Data Visualization to Aid Humanitarian Intervention Strategies
Giang Nguyen1, Star Ying2, Esther Lim3,
Elliott Chun, Hannah Cho, Christian Tae, Cindy Won, Elena Zafarana4, Asaph Young Chun2,
(Note: All authors are affiliated with the International Strategy and Reconciliation Foundation.
Additional affiliations are 1University of Iowa, 2US Census Bureau, 3New York University, and
4
Switzerland Agency of Statistics)
Introduction
In its constitution, the Democratic People’s Republic of Korea (DPRK) describes itself as a self-reliant
socialist nation, founded to represent the interests of its citizens.1 However, the country has been
portrayed as a totalitarian dictatorship, with the lowest democracy index in the world.23 Amidst heated
discussion about the DPRK’s alleged violation of human rights, as well as disturbing news about its
development of nuclear weapons, documents such as the DPRK 2008 Population Census and the DPRK
National Nutrition Survey 2012 received little attention.45
The DPRK 2008 Population Census (hereinafter 2008 Census) and the DPRK Final Report of the National
Nutrition Survey 2012 (hereinafter NNS 2012) both provide insightful information about the lives and
health conditions of the people of the DPRK. The 2008 Census provides data on population size, literacy,
types of disability, and the main fuel used for cooking and heating. The NNS 2012 focuses on the health
status of women and children in the DPRK. Together, these documents portray the everyday lives and
the challenging conditions of DPRK citizens.
We aim to analyze the comprehensive data from these documents, in order to understand the evidencedriven living conditions of the people of the DPRK. More importantly, we want to provide an empirical
framework that may help the United Nations and Non-Governmental Organizations make data-driven
decisions in their humanitarian efforts. Data visualization is an effective way to communicate the
implication of data to both the general public and non-governmental agencies. In particular, interactive
visualizations allow viewers to explore the data themselves, establishing a bond between viewers and
the subject matter.
We start the paper with a literature review section, in which we lay out the major health issues in the
DPRK and discuss the data visualizations relevant to our research. Then, we present our research
questions and methodology. In the next section, we discuss our data visualizations and their findings.
The last section is dedicated to conclusions and suggestions for future research.
Literature Review
1
“‘Naenara’-Politics in Korea - Constitution.”
Freedom House, “Freedom in the World, 2006.”
3
Economist Intelligence Unit, “Democracy Index 2006.”
4
International Coalition to Stop Crimes Against Humanity in North Korea, “ICNK Welcomes UN Inquiry on North
Korea Report, Calls for Action.”
5
Brooke, “North Korea Says It Is Using Plutonium to Make A-Bombs.”
2
I.
Major Health Issues in DPRK
Prior to the 1990s, citizens of the DPRK enjoyed an effective free health-care system, and the population
health status was on par with that of developed countries.6 However, in the early 1990s, the collapse of
the Socialist Economy, together with numerous natural disasters such as severe drought and flooding,
led to worsened health indicators.7 As recent as 2009, the DPRK was facing persistent health challenges,
including high maternal mortality rate, childhood malnutrition, and the prevalence of tuberculosis and
malaria. Each of these issues will be discussed in the following subsections. In general, the capital,
Pyongyang, has the best health status, while Northern provinces, such as Ryanggang and Jagang, show
the worst health indicators in the nation.
Maternal Health
Maternal mortality in DPRK is estimated to be 90 per 100,000 population.8 The latest DPRK Census
conducted in 2008 reports that the maternal mortality ratio (MMR) increased by about 30 percent
during the 1993-2008 period, that is, from 54 to 77 maternal deaths per 100,000 live births. In 2008,
MMR in Pyongyang is 68 per 100,000 live births, which is lower than any other province in the DPRK
(Table 18).9
The NNS 2012, carried out by the Central Bureau of Statistics of the DPRK in collaboration with UN
agencies, reports two indicators for mothers’ health: mid-upper-arm circumference (MUAC) and
anaemia prevalence. At the national level, 5.3% of women aged 18-49 years have low MUAC. Ryanggang
has the highest percentage (6.6%) and Pyongyang has the lowest (3.8%) (Table 6.30). Anaemia
prevalence is assessed through haemoglobin concentration in mothers. Nationwide, 31.2% of women
aged 15-49 years are anaemic. Ryanggang has the highest prevalence (36%) and Pyongyang has the
lowest (28.9%) (Table 6.31). In addition, 74% of women aged 15-49 received the micronutrient
supplement during pregnancy. This percentage was the lowest in Ryanggang (55.1%) and the highest in
Pyongyang (88.4%) (Table 6.32).10
Children Health
The NNS 2012 also reports indicators for the health status of children aged 0 to 59 months. Three of the
key indicators are chronic malnutrition, acute malnutrition, and low MUAC.
Chronic malnutrition, also known as stunting or growth faltering, is caused by prolonged lack of
sufficient nutrition. The national percentage of chronic malnutrition is 27.9%, which has decreased from
32.3% in the last survey. The prevalence of chronic malnutrition is thus labeled “medium” public health
significance according to World Health Organization (WHO) standards. A higher percentage of boys have
6
World Health Organization, WHO Country Cooperation Strategy, DPR Korea 2009-2013.
Ibid.
8
Ibid.
9
Central Bureau of Statistics, DPR Korea 2008 Population Census National Report.
10
Central Bureau of Statistics, Democratic People’s Republic of Korea Final Report of the National Nutrition Survey
2012. Pyongyang.
7
chronic malnutrition than that of girls (29.9% compared to 25.8%). Among the provinces, Ryanggang has
the highest rate (39.6%), and Pyongyang has the lowest rate (19.6%) (Table 6.2).11
Acute malnutrition, also known as wasting or thinness, is an indicator of insufficient dietary intake over a
relatively short period of time. The national prevalence of global acute malnutrition (GAM) is 4%, which
is labeled “acceptable” public health significance according to WHO standards. There is not any
significant difference between boys and girls, or among age groups. Among the provinces, Ryanggang
and Jagang have the highest prevalence (6.1% and 5.7%, respectively, labeled “poor” according to WHO
standards) and Pyongyang has the lowest prevalence (2.3%) (Table 6.3).12
MUAC measurement is a good indicator for acute malnutrition. Low MUAC is correlated with higher
mortality in children. At the national level, 4.1% of children have low MUAC. Ryanggang has the highest
percentage of children with low MUAC (6.6%) and Pyongyang has the lowest percentage (2.1%) (Table
6.4).13
Underweight prevalence provides information on both acute and chronic malnutrition. However, it lacks
precision for definition of interventions. Other indicators (such as MUAC) are preferred. At the national
level, the prevalence of underweight is 15.2%. Ryanggang has the highest prevalence (20%), while
Pyongyang has the lowest (10%) (Table 6.8).14
Discussion about the Health Status of Women and Children
The DPRK has had valuable nutrition interventions for children and women. These interventions include
certified Baby-Friendly Hospitals, which promote breast-feeding, and Child Health Days, during which
micronutrient is supplemented to children.15 Vaccination coverage is high, mostly greater than 90%, and
child mortality is low compared to many South East Asia countries.16
Given the state’s intervention, childhood malnutrition and high MMR could be attributed to the periodic
drought and flooding, which have disrupted agriculture activities and led to malnutrition. Natural
disasters also lead to inconsistent power supply, which disrupts heating in the winter and leads to
deteriorated health condition of the population, especially among women and children. Other health
determinants include the debilitating water and sanitation system (which lead to diarrhea and
consequently malnutrition) and the ill-maintained roads throughout the country (which can prevent
access to the hospitals). Furthermore, females have a disadvantage in education, compared to males.17
This disadvantage may reflect lack of health information, which necessarily leads to worse health
conditions among females, compared to males. Therefore, an improvement in agriculture, sanitation
system, roads, and education could increase the health status among children and women.
11
Ibid.
Ibid.
13
Ibid.
14
Ibid.
15
Ibid.
16
World Health Organization, WHO Country Cooperation Strategy, DPR Korea 2009-2013.
17
Central Bureau of Statistics, DPR Korea 2008 Population Census National Report.
12
Disability, though not used as an indicator for women health, can be an indicator for population health
status. Table 42, 43, and 44 of the 2008 Census provide the counts of citizens who reported difficulty
seeing, hearing, and walking or climbing stairs, respectively. The reported count of disability is low—only
2.5% of the population is impaired with their mobility and 2.4% said they had problems with their sight.
Hearing disability has an even lower proportion. The reported figures might not necessarily reflect the
real health status of the population. Since the government labels difficulty with seeing, hearing, or
mobility as “disability”, there might be some stigma associated with these categories.18 This stigma
might prevent citizens from honestly reporting their health difficulty and lead to data that may
underrepresent the real health status of DPRK citizens.
In the disability category, the citizens from Pyongyang seem to exhibit the best health status in the
nation. In all of these data sets, a lower proportion of urbanites reported difficulty than rural citizens. In
each of these types of disability, females are reported to be more handicapped than males.
The gap in the health statuses of males and females has been attributed to the cultural and social norms
in the DPRK.19 Specifically, the patriarchal society expects a woman to put herself after her husband, her
father-in-law, and her son(s). This is a possible explanation of the difference in the health status
between males and females in the DPRK. Later in this section, the reader will notice the same gender
gap in the prevalence of tuberculosis and malaria in DPRK.
Tuberculosis (TB)
TB is a disease that causes public health concern in the DPRK. According to WHO, the annual incidence
of all forms of TB in the DPRK is 345 per 100,000 populations.20 The (all forms) TB prevalence is 423 per
100,000 populations.21 According to these figures, out of 100,000 people, 423 are currently living with
active TB, and 345 more are expected to contract TB in the next year.
According to the same article, in 2010, WHO was notified of 408 cases of TB (all forms) and 132 cases of
new smear-positive, per 100,000 populations.2223 These figures show that there is a gap between the
estimated number of new cases and the actual number of new cases in 2010. Per 100, 000 populations,
it was estimated that 345 would contract TB (of all forms) in 2010, but it turned out that 408 contracted
the disease. This is a gap of 63 cases per 100,000 populations.
It is possible, however, that the actual number of TB cases was higher than 408 in 2010. A number of
cases could have been unreported. This means that there is potentially a wider gap between the
estimated and the actual number of TB cases. It was also unclear how WHO developed the annual TB
incidence. Other sources discuss different methods of calculating TB incidence.24
18
UNFPA, “2008 Census of Population of DPRK: Key Findings.”
Linhorst, “Visualizing the ‘Hermit Kingdom’ Graphing, Mapping, and Analyzing the 2008 North Korean Census.”
20
WHO DPR Korea, “Tuberculosis in DPR Korea.”
21
These figures are at the time of the article (2010).
22
WHO DPR Korea, “Tuberculosis in DPR Korea.”
23
For a definition of new smear-positive cases, see
http://www.who.int/tb/laboratory/policy_sputum_smearpositive_tb_case/en/.
24
See, for example, http://mdgs.un.org/unsd/mdg/Metadata.aspx?IndicatorId=0&SeriesId=766.
19
On the bright side, notifications for all forms of TB and new smear-positive cases have generally
increased steadily since 2000. Notification for all forms of TB was 150 in 2000, which increased to 408 in
2010 (per 100,000 populations). Notification for new smear-positive was approximately 70 in 2000, and
increased to 132 in 2010 (per 100,000 populations). The number of notified cases of new smear-positive
TB exhibits the same trend for both genders and all age groups. However, notification for males has
been higher than that for females. For example, in 2010, approximately 4,900 cases were notified
among males, while only about 2,900 were notified among females. One possible explanation is that
males are more likely to contract new smear-positive TB. Another interpretation of the figures is that
female cases often go unreported.
While many of the figures reported in the article are numbers per 100,000 populations, the raw counts
are worth mentioning. The DPRK has a population of 24,345,000. The estimated TB incidence (all forms)
for 2010 was 82,000 and the estimated TB prevalence (all forms) was 100,000. So in 2010, 0.41% of the
population were living with active TB, while 0.34% are predicted to contract TB during the next year.
Treatment for TB relies largely on the government for support in staffing, infrastructure, drugs and
surveillance. WHO is also a major source of support, providing technical assistance and staff training, as
well as strengthening laboratory services, upgrading infrastructure, and monitoring and evaluation. In
2009, 85% of the new smear sputum positive cases were cured. However, the TB mortality rate is still
high, estimated at 25% per 100,000 population.
Malaria
Malaria is a source of national concern in the DPRK. According to WHO, 62% of the national population
lives in area with risk of malarial transmission. Six out of nine provinces in DPRK experience malaria
transmission.25
Malaria outbreaks follow the rain fall in May-July, with peak transmission during June, July and August.
93% of malarial cases are reported during the period from May to October.
Malaria is reported amongst all age groups. The age group 16-50 years has 84% of malarial infections
during 2009 and 2010. This is the trend that dates back to 2003, during which 90% of malarial infections
were reported among the age group 16-50 years. This leaves damaging consequences for the nation, as
this age group has the highest academic and economic productivity.
Since 2003, more cases in malarial infections had occurred in males than in females. In 2008, 69% of
malarial infections are among males. Not unlike the case with TB infection, this trend poses the
question: is it plausible that diseases in females are more often unreported?
According to WHO, 47% of malaria patients were farmers and 24% were workers. These two groups are
the new target population for intervention.
Similar to the case of TB, response to malaria in the DPRK is limited due to constraints in resources. In
2008 and 2009, many planned interventions could not be carried out due to lack of national resources,
while global fund was pending. This situation led to a malaria outbreak in 2008-2010. During this
25
WHO DPR Korea, “Malaria in DPR Korea.”
outbreak, transmission spread to areas that were previously free of malarial risk. Hence, funding, be it in
the form of global or national support, is necessary to prevent future malaria outbreaks.
Interestingly, during the malaria outbreak in 2008-2010, three provinces bordering the Republic of
Korea suffered from the most damages. Meanwhile, funding from Republic of Korea ceased, even
though Republic of Korea used to provide substantial support for the DPRK in its fight against malaria.
Interaction between policy makers of the two countries was insignificant, signaling a decrease in
government’s investment in malaria intervention.
In sum, malaria is a source of public health concern in the DPRK. Malaria affected the age group 16-50
years most seriously, causing long term consequences. Global fund and government support are
necessary for the success in the DPRK’s defense against malaria.
Discussion of data collection
The Country Cooperation Strategy DPRK, as well as the documents on TB and malaria in the DPRK, was
prepared by WHO. On the other hand, the Central Bureau of Statistics of DPRK collected data for the
2008 Census and the NNS 2012. Hence, there are limitations to the data in these reports, since the data
were collected through the government, who controlled the type of data collected, as well as the
method of collecting data.
The data in the NNS 2012 were collected during the harvest season. The timing might be associated with
a higher food intake of children. In addition, natural disasters subsided in 2012, which enabled the
government to maintain food ration throughout the year.26
II.
Review of DPRK-related Data Visualization Literature
The literature on DPRK-related data visualizations (DV) has been limited. In this section, we review five
DV applications and discuss their relevance to our research.
Visualizing the "Hermit Kingdom"
Visualizing the "Hermit Kingdom": Graphing, Mapping, and Analyzing the 2008 North Korean Census is
an honors capstone thesis penned by Syracuse University student Molly Linhorst.27 In her thesis, Linhorst
analyzes the data on maternal mortality and disability in the 2008 Census. DVs for each data set include
bar graphs, dot plots, and maps.
DVs on maternal mortality data show that there exists a wide gap in MMR among provinces: Pyongyang
has the lowest MMR, while Ryanggang has the highest MMR (Figure 1). However, the author argues that
MMR in the DPRK is not alarmingly high in an international context.
26
Central Bureau of Statistics, Democratic People’s Republic of Korea Final Report of the National Nutrition Survey
2012. Pyongyang.
27
Linhorst, Visualizing the ‘Hermit Kingdom’ Graphing, Mapping, and Analyzing the 2008 North Korean Census.
Figure 1: Map of MMR by provinces from Visualizing the “Hermit Kingdom”
DVs on disability data confirm our earlier report of the 2008 Census. Rural citizens are more likely than
urbanites to have disabilities, and females are more likely to have disabilities than males. As discussed
above, the gap between female and male health statuses is attributed to the cultural norm. The
discrepancy between the health statuses of rural and urban citizens is explained as follows: more elites
live in the city and therefore have more wealth and more access to black market health care system
where they can afford to by medication that they need for treatment. In addition, the central party
might redistribute resources to the elites as rewards for their loyalty.
Visualizing the “Hermit Kingdom” provides the springboards for our initial data visualization. Mapping is
an effective way to analyze data and display findings. Maps in Visualizing the “Hermit Kingdom” can be
applied to other data sets, and would be even more useful in an interactive form. In our research, we
improve upon the author’s maps to illustrate our findings of the health status in DPRK.
“Engage DPRK” Mapping Initiative28
This data visualization is an interactive map of DPRK that displays information about DPRK’s
demographics and natural hazards (called “base layers”), as well as foreign engagement in the country.
There are five different sectors of foreign engagement: humanitarian relief, business, development
assistance, educational assistance, and professional training. These are divided into further sub-sectors
that target projects and areas of focus that each particular sector would focus on. The base layers depict
flooding over the years, markets that have grown, and population. The timeline on the top of the page
allows viewers to see the trend in foreign engagement from 1995 to 2012. Users can also view
information about the weather, the economy, and the geography of the country, as well as the specifics
of the provinces.
For example, development assistance is primarily focused in the southern area of the DPRK as shown by
the multiple green dots (labeled clusters) that appear towards the southern area (Figure 2). The extent
and amount of aid that is being extended can be determined through the diameter of the clusters. The
figure below shows visualization of development assistance and flooded areas in the DPRK.
Figure 2: Development assistance and flooded areas in DPRK from “Engage DPRK”
28
Engage DPRK, “‘Engage DPRK’ Mapping Initiative.”
“Engage DPRK” takes into account confounding factors such as location of the provinces, population,
geographical effects of flooding, and poverty (shown by markets). Users therefore have a more
comprehensive way of viewing data of the DPRK. The visualization also clearly displays the similarities
and differences across the DPRK provinces.
“Engage DPRK” can be improved by including information about financial assistance. As discussed
above, many persisting health problems in the DPRK can be prevented or ameliorated with more
financial support. Therefore, it would be useful to utilize the approach of “Engage DPRK” for health data
and financial aid data.
TB data in the DPRK by World Bank (1990-2012)29
“North Korea Tuberculosis” is a simple DV that depicts the presence of TB in DPRK from 1990 to 2012.
The average value for DPRK during that period is 386.09 cases per 100,000 population, with a minimum
of 383 cases per 100,000 population in 1990. From 1990 to 2007, the number of TB cases remains close
to 383 (per 100,000). From 2008, this figure rapidly increases, reaching a maximum of 409 cases per
100,000 population in 2012 (Figure 3).
Figure 3: TB in the DPRK from “North Korea Tuberculosis”
A number of factors may have contributed to the increasing trend in TB prevalence. First, the bouts of
natural disasters in the 1990s significantly deteriorated the economic and health care systems, while
disrupting the government’s communication with its citizens. In addition, TB usually remains dormant
for many years, showing symptoms only when the immune system has been weakened due to other
29
TheGlobalEconomy.com, “North Korea Tuberculosis.”
diseases. From 1990 to 2007, the damp environment created by flooding provided the perfect breeding
grounds for TB vectors. At the same time, malnutrition, brought about by the famines of this period,
weakened the population’s immune systems. These factors may have been the cause to the explosive
prevalence of TB in 2008.
The DV suggests the DPRK’s urgent need for TB humanitarian medical aid. During the 1990-2007 period,
TB treatment was continuously provided. However, a recurrence of TB was found, regardless of the
previous treatment efforts. Thus, a shift from reactive to proactive medical assistance might be in order.
Proactive medical actions include improving TB education, regular check-ups, and supervision to ensure
compliance with preventive practice.
Visualizing DPRK’s Drought30
“Visualizing North Korea’s Worst Drought in Decades” uses satellite data to display the impact of the
drought that occurred in June 2014 in DPRK. Current vegetation levels are used as a proxy for drought.
Vegetation from June 10 through June 25 in 2014 is compared to a baseline, which is constructed as the
average level of vegetation in the same June extent for the years 2009-2013. While green areas signal
higher level of vegetation than average, areas covered in red have less vegetation than average (Figure
4).
30
developmentSEED, “Visualizing North Korea’s Worst Drought in Decades.”
Figure 4: The impact of the June 2014 drought from “Visualizing North Korea’s Worst Drought”
The majority of the DPRK is covered in red and dark red, which signals the severe impact of the drought
on the whole nation. Droughts lead to decreases in harvest and increases in food shortages, which in
turn cause malnutrition and deaths in the DPRK. Given the dry condition, fire hazard is also a concern,
posing harm to the nation’s forests and population.
The DV used Mapbox, a mapping platform, to plot the data on a map of the DPRK. Since much of our
data is divided by province, the Mapbox platform could be used to provide mapping visualizations.
North Korea and South Korea in Visualized Data31
The DV “North Korea v South Korea in figures” is an interactive application, which allows users to
compare North and South Korea in chosen categories. DPRK is represented using red figures and South
Korea is represented with blue figures.
The DV has many strengths. First, it includes many categories that encompass multiple aspects of North
and South Korea. Categories displayed are: population, GDP per capita, infant mortality rate, number of
31
The Guardian, “North Korea v South Korea in Figures - Interactive.”
internet users, net official aid, life expectancy, press freedom index, active duty, military expenditure as
a percentage of GDP, and military spending (Figure 5). These categories represent many aspects of the
two nations, such as demographics, economic situation, health status, technology, foreign relations,
press freedom, and military.
Second, the DV is very user-friendly. Users can choose one from the aforementioned categories, and a
simple click allows users to view a visual demonstration of the status of North Korea and South Korea.
The visual demonstrations are eye-catching, easy to read, and sometimes even has a touch of humor.
Lastly, each category specifies its source of data. This enables verification of information and/or
reproducible research.
Figure 5: Infant mortality rate from “North Korea v South Korea in figures”
However, a pressing question arises: how do we create the same DV? The DV does not include any
information about the computing method used in its creation. This is a question that we might consider
investigating, if we would like to produce this type of DV.
We can also learn from the graphics of the DV. We aim to create DVs that are as clear, attractive, and
user-friendly. The data sources specified in the DV can also be used to create our own, different DVs.
It might be a natural impulse to compare DPRK to South Korea, given the history shared by these two
nations. However, there is a stark contrast between GDP per capita of these two nations. South Korea’s
GDP is $32,400, which is more than four times as large as GDP of DPRK. It might be a better idea to
compare DPRK with a country with comparable GDP but with slightly better government. An example is
the Republic of Haiti.
Research Questions
The first goal of our research is to identify data that are meaningful for visualization. The plethora of
data from the 2008 Census, NNS 2012, and other documents provide comprehensive information about
the living conditions and health issues of people in the DPRK. We aim to utilize these rich data sources to
develop visualizations that are useful to both the general public and national and international policy
makers. In order to achieve this goal, we attempt to link data from multiple documents to create
visualizations. Later in this paper, the reader will come across a visualization that portrays malnutrition
and migration in DPRK. This visualization captures the correlation between health indicators and
people’s migration from areas with low health conditions. Another visualization juxtaposes global and
acute malnutrition, showing the similarity in their patterns.
A larger part of the research is dedicated to implementing statistical techniques that allow us to create
meaningful and viewer-friendly visualizations. Simultaneously, we focus on the implication of these
visualizations for the health situation in the DPRK, as well as their merits and drawbacks. In the data
visualization section of the paper, the reader will come across some of the visualizations that we
developed, each with a message that ideally helps guide and assess the health situation of children,
mothers, as well as other demographic groups in the population of DPRK.
Methodology
In order to accomplish the first goal of the research, we set out to transcribe data from the NNS 2012
into machine-readable format. Ours is the first effort to transcribe these health data and make them
available to the public. As such, transcription is the first step to understanding these data, laying the
foundation of our contribution to the research community.
In the process of transcription, each data table in the NNS 2012 was converted into an Excel
spreadsheet. We entered the data into Excel manually, relying on copy-and-paste and rigorous quality
control to ensure accuracy.
We then inputted the transcribed data into the statistical software R to create visualizations. We
explored many graphing techniques in R in order to identify the best methods for visualizing health data.
We decided to utilize the mapping and directed network methods, in order to present the data in the
context of the DPRK’s unique topography. We made use of the packages “igraph” and “ggplot” in R to
create static visualizations. Our interactive visualizations were products of the GeoJSON of DPRK
provided by Highmaps Collection.32
32
Highcharts, “HighMaps - Map Collection.”
Data Visualization and Findings
DPRK has a land area of approximately 123,138 km2 , 80% of which is mountains and uplands.33 The
northeastern part of the country is made up of high mountains, while the southwest has sea-level land.34
The mountainous structure, coupled with the long and cold winters, can present challenges to citizens of
the DPRK, especially those living in the northeastern provinces. In our visualizations, we take into
account the unique topographic structure of the DPRK. As a result, the reader will often see data
presented on a map of the DPRK.
Topography of DPRK
I.
Map Visualization of Maternal Mortality Rate
Maternal Mortality Rate (MMR) is a health metric often used by the World Bank, WHO, and other
agencies to make international comparison of mothers’ health. The reader has already encountered a
33
Data from CBS in June 2012.
The display of topography of DPRK is from the Encyclopaedia Britannica. See
http://kids.britannica.com/comptons/art-166788
34
DV that illustrates MMR in the literature review section. We improved upon this DV, using the mapping
method to delve into the health status of mothers by looking at the percentage of deaths at hospitals.35
In order to create the DVs in this section, we make use of the data from Table 18 in the 2008 Census. We
also used the shape file of the DPRK border from the GADM database.36
MMR by Province:
According to the World Bank, MMR is the number of women who die from pregnancy-related causes
per 100,000 live births.37 MMR is calculated using the formula:
(number of maternal deaths/ number of live births)*100,000.
In Visualization 1 below, MMR is color-coded from low to high, and displayed by province on a map of
the DPRK. Ryanggang, North Hamgyong and North Phyonggan have the highest MMR, while Pyongyang
has the lowest MMR. We see that Northern provinces tend to have higher MMR, while Pyongyang and
North Hwanghae, which are geographically close to each other, have lower MMR.
Percentage of Deaths at Hospital by Province:
For each province, the percentage of maternal deaths at hospital is calculated using the formula:
(number of maternal deaths at hospital/ number of maternal deaths)*100
In Visualization 2, percentage of maternal deaths at hospital is color-coded from low to high, and
displayed by province on a map of the DPRK. Pyongyang has the highest percentage, while Ryanggang,
South Hamgyong and Kangwon have the lowest percentages. A possible explanation is that the capital
has better hospital facilities; therefore, deaths occur at the hospital, as opposed to at home or
elsewhere. The three aforementioned provinces, which have the lowest percentages of deaths at
hospital, are located in mountainous areas. Therefore, citizens of those provinces might have difficulty
accessing the hospital.
35
Even though we were inspired by the Linhorst’s map of MMR, we created the DVs using our own R codes and
data files. We also made different decisions about visual elements of the map, such as choosing a different color
palette in order to bring out the trend in the map, and removing the grey background, the gridlines, and the axes
on the map.
36
www.gadm.org/download
37
http://data.worldbank.org/indicator/SH.STA.MMRT
Visualization 1: MMR by Province
Visualization 2: Percentage of Deaths at Hospital by Province
II.
Directed Network Visualization of Migrant Population
The literature review section introduced the trend that Pyongyang stood out with better health status,
while Ryanggang and Jagang showed the worst health indicators in the nation. For example, of all the
provinces, Ryanggang had the highest percentage of women with low MUAC, the highest prevalence of
anaemia in women, and the lowest percentage of women who received micronutrient supplement
during pregnancy (Table 6.30 – Table 6.32, NNS 2012). Jagang had the second highest prevalence of
anaemia in women, and the second highest prevalence of acute malnutrition in children (Table 6.31 and
Table 6.3, NNS 2012). In all of these health indicators, Pyongyang stood at the other end of the
spectrum. A natural question arises: do citizens of provinces such as Ryanggang and Jagang feel
compelled to migrate to the capital?
We visualized migrant population with three directed networks. These networks show migration from
rural area, from urban area, and from both urban and rural areas.
Visualization 3: Migrant Population with Rural Origin
Visualization 4: Migrant Population with Urban Origin
The directed networks were created using data from Table 20 of the 2008 Census. Table 20 show data
on the migrant population five years of age or older by place of origin, place of destination, and urbanrural origin. Place of origin is defined as the province of residence five years ago, while place of
destination is defined as the province of current residence.
In each of the directed networks, there are ten vertices, which represent the nine provinces and the
capital Pyongyang. We display Pyongyang in blue and the other provinces in red, in order to highlight
the capital. Arrows represent the flow of migration between two provinces. A higher migrant population
corresponds to a thicker and darker arrow. As such, provinces that are on the receiving end of heavier
arrows can be seen as the coveted destinations of migration.
It is important to clarify that each vertex serves two purposes. Each vertex represents the flow of
migration from a rural or urban (or both) origin, to both rural and urban destinations. For example, in
the visualization with urban origin, the thickest arrow shows the migrant population from urban South
Phyongan to both urban and rural Pyongyang. Its counterpart, a lighter arrow, displays the migrant
population from urban Pyongyang to both urban and rural South Phyongan.
In the visualization of migrant population with rural origin, the highest flux of migrants is from South
Phyongan to Pyongyang, as represented by the thickest arrow in the graph. There are also several other
thick arrows pointing at South Phyongan and Pyongyang, signaling the trend of migration into these two
provinces. In contrast, Ryanggang and Jagang appear isolated, as the arrows originating from and
pointing into these provinces are barely visible.
In the visualization of migration from urban area, the highest migrant population is from South
Phyongan to Pyongyang, yet again. Pyongyang and South Phyongan also stand out as destinations with
highest migrant population, as seen by the multiple arrows pointing at these provinces. Ryanggang and
Jagang again stand isolated, with little migration in and out of these provinces. Visualization of migrant
population from both rural and urban areas mirror these trends.
Visualization 5: Migrant Population with Rural and Urban Origin
III.
Interactive Map Visualization of Migration and Malnutrition (Stunting)
The directed networks introduced the idea that bad health conditions might prompt citizens to migrate
to other provinces with better health status, especially Pyongyang. In the interactive visualization
“Migration vs. Global Chronic Malnutrition (Stunting)”, we plot global chronic malnutrition in children
and net migration on the same map, in order to illustrate the relationship between a representative
health indicator and migration. Viewers can click and drag each province, if they wish to examine the
province and its net migration.
Visualization 6: DPRK Net Migration vs. Global Chronic Malnutrition (Stunting)
The visualization illustrates data from Table 20 of the 2008 Census and Table 6.7 in NNS 2012. We
previously used Table 20 to create the directed networks of migrant population. We now used the net
migration from Table 20 to illustrate migrant flow in the DPRK. Table 6.7 presents data on the
prevalence of global chronic and global acute malnutrition in children aged 0-59 months. We plotted
global chronic malnutrition in children aged 24-59.9 months as a heat map. The arrows represent net
migration; their widths are scaled to size. For this visualization and the next visualization “Scaling
Malnutrition to the DPRK”, we also used the GeoJSON of DPRK provided by Highmaps Collection.38
From the visualization, provinces with the worst malnutrition, namely Jagang and Ryanggang, appear
isolated. These provinces have little migration, and their citizens mainly migrate to Pyongyang. A
pressing observation arises: citizens of these areas are suffering from stunting, yet they are unable to
escape that situation.
Visualization 7: DPRK Net Migration vs. Global Chronic Malnutrition (Stunting) with Dislocated Provinces:
Pyongyang is the Center of Migration
IV.
Interactive Map Visualization of the Human Cost of Malnutrition
Malnutrition in children can have damaging long term consequences, as it affects the future generation
of a nation. In the interactive visualization “Scaling Malnutrition to the DPRK”, we allow users to choose
to display chronic or acute malnutrition (or both) on a map of the DPRK.
Data from Table 6.2 and Table 6.3 of NNS 2012 were used to create the visualization. Table 6.2 presents
data on the prevalence of global, moderate, and severe chronic malnutrition (also known as stunting).
Table 6.3 presents data on the prevalence of global, moderate, and severe acute malnutrition (also
38
Highcharts, “HighMaps - Map Collection.”
known as wasting). The prevalence of chronic and acute malnutrition were scaled against the total
landmass of each province.
We highlight the human cost of chronic and acute malnutrition by displaying the prevalence of these
conditions as land areas. Each type of malnutrition takes up a considerable amount of the landmass in
each province. In addition, global and moderate acute malnutrition show very little difference. A child
that is afflicted with global acute malnutrition is actually already under moderate acute malnutrition.
The implication of this trend is significant for non-governmental organizations and humanitarian efforts:
In order to tackle acute malnutrition, we must simultaneously face global and moderate cases.
Visualization 7: Scaling Malnutrition to the DPRK: Display of Global and Acute Malnutrition
Conclusion
The rich sources of data from the 2008 Census, NNS 2012, WHO Country Cooperation Strategy, among
others, portray an insightful picture of the daily lives and health conditions of DPRK citizens. By utilizing
multiple data tables from these sources, we developed a series of static and interactive visualizations
that are informative to both policymakers and the laymen. Throughout the visualizations, a trend
consistently emerges: citizens of Pyongyang enjoy the best health status in the nation, while Northern
provinces such as Ryanggang and Jagang display the worst health conditions.
We emphasize the importance of the DPRK’s natural conditions, such as its topographic structure,
climate, and natural hazards. Provinces in the mountainous areas seem to struggle the most with health
issues such as high maternal deaths, high prevalence of children’s malnutrition, and high prevalence of
TB and malaria. At the same time, people from all over the country migrate to Pyongyang, perhaps in
search of better living conditions.
High mortality and morbidity can lead to long term consequences, especially because children and
women, who are important to the nation’s future generation, seem to be at greater health risks. The
gender gap can be seen most clearly in disability, where a higher percentage of women report having
difficulty with hearing, seeing, and moving in almost every age group. Different cultural norms might
factor in this situation, and present additional challenges to health care for women.
We hope that our visualizations and review of the literature will aid Non-Governmental Organizations
and humanitarian agencies in making decisions about development programs in DPRK. However, we
caution that our visualizations display correlation, rather than causation. It is always a good practice to
understand the situation in the DPRK in depth when implementing any development and aid program.
The next step in analyzing health conditions of DPRK people would be of a comparative nature. Even
though the DPRK stands out as a self-reliant and isolated nation, there may be benefits in assessing the
situation in the DPRK in comparison to those in other countries. Future research might wish to juxtapose
the DPRK and another country in transition with comparable economic conditions.
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