Body composition estimates from bioelectrical impedance and its association with cardiovascular risk.

Jesne Kistan, Jeffrey Wing, Khanyisile Tshabalala, Wesley Van Hougenhouck-Tulleken, Debashis Basu
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Abstract

Background:  Screening for traditional risk factors of cardiovascular disease is well known in primary healthcare (PHC) settings. However, other risk factors through newer tools (such as bioelectrical impedance analysis [BIA]) could also be predictors of increased cardiovascular risk (CVR). Body composition estimates (body fat percentage, body water percentage, body lean mass) by BIA and its association to CVR have been studied with variable results.

Aim:  This study assesses the body composition estimates and their association with CVR in the South African PHC setting.

Methods:  A retrospective record analysis was conducted on a cohort of de-identified patients utilising the ABBY® Health Check Machine at a PHC facility in South Africa between May 2020 and August 2022. The ABBY Machine estimates body fat percentage (BF%) and body water percentage (BW%) estimates from BIA. Cardiovascular risk based on the Framingham-risk-score was stratified into high, medium and low CVR. An analysis of variance was used to determine mean differences of BF% and BW% among these groups.

Results:  A total of 4008 records (n = 4008) were used in the final analysis. The majority of patients were female (70.1%) with a mean age of 33.6 years. Higher mean BF% (35.75% vs. 31.10% vs. 27.73%; p  0.0001) and lower mean BW% (49.46% vs. 53.15% vs. 56.18%; p = 0000) were found to be significantly associated with high CVR.

Lessons learnt:  This study demonstrated the use of newer technologies that could assist in the identification of CVR in low resource PHC settings.

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通过生物电阻抗估计身体成分及其与心血管风险的关系。
背景: 在初级医疗保健(PHC)机构中,对心血管疾病传统风险因素的筛查是众所周知的。然而,通过较新工具(如生物电阻抗分析[BIA])检测其他风险因素也可预测心血管风险(CVR)的增加。目的:本研究评估了南非初级保健中心的身体成分估计值及其与心血管风险的关系: 对 2020 年 5 月至 2022 年 8 月期间在南非一家 PHC 机构使用 ABBY® 健康检查机的一组去身份化患者进行了回顾性记录分析。ABBY 机器通过 BIA 估算体脂率(BF%)和体水率(BW%)。根据弗雷明汉风险评分将心血管风险分为高、中、低三类。采用方差分析来确定这些组别的 BF% 和 BW% 的平均差异: 最终分析共使用了 4008 份记录(n = 4008)。大多数患者为女性(70.1%),平均年龄为 33.6 岁。发现较高的平均 BF% (35.75% vs. 31.10% vs. 27.73%; p 0.0001) 和较低的平均 BW% (49.46% vs. 53.15% vs. 56.18%; p = 0000) 与高 CVR 显著相关: 本研究表明,在资源匮乏的初级保健机构中,使用较新的技术有助于识别 CVR。
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来源期刊
CiteScore
3.30
自引率
10.00%
发文量
81
审稿时长
15 weeks
期刊最新文献
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