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 was conducted among 219 primary school children (105 boys; 114 girls) aged 7 years old-10 years old in Kuala Lumpur, Malaysia in 2016-2017. Children from three main ethnicities, namely Malay, Chinese and Indian, were recruited. Weight, height and waist circumference were measured; body composition was assessed by deuterium dilution technique. CAPA and level of PA were obtained through self-administered questionnaires and reported as CAPA and PA scores.
RESULTS: Median CAPA and PA scores were 3.40 (Q1 = 3.00, Q3 = 3.80) and 2.31 (Q1 = 1.95, Q3 = 2.74), respectively. Significant gender differences were found in CAPA and PA scores, with boys being more attracted to PA (3.16 [Q1 = 2.90, Q3 = 3.44]; P = 0.001) and more physically active compared with girls (2.47 [Q1 = 2.07, Q3 = 3.07]; P = 0.001). CAPA and PA scores correlated positively in both sexes. Boys scored higher than girls in 'liking of games and sports' (ρ = 0.301, P = 0.002) and 'liking of vigorous PA' (ρ = 0.227, P = 0.02) CAPA subscales, which also correlated positively with PA scores. Girls' PA scores correlated with 'peer acceptance in games and sports' (ρ = 0.329, P < 0.001).
CONCLUSION: Boys are more physically active and have higher attraction to PA compared with girls. Differences in PA scores between the sexes were related to gender differences in CAPA scores. Thus, attention should be given to gender differences in CAPA related psychosocial factors when planning interventions to promote PA among children.
OBJECTIVE: This study examined the performance of 3 ML algorithms in comparison with logistic regression (LR) to predict overweight or obesity status among working adults in Malaysia.
METHODS: Using data from 16,860 participants (mean age 34.2, SD 9.0 years; n=6904, 41% male; n=7048, 41.8% with overweight or obesity) in the Malaysia's Healthiest Workplace by AIA Vitality 2019 survey, predictor variables, including sociodemographic characteristics, job characteristics, health and weight perceptions, and lifestyle-related factors, were modeled using the extreme gradient boosting (XGBoost), random forest (RF), and support vector machine (SVM) algorithms, as well as LR, to predict overweight or obesity status based on a BMI cutoff of 25 kg/m2.
RESULTS: The area under the receiver operating characteristic curve was 0.81 (95% CI 0.79-0.82), 0.80 (95% CI 0.79-0.81), 0.80 (95% CI 0.78-0.81), and 0.78 (95% CI 0.77-0.80) for the XGBoost, RF, SVM, and LR models, respectively. Weight satisfaction was the top predictor, and ethnicity, age, and gender were also consistent predictor variables of overweight or obesity status in all models.
CONCLUSIONS: Based on multi-domain online workplace survey data, this study produced predictive models that identified overweight or obesity status with moderate to high accuracy. The performance of both ML-based and logistic regression models were comparable when predicting obesity among working adults in Malaysia.
OBJECTIVE: To quantify the relationship between social jetlag and CRF, independent of other sleep characteristics.
METHODS: This cross-sectional sample includes 276 New Zealand adolescents (14-18 years, 52.5% female). CRF (VO2max) was estimated from a 20-m multi-stage shuttle run. Average sleep duration, sleep disturbances, social jetlag, physical activity, and the number of bedroom screens were estimated from validated self-report surveys. Social jetlag is the difference in hours between the midpoint of sleep during weekdays (school) and weekend days (free). Combined and sex-stratified linear regression assessed the association between sleep outcomes and CRF, controlling for relevant covariates.
RESULTS: Males slept 17.6 min less, had less sleep disturbances, and a 25.1-min greater social jetlag than their female peers (all p
AIMS: To determine levels of work engagement and to identify psychological and work-related characteristics predicting work engagement in employees in Malaysia.
METHODS: We recruited 5235 employees from 47 public and private organizations in Malaysia who responded to an online health survey. We assessed work engagement with the 9-item Utrecht Work Engagement Scale (UWES-9) and psychological distress using the 6-item Kessler scale. We performed multiple linear regression to determine predictors of work engagement.
RESULTS: Employee mean age was 33.8 years (standard deviation [SD] ± 8.8). The mean work engagement score on the UWES-9 was 3.53 (SD ± 0.94). Eleven of 18 variables on multiple regression predicted work engagement, F(18, 4925) = 69.02, P < 0.001, R2 = 0.201. Factors that predicted higher work engagement were age, marital status, education level, job type, job permanency, longer sleep duration, lower psychological distress and no history of workplace bullying.
CONCLUSIONS: Key factors associated with poorer work engagement in Malaysian employees include inadequate sleep, psychological distress and a history of workplace bullying. These are modifiable factors that individuals and employers can target to improve work engagement, ideally tailored according to occupational type.