This blog post is part of a series looking at key questions related to gender analysis within health systems research. In this post we explore how health systems researchers can include more meaningful gender analysis within their research by moving beyond sex disaggregation.
RinGs Steering Committee
On 8 September 2015 Research in Gender and Ethics (RinGs): Building Stronger Health Systems held a cross-RPC webinar on “How to do gender analysis within health systems research”. The webinar involved 26 members from Future Health Systems, ReBUILD, and RESYST.
Webinar participants asked some very interesting and relevant questions about how gender analysis can be incorporated into health systems research. In this blog series, we discuss some of the issues raised and we would be interested in your viewpoints as well. Please let us know in the comments section below!
Q: Most health systems research disaggregates by sex, however, this is often related to demographics and overall descriptive results. How do we move beyond sex disaggregation to ensure that health systems research includes more meaningful gender analysis? Male participant, Uganda
A: While it is true that a lot of research includes a demographic question about sex, this is not necessarily the case. Research on community participation many times fails to disaggregate by sex or any other socio-demographic identifiers. It therefore may unintentionally leave out the most vulnerable.
Sex disaggregation is critical within health systems research as aggregated datasets can mask differences between men and women, a bias which negatively affects the validity and reliability of research evidence. However, sex disaggregation is only a starting point to gender analysis. A study that only disaggregates by sex may be able to tell you that differences exist between men and women, however, it will not be able to tell you why those differences exist and what can be done about them. Or that sex is not statistically significant, contrary to our assumptions, but we don’t understand why or why not.
As suggested by this webinar, by applying gender analysis frameworks to frame further questions in data collection and analysis, research can move beyond sex disaggregation to understand more about how gender power relations operate in health systems. For example, factors underpinning sex differences in accessing health services can be examined by asking who controls resources at the household level and whether or not those resources are used for health care. It may also ask who does what activities within the home and how this impacts a person’s ability to travel to a health center. It may also explore how health care services are organized and whether men feel comfortable seeking care from them.
In addition, analysis should extend beyond sex disaggregation and incorporate intersectional analysis to explore the interactive influence of other social stratifiers, such as age, class, ethnicity, education, or location, for example, and how these intersect with gender. In particular, such analyses will be able to show us how power relations structure the lived experiences of different socially marginalized and vulnerable groups.
Research on health workers, for example, will often ask what type of health worker the respondent is but leave out information related to sex, age, ethnic or caste background, level of training, type of contract, etc. We may therefore assume that having a predominantly female frontline health work force is a positive sign, signaling greater opportunities for women. However, in more marginalized regions of South Asia, for example, many of these women come from the rural elite. On a broader level, it is also problematic if women are primarily employed in levels of the health workforce that have limited career pathways and are poorly paid.
While sex disaggregation is an important component of gender analysis, in order to ensure that health systems research includes more meaningful gender analysis, health systems researchers must move beyond sex disaggregation. The use of gender analysis frameworks to frame futher gender sensitive questions in data collection and analysis, as well as the use of intersectional analysis, can help health systems researchers ensure their research effectively incorporates gender analysis.
Next week this blog series will explore the significance of gender as a variable.
To view a recording of the webinar or the webinar presentation slides, click here.
For more information about RinGs visit our website.