HIV and AIDS Stigma: What Drives the Gender HIV/AIDS Accepting Attitudes Gap in Malawi? Gowokani Chijere Chirwa, Margaret Chilongo, Lonjezo Sithole

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1 HIV and AIDS Stigma: What Drives the Gender HIV/AIDS Accepting Attitudes Gap in Malawi? Gowokani Chijere Chirwa, Margaret Chilongo, Lonjezo Sithole

2 Introduction 1. The issue : Malawi, like other countries has been affected by Stigma of PLWHIV. (GoM, 2015; NSO & ICF Macro, 2011; NSO & ORC Macro, 2001, 2005; Macpherson et al 2011) Consequently affecting HIV programing since many people are reluctant to access HIV and AIDS services including HTS. Those who go for HTS and test positive are reluctant to disclose their HIV status for fear of being ostracized. 2. The puzzle : Despite 99% HIV and AIDS awareness 37.75% of men in urban and 35.2% in rural areas have accepting attitudes. 21.1% of women in urban and 19.4% in rural have accepting attitudes (NSO and ICF Macro 2015) Then why is it so? What's driving the difference? 3. Objectives: To explain the gender differences in HIV accepting attitudes in Malawi Quantify the gap and explain how much a covariate contributes to the gap 4. Our Contribution to knowledge : Our study contributes to literature by investigating the gap using a decomposition analysis.

3 Method We used MDHS 2010 Data set. In decomposition method, a regression of the difference between two groups is run. Dates back to the classic work of Blinder-Oaxaca (Blinder, 1973; Oaxaca, 1973) B-O method applies to continuous variables. The standard Blinder-Oaxaca decomposition for the male/female gap in the average value of the outcome variable, Y, can be expressed as: Y M Y F M F ˆ M F ( ) ( ˆ M ˆ F X X X ) Our analysis uses the extended B-O, to binary outcomes called Farilie Method Y M M F F F N M ( ˆ M N F ) ( ˆ M N F ) ( ˆ M N F F F F X i F X i F X i ) F( X i ) Y M F F F i 1 N i 1 N i 1 N i 1 N

4 Results HIV Acceptance Attitudes northern HIV Acceptance Attitudes central Q : How Much is the gap? Percent Source: Calculated by Author from 2010 MDHS HIV Acceptance Attitudes southern Source: Calculated by Author from 2010 MDHS HIV Acceptance Attitudes Total Its not weighted but when weighted we get same value in DHS. Men =36% Women=20% GAP = = -13% Ho: = mean(female)-mean(male) diff = Ho= 0 t = Pr(T >t) = Source: Calculated by Author from 2010 MDHS Source: Calculated by Author from 2010 MDHS Female Male Graphs by region 4

5 Results. Determinants of GAP SS Gap Contribution Coef. Coef. %Explained Age *** *** Age *** Employment Poorer Middle Richer ** Richest ** * 0.25 TV_ TV > * TV daily Radio_ Rad> * * RAD daily * News/mag_ * * News/Mag> * * News/MagDaily Muslim Christian_Protestant * Chistian_Catholic ** Primary *** *** Secondary *** *** Tertiary *** *** Residence_Type ** ** Residence_Type ** Residence_Type ** HIV_Test HIV_Comprehensive *** *** AIDS_Middle ** ** AIDS_High *** N= Difference (13%) Total Explained (12.785%) Unexplained 87.21% A negative sign above means that if women had characteristics of men, the GAP would have reduced by 13% In the coefficients, a negative sign means that the variable in question serves to reduce the gap A positive sign means that a variable in question increases the GAP in the table, Secondary education, followed by reading news/ mags, pamphlets and tertiary education reduces the GAP by 6.612%, %, 2.078% respectively= hence significant predictors of GAP

6 What can we learn from this? Media Television is not an effective way in reducing HIV/AIDS stigma as compared to radio and newspaper Reading pamphlets/news/ mag and listening to radio more than once a week are highly explaining the GAP Education Primary Education increases GAP where as tertiary and secondary reduces the GAP. Hence need to promote education beyond primary

7 Thank you!

8 BACK UP SLIDES

9 Outline 1. Introduction 2. Objectives 3. What we know about HIV/AIDS accepting attitudes gap 4. Research questions 5. Methods 6. Results 7. Lessons

10 1.0 Introduction Malawi, like other countries in the Sub-Saharan region has also been affected by the problem of non acceptance(stigma) of PLWHIV. (GoM, 2015; NSO & ICF Macro, 2011; NSO & ORC Macro, 2001, 2005; Macpherson et al 2011) Consequently affecting HIV programing since; Many people are unwilling to go for voluntary Counselling and Testing. Those who go for HCT and test positive, are reluctant to disclose their HIV status for fear of not being socially accepted. These societal attitudes also affects those tested positive in their initiation of and adherence to antiretroviral therapy Reducing stigma is therefore an important factor in prevention, management, and control of the HIV pandemic (NSO and ICF Macro 2015).

11 1.0 Introduction cont The puzzle is that despite 99% HIV and AIDS awareness we observed that 37.75% of men in urban and 35.2% in rural areas have accepting attitudes. Whereas for women, 21.1% in urban and 19.4% in rural have accepting attitudes (NSO and ICF Macro 2015) Then why is it so? What's driving the difference? This study therefore tries to make modest contribution to knowledge of stigma against people living with HIV by going beyond to explain the causes of the acceptance gap across different categories. This study is important in that it adds on literature to unearth the factors that would impinge on Universal Health Coverage (UHC) and SDG 2030 Agenda.

12 2.0 Objectives of the study Main Objective To explain the gender differences in HIV accepting attitudes in Malawi Specific Objectives Identify the factors that contribute to the gap in HIV/AIDS accepting attitudes in Malawi Quantify how much each covariate contributes to the gap Quantify the gap in HIV accepting attitudes

13 3. 0 What do we know about the explanations of gender HIV/AIDS accepting gap? There is no study explaining HIV accepting gaps in Malawi But there are studies about assessing 1. HIV knowledge (Chiang et al 2009; Fai et 2009; Barde-O`Fallon et al 2004; 2. HIV stigma of MSM (Andrea L Wirtz et 2013; Beyrer et al, 2011 Baral et al, 2009) Existing studies are mainly foreign : ( Angelo; 1995; Duffy 2005; Mahajan et al 2008; Thomang et al,2009; Monjok et al; 2009 Dahlui et al; 2009; Chao et al; 2009 ; Corno & de Walque 2013; Chiao et al 2009) Empirics show that stigmatized attitudes are; negatively associated with education, age and wealth and positively varies religion for women. Men are less likely to have stigma than females HIV knowledge is negatively associated with stigma

14 3.0.. BUT all these studies do not do a decomposition analysis But rather look at determinants Decomposition is important as it spells out an independent variable exerts more power than another variable Our study contributes to literature by investigating the gap through a decomposition analysis. To our knowledge no existing study is available on this

15 4.0 Research question: What do we need to know? How much is the gap in HIV/AIDS accepting attitudes between Men and Women? By How much does Social economic factors explain the gender HIV/AIDS Accepting attitudes gap?

16 Why Malawi? Malawi is among highest with HIV adult prevalence (10.3%). Prevalence is higher in women (12.9%) as compared to men (8.1%). o o We never achieved the target of reducing HIV prevalence rate among pregnant women (Aged 15-24) to 0% MGD Goal number6 o Attitudes toward HIV testing and acceptance is one cause Recently we adopted the agenda along with the Sustainable development goals to halt AIDS by 2030 o o We don t have explanations as to why the disparity among gender exist? The concept of gender must be mainstreamed into the multi-sectoral response to HIV/AIDS(Matlin and Spence 2000, GoM 2011) HIV Prevalence among year old pregnant women

17 Important definitions: 1. What is gender HIV Accepting gap? The gap between average male and female who have comprehensive HIV and AIDS accepting attitudes Practically we expect women as informal HIV and AIDS ( Chiwaula, Chirwa et al 2016) careers to have more accepting attitudes 2.HIV Accepting attitudes Willingness to care for a family member with AIDS in the respondent s home, Willingness to buy fresh vegetables from a shopkeeper who has HIV, Accepting that a female teacher who has HIV but is not sick should be allowed to continue teaching and Not keeping any secrets that a family member was infected with HIV KudaKwasehe et al 2016, Teshome et al 2016 NSO and ICF Macro(MDHS)- 2004,2010,2016 Measure DHS/USAID

18 5.0 Method: Estimating the gap In Decomposition method a regression of the difference between two groups is run- Emanates from classic work of Blinder-Oaxaca (Blinder, 1973; Oaxaca, 1973) B-O method applies to continuous variables. The standard Blinder-Oaxaca decomposition for the male/female gap in the average value of the outcome variable, Y, can be expressed as: Y M Y F M F ˆ M F ( ) ( ˆ M ˆ F X X X ) Our analysis uses the extended B-O, to binary outcomes called Farilie Method Y M M F F F N M ( ˆ M N F ) ( ˆ M N F ) ( ˆ M N F F F F X i F X i F X i ) F( X i ) Y M F F F i 1 N i 1 N i 1 N i 1 N

19 Results: Descriptive Acceptance attitudes towards people with HIV No No Yes Yes Total Total No. % No. % No. % age 5-year groups age 5-year 5, , , age 5-year 4, , , age 5-year 3, , , age 5-year 2, , , age 5-year 2, , age 5-year 1, , age 5-year 1, , age 5-year 21, , , Pearson chi2(6) = Pr = current marital status never marr 5, , , married 12, , , living toget 1, , widowed divorced , not living to , Total 21, , , Pearson chi2(5) = Pr = respondent currently working no 8, , , yes 13, , , Total 21, , , Pearson chi2(1) = Pr = highest educational level no educati 2, , primary 14, , , secondary 3, , , higher Total 21, , , Pearson chi2(3) = Pr = religion catholic 4, , , ccap 3, , , anglican seventh da 1, , other chris 8, , , muslim 2, , no religion Total 21, , , Pearson chi2(6) = Pr = frequency of reading newspaper or magazine not at all 14, , , less than o 3, , , at least on 2, , almost eve , Total 21, , , Pearson chi2(3) = Pr = 0.000

20 6. 0 Results: HIV Accepting attitudes Percent HIV Acceptance Attitudes northern Source: Calculated by Author from 2010 MDHS HIV Acceptance Attitudes southern HIV Acceptance Attitudes central Source: Calculated by Author from 2010 MDHS HIV Acceptance Attitudes Total Q : How Much is the gap? Its not weighted but when weighted we get same value in DHS. Men =36% Women=20% GAP = = -13% Ho: = mean(female)-mean(male) diff = Ho= 0 t = Pr(T >t) = Source: Calculated by Author from 2010 MDHS Source: Calculated by Author from 2010 MDHS Female Male Graphs by region 20

21 6.0 Results: contribution of ss to the gap? Determinants of GAP SS Gap Contribution Coef. Coef. %Explained Age *** *** Age *** Employment Poorer Middle Richer ** Richest ** * 0.25 No TV TV > * TV daily No Radio Rad> * * RAD daily * No News/mag * * News/Mag> * * News/MagDaily Muslim Christian_Protestant * Chistian_Catholic ** Primary *** *** Secondary *** *** Tertiary *** *** Residence_Type ** ** Residence_Type ** Residence_Type ** HIV_Test HIV_Comprehensive *** *** AIDS_Middle ** ** AIDS_High *** N= Difference Total Explained (12.785%) Unexplained 87.21% A negative sign above means that if women had characteristics of men, the GAP would have reduced by 13% In the coefficients, a negative sign means that the variable in question saves to reduce the gap A positive sign means that a variable in question increases the GAP in the Table, Secondary education, followed by reading News/ mags, pamphlets and Tertiary education reduces the GAP by 6.612%, %, 2.078% respectively= hence significant predictors of GAP 21

22 What can we learn from this? Media Education Television is not an effective way in reducing HIV/AIDS stigma as compared to Radio and news Paper Pamphlets/News/ mag and listening to radio more than Once a week are highly explaining the GAP Primary Education increases GAP where as Tertiary and secondary reduces the GAP Hence need to promote education beyond primary HCT HIV testing is highly associated with accepting attitudes But does not influence the overall gap. This might be associated with the counselling involved

23 What can we learn from this? Poverty Increases the gap in Accepting attitudes. Need for Policy that reduce poverty HIV knowledge Reduces the gap in accepting attitudes There should be health education on issues of HIV AIDS (targeting more on women) Age HIV accepting attitudes increase with Age -Need to target the age categories that are lagging behind on issues of acceptance

24 Thank you!