BMI

initially Height Discrepancies Recognition:

• Observation: Early acknowledgment of lower death rates in taller individuals with similar Wt/Ht ratio.
• Consideration: Recognition that height, particularly leg length, influences calculated body mass adjusted for height.

Efforts to Eliminate Variables:

• Objective: Develop body build representations independent of height and frame size.
• Approaches: Consideration of shoulder width, elbow width, knee width, and more to categorize people by frame size.
• Challenge: Difficulty in widely adopting specific frame size measurements.

Mathematical Adjustments:

• Conceptual Approach: Treating the body as a 3D mass; exploration of cube root equations (3√Wt/Ht) and exponents.
• Observation: Optimal scaling with height raised to the 1.6-1.7 exponent (Wt/Ht^1.6).
• Challenge: Exponential adjustment not ideal for population-based studies, leading to the adoption of Wt/Ht^2.

Introduction of Quetelet Index (BMI):

• Key Figure: Lambert Adolphe Jacque Quetelet, a Flemish astronomer and statistician.
• Initiative: Introduced “social averages” concept and developed Quetelet Index (BMI) = weight (kg) / height^2 (m^2).
• Shift in Usage: Replaced Metropolitan Life Tables in 1972 due to concerns about their validity.

BMI’s Limitations:

• Advantages:
  • Simplicity and widely used: Convenience and widespread adoption for population-based studies.
  • Standardized measure for body weight relative to height
• Limitations and Challenges:
  • Age and Gender:
    • BMI may not be suitable for children, elderly, or pregnant individuals due to age and gender-related variations.
  • Muscle Mass:
    • BMI does not differentiate between muscle and fat, leading to misclassification of individuals with high muscle mass as overweight or obese.
    • Athletes or individuals with high muscle mass may have a higher BMI despite low body fat
    • Older adults or those with low muscle mass may have a lower BMI despite excess body fat.
  • Body Composition:
    • fails to account for distribution of fat, neglecting the health implications of visceral fat(body fat location)
  • Lack of Specifics:
    • Fails to consider detailed factors like lifestyle and comorbidities
    • BMI may misclassify individuals from certain ethnicities, as it does not consider variations in body composition among different ethnic groups.
    • Deurenberg-Yap et al. (2001) found differences in body fat percentages at a given BMI across Chinese, Malay, and Asian Indian populations in Singapore. However, this research did not propose alternative BMI standards for these specific ethnic group

WHO Categorization in 1995:

• Categorization: Underweight, normal, overweight, and obese categories introduced.

BMI (kg/m2)	Classification	Men WC 94–102 cm Women WC 80–88 cm	Men WC >102 cm Women WC >88 cm
18.5–24.9	Normal weight†	–	–
25–29.9	Overweight	Increased	High
30–34.9	Obese class I	High	Very high
35–39.9	Obese class II	Very high	Very high
≥40.0	Obese class III	Extremely high	Extremely high
* Disease risk for type 2 diabetes, hypertension and cardiovascular disease † Increased WC can also be a marker for increased risk even in persons of normal weight Reproduced from the Scottish Intercollegiate Guidelines Network (SIGN). Management of obesity. A national clinical guideline. Edinburgh: SIGN; Year. (SIGN publication no. 115). [cited 10 July 2013]. Available from UR

Population BMI Distribution:

• Trend: Mean or median BMI ranging from 24 to 27 in the population.
• WHO Impact: Significant portions categorized as overweight or obese, skewing the distribution towards higher BMI values.

BMI and Body Fat Location:

• BMI lacks details on body fat location, critical for assessing metabolic and mortality risks.
• Distinction:
  • Android (upper body) vs. gynecoid (lower body) fat distribution associated with varied health implications.
• Android (Upper Body) Fat Distribution:
  • Location: Accumulation of fat around the abdomen, waist, and upper body.
  • Health Implications:
    • Metabolic Syndrome: Higher risk of metabolic syndrome, including insulin resistance, hypertension, and dyslipidemia.
    • Cardiovascular Disease (CVD): Increased likelihood of developing cardiovascular diseases.
    • Type 2 Diabetes
• Gynecoid (Lower Body) Fat Distribution:
  • Location: Fat accumulation in the hips, buttocks, and thighs.
  • Health Implications:
    • Lower Metabolic Risk: Lower risk of metabolic syndrome and associated cardiovascular risks.
    • Protective Effects: Associated with lower risk of type 2 diabetes and cardiovascular diseases compared to android fat distribution.
    • Reproductive Health: May have positive implications for reproductive health in women

Waist-to-Hip Ratio (WHR)

• = waist circumference (cm) / hip circumference (cm)
• Considers fat distribution and provides insights into visceral fat.
• Unfortunately, researchers have varied the measurement site for waist, so that comparisons between data and with cut-points are limited
• Measuring waist tips (https://www.health.gov.au/topics/overweight-and-obesity/bmi-and-waist)
  • take off any bulky clothing, loosen belt and empty your pockets
  • stand with feet shoulder-width apart
  • wrap a tape measure around belly – in line with the belly button, and loose enough to fit one finger inside the tape.
• WHR is considered increased risk of cardiovascular disease if
  • >0.9 for males
  • >0.8 for females

Waist circumference (WC)

WC as an indicator of abdominal adiposity, may be a better predictor of obesity-associated complications for Aboriginal and Torres Strait Islander populations, and should be used in combination with BMI to refine assessment of risk

Gender	Increased risk	Greatly increased risk
Men	94 cm or more	102 cm or more
Women	80 cm or more	88 cm or more

Skinfold measurements

• Skinfold measurements are useful for clinical and research work, but in general are not recommended for population monitoring.
• The time required to accurately conduct these measurements is long, making them generally impractical for use in population based studies.
• Furthermore, it is particularly difficult to conduct accurate measurements of overweight and obese people as the skinfold is difficult to pinch (i.e., difficulty in opening calliper wide enough) and tends to move easily.

Body Fat Percentage:

Directly measures the proportion of fat mass in the body, providing a more accurate representation.

Estimating Body Fat Mass and Location of the Fat:

• Diverse Approaches: Underwater weighing, bioelectrical impedance, DEXA scans, CT slices, and anthropometric measurements.
• Common Practices: Bioelectrical impedance and DEXA scans used for convenience but subject to potential errors.
  • Underwater Weighing: Involves submerging an individual in water and measuring the displacement, providing an accurate measure of body density.
  • Bod Pod: Uses air displacement to determine body density and calculate body fat percentage.
  • Bioelectrical Impedance: Measures the resistance of electrical flow through the body to estimate fat mass.
  • Isotopically Labeled Water Mass: Determines total body water by analyzing isotopically labeled water elimination.
    • Skin-Fold Thickness: Anthropometric method measuring fat thickness at various sites to estimate fat mass.
  • DEXA Scan: A dual-energy x-ray absorptiometry scan provides a 3D image of body organ densities, used for estimating total body fat and its location.
  • CT and MRI: Imaging techniques for assessing fat depots, but MRI is costly.
• Pros and Cons:
  • Underwater Weighing: Accurate but impractical.
  • Bod Pod: Precise and non-invasive but expensive.
  • Bioelectrical Impedance: Convenient but subject to hydration status.
  • DEXA Scan: 3D imaging, but exposes individuals to radiation.
  • CT and MRI: Precise but expensive and limited in practicality for routine use.

Specific Problems in Relating BMI to Medical Issues:

• Challenges:
  • Correlation Issues: BMI may not correlate well with cardiovascular events.
  • Treatment Unknowns: Often overlooks the treatment status of cardiovascular risk factors and diabetes.
  • Smoking Impact: Changes in smoking rates influence BMI distribution.
• Associations with Death Rate:
• Studies:
  • Wide BMI Range: Little impact on death rates within a BMI range of 24-28.
  • Overweight Not Harmful: Some studies indicate lower mortality risk in the “overweight” category.
• Unresolved Issues:
• Predictors of Comorbidities:
  • BMI, Total Body Fat, or Distribution: Debate on which factor is more critical in predicting health outcomes.
  • Fat Distribution Emphasis: Accumulation in specific locations may outweigh the importance of BMI alone.
  • EPIC Study: Highlights the significance of fat location, especially in relation to BMI.