Body Mass Index (BMI)

This website is for informational purposes only and not a substitute for medical advice.
BMI calculator
The evidence clearly demonstrates a non-linear relationship between BMI and mortality, with both insufficient and excessive body weight associated with increased mortality risk and reduced life expectancy.
Male
Female
Usual
Extra
'
cm
lb
kg
18.5
25
30
35
Fill fields above to calculate BMI

Summary

  • BMI is a quick screening measure of body size that can signal higher or lower long-term death risk.
  • In many large studies, the BMI–mortality relationship is U-shaped or J-shaped: risk tends to rise at both low and high BMI.
  • For many adults, the lowest all-cause mortality is often reported around BMI 22–25 kg/m², while in older adults a slightly higher BMI (often 25–30 kg/m²) may look neutral or protective.
  • BMI does not separate fat from muscle and does not show where fat is stored, so waist size and metabolic health markers matter too.

Factor description

Body Mass Index (BMI) is calculated from height and weight:

BMI = weight (kg) / height (m)²

It is measured in kg/m² and is typically used as a snapshot of current body size.

  • Height can be measured with a stadiometer or at home (best done without shoes).
  • Weight can be measured on a scale (best done consistently, similar time of day, similar clothing).
  • BMI is usually self-calculated or calculated by a clinic, but it is not a direct body fat measurement.

Impact on all-cause mortality

  1. High BMI can increase mortality risk through chronic disease pathways
  • Higher body fat (especially abdominal/visceral fat) is linked to insulin resistance, higher blood pressure, abnormal blood lipids, and chronic inflammation.
  • These changes raise risk of major causes of death such as cardiovascular disease and some cancers, which then increases all-cause mortality.
  1. Low BMI can increase mortality risk through frailty and underlying illness
  • Very low BMI can reflect low muscle mass, undernutrition, and reduced physiological reserve, especially in older adults.
  • In some people, low BMI is partly explained by existing disease or smoking (reverse causation), which can make low BMI look riskier in observational studies.
  1. Dose-response and thresholds often look like a U-shape or J-shape
  • Risk tends to be lowest in the mid range and rises at the extremes.
  • The exact “lowest-risk” BMI differs by population, age, smoking status, and how well studies control for illness-related weight loss.
  1. Why BMI alone can mislead
  • BMI cannot distinguish fat from muscle (some athletic people can have a high BMI with low fat).
  • BMI does not capture fat distribution; abdominal fat is generally more harmful than the same weight carried elsewhere.
  • Two people with the same BMI can have very different metabolic risk profiles.

Patterns

  • Age pattern: In older adults, slightly higher BMI can appear neutral or protective in some cohorts, while very low BMI is often strongly linked to frailty and higher risk.
  • Illness and reverse causation: Unintentional weight loss from chronic disease can raise mortality risk and can bias BMI associations if early deaths are not excluded.
  • Smoking pattern: Smoking lowers body weight on average and raises mortality risk, so analyses that do not handle smoking well can distort BMI–mortality patterns.
  • Socioeconomic pattern: Higher obesity prevalence is often linked to lower socioeconomic status due to food environment, stress, shift work, limited time for activity, and access to healthcare.
  • Ethnic and body-composition differences: At the same BMI, body fat percentage and metabolic risk can differ across ethnic groups, so BMI cutoffs may not fit everyone equally well.

KamaLama scoring

KamaLama uses a category-based (threshold) scoring model for BMI. This reflects the broad population evidence that very low BMI and especially high BMI are linked with higher long-term death risk. Because BMI is a screening measure, categories are used rather than a fine-grained dose-response curve in the score table.

Category/RangeScore (in years)
Underweight-1
Normal weight2
Overweight-5
Obesity-7
Severe obesity-12

Practical tips

  • Track trend, not one number: measure weight consistently and review monthly or quarterly patterns.
  • Add a waist measure: waist circumference (or waist-to-height ratio) helps capture abdominal fat risk that BMI misses.
  • If BMI is high, start with small, repeatable changes: more daily walking, fewer sugary drinks, more protein and fiber, and fewer ultra-processed snacks.
  • Protect muscle while changing weight: include strength training 2–3 times per week and aim for adequate protein.
  • Prioritise sleep and stress basics: poor sleep and chronic stress can increase appetite and make weight management harder.
  • If BMI is low or falling without trying, treat it as a signal: check for low protein intake, low strength activity, and possible medical causes of unintended weight loss.
  • Choose safe pace: avoid extreme diets; for people with medical conditions, pregnancy, eating disorder history, or older age, involve a clinician before major weight change.

References

Authoritative guidelines / evaluations

Peer-reviewed / indexed research

Cookie Consent

We ask your permission to use analytics to improve the site and fix bugs. You can accept all cookies or adjust your preferences.

For more details, read our Cookie Policy.

Body Mass Index (BMI) insight | KamaLama