Background: Liver is a vital organ that plays a major role in glucose production and regulationthroughout the body (Musso et al., 2012). Liver disease has long been linked with insulin resistance (IR), dating back to 1906 (Megyesi et al., 1967). IR has been found to be prevalent in a range of liver diseases, including chronic Hepatitis C Virus (HCV), hemochromatosis, and alcoholic liver disease (Goswami et al., 2014). Liver disease is highly prevalent in the United States population with 30 million people (or one out of ten Americans) suffering from some type of liver disease (Peery et al., 2015). Although research demonstrates a significant relationship between liver disease and IR, the University of Arizona (UA) hepatology clinic does not currently screen liver disease patients for IR. Homeostatic model assessment for insulin resistance (HOMA-IR) score is used to study IR in non-insulin resistant population. HOMA-IR score is calculated using formula fasting plasma glucose (mmol/l) times fasting serum insulin (mU/l) divided by 22.5 (Bonora et al., 2002). Low HOMA-IR (HOMA< 2.0) values indicate high insulin sensitivity, whereas high HOMA-IR (HOMA> 2.0) values indicate low insulin sensitivity (insulin resistance) (Bonora et al., 2002). Objective: The purpose of this quality improvement (QI) project is to show the prevalence of IR in euglycemic liver disease patients at the UA hepatology clinic by using their HOMA-IR scores as a screening tool. By screening euglycemic liver disease patients for IR based on their HOMA-IR score, providers at the UA hepatology clinic can prevent liver disease progression and complications associated with IR early on. By doing so, the providers can improve the quality of care for liver disease patients. An essential part of calculating HOMA-IR is the availability of labs (serum glucose and serum insulin). A part of this QI project is to determine if the UA hepatology clinic has necessary labs to calculate HOMA-IR for euglycemic liver disease patients. A related matter is whether there is a correlation between liver disease patients' HOMA-IR score and Model for End-stage Liver Disease (MELD) score. If there is a direct correlation between HOMA-IR and MELD scores, providers can identify severity and progression of liver disease in euglycemic liver disease patients. Design: A case control retrospective study. Study Questions: 1) Do UA Hepatology clinic providers order sufficient labs (fasting plasma glucose and fasting plasma insulin) to calculate HOMA-IR in euglycemic patients? 2) What is the prevalence of IR in euglycemic liver patients indicated by HOMA-IR score? 3) Is there any correlation between HOMA-IR score and MELD score in euglycemic liver disease patients? Participants: Data will be collected from 1000 liver disease patients' at the UA hepatologyclinic, a tertiary level referral center. Settings: Banner University Medical Center (UMC) in Tucson, Arizona from January 1, 2011 until December 31, 2014. Measurements: HOMA-IR score using serum fasting glucose and serum fasting insulin levels laboratory values. MELD score to identify the severity of liver disease in euglycemic liver disease patients. Results: Among 1000 patients, 506 (60.5%) were found to have a previous diagnosis of T2DMand 395 (39.5 %) were euglycemic liver disease patients (Figure 1). Out of the 395 euglycemic liver disease patients, 217 (55%) participants were found to have both insulin level and glucose11level in their charts; 178 (45%) euglycemic liver disease patients were missing either insulin level or glucose level needed to calculate HOMA-IR score (Figure 2). Of the 217 euglycemic liver disease patients, 54.8% of had HOMA-IR> 2 and 45.2% patients had HOMA-IR<2 (Figure 3). The Pearson Correlation between HOMA-R>2 and MELD scores was 0.092 and the significance value using 2-tailed was 0.321 (Table 4). Conclusion: The results showed a significant high prevalence of IR in euglycemic patients with HOMA-IR score> 2 (54.8%) compare to those patients with HOMA-IR score<2 (45.2%). Furthermore, about 178 (45%) euglycemic liver disease patients were missing either insulin level or glucose level needed to calculate HOMA-IR score. This is a significant number of patients missing important labs to identify them as high risk for IR. This QI project identified HOMA-IRas an important screening tool that should be used both in hepatology clinics and primary healthcare settings. Use of such tool will lead to improved quality of care for euglycemic liver disease patients.

The purpose of this investigation was to expand the evaluation of Normal Weight Obesity (NWO) and its association with insulin resistance using a nationally representative sample of U.S. adults. A cross-sectional study including 5,983 subjects was conducted. Body fat percentage was assessed using dual energy X-ray absorptiometry (DXA). Expanded Normal Weight Obesity (eNWO) categories (pairings of BMI and body fat percentage classifications) were determined by standard cut-points for BMI and the gender specific median for body fat percentage. Homeostatic Model Assessment-Insulin Resistance (HOMA-IR) levels were used to index insulin resistance. Mean ± SE values were as follows: BMI: 27.9 ± 0.2 (women) and 27.8 ± 0.1 (men); body fat percentage: 40.5 ± 0.2 (women) and 27.8 ± 0.2 (men); HOMA-IR: 2.04 ± 0.05 (women) 2.47 ± 0.09 (men). HOMA-IR differed systematically and in a dose-response fashion across all levels of the eNWO categories (F = 291.3, P < 0.0001). As BMI levels increased, HOMA-IR increased significantly and within each BMI category, higher levels of body fat were associated significantly with higher levels of HOMA-IR. Both high BMI and high body fat percentage are strongly related to insulin resistance. In this study, insulin resistance increased incrementally according to BMI levels primarily and body fat levels secondarily. Consequently, due to the costs associated with precisely measuring body fat, and the accuracy of using BMI independently, we recommend that BMI be used in its standard form to predict insulin resistance and not be supplemented with an estimate of body fat.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2016-07-21T13:54:37Z No. of bitstreams: 1 aecioflaviomeirellesdesouza.pdf: 588675 bytes, checksum: 84d528796e59a48f1e76239e179980a4 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2016-07-22T15:30:38Z (GMT) No. of bitstreams: 1 aecioflaviomeirellesdesouza.pdf: 588675 bytes, checksum: 84d528796e59a48f1e76239e179980a4 (MD5) / Made available in DSpace on 2016-07-22T15:30:38Z (GMT). No. of bitstreams: 1 aecioflaviomeirellesdesouza.pdf: 588675 bytes, checksum: 84d528796e59a48f1e76239e179980a4 (MD5) Previous issue date: 2011-10-10 / Objetivos: verificar a prevalência de resistência insulínica (RI) em portadores de hepatite crônica C não diabéticos e analisar o impacto da mesma sobre os parâmetros laboratoriais e histológicos. Sujeitos e métodos: foram incluídos no estudo 82 pacientes e amostras de sangue foram coletadas para determinação de glicose, perfil lipídico, ALT, AST, ferritina, HOMA-IR, carga viral e genótipo do VHC. HOMA-IR superior a 2,5 foi considerado resistência insulínica. Resultados: RI foi observada em 27% dos pacientes e foi associada a idade, circunferência abdominal e índice de massa corpórea. Quando comparado a pacientes sem RI, aqueles com HOMA-IR superior a 2,5 apresentaram graus mais acentuados de fibrose hepática e atividade necroinflamatória, maiores níveis de aminotransferases e esteatose hepática mais freqüente. Conclusões: É comum a presença de RI em portadores de hepatite crônica C e esta tem como resultado a acentuação da fibrose hepática induzida pelo vírus da hepatite C. DESCRITORES: Hepatite crônica C, fibrose hepática, resistência insulínica, HOMA-IR / Objectives: To determine the prevalence of insulin resistance (IR) in patients nondiabetic with chronic hepatitis C and analyze the impact of insulin resistance on laboratory and histology parameters. Subjects and methods: The study included 82 patients and blood samples were collected for glucose, lipid profile, CRP, ferritin, ALT, AST, HOMA-IR, viral load and HCV genotype. HOMA-IR greater than 2.5 were considered insulin resistance. Results: Insulin resistance was observed in 27% of patients and was associated with age, waist circumference and body mass index. When compared with patients without RI those with insulin resistance had more pronounced stage of hepatic fibrosis and necroinflammatory activity, higher levels of aminotransferases and liver steatosis more frequently. Conclusions: It is often the presence of insulin resistance in patients with chronic hepatitis C and this has resulted in the exacerbation of liver fibrosis induced by HCV.

<p>Insulin resistance has shown to be a precursor to a number of lifestylerelated chronic diseases and abnormalities in adults and is affected by a number of factors including genetics, age, physical activity and acute exercise, diet, obesity, body fat distribution and medication. Physical activity has shown to have marked effects on improving sensitivity to insulin though various physiological mechanisms, and numerous correlation studies have identified a relationship between these two variables, suggesting the beneficial role of exercise on insulin resistance.&nbsp / This study aimed to identify a relationship between current levels of physical activity, physical fitness and insulin resistance in adults between the ages of 35 and 65 years of age residing in a northern suburb community in Cape Town. A total of 186 volunteers participated in this study ranging from healthy individuals to those with diagnosed chronic conditions. Insulin resistance (determined by the homeostasis model assessment of insulin resistance), physical activity (measured by the Global Physical Activity Questionnaire) and five health-related physical fitness tests were measured. The five components included body composition, determined by body mass index and waist circumference, the 3-minute cardiorespiratory step test, the handgrip&nbsp / muscle strength test, one-minute crunches for muscle endurance and the sit-and-reach flexibility test. Spearman correlation was used to identify the relationships between the homeostasis model assessment of insulin resistance, age, body composition and physical activity and fitness.Results showed that body mass index and waist circumference were the only two variables which produced significant correlations with the homeostasis model assessment of insulin resistance (p &lt / 0.019). No physical activity or fitness data produced significant scores with the homeostasis model assessment of insulin resistance. Body mass index in men was the only significant predictor of HOMA-IR and explained 37% of the variance in insulin resistance, whereas in women, only waist circumference was related to HOMA-IR, but explained less than 16% of the variance. Associations between reported MET-minutes from the Global Physical Activity Questionnaire and the four fitness tests indicated significance with handgrip strength (&rho / = 0.17 / p =0.039), one-minute crunches (&rho / = 0.18 / p = 0.024) and sit-and-reach flexibility (&rho / = 0.17 / 0.034). This study has shown that body composition is an important component in influencing insulin resistance therefore physical activity interventions should be targeted at increasing physical activity levels and reducing body weight.</p>

No description available.

<p>Insulin resistance has shown to be a precursor to a number of lifestylerelated chronic diseases and abnormalities in adults and is affected by a number of factors including genetics, age, physical activity and acute exercise, diet, obesity, body fat distribution and medication. Physical activity has shown to have marked effects on improving sensitivity to insulin though various physiological mechanisms, and numerous correlation studies have identified a relationship between these two variables, suggesting the beneficial role of exercise on insulin resistance.&nbsp / This study aimed to identify a relationship between current levels of physical activity, physical fitness and insulin resistance in adults between the ages of 35 and 65 years of age residing in a northern suburb community in Cape Town. A total of 186 volunteers participated in this study ranging from healthy individuals to those with diagnosed chronic conditions. Insulin resistance (determined by the homeostasis model assessment of insulin resistance), physical activity (measured by the Global Physical Activity Questionnaire) and five health-related physical fitness tests were measured. The five components included body composition, determined by body mass index and waist circumference, the 3-minute cardiorespiratory step test, the handgrip&nbsp / muscle strength test, one-minute crunches for muscle endurance and the sit-and-reach flexibility test. Spearman correlation was used to identify the relationships between the homeostasis model assessment of insulin resistance, age, body composition and physical activity and fitness.Results showed that body mass index and waist circumference were the only two variables which produced significant correlations with the homeostasis model assessment of insulin resistance (p &lt / 0.019). No physical activity or fitness data produced significant scores with the homeostasis model assessment of insulin resistance. Body mass index in men was the only significant predictor of HOMA-IR and explained 37% of the variance in insulin resistance, whereas in women, only waist circumference was related to HOMA-IR, but explained less than 16% of the variance. Associations between reported MET-minutes from the Global Physical Activity Questionnaire and the four fitness tests indicated significance with handgrip strength (&rho / = 0.17 / p =0.039), one-minute crunches (&rho / = 0.18 / p = 0.024) and sit-and-reach flexibility (&rho / = 0.17 / 0.034). This study has shown that body composition is an important component in influencing insulin resistance therefore physical activity interventions should be targeted at increasing physical activity levels and reducing body weight.</p>

Magister Artium (Sport, Recreation and Exercise Science) - MA(SRES) / Insulin resistance has shown to be a precursor to a number of lifestylerelated chronic diseases and abnormalities in adults and is affected by a number of factors including genetics, age, physical activity and acute exercise, diet, obesity, body fat distribution and medication. Physical activity has shown to have marked effects on improving sensitivity to insulin though various physiological mechanisms, and numerous correlation studies have identified a relationship between these two variables, suggesting the beneficial role of exercise on insulin resistance. This study aimed to identify a relationship between current levels of physical activity, physical fitness and insulin resistance in adults between the ages of 35 and 65 years of age residing in a northern suburb community in Cape Town. A total of 186 volunteers participated in this study ranging from healthy individuals to those with diagnosed chronic conditions. Insulin resistance (determined by the homeostasis model assessment of insulin resistance), physical activity (measured by the Global Physical Activity Questionnaire) and five health-related physical fitness tests were measured. The five components included body composition, determined by body mass index and waist circumference, the 3-minute cardiorespiratory step test, the handgrip muscle strength test, one-minute crunches for muscle endurance and the sit-and-reach flexibility test. Spearman correlation was used to identify the relationships between the homeostasis model assessment of insulin resistance, age, body composition and physical activity and fitness.Results showed that body mass index and waist circumference were the only two variables which produced significant correlations with the homeostasis model assessment of insulin resistance (p < 0.019). No physical activity or fitness data produced significant scores with the homeostasis model assessment of insulin resistance. Body mass index in men was the only significant predictor of HOMA-IR and explained 37% of the variance in insulin resistance, whereas in women, only waist circumference was related to HOMA-IR, but explained less than 16% of the variance. Associations between reported MET-minutes from the Global Physical Activity Questionnaire and the four fitness tests indicated significance with handgrip strength (&rho; = 0.17; p =0.039), one-minute crunches (&rho; = 0.18; p = 0.024) and sit-and-reach flexibility (&rho; = 0.17; 0.034). This study has shown that body composition is an important component in influencing insulin resistance therefore physical activity interventions should be targeted at increasing physical activity levels and reducing body weight. / South Africa

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / Insulin resistance is common among obese adolescents; however, the extent of this problem is not clear. We conducted a systematic review of PubMed-Medline, CINAHL, The Web of Science, EMBASE and Scopus for observational studies evaluating components defining insulin resistance (insulin, C-peptide and homeostatic model assessment-insulin resistance [HOMA-IR]) in obese adolescents (12–18 years) versus non-obese adolescents. Our systematic review and meta-analysis followed the PRISMA guidelines. Data were combined using a random-effects model and summary statistics were calculated using the mean differences (MDs). 31 studies were included (n = 8655). In 26 studies, fasting insulin levels were higher in obese adolescents when compared to non-obese adolescents (MD = 64.11 pmol/L, 95%CI 49.48–78.75, p < 0.00001). In three studies, fasting C-peptide levels were higher in obese adolescents when compared to non-obese adolescents (MD = 0.29 nmol/L, 95%CI 0.22–0.36, p < 0.00001). In 24 studies, HOMA-IR values were higher in obese adolescents when compared to non-obese adolescents (MD = 2.22, 95%CI 1.78–2.67, p < 0.00001). Heterogeneity of effects among studies was moderate to high. Subgroup analyses showed similar results to the main analyses. Circulating insulin and C-peptide levels and HOMA-IR values were significantly higher in obese adolescents compared to those non-obese. / Revisión por pares

OBJECTIVE: The main objective of the present study was to assess the association between varying amounts of strength training and insulin resistance. Another goal was to assess the influence of several potential confounding variables on the strength training and insulin resistance relationship. Lastly, the role of waist circumference, fat free mass, and body fat percentage on the association between strength training and insulin resistance was assessed. METHODS: This cross-sectional study included 6561 randomly selected men and women in the US. Data were collected using the precise protocol established by NHANES. HOMA-IR was used as the outcome variable. Both time spent strength training and frequency of strength training bouts were used as exposure variables. RESULTS: There was not a statistically significant relationship between strength training and insulin resistance in women. However, after controlling for 10 potential confounding variables, men who reported no strength training had significantly higher levels of HOMA-IR compared to men who reported moderate or high levels of strength training (F = 9.87, P < 0.0001). Odds ratios were also assessed, and 10 potential confounding variables were controlled. Men reporting no strength training had 2.42 times the odds of having insulin resistance compared to men reporting moderate levels of strength training (95% CI: 1.19 to 4.93). Similarly, men reporting no strength training had 2.50 times the odds of having insulin resistance compared to men reporting high levels of strength training (95% CI: 1.25 to 5.00). CONCLUSION: There was a strong relationship between strength training and insulin resistance in US men, but not in US women. Differences in waist circumference, fat free mass, and body fat percentage, as well as demographic and lifestyle measures, do not appear to mediate the relationship.

No description available.