Modelling of South African Hypertension: Application of Classical Quantile Regression
DOI:
https://doi.org/10.3329/bjms.v21i4.60238Keywords:
Hierarchical Interactions; Group-lasso approach;Classical Quantile Regression; Hypertension; South AfricaAbstract
Background: High blood pressure, medically known as hypertension is the major risk factor for cardiovascular diseases (CVDs) and premature death globally. The aim of the present study was to explore possible interactions amongst systolic blood pressure`s (SBP) and diastolic blood pressure`s (DBP) risk factors in South Africa.
Methods:A retrospective study was conducted using data acquired from the South African National Income Dynamics Study Wave 5, Household Survey which was carried out in 2017-2018.A final data set of 21 180 adults was utilized for data analysis. An application of the hierarchical group-lasso approach to detect interactions between SBP`s and DBP`s risk factors and classical quantile regression analysis were performed in this study.
Results: By using only upper quantilesbody mass index (BMI), age, race, never exercised, and the following nine interactions: BMI and age, BMI and gender male, age and never exercised, gender male and race African, race coloured and depression some or little of the time, BMI and cigarette consumption, age and race white, gender male and employment status, never exercised and cigarette consumptionwere found to be significantdeterminantsof hypertension in South Africa.
Conclusion: The evidence of this study suggests that it is ideal to consider interactions amongst risk factors when modelling hypertension.
Bangladesh Journal of Medical Science Vol. 21 No. 04 October’22 Page : 772-781
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Copyright (c) 2022 Anesu Gelfand Kuhudzai, Guido Van Hal, Stefan Van Dongen, Muhammed Ehsanul Hoque
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