糖尿病前期和糖尿病成人的人体测量指标与心血管疾病风险:NHANES 1999-2018 年横断面分析。

IF 3.9
Yi He , Lingfeng Shi
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引用次数: 0

摘要

背景:由于心血管疾病(CVD)是糖尿病患者的主要死因,而肥胖又是糖尿病和动脉粥样硬化的常见风险因素,因此本研究试图找出这些人群中人体测量指标与心血管疾病风险之间的关系:我们的研究调查了36329名成年人,包括从1999年到2018年的美国国家健康与营养调查(NHANES)数据中确诊的糖尿病患者、糖尿病前期患者和无糖尿病患者。评估了各种人体测量指标,如体重指数(BMI)、腰围、体重调整腰围指数(WWI)、腰围身高比(WHTR)、体重和身高。加权后比较了三个组别的基线特征。然后根据人体测量指标对参与者进行分组,并使用逻辑回归模型分析这些指标与整个糖尿病组(包括糖尿病患者和糖尿病前期患者)的心血管疾病风险之间的关系。阈值效应分析用于探讨非线性关系,中介分析用于评估血清参数是否影响这些关系:这项横断面研究涉及 36,329 名参与者,加权后的人数约为 1.609 亿,其中包括超过 4,590 万名糖尿病前期患者和约 1,660 万名糖尿病患者。基线分析表明,在不同糖尿病状态的患者中,所有六项人体测量指标与心血管疾病风险之间均存在明显关联。加权受限立方样条曲线(RCS)分析显示,与非糖尿病组相比,总糖尿病组中每个人体测量指标的心血管疾病风险都有所增加。然后将人体测量指标分为四等分,在对混杂因素进行调整后,模型3显示,与体重指数最低的组别相比,体重指数最高的组别患心血管疾病的风险更高。在WWI和WHtR亚组中也观察到类似的趋势。人体测量指标的阈值效应分析揭示了腰围、身高、WWI 和心血管疾病风险之间的非线性关系。中介分析表明,血脂参数,尤其是高密度脂蛋白,对这些关系有显著的中介作用:结论:在糖尿病患者和糖尿病前期患者中,体重指数(BMI)、体重和 WHtR 与心血管疾病风险呈一致的线性增长关系。相反,腰围、身高、WWI 与心血管疾病风险之间的关系则呈现出更为复杂的非线性模式。此外,在人体测量指标与心血管疾病风险之间的关系中,高密度脂蛋白水平是一个显著的中介因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Anthropometric indicators and cardiovascular diseases risk in pre-diabetic and diabetic adults: NHANES 1999–2018 cross-sectional analysis

Background

Since cardiovascular disease (CVD) stands as the primary cause of death in those with diabetes, and given the substantial influence of obesity as a common risk factor for both diabetes and atherosclerotic conditions, this investigation sought to find the relationship between anthropometric indicators and CVD risk within these populations.

Methods

Our study examined 36,329 adults, including those with diagnosed diabetes, pre-diabetes, and without diabetes from National Health and Nutrition Examination Survey (NHANES) data spanning 1999 to 2018. Various anthropometric indicators such as body mass index (BMI), waist circumference, weight-adjusted waist index (WWI), waist-to-height ratio (WHtR), weight, and height were assessed. Baseline characteristics were compared among the three groups after weighting. Participants were then grouped based on anthropometric indicators, and logistic regression models were used to analyze the association between these indicators and CVD risk in the total diabetes group (including diabetic and pre-diabetic individuals). Threshold effect analysis was conducted to explore nonlinear relationships, and mediation analyses assessed whether serum parameters influenced these relationships.

Results

This cross-sectional study involved 36,329 participants, weighted to a count of approximately 160.9 million, including over 45.9 million pre-diabetic individuals and around 16.6 million diabetic individuals. Baseline analysis showed significant associations between all six anthropometric indicators and CVD risk across patients with different diabetes statuses. Weighted restricted cubic spline (RCS) curve analysis highlighted increased CVD risk among the total diabetes group for each anthropometric indicator compared to the non-diabetic group. Anthropometric indicators were then divided into quartiles, and after adjusting for confounders, Model 3 revealed that the highest BMI group had a heightened risk of CVD compared to the lowest BMI group. Similar trends were observed in the WWI and WHtR subgroups. Threshold effect analysis of anthropometric indicators unveiled nonlinear associations between waist circumference, height, WWI and CVD risk. Mediation analysis suggested that lipid parameters, especially HDL, significantly mediated these relationships.

Conclusion

In individuals with diabetes and pre-diabetes, BMI, weight, and WHtR displayed a consistent, linear increase correlation with CVD risk. Conversely, the link between waist circumference, height, and WWI and CVD risk showcased a more complex, nonlinear pattern. Moreover, HDL level emerged as notable mediator in the association between anthropometric indicators and the risk of CVD.

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来源期刊
Experimental gerontology
Experimental gerontology Ageing, Biochemistry, Geriatrics and Gerontology
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