Gender and poverty in South Africa in the era of HIV/AIDS: a quantitative study.
Identifieur interne : 000110 ( PubMed/Corpus ); précédent : 000109; suivant : 000111Gender and poverty in South Africa in the era of HIV/AIDS: a quantitative study.
Auteurs : Olive Shisana ; Kathleen Rice ; Nompumelelo Zungu ; Khangelani ZumaSource :
- Journal of women's health (2002) [ 1931-843X ] ; 2010.
English descriptors
- KwdEn :
- Adolescent, Age Distribution, Evaluation Studies as Topic, Female, Financing, Personal, HIV Infections (epidemiology), HIV Infections (psychology), Health Status Disparities, Health Status Indicators, Humans, Male, Odds Ratio, Poverty (psychology), Poverty (statistics & numerical data), Residence Characteristics (statistics & numerical data), Sex Distribution, South Africa (epidemiology), Vulnerable Populations (psychology), Vulnerable Populations (statistics & numerical data), Young Adult.
- MESH :
- geographic , epidemiology : South Africa.
- epidemiology : HIV Infections.
- psychology : HIV Infections, Poverty, Vulnerable Populations.
- statistics & numerical data : Poverty, Residence Characteristics, Vulnerable Populations.
- Adolescent, Age Distribution, Evaluation Studies as Topic, Female, Financing, Personal, Health Status Disparities, Health Status Indicators, Humans, Male, Odds Ratio, Sex Distribution, Young Adult.
Abstract
Recent research identifies gender inequality as a driver of the HIV/AIDS epidemic. The feminization of poverty is also increasingly apparent, as is the disproportionate vulnerability of members of female-headed households. We sought to examine the relationships among sex, gender, age, HIV status, and socioeconomic characteristics, focusing on heads and nonheads of households.
DOI: 10.1089/jwh.2008.1200
PubMed: 20088657
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pubmed:20088657Le document en format XML
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The feminization of poverty is also increasingly apparent, as is the disproportionate vulnerability of members of female-headed households. We sought to examine the relationships among sex, gender, age, HIV status, and socioeconomic characteristics, focusing on heads and nonheads of households.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">20088657</PMID><DateCreated><Year>2010</Year><Month>01</Month><Day>21</Day></DateCreated><DateCompleted><Year>2012</Year><Month>04</Month><Day>05</Day></DateCompleted><DateRevised><Year>2010</Year><Month>01</Month><Day>21</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Electronic">1931-843X</ISSN><JournalIssue CitedMedium="Internet"><Volume>19</Volume><Issue>1</Issue><PubDate><Year>2010</Year><Month>Jan</Month></PubDate></JournalIssue><Title>Journal of women's health (2002)</Title><ISOAbbreviation>J Womens Health (Larchmt)</ISOAbbreviation></Journal><ArticleTitle>Gender and poverty in South Africa in the era of HIV/AIDS: a quantitative study.</ArticleTitle><Pagination><MedlinePgn>39-46</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1089/jwh.2008.1200</ELocationID><Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">Recent research identifies gender inequality as a driver of the HIV/AIDS epidemic. The feminization of poverty is also increasingly apparent, as is the disproportionate vulnerability of members of female-headed households. We sought to examine the relationships among sex, gender, age, HIV status, and socioeconomic characteristics, focusing on heads and nonheads of households.</AbstractText><AbstractText Label="METHODS" NlmCategory="METHODS">We interviewed 6,338 men and 10,057 women.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">Significantly more males (51.4%) than females (34.8%) indicated that they were heads of households (p < 0.001). Female heads of households were significantly more likely to be infected with HIV than their male counterparts (17.9% vs. 13.1%). Among 15-24-year-old males, those who are often without cash are more likely to be infected with HIV than those who are never without cash (OR = 3.33, 95% CI 1.17-9.49). Similar results were observed among females, who sometimes had no cash (OR = 1.86, 95% CI 1.22-2.82), and among adults aged >or=25 years. Results confirmed that age and gender are related to HIV infection in South Africa and that poverty is a social determinant for HIV infection across all age groups. However, sex is a determinant only among the younger age groups. Young female heads of household are more likely to be poor and are more likely to be HIV positive.</AbstractText><AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">The results indicate that the HIV/AIDS epidemic in South Africa is characterized by gender inequalities. Young women are more likely to be HIV infected, especially heads of households. Young women are also more likely to live in poverty, although this study cannot establish the directionality of a causative relationship between poverty and risk of HIV. Greater attention must be paid to young women, especially those who head households, in terms of treatment, prevention, and poverty alleviation.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Shisana</LastName><ForeName>Olive</ForeName><Initials>O</Initials><AffiliationInfo><Affiliation>Human Sciences Research Council, Cape Town, South Africa.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Rice</LastName><ForeName>Kathleen</ForeName><Initials>K</Initials></Author><Author ValidYN="Y"><LastName>Zungu</LastName><ForeName>Nompumelelo</ForeName><Initials>N</Initials></Author><Author ValidYN="Y"><LastName>Zuma</LastName><ForeName>Khangelani</ForeName><Initials>K</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType><PublicationType UI="D013487">Research Support, U.S. Gov't, P.H.S.</PublicationType></PublicationTypeList></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>J Womens Health (Larchmt)</MedlineTA><NlmUniqueID>101159262</NlmUniqueID><ISSNLinking>1540-9996</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000293" MajorTopicYN="N">Adolescent</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D017677" MajorTopicYN="N">Age Distribution</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005069" MajorTopicYN="N">Evaluation Studies as Topic</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005382" MajorTopicYN="N">Financing, Personal</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D015658" MajorTopicYN="N">HIV Infections</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName><QualifierName UI="Q000523" MajorTopicYN="N">psychology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D054624" MajorTopicYN="N">Health Status Disparities</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006305" MajorTopicYN="N">Health Status Indicators</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D016017" MajorTopicYN="N">Odds Ratio</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D011203" MajorTopicYN="N">Poverty</DescriptorName><QualifierName UI="Q000523" MajorTopicYN="N">psychology</QualifierName><QualifierName UI="Q000706" MajorTopicYN="Y">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D012111" MajorTopicYN="N">Residence Characteristics</DescriptorName><QualifierName UI="Q000706" MajorTopicYN="N">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D017678" MajorTopicYN="N">Sex Distribution</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D013019" MajorTopicYN="N" Type="Geographic">South Africa</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D035862" MajorTopicYN="N">Vulnerable Populations</DescriptorName><QualifierName UI="Q000523" MajorTopicYN="N">psychology</QualifierName><QualifierName UI="Q000706" MajorTopicYN="Y">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D055815" MajorTopicYN="N">Young Adult</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2010</Year><Month>1</Month><Day>22</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2010</Year><Month>1</Month><Day>22</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2012</Year><Month>4</Month><Day>6</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">20088657</ArticleId><ArticleId IdType="doi">10.1089/jwh.2008.1200</ArticleId></ArticleIdList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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