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首页> 外文期刊>The American Journal of Tropical Medicine and Hygiene >Analysis of childhood morbidity with geoadditive probit and latent variable model: a case study for Egypt.
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Analysis of childhood morbidity with geoadditive probit and latent variable model: a case study for Egypt.

机译：用地理加和概率和潜变量模型分析儿童发病率：以埃及为例。

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This work applies geoadditive latent variable models to analyze the impact of risk factors and the spatial effects on the latent, unobservable variable "health status" or "frailty" of a child less than 5 years of age using the 2003 Demographic and Health survey (DHS) data from Egypt. Childhood diseases are a major cause of death of children in the developing world. In developing countries a quarter of infant and childhood mortality is related to childhood disease, particularly to diarrhea. Our case study is based on the 2003 Demographic and Health Survey for Egypt (EDHS). It provided data on the prevalence and treatment of common childhood disease such as diarrhea, cough, and fever, which are seen as symptoms or indicators of children's health status, causing increased morbidity and mortality. These causes are often associated with a number of risk factors, including inadequate antenatal care, lack of or inadequate vaccination, and environmental factors that affected the health of the child in early years, various bio-demographic and socioeconomic variables. In this work, we investigate the impact of such factors on childhood disease with flexible geoadditive models. These models allow us to analyze usual linear effects of covariates, nonlinear effects of continuous covariates, and small-area regional effects within a unified, semi-parametric Bayesian framework for modeling and inference. As a first step, we use separate geoadditive probit models the binary target variables for diarrhea, cough, and fever using covariate information from the EDHS. Based on these results, we then apply recently developed geoadditive latent variable models where the three observable disease variables are taken as indicators for the latent individual variable "health status" or "frailty" of a child. This modeling approach allows us to study the common influence of risk factors on individual frailties of children, thereby automatically accounting for association between diseases as indicators for health status.
机译：这项工作应用了地理叠加潜在变量模型，使用2003年人口与健康调查（DHS）分析了风险因素的影响以及空间效应对5岁以下儿童潜在，不可观察的变量“健康状况”或“体弱”的影响）的数据。童年疾病是发展中国家儿童死亡的主要原因。在发展中国家，四分之一的婴儿和儿童死亡率与儿童疾病尤其是腹泻有关。我们的案例研究基于2003年埃及人口与健康调查（EDHS）。它提供了有关儿童常见疾病如腹泻，咳嗽和发烧的流行和治疗数据，这些数据被视为儿童健康状况的症状或指标，从而导致发病率和死亡率增加。这些原因通常与许多风险因素有关，包括产前护理不足，疫苗接种不足或不足以及早年影响儿童健康的环境因素，各种生物人口统计学和社会经济变量。在这项工作中，我们使用灵活的地理添加剂模型调查了这些因素对儿童疾病的影响。这些模型使我们能够在统一的半参数贝叶斯框架内对协变量的常规线性效应，连续协变量的非线性效应以及小区域区域效应进行建模和推断。第一步，我们使用来自EDHS的协变量信息，使用单独的地理累加概率模型对腹泻，咳嗽和发烧的二元目标变量进行建模。基于这些结果，我们然后应用最近开发的地理叠加潜在变量模型，其中将三个可观察到的疾病变量用作儿童潜在个体变量“健康状况”或“脆弱”的指标。这种建模方法使我们能够研究风险因素对儿童个体脆弱的共同影响，从而自动将疾病之间的关联作为健康状况的指标。

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