Micronutrient intake and associated factors among pregnant women in East Africa: Multilevel logistic regression analysis

BackgroundMicronutrient deficiencies during pregnancy pose significant public health issues, considering the potential for negative consequences not only during pregnancy but also throughout life. Anemia in pregnant women is becoming a significant problem in developing countries, with scientific evidence indicating that 41.8 percent of women worldwide suffer from anemia. As a result, investigating the pooled prevalence and factors associated with micronutrient intake among pregnant women in East Africa is critical to alleviate the burden of micronutrient deficiency among pregnant women. MethodThe pooled prevalence of micronutrient intake with a 95% Confidence Interval (CI) was reported and presented in a forest plot for East Africa Countries using STATA version 14.1. Intra-class Correlation Coefficient (ICC), Likelihood Ratio (LR) test, Median Odds Ratio (MOR), and deviance (-2LLR) values were used for model comparison and fitness. Adjusted Odds Ratios (AOR) with a 95% Confidence Interval (CI) and p-value <= 0.05 in the multilevel logistic model were used to declare significant factors associated with micronutrient intake. ResultThe pooled prevalence of micronutrient intake in East African countries was 36.07% (95% CI: 35.82%, 36.33%). In the multilevel logistic regression model, women from the highest wealth quintile were 1.06 [AOR = 1.09, 95%CI: 1.00, 1.11] more likely to take micronutrients compared to their counterparts. Mothers who attained primary education, secondary education, and tertiary education had 1.20 times [AOR = 1.20, 95% CI: 1.15, 1.26], 1.28 times [AOR = 1.28, 95% CI: 1.19, 1.36] and 1.22 times [AOR = 1.22, 95% CI: 1.07, 1.38] more likely take micronutrient compared to mothers who attained no education, respectively. ConclusionThe overall prevalence of micronutrient intake in East Africa was low. Only 36% of the study participants had micronutrient intake practice. Socioeconomic factors (education level, and household wealth status) have been shown to influence micronutrient intake. Therefore, it is necessitates the continuation of ongoing projects as well as the development of fresh ones that concentrate on these variables and include effective treatments and programs, especially among underprivileged and vulnerable populations.