坦桑尼亚心血管疾病的分布:时空调查。

IF 1 4区 医学 Q4 HEALTH CARE SCIENCES & SERVICES Geospatial Health Pub Date : 2024-09-10 DOI:10.4081/gh.2024.1307
Bernada E Sianga, Maurice C Mbago, Amina S Msengwa
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引用次数: 0

摘要

心血管疾病(CVD)是目前人类健康面临的主要挑战,也是世界上最主要的死亡原因。在坦桑尼亚,因心血管疾病死亡的人数约占非传染性疾病死亡总人数的 13%。本研究利用伯努利概率模型对坦桑尼亚 2010 年至 2019 年心血管疾病的时空聚类进行了研究,对从四家选定医院抽取的数据进行了回顾性时空分析。通过空间扫描统计来识别心血管疾病集群,并使用多元逻辑回归来研究协变量对心血管疾病发病率的影响。结果发现,2011-2015年间心血管疾病的风险相对较高,2015-2019年间则有所下降。时空分析发现,2012 年至 2016 年期间,沿海地区和湖泊地区出现了两个高风险疾病集群(p
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The distribution of cardiovascular diseases in Tanzania: a spatio-temporal investigation.

Cardiovascular Disease (CVD) is currently the major challenge to people's health and the world's top cause of death. In Tanzania, deaths due to CVD account for about 13% of the total deaths caused by the non-communicable diseases. This study examined the spatio-temporal clustering of CVDs from 2010 to 2019 in Tanzania for retrospective spatio-temporal analysis using the Bernoulli probability model on data sampled from four selected hospitals. Spatial scan statistics was performed to identify CVD clusters and the effect of covariates on the CVD incidences was examined using multiple logistic regression. It was found that there was a comparatively high risk of CVD during 2011-2015 followed by a decline during 2015-2019. The spatio-temporal analysis detected two high-risk disease clusters in the coastal and lake zones from 2012 to 2016 (p<0.001), with similar results produced by purely spatial analysis. The multiple logistic model showed that sex, age, blood pressure, body mass index (BMI), alcohol intake and smoking were significant predictors of CVD incidence.

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来源期刊
Geospatial Health
Geospatial Health 医学-公共卫生、环境卫生与职业卫生
CiteScore
2.40
自引率
11.80%
发文量
48
审稿时长
12 months
期刊介绍: The focus of the journal is on all aspects of the application of geographical information systems, remote sensing, global positioning systems, spatial statistics and other geospatial tools in human and veterinary health. The journal publishes two issues per year.
期刊最新文献
Childhood stunting in Indonesia: assessing the performance of Bayesian spatial conditional autoregressive models. A two-stage location model covering COVID-19 sampling, transport and DNA diagnosis: design of a national scheme for infection control. The distribution of cardiovascular diseases in Tanzania: a spatio-temporal investigation. Performance of a negative binomial-GLM in spatial scan statistic: a case study of low-birth weights in Pakistan. Tuberculosis in Aceh Province, Indonesia: a spatial epidemiological study covering the period 2019-2021.
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