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Homeostasis model assessment of insulin resistance (HOMA-IR) and metabolic syndrome at baseline of a multicentric Brazilian cohort: ELSA-Brasil study

Modelo de avaliação da homeostase de resistência à insulina (HOMA-IR) e síndrome metabólica na linha de base de uma coorte brasileira multicêntrica: estudo ELSA-Brasil

Modelo homeostático para evaluar la resistencia a la insulina (HOMA-IR) y síndrome metabólico en la línea de base de una cohorte brasileña multicéntrica: estudio ELSA-Brasil

Abstract:

Homeostasis model assessment of insulin resistance (HOMA-IR) is a method to measure insulin resistance. HOMA-IR cut-offs for identifying metabolic syndrome might vary across populations and body mass index (BMI) levels. We aimed to investigate HOMA-insulin resistance cut-offs that best discriminate individuals with insulin resistance and with metabolic syndrome for each BMI category in a large sample of adults without diabetes in the baseline of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Among the 12,313 participants with mean age of 51.2 (SD 8.9) years, the prevalence of metabolic syndrome was 34.6%, and 60.1% had overweight or obesity. The prevalence of metabolic syndrome among normal weight, overweight and obesity categories were, respectively, 13%, 43.2% and 60.7%. The point of maximum combined sensitivity and specificity of HOMA-IR to discriminate the metabolic syndrome was 2.35 in the whole sample, with increasing values at higher BMI categories. This investigation contributes to better understanding HOMA-IR values associated with insulin resistance and metabolic syndrome in a large Brazilian adult sample, and that use of cut-off points according to ROC curve may be the better strategy. It also suggests that different values might be appropriate across BMI categories.

Keywords:
Metabolic Syndrome; Insulin Resistance; Cohort Studies

Resumo:

O modelo de avaliação da homeostase da resistência à insulina (HOMA-IR) é um método para medir a resistência à insulina. Os pontos de corte do HOMA-IR para identificar a síndrome metabólica podem variar entre as populações e os níveis de índice de massa corporal (IMC). Nosso objetivo foi investigar os pontos de corte do HOMA-IR que melhor discriminam indivíduos com resistência à insulina e com síndrome metabólica para cada categoria de IMC em uma grande amostra de adultos sem diabetes na linha de base do Estudo Longitudinal de Saúde do Adulto (ELSA-Brasil). Entre os 12.313 participantes com média de idade de 51,2 (DP 8,9) anos, a prevalência de síndrome metabólica foi de 34,6%, e 60,1% apresentavam sobrepeso ou obesidade. As prevalências de síndrome metabólica nas categorias de peso normal, sobrepeso e obesidade foram, respectivamente, 13%, 43,2% e 60,7%. O ponto de máxima sensibilidade e especificidade combinadas do HOMA-IR para discriminar a síndrome metabólica foi de 2,35 em toda a amostra, com valores crescentes nas categorias de IMC mais elevadas. Esta investigação contribui para o melhor entendimento dos valores de HOMA-IR associados à resistência à insulina e síndrome metabólica em uma grande amostra de adultos brasileiros, e que o uso de pontos de corte de acordo com a curva ROC pode ser a melhor estratégia. Também sugere que valores diferentes podem ser apropriados nas categorias de IMC.

Palavras-chave:
Síndrome Metabólica; Resistência à Insulina; Estudos de Coortes

Resumen:

El modelo homeostático para evaluar la resistencia a la insulina (HOMA-IR) es un método para medir la resistencia a la insulina. Los cortes HOMA-IR para identificar el síndrome metabólico pueden variar entre las poblaciones y los niveles del índice de masa corporal (IMC). El objetivo fue investigar los cortes de HOMA-IR que mejor discriminaban individuos con resistencia a la insulina y con síndrome metabólico para cada categoría de IMC, en una extensa muestra de adultos sin diabetes en la base de referencia del Estudio Longitudinal de Salud del Adulto (ELSA-Brasil). Entre los 12.313 participantes con una media de edad de 51,2 años (DE 8,9), la prevalencia de síndrome metabólico fue 34,6%, y un 60,1% sufría sobrepeso u obesidad. La prevalencia de síndrome metabólico entre las categorías: peso normal, sobrepeso y obesidad fueron respectivamente, 13%, 43,2% y 60,7%. El punto de máxima sensibilidad combinada y especificidad de HOMA-IR para discriminar el síndrome metabólico fue 2,35 en toda la muestra, con valores crecientes en las categorías de IMC más altas. Esta investigación contribuye a entender mejor los valores HOMA-IR, asociados con resistencia a la insulina y síndrome metabólico en una gran muestra de adultos brasileños, además del planteamiento de que el uso de puntos de corte según la curva ROC es quizás la mejor estrategia a seguir. También sugiere que valores diferentes pueden ser apropiados a través de las categorías de IMC.

Palabras-clave:
Síndrome Metabólico; Resistencia a la Insulina; Estudios de Cohortes

Introduction

Insulin resistance is one of the pathogenic mechanisms of the metabolic syndrome and is a common condition that allows identification of the risk of diabetes and metabolic syndrome 11. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 2009; 120:1640-5.. The gold standard method to assess insulin resistance is the hyperinsulinemic-euglycemic clamp, which is not useful for clinical and epidemiological investigations. The homeostasis model assessment of insulin resistance (HOMA-IR) is a method based on fasting glucose and insulin plasmatic levels, which was validated by Matthews et al. 22. 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; 28:412-9. and has been used for defining insulin resistance for clinical and research purposes in several populations. In Brazil, the Brazilian Metabolic Syndrome Study (BRAMS), with a population from 18 to 78 years old, used the 90th percentile to establish 2.7 as a cut-off to define insulin resistance in healthy people (n = 297) with body mass index (BMI) < 30kg/m², and 2.3 as the value that best discriminates the presence of metabolic syndrome 33. Geloneze B, Vasques AC, Stabe CF, Pareja JC, Rosado LE, Queiroz EC, et al. HOMA1-IR and HOMA2-IR indexes in identifying insulin resistance and metabolic syndrome: Brazilian Metabolic Syndrome Study (BRAMS). Arq Bras Endocrinol Metabol 2009; 53:281-7.. However, HOMA-IR cut-offs might differ across populations and BMI levels and establishing HOMA-IR values that correlate with insulin resistance and with metabolic syndrome is still necessary 44. Tang Q, Li X, Song P, Xu L. Optimal cut-off values for the homeostasis model assessment of insulin resistance (HOMA-IR) and pre-diabetes screening: developments in research and prospects for the future. Drug Discov Ther 2015; 9:380-5..

The Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) is a large multicentric cohort conducted in six Brazilian capitals, which analyzed data of 15,105 civil servants from three different geographical regions 55. Schmidt MI, Duncan BB, Mill JG, Lotufo PA, Chor D, Barreto SM, et al. Cohort profile: Longitudinal Study of Adult Health (ELSA-Brasil). Int J Epidemiol 2015; 44:68-75.. We aimed to investigate HOMA-IR cut-offs that best discriminate insulin resistance and metabolic syndrome for each BMI category among individuals without diabetes mellitus in this large sample.

Methods

This is a cross-sectional analysis of the ELSA-Brasil study, described previously 55. Schmidt MI, Duncan BB, Mill JG, Lotufo PA, Chor D, Barreto SM, et al. Cohort profile: Longitudinal Study of Adult Health (ELSA-Brasil). Int J Epidemiol 2015; 44:68-75.. Participants were enrolled between August 2008 and December 2010. All participants were volunteers, between 35 and 74 years old, and provided an informed consent form. All Institutional Review Boards approved this study.

For this analysis, we excluded 7 participants with missing data of fasting glucose, 12 of insulin, 52 of metabolic syndrome, 141 with underweight (BMI < 18.5kg/m2), and 2,580 with diabetes mellitus, which led to a final sample of 12,313 participants.

Height (in cm) was measured using a fixed stadiometer (accuracy of 0.1cm), and weight (kg) was measured with an electronic digital scale (Toledo, Brazil, to the nearest 100g). Waist (mid-point between lowest rib and iliac crest) circumference was measured by inelastic tapes (cm). The average of two measures was used for analyses. BMI [weight (kg)/height (m)2] was calculated. According to BMI, participants were stratified into categories: normal weight ≥ 18.5 to 24.9kg/m2, overweight 25-29.9kg/m2, obesity ≥ 30kg/m2. Blood pressure was defined by the average of two measures, after five minutes of rest in the sitting position 55. Schmidt MI, Duncan BB, Mill JG, Lotufo PA, Chor D, Barreto SM, et al. Cohort profile: Longitudinal Study of Adult Health (ELSA-Brasil). Int J Epidemiol 2015; 44:68-75..

Race/skin color, physical activity, alcohol and tobacco use were self-reported 55. Schmidt MI, Duncan BB, Mill JG, Lotufo PA, Chor D, Barreto SM, et al. Cohort profile: Longitudinal Study of Adult Health (ELSA-Brasil). Int J Epidemiol 2015; 44:68-75.. Blood samples were collected after an overnight fast for fasting glucose, total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-c), insulin. fasting glucose was determined by the hexokinase method (enzymatic colorimetric); total cholesterol by cholesterol oxidase method (enzymatic colorimetric), triglycerides by glycerol-phosphate peroxidase; HDL-c by homogeneous colorimetric without precipitation, insulin by immunoenzymatic assay, all of them with an ADVIA 1200 Siemens system (Deerfield, United States) 66. Fedeli LG, Vidigal PG, Leite CM, Castilhos CD, Pimentel RA, Maniero VC, et al. Logistics of collection and transportation of biological samples and the organization of the central laboratory in the ELSA-Brasil. Rev Saúde Pública 2013; 47 Suppl 2:63-71.. HOMA-IR was calculated from fasting glucose and insulin as [fasting glucose (mg/dL) X 0.0555 X fasting serum insulin (mUI/L)/22.5]2.

The quality and control of all data collected and stored were ensured according to the study protocol 55. Schmidt MI, Duncan BB, Mill JG, Lotufo PA, Chor D, Barreto SM, et al. Cohort profile: Longitudinal Study of Adult Health (ELSA-Brasil). Int J Epidemiol 2015; 44:68-75..

Since there is no consensus about whether the 75th and the 90th percentile of HOMA-IR should be used as cut-off points for identifying individuals with insulin resistance, we calculated both for the overall population and for each BMI category 44. Tang Q, Li X, Song P, Xu L. Optimal cut-off values for the homeostasis model assessment of insulin resistance (HOMA-IR) and pre-diabetes screening: developments in research and prospects for the future. Drug Discov Ther 2015; 9:380-5.,77. Wildman RP, Muntner P, Reynolds K, McGinn AP, Rajpathak S, Wylie-Rosett J, 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 2008; 168:1617-24.. We defined metabolic syndrome by the joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity criteria for Latin American populations 11. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 2009; 120:1640-5..

Data are described as means and standard deviation, median with interquartile range (IQR) and frequencies. Pairwise group comparisons were performed using the Mann-Whitney U test or the chi-square test. Receiving operator characteristic (ROC) analyses were conducted and the area under the curve (AUC) with 95% confidence intervals (95%CI) for the whole population and for each BMI category was estimated to investigate HOMA-IR accuracy at identifying metabolic syndrome. The point of the ROC with maximum sensitivity and specificity was determined by the Youden index 88. Fluss R, Faraggi D, Reiser B. Estimation of the Youden Index and its associated cutoff point. Biom J 2005; 47:458-72..

We performed a sub-analysis with the exclusion of participants with BMI ≥ 30kg/m2 (n = 2,399). All analyses were performed using the statistical software Stata 14 (https://www.stata.com).

Results and discussion

Among the 12,313 participants studied, 34.6% (n = 4,262) had metabolic syndrome and 60.1% (n = 7,399) had overweight or obesity. The prevalence of metabolic syndrome among normal weight, overweight and obesity categories were, respectively, 13%, 43.2% and 60.7%. Table 1 presents the population characteristics. After exclusion of participants with obesity, 2,805 (28.3%) had metabolic syndrome.

Table 1
Characteristics of the population studied according to the metabolic syndrome *, at baseline of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), 2008-2010.

For the population without metabolic syndrome, HOMA-IR 75th and 90th percentiles were 2.75 and 3.73, respectively. Regarding the participants without obesity and metabolic syndrome (n = 7,109), HOMA-IR 75th and 90th percentiles were, respectively, 2.55 and 3.43. The 90th percentile of the population without obesity and metabolic syndrome at ELSA-Brasil baseline was higher than that of the healthy population in the BRAMS study (2.7). This difference might be related to the inclusion of younger participants compared to ELSA-Brasil (≥ 18 years vs. ≥ 35 years, respectively) 99. Gayoso-Diz P, Otero-González A, Rodriguez-Alvarez MX, Gude F, García F, De Francisco A, et al. Insulin resistance (HOMA-IR) cut-off values and the metabolic syndrome in a general adult population: effect of gender and age: EPIRCE cross-sectional study. BMC Endocr Disord 2013; 13:47., and perhaps because ELSA-Brasil included participants from six capitals of different parts of the country: South, Southeast and Northeast.

The value with the maximum combined sensitivity and specificity to discriminate metabolic syndrome was 2.35 both for the whole population and among participants without obesity. Area under the curve ROC (95%CI) for total sample was 0.78 (0.77-0.79). There was a clear gradient of HOMA-IR values that best discriminate the metabolic syndrome across BMI categories with the highest values within the obese subgroup (Table 2). This suggests that it may be appropriate to apply different HOMA-IR values to define insulin resistance, according to the BMI category.

Table 2
Homeostasis model assessment of insulin resistance (HOMA-IR) values for the overall population and according to the body mass index (BMI) at baseline of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), 2008-2010.

The large sample that included participants from diverse Brazilian states, the methodological rigor in data collection, centralized analysis of the laboratory tests, and the rigorous quality control procedures are strengths of this study. However, we acknowledge that the inclusion of participants with a minimum age of 35 years limits generalizing these results to younger Brazilian populations. Also, ELSA-Brasil is not a population-based study, and generalization to the entire Brazilian population should be done with caution.

The point of maximum combined sensitivity and specificity of HOMA-IR to discriminate the metabolic syndrome was 2.35 in the whole sample, with increasing values at higher BMI categories. In a Spanish population the threshold value of HOMA-IR, considering, metabolic syndrome components was 2.05 99. Gayoso-Diz P, Otero-González A, Rodriguez-Alvarez MX, Gude F, García F, De Francisco A, et al. Insulin resistance (HOMA-IR) cut-off values and the metabolic syndrome in a general adult population: effect of gender and age: EPIRCE cross-sectional study. BMC Endocr Disord 2013; 13:47.. Different values were found in the literature according to the HOMA-IR percentile used as criteria to define insulin resistance, mean of age and BMI of studied population 44. Tang Q, Li X, Song P, Xu L. Optimal cut-off values for the homeostasis model assessment of insulin resistance (HOMA-IR) and pre-diabetes screening: developments in research and prospects for the future. Drug Discov Ther 2015; 9:380-5.,99. Gayoso-Diz P, Otero-González A, Rodriguez-Alvarez MX, Gude F, García F, De Francisco A, et al. Insulin resistance (HOMA-IR) cut-off values and the metabolic syndrome in a general adult population: effect of gender and age: EPIRCE cross-sectional study. BMC Endocr Disord 2013; 13:47.. Our investigation contributes to better understanding HOMA-IR values associated with insulin resistance and metabolic syndrome in a large Brazilian adult sample, and that use of cut-off points according to ROC curve may be the better strategy. Our findings also suggest that different values might be appropriate and should be adopted across the different BMI categories.

Acknowledgments

The authors thank all participants and the staff of the ELSA-Brasil for their important contributions.

References

  • 1
    Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 2009; 120:1640-5.
  • 2
    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; 28:412-9.
  • 3
    Geloneze B, Vasques AC, Stabe CF, Pareja JC, Rosado LE, Queiroz EC, et al. HOMA1-IR and HOMA2-IR indexes in identifying insulin resistance and metabolic syndrome: Brazilian Metabolic Syndrome Study (BRAMS). Arq Bras Endocrinol Metabol 2009; 53:281-7.
  • 4
    Tang Q, Li X, Song P, Xu L. Optimal cut-off values for the homeostasis model assessment of insulin resistance (HOMA-IR) and pre-diabetes screening: developments in research and prospects for the future. Drug Discov Ther 2015; 9:380-5.
  • 5
    Schmidt MI, Duncan BB, Mill JG, Lotufo PA, Chor D, Barreto SM, et al. Cohort profile: Longitudinal Study of Adult Health (ELSA-Brasil). Int J Epidemiol 2015; 44:68-75.
  • 6
    Fedeli LG, Vidigal PG, Leite CM, Castilhos CD, Pimentel RA, Maniero VC, et al. Logistics of collection and transportation of biological samples and the organization of the central laboratory in the ELSA-Brasil. Rev Saúde Pública 2013; 47 Suppl 2:63-71.
  • 7
    Wildman RP, Muntner P, Reynolds K, McGinn AP, Rajpathak S, Wylie-Rosett J, 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 2008; 168:1617-24.
  • 8
    Fluss R, Faraggi D, Reiser B. Estimation of the Youden Index and its associated cutoff point. Biom J 2005; 47:458-72.
  • 9
    Gayoso-Diz P, Otero-González A, Rodriguez-Alvarez MX, Gude F, García F, De Francisco A, et al. Insulin resistance (HOMA-IR) cut-off values and the metabolic syndrome in a general adult population: effect of gender and age: EPIRCE cross-sectional study. BMC Endocr Disord 2013; 13:47.

Publication Dates

  • Publication in this collection
    02 Sept 2020
  • Date of issue
    2020

History

  • Received
    18 Apr 2020
  • Reviewed
    10 July 2020
  • Accepted
    17 July 2020
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