Using Series of Maps to Represent Changes in Time: How Diabetes Swept the U.S.

Maps are generally two-dimensional representations of the world, so by their nature they cannot represent time. Yet often it is interesting to see how the spatial distribution of a given parameter changes over time. Some creative ways have been developed to track temporal changes through maps. One such technique is designing a series of similar maps representing different time points and using the same color scheme to depict the scope or intensity of a given feature. For example, in an earlier GeoCurrents post, we have shown the spread of the influence of the Svoboda (“Freedom”) party in Ukraine through a series of maps (reproduced on the left) that represent four time points. As can be seen from these maps, the party’s core area of influence was in and around the city of Lviv in far western Ukraine, from where it has extended first to other major urban centers of western Ukraine, including Ternopil and Ivano-Frankivsk, and then continued to spread eastwards. In October 2012 national elections, Svoboda moved up to the next level and won seats in the Verkhovna Rada, the national parliament, for the first time.

Another example of such a series of maps to represent changes over time (see image on the left) depicts the dramatic rise in diabetes in the U.S., which some people have characterized as an epidemic.* The Centers for Disease Control and Prevention (CDC) provides state-by-state figures on self-reported diabetes in adults collected during 1995–2010 by the Behavioral Risk Factor Surveillance System (BRFSS). But maps make the scale of this problem easier to grasp. According to the CDC, in 2010, some 18.8 million Americans were diagnosed with diabetes and another 7 million had diabetes but had not been diagnosed. This high prevalence of over 8% of the population diagnosed with diabetes is relatively new, as 15 years earlier only about 4.5% of Americans had been diagnosed with diabetes. Since 1990, the prevalence of diagnosed diabetes in the United States has risen sharply among all age groups, both sexes, and all racial/ethnic groups for which data are available.

Another thing to note is that the diabetes rate is not uniform over the country: diabetes appears to be more common in the South, Mid-Atlantic and southern Midwest states, as well as in California and Nevada. In 2010, the figure was highest among states in the South (9.8%), compared to 7.5% in the Midwest, 7.3% in the Northeast, and 7.3% in the West. In 1995, however, only in three states (California, Louisiana, and Mississippi) and in District of Columbia was diabetes prevalence 6% or greater. By 2010, diabetes had increased everywhere to above 6%. In 1995, twelve states, most of them in the north, had less than 4% of the population diagnosed with diabetes, but already five years later not a single state was in the “less than 4%” category. In Kentucky, the figure jumped from less than 4% to above 6% in the span of these five years. By 2005, eleven states moved into the 8-10% category and one—South Carolina—has gone into the “greater than 10%” category. By 2010, five states (West Virginia, Tennessee, South Carolina, Alabama, and Texas) and District of Columbia found themselves in that highest category, while an additional 21 states had 8-10% diabetes rate. The lowest prevalence (6.0%–6.9%) is found in 12 states: Alaska, Colorado, Connecticut, Iowa, Minnesota, Montana, North Dakota, Oregon, South Dakota, Wisconsin, Vermont, and Wyoming.

Clearly, strategies to prevent diabetes and its preventable risk factors are needed, especially for those at highest risk for diabetes, to slow the rise in diabetes prevalence across the United States.

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*The figures above include both Type 1 (“juvenile diabetes”) and Type 2 (“adult-onset diabetes”) diabetes. Figures for gestational diabetes are not included in the calculation.

GeoCurrents.info provides map-illustrated analyses of current events, delving into the often overlooked geographic and cultural contexts that shape these world developments. Led by Stanford University Senior Lecturer Martin W. Lewis and linguist Asya Pereltsvaig.