Muchiri E Wandai1, Shane A Norris2, Jens Aagaard-Hansen3, Samuel O Manda4. 1. MRC Developmental Pathways for Health Research Unit (DPHRU), Department of Paediatrics, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa. Email: muchiriwandai@gmail.com. 2. MRC Developmental Pathways for Health Research Unit (DPHRU), Department of Paediatrics, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa. 3. MRC Developmental Pathways for Health Research Unit (DPHRU), Department of Paediatrics, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; Health Promotion, Steno Diabetes Centre, Copenhagen, Gentofte, Denmark. 4. Department of Statistics, University of Pretoria, Pretoria, South Africa.
Abstract
BACKGROUND: As a response to the growing burden of non-communicable diseases, the South African government has set targets to reduce the prevalence of people with raised blood pressure, through lifestyle changes and medication, by 20% by the year 2020. It has also recognised that the prevalence varies at local administrative level. The study aim was to determine the geographical variation by district of the prevalence of hypertension among South African adults aged 15 years and above. METHODS: Data from all five waves of the National income Dynamics Study, a panel survey, were used for estimation by both design-based and multilevel analysis methods. In the multilevel analysis, a three-level hierarchy was used with panel participants in the first level, repeated measurements on patients in the second level, and districts in the third level. RESULTS: After accounting for demographic, behavioural, socio-economic and environmental factors, significant variation remained in the prevalence of hypertension at the district level. Districts with higher-than-average prevalence were found mostly in the south-western part of the country, while those with a prevalence below average were found in the northern area. Age, body mass index and race were the individual factors found to have a strong effect on hypertension prevalence for this sample. CONCLUSIONS: There were significant differences in hypertension prevalence between districts and therefore the method of analysis and the results could be useful for more targeted preventative and control programmes.
BACKGROUND: As a response to the growing burden of non-communicable diseases, the South African government has set targets to reduce the prevalence of people with raised blood pressure, through lifestyle changes and medication, by 20% by the year 2020. It has also recognised that the prevalence varies at local administrative level. The study aim was to determine the geographical variation by district of the prevalence of hypertension among South African adults aged 15 years and above. METHODS: Data from all five waves of the National income Dynamics Study, a panel survey, were used for estimation by both design-based and multilevel analysis methods. In the multilevel analysis, a three-level hierarchy was used with panel participants in the first level, repeated measurements on patients in the second level, and districts in the third level. RESULTS: After accounting for demographic, behavioural, socio-economic and environmental factors, significant variation remained in the prevalence of hypertension at the district level. Districts with higher-than-average prevalence were found mostly in the south-western part of the country, while those with a prevalence below average were found in the northern area. Age, body mass index and race were the individual factors found to have a strong effect on hypertension prevalence for this sample. CONCLUSIONS: There were significant differences in hypertension prevalence between districts and therefore the method of analysis and the results could be useful for more targeted preventative and control programmes.
Entities:
Keywords:
district variability; hypertension prevalence; multilevel analysis; random effects
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