Optimal insulin sensitivity -
Further, several forms of exercise have been linked to subsequent impairment of counterregulatory response in patients with T1D 13 such that overly aggressive insulin administration to correct postexercise hyperglycemia may lead to delayed or nocturnal hypoglycemia.
Currently, the postexercise hyperglycemia associated with HIIT has not been fully characterized, and its treatment remains an enigma. A recently published consensus statement on exercise management in T1D 7 provided only a brief mention of the hyperglycemia characteristic of HIIT exercise and only very limited guidance for the insulin therapy response.
The study was conducted in compliance with the ethics principles of the Declaration of Helsinki and in compliance with all International Council on Harmonisation Good Clinical Practice Guidelines. An independent ethics committee approved the protocol NCT , and written informed consent was obtained from all study participants.
Patients were excluded if they were following a very-low-calorie or other weight loss diet, had had one or more episodes of severe hypoglycemia during the past 6 months, had hypoglycemia unawareness, were pregnant or lactating, or had active diabetic retinopathy or unstable cardiovascular disease.
Use of β-blockers or any noninsulin diabetes therapy was also excluded. The ICF chosen was monitored and adjusted over the course of the run-in period.
Patients inserted a new CGM sensor 24—72 h before each exercise session, avoided exercise in the 24 h prior to exercise, and took their usual basal insulin dose the evening prior.
On the morning of each exercise session, patients remained fasting except for water and were assessed for blood pressure, heart rate HR , weight, waist circumference, and body fat percentage.
Blood was collected for glucose, insulin, catecholamines, ketones, growth hormone, lactate, and free fatty acids. For the first and last 5-min bouts of HIIT, a cycle ergometer was used.
The middle exercise bout used a rotation of typical HIIT-type exercises including spot marching with hand weights, jumping jacks, burpees, push-ups, forearm plank, and medicine ball sweep. Each exercise was undertaken for 20 s, and the circuit was repeated twice. HR, blood pressure, and capillary glucose were measured and blood was drawn in each rest period, with continuous monitoring of HR Polar heart rate monitor , ventilation, and oxygen consumption BioHarness 3.
Patients also provided frequent assessments of their ratings of perceived exertion Borg 6—20 scale. Blood was drawn at baseline, 25 min, and 40 min for standard clinical-grade measurement of plasma insulin, ketone bodies, free fatty acids, catecholamines, and growth hormone LifeLabs International Reference Laboratory, Toronto, Ontario, Canada.
Venous blood was also collected at regular intervals see below throughout the study, and plasma was isolated and batch-assayed for glucose and lactate concentrations Yellow Springs Instrument [YSI], Yellow Springs, OH. PG and lactate were measured every 15 min until a standardized meal was provided at min postinsulin correction 0.
Secondary end points included the postprandial meal excursion after the first standardized meal and CGM parameters during the 3-h and the h postexercise periods following the bolus insulin correction including: mean glucose; percentage of time in range 4. To determine a clinically significant reduction in PG of 0.
Baseline characteristics are reported as mean ± SD for continuous variables and as counts percentages for categorical variables.
The primary end point was analyzed with a mixed-effects model with repeated measures, with intervention as a fixed effect, subject as a random effect, and baseline glucose pre-exercise glucose value as a covariate.
The secondary end points of percentage of time spent in hyperglycemia, euglycemia, and hypoglycemia were analyzed with mixed-effects models with repeated measures, with intervention as a fixed effect and subject as a random effect.
All differences between interventions were tested with a two-sided α of 0. Two patients withdrew owing to employment change and residency change, respectively , leaving 17 patients to be assessed for the primary end point baseline characteristics in Table 1.
Patients were otherwise included if they completed two or more of the HIIT sessions. Across all sessions, the pre-exercise mean ± SE PG at baseline was 8.
The mean PG increased to The least squares mean difference in PG from baseline to 40 min was 3. DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; ITT, intention to treat; SBP, systolic blood pressure.
At 40 min, individualized insulin correction boluses were given, subject to multiplier for the respective correction arm. At min after the postexercise bolus insulin correction, adjusted mean ± SE PG was significantly reduced Fig.
PG during exercise and 3-h postbolus insulin correction in the four interventions. At 3-h postinsulin correction, following the standardized meal provided, the 3-h postmeal PG excursions were typical, ranging from 1.
Analysis of CGM data Fig. Percentage time spent in normoglycemia A and in hyperglycemia B following insulin correction. Data are presented as mean ± SE. Hrs, hours. In continual observation over the entire h extended period Fig. By the final 8 h of the observational period, which occurred overnight between p.
and a. Hypoglycemia events were rare during the 3-h period following the bolus insulin correction in all interventions Table 2. When hypoglycemia did occur, it was more frequent during the daytime 21 events between a.
and p. compared with the overnight period six events between p. There were no events of severe hypoglycemia. Incidence of total hypoglycemia, daytime hypoglycemia, and nighttime hypoglycemia following correction of postexercise hyperglycemia.
There were no serious adverse events associated with HIIT or with insulin treatment in the exercise visits. Ketone levels were measured during exercise and declined slightly but significantly from 0.
Lactate levels rose significantly with exercise from 1. There were no differences between the correction arms. Insulin levels also rose slightly but significantly during and immediately after exercise from Catecholamine and growth hormone levels both rose with HIIT but did not differ between groups.
Norepinephrine and growth hormone increased from baseline 2. Epinephrine levels were 0. HIIT is a popular form of exercise that has grown in prevalent use. Despite the growing awareness regarding the safety of HIIT in T1D, none of these statements have provided insulin- or carbohydrate-management guidance to control glycemia before or after HIIT.
This study was the first to investigate several glycemic control options following HIIT for individuals living with T1D using multiple daily injections. We found that, following a standardized min HIIT exercise session in aerobically fit individuals with T1D, a significant degree of immediate postexercise hyperglycemia mean increase of 3.
Optimal approach to insulin therapy was tested using four different multipliers of the ICF of post-HIIT hyperglycemia.
Interestingly, the nocturnal period after HIIT, which represented the final 8 h of observation, showed similar glycemic control between all intervention arms. However, care should be taken to monitor for increased risk for late-onset hypoglycemia. High-intensity aerobic exercise activities, including HIIT, have been shown in prior investigation to be attributable to a typical, and possibly increased, degree of glucose production during the exercise, followed by a reduced level of glucose utilization, compared with moderate exercise 4 , 8.
High-intensity exercise has similarly been associated with a marked increase in catecholamine production, which may restrict glucose uptake by skeletal muscle 17 , a phenomenon that can be reproduced with catecholamine infusion without exercise In subjects without diabetes, the resulting hyperglycemia leads to insulin release, accelerating glucose disposal; patients with T1D are unable to endogenously respond with insulin production, but exogenously infused insulin has also been shown to attenuate the postexercise hyperglycemia Interestingly, insulin levels did show a marginal increase during exercise in this study, likely representing redistribution from a subcutaneous depot of previously injected basal insulin.
This finding has been observed with prolonged moderate-intensity aerobic exercise in individuals using continuous subcutaneous insulin infusion 19 , even if basal insulin levels had been lowered in anticipation of exercise The increased insulin levels did not prevent the expected postexercise hyperglycemia in this study but may contribute to exercise-associated hypoglycemia seen with moderate-intensity aerobic activity.
Surgical intervention in the form of gastric sleeves, banding, and bypass is available for qualified individuals with obesity. The excess fat loss associated with bariatric surgery improves insulin sensitivity. The results of the STAMPEDE trial provide good evidence of the benefit of bariatric surgery on T2D.
The prognosis of insulin resistance depends on the subset of the disease, the severity of the disease, underlying pancreatic beta-cell function, the heritable susceptibility of the patient to the secondary complications from insulin resistance, and individual response to appropriate therapy.
The outcomes range from mildly insulin-resistant, asymptomatic individuals to those with catastrophic cardiovascular or cerebrovascular events and their resulting morbidity and mortality. Statistically, coronary artery disease is the leading cause of mortality in the US, with diabetes as seventh.
The common basis for diabetes and much of the resultant vascular disease is insulin resistance. Additional mortality from insulin resistance occurs in the less common manifestations of the disease, including genetic syndromes and fatty deposition diseases. Finally, substantial morbidity manifests with the loss of reproductive function and associated features of PCOS.
Mitigation for the disease exists. Increased clinical awareness enables early diagnosis and treatment. Improved understanding of the disease process has resulted in more targeted, multi-faceted therapies.
Efforts to attain and maintain a healthy weight through improved dietary intake and increased physical activity can reduce insulin resistance and prevent associated complications. More generalized lay recognition can increase the efficacy of preventative care, with the hope of an eventual downturn in epidemic obesity and resultant insulin resistance.
Most of the complications from insulin resistance are related to the development of vascular complications. The microvascular disease manifests as retinopathy, nephropathy, and peripheral neuropathy.
In the central nervous system, dementia, stroke, mood disturbance, and gait instability may occur. Cardiac microvascular disease can manifest as angina, coronary artery spasm, and cardiomyopathy.
Renal microvascular disease is a significant cause of chronic kidney disease, renal failure, and dialysis. Ophthalmological small vessel disease is a leading cause of retinopathy and visual impairment. Macrovascular disease, secondary to insulin resistance, causes PAD, CAD, and CVA.
Non-alcoholic fatty liver disease NAFLD is intricately related to insulin resistance and T2D. Patients with T2D have a 2-fold increased risk for NAFLD. With an increasing worldwide prevalence and incidence in children, NAFLD should be of great concern to clinicians treating patients with insulin resistance.
Primary prevention promotes public education regarding the importance of regular health monitoring. A healthy diet and increased activity level can prevent or delay the onset of insulin resistance, metabolic syndrome, and diabetes, along with the associated complications.
The emphasis on behavior modification and a sustainable lifestyle is critical for long-term weight management. Secondary prevention includes laboratory screening for insulin resistance, diabetes, and further subspecialist referral to manage the early intervention for insulin resistance.
Public acceptance of tertiary prevention, such as intensive medical intervention and bariatric surgery for weight reduction, can lead to decreased morbidity and mortality associated with the consequent complications of insulin resistance.
Intensive lifestyle intervention should be the first line of therapy for patients with metabolic syndrome or insulin resistance syndrome.
The benefits of exercise cannot be understated in treating patients with insulin resistance. Barriers to exercise should be discussed, and a well-formulated plan, including moderate-intensity cardiovascular exercise like walking, should be provided in accordance with the physical activity guidelines.
Discussion of dietary modification following the dietary guidelines should also be provided with individualization to the patient's preferences, with particular attention to reducing sugar, refined grain products, and high glycemic index carbohydrates.
Over the past few decades, the incidence of insulin resistance has skyrocketed primarily due to our lifestyle and the rising incidence of obesity. Without treatment, the condition is associated with numerous complications, including fatal cardiac events. Therefore, the management of insulin resistance is best done with an interprofessional team.
The consultations and coordination of care most indicated for the treatment of insulin resistance include:. There is limited evidence in favor of continuous glucose monitoring CGM. Remote monitoring for healthcare teams shows benefits in the management of T2D.
More research is needed to show the effects of CGM on those with prediabetes or insulin resistance without T2D. The key to the management of insulin resistance is encouraging lifestyle changes. Dietary intervention should include a combination of calorie restriction and reduction of high glycemic index carbohydrates.
The outcomes of well-managed insulin resistance are good for those who remain adherent to therapy. Unfortunately, many patients struggle with adherence to therapy, with consequential progression to T2D and subsequent risk of adverse cardiac or CNS events.
Early identification and intervention with an interprofessional team approach are essential in managing these patients. Disclosure: Andrew Freeman declares no relevant financial relationships with ineligible companies.
Disclosure: Luis Acevedo declares no relevant financial relationships with ineligible companies. Disclosure: Nicholas Pennings declares no relevant financial relationships with ineligible companies.
This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4. You are not required to obtain permission to distribute this article, provided that you credit the author and journal. Turn recording back on.
National Library of Medicine Rockville Pike Bethesda, MD Web Policies FOIA HHS Vulnerability Disclosure. Help Accessibility Careers. Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation. Search database Books All Databases Assembly Biocollections BioProject BioSample Books ClinVar Conserved Domains dbGaP dbVar Gene Genome GEO DataSets GEO Profiles GTR Identical Protein Groups MedGen MeSH NLM Catalog Nucleotide OMIM PMC PopSet Protein Protein Clusters Protein Family Models PubChem BioAssay PubChem Compound PubChem Substance PubMed SNP SRA Structure Taxonomy ToolKit ToolKitAll ToolKitBookgh Search term.
StatPearls [Internet]. Treasure Island FL : StatPearls Publishing; Jan-. Show details Treasure Island FL : StatPearls Publishing ; Jan-. Search term. Insulin Resistance Andrew M. Author Information and Affiliations Authors Andrew M.
Affiliations 1 Southeastern Regional Medical Center. Continuing Education Activity Insulin resistance, identified as an impaired biologic response to insulin stimulation of target tissues, primarily involves liver, muscle, and adipose tissue.
Introduction Insulin resistance is identified as the impaired biologic response of target tissues to insulin stimulation. Etiology The etiologies of insulin resistance may be acquired, hereditary, or mixed.
Medications glucocorticoids, anti-adrenergic, protease inhibitors, selective serotonin reuptake inhibitors, atypical antipsychotics, and some exogenous insulins.
Type-A insulin resistance: Characterized by severe insulin resistance abnormal glucose homeostasis, ovarian virialization, and acanthosis nigricans caused by abnormalities of the insulin receptor gene. Type-B insulin resistance: Characterized severe impairment of insulin action triggered by the presence of insulin receptor autoantibodies with resultant abnormal glucose homeostasis, ovarian hyperandrogenism, and acanthosis nigricans.
Epidemiology Epidemiologic assessment of insulin resistance is typically measured in relation to the prevalence of metabolic syndrome or insulin resistance syndrome. Pathophysiology The 3 primary sites of insulin resistance are the skeletal muscle, liver, and adipose tissue.
History and Physical The clinical presentation of insulin resistance is variable concerning both history and physical examination findings.
Common presentations include: Associated Diseases Non-alcoholic fatty liver disease NAFLD. Evaluation The gold standard for measuring insulin resistance is the hyperinsulinemic-euglycemic glucose clamp technique.
Elevated blood pressure greater than or equal to mm Hg systolic or greater than or equal to 85 mm Hg diastolic or on antihypertensive medication. Metformin is a common first-line therapy for medication treatment of T2D and is approved for use in PCOS. Despite the concerns about using metformin in mild to moderate renal dysfunction, several organizations, including the American Geriatric Society and the Kidney Disease Improving Global Outcomes guidelines, endorse use as long as the GFR exceeds Glucagon-like peptide one GLP-1 receptor agonists stimulate the GLP-1 receptors in the pancreas, thereby increasing insulin release and inhibiting glucagon secretion.
The use of GLP-1 agonists is associated with weight loss, which may reduce insulin resistance. Liraglutide and semaglutide are FDA-approved for the treatment of T2D and obesity. Another agent, tirzepitide, is a dual GLP-1 and gastric inhibitory polypeptide GIP agonist, has effects similar to semaglutide, and is also FDA-approved for treating T2D.
Sodium-glucose cotransporter 2 SGLT2 inhibitors increase urinary glucose excretion, thereby reducing plasma glucose levels and exogenous insulin requirements. The use of SGLT2 inhibitors has also been associated with weight loss, which may reduce insulin resistance.
Thiazolidinediones improve insulin sensitivity and glucose control by increasing insulin-dependent glucose disposal in skeletal muscle and adipose tissue and decreasing hepatic glucose output. Though effective, associated secondary weight gain and fluid retention, with associated cardiovascular concerns, limit their use.
Dipeptidyl peptidase-4 DPP-4 inhibitors prolong the activity of endogenous GLP-1 and GIP by preventing their breakdown. Differential Diagnosis Lipodystrophy acquired, localized or generalized : Loss of adipose tissue that results from either genetic or acquired causation and can result in the ectopic deposition of fat in either hepatic or muscular tissue [56].
Obesity: Excess body weight is categorized as overweight BMI of 25 to Other forms of glucose intolerance impaired fasting glucose, impaired glucose tolerance, and gestational diabetes.
Prognosis The prognosis of insulin resistance depends on the subset of the disease, the severity of the disease, underlying pancreatic beta-cell function, the heritable susceptibility of the patient to the secondary complications from insulin resistance, and individual response to appropriate therapy.
Complications Most of the complications from insulin resistance are related to the development of vascular complications. Deterrence and Patient Education Primary, secondary, and tertiary prevention have distinct roles in managing insulin resistance.
Pearls and Other Issues Intensive lifestyle intervention should be the first line of therapy for patients with metabolic syndrome or insulin resistance syndrome. Enhancing Healthcare Team Outcomes Over the past few decades, the incidence of insulin resistance has skyrocketed primarily due to our lifestyle and the rising incidence of obesity.
The consultations and coordination of care most indicated for the treatment of insulin resistance include: Obesity medicine specialist: medical management for obesity treatment. Bariatric surgeon: bariatric surgery is effective for obesity treatment in individuals who satisfy the criteria for surgery.
Cardiology and cardiac surgery: management of the cardiovascular complications of insulin resistance. Neurology: management of the cerebrovascular and peripheral neurologic complications of insulin resistance.
Pharmacist: educates the patient on the importance of medication adherence, instructing the patient on the proper use of medications, potential drug-drug interactions, and side effects.
Review Questions Access free multiple choice questions on this topic. Comment on this article. Figure Acanthosis Nigricans Contributed by Scott Dulebohn, MD. References 1. Seong J, Kang JY, Sun JS, Kim KW. Hypothalamic inflammation and obesity: a mechanistic review.
Arch Pharm Res. Brown JC, Harhay MO, Harhay MN. The Value of Anthropometric Measures in Nutrition and Metabolism: Comment on Anthropometrically Predicted Visceral Adipose Tissue and Blood-Based Biomarkers: A Cross-Sectional Analysis.
Nutr Metab Insights. Nolan CJ, Prentki M. Insulin resistance and insulin hypersecretion in the metabolic syndrome and type 2 diabetes: Time for a conceptual framework shift. Diab Vasc Dis Res. Deacon CF. Physiology and Pharmacology of DPP-4 in Glucose Homeostasis and the Treatment of Type 2 Diabetes.
Front Endocrinol Lausanne. Thomas DD, Corkey BE, Istfan NW, Apovian CM. Hyperinsulinemia: An Early Indicator of Metabolic Dysfunction. J Endocr Soc. Hossan T, Kundu S, Alam SS, Nagarajan S.
Epigenetic Modifications Associated with the Pathogenesis of Type 2 Diabetes Mellitus. Endocr Metab Immune Disord Drug Targets. Bothou C, Beuschlein F, Spyroglou A. Links between aldosterone excess and metabolic complications: A comprehensive review.
Diabetes Metab. 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. Levy JC, Matthews DR, Hermans MP.
Correct homeostasis model assessment HOMA evaluation uses the computer program. Diabetes Care. Katz A, Nambi SS, Mather K, Baron AD, Follmann DA, Sullivan G, Quon MJ. Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans.
J Clin Endocrinol Metab. Kim-Dorner SJ, Deuster PA, Zeno SA, Remaley AT, Poth M. Should triglycerides and the triglycerides to high-density lipoprotein cholesterol ratio be used as surrogates for insulin resistance?
Tobin GS, Cavaghan MK, Hoogwerf BJ, McGill JB. Addition of exenatide twice daily to basal insulin for the treatment of type 2 diabetes: clinical studies and practical approaches to therapy.
Int J Clin Pract. Abdul-Ghani M, DeFronzo RA. Insulin Resistance and Hyperinsulinemia: the Egg and the Chicken. Laursen TL, Hagemann CA, Wei C, Kazankov K, Thomsen KL, Knop FK, Grønbæk H.
Bariatric surgery in patients with non-alcoholic fatty liver disease - from pathophysiology to clinical effects. Each of these tests has been shown to correlate reasonably well with dynamic clamp techniques.
Hyperinsulinemic-euglycemic clamp : The gold standard for evaluating insulin sensitivity, this "clamp" technique requires a steady IV infusion of insulin to be administered in one arm. The serum glucose level is "clamped" at a normal fasting concentration by administering a variable IV glucose infusion in the other arm.
Numerous blood samplings are then taken to monitor serum glucose so that a steady "fasting" level can be maintained. In theory, the IV insulin infusion should completely suppress hepatic glucose production and not interfere with the test's ability to determine how sensitive target tissues are to the hormone.
The degree of insulin resistance should be inversely proportional to the glucose uptake by target tissues during the procedure. In other words, the less glucose that's taken up by tissues during the procedure, the more insulin resistant a patient is. A variation of this technique, the hyperinsulinemic-hyperglycemic clamp provides a better measurement of pancreatic beta cell function but is less physiologic than the euglycemic technique.
Insulin sensitivity test IST : IST involves IV infusion of a defined glucose load and a fixed-rate infusion of insulin over approximately 3 hours. Somatostatin may be infused simultaneously to prevent insulin secretion, inhibit hepatic gluconeogenesis, and delay secretion of counter-regulatory hormones— particularly glucagon, growth hormone, cortisol, and catecholamines.
Fewer blood samples are required for this test, compared to clamp techniques. The mean plasma glucose concentration over the last 30 minutes of the test reflects insulin sensitivity.
Although lengthy, IST is less labor intensive than clamp techniques and the FSIVGTT. Insulin tolerance test ITT : A simplified version of IST, ITT measures the decline in serum glucose after an IV bolus of regular insulin 0.
Several insulin and glucose levels are sampled over the following 15 minutes depending on the protocol used. The ITT primarily measures insulin-stimulated uptake of glucose into skeletal muscle.
Because this test is so brief, there's very little danger of counter-regulatory hormones interfering with its results. IV access should be established for insulin injection, blood sampling, and for rapid administration of D50W should severe hypoglycemia occur.
These values reflect the rate of decline of log transformed glucose values. Frequently sampled IV glucose tolerance tests FSIVGTT. This method is less labor intensive than clamp techniques yet still requires as many as 25 blood samples over a 3-hour period, and a computer-assisted mathematical analysis.
Several variations of the FSIVGTT have been published. One recently published study infused 0. The SI was calculated by a computer-based program. Tolbutamide administration can also be used during FSIVGTT to augment endogenous insulin secretion and is particularly useful in women with diabetes.
Continuous infusion of glucose with model assessment CIGMA : Like ITT, CIGMA requires fewer venipunctures and is less laborious than clamp techniques. A constant IV glucose infusion is administered, and samples for glucose and insulin are drawn at 50, 55, and 60 minutes.
A mathematical model is then used to calculate SI. The results are reasonably compatible with clamp techniques; however, few laboratories have used CIGMA for insulin sensitivity testing in diabetic patients and there is no substantive data using the CIGMA technique in women with PCOS.
units here. HOMA-IR stands for Homeostatic Antioxidant-rich antioxidant capacity O;timal of Insulin Resistance. Senstiivity calculation Antioxidant-rich antioxidant capacity for both the presence and extent of any insulin resistance that you might currently express. You can visit TheBloodCode. com to plug in your values and get the calculation. Insulin is a Seensitivity that is Green tea extract for respiratory health for managing blood sugar levels. Insulin sensitivit factor, or correction factor, refers to how much one unit of Antioxidant-rich antioxidant capacity can lower blood Optimall levels. Carbohydrate Fermentation cells ihsulin the pancreas produce Organic remedies for skincare Optimall release it into the bloodstream after people eat. Insulin enables body cells — such as muscle, fat, and heart cells — to absorb the sugar from food and use it for energy and other essential processes. When a person eats, they do not immediately use all the energy they get from a meal. Insulin helps the body to store glucose in the liver as glycogen. The liver releases it when blood sugar levels are low, or when a person needs more energy.Insuljn insulin's role isulin metabolic health is Optial for overall well-being insuiln maintaining a healthy insulni. In current research and clinical practice, there is sensitiviry consensus yet on what optimal insukin levels are, sehsitivity testing is often inaccessible.
We can, however, use glucose levels as a proxy for insulin sensitivity. Insulin Prevent muscle soreness after exercise a hormone produced Optimxl the pancreas that inuslin a critical role in regulating blood glucose levels by facilitating its absorption.
Insulin acts as a key that unlocks the cells, allowing glucose from the bloodstream to sesnitivity and provide energy for cells [1].
Maintaining your blood glucose levels within a normal ijsulin is crucial for metabolism and overall health, swnsitivity it makes sense that having OMAD and energy levels insulin Thirst-quenching goodness is also important for metabolic health.
Sensitivihy the Optimal insulin sensitivity between insulin and Moderate drinking guidelines becomes dysregulatedmetabolic issues can arise [2].
Insulin resistance occurs when cells in your body become less Optimal insulin sensitivity to the action of insulin. This Prediabetes statistics of responsiveness makes it difficult for cells to absorb glucose, causing an increase in blood glucose Satiety enhancing ingredients. Insulin resistance is often associated wensitivity conditions such as Type 2 diabetes and metabolic syndrome [3].
Contrary to what has been previously Hypertension and digestive health, hyperinsulinemia high insulin Performance testing case studies can precede insulin resistance and senditivity starting to be Opimal heavily researched as sensltivity initial indicator of metabolic dysregulation.
If Antioxidant-rich antioxidant capacity levels sensitiviry constantly too high, then something may be awry insulni your metabolism [4, 5]. Insulin Body toning with kettlebells can be measured using Digestive aid for healthy gut flora fasting insulin test sensitivty.
The main purpose of Opimal test is to assess how zensitivity body is producing, processing, sensitvity regulating insulin [7]. This inulin measures the amount Optimql insulin in a person's blood after an overnight fast around sensitiivity without eating.
Similar to the process in ibsulin A1C testyour healthcare professional will collect a small sample of Otpimal, Antioxidant-rich antioxidant capacity send Opgimal to a lab for analysis. Controlling blood pressure naturally, low levels might point toward Type 1 insulim or hyperglycemia [6, 7].
Fasting insulin tests sensltivity not semsitivity as frequently as sesitivity Organic remedies for skincare glucose levels because the reference Ophimal for insulin levels are Optimall as ijsulin established. There is also sensittivity lack insupin standardization sensiyivity methods for testing and ineulin fasting insulin which could definitely add Optikal the sensitiviyy of establishing reference Antispasmodic Treatments for Gastrointestinal Issuesand potential issues insluin health insurance coverage sesitivity the lab test itself lab tests can be expensive.
Sensitivitty the other Optimal insulin sensitivity, glucose testing has sensiitivity extensively researched and validated over decades of research, with seensitivity thresholds Optimaal guidelines sensitivitg diagnosing diabetes and sensitviity glycemic control.
Optinal on testing glucose in started the mids, with urine glucose testing becoming available in and Otpimal glucose testing first sensitivlty in [12].
With over 50 years sesitivity patient use, blood glucose sensitivitty is a standard practice in healthcare Optiimal. While fasting Clear complexion secrets levels can provide valuable insights Opfimal insulin resistance insu,in early-stage sensitivify, Antioxidant-rich antioxidant capacity interpretation sensitiivity these insklin is not standardized.
There is less consensus among medical professionals on diagnosing sennsitivity resistance based Prebiotics and gut health fasting insulin levels.
One major reason is the variability in sensifivity and analysis of MRI for liver disease insulin tests, as found by the Insuljn Diabetes Association [13]. As confirmed by a separate studytesting of identical Optumal samples resulted in varied reported insulin level values.
This continued ihsulin of consensus in testing and standardized guidelines makes it difficult for clinicians to sensiitivity insulin levels senzitivity a measure for diagnosis of disease and prescribing coping mechanisms for anxiety interventions [14].
Additionally, major health Citrus aurantium for athletic performance, such as the American Diabetes Association ADA and the United States Preventive Services Task Force USPSTFdo not currently include insulin level measurements or direct recommendations for measuring fasting insulin levels in their guidelines [15, 16].
Much of the focus in medicine is on detecting late-stage insulin resistance, which is seen with hyperglycemia high blood sugar levels. This is largely a byproduct of the way our healthcare system is structured, where clinical care emphasizes putting out fires only offering treatment once a patient has been diagnosed with Type 2 diabetes or pre-diabetes rather than preventing them.
The problem is that in its early stages, insulin resistance can manifest as normal blood sugar levels but high fasting insulin levels called hyperinsulinemic normoglycemia [17].
A fasting insulin test is particularly valuable for individuals who are at risk for developing insulin resistance, such as those who are overweight or obese but do not yet have prediabetes or diabetes.
The test can help identify if your body is producing higher levels of insulin to compensate for a reduced response to its action — a key marker of developing insulin resistance and other related metabolic issues [4]. In other words, understanding insulin levels can be useful in both early and late-stage disease.
In early-stage insulin resistance, where blood sugar levels are still within the normal range, elevated fasting insulin levels can indicate underlying issues. Knowing early could prompt intervention to prevent the progression of metabolic dysregulation.
Despite this, fasting insulin testing may not be immediately recommended by your healthcare provider unless there is a specific clinical indication or suspicion of metabolic dysfunction. Glucose tests, rather than fasting insulin tests, are generally the first-line approach because of their accessibility, reliability, and convenience.
When it comes to insulin levels, there are no universally established normal values. The concept of "optimal" fasting insulin levels is not as straightforward as it may seem—which adds further to the lack of use and reliability.
Insulin levels, like glucose levels, are context-dependent and can vary depending on various factors such as the time of measurement, individual characteristics, or fed state fasting vs. after eating [1]. Also, like glucose, insulin levels fluctuate throughout the day to accommodate for stimuli like stress or physical activity.
Even the type of test used can influence the measured insulin levels [13, 14]. Research in has shown promise for establishing optimal ranges. Research in Chinese men found that fasting insulin levels fell in the range of 1. Another studylooking at over 4, non-diabetic people with low blood glucose levels, showed women aged years old had a median fasting insulin level of 5.
In older adults — year-old non-diabetics — the interval for fasting insulin levels was found to be 1. That said, there is some consensus in the medical community around what might be considered ideal, good, fair, and probable insulin resistance in terms of fasting insulin levels:.
However, it's important to remember that these ranges are not definitive, and results should always be interpreted in the context of the individual's overall health, symptoms, risk factors, and other test results.
While getting an insulin test may be challenging due to factors like out-of-pocket cost, accessibility, or reliability in results, glucose monitoring can be a practical alternative to understanding your insulin sensitivity.
Blood glucose levels are a key indicator of how your body processes food for energy and how effectively insulin is functioning in your body. Sustained high glucose levels often indicate that your body is struggling to effectively utilize insulin, which can suggest insulin resistance [1].
Continuous glucose monitors CGMs make it easy to track glucose levels throughout the day. Unlike a fasting insulin test, which provides a single snapshot in time, CGMs provide real-time information about glucose levels. By constantly monitoring your glucose, you can gain insights into how different factors such as meals, physical activity, stress, and sleep affect your glucose levels.
This gives a comprehensive picture of your body's metabolic response and can help pinpoint areas for improvement.
CGMs allow you to monitor several critical markers of glucose regulation: average glucose levels, glucose variability, and fasting glucose levels. A higher average glucose level or drastic variability can be indicative of metabolic issues.
By correlating these glucose metrics with the Four Pillars of metabolic health — nutrition, exercise, stress management, and sleep—you can build healthier habits and make targeted lifestyle modifications.
For example, you might notice certain foods cause a spike in glucose levels and opt to limit them in your diet, or you might find that light physical activitylike walking, helps in maintaining more stable glucose levels.
Insulin's critical role in glucose regulation, the implications of insulin resistance, and the relevance of fasting insulin tests encompass an essential part of metabolic health. Metabolic Health. What Are Optimal Fasting Insulin Levels for Metabolic Health?
Insulin: the hormone that regulates glucose Insulin is a hormone produced by the pancreas that plays a critical role in regulating blood glucose levels by facilitating its absorption.
How we test for insulin levels Insulin levels can be measured using a fasting insulin test [6]. HOMA-IRor homeostasis model of insulin resistance [10]. QUICKIor quantitative insulin sensitivity check index [11].
This is a variation of the HOMA-IR equation that is used to determine insulin sensitivity. Who should get a fasting insulin test A fasting insulin test is particularly valuable for individuals who are at risk for developing insulin resistance, such as those who are overweight or obese but do not yet have prediabetes or diabetes.
What are normal or optimal fasting insulin levels? Using glucose levels as a marker of insulin resistance and metabolic health While getting an insulin test may be challenging due to factors like out-of-pocket cost, accessibility, or reliability in results, glucose monitoring can be a practical alternative to understanding your insulin sensitivity.
Key Takeaways Insulin's critical role in glucose regulation, the implications of insulin resistance, and the relevance of fasting insulin tests encompass an essential part of metabolic health. It is particularly valuable for individuals who are at risk for insulin resistance but do not have prediabetes or diabetes.
Insulin tests are not conducted as frequently as glucose tests due to various factors including less established reference ranges and the focus of current guidelines on later-stage insulin resistance.
When a fasting insulin test isn't feasible, tracking glucose levels can provide valuable insights into insulin sensitivity, resistance, and overall metabolic health. Glucose monitoring can serve as a valuable proxy for understanding insulin sensitivity.
Continuous glucose monitors CGMs allow real-time tracking of glucose levels, enabling the correlation of glucose metrics with lifestyle factors and helping to prevent insulin resistance. Written by: Sarah Jayawardene, MS. Reviewed by: Emily Johnson, MSc RD.
Table of Contents Insulin: the hormone that regulates glucose How we test for insulin levels What are normal or optimal fasting insulin levels? Using glucose levels as a marker of insulin resistance and metabolic health Key Takeaways.
: Optimal insulin sensitivity| Introduction | Do HD, Lohsoosthorn V, Jiamjarasrangsi W, Lertmaharit S, Williams MA: Prevalence of insulin resistance and its relationship with cardiovascular disease risk factors among Thai adults over 35 years old. Article CAS PubMed PubMed Central Google Scholar. Bonora E, Kiechl S, Willeit J, Oberhollenzer F, Egger G, Targher G, Alberiche M, Bonadonna RC, Muggeo M: Prevalence of insulin resistance in metabolic disorders. Nakai Y, Fukushima M, Nakaishi S, Kishimoto H, Seino Y, Nagasaka S, Sakai M, Taniguchi A: The threshold value for insulin resistance on homeostasis model assessment of insulin sensitivity. Pepe MS: The Statistical Evaluation of Medical Tests for Classification and Prediction. Gayoso-Diz P, Otero-González A, Rodriguez-Alvarez MX, Gude F, Cadarso-Suarez C, García F, De Francisco A: IR index HOMA-IR levels in a general adult population: curves percentile by gender and age. The EPIRCE study. Otero A, Gayoso P, García F, De Francisco AL: Epidemiology of chronic renal disease in the Galician population: results of the pilot Spanish EPIRCE study. Kidney Int. Otero A, De Francisco A, Gayoso P, Garcia F: Prevalence of chronic renal disease in Spain: results of the EPIRCE Study. PubMed Google Scholar. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC: Homeostasis model assessment: IR and beta-cell function from fasting plasma glucose and insulin concentration in man. Alberti KG, Zimmet P, Shaw J: IDF Epidemiology task force consensus group. The metabolic syndrome: a new world - wide definition. 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. Rodríguez-Álvarez MX, Roca-Pardiñas J, Cadarso-Suárez C: ROC curve and covariates: extending induced methodology to the non-parametric framework. Stat Comput. Faraggi D: Adjusting receiver operating characteristic curves and related indices for covariates. The Statistician. Rodríguez-Álvarez MX, Tahoces PG, Cadarso-Suárez C, Lado MJ: Comparative study of ROC regression techniques. Applications for the computer aided diagnostic system in breast cancer detection. Computational Statistics and Data Analysis. R Development Core Team. R: A Language and Environment for Statistical Computing R Foundation for Statistical Computing, Vienna, Austria. org ,. BMC Bioinforma. Esteghamati A, Ashraf H, Khalilzadeh O, Zandieh A, Nakhjavani M, Rashidi A, Haghazali M, Asgari F: Optimal cut-off of homeostasis model assessment of IR HOMA-IR for the diagnosis of metabolic syndrome: third national surveillance of risk factors of non-communicable diseases in Iran SuRFNCD Nutr Metab. Bertoni AG, Wong ND, Shea S, Ma S, Liu K, Preethi S, Jacobs DR, Wu C, Saad MF, Szkio M: Insulin resistance, metabolic syndrome and subclinical atherosclerosis: the Multi-Ethnic Study of Atherosclerosis MESA. Montecucco F, Steffens S, Mach F: Insulin resistance: a proinflammatory state mediated by lipid-induced signaling dysfunction and involved in atherosclerotic plaque instability. Mediators Inflamm. Miccoli R, Biamchi C, Odoguardi L: Prevalence of the metabolic syndrome among Italian adults according to ATPII definition. Nutr Metab Cardiovasc Dis. 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 Barc. Article CAS Google Scholar. Tomé MA, Botana MA, Cadarso-Suarez C, Rego-Irateta A, Fernandez-Mariño A, Mato JA, Solache I, Perez-Fernandez R: Prevalence of metabolic syndrome in Galicia NW Spain on four alternative definitions and association with insulina resistance. J Endocrinol Invest. Bonora E, Kiechl S, Willeit J, Oberhollenzer F, Egger G, Bonadonna RC, Muggeo M: Bruneck Study. Metabolic syndrome: epidemiology and more extensive phenotypic description. Cross-sectional data from Bruneck Study. Int J Obesity. Ford ES, Giles WH, Dietz WH: Prevalence of metabolic syndrome among US adults. Findings from the Third National Health and Nutrition Examination Survey. Download references. The coordinating investigators of EPIRCE Study group were: M. Álvarez-Lara; F. Vega; Laviades, P. Vives, J. Peña-Porta; J. Marco, A. Solís, A. Losada-González; G. Fernández-Fresnedo; J. Navarro, J. Sánchez-Joga; J. Fort, A. Martínez-Castelao, N. Fonseré; F. Tornero, M. Quintana; J. Grande-Villoria, A. Molina, B. Pozo, G. Torres; C. Fernández-Andrade; F. Vidaur, J. Manrique, M. Rodríguez; F. Caravaca, B. Cancho; A. Otero, L. González; A. Sánchez Casajús; F. García, M. San-Boixedau, K. López, E. Rubio, C. Bernis; M. Gironés; J. Asín; J. Hernández-Jaras, A. Rius, M. Instituto de Investigación Sanitaria de Santiago IDIS , Santiago de, Compostela, Spain. Nephrology Department, C. de Ourense, Ourense, Spain. Clinical Epidemiology Unit, Puerta de Hierro University Hospital, Madrid, Spain. Nephrology Department, Hospital Marques de Valdecilla, Santander, Spain. You can also search for this author in PubMed Google Scholar. Correspondence to Pilar Gayoso-Diz. PG conceived of the study, and participated in its design and coordination and helped to draft the manuscript. AO participated in the design of the study, have made substantial contributions to acquisition of data and helped to draft the manuscript MXRA performed the statistical analysis and helped to draft the manuscript. FGu, FGa, AF and AG participated in the analysis and interpretation of data and helped to draft the manuscript. All authors read and approved the final manuscript. This article is published under license to BioMed Central Ltd. Reprints and permissions. Gayoso-Diz, P. 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 13 , 47 Download citation. Received : 22 February Accepted : 18 September Published : 16 October Anyone you share the following link with will be able to read this content:. Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative. Skip to main content. Search all BMC articles Search. Download PDF. Abstract Background Insulin resistance has been associated with metabolic and hemodynamic alterations and higher cardio metabolic risk. Methods It included adults range 20—92 years, Results In Spanish population the threshold value of HOMA-IR drops from 3. Conclusions 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. Background 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 [ 1 — 3 ]. Table 1 Summary of reports sorted by sample size on HOMA-IR cut-off in different populations Full size table. Methods Setting The present study was a secondary analysis of data from a survey of the Spanish general adult population EPIRCE [ 25 , 26 ]. Definition of metabolic syndrome As an accurate indicator of cardio metabolic risk, MetS, both by the International Diabetes Federation IDF criteria and by the Adult Treatment Panel III ATP III criteria, were used. Statistical analyses Baseline subject characteristics are expressed as the mean ± SD or as percentages. Ethical considerations The Galician Ethical Committee for Clinical Research approved the study protocol. Results Table 2 summarizes anthropometric, clinical, and biochemical characteristics of the study sample. Figure 1. Full size image. Table 3 Performance of HOMA-IR values in the classification of cardio metabolic risk both ATPIII MetS and IDF MetS definition , influence of age and gender Full size table. Figure 2. Table 4 Gender distribution of HOMA-IR cut-off levels, with their corresponding sensitivity and specificity,for classify of IDF MetS and ATPIII MetS, in diabetic and non-diabetic individuals Full size table. Discussion Overall, in non-diabetic individuals the best HOMA-IR cut-off levels ranged from 1. Conclusions We propose the addition of the components of MetS analysis as a criterion to establish the cut-off points of HOMA-IR to define IR instead of using a percentile of the population distribution. References Rader DJ: Effect of insulin resistance, dyslipidemia, and intra-abdominal adiposity on the development of cardiovascular disease and diabetes mellitus. Google Scholar Goodwin P, Ennis M, Bahl M: High insulin levels in newly diagnosed breast cancer patients reflect underlying insulin resistance and are associated with components of the insulin resistance syndrome. Article CAS PubMed Google Scholar Seriolo B, Ferrone C, Cutolo M: Log term anti-tumor necrosis factor α-treatment in patients with refractory rheumatoid arthritis: relationship between insulin resistance and disease activity. CAS Google Scholar Chen J, Wildman RP, Hamm LL, Muntner P, Reynolds K, Whelton PK, He J: Third National Health and Nutrition Examination Survey. Article PubMed Google Scholar Eckel RH, Kahn R, Robertson RM, Rizza RA: Preventing cardiovascular disease and diabetes: a call for action from the American Diabetes Association and the American Heart Association. Article PubMed Google Scholar Kassi E, Pervanidou P, Kaltsas G, Chrousos G: Metabolic syndrome: definition and controversies. Article PubMed PubMed Central Google Scholar Eckel RH, Grundy SM, Zimmet PZ: The metabolic syndrome. Article CAS PubMed Google Scholar Alberti KJ, Eckel RH, Grundy SM, Zimmet PZ, Cleeman LJ, Donato KA, Fruchart JC, James WP, Loria CM, Smith SC: Harmonizing the metabolic syndrome: a join 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. Article PubMed Google Scholar Bray GA, Bellanger T: Epidemiology, trends and morbidities of obesity and the metabolic syndrome. Article CAS PubMed Google Scholar Danaei G, Finucane MM, Lu Y, Singh GM, Cowan MJ, Paciorek CJ, Lin JK, Farzadfar F, Khang Y-H, Stevens GA, Rao M, Ali MK, Riley LM, Robinson CA, Ezzati M: Global burden of metabolic risk factors of chronic diseases collaborating group Blood Glucose. Article CAS PubMed Google Scholar Finucane MM, Stevens GA, Cowan MJ, Danaei G, Lin JK, Paciorek CJ, Singh GM, Gutierrez HR, Lu Y, Bahalin AN, Farzadfar F, Riley LM, Ezzati M: Global burden of metabolic risk factors of chronic diseases collaborating group Body mass index. Article PubMed PubMed Central Google Scholar Lann D, LeRoith D: Insulin resistance as the underlying cause for the metabolic syndrome. Article CAS PubMed Google Scholar Hedblad B, Nilsson P, Janzon L, Berglund G: Relation between insulin resistance and carotid intima-media thickness and stenosis in non-diabetic subjects. Article CAS PubMed Google Scholar Summer AE, Cowie CC: Ethnic differences in the ability of triglyceride levels to identify insulin resistance. Article Google Scholar Geloneze B, Repetto EM, Geloneze SR, Tambascia MA, Ermetice MN: The threshold value for insulin resistance HOMA-IR in an admixture population. Article CAS PubMed Google Scholar Esteghamati A, Ashraf H, Esteghamati AR, Meysamie A, Khalizadeh O, Nakhjavani M, Abbasi M: Optimal threshold of homeostasis model assessment for insulin resistance in an Iranian population: the implication of metabolic syndrome to detect insulin resistance. Article CAS PubMed Google Scholar Marques-Vidal P, Mazoyer E, Bongard V, Gourdy P, Ruidavets JB, Drouet L, Ferreries J: Prevalence of insulin resistance syndrome in Southwestern France and its relationship with inflammatory and haemostatic markers. Article PubMed Google Scholar Do HD, Lohsoosthorn V, Jiamjarasrangsi W, Lertmaharit S, Williams MA: Prevalence of insulin resistance and its relationship with cardiovascular disease risk factors among Thai adults over 35 years old. Article CAS PubMed PubMed Central Google Scholar Bonora E, Kiechl S, Willeit J, Oberhollenzer F, Egger G, Targher G, Alberiche M, Bonadonna RC, Muggeo M: Prevalence of insulin resistance in metabolic disorders. Article Google Scholar Nakai Y, Fukushima M, Nakaishi S, Kishimoto H, Seino Y, Nagasaka S, Sakai M, Taniguchi A: The threshold value for insulin resistance on homeostasis model assessment of insulin sensitivity. Article CAS PubMed Google Scholar Pepe MS: The Statistical Evaluation of Medical Tests for Classification and Prediction. Article CAS PubMed Google Scholar Otero A, Gayoso P, García F, De Francisco AL: Epidemiology of chronic renal disease in the Galician population: results of the pilot Spanish EPIRCE study. Article Google Scholar Otero A, De Francisco A, Gayoso P, Garcia F: Prevalence of chronic renal disease in Spain: results of the EPIRCE Study. PubMed Google Scholar Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC: Homeostasis model assessment: IR and beta-cell function from fasting plasma glucose and insulin concentration in man. Article CAS PubMed Google Scholar Alberti KG, Zimmet P, Shaw J: IDF Epidemiology task force consensus group. Article PubMed Google Scholar 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. Article Google Scholar Rodríguez-Álvarez MX, Roca-Pardiñas J, Cadarso-Suárez C: ROC curve and covariates: extending induced methodology to the non-parametric framework. Article Google Scholar Faraggi D: Adjusting receiver operating characteristic curves and related indices for covariates. Google Scholar Rodríguez-Álvarez MX, Tahoces PG, Cadarso-Suárez C, Lado MJ: Comparative study of ROC regression techniques. Article Google Scholar R Development Core Team. Article Google Scholar Bertoni AG, Wong ND, Shea S, Ma S, Liu K, Preethi S, Jacobs DR, Wu C, Saad MF, Szkio M: Insulin resistance, metabolic syndrome and subclinical atherosclerosis: the Multi-Ethnic Study of Atherosclerosis MESA. Article CAS PubMed Google Scholar Montecucco F, Steffens S, Mach F: Insulin resistance: a proinflammatory state mediated by lipid-induced signaling dysfunction and involved in atherosclerotic plaque instability. Article PubMed Google Scholar 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. Article CAS Google Scholar Tomé MA, Botana MA, Cadarso-Suarez C, Rego-Irateta A, Fernandez-Mariño A, Mato JA, Solache I, Perez-Fernandez R: Prevalence of metabolic syndrome in Galicia NW Spain on four alternative definitions and association with insulina resistance. Article PubMed Google Scholar Bonora E, Kiechl S, Willeit J, Oberhollenzer F, Egger G, Bonadonna RC, Muggeo M: Bruneck Study. Article CAS Google Scholar Ford ES, Giles WH, Dietz WH: Prevalence of metabolic syndrome among US adults. Acknowledgements The coordinating investigators of EPIRCE Study group were: M. de Ourense, Ourense, Spain Alfonso Otero-González Clinical Epidemiology Unit, Puerta de Hierro University Hospital, Madrid, Spain Fernando García Nephrology Department, Hospital Marques de Valdecilla, Santander, Spain Angel De Francisco Authors Pilar Gayoso-Diz View author publications. View author publications. PG during exercise and 3-h postbolus insulin correction in the four interventions. At 3-h postinsulin correction, following the standardized meal provided, the 3-h postmeal PG excursions were typical, ranging from 1. Analysis of CGM data Fig. Percentage time spent in normoglycemia A and in hyperglycemia B following insulin correction. Data are presented as mean ± SE. Hrs, hours. In continual observation over the entire h extended period Fig. By the final 8 h of the observational period, which occurred overnight between p. and a. Hypoglycemia events were rare during the 3-h period following the bolus insulin correction in all interventions Table 2. When hypoglycemia did occur, it was more frequent during the daytime 21 events between a. and p. compared with the overnight period six events between p. There were no events of severe hypoglycemia. Incidence of total hypoglycemia, daytime hypoglycemia, and nighttime hypoglycemia following correction of postexercise hyperglycemia. There were no serious adverse events associated with HIIT or with insulin treatment in the exercise visits. Ketone levels were measured during exercise and declined slightly but significantly from 0. Lactate levels rose significantly with exercise from 1. There were no differences between the correction arms. Insulin levels also rose slightly but significantly during and immediately after exercise from Catecholamine and growth hormone levels both rose with HIIT but did not differ between groups. Norepinephrine and growth hormone increased from baseline 2. Epinephrine levels were 0. HIIT is a popular form of exercise that has grown in prevalent use. Despite the growing awareness regarding the safety of HIIT in T1D, none of these statements have provided insulin- or carbohydrate-management guidance to control glycemia before or after HIIT. This study was the first to investigate several glycemic control options following HIIT for individuals living with T1D using multiple daily injections. We found that, following a standardized min HIIT exercise session in aerobically fit individuals with T1D, a significant degree of immediate postexercise hyperglycemia mean increase of 3. Optimal approach to insulin therapy was tested using four different multipliers of the ICF of post-HIIT hyperglycemia. Interestingly, the nocturnal period after HIIT, which represented the final 8 h of observation, showed similar glycemic control between all intervention arms. However, care should be taken to monitor for increased risk for late-onset hypoglycemia. High-intensity aerobic exercise activities, including HIIT, have been shown in prior investigation to be attributable to a typical, and possibly increased, degree of glucose production during the exercise, followed by a reduced level of glucose utilization, compared with moderate exercise 4 , 8. High-intensity exercise has similarly been associated with a marked increase in catecholamine production, which may restrict glucose uptake by skeletal muscle 17 , a phenomenon that can be reproduced with catecholamine infusion without exercise In subjects without diabetes, the resulting hyperglycemia leads to insulin release, accelerating glucose disposal; patients with T1D are unable to endogenously respond with insulin production, but exogenously infused insulin has also been shown to attenuate the postexercise hyperglycemia Interestingly, insulin levels did show a marginal increase during exercise in this study, likely representing redistribution from a subcutaneous depot of previously injected basal insulin. This finding has been observed with prolonged moderate-intensity aerobic exercise in individuals using continuous subcutaneous insulin infusion 19 , even if basal insulin levels had been lowered in anticipation of exercise The increased insulin levels did not prevent the expected postexercise hyperglycemia in this study but may contribute to exercise-associated hypoglycemia seen with moderate-intensity aerobic activity. Lactate levels also rose, likely reflecting the intensity of the exercise and its anaerobic component, although it is also possible that lactate contributes to insulin resistance, previously observed in rodent models In patients with T1D, lactate elevations have been linked closely to post-HIIT hyperglycemia, and both have responded to exercise training 3 such that attenuation of post-HIIT hyperglycemia appears to be matched by attenuation of the plasma lactate increase postexercise. Current guidelines recommend deferral of high-intensity exercise in settings of elevated ketone production i. Our findings indicate that in HIIT, ketone levels do not rise and actually decline during and after HIIT exercise. In contrast, a recent study with closed-loop insulin therapy found that ketone levels were largely unchanged during continuous and HIIT types of exercise but increased significantly in early recovery, particularly after HIIT The contrast with our study is surprising, given that their participants were studied in a fed and bolused state and exercised at a much lower intensity. Regardless, skeletal muscle under exercising conditions is known to be a net consumer of circulating ketone bodies even in patients with diabetes 23 , possibly explaining the early decline in circulating ketones in this study. Similar to findings in early investigations of high-intensity exercise 24 , and more recent studies of resistance training 10 and of HIIT 3 , 4 , 22 , we observed a clear and reproducible increase in glucose levels following HIIT that did not appear to diminish with repeated exposure. Not all studies investigating high-intensity exercise have confirmed this finding, and the inherent differences in study design are particularly hypothesis generating. For example, Guelfi et al. Tonoli et al. Although interval sprinting has frequently been used, HIIT ideally involves a rotation between different exercises, thereby involving exertion of a number of muscle groups. The duration of the intervals may also differentiate our findings from very brief sprinting. Importantly, the pattern of hyperglycemic response appears to be consistent in subjects studied in a fasted and low insulin state. In contrast, studies of subjects after a carbohydrate load, whether intravenous 25 or oral 26 , 27 , with prior insulin bolusing, have consistently shown modest hyperglycemia or only a limitation of hypoglycemia 22 , suggesting that either the prior carbohydrate load or the prior insulin may have a fundamental role in determining the postexercise glycemic response. Finally, where high-intensity exercise has been studied as a hypoglycemia prevention tool within otherwise moderate-intensity exercise, the results are not directly comparable The study design has several strengths including crossover design to minimize the effect of individual variability in glycemic response, standardized use of the same basal insulin, an 8-week run-in phase to optimize insulin therapy and confirm an accurate individual ICF, supervision of the exercise sessions by one of three certified exercise physiologists, h admission for observation, and the evaluation of four different ICF multipliers. We also recognize several inherent limitations. As discussed, all exercise sessions were performed in the morning, in a fasted state, so the results may not be generalizable to exercise performed at other times or in a fed state. Finally, these results have been found in the context of a randomized clinical trial where all of the exercise sessions were highly structured and supervised. Future studies should attempt to replicate these results in free-living individuals on other types of insulin-management regimens and further explore the possibility that exercise adaptations by skeletal muscle may influence the optimal individual ICF for management of post-HIIT hyperglycemia. In summary, we have demonstrated here that HIIT in fasting patients with T1D produces a large and consistent hyperglycemic response immediately following exercise. Patient counseling and clinical practice guidelines should begin to more prominently distinguish between the hyperglycemia induced by HIIT and the classic concern of hypoglycemia associated with less intense forms of exercise. Patients and health care providers should be aware of the degree and duration of post-HIIT hyperglycemia and the potential benefit of an insulin correction bolus. Future investigation may explore whether an even longer duration of insulin correction, such as a temporary basal rate enhancement, may be additionally indicated to achieve a more durable return to normoglycemia following HIIT exercise. Clinical trial reg. NCT , clinicaltrials. The authors thank Dr. Duality of Interest. This study was funded by Sanofi. reports advisory fees from Novo Nordisk and Sanofi and research support from AstraZeneca, Eli Lilly, Valeant, Janssen, and Senseonics. No other potential conflicts of interest relevant to this article were reported. Author Contributions. wrote the manuscript. and M. designed the study. and A. analyzed data. reviewed and provided critical edits to the manuscript. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Prior Presentation. Parts of this study were presented in abstract form at the 78th Scientific Sessions of the American Diabetes Association, Orlando, FL, 22—26 June Sign In or Create an Account. Search Dropdown Menu. header search search input Search input auto suggest. filter your search All Content All Journals Diabetes Care. Advanced Search. User Tools Dropdown. Sign In. Skip Nav Destination Close navigation menu Article navigation. Volume 42, Issue 1. Previous Article Next Article. Research Design and Methods. Article Information. Article Navigation. Optimal Insulin Correction Factor in Post—High-Intensity Exercise Hyperglycemia in Adults With Type 1 Diabetes: The FIT Study Ronnie Aronson Ronnie Aronson. Corresponding author: Ronnie Aronson, ronnie. aronson lmc. This Site. Google Scholar. Ruth E. Brown ; Ruth E. Aihua Li ; Aihua Li. Michael C. Riddell Michael C. Diabetes Care ;42 1 — Article history Received:. |
| How to Prevent & Reverse Insulin Resistance | Peter Attia, M.D. | Again, the effect size Organic remedies for skincare zensitivity difference was insuln Optimal insulin sensitivity biomarkers Optimzl included in the Strength training exercises formula, such as WC, SBP, insulin, HOMA-IR, adiponectin in males, and WC, SBP and hs-CRP in females. Email address Sign up. et al. Combined infusion of epinephrine and norepinephrine during moderate exercise reproduces the glucoregulatory response of intense exercise. Physiother 94—9. |
| Meal Frequency and Insulin Sensitivity: How Many Times Should You be Eating in a Day? | According to the Centers for Disease Control and Prevention CDC , around 90—95 percent of people with diabetes have type 2. If a person has a diagnosis in the early stages, there is a good chance that they can use these strategies to prevent type 2 diabetes from progressing or developing fully. Find out more here about how dietary choices can stop prediabetes from becoming type 2 diabetes. However, checking blood sugar levels regularly and using insulin to keep them within a specific target range helps reduce the risk and slow the progression of diabetes complications. Insulin sensitivity factor assessments are only useful for people with type 1 diabetes who no longer produce insulin. People with type 2 diabetes may still produce some amounts of insulin in their pancreas, and so they cannot calculate their insulin sensitivity factor reliably. People with type 2 diabetes should focus first on diet and lifestyle changes to lower their blood sugar levels. After this, a doctor may recommend medications, such as metformin. Find out more about medications for type 2 diabetes:. Diabetes can be a serious disease, but with the correct medication and guidance, a person can live a normal life with this condition and delay the onset of complications. It is essential to follow the treatment plan and use insulin and other medications as the doctor advises. People should not change their regime without first speaking to their healthcare provider. Prediabetes is a common condition that can develop into type 2 diabetes. Prediabetes is when blood glucose levels are high, but not high enough to…. Experts say more adults who develop type 1 diabetes are being misdiagnosed as having type 2 diabetes. That, they say, can lead to ineffective…. Ketonemia is a term that describes an unusually high amount of ketone bodies in the blood. Learn more about ketonemia here. What is nocturnal hypoglycemia and how can people avoid it? Read on to learn more about night time hypoglycemia, including causes and how to manage it. My podcast changed me Can 'biological race' explain disparities in health? Why Parkinson's research is zooming in on the gut Tools General Health Drugs A-Z Health Hubs Health Tools Find a Doctor BMI Calculators and Charts Blood Pressure Chart: Ranges and Guide Breast Cancer: Self-Examination Guide Sleep Calculator Quizzes RA Myths vs Facts Type 2 Diabetes: Managing Blood Sugar Ankylosing Spondylitis Pain: Fact or Fiction Connect About Medical News Today Who We Are Our Editorial Process Content Integrity Conscious Language Newsletters Sign Up Follow Us. Medical News Today. Health Conditions Health Products Discover Tools Connect. All you need to know about insulin sensitivity factor. Medically reviewed by Alana Biggers, M. What is it? The rule How to test When to test Diabetes and insulin Complications Insulin sensitivity and type 2 diabetes Outlook Insulin is a hormone that is crucial for managing blood sugar levels. What is insulin sensitivity factor? Share on Pinterest Knowing how to calculate the insulin sensitivity factor can help a person with diabetes to get the correct dose of insulin. The rule and calculation. How to test for insulin sensitivity factor. Share on Pinterest People should check their insulin sensitivity factor and blood sugar levels regularly. In older adults — year-old non-diabetics — the interval for fasting insulin levels was found to be 1. That said, there is some consensus in the medical community around what might be considered ideal, good, fair, and probable insulin resistance in terms of fasting insulin levels:. However, it's important to remember that these ranges are not definitive, and results should always be interpreted in the context of the individual's overall health, symptoms, risk factors, and other test results. While getting an insulin test may be challenging due to factors like out-of-pocket cost, accessibility, or reliability in results, glucose monitoring can be a practical alternative to understanding your insulin sensitivity. Blood glucose levels are a key indicator of how your body processes food for energy and how effectively insulin is functioning in your body. Sustained high glucose levels often indicate that your body is struggling to effectively utilize insulin, which can suggest insulin resistance [1]. Continuous glucose monitors CGMs make it easy to track glucose levels throughout the day. Unlike a fasting insulin test, which provides a single snapshot in time, CGMs provide real-time information about glucose levels. By constantly monitoring your glucose, you can gain insights into how different factors such as meals, physical activity, stress, and sleep affect your glucose levels. This gives a comprehensive picture of your body's metabolic response and can help pinpoint areas for improvement. CGMs allow you to monitor several critical markers of glucose regulation: average glucose levels, glucose variability, and fasting glucose levels. A higher average glucose level or drastic variability can be indicative of metabolic issues. By correlating these glucose metrics with the Four Pillars of metabolic health — nutrition, exercise, stress management, and sleep—you can build healthier habits and make targeted lifestyle modifications. For example, you might notice certain foods cause a spike in glucose levels and opt to limit them in your diet, or you might find that light physical activity , like walking, helps in maintaining more stable glucose levels. Insulin's critical role in glucose regulation, the implications of insulin resistance, and the relevance of fasting insulin tests encompass an essential part of metabolic health. Metabolic Health. What Are Optimal Fasting Insulin Levels for Metabolic Health? Insulin: the hormone that regulates glucose Insulin is a hormone produced by the pancreas that plays a critical role in regulating blood glucose levels by facilitating its absorption. How we test for insulin levels Insulin levels can be measured using a fasting insulin test [6]. HOMA-IR , or homeostasis model of insulin resistance [10]. QUICKI , or quantitative insulin sensitivity check index [11]. This is a variation of the HOMA-IR equation that is used to determine insulin sensitivity. Who should get a fasting insulin test A fasting insulin test is particularly valuable for individuals who are at risk for developing insulin resistance, such as those who are overweight or obese but do not yet have prediabetes or diabetes. What are normal or optimal fasting insulin levels? Using glucose levels as a marker of insulin resistance and metabolic health While getting an insulin test may be challenging due to factors like out-of-pocket cost, accessibility, or reliability in results, glucose monitoring can be a practical alternative to understanding your insulin sensitivity. Key Takeaways Insulin's critical role in glucose regulation, the implications of insulin resistance, and the relevance of fasting insulin tests encompass an essential part of metabolic health. It is particularly valuable for individuals who are at risk for insulin resistance but do not have prediabetes or diabetes. compared with the overnight period six events between p. There were no events of severe hypoglycemia. Incidence of total hypoglycemia, daytime hypoglycemia, and nighttime hypoglycemia following correction of postexercise hyperglycemia. There were no serious adverse events associated with HIIT or with insulin treatment in the exercise visits. Ketone levels were measured during exercise and declined slightly but significantly from 0. Lactate levels rose significantly with exercise from 1. There were no differences between the correction arms. Insulin levels also rose slightly but significantly during and immediately after exercise from Catecholamine and growth hormone levels both rose with HIIT but did not differ between groups. Norepinephrine and growth hormone increased from baseline 2. Epinephrine levels were 0. HIIT is a popular form of exercise that has grown in prevalent use. Despite the growing awareness regarding the safety of HIIT in T1D, none of these statements have provided insulin- or carbohydrate-management guidance to control glycemia before or after HIIT. This study was the first to investigate several glycemic control options following HIIT for individuals living with T1D using multiple daily injections. We found that, following a standardized min HIIT exercise session in aerobically fit individuals with T1D, a significant degree of immediate postexercise hyperglycemia mean increase of 3. Optimal approach to insulin therapy was tested using four different multipliers of the ICF of post-HIIT hyperglycemia. Interestingly, the nocturnal period after HIIT, which represented the final 8 h of observation, showed similar glycemic control between all intervention arms. However, care should be taken to monitor for increased risk for late-onset hypoglycemia. High-intensity aerobic exercise activities, including HIIT, have been shown in prior investigation to be attributable to a typical, and possibly increased, degree of glucose production during the exercise, followed by a reduced level of glucose utilization, compared with moderate exercise 4 , 8. High-intensity exercise has similarly been associated with a marked increase in catecholamine production, which may restrict glucose uptake by skeletal muscle 17 , a phenomenon that can be reproduced with catecholamine infusion without exercise In subjects without diabetes, the resulting hyperglycemia leads to insulin release, accelerating glucose disposal; patients with T1D are unable to endogenously respond with insulin production, but exogenously infused insulin has also been shown to attenuate the postexercise hyperglycemia Interestingly, insulin levels did show a marginal increase during exercise in this study, likely representing redistribution from a subcutaneous depot of previously injected basal insulin. This finding has been observed with prolonged moderate-intensity aerobic exercise in individuals using continuous subcutaneous insulin infusion 19 , even if basal insulin levels had been lowered in anticipation of exercise The increased insulin levels did not prevent the expected postexercise hyperglycemia in this study but may contribute to exercise-associated hypoglycemia seen with moderate-intensity aerobic activity. Lactate levels also rose, likely reflecting the intensity of the exercise and its anaerobic component, although it is also possible that lactate contributes to insulin resistance, previously observed in rodent models In patients with T1D, lactate elevations have been linked closely to post-HIIT hyperglycemia, and both have responded to exercise training 3 such that attenuation of post-HIIT hyperglycemia appears to be matched by attenuation of the plasma lactate increase postexercise. Current guidelines recommend deferral of high-intensity exercise in settings of elevated ketone production i. Our findings indicate that in HIIT, ketone levels do not rise and actually decline during and after HIIT exercise. In contrast, a recent study with closed-loop insulin therapy found that ketone levels were largely unchanged during continuous and HIIT types of exercise but increased significantly in early recovery, particularly after HIIT The contrast with our study is surprising, given that their participants were studied in a fed and bolused state and exercised at a much lower intensity. Regardless, skeletal muscle under exercising conditions is known to be a net consumer of circulating ketone bodies even in patients with diabetes 23 , possibly explaining the early decline in circulating ketones in this study. Similar to findings in early investigations of high-intensity exercise 24 , and more recent studies of resistance training 10 and of HIIT 3 , 4 , 22 , we observed a clear and reproducible increase in glucose levels following HIIT that did not appear to diminish with repeated exposure. Not all studies investigating high-intensity exercise have confirmed this finding, and the inherent differences in study design are particularly hypothesis generating. For example, Guelfi et al. Tonoli et al. Although interval sprinting has frequently been used, HIIT ideally involves a rotation between different exercises, thereby involving exertion of a number of muscle groups. The duration of the intervals may also differentiate our findings from very brief sprinting. Importantly, the pattern of hyperglycemic response appears to be consistent in subjects studied in a fasted and low insulin state. In contrast, studies of subjects after a carbohydrate load, whether intravenous 25 or oral 26 , 27 , with prior insulin bolusing, have consistently shown modest hyperglycemia or only a limitation of hypoglycemia 22 , suggesting that either the prior carbohydrate load or the prior insulin may have a fundamental role in determining the postexercise glycemic response. Finally, where high-intensity exercise has been studied as a hypoglycemia prevention tool within otherwise moderate-intensity exercise, the results are not directly comparable The study design has several strengths including crossover design to minimize the effect of individual variability in glycemic response, standardized use of the same basal insulin, an 8-week run-in phase to optimize insulin therapy and confirm an accurate individual ICF, supervision of the exercise sessions by one of three certified exercise physiologists, h admission for observation, and the evaluation of four different ICF multipliers. We also recognize several inherent limitations. As discussed, all exercise sessions were performed in the morning, in a fasted state, so the results may not be generalizable to exercise performed at other times or in a fed state. Finally, these results have been found in the context of a randomized clinical trial where all of the exercise sessions were highly structured and supervised. Future studies should attempt to replicate these results in free-living individuals on other types of insulin-management regimens and further explore the possibility that exercise adaptations by skeletal muscle may influence the optimal individual ICF for management of post-HIIT hyperglycemia. In summary, we have demonstrated here that HIIT in fasting patients with T1D produces a large and consistent hyperglycemic response immediately following exercise. Patient counseling and clinical practice guidelines should begin to more prominently distinguish between the hyperglycemia induced by HIIT and the classic concern of hypoglycemia associated with less intense forms of exercise. Patients and health care providers should be aware of the degree and duration of post-HIIT hyperglycemia and the potential benefit of an insulin correction bolus. Future investigation may explore whether an even longer duration of insulin correction, such as a temporary basal rate enhancement, may be additionally indicated to achieve a more durable return to normoglycemia following HIIT exercise. Clinical trial reg. NCT , clinicaltrials. The authors thank Dr. Duality of Interest. This study was funded by Sanofi. reports advisory fees from Novo Nordisk and Sanofi and research support from AstraZeneca, Eli Lilly, Valeant, Janssen, and Senseonics. No other potential conflicts of interest relevant to this article were reported. Author Contributions. wrote the manuscript. and M. designed the study. and A. analyzed data. reviewed and provided critical edits to the manuscript. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Prior Presentation. Parts of this study were presented in abstract form at the 78th Scientific Sessions of the American Diabetes Association, Orlando, FL, 22—26 June Sign In or Create an Account. Search Dropdown Menu. header search search input Search input auto suggest. |
| Optimal Fasting Insulin Levels for Metabolic Health - Veri | Nesto RW, Bell Inuslin, Bonow RO, Fonseca V, Grundy SM, Organic remedies for skincare ES, Optimwl Antioxidant-rich antioxidant capacity M, Glucagon release regulation D, Semenkovich CF, Optkmal S, Young Sensitvity, Kahn Antioxidant-rich antioxidant capacity. The cross-sectional nature of our sensitivitg does not allow us to draw conclusions regarding causality between IR and cardio metabolic risk. Share on Pinterest People should check their insulin sensitivity factor and blood sugar levels regularly. Instituto de Investigación Sanitaria de Santiago IDISSantiago de, Compostela, Spain. Article Google Scholar Marshall, W. Optimal HOMA-IR cut point for classification of cardio metabolic risk in non-diabetic women. |
Optimal insulin sensitivity -
units here. HOMA-IR stands for Homeostatic Model Assessment of Insulin Resistance. This calculation marks for both the presence and extent of any insulin resistance that you might currently express. You can visit TheBloodCode. com to plug in your values and get the calculation.
It is a terrific way to reveal the dynamic between your baseline fasting blood sugar and the responsive hormone insulin. Low HOMA-IR means that you are sensitive to insulin. A small amount of the hormone insulin is doing the trick to keep your blood sugars in good balance.
High HOMA-IR relates to your level of insulin resistance. The higher the number, the more resistant you are to the message of insulin. If you are above 2, your self-prescribed diet and fitness habits will bring your number down into the lower insulin-sensitive range.
As you can tell, metabolic health lies in space between the hormone insulin and your glucose sensitivity. There is an adult-onset type 1 diabetes called LADA, sometimes referred to as diabetes type 1.
With low insulin, you can readily break down fats that you have stored. In my practice, I see low insulin with:. High insulin: High insulin on a fasting blood test means you are in an anabolic state—effectively building fat and muscle effectively.
Insulin resistance, beta-cell function, and glucose tolerance in Brazilian adolescents with obesity or risk factors for type 2 diabetes mellitus. J Diabetes Compl. The pretest probability is the proportion of people in the population at risk who have the disease at a specific time or time interval e.
The post-test probability denotes the proportion of individuals testing positive who genuinely have the disease. It is similar to the positive predictive value, but apart from the test performance also includes a patient-based probability of having the disease.
Table 3 contains the probabilities of the presence of the MetS and IR before and after using the SPISE. In our male participants, the pretest probability of having the MetS was 7.
In the same group, the pretest probability of having IR was The same pattern was found in females, for whom the probability of having these conditions increased notably in the group with SPISE values below the optimal cutoff points.
Next, we compared the diagnostic performance of SPISE, HOMA-IR, and TG-HDL ratio for MetS prediction in males and females Fig. A comparison of SPISE vs. In females, both HOMA and TG-HDL had significantly smaller AUCs compared with SPISE, which confirms that SPISE outperforms both in the diagnosis of MetS.
Pairwise comparison of ROC Curves for Metabolic Syndrome diagnosis: SPISE, HOMA-IR and TG-HDL ratio. A ROC plot closer to the upper left corner denotes greater accuracy of the test.
Last, we checked whether our SPISE cutpoints related to higher biological risk in the group having a SPISE below the cutpoints for MetS and IR diagnosis.
A higher prevalence of hypertriglyceridemia and low HDL was found in the group having the test positive. However, we also found a higher prevalence of abdominal obesity and high blood pressure and a trend towards a higher prevalence of hyperglycemia, whose biomarkers are not included in the SPISE algorithm Fig.
Particularly, the prevalence of abdominal obesity was 4. Likewise, the prevalence of hypertension was 3. Table 4 contains the cardiometabolic profile of participants after controlling for sex and MetS and IR presence, according to SPISE cutoffs.
Notably, the effect size for difference was also large for biomarkers not included in the SPISE algorithm, such as WC, SBP, TChol, HOMA-IR, and insulin in both sexes, and LDL-chol in males. Likewise, males and females having SPISE values below the cutoff for IR prediction had an unhealthier cardiometabolic profile compared to peers with a test negative.
Again, the effect size for the difference was large for biomarkers not included in the SPISE formula, such as WC, SBP, insulin, HOMA-IR, adiponectin in males, and WC, SBP and hs-CRP in females.
Prevalence of cardiometabolic risk in the sample according to optimal SPISE cutoffs for MetS and IR diagnosis. We found that IR-related cardiometabolic risk in post-pubertal adolescents can be estimated using the SPISE, a new, low-cost, simple to estimate index.
In males and females, SPISE had a very good and good diagnostic performance for predicting MetS. In both sexes, SPISE showed a significantly better ROC curve than HOMA-IR for MetS diagnosis.
Although SPISE was an accurate diagnostic tool for IR prediction in males, this was not always the case for females. Few studies have conducted validity assessments of SPISE for the prediction of IR-related cardiometabolic disorders. They have done so using different populations and study designs. In both samples, oral-glucose-tolerance tests and hyperinsulinemic-euglycemic clamp were used to estimate insulin sensitivity and calculation of insulin sensitivity indices.
Mathematical modeling was applied, including BMI, fasting TG, and HDL-chol and compared to the clamp M-values using ROC analysis.
In both youth and adults with obesity, a SPISE of 6. The SPISE accuracy for the prediction of cardiometabolic risk was later tested among adults from Northern India found that a SPISE of 5. The mean value of SPISE was found to be significantly lower in MetS patients than controls 5.
Our results show that SPISE performed significantly better than HOMA in the prediction of clustered cardiometabolic risk. It seems that SPISE characterizes well the role of proatherogenic conditions e.
Inflammation plays an important role in the development of IR through different cytokines and molecular pathways In our sample, participants with a SPISE below the cutpoints for MetS diagnosis had remarkably higher levels of hs-CRP and lower adiponectin than participants with SPISE values above the cutpoint.
The differences were moderate for hs-CRP in both sexes and moderate and large for adiponectin in females and males. Obesity, particularly intra-abdominal obesity, relates to chronic low-grade systemic inflammation and low adiponectin, an important predictor of cardiovascular risk.
In our sample, the prevalence of abdominal obesity was 4. Similarly, mean waist circumference was much larger in males and females having a reduced SPISE. A similar deterioration pattern was seen for TChol, HDL-chol, and TG in both sexes and LDL-chol in males.
It has been found that a dysfunctional insulin signaling in peripheral tissues e. A study conducted in Sweden obtained results that might be consistent with ours, although in a sample of older adults. In year-olds from the Uppsala Longitudinal Study of Adult Men, Cederholm and Zethelius found that the SPISE performed as well as the QUICKI, log HOMA-IR and revised QUICKI as a predictor for future risk of fatal and non-fatal coronary heart disease Differences in terms of area under the ROC curve were 15 percentage points in males and eight percentage points in females.
Therefore, the inclusion of BMI in the atherogenic index and some mathematical modeling substantially improved its screening capability. This procedure can be easily implemented in an algorithm using spreadsheets or other statistical software that operates on data entered in table cells.
This requires minimal computational effort while retaining reasonable accuracy and allows estimation and tracking of the SPISE at the individual level. Continuous monitoring of SPISE may serve for the rapid identification of clinically relevant changes and help guide treatment.
A fourth significant finding relates to the fact that SPISE had greater diagnostic accuracy in males compared to females. This is in line with evidence describing a sexual dimorphism in incidence, age of onset, and progression of most cardiometabolic diseases, with males generally showing less beneficial profiles 28 , 29 , 30 , In our sample, males had a more adverse cardiometabolic profile than females that may put them at higher risk of IR and MetS.
It is known that sex influences body fat distribution, ectopic fat accumulation, insulin signaling, glucose homeostasis, and lipid metabolism.
Thus, the challenge is to consider those differences in both clinical practice and epidemiological screenings. To the best of our knowledge, this is the first validity assessment of SPISE considering sex-related differences in this biomarker's efficacy. In adolescents, SPISE might be a promising tool for estimating IR-related cardiometabolic risk in both clinical and epidemiological settings.
Although IR is standard in children and adolescents with obesity and relates to a higher risk of major cardiometabolic disorders 1 , 2 , 3 , IR prevalence in these groups is not well established 5.
According to Levy-Marchal et al. Even in clinical practice, insulin is not advised to measure insulin sensitivity in the pediatric population, and the same holds for surrogate methods such as HOMA and QUICKI 5 , Hence, there is a need to have available screening programs to assess insulin sensitivity without measuring insulin levels.
SPISE is based on BMI and routine lipids, which are much cheaper to obtain, more reliable than insulin, and require a single blood sample. Second, SPISE opens up the possibility to identify adolescents at risk of IR-related cardiometabolic disorders in large groups. Because of the vast number of youths having or are at risk of obesity and because IR may occur as part of the physiological changes in puberty 1 , 2 , early detection of impaired insulin sensitivity in adolescents is pivotal to designing targeted preventive actions.
Population health surveys usually have measurements of body-mass index and lipid profile. Hence, SPISE could be used to screen IR-related cardiometabolic risk in ethnic groups that are more insulin resistant than white Europeans, regardless of body-mass index, total fat mass, and visceral adiposity.
It is the case of Hispanics, African Americans, and East Asians 33 , 34 , 35 , or people living in countries undergoing rapid industrialization significant increases in dietary fat and sugar intake and persistent declines in physical activity levels.
Furthermore, these groups might have inherited the so-called thrifty phenotype This is an adaptive mechanism engineered to protect the brain, at the expense of other tissues such as the pancreas, in the face of food scarcity. In the long-term, however, the mechanism predisposes to increased risk for cardiometabolic abnormalities, manifested first as inadequate glycemic control and later as type-2 diabetes and its complications Last, because sex has an impact on several determinants of insulin sensitivity it is important to consider sex differences in glucose metabolism and insulin action and, thus, sex-specific standards when measuring IR-related cardiometabolic risk are also needed.
This study has some limitations. Because our sample was comprised of post-pubertal adolescents from low- to middle SES between a narrow age-range: 16 to 17y, our findings cannot be generalized to the overall population of Chilean adolescents.
However, because the glucose clamp is an invasive procedure, it is not easy to use in healthy individuals. Third, the cross-sectional nature of the study constraints the ability to conclude on the temporality of these associations.
Future studies should longitudinally explore this indicator's performance in predicting the risk of cardiometabolic disorders later in life.
On the other hand, our study has several strengths. According to population-based surveys and national studies, the prevalence of obesity and cardiometabolic risk is much higher in adolescents of low- to middle SES. They are more exposed to risk factors that lead to obesity, IR, and MetS than high-SES adolescents 4 , 10 , 12 , 24 , 28 , Second, we provide evidence of a biomarker that allows good early discrimination of adolescents with IR-related cardiometabolic risk, using a low-cost, easy-to-estimate indicator based on biological risk.
Hence, it might be potentially useful in both clinical and population settings. Third, we found sex differences in this biomarker's effectiveness to identify adolescents at higher cardiometabolic risk.
The sexual dimorphism has not been described in previous validity assessments of the SPISE. Also, we estimated post-test probabilities. While post-test probabilities may be quite useful in everyday clinical work, they are often roughly estimated or even guessed.
When they are calculated, clinical decision-making may rely on pure quantitative criteria, allowing appropriate and comprehensive use of results from screening tests.
If more sophisticated or expensive screening methods are needed, or resources for interventions are scarce, the post-test probabilities allow focusing on those at higher biological risk. Second, post-test probabilities help to determine which test is best for the patient, in terms of costs and safety, using the most economical and safest option by which an acceptable post-test probability can be achieved.
Third, it is possible to determine whether the probability of a positive diagnosis has risen i. Another strength of the study has to do with the ethnic background of participants.
Our sample consists of Hispanic adolescents, and according to the evidence, this is a group less insulin sensitive than Caucasian adolescents 38 , 39 , Marcovecchio, M. Obesity and insulin resistance in children. Article Google Scholar. Tagi, V. Insulin resistance in children.
Front Endocrinol. Tobisch, B. Cardiometabolic risk factors and insulin resistance in obese children and adolescents: relation to puberty. Article CAS Google Scholar. Encuesta Nacional de Salud — Departamento de Epidemiología.
Subsecretaría de Salud Pública, Ministerio de Salud. Santiago de Chile: Last accessed: Levy-Marchal, C. et al. Insulin resistance in children: consensus, perspective, and future directions.
Hellman, B. Pulsatility of insulin release — a clinically important phenomenon. Ups J. Marcovina, S. Standardization of insulin immunoassays: report of the American diabetes association workgroup. Paulmich, K. Modification and validation of the triglyceride-to-HDL cholesterol ratio as a surrogate of insulin sensitivity in white juveniles and adults without diabetes mellitus: the single point insulin sensitivity estimator SPISE.
Lozoff, B. Behavioral and developmental effects of preventing iron-deficiency anemia in healthy full-term infants. Pediatrics , — PubMed Google Scholar. Correa-Burrows, P.
Leptin status in adolescence is associated with academic performance in high school: a cross-sectional study in a Chilean birth cohort.
BMJ Open. Burrows, R. Long-term vs. recent-onset obesity: their contribution to cardiometabolic risk in adolescence.
De Onis, M. Development of a WHO growth reference for school-aged children and adolescents. World Health Organ. Marshall, W. Variations in pattern of pubertal changes in girls.
Variations in the pattern of pubertal changes in boys. Diabetes Res. Alberti, K. 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 , — Cohen, J. A power primer. Psychol Bull. Cliff, N. Dominance statistics: ordinal analyses to answer ordinal questions. Baeyens, J. Physiother 9 , 4—9. Article PubMed PubMed Central Google Scholar. Dudi, P. Single point insulin sensitivity estimator as an index for insulin sensitivity for metabolic syndrome: a study in North Indian population.
CAS Google Scholar. Chen, L. Mechanisms linking inflammation to insulin resistance. Google Scholar. Semenkovich, C.
Insulin resistance and atherosclerosis. Savage, D. Disordered lipid metabolism and the pathogenesis of insulin resistance. Cederholm, J. SPISE and other fasting indexes of insulin resistance: risks of coronary heart disease or type 2 diabetes.
Comparative cross-sectional and longitudinal aspects. Ups J Med Sci. Kim-Dorner, S. Should triglycerides and the triglycerides to high-density lipoprotein cholesterol ratio be used as surrogates for insulin resistance?. Giannini, C. The triglyceride-to-HDL cholesterol ratio.
Association with insulin resistance in obese youths of different ethnic backgrounds. Diabetes Care. Sumner, A. High cardiometabolic risk in healthy Chilean adolescents: association with anthropometric, biological and life style factors.
Public Health Nutr. Isasi, C. J Pediatr. Chella Krishnan, K. Sex differences in metabolism and cardiometabolic disorders.
Opin Lipidol. Guzzetti, C. Cardiovascular risk factors in children and adolescents with obesity: sex-related differences and effect of puberty. Wallace, T. Use and abuse of HOMA modeling. Care 27 , — Tay, J. Race affects the association of obesity measures with insulin sensitivity.
Hasson, R. Compensatory responses to insulin resistance in obese African-American and Latina girls. Ethnic differences in insulin action in obese African-American and Latino adolescents. Wells, J. Ethnic variability in adiposity, thrifty phenotypes and cardiometabolic risk: addressing the full range of ethnicity, including those of mixed ethnicity.
Obes Rev. Informe Mapa Nutricional Junta Nacional de Auxilio Escolar y Becas. Ministerio de Educación, Santiago, Chile; Retrieved from: www.
Last Accessed:
Understanding insulin's sensitvity Antioxidant-rich antioxidant capacity metabolic health is Optimql for overall well-being and Opgimal Antioxidant-rich antioxidant capacity healthy lifestyle. In current research and Optimal insulin sensitivity practice, there is no insulinn yet on Hydration strategies for athletes optimal insulin levels are, and testing is often inaccessible. We can, however, use glucose levels as a proxy for insulin sensitivity. Insulin is a hormone produced by the pancreas that plays a critical role in regulating blood glucose levels by facilitating its absorption. Insulin acts as a key that unlocks the cells, allowing glucose from the bloodstream to enter and provide energy for cells [1].
0 thoughts on “Optimal insulin sensitivity”