肯尼亚尼安扎儿童死亡率决定因素的统计建模和评估

Otieno Otieno, M. Kosgei, Nelson Onyango Owuor
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摘要

千年发展目标之一是到2015年将婴儿和儿童死亡率降低到1990年死亡率的三分之二。总的来说,在降低五岁以下儿童死亡率方面取得了重大进展。全球五岁以下儿童死亡率下降了59%,从1990年的每千例活产死亡93人降至2019年的38人。在肯尼亚,2021年的婴儿死亡率为每1000例活产32.913例死亡,比2020年下降3.36%。2020年,每千名活产婴儿中有34.056人死亡,比2019年下降3.24%。在肯尼亚,尼扬扎省的婴儿死亡率最高(每1 000例活产死亡133人),中部省最低(每1 000例活产死亡44人)。尽管取得了这些进展,但世界仍然需要实现千年发展目标的第四个具体目标,即降低儿童死亡率。这项研究的目的是确定影响肯尼亚儿童死亡率的重要危险因素。本文的主要目标是确定社会经济和人口变量对集群中存在依赖关系的儿童死亡率的影响。然后,我们进行了逻辑回归,并检验了显著协变量的比例性。然后,根据使用问卷调查收集的肯尼亚人口与健康调查(KDHS 2014)数据,进行分层Cox回归模型,最后建立生存分析中的共享脆弱性模型。2014年KDHS数据中的儿童死亡率在老龄化时期进行了分析:从12个月到60个月的死亡率,称为"儿童死亡率"。研究表明,分组(家庭)、产妇的出生年龄、产前间隔时间和过去五年的出生次数对儿童死亡率有重大影响。
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Statistical Modelling and Evaluation of Determinants of Child Mortality in Nyanza, Kenya
: One of the Millennium Development Goals is the reduction of infant and child mortality by two-thirds of 1990 mortality levels by 2015. Generally, significant progress has been made in reducing mortality in children under five years of age. The global under-five mortality rate declined by 59 per cent, from 93 deaths per 1,000 live births in 1990 to 38 in 2019. In Kenya, the infant mortality rate in 2021 is 32.913 deaths per 1000 live births, a 3.36 per cent decline from 2020. In 2020 it was 34.056 deaths per 1,000 live births, a drop of 3.24 per cent from the year 2019. In Kenya, Nyanza Province has the highest infant mortality rate (133 deaths per 1,000 live births) and the lowest in Central Province (44 deaths per 1,000 live births). Despite this advancement, the world still needs to achieve that Millennium Development Goal, target number four, of reducing child mortality. This study aims at identifying vital risk factors affecting child mortality in Kenya. The paper's main objective is to determine the effect of socioeconomic and demographic variables on child mortality in the presence of dependencies in clusters. We then did a logistic regression and tested the proportionality of the significant covariates. Then, performed a Stratified Cox regression model and, finally, a shared frailty model in survival analysis based on data from the Kenya Demographic and Health Survey (KDHS 2014), which was collected using questionnaires. Child mortality from the KDHS 2014 data was analyzed in an ageing period: mortality from the age of 12 months to the age of 60 months, referred to as "child mortality". The study reveals that clusters (households), maternal age at birth, preceding birth interval length and the number of births in the last five years significantly impacted child mortality.
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