What does our dataset look like?
The Gender and Sexual Justice team will explore gaps in reproductive access across various countries, while considering long term repercussions and impacts in areas such as educational attainment, career prospects, and self fulfillment. However, there are gaps in data when examining global data, as not every country has information available. For example, in the indicator: “Women making their own informed decisions regarding sexual relations, contraceptive use and reproductive health care (% of women age 15-49)”, the data for 168 economies is missing entirely. There are indicator sections within the Health dataset that include data with entire countries excluded, therefore inaccurately portraying reality. Additionally, the data availability across the span of years is irregular throughout the past, with the data regarding Health fluctuating, being most available around 2010, at 90.67%, yet having 62.69% availability in 2009, and 61.14% in 2011.
What Information is Included in the Dataset?
The dataset includes a range of variables recording women’s health-related data, split by country and year at which the data was recorded. Several major data categories include reproduction, survival, finance, and government policies.
Reproduction
The dataset outlines variables related to women’s reproduction. It describes domestic factors, such as who the decision makers are regarding a woman’s health care, social factors such as participation in activities during the menstrual period, and contraception-related factors such as condom use at a young age. We are interested in investigating how reproduction factors relate to life quality outcomes throughout a woman’s life.
Survival
The dataset describes women’s mortality rates, life expectancy, and deaths from different causes. Some categories of death causes include non-communicable diseases, maternal, prenatal, and nutritional conditions, and household and ambient air pollution. Some data describe women’s mortality rates from specific causes in contrast to men’s mortality rates from the same factors to uncover gender effects on exposures to certain risks.
Finance
The dataset provides an overview of finance-related factors for women and the general population, and also delves into the specific reasons why women use or do not use a bank account. It also includes factors on women’s financial lending for medical purposes.
Government Policies
Government-related variables include government expenditure per student on primary and secondary education, immunization rates, and the country’s GDP. These factors reflect the state of the economy and the government’s implementation of programs that provide women with basic benefits, such as access to education and immunization against reproductive system diseases.
Where does our data come from?
The Gender Data Portal by the World Bank provided a large amount of data sets pertaining to various gender related issues. The origins of these data sets included Global Findex database, United Nations, UNICEF-WHO, Demographic and Health Surveys, UNAIDS, Global Health Estimates, UNFPA, Global Health Observatory Data Repository/World Health Statistics, International Monetary Fund, World Bank, and UNESCO.
Funding of the Sources
The Gender Data Portal by the World Bank compiles information from a large number of external sources. These sources also require funding. The funders of these sources for the provided data set in the Gender Data Portal include the Bill and Melinda Gates Foundation, USAIDS, voluntary contribution, contributions from members, capital markets, and investments.
What information, events, or phenomena can our dataset illuminate?
The Gender Data Portal enables analysis of key dimensions of women’s well-being across countries and years. It reveals reproductive health trends, for instance, how contraceptive use, decision-making autonomy, and menstrual practices relate to maternal mortality and adolescent fertility. It highlights survival outcomes, tracking women’s life expectancy and cause-specific death rates (e.g., non-communicable diseases, maternal conditions) and comparing them with men’s to expose gendered health risks.
On the economic front, Global Findex indicators show women’s financial inclusion—bank account ownership, medical-loan borrowing, and barriers to formal finance, and link these patterns to national GDP and education spending. Policy variables (education expenditure, immunization rates) can be paired with health and economic data to assess how public investments in schooling or immunization campaigns affect long-term outcomes for women.
Because the dataset spans multiple decades and sources (UNICEF-WHO, DHS, UNAIDS, etc.), it also illuminates the timing and impact of major global events, such as the HIV/AIDS epidemic or financial crises, on gender gaps in health and economic participation.
What our Dataset Cannot Reveal…
While the Gender Data Portal offers valuable insights into women’s health, finance, and survival, there are key limitations. Large gaps in country coverage—such as missing data for 168 economies on reproductive health indicators—reflecting how the dataset does not fully represent global realities. Inconsistent data across years also makes it difficult to track long-term trends.
The datasets ontology lacks contextual information for the data which is presented, for example when considering indicators such as “Births attended by skilled health staff (% of total)” the data table does not divulge information such as economic factors that could be contributing to the total. The cause of such results is not made clear with context.
The dataset lacks important context behind the numbers, such as economic, cultural, or political factors that affect outcomes like maternal health or financial access. It also misses intersectional details like age, ethnicity, and regional differences within countries, flattening complex experiences into averages.
Finally, the way information is divided into indicators shapes what we see. Focused mainly on measurable outcomes, the dataset overlooks less tangible but crucial aspects like social stigma, discrimination, emotional well-being, and informal labor. If this were our only source, much of the lived reality of gender inequality would remain hidden.