983 resultados para predicted glycemic index
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Background Type 2 diabetes mellitus (T2DM) is a common disease with numerous complications. Bariatric surgery is an efficient procedure for controlling T2DM in morbidly obese patients. In T2DM, the incretin effect is either greatly impaired or absent. This study aimed to evaluate the preliminary results from interposing a segment of ileum into the proximal jejunum associated with a sleeve or diverted sleeve gastrectomy to control T2DM in patients with a body mass index (BMI) less than 35 kg/m(2). Methods For this study, 39 patients (16 women and 23 men) underwent two laparoscopic procedures comprising different combinations of ileal interposition into the proximal jejunum via a sleeve or diverted sleeve gastrectomy. The mean age of these patients was 50.3 years (range, 36-66 years). The mean BMI was 30.1 kg/m(2) (range, 23.4-34.9 kg/m(2)). All the patients had a diagnosis of T2DM that had persisted for at least 3 years and evidence of stable treatment with oral hypoglycemic agents or insulin for at least 12 months. The mean duration of T2DM was 9.3 years (range, 3-22 years). Results The mean operative time was 185 min, and the median hospital stay was 4.3 days. Four major complications occurred in the short term (30-days), and the mortality rate was 2.6%. The mean postoperative follow-up period was 7 months (range, 4-16 months), and the mean percentage of weight loss was 22%. The mean postoperative BMI was 24.9 kg/m(2) (range, 18.9-31.7 kg/m2). An adequate glycemic control was achieved for 86.9% of the patients, and 13.1% had important improvement. The patients whose glycemia was not normalized were using a single oral hypoglycemic agent. No patient needed insulin therapy postoperatively. All the patients except experienced normalization of their cholesterol levels. Targeted triglycerides levels were achieved by 71% of the patients, and hypertension was controlled for 95.8%. Conclusions The laparoscopic ileal interposition via either a sleeve gastrectomy or diverted sleeve gastrectomy seems to be a promising procedure for the control of T2DM and the metabolic syndrome. A longer follow-up period is needed.
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BACKGROUND: Alcoholic beverages may have protective cardiovascular effects but are known to increase the plasma levels of triglycerides (TG). Both TG and the ratio of TO to high-density lipoprotein cholesterol (TG/HDL-cholesterol) are associated with increased cardiovascular risk. OBJECTIVES: To determine the predictive factors for variations in plasma levels of TO and the TG/HDL-cholesterol ratio in patients after they had consumed red wine for 14 days. METHODS: Forty-two subjects (64% men, 46 +/- 9 years, baseline body mass index [BMI] 25.13 +/- 2.76 kg/m(2)) were given red wine (12% or 12.2% alc/vol, 250 mL/day with meals). Plasma concentration of lipids and glucose were measured before and after red wine consumption. Blood was collected after 12 hours of fast and alcohol abstention. RESULTS: Red wine increased plasma levels of TO from 105 +/- 42 mg/dL to 120 +/- 56 mg/dL (P = .001) and the TG/HDL-cholesterol ratio from 2.16 +/- 1.10 to 2.50 +/- 1.66 (P = .014). In a multivariate linear regression model that included age, baseline BMI, blood pressure, lipids, and glucose, only BMI was independently predictive of the variation in plasma TO after red wine (beta coefficient 0.592, P < .001). BMI also predicted the variation in TG/HDL-cholesterol ratio (beta coefficient 0.505, P = .001, adjusted model). When individuals were divided into three categories, according to their BMI, the average percentage variation in TG after red wine was -4%, 17%, and 33% in the lower (19.60-24.45 kg/m(2)), intermediate, and greater (26.30-30.44 kg/m(2)) tertiles, respectively (P = .001). CONCLUSIONS: Individuals with higher BMI, although nonobese, might be at greater risk for elevation in plasma TO levels and the TG/HDL-cholesterol ratio after short-term red wine consumption. (C) 2011 National Lipid Association. All rights reserved.
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The risk of developing cardiovascular disease is higher in obese than in non-obese individuals. Surgery for obesity is effective in reducing weight and resolution of diabetes, hypertension, and dyslipidemia. Our aim was to assess the estimated 10-year cardiovascular risk of obese patients before and after treatment of obesity with a gastric bypass. Weight, body mass index systolic and diastolic blood pressure, lipid profile, glycemia, and history of cardiovascular disease were obtained for obese patients before and 2 years after Roux-en-Y gastric bypass surgery. Ten-year cardiovascular risk was calculated using the Framingham score. Forty-two patients were included in the study. We observed a significant reduction (p < 0.05) of 10-year cardiovascular risk mainly associated with weight reduction and improvement of comorbidities associated with obesity. The benefits were greater among patients who already presented known risk factors such as diabetes and hypertension. Superobese patients benefited as early as 2 years after surgery, when weight loss was greater. Weight loss secondary to surgery was sustained after 2 years and promoted improvement of comorbidities, with an important reduction of 10-year cardiovascular risk especially among patients with previous risk factors.
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The disposition kinetics of six cationic drugs in perfused diseased and normal rat livers were determined by multiple indicator dilution and related to the drug physicochemical properties and liver histopathology. A carbon tetrachloride (CCl4)induced acute hepatocellular injury model had a higher fibrosis index (FI), determined by computer-assisted image analysis, than did an alcohol-induced chronic hepatocellular injury model. The alcohol-treated group had the highest hepatic alpha(1)- acid glycoprotein, microsomal protein (MP), and cytochrome P450 (P450) concentrations. Various pharmacokinetic parameters could be related to the octanol-water partition coefficient (log P-app) of the drug as a surrogate for plasma membrane partition coefficient and affinity for MP or P450, the dependence being lower in the CCl4-treated group and higher in the alcohol-treated group relative to controls. Stepwise regression analysis showed that hepatic extraction ratio, permeability-surface area product, tissue-binding constant, intrinsic clearance, partition ratio of influx (k(in)) and efflux rate constant (k(out)), and k(in)/k(out) were related to physicochemical properties of drug (log P-app or pK(a)) and liver histopathology (FI, MP, or P450). In addition, hepatocyte organelle ion trapping of cationic drugs was evident in all groups. It is concluded that fibrosis-inducing hepatic disease effects on cationic drug disposition in the liver may be predicted from drug properties and liver histopathology.
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OBJECTIVE: To determine the best cut-offs of body mass index for identifying alterations of blood lipids and glucose in adolescents. METHODS: A probabilistic sample including 577 adolescent students aged 12-19 years in 2003 (210 males and 367 females) from state public schools in the city of Niterói, Southeastern Brazil, was studied. The Receiver Operating Characteristic curve was used to identify the best age-adjusted BMI cut-off for predicting high levels of serum total cholesterol (>150mg/dL), LDL-C (>100mg/dL), serum triglycerides (>100mg/dL), plasma glucose (>100mg/dL) and low levels of HDL-C (< 45mg/dL). Four references were used to calculate sensitivity and specificity of BMI cut-offs: one Brazilian, one international and two American. RESULTS: The most prevalent metabolic alterations (>50%) were: high total cholesterol and low HDL-C. BMI predicted high levels of triglycerides in males, high LDL-C in females, and high total cholesterol and the occurrence of three or more metabolic alterations in both males and females (areas under the curve range: 0.59 to 0.67), with low sensitivity (57%-66%) and low specificity (58%-66%). The best BMI cut-offs for this sample (20.3 kg/m² to 21.0 kg/m²) were lower than those proposed in the references studied. CONCLUSIONS: Although BMI values lower than the International cut-offs were better predictor of some metabolic abnormalities in Brazilian adolescents, overall BMI is not a good predictor of these abnormalities in this population.
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Species distribution modeling has relevant implications for the studies of biodiversity, decision making about conservation and knowledge about ecological requirements of the species. The aim of this study was to evaluate if the use of forest inventories can improve the estimation of occurrence probability, identify the limits of the potential distribution and habitat preference of a group of timber tree species. The environmental predictor variables were: elevation, slope, aspect, normalized difference vegetation index (NDVI) and height above the nearest drainage (HAND). To estimate the distribution of species we used the maximum entropy method (Maxent). In comparison with a random distribution, using topographic variables and vegetation index as features, the Maxent method predicted with an average accuracy of 86% the geographical distribution of studied species. The altitude and NDVI were the most important variables. There were limitations to the interpolation of the models for non-sampled locations and that are outside of the elevation gradient associated with the occurrence data in approximately 7% of the basin area. Ceiba pentandra (samaúma), Castilla ulei (caucho) and Hura crepitans (assacu) is more likely to occur in nearby water course areas. Clarisia racemosa (guariúba), Amburana acreana (cerejeira), Aspidosperma macrocarpon (pereiro), Apuleia leiocarpa (cumaru cetim), Aspidosperma parvifolium (amarelão) and Astronium lecointei (aroeira) can also occur in upland forest and well drained soils. This modeling approach has potential for application on other tropical species still less studied, especially those that are under pressure from logging.
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Energy expenditure was measured by means of a respiratory chamber in two groups of adult rural Gambian men. The first group (n = 29) had a low body mass index (BMI; in kg/m2) < 18.5), whereas the control group (n = 29) had a higher BMI (> 22). This study shows that the energy expenditure of Gambian men with low BMI is not different from that of Gambian men with normal BMI when the results are normalized for fat-free mass or for weight by analysis of covariance. In Gambian men the nutritional status thus does not seem to affect energy metabolism notably. No differences in respiratory quotient, diet-induced thermogenesis, net work efficiency, spontaneous physical activity, heart rate, or urinary catecholamine excretion were observed between the two groups. It is, however, interesting to note that the basal metabolic rate of Gambian men, regardless of their nutritional status, is approximately 10% (range 4-12% depending on the reference value used) lower than that predicted for individuals living in industrialized countries.
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OBJECTIVE: Low and high body mass index (BMI) values have been shown to increase health risks and mortality and result in variations in fat-free mass (FFM) and body fat mass (BF). Currently, there are no published ranges for a fat-free mass index (FFMI; kg/m(2)), a body fat mass index (BFMI; kg/m(2)), and percentage of body fat (%BF). The purpose of this population study was to determine predicted FFMI and BFMI values in subjects with low, normal, overweight, and obese BMI. METHODS: FFM and BF were determined in 2986 healthy white men and 2649 white women, age 15 to 98 y, by a previously validated 50-kHz bioelectrical impedance analysis equation. FFMI, BFMI, and %BF were calculated. RESULTS: FFMI values were 16.7 to 19.8 kg/m(2) for men and 14.6 to 16.8 kg/m(2) for women within the normal BMI ranges. BFMI values were 1.8 to 5.2 kg/m(2) for men and 3.9 to 8.2 kg/m(2) for women within the normal BMI ranges. BFMI values were 8.3 and 11.8 kg/m(2) in men and women, respectively, for obese BMI (>30 kg/m(2)). Normal ranges for %BF were 13.4 to 21.7 and 24.6 to 33.2 for men and women, respectively. CONCLUSION: BMI alone cannot provide information about the respective contribution of FFM or fat mass to body weight. This study presents FFMI and BFMI values that correspond to low, normal, overweight, and obese BMIs. FFMI and BFMI provide information about body compartments, regardless of height.
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OBJECTIVES: The validity of equations for the calculation of resting metabolic rate (RMR) were studied and new predictive equations were developed. STUDY DESIGN: The RMR was measured in a sample of 371 10- to 16-year-old prepubertal and postpubertal children. The study group included 193 male (116 nonobese and 77 obese) and 178 female (119 nonobese and 59 obese) subjects; for each group the RMRs predicted from five equations recommended for this age group were compared. The RMR was assessed by indirect calorimetry with a ventilated hood system for 45 minutes after an overnight fast. Body composition was estimated from skin-fold measurements. RESULTS: The mean +/- SD RMR was found to be 5600 +/- 972 kJ/24 hr and 7223 +/- 1220 kJ/24 hr in nonobese and obese boys, and 5112 +/- 632 kJ/24 hr and 6665 +/- 1106 kJ/24 hr in nonobese and obese girls, respectively. All five equations applicable to 10- to 16-year-old children overestimated RMR by 7.5% to 18.1% (p < 0.001 for each equation). Stepwise regression analysis, with independent variables such as age, weight, height, and gender, allowed development of new predictive equations for the calculation of RMR in 10- to 16-year-old boys (RMR = 50.9 Weight (kg) + 25.3 Height (cm) -50.3 Age (yr) + 26.9; R2 = 0.884, p < 0.0001) and girls (RMR = 51.2 Weight (kg) + 24.5 Height (cm) - 207.5 Age (yr) + 1629.8; R2 = 0.824, p < 0.0001). These predictive equations were tested in a second, independent cohort of children (80 male and 61 female subject) and were found to give a reliable estimate of RMR in 10- to 16-year-old obese and nonobese adolescents. CONCLUSIONS: The currently used predictive equations overestimate RMR in 10- to 16-year-old children. The use of the newly developed equations is recommended.
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BACKGROUND: Studies about the association between body mass index (BMI) and health-related quality of life (HRQOL) are often limited, because they 1) did not include a broad range of health-risk behaviors as covariates; 2) relied on clinical samples, which might lead to biased results; and 3) did not incorporate underweight individuals. Hence, this study aims to examine associations between BMI (from being underweight through obesity) and HRQOL in a population-based sample, while considering multiple health-risk behaviors (low physical activity, risky alcohol consumption, daily cigarette smoking, frequent cannabis use) as well as socio-demographic characteristics. METHODS: A total of 5 387 young Swiss men (mean age = 19.99; standard deviation = 1.24) of a cross-sectional population-based study were included. BMI was calculated (kg/m²) based on self-reported height and weight and divided into 'underweight' (<18.5), 'normal weight' (18.5-24.9), 'overweight' (25.0-29.9) and 'obese' (≥30.0). Mental and physical HRQOL was assessed via the SF-12v2. Self-reported information on physical activity, substance use (alcohol, cigarettes, and cannabis) and socio-demographic characteristics also was collected. Logistic regression analyses were conducted to study the associations between BMI categories and below average mental or physical HRQOL. Substance use variables and socio-demographic variables were used as covariates. RESULTS: Altogether, 76.3% were normal weight, whereas 3.3% were underweight, 16.5% overweight and 3.9% obese. Being overweight or obese was associated with reduced physical HRQOL (adjusted OR [95% CI] = 1.58 [1.18-2.13] and 2.45 [1.57-3.83], respectively), whereas being underweight predicted reduced mental HRQOL (adjusted OR [95% CI] = 1.49 [1.08-2.05]). Surprisingly, obesity decreased the likelihood of experiencing below average mental HRQOL (adjusted OR [95% CI] = 0.66 [0.46-0.94]). Besides BMI, expressed as a categorical variable, all health-risk behaviors and socio-demographic variables were associated with reduced physical and/or mental HRQOL. CONCLUSIONS: Deviations from normal weight are, even after controlling for important health-risk behaviors and socio-demographic characteristics, associated with compromised physical or mental HRQOL among young men. Hence, preventive programs should aim to preserve or re-establish normal weight. The self-appraised positive mental well-being of obese men noted here, which possibly reflects a response shift, might complicate such efforts.
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BACKGROUND: Knowledge of normal heart weight ranges is important information for pathologists. Comparing the measured heart weight to reference values is one of the key elements used to determine if the heart is pathological, as heart weight increases in many cardiac pathologies. The current reference tables are old and in need of an update. AIMS: The purposes of this study are to establish new reference tables for normal heart weights in the local population and to determine the best predictive factor for normal heart weight. We also aim to provide technical support to calculate the predictive normal heart weight. METHODS: The reference values are based on retrospective analysis of adult Caucasian autopsy cases without any obvious pathology that were collected at the University Centre of Legal Medicine in Lausanne from 2007 to 2011. We selected 288 cases. The mean age was 39.2 years. There were 118 men and 170 women. Regression analyses were performed to assess the relationship of heart weight to body weight, body height, body mass index (BMI) and body surface area (BSA). RESULTS: The heart weight increased along with an increase in all the parameters studied. The mean heart weight was greater in men than in women at a similar body weight. BSA was determined to be the best predictor for normal heart weight. New reference tables for predicted heart weights are presented as a web application that enable the comparison of heart weights observed at autopsy with the reference values. CONCLUSIONS: The reference tables for heart weight and other organs should be systematically updated and adapted for the local population. Web access and smartphone applications for the predicted heart weight represent important investigational tools.
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OBJECTIVES: To analyze the effect of tight glycemic control with the use of intensive insulin therapy on cerebral glucose metabolism in patients with severe brain injury. DESIGN: Retrospective analysis of a prospective observational cohort. SETTING: University hospital neurologic intensive care unit. PATIENTS: Twenty patients (median age 59 yrs) monitored with cerebral microdialysis as part of their clinical care. INTERVENTIONS: Intensive insulin therapy (systemic glucose target: 4.4-6.7 mmol/L [80-120 mg/dL]). MEASUREMENTS AND MAIN RESULTS: Brain tissue markers of glucose metabolism (cerebral microdialysis glucose and lactate/pyruvate ratio) and systemic glucose were collected hourly. Systemic glucose levels were categorized as within the target "tight" (4.4-6.7 mmol/L [80-120 mg/dL]) vs. "intermediate" (6.8-10.0 mmol/L [121-180 mg/dL]) range. Brain energy crisis was defined as a cerebral microdialysis glucose <0.7 mmol/L with a lactate/pyruvate ratio >40. We analyzed 2131 cerebral microdialysis samples: tight systemic glucose levels were associated with a greater prevalence of low cerebral microdialysis glucose (65% vs. 36%, p < 0.01) and brain energy crisis (25% vs.17%, p < 0.01) than intermediate levels. Using multivariable analysis, and adjusting for intracranial pressure and cerebral perfusion pressure, systemic glucose concentration (adjusted odds ratio 1.23, 95% confidence interval [CI] 1.10-1.37, for each 1 mmol/L decrease, p < 0.001) and insulin dose (adjusted odds ratio 1.10, 95% CI 1.04-1.17, for each 1 U/hr increase, p = 0.02) independently predicted brain energy crisis. Cerebral microdialysis glucose was lower in nonsurvivors than in survivors (0.46 +/- 0.23 vs. 1.04 +/- 0.56 mmol/L, p < 0.05). Brain energy crisis was associated with increased mortality at hospital discharge (adjusted odds ratio 7.36, 95% CI 1.37-39.51, p = 0.02). CONCLUSIONS: In patients with severe brain injury, tight systemic glucose control is associated with reduced cerebral extracellular glucose availability and increased prevalence of brain energy crisis, which in turn correlates with increased mortality. Intensive insulin therapy may impair cerebral glucose metabolism after severe brain injury.
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Introduction: Diffuse large B-cell lymphomas (DLBCL) represent a heterogeneous disease with variable clinical outcome. Identifying phenotypic biomarkers of tumor cells on paraffin sections that predict different clinical outcome remain an important goal that may also help to better understand the biology of this lymphoma. Differentiating non-germinal centre B-cell-like (non-GCB) from Germinal Centre B-cell-like (GCB) DLBCL according to Hans algorithm has been considered as an important immunohistochemical biomarker with prognostic value among patients treated with R-CHOP although not reproducibly found by all groups. Gene expression studies have also shown that IgM expression might be used as a surrogate for the GCB and ABC subtypes with a strong preferential expression of IgM in ABC DLBCL subtype. ImmunoFISH index based on the differential expression of MUM-1, FOXP1 by immunohistochemistry and on the BCL6 rearrangement by FISH has been previously reported (C Copie-Bergman, J Clin Oncol. 2009;27:5573-9) as prognostic in an homogeneous series of DLBCL treated with R-CHOP. In addition, oncogenic MYC protein overexpression by immunohistochemistry may represent an easy tool to identify the consequences of MYC deregulation in DLBCL. Our aim was to analyse by immunohistochemistry the prognostic relevance of MYC, IgM, GCB/nonGCB subtype and ImmunoFISH index in a large series of de novo DLBCL treated with Rituximab (R)-chemotherapy (anthracyclin based) included in the 2003 program of the Groupe d'Etude des Lymphomes de l'Adulte (GELA) trials. Methods: The 2003 program included patients with de novo CD20+ DLBCL enrolled in 6 different LNH-03 GELA trials (LNH-03-1B, -B, -3B, 39B, -6B, 7B) stratifying patients according to age and age-adjusted IPI. Tumor samples were analyzed by immunohistochemistry using CD10, BCL6, MUM1, FOXP1 (according to Barrans threshold), MYC, IgM antibodies on tissue microarrays and by FISH using BCL6 split signal DNA probes. Considering evaluable Hans score, 670 patients were included in the study with 237 (35.4%) receiving intensive R-ACVBP regimen and 433 (64.6%) R-CHOP/R-mini-CHOP. Results: 304 (45.4%) DLBCL were classified as GCB and 366 (54.6%) as non-GCB according to Hans algorithm. 337/567 cases (59.4%) were positive for the ImmunoFISH index (i.e. two out of the three markers positive: MUM1 protein positive, FOXP1 protein Variable or Strong, BCL6 rearrangement). Immunofish index was preferentially positive in the non-GCB subtype (81.3%) compared to the GCB subtype (31.2%), (p<0.001). IgM was recorded as positive in tumor cells in 351/637 (52.4%) DLBCL cases with a preferential expression in non-GCB 195 (53.3%) vs GCB subtype 100(32.9%), p<0.001). MYC was positive in 170/577 (29.5%) cases with a 40% cut-off and in 44/577 (14.2%) cases with a cut-off of 70%. There was no preferential expression of MYC among GCB or non-GCB subtype (p>0.4) for both cut-offs. Progression-free Survival (PFS) was significantly worse among patients with high IPI score (p<0.0001), IgM positive tumor (p<0.0001), MYC positive tumor with a 40% threshold (p<0.001), ImmunoFISH positive index (p<0.002), non-GCB DLBCL subtype (p<0.0001). Overall Survival (OS) was also significantly worse among patients with high IPI score (p<0.0001), IgM positive tumor (p=0.02), MYC positive tumor with a 40% threshold (p<0.01), ImmunoFISH positive index (p=0.02), non-GCB DLBCL subtype (p<0.0001). All significant parameters were included in a multivariate analysis using Cox Model and in addition to IPI, only the GCB/non-GCB subtype according to Hans algorithm predicted significantly a worse PFS among non-GCB subgroup (HR 1.9 [1.3-2.8] p=0.002) as well as a worse OS (HR 2.0 [1.3-3.2], p=0.003). This strong prognostic value of non-GCB subtyping was confirmed considering only patients treated with R- CHOP for PFS (HR 2.1 [1.4-3.3], p=0.001) and for OS (HR 2.3 [1.3-3.8], p=0.002). Conclusion: Our study on a large series of patients included in trials confirmed the relevance of immunohistochemistry as a useful tool to identify significant prognostic biomarkers for clinical use. We show here that IgM and MYC might be useful prognostic biomarkers. In addition, we confirmed in this series the prognostic value of the ImmunoFISH index. Above all, we fully validated the strong and independent prognostic value of the Hans algorithm, daily used by the pathologists to subtype DLBCL.
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BACKGROUND: Knowledge of normal heart weight ranges is important information for pathologists. Comparing the measured heart weight to reference values is one of the key elements used to determine if the heart is pathological, as heart weight increases in many cardiac pathologies. The current reference tables are old and in need of an update. AIMS: The purposes of this study are to establish new reference tables for normal heart weights in the local population and to determine the best predictive factor for normal heart weight. We also aim to provide technical support to calculate the predictive normal heart weight. METHODS: The reference values are based on retrospective analysis of adult Caucasian autopsy cases without any obvious pathology that were collected at the University Centre of Legal Medicine in Lausanne from 2007 to 2011. We selected 288 cases. The mean age was 39.2 years. There were 118 men and 170 women. Regression analyses were performed to assess the relationship of heart weight to body weight, body height, body mass index (BMI) and body surface area (BSA). RESULTS: The heart weight increased along with an increase in all the parameters studied. The mean heart weight was greater in men than in women at a similar body weight. BSA was determined to be the best predictor for normal heart weight. New reference tables for predicted heart weights are presented as a web application that enable the comparison of heart weights observed at autopsy with the reference values. CONCLUSIONS: The reference tables for heart weight and other organs should be systematically updated and adapted for the local population. Web access and smartphone applications for the predicted heart weight represent important investigational tools.
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We assessed the association between several cardiometabolic risk factors (CRFs) (blood pressure, LDL-cholesterol, HDL-cholesterol, triglycerides, uric acid, and glucose) in 390 young adults aged 19-20 years in Seychelles (Indian Ocean, Africa) and body mass index (BMI) measured either at the same time (cross-sectional analysis) or at the age of 12-15 years (longitudinal analysis). BMI tracked markedly between age of 12-15 and age of 19-20. BMI was strongly associated with all considered CRFs in both cross-sectional and longitudinal analyses, with some exceptions. Comparing overweight participants with those having a BMI below the age-specific median, the odds ratios for high blood pressure were 5.4/4.7 (male/female) cross-sectionally and 2.5/3.9 longitudinally (P < 0.05). Significant associations were also found for most other CRFs, with some exceptions. In linear regression analysis including both BMI at age of 12-15 and BMI at age of 19-20, only BMI at age of 19-20 remained significantly associated with most CRFs. We conclude that CRFs are predicted strongly by either current or past BMI levels in adolescents and young adults in this population. The observation that only current BMI remained associated with CRFs when including past and current levels together suggests that weight control at a later age may be effective in reducing CRFs in overweight children irrespective of past weight status.