Simultaneous quantile regression and determinants of under-five severe chronic malnutrition in Ghana
Simultaneous quantile regression and determinants of under-five severe chronic malnutrition in Ghana
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DOI：
10.1186/s12889-020-08782-7
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发表时间：
2020-05-07
影响因子：
4.5
通讯作者：
Aheto, Justice Moses K.
中科院分区：
文献类型：
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作者：
Aheto, Justice Moses K.
5岁以下儿童营养不良是造成死亡率和发病率的一个主要公共卫生问题，特别是在加纳这样的发展中国家，那里的营养不良率仍然高得令人无法接受。利用适当和先进的统计方法确定五岁以下儿童营养不良的关键风险因素，有助于制定适当的卫生规划和政策，以实现联合国可持续发展目标2的具体目标2。本研究试图建立一个同步分位数回归，一个深入的统计模型，以确定五岁以下严重慢性营养不良（严重发育不良）的关键危险因素。方法基于2014年加纳人口与健康调查的全国代表性数据，估计身高年龄z分数（HAZ）。采用多变量同步分位数回归模型，根据HAZ（一种衡量人群慢性营养不良的指标）确定严重发育迟缓的关键危险因素。建立了以严重发育不良为重点的HAZ分位数模型，并确定了危险因素的影响。对不同选择的严重发育分位数与其他分位数的坡度差异进行显著性检验。一个分位数的斜率回归图被开发出来，以直观地检查风险因素在这些分位数上的影响。结果共分析2716例儿童资料，其中重度发育不良144例（5.3%）。这些模型确定了儿童层面的因素，如出生类型、性别、年龄、分娩地点和出生时的体型，是五岁以下儿童严重发育迟缓的重要风险因素。被确定为5岁以下儿童严重发育迟缓的显著预测因子的产妇和家庭水平因素是产妇年龄和教育程度、产妇国民健康保险状况、家庭财富状况和家庭中5岁以下儿童人数。在0.1和0.9分位数之间的斜率存在非常显著的差异。从0.1到0.9所选分位数的分位数回归图显示，在所考虑的热影响区分位数中，协变量的影响存在实质性差异。结论确定了有助于制定儿童营养与健康政策和干预措施的关键危险因素，这些政策和干预措施将改善儿童营养结局和生存率。采用多变量同步分位数回归模型对五岁以下儿童严重发育迟缓进行建模，有助于解决五岁以下儿童严重发育迟缓问题。
BackgroundUnder-five malnutrition is a major public health issue contributing to mortality and morbidity, especially in developing countries like Ghana where the rates remain unacceptably high. Identification of critical risk factors of under-five malnutrition using appropriate and advanced statistical methods can help formulate appropriate health programmes and policies aimed at achieving the United Nations SDG Goal 2 target 2. This study attempts to develop a simultaneous quantile regression, an in-depth statistical model to identify critical risk factors of under-five severe chronic malnutrition (severe stunting).MethodsBased on the nationally representative data from the 2014 Ghana Demographic and Health Survey, height-for-age z-score (HAZ) was estimated. Multivariable simultaneous quantile regression modelling was employed to identify critical risk factors for severe stunting based on HAZ (a measure of chronic malnutrition in populations). Quantiles of HAZ with focus on severe stunting were modelled and the impact of the risk factors determined. Significant test of the difference between slopes at different selected quantiles of severe stunting and other quantiles were performed. A quantile regression plots of slopes were developed to visually examine the impact of the risk factors across these quantiles.ResultsData on a total of 2716 children were analysed out of which 144 (5.3%) were severely stunted. The models identified child level factors such as type of birth, sex, age, place of delivery and size at birth as significant risk factors of under-five severe stunting. Maternal and household level factors identified as significant predictors of under-five severe stunting were maternal age and education, maternal national health insurance status, household wealth status, and number of children under-five in households. Highly significant differences exist in the slopes between 0.1 and 0.9 quantiles. The quantile regression plots for the selected quantiles from 0.1 to 0.9 showed substantial differences in the impact of the covariates across the quantiles of HAZ considered.ConclusionCritical risk factors that can aid formulation of child nutrition and health policies and interventions that will improve child nutritional outcomes and survival were identified. Modelling under-five severe stunting using multivariable simultaneous quantile regression models could be beneficial to addressing the under-five severe stunting.