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通过对三个数据源的分析确定在职人群中代谢综合征的患病率。

Prevalence of Metabolic Syndrome in an Employed Population as Determined by Analysis of Three Data Sources.

作者信息

Goetzel Ron Z, Kent Karen, Henke Rachel Mosher, Pack Cory, D'Arco Malinda, Thomas Jordana, Luckett James, Arthur-Hartranft Traci

机构信息

Institute for Health and Productivity Studies, Johns Hopkins Bloomberg School of Public Health, Baltimore (Drs Goetzel, Ms Kent); Truven Health Analytics, an IBM Company, Bethesda (Dr Goetzel, Dr Henke, Ms Pack, Ms D'Arco); and Lockheed Martin Corporation, Bethesda, Maryland (Ms Thomas, Mr Luckett, Dr Arthur-Hartranft).

出版信息

J Occup Environ Med. 2017 Feb;59(2):161-168. doi: 10.1097/JOM.0000000000000931.

Abstract

OBJECTIVE

The aim of this study was to compare estimates of the prevalence and incidence of metabolic syndrome (MetS) using various data sources.

METHODS

We integrated health risk assessment (HRA), claims, and biometric screening data from Lockheed Martin Corporation. We measured the extent to which MetS risk factors measured using HRA and medical claims correlated with biometric screening data.

RESULTS

Using biometric data, 24.9% of employees were identified as having MetS. Prevalence estimates were much lower using HRA data (6.8%) and claims (3.7%). Between 2012 and 2014, 10.4% of the sample newly acquired MetS. The number of MetS risk factors per employee was predictive of diabetes, heart disease, health care costs, and utilization.

CONCLUSION

MetS is prevalent and associated with progression to disease. It is more easily tracked with biometric screening data than with HRA or claims data. Employers should consider efforts to manage and prevent this condition in their workforce.

摘要

目的

本研究旨在比较使用各种数据源估算的代谢综合征(MetS)患病率和发病率。

方法

我们整合了洛克希德·马丁公司的健康风险评估(HRA)、理赔数据和生物特征筛查数据。我们测量了使用HRA和医疗理赔所测得的MetS风险因素与生物特征筛查数据之间的关联程度。

结果

使用生物特征数据,24.9%的员工被确定患有MetS。使用HRA数据(6.8%)和理赔数据(3.7%)估算的患病率要低得多。在2012年至2014年期间,10.4%的样本新患MetS。每名员工的MetS风险因素数量可预测糖尿病、心脏病、医疗保健成本和利用率。

结论

MetS很普遍,且与疾病进展相关。与HRA或理赔数据相比,生物特征筛查数据更容易追踪MetS。雇主应考虑采取措施管理和预防员工中的这种疾病。

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