METHODS: In a parallel, single-blind and placebo-controlled study, 22 healthy overweight and obese volunteers were randomly allocated to receive 30 g day(-1) oligofructose or cellulose for 6 weeks following a 2-week run-in. Subjective appetite and side effect scores, breath hydrogen, serum short chain fatty acids (SCFAs), plasma gut hormones, glucose and insulin concentrations, EI, BW and adiposity were quantified at baseline and post-supplementation.
RESULTS: Oligofructose increased breath hydrogen (P
METHODS: We conducted a cross-sectional study involving teachers recruited via multi-stage sampling from the state of Melaka, Malaysia. MONO was defined as individuals with BMI 18.5-29.9 kg/m(2) and metabolic syndrome. Metabolic syndrome was diagnosed based on the Harmonization criteria. Participants completed self-reported questionnaires that assessed alcohol intake, sleep duration, smoking, physical activity, and fruit and vegetable consumption.
RESULTS: A total of 1168 teachers were included in the analysis. The prevalence of MONO was 17.7% (95% confidence interval [CI], 15.3-20.4). Prevalence of metabolic syndrome among the normal weight and overweight participants was 8.3% (95% CI, 5.8-11.8) and 29.9% (95% CI, 26.3-33.7), respectively. MONO prevalence was higher among males, Indians, and older participants and inversely associated with sleep duration. Metabolic syndrome was also more prevalent among those with central obesity, regardless of whether they were normal or overweight. The odds of metabolic syndrome increased exponentially from 1.9 (for those with BMI 23.0-24.9 kg/m(2)) to 11.5 (for those with BMI 27.5-29.9 kg/m(2)) compared to those with BMI 18.5-22.9 kg/m(2) after adjustment for confounders.
CONCLUSIONS: The prevalence of MONO was high, and participants with BMI ≥23.0 kg/m(2) had significantly higher odds of metabolic syndrome. Healthcare professionals and physicians should start to screen non-obese individuals for metabolic risk factors to facilitate early targeted intervention.
Methods: a cross-sectional study was conducted, using the Kedah audit samples data extracted from the National Diabetes Registry (NDR) from the year 2014 to 2018. A total of 25,062 registered type 2 diabetes mellitus patients were selected using the inclusion and exclusion criteria from the registry. Only patients with complete data on their HbA1C, lipid profile, waist circumference and BMI were analysed using SPSS version 21.
Results: the means for the age, BMI and waist circumference of the samples were 61.5 (±10.85) years, 27.3 (±5.05) kg/m2 and 89.46 (±13.58) cm, respectively. Poor glycaemic control (HbA1c>6.5%) was observed in 72.7% of the patients, with females having poorer glycaemic control. The BMI and waist circumference were found to be significantly associated with glycaemic control (P<0.001). The total cholesterol, triglycerides and low-density lipoproteins values showed positive correlation with glycaemic control (r = 0.178, 0.157, 0.145, p<0.001), while high-density lipoproteins values are negatively correlated (r = -0.019, p<0.001).
Conclusion: implementing lifestyle changes such as physical activity and dietary modifications are important in the management of BMI, waist circumference and body lipids, which in turn results in improved glycaemic control.
METHODS: We analysed data from 4101 adults (Malay, n = 1901 and Indian, n = 2200) who participated in the baseline (2004-2009) and 6-year follow-up (2011-2015) of two independent population-based studies with similar methodology in Singapore. BMI was categorised into normal (<25 kg/m2), overweight (25-29.9 kg/m2) and obese (≥30 kg/m2). DM was diagnosed as random plasma glucose ≥200 mg/dL, HbA1c ≥6.5% or self-reported physician diagnosed DM. DR was assessed from retinal photographs graded using a standard protocol. The associations of baseline BMI with incident DM and DR was examined using multivariable poisson regression models adjusting for potential confounders including duration of DM, family history of DM and HbA1c.
RESULTS: The incidence of DM was 12.8% and among 1586 participants with DM, the incidence of DR was 17.6% over a median follow-up period of 6.2 years. Compared to those with BMI overweight and 2.01 (1.50-2.71) for obese (p trend overweight and 0.60 (0.39-0.92) for obese (p trend = 0.02). In analyses stratified by ethnicity, similar pattern of associations with DM and DR were observed in both ethnicities.
CONCLUSION: Our results suggest that, overweight and obesity increased the 6-year risk of DM but decreased the 6-year risk of DR in these Asian populations.
OBJECTIVES: To investigate the combined effect of FTO rs9930501, rs9930506, and rs9932754 and ADRB2 rs1042713 and rs1042714 using PRS on (1) the odds of obesity and (2) post-intervention differences in dietary, anthropometric, and cardiometabolic parameters in response to high-protein calorie-restricted, high-vitamin E, high-fiber (Hipcref) diet intervention in Malaysian adults.
METHODS: Both a cross-sectional study (n = 178) and a randomized controlled trial (RCT) (n = 128) were conducted to test the aforementioned objectives. PRS was computed as the weighted sum of the risk alleles possessed by each individual participant. Participants were stratified into first (PRS 0-0.64), second (PRS 0.65-3.59), and third (PRS 3.60-8.18) tertiles.
RESULTS: The third tertile of PRS was associated with significantly higher odds of obesity: 2.29 (95% CI = 1.11-4.72, adjusted p = 0.025) compared to the first tertile. Indians (3.9 ± 0.3) had significantly higher PRS compared to Chinese (2.1 ± 0.4) (p = 0.010). In the RCT, a greater reduction in high-sensitivity C-reactive protein (hsCRP) levels was found in second and third tertiles after Hipcref diet intervention compared to the control diet (p interaction = 0.048).
CONCLUSION: Higher PRS was significantly associated with increased odds of obesity. Individuals with higher PRS had a significantly greater reduction in hsCRP levels after Hipcref diet compared to the control diet.