PDF(Pubmed)
Abstract：
UNASSIGNED: As the health status of a population is influenced by a variety of health determinants, we sought to assess their impact on health outcomes, both at the global and regional levels.
UNASSIGNED: This ecological study encompassed all 194 member countries of the World Health Organization (WHO) from 2000 to 2018. We first identified all health determinants and then retrieved the related data from various global databases. We additionally considered three indicators - disability-adjusted life years (DALYs), years of life lost (YLL), and years lived with disability (YLD) - in evaluating health outcomes; we extracted their data from the Global Burden of Disease (GBD) 2019 study. We then applied econometric analyses using a multilevel mixed-effects linear regression model.
UNASSIGNED: The analysis using the DALY indicator showed that the variables of sexually transmitted infections, injuries prevalence, and urbanisation had the highest effect size or regression coefficients (β) for health outcomes. The variables of sexually transmitted infection (β = 0.75, P < 0.001) in the African region; drinking water (β = -0.60, P < 0.001), alcohol use (β = 0.20, P < 0.001), and drug use (β = 0.05, P = 0.036) in the Americas region; urbanisation (β = -0.34, P < 0.001) in the Eastern Mediterranean region; current health expenditure (β = -0.21, P < 0.001) in the Europe region; injuries (β = 0.65, P < 0.001), air pollution (β = 0.29, P < 0.001), and obesity (β = 0.92, P < 0.001) in the South-East Asia region; and gross domestic product (β = -0.25, P < 0.001), education (β = -0.90, P < 0.001), and smoking (β = 0.28, P < 0.001) in the Western Pacific region had the most significant role in explaining global health outcomes. Except for the drug use variable in regional findings, the role of other variables in explaining the YLL indicator was greater than that of the YLD indicator.
UNASSIGNED: To address global health disparities and optimise resource allocation, global and interregional policymakers should focus on determinants that had the highest β with health outcomes in each region compared to other regions. These determinants likely have a higher marginal health product, and investing in them is likely to be more cost-effective.
UNASSIGNED: This ecological study encompassed all 194 member countries of the World Health Organization (WHO) from 2000 to 2018. We first identified all health determinants and then retrieved the related data from various global databases. We additionally considered three indicators - disability-adjusted life years (DALYs), years of life lost (YLL), and years lived with disability (YLD) - in evaluating health outcomes; we extracted their data from the Global Burden of Disease (GBD) 2019 study. We then applied econometric analyses using a multilevel mixed-effects linear regression model.
UNASSIGNED: The analysis using the DALY indicator showed that the variables of sexually transmitted infections, injuries prevalence, and urbanisation had the highest effect size or regression coefficients (β) for health outcomes. The variables of sexually transmitted infection (β = 0.75, P < 0.001) in the African region; drinking water (β = -0.60, P < 0.001), alcohol use (β = 0.20, P < 0.001), and drug use (β = 0.05, P = 0.036) in the Americas region; urbanisation (β = -0.34, P < 0.001) in the Eastern Mediterranean region; current health expenditure (β = -0.21, P < 0.001) in the Europe region; injuries (β = 0.65, P < 0.001), air pollution (β = 0.29, P < 0.001), and obesity (β = 0.92, P < 0.001) in the South-East Asia region; and gross domestic product (β = -0.25, P < 0.001), education (β = -0.90, P < 0.001), and smoking (β = 0.28, P < 0.001) in the Western Pacific region had the most significant role in explaining global health outcomes. Except for the drug use variable in regional findings, the role of other variables in explaining the YLL indicator was greater than that of the YLD indicator.
UNASSIGNED: To address global health disparities and optimise resource allocation, global and interregional policymakers should focus on determinants that had the highest β with health outcomes in each region compared to other regions. These determinants likely have a higher marginal health product, and investing in them is likely to be more cost-effective.
摘要：
■由于人口的健康状况受到多种健康决定因素的影响，我们试图评估它们对健康结果的影响，在全球和区域层面。
■这项生态研究涵盖了2000年至2018年世界卫生组织（WHO）的所有194个成员国。我们首先确定了所有健康决定因素，然后从各种全球数据库中检索相关数据。我们还考虑了三个指标-残疾调整寿命年(DALYs)，多年的生命损失（YLL），和残疾年份（YLD）-评估健康结果;我们从全球疾病负担（GBD）2019研究中提取了他们的数据。然后，我们使用多级混合效应线性回归模型进行计量经济学分析。
■使用DALY指标的分析表明，性传播感染的变量，伤害患病率，城市化对健康结果的影响大小或回归系数(β)最高。非洲地区性传播感染的变量（β=0.75，P<0.001）；饮用水（β=-0.60，P<0.001），饮酒（β=0.20，P<0.001），美洲地区的药物使用（β=0.05，P=0.036）；东地中海地区的城市化（β=-0.34，P<0.001）；欧洲地区的当前卫生支出（β=-0.21，P<0.001）；伤害（β=0.65，P<0.001），空气污染(β=0.29，P<0.001)，东南亚地区的肥胖（β=0.92，P<0.001）；国内生产总值（β=-0.25，P<0.001），教育(β=-0.90，P<0.001)，西太平洋区域的吸烟（β=0.28，P<0.001）在解释全球健康结果方面发挥了最重要的作用。除了区域调查结果中的药物使用变量，其他变量在解释YLL指标中的作用大于YLD指标。
■为了解决全球卫生差距并优化资源分配，全球和区域间政策制定者应将重点放在与其他区域相比每个区域的健康结果β值最高的决定因素上.这些决定因素可能具有更高的边际健康产品，投资它们可能更具成本效益。
■这项生态研究涵盖了2000年至2018年世界卫生组织（WHO）的所有194个成员国。我们首先确定了所有健康决定因素，然后从各种全球数据库中检索相关数据。我们还考虑了三个指标-残疾调整寿命年(DALYs)，多年的生命损失（YLL），和残疾年份（YLD）-评估健康结果;我们从全球疾病负担（GBD）2019研究中提取了他们的数据。然后，我们使用多级混合效应线性回归模型进行计量经济学分析。
■使用DALY指标的分析表明，性传播感染的变量，伤害患病率，城市化对健康结果的影响大小或回归系数(β)最高。非洲地区性传播感染的变量（β=0.75，P<0.001）；饮用水（β=-0.60，P<0.001），饮酒（β=0.20，P<0.001），美洲地区的药物使用（β=0.05，P=0.036）；东地中海地区的城市化（β=-0.34，P<0.001）；欧洲地区的当前卫生支出（β=-0.21，P<0.001）；伤害（β=0.65，P<0.001），空气污染(β=0.29，P<0.001)，东南亚地区的肥胖（β=0.92，P<0.001）；国内生产总值（β=-0.25，P<0.001），教育(β=-0.90，P<0.001)，西太平洋区域的吸烟（β=0.28，P<0.001）在解释全球健康结果方面发挥了最重要的作用。除了区域调查结果中的药物使用变量，其他变量在解释YLL指标中的作用大于YLD指标。
■为了解决全球卫生差距并优化资源分配，全球和区域间政策制定者应将重点放在与其他区域相比每个区域的健康结果β值最高的决定因素上.这些决定因素可能具有更高的边际健康产品，投资它们可能更具成本效益。
