https://ogma.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:52825 8.38 µmol/L) presented relatively elevated serum creatinine levels and a higher number of people with CKD than those in the lower quartiles. TMAO levels were significantly correlated with kidney function biomarkers, including estimated glomerular filtration rate and urinary albumin to creatinine ratio. The association between TMAO and CKD was evident (p < 0.0001) and remained significant after adjusting for risk factors of kidney disease, including age, gender, body mass index, duration of diabetes, and smoking. These findings suggest the association between plasma TMAO and CKD in patients with T2D.]]> Wed 28 Feb 2024 16:34:56 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:49974 Wed 28 Feb 2024 16:14:53 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:51305 Wed 28 Feb 2024 16:11:03 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:34918 Wed 24 Nov 2021 15:53:19 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:30988 2 and the area under the receiver-operating characteristic curve (AUC). Models with and without the genetic risk score (GRS) were compared using the log likelihood ratio Chi-squared test and AUCs. Multiplicative interaction between genetic and environmental risk factors was assessed via logistic regression within and across ancestral groups. Interactions were assessed for the GRS and its 62 constituent variants. Results: The models including environmental risk factors only had pseudo R² values of 16.5–28.3% and AUC of 0.75–0.83. Incorporating a genetic score aggregating 62 T2D-associated risk variants significantly increased the model fit (likelihood ratio P-value of 2.50 × 10⁻⁴–4.83 × 10⁻¹²) and increased the pseudo R² by about 1–2% and AUC by 1–3%. None of the gene–environment interactions reached significance after multiple testing adjustment, either for the GRS or individual variants. For individual variants, 33 out of 310 tested associations showed nominal statistical significance with 0.001 < P < 0.05. Conclusion: This study suggests that known genetic risk variants contribute a significant but small amount to overall T2D risk variation in Malaysian population groups. If gene–environment interactions involving common genetic variants exist, they are likely of small effect, requiring substantially larger samples for detection.]]> Wed 23 Feb 2022 16:06:27 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:48504 Wed 22 Mar 2023 17:09:43 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:51280 Wed 20 Sep 2023 11:45:13 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:34382 Wed 19 Jun 2019 15:24:11 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:32768 Wed 17 Nov 2021 16:31:28 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:45429 Wed 13 Mar 2024 15:49:55 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:52416 Wed 11 Oct 2023 11:59:18 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:15776 Wed 11 Apr 2018 16:59:53 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:15020 Wed 11 Apr 2018 16:06:42 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:14917 Wed 11 Apr 2018 16:00:58 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:16817 Wed 11 Apr 2018 15:56:18 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:16813 Wed 11 Apr 2018 14:42:05 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:9361 Wed 11 Apr 2018 14:11:31 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:21951 Wed 11 Apr 2018 12:43:09 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:20351 Wed 11 Apr 2018 12:14:21 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:20352 Wed 11 Apr 2018 11:01:21 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:15484 Wed 11 Apr 2018 11:00:11 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:16808 Wed 11 Apr 2018 10:57:45 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:17386 Wed 11 Apr 2018 09:59:50 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:22522 Wed 11 Apr 2018 09:19:17 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:20369 Wed 10 Jul 2019 15:20:28 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:15464 Wed 10 Jul 2019 15:19:19 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:21916 Wed 10 Jul 2019 15:18:42 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:29399 Wed 10 Jul 2019 15:16:59 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:32032 A receptors in human islet β cells as biological sensors and reveal that 100–1000 nM GABA elicit the maximal opening frequency of the single-channels. In saturating GABA, the channels desensitized and stopped working. GABA modulated insulin exocytosis and glucose-stimulated insulin secretion. GABA_A receptor currents were enhanced by the benzodiazepine diazepam, the anesthetic propofol and the incretin glucagon-like peptide-1 (GLP-1) but not affected by the hypnotic zolpidem. In type 2 diabetes (T2D) islets, single-channel analysis revealed higher GABA affinity of the receptors. The findings reveal unique GABA_A receptors signaling in human islets β cells that is GABA concentration-dependent, differentially regulated by drugs, modulates insulin secretion and is altered in T2D.]]> Wed 10 Jul 2019 15:15:48 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:30990 Wed 10 Jul 2019 15:13:10 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:32912 Wed 09 Mar 2022 16:02:02 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:24609 trend=0·015). A similar but non-significant trend was seen in overweight men. After adjusting for BMI, no associations were found between n-3I and fasting blood glucose, HbA1c, insulin or HOMA-IR. In conclusion, higher erythrocyte n-3 PUFA status may be protective against the development of T2D in overweight women. Further research is warranted to determine whether dietary interventions that improve n-3 PUFA status can improve measures of IR, and to further elucidate sex-dependent differences.]]> Wed 09 Mar 2022 15:58:29 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:29807 Wed 09 Feb 2022 15:58:30 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:47266 Wed 06 Mar 2024 15:13:30 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:32856 Wed 02 Mar 2022 14:29:23 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:47663 Tue 24 Jan 2023 15:40:59 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:51448 6.40 µmol/L) were associated with the risk of diabetes (OR = 3.36, 95% CI [1.26, 9.04], p = 0.02). The results presented suggest an association between plasma TMAO levels and T2D. A significant correlation was found between red meat consumption and increased levels of TMAO in T2D patients. A longitudinal study is warranted to further evaluate the correlation between TMAO and T2D.]]> Tue 05 Sep 2023 17:55:02 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:52121 Thu 28 Sep 2023 15:03:25 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:25049 Thu 28 Oct 2021 13:05:05 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:30667 Thu 17 Feb 2022 09:30:17 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:30998 1c, fasting insulin, bodyweight, waist-to-hip ratio, BMI, and risk of type 2 diabetes, using a standardised analysis plan, meta-analyses, and weighted gene-centric scores. Findings: Data were available for more than 550 000 individuals and 51 623 cases of type 2 diabetes. Combined analyses of four independent PCSK9 variants (rs11583680, rs11591147, rs2479409, and rs11206510) scaled to 1 mmol/L lower LDL cholesterol showed associations with increased fasting glucose (0·09 mmol/L, 95% CI 0·02 to 0·15), bodyweight (1·03 kg, 0·24 to 1·82), waist-to-hip ratio (0·006, 0·003 to 0·010), and an odds ratio for type diabetes of 1·29 (1·11 to 1·50). Based on the collected data, we did not identify associations with HbA _1c (0·03%, −0·01 to 0·08), fasting insulin (0·00%, −0·06 to 0·07), and BMI (0·11 kg/m², −0·09 to 0·30). Interpretation: PCSK9 variants associated with lower LDL cholesterol were also associated with circulating higher fasting glucose concentration, bodyweight, and waist-to-hip ratio, and an increased risk of type 2 diabetes. In trials of PCSK9 inhibitor drugs, investigators should carefully assess these safety outcomes and quantify the risks and benefits of PCSK9 inhibitor treatment, as was previously done for statins.]]> Thu 17 Feb 2022 09:24:46 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:36980 Thu 14 Mar 2024 12:34:02 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:14164 Thu 11 Jul 2019 14:39:07 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:15943 Thu 11 Jul 2019 11:42:44 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:36076 Thu 09 Dec 2021 11:02:41 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:46927 Thu 08 Dec 2022 12:22:07 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:37017 Thu 06 Aug 2020 14:41:23 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:47330 Thu 02 May 2024 15:45:08 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:9373 Sat 24 Mar 2018 10:45:36 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:7627 Sat 24 Mar 2018 10:44:46 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:9383 Sat 24 Mar 2018 10:44:15 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:7017 Sat 24 Mar 2018 08:38:05 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:7614 Sat 24 Mar 2018 08:34:43 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:15483 Sat 24 Mar 2018 08:21:26 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:13337 Sat 24 Mar 2018 08:17:02 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:11062 25 kg/m2 [odds ratio (OR) 4.50, 95% confidence interval (CI) (3.12, 6.51)], a family history of diabetes [OR 3.80, 95% CI (2.67, 5.33)] and use of insulin during pregnancy [OR 1.92, 95% CI (1.31, 2.61)]. Conclusions: Although women with known risk factors for Type 2 diabetes were more likely to perceive their risk as high, we found that one third still considered themselves to be at low or very low risk for the development of diabetes. These results suggest a need for increased awareness of gestational diabetes as a strong predictor of Type 2 diabetes risk.]]> Sat 24 Mar 2018 08:13:33 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:12324 Sat 24 Mar 2018 08:11:37 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:11419 s] = 0.5983) and weakly with generic measures (r_s=-0.028 for ADDQoL present global QOL scores, 0.310 for EQ-VAS, 0.164 for EQ-5D and 0.281 for SF-6D). Participants who required insulin, those with diabetes-related complications and those who were overweight/obese reported lower AWI scores, but the differences were not statistically significant. Importance scores of zero were assigned 1–28% of the time and the NA options were selected 3–49% of the time. Conclusions: The ADDQoL is reliable and probably valid for assessing QOL among Chinese-speaking Singaporeans with T2DM, although known-groups validity warrants further investigation.]]> Sat 24 Mar 2018 08:11:32 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:18125 Sat 24 Mar 2018 08:04:47 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:19446 Sat 24 Mar 2018 08:02:17 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:20494 Sat 24 Mar 2018 07:59:06 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:16970 Sat 24 Mar 2018 07:55:24 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:19183 Sat 24 Mar 2018 07:55:03 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:21267 Sat 24 Mar 2018 07:54:42 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:21309 n = 287, 53.8% males, mean age = 61.6 ± 11.8 years). Theoretical constructs across the three theories were tested to prospectively predict PA behaviour (objective and self-report) across three 6-month time intervals (baseline-6, 6-12, 12-18 months) using structural equation modelling. PA outcomes were steps/3 days (objective) and minutes of MET-weighted PA/week (self-report). Results: The mean proportion of variance in PA explained by these models was 6.5% for objective PA and 8.8% for self-report PA. Direct pathways to PA outcomes were stronger for self-report compared with objective PA. Conclusions: These theories explained a small proportion of the variance in longitudinal PA studies. Theory development to guide interventions for increasing and maintaining PA in adults with type 2 diabetes requires further research with objective measures. Theory integration across social-cognitive models and the inclusion of ecological levels are recommended to further explain PA behaviour change in this population. Statement of contribution What is already known on this subject? Social-cognitive theories are able to explain partial variance for physical activity (PA) behaviour. What does this study add? The testing of three theories in a longitudinal design over 3, 6-month time intervals. The parallel use and comparison of both objective and self-report PA measures in testing these theories.]]> Sat 24 Mar 2018 07:54:40 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:21193 Sat 24 Mar 2018 07:52:34 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:21644 Sat 24 Mar 2018 07:52:20 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:19393 Sat 24 Mar 2018 07:52:04 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:21370 n = 93) from the control group (standard PA materials, n = 44) and the full intervention group (control + stage-matched printed material and telephone counseling, n = 49) of a larger PA intervention trial were included. PA outcomes were minutes of MET weighted moderate and vigorous PA/week (self-report) and steps/3-days (objective) recorded at baseline and 12-months. Social-cognitive constructs were measured and tested in a mediating variable framework. Results: Perceived behavioral control and barrier self-efficacy mediated intervention effects on objective PA (proportion of intervention effect mediated = 18% and 24% respectively). Intention was a mediator of objective PA (23%). Conclusion: Perceived behavior control, barrier self-efficacy, and intention are effective mechanisms of PA behavior change in women with T2DM.]]> Sat 24 Mar 2018 07:51:26 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:5677 Sat 24 Mar 2018 07:47:32 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:27532 Sat 24 Mar 2018 07:28:58 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:28266 Sat 24 Mar 2018 07:28:35 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:27574 Sat 24 Mar 2018 07:23:41 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:23677 Sat 24 Mar 2018 07:13:57 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:23062 Sat 24 Mar 2018 07:12:27 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:38423 Mon 29 Jan 2024 17:59:52 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:38451 Mon 29 Jan 2024 17:57:23 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:38396 Mon 29 Jan 2024 17:47:06 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:32165 Mon 23 Sep 2019 13:37:13 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:32908 Mon 23 Sep 2019 13:18:51 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:44545 Mon 17 Oct 2022 09:31:31 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:44190 2peak]); ii) MICT (45min of cycling at 60% VO_2peak); or PLA. Training groups exercised thrice weekly for 12 weeks. Central arterial stiffness, hemodynamics and CVD risk factors were assessed at baseline and post-intervention. Analysis of covariance (ANCOVA) was used to examine changes following HIIT, MICT and PLA. Results: Thirty-five participants (age: 55.1 ± 1.4 years, BMI: 36.1 ± 0.8 kg/m²) completed the study. A significant intervention effect was found for changes in pulse wave velocity (PWV) (p = .03), which reduced with HIIT (−0.3 ± 0.9 m/s) and MICT (−0.1 ± 1.1 m/s) but increased with PLA (0.8 ± 1.6 m/s). There was a significant intervention effect for changes in V̇O_2peak (p < .01), glycosylated hemoglobin (p = .03), systolic blood pressure (p b .01), and waist circumference (p = .03), which all improved following MICT or HIIT but not PLA; there was no difference between MICT and HIIT. Conclusions: Twelve minutes of low-volumeHIIT perweek leads to improvements in central arterial stiffness and cardiovascular health in inactive individuals with obesity and T2D.]]> Mon 10 Oct 2022 11:02:37 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:53590 PD >NG, p=0.0046). Post-hoc analysis indicated significantly higher plasma NfL levels in the T2D [12.4 (5.21) pg/mL] group than in the PD [10.2 (4.13) pg/mL] and NG [8.37 (5.65) pg/mL] groups. The relationship between diabetes status and NfL remained significant after adjusting for age, sex, BMI, HOMA-IR and physical activity (adjusted r2 = 0.271, p = 0.035). Conclusions: These results show biomarker evidence of neurodegeneration in adults at risk or with T2D. Larger sample size and longitudinal analysis are required to better understand the application of NfL in people with risk and overt T2D.]]> Fri 08 Dec 2023 15:47:18 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:24091 50 years) and BMI category (25.0-29.9, 30.0-35.9, and 35.0-40 kg/m²) and individually randomized (1:1 ratio) to the intervention (n=53) or waitlist control groups (n=48). Intervention: The intervention group received the PULSE Program, which contained print and video resources on weight loss (Self-Help, Exercise and Diet using Internet Technology [SHED-IT] Weight Loss Program), diet modification, and exercise for Type 2 diabetes mellitus prevention. The waitlist control group received no information until 6 months. Main outcome measures: Data were collected from September 2012 to September 2013 and analyzed in 2014-2015. Linear mixed models (intention-to-treat) were used to determine group X time interactions (differences between groups in changes over time) at 6 months for the primary outcome (weight), glycated hemoglobin, and several secondary outcomes (significance level, p<0.05). Results: Differences between groups in mean changes from baseline to 6 months (group x time interaction) favored the intervention over control group for weight loss (-5.50 kg, 95% CI=-7.40 kg, -3.61 kg, p<0.001, Cohen's d=1.15), glycated hemoglobin (-0.2%, 95% CI=-0.3%, -0.1%, p=0.002, d=0.64), and BMI, waist circumference, body fat percentage, aerobic fitness, and lower body muscular fitness (all p<0.05). No group × time effects were observed for fasting plasma glucose, upper body muscular fitness, physical activity, or energy intake. Conclusions: The PULSE Program improved several Type 2 diabetes mellitus risk factors in men, including weight and glycated hemoglobin. These findings provide evidence for a self-administered and gender-tailored lifestyle intervention, which has potential for dissemination in community settings.]]> Fri 03 Dec 2021 10:33:45 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:24889 Fri 03 Dec 2021 10:32:02 AEDT ]]>