Aims/hypothesis. Increased intra-abdominal fat is associated with insulin resistance and an atherogenic lipoprotein profile. Circulating concentrations of adiponectin, an adipocyte-derived protein, are decreased with insulin resistance. We investigated the relationships between adiponectin and leptin, body fat distribution, insulin sensitivity and lipoproteins. Methods. We measured plasma adiponectin, leptin and lipid concentrations, intra-abdominal and subcutaneous fat areas by CT scan, and insulin sensitivity index (S I ) in 182 subjects (76 M/106F). Results. Adiponectin concentrations were higher in women than in men (7.4±2.9 vs 5.4±2.3 µg/ml, p<0.0001) as were leptin concentrations (19.1±13.7 vs 6.9±5.1 ng/ml, p<0.0001). Women were more insulin sensitive (S I : 6.8±3.9 vs 5.9±4.4×10 −5 min −1 /(pmol/l), p<0.01) and had more subcutaneous (240±133 vs 187±90 cm 2 , p<0.01), but less intra-abdominal fat (82±57 vs 124±68 cm 2 , p<0.0001). By simple regression, adiponectin was positively correlated with age (r=0.227, p<0.01) and S I (r=0.375, p<0.0001), and negatively correlated with BMI (r=−0.333, p<0.0001), subcutaneous (r=−0.168, p<0.05) and intra-abdominal fat (r=−0.35, p<0.0001). Adiponectin was negatively correlated with triglycerides (r=−0.281, p<0.001) and positively correlated with HDL cholesterol (r=0.605, p<0.0001) and Rf, a measure of LDL particle buoyancy (r=0.474, p<0.0001). By multiple regression analysis, adiponectin was related to age (p<0.0001), sex (p<0.005) and intra-abdominal fat (p<0.01). S I was related to intraabdominal fat (p<0.0001) and adiponectin (p<0.0005). Both intra-abdominal fat and adiponectin contributed independently to triglycerides, HDL cholesterol and Rf. Conclusion/interpretation. These data suggest that adiponectin concentrations are determined by intra-abdominal fat mass, with additional independent effects of age and sex. Adiponectin could link intra-abdominal fat with insulin resistance and an atherogenic lipoprotein profile. [Diabetologia (2003) 46:459-469] Keywords Adiponectin, Acrp30, adipoQ, central obesity, subcutaneous fat, intra-abdominal fat, insulin sensitivity, lipids, hepatic lipase, cardiovascular disease, leptin. It is well recognized that obesity and insulin resistance are closely related [1,2,3,4]. Android body fat distribution is associated with insulin resistance more than is a gynoid body fat distribution [5], with the site of abdominal fat distribution being an additional determinant of insulin sensitivity [6,7,8,9,10,11]. We found in both lean and obese subjects that the intraabdominal fat (IAF) depot is a stronger determinant of insulin sensitivity than the subcutaneous fat (SCF) depot [11], while SCF is the main determinant of the plasma concentration of leptin [11], an adipocyte-derived hormone regulating energy metabolism [12,13].

The most frequent component causes for lower-extremity ulcers were trauma, neuropathy, and deformity, which were present in a majority of patients. Clinicians are encouraged to use proven strategies to prevent and decrease the impact of modifiable conditions leading to foot ulcers in patients with diabetes.

The adipocyte hormone, leptin (OB protein), is proposed to be an "adiposity signal" that acts in the brain to lower food intake and adiposity. As plasma leptin levels are elevated in most overweight individuals, obesity may be associated with leptin resistance. To investigate the mechanisms underlying brain leptin uptake and to determine whether reduced uptake may contribute to leptin resistance, we measured immunoreactive leptin levels in plasma and cerebrospinal fluid (CSF) of 53 human subjects. Leptin concentrations in CSF were strongly correlated to the plasma level in a nonlinear manner (r = 0.92; p = 0.0001). Like levels in plasma, CSF leptin levels were correlated to body mass index (r = 0.43; p = 0.001), demonstrating that plasma leptin enters human cerebrospinal fluid in proportion to body adiposity. However, the efficiency of this uptake (measured as the CSF:plasma leptin ratio) was lower among those in the highest as compared with the lowest plasma leptin quintile (5.4-fold difference). We hypothesize that a saturable mechanism mediates CSF leptin transport, and that reduced efficiency of brain leptin delivery among obese individuals with high plasma leptin levels results in apparent leptin resistance.

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Certain foot deformities, reduced skin oxygenation and foot perfusion, poor vision, greater body mass, and both sensory and autonomic neuropathy independently influence foot ulcer risk, thereby providing support for a multifactorial etiology for diabetic foot ulceration.

OBJECTIVE -We sought to determine whether an oral disposition index (DI O ) predicts the development of diabetes over a 10-year period. First, we assessed the validity of the DI O by demonstrating that a hyperbolic relationship exists between oral indexes of insulin sensitivity and ␤-cell function.RESEARCH DESIGN AND METHODS -A total of 613 Japanese-American subjects (322 men and 291 women) underwent a 75-g oral glucose tolerance test (OGTT) at baseline, 5 years, and 10 years. Insulin sensitivity was estimated as 1/fasting insulin or homeostasis model assessment of insulin sensitivity (HOMA-S). Insulin response was estimated as the change in insulin divided by change in glucose from 0 to 30 min (⌬I 0 -30 /⌬G 0 -30 ).RESULTS -⌬I 0 -30 /⌬G 0 -30 demonstrated a curvilinear relationship with 1/fasting insulin and HOMA-S with a left and downward shift as glucose tolerance deteriorated. The confidence limits for the slope of the log e -transformed estimates included Ϫ1 for ⌬I 0 -30 /⌬G 0 -30 versus 1/fasting insulin for all glucose tolerance groups, consistent with a hyperbolic relationship. When HOMA-S was used as the insulin sensitivity measure, the confidence limits for the slope included Ϫ1 only for subjects with normal glucose tolerance (NGT) or impaired fasting glucose (IFG)/impaired glucose tolerance (IGT) but not diabetes. On the basis of this hyperbolic relationship, the product of ⌬I 0 -30 /⌬G 0 -30 and 1/fasting insulin was calculated (DI O ) and decreased from NGT to IFG/IGT to diabetes (P Ͻ 0.001). Among nondiabetic subjects at baseline, baseline DI O predicted cumulative diabetes at 10 years (P Ͻ 0.001) independent of age, sex, BMI, family history of diabetes, and baseline fasting and 2-h glucose concentrations.CONCLUSIONS -The DI O provides a measure of ␤-cell function adjusted for insulin sensitivity and is predictive of development of diabetes over 10 years.

OBJECTIVE -The ability of readily available clinical information to predict the occurrence of diabetic foot ulcer has not been extensively studied. We conducted a prospective study of the individual and combined effects of commonly available clinical information in the prediction of diabetic foot ulcer occurrence.RESEARCH DESIGN AND METHODS -We followed 1,285 diabetic veterans without foot ulcer for this outcome with annual clinical evaluations and quarterly mailed questionnaires to identify foot problems. At baseline we assessed age; race; weight; current smoking; diabetes duration and treatment; HbA 1c (A1C); visual acuity; history of laser photocoagulation treatment, foot ulcer, and amputation; foot shape; claudication; foot insensitivity to the 10-g monofilament; foot callus; pedal edema; hallux limitus; tinea pedis; and onychomycosis. Cox proportional hazards modeling was used with backwards stepwise elimination to develop a prediction model for the first foot ulcer occurrence after the baseline examination.RESULTS -At baseline, subjects were 62.4 years of age on average and 98% male. Mean follow-up duration was 3.38 years, during which time 216 foot ulcers occurred, for an incidence of 5.0/100 person-years. Significant predictors (P Յ 0.05) of foot ulcer in the final model (hazard ratio, 95% CI) included A1C (1.10, 1.06 -1.15), impaired vision (1.48, 1.00 -2.18), prior foot ulcer (2.18, 1.61-2.95), prior amputation (2.57, 1.60 -4.12), monofilament insensitivity (2.03, 1.50 -2.76), tinea pedis (0.73, 0.54 -0.98), and onychomycosis (1.58, 1.16 -2.16). Area under the receiver operating characteristic curve was 0.81 at 1 year and 0.76 at 5 years.CONCLUSIONS -Readily available clinical information has substantial predictive power for the development of diabetic foot ulcer and may help in accurately targeting persons at high risk of this outcome for preventive interventions. Diabetes Care 29:1202-1207, 2006D iabetic foot ulcer and amputation continue to cause considerable morbidity among persons with diabetes (1). Foot ulcer has been recognized as an important antecedent of lower extremity amputation in multiple studies (2,3). Progress has occurred in understanding the pathogenesis of these complications (4), and methods to assist in the prediction of these outcomes have also been developed using various modalities, including lower limb sensory testing (5), thermography (6), and assessment of peak plantar pressure (7). Some of these modalities are unavailable to the vast majority of primary care clinical practitioners who provide much of the preventive and acute care of persons with diabetes.Also, the use of multiple risk indicators in combination to assist in the future prediction of diabetes complications has not been thoroughly explored and reported in a manner that permits assessment of prediction accuracy.Given the need for a prediction model of diabetic foot ulcer that utilizes multiple risk indicators that would be available in all clinical encounters that take place between patients and primary care or n...

Beginning in 2005, the incidence of suicide deaths in the US military began to sharply increase. Unique stressors, such as combat deployments, have been assumed to underlie the increasing incidence. Previous military suicide studies, however, have relied on case series and cross-sectional investigations and have not linked data during service with postservice periods. OBJECTIVE To prospectively identify and quantify risk factors associated with suicide in current and former US military personnel including demographic, military, mental health, behavioral, and deployment characteristics.