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Health and environmental impacts of diets worldwide

The original version of data visualization:



Data Source

💡 Reasons

• When I was looking for a data visualization for analysis, I first looked for food-related reports. That is the report that came into view, so it is a topic that I am interested in, which is healthy food and the environment. Stacked column charts are used in many of the data visualizations in this report. However, similar stacked column charts give me visual fatigue when I read the report.
• Another factor that drew my attention to this data visualization was its color, which is very cute and harmonious. However, there are more than ten colors and patterns on a chart at the same time, and the colors cannot correspond to the content one by one.

✏️ Critique

I first using data visualization effectiveness profile to evaluate the original chart.
This graph is intended to show that there has been little progress in the intake of health-promoting foods over the past decade. At the same time, the growth of foods that promote health and foods that have a greater impact on the environment and health are closely related to the development of the country.

👍 What does work well?

• Usefulness: This chart contains a lot of data to express health and diet information that is meaningful and will serve as a warning to the audience. As a result, this visualization is of high usefulness.
• Truthfulness: This visualization uses bars of varying heights to represent the intake amount of various food types, and the data expression is relatively accurate and authentic.
• Intuitiveness: Stacked column chart which is used in this visualization is also well-known to the audience, with a high level of intuitiveness.
• Aesthetics: The color matching of the chart looks harmonious and does not have many competing colors, which has certain level of aesthetic quality.

👎 What does not work well?

• Completenesss: The chart’s title cannot be inferred directly from the column chart’s data. Although I can see the data from 2010 and 2018, I am unsure of the benchmark or objective by which to measure the progress of the diet, so I consider its completeness to be only fair.
• Perceptibility: Furthermore, I will feel exhausted and confused when I look at this chart because there are so many different food types with various colors, patterns and shadings. I have to compare which color goes with which food type all the time. Particularly, the top portion of the bar has a very small area, making it difficult to see the precise value. Having too many colors will also detract from the presentation. As a result, perceptibility is significantly decreased.
• Engagement: This data visualization does a poor job of improving the interaction between users and data. The audience might be overly preoccupied with the visualization’s color and drawn in by its adorable appearance, but they might not be interested in learning more. Engagement will decline as a result of the confusing information above.

💡 How to change

1. I want to convert the original data into the annual growth rate of dietary intake. This makes the data more meaningful and understandable while also conforming to the information mentioned above. And it will improve the completeness by making the contrast more visible.
2. In response to the above problem, I want to completely change the type of chart. Because I can’t accurately see the change in the growth rate of the last decade, and the comparison between different continents, therefore, I want to construct a bar chart to represent growth rate change of different continents in the last decades.
3. I also want to separate the types of foods that promote health from those that have a greater impact on the environment and health, and merge some food types according to the content of the original text. In this way, it is easier for the audience to understand the meaning of data and thus increase its perceptibility and engagement.
4. In the chart, I want to use as few colors as possible to improve perceptibility.

🙇‍♀️ Primary Audience

-> The general public who hopes to learn about healthy diets from around the world and diet experts of health organizations are the primary audiences.
-> For reaching the audience, this visualization is 40% effective.

1. It has an eye-catching and meaningful title, which is the most attractive information for these primary audiences. This chart has a certain aesthetic quality, the colors are more harmonious, and the style may appeal to the audience. Furthermore, the type of chart used in this visualization is more familiar to the audience, and they will be willing to interpret it.
2. However, too many colors will distract the audience and keep them from focusing on the information to be expressed in the chart. At the same time, viewers want to see which categories or aspects of diet improvement demonstrate the effect. However, this graph only compares food consumption in the world and continents between 2010 and 2018. I’m not sure how this image can represent “The last decade has seen little progress in improving diets” to a general public who is encountering it for the first time. For diet experts looking for specific data, the information presented by this chart is also somewhat hazy. Therefore, when the audiences continue to watch this data visualization, they will slowly lose interest in it.

💡 Thoughts of Critique Method

This evaluation method, in my opinion, is quite effective because it includes all of the information required to analyze a data visualization.

• “Color effectiveness” can be used as an evaluation criterion. While this visualization has some aesthetics, the sheer number of colors makes viewing difficult anyway. This needs to be combined with the kind of chart to change the color. Although many colors represent many kinds, some colors are difficult to observe in the chart. Therefore the visualization is less color efficient.
• “Type of visualization” is another metric. Although the stacked column chart used in this visualization is easy to understand, when there are more than 10 pieces of information that need to be listed, the stacked column chart will not work. Because it is impossible to clearly see the specific data of each category.

✏️ Sketch and Feedbacks

According to the data visualization effectiveness profile, I draw a sketch. I changed the chart format to bar chart. I changed the original data to percentage growth and combined some data so that the overall data doesn’t look too messy. In addition, I changed the color to a uniform color to make the audience look more comfortable.

Health Diet
Infogram

👦Respondent One: Software Developer, Male, mid 40’s

• Q1: Can you tell me what you think this is?
  I think it’s an analysis of dietary health data on different continents of the world using the bar chart.

• Q2: Can you describe to me what this is telling you?
  This graph tells me that the growth rate of healthy food is negative in most countries. However, the growth rate of foods that have a greater impact on the environment and health, such as red meat, processed meat or dairy, is positive. And the intake of healthy food or unhealthy food is related to the degree of development of the country.

• Q3: Is there anything you find surprising or confusing?
  There are so many food types that it can be difficult to analyze. And although the explanatory text below the title mentions what are the foods that have a greater impact on the environment and health, there seems to be no distinction in the chart.

• Q4: Who do you think is the intended audience for this?
  I guess the intended audience will be experts in the field of diet.

• Q5: Is there anything you would change or do differently?
  I would like to replace the above filter, because it is difficult to compare the data of each country in the current form. I would also like to see a chart clearly distinguishing between good and bad foods.

👧Respondent Two: Student, Female, mid 20’s

• Q1: Can you tell me what you think this is?
  This may be a report on the data on the global increase in diet in the past ten years.

• Q2: Can you describe to me what this is telling you?
  I can see that the negative growth of food intake has been relatively significant over the past ten years in some continents, like Africa and Oceania. The least amount of food categories in North America are experiencing negative growth. The positive and negative dietary changes connected to the country’s income profile are displayed in the text below the heading.

• Q3: Is there anything you find surprising or confusing?
  The dynamic display that followed this screening and classification pleasantly surprised me. However, I’m a little perplexed because it doesn’t appear that the foods mentioned in the text that have a significant impact on the environment and health are represented in this chart.

• Q4: Who do you think is the intended audience for this?
  People who work for a health organization, for example, or those who want to learn how to improve their diet, I believe, are the intended audiences.

• Q5: Is there anything you would change or do differently?
  If it were up to me, I would either compare data from various continents in a single plane or group continents that perform reasonably well together. We can only draw the second conclusion from the text in this way.

📓 Feedbacks from classmates

1. Love
   • Love the single color used.
   • Love the pop-up labels on the chart.
   • Love that each continent is represented by a graph.
2. Something could change
   • Remove the marks of percentage numbers for each bar. With pop-ups and X-axis data already in the visualization, too many data flags can get confusing.
   • Put all the charts into one page to make the comparison much clearer.
   • Give different colors for the two large catogories, “health-improving food” and “health-affecting food”.

📓 Conclusions from Feedbacks

1. The current sketch as a whole can correctly express the meaning of the data.
2. The bar charts from various continents should be compared on a single board, and the filter should be removed.
3. Color or other methods that can better explain the problem should be used to distinguish between foods that promote health and foods that are more harmful to the environment and health.
4. I believe some textual expressions can be added to clarify the point of the visualization.
5. I think it will be more clear to remove the marks of percentage data of each bar.

🎆 Final Visualization

💡 Tips: Audiences can use the ranking function to rank the growth rate of different food intake for each country.

📓 Summary for redesign

1. What the redesigned data visualization shows?
The redesigned data visualization is intended for diet experts and staff at national professional health institutions, as well as members of the general public who are interested in dietary health, such as myself.
This data visualization depicts how healthy diwt has changed in different parts of the world over the last decade. Foods with green color are relatively healthy, while those of red color are harmful to the environment and health. The countries in the first row, according to the original text, may have performed better over the last decade. However, both positive and negative dietary change are more common in high-income or upper-middle-income countries. Over the last decade, the world has made little progress in improving diets.

2. Reasons for selecting the redesigned data visualization.
To begin with, the bar chart clearly depicts the rate of growth in consumption of various food types over the last decade. The grid format allows for a clear comparison of food consumption around the world. I added a filter to choose between health-improving and health-affecting foods, and the colors can represent two different food categories. At the same time, each bar chart in this data visualization can be sorted according to the rate of increase in food consumption, making it easier for audiences to observe and study data.

3. The differences between the sketch and the final redesigned one.

• The layout of the chart is different. Sketch employs filters to place various regions on different pages. However, the new visualization arranges them in a grid on a single plane.
• The six areas are divided into two lines in the redesigned visualization. The first line represents the areas that have done relatively well in terms of diet improvement over the last ten years.
• The redesigned data visualization employs two colors to represent two major food categories, which can more accurately reflect the original context meaning.
• The size of the growth rate can be sorted in the new visualization.
• The redesigned visualization can rank the rates of growth of various food groups in each region.
• The redesigned visualization includes additional captions.
• The redesigned visualization includes filters for selecting health-improving food/health-affecting food.
  
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