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Distribution of wealth quintiles and risk factors of non-communicable diseases in Ghana: evidence from the Ghana demographic and health survey 2014 using concentration curves model

INTRODUCTION: in recent times, the assertion of non-communicable diseases afflicting the rich has been demystified but cuts across the rich and the poor. Individuals in all categories of wealth quintiles are affected by the risk factors of non-communicable diseases such as alcohol consumption, tobac...

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Autor principal: Kwasi, Brenyah Joseph
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The African Field Epidemiology Network 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8856973/
https://www.ncbi.nlm.nih.gov/pubmed/35251456
http://dx.doi.org/10.11604/pamj.2021.40.262.31579
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author Kwasi, Brenyah Joseph
author_facet Kwasi, Brenyah Joseph
author_sort Kwasi, Brenyah Joseph
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description INTRODUCTION: in recent times, the assertion of non-communicable diseases afflicting the rich has been demystified but cuts across the rich and the poor. Individuals in all categories of wealth quintiles are affected by the risk factors of non-communicable diseases such as alcohol consumption, tobacco use, unhealthy dietary practices and physical inactivity. However, information on the distribution of these risk factors across different socio-economic status is scanty. This study assessed the distribution of wealth quintiles and the risk factors of non-communicable diseases, using the concentration curve model. METHODS: it was a quantitative study with analytical design using the Ghana Demographic and Health Survey (GDHS), 2014 data. The variables of interest were income status of respondents and risk factors of non-communicable diseases. In the analysis, income levels were categorized into wealth quintiles with assigned percentages (25%, 50%, 75% and 100%) denoting poor, rich, richer and richest respectively. The risk factors of non-communicable diseases were also categorized and assigned percentages (relatively exposed 25%, exposed 50%, more exposed 75% and most exposed 100%). A concentration table was employed to assess the risk factors of non-communicable diseases labelled X-axis and wealth quintiles labelled Y-axis. The cumulative percentage of the wealth quintiles (Y-axis) were plotted against the cumulative percentage of the risk factors of non-communicable diseases on the X-axis. RESULTS: the study found moderate concentration of alcohol consumption among the middle to upper wealth quintiles (richest). Again, the study revealed that, wealth quintiles are practically indifferent to tobacco use and that both the rich and poor equally and minimally use tobacco as the concentration curve is very close to the perfect line of equality (45°). This study found near equal distribution of unhealthy dietary practices among the rich and poor in Ghana. It was found that, 40% - 80% of rich people were physically inactive with the application of a physical activity level of 100%. It was noticed that, 40% of the rich people only performed 20% of physical activities. CONCLUSION: the study concludes that; wealth quintiles have implications for the risk factors of non-communicable diseases.
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spelling pubmed-88569732022-03-04 Distribution of wealth quintiles and risk factors of non-communicable diseases in Ghana: evidence from the Ghana demographic and health survey 2014 using concentration curves model Kwasi, Brenyah Joseph Pan Afr Med J Research INTRODUCTION: in recent times, the assertion of non-communicable diseases afflicting the rich has been demystified but cuts across the rich and the poor. Individuals in all categories of wealth quintiles are affected by the risk factors of non-communicable diseases such as alcohol consumption, tobacco use, unhealthy dietary practices and physical inactivity. However, information on the distribution of these risk factors across different socio-economic status is scanty. This study assessed the distribution of wealth quintiles and the risk factors of non-communicable diseases, using the concentration curve model. METHODS: it was a quantitative study with analytical design using the Ghana Demographic and Health Survey (GDHS), 2014 data. The variables of interest were income status of respondents and risk factors of non-communicable diseases. In the analysis, income levels were categorized into wealth quintiles with assigned percentages (25%, 50%, 75% and 100%) denoting poor, rich, richer and richest respectively. The risk factors of non-communicable diseases were also categorized and assigned percentages (relatively exposed 25%, exposed 50%, more exposed 75% and most exposed 100%). A concentration table was employed to assess the risk factors of non-communicable diseases labelled X-axis and wealth quintiles labelled Y-axis. The cumulative percentage of the wealth quintiles (Y-axis) were plotted against the cumulative percentage of the risk factors of non-communicable diseases on the X-axis. RESULTS: the study found moderate concentration of alcohol consumption among the middle to upper wealth quintiles (richest). Again, the study revealed that, wealth quintiles are practically indifferent to tobacco use and that both the rich and poor equally and minimally use tobacco as the concentration curve is very close to the perfect line of equality (45°). This study found near equal distribution of unhealthy dietary practices among the rich and poor in Ghana. It was found that, 40% - 80% of rich people were physically inactive with the application of a physical activity level of 100%. It was noticed that, 40% of the rich people only performed 20% of physical activities. CONCLUSION: the study concludes that; wealth quintiles have implications for the risk factors of non-communicable diseases. The African Field Epidemiology Network 2021-12-23 /pmc/articles/PMC8856973/ /pubmed/35251456 http://dx.doi.org/10.11604/pamj.2021.40.262.31579 Text en Copyright: Brenyah Joseph Kwasi et al. https://creativecommons.org/licenses/by/4.0/The Pan African Medical Journal (ISSN: 1937-8688). This is an Open Access article distributed under the terms of the Creative Commons Attribution International 4.0 License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Kwasi, Brenyah Joseph
Distribution of wealth quintiles and risk factors of non-communicable diseases in Ghana: evidence from the Ghana demographic and health survey 2014 using concentration curves model
title Distribution of wealth quintiles and risk factors of non-communicable diseases in Ghana: evidence from the Ghana demographic and health survey 2014 using concentration curves model
title_full Distribution of wealth quintiles and risk factors of non-communicable diseases in Ghana: evidence from the Ghana demographic and health survey 2014 using concentration curves model
title_fullStr Distribution of wealth quintiles and risk factors of non-communicable diseases in Ghana: evidence from the Ghana demographic and health survey 2014 using concentration curves model
title_full_unstemmed Distribution of wealth quintiles and risk factors of non-communicable diseases in Ghana: evidence from the Ghana demographic and health survey 2014 using concentration curves model
title_short Distribution of wealth quintiles and risk factors of non-communicable diseases in Ghana: evidence from the Ghana demographic and health survey 2014 using concentration curves model
title_sort distribution of wealth quintiles and risk factors of non-communicable diseases in ghana: evidence from the ghana demographic and health survey 2014 using concentration curves model
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8856973/
https://www.ncbi.nlm.nih.gov/pubmed/35251456
http://dx.doi.org/10.11604/pamj.2021.40.262.31579
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