scholarly journals Bayesian model and spatial analysis of oral and oropharynx cancer mortality in Minas Gerais, Brazil

2018 ◽  
Vol 23 (1) ◽  
pp. 153-160 ◽  
Author(s):  
Emílio Prado da Fonseca ◽  
Cláudia Di Lorenzo Oliveira ◽  
Francisco Chiaravalloti Neto ◽  
Antonio Carlos Pereira ◽  
Silvia Amélia Scudeler Vedovello ◽  
...  
Keyword(s):  
Spatial Analysis ◽  
Mortality Rate ◽  
Cancer Mortality ◽  
Bayesian Model ◽  
Spatial Epidemiology ◽  
Minas Gerais ◽  
Bayesian Estimator ◽  
Empirical Bayesian ◽  
Oropharynx Cancer ◽  
South Central

Abstract The objective of this study was to determine of oral and oropharynx cancer mortality rate and the results were analyzed by applying the Spatial Analysis of Empirical Bayesian Model. To this end, we used the information contained in the International Classification of Diseases (ICD-10), Chapter II, Category C00 to C14 and Brazilian Mortality Information System (SIM) of Minas Gerais State. Descriptive statistics were observed and the gross rate of mortality was calculated for each municipality. Then Empirical Bayesian estimators were applied. The results showed that, in 2012, in the state of Minas Gerais, were registered 769 deaths of patients with cancer of oral and oropharynx, with 607 (78.96%) men and 162 (21.04%) women. There was a wide variation in spatial distribution of crude mortality rate and were identified agglomeration in the South, Central and North more accurately by Bayesian Estimator Global and Local Model. Through Bayesian models was possible to map the spatial clustering of deaths from oral cancer more accurately, and with the application of the method of spatial epidemiology, it was possible to obtain more accurate results and provide subsidies to reduce the number of deaths from this type of cancer.

scholarly journals Geographical Variation in Oral and Oropharynx Cancer Mortality in Brazil: A Bayesian Approach

2018 ◽  
Vol 15 (12) ◽  
pp. 2641 ◽  
Author(s):  
Emílio Prado da Fonseca ◽  
Regiane Cristina do Amaral ◽  
Antonio Carlos Pereira ◽  
Carla Martins Rocha ◽  
Marc Tennant
Keyword(s):  
Cancer Mortality ◽  
Oropharyngeal Cancer ◽  
Bayesian Model ◽  
Mortality Rates ◽  
Alternative Interpretation ◽  
Empirical Bayesian ◽  
Oropharynx Cancer ◽  
Icd 10 ◽  
Oral And Oropharyngeal Cancer ◽  
And Gender

Recent studies have shown a high number of deaths from oral and oropharyngeal cancer worldwide, Brazil included. For this study, the deaths data (ICD-10, chapter II, categories C00 to C14) was obtained from Mortality Information System (SIM) and standardized by gender and population for each of the 554 Microregions of Brazil. The raw mortality rates were adopted as the standard and compared to the application of smoothing by the Bayesian model. In order to describe the geographical pattern of the occurrence of oral cancer, thematic maps were constructed, based on the distributions of mortality rates for Microregions and gender. Results: There were 7882 deaths registered due to oral and oropharyngeal cancer in Brazil, of which 6291 (79.81%) were male and 1591 (20.19%) female. The Empirical Bayesian Model presented greater scattering with mosaic appearance throughout the country, depicting high rates in Southeast and South regions interpolated with geographic voids of low rates in Midwest and North regions. For males, it was possible to identify expressive clusters in the Southeast and South regions. Conclusion: The Empirical Bayesian Model allowed an alternative interpretation of the oral and oropharynx cancer mortality mapping in Brazil.

scholarly journals Leading cancers contributing to educational disparities in cancer mortality in the US, 2017

2021 ◽  
Author(s):  
Diana R. Withrow ◽  
Neal D. Freedman ◽  
James T. Gibson ◽  
Mandi Yu ◽  
Anna M. Nápoles ◽  
...  
Keyword(s):  
Lung Cancer ◽  
High School ◽  
Mortality Rate ◽  
Cancer Mortality ◽  
Death Certificate ◽  
Bachelor's Degree ◽  
Educational Disparities ◽  
Individual Level ◽  
Death Certificate Data ◽  
The Us

Abstract Purpose To inform prevention efforts, we sought to determine which cancer types contribute the most to cancer mortality disparities by individual-level education using national death certificate data for 2017. Methods Information on all US deaths occurring in 2017 among 25–84-year-olds was ascertained from national death certificate data, which include cause of death and educational attainment. Education was classified as high school or less (≤ 12 years), some college or diploma (13–15 years), and Bachelor's degree or higher (≥ 16 years). Cancer mortality rate differences (RD) were calculated by subtracting age-adjusted mortality rates (AMR) among those with ≥ 16 years of education from AMR among those with ≤ 12 years. Results The cancer mortality rate difference between those with a Bachelor's degree or more vs. high school or less education was 72 deaths per 100,000 person-years. Lung cancer deaths account for over half (53%) of the RD for cancer mortality by education in the US. Conclusion Efforts to reduce smoking, particularly among persons with less education, would contribute substantially to reducing educational disparities in lung cancer and overall cancer mortality.

scholarly journals Identification of Mortality Risks in the Advancement of Old Age: Application of Proportional Hazard Models Based on the Stepwise Variable Selection and the Bayesian Model Averaging Approach

Nutrients ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 1098
Author(s):  
Ewelina Łukaszyk ◽  
Katarzyna Bień-Barkowska ◽  
Barbara Bień
Keyword(s):  
Vitamin D ◽  
Mortality Rate ◽  
Plasma Level ◽  
Variable Selection ◽  
Lymphocyte Count ◽  
Bayesian Model ◽  
Bayesian Model Averaging ◽  
Multivariable Analysis ◽  
Model Averaging ◽  
Nutritional Risk Index

Identifying factors that affect mortality requires a robust statistical approach. This study’s objective is to assess an optimal set of variables that are independently associated with the mortality risk of 433 older comorbid adults that have been discharged from the geriatric ward. We used both the stepwise backward variable selection and the iterative Bayesian model averaging (BMA) approaches to the Cox proportional hazards models. Potential predictors of the mortality rate were based on a broad range of clinical data; functional and laboratory tests, including geriatric nutritional risk index (GNRI); lymphocyte count; vitamin D, and the age-weighted Charlson comorbidity index. The results of the multivariable analysis identified seven explanatory variables that are independently associated with the length of survival. The mortality rate was higher in males than in females; it increased with the comorbidity level and C-reactive proteins plasma level but was negatively affected by a person’s mobility, GNRI and lymphocyte count, as well as the vitamin D plasma level.

scholarly journals A Bayesian model for binary Markov chains

2004 ◽  
Vol 2004 (8) ◽  
pp. 421-429 ◽  
Author(s):  
Souad Assoudou ◽  
Belkheir Essebbar
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Markov Chains ◽  
Bayesian Estimation ◽  
Bayesian Model ◽  
Transition Probabilities ◽  
Simulated Data ◽  
Bayesian Estimator ◽  
Jeffreys Prior ◽  
Data Set

This note is concerned with Bayesian estimation of the transition probabilities of a binary Markov chain observed from heterogeneous individuals. The model is founded on the Jeffreys' prior which allows for transition probabilities to be correlated. The Bayesian estimator is approximated by means of Monte Carlo Markov chain (MCMC) techniques. The performance of the Bayesian estimates is illustrated by analyzing a small simulated data set.

scholarly journals A Spatial Analysis of Tuberculosis Related Mortality in South Africa

2021 ◽  
Vol 18 (22) ◽  
pp. 11865
Author(s):  
Dan Kibuuka ◽  
Charles Mpofu ◽  
Penny Neave ◽  
Samuel Manda
Keyword(s):  
Public Health ◽  
South Africa ◽  
Mortality Rate ◽  
Spatial Epidemiology ◽  
Hot Spot ◽  
Mortality Rates ◽  
Cold Spot ◽  
The South ◽  
Female Population ◽  
Death Rates

Background: South Africa, with an estimated annual tuberculosis (TB) incidence of 360,000 cases in 2019, remains one of the countries with the largest burden of TB in the world. The identification of highly burdened TB areas could support public health policy planners to optimally target resources and TB control and prevention interventions. Objective: To investigate the spatial epidemiology and distribution of TB mortality in South Africa in 2010 and its association with area-level poverty and HIV burden. Methods: The study analysed a total of 776,176 TB deaths for the period 2005–2015. Local and global and spatial clustering of TB death rates were investigated by Global and Local Moran’s Indices methods (Moran’s I). The spatial regression analysis was employed to assess the effect of poverty and HIV on TB mortality rates. Results: There was a significant decrease in TB mortality rate, from 179 per 100,000 population in 2005 to 60 per 100,000 population in 2015. The annual TB mortality rate was higher among males (161.5 per 100,000 male population; (95% confidence interval (CI) 132.9, 190.0) than among females (123.2 per 100,000 female population; (95% CI 95.6, 150.8)). The 35–44 age group experienced higher TB mortality rates, regardless of gender and time. Hot spot clusters of TB mortality were found in the South-Eastern parts of the country, whereas cold spot clusters were largely in the north-eastern parts. Tuberculosis death rates were positively associated with poverty, as measured by the South African Multidimension Poverty Index (SAMPI) as well TB death rates in the neighbouring districts. Conclusion: The findings of this study revealed a statistically significant decrease in TB deaths and a disproportionate distribution of TB deaths among certain areas and population groups in South Africa. The existence of the identified inequalities in the burden of TB deaths calls for targeted public health interventions, policies, and resources to be directed towards the most vulnerable populations in South Africa.

Sign in / Sign up

Export Citation Format

Share Document