Ethnic-Specific Threshold Analysis and BMI and Waist Circumference Cutoffs for Cardiovascular Disease and Subjective Wellbeing: Results using Data from the UK Biobank.

IF 3.2 3区医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Journal of Racial and Ethnic Health Disparities Pub Date : 2024-10-11 DOI:10.1007/s40615-024-02193-9

Mubarak Patel, Mohammed Aadil Buchya, Olalekan Uthman

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引用次数: 0

Abstract

Objectives: We aimed to identify ethnicity-specific BMI and waist circumference cutoffs for cardiovascular disease (CVD) and to define optimal thresholds for CVD risk and subjective wellbeing (SWB) through predictive modelling, to inform precise public health initiatives.

Methods: We used data from 296,767 UK Biobank participants and adjusted logistic and linear regression models for CVD and SWB, respectively, complemented by receiver operating characteristic analysis, to explore optimal risk thresholds of CVD in six different ethnic groups and to calculate ethnicity-specific cutoffs of BMI and waist circumference (WC) to further elucidate the relationships between demographic factors and cardiovascular risk among diverse populations.

Results: The logistic regression model of CVD revealed moderate discriminative ability (AUROC ~ 64-65%) across ethnicities for CVD status, with sensitivity and specificity values indicating the model's predictive accuracy. For SWB, the model demonstrated moderate performance with an AUROC of 63%, supported by significant variables that included age, BMI, WC, physical activity, and alcohol intake. Adjusted-incidence rates of CVD revealed the evidence ethnic-specific CVD risk profiles with Whites, South Asians and Blacks demonstrating higher predicted CVD events compared to East Asians, mixed and other ethnic groups.

Conclusion: Alterations of ethnicity-specific BMI and waist circumference are required to ensure ethnic minorities are provided with proper mitigation of cardiovascular risk, addressing the disparities observed in CVD prevalence and outcomes across diverse populations. This tailored approach to risk assessment can facilitate early detection, intervention and management of CVD, ultimately improving health outcomes and promoting health equity. The moderate accuracy of predictive models underscores the need for further research to identify additional variables that may enhance predictive accuracy and refine risk assessment strategies.

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针对心血管疾病和主观幸福感的特定种族阈值分析及体重指数和腰围临界值：使用英国生物库数据得出的结果。

目标：我们旨在确定特定种族的心血管疾病（CVD）BMI 和腰围临界值，并通过预测建模确定心血管疾病风险和主观幸福感（SWB）的最佳阈值，为精确的公共卫生措施提供信息：我们利用 296,767 名英国生物库参与者的数据，分别针对心血管疾病和主观幸福感建立了调整后的逻辑回归模型和线性回归模型，并辅以接受者操作特征分析，以探索六个不同种族群体的最佳心血管疾病风险阈值，并计算出特定种族的体重指数和腰围临界值，从而进一步阐明不同人群中人口因素与心血管疾病风险之间的关系：心血管疾病的逻辑回归模型显示了不同种族对心血管疾病状态的中等辨别能力（AUROC ~ 64-65%），灵敏度和特异性值显示了模型的预测准确性。就腰围而言，该模型表现中等，AUROC 为 63%，得到了年龄、体重指数（BMI）、腹围、体力活动和酒精摄入量等重要变量的支持。调整后的心血管疾病发病率显示了特定种族的心血管疾病风险特征，与东亚人、混血人和其他种族相比，白人、南亚人和黑人的预测心血管疾病发病率更高：结论：需要改变特定种族的体重指数和腰围，以确保为少数民族提供适当的心血管风险缓解措施，解决在不同人群中观察到的心血管疾病发病率和结果差异。这种量身定制的风险评估方法可促进心血管疾病的早期发现、干预和管理，最终改善健康结果并促进健康公平。预测模型的准确性一般，这强调了进一步研究的必要性，以确定可提高预测准确性和完善风险评估策略的其他变量。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Racial and Ethnic Health Disparities PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-

CiteScore

7.30

自引率

5.10%

发文量

263

期刊介绍： Journal of Racial and Ethnic Health Disparities reports on the scholarly progress of work to understand, address, and ultimately eliminate health disparities based on race and ethnicity. Efforts to explore underlying causes of health disparities and to describe interventions that have been undertaken to address racial and ethnic health disparities are featured. Promising studies that are ongoing or studies that have longer term data are welcome, as are studies that serve as lessons for best practices in eliminating health disparities. Original research, systematic reviews, and commentaries presenting the state-of-the-art thinking on problems centered on health disparities will be considered for publication. We particularly encourage review articles that generate innovative and testable ideas, and constructive discussions and/or critiques of health disparities.Because the Journal of Racial and Ethnic Health Disparities receives a large number of submissions, about 30% of submissions to the Journal are sent out for full peer review.