METHODS: We systematically searched for publications in PubMed® and Scopus, manually searched the grey literature and consulted with national health and nutrition officials, with no restrictions on publication type or language. We included low- and middle-income countries in the World Health Organization South-East Asia Region, and the Association of Southeast Asian Nations and China. We analysed the included programmes by adapting the United States Centers for Disease Control and Prevention's public health surveillance evaluation framework.

FINDINGS: We identified 82 surveillance programmes in 18 countries that repeatedly collect, analyse and disseminate data on nutrition and/or related indicators. Seventeen countries implemented a national periodic survey that exclusively collects nutrition-outcome indicators, often alongside internationally linked survey programmes. Coverage of different subpopulations and monitoring frequency vary substantially across countries. We found limited integration of food environment and wider food system indicators in these programmes, and no programmes specifically monitor nutrition-sensitive data across the food system. There is also limited nutrition-related surveillance of people living in urban deprived areas. Most surveillance programmes are digitized, use measures to ensure high data quality and report evidence of flexibility; however, many are inconsistently implemented and rely on external agencies' financial support.

METHODS: This is a cross-sectional study on 9553 adolescents (aged 12-15 years) from 8 Asian metropolitan cities (Tokyo, Hong Kong, Shanghai, Taipei, Bangkok, Kuala Lumpur, Seoul, and Singapore). Cardiorespiratory fitness was assessed by using a 15-m progressive aerobic capacity endurance run (PACER) test. The time spent on MVPA and watching television was assessed using the International Physical Activity Questionnaire-Short Form.

METHODS: This study reports baseline data from a longitudinal study that was conducted at a hospital in Vietnam. KTRs aged ≥18 years and >3 months post-transplantation were recruited. Assessments included sociodemographic and blood biomarkers. Dietary intake was estimated from 24-hour recalls. A Short Form-36 Health Survey, comprising physical (PCS) and mental component summaries (MCS), was administered to assess QoL. Multivariate linear regression models were performed.

RESULTS: The study included 106 patients (79 men) with a mean age of 43.2 years (± 11.9). Mean duration after kidney transplantation was 28.5 months (± 14.9). Patients with MetS had 6.43 lower PCS score (P < .05) and 3.20 lower MCS score (P < .05) than their counterparts without MetS. Calcium intake (β = -0.01; 95% CI, -0.03 to 0.00) and inadequate protein (β = -14.8; 95% CI, -23 to -6.65) were negatively associated with PCS score. MCS score was negatively associated with calcium intake (β = -0.02; 95% CI, -0.04 to -0.01) and inadequate protein intake (β = -15.1; 95% CI, -24.3 to -5.86), and positively associated with fat intake (β = 0.43, 95% CI, 0.02-0.85).

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)].

METHODS: This multinational, cross-sectional study included data from 1071 children 3-5 yr old from 19 countries, collected between 2018 and 2020 (pre-COVID). Sedentary behavior was measured for three consecutive days using activPAL accelerometers. Sedentary time, sedentary fragmentation, and seated transport duration were calculated. Linear mixed models were used to examine the differences in sedentary behavior variables between sex, country-level income groups, urban/rural settings, and population density.

RESULTS: Children spent 56% (7.4 h) of their waking time sedentary. The longest average bout duration was 81.1 ± 45.4 min, and an average of 61.1 ± 50.1 min·d-1 was spent in seated transport. Children from upper-middle-income and high-income countries spent a greater proportion of the day sedentary, accrued more sedentary bouts, had shorter breaks between sedentary bouts, and spent significantly more time in seated transport, compared with children from low-income and lower-middle-income countries. Sex and urban/rural residential setting were not associated with any outcomes. Higher population density was associated with several higher sedentary behavior measures.

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.

METHOD: Participants of Juara Sihat (n=55) were followed-up at 18 months after completion of the intervention. Juara Sihat intervention was implemented over 12 weeks and focused on four key components: (i) five one-hour nutrition education classes, (ii) four one-hour physical activity education sessions, (iii) family involvement, and (iv) empowerment of Parents and Teachers Association. Anthropometric variables (body mass index, body fat percentage and waist circumference) were measured and physical activity level was evaluated by using Physical Activity Questionnaire for Children (PAQ-C) at baseline (P0), immediately upon completion of intervention (P1), at three-month post-intervention (P2), and at 18-month postintervention (P3). Analyses of repeated measures analysis of covariance (ANCOVA) with intention-to-treat principle were applied.

RESULTS: Sustained effects were found in BMI-for-age z-score which showed a reduction (P0 2.41±0.84 vs P3 2.27±0.81) and physical activity level which showed positive improvements (P0 2.46±0.62 vs P3 2.87±0.76) at 18 months after intervention was completed. Body fat and waist circumference had increased over the same time period.

OBJECTIVE: To develop international WC percentile cutoffs for children and adolescents with normal weight based on data from 8 countries in different global regions and to examine the relation with cardiovascular risk.

DESIGN AND SETTING: We used pooled data on WC in 113,453 children and adolescents (males 50.2%) aged 4 to 20 years from 8 countries in different regions (Bulgaria, China, Iran, Korea, Malaysia, Poland, Seychelles, and Switzerland). We calculated WC percentile cutoffs in samples including or excluding children with obesity, overweight, or underweight. WC percentiles were generated using the general additive model for location, scale, and shape (GAMLSS). We also estimated the predictive power of the WC 90th percentile cutoffs to predict cardiovascular risk using receiver operator characteristics curve analysis based on data from 3 countries that had available data (China, Iran, and Korea). We also examined which WC percentiles linked with WC cutoffs for central obesity in adults (at age of 18 years).

MAIN OUTCOME MEASURE: WC measured based on recommendation by the World Health Organization.

RESULTS: We validated the performance of the age- and sex-specific 90th percentile WC cutoffs calculated in children and adolescents (6-18 years of age) with normal weight (excluding youth with obesity, overweight, or underweight) by linking the percentile with cardiovascular risk (area under the curve [AUC]: 0.69 for boys; 0.63 for girls). In addition, WC percentile among normal weight children linked relatively well with established WC cutoffs for central obesity in adults (eg, AUC in US adolescents: 0.71 for boys; 0.68 for girls).

METHODS: Parents of children aged 3-5 years, from 14 countries (8 low- and middle-income countries, LMICs) completed surveys to assess changes in movement behaviours and how these changes were associated with the COVID-19 pandemic. Surveys were completed in the 12 months up to March 2020 and again between May and June 2020 (at the height of restrictions). Physical activity (PA), sedentary screen time (SST) and sleep were assessed via parent survey. At Time 2, COVID-19 factors including level of restriction, environmental conditions, and parental stress were measured. Compliance with the World Health Organizations (WHO) Global guidelines for PA (180 min/day [≥60 min moderate- vigorous PA]), SST (≤1 h/day) and sleep (10-13 h/day) for children under 5 years of age, was determined.

RESULTS: Nine hundred- forty-eight parents completed the survey at both time points. Children from LMICs were more likely to meet the PA (Adjusted Odds Ratio [AdjOR] = 2.0, 95%Confidence Interval [CI] 1.0,3.8) and SST (AdjOR = 2.2, 95%CI 1.2,3.9) guidelines than their high-income country (HIC) counterparts. Children who could go outside during COVID-19 were more likely to meet all WHO Global guidelines (AdjOR = 3.3, 95%CI 1.1,9.8) than those who were not. Children of parents with higher compared to lower stress were less likely to meet all three guidelines (AdjOR = 0.5, 95%CI 0.3,0.9).

METHODS: Two schools in Kuala Lumpur with similar socio-demographic characteristics were assigned as intervention (IG) and control (CG), respectively. Inclusion criteria were healthy Malaysian overweight/obese children aged 9 to 11 years who had no serious co-morbidity. Children who reported consuming whole grain foods in their 3-day diet-recall during recruitment were excluded. A total of 63 children (31 IG; 32 CG) completed the intervention. KAP questionnaire was self-administered at baseline [T0] and post intervention (at 3rd [T1] and 9th month [T2]). The baseline differences between the IG and CG across socio-demographics and scores of KAP toward whole grains were determined using chi-square and t-test, respectively. ANCOVA was performed to determine the effect of the GReat-Child Trial™ on KAP towards whole grains at post-intervention and follow-up. Baseline variables were considered as covariates.