METHODS: This study included people living with HIV enrolled in a longitudinal cohort study from 2003 to 2019, receiving antiretroviral therapy (ART), and without prior tuberculosis. BMI at ART initiation was categorized using Asian BMI classifications: underweight (<18.5 kg/m2 ), normal (18.5-22.9 kg/m2 ), overweight (23-24.9 kg/m2 ), and obese (≥25 kg/m2 ). High FBG was defined as a single post-ART FBG measurement ≥126 mg/dL. Factors associated with high FBG were analyzed using Cox regression models stratified by site.
RESULTS: A total of 3939 people living with HIV (63% male) were included. In total, 50% had a BMI in the normal weight range, 23% were underweight, 13% were overweight, and 14% were obese. Median age at ART initiation was 34 years (interquartile range 29-41). Overall, 8% had a high FBG, with an incidence rate of 1.14 per 100 person-years. Factors associated with an increased hazard of high FBG included being obese (≥25 kg/m2 ) compared with normal weight (hazard ratio [HR] = 1.79; 95% confidence interval [CI] 1.31-2.44; p 25 kg/m2 were at increased risk of high FBG. This indicates that regular assessments should be performed in those with high BMI, irrespective of the classification used.
DESIGN: Cross-sectional.
SETTING: Central and eastern regions of Peninsular Malaysia.
PARTICIPANTS: A stratified random sampling was employed to select 917 secondary school-going adolescents (aged 15-17 years).
RESULTS: The prevalence of under-reporters was 17·4 %, while no over-reporters were identified. Under-reporters had higher body composition and lower dietary intakes (except for vitamin C, Cr and Fl) compared with plausible reporters (P < 0·05). Adolescents with overweight and obesity had a higher odds of under-reporting compared with under-/normal weight adolescents (P < 0·001). In model 3, the highest regression coefficient (R2 = 0·404, P < 0·001) was obtained after adjusting for reporting status.
CONCLUSIONS: Overweight and obese adolescents were more likely to under-report their food intake and consequently affect nutrient intakes estimates. Future analyses that include nutrient intake data should adjust for reporting status so that the impact of misreporting on study outcomes can be conceded and consequently improve the accuracy of dietary-related results.
OBJECTIVE: We hypothesized that people with a high BMI have altered plasma Aβ homeostasis compared with people with a lower BMI. We also tested whether reducing BMI by calorie-restriction could normalize plasma concentrations of Aβ.
METHODS: Plasma concentrations of Aβ40, Aβ42, and Aβ42/40 ratio were measured in 106 participants with BMIs classified as lean, overweight, or obese. From this cohort, twelve participants with overweight or obese BMIs entered a 12-week calorie-restriction weight loss program. We then tested whether decreasing BMI affected plasma Aβ concentrations.
RESULTS: Plasma Aβ42/40 ratio was 17.54% lower in participants with an obese BMI compared to lean participants (p
MATERIALS AND METHODS: This cross-sectional study was conducted on 124 breast cancer outpatients within the first year of diagnosis and yet to commence oncological treatment. Body composition parameters [body weight, body mass index (BMI), body fat percentage, fat mass over fat-free mass ratio (FM/FFM), muscle mass, and visceral fat] were obtained using a bioelectrical impedance analyzer. Body fat percentage was categorized into two groups which were normal (<35%) and high (≥35%). The E-DII was calculated from the validated 165-items Food Frequency Questionnaire (FFQ) and categorized into three groups or tertiles. Multiple logistic regression analysis was used to determine the association between the E-DII and body fat percentage.
RESULTS: Mean body weight, body fat percentage, FM/FFM, and visceral fat increased as E-DII increased from the lowest tertile (T1) to the most pro-inflammatory tertile (T3) (p for trend <0.05). E-DII was positively associated with body fat percentage (OR 2.952; 95% CI 1.154-7.556; p = 0.024) and remained significant after adjustment for cancer stage, age, physical activity, ethnicity, smoking history, and presence of comorbidities. Compared to T1, participants in T3 had a significantly lower consumption of fiber, vitamin A, beta-carotene, vitamin C, iron, thiamine, riboflavin, niacin, vitamin B6, folic acid, zinc, magnesium, and selenium, but a higher intake of total fat, saturated fat, and monounsaturated fatty acids.
CONCLUSIONS: A higher E-DII was associated with increased body fat percentage, suggesting the potential of advocating anti-inflammatory diet to combat obesity among newly diagnosed breast cancer patients.
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.
METHODS: Between June 2000 and June 2020, patients with a BMI ≥ 50 kg/m2 underwent either IGB insertion followed by LRYGB (two-stage group), or LRYGB as the definitive bariatric procedure (single-stage group) in our institution. The two-stage procedure was adopted for high risk individuals. Primary outcome measures were percentage total weight loss (%TWL) at 24 months, length of stay and postoperative morbidity. Propensity score analysis was used to account for differences between groups.
RESULTS: A total of 155 (mean age 42.9 years ± 10.60; mean BMI 54.6 kg/m2 ± 4.53) underwent either the two-stage (n = 30) or single-stage procedure (n = 125) depending on preoperative fitness. At 6 months following LRYGB, there was a significant difference in %TWL between the groups in a matched analysis (11.9% vs 23.7%, p < 0.001). At 24 months, there was no difference in %TWL (32.0% vs 34.7%, p = 0.13). Median hospital stay following LRYGB was 2.0 (1-4) days with the two-stage vs 2.0 (0-14) days for the single-stage approach (p = 0.75). There was also no significant difference in complication rates (p = 0.058) between the two groups.
CONCLUSIONS: There was no difference in weight loss after one or two-stage procedures in the treatment of patients with a BMI ≥ 50 kg/m2 super obesity in a propensity score weighted analysis at 24 months. Length of stay and perioperative complications were similar for high risk patients; however, the two-stage approach was associated with delayed weight loss. Single-stage management is recommended for moderate risk patients, particularly with significant metabolic disorders, whilst two-stage approach is a safe and feasible pathway for high risk individuals.
AIM: This study aimed to compare the performance of BMI, waist circumference (WC) and waist-to-height ratio (WtHR) in predicting Malaysians with excess body fat defined by dual-energy X-ray absorptiometry (DXA).
SUBJECTS AND METHODS: A total of 399 men and women aged ≥40 years were recruited from Klang Valley, Malaysia. The body composition of the subjects, including body fat percentage, was measured by DXA. The weight, height, WC and WHtR of the subjects were also determined.
RESULTS: BMI [sensitivity = 55.7%, specificity = 86.1%, area under curve (AUC) = 0.709] and WC (sensitivity = 62.7%, specificity = 90.3%, AUC = 0.765) performed moderately in predicting excess adiposity. Their performance and sensitivity improved with lower cut-off values. The performance of WHtR (sensitivity = 96.6%, specificity = 36.1, AUC = 0.664) was optimal at the standard cut-off value and no modification was required.
CONCLUSION: The performance of WC in identifying excess adiposity was greater than BMI and WHtR based on AUC values. Modification of cut-off values for BMI and WC could improve their performance and should be considered by healthcare providers in screening individuals with excess adiposity.
METHODS: In a sample of 9448 participants followed for a mean of 15.3 years (186,158.5 person-years) from the Monitoring of Trends and Determinants in Cardiovascular Disease Augsburg/Cooperative Health Research in the Region of Augsburg population-based cohort conducted in Germany, we investigated the association of social connectivity, measured by the Social Network Index, and body mass index (BMI) with the risk of clinically validated T2D incidence using stratified Cox proportional hazards regression models adjusted for sociodemographic, life-style, cardiometabolic, and psychosocial risk factors.
RESULTS: During a mean follow-up of 14.1 years (186,158.5 person-years), 975 (10.3%) participants developed T2D. Participants with low social connectivity developed T2D at a higher rate than socially connected participants (10.0 versus 8.0 cases/10,000 person-years); however, BMI played a significant role in the association of social connectivity with T2D ( p < .001). In comparison to their socially connected counterparts, low social connectivity was associated with a higher rate of T2D incidence in normal-weight (6.0 versus 2.0 cases/10,000 person-years), but not overweight (13.0 versus 13.0 cases/10,000 person-years) or obese participants (32.0 versus 30.0 cases/10,000 person-years). Correspondingly, Cox regression analysis showed that 5-unit increments in BMI increased the risk of T2D in socially connected participants (hazard ratio = 3.03, 95% confidence interval = 2.48-3.79, p < .001) at a substantially higher rate than in low socially connected participants (hazard ratio = 1.77, 95% confidence interval = 1.45-2.16, p < .001).
CONCLUSION: The detrimental link between low social connectivity and increased risk of T2D is substantially stronger in participants with a lower BMI.