The Australian National University, Canberra, ACT, Australia.
Bahir Dar University, Bahir Dar, Ethiopia.
J Prim Care Community Health. 2024 Jan-Dec;15:21501319241288312. doi: 10.1177/21501319241288312.
Cardiovascular disease (CVD) varies across regions due to socioeconomic, cultural, lifestyle, healthcare access, and environmental factors.
To find geographical variations in 10-year primary CVD risk and assess the impact of contextual factors on CVD risk.
Data from 2658 Ethiopians aged 40 to 69 years with no previous CVD who participated in a nationally representative World Health Organization (WHO) STEPS survey in 2015 were included in the analysis. The mean 10-year CVD risk for 450 enumeration areas (EA) was used to identify spatial autocorrelation (using Global Moran's ) and CVD hot spots (using getas-Ord Gi*). Geographically Weighted Regression (GWR) analysis quantified the relationship between mean 10-year CVD risk and climate-related factors across areas.
The spatial autocorrelation analysis identified significant spatial variation in the 10-year CVD risk at the EA level, with a global Moran's value of 0.016. Statistically significant hot spot areas with 10-year CVD risk were identified in Addis Ababa (the capital), Benishangul Gumuz, SNNPR (Southern Nations, Nationalities, and Peoples' Region), Amhara, Afar, Oromia, and Hareri regions. In a multivariable GWR analysis, average water vapor pressure was a statistically significant explanatory variable for the geographical variations in 10-year CVD risk.
Hot spot areas for 10-year CVD risk were identified across numerous country regions rather than concentrated in a specific region. Alongside these hot spot areas, regions with a higher annual water vapor pressure (humidity) were identified as geographical targets for CVD prevention.
心血管疾病（CVD）因社会经济、文化、生活方式、医疗保健可及性和环境因素在不同地区存在差异。
寻找 10 年主要 CVD 风险的地域差异，并评估背景因素对 CVD 风险的影响。
纳入了 2015 年参加世界卫生组织（WHO）STEP 调查的 2658 名年龄在 40 至 69 岁之间、无既往 CVD 的埃塞俄比亚人的数据。使用 450 个普查区（EA）的平均 10 年 CVD 风险来识别空间自相关（使用全局 Moran's ）和 CVD 热点（使用 getas-Ord Gi*）。地理加权回归（GWR）分析量化了各地区平均 10 年 CVD 风险与气候相关因素之间的关系。
空间自相关分析发现，EA 水平上的 10 年 CVD 风险存在显著的空间变异，全局 Moran's 值为 0.016。在首都亚的斯亚贝巴、本尚古勒-古马兹、南方各族州、阿姆哈拉、阿法尔、奥罗米亚和哈拉里地区确定了具有统计学意义的 10 年 CVD 风险热点地区。在多变量 GWR 分析中，平均水汽压是 10 年 CVD 风险地理变异的一个统计学上显著的解释变量。
确定了许多国家地区的 10 年 CVD 风险热点地区，而不是集中在一个特定的地区。除了这些热点地区外，还确定了年水汽压（湿度）较高的地区为 CVD 预防的地理目标。
