METHODS: Data from World Health Survey conducted in 2002-2004 in low-middle- and high-income countries were used. Participants aged 18 years and over were selected using multistage, stratified cluster sampling. BMI was used as an outcome variable. Culture of the countries was measured using Hofstede's cultural dimensions: Uncertainty avoidance, individualism, Power Distance and masculinity. The potential determinants of individual-level BMI were participants' sex, age, marital status, education, occupation as well as household-wealth and location (rural/urban) at the individual-level. The country-level factors used were average national income (GNI-PPP), income inequality (Gini-index) and Hofstede's cultural dimensions. A two-level random-intercepts and fixed-slopes model structure with individuals nested within countries were fitted, treating BMI as a continuous outcome variable.

RESULTS: A sample of 156,192 people from 53 countries was included in this analysis. The design-based (weighted) mean BMI (SE) in these 53 countries was 23.95(0.08). Uncertainty avoidance (UAI) and individualism (IDV) were significantly associated with BMI, showing that people in more individualistic or high uncertainty avoidance countries had higher BMI than collectivist or low uncertainty avoidance ones. This model explained that one unit increase in UAI or IDV was associated with 0.03 unit increase in BMI. Power distance and masculinity were not associated with BMI of the people. National level Income was also significantly associated with individual-level BMI.

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.

METHODS: A cross-sectional study was carried out on 446 older adults aged 50 years and above from 20 randomly selected villages. Respondents were interviewed to collect information on their demographic characteristics and oral health perception, followed by physical examination to measure height, weight and body mass index (BMI) of respondents. The validated Malay version of General Oral Health Assessment Index (GOHAI) was used to measure OHRQoL.

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: A cross-sectional study was conducted to recruit a total of 357 mothers aged 18-50 years. Interviews were carried out among mothers to collect sociodemographic information, nutritional information, and physical activity. Anthropometric measurements [height, weight and waist circumference (WC)] were conducted with the mothers. Body Mass Index (BMI) was computed to determine the prevalence of overweight and obesity. Multinomial logistic regression was used to examine the associated factors of overweight and obesity.

METHODS: Two cross-sectional studies were conducted in urban and rural areas of Yangon Region in 2013 and 2014 respectively, using the WHO STEPwise approach to surveillance of risk factors of NCDs. Through a multi-stage cluster sampling method, 1486 participants were recruited.

RESULTS: Age-standardized prevalence of the behavioral risk factors tended to be higher in the rural than urban areas for all included factors and significantly higher for alcohol drinking (19.9% vs. 13.9%; p = 0.040) and low fruit & vegetable consumption (96.7% vs. 85.1%; p = 0.001). For the metabolic risk factors, the tendency was opposite, with higher age-standardized prevalence estimates in urban than rural areas, significantly for overweight and obesity combined (40.9% vs. 31.2%; p = 0.023), obesity (12.3% vs.7.7%; p = 0.019) and diabetes (17.2% vs. 9.2%; p = 0.024). In sub-group analysis by gender, the prevalence of hypercholesterolemia and hypertriglyceridemia were significantly higher in urban than rural areas among males, 61.8% vs. 40.4%; p = 0.002 and 31.4% vs. 20.7%; p = 0.009, respectively. Mean values of age-standardized metabolic parameters showed higher values in urban than rural areas for both male and female. Based on WHO age-standardized Framingham risk scores, 33.0% (95% CI = 31.7-34.4) of urban dwellers and 27.0% (95% CI = 23.5-30.8) of rural dwellers had a moderate to high risk of developing CHD in the next 10 years.

METHODS: A total of 50 obese children (7-11 years old) were randomized to the intervention group (IG, n = 25) or the control group (CG, n = 25). Data were collected at baseline, at follow-up (every month) and at six months after the end of the intervention. IG received stage-based lifestyle modification intervention based on the Nutrition Practice Guideline for the Management of Childhood Obesity, while CG received standard treatment. Changes in body composition, physical activity and dietary intake were examined in both the intervention and control groups.

METHODS: Four-hundred and ninety Malaysian adults (n = 490) aged 20 to 65 years old participated in this cross-sectional study. Their body weight, height, and WC measurements were measured according to standard procedures. Physical activity was assessed objectively with accelerometers for five to seven consecutive days. The International Physical Activity Questionnaire (IPAQ) was used to estimate the amount of time spent on various domains of physical activity. Mixed models were used to determine the associations between physical activity variables and both BMI and WC.

RESULTS: The mean value of objectively measured moderate-to-vigorous physical activity (MVPA) was 13.5 min per day, in which male participants recorded a significantly higher amount of time compared to females. On the other hand, the mean self-reported total physical activity was 380 min per week; male participants reported a significantly higher amount of time on physical activity in the occupation/work and leisure/recreation domains while female participants spent significantly more time in the domestic/household chores domain. We also observed that the mean values of objectively measured total MVPA, self-reported time spent on walking for leisure/recreation, and total time amount of time spent on MVPA for leisure/recreation were significantly higher among participants with BMI of less than 25 kg/m2. The final statistical model yielded a significant negative association between objectively measured total MVPA and BMI, but not with WC measurement. No significant association was reported between self-reported total physical activity with BMI and WC measurement.

METHODS: This is an analytical cross sectional study. A total of 380 subjects were sampled and their vitamins D status (25-hydroxyvitamin D), fasting blood glucose, full lipid profile were assessed using venous blood. Systolic and diastolic blood pressure, weight, height and waist circumference were measured following standard protocols. Socio-demographic data such as sex, age, smoking status etc were also collected. Data was analysed using t-test, chi-square test, General Linear Model and multiple logistic regression.

RESULTS: Females made up 58% of the sample. The mean age of respondents was 48.5 (SD 5.2) years. Females had significantly lower mean Vitamin D levels (36.2; 95% CI: 34.5, 38.0 nmol/L) compared to males (56.2; 95% CI: 53.2, 59.2 nmol/L). Approximately 41% and 87% of males and females respectively had insufficient (< 50 nmol/L) levels of 25-hydroxyvitamin D (p < 0.001). The prevalence of Metabolic Syndrome for the whole sample was 38.4 (95% CI: 33.5, 43.3)%. In the multivariate model (adjusted for age, sex, abdominal obesity, HDL-cholesterol, diastolic blood pressure), insufficient Vitamin D status was significantly associated with 1-year age increments (OR: 0.93; 95% CI: 0.88, 0.98), being female (OR: 8.68; 95% CI: 5.08, 14.83) and abdominal obesity (OR: 2.57; 95% CI: 1.51, 4.39). Respondents with insufficient vitamin D were found to have higher odds of having Metabolic Syndrome (OR: 1.73; 95% CI: 1.02, 2.92) after adjusting for age and sex.

METHODS: Using a cross-sectional study design, body weight and height were measured, and BMI was calculated and classified using WHO BMI-for-age Z-score. Data was obtained using the National Fitness Standard (SEGAK) assessment, which was uploaded in a specific Health Monitoring System (HEMS).

METHODS: This study used data from the 2015 National Health and Morbidity Survey (NHMS), a nationwide cross-sectional survey that implemented a two-stage stratified random sampling design. Respondents aged 18 years and above (n = 17,261) were included in the analysis. The short version of International Physical Activity Questionnaire (IPAQ) was administered to assess the respondents' PA levels. The respondents' height and weight were objectively measured and body mass index (BMI) was calculated. The respondents were categorized according to BMI as either normal-weight (18.5-24.9 kg/m2) or overweight/obese (≥ 25 kg/m2). Descriptive and complex sample logistic regression analyses were employed as appropriate.

METHODS: This was a cross sectional study carried out in two primary care clinics in a semi-urban locality of Ampangan, Negeri Sembilan, Malaysia. Data was collected through self-administered questionnaires assessing the demographic characteristics, medical history, lifestyle and physical activity. The Short Form 36-items health survey was used to measure HRQOL among the pre-diabetics. Data entry and analysis were performed using the SPSS version 19.

RESULTS: A total of 268 eligible pre-diabetics participated in this study. The prevalence of normal weight, overweight and obesity were 7.1%, 21.6% and 71.3% respectively. Their mean (SD) age was 52.5 (8.3) years and 64.2% were females. Among the obese pre-diabetics, 42.2% had both IFG and IGT, 47.0% had isolated IFG and 10.8% had isolated IGT, 36.2% had combination of hypertension, dyslipidemia and musculoskeletal diseases. More than 53.4% of the obese pre-diabetics had family history of diabetes, 15.7% were smokers and 60.8% were physically inactive with mean PA of <600 MET-minutes/week. After adjusted for co-variants, Physical Component Summary (PCS) was significantly associated with BMI categories [F (2,262)=11.73, p<0.001] where pre-diabetics with normal weight and overweight had significantly higher PCS than those obese; normal vs obese [Mdiff=9.84, p=0.006, 95% CIdiff=2.28, 17.40] and between overweight vs obese [Mdiff=8.14, p<0.001, 95% CIdiff=3.46, 12.80].

METHODS: The scoping review was conducted based on the framework by Arksey and O'Malley. The Preferred Reporting Items for Systematic Reviews and Meta Analysis (PRISMA) diagram was used as a guide to record the review process. Articles from year 2008 until 2017 on overweight and obesity among adults aged 18 years and above were retrieved based on the keywords using electronic databases (Embase/Ovid, Pubmed, Cochrane library and Google Scholar). Local journals, Nutrition Research in Malaysia Biblography (2011 and 2016), online local theses databases, virtual library databases were also included in the searches. Consultations with relevant key informants from the National Institutes of Health and local universities were also conducted. Search activities were managed using Endnote software and MS Excelsheet.

RESULTS: The characteristics of the results were described based on the objectives of the review. A total of 2004 articles and reports were retrieved, and 188 articles related to obesity in Malaysia were included in the final review. Scopes and topics of obesity research based on the Nutrition Research Priorities in Malaysia (NRPM) for 11th Malaysia Plan were obesity prevalence, weight loss intervention, association of physical activities and dietary factors with obesity. The majority of obesity research among adults in Malaysia was cross sectional studies and only a small number of intervention studies, qualitative studies and systematic review were indentified. Research gaps were identified in order to make useful recommendations to the stakeholders.

METHODS: This is a follow-up study among 84 obese housewives without co-morbidities aged 18 to 59 years old who previously participated as a control group (delayed intervention, G1) in the My Body is Fit and Fabulous at Home (MyBFF@home) Phase II. Baseline data were obtained from 12 month data collection for this group. A new group of 42 obese housewives with co-morbidities (G2) were also recruited. Both groups received a 6 month intervention (July-December 2015) consisting of dietary counselling, physical activity (PA) and self-monitoring tools (PA diary, food diary and pedometer). Study parameters included weight, height, waist circumference, blood pressure and body compositions. Body compositions were measured using a bioelectrical impedance analysis device, Inbody 720. Descriptive and repeated measures ANOVA analyses were performed using SPSS 21.

METHODS: A total of 322 participants from the MyBFF@home study completed the Newest Vital Sign (NVS) test at baseline. However, only data from 209 participants who completed the NVS test from baseline to WL intervention were used to determine the HL groups. Change of the NVS scores from baseline to WL intervention phase was categorized into two groups: those with HL improvement (increased 0.1 score and above) and those without HL improvement (no change or decreased 0.1 score and more). Independent variables in this study were change of energy intake, nutrient intake, physical activity, anthropometry measurements, and body composition measurements between baseline and WL intervention as well as between WL intervention and WL maintenance. An Independent sample t-test was used in the statistical analysis.

RESULTS: In general, both intervention and control participants have low HL. The study revealed that the intervention group increased the NVS mean score from baseline (1.19 scores) to the end of the WL maintenance phase (1.51 scores) compared to the control group. There was no significant difference in sociodemographic characteristics between the group with HL improvement and the group without HL improvement at baseline. Most of the dietary intake measurements at WL intervention were significantly different between the two HL groups among intervention participants. Physical activity and body composition did not differ significantly between the two HL groups among both intervention and control groups.

METHODS: Baseline and sixth month data from the MyBFF@home study were used for this purpose. A total of 169 of overweight and obese respondents answered the IPAQ-SF and were asked to use a pedometer for 7 days. Data from IPAQ-SF were categorised as inactive and active while data from pedometer were categorised as insufficiently active and sufficiently active by standard classification. Data on sociodemographic and anthropometry were also obtained. Cohen's kappa was applied to measure the agreement of IPAQ-SF and pedometer in determining the physical activity level. Pre-post cross tabulation table was created to evaluate the changes in physical activity over 6 months.

RESULTS: From 169 available respondents, 167 (98.8%) completed the IPAQ-SF and 107 (63.3%) utilised the pedometer. A total of 102 (61.1%) respondents were categorised as active from the IPAQ-SF. Meanwhile, only 9 (8.4%) respondents were categorised as sufficiently active via pedometer. Cohen's κ found there was a poor agreement between the two methods, κ = 0.055, p > 0.05. After sixth months, there was + 9.4% increment in respondents who were active when assessed by IPAQ-SF but - 1.3% reductions for respondents being sufficiently active when assessed by pedometer. McNemar's test determined that there was no significant difference in the proportion of inactive and active respondents by IPAQ-SF or sufficiently active and insufficiently active by pedometer from the baseline and sixth month of intervention.

DISCUSSION: The MyBFF@home (Phase II) was a quasi-experimental study and it was conducted among overweight and obese housewives living in the urban areas in Malaysia. In this phase, the study involved a weight loss intervention phase (6 months) and a weight loss maintenance phase (6 months). The intervention group received a standard weight loss intervention package and the control group received group seminars related to women's health. Measurements of weight, height, waist circumference, body composition, fasting blood lipids, dietary intake, physical activity, health literacy, body pain and quality of life were conducted during the study. Overweight and obese housewives from 14 People's Housing/Home Project (PHP) in Federal Territory of Kuala Lumpur (Klang Valley) were selected as control and intervention group (N = 328). Majority of the participants (76.1%) were from the low socioeconomic group. Data were analysed and presented according to the specific objectives and the needs for the particular topic in the present supplement report.