DESIGN AND METHODS: This cross-sectional study was carried out among 254 primary and secondary school adolescents aged 10 to 16 years. Anthropometric measurements and blood pressure were determined through standardized protocols, while participants' birth weight was obtained from birth certificate. Body mass index (BMI), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR) and a body shape index (ABSI) were calculated.
RESULTS: Boys had significantly higher weight, height, WC, WHtR and systolic blood pressure (SBP) than girls (p +1SD had higher odds of being prehypertensive or hypertensive (aOR 8.97; 95% CI 3.16, 25.48), followed by participants with WC ≥ 90th percentile (aOR 6.31; 95% CI 2.48, 16.01) and participants with WHtR > 0.5 (aOR 5.10; 95% CI 2.05, 12.69). Multiple linear regression showed BMI was positively associated with both SBP and DBP. No significant association was found between birth weight and BP.
CONCLUSION: BMI had the best predictive ability for SBP and DBP. These findings strongly emphasize the importance of primary prevention of hypertension in adolescents, especially among those with high BMI.
OBJECTIVE: This study aims to determine the accuracy of MEDAL in assessing the dietary intake of Malaysian school children, using photographs of the children's meals taken by their parents as an objective reference.
METHODS: A convenience sample of 46 children aged 10 to 11 years recorded their daily meals in MEDAL for 4 days (2 weekdays and 2 weekend days). Their parents took photographs of the meals and snacks of their children before and after consumption during the 4-day period and sent them along with a brief description of food and drinks consumed via an instant SMS text messaging app. The accuracy of the children's reports of the food they had consumed was determined by comparing their MEDAL reports to the photographs of the food sent by their parents.
RESULTS: Overall, the match, omission, and intrusion rates were 62% (IQR 46%-86%), 39% (IQR 16%-55%), and 20% (IQR 6%-44%), respectively. Carbohydrate-based items from the food categories "rice and porridge"; "breads, spreads, and cereals"; and "noodles, pasta, and potatoes" were reported most accurately (total match rates: 68%-76%). "Snack and dessert" items were omitted most often (omission rate: 54%). Furthermore, side dishes from "vegetables and mushrooms," "eggs and tofu," "meat and fish," and "curry" food groups were often omitted (omission rates: 42%-46%). Items from "milk, cheese, and yogurt"; "snacks and desserts"; and "drinks" food groups intruded most often (intrusion rates: 37%-46%). Compared to the items reported by the boys, those reported by the girls had higher match rates (69% vs 53%) and lesser omission rates (31% vs 49%; P=.03, respectively).
CONCLUSIONS: In conclusion, children aged 10 to 11 years can self-report all their meals in MEDAL, although some items are omitted or intruded. Therefore, MEDAL is a tool that can be used to assess the dietary intake of Malaysian school children.
DESIGN: This was a single-center prospective observational study that compared resting energy expenditure estimated by 15 commonly used predictive equations against resting energy expenditure measured by indirect calorimetry at different phases. Degree of agreement between resting energy expenditure calculated by predictive equations and resting energy expenditure measured by indirect calorimetry was analyzed using intraclass correlation coefficient and Bland-Altman analyses. Resting energy expenditure values calculated from predictive equations differing by ± 10% from resting energy expenditure measured by indirect calorimetry was used to assess accuracy. A score ranking method was developed to determine the best predictive equations.
SETTING: General Intensive Care Unit, University of Malaya Medical Centre.
PATIENTS: Mechanically ventilated critically ill patients.
INTERVENTIONS: None.
MEASUREMENTS AND MAIN RESULTS: Indirect calorimetry was measured thrice during acute, late, and chronic phases among 305, 180, and 91 ICU patients, respectively. There were significant differences (F= 3.447; p = 0.034) in mean resting energy expenditure measured by indirect calorimetry among the three phases. Pairwise comparison showed mean resting energy expenditure measured by indirect calorimetry in late phase (1,878 ± 517 kcal) was significantly higher than during acute phase (1,765 ± 456 kcal) (p = 0.037). The predictive equations with the best agreement and accuracy for acute phase was Swinamer (1990), for late phase was Brandi (1999) and Swinamer (1990), and for chronic phase was Swinamer (1990). None of the resting energy expenditure calculated from predictive equations showed very good agreement or accuracy.
CONCLUSIONS: Predictive equations tend to either over- or underestimate resting energy expenditure at different phases. Predictive equations with "dynamic" variables and respiratory data had better agreement with resting energy expenditure measured by indirect calorimetry compared with predictive equations developed for healthy adults or predictive equations based on "static" variables. Although none of the resting energy expenditure calculated from predictive equations had very good agreement, Swinamer (1990) appears to provide relatively good agreement across three phases and could be used to predict resting energy expenditure when indirect calorimetry is not available.