Characteristics of an Adult Population With Newly Diagnosed Type 2 Diabetes: The relation of obesity and age of onset

OBJECTIVE — To determine whether adults diagnosed with type 2 diabetes at 18–44 years of age (early type 2 diabetes) have different metabolic profiles at diagnosis than adults diagnosed at $45 years of age (usual type 2 diabetes). RESEARCH DESIGN AND METHODS — Within a health maintenance organization, we studied characteristics among 2,437 adults newly diagnosed with type 2 diabetes between 1996 and 1998 who had measured weight, HbA1c, blood pressure, and cholesterol within 3 months of diagnosis. We abstracted clinical data from electronic medical records. We compared mean and proportional differences with parametric t tests and x2 analyses, respectively. We used multiple logistic regression to identify the factors independently associated with the onset group (early vs. usual type 2 diabetes). RESULTS — There was an inverse linear relationship between BMI and age at diagnosis of type 2 diabetes (P, 0.001). On univariate analysis, adults with early type 2 diabetes were more obese (BMI 39 vs. 33 kg/m2, P, 0.001), were more likely to be female (P 5 0.04), had slightly worse glycemic control (HbA1c 7.7 vs. 7.5%, P 5 0.03), had a higher prevalence of diastolic hypertension (37 vs. 26%, P, 0.001), despite a lower prevalence of systolic hypertension (3

Modulating an oxidative-inflammatory cascade: potential new treatment strategy for improving glucose metabolism, insulin resistance, and vascular function

Type 2 diabetes is a result of derangement of homeostatic systems of metabolic control and immune defense. Increases in visceral fat and organ adipose, environmental factors and genetic predisposition create imbalances of these homeostatic mechanisms, ultimately leading to a condition in which the oxidative environment cannot be held in check. A significant imbalance between the production of reactive oxygen species and antioxidant defenses, a condition called to oxidative stress, ensues, leading to alterations in stress-signalling pathways and potentially end-organ damage. Oxidative stress and metabolic inflammation upregulate the expression pro-inflammatory cytokines, including tissue necrosis factor alpha, monocyte chemoattractant protein-1 and interleukin-6, as well as activating stress-sensitive kinases, such as c-Jun N-terminal kinase (JNK), phosphokinase C isoforms, mitogen-activated protein kinase and inhibitor of kappa B kinase. The JNK pathway (specifically JNK-1) appears to be a regulator that triggers the oxidative-inflammation cascade that, if left unchecked, can become chronic and cause abnormal glucose metabolism. This can lead to insulin resistance and dysfunction of the vasculature and pancreatic β-cell. The series of events set in motion by the interaction between metabolic inflammation and oxidative stress constitutes an ‘oxidative-inflammatory cascade’, a delicate balance driven by mediators of the immune and metabolic systems, maintained through a positive feedback loop. Modulating an oxidative-inflammation cascade may improve glucose metabolism, insulin resistance and vascular function, thereby slowing the development and progression to cardiovascular diseases and type 2 diabetes

Indicators of "Healthy Aging" in older women (65-69 years of age). A data-mining approach based on prediction of long-term survival

<p>Abstract</p> <p>Background</p> <p>Prediction of long-term survival in healthy adults requires recognition of features that serve as early indicators of successful aging. The aims of this study were to identify predictors of long-term survival in older women and to develop a multivariable model based upon longitudinal data from the Study of Osteoporotic Fractures (SOF).</p> <p>Methods</p> <p>We considered only the youngest subjects (<it>n </it>= 4,097) enrolled in the SOF cohort (65 to 69 years of age) and excluded older SOF subjects more likely to exhibit a "frail" phenotype. A total of 377 phenotypic measures were screened to determine which were of most value for prediction of long-term (19-year) survival. Prognostic capacity of individual predictors, and combinations of predictors, was evaluated using a cross-validation criterion with prediction accuracy assessed according to time-specific AUC statistics.</p> <p>Results</p> <p>Visual contrast sensitivity score was among the top 5 individual predictors relative to all 377 variables evaluated (mean AUC = 0.570). A 13-variable model with strong predictive performance was generated using a forward search strategy (mean AUC = 0.673). Variables within this model included a measure of physical function, smoking and diabetes status, self-reported health, contrast sensitivity, and functional status indices reflecting cumulative number of daily living impairments (HR ≥ 0.879 or RH ≤ 1.131; P < 0.001). We evaluated this model and show that it predicts long-term survival among subjects assigned differing causes of death (e.g., cancer, cardiovascular disease; P < 0.01). For an average follow-up time of 20 years, output from the model was associated with multiple outcomes among survivors, such as tests of cognitive function, geriatric depression, number of daily living impairments and grip strength (P < 0.03).</p> <p>Conclusions</p> <p>The multivariate model we developed characterizes a "healthy aging" phenotype based upon an integration of measures that together reflect multiple dimensions of an aging adult (65-69 years of age). Age-sensitive components of this model may be of value as biomarkers in human studies that evaluate anti-aging interventions. Our methodology could be applied to data from other longitudinal cohorts to generalize these findings, identify additional predictors of long-term survival, and to further develop the "healthy aging" concept.</p