Waist-to-height ratio

Last updated

A person's waist-to-height ratio (WHtR), occasionally written WtHR or called waist-to-stature ratio (WSR), is defined as their waist circumference divided by their height, both measured in the same units. It is used as a predictor of obesity-related cardiovascular disease. The WHtR is a measure of the distribution of body fat. Higher values of WHtR indicate higher risk of obesity-related cardiovascular diseases; it is correlated with abdominal obesity. [1]

Contents

More than twenty-five years ago, waist-to-height ratio (WHtR) was first suggested as a simple health risk assessment tool because it is a proxy for harmful central adiposity [2] and a boundary value of 0.5 was proposed to indicate increased risk. [3] [4] A WHtR of over 0.5 is critical and signifies an increased risk; a 2010 systematic review of published studies concluded that "WHtR may be advantageous because it avoids the need for age-, sex- and ethnic-specific boundary values". [5] In April 2022, the UK's National Institute for Health and Care Excellence (a government body) proposed new guidelines which suggested that all adults "ensure their waist size is less than half their height in order to help stave off serious health problems". [6] In September 2022, NICE formally adopted this guideline. [7]

According to World Health Organization guidance, the waist circumference is usually measured midway between the lower rib and the iliac crest. [8]

Guidelines

United Kingdom

In April 2022, the UK's National Institute for Health and Care Excellence (a government body) proposed new guidelines which suggested that all adults "ensure their waist size is less than half their height in order to help stave off serious health problems". [9] In September 2022, NICE formally adopted this guideline. [10]

Suggested boundary values

The October 2022 NICE guidelines have suggested boundary values for WHtR (defining the degree of central adiposity) as follows:

  • healthy central adiposity: waist-to-height ratio 0.4 to 0.49, indicating no increased health risks
  • increased central adiposity: waist-to-height ratio 0.5 to 0.59, indicating increased health risks
  • high central adiposity: waist-to-height ratio 0.6 or more, indicating further increased health risks.

NICE say that these classifications can be used for people with a body mass index (BMI) of under 35, for both sexes and all ethnicities, including adults with high muscle mass. The health risks associated with higher levels of central adiposity include type 2 diabetes, hypertension and cardiovascular disease. NICE have proposed the same boundary values for children of 5 years and over. [11]

Boundary values were first suggested for WHtR in 1996 to reflect health implications and were portrayed on a simple chart of waist circumference against height. The boundary value of WHtR = 0.4 was suggested to indicate the start of the 'OK' range. The 0.5 boundary value was suggested to indicate the start of the 'Take Care' range, with the 0.6 boundary value indicated the start of the 'Take Action' range. [12]

Simplified guidelines

The first boundary value for increased risk of WHtR 0.5 translates into the simple message "Keep your waist to less than half your height". [13] [14] The updated NICE guideline says "When talking to a person about their waist-to-height ratio, explain that they should try and keep their waist to half their height (so a waist-to height ratio of under 0.5)". [10]

Age-adjusted boundary values

A 2013 study identified critical threshold values according to age, with consequent significant reduction in life expectancy if exceeded. These are: WHtR greater than 0.5 for people under 40 years of age, 0.5 to 0.6 for people aged 40–50, and greater than 0.6 for people over 50 years of age. [15]

Public health tool

WHtR is a proxy for central (visceral or abdominal) adiposity: values of WHtR are significantly correlated with direct measures of central (visceral or abdominal) adiposity using techniques such as CT, MRI or DEXA. [4] [16] [17] [18]

WHtR is an indicator of 'early health risk': several systematic reviews and meta-analyses of data in adults of all ages, [19] [20] [21] [22] as well as in children and adolescents, [23] [24] have supported the superiority of WHtR over the use of BMI and waist circumference in predicting early health risk.

Cross-sectional studies in many different global populations have supported the premise that WHtR is a simple and effective anthropometric index to identify health risks in adults of all ages [20] [21] [25] [26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] and in children and adolescents. [37] [38] [39] [40] [41] [42]

In a comprehensive narrative review, Yoo concluded that "additional use of WHtR with BMI or WC may be helpful because WHtR considers both height and central obesity. WHtR may be preferred because of its simplicity and because it does not require sex- and age-dependent cut-offs". [43]

As an indicator of mortality

Not only does WHtR have a close relationship with morbidity, it also has a clearer relationship with mortality than BMI. [44] [45] [46]

As an indicator of central adiposity

Many cross- sectional studies have shown that, even within the normal BMI range, many adults have WHtR which is above 0.5. [47] [48] [36] Many children show the same phenomenon. [49] [50] Risk factors for metabolic diseases [48] [51] and mortality are raised in these subjects. [52] [53] [54]

See also

Related Research Articles

<span class="mw-page-title-main">Body mass index</span> Relative weight based on mass and height

Body mass index (BMI) is a value derived from the mass (weight) and height of a person. The BMI is defined as the body mass divided by the square of the body height, and is expressed in units of kg/m2, resulting from mass in kilograms (kg) and height in metres (m).

<span class="mw-page-title-main">Metabolic syndrome</span> Medical condition

Metabolic syndrome is a clustering of at least three of the following five medical conditions: abdominal obesity, high blood pressure, high blood sugar, high serum triglycerides, and low serum high-density lipoprotein (HDL).

<span class="mw-page-title-main">Abdominal obesity</span> Excess fat around the stomach and abdomen

Abdominal obesity, also known as central obesity and truncal obesity, is the human condition of an excessive concentration of visceral fat around the stomach and abdomen to such an extent that it is likely to harm its bearer's health. Abdominal obesity has been strongly linked to cardiovascular disease, Alzheimer's disease, and other metabolic and vascular diseases.

<span class="mw-page-title-main">Obesity</span> Medical condition in which excess body fat harms health

Obesity is a medical condition, sometimes considered a disease, in which excess body fat has accumulated to such an extent that it can potentially have negative effects on health. People are classified as obese when their body mass index (BMI)—a person's weight divided by the square of the person's height—is over 30 kg/m2; the range 25–30 kg/m2 is defined as overweight. Some East Asian countries use lower values to calculate obesity. Obesity is a major cause of disability and is correlated with various diseases and conditions, particularly cardiovascular diseases, type 2 diabetes, obstructive sleep apnea, certain types of cancer, and osteoarthritis.

<span class="mw-page-title-main">Waist</span> Part of the abdomen between the rib cage and hips

The waist is the part of the abdomen between the rib cage and hips. Normally, the waist is the narrowest part of the torso.

<span class="mw-page-title-main">Waist–hip ratio</span>

The waist–hip ratio or waist-to-hip ratio (WHR) is the dimensionless ratio of the circumference of the waist to that of the hips. This is calculated as waist measurement divided by hip measurement. For example, a person with a 75 cm waist and 95 cm hips has WHR of about 0.79.

Sagittal abdominal diameter (SAD) is a measure of visceral obesity, the amount of fat in the gut region. SAD is the distance from the small of the back to the upper abdomen. SAD may be measured when standing or supine. SAD may be measured at any point from the narrowest point between the last rib and the iliac crests to the midpoint of the iliac crests.

Bariatric surgery is a medical term for surgical procedures used to manage obesity and obesity-related conditions. Long term weight loss with bariatric surgery may be achieved through alteration of gut hormones, physical reduction of stomach size, reduction of nutrient absorption, or a combination of these. Standard of care procedures include Roux en-Y bypass, sleeve gastrectomy, and biliopancreatic diversion with duodenal switch, from which weight loss is largely achieved by altering gut hormone levels responsible for hunger and satiety, leading to a new hormonal weight set point.

The obesity paradox is the finding in some studies of a lower mortality rate for overweight or obese people within certain subpopulations. The paradox has been observed in people with cardiovascular disease and cancer. Explanations for the paradox range from excess weight being protective to the statistical association being caused by methodological flaws such as confounding, detection bias, reverse causality, or selection bias.

<span class="mw-page-title-main">Classification of obesity</span> Overview of the classification of the condition of obesity

Obesity classification is a ranking of obesity, the medical condition in which excess body fat has accumulated to the extent that it has an adverse effect on health. The World Health Organization (WHO) classifies obesity by body mass index (BMI). BMI is further evaluated in terms of fat distribution via the waist–hip ratio and total cardiovascular risk factors. In children, a healthy weight varies with age and sex, and obesity determination is in relation to a historical normal group.

<span class="mw-page-title-main">Android fat distribution</span> Distribution of human adipose tissue mainly around the trunk and upper body

Android fat distribution describes the distribution of human adipose tissue mainly around the trunk and upper body, in areas such as the abdomen, chest, shoulder and nape of the neck. This pattern may lead to an "apple”-shaped body or central obesity, and is more common in males than in females. Thus, the android fat distribution of men is about 48.6%, which is 10.3% higher than that of premenopausal women. In other cases, an ovoid shape forms, which does not differentiate between men and women. Generally, during early adulthood, females tend to have a more peripheral fat distribution such that their fat is evenly distributed over their body. However, it has been found that as females age, bear children and approach menopause, this distribution shifts towards the android pattern of fat distribution, resulting in a 42.1% increase in android body fat distribution in postmenopausal women. This could potentially provide evolutionary advantages such as lowering a woman's center of gravity making her more stable when carrying offspring.

The body adiposity index (BAI) is a method of estimating the amount of body fat in humans. The BAI is calculated without using body weight, unlike the body mass index (BMI). Instead, it uses the size of the hips compared to the person's height.

A number of lifestyle factors are known to be important to the development of type 2 diabetes including: obesity, physical activity, diet, stress, and urbanization. Excess body fat underlies 64% of cases of diabetes in men and 77% of cases in women. A number of dietary factors such as sugar sweetened drinks and the type of fat in the diet appear to play a role.

<span class="mw-page-title-main">TOFI</span> Individual with disproportionate amount of fat

TOFI (thin-outside-fat-inside) is used to describe lean individuals with a disproportionate amount of fat stored in their abdomen. The figure to illustrate this shows two men, both 35 years old, with a BMI of 25 kg/m2. Despite their similar size, the TOFI had 5.86 litres of internal fat, whilst the healthy control had only 1.65 litres.

This article provides a global overview of the current trends and distribution of metabolic syndrome. Metabolic syndrome refers to a cluster of related risk factors for cardiovascular disease that includes abdominal obesity, diabetes, hypertension, and elevated cholesterol.

<span class="mw-page-title-main">Body shape index</span> Human health index

A Body Shape Index (ABSI) or simply body shape index (BSI) is a metric for assessing the health implications of a given human body height, mass and waist circumference (WC). The inclusion of WC is believed to make the BSI a better indicator of risk of mortality from excess weight than the standard body mass index. ABSI correlates only slightly with height, weight and BMI, indicating that it is independent of other anthropometric variables in predicting mortality.

Metabolically healthy obesity (MHO) is a disputed medical condition characterized by obesity which does not produce metabolic complications.

Normal weight obesity is the condition of having normal body weight, but with a high body fat percentage, leading to some of the same health risks as obesity.

Relative Fat Mass (RFM) is a simple formula for the estimation of overweight or obesity in humans that requires only a calculation based on a ratio of height and waist measurements.

The benefits of physical activity range widely. Most types of physical activity improve health and well-being.

References

  1. Lee CM, Huxley RR, Wildman RP, Woodward M (July 2008). "Indices of abdominal obesity are better discriminators of cardiovascular risk factors than BMI: a meta-analysis". Journal of Clinical Epidemiology. 61 (7): 646–653. doi: 10.1016/j.jclinepi.2007.08.012 . PMID   18359190.
  2. Vague J (1956). "The degree of masculine differentiation of obesities: a factor determining predisposition to diabetes, atherosclerosis, gout, and uric calculous disease". primary. The American Journal of Clinical Nutrition. 4 (1): 20–34. doi: 10.1093/ajcn/4.1.20 . PMID   13282851.
  3. Hsieh SD, Yoshinaga H (December 1995). "Waist/height ratio as a simple and useful predictor of coronary heart disease risk factors in women". primary. Internal Medicine. 34 (12): 1147–1152. doi: 10.2169/internalmedicine.34.1147 . PMID   8929639.
  4. 1 2 Ashwell M, Lejeune S, McPherson K (February 1996). "Ratio of waist circumference to height may be better indicator of need for weight management". primary. BMJ. 312 (7027): 377. doi:10.1136/bmj.312.7027.377. PMC   2350287 . PMID   8611847.
  5. Browning LM, Hsieh SD, Ashwell M (December 2010). "A systematic review of waist-to-height ratio as a screening tool for the prediction of cardiovascular disease and diabetes: 0·5 could be a suitable global boundary value". Nutrition Research Reviews. 23 (2): 247–269. doi: 10.1017/S0954422410000144 . PMID   20819243.
  6. Gregory A (8 April 2022). "Ensure waist size is less than half your height, health watchdog says". The Guardian . Retrieved 8 April 2022.
  7. "Obesity: identification, assessment and management | Clinical guideline [CG189]". National Institute for Health and Care Excellence. 8 September 2022. Recommendations 1.2.11 and 1.2.12
  8. Waist circumference and waist-hip ratio: report of a WHO expert consultation 2008 (Report). Geneva: World Health Organization. 2011.
  9. "Obesity: identification and classification of overweight and obesity (update)". National Institute for Health and Care Excellence (NICE). 2022.
  10. 1 2 "Obesity: identification and classification of overweight and obesity (update) | Recommendations 1.2.11 and 1.2.12". National Institute for Health and Care Excellence (NICE). 2022.
  11. "Obesity: identification and classification of overweight and obesity (update) Recommendations 1.2.25 and 1.2.26". National Institute for Health and Care Excellence (NICE). 2022.
  12. Antwi F, Fazylova N, Garcon MC, Lopez L, Rubiano R, Slyer JT (2012). "The effectiveness of web-based programs on the reduction of childhood obesity in school-aged children: A systematic review". secondary. JBI Library of Systematic Reviews. 10 (42 Suppl): 1–14. doi:10.11124/jbisrir-2012-248. PMID   27820152.
  13. Ashwell M, Hsieh SD (August 2005). "Six reasons why the waist-to-height ratio is a rapid and effective global indicator for health risks of obesity and how its use could simplify the international public health message on obesity". primary. International Journal of Food Sciences and Nutrition. 56 (5): 303–307. doi:10.1080/09637480500195066. PMID   16236591. S2CID   24420745.
  14. McCarthy HD, Ashwell M (June 2006). "A study of central fatness using waist-to-height ratios in UK children and adolescents over two decades supports the simple message--'keep your waist circumference to less than half your height'". primary. International Journal of Obesity. 30 (6): 988–992. doi:10.1038/sj.ijo.0803226. PMID   16432546. S2CID   26576960.
  15. HospiMedica International staff writers (18 Jun 2013). "Waist-Height Ratio Better Than BMI for Gauging Mortality". Archived from the original on 17 April 2016. Retrieved 7 April 2016.
  16. Roriz AK, Passos LC, de Oliveira CC, Eickemberg M, Moreira P, Sampaio LR (2014). "Evaluation of the accuracy of anthropometric clinical indicators of visceral fat in adults and elderly". primary. PLOS ONE. 9 (7): e103499. Bibcode:2014PLoSO...9j3499R. doi: 10.1371/journal.pone.0103499 . PMC   4117503 . PMID   25078454.
  17. Martin-Calvo N, Moreno-Galarraga L, Martinez-Gonzalez MA (August 2016). "Association between Body Mass Index, Waist-to-Height Ratio and Adiposity in Children: A Systematic Review and Meta-Analysis". secondary. Nutrients. 8 (8): E512. doi: 10.3390/nu8080512 . PMC   4997425 . PMID   27556485.
  18. Swainson MG, Batterham AM, Tsakirides C, Rutherford ZH, Hind K (2017). "Prediction of whole-body fat percentage and visceral adipose tissue mass from five anthropometric variables". primary. PLOS ONE. 12 (5): e0177175. Bibcode:2017PLoSO..1277175S. doi: 10.1371/journal.pone.0177175 . PMC   5426673 . PMID   28493988.
  19. Lee CM, Huxley RR, Wildman RP, Woodward M (July 2008). "Indices of abdominal obesity are better discriminators of cardiovascular risk factors than BMI: a meta-analysis". secondary. Journal of Clinical Epidemiology. 61 (7): 646–653. doi: 10.1016/j.jclinepi.2007.08.012 . PMID   18359190.
  20. 1 2 Ashwell M, Gunn P, Gibson S (March 2012). "Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: systematic review and meta-analysis". secondary. Obesity Reviews. 13 (3): 275–86. doi:10.1111/j.1467-789X.2011.00952.x. PMID   22106927. S2CID   7290185.
  21. 1 2 Savva SC, Lamnisos D, Kafatos AG (October 2013). "Predicting cardiometabolic risk: waist-to-height ratio or BMI. A meta-analysis". secondary. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy. 6: 403–19. doi: 10.2147/DMSO.S34220 . PMC   3810792 . PMID   24179379.
  22. Corrêa MM, Thumé E, De Oliveira ER, Tomasi E (2016). "Performance of the waist-to-height ratio in identifying obesity and predicting non-communicable diseases in the elderly population: A systematic literature review". secondary. Archives of Gerontology and Geriatrics. 65: 174–82. doi:10.1016/j.archger.2016.03.021. PMID   27061665.
  23. Lo K, Wong M, Khalechelvam P, Tam W (December 2016). "Waist-to-height ratio, body mass index and waist circumference for screening paediatric cardio-metabolic risk factors: a meta-analysis". secondary. Obesity Reviews. 17 (12): 1258–1275. doi:10.1111/obr.12456. PMID   27452904. S2CID   3597681.
  24. Ochoa Sangrador C, Ochoa-Brezmes J (July 2018). "Waist-to-height ratio as a risk marker for metabolic syndrome in childhood. A meta-analysis". secondary. Pediatric Obesity. 13 (7): 421–432. doi:10.1111/ijpo.12285. PMID   29700992. S2CID   13795818.
  25. Park SH, Choi SJ, Lee KS, Park HY (September 2009). "Waist circumference and waist-to-height ratio as predictors of cardiovascular disease risk in Korean adults". primary. Circulation Journal. 73 (9): 1643–1650. doi: 10.1253/circj.cj-09-0161 . PMID   19638708. S2CID   23639450.
  26. Khoury M, Manlhiot C, McCrindle BW (August 2013). "Role of the waist/height ratio in the cardiometabolic risk assessment of children classified by body mass index". primary. Journal of the American College of Cardiology. 62 (8): 742–751. doi: 10.1016/j.jacc.2013.01.026 . PMID   23500256. S2CID   25857523.
  27. Jayawardana R, Ranasinghe P, Sheriff MH, Matthews DR, Katulanda P (March 2013). "Waist to height ratio: a better anthropometric marker of diabetes and cardio-metabolic risks in South Asian adults". primary. Diabetes Research and Clinical Practice. 99 (3): 292–299. doi:10.1016/j.diabres.2012.12.013. PMID   23298662.
  28. Rodea-Montero ER, Evia-Viscarra ML, Apolinar-Jiménez E (2014). "Waist-to-Height Ratio Is a Better Anthropometric Index than Waist Circumference and BMI in Predicting Metabolic Syndrome among Obese Mexican Adolescents". primary. International Journal of Endocrinology. 2014: 195407. doi: 10.1155/2014/195407 . PMC   4276350 . PMID   25574166.
  29. Liu XL, Yin FZ, Ma CP, Gao GQ, Ma CM, Wang R, Lu Q (September 2015). "Waist-to-height ratio as a screening measure for identifying adolescents with hypertriglyceridemic waist phenotype". primary. Journal of Pediatric Endocrinology & Metabolism. 28 (9–10): 1079–1083. doi:10.1515/jpem-2015-0043. PMID   25901712. S2CID   24226966.
  30. Kazlauskaite R, Avery-Mamer EF, Li H, Chataut CP, Janssen I, Powell LH, Kravitz HM (January 2017). "Race/ethnic comparisons of waist-to-height ratio for cardiometabolic screening: The study of women's health across the nation". primary. American Journal of Human Biology. 29 (1): e22909. doi:10.1002/ajhb.22909. PMC   5426803 . PMID   27801534.
  31. Rådholm K, Chalmers J, Ohkuma T, Peters S, Poulter N, Hamet P, et al. (August 2018). "Use of the waist-to-height ratio to predict cardiovascular risk in patients with diabetes: Results from the ADVANCE-ON study". primary. Diabetes, Obesity & Metabolism. 20 (8): 1903–1910. doi:10.1111/dom.13311. hdl: 11343/283783 . PMID   29603537. S2CID   4508840.
  32. Song P, Li X, Bu Y, Ding S, Zhai D, Wang E, Yu Z (April 2019). "Temporal trends in normal weight central obesity and its associations with cardiometabolic risk among Chinese adults". primary. Scientific Reports. 9 (1): 5411. Bibcode:2019NatSR...9.5411S. doi:10.1038/s41598-019-41986-5. PMC   6443661 . PMID   30931996.
  33. Hou X, Chen S, Hu G, Chen P, Wu J, Ma X, et al. (January 2019). "Stronger associations of waist circumference and waist-to-height ratio with diabetes than BMI in Chinese adults". primary. Diabetes Research and Clinical Practice. 147: 9–18. doi:10.1016/j.diabres.2018.07.029. PMID   30144478. S2CID   207117199.
  34. Dong J, Wang SS, Chu X, Zhao J, Liang YZ, Yang YB, Yan YX (April 2019). "Optimal Cut-off Point of Waist to Height Ratio in Beijing and Its Association with Clusters of Metabolic Risk Factors". primary. Current Medical Science. 39 (2): 330–336. doi:10.1007/s11596-019-2039-x. PMID   31016530. S2CID   128359229.
  35. Kawamoto R, Kikuchi A, Akase T, Ninomiya D, Kumagi T (2019). "Usefulness of waist-to-height ratio in screening incident metabolic syndrome among Japanese community-dwelling elderly individuals". primary. PLOS ONE. 14 (4): e0216069. Bibcode:2019PLoSO..1416069K. doi: 10.1371/journal.pone.0216069 . PMC   6488078 . PMID   31034487.
  36. 1 2 Gibson S, Ashwell M (March 2020). "A simple cut-off for waist-to-height ratio (0·5) can act as an indicator for cardiometabolic risk: recent data from adults in the Health Survey for England". primary. The British Journal of Nutrition. 123 (6): 681–690. doi:10.1017/S0007114519003301. PMID   31840619. S2CID   209386183.
  37. Choi DH, Hur YI, Kang JH, Kim K, Cho YG, Hong SM, Cho EB (March 2017). "Usefulness of the Waist Circumference-to-Height Ratio in Screening for Obesity and Metabolic Syndrome among Korean Children and Adolescents: Korea National Health and Nutrition Examination Survey, 2010-2014". primary. Nutrients. 9 (3): 256. doi: 10.3390/nu9030256 . PMC   5372919 . PMID   28287410.
  38. Jiang Y, Dou YL, Xiong F, Zhang L, Zhu GH, Wu T, et al. (March 2018). "Waist-to-height ratio remains an accurate and practical way of identifying cardiometabolic risks in children and adolescents". primary. Acta Paediatrica. 107 (9): 1629–1634. doi:10.1111/apa.14323. PMID   29569350. S2CID   4206581.
  39. Alvim RO, Zaniqueli D, Neves FS, Pani VO, Martins CR, Peçanha MA, et al. (2019). "Waist-to-height ratio is as reliable as biochemical markers to discriminate pediatric insulin resistance". primary. Jornal de Pediatria. 95 (4): 428–434. doi: 10.1016/j.jped.2018.04.004 . PMID   29746812. S2CID   13682700.
  40. Ejtahed HS, Kelishadi R, Qorbani M, Motlagh ME, Hasani-Ranjbar S, Angoorani P, et al. (August 2019). "Utility of waist circumference-to-height ratio as a screening tool for generalized and central obesity among Iranian children and adolescents: The CASPIAN-V study". primary. Pediatric Diabetes. 20 (5): 530–537. doi: 10.1111/pedi.12855 . PMID   30968521. S2CID   106410872.
  41. Wariri O, Jalo I, Bode-Thomas F (2018). "Discriminative ability of adiposity measures for elevated blood pressure among adolescents in a resource-constrained setting in northeast Nigeria: a cross-sectional analysis". primary. BMC Obesity. 5: 35. doi: 10.1186/s40608-018-0211-7 . PMC   6276203 . PMID   30524740.
  42. Tee JY, Gan WY, Lim PY (January 2020). "Comparisons of body mass index, waist circumference, waist-to-height ratio and a body shape index (ABSI) in predicting high blood pressure among Malaysian adolescents: a cross-sectional study". primary. BMJ Open. 10 (1): e032874. doi:10.1136/bmjopen-2019-032874. PMC   7044891 . PMID   31932391.
  43. Yoo EG (November 2016). "Waist-to-height ratio as a screening tool for obesity and cardiometabolic risk". secondary. Korean Journal of Pediatrics. 59 (11): 425–431. doi:10.3345/kjp.2016.59.11.425. PMC   5118501 . PMID   27895689.
  44. Schneider HJ, Friedrich N, Klotsche J, Pieper L, Nauck M, John U, et al. (April 2010). "The predictive value of different measures of obesity for incident cardiovascular events and mortality". primary. The Journal of Clinical Endocrinology and Metabolism. 95 (4): 1777–1785. doi: 10.1210/jc.2009-1584 . PMID   20130075.
  45. Ashwell M, Mayhew L, Richardson J, Rickayzen B (2014). "Waist-to-height ratio is more predictive of years of life lost than body mass index". primary. PLOS ONE. 9 (9): e103483. Bibcode:2014PLoSO...9j3483A. doi: 10.1371/journal.pone.0103483 . PMC   4157748 . PMID   25198730.
  46. Jayedi A, Soltani S, Zargar MS, Khan TA, Shab-Bidar S (September 2020). "Central fatness and risk of all cause mortality: systematic review and dose-response meta-analysis of 72 prospective cohort studies". secondary. BMJ (Clinical Research Ed.). 370: m3324. doi:10.1136/bmj.m3324. PMC   7509947 . PMID   32967840.
  47. Šebeková K, Csongová M, Gurecká R, Krivošíková Z, Šebek J (May 2018). "Gender Differences in Cardiometabolic Risk Factors in Metabolically Healthy Normal Weight Adults with Central Obesity". primary. Experimental and Clinical Endocrinology & Diabetes. 126 (5): 309–315. doi:10.1055/s-0043-119877. PMID   29117621.
  48. 1 2 Ashwell M, Gibson S (2017). "Normal weight central obesity: the value of waist-to-height ratio in its identification. In response to Waist measurement, not BMI, is stronger predictor of death risk, study finds". secondary. BMJ. 357: j2033. doi:10.1136/bmj.j2033. S2CID   32653852.
  49. Mokha JS, Srinivasan SR, Dasmahapatra P, Fernandez C, Chen W, Xu J, Berenson GS (October 2010). "Utility of waist-to-height ratio in assessing the status of central obesity and related cardiometabolic risk profile among normal weight and overweight/obese children: the Bogalusa Heart Study". primary. BMC Pediatrics. 10: 73. doi: 10.1186/1471-2431-10-73 . PMC   2964659 . PMID   20937123.
  50. Srinivasan SR, Wang R, Chen W, Wei CY, Xu J, Berenson GS (September 2009). "Utility of waist-to-height ratio in detecting central obesity and related adverse cardiovascular risk profile among normal weight younger adults (from the Bogalusa Heart Study)". primary. The American Journal of Cardiology. 104 (5): 721–4. doi:10.1016/j.amjcard.2009.04.037. PMID   19699351.
  51. Liu PJ, Ma F, Lou HP, Zhu YN (April 2017). "Comparison of the ability to identify cardiometabolic risk factors between two new body indices and waist-to-height ratio among Chinese adults with normal BMI and waist circumference". primary. Public Health Nutrition. 20 (6): 984–991. doi: 10.1017/S1368980016003281 . PMC   10261557 . PMID   27989263. S2CID   3574565.
  52. Yu Y (August 2016). "Normal-Weight Central Obesity and Mortality Risk". Annals of Internal Medicine. 165 (4): 298. doi:10.7326/L16-0074. PMID   27538167. S2CID   26722676.
  53. Sharma S, Batsis JA, Coutinho T, Somers VK, Hodge DO, Carter RE, et al. (March 2016). "Normal-Weight Central Obesity and Mortality Risk in Older Adults With Coronary Artery Disease". primary. Mayo Clinic Proceedings. 91 (3): 343–351. doi:10.1016/j.mayocp.2015.12.007. PMID   26860580.
  54. Carter RE, Hodge DO, Lopez-Jimenez F (August 2016). "Normal-Weight Central Obesity and Mortality Risk". Annals of Internal Medicine. 165 (4): 298–299. doi:10.7326/L16-0073. PMID   27538166. S2CID   6941690.

Further reading