Measuring the local burden of disease. A study of years of life lost in sub-Saharan Africa.
Measuring the local burden of disease. A study of years of life lost in sub-Saharan Africa.
复制标题
衡量当地疾病负担。
DOI：
--
复制
发表时间：
2001
影响因子：
7.7
通讯作者：
Christoph M. Schmidt
中科院分区：
文献类型：
--
作者：
R. Würthwein;A. Gbangou;Rainer Sauerborn;Christoph M. Schmidt
背景
一个有效的卫生政策需要一个可靠的定性疾病负担（BOD）的原因。全球疾病负担研究（GBDS）旨在提供这一信息。特别是对于撒哈拉以南非洲（SSA），GBDS依赖于推断和专家猜测。其结果缺乏当地测量的流行病学数据的验证。
方法
本研究介绍了当地测量的BOD数据在布基纳法索的一个卫生区，并将其与SSA的GBDS的结果进行比较。作为BOD指标，使用GBDS建议的标准寿命损失年数（年龄加权YLL，贴现率为3%）。为了研究不同的年龄和时间偏好权重对我们结果的影响，BOD模式再次估计，第一，YLL没有折扣，没有年龄加权，第二，死亡率的数字。
结果
我们的数据表现出相同的定性BOD模式的GBDS结果的年龄和性别。我们估计53.9%的BOD由男性承担，而GBDS报告的这一比例为53.2%。然而，按生化需氧量所占份额对疾病进行的排序却有很大的不同。在我们的研究和GBDS中，疟疾、肠道疾病和下呼吸道感染占据了前三位，只是它们各自的顺序不同。蛋白质-能量营养不良、细菌性脑膜炎和肠道线虫感染在努纳排名第5、6和7位，而在GBDS排名第15、27和38位。结果是不敏感的不同年龄和时间偏好的权重。具体而言，参数的选择不如指标的选择重要。
结论
地方卫生政策应该基于当地的BOD测量，而不是依赖于推断，可能不代表真正的BOD结构的原因。
BACKGROUND
An effective health policy necessitates a reliable characterization of the burden of disease (BOD) by cause. The Global Burden of Disease Study (GBDS) aims to deliver this information. For sub-Saharan Africa (SSA) in particular, the GBDS relies on extrapolations and expert guesses. Its results lack validation by locally measured epidemiological data.
METHODS
This study presents locally measured BOD data for a health district in Burkina Faso and compares them to the results of the GBDS for SSA. As BOD indicator, standard years of life lost (age-weighted YLL, discounted with a discount rate of 3%) are used as proposed by the GBDS. To investigate the influence of different age and time preference weights on our results, the BOD pattern is again estimated using, first, YLL with no discounting and no age-weighting, and, second, mortality figures.
RESULTS
Our data exhibit the same qualitative BOD pattern as the GBDS results regarding age and gender. We estimated that 53.9% of the BOD is carried by men, whereas the GBDS reported this share to be 53.2%. The ranking of diseases by BOD share, though, differs substantially. Malaria, diarrhoeal diseases and lower respiratory infections occupy the first three ranks in our study and in the GBDS, only differing in their respective order. Protein-energy malnutrition, bacterial meningitis and intestinal nematode infections occupy ranks 5, 6 and 7 in Nouna but ranks 15, 27 and 38 in the GBDS. The results are not sensitive to the different age and time preference weights used. Specifically, the choice of parameters matters less than the choice of indicator.
CONCLUSIONS
Local health policy should rather be based on local BOD measurement instead of relying on extrapolations that might not represent the true BOD structure by cause.