
LV-GB Complex
LV-GB Complex by Designs for Health is a botanical and nutrient blend featuring milk thistle, ox bile, and L-Methionine. This supplement includes vitamins A, B-6, and B12. It has an N+ Score of 75, categorizing it as a good-tier product.
About This Product
LV-GB Complex by Designs for Health is a herbal & botanical supplement containing 14 active ingredients. It has earned an N+ Score of 75/100 (Grade C+).
This product features a fully transparent label with individual ingredient amounts disclosed, and key ingredients are present at clinically effective doses based on peer-reviewed research.
Notable clinical-dose ingredients include Vitamin B12, Vitamin A, Taurine.
N+ Score Breakdown
Are key ingredients present at clinically effective doses based on research?
Does the product include all expected ingredients for its supplement category?
Are individual ingredient amounts clearly disclosed without proprietary blends?
Does the formula include a breadth of beneficial compounds from multiple pathways?
Strengths
- +Key ingredients at clinically effective doses
- +Fully transparent label with individual ingredient amounts disclosed
- +Broad ingredient diversity exceeding category norms
- +3 ingredient(s) at clinical dose levels
- +Rich formula with 14 active ingredients
Weaknesses
- −Missing several expected ingredients for its category
Ingredient Analysis (14 ingredients)
| Ingredient | Amount | Dose Adequacy |
|---|---|---|
| Vitamin B12 | 5.000 mcg | Optimal |
| Vitamin A | 1666.000 IU | Optimal |
| Inositol | 33.000 mg | N/A |
| Dandelion | 16.000 mg | N/A |
| Taurine | 33.000 mg | High |
| Beet powder | 8.000 mg | N/A |
| Vitamin B-6 | 1.600 mg | N/A |
| L-Methionine | 50.000 mg | N/A |
| Lecithin | 33.000 mg | N/A |
| Milk Thistle | 33.000 mg | N/A |
| Ox Bile | 25.000 mg | N/A |
| Greater Celandine | 16.000 mg | N/A |
| Fringe Tree | 16.000 mg | N/A |
| Artichoke | 16.000 mg | N/A |
Clinical ranges based on NIH ODS Fact Sheets and peer-reviewed research. Status indicates whether the amount meets evidence-based thresholds.