METHODS: Secondary data analysis was conducted using the 2019 mini Ethiopian Demographic and Health Survey data. A total weighted sample of 1,532 children aged 6-23 months were included. To identify significant factors associated with of inadequate meal frequency, multilevel binary logistic regression model was fitted. Variables with p-value < 0.25 from the bi-variable model were exported to multivariable analysis. In the multivariable model, variables with p-value < 0.05 were declared as significantly associated factors and adjusted odds ratio (AOR) with its 95% confidence interval were reported. Multilevel models were compared using deviance and log-likelihood. Spatial analysis tools were utilized to visualize the distribution of inadequate meal frequency. Bernoulli model was fitted using SaTScan V.9.6 to identify most likely clusters and ArcGIS V.10.8 was used to map the hotspot areas. Ordinary least square and geographic weighted regression models were used and compared using information criteria and adjusted-R2. Local coefficients of factors associated with hotspots of inadequate meal frequency were mapped.
RESULTS: The prevalence of inadequate meal frequency was 47.03% (95% CI: 44.54%, 49.53%) in Ethiopia. Age of the child, sex of the household head, timely initiation of breastfeeding, current breastfeeding status, number of antenatal care visit, maternal education, and region were significantly associated with inadequate meal frequency. The spatial distribution of inadequate meal frequency was showed significant variation across Ethiopia (Global Moran\'s I = 0.164, p-value <0.001). A total of 38 significant clusters were detected through SaTScan analysis, from these the 22 primary clusters were located in Somali and Harari.
CONCLUSIONS: The prevalence of inadequate meal frequency was high in Ethiopia and had significant clustering patter. Significant hotspot clusters were located in Somali, northern Afar, Harari, Amhara, Gambela, and eastern South nation nationalities and peoples\' region. Therefore, public health interventions which enhance breastfeeding practice, optimal number of antenatal care visits, educational empowerments should target hotspot areas to decrease inadequate meal frequency practice.
方法:次要数据分析是使用2019年小型埃塞俄比亚人口与健康调查数据进行的。包括1,532名6-23个月的儿童的总加权样本。为了确定与进餐频率不足相关的重要因素,拟合多元二元Logistic回归模型。将来自双变量模型的p值<0.25的变量导出到多变量分析。在多变量模型中,p值<0.05的变量被宣布为显著相关因素,并报告了其95%置信区间的校正比值比(AOR).使用偏差和对数似然比较了多水平模型。利用空间分析工具来可视化膳食频率不足的分布。使用SaTScanV.9.6拟合伯努利模型以识别最可能的簇,并使用ArcGISV.10.8绘制热点区域。使用普通最小二乘和地理加权回归模型,并使用信息标准和调整后的R2进行比较。绘制了与进餐频率不足的热点相关的因素的局部系数。
结果:用餐频率不足的患病率为47.03%(95%CI:44.54%,49.53%)在埃塞俄比亚。孩子的年龄,户主的性别,及时开始母乳喂养,母乳喂养现状,产前护理访问次数,母亲教育,和区域与用餐频率不足显着相关。整个埃塞俄比亚的膳食频率不足的空间分布显示出显着变化(GlobalMoran'sI=0.164,p值<0.001)。通过SaTScan分析共检测到38个显著的聚类,其中22个主要集群位于索马里和哈拉里。
结论:埃塞俄比亚膳食不足频率的患病率很高,并且具有明显的聚类模式。重要的热点集群位于索马里,阿法尔北部,Harari,阿姆哈拉,Gambela,和东部南方民族和人民地区。因此,加强母乳喂养实践的公共卫生干预措施,产前护理就诊的最佳次数,教育赋权应针对热点地区,以减少用餐频率练习不足。