Whose Range Are You In?
Understanding Why Different Experts Recommend Different Thresholds
When you search for optimal TG/HDL ratio, HOMA-IR, or waist-to-height ratio, you'll find different numbers from different sources. This isn't because some experts are wrong and others are right. It's because they're answering different questions. This page explains what those different questions are — so you can decide which framework matches your goals.
The Four Paradigms
Conventional Medicine
“At what point is this person sick enough to treat?”
Philosophy: Population-level risk stratification. Set thresholds where intervention clearly outweighs risk. Avoid "over-diagnosing" people who may never develop disease.
Evidence basis: Large epidemiological studies (Framingham, MESA) identifying statistical breakpoints where disease risk increases significantly.
Best for: Understanding where you stand relative to general population risk categories.
Limitation: By definition, this catches problems later. The threshold is set where disease is already developing, not where optimal function begins to decline.
Research Consensus
“At what level do we see the best outcomes in research populations?”
Philosophy: Prevention-focused. Use research data to identify where health markers correlate with lowest disease risk, highest function, longest healthspan.
Evidence basis: McLaughlin et al. (2003) showed TG/HDL ≥3.0 identified insulin resistance with 79% sensitivity. Research populations with ratios <2.0 show better metabolic profiles.
Best for: People prioritizing prevention and optimization, not just avoiding diagnosed disease.
Limitation: Research populations may not perfectly match your individual context (genetics, history, goals).
Metabolic Practitioners
“What levels do we see in metabolically restored patients?”
Philosophy: Metabolic restoration through dietary intervention. The "normal" range in a metabolically damaged population isn't actually normal — it's just common. Look at what's achievable when metabolic function is restored.
Evidence basis: Virta Health (2018) showed average TG/HDL of ~1.0 in sustained ketogenic dieters. Many practitioners report patients routinely achieving TG/HDL <1.0 with dietary intervention.
Best for: People actively pursuing metabolic optimization through low-carb or ketogenic approaches. Understanding what's achievable, not just "acceptable."
Limitation: These thresholds may not be achievable for everyone, and forcing them through extreme measures may not be appropriate for all individuals.
Functional Medicine
“What indicates the body is functioning optimally at a cellular level?”
Philosophy: Root cause resolution. Don't just treat symptoms or hit arbitrary thresholds — restore the underlying systems to full function. Markers should reflect optimal physiology, not just absence of diagnosable disease.
Evidence basis: Combination of research evidence and clinical pattern recognition. Emphasis on mechanistic understanding (insulin signaling, lipid metabolism, mitochondrial function).
Best for: People working with functional medicine practitioners on comprehensive metabolic optimization.
Limitation: Some targets may be aspirational rather than evidence-based for all populations. Individual variation matters.
Why the Differences Exist
Different Risk Tolerance
Conventional medicine is necessarily conservative. Setting thresholds too tight means more "false positives" (healthy people told they're sick), more interventions with side effects, higher healthcare costs, and liability concerns. Prevention-focused frameworks accept that some people will be flagged who wouldn't have developed disease — but consider early intervention worth it.
Different Populations
Thresholds derived from sick populations (hospital patients, people already in clinical trials) differ from thresholds derived from healthy populations or intervention success stories. If "normal" TG/HDL is 2.5 in the general American population, and the general American population is metabolically unhealthy, then 2.5 isn't actually "normal" in any biological sense — it's just common.
Different Evidence Sources
Each has strengths and weaknesses. Large cohort studies have statistical power but may miss individual variation. Clinical experience captures real-world complexity but may have selection bias.
The TG/HDL Example in Detail
What the Research Shows
| Study | Finding |
|---|---|
| Gaziano et al. 1997 | TG/HDL ratio is the strongest lipid predictor of heart attack |
| McLaughlin et al. 2003 | TG/HDL ≥3.0 identifies insulin resistance with 79% sensitivity |
| Hanak et al. 2004 | TG/HDL 3.8 predicts small, dense LDL particles with ~80% accuracy |
| Virta Health 2018 | 1-year keto: TG/HDL improved to ~1.0 average |
Example Interpretations
The Bigger Picture: Why Early Detection Matters
Conventional medicine thresholds are set to catch disease. They're not set to catch the dysfunction that precedes disease by 10-20 years. Fasting insulin can be elevated for a decade before glucose becomes abnormal. TG/HDL ratio can signal metabolic problems while standard cholesterol panels look "fine." By the time conventional thresholds are crossed, significant metabolic damage has often occurred. Some of that damage may be irreversible. Earlier detection using tighter thresholds — and markers that catch dysfunction before disease — gives you more runway to intervene.
That's what this is about: not telling you which paradigm is "right," but giving you the information to detect problems early, understand your options, and make informed choices.
Frequently Asked Questions
“Which threshold should I use?”
There's no universal answer. Consider your personal health goals, your risk tolerance, your willingness to make lifestyle changes, and your healthcare provider's input.
“My doctor says I'm fine, but your calculator shows "suboptimal." Who's right?”
Both can be correct. Your doctor is likely using conventional thresholds — you're not in a high-risk disease category. Our calculator is showing you where optimization-focused frameworks would place you. These are different questions with different answers.
“If lower is better, why isn't everyone targeting <1.0?”
Several reasons: Not everyone can achieve these levels. Extremely low levels may not confer additional benefit. Some people function well at higher ratios. Individual variation exists. Thresholds are guidelines, not gospel.
“Does ethnicity affect optimal thresholds?”
Yes. Some research suggests optimal TG/HDL thresholds vary by ethnic background. This is an area of ongoing research. We present thresholds derived primarily from studies of Western populations; your individual optimal may differ.
Summary
Different experts recommend different thresholds because they're answering different questions.
| Framework | Question | Threshold Style |
|---|---|---|
| Conventional | When is intervention clearly warranted? | Higher (catches disease) |
| Optimal | What do research populations with best outcomes show? | Medium (catches risk) |
| Practitioner | What's achievable with intervention? | Lower (shows potential) |
| Functional | What indicates optimal physiological function? | Lowest (aspires to ideal) |
Our approach: Show you all four. Let you decide which framework matches your goals. Respect your intelligence enough to present the complexity honestly.
Because the honest answer to "what's optimal?" is: it depends on what you're optimizing for.
Metabolicum is for educational purposes and does not replace professional medical advice.