Insulin Resistance – Market Outlook, Epidemiology, Competitive Landscape, and Market Forecast Report – 2023 To 2033 thelansis.com

Insulin resistance is when the body exhibits an insufficient biological response to normal insulin levels. In essence, it can affect various insulin-related functions in different bodily tissues. However, in clinical practice, insulin resistance is commonly understood as a state in which a given amount of insulin results in an inadequate glucose response. The origins of insulin resistance can be attributed to genetic and acquired factors. Genetic factors include mutations in insulin receptors, glucose transporters, and signaling proteins, although the precise causes of common forms remain largely unknown. Acquired factors encompass physical inactivity, dietary habits, medications, high blood sugar levels (known as glucose toxicity), elevated levels of free fatty acids, and the natural aging process. The underlying causes of insulin resistance can be classified based on whether their primary impact occurs before, at, or after the insulin receptor. Pre-receptor causes include abnormal insulin (due to mutations) and anti-insulin antibodies. Receptor-related causes include reduced receptors, failure to activate tyrosine kinase, diminished insulin binding, insulin receptor mutations, and antibodies that block insulin receptors. Post-receptor causes encompass defective signal transduction and, in theory, mutations in the GLUT4 gene, although these mutations are rare. Symptoms of insulin resistance encompass increased thirst, frequent urination, heightened appetite, blurred vision, headaches, vaginal and skin infections, and slow wound healing. Factors associated with a higher likelihood of developing insulin resistance include a strong family history of diabetes, gestational diabetes, and polycystic ovary syndrome. Impaired glucose metabolism, defined as fasting glucose levels between 110 and 125 mg per dL (6.1 and 7.1 mmol per L) or impaired glucose tolerance with a two-hour post–75-g glucose load level between 140 and 199 mg per dL (7.8 and 11.1 mmol per L), also contribute to this condition. Additionally, obesity, defined as a body mass index of 30 kg per m2 or higher, and an increased waist-to-hip ratio (1.0 in men and 0.8 in women) are associated with insulin resistance.
• Globally, the prevalence of insulin resistance among adults varies, ranging from 15.5% to 46.5%. The lowest prevalence is observed among underweight individuals (7.1%), while the highest rates are found among those who are obese (45%).

Thelansis’s “Insulin Resistance Market Outlook, Epidemiology, Competitive Landscape, and Market Forecast Report – 2023 To 2033″ covers disease overview, epidemiology, drug utilization, prescription share analysis, competitive landscape, clinical practice, regulatory landscape, patient share, market uptake, market forecast, and key market insights under the potential Insulin Resistance treatment modalities options for eight major markets (USA, Germany, France, Italy, Spain, UK, Japan, and China).

KOLs insights of Insulin Resistance across 8 MM market from the centre of Excellence/ Public/ Private hospitals participated in the study. Insights around current treatment landscape, epidemiology, clinical characteristics, future treatment paradigm, and Unmet needs.

Insulin Resistance Market Forecast Patient Based Forecast Model (MS. Excel Based Automated Dashboard), which Data Inputs with sourcing, Market Event, and Product Event, Country specific Forecast Model, Market uptake and patient share uptake, Attribute Analysis, Analog Analysis, Disease burden, and pricing scenario, Summary, and Insights.

Thelansis Competitive Intelligence (CI) practice has been established based on a deep understanding of the pharma/biotech business environment to provide an optimized support system to all levels of the decision-making process. It enables business leaders in forward-thinking and proactive decision-making. Thelansis supports scientific and commercial teams in seamless CI support by creating an AI/ ML-based technology-driven platform that manages the data flow from primary and secondary sources.

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