Abstract：
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).
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.
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.
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.
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.
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.
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.
摘要：
目的：我们旨在结合全球疾病负担（GBD）研究数据和当地数据，以确定在新西兰奥特亚罗（新西兰）的案例研究国家中预防心血管疾病（CVD）的最优先干预领域。
方法：使用“GBD结果工具”从GBD中提取NZ中CVD的危险因素数据。“我们根据对健康负担大小（残疾调整生命年[DALYs]）的考虑，然后通过特定领域的干预措施，实现了最高的健康收益和成本节约，对风险因素领域进行了优先排序。
结果：根据DALYs中CVD健康负担的大小，五个优先考虑的风险因素领域是：高收缩压(84,800DALYs；2019年5400例死亡)，然后是饮食风险因素，然后高低密度脂蛋白胆固醇，然后是高BMI，然后是烟草(30,400DALYs；1400例死亡)。但是，如果决策者旨在从已经研究的具体干预措施中最大限度地提高健康收益和节约成本，然后他们会倾向于饮食风险域(例如，水果和蔬菜补贴加上糖税的总和估计可节省894,000个健康调整后的生命年，并节省了110亿美元的卫生系统成本；两者均为3％的贴现率）。确定优先次序的其他潜在考虑因素包括总健康收益的潜力，包括非心血管疾病健康损失，以及毛利人(土著)实现相对更大的人均健康收益以减少健康不平等的潜力。
结论：我们能够展示如何使用GBD和国家/地区数据的混合对CVD风险因素领域进行系统的优先排序。如果政策制定者只关注健康损失的大小，那么解决高收缩压将是排名最高的领域。但是，如果决策者希望使用评估的干预措施来最大程度地提高健康收益和节省成本，饮食干预将被优先考虑，例如，食品税和补贴。
方法：使用“GBD结果工具”从GBD中提取NZ中CVD的危险因素数据。“我们根据对健康负担大小（残疾调整生命年[DALYs]）的考虑，然后通过特定领域的干预措施，实现了最高的健康收益和成本节约，对风险因素领域进行了优先排序。
结果：根据DALYs中CVD健康负担的大小，五个优先考虑的风险因素领域是：高收缩压(84,800DALYs；2019年5400例死亡)，然后是饮食风险因素，然后高低密度脂蛋白胆固醇，然后是高BMI，然后是烟草(30,400DALYs；1400例死亡)。但是，如果决策者旨在从已经研究的具体干预措施中最大限度地提高健康收益和节约成本，然后他们会倾向于饮食风险域(例如，水果和蔬菜补贴加上糖税的总和估计可节省894,000个健康调整后的生命年，并节省了110亿美元的卫生系统成本；两者均为3％的贴现率）。确定优先次序的其他潜在考虑因素包括总健康收益的潜力，包括非心血管疾病健康损失，以及毛利人(土著)实现相对更大的人均健康收益以减少健康不平等的潜力。
结论：我们能够展示如何使用GBD和国家/地区数据的混合对CVD风险因素领域进行系统的优先排序。如果政策制定者只关注健康损失的大小，那么解决高收缩压将是排名最高的领域。但是，如果决策者希望使用评估的干预措施来最大程度地提高健康收益和节省成本，饮食干预将被优先考虑，例如，食品税和补贴。
