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.

METHODS: REDISCOVER, a prospective study, enrolled 11,288 adults where sociodemographic data, anthropometric and blood pressure measurements, fasting lipid profile and glucose, and history of diabetes, hypertension, and smoking were obtained. The cross-sectional analytic sample presented in this article comprised 10,482 participants from baseline recruitment. The data was analysed by descriptive statistics and multivariable logistic regression.

RESULTS: The overall prevalence of elevated TC, elevated LDL-c, elevated TG, low HDL-c, and elevated non-HDL-c were 64.0% (95% CI 63.0-65.0), 56.7% (CI 55.7-57.7), 37.4% (CI 36.5-38.4), 36.2% (CI 35.2-37.1), and 56.2% (CI 55.3-57.2), respectively. Overweight, obesity, and central obesity were highly prevalent and significantly associated with elevated TC and all dyslipidaemia subtypes. Older age was associated with elevated TC, elevated LDL-c and elevated non-HDL-c. Hypertension was associated with elevated TC, elevated TG, and elevated non-HDL-c, while diabetes was associated with elevated TG and low HDL-c.

METHODS: We conducted a cross-sectional study involving teachers recruited via multi-stage sampling from the state of Melaka, Malaysia. MONO was defined as individuals with BMI 18.5-29.9 kg/m(2) and metabolic syndrome. Metabolic syndrome was diagnosed based on the Harmonization criteria. Participants completed self-reported questionnaires that assessed alcohol intake, sleep duration, smoking, physical activity, and fruit and vegetable consumption.

RESULTS: A total of 1168 teachers were included in the analysis. The prevalence of MONO was 17.7% (95% confidence interval [CI], 15.3-20.4). Prevalence of metabolic syndrome among the normal weight and overweight participants was 8.3% (95% CI, 5.8-11.8) and 29.9% (95% CI, 26.3-33.7), respectively. MONO prevalence was higher among males, Indians, and older participants and inversely associated with sleep duration. Metabolic syndrome was also more prevalent among those with central obesity, regardless of whether they were normal or overweight. The odds of metabolic syndrome increased exponentially from 1.9 (for those with BMI 23.0-24.9 kg/m(2)) to 11.5 (for those with BMI 27.5-29.9 kg/m(2)) compared to those with BMI 18.5-22.9 kg/m(2) after adjustment for confounders.

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).