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机械加工企业噪声从业人员高血压患病率及其影响因素
引用本文:庞力娟,陈立章,付本燕.机械加工企业噪声从业人员高血压患病率及其影响因素[J].中南大学学报(医学版),2005,30(3):276-279.
作者姓名:庞力娟  陈立章  付本燕
作者单位:中南大学公共卫生学院,长沙,410078;岳阳职业技术学院,岳阳,414200
摘    要:目的:探讨机械加工企业噪声从业人员高血压患病情况及其影响因素,为预防和减少高血压病提供科学依据。方法:对噪声作业现场进行现场噪声测定,对噪声从业人员进行现场问卷调查,对其高血压患病率及影响因素进行分析。结果:噪声从业人员高血压患病率为12.1%。非条件logistic回归分析结果表明,年龄、体质量指数、高血压家族史、饮酒、经常食用咸鱼和累积噪声暴露量是噪声从业人员高血压患病的主要影响因素。结论:控制体质量、戒酒、降低从业人员的噪声暴露及提倡健康饮食,可以降低机械加工企业噪声从业人员的高血压患病率。

关 键 词:噪声  logistic回归模型  高血压
文章编号:1672-7347(2005)03-0276-04
收稿时间:2004-11-10
修稿时间:2004年11月10

Prevalence and influence factors of hypertension among mechanic factory workers
PANG Li-juan,CHEN Li-zhang,FU Ben-yan.Prevalence and influence factors of hypertension among mechanic factory workers[J].Journal of Central South University (Medical Sciences)Journal of Central South University (Medical Sciences),2005,30(3):276-279.
Authors:PANG Li-juan  CHEN Li-zhang  FU Ben-yan
Institution:1.School of Public Health, Central South University, Changsha 410078, China; 2.Yueyang Professional Technology College ,Yueyang 414200,China
Abstract:OBJECTIVE: To determine the status and influence factors of hypertension on mechanic factory workers and to provide reference for further hypertension prevention and control. METHODS: A cross-sectional study on 1205 workers (exposed to different noise levels) in Hunan was carried out by using questionaire and measuring the blood pressure of the workers and the noise exposure level in the workplace. The prevalence and the influence factors of hypertension among mechanic factory workers were analysed. RESULTS: The hypertension prevalence was 12.1%. Logistic regression analysis showed the body weight index (BMI), age, and history of hypertension in parents and accumulative noise dose levels influenced the hypertension prevalence. CONCLUSION: Controlling the body weight, reducing alcohol consumption, decreasing the sound pressure level in workshops and advocating healthy diet may reduce the prevalence rate of hypertension among mechanic factory workers.
Keywords:noise  logistic regression model  hypertension
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