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Risk factor contributions to socioeconomic inequality in cardiovascular risk in the Philippines: a cross-sectional study of nationally representative survey data

BACKGROUND: Primary prevention of cardiovascular diseases (CVD) increasingly relies on monitoring global CVD risk scores. Lack of evidence on socioeconomic inequality in these scores and the contributions that specific risk factors make to this inequality impedes effective targeting of CVD preventio...

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Autores principales: Brindley, Callum, Van Ourti, Tom, Capuno, Joseph, Kraft, Aleli, Kudymowa, Jenny, O’Donnell, Owen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10092926/
https://www.ncbi.nlm.nih.gov/pubmed/37046247
http://dx.doi.org/10.1186/s12889-023-15517-x
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author Brindley, Callum
Van Ourti, Tom
Capuno, Joseph
Kraft, Aleli
Kudymowa, Jenny
O’Donnell, Owen
author_facet Brindley, Callum
Van Ourti, Tom
Capuno, Joseph
Kraft, Aleli
Kudymowa, Jenny
O’Donnell, Owen
author_sort Brindley, Callum
collection PubMed
description BACKGROUND: Primary prevention of cardiovascular diseases (CVD) increasingly relies on monitoring global CVD risk scores. Lack of evidence on socioeconomic inequality in these scores and the contributions that specific risk factors make to this inequality impedes effective targeting of CVD prevention. We aimed to address this evidence gap by measuring and decomposing socioeconomic inequality in CVD risk in the Philippines. METHODS: We used data on 8462 individuals aged 40–74 years from the Philippines National Nutrition Survey and the laboratory-based Globorisk equation to predict 10-year risk of a CVD event from sex, age, systolic blood pressure, total cholesterol, high blood glucose, and smoking. We used a household wealth index to proxy socioeconomic status and measured socioeconomic inequality with a concentration index that we decomposed into contributions of the risk factors used to predict CVD risk. We measured socioeconomic inequalities in these risk factors and decomposed them into contributions of more distal risk factors: body mass index, fat share of energy intake, low physical activity, and drinking alcohol. We stratified by sex. RESULTS: Wealthier individuals, particularly males, had greater exposure to all risk factors, with the exception of smoking, and had higher CVD risks. Total cholesterol and high blood glucose accounted for 58% and 34%, respectively, of the socioeconomic inequality in CVD risk among males. For females, the respective estimates were 63% and 69%. Systolic blood pressure accounted for 26% of the higher CVD risk of wealthier males but did not contribute to inequality among females. If smoking prevalence had not been higher among poorer individuals, then the inequality in CVD risk would have been 35% higher for males and 75% higher for females. Among distal risk factors, body mass index and fat intake contributed most to inequalities in total cholesterol, high blood sugar, and, for males, systolic blood pressure. CONCLUSIONS: Wealthier Filipinos have higher predicted CVD risks and greater exposure to all risk factors, except smoking. There is need for a nuanced approach to CVD prevention that targets anti-smoking programmes on the poorer population while targeting diet and exercise interventions on the wealthier. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-15517-x.
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spelling pubmed-100929262023-04-14 Risk factor contributions to socioeconomic inequality in cardiovascular risk in the Philippines: a cross-sectional study of nationally representative survey data Brindley, Callum Van Ourti, Tom Capuno, Joseph Kraft, Aleli Kudymowa, Jenny O’Donnell, Owen BMC Public Health Research BACKGROUND: Primary prevention of cardiovascular diseases (CVD) increasingly relies on monitoring global CVD risk scores. Lack of evidence on socioeconomic inequality in these scores and the contributions that specific risk factors make to this inequality impedes effective targeting of CVD prevention. We aimed to address this evidence gap by measuring and decomposing socioeconomic inequality in CVD risk in the Philippines. METHODS: We used data on 8462 individuals aged 40–74 years from the Philippines National Nutrition Survey and the laboratory-based Globorisk equation to predict 10-year risk of a CVD event from sex, age, systolic blood pressure, total cholesterol, high blood glucose, and smoking. We used a household wealth index to proxy socioeconomic status and measured socioeconomic inequality with a concentration index that we decomposed into contributions of the risk factors used to predict CVD risk. We measured socioeconomic inequalities in these risk factors and decomposed them into contributions of more distal risk factors: body mass index, fat share of energy intake, low physical activity, and drinking alcohol. We stratified by sex. RESULTS: Wealthier individuals, particularly males, had greater exposure to all risk factors, with the exception of smoking, and had higher CVD risks. Total cholesterol and high blood glucose accounted for 58% and 34%, respectively, of the socioeconomic inequality in CVD risk among males. For females, the respective estimates were 63% and 69%. Systolic blood pressure accounted for 26% of the higher CVD risk of wealthier males but did not contribute to inequality among females. If smoking prevalence had not been higher among poorer individuals, then the inequality in CVD risk would have been 35% higher for males and 75% higher for females. Among distal risk factors, body mass index and fat intake contributed most to inequalities in total cholesterol, high blood sugar, and, for males, systolic blood pressure. CONCLUSIONS: Wealthier Filipinos have higher predicted CVD risks and greater exposure to all risk factors, except smoking. There is need for a nuanced approach to CVD prevention that targets anti-smoking programmes on the poorer population while targeting diet and exercise interventions on the wealthier. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-15517-x. BioMed Central 2023-04-12 /pmc/articles/PMC10092926/ /pubmed/37046247 http://dx.doi.org/10.1186/s12889-023-15517-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Brindley, Callum
Van Ourti, Tom
Capuno, Joseph
Kraft, Aleli
Kudymowa, Jenny
O’Donnell, Owen
Risk factor contributions to socioeconomic inequality in cardiovascular risk in the Philippines: a cross-sectional study of nationally representative survey data
title Risk factor contributions to socioeconomic inequality in cardiovascular risk in the Philippines: a cross-sectional study of nationally representative survey data
title_full Risk factor contributions to socioeconomic inequality in cardiovascular risk in the Philippines: a cross-sectional study of nationally representative survey data
title_fullStr Risk factor contributions to socioeconomic inequality in cardiovascular risk in the Philippines: a cross-sectional study of nationally representative survey data
title_full_unstemmed Risk factor contributions to socioeconomic inequality in cardiovascular risk in the Philippines: a cross-sectional study of nationally representative survey data
title_short Risk factor contributions to socioeconomic inequality in cardiovascular risk in the Philippines: a cross-sectional study of nationally representative survey data
title_sort risk factor contributions to socioeconomic inequality in cardiovascular risk in the philippines: a cross-sectional study of nationally representative survey data
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10092926/
https://www.ncbi.nlm.nih.gov/pubmed/37046247
http://dx.doi.org/10.1186/s12889-023-15517-x
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