Modelling of South African Hypertension: Comparative Analysis of the Classical and Bayesian Quantile Regression Approaches.

Hypertension has become a major public health challenge and a crucial area of research due to its high prevalence across the world including the sub-Saharan Africa. No previous study in South Africa has investigated the impact of blood pressure risk factors on different specific conditional quantile...

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Publicado en:Inquiry (00469580) pp. 1 - 10
Autores principales: Kuhudzai, Anesu Gelfand, Van Hal, Guido, Van Dongen, Stefan, Hoque, Muhammad
Formato: Artículo
Publicado: Sage Publications Inc. 4/4/2022
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Modelling of South African Hypertension: Comparative Analysis of the Classical and Bayesian Quantile Regression Approaches.
      aug:
        au:
          Kuhudzai, Anesu Gelfand
          Van Hal, Guido
          Van Dongen, Stefan
          Hoque, Muhammad
        affil:
          Department of Social Epidemiology and Healthy Policy, 26660 University of Antwerp, Belgium
          Statistical Consultation Services, University of Johannesburg, South Africa
          Department of Evolutionary Ecology and Biology, 26660 University of Antwerp, Belgium
      su:
        Hypertension risk factors
        Hypertension
        Confidence intervals
        Systolic blood pressure
        Age distribution
        Regression analysis
        Retrospective studies
        Race
        Risk assessment
        Comparative studies
        Sex distribution
        Descriptive statistics
        Exercise
        Mental depression
        Employment
        Time series analysis
        Statistical models
        Cluster analysis (Statistics)
        Statistical sampling
        Body mass index
        Smoking
        Data analysis software
        Algorithms
        South Africa
      sug:
        subj:
          South Africa
          Hypertension risk factors
          Hypertension
          Confidence intervals
          Systolic blood pressure
          Age distribution
          Regression analysis
          Retrospective studies
          Race
          Risk assessment
          Comparative studies
          Sex distribution
          Descriptive statistics
          Exercise
          Mental depression
          Employment
          Time series analysis
          Statistical models
          Cluster analysis (Statistics)
          Statistical sampling
          Body mass index
          Smoking
          Data analysis software
          Algorithms
      keyword:
        Bayesian quantile regression
        classical quantile regression
        confidence and credible intervals
        hypertension
      ab: Hypertension has become a major public health challenge and a crucial area of research due to its high prevalence across the world including the sub-Saharan Africa. No previous study in South Africa has investigated the impact of blood pressure risk factors on different specific conditional quantile functions of systolic and diastolic blood pressure using Bayesian quantile regression. Therefore, this study presents a comparative analysis of the classical and Bayesian inference techniques to quantile regression. Both classical and Bayesian inference techniques were demonstrated on a sample of secondary data obtained from South African National Income Dynamics Study (2017–2018). Age, BMI, gender male, cigarette consumption and exercises presented statistically significant associations with both SBP and DBP across all the upper quantiles (τ ∈ { 0.75 , 0.95 }) . The white noise phenomenon was observed on the diagnostic tests of convergence used in the study. Results suggested that the Bayesian approach to quantile regression reveals more precise estimates than the frequentist approach due to narrower width of the 95% credible intervals than the width of the 95% confidence intervals. It is therefore suggested that Bayesian approach to quantile regression modelling to be used to estimate hypertension.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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