期刊名称：The Journal of Health, Population and Nutrition
印刷版ISSN：1606-0997
电子版ISSN：2072-1315
出版年度：2019
卷号：38
DOI：10.1186/s41043-019-0196-y
出版社：International Centre for Diarrhoeal Disease Research Bangladesh
摘要：Background Correcting anemia during pregnancy often requires integrating food and non-food-based approaches. Nonetheless, little is known about specific dietary diversity (DD) cutoff values predicting risk of anemia during the different trimesters of pregnancy. Objective We aimed to determine the lowest possible DD cutoff values associated with risk of maternal anemia at mid and term of pregnancy in a rural resource limited setting of Ethiopia. Design A multi-center prospective cohort study was conducted enrolling 432 eligible pregnant women from eight rural health centers selected from four districts in Arsi zone, Central Ethiopia. Women were classified into exposed ( n = 216) and unexposed ( n = 216) groups, based on Women’s Individual Dietary Diversity (WIDD) score, and were followed from mid to term of pregnancy. The cutoff values for WIDD corresponding to the lowest risk of anemia were defined by receiver operating characteristic (ROC) curve analysis. Logistic regressions were also fitted to identify food groups associated with low anemia risk during pregnancy. Results The overall prevalence of anemia increased from 28.6 to 32.4% between mid and term of pregnancy. Calculatedly, using the ROC curve analysis, the minimum WIDD score associated with lower risk of anemia was three and four respectively at these periods. Not consuming animal source foods [adjusted odds ratio (AOR), 2.36; 95% confidence interval (CI), 1.35–4.14], pre-existing anemia (AOR 28.56; 95% CI, 14.33, 56.79), and low DD during pregnancy (AOR, 2.22; 95% CI, 1.09–4.52) were associated with risk of anemia at term. Conclusion The cutoff for WIDD score predicting risk of anemia varied significantly, increasing from three to four, between mid and term of pregnancy. Additional population-based observational and experimental studies validating the metrics are needed before policy level recommendations.
