ABSTRACT
Background: Analyses of predictors of anemia or malnutrition often pool national or regional data, which may hide variability at subnational levels. Objectives: We sought to identify the risk factors for anemia in young Nepali children aged 6-23 mo in 2 districts: Kapilvastu and Achham. Methods: This is an analysis of two cross-sectional surveys that were conducted as part of a program evaluation of an infant and young child feeding and micronutrient powder intervention that included anemia as a primary outcome. Baseline and endline surveys in each district (in 2013 and 2016) included hemoglobin assessments in n = 4709 children who were representative of children 6-23 mo in each district. Log-binomial regression models accounting for the survey design were used to estimate univariable and multivariable prevalence ratios for risk factors at multiple levels-underlying, direct, and biological causes. Average attributable fractions (AFs) for the population were calculated for significant predictor biomarkers of anemia in multivariable models. Results: In Accham, the prevalence of anemia was 31.4%; significant predictors included child's age, household asset ownership, length-for-age z-score, inflammation (CRP concentration > 0.5 mg/L; α-1 acid glycoprotein concentration > 1 mg/mL), and iron deficiency (serum ferritin concentration < 12 µg/L with BRINDA-inflammation adjustment). In Kapilvastu, the prevalence of anemia was 48.1%; significant predictors included child's sex and ethnicity, wasting and weight-for-length z-score, any morbidity in the previous 2 wk, consumption of fortified foods, receipt of multiple micronutrient powder distributions, iron deficiency, zinc deficiency (nonfasting serum zinc concentration of <65 µg/dL in the morning and that of <57 µg/dL in the afternoon), and inflammation. In Achham, average AFs were 28.2% and 19.8% for iron deficiency and inflammation, respectively. Average AFs for anemia in Kapilvastu were 32.1%, 4.2%, and 4.9% for iron deficiency, zinc deficiency, and inflammation, respectively. Conclusions: The prevalence of anemia and its risk factors varied between districts, with inflammation contributing to a greater share of anemia in Achham than in Kapilvastu. The estimated AF for iron deficiency was around 30% in both districts; iron-delivering interventions and multisectoral approaches to anemia are warranted.