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.
METHODS: This cross-sectional study included adolescents aged 15-17 years from five randomly selected secondary schools in the Hulu Langat district of Selangor state, Malaysia. Waist circumference (WC) was measured at the midpoint between the lower margin of the last palpable rib and the top of the iliac crest. Information on sociodemographic data, dietary habits, physical activity levels and duration of sleep was obtained via interviewer-administered questionnaires. Participants' habitual food intake was determined using a 73-item Food Frequency Questionnaire.
RESULTS: Among 832 participants, 56.0% were girls; 48.4% were Malay, 40.5% Chinese, 10.2% Indian and 0.8% of other ethnic groups. Median age and WC were 16 (interquartile range [IQR] 15-16) years and 67.9 (IQR 63.0-74.6) cm, respectively. Overall prevalence of AO (> 90th percentile on the WC chart) was 11.3%. A higher proportion (22.4%) of Indian adolescents were found to have AO compared with Malay and Chinese adolescents. Logistic regression analysis showed that female gender (adjusted odds ratio [OR] 7.064, 95% confidence interval [CI] 2.087-23.913; p = 0.002), Indian ethnicity (adjusted OR 10.164, 95% CI 2.182-47.346; p = 0.003), irregular meals (adjusted OR 3.193, 95% CI 1.043-9.774; p = 0.042) and increasing body mass index (BMI) (adjusted OR 2.867, 95% CI 2.216-3.710; p < 0.001) were significantly associated with AO.
CONCLUSION: AO was common among Malaysian adolescents. Female gender, Indian ethnicity, irregular meals and increasing BMI were significant risk factors.
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
METHODS: This human postprandial study evaluated 3 edible fat blends with differing polyunsaturated to saturated fatty acids (P/S) ratios (POL = 0.27, AHA = 1.00, PCAN = 1.32). A cross-over design included mildly hypercholestrolemic subjects (9 men and 6 women) preconditioned on test diets fats at 31% energy for 7 days prior to the postprandial challenge on the 8th day with 50 g test fat. Plasma lipids and lipoproteins were monitored at 0, 1.5, 3.5, 5.5 and 7 hr.
RESULTS: Plasma triacylglycerol (TAG) concentrations in response to POL, AHA or PCAN meals were not significant for time x test meal interactions (P > 0.05) despite an observed trend (POL > AHA > PCAN). TAG area-under-the-curve (AUC) increased by 22.58% after POL and 7.63% after PCAN compared to AHA treatments (P > 0.05). Plasma total cholesterol (TC) response was not significant between meals (P > 0.05). Varying P/S ratios of test meals significantly altered prandial high density lipoprotein-cholesterol (HDL-C) concentrations (P AHA > PCAN). Paired comparisons was significant between POL vs PCAN (P = 0.009) but not with AHA or between AHA vs PCAN (P > 0.05). A significantly higher HDL-C AUC for POL vs AHA (P = 0.015) and PCAN (P = 0.001) was observed. HDL-C AUC increased for POL by 25.38% and 16.0% compared to PCAN and AHA respectively. Plasma low density lipoprotein-cholesterol (LDL-C) concentrations was significant (P = 0.005) between meals and significantly lowest after POL meal compared to PCAN (P = 0.004) and AHA (P > 0.05) but not between AHA vs PCAN (P > 0.05). AUC for LDL-C was not significant between diets (P > 0.05). Palmitic (C16:0), oleic (C18:1), linoleic (C18:2) and linolenic (C18:3) acids in TAGs and cholesteryl esters were significantly modulated by meal source (P
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.