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Understanding Your BMI Result

The Body Mass Index (BMI) is a weight-for-height index that classifies underweight, overweight, and obesity in adults. 

BMI is calculated by dividing weight in kilograms by the square of height in meters (BMI values represent units of kg/m2, and all BMI values throughout this article should be assumed to be measured in this unit).

There are different BMI categories, explored in detail below.

Underweight BMI Range

BMI result: Below 18.5

Those who fall into this category are defined as underweight.

Being underweight could be a sign you're not eating enough or may indicate an underlying medical condition. If you're underweight, contact your doctor for further evaluation.

Normal Weight BMI Range

BMI result: Between 18.5 and 24.9

The medical community recommends keeping your weight within this range.

Overweight BMI Range

BMI result: between 25 and 29.9

People in this category may be at risk of developing obesity

There may also be a risk of developing other health problems or current health problems worsening over time. Based on European and American clinical guidelines for obesity management in adults, the following are the most likely recommendations based on BMI ranges.

BMI result between 25 and 26.9
People who do not have weight-related health problems (for example, high blood pressure or high cholesterol) are encouraged to eat healthy and increase their physical activity to prevent further weight gain.

BMI result between 27 and 29.9
People in this range who also have weight-related health problems will likely be recommended to lose weight by combining lifestyle interventions and consider anti-obesity medications.

Committing to health interventions can lead to weight loss, improved health, and experiencing a higher quality of life.

Classification of obesity

There are three classes of obesity based on BMI ranges:

Obesity classification  BMI
 Class I  30.0–34.9
 Class II  35.0–39.9
 Class III  Above 40

BMI ranges are based on the effect excess body fat has on an individual’s health, life expectancy, and the risk of developing weight-related health complications.

BMI result: 30.0 or higher

People who have a BMI equal to or above 30 may suffer from obesity.

Health organizations now recognize obesity as a chronic, but manageable disease that is best dealt with using a multi-disciplinary weight loss treatment approach. 

As BMI increases into the range to be considered living with obesity, so does the risk factor of certain chronic diseases.

Higher BMIs (greater than or equal to 30) have statistically significant associations with several medical conditions. These conditions include but are not limited to - cardiovascular disease, type 2 diabetes, osteoarthritis, and various cancers. 

BMI is not a diagnosis of obesity but instead can be used to screen for health risks. 

People with a BMI equal to or above 30 are highly recommended to consult a doctor trained in obesity management.

There are various scientifically proven treatment options for obesity. Treatment options are dependent on the specific needs of the individual, their current health status, and presence of weight-related health complications.

Treatments may include a combination of the following options:

*Bariatric surgery is considered for adults with a BMI of 40 or above or adults with a BMI of over 35 who also have weight-related comorbidities.

Disclaimer: This information is not a substitute for the advice of a healthcare provider. If you have any questions regarding your health, you should contact your general practitioner or another qualified healthcare provider.

Related articles

Why is BMI important?

Obesity is a chronic disease which requires medical attention. For most populations, living with overweight or obesity (BMI greater than or equal to 25) is associated with increased risk of mortality and increased risk of comorbidities.

Obesity screenings can take BMI threshold levels into account. Obesity can also be an indicator of potential future health issues that may require medical advice.

In general, the higher your BMI in the range to be considered living with obesity, the greater the risk of developing other chronic obesity-related diseases including:

  • Type II diabetes
  • Cardiovascular disease
  • Stroke
  • High blood pressure
  • Infertility
  • Depression and anxiety
  • Coronary heart disease
  • Dyslipidemia
  • Nonalcoholic fatty liver disease  (NAFLD)/Nonalcoholic steatohepatitis (NASH)
  • Gastroesophageal reflux disease (GERD)
  • Metabolic syndrome (MetS)
  • Urinary incontinence
  • Obstructive sleep apnea and breathing problems
  • Chronic kidney disease
  • Various types of cancer: including but not limited to - breast, colon, endometrial, oesophageal, kidney, ovarian, and pancreatic cancer
  • Knee osteoarthritis
  • Gallstone disease
  • Thrombosis
  • Gout

If you are concerned about any of these diseases and how they relate to your BMI, consult your doctor for further information and evaluation.

Understanding BMI for various ethnic backgrounds

Evidence suggests that fat distribution and body composition differ across certain ethnic groups.

People with certain ethnic backgrounds may have higher or lower health risks compared to those from another ethnic background with the same BMI.

This means some groups may have a greater predisposition for developing obesity-related diseases such as type 2 diabetes or heart disease, for example. Therefore, based on your genetics, you may incur greater health risks associated with excess weight.

This has led to proposals for specific BMI thresholds based on ethnic backgrounds.

For instance, lower BMI cut-off values has been suggested for certain Asian populations. For example, lowering the cut-off values by 3 units for Indonesian, Singaporean, and Hong Kong Chinese populations.

This is because Asian populations tend to have a higher amount of body fat at a lower BMI. As a result, there is an increased risk of associated health complications, compared to other populations.

In the section below, research has pointed to links between BMI and different ethnic backgrounds. These factors may be a consideration when determining if taking action is right for you. 

South Asian ethnic group and BMI (Indian, Bangladeshi, Pakistani)

In a study comparing Singaporean Indian, Malay, Chinese, and Caucasian populations, Indians had the highest body fat percentage at equivalent BMIs. Higher body fat percentages have been linked with greater cardiovascular risk factors.

Indian populations were shown to have same amount of body fat at a BMI of 26, as Caucasians with a BMI of 30, the threshold to be considered obese.

When compared to Caucasian, Chinese, and Aboriginal ethnic groups, a study found that South Asian populations had a higher body fat to lean mass ratio. This indicates that South Asian populations have increased risk of diabetes.

Populations of South Asian descent living in the UK experienced higher incidences of coronary heart disease and stroke than Caucasians. Both coronary heart disease and stroke are associated with body fat and body fat distribution.

East Asian ethnic group and BMI (Chinese, Taiwanese, Japanese, Korean)

A study of East Asian populations found that those with a BMI of 25 or above had a higher risk of mortality from cardiovascular disease, coronary heart disease, and stroke when compared to the reference range typically associated with a given BMI.

In the study of Taiwanese populations, significantly increased mortality risks were experienced at BMI greater than or equal to 25. These findings support the need to define obesity in East Asian populations differently, lowering the BMI cut-off point by 5 units from 30 to 25.

Similarly, data suggested that for Japanese populations obesity should be categorized as a BMI greater than or equal to 25.

Studies have shown that Asian populations had a higher body fat percentage compared to Caucasians for a given BMI. Asian populations also have elevated risk of comorbidities such as type 2 diabetes, hypertension, and hyperlipidemia.

Southeast Asian ethnic group and BMI (Vietnamese, Thai, Filipino, Indonesian, Malaysian)

In a study of the Thai population, waist circumference was shown to be a better predictor of diabetes than BMI. This may be because most studies evaluating the association of BMI with mortality risks have been conducted on populations of European descent (Caucasians).

According to a multi-ethnic study in Singapore, Malay populations had a higher body fat percentage than Caucasians at an equivalent BMI. Data suggested that average amount of body fat in Caucasians with obesity (BMI 30), could be found in Malays with a BMI of 27.

Studies of Southeast Asian populations in California found that Filipino- and Vietnamese-Americans were significantly more likely to suffer from type 2 diabetes compared to Caucasians. Therefore, such populations should take into account that being overweight/obese can increase risk factors for type 2 diabetes.

Pacific Islander ethnic group and BMI

Certain Pacific Islander populations have lower body fat percentages compared to Caucasians at the same BMI, though this is not the case for all populations considered to be ‘Pacific Islander’.

A study showed that Pacific Islanders suffering from overweight or obesity had a significantly higher likelihood of having hypertension, compared to Caucasian populations.

Native Hawaiians have been shown to be 3 times more likely to have diabetes compared to Caucasian populations, across all BMI categories.

Latin(o/a) & Hispanic ethnic group and BMI

A study found that for populations of the same BMI, Mexicans had a greater total body fat and less skeletal muscle compared to Caucasians.

A separate study found that Mexican-Americans had a higher prevalence of obesity compared to Caucasians, but a lower prevalence of associated hypertension.

Similarly, research on Latino populations in the USA found them to be at least twice as likely to suffer from diabetes when compared with Caucasians, regardless of BMI category.

Various studies of Hispanic/Latino populations have suggested that BMI and waist circumference threshold levels for predicting the likelihood of chronic diseases should be unique to ethnic populations.

Black ethnic group and BMI

In the USA, differences in BMI between populations account for almost 30% of the difference in Black and White mortality rates amongst females aged 40-79.

When comparing Caucasians with a BMI of 25, the equivalent type 2 diabetes risk in Black populations was seen at lower BMIs (between 21-23). For a BMI of 30 in Caucasian populations, the equivalent diabetes risk in black populations is at BMI values 0.1–4 units lower (26–29.9).

Middle Eastern ethnic group and BMI

A study conducted in Saudi Arabia highlighted the limitation of using the current BMI cut-off (≥30) in diagnosing obesity among the Saudi and possibly the Arab population. The study suggested lowering the BMI threshold for obesity to 27 in order to accurately reflect the obesity-related health risks in these populations.

In a study conducted in Sweden, the diabetes risk of Caucasians living with obesity (BMI of 30) was equal to that of Iraqi men with a BMI of 28.5, and Iraqi women with BMI of 27.5.

This is one of the main determinants of type 2 diabetes, implying a greater risk for Iraqi populations than Caucasians at the same level of BMI.

When observing the population in Jeddah, Saudi Arabia, researchers reported that women with obesity had a higher risk of prediabetes, diabetes, and dyslipidemia. Men in the same population with obesity had greater risk of having high blood pressure.

White/Caucasian ethnic group and BMI

Studied White/Caucasian populations were shown to have a greater risk of mortality associated with a higher BMI, compared to Black populations at equivalent BMI levels.

The researchers noted greater risk associated with obesity for coronary heart disease, stroke and heart disease among White/Caucasian populations.

BMI in special populations

BMI can be misleading in certain cases. Research has shown that BMI can less accurately predict the disease risks for some groups of people:

  • Elderly
  • Athletes
  • People of tall or short stature
  • Body types with more muscle mass

For instance, in certain populations such as elite athletes or bodybuilders an elevated BMI does not directly correlate with their health status. Their increased muscle mass and therefore weight also increases their BMI.

The table below shows how the average body fat percentages differ according to specific groups and categories:

 Description  Men  Women
 Essential fat  2 - 5 %  10 - 13 %
 Athletes  6 - 13 %  14 - 20 %
 Fitness  14 - 17 %  21 - 24 %
 Acceptable  18 - 24 %  25 - 31 %
 Obesity  >25 %  >32 %

BMI & gender

At present, there is no individual BMI calculation for women and men. However, whilst gender is not factored into BMI calculations, the physiological differences between genders may imply a difference in the degree of risk at a given BMI.


In terms of weight distribution, it has been reported that men tend to accumulate body fat in the upper body, including the abdomen.

Abdominal obesity and higher concentrations of visceral fat in men lead to a higher risk of heart disease and type 2 diabetes.


Whilst women tend to have a higher percentage of body fat than men, fat deposits in females tends to be distributed in the hips and buttocks.

Due to differences in fat deposition, women may be at lower risk of the comorbidities associated with obesity compared to men at the same or similar BMI.

BMI & age

Adult BMI calculations do not take age into account. However, research suggests that whilst obesity increases mortality risk at any age, this correlation is much stronger in people below the age of 50.

Accelerated weight gain as a child has been shown to imply further weight gain during adolescence and adulthood. Weight gain as a child is therefore a strong indicator of obesity in adulthood. A study shows that 40% of children with obesity will become obese adults.

Whilst BMI is interpreted differently for children and adolescents compared to adults, growing evidence suggests that BMI guidelines should be age-specific for adult populations as well.

Children & adolescents

BMI interpretation in children and adolescents is both age- and gender-specific. This is because girls and boys develop at different rates, with body fat varying during developmental periods such as puberty.

Obesity in childhood has been shown to be a strong predictor of various obesity-related diseases such as type 2 diabetes, dyslipidemia, and sleep apnea. Children with obesity are also more likely to suffer from psychological distress. This can include low self-esteem, anxiety disorders, and depressive symptoms.

If you are a parent concerned about the health of your child with relation to their weight, consult your doctor for guidance on weight management and possible treatment options.

Elderly adult

The composition of our bodies naturally changes with age. An increase in body fat is statistically likely to occur over adulthood, whilst total muscle mass also decreases with age.

Muscle mass and strength are considered important for the maintenance of physical activity.

Studies have shown that when using standard BMI calculations, being slightly overweight is associated with a reduced risk of mortality compared to the ‘normal’ weight range in older populations.

The standard BMI calculation can also underestimate or overestimate the amount of excess fat carried by elderly persons. Assessments such as waist circumference have therefore been recommended as better options when measuring body fat in the elderly.

Diagnosis of obesity

Diagnosing obesity should not be limited to measuring BMI alone. However, BMI can help identify people who would experience health improvements from obesity management.

Diagnostic testing is often ordered during initial obesity assessments, with the aim of discovering metabolic problems and personalizing treatment options. Screening will typically involve various types of laboratory testing:

  • HbA1C
  • Electrolytes renal function tests (creatinine, eGFR)
  • Total cholesterol, HDL- and LDL-cholesterol, triglycerides
  • Alanine aminotransferase (ALT)
  • Age appropriate cancer screening

In addition to these tests, healthcare providers may take a comprehensive diagnostic approach to understand the underlying causes of obesity. A comprehensive approach aims to discover potential contributing factors to a person’s obesity, and therefore provide an individualized treatment program.

Consult your doctor if you would like to learn more about comprehensive diagnoses for obesity.

Waist circumference vs BMI

To gain a better understanding of health, other diagnostics and measurements may be taken alongside BMI (for example, waist circumference). 

Waist circumference is an indirect measure of abdominal fat, whereas BMI is a representation of total body fat. Waist circumference has therefore been cited as a more accurate measure of obesity-related health risk, such as comorbidity and mortality.

Researchers have recommended that waist circumference be used together with BMI to more accurately evaluate an individual’s health risk factors.

Regardless of BMI, you should consult your doctor if you have concerns about your health.

Weight management programs may be relevant if your waist measurements are or exceed:

  • Men: 94cm (37in) or more
  • Women: 80cm (31.5in) or more

Higher waist circumferences are associated with greater health risk. You may want to consider obesity treatment programs if your waist measurements are as follows:

  • Men: 102cm (40in) or more
  • Women: 88cm (34.5in) or more

Is it possible to have a higher BMI and be healthy?

Typically, people suffering from obesity present a variety of health conditions collectively known as metabolic syndrome.

Screening for metabolic syndrome is recommended for the majority of people with higher BMIs.

This involves looking for the metabolic risk factors associated with obesity, including the following:

  • Waist circumference
  • High triglyceride levels
  • Low HDL cholesterol levels
  • High LDL cholesterol levels
  • High blood pressure
  • High blood sugar

At least three metabolic risk factors must be present to be diagnosed with metabolic syndrome. As such, metabolic syndrome is defined as a cluster of conditions, and can raise the risk of heart disease, type 2 diabetes, and stroke.

Metabolic Healthy Obesity

The link between obesity and obesity-related complications is strong but not absolute.

Some people with obesity do not present with metabolic syndrome and are reported to have limited health risks at higher BMIs. This group is defined as metabolically healthy obese individuals.

These individuals have lower risk of developing diabetes and heart disease compared to other people with obesity who suffer from metabolic syndrome.

However, clinical guidelines specify that people who are metabolically-healthy and obese cannot be considered ‘medically healthy’. They are at greater risk of mortality, as well as other non-metabolic conditions such as depression, back pain, and sleep apnea.

Despite the absence of metabolic risk factors, a study found that people who are metabolically-healthy and obese were likely to develop metabolic abnormalities within 10 years. This means they are still at risk of progressing to an unhealthy metabolic state.

If you are living with obesity but do not present with chronic disease symptoms associated with obesity, you may consider consulting your doctor to evaluate your metabolic risk factors.

Adopting a healthier lifestyle can help this risk group to prevent medical complications and avoid further weight gain.

History of the BMI

The BMI was conceived by the Belgian mathematician, Lambert Adolphe Jacques Quetelet, in the mid-19th century.

Despite not being a doctor, Quetelet introduced the concept of social averages. He noted the relationship between weight and height in what was first known as the “Quetelet Index.”

Keys et al later popularised the measurement, describing it as the Body Mass Index and using it as a classification in population-based studies.

The BMI has been adopted into modern medical practices, especially in Western societies with rising obesity rates.

Limitations of BMI

BMI is a simple and objective measurement, which can be easily conducted by a doctor or anyone concerned about their health.

However, beyond the previously discussed limitations, you may also consider that BMI measurements do not take account of the following:

  • Hereditary risk factors associated with obesity-related diseases such as metabolic syndrome.
  • Environmental and lifestyle factors other than obesity that can contribute to chronic disease risk.
  • Individual body fat distribution.

It is also important to remember that obesity is not a definitive indicator of ill-health, just as being at a ‘normal’ weight does not mean you are healthy.

Your BMI does not define you, but knowing and understanding your BMI can be a powerful tool for taking charge of your own health.

Consult with your doctor in order to discuss your weight and health status and evaluate what actions may be needed.


There is an important relationship between the amount of body fat a person has and the impacts on our health. Studies have demonstrated health risks associated with both extremes of the BMI spectrum.

Various factors independent of weight can put you at risk of developing chronic diseases (such as ethnicity and genetics). It is important to be aware of these factors, and how they might contribute to your risk if you do suffer from obesity.

BMI levels greater than or equal to 30 are associated with increased mortality and risk of health complications. Obesity screenings should take such BMI thresholds into account.

There are ‘metabolically healthy’ people that sustain limited health issues at higher BMIs. However, obesity can still increase other health risks for such individuals compared to those at lower BMIs.

For the majority of people with obesity, screening for metabolic syndrome is recommended.

Understanding your BMI can help you find a healthy weight range and identify the best way to reach or maintain it together with your healthcare team. For most populations, having a BMI over 25 increases health risk factors.

Your BMI should be used as a guideline and first step towards understanding your weight and height. Adhering to a healthy diet and lifestyle is recommended by healthcare professionals – regardless of your current BMI.

For BMIs equal to or above 25, other actions might be needed in addition to diet and physical exercise. Consulting your doctor is the best way to define the right solutions for you.

Seek medical advice if you have any concerns regarding your weight.

  • Rueda-Clausen, C F et al, “Assessment of People Living with Obesity,” Can. Adult Obes. Clin. Pract. Guidel., pp. 1–17, 2020, [Online]. Available: http://obesitycanada.ca/wp-content/uploads/2020/09/6-Obesity-Assessment-v5-with-links.pdf
  • Yumuk, V et al, “European Guidelines for Obesity Management in Adults” Obes Facts. 2015 Dec; 8(6): 402–424. Published online 2015 Dec 5. doi: 10.1159/000442721
  • Garvey, W T et al, “American Association of Clinical Endocrinologists and American College of Endocrinology comprehensive clinical practice guidelines for medical care of patients with obesity.” Endocrine Practice 2016;22:1–203. DOI:https://doi.org/10.4158/EP161365.GL
  • Guh, D P et al, “The incidence of co-morbidities related to obesity and overweight: A systematic review and meta-analysis,” BMC Public Health, vol. 9, no. 1, p. 88, 2009, doi: 10.1186/1471-2458-9-88.
  • Prospective Studies Collaboration, “Body-mass index and cause-specific mortality in 900000 adults: collaborative analyses of 57 prospective studies,” Lancet, vol. 373, no. 9669, pp. 1083–1096, Mar. 2009, doi: 10.1016/S0140-6736(09)60318-4.
  • “Obesity Screening – Medline Plus, U.S. National Library of Medicine” Available: https://medlineplus.gov/lab-tests/obesity-screening/
  • “Assessing Your Weight and Health Risk – National Heart, Lung, and Blood Association – U.S. Department of Health & Human Services” Available: https://www.nhlbi.nih.gov/health/educational/lose_wt/risk.htm
  • Hussain, A et al, “Type 2 Diabetes and obesity: A review” Journal of Diabetology, June 2010; 2:1
  • Katzmarzyk, P T et al, “Body mass index and risk of cardiovascular disease, cancer and all-cause mortality” Can. J. Public Health, vol. 103, no. 2, pp. 147–151, 2012, doi: 10.1007/BF03404221.
  • Kurth, T et al, “Prospective Study of Body Mass Index and Risk of Stroke in Apparently Healthy Women,” Circulation, vol. 111, no. 15, pp. 1992–1998, Apr. 2005, doi: 10.1161/01.CIR.0000161822.83163.B6.
  • Landi, F et al, “Body Mass Index is Strongly Associated with Hypertension: Results from the Longevity Check-Up 7+ Study” Nutrients. 2018 Dec; 10(12): 1976. Published online 2018 Dec 13. doi: 10.3390/nu10121976
  • Dağ, Z Ö et al, “Impact of obesity on infertility in women,” J. Turkish Ger. Gynecol. Assoc., vol. 16, no. 2, pp. 111–117, Jun. 2015, doi: 10.5152/jtgga.2015.15232.
  • Moussa, O M et al, “Effect of body mass index on depression in a UK cohort of 363037 obese patients: A longitudinal analysis of transition,” Clin. Obes., vol. 9, no. 3, p. e12305, Jun. 2019, doi: https://doi.org/10.1111/cob.12305.
  • Zhao, G et al, “Depression and anxiety among US adults: associations with body mass index,” Int. J. Obes., vol. 33, no. 2, pp. 257–266, 2009, doi: 10.1038/ijo.2008.268.
  • Lamon-Fava, S et al, “Impact of Body Mass Index on Coronary Heart Disease Risk Factors in Men and Women,” Arterioscler. Thromb. Vasc. Biol., vol. 16, no. 12, pp. 1509–1515, Dec. 1996, doi: 10.1161/01.ATV.16.12.1509.
  • Van Hemelrijck, M et al, “Longitudinal study of body mass index, dyslipidemia, hyperglycemia, and hypertension in 60,000 men and women in Sweden and Austria” Published: June 13, 2018https://doi.org/10.1371/journal.pone.0197830
  • Loomis, A K et al, “Body Mass Index and Risk of Nonalcoholic Fatty Liver Disease: Two Electronic Health Record Prospective Studies,” J. Clin. Endocrinol. Metab., vol. 101, no. 3, pp. 945–952, Mar. 2016, doi: 10.1210/jc.2015-3444.
  • Zafar, S et al, “Correlation of gastroesophageal reflux disease symptoms with body mass index,” Saudi J. Gastroenterol., vol. 14, no. 2, pp. 53–57, Apr. 2008, doi: 10.4103/1319-3767.39618.
  • Han, T S et al, “A clinical perspective of obesity, metabolic syndrome and cardiovascular disease,” JRSM Cardiovasc. Dis., vol. 5, pp. 2048004016633371–2048004016633371, Feb. 2016, doi: 10.1177/2048004016633371.
  • Subak, L L et al, “Obesity and Urinary Incontinence: Epidemiology and Clinical Research Update” J Urol. 2009 Dec; 182(6 Suppl): S2–S7 doi: 10.1016/j.juro.2009.08.071
  • Romero-Corral, A et al, “Interactions Between Obesity and Obstructive Sleep Apnea - Implications for Treatment” Chest. 2010 Mar; 137(3): 711–719. doi: 10.1378/chest.09-0360
  • Herrington, W G et al, “Body-mass index and risk of advanced chronic kidney disease: Prospective analyses from a primary care cohort of 1.4 million adults in England,” PLoS One, vol. 12, no. 3, p. e0173515, Mar. 2017, [Online]. Available: https://doi.org/10.1371/journal.pone.0173515.
  • Bhaskaran, K et al, “Body-mass index and risk of 22 specific cancers: a population-based cohort study of 5.24 million UK adults,” Lancet, vol. 384, no. 9945, pp. 755–765, Aug. 2014, doi: 10.1016/S0140-6736(14)60892-8.
  • Zheng, H et al, “Body mass index and risk of knee osteoarthritis: Systematic review and meta-analysis of prospective studies,” BMJ Open, vol. 5, no. 12, 2015, doi: 10.1136/bmjopen-2014-007568.
  • Su, Y P et al, “Strong association between metabolically-abnormal obesity and gallstone disease in adults under 50 years” BMC Gastroenterol 19, 117 (2019). https://doi.org/10.1186/s12876-019-1032-y
  • Yang, G et al, “The effects of obesity on venous thromboembolism: A review” Open J Prev Med. 2012 Nov; 2(4): 499–509. doi: 10.4236/ojpm.2012.24069
  • Bai, L et al, “Incident gout and weight change patterns: a retrospective cohort study of US adults” Arthritis Res Ther. 2021; 23: 69. Published online 2021 Mar 2. doi: 10.1186/s13075-021-02461-7
  • Klatsky, A L et al, “Body Mass Index and Mortality in a Very Large Cohort: Is It Really Healthier to Be Overweight?,” Perm. J., vol. 21, pp. 16–142, 2017, doi: 10.7812/TPP/16-142.
  • Heymsfield, S B et al, “Why are there race/ethnic differences in adult body mass index-adiposity relationships? A quantitative critical review,” Obes. Rev., vol. 17, no. 3, pp. 262–275, Mar. 2016, doi: 10.1111/obr.12358.
  • “Ethnic Differences in BMI and Disease Risk | Obesity Prevention Source | Harvard T.H. Chan School of Public Health.” [Online]. Available: https://www.hsph.harvard.edu/obesity-prevention-source/ethnic-differences-in-bmi-and-disease-risk/
  • Cossrow, N et al, “Race/Ethnic Issues in Obesity and Obesity-Related Comorbidities,” J. Clin. Endocrinol. Metab., vol. 89, no. 6, pp. 2590–2594, Jun. 2004, doi: 10.1210/jc.2004-0339.
  • “Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies – Public Health – WHO international” Available: https://www.who.int/nutrition/publications/bmi_asia_strategies.pdf
  • Deurenberg-Yap, M et al, “The paradox of low body mass index and high body fat percentage among Chinese, Malays and Indians in Singapore.” Int J Obes Relat Metab Disord. 2000 Aug;24(8):1011-7. doi: 10.1038/sj.ijo.0801353. PMID: 10951540.
  • Valentino, G et al, “Body fat and its relationship with clustering of cardiovascular risk factors” Nutr Hosp. 2015;31(5):2253-2260 ISSN 0212-1611 • CODEN NUHOEQ S.V.R. 318
  • Lear, S A et al, “Ethnic Variation in Fat and Lean Body Mass and the Association with INS Resistance” The Journal of Clinical Endocrinology & Metabolism, Volume 94, Issue 12, 1 December 2009, Pages 4696–4702, https://doi.org/10.1210/jc.2009-1030
  • Tillin, T et al, “The relationship between metabolic risk factors and incident cardiovascular disease in Europeans, South Asians, and African Caribbeans: SABRE (Southall and Brent Revisited) -- a prospective population-based study,” J. Am. Coll. Cardiol., vol. 61, no. 17, pp. 1777–1786, Apr. 2013, doi: 10.1016/j.jacc.2012.12.046.
  • Tanne, D et al, “Body Fat Distribution and Long-Term Risk of Stroke Mortality” Stroke. Originally published 31 Mar 2005 https://doi.org/10.1161/01.STR.0000162584.39366.1c
  • Chen, Y et al, “Association between body mass index and cardiovascular disease mortality in east Asians and south Asians: pooled analysis of prospective data from the Asia Cohort Consortium,” BMJ  Br. Med. J., vol. 347, p. f5446, Oct. 2013, doi: 10.1136/bmj.f5446.
  • Wen, C P et al, “Are Asians at greater mortality risks for being overweight than Caucasians? Redefining obesity for Asians” Public Health Nutrition, 12(4), 497-506. doi:10.1017/S1368980008002802
  • J. S. for the S. of O. The Examination Committee of Criteria for `Obesity Disease’ in Japan, “New Criteria for `Obesity Disease’ in Japan,” Circ. J., vol. 66, no. 11, pp. 987–992, 2002, doi: 10.1253/circj.66.987.
  • Zheng, W et al, “Association between Body-Mass Index and Risk of Death in More Than 1 Million Asians,” N. Engl. J. Med., vol. 364, no. 8, pp. 719–729, Feb. 2011, doi: 10.1056/NEJMoa1010679.
  • Aekplakorn, W et al, “Obesity indices and cardiovascular risk factors in Thai adults.” Int J Obes 30, 1782–1790 (2006). https://doi.org/10.1038/sj.ijo.0803346
  • Choi, S E et al, “Do Risk Factors Explain the Increased Prevalence of Type 2 Diabetes Among California Asian Adults?” J Immigr Minor Health. 2011; 13(5): 803–808. Published online 2010 Oct 9. doi: 10.1007/s10903-010-9397-6
  • Swinburn, B et al, “Body size and composition in Polynesians” Int J Obes 23, 1178–1183 (1999). https://doi.org/10.1038/sj.ijo.0801053
  • Young, D R et al, “Associations of overweight/obesity and socioeconomic status with hypertension prevalence across racial and ethnic groups,” J. Clin. Hypertens., vol. 20, no. 3, pp. 532–540, Mar. 2018, doi: https://doi.org/10.1111/jch.13217.
  • Maskarinec, G et al, “Diabetes Prevalence and Body Mass Index Differ by Ethnicity: The Multiethnic Cohort” Ethn Dis. 2009; 19(1): 49–55. PMCID: PMC2702477
  • Aleman-Mateo, H et al, “Elderly Mexicans have less muscle and greater total and truncel fat compared to African-Americans and Caucasians with the same BMI” J Nutr Health Aging. 2009 Dec; 13(10): 919. doi: 10.1007/s12603-009-0252-1
  • Cossrow, N et al, “Race/Ethnic Issues in Obesity and Obesity-Related Comorbidities” The Journal of Clinical Endocrinology & Metabolism, Volume 89, Issue 6, 1 June 2004, Pages 2590–2594, https://doi.org/10.1210/jc.2004-0339
  • Berber, A et al, “Anthropometric indexes in the prediction of type 2 diabetes mellitus, hypertension and dyslipidaemia in a Mexican population,” Int. J. Obes., vol. 25, no. 12, pp. 1794–1799, 2001, doi: 10.1038/sj.ijo.0801827.
  • Chirinos, D A et al, “Defining Abdominal Obesity as a Risk Factor for Coronary Heart Disease in the U.S.: Results From the Hispanic Community Health Study/Study of Latinos (HCHS/SOL)” Diabetes Care Aug 2020, 43 (8) 1774-1780; DOI: 10.2337/dc19-1855
  • Elo, I T et al, “The Contribution of Weight Status to Black-White Differences in Mortality” Biodemography Soc Biol. 2017; 63(3): 206–220. doi: 10.1080/19485565.2017.1300519
  • “9 The evidence | BMI: preventing ill health and premature death in black, Asian and other minority ethnic groups | Guidance | NICE.” [Online]. Available: https://www.nice.org.uk/guidance/ph46/chapter/9-The-evidence.
  • Alammar, M et al, “Diagnostic Accuracy of Body Mass Index (BMI) When Diagnosing Obesity in a Saudi Adult Population in a Primary Care Setting, Cross Sectional, Retrospective Study” Diabetes Metab Syndr Obes. 2020; 13: 2515–2520. Published online 2020 Jul 14. doi: 10.2147/DMSO.S263063
  • Bennet, L et al, “BMI and waist circumference cut-offs for corresponding levels of INS sensitivity in a Middle Eastern immigrant versus a native Swedish population – the MEDIM population based study” BMC Public Health. 2016; 16: 1242. Published online 2016 Dec 9. doi: 10.1186/s12889-016-3892-1
  • Al-Raddadi, R et al, “The prevalence of obesity and overweight, associated demographic and lifestyle factors, and health status in the adult population of Jeddah, Saudi Arabia,” Ther. Adv. Chronic Dis., vol. 10, p. 2040622319878997, Jan. 2019, doi: 10.1177/2040622319878997.
  • Abell, J E et al, “Differences in Cardiovascular Disease Mortality Associated With Body Mass Between Black and White Persons,” Am. J. Public Health, vol. 98, no. 1, pp. 63–66, Jan. 2008, doi: 10.2105/AJPH.2006.093781.
  • Batsis, J A et al, “Diagnostic Accuracy of Body Mass Index to Identify Obesity in Older Adults: NHANES 1999–2004” Int J Obes (Lond). 2016 May; 40(5): 761–767. Published online 2015 Dec 1. doi: 10.1038/ijo.2015.243
  • Michigan State University. "BMI Not Accurate Indicator Of Body Fat, New Research Suggests." ScienceDaily. ScienceDaily, 7 March 2007. Available: www.sciencedaily.com/releases/2007/03/070305202535.htm
  • Sperrin, M et al, “Body mass index relates weight to height differently in women and older adults: serial cross-sectional surveys in England (1992-2011)” J. Public Health (Oxf)., vol. 38, no. 3, pp. 607–613, Sep. 2016, doi: 10.1093/pubmed/fdv067.
  • Weir CB, et al, “BMI Classification Percentile And Cut Off Points.” In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2021 Jan
  • “What Is My Ideal Body Fat Percentage? - Healthline” [Online] Available: https://www.healthline.com/health/exercise-fitness/ideal-body-fat-percentage
  • Nuttall, F Q. “Body Mass Index: Obesity, BMI, and Health: A Critical Review” Nutr Today. 2015 May; 50(3): 117–128. Published online 2015 Apr 7. doi: 10.1097/NT.0000000000000092
  • Karastergiou, K et al, “Sex differences in human adipose tissues – the biology of pear shape,” Biol. Sex Differ., vol. 3, no. 1, p. 13, 2012, doi: 10.1186/2042-6410-3-13.
  • Nauli, A M et al, “Why Do Men Accumulate Abdominal Visceral Fat?” Front. Physiol., vol. 10, p. 1486, Dec. 2019, doi: 10.3389/fphys.2019.01486.
  • Thorpe Jr., R J et al, “Aging, Obesity, and Mortality: Misplaced Concern About Obese Older People?” Res Aging. 2004 Jan 1; 26(1): 108–129. doi: 10.1177/0164027503258738
  • Yanovski, J A “Pediatric obesity. An introduction” Appetite. 2015 Oct 1; 93: 3–12. Published online 2015 Mar 30. doi: 10.1016/j.appet.2015.03.028
  • “About Child & Teen BMI – Center for Disease Control and Prevention” Available: https://www.cdc.gov/healthyweight/assessing/bmi/childrens_bmi/about_childrens_bmi.html
  • Chung, S “Growth and Puberty in Obese Children and Implications of Body Composition” J Obes Metab Syndr. 2017 Dec; 26(4): 243–250. Published online 2017 Dec 30. doi: 10.7570/jomes.2017.26.4.243
  • St-Onge, M P et al, “Body composition changes with aging: The cause or the result of alterations in metabolic rate and macronutrient oxidation?” Nutrition. 2010 Feb; 26(2): 152–155. Published online 2009 Dec 8. doi: 10.1016/j.nut.2009.07.004
  • Studenski, S A et al, “The FNIH sarcopenia project: rationale, study description, conference recommendations, and final estimates,” J. Gerontol. A. Biol. Sci. Med. Sci., vol. 69, no. 5, pp. 547–558, May 2014, doi: 10.1093/gerona/glu010.
  • McKee, A et al, “Obesity in the Elderly” In: Endotext [Internet]. South Dartmouth (MA): MDText.com, Inc.; 2000.
  • Van Der Valk, E S et al, “A comprehensive diagnostic approach to detect underlying causes of obesity in adults” Obesity Reviews First published: 01 March 2019 https://doi.org/10.1111/obr.12836
  • Hetherington-Rauth, M et al, “Comparison of direct measures of adiposity with indirect measures for assessing cardiometabolic risk factors in preadolescent girls” Nutr J. 2017; 16: 15. Published online 2017 Feb 23. doi: 10.1186/s12937-017-0236-7
  • Janssen, I et al, “Waist circumference and not body mass index explains obesity-related health risk” The American Journal of Clinical Nutrition, Volume 79, Issue 3, March 2004, Pages 379–384, https://doi.org/10.1093/ajcn/79.3.379
  • Robert Ross et al, “Waist circumference as a vital sign in clinical practice: a Consensus Statement from the IAS and ICCR Working Group on Visceral Obesity” Nat Rev Endocrinol. 2020; 16(3): 177–189. Published online 2020 Feb 4. doi: 10.1038/s41574-019-0310-7
  • “Why is my waist size important? - NHS.” [Online]. Available: https://www.nhs.uk/common-health-questions/lifestyle/why-is-my-waist-size-important/.
  • “Metabolic syndrome - Symptoms and causes - Mayo Clinic.” [Online]. Available: https://www.mayoclinic.org/diseases-conditions/metabolic-syndrome/symptoms-causes/syc-20351916
  • “Metabolic Syndrome – Cedars Sinai” [Online]. Available: https://www.cedars-sinai.org/health-library/diseases-and-conditions/m/metabolic-syndrome.html
  • “Metabolic Syndrome | NHLBI, NIH.” [Online]. Available: https://www.nhlbi.nih.gov/health-topics/metabolic-syndrome
  • “HDL cholesterol: How to boost your ‘good’ cholesterol - Mayo Clinic.” [Online]. Available: https://www.mayoclinic.org/diseases-conditions/high-blood-cholesterol/in-depth/hdl-cholesterol/art-20046388.
  • Yanai, H et al, “The underlying mechanisms for development of hypertension in the metabolic syndrome” Nutr J. 2008; 7: 10. Published online 2008 Apr 17. doi: 10.1186/1475-2891-7-10
  • “What is Cardiovascular Disease? | American Heart Association.” [Online]. Available: https://www.heart.org/en/health-topics/consumer-healthcare/what-is-cardiovascular-disease
  • “Type 2 Diabetes - Symptoms | ADA.” [Online]. Available: https://www.diabetes.org/diabetes/type-2/symptoms.
  • Arenillas, J F et al, “The Metabolic Syndrome and Stroke - Potential Treatment Approaches” Stroke Originally published 31 May 2007 https://doi.org/10.1161/STROKEAHA.106.480004
  • Lin, H et al, “The prevalence, metabolic risk and effects of lifestyle intervention for metabolically healthy obesity: a systematic review and meta-analysis: A PRISMA-compliant article” Medicine (Baltimore). 2017 Nov; 96(47): e8838. Published online 2017 Nov 27. doi: 10.1097/MD.0000000000008838
  • Hinnouho, G M et al, “Metabolically healthy obesity and risk of mortality: does the definition of metabolic health matter?,” Diabetes Care, vol. 36, no. 8, pp. 2294–2300, Aug. 2013, doi: 10.2337/dc12-1654.
  • Eknoyan, G. “Adolphe Quetelet (1796–1874) — the average man and indices of obesity” Nephrology Dialysis Transplantation, Volume 23, Issue 1, January 2008, Pages 47–51, https://doi.org/10.1093/ndt/gfm517
  • Abou Ziki, M D et al, “Metabolic Syndrome: Genetic Insights into Disease Pathogenesis” Curr Opin Lipidol. 2016 Apr; 27(2): 162–171. doi: 10.1097/MOL.0000000000000276
  • Kolb, H et al, “Environmental/lifestyle factors in the pathogenesis and prevention of type 2 diabetes.” BMC Med 15, 131 (2017). https://doi.org/10.1186/s12916-017-0901-x
  • Jensen, M D “Role of Body Fat Distribution and the Metabolic Complications of Obesity” J Clin Endocrinol Metab. 2008 Nov; 93(11 Suppl 1): S57–S63. doi: 10.1210/jc.2008-1585
  • Wildman, R P et al, “The Obese Without Cardiometabolic Risk Factor Clustering and the Normal Weight With Cardiometabolic Risk Factor Clustering: Prevalence and Correlates of 2 Phenotypes Among the US Population (NHANES 1999-2004),” Arch. Intern. Med., vol. 168, no. 15, pp. 1617–1624, Aug. 2008, doi: 10.1001/archinte.168.15.1617.
  • Bhaskaran, K et al, “Association of BMI with overall and cause-specific mortality: a population-based cohort study of 3.6 million adults in the UK” Lancet Diabetes Endocrinol. 2018 Dec; 6(12): 944–953. doi: 10.1016/S2213-8587(18)30288-2

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