Assessing adult mortality in HIV-1-afflicted Zimbabwe (1998 -2003).
Identifieur interne : 000B63 ( Pmc/Corpus ); précédent : 000B62; suivant : 000B64Assessing adult mortality in HIV-1-afflicted Zimbabwe (1998 -2003).
Auteurs : Ben A. Lopman ; Ruanne Barnabas ; Timothy B. Hallett ; Constance Nyamukapa ; Costa Mundandi ; Phyllis Mushati ; Geoff P. Garnett ; Simon GregsonSource :
- Bulletin of the World Health Organization [ 0042-9686 ] ; 2006.
Abstract
OBJECTIVE: To compare alternative methods to vital registration systems for estimating adult mortality, and describe patterns of mortality in Manicaland, Zimbabwe, which has been severely affected by HIV. METHODS: We compared estimates of adult mortality from (1) a single question on household mortality, (2) repeated household censuses, and (3) an adult cohort study with linked HIV testing from Manicaland, with a mathematical model fitted to local age-specific HIV prevalence (1998 -2000). FINDINGS: The crude death rate from the single question (29 per 1000 person-years) was roughly consistent with that from the mathematical model (22 -25 per 1000 person-years), but much higher than that from the household censuses (12 per 1000 person-years). Adult mortality in the household censuses (males 0.65; females 0.51) was lower than in the cohort study (males 0.77; females 0.57), while mathematical models gave a much higher estimate, especially for females (males 0.80 -0.83; females 0.75 -0.80). The population attributable fraction of adult deaths due to HIV was 0.61 for men and 0.70 for women, with life expectancy estimated to be 34.3 years for males and 38.2 years for females. CONCLUSION: Each method for estimating adult mortality had limitations in terms of loss to follow-up (cohort study), under-ascertainment (household censuses), transparency of underlying processes (single question), and sensitivity to parameterization (mathematical model). However, these analyses make clear the advantages of longitudinal cohort data, which provide more complete ascertainment than household censuses, highlight possible inaccuracies in model assumptions, and allow direct quantification of the impact of HIV.
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PubMed: 16583077
PubMed Central: 1808347
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Assessing adult mortality in HIV-1-afflicted Zimbabwe (1998 -2003).</title><author><name sortKey="Lopman, Ben A" sort="Lopman, Ben A" uniqKey="Lopman B" first="Ben A." last="Lopman">Ben A. Lopman</name></author><author><name sortKey="Barnabas, Ruanne" sort="Barnabas, Ruanne" uniqKey="Barnabas R" first="Ruanne" last="Barnabas">Ruanne Barnabas</name></author><author><name sortKey="Hallett, Timothy B" sort="Hallett, Timothy B" uniqKey="Hallett T" first="Timothy B." last="Hallett">Timothy B. Hallett</name></author><author><name sortKey="Nyamukapa, Constance" sort="Nyamukapa, Constance" uniqKey="Nyamukapa C" first="Constance" last="Nyamukapa">Constance Nyamukapa</name></author><author><name sortKey="Mundandi, Costa" sort="Mundandi, Costa" uniqKey="Mundandi C" first="Costa" last="Mundandi">Costa Mundandi</name></author><author><name sortKey="Mushati, Phyllis" sort="Mushati, Phyllis" uniqKey="Mushati P" first="Phyllis" last="Mushati">Phyllis Mushati</name></author><author><name sortKey="Garnett, Geoff P" sort="Garnett, Geoff P" uniqKey="Garnett G" first="Geoff P." last="Garnett">Geoff P. Garnett</name></author><author><name sortKey="Gregson, Simon" sort="Gregson, Simon" uniqKey="Gregson S" first="Simon" last="Gregson">Simon Gregson</name></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">16583077</idno><idno type="pmc">1808347</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1808347</idno><idno type="RBID">PMC:1808347</idno><date when="2006">2006</date><idno type="wicri:Area/Pmc/Corpus">000B63</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000B63</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Assessing adult mortality in HIV-1-afflicted Zimbabwe (1998 -2003).</title><author><name sortKey="Lopman, Ben A" sort="Lopman, Ben A" uniqKey="Lopman B" first="Ben A." last="Lopman">Ben A. Lopman</name></author><author><name sortKey="Barnabas, Ruanne" sort="Barnabas, Ruanne" uniqKey="Barnabas R" first="Ruanne" last="Barnabas">Ruanne Barnabas</name></author><author><name sortKey="Hallett, Timothy B" sort="Hallett, Timothy B" uniqKey="Hallett T" first="Timothy B." last="Hallett">Timothy B. Hallett</name></author><author><name sortKey="Nyamukapa, Constance" sort="Nyamukapa, Constance" uniqKey="Nyamukapa C" first="Constance" last="Nyamukapa">Constance Nyamukapa</name></author><author><name sortKey="Mundandi, Costa" sort="Mundandi, Costa" uniqKey="Mundandi C" first="Costa" last="Mundandi">Costa Mundandi</name></author><author><name sortKey="Mushati, Phyllis" sort="Mushati, Phyllis" uniqKey="Mushati P" first="Phyllis" last="Mushati">Phyllis Mushati</name></author><author><name sortKey="Garnett, Geoff P" sort="Garnett, Geoff P" uniqKey="Garnett G" first="Geoff P." last="Garnett">Geoff P. Garnett</name></author><author><name sortKey="Gregson, Simon" sort="Gregson, Simon" uniqKey="Gregson S" first="Simon" last="Gregson">Simon Gregson</name></author></analytic><series><title level="j">Bulletin of the World Health Organization</title><idno type="ISSN">0042-9686</idno><imprint><date when="2006">2006</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>OBJECTIVE: To compare alternative methods to vital registration systems for estimating adult mortality, and describe patterns of mortality in Manicaland, Zimbabwe, which has been severely affected by HIV. METHODS: We compared estimates of adult mortality from (1) a single question on household mortality, (2) repeated household censuses, and (3) an adult cohort study with linked HIV testing from Manicaland, with a mathematical model fitted to local age-specific HIV prevalence (1998 -2000). FINDINGS: The crude death rate from the single question (29 per 1000 person-years) was roughly consistent with that from the mathematical model (22 -25 per 1000 person-years), but much higher than that from the household censuses (12 per 1000 person-years). Adult mortality in the household censuses (males 0.65; females 0.51) was lower than in the cohort study (males 0.77; females 0.57), while mathematical models gave a much higher estimate, especially for females (males 0.80 -0.83; females 0.75 -0.80). The population attributable fraction of adult deaths due to HIV was 0.61 for men and 0.70 for women, with life expectancy estimated to be 34.3 years for males and 38.2 years for females. CONCLUSION: Each method for estimating adult mortality had limitations in terms of loss to follow-up (cohort study), under-ascertainment (household censuses), transparency of underlying processes (single question), and sensitivity to parameterization (mathematical model). However, these analyses make clear the advantages of longitudinal cohort data, which provide more complete ascertainment than household censuses, highlight possible inaccuracies in model assumptions, and allow direct quantification of the impact of HIV.</p></div></front></TEI><pmc article-type="research-article"><pmc-comment>The publisher of this article does not allow downloading of the full text in XML form.</pmc-comment>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Bull World Health Organ</journal-id><journal-id journal-id-type="pmc">bullwho</journal-id><journal-title>Bulletin of the World Health Organization</journal-title><issn pub-type="ppub">0042-9686</issn><publisher><publisher-name>World Health Organization</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">16583077</article-id><article-id pub-id-type="pmc">1808347</article-id><article-id pub-id-type="pii">S0042-96862006000300013</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group></article-categories><title-group><article-title>Assessing adult mortality in HIV-1-afflicted Zimbabwe (1998 -2003).</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Lopman</surname><given-names>Ben A.</given-names></name><email>b.lopman@imperial.ac.uk</email></contrib><contrib contrib-type="author"><name><surname>Barnabas</surname><given-names>Ruanne</given-names></name></contrib><contrib contrib-type="author"><name><surname>Hallett</surname><given-names>Timothy B.</given-names></name></contrib><contrib contrib-type="author"><name><surname>Nyamukapa</surname><given-names>Constance</given-names></name></contrib><contrib contrib-type="author"><name><surname>Mundandi</surname><given-names>Costa</given-names></name></contrib><contrib contrib-type="author"><name><surname>Mushati</surname><given-names>Phyllis</given-names></name></contrib><contrib contrib-type="author"><name><surname>Garnett</surname><given-names>Geoff P.</given-names></name></contrib><contrib contrib-type="author"><name><surname>Gregson</surname><given-names>Simon</given-names></name></contrib></contrib-group><aff>Department of Infectious Disease Epidemiology, Imperial College London, England.</aff><pub-date pub-type="ppub"><month>3</month><year>2006</year></pub-date><pub-date pub-type="epub"><day>22</day><month>3</month><year>2006</year></pub-date><volume>84</volume><issue>3</issue><fpage>189</fpage><lpage>197</lpage><abstract><p>OBJECTIVE: To compare alternative methods to vital registration systems for estimating adult mortality, and describe patterns of mortality in Manicaland, Zimbabwe, which has been severely affected by HIV. METHODS: We compared estimates of adult mortality from (1) a single question on household mortality, (2) repeated household censuses, and (3) an adult cohort study with linked HIV testing from Manicaland, with a mathematical model fitted to local age-specific HIV prevalence (1998 -2000). FINDINGS: The crude death rate from the single question (29 per 1000 person-years) was roughly consistent with that from the mathematical model (22 -25 per 1000 person-years), but much higher than that from the household censuses (12 per 1000 person-years). Adult mortality in the household censuses (males 0.65; females 0.51) was lower than in the cohort study (males 0.77; females 0.57), while mathematical models gave a much higher estimate, especially for females (males 0.80 -0.83; females 0.75 -0.80). The population attributable fraction of adult deaths due to HIV was 0.61 for men and 0.70 for women, with life expectancy estimated to be 34.3 years for males and 38.2 years for females. CONCLUSION: Each method for estimating adult mortality had limitations in terms of loss to follow-up (cohort study), under-ascertainment (household censuses), transparency of underlying processes (single question), and sensitivity to parameterization (mathematical model). However, these analyses make clear the advantages of longitudinal cohort data, which provide more complete ascertainment than household censuses, highlight possible inaccuracies in model assumptions, and allow direct quantification of the impact of HIV.</p></abstract></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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