## Step 1: Define the optimization problem
The problem is to minimize the objective function $3x_0 + 2x_1$, where $x_0$ represents the milligrams of iron and $x_1$ represents the grams of protein.

## Step 2: List all the constraints
The constraints are:
- $4x_0 + 6x_1 \geq 14$
- $11x_0 + 7x_1 \geq 48$
- $15x_0 + 15x_1 \geq 26$
- $2x_0 + 14x_1 \geq 22$
- $8x_0 + 12x_1 \geq 30$
- $x_0 - 5x_1 \geq 0$
- $4x_0 + 6x_1 \leq 32$
- $11x_0 + 7x_1 \leq 95$
- $15x_0 + 15x_1 \leq 37$
- $2x_0 + 14x_1 \leq 35$
- $8x_0 + 12x_1 \leq 67$

## 3: Identify the bounds for the variables
The variables $x_0$ and $x_1$ are fractional, implying they can take any non-negative real value.

## 4: Formulate the problem in Gurobi
To solve this problem using Gurobi, we need to define the model, add the variables, the objective function, and all the constraints.

## 5: Write the Gurobi code
```python
import gurobi

def solve_optimization_problem():
    # Create a new model
    model = gurobi.Model()

    # Define the variables
    x0 = model.addVar(name="milligrams_of_iron", lb=0)  # lower bound 0, no upper bound
    x1 = model.addVar(name="grams_of_protein", lb=0)  # lower bound 0, no upper bound

    # Define the objective function
    model.setObjective(3 * x0 + 2 * x1, gurobi.GRB.MINIMIZE)

    # Add constraints
    model.addConstr(4 * x0 + 6 * x1 >= 14, name="muscle_growth_index_min")
    model.addConstr(11 * x0 + 7 * x1 >= 48, name="cognitive_performance_index_min")
    model.addConstr(15 * x0 + 15 * x1 >= 26, name="cardiovascular_support_index_min")
    model.addConstr(2 * x0 + 14 * x1 >= 22, name="kidney_support_index_min")
    model.addConstr(8 * x0 + 12 * x1 >= 30, name="digestive_support_index_min")
    model.addConstr(x0 - 5 * x1 >= 0, name="iron_protein_balance")
    model.addConstr(4 * x0 + 6 * x1 <= 32, name="muscle_growth_index_max")
    model.addConstr(11 * x0 + 7 * x1 <= 95, name="cognitive_performance_index_max")
    model.addConstr(15 * x0 + 15 * x1 <= 37, name="cardiovascular_support_index_max")
    model.addConstr(2 * x0 + 14 * x1 <= 35, name="kidney_support_index_max")
    model.addConstr(8 * x0 + 12 * x1 <= 67, name="digestive_support_index_max")

    # Optimize the model
    model.optimize()

    # Print the status
    if model.status == gurobi.GRB.Status.OPTIMAL:
        print("Optimal solution found.")
        print(f"Milligrams of iron: {x0.varValue}")
        print(f"Grams of protein: {x1.varValue}")
        print(f"Objective: {model.objVal}")
    elif model.status == gurobi.GRB.Status.INFEASIBLE:
        print("No feasible solution exists.")
    else:
        print("Optimization failed.")

solve_optimization_problem()
```