I. What is gender analysis?  

Gender analysis is a structured analytical method used to detect, evaluate, and describe gender differences within a dataset. Gender analysis examines the different roles, rights, and opportunities of men, women, and non-binary people, and their interrelationships. Gender analysis uncovers disparities and gaps between genders, examines the reason behind the disparities, and looks for ways to address them. 

II. Why conduct a gender analysis? 

There are four main reasons to conduct a gender analysis on health data: 

  • To understand the cultural context of gender roles and experiences 
  • To identify root causes of gender inequity within a health issue or area  
  • To analyze how power and policies impact genders differently 
  • To identify ways to address gendered health inequities in a given country or region through changes in policies and programs.  
This illustration is AI10 EPS.

III. How to conduct a gender analysis 

The steps to conducting a gender analysis are to 1) define the issue, 2) look at secondary data, 3) conduct further research to understand data gaps, and 4) analyze the data to conceptualize new programs and policies that are gender equitable.  

Gender analysis can be done on health impact data, disease prevalence data, health systems data, or any other health issue that potentially impacts people of different genders disproportionately. 

1) Define the issue 

The first step in gender analysis is to identify an issue you want to explore and develop a hypothesis. Here’s an example: We know that there are different rates of tobacco smoking among men and women in different environments, and that smoking is the leading cause of lung cancer deaths around the world. Smoking is seen as a masculine behavior in many countries (gender norm), leading to higher rates of smoking among men. Women who are related to these men smoke less, and yet are still affected by the secondhand smoke from their male family members.   

A hypothesis based on cancer registry data could be: Women in my country may have higher rates of cancer mortality from secondhand tobacco smoke due to the high rates of smoking of their male family members.   

 2) Secondary Data 

The next step is to look at available data on the health topic in your country or region. Create a data collection matrix that contains the gender-related research questions to be answered, the data to be acquired, the source of the data, who will collect it, methodology for collection and analysis, and how the information will be utilized.  

Data Matrix Sample 

Question Data Source Responsible party Methodology Use  
How can we reduce the effects of secondhand smoke on women in India? Cancer registry and cause of death data disaggregated by sex; smoking rates disaggregated by sex Cancer registries, household surveys; cause of death registries Demographer/ statistician Cross reference lung cancer mortality by sex with smoking rates by sex Develop programs and policies to reduce women’s access to secondhand smoke 

Once the sources are recognized and data is collected, the data needs to be analyzed using a gender analytical framework focusing on these four areas: 

a. Access to assets: This means tangible assets such as land, money, and tools, and intangible assets such as knowledge, education and information.  

Example: Women in many countries have less monetary assets, and so may not be able to spend money to improve the ventilation in their homes in order to reduce secondhand smoke. 

b. Practices and participation: This area captures information on men and women’s roles, the timing and place where their activities occur, their capacity to participate in different types of economic, political, and social activities, and their decision-making. 

Example: In many low and middle-income countries, women bear the burden of domestic work, placing them in increased contact with secondhand smoke from their relatives.  

c. Beliefs and perceptions: This covers belief systems and norms about what it means to be a man or woman in a given culture or society. 

Example: In many countries, more men smoke cigarettes than women because it is considered a masculine norm.  

d. Institutions, laws, and policies: This area is about men’s and women’s formal and informal rights and how each gender is affected by health system policies and rules.  

Example: Some national tobacco prevention programs are designed to prevent smoking during pregnancy, focusing only on the health of the unborn child. This program overlooks secondhand smoke that some women are exposed to throughout their lives.   

3) Mind the Data Gaps 

In many cases, secondary research on data collected prior identifies critical gender data gaps. There are two ways to address gender gaps at this stage. One is to conduct additional primary research. You can use qualitative or quantitative data collection tools to conduct primary research on items that might fill the data gaps. Another way to address the gaps is to cross reference multiple data sources – for example, you can look at death registration data and data collected from verbal autopsies to uncover gender disparities in tobacco-related deaths among women from secondhand smoke. 

4) Data analysis and conclusion 

The last step is to analyze all the collected data on the four domains of the gender analytical framework. This analysis will answer questions posed about the gender inequalities that exist and how and why they affect men’s and women’s lives differently. You can then use the results of the analysis to collaborate with partners and design new programs and policies that are gender-responsive and designed to have an impact on health outcomes for the affected populations and subpopulations.