Department of Epidemiology and Biostatistics, Institute of Public Health College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.
BMJ Paediatr Open. 2021 May 5;5(1):e000968. doi: 10.1136/bmjpo-2020-000968. eCollection 2021.
This study aimed to assess the spatial distribution, individual and community-level factors associated with low birth weight in Ethiopia.
Secondary data analysis was conducted using the 2016 Ethiopian Demographic and Health Survey data. A total of 2110 neonates were included in this study. Spatial autocorrelation analysis was conducted to assess the spatial clustering of LBW. Besides, the spatial scan statistics and ordinary kriging interpolation were done to detect the local level clusters and to assess predicted risk areas, respectively. Furthermore, a multilevel logistic regression model was fitted to determine individual and community-level factors associated with LBW. Finally, most likely clusters with log-likelihood ratio (LLR), relative risk and p value from spatial scan statistics and adjusted OR (AOR) with 95% CI for multilevel logistic regression model were reported.
LBW was spatially clustered in Ethiopia. Primary (LLR=11.57; p=0.002) clusters were detected in the Amhara region. Neonates within this spatial window had a 2.66 times higher risk of being LBW babies as compared with those outside the window. Besides, secondary (LLR=11.4; p=0.003; LLR=10.14, p=0.0075) clusters were identified at southwest Oromia, north Oromia, south Afar and southeast Amhara regions. Neonates who were born from severely anaemic (AOR=1.40, 95% CI (1.03 to 2.15)), and uneducated (AOR=1.90, 95% CI (1.23 to 2.93)) mothers, those who were born before 37 weeks of gestation (AOR=5.97, 95% CI (3.26 to 10.95)) and women (AOR=1.41, 95% CI (1.05 to 1.89)), had significantly higher odds of being LBW babies.
The high-risk areas of LBW were detected in Afar, Amhara and Oromia regions. Therefore, targeting the policy interventions in those hotspot areas and focusing on the improvement of maternal education, strengthening anaemia control programmes and elimination of modifiable causes of prematurity could be vital for reducing the LBW disparity in Ethiopia.
本研究旨在评估埃塞俄比亚低出生体重的空间分布以及与个体和社区层面相关的因素。
本研究使用了 2016 年埃塞俄比亚人口与健康调查的数据进行二次数据分析。共纳入了 2110 名新生儿。采用空间自相关分析评估低出生体重的空间聚类。此外，还进行了空间扫描统计和普通克里金插值，以分别检测局部水平聚类和评估预测风险区域。进一步，采用多水平逻辑回归模型确定与低出生体重相关的个体和社区层面的因素。最后，报告了空间扫描统计中的最可能聚类的对数似然比（LLR）、相对风险和 p 值，以及多水平逻辑回归模型的调整后比值比（AOR）和 95%置信区间。
低出生体重在埃塞俄比亚呈空间聚类分布。在阿姆哈拉地区发现了初级（LLR=11.57；p=0.002）聚类。与不在该窗口内的新生儿相比，处于该空间窗口内的新生儿发生低出生体重的风险高 2.66 倍。此外，在奥罗米亚西南部、奥罗米亚北部、阿法尔南部和阿姆哈拉东南部地区也发现了二级（LLR=11.4；p=0.003；LLR=10.14，p=0.0075）聚类。出生时母亲严重贫血（AOR=1.40，95%置信区间（1.03 至 2.15））和未受教育（AOR=1.90，95%置信区间（1.23 至 2.93））、妊娠 37 周前分娩（AOR=5.97，95%置信区间（3.26 至 10.95））和女性（AOR=1.41，95%置信区间（1.05 至 1.89））的新生儿发生低出生体重的可能性显著更高。
在阿法尔、阿姆哈拉和奥罗米亚地区发现了低出生体重的高风险区域。因此，针对这些热点地区的政策干预，并注重提高孕产妇教育水平、加强贫血控制计划以及消除可改变的早产原因，可能对降低埃塞俄比亚的低出生体重差距至关重要。
