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Prioritization of intervention domains to prevent cardiovascular disease: a country-level case study using global burden of disease and local data

AIM: We aimed to combine Global Burden of Disease (GBD) Study data and local data to identify the highest priority intervention domains for preventing cardiovascular disease (CVD) in the case study country of Aotearoa New Zealand (NZ). METHODS: Risk factor data for CVD in NZ were extracted from the...

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Autores principales: Wilson, Nick, Cleghorn, Christine, Nghiem, Nhung, Blakely, Tony
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9878487/
https://www.ncbi.nlm.nih.gov/pubmed/36703150
http://dx.doi.org/10.1186/s12963-023-00301-1
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author Wilson, Nick
Cleghorn, Christine
Nghiem, Nhung
Blakely, Tony
author_facet Wilson, Nick
Cleghorn, Christine
Nghiem, Nhung
Blakely, Tony
author_sort Wilson, Nick
collection PubMed
description AIM: We aimed to combine Global Burden of Disease (GBD) Study data and local data to identify the highest priority intervention domains for preventing cardiovascular disease (CVD) in the case study country of Aotearoa New Zealand (NZ). METHODS: Risk factor data for CVD in NZ were extracted from the GBD using the “GBD Results Tool.” We prioritized risk factor domains based on consideration of the size of the health burden (disability-adjusted life years [DALYs]) and then by the domain-specific interventions that delivered the highest health gains and cost-savings. RESULTS: Based on the size of the CVD health burden in DALYs, the five top prioritized risk factor domains were: high systolic blood pressure (84,800 DALYs; 5400 deaths in 2019), then dietary risk factors, then high LDL cholesterol, then high BMI and then tobacco (30,400 DALYs; 1400 deaths). But if policy-makers aimed to maximize health gain and cost-savings from specific interventions that have been studied, then they would favor the dietary risk domain (e.g., a combined fruit and vegetable subsidy plus a sugar tax produced estimated lifetime savings of 894,000 health-adjusted life years and health system cost-savings of US$11.0 billion; both 3% discount rate). Other potential considerations for prioritization included the potential for total health gain that includes non-CVD health loss and potential for achieving relatively greater per capita health gain for Māori (Indigenous) to reduce health inequities. CONCLUSIONS: We were able to show how CVD risk factor domains could be systematically prioritized using a mix of GBD and country-level data. Addressing high systolic blood pressure would be the top ranked domain if policy-makers focused just on the size of the health loss. But if policy-makers wished to maximize health gain and cost-savings using evaluated interventions, dietary interventions would be prioritized, e.g., food taxes and subsidies.
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spelling pubmed-98784872023-01-26 Prioritization of intervention domains to prevent cardiovascular disease: a country-level case study using global burden of disease and local data Wilson, Nick Cleghorn, Christine Nghiem, Nhung Blakely, Tony Popul Health Metr Research AIM: We aimed to combine Global Burden of Disease (GBD) Study data and local data to identify the highest priority intervention domains for preventing cardiovascular disease (CVD) in the case study country of Aotearoa New Zealand (NZ). METHODS: Risk factor data for CVD in NZ were extracted from the GBD using the “GBD Results Tool.” We prioritized risk factor domains based on consideration of the size of the health burden (disability-adjusted life years [DALYs]) and then by the domain-specific interventions that delivered the highest health gains and cost-savings. RESULTS: Based on the size of the CVD health burden in DALYs, the five top prioritized risk factor domains were: high systolic blood pressure (84,800 DALYs; 5400 deaths in 2019), then dietary risk factors, then high LDL cholesterol, then high BMI and then tobacco (30,400 DALYs; 1400 deaths). But if policy-makers aimed to maximize health gain and cost-savings from specific interventions that have been studied, then they would favor the dietary risk domain (e.g., a combined fruit and vegetable subsidy plus a sugar tax produced estimated lifetime savings of 894,000 health-adjusted life years and health system cost-savings of US$11.0 billion; both 3% discount rate). Other potential considerations for prioritization included the potential for total health gain that includes non-CVD health loss and potential for achieving relatively greater per capita health gain for Māori (Indigenous) to reduce health inequities. CONCLUSIONS: We were able to show how CVD risk factor domains could be systematically prioritized using a mix of GBD and country-level data. Addressing high systolic blood pressure would be the top ranked domain if policy-makers focused just on the size of the health loss. But if policy-makers wished to maximize health gain and cost-savings using evaluated interventions, dietary interventions would be prioritized, e.g., food taxes and subsidies. BioMed Central 2023-01-26 /pmc/articles/PMC9878487/ /pubmed/36703150 http://dx.doi.org/10.1186/s12963-023-00301-1 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
Wilson, Nick
Cleghorn, Christine
Nghiem, Nhung
Blakely, Tony
Prioritization of intervention domains to prevent cardiovascular disease: a country-level case study using global burden of disease and local data
title Prioritization of intervention domains to prevent cardiovascular disease: a country-level case study using global burden of disease and local data
title_full Prioritization of intervention domains to prevent cardiovascular disease: a country-level case study using global burden of disease and local data
title_fullStr Prioritization of intervention domains to prevent cardiovascular disease: a country-level case study using global burden of disease and local data
title_full_unstemmed Prioritization of intervention domains to prevent cardiovascular disease: a country-level case study using global burden of disease and local data
title_short Prioritization of intervention domains to prevent cardiovascular disease: a country-level case study using global burden of disease and local data
title_sort prioritization of intervention domains to prevent cardiovascular disease: a country-level case study using global burden of disease and local data
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9878487/
https://www.ncbi.nlm.nih.gov/pubmed/36703150
http://dx.doi.org/10.1186/s12963-023-00301-1
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