What explains gender inequalities in HIV/AIDS prevalence in sub-Saharan Africa? Evidence from the demographic and health surveys.
Identifieur interne : 000077 ( PubMed/Checkpoint ); précédent : 000076; suivant : 000078What explains gender inequalities in HIV/AIDS prevalence in sub-Saharan Africa? Evidence from the demographic and health surveys.
Auteurs : Drissa Sia [Canada] ; Yentéma Onadja [Burkina Faso] ; Mohammad Hajizadeh [Canada] ; S Jody Heymann [États-Unis] ; Timothy F. Brewer [États-Unis] ; Arijit Nandi [Canada]Source :
- BMC public health [ 1471-2458 ] ; 2016.
Descripteurs français
- KwdFr :
- Adolescent, Adulte, Adulte d'âge moyen, Afrique subsaharienne (épidémiologie), Cameroun (épidémiologie), Comportement sexuel, Disparités de l'état de santé, Enquêtes de santé, Facteurs de risque, Facteurs sexuels, Femelle, Ghana (épidémiologie), Humains, Infections à VIH (épidémiologie), Infections à VIH (étiologie), Malawi (épidémiologie), Mâle, Ouganda (épidémiologie), Prévalence, Répartition par sexe, Swaziland (épidémiologie).
- MESH :
- épidémiologie : Afrique subsaharienne, Cameroun, Ghana, Infections à VIH, Malawi, Ouganda, Swaziland.
- étiologie : Infections à VIH.
- Adolescent, Adulte, Adulte d'âge moyen, Comportement sexuel, Disparités de l'état de santé, Enquêtes de santé, Facteurs de risque, Facteurs sexuels, Femelle, Humains, Mâle, Prévalence, Répartition par sexe.
English descriptors
- KwdEn :
- Adolescent, Adult, Africa South of the Sahara (epidemiology), Cameroon (epidemiology), Female, Ghana (epidemiology), HIV Infections (epidemiology), HIV Infections (etiology), Health Status Disparities, Health Surveys, Humans, Malawi (epidemiology), Male, Middle Aged, Prevalence, Risk Factors, Sex Distribution, Sex Factors, Sexual Behavior, Swaziland (epidemiology), Uganda (epidemiology).
- MESH :
- epidemiology : Africa South of the Sahara, Cameroon, Ghana, HIV Infections, Malawi, Swaziland, Uganda.
- etiology : HIV Infections.
- Adolescent, Adult, Female, Health Status Disparities, Health Surveys, Humans, Male, Middle Aged, Prevalence, Risk Factors, Sex Distribution, Sex Factors, Sexual Behavior.
Abstract
Women are disproportionally affected by human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) in sub-Saharan Africa (SSA). The determinants of gender inequality in HIV/AIDS may vary across countries and require country-specific interventions to address them. This study aimed to identify the socio-demographic and behavioral characteristics underlying gender inequalities in HIV/AIDS in 21 SSA countries.
DOI: 10.1186/s12889-016-3783-5
PubMed: 27809824
Affiliations:
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pubmed:27809824Le document en format XML
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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adolescent</term>
<term>Adult</term>
<term>Africa South of the Sahara (epidemiology)</term>
<term>Cameroon (epidemiology)</term>
<term>Female</term>
<term>Ghana (epidemiology)</term>
<term>HIV Infections (epidemiology)</term>
<term>HIV Infections (etiology)</term>
<term>Health Status Disparities</term>
<term>Health Surveys</term>
<term>Humans</term>
<term>Malawi (epidemiology)</term>
<term>Male</term>
<term>Middle Aged</term>
<term>Prevalence</term>
<term>Risk Factors</term>
<term>Sex Distribution</term>
<term>Sex Factors</term>
<term>Sexual Behavior</term>
<term>Swaziland (epidemiology)</term>
<term>Uganda (epidemiology)</term>
</keywords>
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<term>Adulte</term>
<term>Adulte d'âge moyen</term>
<term>Afrique subsaharienne (épidémiologie)</term>
<term>Cameroun (épidémiologie)</term>
<term>Comportement sexuel</term>
<term>Disparités de l'état de santé</term>
<term>Enquêtes de santé</term>
<term>Facteurs de risque</term>
<term>Facteurs sexuels</term>
<term>Femelle</term>
<term>Ghana (épidémiologie)</term>
<term>Humains</term>
<term>Infections à VIH (épidémiologie)</term>
<term>Infections à VIH (étiologie)</term>
<term>Malawi (épidémiologie)</term>
<term>Mâle</term>
<term>Ouganda (épidémiologie)</term>
<term>Prévalence</term>
<term>Répartition par sexe</term>
<term>Swaziland (épidémiologie)</term>
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<term>Cameroon</term>
<term>Ghana</term>
<term>HIV Infections</term>
<term>Malawi</term>
<term>Swaziland</term>
<term>Uganda</term>
</keywords>
<keywords scheme="MESH" qualifier="etiology" xml:lang="en"><term>HIV Infections</term>
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<keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Afrique subsaharienne</term>
<term>Cameroun</term>
<term>Ghana</term>
<term>Infections à VIH</term>
<term>Malawi</term>
<term>Ouganda</term>
<term>Swaziland</term>
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<keywords scheme="MESH" qualifier="étiologie" xml:lang="fr"><term>Infections à VIH</term>
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<keywords scheme="MESH" xml:lang="en"><term>Adolescent</term>
<term>Adult</term>
<term>Female</term>
<term>Health Status Disparities</term>
<term>Health Surveys</term>
<term>Humans</term>
<term>Male</term>
<term>Middle Aged</term>
<term>Prevalence</term>
<term>Risk Factors</term>
<term>Sex Distribution</term>
<term>Sex Factors</term>
<term>Sexual Behavior</term>
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<term>Adulte</term>
<term>Adulte d'âge moyen</term>
<term>Comportement sexuel</term>
<term>Disparités de l'état de santé</term>
<term>Enquêtes de santé</term>
<term>Facteurs de risque</term>
<term>Facteurs sexuels</term>
<term>Femelle</term>
<term>Humains</term>
<term>Mâle</term>
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<front><div type="abstract" xml:lang="en">Women are disproportionally affected by human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) in sub-Saharan Africa (SSA). The determinants of gender inequality in HIV/AIDS may vary across countries and require country-specific interventions to address them. This study aimed to identify the socio-demographic and behavioral characteristics underlying gender inequalities in HIV/AIDS in 21 SSA countries.</div>
</front>
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<pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">27809824</PMID>
<DateCreated><Year>2016</Year>
<Month>11</Month>
<Day>04</Day>
</DateCreated>
<DateCompleted><Year>2017</Year>
<Month>07</Month>
<Day>14</Day>
</DateCompleted>
<DateRevised><Year>2017</Year>
<Month>07</Month>
<Day>14</Day>
</DateRevised>
<Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1471-2458</ISSN>
<JournalIssue CitedMedium="Internet"><Volume>16</Volume>
<Issue>1</Issue>
<PubDate><Year>2016</Year>
<Month>Nov</Month>
<Day>03</Day>
</PubDate>
</JournalIssue>
<Title>BMC public health</Title>
<ISOAbbreviation>BMC Public Health</ISOAbbreviation>
</Journal>
<ArticleTitle>What explains gender inequalities in HIV/AIDS prevalence in sub-Saharan Africa? Evidence from the demographic and health surveys.</ArticleTitle>
<Pagination><MedlinePgn>1136</MedlinePgn>
</Pagination>
<Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">Women are disproportionally affected by human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) in sub-Saharan Africa (SSA). The determinants of gender inequality in HIV/AIDS may vary across countries and require country-specific interventions to address them. This study aimed to identify the socio-demographic and behavioral characteristics underlying gender inequalities in HIV/AIDS in 21 SSA countries.</AbstractText>
<AbstractText Label="METHODS" NlmCategory="METHODS">We applied an extension of the Blinder-Oaxaca decomposition approach to data from Demographic and Health Surveys and AIDS Indicator Surveys to quantify the differences in HIV/AIDS prevalence between women and men attributable to socio-demographic factors, sexual behaviours, and awareness of HIV/AIDS. We decomposed gender inequalities into two components: the percentage attributable to different levels of the risk factors between women and men (the "composition effect") and the percentage attributable to risk factors having differential effects on HIV/AIDS prevalence in women and men (the "response effect").</AbstractText>
<AbstractText Label="RESULTS" NlmCategory="RESULTS">Descriptive analyses showed that the difference between women and men in HIV/AIDS prevalence varied from a low of 0.68 % (P = 0.008) in Liberia to a high of 11.5 % (P < 0.001) in Swaziland. The decomposition analysis showed that 84 % (P < 0.001) and 92 % (P < 0.001) of the higher prevalence of HIV/AIDS among women in Uganda and Ghana, respectively, was explained by the different distributions of HIV/AIDS risk factors, particularly age at first sex between women and men. In the majority of countries, however, observed gender inequalities in HIV/AIDS were chiefly explained by differences in the responses to risk factors; the differential effects of age, marital status and occupation on prevalence of HIV/AIDS for women and men were among the significant contributors to this component. In Cameroon, Guinea, Malawi and Swaziland, a combination of the composition and response effects explained gender inequalities in HIV/AIDS prevalence.</AbstractText>
<AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">The factors that explain gender inequality in HIV/AIDS in SSA vary by country, suggesting that country-specific interventions are needed. Unmeasured factors also contributed substantially to the difference in HIV/AIDS prevalence between women and men, highlighting the need for further study.</AbstractText>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Sia</LastName>
<ForeName>Drissa</ForeName>
<Initials>D</Initials>
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<AffiliationInfo><Affiliation>Département des sciences infirmières, Campus de Saint-Jérôme, Université du Québec en Outaouais, 5, rue Saint-Joseph, bureau J-3226, Saint Jérôme, Québec, J7Z 0B7, Canada. drissa.sia@uqo.ca.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Onadja</LastName>
<ForeName>Yentéma</ForeName>
<Initials>Y</Initials>
<AffiliationInfo><Affiliation>Institut Supérieur des Sciences de la Population (ISSP), Université Ouaga I Pr Joseph Ki-Zerbo, 03 BP 7118 Ouagadougou 03, Ouagadougou, Burkina Faso.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Hajizadeh</LastName>
<ForeName>Mohammad</ForeName>
<Initials>M</Initials>
<AffiliationInfo><Affiliation>School of Health Administration, Dalhousie University, Halifax, Nova Scotia, Canada.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Heymann</LastName>
<ForeName>S Jody</ForeName>
<Initials>SJ</Initials>
<AffiliationInfo><Affiliation>Fielding School of Public Health, The University of California, Los Angeles (UCLA), Los Angeles, CA, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Brewer</LastName>
<ForeName>Timothy F</ForeName>
<Initials>TF</Initials>
<AffiliationInfo><Affiliation>David Geffen School of Medicine, The University of California, Los Angeles (UCLA), Los Angeles, CA, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Nandi</LastName>
<ForeName>Arijit</ForeName>
<Initials>A</Initials>
<AffiliationInfo><Affiliation>Institute for Health and Social Policy and Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Québec, Canada.</Affiliation>
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<MeshHeadingList><MeshHeading><DescriptorName UI="D000293" MajorTopicYN="N">Adolescent</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000328" MajorTopicYN="N">Adult</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D017954" MajorTopicYN="N">Africa South of the Sahara</DescriptorName>
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<MeshHeading><DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName>
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<MeshHeading><DescriptorName UI="D015995" MajorTopicYN="N">Prevalence</DescriptorName>
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<MeshHeading><DescriptorName UI="D012307" MajorTopicYN="N">Risk Factors</DescriptorName>
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<MeshHeading><DescriptorName UI="D017678" MajorTopicYN="N">Sex Distribution</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D012737" MajorTopicYN="N">Sex Factors</DescriptorName>
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<MeshHeading><DescriptorName UI="D012725" MajorTopicYN="N">Sexual Behavior</DescriptorName>
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<MeshHeading><DescriptorName UI="D013541" MajorTopicYN="N">Swaziland</DescriptorName>
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<KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Blinder-Oaxaca decomposition</Keyword>
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<Keyword MajorTopicYN="N">HIV/AIDS</Keyword>
<Keyword MajorTopicYN="N">Sub-Saharan Africa</Keyword>
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