegetable consumption. Conclusions: Socioeconomic class, literacy, occupation, getting nutritional counseling, habits of food craving, food aversion, and fasting can predict a woman’s dietary pattern.