不见树木不见森林:印度北比哈尔邦分区级死亡率模式调查

S. Cynthia, M. George, P. Finny, Mathew Thomas, L. Armstrong
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引用次数: 0

摘要

背景和目的:在比哈尔邦这样一个拥有2亿人口的邦,由于缺乏对死亡率模式的了解,导致卫生支出的规划和优先次序被误导。本研究旨在估计北比哈尔邦一个地区与邦内其他地区和国家之间死亡率的区域差异。方法:采用多阶段聚类设计,对北比哈尔邦六个社区发展街区的4159户家庭进行了访谈,确定了2014年至2015年Chhath节日期间的死亡人数。死因通过尸检评估,并使用国际疾病分类10进行编码。计算比例死亡率和特定死亡率。结果:229例死亡中,仅有7%登记在册。该地区的流行病学过渡水平为1.12,婴儿死亡率为每1000例活产72例(95%可信区间[CI] 55.7-88.4),五岁以下儿童死亡率为每1000例活产93.2例(95%可信区间[CI] 74.6-111.7)。这些比率是政府估计的两倍。在婴儿死亡中,感染占主导地位,而在成人死亡中,呼吸系统疾病超过循环系统疾病,这在州和国家死亡率中可见一斑。结论:本研究表明,区域死亡率模式与州和全国平均估计存在很大差异。孕产妇和新生儿疾病以及传染病造成的死亡仍然占主导地位,超过其他原因。通过加强生命登记制度获得关于死亡原因的分类信息,将使这些差异得到关注。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Missing the trees for the forest: A survey of sub-district-level mortality pattern in North Bihar, India
Background and Objective: The paucity of knowledge on mortality patterns in a state such as Bihar with its population of 200 million contributes to misdirected planning and prioritization of health expenditure. This study aims to estimate the regional differences in mortality rates between a region in North Bihar and the rest of state and country. Methodology: Using a multi-stage cluster design, 4159 households were interviewed across six Community Development blocks in North Bihar, identifying deaths between the Chhath festivals of 2014 and 2015. The cause of death was assessed by verbal autopsy and coded using the International Classification of Disease 10. Proportionate and specific mortality rates were calculated. Results: Of 229 deaths, only 7% were registered. The epidemiological transition level for the region was 1.12 with an infant mortality rate of 72 per 1000 live births (95% confidence interval [CI] 55.7–88.4) and under-five mortality rate of 93.2 per 1000 live births (95% CI 74.6–111.7). These rates were double that of the state estimates. Among infant deaths, infections predominated over prematurity while in adult deaths diseases of the respiratory system exceed diseases of the circulatory system as seen in the state and country mortality rates. Conclusions: This study indicates that regional mortality patterns widely differ from state and national average estimates. Deaths due to maternal and neonatal conditions along with communicable diseases still predominate over other causes. Obtaining disaggregated information on causes of death by strengthening the vital registration system will bring these variations into focus.
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