Illness Absence Patterns Among Employees in a Petrochemical Facility: Impact of Selected Health Risk Factors
Background: Illness absence in a working population is a complex phenomenon and can be influenced by many factors, such as age, gender, and personal health nsk factors. The current study used prospectively collected employee health nsk and morbidity data to examine illness absence patterns for a wor...
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Veröffentlicht in: | Journal of occupational and environmental medicine 2005-08, Vol.47 (8), p.838-846 |
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creator | Tsai, Shan P. Wendt, Judy K. Ahmed, Farah S. Donnelly, Robin P. Strawmyer, Thomas R. |
description | Background: Illness absence in a working population is a complex phenomenon and can be influenced by many factors, such as age, gender, and personal health nsk factors. The current study used prospectively collected employee health nsk and morbidity data to examine illness absence patterns for a working population and to quantify the impact of selected health nsk factors on employee illness absence. Methods: The study population consisted of 2550 regular employees working at a Texas petrochemical facility. Morbidity data were extracted from the company's Health Surveillance System, and records of absences were derived from personnel and payroll systems. The morbidity frequency rate and average duration of absence per employee per year were calculated by age, gender, and selected health risk factors, including smoking, body mass index, cholesterol, triglycérides, hypertension, and fasting glucose. Results. Morbidity frequency rates and average duration of absence increased with age and with the presence of health risk factors. The absence frequency rate increased with an increase in the number of risk factors present from no risk factors (11.8 per 100 employees) to four or more risk factors (32.3 per 100 employees). The number of workdays lost also increased with the number of risk factors present, with the least number of workdays lost by employees with zero risk factors (4.1 day), followed by one (6.4 days), two (8.8 days), three (9.3 days), and four or more risk factors (12.6 days). Conclusions: The impact of employee health risk factors has been shown in this study to be associated with absence frequency and duration of absence. Reduction in employee health risk factors can be an effective means of improving employees' health and increasing a company's productivity. |
doi_str_mv | 10.1097/01.jom.0000169091.28589.8a |
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The current study used prospectively collected employee health nsk and morbidity data to examine illness absence patterns for a working population and to quantify the impact of selected health nsk factors on employee illness absence. Methods: The study population consisted of 2550 regular employees working at a Texas petrochemical facility. Morbidity data were extracted from the company's Health Surveillance System, and records of absences were derived from personnel and payroll systems. The morbidity frequency rate and average duration of absence per employee per year were calculated by age, gender, and selected health risk factors, including smoking, body mass index, cholesterol, triglycérides, hypertension, and fasting glucose. Results. Morbidity frequency rates and average duration of absence increased with age and with the presence of health risk factors. The absence frequency rate increased with an increase in the number of risk factors present from no risk factors (11.8 per 100 employees) to four or more risk factors (32.3 per 100 employees). The number of workdays lost also increased with the number of risk factors present, with the least number of workdays lost by employees with zero risk factors (4.1 day), followed by one (6.4 days), two (8.8 days), three (9.3 days), and four or more risk factors (12.6 days). Conclusions: The impact of employee health risk factors has been shown in this study to be associated with absence frequency and duration of absence. Reduction in employee health risk factors can be an effective means of improving employees' health and increasing a company's productivity.</description><identifier>ISSN: 1076-2752</identifier><identifier>EISSN: 1536-5948</identifier><identifier>DOI: 10.1097/01.jom.0000169091.28589.8a</identifier><identifier>PMID: 16093934</identifier><identifier>CODEN: JOEMFM</identifier><language>eng</language><publisher>Hagerstown, MD: Lippincott Williams & Wilkins</publisher><subject>Absenteeism ; Adolescent ; Adult ; Age Factors ; Aged ; Biological and medical sciences ; Blood Glucose - analysis ; Chemical Industry - manpower ; Comorbidity ; Correlation analysis ; Databases, Factual ; Female ; Health risk assessment ; Health Status Indicators ; Humans ; Hypertension - epidemiology ; Illnesses ; Male ; Medical sciences ; Middle Aged ; Miscellaneous ; Occupational Health - statistics & numerical data ; Occupational medicine ; ORIGINAL ARTICLES ; Petrochemicals ; Petroleum ; Productivity ; Public health. Hygiene-occupational medicine ; Risk Factors ; Sentinel Surveillance ; Sex Distribution ; Sick Leave - statistics & numerical data ; Smoking Cessation - statistics & numerical data ; Texas - epidemiology</subject><ispartof>Journal of occupational and environmental medicine, 2005-08, Vol.47 (8), p.838-846</ispartof><rights>Copyright © 2005 American College of Occupational and Environmental Medicine</rights><rights>2005The American College of Occupational and Environmental Medicine</rights><rights>2005 INIST-CNRS</rights><rights>Copyright Lippincott Williams & Wilkins Aug 2005</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/44997467$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/44997467$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,776,780,799,27901,27902,57992,58225</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=17051233$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/16093934$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Tsai, Shan P.</creatorcontrib><creatorcontrib>Wendt, Judy K.</creatorcontrib><creatorcontrib>Ahmed, Farah S.</creatorcontrib><creatorcontrib>Donnelly, Robin P.</creatorcontrib><creatorcontrib>Strawmyer, Thomas R.</creatorcontrib><title>Illness Absence Patterns Among Employees in a Petrochemical Facility: Impact of Selected Health Risk Factors</title><title>Journal of occupational and environmental medicine</title><addtitle>J Occup Environ Med</addtitle><description>Background: Illness absence in a working population is a complex phenomenon and can be influenced by many factors, such as age, gender, and personal health nsk factors. The current study used prospectively collected employee health nsk and morbidity data to examine illness absence patterns for a working population and to quantify the impact of selected health nsk factors on employee illness absence. Methods: The study population consisted of 2550 regular employees working at a Texas petrochemical facility. Morbidity data were extracted from the company's Health Surveillance System, and records of absences were derived from personnel and payroll systems. The morbidity frequency rate and average duration of absence per employee per year were calculated by age, gender, and selected health risk factors, including smoking, body mass index, cholesterol, triglycérides, hypertension, and fasting glucose. Results. Morbidity frequency rates and average duration of absence increased with age and with the presence of health risk factors. The absence frequency rate increased with an increase in the number of risk factors present from no risk factors (11.8 per 100 employees) to four or more risk factors (32.3 per 100 employees). The number of workdays lost also increased with the number of risk factors present, with the least number of workdays lost by employees with zero risk factors (4.1 day), followed by one (6.4 days), two (8.8 days), three (9.3 days), and four or more risk factors (12.6 days). Conclusions: The impact of employee health risk factors has been shown in this study to be associated with absence frequency and duration of absence. Reduction in employee health risk factors can be an effective means of improving employees' health and increasing a company's productivity.</description><subject>Absenteeism</subject><subject>Adolescent</subject><subject>Adult</subject><subject>Age Factors</subject><subject>Aged</subject><subject>Biological and medical sciences</subject><subject>Blood Glucose - analysis</subject><subject>Chemical Industry - manpower</subject><subject>Comorbidity</subject><subject>Correlation analysis</subject><subject>Databases, Factual</subject><subject>Female</subject><subject>Health risk assessment</subject><subject>Health Status Indicators</subject><subject>Humans</subject><subject>Hypertension - epidemiology</subject><subject>Illnesses</subject><subject>Male</subject><subject>Medical sciences</subject><subject>Middle Aged</subject><subject>Miscellaneous</subject><subject>Occupational Health - statistics & numerical data</subject><subject>Occupational medicine</subject><subject>ORIGINAL ARTICLES</subject><subject>Petrochemicals</subject><subject>Petroleum</subject><subject>Productivity</subject><subject>Public health. Hygiene-occupational medicine</subject><subject>Risk Factors</subject><subject>Sentinel Surveillance</subject><subject>Sex Distribution</subject><subject>Sick Leave - statistics & numerical data</subject><subject>Smoking Cessation - statistics & numerical data</subject><subject>Texas - epidemiology</subject><issn>1076-2752</issn><issn>1536-5948</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkltv1DAQhSMEoqXwE0BWpfKW4PuFt6pq6UqVqLg8R44zYZM68RJnVe2_Z5ZdQOKlfrHH-makc84UxTmjFaPOfKCsGtJYUTxMO-pYxa2yrrL-WXHKlNClctI-xzc1uuRG8ZPiVc4D4opR9bI4YZo64YQ8LeIqxglyJpdNhikAuffLAvOEH2OafpDrcRPTDiCTfiKe3MMyp7CGsQ8-khsf-tgvu49kNW58WEjqyFeIEBZoyS34uKzJlz4_7MElzfl18aLzMcOb431WfL-5_nZ1W959_rS6urwrB-EULW3oaNcpq4VFAQ3XLcr0vKPUCguhcUp1SrZNowFki7UB1QglWWugkUGIs-L9Ye5mTj-3kJd67HOAGP0EaZtrbaVWgponQe7QX4bsUyAzmjLmOILn_4FD2s4Tqq0549oJzRhC747QthmhrTdzP_p5V_-JBYGLI-AzGt3Nfgp9_scZqhgXe6HywD2miKnlh7h9hLle_7a-xv2QwmhZckoVtViW-5Wh2Pb20DZkjOXvWCmdM1Ib8QtmHLaR</recordid><startdate>200508</startdate><enddate>200508</enddate><creator>Tsai, Shan P.</creator><creator>Wendt, Judy K.</creator><creator>Ahmed, Farah S.</creator><creator>Donnelly, Robin P.</creator><creator>Strawmyer, Thomas R.</creator><general>Lippincott Williams & Wilkins</general><general>The American College of Occupational and Environmental Medicine</general><general>Lippincott Williams & Wilkins Ovid Technologies</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>7T2</scope><scope>7U7</scope><scope>7U9</scope><scope>C1K</scope><scope>H94</scope><scope>K9.</scope><scope>7U1</scope><scope>7U2</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope><scope>7X8</scope></search><sort><creationdate>200508</creationdate><title>Illness Absence Patterns Among Employees in a Petrochemical Facility: Impact of Selected Health Risk Factors</title><author>Tsai, Shan P. ; Wendt, Judy K. ; Ahmed, Farah S. ; Donnelly, Robin P. ; Strawmyer, Thomas R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-j3950-8cf0ff58638076b26d169a2f00838ecb955f54dbb6ee4dcb97e5b3541d7eb4c33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Absenteeism</topic><topic>Adolescent</topic><topic>Adult</topic><topic>Age Factors</topic><topic>Aged</topic><topic>Biological and medical sciences</topic><topic>Blood Glucose - analysis</topic><topic>Chemical Industry - manpower</topic><topic>Comorbidity</topic><topic>Correlation analysis</topic><topic>Databases, Factual</topic><topic>Female</topic><topic>Health risk assessment</topic><topic>Health Status Indicators</topic><topic>Humans</topic><topic>Hypertension - epidemiology</topic><topic>Illnesses</topic><topic>Male</topic><topic>Medical sciences</topic><topic>Middle Aged</topic><topic>Miscellaneous</topic><topic>Occupational Health - statistics & numerical data</topic><topic>Occupational medicine</topic><topic>ORIGINAL ARTICLES</topic><topic>Petrochemicals</topic><topic>Petroleum</topic><topic>Productivity</topic><topic>Public health. Hygiene-occupational medicine</topic><topic>Risk Factors</topic><topic>Sentinel Surveillance</topic><topic>Sex Distribution</topic><topic>Sick Leave - statistics & numerical data</topic><topic>Smoking Cessation - statistics & numerical data</topic><topic>Texas - epidemiology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tsai, Shan P.</creatorcontrib><creatorcontrib>Wendt, Judy K.</creatorcontrib><creatorcontrib>Ahmed, Farah S.</creatorcontrib><creatorcontrib>Donnelly, Robin P.</creatorcontrib><creatorcontrib>Strawmyer, Thomas R.</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Toxicology Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Risk Abstracts</collection><collection>Safety Science and Risk</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of occupational and environmental medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tsai, Shan P.</au><au>Wendt, Judy K.</au><au>Ahmed, Farah S.</au><au>Donnelly, Robin P.</au><au>Strawmyer, Thomas R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Illness Absence Patterns Among Employees in a Petrochemical Facility: Impact of Selected Health Risk Factors</atitle><jtitle>Journal of occupational and environmental medicine</jtitle><addtitle>J Occup Environ Med</addtitle><date>2005-08</date><risdate>2005</risdate><volume>47</volume><issue>8</issue><spage>838</spage><epage>846</epage><pages>838-846</pages><issn>1076-2752</issn><eissn>1536-5948</eissn><coden>JOEMFM</coden><abstract>Background: Illness absence in a working population is a complex phenomenon and can be influenced by many factors, such as age, gender, and personal health nsk factors. The current study used prospectively collected employee health nsk and morbidity data to examine illness absence patterns for a working population and to quantify the impact of selected health nsk factors on employee illness absence. Methods: The study population consisted of 2550 regular employees working at a Texas petrochemical facility. Morbidity data were extracted from the company's Health Surveillance System, and records of absences were derived from personnel and payroll systems. The morbidity frequency rate and average duration of absence per employee per year were calculated by age, gender, and selected health risk factors, including smoking, body mass index, cholesterol, triglycérides, hypertension, and fasting glucose. Results. Morbidity frequency rates and average duration of absence increased with age and with the presence of health risk factors. The absence frequency rate increased with an increase in the number of risk factors present from no risk factors (11.8 per 100 employees) to four or more risk factors (32.3 per 100 employees). The number of workdays lost also increased with the number of risk factors present, with the least number of workdays lost by employees with zero risk factors (4.1 day), followed by one (6.4 days), two (8.8 days), three (9.3 days), and four or more risk factors (12.6 days). Conclusions: The impact of employee health risk factors has been shown in this study to be associated with absence frequency and duration of absence. Reduction in employee health risk factors can be an effective means of improving employees' health and increasing a company's productivity.</abstract><cop>Hagerstown, MD</cop><pub>Lippincott Williams & Wilkins</pub><pmid>16093934</pmid><doi>10.1097/01.jom.0000169091.28589.8a</doi><tpages>9</tpages></addata></record> |
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subjects | Absenteeism Adolescent Adult Age Factors Aged Biological and medical sciences Blood Glucose - analysis Chemical Industry - manpower Comorbidity Correlation analysis Databases, Factual Female Health risk assessment Health Status Indicators Humans Hypertension - epidemiology Illnesses Male Medical sciences Middle Aged Miscellaneous Occupational Health - statistics & numerical data Occupational medicine ORIGINAL ARTICLES Petrochemicals Petroleum Productivity Public health. Hygiene-occupational medicine Risk Factors Sentinel Surveillance Sex Distribution Sick Leave - statistics & numerical data Smoking Cessation - statistics & numerical data Texas - epidemiology |
title | Illness Absence Patterns Among Employees in a Petrochemical Facility: Impact of Selected Health Risk Factors |
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