The five most commonly cited ideal weight formulas (Devine, Robinson, Miller, Hamwi, and Peters) were all derived between 1964 and 1983 — primarily from military recruits, insurance actuarial tables, and drug dosing studies — not from comprehensive health outcome research, which is why they produce different answers for the same person and none of them accounts for body composition
The previous articles on this site covered ideal weight formula origins, set-point theory, why formulas break down for athletes, the range vs single number distinction, and waist circumference as a metabolic risk predictor. This article addresses what research actually shows about "healthy" weight — specifically the relationship between weight, health outcomes, and the specific populations for whom the standard formulas were never validated.
The Devine formula: where the 106 pounds + 6 pounds rule came from
The Devine formula (published by BJ Devine in 1974 in a drug dosing paper) is the most widely used ideal body weight formula in clinical settings:
Men: IBW (kg) = 50 + 2.3 × (height in inches above 60) Women: IBW (kg) = 45.5 + 2.3 × (height in inches above 60)
What Devine actually wrote: the formula appeared in a 1974 paper on gentamicin dosing, not in a weight-health research paper. Devine was solving a drug pharmacokinetics problem (what weight should gentamicin dose be calculated from?) — not defining what weight people should be for health. The formula gained clinical adoption through drug dosing guidelines rather than being validated as a "healthy weight" target.
The formula's limitations Devine acknowledged: it was derived from tables in the Build and Blood Pressure Study (1959) — an insurance actuarial study of predominantly white, North American, middle-class adults who were well enough to obtain life insurance. It has no direct validation for elderly populations, non-Western populations, or women (the female formula was extrapolated from the male formula, not derived independently).
The obesity paradox and healthy weight: what outcomes research shows
Population-level epidemiological research on weight and mortality produces a finding that complicates the "lower BMI is healthier" narrative:
The obesity paradox: in certain clinical populations (heart failure, chronic kidney disease, COPD, type 2 diabetes), overweight and mildly obese patients (BMI 25-35) have better survival outcomes than normal-weight patients with the same conditions.
The general population mortality curve: studies of large non-clinical populations (like the Global BMI Mortality Collaboration, 2016, using 239 prospective studies covering 10+ million adults) find lowest mortality at BMI approximately 22-25 — consistent with "normal" BMI range thresholds. However, the mortality curve is relatively flat between BMI 20-27, steepening at higher and lower extremes.
The "lean" paradox: BMI below 20 is associated with increased mortality in general population studies, even when controlling for smoking (which reduces BMI and increases mortality). Extremely lean adults have higher mortality — which the ideal weight formulas don't capture (they suggest lower weight is always better).
Muscle mass vs fat mass: the body composition dimension
Ideal weight formulas produce a number based solely on height — they have no body composition dimension. Two people at the same height and weight can have very different health profiles depending on whether that weight is primarily muscle or fat.
The sarcopenic obesity pattern: an older adult who has lost muscle mass (sarcopenia) while gaining fat mass may have a "normal" weight but poor metabolic health. Their weight on the scale appears fine; their body composition is problematic.
The athletic pattern: a competitive athlete with high muscle mass may appear "overweight" by ideal body weight calculations — despite having excellent cardiovascular fitness, metabolic health, and body composition.
The BMI equivalent problem: ideal weight formulas are essentially height-normalised — for a given height, they produce one "correct" weight. They're no better than BMI at accounting for body composition, which is the crucial dimension that actual health outcomes depend on.
Adjusted body weight: a clinical modification for extremes
Adjusted body weight (AdjBW) is used in clinical pharmacokinetics when actual body weight and ideal body weight diverge significantly:
AdjBW = IBW + 0.4 × (TBW − IBW)
Where TBW = Total Body Weight (actual) and IBW = Ideal Body Weight.
When used: for obese patients, many drugs distribute into some (but not all) additional adipose tissue — using TBW overestimates drug distribution, using IBW underestimates it. AdjBW attempts to split the difference.
For underweight patients: using IBW rather than TBW for dosing prevents underdosing — thin patients shouldn't receive doses calculated from their low actual weight if the drug targets lean tissue.
The 0.4 factor: the 40% adjustment factor is a clinical approximation — it varies by drug lipophilicity. Some drugs use 0.3, others 0.45. The AdjBW formula acknowledges that "ideal weight" is a proxy, not a gold standard.
Weight stigma and the clinical harm of ideal weight framing
Research on weight stigma in healthcare (an emerging area since approximately 2010) has documented specific harms from clinical fixation on "ideal weight":
Avoidance of healthcare: people who have experienced weight-focused medical encounters are more likely to delay or avoid seeking healthcare, resulting in later diagnosis of unrelated conditions.
Misattribution of symptoms: conditions unrelated to weight (fatigue, joint pain, depression) are sometimes attributed to weight by clinicians without adequate investigation.
Eating disorder risk: for individuals with disordered eating history, ideal weight targets and calorie-focused clinical advice can trigger or exacerbate eating disorders.
The clinical reframe: major medical organisations (AMA, HAES advocates, and increasingly mainstream obesity medicine) now recommend a health-behaviour-focused approach ("how are you eating and moving?") rather than a weight-target approach ("you should be X kg") for most clinical scenarios.
How to use the Ideal Weight Calculator on sadiqbd.com
- As a reference range, not a target: the calculator shows multiple formula outputs simultaneously — the spread between them (sometimes 5-10 kg) illustrates why no single "ideal weight" number is valid, and why interpreting results as a reference range is more appropriate
- For drug dosing context: if using IBW for a clinical dosing calculation, identify which formula is used in the relevant drug's dosing guidelines — not all clinical contexts use Devine; some use Robinson or Miller
- Complement with body composition measures: interpret the ideal weight range alongside waist circumference (or waist-to-height ratio) for a more complete picture than weight alone provides
Frequently Asked Questions
If ideal weight formulas are so limited, why are they still used in clinical settings? Because they're simple, reproducible, and good enough for their original purpose — drug dosing estimation. For gentamicin dosing, you need a quick estimate of lean body mass. The Devine formula gives a consistent, calculable number that's correlated with lean mass without requiring body composition measurement. For this narrow clinical purpose, the formula works adequately. The problem isn't using it for drug dosing — it's using it as a general health target or a weight loss goal, contexts it was never designed for and for which its limitations (no body composition, narrow derivation population) are much more relevant.
Is the Ideal Weight Calculator free? Yes — completely free, no sign-up required.
Try the Ideal Weight Calculator free at sadiqbd.com — see ideal body weight estimates from multiple validated formulas for any height.
