![]() ![]() ![]() Details of the study design were previously published. The study was primarily intended to investigate the prevalence of chronic kidney disease (CKD) in the Spanish adult population. The EPIRCE is an observational, cross-sectional study that included a randomly selected sample of Spanish persons aged 20 years and older stratified by age, gender, and habitat. The present study was a secondary analysis of data from a survey of the Spanish general adult population (EPIRCE). However, it is well known that a biomarker’s performance and, by extension, its discriminatory capacity can be affected by covariates. In addition, in these studies the results have been reported without taking into account the possible effects of covariates on test results. However, no studies have examined the ability of proposed cutoff points to identify risk of clinically relevant outcomes. Table 1 shows the cut-off values, as can be seen in most of cases the cutoff point’s determination were made on the percentile criterion (80 or 90 according to studies) of values in the general population. Population based studies for defining cut-off values of HOMA-IR for the diagnosis of IR had been conducted in different geographic areas. However, there is great variability in the threshold HOMA-IR levels to define IR. The Homeostasis Model Assessment of IR (HOMA-IR) has proved to be a robust tool for the surrogate assessment of IR. The worldwide prevalence of these factors has risen dramatically in recent decades. Metabolic syndrome (MetS) definition is widely used as a practical tool to describe a cluster of clinical signs (central obesity, dyslipidemia, impaired glucose metabolism, and elevated blood pressure) that regardless of cause, identifies individuals at risk of atherosclerotic cardiovascular disease (CVD), and DM2. Insulin resistance (IR) has been proposed, more than a primary cause, as a sort of final common pathway for negative environmental factors, which interact with the individual genetic background to cause metabolic and hemodynamic alterations and is associated with inflammation. Insulin resistance (IR) is a feature of disorders such as diabetes mellitus type 2 (DM2) and is also implicated in obesity, hypertension, cancer or autoimmune diseases. The threshold levels must be modified by age in non-diabetic women. The consideration of the cardio metabolic risk to establish the cut-off points of HOMA-IR, to define insulin resistance instead of using a percentile of the population distribution, would increase its clinical utility in identifying those patients in whom the presence of multiple metabolic risk factors imparts an increased metabolic and cardiovascular risk. All values are between 70th-75th percentiles of HOMA-IR levels in adult Spanish population. ![]() In non-diabetic men, the cut-off values were 1.85. ![]() In non-diabetic women, but no in men, we found a significant non-linear effect of age on the accuracy of HOMA-IR. In Spanish population the threshold value of HOMA-IR drops from 3.46 using 90th percentile criteria to 2.05 taking into account of MetS components. ROC regression methodology was used to evaluate the effect of age on HOMA-IR performance in classifying cardio metabolic risk. The effect of age was analyzed in individuals with and without diabetes mellitus separately. As an accurate indicator of cardio metabolic risk, Metabolic Syndrome (MetS), both by International Diabetes Federation criteria and by Adult Treatment Panel III criteria, were used. It included 2459 adults (range 20–92 years, 58.4% women) in a random Spanish population sample. The purpose of this study was to describe the influence of age and gender in the estimation of HOMA-IR optimal cut-off values to identify subjects with higher cardio metabolic risk in a general adult population. There is great variability in the threshold homeostasis model assessment of insulin resistance (HOMA-IR) levels to define insulin resistance. Insulin resistance has been associated with metabolic and hemodynamic alterations and higher cardio metabolic risk. ![]()
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