METHODS: We randomized 108 overweight and obese patients with T2D (46 M/62F; age 60 ± 10 years; HbA1c 8.07 ± 1.05%; weight 101.4 ± 21.1 kg and BMI 35.2 ± 7.7 kg/m2) into three groups. Group A met with RDN to develop an individualized eating plan. Group B met with RDN and followed a structured meal plan. Group C did similar to group B and received weekly phone support by RDN.
RESULTS: After 16 weeks, all three groups had a significant reduction of their energy intake compared to baseline. HbA1c did not change from baseline in group A, but decreased significantly in groups B (- 0.66%, 95% CI -1.03 to - 0.30) and C (- 0.61%, 95% CI -1.0 to - 0.23) (p value for difference among groups over time waist circumference.
CONCLUSION: Structured NT alone improves glycemia in comparison to individualized eating plans in overweight and obese patients with T2D. It also reduces other important cardiovascular disease risk factors like body fat percentage and waist circumference.
TRIAL REGISTRATION: The trial was retrospectively registered at clinicaltrials.gov( NCT02520050 ).
METHODS: A sample of 3895 individuals without known diabetes underwent detailed interview and health examination, including anthropometric and biochemical evaluation, between 2004 and 2007. Pearson's correlation, analysis of variance and multiple linear regression analyses were used to examine the influence of ethnicity on HbA(1c) .
RESULTS: As fasting plasma glucose increased, HbA(1c) increased more in Malays and Indians compared with Chinese after adjustment for age, gender, waist circumference, serum cholesterol, serum triglyceride and homeostasis model assessment of insulin resistance (P-interaction < 0.001). This translates to an HbA(1c) difference of 1.1 mmol/mol (0.1%, Indians vs. Chinese), and 0.9 mmol/mol (0.08%, Malays vs. Chinese) at fasting plasma glucose 5.6 mmol/l (the American Diabetes Association criterion for impaired fasting glycaemia); and 2.1 mmol/mol (0.19%, Indians vs. Chinese) and 2.6 mmol/mol (0.24%, Malays vs. Chinese) at fasting plasma glucose 7.0 mmol/l, the diagnostic criterion for diabetes mellitus.
CONCLUSIONS: Using HbA(1c) in place of fasting plasma glucose will reclassify different proportions of the population in different ethnic groups. This may have implications in interpretation of HbA(1c) results across ethnic groups and the use of HbA(1c) for diagnosing diabetes mellitus.
METHODS: In this cross-sectional study, 482 adults (223 men, 259 women) aged ≥18 years old were measured for body mass index (BMI), waist circumference (WC), waist-height ratio (WHtR), waist-hip ratio (WHR), and blood pressure. Receiver operating characteristic (ROC) analysis was used to determine the predictive ability of obesity indices for hypertension in men and women. Gender-specific logistic regression analyses were done to examine the association between obesity, defined by BMI, WC, WHtR and WHR, and hypertension.
RESULTS: Prevalence of hypertension was 25.5%. Overall, WHtR was the best predictor of the presence of hypertension, in both men and women. The optimal WHtR cut-off values for hypertension were 0.45 and 0.52 in men and women, respectively. Obese adults with WHtR ≥0.5 had about two times increased odds of having hypertension compared to non-obese adults.
CONCLUSIONS: WHtR may serve as a simple and inexpensive screening tool to identify individuals with hypertension in this relatively difficult to reach population.
METHODS AND FINDINGS: The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of <0.05 was considered statistically significant. In multivariable-adjusted conditional logistic regression models with BMI used to define adiposity, compared with metabolically healthy/normal weight individuals, we observed a higher colorectal cancer risk among metabolically unhealthy/normal weight (odds ratio [OR] = 1.59, 95% CI 1.10-2.28) and metabolically unhealthy/overweight (OR = 1.40, 95% CI 1.01-1.94) participants, but not among metabolically healthy/overweight individuals (OR = 0.96, 95% CI 0.65-1.42). Among the overweight individuals, lower colorectal cancer risk was observed for metabolically healthy/overweight individuals compared with metabolically unhealthy/overweight individuals (OR = 0.69, 95% CI 0.49-0.96). These associations were generally consistent when waist circumference was used as the measure of adiposity. To our knowledge, there is no universally accepted clinical definition for using C-peptide level as an indication of hyperinsulinaemia. Therefore, a possible limitation of our analysis was that the classification of individuals as being hyperinsulinaemic-based on their C-peptide level-was arbitrary. However, when we used quartiles or the median of C-peptide, instead of tertiles, as the cut-point of hyperinsulinaemia, a similar pattern of associations was observed.
CONCLUSIONS: These results support the idea that individuals with the metabolically healthy/overweight phenotype (with normal insulin levels) are at lower colorectal cancer risk than those with hyperinsulinaemia. The combination of anthropometric measures with metabolic parameters, such as C-peptide, may be useful for defining strata of the population at greater risk of colorectal cancer.
METHODS: In this investigator-initiated, single-arm, open-label, pilot study, nine biopsy-proven NASH patients with T2DM were given empagliflozin 25 mg daily for 24 weeks. Liver biopsy was repeated at the end of treatment. The histological outcomes were compared with the placebo group of a previous 48-week clinical trial.
RESULTS: There was a significant reduction in body mass index (median change, Δ = -0.7 kg per m2, p = 0.011), waist circumference (Δ = -3 cm, p = 0.033), systolic blood pressure (Δ = -9 mmHg, p = 0.024), diastolic blood pressure (Δ = -6 mmHg, p = 0.033), fasting blood glucose (Δ = -1.7 mmol/L, p = 0.008), total cholesterol (Δ = -0.5 mmol/L, p = 0.011), gamma glutamyl transpeptidase (Δ = -19 U/L, p = 0.013), volumetric liver fat fraction (Δ = -7.8%, p = 0.017), steatosis (Δ = -1, p = 0.014), ballooning (Δ = -1, p = 0.034), and fibrosis (Δ = 0, p = 0.046). All histological components either remained unchanged or improved, except in one patient who had worsening ballooning. Empagliflozin resulted in significantly greater improvements in steatosis (67% vs. 26%, p = 0.025), ballooning (78% vs. 34%, p = 0.024), and fibrosis (44% vs. 6%, p = 0.008) compared with historical placebo.
CONCLUSION: This pilot study provides primary histological evidence that empagliflozin may be useful for the treatment of NASH. This preliminary finding should prompt larger clinical trials to assess the effectiveness of empagliflozin and other SGLT2 inhibitors for the treatment of NASH in T2DM patients. Trial registry number ClincialTrials.gov number, NCT02964715.
METHODS: Premenopausal women (n = 136, mean age 41 (±5) years) and postmenopausal women [n = 121, mean age 59 (±4) years] were recruited, and each age group randomised into two groups to take two glasses per day of control = regular milk (500 mg calcium per day) or intervention (Int) = fortified milk (1000 mg calcium for pre-M women and 1200 mg calcium for PM women, 96 mg magnesium, 2.4 mg zinc, 15 µg vitamin D, 4 g FOS-inulin per day). At baseline, week 4 and week 12 serum minerals and bone biochemical markers were measured and bone density was measured at baseline.
RESULTS: Mean 25-hydroxyvitamin D [25(OH) vitamin D3] levels among groups were between 49 and 65 nmol/L at baseline, and over the 12 weeks of supplementation, the fortified milk improved vitamin D status in both Int groups. CTx-1 and PINP reduced significantly in both Pre-M and PM groups over the 12 weeks, with the changes in CTx-1 being significantly different (P
METHODS: Seventy-six obese subjects were randomly placed into two groups. The first group received three daily 120 mg dosages of orlistat for nine months (n=39), and the second group received a once daily 10 or 15 mg dosage of sibutramine for nine months (n=37). Baseline measurements for weight, body mass index (BMI), waist circumference (WC), body fat percentage (BF), visceral fat (VF), adiponectin, fasting plasma glucose (FPG), fasting insulin, pancreatic B cell secretory capacity (HOMA%B), insulin sensitivity (HOMA%S), insulin resistance (HOMA-IR) and serum high sensitivity C-reactive protein (hs-CRP) were performed and repeated during the sixth and ninth months of treatment.
RESULTS: Twenty-four subjects completed the trial in both groups. For both groups, weight, BMI, WC, BF, VF, HOMA-IR and hs-CRP were significantly lower at the end of the nine month intervention. However, there were no significant differences between the two groups for these parameters with nine months treatment. There was a significant decrease in FPG in orlistat group; while fasting insulin and HOMA%B reduced in sibutramine group. For both groups, there were also significant increases in adiponectin levels and HOMA%S at the end of the nine month intervention.
CONCLUSION: Nine months of treatment with orlistat and sibutramine not only reduced weight but also significantly improved BMI, WC, BF, VF, FPG, adiponectin, fasting insulin, HOMA%B, HOMA%S, HOMA-IR and hs-CRP. These improvements could prove useful in the reduction of metabolic and cardiovascular risks in obese subjects.
METHODS: This cross-sectional study aimed to evaluate (i) the effect of FTO rs9930506 on obesity and related parameters and (ii) the influence of diet on the above association in Malaysian adults. In total, 79 obese and 99 nonobese Malaysian adults were recruited.
RESULTS: In comparison with Chinese and Malays, Indians had significantly higher waist circumference (P ≤ 0.001 and P = 0.016), waist-hip ratio (P = 0.001 and P < 0.001), body fat percentage (P = 0.001 and P = 0.042), fasting insulin (P = 0.001 and P = 0.001), homeostatic model assessment-insulin resistance (P = 0.001 and P = 0.001) and lower high-density lipoprotein-cholesterol levels (P < 0.001 and P < 0.001), respectively. Indians consumed significantly lower dietary cholesterol (P = 0.002), percentage energy from protein (P < 0.001) and higher fibre (P = 0.006) compared to the other two groups. Malaysian Indians expressed the highest risk allele frequency (G) of FTO rs9930506 compared to the Malays and the Chinese (P < 0.001). No significant association was found between FTO rs9930506 and obesity (dominant model). Risk allele carriers (G) consumed significantly lower vitamin E (P = 0.020) and had a higher fibre intake (P = 0.034) compared to the noncarriers (A). Gene-diet interaction analysis revealed that risk allele carriers (G) had lower high sensitivity C-reactive protein (hsCRP) levels with higher energy from protein (≥14% day-1 ; P = 0.049) and higher vitamin E (≥5.4 mg day-1 ; P = 0.038).
CONCLUSIONS: The presence of the risk allele (G) of FTO rs9930506 was not associated with an increased risk of obesity. Malaysian Indians had a significantly higher frequency of the risk allele (G). Indian participants expressed higher atherogenic phenotypes compared to Chinese and Malays. FTO rs9930506 may interact with dietary protein and vitamin E and modulate hsCRP levels.
METHODS: A case-control study was conducted involving 600 people with type 2 diabetes (300 chronic kidney disease cases, 300 controls) who participated in The Malaysian Cohort project. Retrospective subanalysis was performed on the chronic kidney disease cases to assess chronic kidney disease progression from the recruitment phase. We genotyped 32 single nucleotide polymorphisms using mass spectrometry. The probability of chronic kidney disease and predicted rate of newly detected chronic kidney disease progression were estimated from the significant gene-environment interaction analyses.
RESULTS: Four single nucleotide polymorphisms (eNOS rs2070744, PPARGC1A rs8192678, KCNQ1 rs2237895 and KCNQ1 rs2283228) and five environmental factors (age, sex, smoking, waist circumference and HDL) were significantly associated with chronic kidney disease. Gene-environment interaction analyses revealed significant probabilities of chronic kidney disease for sex (PPARGC1A rs8192678), smoking (eNOS rs2070744, PPARGC1A rs8192678 and KCNQ1 rs2237895), waist circumference (eNOS rs2070744, PPARGC1A rs8192678, KCNQ1 rs2237895 and KCNQ1 rs2283228) and HDL (eNOS rs2070744 and PPARGC1A rs8192678). Subanalysis indicated that the rate of newly detected chronic kidney disease progression was 133 cases per 1000 person-years (95% CI: 115, 153), with a mean follow-up period of 4.78 (SD 0.73) years. There was a significant predicted rate of newly detected chronic kidney disease progression in gene-environment interactions between KCNQ1 rs2283228 and two environmental factors (sex and BMI).
CONCLUSIONS: Our findings suggest that the gene-environment interactions of eNOS rs2070744, PPARGC1A rs8192678, KCNQ1 rs2237895 and KCNQ1 rs2283228 with specific environmental factors could modify the probability for chronic kidney disease.