Body mass index

The body mass index (BMI), or Quetelet index, is a measure of relative size based on the mass and height of an individual.

The index was devised by Adolphe Quetelet during the course of developing what he called "social physics", between 1830 and 1850. The BMI value for an individual is defined as the body mass (in kilograms) of the individual divided by the square of their height (in metres) – with the value universally being given in units of kg/m².

$\mathrm {BMI}$	$={\frac {{\text{mass}}({\text{kg}})}{\left({\text{height}}({\text{m}})\right)^{2}}}$
	$={\frac {{\text{mass}}({\text{lb}})}{\left({\text{height}}({\text{in}})\right)^{2}}}\times 703$

The BMI of an individual may also be determined using a table or chart, which displays BMI as a function of mass and height using contour lines or colors for different BMI categories, and may use two different units of measurement.

There are a wide variety of contexts where the BMI of an individual can be used as a simple method to assess how much the recorded body weight departs from what is healthy or desirable for a person of that height. There is, however, some debate about which values on the BMI scale the thresholds for 'underweight', 'overweight' and 'obese' should be set.

Usage

A graph of body mass index as a function of body mass and body height is shown above. The dashed lines represent subdivisions within a major class. For instance, the "Underweight" classification is further divided into "severe", "moderate", and "mild" subclasses.

The modern term "body mass index" (BMI) for the ratio owes its popularity to a paper published in the July 1972 edition of the Journal of Chronic Diseases by Ancel Keys. This found the BMI to be the best proxy for body fat percentage among ratios of weight and height. The interest in an index that measures body fat came with increasing obesity in prosperous Western societies. BMI was explicitly cited by Keys as appropriate for population studies and inappropriate for individual evaluation. Nevertheless, due to its simplicity, it has come to be widely used for preliminary diagnosis. Additional metrics, such as waist circumference, can be more useful.

BMI ranges from underweight to obese and is commonly employed among children and adults to predict health outcomes. The BMI trait is influenced by both genetic and non-genetic factors, and it provides a paradigm to understand and estimate the risk factors for health problems.

BMI provides a simple numeric measure of a person's thickness or thinness, allowing health professionals to discuss weight problems more objectively with their patients. BMI was designed to be used as a simple means of classifying average sedentary (physically inactive) populations, with an average body composition. For these individuals, the current value recommendations are as follow: a BMI from 18.5 up to 25 may indicate optimal weight, a BMI lower than 18.5 suggests the person is underweight, a number from 25 up to 30 may indicate the person is overweight, and a number from 30 upwards suggests the person is obese. Athletes, who tend to have an atypical muscle/fat ratio (atypical body fat percentage), may have a BMI that is misleading at first sight.

Scalability

BMI is proportional to mass and inversely proportional to the square of the height. So, if all body dimensions double, and mass scales naturally with the cube of the height, then BMI doubles instead of remaining the same. This results in taller people having a reported BMI that is uncharacteristically high, compared to their actual body fat levels. In comparison, the Ponderal index is based on the natural scaling of mass with the third power of the height. However, many taller people are not just "scaled up" short people but tend to have narrower frames in proportion to their height. Nick Korevaar (a mathematics lecturer from the University of Utah) suggests that instead of squaring the body height (as the BMI does) or cubing the body height (as the Ponderal index does), it would be more appropriate to use an exponent of between 2.3 and 2.7 (as originally noted by Quetelet). (For a theoretical basis for such values see MacKay.)

BMI Prime

BMI Prime, a simple modification of the BMI system, is the ratio of actual BMI to upper limit BMI (currently defined at BMI 25). As defined, BMI Prime is also the ratio of body weight to upper body weight limit, calculated at BMI 25. Since it is the ratio of two separate BMI values, BMI Prime is a dimensionless number without associated units. Individuals with BMI Prime less than 0.74 are underweight; those with between 0.74 and 1.00 have optimal weight; and those at 1.00 or greater are overweight. BMI Prime is useful clinically because individuals can tell, at a glance, by what percentage they deviate from their upper weight limits. For instance, a person with BMI 34 has a BMI Prime of 34/25 = 1.36, and is 36% over his or her upper mass limit. In South East Asian and South Chinese populations (see international variation section below), BMI Prime should be calculated using an upper limit BMI of 23 in the denominator instead of 25. Nonetheless, BMI Prime allows easy comparison between populations whose upper-limit BMI values differ.

Categories

A frequent use of the BMI is to assess how much an individual's body weight departs from what is normal or desirable for a person of his or her height. The weight excess or deficiency may, in part, be accounted for by body fat (adipose tissue) although other factors such as muscularity also affect BMI significantly (see discussion below and overweight). The WHO regards a BMI of less than 18.5 as underweight and may indicate malnutrition, an eating disorder, or other health problems, while a BMI greater than 25 is considered overweight and above 30 is considered obese. These ranges of BMI values are valid only as statistical categories

Category	BMI range – kg/m2	BMI Prime
Very severely underweight	less than 15	less than 0.60
Severely underweight	from 15.0 to 16.0	from 0.60 to 0.64
Underweight	from 16.0 to 18.5	from 0.64 to 0.74
Normal (healthy weight)	from 18.5 to 25	from 0.74 to 1.0
Overweight	from 25 to 30	from 1.0 to 1.2
Obese Class I (Moderately obese)	from 30 to 35	from 1.2 to 1.4
Obese Class II (Severely obese)	from 35 to 40	from 1.4 to 1.6
Obese Class III (Very severely obese)	over 40	over 1.6

BMI in Children (aged 2 to 20)

BMI for age percentiles for boys 2 to 20 years of age.

BMI is used differently for children. It is calculated in the same way as for adults, but then compared to typical values for other children of the same age. Instead of comparison against fixed thresholds for underweight and overweight, the BMI is compared against the percentile for children of the same gender and age.

A BMI that is less than the 5th percentile is considered underweight and above the 95th percentile is considered obese. Children with a BMI between the 85th and 95th percentile are considered to be overweight.

Recent studies in Britain have indicated that females between the ages 12 and 16 have a higher BMI than males of the same age by 1.0 kg/m² on average.

International variations

These recommended distinctions along the linear scale may vary from time to time and country to country, making global, longitudinal surveys problematic.

Hong Kong

The Hospital Authority of Hong Kong recommends the use of the following BMI ranges:

Category	BMI range – kg/m2
Underweight	< 18.5
Normal Range	18.5 - 22.9
Overweight - At Risk	23.0 - 24.9
Overweight - Moderately Obese	25.0 - 29.9
Overweight - Severely Obese	≥ 30.0

Japan

Japan Society for the Study of Obesity (2000):

Category	BMI range – kg/m2
Low	18.5 and below
Normal	from 18.5 to 25.0 (Standard weight is 22)
Obese (Level 1)	from 25.0 to 30.0
Obese (Level 2)	from 30.0 to 35.0
Obese (Level 3)	from 35.0 to 40.0
Obese (Level 4)	40.0 and above

Singapore

In Singapore, the BMI cut-off figures were revised in 2005, motivated by studies showing that many Asian populations, including Singaporeans, have higher proportion of body fat and increased risk for cardiovascular diseases and diabetes mellitus, compared with Caucasians at the same BMI. The BMI cut-offs are presented with an emphasis on health risk rather than weight.

BMI range – kg/m2	Health Risk
27.5 and above	High risk of developing heart disease, high blood pressure, stroke, diabetes
23.0 to 27.4	Moderate risk of developing heart disease, high blood pressure, stroke, diabetes
18.5 to 22.9	Low Risk (healthy range)
18.4 and below	Risk of developing problems such as nutritional deficiency and osteoporosis

United States

In 1998, the U.S. National Institutes of Health and the Centers for Disease Control and Prevention brought U.S. definitions in line with World Health Organization guidelines, lowering the normal/overweight cut-off from BMI 27.8 to BMI 25. This had the effect of redefining approximately 29 million Americans, previously healthy to overweight. It also recommends lowering the normal/overweight threshold for South East Asian body types to around BMI 23, and expects further revisions to emerge from clinical studies of different body types.

The U.S. National Health and Nutrition Examination Survey of 1994 indicated that 59% of American men and 49% of women had BMIs over 25. Morbid obesity—a BMI of 40 or more—was found in 2% of the men and 4% of the women. The newest survey in 2007 indicates a continuation of the increase in BMI: 63% of Americans are overweight or obese, with 26% now in the obese category (a BMI of 30 or more). There are differing opinions on the threshold for being underweight in females; doctors quote anything from 18.5 to 20 as being the lowest index, the most frequently stated being 19. A BMI nearing 15 is usually used as an indicator for starvation and the health risks involved, with a BMI less than 17.5 being an informal criterion for the diagnosis of anorexia nervosa.

Health consequences of overweight and obesity in adults

The BMI ranges are based on the relationship between body weight and disease and death. Overweight and obese individuals are at an increased risk for many diseases and health conditions, including the following:

• Hypertension
• Dyslipidemia (for example, high LDL cholesterol, low HDL cholesterol, or high levels of triglycerides)
• Type 2 diabetes
• Coronary heart disease
• Stroke
• Gallbladder disease
• Osteoarthritis
• Sleep apnea and respiratory problems
• At least 10 cancers (including endometrial, breast, and colon).

However recent research has shown that those classified as overweight, having a BMI between 25 and 29.9, show lower overall mortality than all other categories.

Applications

Statistical device

The BMI is generally used as a means of correlation between groups related by general mass and can serve as a vague means of estimating adiposity. The duality of the BMI is that, while it is easy to use as a general calculation, it is limited as to how accurate and pertinent the data obtained from it can be. Generally, the index is suitable for recognizing trends within sedentary or overweight individuals because there is a smaller margin of error.

This general correlation is particularly useful for consensus data regarding obesity or various other conditions because it can be used to build a semi-accurate representation from which a solution can be stipulated, or the RDA for a group can be calculated. Similarly, this is becoming more and more pertinent to the growth of children, due to the majority of their exercise habits.

The growth of children is usually documented against a BMI-measured growth chart. Obesity trends can be calculated from the difference between the child's BMI and the BMI on the chart.

Clinical practice

BMI has been used by the WHO as the standard for recording obesity statistics since the early 1980s. In the United States, BMI is also used as a measure of underweight, owing to advocacy on behalf of those suffering with eating disorders, such as anorexia nervosa and bulimia nervosa.

BMI can be calculated quickly and without expensive equipment. However, BMI categories do not take into account many factors such as frame size and muscularity. The categories also fail to account for varying proportions of fat, bone, cartilage, water weight, and more.

Despite this, BMI categories are regularly regarded as a satisfactory tool for measuring whether sedentary individuals are underweight, overweight or obese with various exemptions, such as: athletes, children, the elderly, and the infirm.

One basic problem, especially in athletes, is that muscle weight contributes to BMI. Some professional athletes would be overweight or obese according to their BMI, despite carrying little fat, unless the number at which they are considered overweight or obese is adjusted upward in some modified version of the calculation. In children and the elderly, differences in bone density and, thus, in the proportion of bone to total weight can mean the number at which these people are considered underweight should be adjusted downward.

Medical underwriting

In the United States, where medical underwriting of private health insurance plans is widespread, most private health insurance providers will use a particular high BMI as a cut-off point in order to raise insurance rates for or deny insurance to higher-risk patients, thereby reducing the cost of insurance coverage to all other subscribers in a lower BMI range. The cutoff point is determined differently for every health insurance provider and different providers will have vastly different ranges of acceptability. Many will implement phased surcharges, in which the subscriber will pay an additional penalty, usually as a percentage of the monthly premium, based on membership in an actuarially determined risk tier corresponding to a given range of BMI points above a certain acceptable limit, up to a maximum BMI past which the individual will simply be denied admissibility regardless of price. This can be contrasted with group insurance policies which do not require medical underwriting and where insurance admissibility is guaranteed by virtue of being a member of the insured group, regardless of BMI or other risk factors that would likely render the individual inadmissible to an individual health plan.

Limitations and shortcomings

This graph shows the correlation between body mass index (BMI) and percent body fat (%BF) for 8550 men in NCHS' NHANES 1994 data. Data in the upper left and lower right quadrants show some limitations of BMI.

The medical establishment and statistical community have both highlighted the limitations of BMI. Because the BMI depends upon weight and the square of height, it ignores basic scaling laws whereby mass increases to the 3rd power of linear dimensions. Hence, larger individuals, even if they had exactly the same body shape and relative composition, always have a larger BMI. Also, its assumptions about the distribution between lean mass and adipose tissue are inexact. BMI generally overestimates adiposity on those with more lean body mass (e.g., athletes) and underestimates excess adiposity on those with less lean body mass. A study in June 2008 by Romero-Corral et al. examined 13,601 subjects from the United States' third National Health and Nutrition Examination Survey (NHANES III) and found that BMI-defined obesity (BMI > 30) was present in 21% of men and 31% of women. Using body fat percentages (BF%), however, BF%-defined obesity was found in 50% of men and 62% of women. While BMI-defined obesity showed high specificity (95% for men and 99% for women), BMI showed poor sensitivity (36% for men and 49% for women). Despite this undercounting of obesity by BMI, BMI values in the intermediate BMI range of 20–30 were found to be associated with a wide range of body fat percentages. For men with a BMI of 25, about 20% have a body fat percentage below 20% and about 10% have body fat percentage above 30%.

Mathematician Keith Devlin and the restaurant industry association Center for Consumer Freedom argue that the error in the BMI is significant and so pervasive that it is not generally useful in evaluation of health. University of Chicago political science professor Eric Oliver says BMI is a convenient but inaccurate measure of weight, forced onto the populace, and should be revised.

A study published by Journal of the American Medical Association (JAMA) in 2005 showed that overweight people had a similar relative risk of mortality to normal weight people as defined by BMI, while underweight and obese people had a higher death rate. High BMI is associated with type 2 diabetes only in persons with high serum gamma-glutamyl transpeptidase.

In an analysis of 40 studies involving 250,000 people, patients with coronary artery disease with normal BMIs were at higher risk of death from cardiovascular disease than people whose BMIs put them in the overweight range (BMI 25–29.9). In the overweight, or intermediate, range of BMI (25–29.9), the study found that BMI failed to discriminate between bodyfat percentage and lean mass. The study concluded that "the accuracy of BMI in diagnosing obesity is limited, particularly for individuals in the intermediate BMI ranges, in men and in the elderly. These results may help to explain the unexpected better survival in overweight/mild obese patients."

A 2010 study that followed 11,000 subjects for up to eight years concluded that BMI is not a good measure for the risk of heart attack, stroke or death. A better measure was found to be the waist-to-height ratio. A 2011 study that followed 60,000 participants for up to 13 years found that waist–hip ratio was a better predictor of ischaemic heart disease mortality.

BMI is particularly inaccurate for people who are very fit or athletic, as their high muscle mass can classify them in the overweight category by BMI, even though their body fat percentages frequently fall in the 10–15% category, which is below that of a more sedentary person of average build who has a normal BMI number. Body composition for athletes is often better calculated using measures of body fat, as determined by such techniques as skinfold measurements or underwater weighing and the limitations of manual measurement have also led to new, alternative methods to measure obesity, such as the body volume index. However, recent studies of American football linemen who undergo intensive weight training to increase their muscle mass show that they frequently suffer many of the same problems as people ordinarily considered obese, notably sleep apnea.

BMI also does not account for body frame size; a person may have a small frame and be carrying more fat than optimal, but their BMI reflects that they are normal. Conversely, a large framed individual may be quite healthy with a fairly low body fat percentage, but be classified as overweight by BMI. Accurate frame size calculators use several measurements (wrist circumference, elbow width, neck circumference and others) to determine what category an individual falls into for a given height. The standard is to use frame size in conjunction with ideal height/weight charts and add roughly 10% for a large frame or subtract roughly 10% for a smaller frame.

For example, a chart may say the ideal weight for a man 5 ft 10 in (178 cm) is 165 pounds (75 kg). But if that man has a slender build (small frame), he may be overweight at 165 pounds (75 kg) and should reduce by 10%, to roughly 150 pounds (68 kg). In the reverse, the man with a larger frame and more solid build can be quite healthy at 180 pounds (82 kg). If one teeters on the edge of small/medium or medium/large, a dose of common sense should be used in calculating their ideal weight. However, falling into your ideal weight range for height and build is still not as accurate in determining health risk factors as waist/height ratio and actual body fat percentage.

A further limitation of BMI relates to loss of height through aging. In this situation, BMI will increase without any corresponding increase in weight.

The exponent of 2 in the denominator of the formula for BMI is arbitrary. It is meant to reduce variability in the BMI associated only with a difference in size, rather than with differences in weight relative to one's ideal weight. If taller people were simply scaled-up versions of shorter people, the appropriate exponent would be 3, as weight would increase with the cube of height. However, on average, taller people have a slimmer build relative to their height than do shorter people, and the exponent which matches the variation best is less than 3. An analysis based on data gathered in the US suggested an exponent of 2.6 would yield the best fit for children aged 2 to 19 years old. For US adults, exponent estimates range from 1.92 to 1.96 for males and from 1.45 to 1.95 for females. The exponent 2 is used by convention and for simplicity.

As a possible alternative to BMI, the concepts fat-free mass index (FFMI) and fat mass index (FMI) were introduced in the early 1990s, and Body Shape Index in 2012.

Varying standards

It is not clear where on the BMI scale the threshold for overweight and obese should be set. Because of this the standards have varied over the past few decades. Between 1980 and 2000 the U.S. Dietary Guidelines have defined overweight at a variety of levels ranging from a BMI of 24.9 to 27.1. In 1985 the National Institutes of Health (NIH) consensus conference recommended that overweight BMI be set at a BMI of 27.8 for men and 27.3 for women. In 1998 a NIH report concluded that a BMI over 25 is overweight and a BMI over 30 is obese. In the 1990s the World Health Organization (WHO) decided that a BMI of 25 to 30 should be considered overweight and a BMI over 30 is obese, the standards the NIH set. This became the definitive guide for determining if someone is overweight.

The current WHO and NIH ranges of normal weights are proved to be associated with decreased risks of some diseases such as diabetes type II; however using the same range of BMI for men and women is considered arbitrary, and makes the definition of underweight quite unsuitable for men.

Global statistics

Researchers at the London School of Hygiene & Tropical Medicine calculated the average BMI for 177 countries using UN data on population, WHO estimates of global weight, and mean height from national health examination surveys.

Country	Average BMI	Relative size of average BMI	Male BMI	Relative size of male BMI	Female BMI	Relative size of female BMI	Ratio of male to female BMI	Relative size of ratio
Afghanistan	21.01	21.01	21.36	21.36	20.65	20.65	1.034	1.034
Albania	24.53	24.53	27.60	27.6	21.45	21.45	1.287	1.287
Algeria	23.87	23.87	24.38	24.38	23.36	23.36	1.044	1.044
Angola	22.73	22.73	23.24	23.24	22.22	22.22	1.046	1.046
Argentina	26.44	26.44	27.76	27.76	25.11	25.11	1.106	1.106
Armenia	24.26	24.26	25.72	25.72	22.80	22.8	1.128	1.128
Australia	26.10	26.1	27.24	27.24	24.95	24.95	1.092	1.092
Austria	25.00	25	26.97	26.97	23.03	23.03	1.171	1.171
Azerbaijan	24.65	24.65	26.21	26.21	23.08	23.08	1.136	1.136
Bahamas	27.09	27.09	27.60	27.6	26.57	26.57	1.039	1.039
Bahrain	26.33	26.33	27.97	27.97	24.69	24.69	1.133	1.133
Bangladesh	20.32	20.32	21.00	21	19.63	19.63	1.070	1.07
Barbados	27.70	27.7	26.84	26.84	28.55	28.55	0.940	0.94
Belarus	26.72	26.72	26.32	26.32	27.11	27.11	0.971	0.971
Belgium	24.15	24.15	25.93	25.93	22.36	22.36	1.160	1.16
Belize	26.09	26.09	26.60	26.6	25.58	25.58	1.040	1.04
Benin	22.48	22.48	22.52	22.52	22.43	22.43	1.004	1.004
Bhutan	20.37	20.37	20.88	20.88	19.85	19.85	1.052	1.052
Bolivia	25.86	25.86	26.07	26.07	25.65	25.65	1.016	1.016
Bosnia and Herzegovina	23.94	23.94	26.18	26.18	21.69	21.69	1.207	1.207
Botswana	24.45	24.45	24.96	24.96	23.94	23.94	1.043	1.043
Brazil	24.79	24.79	25.85	25.85	23.72	23.72	1.090	1.09
Brunei	22.67	22.67	23.18	23.18	22.16	22.16	1.046	1.046
Bulgaria	23.77	23.77	26.53	26.53	21.01	21.01	1.263	1.263
Burkina Faso	21.25	21.25	21.86	21.86	20.64	20.64	1.059	1.059
Burundi	20.40	20.4	20.91	20.91	19.89	19.89	1.051	1.051
Cambodia	21.51	21.51	22.30	22.3	20.72	20.72	1.076	1.076
Cameroon	24.70	24.7	26.65	26.65	22.75	22.75	1.171	1.171
Canada	25.70	25.7	27.04	27.04	24.36	24.36	1.110	1.11
Cape Verde	23.44	23.44	23.95	23.95	22.93	22.93	1.044	1.044
Central African Republic	20.99	20.99	20.97	20.97	21.01	21.01	0.998	0.998
Chad	21.42	21.42	22.04	22.04	20.80	20.8	1.060	1.06
Chile	26.05	26.05	25.94	25.94	26.15	26.15	0.992	0.992
China	22.86	22.86	23.78	23.78	21.93	21.93	1.084	1.084
Colombia	24.94	24.94	26.30	26.3	23.58	23.58	1.115	1.115
Comoros	22.99	22.99	23.39	23.39	22.59	22.59	1.035	1.035
Congo	21.91	21.91	22.30	22.3	21.52	21.52	1.036	1.036
Costa Rica	24.87	24.87	26.06	26.06	23.68	23.68	1.101	1.101
Côte d'Ivoire	22.03	22.03	21.64	21.64	22.42	22.42	0.965	0.965
Croatia	26.61	26.61	30.21	30.21	23.00	23	1.313	1.313
Cuba	25.64	25.64	26.78	26.78	24.49	24.49	1.094	1.094
Cyprus	26.70	26.7	27.21	27.21	26.18	26.18	1.039	1.039
Czech Republic	23.78	23.78	26.50	26.5	21.06	21.06	1.258	1.258
Denmark	24.24	24.24	25.75	25.75	22.73	22.73	1.133	1.133
Djibouti	22.96	22.96	23.47	23.47	22.44	22.44	1.046	1.046
Dominican Republic	25.45	25.45	25.55	25.55	25.34	25.34	1.008	1.008
DR Congo	20.25	20.25	20.76	20.76	19.74	19.74	1.052	1.052
East Timor	20.72	20.72	21.23	21.23	20.20	20.2	1.051	1.051
Ecuador	25.58	25.58	26.09	26.09	25.06	25.06	1.041	1.041
Egypt	26.70	26.7	27.14	27.14	26.25	26.25	1.034	1.034
El Salvador	25.80	25.8	26.31	26.31	25.28	25.28	1.041	1.041
Equatorial Guinea	24.75	24.75	25.26	25.26	24.24	24.24	1.042	1.042
Eritrea	19.85	19.85	20.27	20.27	19.43	19.43	1.043	1.043
Estonia	23.06	23.06	25.21	25.21	20.90	20.9	1.206	1.206
Ethiopia	20.46	20.46	20.97	20.97	19.94	19.94	1.052	1.052
Fiji	24.99	24.99	25.25	25.25	24.72	24.72	1.021	1.021
Finland	25.06	25.06	26.76	26.76	23.36	23.36	1.146	1.146
France	23.56	23.56	24.90	24.9	22.22	22.22	1.121	1.121
Gabon	23.40	23.4	23.75	23.75	23.05	23.05	1.030	1.03
Gambia	21.73	21.73	21.94	21.94	21.52	21.52	1.020	1.02
Georgia	25.27	25.27	25.78	25.78	24.75	24.75	1.042	1.042
Germany	25.32	25.32	27.17	27.17	23.46	23.46	1.158	1.158
Ghana	23.15	23.15	24.64	24.64	21.65	21.65	1.138	1.138
Greece	26.13	26.13	27.68	27.68	24.57	24.57	1.127	1.127
Grenada	26.43	26.43	26.94	26.94	25.91	25.91	1.040	1.04
Guatemala	25.88	25.88	26.42	26.42	25.34	25.34	1.043	1.043
Guinea	22.06	22.06	22.41	22.41	21.71	21.71	1.032	1.032
Guinea-Bissau	21.04	21.04	21.55	21.55	20.53	20.53	1.050	1.05
Guyana	25.10	25.1	25.61	25.61	24.59	24.59	1.041	1.041
Haiti	23.12	23.12	22.21	22.21	24.03	24.03	0.924	0.924
Honduras	25.12	25.12	25.63	25.63	24.61	24.61	1.041	1.041
Hungary	24.45	24.45	26.50	26.5	22.39	22.39	1.184	1.184
Iceland	25.93	25.93	26.80	26.8	25.06	25.06	1.069	1.069
India	21.05	21.05	22.50	22.5	19.60	19.6	1.148	1.148
Indonesia	21.59	21.59	21.91	21.91	21.26	21.26	1.031	1.031
Iran	24.28	24.28	25.21	25.21	23.35	23.35	1.080	1.08
Iraq	24.53	24.53	25.04	25.04	24.01	24.01	1.043	1.043
Ireland	24.40	24.4	26.14	26.14	22.65	22.65	1.154	1.154
Israel	25.05	25.05	26.72	26.72	23.37	23.37	1.143	1.143
Italy	23.49	23.49	25.78	25.78	21.19	21.19	1.217	1.217
Jamaica	26.21	26.21	24.82	24.82	27.60	27.6	0.899	0.899
Japan	21.93	21.93	23.52	23.52	20.34	20.34	1.156	1.156
Jordan	25.09	25.09	26.65	26.65	23.52	23.52	1.133	1.133
Kazakhstan	22.99	22.99	25.02	25.02	20.96	20.96	1.194	1.194
Kenya	21.41	21.41	21.59	21.59	21.23	21.23	1.017	1.017
Kuwait	27.92	27.92	28.77	28.77	27.07	27.07	1.063	1.063
Kyrgyzstan	22.90	22.9	23.99	23.99	21.80	21.8	1.100	1.1
Laos	21.99	21.99	22.50	22.5	21.48	21.48	1.047	1.047
Latvia	23.73	23.73	25.38	25.38	22.07	22.07	1.150	1.15
Lebanon	24.57	24.57	26.60	26.6	22.54	22.54	1.180	1.18
Lesotho	24.56	24.56	22.96	22.96	26.16	26.16	0.878	0.878
Liberia	21.00	21	21.51	21.51	20.49	20.49	1.050	1.05
Libya	26.06	26.06	26.57	26.57	25.55	25.55	1.040	1.04
Lithuania	24.29	24.29	26.44	26.44	22.14	22.14	1.194	1.194
Luxembourg	25.06	25.06	25.60	25.6	24.51	24.51	1.044	1.044
Macedonia	23.81	23.81	24.25	24.25	23.36	23.36	1.038	1.038
Madagascar	21.60	21.6	22.31	22.31	20.89	20.89	1.068	1.068
Malawi	21.96	21.96	22.02	22.02	21.90	21.9	1.005	1.005
Malaysia	22.58	22.58	23.06	23.06	22.09	22.09	1.044	1.044
Maldives	22.21	22.21	23.54	23.54	20.88	20.88	1.127	1.127
Mali	22.18	22.18	22.11	22.11	22.24	22.24	0.994	0.994
Malta	26.04	26.04	27.91	27.91	24.17	24.17	1.155	1.155
Mauritania	23.74	23.74	24.17	24.17	23.30	23.3	1.037	1.037
Mauritius	24.46	24.46	25.05	25.05	23.87	23.87	1.049	1.049
Mexico	26.54	26.54	27.70	27.7	25.37	25.37	1.092	1.092
Micronesia	32.82	32.82	32.80	32.8	32.84	32.84	0.999	0.999
Moldova	25.24	25.24	25.75	25.75	24.73	24.73	1.041	1.041
Mongolia	25.94	25.94	24.78	24.78	27.10	27.1	0.914	0.914
Morocco	23.76	23.76	23.71	23.71	23.80	23.8	0.996	0.996
Mozambique	21.27	21.27	21.27	21.27	21.27	21.27	1.000	1
Myanmar	22.40	22.4	22.91	22.91	21.89	21.89	1.047	1.047
Namibia	22.00	22	22.01	22.01	21.99	21.99	1.001	1.001
Nepal	20.55	20.55	20.82	20.82	20.27	20.27	1.027	1.027
Netherlands	24.14	24.14	25.72	25.72	22.56	22.56	1.140	1.14
New Zealand	26.61	26.61	27.55	27.55	25.67	25.67	1.073	1.073
Nicaragua	25.61	25.61	25.83	25.83	25.38	25.38	1.018	1.018
Niger	21.49	21.49	22.27	22.27	20.71	20.71	1.075	1.075
Nigeria	22.88	22.88	23.98	23.98	21.77	21.77	1.102	1.102
North Korea	20.78	20.78	21.29	21.29	20.27	20.27	1.050	1.05
Norway	24.69	24.69	26.28	26.28	23.10	23.1	1.138	1.138
Oman	24.15	24.15	25.41	25.41	22.89	22.89	1.110	1.11
Pakistan	21.53	21.53	21.92	21.92	21.14	21.14	1.037	1.037
Panama	26.16	26.16	26.67	26.67	25.65	25.65	1.040	1.04
Papua New Guinea	23.79	23.79	23.16	23.16	24.41	24.41	0.949	0.949
Paraguay	25.32	25.32	25.83	25.83	24.81	24.81	1.041	1.041
Peru	25.23	25.23	25.87	25.87	24.59	24.59	1.052	1.052
Philippines	22.35	22.35	22.73	22.73	21.96	21.96	1.035	1.035
Poland	23.21	23.21	25.88	25.88	20.54	20.54	1.260	1.26
Portugal	24.59	24.59	26.49	26.49	22.69	22.69	1.167	1.167
Qatar	27.47	27.47	27.98	27.98	26.96	26.96	1.038	1.038
Romania	22.98	22.98	24.62	24.62	21.33	21.33	1.154	1.154
Russian Federation	23.25	23.25	24.80	24.8	21.69	21.69	1.143	1.143
Rwanda	21.67	21.67	21.15	21.15	22.19	22.19	0.953	0.953
Saint Lucia	25.23	25.23	24.59	24.59	25.86	25.86	0.951	0.951
Samoa	28.34	28.34	28.79	28.79	27.88	27.88	1.033	1.033
São Tomé and Príncipe	21.75	21.75	22.26	22.26	21.24	21.24	1.048	1.048
Saudi Arabia	26.11	26.11	27.88	27.88	24.33	24.33	1.146	1.146
Senegal	22.68	22.68	23.73	23.73	21.62	21.62	1.098	1.098
Sierra Leone	23.45	23.45	23.87	23.87	23.03	23.03	1.036	1.036
Singapore	22.19	22.19	22.80	22.8	21.58	21.58	1.057	1.057
Slovakia	25.34	25.34	25.85	25.85	24.83	24.83	1.041	1.041
Slovenia	25.38	25.38	25.89	25.89	24.87	24.87	1.041	1.041
Solomon Islands	27.34	27.34	27.85	27.85	26.83	26.83	1.038	1.038
Somalia	20.48	20.48	20.99	20.99	19.97	19.97	1.051	1.051
South Africa	24.96	24.96	24.95	24.95	24.97	24.97	0.999	0.999
South Korea	24.06	24.06	25.34	25.34	22.78	22.78	1.112	1.112
Spain	24.52	24.52	26.47	26.47	22.57	22.57	1.173	1.173
Sri Lanka	20.51	20.51	21.44	21.44	19.57	19.57	1.096	1.096
St Vincent and the Grenadines	26.04	26.04	26.55	26.55	25.53	25.53	1.040	1.04
Sudan	21.97	21.97	22.48	22.48	21.46	21.46	1.048	1.048
Suriname	25.71	25.71	26.22	26.22	25.20	25.2	1.040	1.04
Swaziland	23.39	23.39	23.90	23.9	22.88	22.88	1.045	1.045
Sweden	24.54	24.54	26.11	26.11	22.97	22.97	1.137	1.137
Switzerland	24.94	24.94	25.47	25.47	24.40	24.4	1.044	1.044
Syria	25.00	25	25.51	25.51	24.49	24.49	1.042	1.042
Tajikistan	25.21	25.21	25.72	25.72	24.70	24.7	1.041	1.041
Tanzania	21.83	21.83	21.87	21.87	21.78	21.78	1.004	1.004
Thailand	22.34	22.34	23.36	23.36	21.32	21.32	1.096	1.096
Togo	22.22	22.22	22.72	22.72	21.72	21.72	1.046	1.046
Tonga	32.90	32.9	32.03	32.03	33.77	33.77	0.948	0.948
Trinidad and Tobago	26.90	26.9	26.46	26.46	27.33	27.33	0.968	0.968
Tunisia	23.86	23.86	24.63	24.63	23.08	23.08	1.067	1.067
Turkey	24.92	24.92	25.33	25.33	24.50	24.5	1.034	1.034
Turkmenistan	23.55	23.55	25.13	25.13	21.96	21.96	1.144	1.144
Uganda	21.53	21.53	21.03	21.03	22.02	22.02	0.955	0.955
Ukraine	23.34	23.34	24.84	24.84	21.84	21.84	1.137	1.137
United Arab Emirates	26.66	26.66	27.60	27.6	25.71	25.71	1.074	1.074
United Kingdom	26.19	26.19	27.62	27.62	24.76	24.76	1.116	1.116
United States	27.82	27.82	28.64	28.64	27.00	27	1.061	1.061
Uruguay	25.06	25.06	26.88	26.88	23.24	23.24	1.157	1.157
Uzbekistan	23.80	23.8	24.99	24.99	22.60	22.6	1.106	1.106
Vanuatu	25.53	25.53	26.46	26.46	24.60	24.6	1.076	1.076
Venezuela	26.19	26.19	27.52	27.52	24.86	24.86	1.107	1.107
Vietnam	19.96	19.96	21.18	21.18	18.73	18.73	1.131	1.131
Yemen	22.07	22.07	22.91	22.91	21.22	21.22	1.080	1.08
Zambia	21.02	21.02	21.02	21.02	21.01	21.01	1.000	1
Zimbabwe	22.38	22.38	21.70	21.7	23.06	23.06	0.941	0.941
Country	Average BMI	Relative size of average BMI	Male BMI	Relative size of male BMI	Female BMI	Relative size of female BMI	Ratio of male to female BMI	Relative size of ratio

See also

• Allometric law
• Body water
• Pignet Index

Other measures of obesity:

• Body adiposity index
• Body fat percentage
• Body volume index
• Ponderal index
• Sagittal Abdominal Diameter (SAD)
• Waist-hip ratio
• Waist-to-height ratio

Further reading

• Ferrera, Linda A., ed. (2006). Focus on Body Mass Index And Health Research. New York: Nova Science. ISBN 978-1-59454-963-2.
• Samaras, Thomas T., ed. (2007). Human Body Size and the Laws of Scaling: Physiological, Performance, Growth, Longevity and Ecological Ramifications. New York: Nova Science. ISBN 978-1-60021-408-0.
• Sothern, Melinda S.; Gordon, Stewart T.; von Almen, T. Kristian, eds. (2006). Handbook of Pediatric Obesity: Clinical Management (illustrated ed.). CRC Press. ISBN 978-1-4200-1911-7.

External links

• U.S. National Center for Health Statistics:
  • BMI Growth Charts for children and young adults
  • BMI calculator ages 2–19
  • BMI calculator ages 20 and older