Life table methods for quantitative impact assessments in chronic mortality
Quantitative health impact assessments of chronic mortality, where the impacts are expected to be observed over a number of years, are complicated by the link between death rates and surviving populations. A general calculation framework for quantitative impact assessment is presented, based on stan...
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| Veröffentlicht in: | Journal of epidemiology and community health (1979) 2003-03, Vol.57 (3), p.200-206 |
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| container_end_page | 206 |
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| container_issue | 3 |
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| container_title | Journal of epidemiology and community health (1979) |
| container_volume | 57 |
| creator | Miller, B G Hurley, J F |
| description | Quantitative health impact assessments of chronic mortality, where the impacts are expected to be observed over a number of years, are complicated by the link between death rates and surviving populations. A general calculation framework for quantitative impact assessment is presented, based on standard life table calculation methods, which permits consistent future projections of impacts on mortality from changes in death rates. Implemented as a series of linked spreadsheets, the framework offers complete flexibility in the sex specific, age specific, and year specific patterns of baseline mortality death rates; in the predicted impacts upon these; in the weights or values placed on gains in life; and in the summary measures of impact. Impacts can be differential by cause of death. Some examples are given of predictions of the impacts of reductions in chronic mortality in the populations of England and Wales and of Scotland. |
| doi_str_mv | 10.1136/jech.57.3.200 |
| format | Article |
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A general calculation framework for quantitative impact assessment is presented, based on standard life table calculation methods, which permits consistent future projections of impacts on mortality from changes in death rates. Implemented as a series of linked spreadsheets, the framework offers complete flexibility in the sex specific, age specific, and year specific patterns of baseline mortality death rates; in the predicted impacts upon these; in the weights or values placed on gains in life; and in the summary measures of impact. Impacts can be differential by cause of death. Some examples are given of predictions of the impacts of reductions in chronic mortality in the populations of England and Wales and of Scotland.</description><identifier>ISSN: 0143-005X</identifier><identifier>EISSN: 1470-2738</identifier><identifier>DOI: 10.1136/jech.57.3.200</identifier><identifier>PMID: 12594196</identifier><identifier>CODEN: JECHDR</identifier><language>eng</language><publisher>London: BMJ Publishing Group Ltd</publisher><subject>Adolescent ; Adult ; Age ; Age groups ; Aged ; Aged, 80 and over ; Air pollution ; Biological and medical sciences ; Child ; Child, Preschool ; chronic mortality ; Death ; Economic value ; Epidemiology ; Estimates ; Female ; Flexibility ; Forecasting ; Forecasts and trends ; General aspects ; Health aspects ; Health hazards ; health impact assessment ; Humans ; Infant ; Infant, Newborn ; Life Expectancy ; life table calculations ; Life Tables ; Long term ; Male ; Medical sciences ; Mens health ; Methodology ; Methods ; Middle Aged ; Mortality ; Population estimates ; Probability ; Proportional Hazards Models ; Public health. 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Hygiene-occupational medicine ; Sex Distribution ; Spreadsheets ; Statistics ; Survival Analysis ; Survival Rate ; Theory and Methods ; United Kingdom ; United Kingdom - epidemiology ; Women</subject><ispartof>Journal of epidemiology and community health (1979), 2003-03, Vol.57 (3), p.200-206</ispartof><rights>Copyright 2003 Journal of Epidemiology and Community Health</rights><rights>2003 INIST-CNRS</rights><rights>COPYRIGHT 2003 BMJ Publishing Group Ltd.</rights><rights>Copyright: 2003 Copyright 2003 Journal of Epidemiology and Community Health</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-b609t-bd38601abfebabc4cda5dcc75c73124ebc448a0e8a0d996277586e9839a479dd3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/25569960$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/25569960$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>230,314,723,776,780,799,881,27903,27904,53769,53771,57995,58228</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=14530988$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/12594196$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Miller, B G</creatorcontrib><creatorcontrib>Hurley, J F</creatorcontrib><title>Life table methods for quantitative impact assessments in chronic mortality</title><title>Journal of epidemiology and community health (1979)</title><addtitle>J Epidemiol Community Health</addtitle><description>Quantitative health impact assessments of chronic mortality, where the impacts are expected to be observed over a number of years, are complicated by the link between death rates and surviving populations. A general calculation framework for quantitative impact assessment is presented, based on standard life table calculation methods, which permits consistent future projections of impacts on mortality from changes in death rates. Implemented as a series of linked spreadsheets, the framework offers complete flexibility in the sex specific, age specific, and year specific patterns of baseline mortality death rates; in the predicted impacts upon these; in the weights or values placed on gains in life; and in the summary measures of impact. Impacts can be differential by cause of death. Some examples are given of predictions of the impacts of reductions in chronic mortality in the populations of England and Wales and of Scotland.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Age</subject><subject>Age groups</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Air pollution</subject><subject>Biological and medical sciences</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>chronic mortality</subject><subject>Death</subject><subject>Economic value</subject><subject>Epidemiology</subject><subject>Estimates</subject><subject>Female</subject><subject>Flexibility</subject><subject>Forecasting</subject><subject>Forecasts and trends</subject><subject>General aspects</subject><subject>Health aspects</subject><subject>Health hazards</subject><subject>health impact assessment</subject><subject>Humans</subject><subject>Infant</subject><subject>Infant, Newborn</subject><subject>Life Expectancy</subject><subject>life table calculations</subject><subject>Life Tables</subject><subject>Long term</subject><subject>Male</subject><subject>Medical sciences</subject><subject>Mens health</subject><subject>Methodology</subject><subject>Methods</subject><subject>Middle Aged</subject><subject>Mortality</subject><subject>Population estimates</subject><subject>Probability</subject><subject>Proportional Hazards Models</subject><subject>Public health. Hygiene</subject><subject>Public health. Hygiene-occupational medicine</subject><subject>Sex Distribution</subject><subject>Spreadsheets</subject><subject>Statistics</subject><subject>Survival Analysis</subject><subject>Survival Rate</subject><subject>Theory and Methods</subject><subject>United Kingdom</subject><subject>United Kingdom - epidemiology</subject><subject>Women</subject><issn>0143-005X</issn><issn>1470-2738</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2003</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqFktGL1DAQxoso3nr66KNSEMUHuyZN0jQvwrGoJy6ncKf4FtJ0upu1TfaS9PD-e1N22VURJYSEmR_fzJdMlj3GaI4xqV5vQK_njM_JvEToTjbDlKOi5KS-m80QpqRAiH07yR6EsEHpyktxPzvBJRMUi2qWfVyaDvKomh7yAeLatSHvnM-vR2WjiSqaG8jNsFU65ioECGEAG0NubK7X3lmj88H5qHoTbx9m9zrVB3i0P0-zL-_eXi3Oi-Wn9x8WZ8uiqZCIRdOSukJYNR00qtFUt4q1WnOmOcElhRSitUKQditEVXLO6gpETYSiXLQtOc3e7HS3YzNAq1NDXvVy682g_K10ysjfM9as5crdSMxJSQRJAi_2At5djxCiHEzQ0PfKghuD5AQRWpV1Ap_9AW7c6G0yl7S4KBHmdKJe7aiV6kEa27lUVa_AQiruLHQmhc9EMl1xNOHFX_C0WhiM_gevvQvBQ3dwipGcZkBOMyAZl0SmGUj801-f50jvPz0Bz_eAClr1nVdWm3DkKCNI1FPhJztuE6Lzh3zJWJX-BR0bMyHCj0Ne-e-y4oQzefF1Ic_p1Wd-eXEpWeJf7vhm2PzHw0-VSeE_</recordid><startdate>20030301</startdate><enddate>20030301</enddate><creator>Miller, B G</creator><creator>Hurley, J F</creator><general>BMJ Publishing Group Ltd</general><general>BMJ Publishing Group</general><general>BMJ</general><general>BMJ Publishing Group LTD</general><general>BMJ Group</general><scope>BSCLL</scope><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>88I</scope><scope>8AF</scope><scope>8C1</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AN0</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BTHHO</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>M2P</scope><scope>M7P</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20030301</creationdate><title>Life table methods for quantitative impact assessments in chronic mortality</title><author>Miller, B G ; Hurley, J F</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-b609t-bd38601abfebabc4cda5dcc75c73124ebc448a0e8a0d996277586e9839a479dd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Adolescent</topic><topic>Adult</topic><topic>Age</topic><topic>Age groups</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Air pollution</topic><topic>Biological and medical sciences</topic><topic>Child</topic><topic>Child, Preschool</topic><topic>chronic mortality</topic><topic>Death</topic><topic>Economic value</topic><topic>Epidemiology</topic><topic>Estimates</topic><topic>Female</topic><topic>Flexibility</topic><topic>Forecasting</topic><topic>Forecasts and trends</topic><topic>General aspects</topic><topic>Health aspects</topic><topic>Health hazards</topic><topic>health impact assessment</topic><topic>Humans</topic><topic>Infant</topic><topic>Infant, Newborn</topic><topic>Life Expectancy</topic><topic>life table calculations</topic><topic>Life Tables</topic><topic>Long term</topic><topic>Male</topic><topic>Medical sciences</topic><topic>Mens health</topic><topic>Methodology</topic><topic>Methods</topic><topic>Middle Aged</topic><topic>Mortality</topic><topic>Population estimates</topic><topic>Probability</topic><topic>Proportional Hazards Models</topic><topic>Public health. Hygiene</topic><topic>Public health. Hygiene-occupational medicine</topic><topic>Sex Distribution</topic><topic>Spreadsheets</topic><topic>Statistics</topic><topic>Survival Analysis</topic><topic>Survival Rate</topic><topic>Theory and Methods</topic><topic>United Kingdom</topic><topic>United Kingdom - epidemiology</topic><topic>Women</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Miller, B G</creatorcontrib><creatorcontrib>Hurley, J F</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Proquest Nursing & Allied Health Source</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>Science Database (Alumni Edition)</collection><collection>STEM Database</collection><collection>Public Health Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>British Nursing Database</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection (ProQuest)</collection><collection>BMJ Journals</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest Psychology</collection><collection>Science Database</collection><collection>Biological Science Database</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of epidemiology and community health (1979)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Miller, B G</au><au>Hurley, J F</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Life table methods for quantitative impact assessments in chronic mortality</atitle><jtitle>Journal of epidemiology and community health (1979)</jtitle><addtitle>J Epidemiol Community Health</addtitle><date>2003-03-01</date><risdate>2003</risdate><volume>57</volume><issue>3</issue><spage>200</spage><epage>206</epage><pages>200-206</pages><issn>0143-005X</issn><eissn>1470-2738</eissn><coden>JECHDR</coden><abstract>Quantitative health impact assessments of chronic mortality, where the impacts are expected to be observed over a number of years, are complicated by the link between death rates and surviving populations. A general calculation framework for quantitative impact assessment is presented, based on standard life table calculation methods, which permits consistent future projections of impacts on mortality from changes in death rates. Implemented as a series of linked spreadsheets, the framework offers complete flexibility in the sex specific, age specific, and year specific patterns of baseline mortality death rates; in the predicted impacts upon these; in the weights or values placed on gains in life; and in the summary measures of impact. Impacts can be differential by cause of death. Some examples are given of predictions of the impacts of reductions in chronic mortality in the populations of England and Wales and of Scotland.</abstract><cop>London</cop><pub>BMJ Publishing Group Ltd</pub><pmid>12594196</pmid><doi>10.1136/jech.57.3.200</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Journal of epidemiology and community health (1979), 2003-03, Vol.57 (3), p.200-206 |
| issn | 0143-005X 1470-2738 |
| language | eng |
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| source | MEDLINE; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Jstor Complete Legacy; PubMed Central; Alma/SFX Local Collection |
| subjects | Adolescent Adult Age Age groups Aged Aged, 80 and over Air pollution Biological and medical sciences Child Child, Preschool chronic mortality Death Economic value Epidemiology Estimates Female Flexibility Forecasting Forecasts and trends General aspects Health aspects Health hazards health impact assessment Humans Infant Infant, Newborn Life Expectancy life table calculations Life Tables Long term Male Medical sciences Mens health Methodology Methods Middle Aged Mortality Population estimates Probability Proportional Hazards Models Public health. Hygiene Public health. Hygiene-occupational medicine Sex Distribution Spreadsheets Statistics Survival Analysis Survival Rate Theory and Methods United Kingdom United Kingdom - epidemiology Women |
| title | Life table methods for quantitative impact assessments in chronic mortality |
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