METHODS: Data from four population-based National Health and Morbidity Surveys conducted in 1996, 2006, 2010, and 2015 were pooled. Hierarchical Age-Period-Cohort (HAPC) analysis explored the trajectories of BMI and waist circumference across the life course and birth cohorts by sex and ethnicity. These models assumed no period effect.
RESULTS: Generally, BMI and waist circumference trajectories increased across age and birth cohorts. These trajectories varied by sex and ethnicity. Females have more profound increasing BMI and waist circumference trajectories than their male counterparts as they age and as cohort recency increases. Chinese have less profound BMI and waist circumference increases across the life course and birth cohorts than other ethnic groups.
CONCLUSIONS: The profound increasing cohort trajectories of obesity, regardless of sex and ethnicity, are alarming. Future studies should focus on identifying factors associated with the less profound cohort effect among the Chinese to reduce the magnitude of trajectories in obesity, particularly among future generations.
METHODS: A cross-sectional study was conducted from November 2019 to August 2020 on T1DM children between 6 and 18 years old who attended the Paediatric Endocrine Clinic Putrajaya Hospital. Anthropometry and bioelectrical impedance analysis (Inbody 720) were measured to analyse their effects towards glycated haemoglobin (HbA1c) via SPSS 21.
RESULTS: A total of 63 T1DM were recruited with an equal male-to-female ratio. The mean age was 12.4 ± 3.3 years old with a mean HbA1c of 9.8 ± 2.0%. The prevalence of overweight/obese and excessive body fat was 17.5 and 34.9%, respectively. Only 3 (6.8%) fulfilled the metabolic syndrome criteria. The waist circumference had a significant relationship with HbA1c. Every 10 cm increment of waist circumference was predicted to raise HbA1c by 0.8. The odds ratio of having abdominal obesity among T1DM with excessive body fat was 9.3 times.
CONCLUSIONS: Abdominal obesity is significantly associated with a poorer glycaemic control in T1DM children. Monitoring of waist circumference should be considered as part of the routine diabetic care.
DESIGN: Cross-sectional study.
SETTING: Probability proportionate to size was used to randomly select two schools in Selangor state, Malaysia.
PARTICIPANTS: A total of 513 adolescents (58.9% women and 41.1% men) aged 12-16 years were recruited.
PRIMARY AND SECONDARY OUTCOME MEASURES: Weight, height, WC and BP of the adolescents were measured. The predictive power of anthropometric indices was analysed by sex using the receiver operating characteristic curve.
RESULTS: BMI and WHtR were the indices with higher areas under the curve (AUCs), yet the optimal cut-offs to predict high BP using the 95th percentile were higher than the threshold for overweight/obesity. Most indices showed poor sensitivity under the suggested cut-offs. In contrast, the optimal BMI and WHtR cut-offs to predict high BP using the 90th percentile were lower (men: BMI-for-age=0.79, WHtR=0.46; women: BMI-for-age=0.92, WHtR=0.45). BMI showed the highest AUC in both sexes but had poor sensitivity among women. WHtR presented good sensitivity and specificity in both sexes.
CONCLUSIONS: These findings suggested that WHtR might be a useful indicator for screening high blood pressure risk in the routine primary-level health services for adolescents. Future studies are warranted to involve a larger sample size to confirm these findings.
METHODS AND STUDY DESIGN: This nationwide cross-sectional study involved 5,332 primary school children aged 6 to 12 years and 3,000 secondary school children aged 13 to 17 years. Height and weight were measured and BMI-for-age was determined. Socio-demographic backgrounds, breakfast habits and physical activity levels were assessed using questionnaires. Breakfast frequency was defined as follows: breakfast skippers (ate breakfast 0-2 days/week), irregular breakfast eaters (ate breakfast 3-4 days/week) and regular breakfast eaters (ate breakfast ≥5 days/week).
RESULTS: The overall prevalence of breakfast skippers and irregular breakfast eaters was 11.7% and 12.7% respectively. Breakfast skipping was related to age, sex, ethnicity, income and physical activity level. Among primary school boys and secondary school girls, the proportion of overweight/obesity was higher among breakfast skippers (boys: 43.9%, girls: 30.5%) than regular breakfast eaters (boys: 31.2%, girls: 22.7%). Among primary school children, only boys who skipped breakfast had a higher mean BMI-for-age z-score than regular breakfast eaters. Among secondary school boys and girls, BMI-for-age z-score was higher among breakfast skippers than regular breakfast eaters. Compared to regular breakfast eaters, primary school boys who skipped breakfast were 1.71 times (95% CI=1.26-2.32, p=0.001) more likely to be overweight/obese, while the risk was lower in primary school girls (OR=1.36, 95% CI=1.02-1.81, p=0.039) and secondary school girls (OR=1.38, 95% CI=1.01-1.90, p=0.044).
CONCLUSION: Regular breakfast consumption was associated with a healthier body weight status and is a dietary behaviour which should be encouraged.
METHODS: This study examined self-monitoring data from 61 Chinese adults who participated in a 5-week online group intervention for weight loss. Participants reported their baseline Body Mass Index (BMI), weight loss motivation, and engaged in both daily quantitative self-monitoring (e.g., caloric intake, mood, sedentary behavior, etc.) and qualitative self-monitoring (e.g., daily log that summarizes the progress of weight loss). The timeliness of participants' daily self-monitoring data filling was assessed using a scoring rule. One-way repeated measurement ANOVA was employed to analyze the dynamics of each self-monitoring indicator. Correlation and regression analyses were used to reveal the relationship between baseline data, self-monitoring indicators, and weight change. Content analysis was utilized to analyze participants' qualitative self-monitoring data. Participants were categorized into three groups based on their weight loss outcomes, and a chi-square test was used to compare the frequency distribution between these groups.
RESULTS: After the intervention, participants achieved an average weight loss of 2.52 kg (SD = 1.36) and 3.99% (SD = 1.96%) of their initial weight. Daily caloric intake, weight loss satisfaction, frequency of daily log, and the speed of weight loss showed a downward trend, but daily sedentary time gradually increased. Moreover, regression analysis showed that baseline BMI, weight loss motivation, and timeliness of daily filling predicted final weight loss. Qualitative self-monitoring data analysis revealed four categories and nineteen subcategories. A significant difference in the frequency of qualitative data was observed, with the excellent group reporting a greater number of daily logs than expected in all categories and most subcategories, and the moderate and poor groups reporting less than expected in all categories and most subcategories.
CONCLUSION: The self-monitoring data in short-term online group intervention exhibited fluctuations. Participants with higher baseline BMI, higher levels of weight loss motivation, and timely self-monitoring achieved more weight loss. Participants who achieved greater weight loss reported a higher quantity of qualitative self-monitoring data. Practitioners should focus on enhancing dieters' weight loss motivation and promote adherence to self-monitoring practices.
MATERIALS AND METHODS: This was a retrospective cohort study undertaken at a public tertiary care centre in the state of Perak, Malaysia. Information of obese patients who underwent bariatric surgery was obtained from their medical records. The changes in the BMI, HbA1C, systolic and diastolic blood pressure (SBP and DBP), and lipid levels between three months before and after the surgery were assessed.
RESULTS: The patients (n=106) were mostly Malay (66.0%), had at least one comorbidity (61.3%), and had a mean age of 40.38±11.75 years. Following surgery, the BMI of the patients was found to reduce by 9.78±5.82kg/m2. For the patients who had diabetes (n=24) and hypertension (n=47), their mean HbA1C, SBP and DBP were also shown to reduce significantly by 2.02±2.13%, 17.19±16.97mmHg, and 11.45±12.63mmHg, respectively. Meanwhile, the mean total cholesterol, triglyceride and low-density lipoprotein levels of those who had dyslipidaemia (n=21) were, respectively, lowered by 0.91±1.18mmol/L, 0.69±1.11mmol/L and 0.47±0.52mmol/L.
CONCLUSION: The findings suggest that in addition to weight reduction, bariatric surgery is helpful in improving the diabetes, hypertension and dyslipidaemia control among obese patients. However, a large-scale trial with a control group is required to verify our findings.
METHODS: We estimated global and regional temporal trends in the burden of cancer attributable to high BMI, and the contributions of various cancer types using the framework of the Global Burden of Disease Study.
RESULTS: From 2010 to 2019, there was a 35 % increase in deaths and a 34 % increase in disability-adjusted life-years from cancers attributable to high BMI. The age-standardized death rates for cancer attributable to high BMI increased over the study period (annual percentage change [APC] +0.48 %, 95 % CI 0.22 to 0.74 %). The greatest number of deaths from cancer attributable to high BMI occurred in Europe, but the fastest-growing age-standardized death rates and disability-adjusted life-years occurred in Southeast Asia. Liver cancer was the fastest-growing cause of cancer mortality (APC: 1.37 %, 95 % CI 1.25 to 1.49 %) attributable to high BMI.
CONCLUSION: The global burden of cancer-related deaths attributable to high BMI has increased substantially from 2010 to 2019. The greatest increase in age-standardized death rates occurred in Southeast Asia, and liver cancer is the fastest-growing cause of cancer mortality attributable to high BMI. Urgent and sustained measures are required at a global and regional level to reverse these trends and slow the growing burden of cancer attributed to high BMI.
METHODS: Data were obtained from the 2012 Malaysia Global School-based Student Health Survey. Generalized ordered logit regression analysis was conducted on 24 339 adolescents by PA status.
RESULTS: Early- (ages 11-13) and middle-stage (ages 14-16) adolescents were associated with higher overweight and obesity risks than their older peers (ages 17-18). Male adolescents faced higher underweight and obesity likelihoods than females. Hunger due to food shortage at home was associated with higher likelihoods of underweight and normal weight BMI categories. Smokers were more likely to be underweight or normal weight than non-smokers. Segmented-sample analysis by PA status indicated that, while the direction of associations was parallel across PA status, the magnitudes of association between age, hunger and smoking status with BMI status were greater among active than inactive adolescents.
CONCLUSIONS: Male adolescents faced a dual burden of underweight and obesity. Other sociodemographic and dietary-lifestyle factors were associated with adolescent BMI categories. Segmented-sample analysis by PA status uncovered varying associations between factors that would otherwise be masked in pooled sample analysis. Public health authorities should take these factors into consideration when deliberating programs to ensure healthy adolescent body weight.