Exploring how dietary patterns shape the global obesity crisis
An interactive data storytelling project using open global health
datasets
Course Name & Code: Data Visualisation and
Communication (MATH2270)
Prathibha Magesh
Introduction
A Global Weight Gain Story
In the last few decades, our plates and waistlines have changed
dramatically.
Once, traditional home-cooked meals nourished families. Today,
processed snacks and fast food dominate diets across both developed and
developing nations. With drive-thrus replacing dinner tables, the world
is gaining weight fast.
Obesity is now a global epidemic, affecting over
650 million adults worldwide (WHO, 2024). The culprits?
A rapid rise in high-calorie, nutrient-poor diets,
often rich in sugar, saturated fats, and refined carbohydrates.
As countries industrialize, fast food becomes more accessible and
affordable gradually replacing traditional diets once rich in fibre,
plant-based protein, and whole grains.
This dietary shift leads to an energy imbalance,
causing excess body fat accumulation and elevating risks of type
2 diabetes, heart disease, and cancer.
How do changing intakes of sugar, fat, protein, and carbs
shape the global obesity crisis?
This project explores that question using global data from
1990 to 2022, investigating the correlations between
macronutrient intake and obesity rates
over time and geography.
Data Sources & Preprocessing
Where Our Data Comes From
To explore the nutrition-obesity link, we combined three open
global datasets:
Obesity Rates (WHO GHO)
> Age-standardized % of obese adults (BMI ≥ 30), 1990–2022
Diet Composition (FAO)
> Per capita daily kilocalories from food groups like sugar, fats,
oils, etc.
Macronutrient Supply (Our World in Data)
> Average kcal/day from carbohydrates, fat, and animal vs. plant
protein
Preprocessing Steps
- Merged datasets by
Country and Year
- Selected variables: Obesity Rate,
Sugar, Fat, Carbs,
Animal & Plant Protein
- Filtered for complete cases (no missing kcal values)
- Final dataset: 5,600+ country-year observations
(1990–2022)
This cleaned dataset is the foundation of our interactive visual
analysis.
Global Macronutrient Intake Trends (1990–2022)
Are We Eating Differently
Over Time?
This stacked area chart visualizes the average global intake (in
kcal/day) of five macronutrients from 1990 to 2022:
Key Observations:
- Carbohydrates remain the largest energy source,
though their share has slightly declined.
- Fat intake has steadily increased, reflecting
dietary shifts toward processed and high-fat foods.
- Sugar consumption rose modestly, especially
post-2000.
- Animal protein has gradually overtaken
plant protein in global diets, especially in
industrialized nations.
Implication:
These macronutrient shifts reflect a nutrition
transition from traditional diets to modern, energy-dense foods
— that aligns with rising obesity rates.
Let’s see how this connects with the global obesity curve.
Global Obesity and Nutrition Trends (1990–2022)
How Has Global Nutrition
Shifted?
Between 1990 and 2022, the world witnessed a steady
rise in obesity rates alongside noticeable dietary
shifts:
- 🍭 Sugar intake increased, particularly in
urbanized and high-income regions.
- 🧈 Fat consumption (especially from animal sources)
rose significantly.
- 🥩 Animal protein replaced many traditional
plant-based staples.
- 📉 Carbohydrate intake plateaued or declined
slightly in many regions.
What the Data Shows
- The global obesity rate has more than
doubled, climbing from ~10% in 1990 to over
23% by 2022.
- The trend aligns with increased energy-dense, nutrient-poor
diets.
- The sharpest growth occurred post-2000, coinciding
with fast food proliferation and lifestyle changes.
This global rise signals a deeper nutritional shift.
Up next: What macronutrients are most strongly
linked to this pattern?
What Drives Obesity? Macronutrient Correlations
Identifying Key Dietary
Drivers
To investigate potential contributors to the global rise in obesity,
we examined correlations between macronutrient intake and obesity rates
from 1990 to 2022.
Key Insights:
- Sugar and fat intake are strongly
and positively correlated with obesity rates.
- Animal protein shows moderate positive
correlation.
- Carbohydrates have a weak or slightly negative
correlation.
- Plant protein exhibits a weak negative
association.
Interpretation:
Diets high in sugar and fat appear to be key contributors to rising
obesity rates, while plant-based diets may offer a protective
effect.
This evidence highlights the nutritional transition driving global
obesity trends.
Next: We explore how each macronutrient individually relates to
obesity rates.
Obesity vs. Macronutrient Intake
How Does Each Nutrient
Influence Obesity?
This section explores how specific macronutrients correlate with
obesity rates based on global data (1990–2022):
- Sugar: Strong positive correlation — countries with
higher sugar intake generally have higher obesity rates.
- Fat: Also positively associated with obesity,
though less consistent than sugar.
- Carbohydrates: Weak or no clear association — some
high-carb diets correspond with lower obesity rates.
- Protein:
- Animal protein shows a mild positive trend.
- Plant protein tends to have a neutral or slightly
protective effect.

Summary: What Drives Obesity?
- Obesity has more than doubled globally since 1990.
- Sugar and fat intake show strong positive relationships with
obesity.
- Plant-based diets appear to offer modest protective effects.
- The transition to energy-dense, processed foods is a major global
concern.
These patterns offer a big-picture view, but which regions are most
affected?
Country Focus: Top 10 by Average Obesity Rate (1990–2022)
- Small island nations in the Pacific region dominate
the list.
- These countries have undergone rapid dietary
westernization, often replacing traditional, nutrient-dense
diets with imported processed foods.
- Tonga, Nauru, and Tuvalu consistently show average
obesity rates above 60%.
- High prevalence is linked to affordability of processed imports and
limited access to fresh, local foods.
Global solutions must consider localized dietary
shifts and cultural influences.
Can We Predict Obesity From Diet?
- A linear regression shows that sugar intake alone
explains ~29% of the variance in obesity.
- A multiple regression model using sugar, fat,
carbs, and proteins improves explanatory power to ~37% (R² =
0.37).
What the Prediction Plot
Shows:
- The red line represents perfect prediction (Actual =
Predicted).
- The scatter shows some variability indicating other
lifestyle, economic, and genetic factors also play a role.
- Still, macronutrient intake has a measurable and
statistically significant effect on obesity trends.
Final Reflections
Over the past three decades, global obesity rates have more
than doubled, rising alongside significant shifts in dietary
patterns. This analysis uncovered clear patterns:
- High intake of sugar, fat, and animal protein is
strongly linked to higher obesity rates.
- Nations most affected — including many Pacific
islands and resource-rich countries are
experiencing rapid nutrition and lifestyle
transitions.
- In contrast, plant-based diets and moderate
sugar consumption appear to offer protective
benefits. Together, these findings paint a powerful
picture:
Obesity is not just a personal health issue it’s a global
nutritional consequence.
Effective policy, education, and access to healthier foods are
essential to reverse this rising tide.
Reference
[1]Ritchie, H., & Roser, M. (2024). Obesity prevalence among
adults (WHO). Our World in Data. https://ourworldindata.org/grapher/obesity-prevalence-adults-who-gho
[2]Ritchie, H., & Roser, M. (2024). Daily caloric supply from
carbohydrates, protein and fat. Our World in Data. https://ourworldindata.org/grapher/daily-caloric-supply-derived-from-carbohydrates-protein-and-fat
[3]Ritchie, H., & Roser, M. (2024). Dietary composition by
country. Our World in Data. https://ourworldindata.org/grapher/dietary-composition-by-country