空勤人员
医学
人口
环境卫生
军事人员
肥胖
工作量
考试(生物学)
代谢综合征
星团(航天器)
人口学
内科学
航空学
工程类
地理
生物
计算机科学
古生物学
程序设计语言
考古
社会学
操作系统
作者
K G Kalff,P Maya-Pelzer,A Andexer,Heinz Jürgen Deuber
出处
期刊:PubMed
日期:1999-12-01
卷期号:70 (12): 1223-6
被引量:13
摘要
The metabolic syndrome (MS) affects 20-30% of the middle-aged population in highly industrialized countries, consisting of a cluster of diseases including obesity, hypertension, dyslipoproteinemia and glucose intolerance.If the population of flying personnel (FP) faces a high risk to develop MS, due to the specific workload of specialized aircrew, the consequences for aeromedical screening are to be reconsidered.Data of the complete military flying personnel (MFP) of Germany were screened to develop MS-related risk factors, regular physical activity and determination of nicotin and alcohol consumption. A comparable screening of a population of German civilian flying personnel (CFP) was undertaken by questionnaire. Statistics were completed by comparison of averages by t-test for independent random-samples of different variances and testing of independence of single characteristics by chi2-test.Data of approximately 10,000 aircrew members were obtained. It was possible to determine a group of MFP with higher risk to develop MS later in life, called "possible future metabolics" (PFM). Comparison of PFM with the MFP control group (MCG) and CFP clearly showed that obesity, dyslipoproteinemia and hypertension are the main single and/or combined risk factors. As a new aspect, data of MFP showed possible connections between thyroideal dysfunction and the prevalence of relevant MS-risk factors.The purpose of this investigation was to determine the actual risk of MS in German FP and to confirm the current MS-related regular screening measures. This study revealed that German MFP and CFP show a high quality health status without significant differences between both groups. Continuing the current regular flight medical screening will prevent FP from losing its high quality health status.
科研通智能强力驱动
Strongly Powered by AbleSci AI