Medicines Need and Access: Are there Gender Inequities? Anita Wagner Paul Ashigbie João Carapinha Aakanksha Pande Dennis Ross-Degnan Peter Stephens Saul Walker Catherine Vialle-Valentin WHO Collaborating Center in Pharmaceutical Policy

“Well, if you're not fully utilizing half the talent in the country, you're not going to get too close to the top.” Washington Post, January 27, 2007

The Economist, April 7, 2011

Reproductive Morbidity/Mortality One woman dies every 90 seconds 30 more suffer permanent disability

Lack of Physical Security

More social and statistical data are needed … to fully understand the impact of gender on access to and use of medicines. Improving access to essential medicines will be possible only if countries introduce a gender perspective in their medicines policies.

Selected Medicines & Gender Projects* 1.Household need for and access to chronic adult medicines and preventive care for children – World Health Survey, 2002, 53 mostly LMIC 2.Household access to acute and chronic medicines – MeTA/WHO Medicines Survey, , 5 African LMIC 3.Physician prescribing for diabetes, depression, and upper respiratory illness – IMS Health prescribing data , 15 LMIC 4.Gender in the HIV, TB, and malaria literature – Literature review, 126 studies, *Supported by the UK Government

No. of Countries with Gender Differences: Access to Adult Chronic Care Wagner et al, work in progress

No. of Countries with Gender Differences: Access to Adult and Child Care Wagner et al, work in progress

Adjusted Gender Effects Among Adults Odds ratio (95% CI) Self-rated health moderate, bad, very bad1.36 (1.33, 1.38) At least one chronic condition1.41 (1.38, 1.44) Arthritis diagnosis or symptoms1.46 (1.43, 1.50) Needed care within past year1.51 (1.45, 1.57) Treatment for all reported chronic conditions1.00 (0.96, 1.04) Arthritis treatment1.22 (1.16, 1.28) Acute care when needed in past year0.95 (0.85, 1.06) All or most medicines needed during last visit0.98 (0.93, 1.03) High satisfaction with health care in country1.15 (1.13, 1.17) Perceived discrimination in outpatient care due to gender1.00 (0.88, 1.14) Females coded as 1. Models control for household size; having a member age 60 years and older or a child under 5 years (adult models only); highest education of any household member; household poverty; urban location; insurance coverage; respondent age, marital status, education, and health status. Wagner et al, work in progress

Odds ratio (95% CI) At least one Vitamin A capsule in past 12 months1.03 (1.00, 1.07) At least one measles and one DPT vaccine received1.01 (0.98, 1.04) Fever, severe diarrhoea, or other illness 0.93 (0.90, 0.97) Care received for last illness 0.98 (0.94, 1.03) Treatment for malaria during last episode of fever1.01 (0.96, 1.06) Females coded as 1. Models control for household size; having a member age 60 years and older or a child under 5 years (adult models only); highest education of any household member; household poverty; urban location; insurance coverage; respondent age, marital status, education, and health status. Adjusted Gender Effects Among Children Wagner et al, work in progress

Equally Poor Access for Women & Men FemaleMale Adults Diabetes treatment, last 2 weeks 53.9 (37.8, 64.0) 54.6 (42.8, 69.3) Depression treatment, last 2 weeks 30.5 (23.4, 38.0) 27.9 (17.2, 43.7) Children <5 Vitamin A capsule, past 12 months 57.1 (30.6, 76.3) 55.3 (30.7, 73.3) Measles and one DPT vaccine 39.2 (27.0, 58.4) 39.6 (26.8, 58.7) Median (25 th, 75 th percentiles) across households in 53 countries Wagner et al, work in progress

Acute Care for Children < 5 Years in 5 African Countries*: No Systematic Gender Bias Pande et al. ICIUM2011 abstract #854 Symptom recognitionMaleFemale Fever, headache, hot body Care seeking Outside home91.2 Medicine access Medicine taken Number of medicines (mean)2.7 Medicines prescribed by doctor, nurse Medicines from private pharmacy Adherence Took all medicines recommended *Gambia, Ghana, Kenya, Nigeria, Uganda

Across Countries, More and Less than Expected Consultations for Depression Stephens et al. ICIUM2011 abstract #954 Women higher than expected Women lower than expected

Gender & Medicines in the HIV, TB, and Malaria Literature N=105 studies of gender effects on outcomes (HIV/AIDS: 68; TB: 26; malaria: 11) Most studies assess access and adherence Carapinha et al. ICIUM2011 abstract #640

Aggregate Analyses, Based on Different Data Sources, Suggest: Women frequently report more need for chronic illness care When controlling for need, no consistent gender inequities in access identified Access to care is equally poor for women and men in many countries – Need for measures of quality of care Situations in individual countries vary widely – Need for country and regional analyses

Possible Explanations? Masculinity concept – “Real men don’t get sick (or seek care or take medicines).” Women have contact with the system – Care givers – Reproductive care Equally poor access for men & women

Recommendations to Inform Decision Making Assess content of health and essential medicines policies and programs with an equity focus – International, national, and institutional level Monitor effects of policies and programs – By gender, socio-economic status, education, caste Present results from medicines research by gender and assess gender impact on outcomes – In households, facilities, systems Conduct sound comparative global and national research to address equity questions – Multi-disciplinary, multi-method

International manufacturers Drug importers Domestic manufacturers SUPPLY OF MEDICINES Manufacture & import Key questions: Are products for gender- specific conditions licensed? Are they quality-controlled? ` Wholesalers and distributors Pharmacies and retail outlets Private physicians/ other providers Private health facilities Private sector care Government procurement systems Government health facilities Public sector care Consumers and patients Insurance and risk carriers Consumer demand DEMAND FOR MEDICINES Key questions: Does household decision making on care seeking and treatment differ by gender? Can women and men access, afford, and adhere to needed medicines? Key questions: Are budgets allocated for gender-specific medicines? Do distribution channels bring medicines to where women and men need them? Key questions: Do women and men access different parts of the system? Do Standard Treatment Guidelines consider potential gender differences? Does quality of care differ for women and men? Are trained male and female health workers available, accessible, used? Do all health workers treat all patients with respect, regardless of gender? Key questions: Do risk protection schemes cover women and men equitably? Do they pay for gender-specific care and medicines?

“Women Hold up Half the Sky”…