Anthropometric indicators of insulin resistance

Abstracts

Alguns estudos têm analisado a eficiência de indicadores antropométricos em predizer resistência à insulina (RI), por serem mais econômicos e acessíveis. Neste estudo, objetivou-se discutir sobre as medidas e índices antropométricos que têm sido associados à RI. Realizou-se um levantamento bibliográfico nas bases Scielo, Science Direct e Pubmed. Dentre os estudos analisados, perímetro da cintura e diâmetro abdominal sagital apresentaram melhor capacidade preditiva para RI, com resultados mais consistentes. As relações cintura/coxa, cintura/estatura, pescoço/coxa, o índice de conicidade e o índice sagital demonstraram resultados positivos, contudo mais estudos são necessários para consolidá-los como preditores de RI. Os resultados obtidos com o uso do índice de massa corporal e da relação cintura/quadril foram mais inconsistentes. Sugere-se a realização de estudos avaliando o desempenho desses indicadores em predizer RI na população brasileira, pois resultados de estudos feitos com outras populações muitas vezes não são aplicáveis à nossa, devido às diferenças étnicas resultantes da grande miscigenação no País.

Resistência à insulina; antropometria; obesidade; gordura intra-abdominal; circunferência abdominal

Algunos estudios han analizado la eficiencia de indicadores antropométricos para predecir resistencia a la insulina (RI), por ser más económicos y accesibles. En este estudio, se buscó discutir sobre las medidas e índices antropométricos que han sido asociados a la RI. Se realizó un levantamiento bibliográfico en las bases Scielo, Science Direct y Pubmed. Entre los estudios analizados, perímetro de la cintura y diámetro abdominal sagital presentaron mejor capacidad predictiva para RI, con resultados más consistentes. Las relaciones cintura/muslo, cintura/estatura, cuello/muslo, el índice de conicidad y el índice sagital demostraron resultados positivos, con todo son necesarios más estudios para consolidarlos como predictores de RI. Los resultados obtenidos con el uso del índice de masa corporal y de la relación cintura/cadera fueron más inconsistentes. Se sugiere la realización de estudios evaluando el desempeño de esos indicadores para predecir RI en la población brasileña, pues resultados de estudios hechos con otras poblaciones muchas veces no son aplicables a la nuestra, debido a las diferencias étnicas resultantes de la gran mezcla de razas en el País.

Resistencia a la insulina; antropometría; obesidad; grasa intra-abdominal; circunferencia abdominal

CLINICAL UPDATE

Anthropometric indicators of insulin resistance

Ana Carolina Vasques^I; Lina Rosado^I; Gilberto Rosado^I; Rita de Cassia Ribeiro^I; Sylvia Franceschini^I; Bruno Geloneze^II

^IUniversidade Federal de Viçosa (UFV), Viçosa, MG

^IIUniversidade Estadual de Campinas (UNICAMP), Campinas, SP - Brazil

Mailing address

ABSTRACT

Some studies have analyzed the efficacy of anthropometric indicators in predicting insulin resistance (IR), for they are more economic and accessible. In this study, the objective was to discuss the measures and anthropometric indices that have been associated with IR. A bibliographic review was done, based on Scielo, Science Direct and Pubmed. Among these studies, waist and sagittal abdominal diameter presented better predictive capacity for IR, with more consistent results. The waist-to-thigh, waist-to-size, neck-to-thigh ratios, the conicity and the sagittal index have showed positive results; nevertheless, more studies are necessary to consolidate them as predictors to IR. The obtained results, with the use of body mass index and of the waist-to-hip ratio, were inconsistent. In the Brazilian population, the realization of studies evaluating the performance of these indicators in predicting IR is suggested, since the results of the studies conducted in other populations are not always applicable to ours, due to ethnical differences resulting from the great miscegenation in the country.

Key words: Insulin resistance; anthropometry; obesity; intra-abdominal fat; abdominal circumference.

Introduction

Insulin resistance (IR) syndrome is one of the main risk factors for cardiovascular diseases, presenting high morbimortality and socioeconomic expenses. The IR, which is considered a link between the other physiological changes that compound the complex state of this syndrome, is associated with visceral obesity; arterial hypertension; intolerance to glucose and to type 2 diabetes; dyslipidaemia; hyperuricemia, and other metabolic changes^1-,3.

The evaluation of the IR has received considerable attention in the last few years. In Brazil, the determination of IR has not been in the routine medical exams yet, and is not available in most of the health services. The laboratorial methods for the determination of IR are expensive and with standardization deficiencies for its execution, limiting the comparison between different laboratories results' and its application in clinical practice⁴.

Studies have correlated the isolated anthropometric measures and the anthropometric indexes with IR^5-9. The anthropometric indicators arise as an alternative for IR's evaluation with lower cost and higher easiness of application in epidemiological studies and in health basic attention services. Because of the importance of this theme, the objective was to discuss about the main measures and the anthropometric indexes that have been associated with IR.

Methodology

A bibliographic review was performed on available periodics in scientific bases, such as Scielo, Science Direct and Pubmed. The keywords used for the search of articles were: insulin resistance; anthropometry; body mass index; waist circumference; sagittal abdominal diameter; waist-hip ratio; conicity index; waist-thigh ratio; neck circumference; and waist-stature ratio. Published articles were selected between 1990 and 2007, besides of the incorporation of classic previously published papers concerning the theme. Most of the studies included in this review were transversal. Some case-control and cohorts works were also discussed. Articles characterized by scientific rigidity, concerning the sample's size and statistical analysis appropriate to the objectives of the study.

Insulin resistance

Laboratorial determination

IR can be determined directly from the management of a predetermined quantity of exogenous insulin, or indirectly, based on the concentrations of endogenous insulin¹⁰.

The euglycemic hyperinsulinemic clamp is an example of a direct technique that allows the determination of a metabolized insulin quantity, by the peripheric tissues during the stimulation with insulin. Although nowadays it is the golden standard technique for evaluating the IR in vivo, it is costly, slowly and of high complexity, being feasible its application in population studies, and especially in clinical practice¹¹.

The Homeostasis Model Assessment (HOMA) index represents one of the alternatives to the clamp technique for evaluating IR. It is a mathematic model that predicts IR's level from the basal glycaemia and insulinaemia, in homeostasis conditions, being represented by the equation¹²:

HOMA = [Fasting insulinaemia (mU/l) x Fasting glycaemia (mmol/l)] / 22.5

The HOMA has been widely used, specially in population studies, due to its easiness of application and to the strong and significant correlation with the direct techniques of evaluation of IR, observed in validations papers^13,14. Nevertheless, for diagnosis or individual follow-up, its use still requires caution in questions related to the blood sample and to the defective standardization of assays to be used by the laboratories in the insulin dosage⁴, pointing the need of more accessible and viable methods for clinical practice.

Anthropometric indicators

The development of computed tomography and of magnetic resonance image represented an important advance in the research of a body composition in human beings, because they allow accurate and precise measurement of the visceral and subcutaneous fat, located in the abdominal region. Ultrasonography and dual energy x-ray absorptiometry (DEXA) can also be used to evaluate abdominal fat, although the latter does not distinction between subcutaneous and visceral fat^15,16. However, these techniques are costly and many times unavailable.

The anthropometric measures are indicatives of the nutritional state, present low cost, inocuity, simplicity in its execution and have acted as obesity indicators¹⁷. The correlations between the anthropometric indicators and IR have been widely studied, detaching them as non-invasive indicators for the evaluation of risk of IR, both in the epidemiologic search as in clinical practice.

The anthropometric indexes can be classified according to the evaluated obesity type¹⁷. Amongst the central obesity indicators there are: waist perimeter (WP), the sagittal abdominal diameter (SAD), conicity index (COI) and the waist-stature ratio. The body fat distribution has been evaluated by the waist-hip ratio, the sagittal index (SI), the waist-thigh ratio and the neck-thigh ratio. For the generalized obesity, the body mass index (BMI) has been the most used. Table 1 summarizes the main discussed studies in this review, which evaluated anthropometric indicators as predictors of IR.

Although the obesity indicators are related to IR, it should be noteworthy that IR is not a metabolic alteration exclusive of obesity and diabetes mellitus type 2 porters, as it happens in patients with of lipoatrophic diabetes, in which there is a genetic defect of insulin's action in skinny subjects. In the same way, some patients with normal BMI can present IR because of the visceral fat accumulation, composing a phenotype known as Metabolically Obese Normal Weight (MONW)¹⁸.

Waist perimeter

The practicality in the application of WP, its association with cardiovascular risk factors and the strong correlation with the visceral fat area measured by computed tomography, from the order 0.73 to 0.81^19,20, are characteristics that have made it the most used indicator of abdominal adiposity. Besides that, the evaluation of the WP is in the proposals of the European Group for the Study of Insulin Resistance²¹, the International Diabetes Federation²² and of the National Cholesterol Education Program (NCEP-ATP III)²³, for the diagnosis of the IR syndrome.

In 1995, Han et al²⁴ have showed that the WP values above 80 and 88 cm for women, and above 94 and 102 cm for men, indicated increased and very increased risk, respectively, of metabolic complications. Later, the NCEP-ATP III²³ adopted the 88 and 102 cm values for the diagnosis of central obesity in men and women, respectively, these which have been used especially in Brazil. Populations differ between each other, according to the risk level presented for a WP datum, being impossible to determine cut points globally applicable. The International Diabetes Federation recommends the use of different cut points, according to ethnicity (Table 2)²².

Although WP is largely diffusive, there are different descriptions for assessing and, consequently, consensus absence between researchers and published protocols, which can create conflicts at the time the measure is taken. Between the most used, there is the medium point between the iliac crest and the last rib, recommended by the World Health Organization (WHO)²⁵; the smallest waist between the thorax and the hip, recommended by the Anthropometric Standardization Reference Manual²⁶; the level immediately above the iliac crests, as recommended by the National Institute of Health²⁷; and the umbilical level⁸ (Figure 1).

Ross et al²⁸ have checked that the protocol used for measurement of the WP does not have essential influence in its association with cardiovascular diseases and type 2 diabetes. In Wang et al study²⁹, although no correlations between WP and morbidity risks have been carried out, the authors suggest that the comparisons among different papers are only valid when the same anatomic place is used for checking. These researchers have made comparisons between WP measures, taken in four places (smallest waist; immediately below the last rib; medium point between the iliac crest and the last rib and right above the iliac crest) in 111 subjects. In both sexes, differences were found, showing that the four places are not identical.

Several studies have evaluated the relation between WP and IR. In a study carried out with 8,400 subjects, WP associated positively and independently with type 2 diabetes³⁰. In Weidner et al work³¹, WP was the first anthropometric variable in the multivariated regression analysis, contributing with approximately 37% for a variation in insulin's sensibility. In a case-control study carried out with 300 Indians, WP was identified as the precisest predictor of risk for type 2 diabetes and its biochemical indicators³².

In a paper carried out with Caucasians, WP was identified as a strong predictor of IR, especially in men. The best cut points of WP were evaluated for predicting IR, being 97.5 cm and 106.5 cm the values found for women and men, respectively. Yet, when the values of 88 cm for women and 102 cm, for men are compared, recommended by the NCEP-ATP III²³, the new cut points did not seem to be superior in identifying subjects with IR³³.

In Pouliot et al study¹⁹, the increment in WP measures was consistent to the increase of glycaemia and insulinaemia of fasting and post-prandial, especially in women, suggesting that these measures are cardiovascular risk indicators. The authors suggest that the WP values above 100 cm are related to the greatest chance of development of metabolic complications.

Sagittal abdominal diameter

The SAD represents an abdominal height, comprising the distance between the back and the abdomen³⁴. It can be checked with the person standing³⁵ or in the supine position (Figure 2), this last position is the most used^7,35,36.

In the supine position, the visceral adipose tissue tends to raise the abdominal wall in the sagittal direction, and the abdominal adipose subcutaneous anterior or lateral tissue compresses the abdomen or tends to descend to both sides due to the gravity strength. Thus, it is expected that the assessed SAD in the supine position reflects specially the volume of the visceral adipose tissue³⁷.

The anatomical place used for the assessing differs between the studies, being used the smallest waist between the thorax and hip³⁸; the highest abdominal height³⁹; the umbilical scar⁴⁰; the medium point between the last rib and the iliac crest³⁶; and the medium point between the iliac crests⁴¹. The latter coincides with the localization of the lombar vertebral L4 and L5, the most used place by the images techniques for quantification of the visceral adipose tissue area and, maybe, the most indicated for assessing of SAD⁴².

The measurement of SAD can be done by anthropometry with the help of one abdominal caliper, or by image techniques, like the computed tomography or magnetic resonance image, since lots of studies have showed strong correlation between both techniques^36,43.

SAD has been recommended as an indicator of deposition of visceral abdominal fat and of cardiovascular risk evaluation^44,45. Recently, cut points were proposed for SAD evaluation in Brazilians, based on a quantity of increased visceral abdominal fat, which corresponds to a superior value to 100 cm². For the female and male sex, the cut points were 19.3 and 20.5 cm, respectively²⁰.

SAD has showed strong association with glucose intolerance and with IR. Gustat et al³⁸ have identified SAD as an independent predictor of glycaemia and insulinaemia, pointing this anthropometric measure as an excellent marker of IR.

In Risérus et al study⁷, SAD presented stronger correlation with IR, glycaemia, insulinaemia, C-peptide and hyperproinsulinemia than the BMI, WP and waist-hip ratio. In the analysis of a univariated multiple regression, including all the anthropometric variables, SAD was the only independent predictor of IR. The study of Petersson et al⁴⁴, which was done with Swedish women, the SAD was also the best clinical marker of IR among the others, including WP, the waist-hip ratio and the BMI. In Pouliot et al study¹⁹, besides WP, the SAD increment was also consistent to the increase on the fasting and post-prandial glycaemia and insulinaemia. In this paper, SAD values above 25 cm were associated with the highest development probability of metabolic disturbances with atherogenic potential.

Waist-hip ratio

The waist-hip ratio is the index of regional distribution of body fat most used in the epidemiological research. It is based on the ratio between the WP values and the hip's perimeter (HP). The anatomical place most used for the assessing of HP is in the height of the greatest trochanter, recommended by the WHO²⁵. The waist and hip's perimeter reflect different aspects of the body composition, and possess independent and opposite effects in determining the risk of cardiovascular diseases and its risk factors. Narrow waists and large hips are associated with protection against cardiovascular diseases. This ratio has been explained by the following theory: narrow hips reflect a reduced quantity of muscular mass, which contributes for the minor insulin activity in the skeptical musculature and for the minor concentration and activity of lipoproteic lipase in the muscles, with concomitant reduction in the capture and use of fatty acid by the muscular cells. In contrast, large hips present higher concentration of lipoproteic lipase due to the biggest quantity of muscular tissue. Besides that, there is lower turnover of fatty acids in the gluteofemoral adipose tissue in relation to the visceral adipose tissue, which aids insulin sensibility. However, the independent effects of each one of the perimeters can be confused in the waist-hip ratio, so the interpretation of its values is much more complex⁴⁶.

Waist-hip ratio is partially independent of total adiposity. Skinny and obese individuals can present the same waist-hip ratio value, even though there is a substantial interindividual variation in the total fat mass and in the visceral and subcutaneous abdominal adipose tissue¹⁹. Moreover, waist-hip ratio can be unaltered even when changes in the body adiposity happens, due to similar alterations in both perimeters that not alter the final relation. Thus, it is important to be cautious when using waist-hip ratio as an indicator of visceral fat accumulation, being this an inappropriate relation to assess changes in visceral fat quantity during the loss or gain of weight⁴⁷.

In Pouliot et al study¹⁹, although the waist-hip ratio has not been the best predictor of disturbances in the glucose and insulin metabolism, authors have suggested that the waist-hip ratio values above 0.8 for women, and 1.0 for men, would be associated with these metabolic alterations.

In Riserus et al⁷, Mamtani et al³² and Petterson et al⁴⁴ studies, waist-hip ratio has presented as a less useful instrument to predict IR, compared to the other anthropometric measures studies.

Sagittal index

Although less known and used between researchers and health professionals, the SI was proposed as an alternative to waist-hip ratio for estimation of the body fat distribution and for the prediction of morbidities. The SI is represented by the reason between SAD (cm) and the thigh medium perimeter (cm). In order to use it, SAD and the thigh medium perimeter, assessed in the medium point between the inguinal fold and the proximal border of patella (Figure 3), they would be measured with better representivity of the tissues in interest, compared to the waist and hip's perimeter, respectively⁴⁷.

The measure of the thigh's medium perimeter comprises the skeptical musculature, the femur and the subcutaneous and intramuscular adipose tissue. These three tissues are analogue to the ones that surround the intra-abdominal content, composed of the skeptical musculature, the vertebras and the subcutaneous adipose tissue. As the visceral adipose tissue is the abdominal compartment of interest, the thigh's medium perimeter represents a measure of comparison with the abdominal measures⁴⁷. As an advantage, in contrary to the hip's perimeter, the thigh's medium perimeter is not affected by the variations in the pelvic architecture. Besides, the thigh's medium perimeter and the SAD are measured with increased precision³⁴. The thigh's medium point is the most used to represent the central portion of the muscle, which reflects the muscular mass and the practice of physical exercises. Individuals with increased content of muscular mass and subcutaneous adipose tissue in the thigh can present a bigger answer to the signalization of insulin and low cardiovascular risk⁴⁷.

In a study carried out in Brazil, the SI presented lesser correlation with the visceral adipose tissue than SAD; however, there was no correlation of the SI with the area of subcutaneous abdominal fat²⁰. In the study of Kahn et al⁴⁸, among the traditional anthropometric measures, like BMI and the waist-hip ratio, the SI was a better predictor of sudden coronary death in men. Smith et al⁴⁹ evaluated the strength of the association of six anthropometric parameters with known factors of cardiovascular risk in men of different ethnicities. SI was the one which presented the highest Odds Ratio for the cardiovascular disease. Although these papers have presented good results for the SI, studies evaluating its utility in predicting IR and other factors of cardiovascular risk are still scarce.

Waist-thigh ratio

Waist-thigh ratio presents a fundamental similar to the one applied in the SI, regarding the use advantages' of the thigh's perimeter in prejudice to hip's perimeter, calculated from the ratio between WP values' (cm) and the thigh's medium perimeter (cm).

In Chuang et al study⁸ with Orientals (n = 6,007), between the 32 evaluated measures by laser scanning in three dimensions, the WP, representing the trunk, and the thigh's medium perimeter, representing the inferior part of the body, were the best indicators of type 2 diabetes. By the comparison between the waist-thigh ratio and the known anthropometric indicators, among them there is the BMI, the waist-hip ratio and thigh's perimeter, the authors have identified stronger correlations for the waist-thigh ratio. Kahn et al⁴⁸ have showed in their study that, the waist-thigh ratio have had great performance for evaluating cardiovascular risk disease, parallel to SI.

Neck-thigh ratio

Neck-thigh ratio comprises the reason between neck's perimeter (cm), assessed in the medium point of the neck's height (Figure 4), and the thigh's medium perimeter (cm), those which have been used as distribution indexes of subcutaneous adipose tissue of superior and inferior body parts, respectively. Following the tricompartimental body composition (visceral and subcutaneous adipose tissue), after adjustment for scarce mass and visceral adipose tissue, Sjöström et al identified positive correlation between neck's perimeter and cardiovascular risk factors related to IR, while the thigh's perimeter showed inverse correlation⁵⁰.

Laakso et al⁵¹, in a study carried out with 541 adults distributed according to quintiles of the neck's perimeter, identified major frequencies of hyperglycemia and hyperinsulinemia in the superior quintiles of measure, suggesting the use of neck's perimeter, in population screenings as a marker of risk individuals for IR. Ben-Noun and Laor⁵² also found significant correlation between the neck's perimeter, with several cardiovascular risk factors related to IR.

Although papers evaluating neck-thigh ratio are rare, it is noteworthy that the neck's perimeter represents a quick and easy measure to happen, yonder not presenting variations in its extent throughout the day.

Waist-stature ratio

Waist-stature ratio is the reason between WP (cm) and the stature (cm). It is assumed that, for a determined stature, there is an acceptable fat degree stored in the body's superior part. Even so the precise effect of stature on the WP is quantitatively unknown, some authors assert that stature has an influence on the magnitude of WP through growing and adult life^53,54.

Studies show that, although waist-stature ratio has good correlation with visceral fat, it should be the anthropometric indicator used for the prediction of metabolic risks associated with obesity^17,54. The most used argument is that WP⁵⁴ and the BMI⁵⁵ need several cut points, depending on the ethnicity and gender^22,25, which would supposedly difficult its use. According to these authors, WP value's maintenance below the value corresponding to stature's measure, would represent a simple and effective message for all the population, in a way that it can helps to prevent IR syndrome^54,55. A study conducted with Iranian men showed that the waist-stature ratio presented better performance in predicting type 2 diabetes, compared to BMI⁹.

Amongst waist-stature ratio, there would be the relation with cardiovascular risk factors, including fasting insulinaemia¹⁷; the increased sensibility in detecting precociously risk factors, when compared to BMI; and the simplicity of execution united to easiness of one cut point for individual's classification, in which the 0.5-value, determined based on the great balance between sensibility and specificity, could be universally used^55,56. Ho et al¹⁷ study found 0.48 value as the best cut point for the prediction of hyperinsulinemia in Chinese men.

In spite of waist-stature ratio uses stature and allows its application in several ethnicities, it can be questioned if the distinguished standard of body fat distribution, among men and women, would difficult the use of only one cut point for both sexes. However, men are taller and present higher measures for WP in relation to women. Thus, waist-stature ratio means are similar to both sexes due to the adjustment for the stature⁵⁴.

Conicity index

COI represents an abdominal obesity indicator and was proposed by Valdez⁵⁷. This index considers that, individuals with less accumulation of fat in the central part would have a body form similar to a cylinder, while those with bigger accumulation would assimilate to a double cone, with this as a common basis.

COI equation's regards WP measures, body weight, stature and 0.109 constant, which represents the conversion of volume and mass units' for lengths units⁵⁸:

COI is a simple interpretation, once the denominator is the cylinder produced by the evaluated weight and stature. Hence, a COI equals to 1.20 means that the WP is 1.20 higher than the cylinder perimeter created from the by the evaluated weight and stature, reflecting the adiposity excess in the abdominal region. COI does not have a measure unit and its theoretical range is of 1.00 (perfect cylinder) to 1.73 (double cone)⁵⁸.

In its advantages, there is the fact of including in its stature, a WP adjustment for weight and stature, allowing direct comparisons of abdominal adiposity among the subjects our populations. Farther on, COI has a weak correlation with stature that is desirable for any indicator of obesity^57,58.

In a multicenter study, with 2,240 adults, insulinaemia has presented correlation standards consistent with COI⁵⁸. Pitanga and Lessa⁶ conducted a work in Brazil, with 2,297 people, and identified COI as a glycaemia discriminator and of cardiovascular risk. These authors made a table to make easy the use of COI, in which, from weight and stature values, it has already calculated the index denominator. Thus, conicity of any waist value, for a given weight and stature, can be promptly analyzed, enabling to foretell the risks of diseases associated with abdominal adiposity, like IR.

In contrast, in Mantzoros et al study⁵⁹, carried out in Greece, with 280 healthy women of 18 to 24 years old, COI presented a very weak correlation (r = 0.13, p = 0.03) with fasting insulinaemia. Mamtani and Kuljarni³², comparing the performance of various anthropometric parameters related to central obesity, have checked that COI was the one which presented less predictive accuracy for the central obesity measures'. In the same study, COI did not show correlation with fasting and post-prandial glycaemia. So, it is observed the need of more investigations about this index, to determine its viability in the risk prediction of IR.

Body mass index

The BMI is weight in kilograms divided by height in meters squared⁶⁰. It represents the most known and used indicator of nutritional status to evaluate adults and old-aged, due to its easiness of application and low cost. Due to its incapacity of evaluating the distribution of body fat, it characterizes as an indicator of generalized adiposity. Changes in the BMI do not reflect the anatomical place in which the subject can have lost or loosen weight⁶¹. Generally, BMI shows weaker correlations with visceral fat than the WP and SAD^20,43.

The papers that evaluated the capacity of BMI in predicting IR are presenting conflicting results. In the study of Farin et al⁶², there were no differences in the magnitude of correlations between BMI with IR in Caucasians. From the regression analysis, both indicators of generalized and central adiposity showed the same capacity of identifying subjects with IR. In the paper of Ascaso et al⁶³, conducted with Spanish people, both WP or the BMI correlated with IR. In the logistic regression analysis, only the BMI remained in the model as an Odds Ratio of 2.6, while WP lost statistical significance. Chang et al⁶⁴ identified the BMI as the most important determinant of IR in Orientals. However, the correlations among the BMI and IR were weak, and this was the only anthropometric indicator used in the study. Ybarra et al³³ affirmed that the best cut points of BMI to predict IR, are values from 29.5 kg/m², for women, and 30.5 kg/m², for men. Such cut points assimilate to 30 kg/m², proposed by the WHO²⁵, for obesity's classification. Nevertheless, as this paper was conducted with Spanish people, it can not be generalized to the other ethnicities. Stern et al⁶⁵ evaluated 2,321 subjects of several ethnicities and identified, as cut points for predicting IR, BMI values' > 28.7 kg/m².

Even though the mentioned papers have indicated positive results for the BMI in the prediction of IR, several studies which evaluated central adiposity measures^{7,17,44,54,66} or of body fat distribution^8,17, showed their superiority related to the BMI, probably due to the association between IR and the accumulation of visceral adipose tissue that is better represented by these measures. Moreover, due to the BMI's incapacity of distinguishing thin or fat body mass, its use for the prediction of IR can overestimate the risk in individuals with increased quantity of muscular mass, like athletes, and overestimate the risk in old-aged whose muscular mass, generally, is reduced and there is an increased accumulation of visceral adipose tissue¹⁷.

Conclusion

The scarcity of studies comparing several anthropometric indicators in only one paper difficults the conclusion of which one is the best indicator for predicting IR. Yet, WP and SAD seem to present better predictive capacity for IR, once the results were more consistent among the papers. Waist-thigh ratio, the COI, the SI, neck-thigh ratio and waist-height ratio have demonstrated positive results; however, more studies are necessary to solidify them as IR indicators. The results of the BMI and waist-hip ratio were more inconsistent. Although it is extremely useful, from a clinical point of view, to identify adiposity anthropometric indicators that present the best capacity of identifying subjects with IR, it is important to consider that, from them, the risk will always be evaluated, for they are alternative methods and do not explain IR as a whole. Important variables which have an influence in the modulation of insulin's action, as the life style and the genetic factors, must be considered.

Acknowledgements

Support from Fundação de Amparo à Pesquisa do Estado de Minas Gerais (Fapemig) and the National Counsel of Technological and Scientific Development (CNPq).

Potential Conflict of Interest

No potential conflict of interest relevant to this article was reported.

Sources of Funding

This study was funded by CNPq and FAPEMIG.

Study Association

This article is part of the thesis of master submitted by Ana Carolina Junqueira Vasques, from Universidade Federal de Viçosa.

References

• 1.   Silva EA, Flexa F, Zanella MT. Obesidade abdominal, resistência à insulina e hipertensão: impacto sobre a massa e a função do ventrículo esquerdo em mulheres. Arq Bras Cardiol. 2007; 89 (2): 86-92.
• 2.  Boden-Albala B, Sacco RL, Lee HS, Grahame-Clarke C, Rundek T, Elkind MV, et al. Metabolic syndrome and ischemic stroke risk: Northern Manhattan Study. Stroke. 2008; 39 (1): 30-5.
• 3.  Ribeiro Filho FF, Mariosa LS, Ferreira SR, Zanella MT. Gordura visceral e síndrome metabólica: mais que uma simples associação. Arq Bras Endocrinol Metab. 2006; 50 (2): 230-8.
• 4.  Vasques ACJ, Rosado LEFPL, Alfenas RCG, Geloneze B. Análise crítica do uso dos índices do Homeostasis Model Assessment (HOMA) na avaliação da resistência à insulina e capacidade funcional das células-b pancreáticas. Arq Bras Endocrinol Metab. 2008; 52 (1): 32-9.
• 5.  Taniguchi A, Fukushima M, Sakai M, Kataoka K, Nagata I, Doi K, et al. The role of the body mass index and triglyceride levels in identifying insulin-sensitive and insulin-resistant variants in Japanese non-insulin-dependent diabetic patients. Metabolism. 2000; 49 (8): 1001-5.
• 6.  Pitanga FJG, Lessa I. Sensibilidade e especificidade do índice de conicidade como discriminador do risco coronariano de adultos em Salvador, Brasil. Rev Bras Epidemiol. 2004; 7 (3): 259-69.
• 7.  Riserus U, Arnlov J, Brismar K, Zethelius B, Berglund L, Vessby B. Sagittal abdominal diameter is a strong anthropometric marker of insulin resistance and hyperproinsulinemia in obese men. Diabetes Care. 2004; 27 (8): 2041-6.
• 8.  Chuang YC, Hsu KH, Hwang CJ, Hu PM, Lin TM, Chiou WK. Waist-to-thigh ratio can also be a better indicator associated with type 2 diabetes than traditional anthropometrical measurements in Taiwan population. Ann Epidemiol. 2006; 16 (5): 321-31.
• 9.  Meshkani R, Taghikhani M, Larijani B, Khatami S, Khoshbin E, Adeli K. The relationship between homeostasis model assessment and cardiovascular risk factors in Iranian subjects with normal fasting glucose and normal glucose tolerance. Clin Chim Acta. 2006; 371 (1-2): 169-75
• 10. Geloneze B, Tambascia MA. Avaliação laboratorial e diagnóstico de resistência insulínica. Arq Bras Endocrinol Metab. 2006; 50 (2): 208-15.
• 11. DeFronzo RA, Tobin JD, Andres R. Glucose clamp technique: a method for quantifying insulin secretion and resistance. Am J Physiol. 1979; 237 (3): 214-23.
• 12. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985; 28 (7): 412-9.
• 13. Hermans MP, Pepersack TM, Godeaux LH, Beyer I, Turc AP. Prevalence and determinants of impaired glucose metabolism in frail elderly patients: the Belgian Elderly Diabetes Survey (BEDS). J Gerontol A Biol Sci Med Sci. 2005; 60 (2): 241-7.
• 14. Bonora E, Targher G, Alberiche M, Bonadonna RC, Saggiani F, Zenere MB, et al. Homeostasis model assessment closely mirrors the glucose clamp technique in the assessment of insulin sensitivity: studies in subjects with various degrees of glucose tolerance and insulin sensitivity. Diabetes Care. 2000; 23 (1): 57-63.
• 15. Ross R. Advances in the application of imaging methods in applied and clinical physiology. Acta Diabetol. 2003; 40 (Suppl 1): 45-50.
• 16. Leite CC, Matsuda D, Wajchenberg BL, Cerri GG, Halpern A. Correlação da medida de espessura intra-abdominal medida pela ultra-sonografia com os fatores de risco cardiovascular. Arq Bras Endocrinol Metab. 2000; 44 (1): 49-56.
• 17. Ho SY, Lam TH, Janus ED. Waist to stature ratio is more strongly associated with cardiovascular risk factors than other simple anthropometric indices. Ann Epidemiol. 2003; 13 (10): 683-91.
• 18. Conus F, Allison DB, Rabasa-Lhoret R, St-Onge M, St-Pierre DH, Tremblay-Lebeau A, et al. Metabolic and behavioral characteristics of metabolically obese but normal-weight women. J Clin Endocrinol Metab. 2004; 89 (10): 5013-20.
• 19. Pouliot MC, Despres JP, Lemieux S, Moorjani S, Bouchard C, Tremblay A, et al. Waist circumference and abdominal sagittal diameter: best simple anthropometric indexes of abdominal visceral adipose tissue accumulation and related cardiovascular risk in men and women. Am J Cardiol. 1994; 73 (7): 460-8.
• 20. Sampaio LR, Simoes EJ, Assis AM, Ramos LR. Validade e confiabilidade do diâmetro abdominal sagital enquanto preditor de gordura abdominal visceral. Arq Bras Endocrinol Metab. 2007; 51 (6): 980-6.
• 21. Balkau B, Charles MA. Comment on the provisional report from the WHO consultation. European Group for the Study of Insulin Resistance (EGIR). Diabet Med. 1999; 16 (5): 442-3.
• 22. Alberti KG, Zimmet P, Shaw J. Metabolic syndrome--a new world-wide definition. A Consensus Statement from the International Diabetes Federation. Diabet Med. 2006; 23 (5): 469-80.
• 23. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III). JAMA. 2001; 285 (19): 2486-97.
• 24. Han TS, van Leer EM, Seidell JC, Lean ME. Waist circumference action levels in the identification of cardiovascular risk factors: prevalence study in a random sample. BMJ. 1995; 311: 1401-5.
• ²⁵
  World Health Organization. Obesity: preventing and managing the global epidemic. Report of a WHO Consultation. Geneva: WHO Technical Report Series 894. World Health Organization, 2000.
• 26. Lohman TG, Roche AF, Martorell R. Anthropometric standardization reference manual. Champaign: Human Kinetics Pub; 1988.
• ²⁷
  National Institute of Health (NIH). The practical guide identification, evaluation, and treatment of overweight and obesity in adults. Bethesda: NIH; 2000.
• 28. Ross R, Berentzen T, Bradshaw AJ, Jansson I, Kahn HS, Katzmarzyk PT, et al. Does the relationship between waist circumference, morbidity and mortality depend on measurement protocol for waist circumference? Obes Rev. 2007; 9 (4): 312-25.
• 29. Wang J, Thornton JC, Bari S, Williamson B, Gallagher D, Heymsfield SB, et al. Comparisons of waist circumferences measured at 4 sites. Am J Clin Nutr. 2003; 77 (2): 379-84.
• 30. Snijder MB, Zimmet PZ, Visser M, Dekker JM, Seidell JC, Shaw JE. Independent and opposite associations of waist and hip circumferences with diabetes, hypertension and dyslipidemia: the AusDiab Study. Int J Obes Relat Metab Disord. 2004; 28 (3): 402-9.
• 31. Weidner MD, Gavigan KE, Tyndall GL, Hickey MS, McCammon MR, Houmard JA. Which anthropometric indices of regional adiposity are related to the insulin resistance of aging? Int J Obes Relat Metab Disord. 1995; 19 (5): 325-30.
• 32. Mamtani MR, Kulkarni HR. Predictive performance of anthropometric indexes of central obesity for the risk of type 2 diabetes. Arch Med Res. 2005; 36 (5): 581-9.
• 33. Ybarra J, Sanchez-Hernandez J, Pou J, Fernandez S, Gich I, Ordonez-Llamos J, et al. Anthropometrical measures are easily obtainable sensitive and specific predictors of insulin resistance in healthy individuals. Prevention and Control. 2005; 1 (2): 175-81.
• 34. Williamson DF, Kahn HS, Worthman CM, Burnette JC, Russell CM. Precision of recumbent anthropometry. Am J Hum Biol. 1993; 5 (2): 159-67.
• 35. Iribarren C, Darbinian JA, Lo JC, Fireman BH, Go AS. Value of the sagittal abdominal diameter in coronary heart disease risk assessment: cohort study in a large, multiethnic population. Am J Epidemiol. 2006; 164 (12): 1150-9.
• 36. van der Kooy K, Leenen R, Seidell JC, Deurenberg P, Visser M. Abdominal diameters as indicators of visceral fat: comparison between magnetic resonance imaging and anthropometry. Br J Nutr. 1993; 70 (1): 47-58.
• 37. Sjöstrom L. A computer-tomography based multicompartment body composition technique and anthropometric predictions of lean body mass, total and subcutaneous adipose tissue. Int J Obes. 1991; 15 (Suppl 2): 19-30.
• 38. Gustat J, Elkasabany A, Srinivasan S, Berenson GS. Relation of abdominal height to cardiovascular risk factors in young adults: the Bogalusa heart study. Am J Epidemiol. 2000; 151 (9): 885-91.
• 39. Kullberg J, von Below C, Lonn L, Lind L, Ahlstrom H, Johansson L. Practical approach for estimation of subcutaneous and visceral adipose tissue. Clin Physiol Funct Imaging. 2007; 27 (3): 148-53.
• 40. Ohrvall M, Berglund L, Vessby B. Sagittal abdominal diameter compared with other anthropometric measurements in relation to cardiovascular risk. Int J Obes Relat Metab Disord. 2000; 24 (4): 497-501.
• 41. Kahn HS, Simoes EJ, Koponen M, Hanzlick R. The abdominal diameter index and sudden coronary death in men. Am J Cardiol. 1996; 78 (8): 961-4.
• 42. Kahn HS. Alternative anthropometric measures of risk: possible improvements on the waist-hip ratio. In: Medeiros-Neto G, Halpern A, Bouchard C. (eds.). Progress in obesity research. 9th ed. London: John Libbey Eurotext Ltd; 2003 .p. 639-43.
• 43. Despres JP, Prud'homme D, Pouliot MC, Tremblay A, Bouchard C. Estimation of deep abdominal adipose-tissue accumulation from simple anthropometric measurements in men. Am J Clin Nutr. 1991; 54 (3): 471-7.
• 44. Petersson H, Daryani A, Riserus U. Sagittal abdominal diameter as a marker of inflammation and insulin resistance among immigrant women from the Middle East and native Swedish women: a cross-sectional study. Cardiovasc Diabetol. 2007; 6: 10.
• 45. Seidell JC, Perusse L, Despres JP, Bouchard C. Waist and hip circumferences have independent and opposite effects on cardiovascular disease risk factors: the Quebec Family Study. Am J Clin Nutr. 2001; 74 (3): 315-21.
• 46. van der Kooy K, Leenen R, Seidell JC, Deurenberg P, Droop A, Bakker CJ. Waist-hip ratio is a poor predictor of changes in visceral fat. Am J Clin Nutr. 1993; 57 (3): 327-33.
• 47. Kahn HS. Choosing an index for abdominal obesity: an opportunity for epidemiologic clarification. J Clin Epidemiol. 1993; 46: 491-4.
• 48. Kahn HS, Austin H, Williamson DF, Arensberg D. Simple anthropometric indices associated with ischemic heart disease. J Clin Epidemiol. 1996; 49 (9): 1017-24.
• 49. Smith DA, Ness EM, Herbert R, Schechter CB, Phillips RA, Diamond JA, et al. Abdominal diameter index: a more powerful anthropometric measure for prevalent coronary heart disease risk in adult males. Diabetes Obes Metab. 2005; 7 (4): 370-80.
• 50. Sjöström CD, Hĺkangĺrd AC, Lissner L, Sjöström L. Body compartment and subcutaneous adipose tissue distribution- risk factor patterns in obese subjects. Obes Res. 1995; 3: 9-22.
• 51. Laakso M, Matilainen V, Keinänen-Kiukaanniemi S. Association of neck circumference with insulin resistance-related factors. Int J Obes Relat Metab Disord. 2002; 26 (6): 873-5.
• 52. Ben-Noun L, Laor A. Relationship of neck circumference to cardiovascular risk factors. Obes Res. 2003; 11 (2): 226-31.
• 53. McCarthy HD, Ashwell M. 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'. Int J Obes. 2006; 30 (6): 988-92.
• 54. Parikh RM, Joshi SR, Menon PS, Shah NS. Index of central obesity: a novel parameter. Med Hypotheses. 2007; 68 (6): 1272-5.
• 55. Ashwell M, Hsieh SD. 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. Int J Food Sci Nutr. 2005; 56 (5): 303-7.
• 56. Hsieh SD, Muto T. The superiority of waist-to-height ratio as an anthropometric index to evaluate clustering of coronary risk factors among non-obese men and women. Prev Med. 2005; 40 (2): 216-20.
• 57. Valdez R. A simple model-based index of abdominal adiposity. J Clin Epidemiol. 1991; 44 (9): 955-6.
• 58. Valdez R, Seidell JC, Ahn YI, Weiss KM. A new index of abdominal adiposity as an indicator of risk for cardiovascular disease: a cross-population study. Int J Obes Relat Metab Disord. 1993; 17 (2): 77-82.
• 59. Mantzoros CS, Evagelopoulou K, Georgiadis EI, Katsilambros N. Conicity index as a predictor of blood pressure levels, insulin and triglyceride concentrations of healthy premenopausal women. Horm Metab Res. 1996; 28 (1): 32-4.
• 60. Monteiro JC. Obesidade: diagnóstico, métodos e fundamentos. In: Halpern A, Matos AFG, Suplicy HL, Mancini MC, Zanella MT. Obesidade. São Paulo: Lemos; 1998. p. 31.
• 61. Snijder MB, van Dam RM, Visser M, Seidell JC. What aspects of body fat are particularly hazardous and how do we measure them? Int J Epidemiol. 2006; 35 (1): 83-92.
• 62. Farin HM, Abbasi F, Reaven GM. Body mass index and waist circumference both contribute to differences in insulin-mediated glucose disposal in nondiabetic adults. Am J Clin Nutr. 2006; 83 (1): 47-51.
• 63. Ascaso JF, Romero P, Real JT, Priego A, Valdecabres C, Carmena R. Insulin resistance quantification by fasting insulin plasma values and HOMA index in a non-diabetic population. Med Clin. 2001; 117 (14): 530-3.
• 64. Chang SA, Kim HS, Yoon KH, Ko SH, Kwon HS, Kim SR, et al. Body mass index is the most important determining factor for the degree of insulin resistance in non-obese type 2 diabetic patients in Korea. Metabolism. 2004; 53 (2): 142-6.
• 65. Stern SE, Williams K, Ferrannini E, DeFronzo RA, Bogardus C, Stern MP. Identification of individuals with insulin resistance using routine clinical measurements. Diabetes. 2005; 54 (2): 333-9.
• 66. Tarastchuk JCE, Guerios EE, Bueno RRL, Andrade Pm, Nercolini PC, Ferraz JG, et al. Obesidade e intervenção coronariana: devemos continuar valorizando o índice de Massa Corpórea? Arq Bras Cardiol. 2008; 90 (5): 311-6.

Publication Dates

• Publication in this collection
  29 Sept 2010
• Date of issue
  July 2010

History

• Accepted
  11 May 2009
• Reviewed
  17 Mar 2009
• Received
  29 Aug 2008