Multilevel Analysis of the Predictors of HIV Prevalence among Pregnant Women Enrolled in Annual HIV Sentinel Surveillance in Four States in Southern India
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{"title"=>"Multilevel analysis of the predictors of HIV prevalence among pregnant women enrolled in annual HIV sentinel surveillance in four states in Southern India", "type"=>"journal", "authors"=>[{"first_name"=>"Usha", "last_name"=>"Thamattoor", "scopus_author_id"=>"56177069200"}, {"first_name"=>"Tinku", "last_name"=>"Thomas", "scopus_author_id"=>"7401540021"}, {"first_name"=>"Pradeep", "last_name"=>"Banandur", "scopus_author_id"=>"36058384700"}, {"first_name"=>"S.", "last_name"=>"Rajaram", "scopus_author_id"=>"36143182100"}, {"first_name"=>"Thierry", "last_name"=>"Duchesne", "scopus_author_id"=>"6603180750"}, {"first_name"=>"Belkacem", "last_name"=>"Abdous", "scopus_author_id"=>"6603306573"}, {"first_name"=>"Reynold", "last_name"=>"Washington", "scopus_author_id"=>"15021550000"}, {"first_name"=>"B. M.", "last_name"=>"Ramesh", "scopus_author_id"=>"8719988400"}, {"first_name"=>"Stephen", "last_name"=>"Moses", "scopus_author_id"=>"7102445987"}, {"first_name"=>"Michel", "last_name"=>"Alary", "scopus_author_id"=>"7006788290"}], "year"=>2015, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "pui"=>"605749678", "doi"=>"10.1371/journal.pone.0131629", "sgr"=>"84940062445", "pmid"=>"26147208", "scopus"=>"2-s2.0-84940062445"}, "id"=>"6b7bd9a8-f2c7-3dd3-9ca3-20dc2b37ec10", "abstract"=>"BACKGROUND: Heterogeneity of the HIV epidemic across districts of south India is reflected in HIV positivity among antenatal clinic (ANC) attendees. Along with individual factors, contextual factors also need consideration for effective HIV interventions. Thus, identifying district and individual level factors that influence ANC HIV positivity assumes importance to intervene effectively. METHODS: Data on HIV sentinel surveillance among the ANC population were obtained from the National AIDS Control Organization (NACO) between years 2004 and 2007. Data from serial cross-sectional studies among female sex workers (FSWs) conducted during this time period in 24 districts were used to generate district level variables corresponding to parameters concerning this high risk population. Other district level data were obtained from various official/governmental agencies. Multilevel logistic regression was used to identify individual and district level factors associated with ANC-HIV positivity. RESULTS: The average ANC-HIV prevalence from 2004 to 2007 in the 24 integrated biological and behavioural assessments (IBBA) districts ranged from 0.25 to 3.25%. HIV positivity was significantly higher among ANC women with age ≥ 25 years [adjusted odds ratio (AOR):1.49; 95% confidence interval (95%CI):1.27 to 1.76] compared to those with age<25 years; illiterate (AOR:1.62; 95%CI:1.03 to 2.54) compared to literate; employed in agriculture (AOR:1.34; 95%CI:1.11 to 1.62) or with occupations like driver/helper/industry/factory workers/hotel staff (AOR:1.59; 95%CI:1.26 to 2.01) compared to unemployed. District level HIV prevalence among FSWs (AOR:1.03; 95%CI:1.0 to 1.05) and percentage women marrying under 18 years were significantly associated with ANC-HIV positivity (AOR:1.02; 95%CI:1.00 to 1.04). CONCLUSION: Illiteracy of the woman, higher HIV prevalence among FSWs and early marriage were associated with HIV positivity among pregnant women in southern India. In addition to targeted HIV preventive interventions among FSWs, studying and changing the behavior of FSW clients and addressing structural drivers of the epidemic might indirectly help reduce HIV infection among women in southern India.", "link"=>"http://www.mendeley.com/research/multilevel-analysis-predictors-hiv-prevalence-among-pregnant-women-enrolled-annual-hiv-sentinel-surv", "reader_count"=>21, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>1, "Librarian"=>1, "Researcher"=>3, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>3, "Student > Master"=>5, "Student > Bachelor"=>2, "Lecturer"=>1, "Professor"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>1, "Librarian"=>1, "Researcher"=>3, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>3, "Student > Master"=>5, "Student > Bachelor"=>2, "Lecturer"=>1, "Professor"=>1}, "reader_count_by_subject_area"=>{"Engineering"=>1, "Unspecified"=>2, "Nursing and Health Professions"=>2, "Biochemistry, Genetics and Molecular Biology"=>1, "Medicine and Dentistry"=>9, "Psychology"=>2, "Social Sciences"=>4}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>9}, "Social Sciences"=>{"Social Sciences"=>4}, "Psychology"=>{"Psychology"=>2}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Unspecified"=>{"Unspecified"=>2}}, "group_count"=>0}

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  • {"files"=>["https://ndownloader.figshare.com/files/2163322"], "description"=>"<p>*Antenatal care</p><p>† Percentage</p><p>Selected characteristics of districts where integrated biological and behavioral assessment (IBBA) was conducted.</p>", "links"=>[], "tags"=>["aor", "district level variables", "influence ANC HIV positivity", "Pregnant Women Enrolled", "NACO", "IBBA", "HIV positivity", "fsw", "district level HIV prevalence", "ci", "Annual HIV Sentinel Surveillance", "National AIDS Control Organization", "Southern India BackgroundHeterogeneity", "HIV Sentinel Surveillance", "Other district level data", "district level factors"], "article_id"=>1474288, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Usha Thamattoor", "Tinku Thomas", "Pradeep Banandur", "Rajaram S", "Thierry Duchesne", "Belkacem Abdous", "Reynold Washington", "Ramesh B M", "Stephen Moses", "Michel Alary"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0131629.t001", "stats"=>{"downloads"=>6, "page_views"=>21, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Selected_characteristics_of_districts_where_integrated_biological_and_behavioral_assessment_IBBA_was_conducted_/1474288", "title"=>"Selected characteristics of districts where integrated biological and behavioral assessment (IBBA) was conducted.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-07-06 03:26:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/2163323"], "description"=>"<p>All figures represent percentage of the total antenatal women attending HIV sentinel surveillance sites from 2004–2007 in each district.</p><p>* Antenatal care,</p><p>†12<sup>th</sup> to Graduate data not collected in HSS data.</p><p>‡ Includes truck/auto/taxi driver/helper/industry/factory workers/hotel staff,</p><p>§ Includes unemployed/house wife/student.</p><p>Individual level characteristics of ANC<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0131629#t002fn002\" target=\"_blank\"><sup>*</sup></a> women in IBBA districts; Annual HIV Sentinel Surveillance 2004–2007.</p>", "links"=>[], "tags"=>["aor", "district level variables", "influence ANC HIV positivity", "Pregnant Women Enrolled", "NACO", "IBBA", "HIV positivity", "fsw", "district level HIV prevalence", "ci", "Annual HIV Sentinel Surveillance", "National AIDS Control Organization", "Southern India BackgroundHeterogeneity", "HIV Sentinel Surveillance", "Other district level data", "district level factors"], "article_id"=>1474289, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Usha Thamattoor", "Tinku Thomas", "Pradeep Banandur", "Rajaram S", "Thierry Duchesne", "Belkacem Abdous", "Reynold Washington", "Ramesh B M", "Stephen Moses", "Michel Alary"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0131629.t002", "stats"=>{"downloads"=>4, "page_views"=>25, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Individual_level_characteristics_of_ANC_women_in_IBBA_districts_Annual_HIV_Sentinel_Surveillance_2004_2007_/1474289", "title"=>"Individual level characteristics of ANC<sup>*</sup> women in IBBA districts; Annual HIV Sentinel Surveillance 2004–2007.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-07-06 03:26:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/2163324"], "description"=>"<p>*Odds Ratio,</p><p>† Confidence interval</p><p>‡ Includes truck/auto/taxi driver/helper/industry/factory workers/hotel staff</p><p>§ Unadjusted for locality and migrant status, NA Not Applicable.</p><p>Association of individual level variables with HIV positivity in antenatal women.</p>", "links"=>[], "tags"=>["aor", "district level variables", "influence ANC HIV positivity", "Pregnant Women Enrolled", "NACO", "IBBA", "HIV positivity", "fsw", "district level HIV prevalence", "ci", "Annual HIV Sentinel Surveillance", "National AIDS Control Organization", "Southern India BackgroundHeterogeneity", "HIV Sentinel Surveillance", "Other district level data", "district level factors"], "article_id"=>1474290, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Usha Thamattoor", "Tinku Thomas", "Pradeep Banandur", "Rajaram S", "Thierry Duchesne", "Belkacem Abdous", "Reynold Washington", "Ramesh B M", "Stephen Moses", "Michel Alary"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0131629.t003", "stats"=>{"downloads"=>10, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Association_of_individual_level_variables_with_HIV_positivity_in_antenatal_women_/1474290", "title"=>"Association of individual level variables with HIV positivity in antenatal women.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-07-06 03:26:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/2163325"], "description"=>"<p>%: Percentage, FSW: Female Sexual Worker, HSS: HIV Sentinel Surveillance, AOR: Adjusted Odds Ratio,</p><p>CI: Confidence Interval.</p><p>*Adjusted for age, occupation and education.</p><p>† Includes Truck/auto/taxi driver/helper/industry/factory workers/hotel staff.</p><p>Multilevel analysis of factors associated with HIV in antenatal women: ANC HSS 2004–2007.</p>", "links"=>[], "tags"=>["aor", "district level variables", "influence ANC HIV positivity", "Pregnant Women Enrolled", "NACO", "IBBA", "HIV positivity", "fsw", "district level HIV prevalence", "ci", "Annual HIV Sentinel Surveillance", "National AIDS Control Organization", "Southern India BackgroundHeterogeneity", "HIV Sentinel Surveillance", "Other district level data", "district level factors"], "article_id"=>1474291, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Usha Thamattoor", "Tinku Thomas", "Pradeep Banandur", "Rajaram S", "Thierry Duchesne", "Belkacem Abdous", "Reynold Washington", "Ramesh B M", "Stephen Moses", "Michel Alary"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0131629.t004", "stats"=>{"downloads"=>1, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Multilevel_analysis_of_factors_associated_with_HIV_in_antenatal_women_ANC_HSS_2004_8211_2007_/1474291", "title"=>"Multilevel analysis of factors associated with HIV in antenatal women: ANC HSS 2004–2007.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-07-06 03:26:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/2163327"], "description"=>"<div><p>Background</p><p>Heterogeneity of the HIV epidemic across districts of south India is reflected in HIV positivity among antenatal clinic (ANC) attendees. Along with individual factors, contextual factors also need consideration for effective HIV interventions. Thus, identifying district and individual level factors that influence ANC HIV positivity assumes importance to intervene effectively.</p><p>Methods</p><p>Data on HIV sentinel surveillance among the ANC population were obtained from the National AIDS Control Organization (NACO) between years 2004 and 2007. Data from serial cross-sectional studies among female sex workers (FSWs) conducted during this time period in 24 districts were used to generate district level variables corresponding to parameters concerning this high risk population. Other district level data were obtained from various official/governmental agencies. Multilevel logistic regression was used to identify individual and district level factors associated with ANC-HIV positivity.</p><p>Results</p><p>The average ANC-HIV prevalence from 2004 to 2007 in the 24 integrated biological and behavioural assessments (IBBA) districts ranged from 0.25 to 3.25%. HIV positivity was significantly higher among ANC women with age≥25 years [adjusted odds ratio (AOR):1.49; 95% confidence interval (95%CI):1.27 to 1.76] compared to those with age<25 years; illiterate (AOR:1.62; 95%CI:1.03 to 2.54) compared to literate; employed in agriculture (AOR:1.34; 95%CI:1.11 to 1.62) or with occupations like driver/helper/industry/factory workers/hotel staff (AOR:1.59; 95%CI:1.26 to 2.01) compared to unemployed. District level HIV prevalence among FSWs (AOR:1.03; 95%CI:1.0 to 1.05) and percentage women marrying under 18 years were significantly associated with ANC-HIV positivity (AOR:1.02; 95%CI:1.00 to 1.04).</p><p>Conclusion</p><p>Illiteracy of the woman, higher HIV prevalence among FSWs and early marriage were associated with HIV positivity among pregnant women in southern India. In addition to targeted HIV preventive interventions among FSWs, studying and changing the behavior of FSW clients and addressing structural drivers of the epidemic might indirectly help reduce HIV infection among women in southern India.</p></div>", "links"=>[], "tags"=>["aor", "district level variables", "influence ANC HIV positivity", "Pregnant Women Enrolled", "NACO", "IBBA", "HIV positivity", "fsw", "district level HIV prevalence", "ci", "Annual HIV Sentinel Surveillance", "National AIDS Control Organization", "Southern India BackgroundHeterogeneity", "HIV Sentinel Surveillance", "Other district level data", "district level factors"], "article_id"=>1474293, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Usha Thamattoor", "Tinku Thomas", "Pradeep Banandur", "Rajaram S", "Thierry Duchesne", "Belkacem Abdous", "Reynold Washington", "Ramesh B M", "Stephen Moses", "Michel Alary"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0131629", "stats"=>{"downloads"=>3, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Multilevel_Analysis_of_the_Predictors_of_HIV_Prevalence_among_Pregnant_Women_Enrolled_in_Annual_HIV_Sentinel_Surveillance_in_Four_States_in_Southern_India_/1474293", "title"=>"Multilevel Analysis of the Predictors of HIV Prevalence among Pregnant Women Enrolled in Annual HIV Sentinel Surveillance in Four States in Southern India", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-07-06 03:26:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/2163321"], "description"=>"<p>Schematic representation for selection of variables for multilevel modelling analysis.</p>", "links"=>[], "tags"=>["aor", "district level variables", "influence ANC HIV positivity", "Pregnant Women Enrolled", "NACO", "IBBA", "HIV positivity", "fsw", "district level HIV prevalence", "ci", "Annual HIV Sentinel Surveillance", "National AIDS Control Organization", "Southern India BackgroundHeterogeneity", "HIV Sentinel Surveillance", "Other district level data", "district level factors"], "article_id"=>1474287, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Usha Thamattoor", "Tinku Thomas", "Pradeep Banandur", "Rajaram S", "Thierry Duchesne", "Belkacem Abdous", "Reynold Washington", "Ramesh B M", "Stephen Moses", "Michel Alary"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0131629.g001", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Schematic_representation_for_selection_of_variables_for_multilevel_modelling_analysis_/1474287", "title"=>"Schematic representation for selection of variables for multilevel modelling analysis.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-07-06 03:26:12"}

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{"start_date"=>"2015-01-01T00:00:00Z", "end_date"=>"2015-12-31T00:00:00Z", "subject_areas"=>[]}
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