METHODS AND STUDY DESIGN: The data used for this analysis were from 1143 children, 6-12 years old, that participated in the South East Asian Nutrition Survey (SEANUTS). Physical activity (PA) was measured using pedometers for 2 consecutive days and was categorized low, moderate and high. Child nutritional status was categorized based on body mass index for age z-scores (BAZ) into normal weight (-2 SD ≤BAZ≤1 SD) or overweight (BAZ >1 SD). Energy intake was calculated from a one day 24 hour recall and compared to the Indonesian recommended dietary allowance (RDA) for energy.
RESULTS: Children with low PA had higher risk (ODDs 3.4, 95% CI: 2.0, 6.0) of being overweight compared to children who had high PA. Children with moderate PA and energy take >100% RDA had higher risk (ODDs 4.2, 95% CI 1.9, 9.3) of being overweight than children with high PA and energy intakes ≤100% RDA.
CONCLUSIONS: Low physical activity independently or moderate physical activity and high energy intake are risk factors for Indonesian children to get overweight. Program intervention such as increasing physical activity at school and home is needed to reduce overweight among children.
METHODS AND STUDY DESIGN: Using a stratified multi-stage sampling, a total of 816 children (282 boys and 534 girls) aged 10 to 11 years from 12 selected primary schools in the state of Selangor, participated in this study. Data were collected on socio-demographic characteristics, pubertal status and disordered eating behaviors. The Pubertal Development Scale and the Children's Eating Attitudes Test (ChEAT) were used to assess pubertal status and disordered eating, respectively. Logistic regression analysis was conducted to determine the risk factors of disordered eating.
RESULTS: The prevalence of disordered eating was 30.8% (32.8% in boys and 29.7% in girls). However, the sex difference in the prevalence was not statistically significant. Age, ethnicity and pubertal status were significantly associated with disordered eating in univariate logistic regression analysis. Multivariate logistic regression analysis showed that among boys, being either in an advanced or post-pubertal stage (adjusted OR=8.64) and older age group (adjusted OR=2.03) were risk factors of disordered eating. However, among girls, being a Malay (adjusted OR=3.79) or Indian (adjusted OR=5.04) in an advanced or post-pubertal stage (adjusted OR=2.34) and older age group (adjusted OR=1.53) were risk factors of disordered eating.
CONCLUSION: This study found one in three children had disordered eating. Since ethnicity and pubertal status were identified as risk factors, ethnicity-specific intervention programs on the prevention of disordered eating among children should take into consideration their pubertal status.
METHODS AND STUDY DESIGN: This nationwide cross-sectional study involved 5,332 primary school children aged 6 to 12 years and 3,000 secondary school children aged 13 to 17 years. Height and weight were measured and BMI-for-age was determined. Socio-demographic backgrounds, breakfast habits and physical activity levels were assessed using questionnaires. Breakfast frequency was defined as follows: breakfast skippers (ate breakfast 0-2 days/week), irregular breakfast eaters (ate breakfast 3-4 days/week) and regular breakfast eaters (ate breakfast ≥5 days/week).
RESULTS: The overall prevalence of breakfast skippers and irregular breakfast eaters was 11.7% and 12.7% respectively. Breakfast skipping was related to age, sex, ethnicity, income and physical activity level. Among primary school boys and secondary school girls, the proportion of overweight/obesity was higher among breakfast skippers (boys: 43.9%, girls: 30.5%) than regular breakfast eaters (boys: 31.2%, girls: 22.7%). Among primary school children, only boys who skipped breakfast had a higher mean BMI-for-age z-score than regular breakfast eaters. Among secondary school boys and girls, BMI-for-age z-score was higher among breakfast skippers than regular breakfast eaters. Compared to regular breakfast eaters, primary school boys who skipped breakfast were 1.71 times (95% CI=1.26-2.32, p=0.001) more likely to be overweight/obese, while the risk was lower in primary school girls (OR=1.36, 95% CI=1.02-1.81, p=0.039) and secondary school girls (OR=1.38, 95% CI=1.01-1.90, p=0.044).
CONCLUSION: Regular breakfast consumption was associated with a healthier body weight status and is a dietary behaviour which should be encouraged.
METHODS AND STUDY DESIGN: Collective food data from MyHeARTs 2012 database were used to construct the MyUM Adolescent FFQ. Seventy-eight participants between 13 and 15 years old in 2014 were selected through convenient sampling for test-retest study. They completed the MyUM Adolescent FFQ twice, with an interval period of one week. One hundred and fifty-six MyHeARTs study participants who were 15 years old in 2014 were randomly selected for this comparative valid-ity study. They completed a 7-day diet history (7DDH) and subsequently completed the self-administered MyUM Adolescent FFQ.
RESULTS: Pearson's correlations between the FFQ and 7DDH for all macronutrients were statistically significant. Energy-adjusted correlations for protein, carbohydrate, and fat were 0.54, 0.63 and 0.49 respectively. Most of the micronutrients and minerals, were statistically correlated ranging from 0.31 to 0.49 after energy adjustment. Cross-classification analyses revealed that more than 70 percent of adolescents were classified into either the same or adjacent quartile of nutrient intake when comparing data of 7DDH and FFQ. No serious systematic bias was evident in the Bland-Altman plots.
CONCLUSION: The 200-item FFQ developed for Malaysian adolescents has moderate to good comparative validity for assessment of macronutrient and micronutrient intake.
METHODS AND STUDY DESIGN: This study comprised development and validation phases. In the development phase, 129 young adults from a public university in Klang Valley completed a 3-day food record (3DFR), and the data were used to create a food list for the FFQ. Two weeks later, in the validation phase, another 100 participants recruited from the same university completed the 3DFR and a newly developed FFQ for assessing consumption of 38 food items. Finally, the data obtained from the FFQ and 3DFR were used to analyze the nutrient intake of each participant, and the developed FFQ was validated using Spearman correla-tion coefficients (r) and Bland-Altman methods.
RESULTS: For the development phase, 38 food items were determined to contribute to 90% of the participants' total energy and macronutrient intake, and these items were included on the FFQ. For the validation phase, the average Spearman correlation coefficient for energy and all nutrients was 0.43, which indicated good agreement between the 3DFR and FFQ. Cross-classification analysis of the 3DFR and FFQ results revealed that 79% of the young adults were classified into similar or neighboring quartiles when each set of results was used. The Bland-Altman plots revealed that the results obtained using the two methods were parallel.
CONCLUSIONS: The FFQ is a simple and validated tool that can be self-administered to young adults to assess their energy and nutrient consumption.