Equity and gender analysis of health information
SEARO/WPRO Bi-Regional Health Information Systems Meeting, Bangkok, December 13-15, 2004 Gabrielle Ross, SEARO and Anjana Bhushan, WPRO
Gender analysis and planning (gender mainstreaming)
3 Steps
Sex disaggregated data Determining why Planning different responses for different needs
Polio cases (India)
2000 1500 1000 500 0 2000 2001 2002 2003 2004
Polio cases (India)
1000 800 600 400 200 0 2000 2001 2002 2003 2004 Girls Boys
Determining why
Biological/epidemiological factors (sex)
Do girls have a natural advantage? Does this reflect a skewed sex ratio?
Sociocultural factors (gender)
Are girls less exposed? Are fewer boys immunized? Are surveillance systems missing girls?
Male:Female ratio of smear-positive TB notifications, by age group
WHO Region 0-14 15-24 25-34
SEARO WPRO 0.60 1.33 1.66
Age Group (years) 35-44
2.39
45-54
2.90
55-64
3.08
65+
3.15
Total
2.03
0.78
1.40
1.78
2.27
2.54
2.51
2.48
2.09
Smear positive cases
Viet Nam 1990-1999
4000 3500 3000 2500 2000 1500 1000 500 0 1991 1993 1995 1997 1999 Male Female
Determining why
Biological/epidemiological factors (sex)
Are there fewer women in the population with active TB?
Socio-cultural factors (gender)
Do men work at jobs that place them at greater risk of contracting TB? Do fewer women seek treatment? Are women less likely to test positive?
Developing appropriate responses
Gender blind
„Do no harm‟
Gender sensitive
Gender transformative
WHO gender policy
“. . . all programmes will be expected to collect data disaggregated by sex, review and reflect on the gender aspects of their respective areas of work, and initiate work to develop context-specific materials.”
-WHO, Integrating Gender Perspectives in the Work of WHO: The WHO Gender Policy, 2002
Other dimensions of equity
• • Disaggregation by income: measurement difficulties Examine disparities by other “proxies”:
Geographical location (rural/urban) Age Ethnicity Employment status Etc.
• •
Try to assess why the disparities exist Develop appropriate responses
Why do we need equity analysis?
Efficiency
Blunt, across-the-board approaches often miss the mark, waste resources
Social justice
Women and men have distinct health needs due to biological (sex) and social cultural (gender) factors Similar differences exist between various groups
Human rights
Health equity and rights
Recommendations
1. Request disaggregated data in WHO and Member States 2. Strengthen equity and gender analysis skills among health policy analysts in WHO and countries 3. Produce “MDG plus” reports which include disaggregated data and equity and gender analysis