Ngwira Alfred, Chamera Francisco, Soko Matrina Mpeketula
Basic Sciences Department, Lilongwe University of Agriculture and Natural Resources, Lilongwe, Malawi.
PeerJ. 2021 Mar 1;9:e10917. doi: 10.7717/peerj.10917. eCollection 2021.
Estimation of prevalence of feeding practices during diarrhea using conventional imputation methods may be biased as these methods apply to observed factors and in this study, feeding practice status was unobserved for those without diarrhea. The study aimed at re-estimating the prevalence of feeding practices using the bivariate sample selection model.
The study used 2015-2016 Malawi demographic health survey (MDHS) data which had 16,246 children records who had diarrhea or not. A bivariate Joe copula regression model with 90 degrees rotation was fitted to either drinking or eating more, with diarrhea as a sample selection outcome in the bivariate models. The prevalence of drinking more than usual and prevalence of eating more than usual were then estimated based on the fitted bivariate model. These prevalences were then compared to the prevalences estimated using the conventional imputation method.
There was a substantial increase in the re-estimated national prevalence of drinking more fluids (40.0%, 95% CI [31.7-50.5]) or prevalence of eating more food (20.46%, 95% CI [9.87-38.55]) using the bivariate model as compared to the prevalences estimated by the conventional imputation method, that is, (28.9%, 95% CI [27.0-30.7]) and (13.1%, 95% CI [12.0-15.0]) respectively. The maps of the regional prevalences showed similar results where the prevalences estimated by the bivariate model were relatively higher than those estimated by the standard imputation method. The presence of diarrhea was somehow weakly negatively correlated with either drinking more fluids or eating more food.
The estimation of prevalence of drinking more fluids or eating more food during diarrhea should use bivariate modelling to model sample selection variable so as to minimize bias. The observed negative correlation between diarrhea presence and feeding practices implies that mothers should be encouraged to let their children drink more fluids or eat more food during diarrhea episode to avoid dehydration and malnutrition.
使用传统插补方法估计腹泻期间喂养行为的患病率可能存在偏差，因为这些方法适用于观察到的因素，而在本研究中，未患腹泻者的喂养行为状态未被观察到。该研究旨在使用双变量样本选择模型重新估计喂养行为的患病率。
该研究使用了2015 - 2016年马拉维人口与健康调查（MDHS）数据，其中有16246名儿童的记录，这些儿童是否患有腹泻。采用旋转90度的双变量乔伊 copula回归模型，以腹泻作为双变量模型中的样本选择结果，对饮水或进食增多的情况进行拟合。然后根据拟合的双变量模型估计比平时饮水更多和比平时进食更多的患病率。接着将这些患病率与使用传统插补方法估计的患病率进行比较。
与传统插补方法估计的患病率相比，即分别为（28.9%，95%置信区间[27.0 - 30.7]）和（13.1%，95%置信区间[12.0 - 15.0]），使用双变量模型重新估计的全国比平时饮水更多的患病率（40.0%，95%置信区间[31.7 - 50.5]）或比平时进食更多的患病率（20.46%，95%置信区间[9.87 - 38.55]）有显著增加。区域患病率地图显示了类似的结果，双变量模型估计的患病率相对高于标准插补方法估计的患病率。腹泻的存在与饮水增多或进食增多之间存在某种程度的弱负相关。
估计腹泻期间饮水增多或进食增多的患病率应使用双变量建模来模拟样本选择变量，以尽量减少偏差。腹泻存在与喂养行为之间观察到的负相关意味着应鼓励母亲在孩子腹泻期间让他们多喝水或多吃东西，以避免脱水和营养不良。
