Socio-environmental predictors of diabetes incidence disparities in Tanzania mainland: a comparison of regression models for count data

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dc.contributor.authorMbwambo, Sauda Hatibu
dc.contributor.authorMbago, Maurice C.
dc.contributor.authorRao, Gadde Srinivasa
dc.date.accessioned2024-08-17T09:23:08Z
dc.date.available2024-08-17T09:23:08Z
dc.date.issued2024
dc.descriptionAbstract. Full text available at https://link.springer.com/article/10.1186/s12874-024-02166-w
dc.description.abstractAbstract Background Diabetes is one of the top four non-communicable diseases that cause death and illness to many people around the world. This study aims to use an efficient count data model to estimate socio-environmental factors associated with diabetes incidences in Tanzania mainland, addressing lack of evidence on the efficient count data model for estimating factors associated with disease incidences disparities. Methods This study analyzed diabetes counts in 184 Tanzania mainland councils collected in 2020. The study applied generalized Poisson, negative binomial, and Poisson count data models and evaluated their adequacy using information criteria and Pearson chi-square values. Results The data were over-dispersed, as evidenced by the mean and variance values and the positively skewed histograms. The results revealed uneven distribution of diabetes incidence across geographical locations, with northern and urban councils having more cases. Factors like population, GDP, and hospital numbers were associated with diabetes counts. The GP model performed better than NB and Poisson models. Conclusion The occurrence of diabetes can be attributed to geographical locations. To address this public health issue, environmental interventions can be implemented. Additionally, the generalized Poisson model is an effective tool for analyzing health information system count data across different population subgroups.
dc.identifier.citationMbwambo, S. H., Mbago, M. C., & Rao, G. S. (2024). Socio-environmental predictors of diabetes incidence disparities in Tanzania mainland: a comparison of regression models for count data. BMC Medical Research Methodology, 24(1), 75.
dc.identifier.doi10.1186/s12874-024-02166-w
dc.identifier.otherURL: https://link.springer.com/article/10.1186/s12874-024-02166-w
dc.identifier.urihttps://repository.udom.ac.tz/handle/20.500.12661/4665
dc.language.isoen
dc.publisherSpringer Science and Business Media LLC
dc.relation.ispartofBMC Medical Research Methodology
dc.subjectDiabetes Incidence
dc.subjectCount Data Models
dc.subjectGeneralized Poisson Model
dc.subjectGeographical Distribution
dc.subjectSocio-Environmental Factors
dc.titleSocio-environmental predictors of diabetes incidence disparities in Tanzania mainland: a comparison of regression models for count data
dc.typeArticle
oaire.citation.issue1
oaire.citation.volume24
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