Data Visualization

Blog of the Data Visualization & Communication Course at OSB-AUB

This is my favorite part about analytics: Taking boring flat data and bringing it to life through visualization” John Tukey

Health Behaviors and Medical Bills: A Story Told Through Data

Health Behaviors and Medical Bills: A Story Told Through Data

We all know that smoking is bad, drinking adds risk, and skipping workouts isn’t ideal.
But what if we could see the financial price of these choices, in dollars, not just diagnoses?

Our project, “The Cost of Health,” does exactly that.

Using a dataset of 100,000 individuals, we visualized how small, everyday behaviours quietly add up to big medical bills.
This story isn’t about judgment, it’s about awareness through data.

The Numbers Behind Everyday Habits:

 

Smoking: The 30% Surcharge on Health

The data spoke clearly , smokers pay about 30% more every year in medical expenses.
Even former smokers, who may have quit years ago, still carry higher costs.
Quitting improves health, but the financial scars of smoking linger long after the last cigarette.

A reminder that every puff today becomes a price tomorrow.

 
Alcohol: A Quiet Contributor to Rising Costs

Not all habits seem harmful at first glance, a drink after work, a skipped walk, a few extra pounds.
But the data showed that even these add up:
Every 5-point rise in BMI brought a 7% increase in annual medical costs, and daily drinkers consistently spent more than occasional ones.

Health choices we normalize today become costs we pay tomorrow.

 

Hospital Visits: The Costliest Habit of All

Among all factors, hospitalization frequency had the strongest impact on spending.
The data showed that individuals hospitalized three or more times per year paid three to four times more in annual healthcare costs.

Each extra hospital stay turns prevention into an even higher price to pay.

Behind this number are thousands of preventable conditions (unmanaged blood pressure, skipped screenings, and delayed doctor visits) that eventually lead to hospitalization. The message is clear: investing in prevention costs far less than paying for treatment later.

 

BMI: When Weight and Wallet Move Together

Weight turned out to be more than a health number, it’s an economic one too.
For every five-point increase in BMI, annual medical spending rose by about 7%.
Healthy BMI levels (20–25) aligned with noticeably lower costs, while obesity pushed expenses sharply higher.

A few extra points on the scale can mean hundreds more dollars each year.

This is one of the clearest examples of how small daily choices (diet, movement, and routine) ripple into real economic outcomes.

 

Chronic Illness: The Multiplier Effect

For those living with multiple health conditions, the financial impact is staggering.
Someone managing four chronic diseases pays nearly three times more in yearly healthcare costs than someone without any.
Each hospital visit doesn’t just affect the body, it affects the wallet.

Health, once lost, becomes the most expensive asset to recover.

 

What About Lebanon?

To bring the story closer to home, we conducted a small survey in Lebanon to understand how people perceive the link between lifestyle and healthcare costs. The responses reflected the same global trends, showing that smoking, excess weight, and frequent hospital visits are seen as major cost drivers.

When asked what could encourage healthier habits, more than half said workplace wellness programs (50.6%) or insurance rewards (49.4%) would motivate them to take better care of their health,  more than social media campaigns or community events.

Money talks, even when it comes to health.

This finding connects back to our main insight:
If prevention saves both lives and money, then maybe the most effective awareness strategy isn’t guilt, it’s financial incentive.

 

Visualizing the Invisible

Our Power BI dashboard was designed not just to show data, but to start a conversation.
Anyone can explore it, filter by gender, smoker status, or work type, and see how lifestyle, health, and costs intertwine.

An interactive way to see how lifestyle choices shape your health costs.

 

The Story Beneath the Numbers

Behind every data point is a life: a mother managing diabetes, a student stressed and sleepless, a retiree balancing medications and bills.
Numbers can’t capture the full story, but they can reveal patterns that change it.

Our visualization doesn’t tell people what to do.
It simply holds up a mirror

Your health choices have a price tag. But that also means, you have the power to lower it.

Mapping Lebanon’s Healthcare Divide: When Access Depends on Where You Live

Mapping Lebanon’s Healthcare Divide: When Access Depends on Where You Live

A Country of Contrasts

In Lebanon, access to healthcare can change drastically with geography.
A person in Tripoli can find a clinic or pharmacy on nearly every corner, while someone in Hermel or Zahleh might travel hours for the same care.

Using data obtained from the AUB Linked Open Data Portal, I explored how healthcare facilities are distributed across more than 1,100 Lebanese towns. The goal was to understand whether medical services are spread evenly across the country or concentrated in only a few locations.

Uneven Access Across Towns

The data reveals a clear imbalance.
Healthcare services are heavily centralized in urban areas, particularly Tripoli, Saida, and Haret Hreik, which together host the largest share of Lebanon’s medical facilities.

Tripoli alone has more than 230 healthcare establishments, while dozens of smaller towns have fewer than 20 facilities, and some have none at all.

This concentration means that people living in rural and inland areas often need to travel long distances for even basic medical services, while urban hospitals and clinics struggle with overcrowding and high patient loads.

It highlights a system where location determines opportunity, where healthcare is available not based on need, but on proximity to major cities.

What Kinds of Facilities Exist?

When we look at the types of healthcare facilities, pharmacies and clinics dominate the landscape.
They make up the majority of Lebanon’s healthcare infrastructure, far outnumbering hospitals and specialized centers.

While pharmacies and small clinics ensure access to medication and consultations, hospitals and diagnostic centers are much fewer, especially outside major cities.
This shows a healthcare system that leans more on treatment through medication than on preventive or emergency care.

Balancing the Map: How Geography Shapes Access

Together, these findings reveal how geography continues to shape healthcare opportunities in Lebanon.
The concentration of facilities in urban centers not only affects access but also contributes to inequalities in health outcomes.
Urban residents have quicker access to doctors, specialists, and emergency units, while rural populations often rely on limited local clinics or travel hours to reach adequate care.

These patterns underline the urgent need for balanced healthcare investment.
Rural areas require new clinics, laboratories, and emergency units that bring services closer to people’s homes.
Improving healthcare equity is not only a matter of infrastructure, it’s about ensuring that every Lebanese citizen, regardless of location, can access timely, reliable care.

Final Reflection

This analysis shows how data visualization can make inequality visible.
By mapping and quantifying healthcare access, we can move beyond perception and use data to guide smarter, fairer policy decisions.
Ultimately, every dataset tells a story, and in this one, the message is clear:

“Health should not depend on your zip code.”

 

Tags: healthcare, Lebanon, inequality, data visualization, open data, AUB