中老年人群心血管代谢指数与全因死亡率和心血管死亡率的关系-动脉网

Association of cardiometabolic index with all-cause and cardiovascular mortality among middle-aged and elderly populations

Nature 等信源发布 2025-01-03 22:35



可切换为仅中文







Abstract

摘要

The Cardiometabolic Index (CMI) is a well-recognized risk factor for a range of cardiovascular diseases and diabetes mellitus. However, the population-level characteristics of CMI and its potential association with mortality risk among individuals over 40 years of age have not been investigated. This study aims to assess the association between CMI and both all-cause and cardiovascular mortality among the middle-aged and elderly population.

心脏代谢指数（CMI）是一系列心血管疾病和糖尿病的公认危险因素。然而，尚未调查CMI的人口水平特征及其与40岁以上个体死亡风险的潜在关联。本研究旨在评估中老年人群CMI与全因死亡率和心血管死亡率之间的关系。

This cohort study utilized data from 3752 American adults extracted from the Sleep Heart Health Study (SHHS) conducted from 1995 to 2011. The CMI was calculated using the waist-to-height ratio, triglycerides (TG), and high-density lipoprotein cholesterol (HDL-C). The primary outcomes were all-cause mortality and cardiovascular mortality, with mortality data sourced from the SHHS Linked Mortality File.

这项队列研究利用了从1995年至2011年进行的睡眠心脏健康研究（SHHS）中提取的3752名美国成年人的数据。使用腰高比，甘油三酯（TG）和高密度脂蛋白胆固醇（HDL-C）计算CMI。主要结果是全因死亡率和心血管死亡率，死亡率数据来自与SHHS相关的死亡率文件。

Kaplan-Meier survival curves and Cox regression models were employed to assess the prognostic value of the CMI. Among the 3752 American adults, the mean (SD) age was 65.9 (10.1) years, and 1969 (52.5%) were women. The mean (SD) CMI was 0.914 ± 0.939. Over an average follow-up period of 10.7 years, there were 926 all-cause deaths and 289 cardiovascular deaths.

采用Kaplan-Meier生存曲线和Cox回归模型评估CMI的预后价值。在3752名美国成年人中，平均（SD）年龄为65.9（10.1）岁，1969年（52.5%）为女性。平均（SD）CMI为0.914±0.939。平均随访10.7年，共有926例全因死亡和289例心血管死亡。

Participants were categorized into three groups based on their CMI levels: tertile (T) 1: 0.315 ± 0.0994; T2: 0.680 ± 0.128; T3: 1.75 ± 1.23. Multivariate Cox proportional hazards analysis showed that elevated CMI was significantly associated with all-cause mortality (HR 1.215, 95% CI 1.032–1.43 for T2; HR 1.309, 95% CI 1.115–1.537 for T3) and cardiovascular mortality (HR 1.305, 95% CI 0.971–1.755 for T2; HR 1.457, 95% CI 1.091–1.947 for T3).

参与者根据其CMI水平分为三组：三分位数（T）1：0.315±0.0994；T2：0.680±0.128；T3：1.75±1.23。多变量Cox比例风险分析显示，CMI升高与全因死亡率（T2为HR 1.215，95%CI 1.032-1.43；T3为HR 1.309，95%CI 1.115-1.537）和心血管死亡率（T2为HR 1.305，95%CI 0.971-1.755；T3为HR 1.457，95%CI 1.091-1.947）显着相关。

After adjusting for confounders, elevated CMI remained significantly associated with all-cause mortality (HR 1.315, 95% CI 1.098–1.575 for T3.

调整混杂因素后，CMI升高与全因死亡率显着相关（HR 1.315，T3的95%CI 1.098-1.575）。

= 0.0035) and cardiovascular mortality (log-rank

==0.0035）和心血管死亡率（对数秩

= 0.035). This national cohort study found that CMI is significantly associated with both all-cause and cardiovascular mortality among American adults aged over 40. These findings suggest that CMI could be a valuable tool for identifying high-risk individuals, thereby aiding in the implementation of targeted preventive strategies..

= 0.035）。这项全国队列研究发现，CMI与40岁以上美国成年人的全因死亡率和心血管死亡率显着相关。这些发现表明，CMI可能是识别高危人群的有价值的工具，从而有助于实施有针对性的预防策略。。

Introduction

导言

Cardiometabolic diseases (CMD), which include cardiovascular disease (CVD) and diabetes mellitus (DM), are among the predominant causes of morbidity and mortality worldwide in adults

心脏代谢疾病（CMD），包括心血管疾病（CVD）和糖尿病（DM），是全球成年人发病率和死亡率的主要原因之一

. These diseases account for approximately 15% of total healthcare expenditures, thereby exerting a substantial strain on healthcare resources

。这些疾病约占医疗保健总支出的15%，因此对医疗保健资源造成了巨大压力

. These burdens further exacerbate significant health disparities, disproportionately impacting lower-income, less educated, and minority racial and ethnic populations

这些负担进一步加剧了严重的健康差距，对低收入、受教育程度低以及少数民族和族裔人口产生了不成比例的影响

. Therefore, it is essential to identify modifiable risk factors for cardiometabolic diseases in the middle-aged and elderly population, which will promote the advancement of global public health initiatives and the development of comprehensive preventive strategies.

因此，必须确定中老年人群心脏代谢疾病的可改变风险因素，这将促进全球公共卫生举措的推进和综合预防策略的制定。

The cardiometabolic index (CMI), developed by Wakabayashi in 2015, is a metabolism-related measure designed to identify diabetes mellitus

Wakabayashi于2015年开发的心脏代谢指数（CMI）是一种与代谢相关的指标，旨在识别糖尿病

. It comprises three key components: the waist-to-height ratio (WHtR), triglyceride levels (TG), and high-density lipoprotein cholesterol (HDL-C). WHtR primarily measures the degree of obesity, while the TG/HDL-C ratio assesses blood lipid levels. This index provides a comprehensive evaluation of metabolic health, facilitating the discrimination of diabetes and related conditions.

。它包括三个关键组成部分：腰高比（WHtR），甘油三酯水平（TG）和高密度脂蛋白胆固醇（HDL-C）。WHtR主要测量肥胖程度，而TG/HDL-C比率评估血脂水平。该指数提供了代谢健康的综合评估，有助于区分糖尿病和相关疾病。

. Shi et al. illuminated the efficacy and economic advantage of the CMI through an extensive analysis involving 11,478 participants from Northeast China, which confirmed that the CMI serves as a robust tool for screening and quantifying diabetes within the Chinese population

Shi等人通过对来自东北地区的11478名参与者进行的广泛分析，阐明了CMI的功效和经济优势，这证实了CMI是筛查和量化中国人群糖尿病的有力工具

. Additionally, numerous studies have demonstrated the clinical value of the CMI across a range of metabolic-related diseases, including atherosclerosis

此外，许多研究已经证明了CMI在包括动脉粥样硬化在内的一系列代谢相关疾病中的临床价值

, hypertension

，高血压

, and ischemic stroke

和缺血性中风

. Recently, Xu et al. demonstrated positive associations between CMI and inflammation-related indicators, which are, in turn, positively correlated with both all-cause and cardiovascular mortality in adults aged over 65

最近，Xu等人证明CMI与炎症相关指标呈正相关，而炎症相关指标又与65岁以上成年人的全因死亡率和心血管死亡率呈正相关

. However, to date, no studies have directly assessed the prognostic value of the CMI in the middle-aged and elderly population with long-term follow-up.

然而，迄今为止，还没有研究直接评估CMI在长期随访的中老年人群中的预后价值。

Based on the current state of research, our study aimed to evaluate the role of the CMI in predicting all-cause and cardiovascular mortality over a long-term follow-up by analyzing data from the Sleep Heart Health Study (SHHS).

根据目前的研究状况，我们的研究旨在通过分析睡眠心脏健康研究（SHHS）的数据，评估CMI在预测长期随访中全因和心血管死亡率方面的作用。

Methods

方法

Study design and participants

研究设计和参与者

SHHS is a multi-center, prospective, community-based cohort study that enrolled 6441 participants aged 40 years and older between 1995 and 1998

SHHS是一项多中心，前瞻性，基于社区的队列研究，在1995年至1998年间招募了6441名40岁及以上的参与者

. Eligible participants, who had no history of sleep apnea treatment, no tracheostomy, and were not receiving home oxygen therapy, were recruited from nine existing epidemiological studies that had previously collected data on cardiovascular risk factors. The recruitment occurred at various sites, including the Framingham Offspring Cohort, ARIC study sites in Hagerstown and Minneapolis/St.

符合条件的参与者，没有睡眠呼吸暂停治疗史，没有气管切开术，也没有接受家庭氧疗，是从先前收集过心血管危险因素数据的九项现有流行病学研究中招募的。招募发生在多个地点，包括弗雷明汉后代队列，哈格斯敦和明尼阿波利斯/圣路易斯的ARIC研究地点。

Paul, and the Cardiovascular Health Study sites. Participants underwent baseline examinations, including an initial polysomnogram (SHHS-1). Participants were followed for an average of 10.7 years, with assessments conducted using questionnaires and home-based polysomnography (PSG) recordings. Data on 5,804 individuals were available from the National Sleep Research Resource as of July 2024 (shhs1-dataset-0.21.0), excluding participants from the Strong Heart Study.

保罗和心血管健康研究网站。参与者接受了基线检查，包括初始多导睡眠图（SHHS-1）。参与者平均随访10.7年，使用问卷和家庭多导睡眠图（PSG）记录进行评估。截至2024年7月，国家睡眠研究资源（shhs1-dataset-0.21.0）提供了5804个人的数据，不包括强心研究的参与者。

All experiments involving human participants and human tissue samples were conducted in accordance with relevant ethical guidelines and regulations. The study protocol was approved by the Ethical Committee of the National Heart, Lung, and Blood Institute (NHLBI) cooperative. Informed consent was obtained from all participants or their legal guardians prior to their participation in the study.

所有涉及人类参与者和人体组织样本的实验均按照相关的道德准则和法规进行。该研究方案得到了国家心肺血液研究所（NHLBI）合作社伦理委员会的批准。在参与研究之前，已获得所有参与者或其法定监护人的知情同意。

SHHS was supported by the National Heart, Lung, and Blood Institute cooperative agreements (detailed grant numbers were in the Acknowledgement part)..

SHHS得到了国家心脏，肺和血液研究所合作协议的支持（详细的拨款数字在确认部分）。。

To uphold the integrity and reliability of the results, specific exclusion criteria were applied: (1) individuals without complete mortality data (

为了维护结果的完整性和可靠性，采用了特定的排除标准：（1）没有完整死亡率数据的个体(

= 762); (2) individuals without CMI values (

=762）；（2）没有CMI值的个人(

= 619); and (3) individuals lacking records of essential covariates, including education (

；（3）缺乏包括教育在内的基本协变量记录的个人(

= 446), marital status (

=446），婚姻状况(

= 6), BMI (

===6），体重指数（BMI）

= 17), smoking status (

17），吸烟状况(

= 7), drinking status (

=7），饮酒状况(

= 318), diabetes (

=318），糖尿病(

= 112), heart failure (

=112），心力衰竭(

= 32), COPD (

===32），慢性阻塞性肺病（COPD）

= 37), myocardial infarction (

=37），心肌梗塞(

= 50), and stroke (

=50），和中风(

= 24). Due to overlapping exclusions where some participants lacked multiple covariates, a total of 3752 unique participants remained after applying these criteria (Fig.

。

Fig. 1

图1

Flow chart of participants selection.

参与者选择流程图。

Full size image

全尺寸图像

Assessment of all-cause and cardiovascular mortality

全因和心血管死亡率的评估

Deaths from any cause, including cardiovascular deaths, were identified and confirmed through multiple approaches. These included follow-up interviews, annual written questionnaires, or telephone contacts with study participants or their next-of-kin. Additionally, local hospital records and community obituaries were monitored, and data were linked with the Social Security Administration Death Master File.

通过多种方法确定并确认了包括心血管死亡在内的任何原因造成的死亡。这些措施包括后续访谈，年度书面问卷调查或与研究参与者或其近亲的电话联系。此外，还监测了当地医院记录和社区讣告，并将数据与社会保障管理局的死亡主文件相关联。

This comprehensive approach ensured the accurate identification and confirmation of mortality, serving as the primary endpoint for this study.

这种综合方法确保了死亡率的准确识别和确认，是本研究的主要终点。

Assessment of covariates

协变量的评估

At baseline, a comprehensive investigation of sociodemographic characteristics and lifestyle factors was conducted, including age, gender (male and female), self-reported race (White, Black, and other), marital status (married, widowed, divorced/separated, never married), education levels (< 10 years, 11–15 years, 16–20 years, > 20 years), body mass index (BMI), smoking status (never, current, former), and drinking status (0–1 drink per day, > 1 drink per day), TG (fasting condition), HDL-C (fasting condition), waist circumference (WC, c), height (cm).

在基线时，对社会人口学特征和生活方式因素进行了全面调查，包括年龄、性别（男性和女性）、自我报告的种族（白人、黑人和其他种族）、婚姻状况（已婚、丧偶、离婚/分居、未婚）、受教育程度（10岁、11-15岁、16-20岁） 20 年），体重指数（BMI），吸烟状况（从未，现在，以前）和饮酒状况（每天0-1杯，> 1 每天饮酒），TG（禁食条件），HDL-C（禁食条件），腰围（WC，C），身高（cm）。

Medical history data were collected on conditions such as heart failure (HF), hypertension, diabetes, myocardial infarction (MI), stroke, and chronic obstructive pulmonary disease (COPD). Hypertension was defined as a new physician diagnosis of hypertension (SHHS criteria), initiation of treatment with antihypertensive medications, or a systolic BP > 160 mmHg or a diastolic BP > 95 mmHg, while diabetes was determined by self-reported history or the use of insulin or hypoglycemic medications.

收集心力衰竭（HF），高血压，糖尿病，心肌梗塞（MI），中风和慢性阻塞性肺病（COPD）等病史数据。高血压被定义为高血压的新医生诊断（SHHS标准），开始使用抗高血压药物治疗，或收缩压>160 mmHg或舒张压>95 mmHg，而糖尿病是由自我报告的病史或使用胰岛素或降糖药物确定的。

Heart failure, myocardial infarction, stroke, and COPD were identified through parent study cohorts or self-reports based on physician-reported disease or history of coronary revascularization procedures..

根据医生报告的疾病或冠状动脉血运重建手术史，通过父母研究队列或自我报告确定心力衰竭，心肌梗死，中风和COPD。。

The CMI was calculated using the following formulas

使用以下公式计算CMI

\({\text{CMI }}={\text{ }}\left[ {{\text{TG }}\left( {{\text{mmol}}/{\text{L}}} \right){\text{ }}/{\text{ HDL}} - {\text{C }}\left( {{\text{mmol}}/{\text{L}}} \right)} \right]{\text{ }}*{\text{ }}\left[ {{\text{waist circumference }}\left( {{\text{cm}}} \right){\text{ }}/{\text{ height }}\left( {{\text{cm}}} \right)} \right]\).

\（{\text{CMI}}={\text{}}\left[{\text{TG}}\left（{\text{mmol}/{\text{L}}}\right）{\text{}/{\text{HDL}-{\text{C}}\left（{\text{mmol}/{\text{L}}}\right）}\right]{\text{}}*{\文本{}}\左[{\文本{腰围}}\左（{\文本{厘米}}\右）{\文本{}/{\文本{高度}}\左（{\文本{厘米}}\右）}\右]\）。

Participants were divided into tertiles according to their CMI values for subsequent analyses.

参与者根据其CMI值分为三分位数，以进行后续分析。

Statistical analysis

统计分析

Categorical variables were presented as frequencies and percentages, while continuous variables were expressed as medians and standard deviations. The Chi-squared test or Kruskal-Wallis H test was utilized to analyze differences across various CMI tertile categories. Statistical significance was determined using a two-sided p-value < 0.05..

分类变量表示为频率和百分比，而连续变量表示为中位数和标准差。卡方检验或Kruskal-Wallis H检验用于分析各种CMI三分位数类别的差异。统计学显着性采用双侧p值<0.05确定。。

A series of Cox proportional hazards models were developed to estimate the associations between CMI and both all-cause and cardiovascular mortality. The results were presented as hazard ratios (HRs) with 95% confidence intervals (CIs). Model 1 was unadjusted. Model 2 adjusted for demographic and lifestyle factors including age, gender, race, marital status, education level, BMI, smoking status, and drinking status.

开发了一系列Cox比例风险模型来估计CMI与全因死亡率和心血管死亡率之间的关联。结果以95%置信区间（CI）的风险比（HR）表示。模型1未经调整。模型2根据人口统计学和生活方式因素进行了调整，包括年龄，性别，种族，婚姻状况，教育水平，BMI，吸烟状况和饮酒状况。

Model 3, building on Model 2, further adjusted for clinical factors such as heart failure, DM, hypertension, myocardial infarction, stroke, and COPD. Trend p-values were calculated using the tertile levels. We utilized the ‘.

模型3建立在模型2的基础上，进一步调整了心力衰竭，糖尿病，高血压，心肌梗塞，中风和COPD等临床因素。使用三分位数水平计算趋势p值。我们利用了'。

coxph’

舵手

function from the survival package in R to fit the model, and the ‘

从R中的生存包中提取函数以拟合模型

summary’

“摘要”

function provided the C-statistics value, which reflects the model’s performance in distinguishing between individuals who experienced the event of interest and those who did not. A C-statistic of 0.5 indicates no discrimination, while a value closer to 1.0 indicates excellent discrimination. Kaplan-Meier survival curves were generated to estimate survival over time, and the log-rank test was employed to assess differences among the survival curves..

函数提供了C统计值，它反映了模型在区分经历过感兴趣事件的个体和没有经历过感兴趣事件的个体方面的表现。C统计量为0.5表示没有歧视，而接近1.0的值表示出色的歧视。生成Kaplan-Meier生存曲线以估计随时间的生存率，并使用对数秩检验来评估生存曲线之间的差异。。

Further subgroup analyses were conducted to evaluate the consistency of the prognostic value of the CMI within different subgroups defined by gender, smoking status, drinking status, heart failure, diabetes mellitus, hypertension, and myocardial infarction. The interactions between CMI and the stratification variables were examined using likelihood ratio tests.

进行了进一步的亚组分析，以评估CMI在由性别，吸烟状况，饮酒状况，心力衰竭，糖尿病，高血压和心肌梗塞定义的不同亚组中预后价值的一致性。使用似然比检验检查了CMI与分层变量之间的相互作用。

A double-sided p-value < 0.05 was considered statistically significant. All statistical analyses were conducted using R software (version 4.4.0, .

双侧p值<0.05被认为具有统计学意义。所有统计分析均使用R软件（版本4.4.0。

http://www.r-project.org

) and the following R packages: rms (version 6.8-1), MASS (version 7.3–60.2), and survival (version 3.5-8).

)以及以下R包：rms（版本6.8-1），MASS（版本7.3-60.2）和survival（版本3.5-8）。

Results

结果

Baseline characteristics

基线特征

In this study, a total of 3752 participants with complete information were enrolled, with a follow-up period of 10.7 ± 2.85 years. The mean age of the participants was 65.9 ± 10.1 years. The cohort included 1969 women (52.5%). Among the participants, 3,511 (93.6%) were white individuals. The mean CMI for all participants was 0.914 ± 0.939.

在这项研究中，共招募了3752名信息完整的参与者，随访期为10.7±2.85年。参与者的平均年龄为65.9±10.1岁。该队列包括1969名女性（52.5%）。在参与者中，有3511名（93.6%）是白人。所有参与者的平均CMI为0.914±0.939。

The all-cause mortality and cardiovascular mortality rates were 24.7% and 7.7%, respectively (Table .

全因死亡率和心血管死亡率分别为24.7%和7.7%（表）。

). Baseline characteristics of participants stratified according to CMI tertiles are presented in Table

)。表中列出了根据CMI三分位数分层的参与者的基线特征

. Participants were categorized into three groups based on their CMI levels: tertile (T) 1: 0.315 ± 0.0994; T2: 0.680 ± 0.128; T3: 1.75 ± 1.23. Individuals in the highest tertile of CMI generally exhibited a higher percentage of males, higher BMI, and increased prevalence of diabetes, hypertension, and myocardial infarction compared to those in the lower tertiles.

.参与者根据其CMI水平分为三组：三分位数（T）1：0.315±0.0994；T2：0.680±0.128；T3：1.75±1.23。与低三分位数相比，CMI最高三分位数的个体通常表现出更高的男性百分比，更高的BMI以及糖尿病，高血压和心肌梗塞的患病率增加。

Furthermore, participants in the highest tertile of CMI had significantly higher all-cause mortality rates compared to those in the lower tertiles (21.3% vs. 25.4% vs. 27.3%, .

。

= 0.005).

== 0.005).

Table 1 Characteristics of participants with various CMI tertiles.

表1具有各种CMI三分位数的参与者的特征。

Full size table

全尺寸表

Associations of CMI with all-cause and cardiovascular mortality

CMI与全因死亡率和心血管死亡率的关系

To evaluate the associations of CMI with all-cause and cardiovascular mortality, we first presented the Kaplan-Meier survival analysis curves (Fig.

为了评估CMI与全因死亡率和心血管死亡率的关系，我们首先提出了Kaplan-Meier生存分析曲线（图）。

), followed by the results from the Cox regression models (Table

)，然后是Cox回归模型的结果（表

). The Kaplan-Meier survival analysis curves, presented in Fig.

)。Kaplan-Meier生存分析曲线，如图所示。

, were used to evaluate all-cause mortality and cardiovascular mortality among groups stratified by CMI tertiles. The results indicated that participants in the higher CMI tertiles experienced significantly worse outcomes for both all-cause mortality (log-rank

，用于评估CMI三分位数分层组的全因死亡率和心血管死亡率。结果表明，CMI三分位数较高的参与者在全因死亡率方面的结果明显较差（对数秩

= 0.0035) and cardiovascular mortality (log-rank

==0.0035）和心血管死亡率（对数秩

= 0.035).

== 0.035).

Fig. 2

图2

Kaplan–Meier survival curves for (A) all-cause mortality and (B) cardiovascular mortality among different CMI tertiles.

（A）全因死亡率和（B）不同CMI三分位数之间心血管死亡率的Kaplan-Meier生存曲线。

Full size image

全尺寸图像

Table 2 Cox proportional hazard ratios (HR) for all-cause mortality and cardiovascular mortailty.

表2全因死亡率和心血管死亡率的Cox比例风险比（HR）。

Full size table

全尺寸表

The results of the Cox regression models are presented in Table

表中列出了Cox回归模型的结果

. In the unadjusted model, the hazard ratios for all-cause mortality were 1.215 (95% confidence interval [CI] 1.032–1.43) for tertile 2 and 1.309 (95% CI 1.115–1.537) for tertile 3. For cardiovascular mortality, the hazard ratios were 1.305 (95% CI 0.971–1.755) for tertile 2 and 1.457 (95% CI 1.091–1.947) for tertile 3, showing a tendency to increase with CMI (Table .

在未经调整的模型中，三分位数2的全因死亡率风险比为1.215（95%置信区间为1.032-1.43），三分位数3的全因死亡率风险比为1.309（95%置信区间为1.115-1.537）。对于心血管死亡率，三分位数2的危险比为1.305（95%CI 0.971-1.755），三分位数3的危险比为1.457（95%CI 1.091-1.947），显示出随着CMI的增加而增加的趋势（表。

, Model 1). After adjusting for anthropometric and demographic variables, including age, gender, race, marital status, education, BMI, smoking status, and drinking status, the hazard ratios for all-cause mortality and cardiovascular mortality in tertile 3 remained significant at 1.424 (95% CI 1.192–1.702) and 1.853 (95% CI 1.34–2.56), respectively, continuing to show a tendency to increase with CMI (Table .

，型号1）。在调整了人体测量和人口统计学变量（包括年龄，性别，种族，婚姻状况，教育程度，BMI，吸烟状况和饮酒状况）后，三分位数3的全因死亡率和心血管死亡率的风险比仍然显着，分别为1.424（95%CI 1.192-1.702）和1.853（95%CI 1.34-2.56），继续显示出随着CMI的增加而增加的趋势（表）。

, Model 2). The association between CMI and both all-cause and cardiovascular mortality persisted and remained significant for tertile 3 after further adjustment for medical history, including HF, DM, hypertension, MI, stroke, and COPD. The adjusted hazard ratios were 1.315 (95% CI 1.098–1.575) for all-cause mortality and 1.562 (95% CI 1.124–2.17) for cardiovascular mortality, again showing a tendency to increase with CMI (Table .

，型号2）。CMI与全因死亡率和心血管死亡率之间的关联持续存在，并且在进一步调整病史（包括HF，DM，高血压，MI，中风和COPD）后，三分位数3仍然显着。调整后的全因死亡率危险比为1.315（95%CI 1.098-1.575），心血管死亡率危险比为1.562（95%CI 1.124-2.17），再次显示出随着CMI的增加而增加的趋势（表1）。

, Model 3). The discriminative ability of Model 3 for all-cause and cardiovascular mortality was also assessed using the C-statistics, which were 0.786 for all-cause mortality and 0.862 for cardiovascular mortality.

，型号3）。。

Subgroup analysis

亚组分析

The risk stratification value of the CMI for all-cause and cardiovascular mortality was further analyzed in multiple subgroups of the enrolled participants, including gender, smoking status, drinking status, heart failure, diabetes, hypertension, and myocardial infarction (Figs.

在入选参与者的多个亚组中进一步分析了CMI对全因和心血管死亡率的风险分层值，包括性别，吸烟状况，饮酒状况，心力衰竭，糖尿病，高血压和心肌梗死（图）。

and

和

). The CMI was significantly associated with a higher risk of all-cause mortality in the subgroups of males [HR (95% CI) 1.1 (1.014–1.193)], former smokers [HR (95% CI) 1.13 (1.043–1.225)], those consuming more than one drink per day [HR (95% CI) 1.193 (1.06–1.343)], those without heart failure [HR (95% CI) 1.091 (1.029–1.157)], those without diabetes [HR (95% CI) 1.107 (1.031–1.188)], those with hypertension [HR (95% CI) 1.103 (1.028–1.184)], and those without myocardial infarction [HR (95% CI) 1.079 (1.012–1.152)] (Fig. .

)。男性亚组[HR（95%CI）1.1（1.014-1.193）]，前吸烟者[HR（95%CI）1.13（1.043-1.225）]，每天饮酒超过一杯的人群[HR（95%CI）1.193（1.06-1.343）]，无心力衰竭的人群[HR（95%CI）1.091（1.029-1.157）]，无糖尿病的人群[HR（95%CI）1.107（1.031-1.188）]的CMI与全因死亡风险显着相关。高血压[HR（95%CI）1.103（1.028-1.184）]，无心肌梗死[HR（95%CI）1.079（1.012-1.152）]（图。

). Similarly, in the stratified analyses of cardiovascular mortality, the CMI demonstrated a significant association with a higher risk of cardiovascular mortality in the subgroups of males [HR (95% CI) 1.154 (1.006–1.323)], former smokers [HR (95% CI) 1.304 (1.1–1.546)], those consuming 0–1 drink per day [HR (95% CI) 1.12 (1.021–1.227)], those without heart failure [HR (95% CI) 1.114 (1.012–1.226)], and those with hypertension [HR (95% CI) 1.129 (1.01–1.262)] (Fig. .

)。同样，在心血管死亡率的分层分析中，CMI与男性亚组[HR（95%CI）1.154（1.006-1.323）]、前吸烟者[HR（95%CI）1.304（1.1-1.546）]、每天饮酒0-1次者[HR（95%CI）1.12（1.021-1.227）]、无心力衰竭者[HR（95%CI）1.114（1.012-1.226）]和高血压患者[HR（95%CI）1.129（1.01-1.262）]（图。

). Additionally, there is a significant interaction between gender and CMI regarding all-cause mortality (p for interaction = 0.022), indicating that gender significantly influences the association of CMI with survival outcomes. This indicates that the association between CMI and survival outcomes may differ between genders, highlighting the need for further research..

)。此外，性别和CMI在全因死亡率方面存在显著的交互作用（交互作用p = 0.022), 表明性别显着影响CMI与生存结果的关联。这表明CMI与生存结果之间的关联可能因性别而异，突出了进一步研究的必要性。。

Fig. 3

图3

Subgroup analysis of the associations between CMI and all-cause mortality.

CMI与全因死亡率之间关联的亚组分析。

Full size image

全尺寸图像

Fig. 4

图4

Subgroup analysis of the associations between CMI and cardiovascular mortality.

CMI与心血管死亡率之间关联的亚组分析。

Full size image

全尺寸图像

Discussion

讨论

In the present study, we investigated the association between the CMI and clinical outcomes in the American adults aged 40 years and older from a multi-center, community-based cohort. Our findings indicate that a higher CMI is significantly associated with increased all-cause and cardiovascular mortality among the middle-aged and elderly population in the USA.

在本研究中，我们调查了来自多中心社区队列的40岁及以上美国成年人的CMI与临床结果之间的关联。我们的研究结果表明，较高的CMI与美国中老年人群的全因和心血管死亡率增加显着相关。

These associations remained significant even after adjusting for confounding risk factors. Therefore, CMI may serve as a valuable decision-making tool for clinicians, aiding in risk stratification and the development of personalized treatment plans. Monitoring CMI in this population provides a straightforward yet powerful method for conducting epidemiological studies on adverse prognoses, thereby facilitating early intervention and improving patient outcomes..

即使调整了混杂的风险因素，这些关联仍然很重要。因此，CMI可以作为临床医生有价值的决策工具，有助于风险分层和个性化治疗计划的制定。在这一人群中监测CMI为进行不良预后的流行病学研究提供了一种简单而有力的方法，从而有助于早期干预和改善患者预后。。

Despite the use of treatment strategies and interventions based on clinical practice guidelines, cardiometabolic diseases, including cardiovascular disease and diabetes mellitus, continue to be prevalent and severe conditions associated with considerable morbidity and mortality

尽管使用了基于临床实践指南的治疗策略和干预措施，但包括心血管疾病和糖尿病在内的心脏代谢疾病仍然普遍存在，并且病情严重，发病率和死亡率都很高

. These diseases place an increasing public health burden worldwide

这些疾病给全世界带来了越来越大的公共卫生负担

. Therefore, there is an urgent need to explore new biomarkers that can identify individuals at high risk for cardiometabolic diseases. By identifying these high-risk individuals, we can enhance preventive measures, improve early detection, and ultimately reduce the disease burden.

因此，迫切需要探索新的生物标志物，以识别心脏代谢疾病高危人群。通过识别这些高危人群，我们可以加强预防措施，改善早期发现，并最终减轻疾病负担。

CMI, consisting of the waist-to-height ratio, TG, and HDL-C, was initially introduced as a potential indicator of diabetes mellitus

CMI由腰高比、TG和HDL-C组成，最初被引入作为糖尿病的潜在指标

. Accumulating evidence suggests that the CMI is not only a risk factor for the deterioration of cardiac and renal function but also influences the incidence of adverse outcomes

越来越多的证据表明，CMI不仅是心脏和肾功能恶化的危险因素，而且还影响不良结局的发生率

. In the context of cardiovascular diseases, Merkin et al. conducted a study revealing that an increase in CMI over time was significantly associated with a higher risk of subsequent cardiovascular events among patients with elevated cardiometabolic risk at baseline

在心血管疾病的背景下，Merkin等人进行了一项研究，发现随着时间的推移，CMI的增加与基线时心脏代谢风险升高的患者随后发生心血管事件的风险显着相关

. Tang highlighted the intricate link between the CMI and arteriosclerosis in patients with type 2 diabetes mellitus

唐强调了2型糖尿病患者CMI与动脉硬化之间的复杂联系

. Furthermore, Wang’s research found that the CMI was associated with a higher risk of obesity-related hypertension

此外，王的研究发现，CMI与肥胖相关高血压的风险较高有关

. Li demonstrated a strong and independent association between CMI and the risk of stroke in the general population

李证明了CMI与普通人群中风风险之间存在强烈而独立的关联

. In the context of diabetes, several studies have highlighted the relevance and utility of the CMI. Wakabayashi demonstrated that in men with diabetes, CMI is lower in light-to-moderate drinkers compared to nondrinkers, suggesting that moderate alcohol consumption may benefit diabetic patients

在糖尿病的背景下，一些研究强调了CMI的相关性和实用性。Wakabayashi证明，在糖尿病男性中，轻度至中度饮酒者的CMI低于非饮酒者，这表明适度饮酒可能有益于糖尿病患者

. Additionally, Wakabayashi showed a dose-dependent relationship between CMI and smoking in diabetic patients, indicating that CMI can effectively discriminate diabetes in both smokers and nonsmokers

此外，Wakabayashi在糖尿病患者中显示出CMI与吸烟之间的剂量依赖关系，这表明CMI可以有效区分吸烟者和非吸烟者的糖尿病

. Song further elucidated CMI’s role by demonstrating a positive correlation between CMI and insulin resistance, impaired fasting glucose, and type 2 diabetes mellitus in the general population, underscoring CMI’s potential as a predictor for various metabolic disorders

宋通过证明CMI与普通人群的胰岛素抵抗、空腹血糖受损和2型糖尿病之间存在正相关关系，进一步阐明了CMI的作用，强调了CMI作为各种代谢紊乱预测因子的潜力

. Shi’s research supported CMI’s use in diabetes management, showing that an increasing CMI correlates with higher odds of diabetes and emphasizing CMI as a useful and cost-effective measure for screening and quantifying diabetes in the general Chinese population

Shi的研究支持CMI在糖尿病管理中的应用，表明CMI的增加与糖尿病发病率的增加相关，并强调CMI是筛查和量化中国普通人群糖尿病的有用且具有成本效益的措施

. Therefore, the CMI has been proven to be a significant marker for various cardiovascular diseases, diabetes mellitus, and other metabolic-related conditions. By identifying high-risk individuals, CMI can help clinicians target interventions more effectively, enable personalized treatment plans based on individual risk profiles, and enhance patient education by communicating risks.

因此，CMI已被证明是各种心血管疾病，糖尿病和其他代谢相关疾病的重要标志。通过识别高危人群，CMI可以帮助临床医生更有效地针对干预措施，根据个人风险概况制定个性化治疗计划，并通过沟通风险来加强患者教育。

Regular assessment of CMI allows for ongoing monitoring and follow-up, guiding preventive strategies to prioritize interventions for patients with elevated scores. Ultimately, these measures can improve early detection and significantly reduce the disease burden..

对CMI的定期评估可以进行持续的监测和随访，指导预防策略，优先对得分升高的患者进行干预。。。

However, the clinical utility of the CMI for predicting outcomes in the middle-aged and elderly population and among patients with cardiometabolic diseases has faced several challenges. The first challenge is the potential influence of hyperlipidemia on the CMI. In patients with exceptionally TG levels, the applicability of the CMI may be compromised, limiting its use in those with severe cardiometabolic disorders.

然而，CMI在预测中老年人群和心脏代谢疾病患者预后方面的临床应用面临着一些挑战。第一个挑战是高脂血症对CMI的潜在影响。在TG水平异常的患者中，CMI的适用性可能会受到影响，从而限制了其在严重心脏代谢紊乱患者中的使用。

. Additionally, most studies on the CMI have focused on elderly patients

此外，大多数关于CMI的研究都集中在老年患者身上

, leaving its predictive value in younger individuals uncertain. For instance, Xu’s research provided evidence for positive associations between the CMI, inflammation-related indicators, and all-cause mortality in older adults. However, the same study found no direct association between the CMI and all-cause mortality or cardiovascular mortality in the elderly population when analyzed using Kaplan-Meier survival curves and Cox regression models.

，使其对年轻人的预测价值不确定。例如，徐的研究为CMI，炎症相关指标和老年人全因死亡率之间的正相关提供了证据。然而，同一项研究发现，当使用Kaplan-Meier生存曲线和Cox回归模型进行分析时，CMI与老年人群的全因死亡率或心血管死亡率之间没有直接关联。

In contrast, our study found a positive relationship between the CMI and both all-cause and cardiovascular mortality in the middle-aged and elderly population. Notably, our follow-up period was over 15 years, significantly longer than that of previous studies. This extended follow-up period allowed us to capture more robust data, reinforcing the prognostic value of the CMI across a broader demographic..

相比之下，我们的研究发现CMI与中老年人群的全因死亡率和心血管死亡率呈正相关。值得注意的是，我们的随访期超过15年，明显长于以前的研究。这一延长的随访期使我们能够捕获更可靠的数据，从而在更广泛的人口统计学中增强了CMI的预后价值。。

Cardiometabolic indices, including the triglyceride glucose (TyG) index, visceral adiposity index (VAI), and lipid accumulation product (LAP), have each been validated as markers associated with higher mortality in patients with cardiometabolic diseases. Zhang demonstrated a U-shaped association between the baseline TyG index and both cardiovascular and all-cause mortality in cardiovascular disease patients with diabetes or pre-diabetes in an American population.

心脏代谢指标，包括甘油三酯-葡萄糖（TyG）指数，内脏肥胖指数（VAI）和脂质积累产物（LAP），均已被验证为与心脏代谢疾病患者死亡率较高相关的标志物。张证明了基线TyG指数与美国人群中患有糖尿病或糖尿病前期的心血管疾病患者的心血管和全因死亡率之间存在U型关联。

. Yao found that a higher TyG index was linked to an increased risk of all-cause and non-cardiovascular mortality in type 2 diabetes mellitus patients younger than 65 years old, but this association was not observed in older patients

姚发现，在65岁以下的2型糖尿病患者中，较高的TyG指数与全因和非心血管死亡风险增加有关，但在老年患者中未观察到这种关联

. Wu showed that the VAI has predictive value for all-cause, CVD, and cancer mortality risks in a Chinese population

Wu表明，VAI对中国人群的全因、心血管疾病和癌症死亡风险具有预测价值

. Similarly, Chen reported that a higher LAP was significantly associated with higher all-cause and CVD mortality in an American cohort, suggesting that maintaining a low LAP status may reduce the risk of death

同样，陈报告说，在美国队列中，较高的圈数与较高的全因死亡率和心血管疾病死亡率显着相关，这表明保持较低的圈数状态可能会降低死亡风险

. In the present study, we introduced the CMI as a novel predictor of all-cause and cardiovascular mortality in the middle-aged and elderly American adults. This study is pioneering in its evaluation of the prognostic value of the CMI in a broad population cohort. A major strength of our research is its prospective cohort design, utilizing the extensive and representative SHHS database with over 15 years of follow-up.

在本研究中，我们引入了CMI作为美国中老年人全因死亡率和心血管死亡率的新型预测指标。这项研究在评估CMI在广泛人群中的预后价值方面具有开创性。我们研究的一个主要优势是其前瞻性队列设计，利用了广泛且具有代表性的SHHS数据库，并进行了超过15年的随访。

This large-scale dataset enhances the generalizability of our findings across diverse demographic groups..

这个大规模的数据集增强了我们在不同人口群体中发现的普遍性。。

The present study had several limitations. Firstly, despite the SHHS combining data from several large healthcare centers, the overall sample size was still relatively modest. This limitation may have constrained the statistical power of some analyses. Secondly, as a novel anthropometric index, the CMI has not been extensively studied in terms of evaluating different comorbidities in the middle-aged and elderly population for predicting mortality.

本研究有几个局限性。首先，尽管SHHS结合了几个大型医疗中心的数据，但总体样本量仍然相对适中。这种限制可能限制了某些分析的统计能力。其次，作为一种新的人体测量指标，CMI尚未在评估中老年人群不同合并症以预测死亡率方面进行广泛研究。

Consequently, it remains unclear whether the CMI contributes to increased mortality through its association with various comorbidities. Future research is necessary to further evaluate the predictive power of the CMI in this context. Additionally, the medical history data for conditions such as hypertension, diabetes, heart failure, stroke, myocardial infarction, and COPD were self-reported via questionnaires.

因此，尚不清楚CMI是否通过与各种合并症的关联而导致死亡率增加。未来的研究对于进一步评估CMI在这种情况下的预测能力是必要的。此外，高血压，糖尿病，心力衰竭，中风，心肌梗塞和COPD等疾病的病史数据是通过问卷自我报告的。

This reliance on self-reported information introduces the possibility of recall bias, which could affect the accuracy of the diagnoses and potentially influence the study’s findings. Moreover, our analysis revealed significant differences in age and race between the included and excluded participants (Table .

这种对自我报告信息的依赖引入了回忆偏倚的可能性，这可能会影响诊断的准确性，并可能影响研究结果。此外，我们的分析显示，纳入和排除参与者之间的年龄和种族存在显着差异（表）。

S1级

), suggesting the possibility of selection bias due to missing data. This potential bias should be considered when interpreting the results.

)，表明由于缺少数据而可能存在选择偏差。在解释结果时应考虑这种潜在的偏见。

Conclusion

结论

In summary, our findings expand the applicability of the CMI to the middle-aged and elderly population and indicate that it could serve as a valuable tool for risk stratification of all-cause and cardiovascular mortality. Incorporating CMI monitoring into clinical practice can enhance decision-making and disease management.

总之，我们的研究结果扩大了CMI对中老年人群的适用性，并表明它可以作为全因和心血管死亡率风险分层的有价值的工具。将CMI监测纳入临床实践可以加强决策和疾病管理。

Furthermore, it offers significant insights for early risk stratification and the formulation of effective intervention strategies in public health..

此外，它为早期风险分层和制定有效的公共卫生干预策略提供了重要的见解。。

Data availability

数据可用性

The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.

在当前研究期间生成和分析的数据集可根据合理的要求从通讯作者处获得。

References

参考文献

Guariguata, L. et al. Global estimates of diabetes prevalence for 2013 and projections for 2035.

Guariguata，L.等人，《2013年全球糖尿病患病率估计和2035年预测》。

Diabetes Res. Clin. Pract.

糖尿病研究临床。实践。

103

, 137–149.

https://doi.org/10.1016/j.diabres.2013.11.002

(2014).

Article

文章

CAS

中科院

PubMed

Google Scholar

谷歌学者

Dieleman, J. L. et al. US Health care spending by payer and health condition, 1996–2016.

Dieleman，J.L.等人，《1996-2016年按付款人和健康状况划分的美国医疗保健支出》。

JAMA

日本汽车制造商协会

323

, 863–884.

https://doi.org/10.1001/jama.2020.0734

(2020).

Article

文章

PubMed

PubMed Central

公共医学中心

MATH

数学

Google Scholar

谷歌学者

Virani, S. S. et al. Heart disease and stroke statistics-2021 update: A report from the American heart association.

Virani，S.S.等人，《心脏病和中风统计-2021年更新：美国心脏协会的报告》。

Circulation

流通

143

, e254–e743.

，e254–e743。

https://doi.org/10.1161/cir.0000000000000950

(2021).

Article

文章

PubMed

MATH

数学

Google Scholar

谷歌学者

Wakabayashi, I. & Daimon, T. The cardiometabolic index as a new marker determined by adiposity and blood lipids for discrimination of diabetes mellitus.

Wakabayashi，I。＆Daimon，T。心脏代谢指数是由肥胖和血脂决定的用于区分糖尿病的新标志物。

Clin. Chim. Acta

克林。奇姆。会议记录

438

, 274–278.

https://doi.org/10.1016/j.cca.2014.08.042

(2015).

Article

文章

CAS

中科院

PubMed

MATH

数学

Google Scholar

谷歌学者

Shi, W. R. et al. Estimate of prevalent diabetes from cardiometabolic index in general Chinese population: A community-based study.

Shi，W.R.等人。从中国普通人群的心脏代谢指数估计糖尿病患病率：一项基于社区的研究。

Lipids Health Dis.

脂质健康疾病。

, 236.

https://doi.org/10.1186/s12944-018-0886-2

(2018).

Article

文章

CAS

中科院

PubMed

PubMed Central

公共医学中心

MATH

数学

Google Scholar

谷歌学者

Wakabayashi, I., Sotoda, Y., Hirooka, S. & Orita, H. Association between cardiometabolic index and atherosclerotic progression in patients with peripheral arterial disease.

Wakabayashi，I.，Sotoda，Y.，Hirooka，S。＆Orita，H。外周动脉疾病患者心脏代谢指数与动脉粥样硬化进展之间的关联。

Clin. Chim. Acta

克林。奇姆。会议记录

446

, 231–236.

https://doi.org/10.1016/j.cca.2015.04.020

(2015).

Article

文章

CAS

中科院

PubMed

Google Scholar

谷歌学者

Wang, H. et al. Validity of cardiometabolic index, lipid accumulation product, and body adiposity index in predicting the risk of hypertension in Chinese population.

Wang，H。等人。心脏代谢指数、脂质累积产物和身体肥胖指数在预测中国人群高血压风险中的有效性。

Postgrad. Med.

研究生。医学。

130

, 325–333.

https://doi.org/10.1080/00325481.2018.1444901

(2018).

Article

文章

PubMed

MATH

数学

Google Scholar

谷歌学者

Wang, H., Chen, Y., Guo, X., Chang, Y. & Sun, Y. Usefulness of cardiometabolic index for the estimation of ischemic stroke risk among general population in rural China.

Wang，H.，Chen，Y.，Guo，X.，Chang，Y。＆Sun，Y。心脏代谢指数在中国农村普通人群缺血性卒中风险评估中的有用性。

Postgrad. Med.

研究生。医学。

129

, 834–841.

https://doi.org/10.1080/00325481.2017.1375714

(2017).

Article

文章

PubMed

MATH

数学

Google Scholar

谷歌学者

Xu, B. et al. Is systemic inflammation a missing link between cardiometabolic index with mortality? Evidence from a large population-based study.

Xu，B.等人，全身炎症是心脏代谢指数与死亡率之间缺失的联系吗？来自大规模人群研究的证据。

Cardiovasc. Diabetol.

心血管疾病。糖尿病。

, 212.

https://doi.org/10.1186/s12933-024-02251-w

(2024).

Article

文章

CAS

中科院

PubMed

PubMed Central

公共医学中心

MATH

数学

Google Scholar

谷歌学者

Zhang, G. Q. et al. The National Sleep Research Resource: Towards a sleep data commons.

Zhang，G.Q.等人，《国家睡眠研究资源：走向睡眠数据共享空间》。

J. Am. Med. Inf. Assoc.

美国医学信息协会。

, 1351–1358.

https://doi.org/10.1093/jamia/ocy064

(2018).

Article

文章

MATH

数学

Google Scholar

谷歌学者

Quan, S. F. et al. The Sleep Heart Health Study: Design, rationale, and methods.

。

Sleep

睡眠

, 1077–1085 (1997).

CAS

中科院

PubMed

MATH

数学

Google Scholar

谷歌学者

Punjabi, N. M. et al. Sleep-disordered breathing and mortality: A prospective cohort study.

Punjabi，N.M.等人，《睡眠呼吸障碍与死亡率：一项前瞻性队列研究》。

PLoS Med.

《公共科学图书馆·医学》。

6, e1000132 (2009).

6，e1000132（2009）。

https://doi.org/10.1371/journal.pmed.1000132

Malik, V. S. & Hu, F. B. The role of sugar-sweetened beverages in the global epidemics of obesity and chronic diseases.

Malik，V.S.＆Hu，F.B。含糖饮料在全球肥胖和慢性病流行中的作用。

Nat. Rev. Endocrinol.

《国家内分泌杂志》。

, 205–218.

https://doi.org/10.1038/s41574-021-00627-6

(2022).

Article

文章

PubMed

PubMed Central

公共医学中心

MATH

数学

Google Scholar

谷歌学者

Lavie, C. J., Ozemek, C., Carbone, S., Katzmarzyk, P. T. & Blair, S. N. Sedentary behavior, exercise, and cardiovascular health.

Lavie，C.J.，Ozemek，C.，Carbone，S.，Katzmarzyk，P.T。＆Blair，S.N。久坐行为，运动和心血管健康。

Circ. Res.

Circ。我没有。

124

, 799–815.

https://doi.org/10.1161/circresaha.118.312669

(2019).

Article

文章

CAS

中科院

PubMed

Google Scholar

谷歌学者

Merkin, S. S., Karlamangla, A., Elashoff, D., Grogan, T. & Seeman, T. Change in cardiometabolic score and incidence of cardiovascular disease: The multi-ethnic study of atherosclerosis.

Merkin，S.S.，Karlamangla，A.，Elashoff，D.，Grogan，T。＆Seeman，T。心脏代谢评分和心血管疾病发病率的变化：动脉粥样硬化的多种族研究。

Ann. Epidemiol.

安。流行病。

, 912–917e911.

，912–917e911。

https://doi.org/10.1016/j.annepidem.2015.09.006

(2015).

Article

文章

PubMed

PubMed Central

公共医学中心

MATH

数学

Google Scholar

谷歌学者

Tang, C. et al. Correlation between the cardiometabolic index and arteriosclerosis in patients with type 2 diabetes mellitus.

Tang，C.等人。2型糖尿病患者心脏代谢指数与动脉硬化的相关性。

BMC Cardiovasc. Disord

BMC心血管。不一致

, 186.

https://doi.org/10.1186/s12872-024-03853-8

(2024).

Article

文章

CAS

中科院

PubMed

PubMed Central

公共医学中心

MATH

数学

Google Scholar

谷歌学者

Li, F. E. et al. Association between cardiometabolic index and stroke: A population- based cross-sectional study.

Li，F.E.等人。心脏代谢指数与中风之间的关联：一项基于人群的横断面研究。

Curr. Neurovasc Res.

Curr。我简直不敢相信。

, 324–332.

https://doi.org/10.2174/1567202618666211013123557

(2021).

Article

文章

ADS

CAS

中科院

PubMed

MATH

数学

Google Scholar

谷歌学者

Wakabayashi, I. Inverse association of light-to-moderate alcohol drinking with cardiometabolic index in men with diabetes mellitus.

Wakabayashi，I。轻度至中度饮酒与糖尿病男性心脏代谢指数的负相关。

Diabetes Metab. Syndr.

糖尿病代谢。Syndr公司。

, 1013–1017.

https://doi.org/10.1016/j.dsx.2018.06.016

(2018).

Article

文章

PubMed

MATH

数学

Google Scholar

谷歌学者

Wakabayashi, I. Relationship between smoking and cardiometabolic index in middle-aged men.

Wakabayashi，I。中年男性吸烟与心脏代谢指数的关系。

Clin. Lab.

临床。实验室。

, 1045–1051.

https://doi.org/10.7754/clin.lab.2015.150939

(2016).

Article

文章

CAS

中科院

PubMed

MATH

数学

Google Scholar

谷歌学者

Song, J. et al. Non-linear associations of cardiometabolic index with insulin resistance, impaired fasting glucose, and type 2 diabetes among US adults: A cross-sectional study.

Song，J.等人。美国成年人心脏代谢指数与胰岛素抵抗、空腹血糖受损和2型糖尿病的非线性关联：一项横断面研究。

Front. Endocrinol.

。内分泌。

, 1341828.

https://doi.org/10.3389/fendo.2024.1341828

(2024).

Article

文章

Google Scholar

谷歌学者

Simental-Mendía, L. E., Rodríguez-Morán, M. & Guerrero-Romero, F. The product of fasting glucose and triglycerides as surrogate for identifying insulin resistance in apparently healthy subjects.

Simental Mendía，L.E.，Rodríguez Morán，M。＆Guerrero-Romero，F。空腹血糖和甘油三酯的产物，可替代表面健康受试者的胰岛素抵抗。

Metab. Syndr. Relat. Disord

代谢。Syndr公司。相关。不一致

, 299–304.

https://doi.org/10.1089/met.2008.0034

(2008).

Article

文章

CAS

中科院

PubMed

Google Scholar

谷歌学者

Zhang, Q., Xiao, S., Jiao, X. & Shen, Y. The triglyceride-glucose index is a predictor for cardiovascular and all-cause mortality in CVD patients with diabetes or pre-diabetes: Evidence from NHANES 2001–2018.

Zhang，Q.，Xiao，S.，Jiao，X。＆Shen，Y。甘油三酯-葡萄糖指数是糖尿病或糖尿病前期CVD患者心血管和全因死亡率的预测指标：NHANES 2001-2018年的证据。

Cardiovasc. Diabetol.

心血管疾病。糖尿病。

, 279.

https://doi.org/10.1186/s12933-023-02030-z

(2023).

Article

文章

CAS

中科院

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Yao, Y. et al. The association between TyG and all-cause/non-cardiovascular mortality in general patients with type 2 diabetes mellitus is modified by age: Results from the cohort study of NHANES 1999–2018.

Yao，Y.等人。一般2型糖尿病患者的TyG与全因/非心血管死亡率之间的关联因年龄而异：NHANES 1999-2018年队列研究的结果。

Cardiovasc. Diabetol.

心血管疾病。糖尿病。

, 43.

https://doi.org/10.1186/s12933-024-02120-6

(2024).

Article

文章

CAS

中科院

PubMed

PubMed Central

公共医学中心

MATH

数学

Google Scholar

谷歌学者

Wu, X. et al. Associations between Chinese visceral adiposity index and risks of all-cause and cause-specific mortality: A population-based cohort study.

Wu，X。等人。中国内脏肥胖指数与全因和特定原因死亡风险之间的关联：一项基于人群的队列研究。

Diabetes Obes. Metab.

糖尿病Obes。代谢。

, 1264–1272.

https://doi.org/10.1111/dom.15424

(2024).

Article

文章

CAS

中科院

PubMed

MATH

数学

Google Scholar

谷歌学者

Chen, S. et al. Association of lipid accumulation product with all-cause and cardiovascular disease mortality: result from NHANES database.

Chen，S.等人。脂质积累产物与全因和心血管疾病死亡率的关联：来自NHANES数据库的结果。

Nutr. Metab. Cardiovasc. Dis.

营养。代谢。心血管。Dis。

, 1467–1476.

https://doi.org/10.1016/j.numecd.2023.10.015

(2024).

Article

文章

CAS

中科院

PubMed

MATH

数学

Google Scholar

谷歌学者

Download references

下载参考资料

Acknowledgements

致谢

The Sleep Heart Health Study (SHHS) was supported by National Heart, Lung, and Blood Institute cooperative agreements U01HL53916 (University of California, Davis), U01HL53931 (New York University), U01HL53934 (University of Minnesota), U01HL53937 and U01HL64360 (Johns Hopkins University), U01HL53938 (University of Arizona), U01HL53940 (University of Washington), U01HL53941 (Boston University), and U01HL63463 (Case Western Reserve University).

睡眠心脏健康研究（SHHS）得到了国家心肺血液研究所合作协议U01HL53916（加利福尼亚大学戴维斯分校），U01HL53931（纽约大学），U01HL53934（明尼苏达大学），U01HL53937和U01HL64360（约翰霍普金斯大学），U01HL53938（亚利桑那大学），U01HL53940（华盛顿大学），U01HL53941（波士顿大学）和U01HL63463（凯斯西储大学）的支持。

The National Sleep Research Resource was supported by the National Heart, Lung, and Blood Institute (R24 HL114473, 75N92019R002)..

国家睡眠研究资源得到了国家心肺血液研究所（R24 HL11447375N92019R002）的支持。。

Author information

作者信息

Author notes

作者注释

Mengya Zhu and Hui Jin contributed equally to this work.

朱梦娅和惠金对这项工作做出了同样的贡献。

Authors and Affiliations

作者和隶属关系

Huai’an No. 3 People’s Hospital, Huaian Second Clinical College of Xuzhou Medical University, Huaian, China

徐州医科大学淮安第二临床学院淮安市第三人民医院，淮安

Mengya Zhu

朱梦娅

Mental Health Center, West China Hospital, Sichuan University, Sichuan, China

四川大学华西医院心理健康中心，四川

Hui Jin

惠金

Nanjing Jiangbei Hospital, Affiliated Nanjing Jiangbei Hospital of Xinglin College, Nantong University, 552 Geguan Road, Jiangsu, 210048, China

南京江北医院，南通大学兴林学院附属南京江北医院，江苏省葛官路552号，210048

Yujie Yin & Ya Xu

尹玉洁

Lianshui People’s Hospital of Kangda college Affiliated to Nanjing Medical University, Hong Ri Dong Road, Lianshui County, 223499, Jiangsu, China

南京医科大学附属康达学院涟水人民医院，涟水县红日东路，223499，江苏

Yangang Zhu

朱扬刚

Authors

作者

Mengya Zhu

朱梦娅

View author publications

查看作者出版物

You can also search for this author in

您也可以在中搜索此作者

PubMed

Google Scholar

谷歌学者

Hui Jin

惠金

View author publications

查看作者出版物

You can also search for this author in

您也可以在中搜索此作者

PubMed

Google Scholar

谷歌学者

Yujie Yin

尹玉杰

View author publications

查看作者出版物

You can also search for this author in

您也可以在中搜索此作者

PubMed

Google Scholar

谷歌学者

Ya Xu

亚旭

View author publications

查看作者出版物

You can also search for this author in

您也可以在中搜索此作者

PubMed

Google Scholar

谷歌学者

Yangang Zhu

朱扬刚

View author publications

查看作者出版物

You can also search for this author in

您也可以在中搜索此作者

PubMed

Google Scholar

谷歌学者

Contributions

捐款

Material preparation, data collection, and analysis were performed by M.Z, H.J and Y.Y. The first draft of the manuscript was written by M.Z and H.J, and the manuscript was critically revised by Y.X and Y.Z. All authors reviewed the manuscript.

材料准备，数据收集和分析由M.Z，H.J和Y.Y.进行。手稿的初稿由M.Z和H.J撰写，手稿由Y.X和Y.Z.严格修订。所有作者都审阅了手稿。

Corresponding author

通讯作者

Correspondence to

通信对象

Yangang Zhu

朱扬刚

Ethics declarations

道德宣言

Competing interests

相互竞争的利益

The authors declare no competing interests.

作者声明没有利益冲突。

Additional information

其他信息

Publisher’s note

出版商注释

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Springer Nature在已发布的地图和机构隶属关系中的管辖权主张方面保持中立。

Electronic supplementary material

电子补充材料

Below is the link to the electronic supplementary material.

以下是电子补充材料的链接。

Supplementary Material 1

补充材料1

Rights and permissions

权限和权限

Open Access

开放存取

This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material.

本文是根据知识共享署名非商业性NoDerivatives 4.0国际许可证授权的，该许可证允许以任何媒介或格式进行任何非商业性使用，共享，分发和复制，只要您对原始作者和来源给予适当的信任，提供知识共享许可证的链接，并指出您是否修改了许可材料。

You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

To view a copy of this licence, visit .

要查看此许可证的副本，请访问。

http://creativecommons.org/licenses/by-nc-nd/4.0/

Reprints and permissions

重印和许可

About this article

关于本文

Cite this article

引用本文

Zhu, M., Jin, H., Yin, Y.

朱，M，金，H，尹，Y。

et al.