METHODOLOGY: A cross-sectional study with a universal sampling of children and adolescents with special needs aged 2-18 years old, diagnosed with cerebral palsy, down syndrome, autism and attention-deficit/hyperactivity disorder was conducted at Community-Based Rehabilitation in Central Zone Malaysia. Socio-demographic data were obtained from files, and medical reports and anthropometric measurements (body weight, height, humeral length, and mid-upper arm circumference) were collected using standard procedures. Data were analysed using IBM SPSS version 26. The accuracy of the formula was determined by intraclass correlation, prediction at 20% of actual body weight, residual error (RE) and root mean square error (RMSE).

STUDY DESIGN: We assessed data from 6414 children aged 6-18 years, collected by the South East Asia Community Observatory. Child underweight, overweight, and obesity were expressed according to 3 internationally used BMI references: World Health Organization 2007, International Obesity Task Force 2012, and Centers for Disease Control and Prevention 2000. We assessed agreement in classification of anthropometric status among the references using Cohen's kappa statistic and estimated underweight, overweight, and obesity prevalence according to each reference using mixed effects Poisson regression.

RESULTS: There was poor to moderate agreement between references when classifying underweight, but generally good agreement when classifying overweight and obesity. Underweight, overweight, and obesity prevalence estimates generated using the 3 references were notably inconsistent. Overweight and obesity prevalence estimates were higher using the World Health Organization reference vs the other 2, and underweight prevalence was up to 8.5% higher and obesity prevalence was about 4% lower when using the International Obesity Task Force reference.

OBJECTIVE: This study aims to elucidate the relationships between food fussiness, fresh fruit and vegetable consumption, and anthropometric indices of children residing in Klang Valley, Malaysia.

METHODS: A cross-sectional study was conducted to recruit 179 pairs of consenting caregiver-child. Caregivers were required to report the surveyed child's sex, date of birth, and ethnicity. The six-item food fussiness subscale from the Child Eating Behavior Questionnaire (CEBQ) was used to assess food fussiness in children. In addition, caregivers were asked to report whether their child had consumed fresh fruits and vegetables over the past month and to list all those they consistently refused to consume. For anthropometric measurements, children's body weight was measured with a digital bathroom scale, and height was measured using a portable stadiometer. Height-for-age z-scores (HAZ) and BMI-for-age z-scores (BAZ) were determined using the WHO Anthro software version 3.2.2 (for children below five) or the WHO AnthroPlus software version 1.0.4 (for children above five). The relationships between the studied variables were analyzed using IBM SPSS statistics version 27.0.

RESULTS: This study revealed that one in two children (54.2%) were fussy eaters, 9.5% did not consume fresh fruits, and 32.4% did not consume fresh vegetables over the past month. The findings from path analyses indicated that food fussiness was negatively correlated with fresh fruit and vegetable consumption. However, there were no significant direct and indirect relationships between food fussiness and anthropometric indices as indicated by HAZ and BAZ of children.

METHODS: A cross-sectional study was conducted among 134 geriatric patients with a mean age of 68.9 ± 8.4 who stayed at acute care wards in Hospital Tuanku Ampuan Rahimah, Klang from July 2017 to August 2017. The SGA, MNA, and GNRI were administered through face-to-face interviews with all the participants who gave their consent. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the GNRI and MNA were analyzed against the SGA. Receiver-operating characteristic (ROC) curve analysis was used to obtain the area under the curve (AUC) and suitable optimal cutoff values for both the GNRI and MNA.

RESULTS: According to the SGA, MNA, and GNRI, 26.9%, 42.5%, and 44.0% of the participants were malnourished, respectively. The sensitivity, specificity, PPV, and NPV for the GNRI were 0.622, 0.977, 0.982, and 0.558, respectively, while those for the MNA were 0.611, 0.909, 0.932, and 0.533, respectively. The AUC of the GNRI was comparable to that of the MNA (0.831 and 0.898, respectively). Moreover, the optimal malnutrition cutoff value for the GNRI was 94.95.