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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Journal
Geospatial health
Published
2024-09-10
DOI
https://doi.org/10.4081/gh.2024.1307
Citations
1
Primary Topic
Global Public Health Policies and Epidemiology
Type
article
Field-Weighted Citation Impact
0.67
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article

The distribution of cardiovascular diseases in Tanzania: a spatio-temporal investigation

Amina S. Msengwa, Bernada E Sianga, Maurice C. Y. Mbago
1 citations
Geospatial health
Global Public Health Policies and Epidemiology
0.67
article

The distribution of cardiovascular diseases in Tanzania: a spatio-temporal investigation

Amina S. Msengwa, Bernada E Sianga, Maurice C. Y. Mbago
article en
1 citations

Abstract

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.

Geospatial healthVol. 19(2)
University of Dar es Salaam (TZ)
Life below water
Openalex Percentile: Top 23%
Global Public Health Policies and Epidemiology
0.67
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The distribution of cardiovascular diseases in Tanzania: a spatio-temporal investigation — Amina S. Msengwa, Bernada E Sianga, et al. · Geospatial health (2024) | TGRS Research Map | TGRS