Maternal Mortality Ratios

Nina Gertsvolf


The Millennium Development Goals were established at the United Nations Millennium Summit in 2000 in order to improve social and economic conditions in low-income countries throughout the world. They are unique in that they specify particular targets for achieving human development goals and reducing poverty, as opposed to previous goals that focused solely on economic growth. This information visualization project will focus on MDG 5 – improving maternal health. The two specific targets for this goal are to reduce the maternal mortality ratio by three quarters (between 1990 and 2015) and to achieve universal access to reproductive health care. This statistic is a good way to measure access to health care because the majority of these deaths are preventable (and generally represent the first cases that doctors attend to if medical care is available in that region). It is also an important issue to keep in mind because it represents women’s health and empowerment.

I will present the data for the maternal mortality ratios in several different ways – each graphic targeted at a specific audience. This statistic is calculated as the ratio of the number of maternal deaths to the number of live births in a given year, expressed per 100,000 live births. The data used to create these visualizations are those available to the Human Development Report Office in May 2011. They were collected by the WHO, UNICEF, UNFPA and the World Bank in 2010.

Visualization #1: Gapminder World Map (2008)

The world map is perhaps one of the easiest ways to understand the implications of this data. Rather than coloring different regions, I chose to use bubbles to represent maternal mortality, with larger bubbles representing a higher rate. This representation highlights different regions by color, so geographic trends will be easier to analyze. For example, there is a significant difference in bubble size between North and South Africa, indicating that sub-Saharan countries have a much higher maternal mortality rate. This is a trend that a regular excel presentation of the data would not necessarily highlight. The map is also interactive and allows the viewer to scroll over different bubbles to learn more specific information such as country name and maternal mortality rate. The map clearly represents the information in a manner that allows the viewer to understand regional relationships and patterns while also including pertinent statistics in the sidebar. The target audience would probably be most students studying this topic (at any age or grade level) or even the general public – for example, the map might be printed in a high school textbook or a newspaper article about MDG progress.

Visualization #2: Bubble Chart (1980 – 2008)

The Bubble Chart portrays the data in an abstract, less conventional manner. Rather than graphing the statistics, it presents an interactive, comparative visualization that allows the viewer to analyze the mortality rates in terms of one another. Additionally, the sidebar allows the viewer to scroll through the dates and watch the bubbles growing or shrinking with time, often associated with various political, social and economic changes in each country. In much the same manner as the world map, the bubble sizes correspond with maternal mortality rates rather than population size. An interesting thing to note is that the number of large bubbles decreases significantly between 1980 and 2008, perhaps because the number of countries with high maternal mortality rates has decreased as well. While this is generally a sign of progress in that most countries have increased access to maternal health care, certain regions have accomplished little to no improvements at all. Unfortunately, in certain countries the rate has even increased, such as the Central African Republic. This type of graphic is especially useful for viewers that want to compare rates between countries and are more abstract in their perspectives. The benefit is that this type of graphic is more creative and presents the same data in a fresh, unconventional manner. It is more accessible for someone with a computer as well as Internet access because it requires switching between years and scrolling over bubbles with a mouse. The graphic might be embedded into a website or blog that discusses the impacts and perhaps the progress (or lack thereof) of the MDGs.

Visualization #3: Stack Graph (1980- 2008)

The stack graph is perhaps the most conventional of all data visualizations. It charts maternal mortality rates per country over time. Similarly to the bubble chart, the stack graph requires the viewer to use the sidebar to scroll through different countries in order to compare. The benefits of this type of visualization is that it allows viewers to track progress per country. However, one of the drawbacks is that each country has a different scaling for maternal mortality rates on the y-axis (i.e. for Afghanistan, values range from 0 to 2,000 per 100,000, while for Belgium, values range from 0 to 12 per 100,000). For someone unfamiliar with statistics or mathematics, this might be somewhat confusing when comparing progress. However, this visualization is especially important in analyzing trends in each country and determining the extent of improvement (or failure) in increasing access to health care. This type of visualization might be included in a modern version of a journal publication that is disseminated online. It allows viewers to obtain valuable data in far less space. While a conventional paper publication would necessitate that the author pick and choose specific countries and then print multiple graphs presenting the change in maternal mortality over time, this visualization gives the viewer control and allows him or her to choose the parameters. Though multimedia is typically thought to target the general public, now it can be used to spread information to the scientific community as well.

Visualization #4: Wordle

The final visualization is perhaps the least conventional method to represent data. Rather than presenting the statistics as in the three previous graphics, I used a word map to analyze common themes and ideas in an article from the Lancet analyzing some of the difficulties associated with MDG #5, improving maternal health. This graphic conveys the same message that reading the article would convey to the reader, but in a much quicker, more accessible manner. Words that are used most often are largest, instantly grabbing the viewers attention. The most common themes include estimates, predictability and uncertainty, indicating that though researchers, policy makers, health care providers, and communities are working hard to improve maternal health care, it is difficult to track progress and accurately analyze trends. Global issues and trends are also a prevalent theme. Though this graphic is far less “scientific” than the others, it provides valuable insight and information that the others don’t highlight. The wordle tells the viewer that despite all the statistics and measurements presented in conventional data visualizations, there still exists some ambiguity as to their validity. Given political instability, lack of sufficient documentation, and human error, there still exists the possibility that not all of the data collected is accurate – perhaps maternal mortality rates in certain countries is much higher than reported (as for other diseases as well). The benefit of the wordle is that it allows the viewer to learn more about the article without having to read through the entire document.


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