Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, 510080, China.
Department of Respiratory and Critical Care Medicine, The First People's Hospital of Kashi (The Affiliated Kashi Hospital of Sun Yat-Sen University), No.66, Yingbin Avenue, Kashgar City, 844000, China.
Glob Health Res Policy. 2022 Dec 6;7(1):48. doi: 10.1186/s41256-022-00282-y.
Identifying factors associated with cardiovascular disease (CVD) is critical for its prevention, but this topic is scarcely investigated in Kashgar prefecture, Xinjiang, northwestern China. We thus explored the CVD epidemiology and identified prominent factors associated with CVD in this region.
A total of 1,887,710 adults at baseline (in 2017) of the Kashgar Prospective Cohort Study were included in the analysis. Sixteen candidate factors, including seven demographic factors, 4 lifestyle factors, and 5 clinical factors, were collected from a questionnaire and health examination records. CVD was defined according to International Clinical Diagnosis (ICD-10) codes. We first used logistic regression models to investigate the association between each of the candidate factors and CVD. Then, we employed 3 machine learning methods-Random Forest, Random Ferns, and Extreme Gradient Boosting-to rank and identify prominent factors associated with CVD. Stratification analyses by sex, ethnicity, education level, economic status, and residential setting were also performed to test the consistency of the ranking.
The prevalence of CVD in Kashgar prefecture was 8.1%. All the 16 candidate factors were confirmed to be significantly associated with CVD (odds ratios ranged from 1.03 to 2.99, all p values < 0.05) in logistic regression models. Further machine learning-based analysis suggested that age, occupation, hypertension, exercise frequency, and dietary pattern were the five most prominent factors associated with CVD. The ranking of relative importance for prominent factors in stratification analyses showed that the factor importance generally followed the same pattern as that in the overall sample.
CVD is a major public health concern in Kashgar prefecture. Age, occupation, hypertension, exercise frequency, and dietary pattern might be the prominent factors associated with CVD in this region.In the future, these factors should be given priority in preventing CVD in future.
识别与心血管疾病（CVD）相关的因素对于预防 CVD 至关重要，但在中国西北部的新疆喀什地区，这一主题的研究甚少。因此，我们探讨了该地区 CVD 的流行病学，并确定了与 CVD 相关的显著因素。
我们纳入了喀什前瞻性队列研究的 1887710 名成年人（基线时为 2017 年）进行分析。从问卷和健康检查记录中收集了 16 个候选因素，包括 7 个人口统计学因素、4 个生活方式因素和 5 个临床因素。CVD 根据国际临床诊断（ICD-10）代码定义。我们首先使用逻辑回归模型调查每个候选因素与 CVD 的关联。然后，我们使用 3 种机器学习方法（随机森林、随机蕨类和极端梯度提升）对与 CVD 相关的显著因素进行排名和识别。还进行了性别、民族、教育水平、经济状况和居住环境的分层分析，以检验排名的一致性。
喀什地区 CVD 的患病率为 8.1%。在逻辑回归模型中，所有 16 个候选因素均被证实与 CVD 显著相关（比值比范围为 1.03 至 2.99，均 p 值<0.05）。进一步的基于机器学习的分析表明，年龄、职业、高血压、运动频率和饮食模式是与 CVD 最相关的五个显著因素。分层分析中显著因素的重要性排名表明，因素的重要性通常与总体样本中的模式相同。
CVD 是喀什地区的一个主要公共卫生问题。年龄、职业、高血压、运动频率和饮食模式可能是该地区与 CVD 相关的显著因素。在未来，这些因素应该在预防未来 CVD 中优先考虑。
