METHODS: We examined associations of body mass index (BMI), waist circumference (WC), and waist-hip ratio (WHR) with lung cancer risk among 1.6 million Americans, Europeans, and Asians. Cox proportional hazard regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) with adjustment for potential confounders. Analyses for WC/WHR were further adjusted for BMI. The joint effect of BMI and WC/WHR was also evaluated.
RESULTS: During an average 12-year follow-up, 23 732 incident lung cancer cases were identified. While BMI was generally associated with a decreased risk, WC and WHR were associated with increased risk after controlling for BMI. These associations were seen 10 years before diagnosis in smokers and never smokers, were strongest among blacks, and varied by histological type. After excluding the first five years of follow-up, hazard ratios per 5 kg/m2 increase in BMI were 0.95 (95% CI = 0.90 to 1.00), 0.92 (95% CI = 0.89 to 0.95), and 0.89 (95% CI = 0.86 to 0.91) in never, former, and current smokers, and 0.86 (95% CI = 0.84 to 0.89), 0.94 (95% CI = 0.90 to 0.99), and 1.09 (95% CI = 1.03 to 1.15) for adenocarcinoma, squamous cell, and small cell carcinoma, respectively. Hazard ratios per 10 cm increase in WC were 1.09 (95% CI = 1.00 to 1.18), 1.12 (95% CI = 1.07 to 1.17), and 1.11 (95% CI = 1.07 to 1.16) in never, former, and current smokers, and 1.06 (95% CI = 1.01 to 1.12), 1.20 (95% CI = 1.12 to 1.29), and 1.13 (95% CI = 1.04 to 1.23) for adenocarcinoma, squamous cell, and small cell carcinoma, respectively. Participants with BMIs of less than 25 kg/m2 but high WC had a 40% higher risk (HR = 1.40, 95% CI = 1.26 to 1.56) than those with BMIs of 25 kg/m2 or greater but normal/moderate WC.
CONCLUSIONS: The inverse BMI-lung cancer association is not entirely due to smoking and reverse causation. Central obesity, particularly concurrent with low BMI, may help identify high-risk populations for lung cancer.
OBJECTIVE: To develop international WC percentile cutoffs for children and adolescents with normal weight based on data from 8 countries in different global regions and to examine the relation with cardiovascular risk.
DESIGN AND SETTING: We used pooled data on WC in 113,453 children and adolescents (males 50.2%) aged 4 to 20 years from 8 countries in different regions (Bulgaria, China, Iran, Korea, Malaysia, Poland, Seychelles, and Switzerland). We calculated WC percentile cutoffs in samples including or excluding children with obesity, overweight, or underweight. WC percentiles were generated using the general additive model for location, scale, and shape (GAMLSS). We also estimated the predictive power of the WC 90th percentile cutoffs to predict cardiovascular risk using receiver operator characteristics curve analysis based on data from 3 countries that had available data (China, Iran, and Korea). We also examined which WC percentiles linked with WC cutoffs for central obesity in adults (at age of 18 years).
MAIN OUTCOME MEASURE: WC measured based on recommendation by the World Health Organization.
RESULTS: We validated the performance of the age- and sex-specific 90th percentile WC cutoffs calculated in children and adolescents (6-18 years of age) with normal weight (excluding youth with obesity, overweight, or underweight) by linking the percentile with cardiovascular risk (area under the curve [AUC]: 0.69 for boys; 0.63 for girls). In addition, WC percentile among normal weight children linked relatively well with established WC cutoffs for central obesity in adults (eg, AUC in US adolescents: 0.71 for boys; 0.68 for girls).
CONCLUSION: The international WC cutoffs developed in this study could be useful to screen central obesity in children and adolescents aged 6 to 18 years and allow direct comparison of WC distributions between populations and over time.
Methods: A multi-centred matched case control study was conducted in five local hospitals. A total of 140 histologically confirmed CRC cases were matched with 280 cancer free controls. Mean value and prevalence of the components of metabolic syndrome between cases and controls were measured based on the three definitions. A multiple variable analysis using Cox regression was conducted to measure the strength of the association between the definitions of MetS, components of MetS and risk of CRC.
Results: Multiple variable analyses showed that metabolic syndrome significantly and independently increased the risk of CRC, with an odds ratio ranging from 1.79 to 2.61. This study identified that the definition of metabolic syndrome by the International Diabetes Federation is the most sensitive in predicting the risk of CRC, compared to metabolic syndrome as defined by the World Health Organization and National Cholesterol Education Program Adults Treatment Panel III. Abdominal obesity, low HDL-cholesterol, and hypertension were identified as the three core risk factors, which promote inflammatory signals that contribute to metabolic syndrome and an increased risk of CRC.
Conclusions: These data hypothesized that simple measurement of abdominal obesity, abnormal BP and HDL-cholesterol especially using International Diabetes Federation (IDF) definition of MetS for South Asians for to detect individuals at CRC risk may have higher clinical utility than applying other universal complex MetS definitions.
OBJECTIVE: The objective of this study was to determine the relationship between obesity and blood lipids with a risk of colorectal cancer (CRC).
METHODOLOGY: Histologically confirmed CRC patients from five local hospitals were matched with cancer-free controls for age, gender, and ethnicity (n = 140: 280). The study participants underwent physical assessment for the presence of obesity and 10 mL of fasting blood was drawn for blood lipid analysis.
RESULTS: In this study, abdominal obesity significantly doubled the risk of CRC (adjusted odds ratio [AOR] =1.69, 95% confidence interval [CI] = 1-2.83). Hypercholesterolemia and low high-density lipoprotein cholesterol (HDL) increased the risk of CRC more than twofolds (AOR = 2.6, 95% CI = 1.7-3.9 and AOR = 3.8, 95% CI = 2.3-6.3, respectively). Abdominal obesity and hypercholesterolemia synergically doubled the risk of CRC (AOR = 2.0, 95% CI = 1-4). Low-HDL has shown no synergic association with other dyslipidemic states with an increased CRC risk.
CONCLUSION: Improving abdominal obesity, hypercholesterolemia, and low HDL may be a clinically relevant strategy to reduce the risk of CRC among Malaysians.
METHODS: We recruited 54 abdominally obese subjects to participate in a prospective cross-over design, single-blind trial comparing isocaloric 2000 kcal MUFA or carbohydrate-enriched diet with SFA-enriched diet (control). The control diet consisted of 15E% protein, 53E% carbohydrate and 32E% fat (12E% SFA, 13E% MUFA). A total of ∼7E% of MUFA or refined carbohydrate was exchanged with SFA in the MUFA-rich and carbohydrate-rich diets respectively for 6-weeks. Blood samples were collected at fasting upon trial commencement and at week-5 and 6 of each dietary-intervention phase to measure levels of cytokines (IL-6, IL-1β), C-reactive protein (CRP), thrombogenic markers (E-selectin, PAI-1, D-dimer) and lipid subfractions. Radial pulse wave analysis and a 6-h postprandial mixed meal challenge were carried out at week-6 of each dietary intervention. Blood samples were collected at fasting, 15 and 30 min and hourly intervals thereafter till 6 h after a mixed meal challenge (muffin and milkshake) with SFA or MUFA (872.5 kcal, 50 g fat, 88 g carbohydrates) or CARB (881.3 kcal, 20 g fat, 158 g carbohydrates)- enrichment corresponding to the background diets.
RESULTS: No significant differences in fasting inflammatory and thrombogenic factors were noted between diets (P > 0.05). CARB meal was found to increase plasma IL-6 whereas MUFA meal elevated plasma D-dimer postprandially compared with SAFA meal (P
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.
MATERIALS AND METHODS: A dose-ranging analysis using SKF7® was conducted through a randomized, double-blind, multicentre, placebo-controlled, phase 2 clinical trial involving individuals with obesity (N = 133) between January 2020 and April 2021. The potential percentage of change was assessed in relation to BW, BMI, WC and WHtR.
RESULTS: Average treatment effect estimates (treatment group vs. placebo) show a statistically significant reduction in the percentage of change for BW (mean = -2.915; CI: -4.546, -1.285), BMI (-2.921; CI: -4.551, -1.291), WC (mean = -2.187; CI: -3.784, -0.589) and WHtR (mean = -2.294, CI: -3.908, -0.681) in the group with a total of 750 mg of SKF7® (p
AIMS: To systematically identify and summarize the available literature on whether the modifiable risk factors associated with prediabetes displays similar relationship in both the genders.
METHODS: A systematic search was performed on electronic databases i.e. PubMed, EBSCOhost, and Scopus using "sex", "gender", "modifiable risk factors" and "prediabetes" as keywords. Reference list from identified studies was used to augment the search strategy. Methodological quality and results from individual studies were summarized in tables.
RESULTS: Gender differences in the risk factor association were observed among reviewed studies. Overall, reported association between risk factors and prediabetes apparently stronger among men. In particular, abdominal obesity, dyslipidemia, smoking and alcohol drinking habits were risk factors that showed prominent association among men. Hypertension and poor diet quality may appear to be stronger among women. General obesity showed stringent hold, while physical activity not significantly associated with the risk of prediabetes in both the genders.
CONCLUSIONS: Evidence suggests the existence of gender differences in risk factors associated with prediabetes, demands future researchers to analyze data separately based on gender. The consideration and the implementation of gender differences in health policies and in diabetes prevention programs may improve the quality of care and reduce number of diabetes prevalence among prediabetic subjects.