Methods: Analyses were performed on 243 women (mean body mass index 31.27 ± 4.14 kg/m2) who completed a 12-month lifestyle intervention in low socioeconomic communities in Klang Valley, Malaysia. Analysis of covariance (ANCOVA) was used to compare changes of cardiometabolic risk factors across weight change categories (2% gain, ±2% maintain, >2 to <5% loss, and 5 to 20% loss) within intervention and control group.
Results: A graded association for changes in waist circumference, fasting insulin, and total cholesterol (p=0.002, for all variables) across the weight change categories were observed within the intervention group at six months postintervention. Participants who lost 5 to 20% of weight had the greatest improvements in those risk markers (-5.67 cm CI: -7.98 to -3.36, -4.27 μU/mL CI: -7.35, -1.19, and -0.59 mmol/L CI: -.99, -0.19, respectively) compared to those who did not. Those who lost >2% to <5% weight reduced more waist circumference (-4.24 cm CI: -5.44 to -3.04) and fasting insulin (-0.36 μU/mL CI: -1.95 to 1.24) than those who maintained or gained weight. No significant association was detected in changes of risk markers across the weight change categories within the control group except for waist circumference and adiponectin.
Conclusion: Weight loss of >2 to <5% obtained through lifestyle intervention may represent a reasonable initial weight loss target for women in the low socioeconomic community as it led to improvements in selected risk markers, particularly of diabetes risk.
METHODS AND RESULTS: Data was sourced from participants in the Western Australian Pregnancy (Raine) Cohort Study. At 14 and 17 y, dietary intake, anthropometric and biochemical data were measured and z-scores for an 'energy dense, high fat and low fibre' DP were estimated using reduced rank regression (RRR). Associations between DP z-scores and cardiometabolic risk factors were examined using regression models. Tracking of DP z-scores was assessed using Pearson's correlation coefficient. A 1 SD unit increase in DP z-score between 14 and 17 y was associated with a 20% greater odds of high metabolic risk (95% CI: 1.01, 1.41) and a 0.04 mmol/L higher fasting glucose in boys (95% CI: 0.01, 0.08); a 28% greater odds of a high-waist circumference (95% CI: 1.00, 1.63) in girls. An increase of 3% and 4% was observed for insulin and HOMA (95% CI: 1%, 7%), respectively, in boys and girls, for every 1 SD increase in DP z-score and independently of BMI. The DP showed moderate tracking between 14 and 17 y of age (r = 0.51 for boys, r = 0.45 for girls).
CONCLUSION: An 'energy dense, high fat, low fibre' DP is positively associated with cardiometabolic risk factors and tends to persist throughout adolescence.
METHODS AND ANALYSIS: The PUTRA-Adol is a prospective follow-up study that builds up from 933 Malaysian adolescents who were initially recruited from three southern states in Peninsular Malaysia in 2016 (aged 13 years then). Two sessions are planned; the first session will involve the collection of socio-economy, physical activity, dietary intakes, mental well-being, body image, risk taking behaviour, sun exposure, family functioning and menstrual (in women) information. The second session of data collection will be focused on direct assessments such as venesection for blood biochemistry, anthropometry and ultrasonography imaging of liver and bilateral carotid arteries. Z-scores for an empirical DP will be identified at 16 years using reduced rank regression. Multilevel modelling will be conducted to assess the tracking of DP and prospective analysis between the DP, cardiometabolic health, NAFLD, CIMT and mental well-being.
ETHICS AND DISSEMINATION: Ethical approval for the conduct of this follow-up study was obtained from the Universiti Putra Malaysia's Ethics Committee for Research Involving Human Subjects (JKEUPM) (Reference number: JKEUPM-2019-267). The findings from this study will be disseminated in conferences and peer-reviewed journals.
DISCUSSION: The findings gathered from this study will provide evidence on prospective relationships between DPs, cardiometabolic risk factors, NAFLD, early atherosclerosis and mental well-being and that it may be mediated particularly DED and added sugar during adolescence.
METHODS: We examined determinants and tracking of a dietary pattern (DP) associated with metabolic risk and its key food groups among 860 adolescents in the Western Australian Pregnancy (Raine) Cohort study. Food intake was reported using a food frequency questionnaire (FFQ) at 14 and 17 years. Z-scores for an 'energy-dense, high-fat, low-fibre' DP were estimated by applying reduced rank regression at both ages. Tracking was based on the predictive value (PV) of remaining in the DPZ-score or food intake quartile at 14 and 17 years. Early-life exposures included: maternal age; maternal pre-pregnancy body mass index; parent smoking status during pregnancy; and parent socio-economic position (SEP) at 14 and 17 years. Associations between the DPZ-scores, early-life factors and SEP were analysed using regression analysis.
RESULTS: Dietary tracking was strongest among boys with high DPZ-scores, high intakes of processed meat, low-fibre bread, crisps and savoury snacks (PV > 1) and the lowest intakes of vegetables, fruit and legumes. Lower maternal education (β = 0.09, P = 0.002 at 14 years; β = 0.14, P
OBJECTIVES: We examined trajectories across adolescence and early adulthood for 2 major dietary patterns and their associations with childhood and parental factors.
METHODS: Using data from the Western Australian Pregnancy Cohort (Raine Study), intakes of 38 food groups were estimated at ages 14, 17, 20 and 22 y in 1414 participants using evaluated FFQs. Using factor analysis, 2 major dietary patterns (healthy and Western) were consistently identified across follow-ups. Sex-specific group-based modeling assessed the variation in individual dietary pattern z scores to identify group trajectories for each pattern between ages 14 and 22 y and to assess their associations with childhood and parental factors.
RESULTS: Two major trajectory groups were identified for each pattern. Between ages 14 and 22 y, a majority of the cohort (70% males, 73% females) formed a trajectory group with consistently low z scores for the healthy dietary pattern. The remainder had trajectories showing either declining (27% females) or reasonably consistent healthy dietary pattern z scores (30% males). For the Western dietary pattern, the majority formed trajectories with reasonably consistent average scores (79% males, 81% females) or low scores that declined over time. However, 21% of males had a trajectory of steady, marked increases in Western dietary pattern scores over time. A lower maternal education and higher BMI (in kg/m2) were positively associated with consistently lower scores of the healthy dietary pattern. Lower family income, family functioning score, maternal age, and being in a single-parent family were positively related to higher scores of the Western dietary pattern.
CONCLUSIONS: Poor dietary patterns established in adolescence are likely to track into early adulthood, particularly in males. This study highlights the transition between adolescence and early adulthood as a critical period and the populations that could benefit from dietary interventions.
METHODS: This cross-sectional study was conducted among 555 (164 men, 391 women) Orang Asli adults aged 18-65 years of Jah Hut sub-tribe in Krau Wildlife Reserve (KWR), Peninsular Malaysia. Demographic and socio-economic information were obtained using interviewer-administered questionnaire. Participants were also assessed for serum 25-hydroxyvitamin D (25(OH)D) concentration, adiposity indices (BMI, WC, WHtR, WHR, %BF) and lipid parameters (TC, LDL-C, HDL-C, TG). Data were analyzed using binary logistic regression via SPSS.
RESULTS: The prevalence of suboptimal 25(OH)D concentration was 26.3%, comprising 24.9% insufficiency (50 to <75 nmol/L) and 1.4% deficiency (<50 nmol/L). While men (14-30.5%) were associated with a more proatherogenic lipid profile than women (6.1-14.3%), more women were with central obesity (M: 19.5-46.3%; F: 34.5-49.1%) and suboptimal (<75 nmol/L) vitamin D status (M: 11.6%; F: 32.4%). While suboptimal 25(OH)D concentration was significantly associated with higher odds of at-risk LDL-C (p < 0.01) and obesity (WC, WHtR) (p < 0.05) in men, no significant association was observed for women. Nonetheless, it should be noted that there were only 19 men with suboptimal (<75 nmol/L) vitamin D status.
CONCLUSIONS: While suboptimal vitamin D status was relatively low in Orang Asli adults, the prevalence of obesity and undesirable serum lipids were relatively high. The sex-specific associations between vitamin D status with adiposity indices and serum lipids warrant further investigation.
Methods: This is a cross-sectional study among 335 adolescents who provided both dietary information assessed using a validated food frequency questionnaire (FFQ) and biochemical parameters including lipid profile, blood glucose, serum insulin and homeostatic model assessment-insulin resistance (HOMA-IR). Anthropometric measurements included weight (kg), height (cm) and waist circumference (cm), while body mass index (BMI) in kg/m2 was estimated, respectively. Reduced rank regression (RRR) identified a DP with percentage of energy from sugar and total fat, DED and fibre density intake as response variables.
Results: The identified 'high sugar, high fibre, high DED and low fat' DP was characterised by high intakes of sugar-sweetened beverages, fruits, sweets and low intakes of meat and cereal. Adolescents in the highest tertile of the identified DP had about 3.0 (OR = 2.7; 95%CI: 1.3, 5.6) and 2.0 (OR = 1.9; 95%CI: 1.0, 3.5) times higher odds of having dyslipideamia or elevated total cholesterol and LDL-cholesterol level, respectively compared to adolescents in the lowest tertile DP after adjusting for sex, school location, maternal education, physical activity, dietary misreporting and BMI z-score. This DP was not significantly associated with overweight and obesity.
Conclusions: Higher adherence to a DP characterised mainly by free sugars and DED was associated with greater odds of having dyslipideamia, elevated total cholesterol and LDL-cholesterol levels in Malaysian adolescents.
METHODS: A total of 243 participants from MyBFF@home were included in this study. Fasting blood samples at baseline, 6- and 12-month were assessed for fasting plasma glucose (FPG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglycerides. The effect of the intervention on cardiometabolic risk markers were investigated within and between study groups using t-test and general linear model (GLM) repeated measure ANOVA.
RESULTS: Results from repeated measures ANOVA showed intervention effect only in TC where significant reduction was found in the intervention group (- 0.26 mmol/L [95% CI: - 0.47 to - 0.06], p
MATERIALS AND METHODS: A cross-sectional study was performed involving 331 subjects between 45-90 years recruited at a health screening programme. Sociodemographic and clinical characteristics were recorded. Biochemical analyses on fasting blood samples and dual energy X-ray absorptiometry scan to determine bone mineral density (BMD) were performed.
RESULTS: Increased waist circumference (WC) was protective for abnormal BMD status (osteopenia and OP). Males with increased high-density lipoprotein cholesterol (HDL) were more likely to be osteoporotic. WC, fasting blood glucose (FBG) and triglyceride (TG) were positively associated with BMD at all sites but was gender specific. In contrast, WC was negatively associated with trabecular bone score (TBS) for females but this association became attenuated when adjusted for fat percentage. HDL and MetS were negatively and positively associated with BMD, respectively in males.
CONCLUSION: The cardiovascular risk factors of raised WC, FBG, TG and low HDL were significantly associated with increased BMD with skeletal site and gender specific differences after adjusting for confounders. However, a higher WC was associated with a weaker skeletal microstructure reflected by lower TBS in females driven by fat percentage. A higher BMD was demonstrated among MetS individuals. These findings suggest that adiposity may have a protective effect on BMD.
METHODS: This was a quasi-experimental study conducted in low-cost flats in Kuala Lumpur, Malaysia. A total of 255 overweight and obesity individuals aged between 18 to 59 years old were assigned to either the lifestyle intervention group (n = 169) or the usual care group (n = 146) over a period of 6 months. Individuals in the intervention group received 6 individual lifestyle counselling comprised of physical activity, diet counselling and self-monitoring components aimed to achieve at least 5% weight loss while individuals in the usual care group obtained six sessions of health care seminars from health care providers. These individuals were then followed-up for another 6 months without any intervention as part of maintenance period.
RESULTS: An intention-to-treat analysis of between-groups at 6-month of intervention (β, 95% CI) revealed greater changes in weight among intervention individuals' (- 1.09 kg vs. -0.99; p 0.05). Individuals in the intervention group showed a significant increase for skeletal muscle mass (0.13 kg) than those individuals in the control group (- 0.37 kg), p = 0.033, throughout the study period.
CONCLUSION: This study provides evidence that an overweight and obesity prevention program can be implemented in a community setting, with some reduction of several anthropometric and body composition parameters.
METHODS: Data of participants in the MyBFF@home study (intervention and control groups) were analysed. Participants in the intervention group received personalised dietary counselling consisted of reduced calorie diet 1200-1500 kcal/day, while the control group was assigned to receive women's health seminars. The dietary assessment was done during the intervention phase at baseline, 1 month (m), 2 m, 3 m and 6 m using a 3-day food diary. Body fat was measured using a bioelectrical impedance analyser (In-body 720) at baseline and at the end of the intervention phase. The mean differences of nutrient intake and body compositions during the intervention phase were measured with paired t-test. The changes in body fat and nutrients intake were calculated by subtracting baseline measurements from those taken at 6 months. Multiple linear regression analysis was conducted to determine the extent to which the changes in each gram of nutrients per 1000 kcal were predictive of changes in body fat mass.
RESULTS: There were significant reductions in energy, all macronutrients, dietary fibre, calcium and iron intake in both study groups after the intervention phase (p
SUBJECTS/METHODS: The Radimer/Cornell Hunger and Food Insecurity Instrument and the Malaysian Healthy Eating Index (HEI) were used to assess household food security status and diet quality, respectively. Information on socio-demographic characteristics and 24-hour dietary recall data were collected through face-to-face interview, and anthropometric measurements including weight, height, and body mass index (BMI) were obtained from 222 women.
RESULTS: Majority of households (82.9%) experienced different levels of food insecurity: 29.3% household food insecurity, 23.4% individual food insecurity, and 30.2% fell into the child hunger group. The food-secure group had significantly fewer children and smaller household sizes than the food-insecure groups (P < 0.05). The mean household income, income per capita, and food expenditure significantly decreased as food insecurity worsened (P < 0.001). The food-secure group had significantly higher Malaysian HEI scores for grains and cereals (P < 0.01), as well as for meat, poultry, and eggs (P < 0.001), than the food-insecure groups. The child-hunger group had significantly higher fat (P < 0.05) and sodium (P < 0.001) scores than the food-secure and household food-insecure groups. Compared to the individual food-insecure and child-hunger groups, multivariate analysis of covariance showed that the food-secure group was significantly associated with a higher Malaysian HEI score while the household food-insecure group was significantly associated with a higher BMI after controlling for age (P < 0.025).
CONCLUSIONS: The majority of indigenous households faced food insecurity. Food insecurity at the individual and child levels was associated with lower quality of diet, while food insecurity at the household level was associated with higher body weight. Therefore, a substantial effort by all stakeholders is warranted to improve food insecurity among poorer households. The results suggest a pressing need for nutritional interventions to improve dietary intake among low income households.