METHODS: Over 21 days, ten healthy participants consumed OsomeFood meals for five consecutive weekday lunches and dinners and resumed their regular diets for other days/meals. On follow-up days, participants completed questionnaires to record satiety, energy and health, and provided stool samples. To document microbiome variations and identify associations, species and functional pathway annotations were analyzed by shotgun sequencing. Shannon diversity and regular diet calorie intake subsets were also assessed.
RESULTS: Overweight participants gained more species and functional pathway diversity than normal BMI participants. Nineteen disease-associated species were suppressed in moderate-responders without gaining diversity, and in strong-responders with diversity gains along with health-associated species. All participants reported improved short-chain fatty acids production, insulin and γ-aminobutyric acid signaling. Moreover, fullness correlated positively with Bacteroides eggerthii; energetic status with B. uniformis, B. longum, Phascolarctobacterium succinatutens, and Eubacterium eligens; healthy status with Faecalibacterium prausnitzii, Prevotella CAG 5226, Roseburia hominis, and Roseburia sp. CAG 182; and overall response with E. eligens and Corprococcus eutactus. Fiber consumption was negatively associated with pathogenic species.
CONCLUSION: Although the AWE diet was consumed for only five days a week, all participants, especially overweight ones, experienced improved fullness, health status, energy and overall responses. The AWE diet benefits all individuals, especially those of higher BMI or low-fiber consumption.
OBJECTIVES: This study aimed to determine the accuracy of self-reported food intake by primary school children aged 7-9 y.
METHODS: A total of 105 children (51% boys), aged 8.0 ± 0.8 y, were recruited from three primary schools in Selangor, Malaysia. Individual meal intakes during a school break time were determined using a food photography method as the reference method. The children were then interviewed the following day to assess their recall of their meal intakes the previous day. ANOVA and Kruskal-Wallis tests were used to determine mean differences in the accuracy of reporting food items and amount by age and weight status, respectively.
RESULTS: On average, the children achieved 85.8% match rate, 14.2% omission rate, and 3.2% intrusion rate for accuracy in reporting food items. The children also achieved 85.9% correspondence rate and 6.8% inflation ratio for accuracy in reporting food amounts. Children living with obesity had notably higher intrusion rates compared with normal weight children (10.6% vs. 1.9%) (P < 0.05). Children aged >9 y had notably higher correspondence rates, compared with children aged 7 y (93.3% vs. 78.8%) (P < 0.05).
CONCLUSIONS: The low omission and intrusion rates and the high correspondence rate indicate that primary school children aged 7-9 y are capable of self-reporting food intake accurately for a lunch meal without proxy assistance. However, to confirm children's abilities to report their daily food intakes, further studies should be conducted to assess the accuracy of children in reporting their food intakes for more than one meal in a day.
AIM: To investigate the effects of food order on postprandial glucose (PPG) excursion, in Indian adults with normal (NL) and overweight/obese (OW) Body Mass Index.
METHODS: This randomised crossover study was conducted at a Malaysian university among Indian adults without diabetes. The participants consumed isocaloric test meals at three study visits based on randomised food orders: carbohydrate first/protein last (CF); protein first/carbohydrate last (CL); and a composite meal containing carbohydrate and protein (CM). Capillary blood glucose was measured at baseline, 30, 60, 90 and 120 minutes after starting the meal.
RESULTS: The CL food order had a blunting effect on PPG excursion at 30 and 60 minutes (p < 0.01). The CL food order resulted in lower glucose peak when compared with the CF and CM food order (p < 0.001). The CL food order resulted in lower incremental glucose peak (mmol/L) (NL: CF 3.9 ± 0.3, CM 3.0 ± 0.3, CL 2.0 ± 0.2; OW: CF 2.9 ± 0.3, CM 2.5 ± 0.3, CL 1.8 ± 0.2) and iAUC 0-120 min (mmol/Lxmin) (NL: CF 272.4 ± 26.7, CM 206.2 ± 30.3, CL 122.0 ± 14.8; OW: CF 193.2 ± 23.1, CM 160.1 ± 21.7, CL 113.6 ± 15.3) when compared with the CF food order (p < 0.001). The effect of food order on postprandial excursion did not differ between the NL (n = 14) and the OW (n = 17) groups.
CONCLUSION: In participants with normal and overweight/obese BMI, consuming food in the protein first/carbohydrate last order had the biggest effect in reducing PPG excursion.
DESIGN AND METHODS: This is a cross-sectional study conducted among 184 eligible hemodialysis patients at four dialysis units in Malaysia. Three days dietary recall were used in the analysis of dietary intake and behavior. Sleep quality was assessed through Pittsburgh Sleep Quality Index.
RESULTS: More than half of the patients were poor sleepers. Among the sleep components, sleep latency affected patients the most, with the use of sleep medications was relatively low. A majority of the patients had inadequate dietary intake of energy (88%) and protein (75%). Dietary protein, potassium adjusted for body weight, and sodium intake were significantly increased in poor sleepers. Lower percentage of energy from carbohydrates; higher percentage of energy from fats; higher intakes of dietary protein, fat, phosphorus, and sodium were correlated with poorer sleep quality and its components. Skipping dinner on non-dialysis days and having supper on dialysis days were associated with poor sleep quality.
CONCLUSION: Poor sleep is prevalent among hemodialysis patients. Sleep quality of hemodialysis patients was highly associated with certain dietary factors. Periodical assessment of sleep quality and dietary intake is necessary to identify poor sleepers with inappropriate dietary intake to allow effective clinical and nutritional interventions to improve the sleep quality and nutritional status of these patients.
METHODS: Twenty healthy subjects were enrolled in a randomized, 3-way, blinded cross-over trial. The study was registered under ClinicalTrials.gov Identifier no. NCT00123456. At each test day, the subjects received one of three meals comprising 30 g of starch with 5 g of LD or UP or an energy-adjusted control meal containing pea protein. Fasting and postprandial blood glucose, insulin, C-peptide and glucagon-like peptide-1 (GLP-1) concentrations were measured. Subjective appetite sensations were scored using visual analogue scales (VAS).
RESULTS: Linear mixed model (LMM) analysis showed a lower blood glucose, insulin and C-peptide response following the intake of LD and UP, after correction for body weight. Participants weighing ≤ 63 kg had a reduced glucose response compared to control meal between 40 and 90 min both following LD and UP meals. Furthermore, LMM analysis for C-peptide showed a significantly lower response after intake of LD. Compared to the control meal, GLP-1 response was higher after the LD meal, both before and after the body weight adjustment. The VAS scores showed a decreased appetite sensation after intake of the seaweeds. Ad-libitum food intake was not different three hours after the seaweed meals compared to control.
CONCLUSIONS: Concomitant ingestion of brown seaweeds may help improving postprandial glycaemic and appetite control in healthy and normal weight adults, depending on the dose per body weight.
CLINICAL TRIAL REGISTRY NUMBER: Clinicaltrials.gov (ID# NCT02608372).