Association of Screenings for Hypertension, Diabetes, and High Cholesterol With All-Cause and Cardiovascular Mortality: Evidence From a Cohort Study

IF 2.7 3区 医学 Q2 PERIPHERAL VASCULAR DISEASE
Jiayue Zhang, Shuting Wang, Ying Huang, Wenxiao Zheng, Ying Xiao, Zuyao Yang
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Abstract

Screenings for hypertension, diabetes, and high cholesterol are widely conducted in routine clinical practice for cardiovascular disease (CVD) prevention. However, few studies have investigated whether these screenings could eventually lead to lower risks of hard outcomes such as mortality. This cohort study aimed to examine directly the association of screenings for hypertension, diabetes, and high cholesterol with all-cause and cardiovascular mortality and whether the association, if existent, varied with important characteristics. A nationally representative sample of 86 587 US adults without the three conditions and CVD at baseline were recruited. The history of screenings for the three conditions was elicited by a series of questions in the surveys. All-cause and cardiovascular mortality were ascertained by linkage to National Death Index records through December 31, 2019. The association of screenings with mortality was investigated by multivariable Cox regression analysis and expressed as hazard ratio (HR) with 95% confidence interval (CI), adjusting for major risk factors of CVD and mortality. The “1 screening,” “2 screenings,” “3 screenings,” and “any screening” (combining the above three) groups were compared with the “no screening” group separately. During a median follow-up of 51 months (4.3 years), 1783 participants died and 366 of them were attributed to CVD. After adjusting for all covariates, no statistically significant association was found between “any screening” and all-cause mortality (HR = 1.08, 95% CI 0.92–1.26) or cardiovascular mortality (HR = 1.06, 95% CI 0.76–1.47). The results were consistent across various subgroups. The associations of “1 screening,” “2 screenings,” and “3 screenings” respectively with all-cause and cardiovascular mortality were not statistically significant either (HRs ranging from 0.65 to 1.40). Overall, in this population of US general adults, there was no evidence that screening for hypertension, diabetes, and high cholesterol could lead to lower all-cause or cardiovascular mortality.

Abstract Image

高血压、糖尿病和高胆固醇筛查与全因死亡率和心血管死亡率的关系:来自队列研究的证据
高血压、糖尿病和高胆固醇筛查在心血管疾病(CVD)预防的常规临床实践中广泛进行。然而,很少有研究调查这些筛查是否最终会降低硬性结果(如死亡率)的风险。本队列研究旨在直接研究高血压、糖尿病和高胆固醇筛查与全因死亡率和心血管死亡率之间的关系,以及如果存在这种关系,这种关系是否因重要特征而异。招募了一个具有全国代表性的86587名美国成年人,他们在基线时没有这三种情况和心血管疾病。这三种情况的筛查历史是由调查中的一系列问题引出的。通过与截至2019年12月31日的国家死亡指数记录的联系,确定了全因死亡率和心血管死亡率。通过多变量Cox回归分析研究筛查与死亡率的关系,并表示为95%置信区间(CI)的风险比(HR),调整了心血管疾病和死亡率的主要危险因素。将“1次筛查”、“2次筛查”、“3次筛查”和“任意筛查”(以上三种组合)组分别与“未筛查”组进行比较。在平均51个月(4.3年)的随访期间,1783名参与者死亡,其中366人死于心血管疾病。在对所有协变量进行调整后,“任何筛查”与全因死亡率(HR = 1.08, 95% CI 0.92-1.26)或心血管死亡率(HR = 1.06, 95% CI 0.76-1.47)之间没有统计学上显著的关联。结果在不同的亚组中是一致的。“1次筛查”、“2次筛查”和“3次筛查”与全因死亡率和心血管死亡率的相关性也无统计学意义(hr为0.65 ~ 1.40)。总的来说,在美国普通成年人人群中,没有证据表明高血压、糖尿病和高胆固醇筛查可以降低全因死亡率或心血管死亡率。
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来源期刊
Journal of Clinical Hypertension
Journal of Clinical Hypertension PERIPHERAL VASCULAR DISEASE-
CiteScore
5.80
自引率
7.10%
发文量
191
审稿时长
4-8 weeks
期刊介绍: The Journal of Clinical Hypertension is a peer-reviewed, monthly publication that serves internists, cardiologists, nephrologists, endocrinologists, hypertension specialists, primary care practitioners, pharmacists and all professionals interested in hypertension by providing objective, up-to-date information and practical recommendations on the full range of clinical aspects of hypertension. Commentaries and columns by experts in the field provide further insights into our original research articles as well as on major articles published elsewhere. Major guidelines for the management of hypertension are also an important feature of the Journal. Through its partnership with the World Hypertension League, JCH will include a new focus on hypertension and public health, including major policy issues, that features research and reviews related to disease characteristics and management at the population level.
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