## Step 1: Define the optimization problem
The problem is to minimize the objective function $8x_0 + 4x_1 + 8x_2 + 9x_3$, where $x_0$ represents milligrams of vitamin B2, $x_1$ represents milligrams of vitamin B3, $x_2$ represents milligrams of zinc, and $x_3$ represents grams of fiber.

## Step 2: List all the constraints
The constraints are as follows:
- $2x_0 \leq 195$
- $13x_0 \leq 270$
- $6x_0 \leq 168$
- $4x_0 \leq 207$
- $5x_1 \leq 195$
- $10x_1 \leq 270$
- $5x_1 \leq 168$
- $10x_1 \leq 207$
- $6x_2 \leq 195$
- $12x_2 \leq 270$
- $11x_2 \leq 168$
- $8x_2 \leq 207$
- $11x_3 \leq 195$
- $2x_3 \leq 270$
- $12x_3 \leq 168$
- $8x_3 \leq 207$
- $5x_1 + 11x_3 \geq 33$
- $2x_0 + 6x_2 \geq 37$
- $6x_2 + 11x_3 \geq 45$
- $5x_1 + 6x_2 \geq 39$
- $2x_0 + 6x_2 + 11x_3 \geq 39$
- $2x_0 + 5x_1 + 11x_3 \geq 39$
- $2x_0 + 6x_2 + 11x_3 \geq 40$
- $2x_0 + 5x_1 + 11x_3 \geq 40$
- $2x_0 + 5x_1 + 6x_2 + 11x_3 \geq 40$
- $13x_0 + 2x_3 \geq 52$
- $10x_1 + 2x_3 \geq 33$
- $12x_2 + 2x_3 \geq 45$
- $13x_0 + 12x_2 \geq 49$
- $10x_1 + 12x_2 + 2x_3 \geq 49$
- $13x_0 + 10x_1 + 12x_2 + 2x_3 \geq 49$
- $11x_2 + 12x_3 \geq 35$
- $5x_1 + 11x_2 \geq 27$
- $6x_0 + 5x_1 + 11x_2 + 12x_3 \geq 27$
- $4x_0 + 8x_2 \geq 37$
- $4x_0 + 8x_3 \geq 37$
- $10x_1 + 8x_2 \geq 29$
- $8x_2 + 8x_3 \geq 35$
- $4x_0 + 10x_1 \geq 43$
- $10x_1 + 8x_3 \geq 26$
- $10x_1 + 8x_2 + 8x_3 \geq 32$
- $4x_0 + 10x_1 + 8x_2 \geq 32$
- $10x_1 + 8x_2 + 8x_3 \geq 27$
- $4x_0 + 10x_1 + 8x_2 \geq 27$
- $4x_0 + 10x_1 + 8x_2 + 8x_3 \geq 27$
- $-8x_2 + 10x_3 \geq 0$
- $5x_0 - 2x_2 \geq 0$
- $2x_0 + 5x_1 + 11x_3 \leq 105$
- $5x_1 + 6x_2 + 11x_3 \leq 74$
- $2x_0 + 6x_2 + 11x_3 \leq 132$
- $10x_1 + 2x_3 \leq 70$
- $10x_1 + 12x_2 \leq 169$
- $13x_0 + 12x_2 \leq 186$
- $13x_0 + 12x_2 + 2x_3 \leq 238$
- $5x_1 + 11x_2 + 12x_3 \leq 85$
- $6x_0 + 5x_1 + 12x_3 \leq 157$

## Step 3: Implement the optimization problem using Gurobi
```python
import gurobi as gp

# Define the model
m = gp.Model("optimization_problem")

# Define the variables
x0 = m.addVar(lb=0, name="milligrams of vitamin B2")  # milligrams of vitamin B2
x1 = m.addVar(lb=0, name="milligrams of vitamin B3")  # milligrams of vitamin B3
x2 = m.addVar(lb=0, name="milligrams of zinc")  # milligrams of zinc
x3 = m.addVar(lb=0, name="grams of fiber")  # grams of fiber

# Define the objective function
m.setObjective(8*x0 + 4*x1 + 8*x2 + 9*x3, gp.GRB.MINIMIZE)

# Add constraints
m.addConstr(2*x0 <= 195, name="kidney_support_index_vitamin_B2")
m.addConstr(13*x0 <= 270, name="cognitive_performance_index_vitamin_B2")
m.addConstr(6*x0 <= 168, name="digestive_support_index_vitamin_B2")
m.addConstr(4*x0 <= 207, name="immune_support_index_vitamin_B2")

m.addConstr(5*x1 <= 195, name="kidney_support_index_vitamin_B3")
m.addConstr(10*x1 <= 270, name="cognitive_performance_index_vitamin_B3")
m.addConstr(5*x1 <= 168, name="digestive_support_index_vitamin_B3")
m.addConstr(10*x1 <= 207, name="immune_support_index_vitamin_B3")

m.addConstr(6*x2 <= 195, name="kidney_support_index_zinc")
m.addConstr(12*x2 <= 270, name="cognitive_performance_index_zinc")
m.addConstr(11*x2 <= 168, name="digestive_support_index_zinc")
m.addConstr(8*x2 <= 207, name="immune_support_index_zinc")

m.addConstr(11*x3 <= 195, name="kidney_support_index_fiber")
m.addConstr(2*x3 <= 270, name="cognitive_performance_index_fiber")
m.addConstr(12*x3 <= 168, name="digestive_support_index_fiber")
m.addConstr(8*x3 <= 207, name="immune_support_index_fiber")

m.addConstr(5*x1 + 11*x3 >= 33, name="kidney_support_index_vitamin_B3_fiber")
m.addConstr(2*x0 + 6*x2 >= 37, name="kidney_support_index_vitamin_B2_zinc")
m.addConstr(6*x2 + 11*x3 >= 45, name="kidney_support_index_zinc_fiber")
m.addConstr(5*x1 + 6*x2 >= 39, name="kidney_support_index_vitamin_B3_zinc")
m.addConstr(2*x0 + 6*x2 + 11*x3 >= 39, name="kidney_support_index_vitamin_B2_zinc_fiber")
m.addConstr(2*x0 + 5*x1 + 11*x3 >= 39, name="kidney_support_index_vitamin_B2_vitamin_B3_fiber")
m.addConstr(2*x0 + 6*x2 + 11*x3 >= 40, name="kidney_support_index_vitamin_B2_zinc_fiber_2")
m.addConstr(2*x0 + 5*x1 + 11*x3 >= 40, name="kidney_support_index_vitamin_B2_vitamin_B3_fiber_2")
m.addConstr(2*x0 + 5*x1 + 6*x2 + 11*x3 >= 40, name="kidney_support_index_all")

m.addConstr(13*x0 + 2*x3 >= 52, name="cognitive_performance_index_vitamin_B2_fiber")
m.addConstr(10*x1 + 2*x3 >= 33, name="cognitive_performance_index_vitamin_B3_fiber")
m.addConstr(12*x2 + 2*x3 >= 45, name="cognitive_performance_index_zinc_fiber")
m.addConstr(13*x0 + 12*x2 >= 49, name="cognitive_performance_index_vitamin_B2_zinc")
m.addConstr(10*x1 + 12*x2 + 2*x3 >= 49, name="cognitive_performance_index_vitamin_B3_zinc_fiber")
m.addConstr(13*x0 + 10*x1 + 12*x2 + 2*x3 >= 49, name="cognitive_performance_index_all")

m.addConstr(11*x2 + 12*x3 >= 35, name="digestive_support_index_zinc_fiber")
m.addConstr(5*x1 + 11*x2 >= 27, name="digestive_support_index_vitamin_B3_zinc")
m.addConstr(6*x0 + 5*x1 + 11*x2 + 12*x3 >= 27, name="digestive_support_index_all")

m.addConstr(4*x0 + 8*x2 >= 37, name="immune_support_index_vitamin_B2_zinc")
m.addConstr(4*x0 + 8*x3 >= 37, name="immune_support_index_vitamin_B2_fiber")
m.addConstr(10*x1 + 8*x2 >= 29, name="immune_support_index_vitamin_B3_zinc")
m.addConstr(8*x2 + 8*x3 >= 35, name="immune_support_index_zinc_fiber")
m.addConstr(4*x0 + 10*x1 >= 43, name="immune_support_index_vitamin_B2_vitamin_B3")
m.addConstr(10*x1 + 8*x3 >= 26, name="immune_support_index_vitamin_B3_fiber")
m.addConstr(10*x1 + 8*x2 + 8*x3 >= 32, name="immune_support_index_vitamin_B3_zinc_fiber")
m.addConstr(4*x0 + 10*x1 + 8*x2 >= 32, name="immune_support_index_vitamin_B2_vitamin_B3_zinc")
m.addConstr(10*x1 + 8*x2 + 8*x3 >= 27, name="immune_support_index_vitamin_B3_zinc_fiber_2")
m.addConstr(4*x0 + 10*x1 + 8*x2 >= 27, name="immune_support_index_vitamin_B2_vitamin_B3_zinc_2")
m.addConstr(4*x0 + 10*x1 + 8*x2 + 8*x3 >= 27, name="immune_support_index_all")

m.addConstr(-8*x2 + 10*x3 >= 0, name="zinc_fiber_constraint")
m.addConstr(5*x0 - 2*x2 >= 0, name="vitamin_B2_zinc_constraint")

m.addConstr(2*x0 + 5*x1 + 11*x3 <= 105, name="kidney_support_index_vitamin_B2_vitamin_B3_fiber_upper")
m.addConstr(5*x1 + 6*x2 + 11*x3 <= 74, name="kidney_support_index_vitamin_B3_zinc_fiber_upper")
m.addConstr(2*x0 + 6*x2 + 11*x3 <= 132, name="kidney_support_index_vitamin_B2_zinc_fiber_upper")

m.addConstr(10*x1 + 2*x3 <= 70, name="cognitive_performance_index_vitamin_B3_fiber_upper")
m.addConstr(10*x1 + 12*x2 <= 169, name="cognitive_performance_index_vitamin_B3_zinc_upper")
m.addConstr(13*x0 + 12*x2 <= 186, name="cognitive_performance_index_vitamin_B2_zinc_upper")
m.addConstr(13*x0 + 12*x2 + 2*x3 <= 238, name="cognitive_performance_index_vitamin_B2_zinc_fiber_upper")

m.addConstr(5*x1 + 11*x2 + 12*x3 <= 85, name="digestive_support_index_vitamin_B3_zinc_fiber_upper")
m.addConstr(6*x0 + 5*x1 + 12*x3 <= 157, name="digestive_support_index_vitamin_B2_vitamin_B3_fiber_upper")

# Solve the model
m.optimize()

# Print the solution
if m.status == gp.GRB.OPTIMAL:
    print("Optimal solution found.")
    print("Milligrams of vitamin B2: ", x0.varValue)
    print("Milligrams of vitamin B3: ", x1.varValue)
    print("Milligrams of zinc: ", x2.varValue)
    print("Grams of fiber: ", x3.varValue)
    print("Objective function value: ", m.objVal)
else:
    print("No optimal solution found.")
```