The reason we must think about gender and M&E is because it has a powerful impact on health status outcomes. Studies for 25 years have documented that gender, measured in a variety of ways, influences a range health outcomes, including HIV/AIDS. This effect has shown to be independent of other factors. In other words, these health outcomes are influenced by gender equality regardless of economic and educational status, age, religion, urban or rural residence and a host of other factors. These factors mediate the effect of gender. For example, in the Indian state of Uttar Pradesh, it was observed that poor women with low autonomy are less likely to use antenatal and delivery care than are their wealthier counterparts with low autonomy, but poor women with higher autonomy were more likely to use maternal health services than richer women with low autonomy. This applies to almost any health outcome studied. We next focus on HIV/AIDS.
This slide gives practical examples of what has been used to indicate gender factors in quantitative analyses. At the most basic level, most health information systems collect information by sex on many areas related to HIV/AIDS programming, such as surveillance of prevalence in different populations, service utilization like VCT, PMTCT, and service delivery. Doing analyses by sex will reveal any gender differentials in these areas.Measuring other aspects of gender is more complicated. Unlike other risk factors for HIV, such as alcohol use, mobility, number of partners etc., gender is a complex construct that covers a range of areas in of itself. Many of these measures are composites of several variables, or scales with many items. The reason for this is that these areas cannot be captured with a single question or variable.The areas of measurement are important to define: what aspect of gender do we want to measure? The possibilities are listed here:Norms or roles: what people believe is defines acceptable behavior for women and menRelationship factors: how women and men relate to each other—sexual negotiation, communication about other thingsWomen’s autonomy: ability to do what she wants, make decisions, freedom of movement (going places), financial decision-making (spending money independently)Access to economic resources: land, income
Getting the G into M&EGender and Monitoring and EvaluationShelah Bloom, ScD
Overview Gender—what are we talking about? Why gender and health? New strategic developments Health programming models Getting the G into M&E
Definitions1 Sex: Biological difference between males & females1 WHO 2009: Integrating gender into HIV/AIDS programmes in the health sector
Definitions1 Gender: Beliefs about the appropriate roles, duties, rights, responsibilities, accepted behaviors, opportunities and status of women and men, in relation to one another Vary between places & change over time in the same place1 WHO 2009: Integrating gender into HIV/AIDS programmes in thehealth sector
Definitions1 Gender Equality Equal treatment in laws and policies, equal access to health resources and services within families, communities and society at large Gender Equity Absence of unfair/avoidable or preventable differences in health between women and men. Accounting for different barriers affecting women and men in benefiting from health-care programs1 WHO 2009: Integrating gender into HIV/AIDS programmes in the health sector
Gender inequality is the most pervasive form of social inequality Gender inequality cuts across all other forms such as class, caste, race and ethnicity11 WHO 2009: Integrating gender into HIV/AIDS programmes in the health sector
Why Gender? Gender inequality influences Higher child mortality, rates of stunting and wasting Lower rates of health care utilization for maternal, child, and reproductive health services (including STI/HIV) Higher maternal mortality Higher GBV Gender Inequality recognized as driver of the AIDS pandemic
Why Gender? Gender inequality index (75 countries) Low birth weight, higher fertility, infant & <5 mortality1 Lower women’s empowerment Trafficked FSWs , increased HIV risk in India2 Decreased use of maternal health services in India3 Increased neonatal mortality in Bangladesh4 Increased family planning use in Ghana5 Increased wasting in 6 African countries61Varkey et al. 2010;2 Silverman et al., 32011;Bloom et. al, 2001,4Hossain et al., 2007 5 Norwood 2011; 6Singh et al. 2011
Addressing Gender in health programs: Gender-Based Analysis1 Analyze: gender differentials Health status & determinants Care utilization needs Ability to pay Participation of in health management Gender-related influences, omissions & implications in health policy, programming & planning Leads to addressing gender explicitly1PAHO (2009). Guidelines for gender-based analysis of health data fordecision making. PAHO.
GBA Data requirements 1 Quantitative Collecting, reporting & analyzing sex disaggregated Socioeconomic determinants Gender measures Qualitative Personal experiences and perspectives, motivations, attitudes, behaviors, choices etc. Gets to the why of what quantitative data shows but often cannot explain1PAHO (2009). Guidelines for gender-based analysis of health data fordecision making. PAHO.
Monitoring Indicators that measure gender-specific outputs Indicators that track progress and effectiveness of gender-specific elements of programming Disaggregated data collection and analyses Data collection in areas such as attitudes and behavior that reflect gender norms USAID IGWG 2009, A manual for integrating gender into reproductive health and HIV programs
Evaluation Measuring impact on outcomes that relate to gender- specific programming Elements that address gender equality Data used to demonstrate progress and impact, influences demand for richer data USAID IGWG 2009, A manual for integrating gender intoreproductive health and HIV programs
Measuring Gender Sex disaggregated data: differentials in disease incidence/prevalence and service utilization/delivery Complex construct unlike many risk factors Gender equality measures that have been used for quantitative analyses in HIV/AIDS studies Norms for women and men, including attitudes about gender- based violence (GBV) Beliefs about roles Relationship factors Women’s autonomy—decision making power in various areas Independent access to economic resources Experience of GBV
Example of complex gender equalitymeasure: GEM Scale Objective is to measure attitudes towards gender norms in intimate relationships among men Used to predict multiple partners & IPV in varied contexts (Brazil, India, China, Uganda etc.) 24 items, 2 sub scales: Inequitable gender norms, Equitable gender norms Requires asking 24 (can be more or less, depending on context) items, then performing a statistical analysis
Sample Indicators Gender Equality Measures Proportion of people who say that wife beating is an acceptable way for husbands to discipline their wives Numerator: Number of respondents in an area (region, community, country) who respond "yes" to any of the following questions: Sometimes a husband is annoyed or angered by things that his wife does. In your opinion, is a husband justified in hitting or beating his wife if she is unfaithful to him disobeys her husband argues with him refuses to have sex with him does not do the housework adequately Denominator: Total number of people surveyed
Gender and Health M&E: Basics How can health information systems address gender inequality? 1 Involvement of stakeholders at all levels Sex-disaggregated data Ongoing gender training for M&E system staff Gender-integrated M&E plans1Payne, Sarah (2009). How can genderequity be addressed through healthsystems? WHO, policy brief #12
MEASURE Evaluation Provide M&E CBT to improve gender data use Improve existing data use, new data collection to capture gender-related effects of programs and policies Research to improve evidence demonstrating effects of gender on health programming and policy Global collaboration to promote knowledge base of gender M&E
Capacity building & training Regional M&E trainings: Gender module Tailored to region, context (PHN/HIV) Understanding gender basics Applied gender concepts Integrating gender into M&E plans Used in India, Senegal (French), Nigeria, South Africa Online module
Existing Data Use Know your HIV/AIDS epidemic from a gender perspective: Rwanda Objectives Illuminate gender effects on programmatic response Generate demand for richer gender-related data Assess existing national level data for potential Analyses using gender indicators (menu of options) & show gender effects Enhance data use with tool
Research to improve evidence WJEI: Benin, Kenya, South Africa, Zambia GBV initiative Qualitative evaluation Influences on design, implementation Effects
Global Collaboration Global AIDS Response Reporting “Gender Indicator” wanted Prevalence of Recent Intimate Partner Violence (IPV) Numerator: Women 15-49, have/had intimate partner, reporting physical or sexual violence in past 12 months Denominator Total women surveyed aged 15-49 who currently have or had an intimate partner
Gender M&E Resources and Tools VAW/G compendium Gender scales http://www.c-changeprogram.org/content/gender-scales- compendium/index.html K4 Health IGWG Gender and Health Toolkit http://www.k4health.org/toolkits/igwg-gender MEASURE Evaluation gender website: http://www.cpc.unc.edu/measure/our-work/gender
Gender M&E Resources and Tools:Coming soon Gender and HIV indicator menu of options Set of harmonized, agreed-on indicators TAG includes USG (PEPFAR USAID), UN (UNWomen UNAIDS, WHO, UNFPA), World Bank, GFATM & other experts Resource guide for gender data and statistics (WHO, IGWG/USAID & MEASURE Evaluation)
MEASURE Evaluation is a MEASURE project funded by theU.S. Agency for International Development and implemented bythe Carolina Population Center at the University of North Carolinaat Chapel Hill in partnership with Futures Group International,ICF Macro, John Snow, Inc., Management Sciences for Health,and Tulane University. Views expressed in this presentation do notnecessarily reflect the views of USAID or the U.S. Government.MEASURE Evaluation is the USAID Global Health Bureausprimary vehicle for supporting improvements in monitoring andevaluation in population, health and nutrition worldwide.