Increased Rate of Hospitalization for Diabetes and Residential Proximity of Hazardous Waste Sites

BACKGROUND: Epidemiologic studies suggest that there may be an association between environmental exposure to persistent organic pollutants (POPs) and diabetes. OBJECTIVE: The aim of this study was to test the hypothesis that residential proximity to POP-contaminated waste sites result in increased rates of hospitalization for diabetes. METHODS: We determined the number of hospitalized patients 25–74 years of age diagnosed with diabetes in New York State exclusive of New York City for the years 1993–2000. Descriptive statistics and negative binomial regression were used to compare diabetes hospitalization rates in individuals who resided in ZIP codes containing or abutting hazardous waste sites containing POPs (“POP” sites); ZIP codes containing hazardous waste sites but with wastes other than POPs (“other” sites); and ZIP codes without any identified hazardous waste sites (“clean” sites). RESULTS: Compared with the hospitalization rates for diabetes in clean sites, the rate ratios for diabetes discharges for people residing in POP sites and “other” sites, after adjustment for potential confounders were 1.23 [95% confidence interval (CI), 1.15–1.32] and 1.25 (95% CI, 1.16–1.34), respectively. In a subset of POP sites along the Hudson River, where there is higher income, less smoking, better diet, and more exercise, the rate ratio was 1.36 (95% CI, 1.26–1.47) compared to clean sites. CONCLUSIONS: After controlling for major confounders, we found a statistically significant increase in the rate of hospitalization for diabetes among the population residing in the ZIP codes containing toxic waste sites

Polychlorinated Biphenyl (PCB) Exposure and Diabetes: Results from the Anniston Community Health Survey

Background: Polychlorinated biphenyls (PCBs) manufactured in Anniston, Alabama, from 1929 to 1971 caused significant environmental contamination. The Anniston population remains one of the most highly exposed in the world

Синантропные членистоногие и их роль в развитии аллергических заболеваний

Synanthropic arthropods and their role in occurrence of allergic diseases.Синантропные членистоногие и их роль в развитии аллергических заболеваний

The Influence of the Brain‐Derived Neurotropic Factor Val66Met ‐Genotype and HMG‐CoA Reductase Inhibitors on Insulin Resistance in the Schizophrenia and Bipolar Populations

Introduction: The brain‐derived neurotrophic factor (BDNF) Val66Met variant and HMG‐COA reductase inhibitors (statins) have been implicated in insulin resistance with a possible increased risk of diabetes. We sought to determine the effect of the BDNF Met variant and statin medication use on insulin resistance in schizophrenia and bipolar disorder using the homeostasis model assessment of insulin resistance (HOMA‐IR). Methods: A cross‐sectional design was used and patients with diabetes or on any medications affecting glucose regulation were ‐excluded. Associations between insulin resistance and genotype were then analyzed by ANOVA and regression analysis. Subjects were grouped by BDNF genotype as well as presence of statin. Results: Two hundred fifty‐two subjects with a mean age of 44 years were included. The group was 53% male and 41% had a diagnosis of bipolar disorder; 78% and 19% were receiving atypical antipsychotics (AAPs) and statin medications, respectively. Analysis showed schizophrenia subjects with the BDNF met allele as well as schizophrenia subjects with both the BDNF met allele and were receiving a statin had significantly higher HOMA‐IR values compared to the other groups ( p = 0.046 and p = 0.016, respectively). Conclusions: Our results suggest that in the metabolically high‐risk population of schizophrenia the BDNF met allele alone and in combination with statin medications is associated with higher insulin resistance values. This was not seen in the bipolar population. Further validation of these associations remains necessary. Clin Trans Sci 2012; Volume 5: 486–490Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95082/1/cts.12001.pd

Dimensional analysis of MINMOD leads to definition of the disposition index of glucose regulation and improved simulation algorithm

BACKGROUND: Frequently Sampled Intravenous Glucose Tolerance Test (FSIVGTT) together with its mathematical model, the minimal model (MINMOD), have become important clinical tools to evaluate the metabolic control of glucose in humans. Dimensional analysis of the model is up to now not available. METHODS: A formal dimensional analysis of MINMOD was carried out and the degree of freedom of MINMOD was examined. Through re-expressing all state variable and parameters in terms of their reference scales, MINMOD was transformed into a dimensionless format. Previously defined physiological indices including insulin sensitivity, glucose effectiveness, and first and second phase insulin responses were re-examined in this new formulation. Further, the parameter estimation from FSIVGTT was implemented using both the dimensional and the dimensionless formulations of MINMOD, and the performances were compared utilizing Monte Carlo simulation as well as real human FSIVGTT data. RESULTS: The degree of freedom (DOF) of MINMOD was found to be 7. The model was maximally simplified in the dimensionless formulation that normalizes the variation in glucose and insulin during FSIVGTT. In the new formulation, the disposition index (Dl), a composite parameter known to be important in diabetes pathology, was naturally defined as one of the dimensionless parameters in the system. The numerical simulation using the dimensionless formulation led to a 1.5–5 fold gain in speed, and significantly improved accuracy and robustness in parameter estimation compared to the dimensional implementation. CONCLUSION: Dimensional analysis of MINMOD led to simplification of the model, direct identification of the important composite factors in the dynamics of glucose metabolic control, and better simulations algorithms

Assessment of insulin resistance by a 13C glucose breath test: a new tool for early diagnosis and follow-up of high-risk patients

<p>Abstract</p> <p>Background/Aims</p> <p>Insulin resistance (IR) plays an important role in the pathogenesis of diabetes and non-alcoholic fatty liver disease (NAFLD). Current methods for insulin resistance detection are cumbersome, or not sensitive enough for early detection and follow-up. The BreathID^®system can continuously analyse breath samples in real-time at the point-of-care. Here we determined the efficacy of the BreathID^®using the ¹³C-Glucose breath test (GBT) for evaluation of insulin resistance.</p> <p>Methods</p> <p>Twenty healthy volunteers were orally administered 75 mg of ¹³C-glucose 1-¹³C. An oral glucose tolerance test (OGTT) was performed immediately; followed by serum glucose and insulin level determinations using GBT. GBT and OGTT were repeated following exercise, which alters insulin resistance levels.</p> <p>Results</p> <p>Within-subject correlations of GBT parameters with serum glucose and serum insulin levels were high. Before and after exercise, between-subjects correlations were high between the relative insulin levels and the % dose recoveries at 90 min (PDR 90), and the cumulative PDRs at 60 min (CPDR 60). Pairwise correlations were identified between pre-exercise Homeostasis Model Assessment (HOMA) IR at 90 min and PDR 90; HOMA B (for beta cell function) 120 and CPDR 30; HOMA IR 60 and peak time post-exercise; and HOMA B 150 with PDR 150.</p> <p>Conclusions</p> <p>The non-invasive real-time BreathID^®GBT reliably assesses changes in liver glucose metabolism, and the degree of insulin resistance. It may serve as a non-invasive tool for early diagnosis and follow up of patients in high-risk groups.</p