Department of Medicine, Division of General Internal Medicine, Medical College of Wisconsin, Milwaukee, WI 53226, USA; Center for Advancing Population Science, Medical College of Wisconsin, Milwaukee, WI 53226, USA.
College of Health Professions, Medical University of South Carolina, Charleston, SC 29425, USA.
J Natl Med Assoc. 2020 Apr;112(2):186-197. doi: 10.1016/j.jnma.2020.02.004. Epub 2020 Mar 11.
Hypertension is responsible for about 12.8% of deaths around the world. Immigrants' risk of developing hypertension increases with length of residency. There is limited work on the role of social determinants of health and blood pressure control in immigrants. We created a theory-based conceptual model for immigrant-specific and general social determinants variables and their relationship to blood pressure.
Use a theory-based model to identify latent variables for immigrant-specific social determinants using confirmatory factor analysis (CFA) and structural equation modeling (SEM) to test theoretical validity and relationship with blood pressure (BP).
CFA was used to identify latent variables for global socioeconomic status, stressors of immigration, adaptation to immigration, acculturation, and burden of disease. SEM was used to test the structural relationships between latent variables and BP.
181 immigrants were included in the analysis. The final model (chi2 (68, n = 181) = 149.87, p < 0.001, RMSEA = 0.055, CFI = 0.94, TLI = 0.91, CD = 0.99) found burden of disease was significantly related to BP (r = 0.35, p < 0.001).
One latent variable measuring need was significantly associated with BP in an immigrant sample. This suggests that interventions targeting burden of disease are likely to be effective in controlling blood pressure in immigrants.
高血压在全球范围内导致约 12.8%的死亡。移民患高血压的风险随着居住时间的延长而增加。关于健康社会决定因素和血压控制在移民中的作用的研究有限。我们创建了一个基于理论的概念模型，用于确定移民特定和一般社会决定因素变量及其与血压的关系。
使用基于理论的模型，通过验证性因子分析（CFA）和结构方程建模（SEM）来确定移民特定社会决定因素的潜在变量，以检验理论有效性及其与血压（BP）的关系。
CFA 用于确定全球社会经济地位、移民压力源、移民适应、文化适应和疾病负担的潜在变量。SEM 用于测试潜在变量与 BP 之间的结构关系。
共纳入 181 名移民进行分析。最终模型（卡方（68，n=181）=149.87，p<0.001，RMSEA=0.055，CFI=0.94，TLI=0.91，CD=0.99）发现疾病负担与 BP 显著相关（r=0.35，p<0.001）。
在移民样本中，一个衡量负担的潜在变量与 BP 显著相关。这表明针对疾病负担的干预措施可能有助于控制移民的血压。
