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Abstract：
BACKGROUND: Many studies have been conducted on under-five mortality in India and most of them focused on the associations between individual-level factors and under-five mortality risks. On the contrary, only a scarce number of literatures talked about contextual level effect on under-five mortality. Hence, it is very important to have thorough study of under-five mortality at various levels. This can be done by applying multilevel analysis, a method that assesses both fixed and random effects in a single model. The multilevel analysis allows extracting the influence of individual and community characteristics on under-five mortality. Hence, this study would contribute substantially in understanding the under-five mortality from a different perspective.
METHODS: The study used data from the Demographic and Health Survey (DHS) acquired in India, i.e., the fourth round of National Family and Health Survey (2015-16). It is a nationally representative repeated cross-sectional data. Multilevel Parametric Survival Model (MPSM) was employed to assess the influence of contextual correlates on the outcome. The assumption behind this study is that \'individuals\' (i.e., level-1) are nested within \'districts\' (i.e., level-2), and districts are enclosed within \'states\' (i.e., level-3). This suggests that people have varying health conditions, residing in dissimilar communities with different characteristics.
RESULTS: Highest under-five mortality i.e., 3.85% are happening among those women whose birth interval is less than two years. In case of parity, around 4% under-five mortality is among women with Third and above order parity. Further, findings from the full model is that ICC values of 1.17 and 0.65% are the correlation of the likelihood of having under-five mortality risk among people residing in the state and district communities, respectively. Besides, the risk of dying was increased alarmingly in the first year of life and slowly to aged 3 years and then it remains steady.
CONCLUSIONS: This study has revealed that both aspects viz. individual and contextual effect of the community are necessary to address the importance variations in under-five mortality in India. In order to ensure substantial reduction in under-five mortality, findings of the study support some policy initiatives that involves the need to think beyond individual level effects and considering contextual characteristics.
METHODS: The study used data from the Demographic and Health Survey (DHS) acquired in India, i.e., the fourth round of National Family and Health Survey (2015-16). It is a nationally representative repeated cross-sectional data. Multilevel Parametric Survival Model (MPSM) was employed to assess the influence of contextual correlates on the outcome. The assumption behind this study is that \'individuals\' (i.e., level-1) are nested within \'districts\' (i.e., level-2), and districts are enclosed within \'states\' (i.e., level-3). This suggests that people have varying health conditions, residing in dissimilar communities with different characteristics.
RESULTS: Highest under-five mortality i.e., 3.85% are happening among those women whose birth interval is less than two years. In case of parity, around 4% under-five mortality is among women with Third and above order parity. Further, findings from the full model is that ICC values of 1.17 and 0.65% are the correlation of the likelihood of having under-five mortality risk among people residing in the state and district communities, respectively. Besides, the risk of dying was increased alarmingly in the first year of life and slowly to aged 3 years and then it remains steady.
CONCLUSIONS: This study has revealed that both aspects viz. individual and contextual effect of the community are necessary to address the importance variations in under-five mortality in India. In order to ensure substantial reduction in under-five mortality, findings of the study support some policy initiatives that involves the need to think beyond individual level effects and considering contextual characteristics.
摘要：
背景：印度已经对五岁以下儿童死亡率进行了许多研究，其中大多数研究集中在个体水平因素与五岁以下儿童死亡风险之间的关联。相反,只有很少的文献谈到上下文水平对五岁以下儿童死亡率的影响。因此，对各级五岁以下儿童死亡率进行深入研究非常重要。这可以通过应用多层次分析来完成，一种在单一模型中同时评估固定效应和随机效应的方法。多水平分析可以提取个人和社区特征对五岁以下儿童死亡率的影响。因此，这项研究将有助于从不同角度理解5岁以下儿童死亡率.
方法：该研究使用了来自印度人口与健康调查（DHS）的数据，即，第四轮全国家庭和健康调查（2015-16）。它是具有全国代表性的重复横截面数据。采用多水平参数生存模型（MPSM）来评估上下文相关因素对结果的影响。这项研究背后的假设是“个体”(即，级别1)嵌套在“地区”(即，Level-2),和地区被封闭在\“州\”(即，3级）。这表明人们的健康状况各不相同，居住在具有不同特征的不同社区。
结果：五岁以下儿童死亡率最高，即3.85%发生在生育间隔少于两年的妇女中。在奇偶校验的情况下，大约4%的五岁以下儿童死亡率是三等及以上等级的女性。Further,从整个模型的发现是，ICC值1.17和0.65%是居住在州和地区社区的人群中五岁以下儿童死亡风险的可能性的相关性，分别。此外,死亡的风险在生命的第一年惊人地增加，慢慢地增加到3岁，然后保持稳定。
结论：这项研究揭示了这两个方面。社区的个人和背景影响对于解决印度五岁以下儿童死亡率的重要性变化是必要的。为了确保大幅度降低五岁以下儿童的死亡率，该研究的结果支持一些政策举措，这些举措涉及超越个人层面的影响和考虑背景特征的需要。
方法：该研究使用了来自印度人口与健康调查（DHS）的数据，即，第四轮全国家庭和健康调查（2015-16）。它是具有全国代表性的重复横截面数据。采用多水平参数生存模型（MPSM）来评估上下文相关因素对结果的影响。这项研究背后的假设是“个体”(即，级别1)嵌套在“地区”(即，Level-2),和地区被封闭在\“州\”(即，3级）。这表明人们的健康状况各不相同，居住在具有不同特征的不同社区。
结果：五岁以下儿童死亡率最高，即3.85%发生在生育间隔少于两年的妇女中。在奇偶校验的情况下，大约4%的五岁以下儿童死亡率是三等及以上等级的女性。Further,从整个模型的发现是，ICC值1.17和0.65%是居住在州和地区社区的人群中五岁以下儿童死亡风险的可能性的相关性，分别。此外,死亡的风险在生命的第一年惊人地增加，慢慢地增加到3岁，然后保持稳定。
结论：这项研究揭示了这两个方面。社区的个人和背景影响对于解决印度五岁以下儿童死亡率的重要性变化是必要的。为了确保大幅度降低五岁以下儿童的死亡率，该研究的结果支持一些政策举措，这些举措涉及超越个人层面的影响和考虑背景特征的需要。
