Amek Nyaguara O, Odhiambo Frank O, Khagayi Sammy, Moige Hellen, Orwa Gordon, Hamel Mary J, Van Eijk Annemieke, Vulule John, Slutsker Laurence, Laserson Kayla F
Center for Global Health Research, Kenya Medical Research Institute, Kisumu, Kenya;
Center for Global Health Research, Kenya Medical Research Institute, Kisumu, Kenya.
Glob Health Action. 2014 Oct 29;7:25581. doi: 10.3402/gha.v7.25581. eCollection 2014.
Assessing the progress in achieving the United Nation's Millennium Development Goals in terms of population health requires consistent and reliable information on cause-specific mortality, which is often rare in resource-constrained countries. Health and demographic surveillance systems (HDSS) have largely used medical personnel to review and assign likely causes of death based on the information gathered from standardized verbal autopsy (VA) forms. However, this approach is expensive and time consuming, and it may lead to biased results based on the knowledge and experience of individual clinicians. We assessed the cause-specific mortality for children under 5 years old (under-5 deaths) in Siaya County, obtained from a computer-based probabilistic model (InterVA-4).
Successfully completed VA interviews for under-5 deaths conducted between January 2003 and December 2010 in the Kenya Medical Research Institute/US Centers for Disease Control and Prevention HDSS were extracted from the VA database and processed using the InterVA-4 (version 4.02) model for interpretation. Cause-specific mortality fractions were then generated from the causes of death produced by the model.
A total of 84.33% (6,621) childhood deaths had completed VA data during the study period. Children aged 1-4 years constituted 48.53% of all cases, and 42.50% were from infants. A single cause of death was assigned to 89.18% (5,940) of cases, 8.35% (556) of cases were assigned two causes, and 2.10% (140) were assigned 'indeterminate' as cause of death by the InterVA-4 model. Overall, malaria (28.20%) was the leading cause of death, followed by acute respiratory infection including pneumonia (25.10%), in under-5 children over the study period. But in the first 5 years of the study period, acute respiratory infection including pneumonia was the main cause of death, followed by malaria. Similar trends were also reported in infants (29 days-11 months) and children aged 1-4 years.
Under-5 cause-specific mortality obtained using the InterVA-4 model is consistent with existing knowledge on the burden of childhood diseases in rural western Kenya.
要从人口健康方面评估联合国千年发展目标的进展情况,需要有关于特定病因死亡率的一致且可靠的信息,而在资源有限的国家,此类信息往往很稀缺。卫生与人口监测系统(HDSS)大多利用医务人员根据从标准化的口头尸检(VA)表格收集的信息来审查并确定可能的死因。然而,这种方法成本高昂且耗时,还可能因个别临床医生的知识和经验而导致结果有偏差。我们评估了从基于计算机的概率模型(InterVA - 4)获得的西亚亚县5岁以下儿童(5岁以下儿童死亡)的特定病因死亡率。
从VA数据库中提取2003年1月至2010年12月在肯尼亚医学研究所/美国疾病控制与预防中心卫生与人口监测系统中成功完成的5岁以下儿童死亡的VA访谈,并使用InterVA - 4(版本4.02)模型进行处理以进行解读。然后根据该模型得出的死因生成特定病因死亡率。
在研究期间,共有84.33%(6621例)儿童死亡病例有完整的VA数据。1 - 4岁儿童占所有病例的48.53%,婴儿占42.50%。89.18%(5940例)的病例被确定为单一死因,8.35%(556例)的病例被确定为两种死因,2.10%(140例)的病例被InterVA - 4模型判定为“死因不明”。总体而言,在研究期间,疟疾(28.20%)是5岁以下儿童的主要死因,其次是包括肺炎在内的急性呼吸道感染(25.10%)。但在研究期的前5年,包括肺炎在内的急性呼吸道感染是主要死因,其次是疟疾。在婴儿(29天至ll个月)和1 - 4岁儿童中也报告了类似趋势。
使用InterVA - 4模型得出的5岁以下儿童特定病因死亡率与肯尼亚西部农村地区儿童疾病负担的现有知识相符。