METHODS: The development process follows the systematic steps recommended by the Active Healthy Kids Global Alliance was used. Nationally representative data from 2016 to 2021, government reports and unpublished data were reviewed and consolidated by a panel of experts. Letter grades were assigned based on predefined benchmarks to 12 indicators including 10 core physical activity indicators that are common to Global Matrix 4.0 and two additional indicators (Diet and Weight Status). The current grading was then compared against those obtained in 2016.
RESULTS: Four of six indicators in the Daily Behaviors category received D- or C grades [Overall Physical Activity, Active Transportation and Diet (D-); Sedentary Behaviors (C)], which remains poor, similar to the 2016 report card. School indicator was graded for the Settings and Sources of Influence category, which showed an improvement from grade B (2016) to A- (2022). As for the Strategies and Investments category, B was again assigned to the Government indicator. Two new indicators were added after the 2016 Report Card, and they were graded B (Physical Fitness) and B- (Weight Status). Four indicators (Organized Sports and Physical Activity, Active Play, Family and Peers, and Community and Environment) were again graded Incomplete due to a lack of nationally representative data.
CONCLUSION: The 2022 Report Card revealed that Malaysian children and adolescents are still caught in the "inactivity epidemic". This warrants more engagement from all stakeholders, public health actions, and timely research, to comprehensively evaluate all indicators and drive a cultural shift to see Malaysian children and adolescents moving more every day.
DESIGN: Body weight and length/height were measured. The LMS method was used for calculating smoothened body-weight- and BMI-for-age percentile values. The standardized site effect (SSE) values were used for identifying large differences (i.e. $\left| {{\rm SSE}} \right|$ >0·5) between the pooled SEANUTS sample and the remaining pooled SEANUTS samples after excluding one single country each time, as well as with WHO growth references.
SETTING: Malaysia, Thailand, Vietnam and Indonesia.
SUBJECTS: Data from 14 202 eligible children.
RESULTS: The SSE derived from the comparisons of the percentile values between the pooled and the remaining pooled SEANUTS samples were indicative of small/acceptable (i.e. $\left| {{\rm SSE}} \right|$ ≤0·5) differences. In contrast, the comparisons of the pooled SEANUTS sample with WHO revealed large differences in certain percentiles.
CONCLUSIONS: The findings of the present study support the use of percentile values derived from the pooled SEANUTS sample for evaluating the weight status of children in each SEANUTS country. Nevertheless, large differences were observed in certain percentiles values when SEANUTS and WHO reference values were compared.
DESIGN: Data on length/height-for-age percentile values were collected. The LMS method was used for calculating smoothened percentile values. Standardized site effects (SSE) were used for identifying large or unacceptable differences (i.e. $\mid\! \rm SSE \!\mid$ >0·5) between the pooled SEANUTS sample (including all countries) and the remaining pooled SEANUTS samples (including three countries) after weighting sample sizes and excluding one single country each time, as well as with WHO growth references.
SETTING: Malaysia, Thailand, Vietnam and Indonesia.
SUBJECTS: Data from 14202 eligible children were used.
RESULTS: From pair-wise comparisons of percentile values between the pooled SEANUTS sample and the remaining pooled SEANUTS samples, the vast majority of differences were acceptable (i.e. $\mid\! \rm SSE \!\mid$ ≤0·5). In contrast, pair-wise comparisons of percentile values between the pooled SEANUTS sample and WHO revealed large differences.
CONCLUSIONS: The current study calculated length/height percentile values for South East Asian children aged 0·5-12 years and supported the appropriateness of using pooled SEANUTS length/height percentile values for assessing children's growth instead of country-specific ones. Pooled SEANUTS percentile values were found to differ from the WHO growth references and therefore this should be kept in mind when using WHO growth curves to assess length/height in these populations.
METHODS: A total of 2406 Malaysian children aged 5 to 12 years, who had participated in the South East Asian Nutrition Surveys (SEANUTS), were included in this study. Cognitive performance [non-verbal intelligence quotient (IQ)] was measured using Raven's Progressive Matrices, while socioeconomic characteristics were determined using parent-report questionnaires. Body mass index (BMI) was calculated using measured weight and height, while BMI-for-age Z-score (BAZ) and height-for-age Z-score (HAZ) were determined using WHO 2007 growth reference.
RESULTS: Overall, about a third (35.0%) of the children had above average non-verbal IQ (high average: 110-119; superior: ≥120 and above), while only 12.2% were categorized as having low/borderline IQ ( 3SD), children from very low household income families and children whose parents had only up to primary level education had the highest prevalence of low/borderline non-verbal IQ, compared to their non-obese and higher socioeconomic counterparts. Parental lack of education was associated with low/borderline/below average IQ [paternal, OR = 2.38 (95%CI 1.22, 4.62); maternal, OR = 2.64 (95%CI 1.32, 5.30)]. Children from the lowest income group were twice as likely to have low/borderline/below average IQ [OR = 2.01 (95%CI 1.16, 3.49)]. Children with severe obesity were twice as likely to have poor non-verbal IQ than children with normal BMI [OR = 2.28 (95%CI 1.23, 4.24)].
CONCLUSIONS: Children from disadvantaged backgrounds (that is those from very low income families and those whose parents had primary education or lower) and children with severe obesity are more likely to have poor non-verbal IQ. Further studies to investigate the social and environmental factors linked to cognitive performance will provide deeper insights into the measures that can be taken to improve the cognitive performance of Malaysian children.
DESIGN: Cross-sectional survey conducted in 2019-2020.
SETTING: Multistage cluster sampling conducted in Central, Northern, Southern, and East Coast regions of Peninsular Malaysia.
PARTICIPANTS: 2989 children aged 0.5-12.9 years.
RESULTS: Prevalences of stunting, thinness, overweight, and obesity among children aged 0.5-12.9 years were 8.9%, 6.7%, 9.2%, and 8.8%, respectively. Among children below 5 years old, 11.4% were underweight, 13.8% had stunting, and 6.2% wasting. Data on nutritional biomarkers showed a small proportion of children aged 4-12 years had iron (2.9%) and vitamin A deficiencies (3.1%). Prevalence of anaemia was distinctly different between children below 4 years old (40.3%) and those aged 4 years and above (3.0%). One-fourth of children (25.1%) had vitamin D insufficiency, which was twice as prevalent in girls (35.2% vs. boys: 15.6%). The majority of children did not meet the recommended dietary intake for calcium (79.4%) and vitamin D (94.8%).
CONCLUSIONS: Data from SEANUTS II Malaysia confirmed that triple burden of malnutrition co-exists among children in Peninsular Malaysia, with higher prevalence of overnutrition than undernutrition. Anaemia is highly prevalent among children below 4 years old, while vitamin D insufficiency is more prevalent among girls. Low intakes of dietary calcium and vitamin D are also of concern. These findings provide policymakers with useful and evidence-based data to formulate strategies that address the nutritional issues of Malaysian children.
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.