Are We on Track for 2030?


Predicting Hunger Reduction in the Philippines: Analyzing Food Security Factors and Progress Toward 2030

About Our Study
About Our Study

OVERVIEW

Our project analyzes global hunger and food security trends, focusing on the Philippines' progress toward hunger reduction. Using data-driven predictions, we examine key food security factors influencing hunger levels and assess whether current efforts are sufficient to meet global targets. By leveraging current data, we aim to determine if the Philippines is on track for the Zero Hunger 2030 goal.

Our project analyzes global hunger trends and uses data-driven predictions to forecast future hunger levels in the Philippines. By leveraging current data, we aim to determine if the country's hunger reduction efforts align with global progress—or if urgent action is needed to meet the Zero Hunger target by 2030.

The bigger picture

Hunger and food insecurity are problems faced globally - particularly third-world nations such as the Philippines. Because of this, we aim to analyze the situation of hunger levels in the country, how we compare globally, and what will be the status of hunger in the Philippines in the near future.

Agriculture is a significant contributor to the Philippine economy, making up 8.4% of our Gross Domestic Product (GDP), according to the Philippine Statistics Authority (PSA). But despite this, hunger and food insecurity are one of the biggest challenges facing the Philippines today. As a country with a considerable agricultural output, the fact that as much as 44.7% of the population in the country experience moderate to severe levels of food insecurity is alarming. This poses considerable risks to the nutrition of the country, especially with children, as poor nutrition may lead to the stunting of their development.

This led us to the questions...

1.HOW DOES THE PHILIPPINES’ PROGRESS IN REDUCING HUNGER COMPARE TO GLOBAL TRENDS?

2.WHAT ARE THE KEY FOOD SECURITY FACTORS INFLUENCING HUNGER REDUCTION IN THE PHILIPPINES?

3.WHAT ARE THE PROJECTED HUNGER LEVELS IN THE PHILIPPINES BY 2030?


PROBLEM

The Philippines’s state of food insecurity compared to other countries, as well as our current level of hunger in 2024 compared to past years.

SOLUTION

Our solution is to use data science to gain insights on the state of food insecurity and hunger in the Philippines, what could be our hunger level by 2030, and from there, what we can do to address this issue.

Image Illustration: iStockphoto.com

The bigger picture

Hunger and food insecurity are problems faced globally - particularly third-world nations such as the Philippines. Because of this, we aim to analyze the situation of hunger levels in the country, how we compare globally, and what will be the status of hunger in the Philippines in the near future.

Agriculture is a significant contributor to the Philippine economy, making up 8.4% of our Gross Domestic Product (GDP), according to the Philippine Statistics Authority (PSA). But despite this, hunger and food insecurity are one of the biggest challenges facing the Philippines today. As a country with a considerable agricultural output, the fact that as much as 44.7% of the population in the country experience moderate to severe levels of food insecurity is alarming. This poses considerable risks to the nutrition of the country, especially with children, as poor nutrition may lead to the stunting of their development.

This led us to the questions...

1.HOW DOES THE PHILIPPINES’ PROGRESS IN REDUCING HUNGER COMPARE TO GLOBAL TRENDS?

2.WHAT ARE THE KEY FOOD SECURITY FACTORS INFLUENCING HUNGER REDUCTION IN THE PHILIPPINES?

3.WHAT ARE THE PROJECTED HUNGER LEVELS IN THE PHILIPPINES BY 2030?


PROBLEM

The Philippines’s state of food insecurity compared to other countries, as well as our current level of hunger in 2024 compared to past years.

SOLUTION

Our solution is to use data science to gain insights on the state of food insecurity and hunger in the Philippines, what could be our hunger level by 2030, and from there, what we can do to address this issue.

Image Illustration: iStockphoto.com

The bigger picture

Hunger and food insecurity are problems faced globally - particularly third-world nations such as the Philippines. Because of this, we aim to analyze the situation of hunger levels in the country, how we compare globally, and what will be the status of hunger in the Philippines in the near future.

Agriculture is a significant contributor to the Philippine economy, making up 8.4% of our Gross Domestic Product (GDP), according to the Philippine Statistics Authority (PSA). But despite this, hunger and food insecurity are one of the biggest challenges facing the Philippines today. As a country with a considerable agricultural output, the fact that as much as 44.7% of the population in the country experience moderate to severe levels of food insecurity is alarming. This poses considerable risks to the nutrition of the country, especially with children, as poor nutrition may lead to the stunting of their development.

This led us to the questions...

1.HOW DOES THE PHILIPPINES’ PROGRESS IN REDUCING HUNGER COMPARE TO GLOBAL TRENDS?

2.WHAT ARE THE KEY FOOD SECURITY FACTORS INFLUENCING HUNGER REDUCTION IN THE PHILIPPINES?

3.WHAT ARE THE PROJECTED HUNGER LEVELS IN THE PHILIPPINES BY 2030?


PROBLEM

The Philippines’s state of food insecurity compared to other countries, as well as our current level of hunger in 2024 compared to past years.

SOLUTION

Our solution is to use data science to gain insights on the state of food insecurity and hunger in the Philippines, what could be our hunger level by 2030, and from there, what we can do to address this issue.

Image Illustration: iStockphoto.com

Hypothesis

NULL HYPOTHESIS

There is no significant trend in hunger reduction in the Philippines; future hunger levels will remain unchanged or fluctuate randomly. Food insecurity does not contribute significantly to hunger levels in the country.

NULL HYPOTHESIS

There is no significant trend in hunger reduction in the Philippines; future hunger levels will remain unchanged or fluctuate randomly. Food insecurity does not contribute significantly to hunger levels in the country.

NULL HYPOTHESIS

There is no significant trend in hunger reduction in the Philippines; future hunger levels will remain unchanged or fluctuate randomly. Food insecurity does not contribute significantly to hunger levels in the country.

NULL HYPOTHESIS

Food insecurity does not contribute significantly to hunger levels in the country.

ALTERNATIVE HYPOTHESIS

There is a significant trend in hunger reduction in the Philippines, indicating that future hunger levels can be predicted. Food insecurity contributes significantly to hunger levels in the country.

ALTERNATIVE HYPOTHESIS

There is a significant trend in hunger reduction in the Philippines, indicating that future hunger levels can be predicted. Food insecurity contributes significantly to hunger levels in the country.

ALTERNATIVE HYPOTHESIS

There is a significant trend in hunger reduction in the Philippines, indicating that future hunger levels can be predicted. Food insecurity contributes significantly to hunger levels in the country.

ALTERNATIVE HYPOTHESIS

Food insecurity contributes significantly to hunger levels in the country.

Data
Data
Data
Data

Data Collection

For this project, we utilized the comprehensive dataset used by the Global Hunger Index (GHI), a widely recognized tool for measuring and monitoring hunger on a global scale. The dataset integrates key indicators from reputable sources, including the Food and Agriculture Organization (FAO), the World Health Organization (WHO), the United Nations Children’s Fund (UNICEF), and the United Nations (UN). We also incorporated existing datasets from the Food and Agriculture Organization (FAO), with a particular focus on their Food Security Indicators.

The Global Hunger Index (GHI) includes data from 1988 to 2024, while Philippine food security indicators cover 2002 to 2023, with an estimated data size of 1,508.

PH FOOD SECURITY INDICATORS

Explore Our Dataset

Datasets include key indicators on hunger levels, food security, and malnutrition trends. However, there may be some inherent biases, as the data is collected at the national level, which may not fully capture regional disparities.

HUNGER HEROES DATA SET

To ensure continuity and avoid gaps, the dataset is divided into four non-overlapping time ranges: 1998–2004, 2005–2012, 2013–2020, and 2021–2024, centered on key years (2000, 2008, 2016, and 2024). Each entry is assigned to a range based on its starting year, even if the data spans multiple years. Ranges are contiguous, with no overlaps or gaps: 2004 ends precisely before 2005 begins, and 2020 transitions cleanly to 2021. This approach ensures consistent, transparent grouping for analysis across the entire 1998–2024 period.


Dive into our EDA

preprocessing

preprocessing

The dataset was standardized by assigning entries to four time ranges (1998–2004, 2005–2012, 2013–2020, 2021–2024) based on their start year to ensure continuity and eliminate overlaps. Multi-year entries were grouped by their starting date, even if they spanned into subsequent ranges. Inconsistent year formats were cleaned, and edge cases were resolved by prioritizing the initial year. This method guarantees full coverage from 1998 to 2024 with no gaps or redundancies.

In addition to standardizing the time ranges, we also did the following in cleaning the data.

Handling missing values: For both GHI scores and food security indicators, we decided to drop rows that had key columns missing. For GHI scores, we dropped rows whose hunger index data was not present in the reshaped training data. For food security indicators, we first dropped rows whose reference years were not within the years we counted for training data.

Conversion to numeric data: Using pandas, we converted data within certain columns such as the year for both datasets, hunger index for GHI scores, or indicator value for the food insecurity data set into numeric data.

model

model

The team plans to use time series forecasting models to predict future hunger trends in the Philippines. These models will leverage historical data to identify patterns and project future outcomes. Visualization tools will support the interpretation of these predictions.



visualization

visualization

The team utilizes data visualization tools like Matplotlib, Seaborn, and Plotly in Python to create charts and graphs that analyze trends and patterns in hunger and food security data. The resulting visuals will be tailored to highlight comparisons between the Philippines and global trends.

testing

testing

The team validates and tests the data using statistical analysis techniques to ensure accuracy and reliability in predictions. This involves assessing model performance with metrics like mean squared error. The process also includes cross-validation to confirm the robustness of the findings.


Image Illustration: iStockphoto.com

Dive Deep
Dive Deep
Dive Deep
Dive Deep

Discussion

The exploratory data analysis (EDA) revealed several important insights about the state of hunger both globally and in the Philippines. By examining key variables such as undernourishment, GDP per capita, agricultural land use, and a range of food security indicators, the analysis uncovered complex patterns that shed light on the structural nature of food insecurity—particularly in low- and middle-income countries.

At the global level, countries with lower GDP per capita consistently exhibited higher rates of undernourishment. This supports long-standing international research highlighting the role of economic strength in ensuring access to adequate food. However, this relationship is not perfectly linear. Several countries with similar income levels demonstrated vastly different hunger outcomes, suggesting that other factors—such as governance quality, efficiency of food distribution systems, levels of agricultural innovation, and social protection policies—play equally critical roles in shaping a country’s ability to combat hunger.

In the case of the Philippines, the data paints a mixed picture. The country falls within the global mid-range in terms of GDP per capita, yet continues to report troubling levels of undernourishment. This disconnect between macroeconomic growth and nutritional outcomes underscores a fundamental issue: economic growth alone does not automatically translate to improved food security. One likely contributing factor is the steady decline in agricultural land as a share of total land area over the past decades. This trend may be attributed to increased urbanization, land conversion, or underutilization of arable land—all of which compromise local food production and weaken the resilience of domestic food systems.

This national experience both mirrors and diverges from global patterns. Like many countries, the Philippines struggles with food insecurity not just as a result of limited food supply, but due to a confluence of systemic challenges. These include widespread poverty, educational disparities, persistent inflation, inadequate public health systems, and barriers to basic services in rural and geographically isolated communities. Although national-level statistics offer a broad view, they often obscure the deeper realities faced by vulnerable populations—particularly those living in rural, indigenous, and conflict-affected areas, where food access is especially precarious.

Government initiatives such as the Pantawid Pamilyang Pilipino Program (4Ps) have provided some level of social protection by offering conditional cash transfers to low-income families. However, our findings indicate that financial support alone is insufficient to resolve the multifaceted nature of hunger. Ongoing food inflation, combined with sluggish wage growth and employment instability, continues to erode the purchasing power of many households. As a result, even when food is physically available in markets, it remains inaccessible for a significant portion of the population due to affordability constraints. This highlights the importance of viewing food security through a holistic lens that accounts not only for supply and availability but also for access, utilization, and stability.

These insights collectively point toward the need for a comprehensive, long-term approach to tackling hunger. Short-term relief programs, while essential, must be complemented by systemic investments. These include strengthening agricultural infrastructure, enhancing supply chain logistics, promoting sustainable farming practices, bolstering nutritional education, and supporting community-based food systems. Moreover, it is essential to design and implement policies that are evidence-based and grounded in local realities, ensuring that interventions address the root causes of hunger rather than its symptoms.

Supporting these conclusions are visual trends from the data. The line graph on hunger index trends illustrates that both globally and in the Philippines, hunger levels have shown a gradual decline over recent years. This positive trend suggests that ongoing development efforts are making a measurable impact. Additionally, the graphs on food security indicators in the Philippines reveal that most indicators—such as food affordability, availability, and stability—are inversely proportional to the percentage of the undernourished population. This reinforces the idea that improving food security involves improving multiple interrelated factors. Finally, projections of the Philippine hunger index by 2030 indicate that, if current trajectories are maintained, hunger levels are expected to continue decreasing. This is an encouraging sign, but one that is contingent upon sustained policy commitment and targeted action.

While the global and national hunger landscapes show signs of improvement, persistent gaps remain—especially in contexts where economic progress is not matched by equitable development. The Philippines’ experience emphasizes that hunger is not merely the result of food scarcity, but of a web of socioeconomic and structural issues that require integrated and adaptive solutions. With the right data-driven strategies, meaningful progress toward ending hunger by 2030 remains within reach.

Limitations

Despite the strengths in our data, there are limits to what our analysis can capture:

  • Some datasets were outdated, making it hard to reflect current conditions.

  • Most data was regional, which limits our understanding of specific communities.

  • We didn’t explore behavioral or cultural factors, which can affect how families make food choices.

More timely and local data would allow for deeper insights. Future research could also combine this quantitative work with interviews or case studies to understand the “why” behind the numbers.


Future Work

To continue and build more on this work, we suggest the following:

  • Expanding data sources to include barangay-level and real-time data from local governments or NGOs.

  • Exploring what-if scenarios to test the impact of different policies, like school feeding programs or food subsidies.

Conclusion
Conclusion
Conclusion
Conclusion

Conclusion

Hunger and food insecurity continue to be pressing global challenges, particularly in developing nations like the Philippines. Despite having a substantial agricultural sector, nearly half of the Philippine population experiences moderate to severe food insecurity. This stark disconnect between food production capacity and actual access to nutritious food highlights systemic inefficiencies and raises deep concerns about long-term public health—especially for vulnerable groups such as children, the elderly, and rural communities.

This project aimed to explore three central questions: how the Philippines compares to global hunger trends, which local factors most significantly influence food security, and what the country’s trajectory looks like heading toward 2030. The findings reveal that although the Philippines is making some progress in reducing hunger, it remains behind many countries with comparable economic standing. Key contributing factors include the declining share of agricultural land, persistent food inflation, stagnating wage growth, and inequitable food distribution systems.

If these trends are not addressed, the risk is clear: food insecurity may persist or worsen, undermining national development and widening existing inequalities. However, the analysis also points to actionable opportunities. Moreover, reinforcing social protection initiatives with nutrition-focused goals can help ensure that no Filipino is left behind.

Critically, this project underscores that solving hunger is not simply about producing more food—it is about creating an equitable, resilient system where all individuals can consistently access safe, affordable, and nutritious meals. Data-informed policymaking, inclusive economic strategies, and a commitment to long-term planning are essential to achieving this goal.

With sustained effort, cross-sector collaboration, and a focus on both local context and global best practices, the Philippines has the potential to make real, measurable progress toward ending hunger. Achieving Zero Hunger by 2030 is an ambitious target—but with the right interventions, it remains an attainable one.

The Team
The Team
The Team
The Team

MEET THE TEAM

Coding a hunger-free Tomorrow

Jakin Bacalla

Jakin Bacalla

Jakin Bacalla

Jakin Bacalla

Gio Capili

Gio Capili

Gio Capili

Gio Capili

Michael Felizardo

Michael Felizardo

Michael Felizardo

Michael Felizardo

CS 132

GROUP 2: ZERO HUNGER

BACALLA, JAKIN MISHLE
CAPILI, GIO

FELIZARDO, MICHAEL

Our project analyzes global hunger and food security trends, focusing on the Philippines' progress toward hunger reduction. Using data-driven predictions, we examine key food security factors influencing hunger levels and assess whether current efforts are sufficient to meet global targets. By leveraging current data, we aim to determine if the Philippines is on track for the Zero Hunger 2030 goal.

© 2025 | Coding a hunger-free Tomorrow

CS 132 / 2024 - 2025

CS 132

GROUP 2: ZERO HUNGER

BACALLA, JAKIN MISHLE
CAPILI, GIO

FELIZARDO, MICHAEL

Our project analyzes global hunger and food security trends, focusing on the Philippines' progress toward hunger reduction. Using data-driven predictions, we examine key food security factors influencing hunger levels and assess whether current efforts are sufficient to meet global targets. By leveraging current data, we aim to determine if the Philippines is on track for the Zero Hunger 2030 goal.

© 2025 | Coding a hunger-free Tomorrow

CS 132 / 2024 - 2025

CS 132

GROUP 2: ZERO HUNGER

BACALLA, JAKIN MISHLE
CAPILI, GIO

FELIZARDO, MICHAEL

Our project analyzes global hunger and food security trends, focusing on the Philippines' progress toward hunger reduction. Using data-driven predictions, we examine key food security factors influencing hunger levels and assess whether current efforts are sufficient to meet global targets. By leveraging current data, we aim to determine if the Philippines is on track for the Zero Hunger 2030 goal.

© 2025 | Coding a hunger-free Tomorrow

CS 132 / 2024 - 2025

CS 132

GROUP 2: ZERO HUNGER

BACALLA, JAKIN MISHLE
CAPILI, GIO

FELIZARDO, MICHAEL

Our project analyzes global hunger and food security trends, focusing on the Philippines' progress toward hunger reduction. Using data-driven predictions, we examine key food security factors influencing hunger levels and assess whether current efforts are sufficient to meet global targets. By leveraging current data, we aim to determine if the Philippines is on track for the Zero Hunger 2030 goal.

© 2025 | Coding a hunger-free Tomorrow

CS 132 / 2024 - 2025