Why We Overcomplicate Obesity: The Case for a Much Simpler Explanation

Rishi Bhojnagarwala
December 19, 2025

Why We Overcomplicate Obesity: The Case for a Much Simpler Explanation

As humans, we love complicated explanations — especially when it comes to health.

We’ve spent years (decades, really) trying to decode obesity, diabetes, and metabolic disorders with increasingly sophisticated models:

  • Low protein

  • Too much protein

  • Sugar

  • Refined carbs

  • High-carb diets

  • Packaged foods

  • Street foods

  • Seed oils

  • Salt

  • Lack of steps

  • Lack of weight training

  • Stress

  • Sleep

  • Hormones

  • Gut health

  • Circadian rhythm

  • Even the idea that “some people just have bad genetics”

Every year, a new villain gets added to the list.

But what if — despite all the complexity — the real answer is dramatically simpler?

What if the #1 driver of obesity is the most obvious one?

A Lesson From Data Science: Sometimes Complexity Is Just Noise

Years ago, during an online statistics program with UC Berkeley on edX, we studied a fascinating case involving Wikipedia.

The problem:
Predict which Wikipedia edits were factually incorrect.

The research team threw every possible variable into a sophisticated multivariate model:

  • edit length

  • time of day

  • article category

  • topic sensitivity

  • type of contributor

  • length of article

  • sentiment

  • revision patterns

  • dozens more

They ran random forests.
Feature engineering.
All the complex stuff you’d expect in a graduate-level data science course.

And after all that?

Only one feature truly mattered.
A single binary variable:

👉 Was the editor logged in or anonymous?

That one factor predicted incorrect submissions with the highest reliability.

Not edit length.
Not topic.
Not timing.
Not word count.
Just login status.

The simplest possible signal turned out to be the strongest.

Maybe Obesity Works the Same Way

In nutrition, we’ve made the same mistake Wikipedia researchers initially made:

We’ve overcomplicated the problem.

We’ve blamed every nutrient and habit we can find:

  • carbs

  • sugar

  • dairy

  • fats

  • salt

  • low protein

  • gut imbalance

  • lack of sunlight

  • keto

  • intermittent fasting

  • vegan diets

  • ultra-processed foods

But what if multivariate models are hiding the simplicity?

What if the strongest predictor — the “logged in vs anonymous” of health — is something we already know?

The Uncomfortable Simplicity: We Are Mostly Just Overeating

Not because we’re weak.
Not because we lack discipline.
Not because of moral failure.

But because:

  • Portions have grown

  • Restaurants use far more oil and fat

  • Packaged foods have become addictive

  • Eating out has become frequent

  • Sedentary work has increased

  • Calorie-dense foods are everywhere

  • Traditional meals are larger than ever

  • Physical activity has plummeted

Most people are simply eating more calories than they burn — consistently, quietly, unintentionally.

That’s it.

Overeating is the hidden binary predictor of modern metabolic disease.

The uncomfortable truth is:

The human body — Indian or global — gains fat in a calorie surplus.

And loses fat in a calorie deficit.

Everything else matters after this.

Protein helps.
Fiber helps.
Strength training helps.
Sleep helps.
Stress matters.
Hormones play a role.

But none of these overturn the fundamental physics of energy balance.

We are not in a global obesity crisis because of one nutrient.
We are here because of portion creep and calorie overload.

Why Indians Are Hit Even Harder (India & NRIs)

Indians — both in India and abroad — have a specific metabolic profile:

  • lower muscle mass

  • higher fat percentage

  • higher visceral fat

  • higher insulin resistance

  • higher sensitivity to carbs

  • lower baseline protein intake

  • lower BMR

This means:

  • overeating affects Indians faster

  • belly fat accumulates more quickly

  • diabetes risk rises sooner

  • weight loss becomes harder

  • macros matter even more

But the principle still holds:

**Overeating → metabolic dysfunction.

Calorie control → metabolic healing.**

Simple, but powerful.

Why We Built CalTrac Around This Simplicity

CalTrac is designed on the exact philosophy revealed by that Wikipedia case study:

👉 Find the strongest signal.
Ignore the noise.
Build around the truth.

For weight loss, that truth is:

**Daily calorie deficit = weight loss.

Daily calorie surplus = weight gain.**

Everything else — macros, timing, gut health, exercise — are supporting factors, not primary causes.

So CalTrac simplifies weight loss to:

  • a single CalTrac Score

  • accurate Indian calorie & portion detection

  • real Indian food data

  • protein scoring for metabolic stability

  • easy deficit tracking

  • photo AI for Indian meals

  • GLP-safe tracking for medication users

No complex dashboards.
No 40-metric tracking.
No overcomplicating.
Just the signal — your deficit.

Conclusion: Sometimes the Simplest Answer Is the Right One

The more we study metabolic health, the more it resembles that Wikipedia case:

  • You can build complex models

  • You can analyze dozens of variables

  • You can debate food trends endlessly

  • You can chase the latest nutrition theory

But in the end?

Overeating is the logged-in vs anonymous variable of obesity.

We can complicate the story.
But the solution still starts with the simplest foundation:

**Eat slightly less than you burn.

Sustain it.
Support it with better habits.
And consistency becomes unstoppable.**

Subscribe to our newsletter
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.