Combination Of Body Mass Index Research Articles

Overweight Is an Independent Risk Factor for Reduced Lung Volumes in Myotonic Dystrophy Type 1.

BackgroundIn this large observational study population of 105 myotonic dystrophy type 1 (DM1) patients, we investigate whether bodyweight is a contributor of total lung capacity (TLC) independent of the impaired inspiratory muscle strength.MethodsBody composition was assessed using the combination of body mass index (BMI) and fat-free mass index. Pulmonary function tests and respiratory muscle strength measurements were performed on the same day. Patients were stratified into normal (BMI < 25 kg/m2) and overweight (BMI ≥ 25 kg/m2) groups. Multiple linear regression was used to find significant contributors for TLC.ResultsOverweight was present in 59% of patients, and body composition was abnormal in almost all patients. In overweight patients, TLC was significantly (p = 2.40×10−3) decreased, compared with normal-weight patients, while inspiratory muscle strength was similar in both groups. The decrease in TLC in overweight patients was mainly due to a decrease in expiratory reserve volume (ERV) further illustrated by a highly significant (p = 1.33×10−10) correlation between BMI and ERV. Multiple linear regression showed that TLC can be predicted using only BMI and the forced inspiratory volume in 1 second, as these were the only significant contributors.ConclusionsThis study shows that, in DM1 patients, overweight further reduces lung volumes, as does impaired inspiratory muscle strength. Additionally, body composition is abnormal in almost all DM1 patients.

Quantifying the proportion of deaths due to body mass index- and waist circumference-defined obesity.

To determine the risk of mortality associated with and quantify the deaths attributable to combinations of body mass index (BMI) and waist circumference (WC). This study included 41,439 participants. For the hazard ratio (HR) calculation, adiposity categories were defined as: BMI(N) /WC(N) , BMI(N) /WC(O) , BMI(O) /WC(N) , and BMI(O) /WC(O) (N = non-obese, O = obese). For the population attributable fraction analysis, obesity was classified as: (i) obese by BMI and/or WC; (ii) obese by BMI; and (iii) obese by WC. Mortality data was complete to the end of 2012. The prevalence of BMI(N) /WC(N) , BMI(N) /WC(O) , BMI(O) /WC(N) , and BMI(O) /WC(O) was 73%, 6%, 6%, and 15%, respectively. There was an increased risk of all-cause and cardiovascular disease (CVD) mortality in those with BMI(N) /WC(O) (HR (95% CI) 1.2 (1.2, 1.3) and 1.3 (1.1, 1.6)) and BMI(O) /WC(O) (1.3 (1.3, 1.4) and 1.7 (1.5, 1.9)) compared to those with BMI(N) /WC(N) . The estimated proportion of all-cause and CVD mortality attributable to obesity defined using WC or using BMI and/or WC was higher compared to obesity defined using BMI. Current population obesity monitoring misses those with BMI(N) /WC(O) who are at increased risk of mortality. By targeting reductions in population WC, the potential exists to prevent more deaths in the population than if we continue to target reductions in BMI alone.

Body Mass Index, Left Ventricular Mass Index and Cardiovascular Events in Chronic Kidney Disease

BackgroundObesity and left ventricular hypertrophy are prevalent in chronic kidney disease (CKD), but the association of body mass index (BMI) and left ventricular mass index (LVMI) with cardiovascular outcomes in patients with CKD is unclear. This study was designed to assess whether the combination of BMI and LVMI is independently associated with cardiovascular events in patients with CKD stages 3-5. MethodsFrom the outpatient department, 523 patients with CKD who received echocardiographic examination were enrolled. The patients under study were classified into 4 groups according to sex-specific median BMIs and LVMIs. Cardiovascular events were defined as cardiovascular death, hospitalization for unstable angina, nonfatal myocardial infarction, sustained ventricular arrhythmia, hospitalization for congestive heart failure, transient ischemia attack and stroke. The relative cardiovascular event risk was analyzed using Cox-regression methods. ResultsThe patients were stratified into 4 groups according to sex-specific median BMIs (men: 25.2kg/m2; women: 24.9kg/m2) and LVMIs (men: 140.1g/m2; women: 131.6g/m2). A combination of low BMI and high LVMI (versus the combination of high BMI and low LVMI) was significantly associated with cardiovascular events in an unadjusted model (hazard ratio [HR] = 3.178; 95% confidence interval [CI]: 1.645-6.140; P < 0.001) and in a multivariable model after adjustment for demographic, clinical and biochemical characteristics and medications (HR = 3.553; 95% CI: 1.494-8.450; P = 0.004). ConclusionsThe findings showed that the combination of low BMI and high LVMI was associated with adverse cardiovascular events in patients with CKD stages 3–5.

Addition of Cardiorespiratory Fitness Within an Obesity Risk Classification Model Identifies Men at Increased Risk of All-Cause Mortality

ObjectiveGuidelines for identification of obesity-related risk which stratify disease risk using specific combinations of body mass index and waist circumference. Whether the addition of cardiorespiratory fitness, an independent predictor of disease risk, provides better risk prediction of all-cause mortality within current body mass index and waist circumference categories is unknown. The study objective was to determine whether the addition of cardiorespiratory fitness improves prediction of all-cause mortality risk classified by the combination of body mass index and waist circumference. MethodsWe performed a prospective observational study using data from the Aerobics Center Longitudinal Study. A total of 31,267 men (mean age, 43.9 years; standard deviation, 9.4 years) who completed a baseline medical examination between 1974 and 2002 were included. The main outcome measure was all-cause mortality. Participants were grouped using body mass index– and waist circumference–specific threshold combinations: normal body mass index: 18.5 to 24.9 kg/m2, waist circumference threshold of 90 cm; overweight body mass index: 25.0 to 29.9 kg/m2, waist circumference threshold of 100 cm, and obese body mass index: 30.0 to 34.9 kg/m2, waist circumference threshold of 110 cm. Participants were classified using cardiorespiratory fitness as unfit or fit, where unfit was the lowest fifth of the age-specified distribution of maximal exercise test time on the treadmill among the entire Aerobics Center Longitudinal Study population. ResultsA total of 1399 deaths occurred over a follow-up of 14.1 ± 7.4 years, for a total of 439,991 person-years of observation. Men who were unfit and had normal body mass index with waist circumference <90 cm and ≥90 cm had 95% (hazard ratio [HR], 1.95; 95% confidence interval [CI], 1.34-2.83) and 163% (HR, 2.63; 95% CI, 1.58-4.40) higher mortality risk than men who were fit, respectively (P <.05). Men who were unfit and overweight had 41% (HR, 1.41; 95% CI, 1.04-1.90) higher mortality risk with a waist circumference <100 cm (P <.05), but were at no greater risk (HR, 1.30; 95% CI, 0.92-1.84) if their waist circumference was ≥100 cm (P = .14). Men who were unfit and obese were not at increased mortality risk (HR, 1.37; 95% CI, 0.90-2.09) with a waist circumference <110 cm (P = .14), but were at 111% (HR, 2.11; 95% CI, 1.31-3.42) increased risk with a waist circumference ≥110 cm (P <.05). ConclusionsFor most of the body mass index and waist circumference categories, inclusion of cardiorespiratory fitness allowed for improved identification of men at increased mortality risk.

Abstract 12188: Combined Effect of BMI and Renal Function on Long-term Clinical Outcomes in the Elderly Following Percutaneous Coronary Intervention

Introduction: Accompanied by aging society, percutaneous coronary intervention (PCI) has been widely performed in the elderly for the past few decades. However, a paucity of data examining clinical features and outcomes is available. Previously, low body mass index (BMI) and renal insufficiency were demonstrated to be negative predictors in patients with coronary artery disease. However, the effect of BMI and renal insufficiency on clinical outcome in elderly following PCI was not fully examined. Methods: We analyzed data of patients with the age of 70 to 85 following PCI in Juntendo University (Tokyo, Japan) from 1985 to 2010. Cox regression analysis was performed to assess an effect of combination with BMI less than 22 and eGFR less than 60 on all-cause mortality that was evaluated at 3-year after the index PCI. Results: Of 3824 patients, 1019 patients with the age of between 70 and 85 were examined. Mean age, BMI and eGFR were 75.2, 23.3 and 59.6, respectively. The population was divided into 3 groups according to the value of BMI and eGFR (BMI &lt; 22 and eGFR &lt; 60; high risk, BMI &lt; 22 or eGFR &lt; 60; intermediate risk, BMI ≥ 22 and eGFR ≥ 60; low risk). The higher incidence of all-cause mortality was observed in accordance with the greater risk determined by BMI and eGFR (P for trend &lt; 0.0001) (Figure 1). Kaplan-Meier estimation for all-cause mortality was significantly different between the three groups (Figure 2). In multivariable Cox regression analysis including traditional coronary risk factors, combined effect of BMI and eGFR was associated with all-cause mortality. Conclusions: Combination of BMI and eGFR was independently associated with all-cause mortality in the elderly following PCI.

Relationships between Body Image, Body Mass Index, and Smoking in Korean Adolescents: Results of a Nationwide Korea Youth Risk Behavior Web-based Survey.

This study assessed the association between subjective body image or objective body mass index (BMI) and the risk of daily smoking in Korean adolescents, with a purpose of identifying the most suitable models. Using the 2013 9th Korea Youth Risk Behavior Web-based Survey data for 72,435 students, odds ratios were calculated for daily smoking in the past month, according to the subjective body image and calculated BMI using a respective multiple logistic regression model. The combined effect of these two factors was also analyzed by pairing a BMI category with a subjective body image category, using odds ratios for the same event within each sex group. Among the surveyed students, 7.2% of boys and 1.8% of girls were classified as daily smokers. Students who perceived themselves as being very obese tended to be at lower risk of daily smoking (OR=0.61 in boys with 95% CI=0.47 to 0.79; OR=0.66 in women with 95% CI=0.47 to 0.93). In addition, boys within the obese or overweight BMI category showed a lower risk of daily smoking (OR=0.86, 95% CI: 0.77-0.96). Lean BMI was significantly associated with higher odds ratios for daily smoking only in female students (OR=1.24, 95% CI: 1.02-1.52). When pairing these two objective and subjective factors, results suggested that subjective body image has a greater effect on daily smoking than BMI in both boys and girls. In both male and female students, subjective body image had a greater effect on daily smoking than body mass index. A model using the combination of BMI and subjective body image was the best fit in girls, in contrast to the model using subjective body image only best suitable in boys, for the prediction of daily smoking. These results including several factors associated with daily smoking in Korean students, provide useful data for the development and implementation of smoking intervention and cessation programs for adolescents.

Normal weight adiposity in a Swedish population: how well is cardiovascular risk associated with excess body fat captured by BMI?

SummaryObjectiveThe aim of this study was to examine how well body mass index (BMI) reflects cardiovascular risk associated with excess adiposity in a Swedish population by examining the association between body fat, BMI and cardiovascular risk factors.MethodsA total of 3,010 adults participated. Normal weight adiposity was defined as the combination of BMI < 25 kg/m2 and percentage body fat ≥35% for women and ≥25% for men. Associations with blood pressure, blood lipids, apolipoproteins and C‐reactive protein were analysed in age‐adjusted regression models.ResultsThe majority of the individuals with overweight and obesity were correctly classified to adiposity, while a wide range of body fat was observed among the normal weight subjects. In total, 9% of the participants were categorised as normal weight with adiposity. Compared with the normal weight leanness group, participants with normal weight adiposity had higher levels of serum triglycerides, low‐density lipoprotein cholesterol, C‐reactive protein, apolipoptotein B and the apolipoprotein B/A‐I ratio. In normal weight men, adiposity was also associated with higher blood pressure and lower high‐density lipoprotein cholesterol.ConclusionsHigher percentage of body fat was associated with less favourable risk factor profile even in subjects who were normal weight. Thus, it might be relevant to screen for metabolic risk factors in the upper end of the normal weight category.

Assessing cardiometabolic risk in middle-aged adults using body mass index and waist-height ratio: are two indices better than one? A cross-sectional study.

BackgroundA novel obesity classification method has been proposed using body mass index (BMI) and waist–height ratio (WHtR) together. However, the utility of this approach is unclear. In this study we compare the metabolic profiles in subjects defined as overweight or obese by both measures. We examine a range of metabolic syndrome features, pro-inflammatory cytokines, acute-phase response proteins, coagulation factors and white blood cell counts to determine whether a combination of both indices more accurately identifies individuals at increased obesity-related cardiometabolic risk.MethodsThis was a cross-sectional study involving a random sample of 1856 men and women aged 46–73 years. Metabolic and anthropometric profiles were assessed. Linear and logistic regression analyses were used to compare lipid, lipoprotein, blood pressure, glycaemic and inflammatory biomarker levels between BMI and WHtR tertiles. Multinomial logistic regression was performed to determine cardiometabolic risk feature associations with BMI and WHtR groupings. Receiver operating characteristic curve analysis was used to evaluate index discriminatory ability.ResultsThe combination of BMI and WHtR tertiles identified consistent metabolic variable differences relative to those characterised on the basis of one index. Similarly, odds ratios of having cardiometabolic risk features were noticeably increased in subjects classified as overweight or obese by both measures when compared to study participants categorised by either BMI or WHtR separately. Significant discriminatory improvement was observed for detecting individual cardiometabolic risk features and adverse biomarker levels. In a fully adjusted model, only individuals within the highest tertile for both indices displayed a significant and positive association with pre-diabetes, OR: 3.4 (95 % CI: 1.9, 6.0), P < 0.001.ConclusionsThese data provide evidence that the use of BMI and WHtR together may improve body fat classification. Risk stratification using a composite index may provide a more accurate method for identifying high and low-risk subjects.

OP01 Assessing cardiometabolic risk in middle-aged adults using body mass index and waist-height ratio – are two indices better than one?

Background A novel obesity classification method has been proposed utilising body mass index (BMI) and waist-height ratio (WHtR) together. However, the utility of this approach is unclear. In this study we compare the metabolic profiles in subjects defined as overweight or obese by both measures. We examine a range of metabolic risk features, pro-inflammatory cytokines, acute-phase response proteins, coagulation factors and white blood cell counts to determine whether a combination of both indices more accurately identifies individuals at increased cardiometabolic risk. Methods This was a cross-sectional study involving a random sample of 2,047 men and women aged 50–69 years. Metabolic and anthropometric profiles were assessed in study participants. Independent t or Mann-Whitney U tests were used to compare lipid, lipoprotein, blood pressure, glycaemic and inflammatory biomarker levels between BMI and WHtR tertiles. Multinomial logistic regression was performed to determine adverse metabolic feature and biomarker associations with BMI and WHtR groupings. Results The combination of BMI and WHtR tertiles identified consistent metabolic variable differences relative to those characterised on the basis of one index. Similarly, odds ratios for cardiometabolic risk factors were noticeably increased in subjects classified by both measures when compared to study participants categorised by either BMI or WHtR separately. In a fully adjusted model, only individuals within the highest percentile for both indices displayed a significant and positive association with pre-diabetes (OR: 3.4, 95% CI: 2.0–6.0, P Conclusion Risk stratification using a composite index may provide a more accurate method for identifying high and low-risk subjects.

Combined effect of body mass index and body size perception on metabolic syndrome in South Korea: results of the fifth Korea National Health and Nutrition Examination Surveys (2010-2012)

BackgroundBody mass index (BMI) has been used as an indirect predictor for the risk of metabolic syndrome. However, there are challenges in evaluating the risk of metabolic syndrome using BMI in certain parts of the world. Therefore, it is worth exploring additional factors that could supplement BMI to predict the risk of metabolic syndrome. In this study, we assessed the combined effect of BMI and perception for predicting metabolic syndrome.MethodsWe used the fifth Korea National Health and Nutrition Examination Surveys (KNHANES V, 2010–12, N = 16,537) in this study. Multivariable logistic regression analysis was performed to examine the association while controlling for potential confounding variables. We also performed an analysis for the combined effect of BMI and perception of body size, and subgroup analysis by age group or moderate physical activity.ResultsData from 16,537 participants were analyzed in this study (males: 6,978, females: 9,559). Among them, metabolic syndrome was diagnosed in 1,252 (17.9 %) males and 2,445 (25.6 %) females, respectively. The combination of BMI and body size perception had a positive relation with the presence of metabolic syndrome. People who perceived themselves to be overweight for their body size had a higher risk for metabolic syndrome even if they have the same BMI.ConclusionOur findings suggest that the combination of body size perception and BMI is useful in predicting the risk of metabolic syndrome. The use of complementary predictors could reduce the risk for inaccurate prediction of metabolic syndrome.

Combination of body mass index and oxidized low density lipoprotein receptor 1 in prognosis prediction of patients with squamous non-small cell lung cancer.

Lung cancer, especially non-small cell lung cancer (NSCLC), represents enormous challenges in continuously achieving treatment improvements. Besides cancer, obesity is becoming ever more prevalent. Obesity is increasingly acknowledged as a major risk factor for several types of common cancers. Significant mechanisms overlap in the pathobiology of obesity and tumorigenesis. One of these mechanisms involves oxidized low density lipoprotein receptor 1 (OLR1), as a link between obesity and cancer. Additionally, body mass index (BMI) has been widely used in exploiting the role of obesity on a series of diseases, including cancer. Significantly, squamous NSCLC revealed to be divergent clinical and molecular phenotypes compared with non-squamous NSCLC. Consequently, OLR1 immunostaining score and BMI were assessed by Fisher's linear discriminant analysis to discriminate if progression-free survival (PFS) would exceed 2 years. In addition, the final model was utilized to calculate the discriminant score in each study participant. Finally, 131 patients with squamous NCSLC were eligible for analysis. And a prediction model was established for PFS based on these 2 markers and validated in a second set of squamous NCSLC patients. The model offers a novel tool for survival prediction and could establish a framework for future individualized therapy for patients with squamous NCSLC.

Impaired phenotype of circulating endothelial microparticles in chronic heart failure patients: Relevance to body mass index

AimsThe objective of the study was to investigate the relationship of circulating endothelial-derived microparticls (EMP) pattern with body mass index (BMI) in CHF patients. MethodsThe study retrospectively evolved 153 patients (86 males) who were underwent multispiral contrast-enhanced computed tomography angiography or conventional angiographic examination of coronary arteries. Flowcytometry analysis for quantifying the number of EMPs was used at baseline. ResultsUsing C-statistics for models with CHF, BMI, and circulating biomarkers (NT-pro-BNP, OPG and adiponectin) as continuous variables we found that adding of BMI to the based model (NYHA class of CHF) improved the relative IDI by 12.5% for increased CD31+/annexin V+ EMPs to CD62E+ EMPs ratio. When we used other model constructed on entering variables IDI appears to be improved up to 5.8% for increased EMPs (available for NT-pro-BNP as continuous variable). Three biomarkers (NYHA class of CHF+NT-pro-BNP+OPG) and four biomarkers (NYHA class of CHF+NT-pro-BNP+OPG+adiponectin) could not significantly improve predictive model based on combination of BMI and NYHA class of CHF for increased CD31+/annexin V+ EMPs to CD62E+ EMPs ratio. ConclusionWe suggested that lower BMI is significant predictor for impaired phenotype of circulating EMPs in CHF patients.

Multiple anthropometric measures in relation to incidence of diabetes: a Swedish population-based cohort study.

Obesity is the major modifiable risk factor for diabetes. This study investigated the incidence of diabetes in relation to multiple anthropometric measures. Body mass index (BMI), waist circumference (WC), waist-height ratio (WHtR), waist-hip ratio (WHR) and body fat percentage (BF %) were measured among 26,604 subjects (aged 45-73 years) without history of diabetes from the Malmö Diet and Cancer cohort. During 14 years of follow-up, 2935 subjects (1519 men, 1416 women) were diagnosed with diabetes. In men, incidence of diabetes was 24.1 and 4.0 per 1000 person-years comparing the fourth vs. first quartile of WHtR. The multivariate adjusted hazard ratios (HR; fourth vs first quartile) were 6.00 [95% confidence interval (CI): 5.02-7.16) for WHtR, 5.95 (CI: 4.96-7.14) for WC, 5.19 (CI: 4.38-6.15) for BMI, 4.71 (CI: 3.96-5.60) for WHR and 3.21 (CI: 2.75-3.76] for BF%. For women, incidence of diabetes was 15.1 and 1.4 per 1000 person-years for fourth vs first quartile of WHtR (HR: 10.19, CI: 8.10-12.82). HR was 9.16 (CI: 7.40-11.33) for WC, 6.42 (CI: 5.27-7.81) for BMI, 6.75 (CI: 5.52-8.25) for WHR and 5.39 (CI: 4.42-6.57) for BF%. Model discrimination was marginally increased when WC, WHtR or WHR was used in combination with BMI. All measures of obesity were associated with substantially increased incidence of diabetes. Abdominal obesity was associated with higher incidence rates in men than in women, but in terms of relative risks the relationships were stronger in women. The combination of BMI and abdominal obesity measures had stronger association with diabetes than BMI alone.

Combined nutritional indicators and associated factors in the Quilombo population (hinterland settlements founded by people of African origin) in southwestern Bahia, Brazil

This study sought to estimate the prevalence of the combination of Body Mass Index (BMI) plus Waist Circumference (WC) and of BMI plus Waist to Height Ratio (WHR) and to investigate associated factors. A two-stage random sample of adults (>20 years) living in former African slaves communities (Quilombos) was taken in Vitória da Conquista in the State of Bahia in 2011. Combined BMI+WHR nutritional risk was defined by the simultaneous presence of BMI > 25.0Kg/m2 or > 27.0Kg/m2, if aged > 60 years and WHR > 0.5. BMI + WC nutritional risk was defined by elevated BMI in addition to WC > 80cm for women, or > 94cm for men. Among the 739 participants, the prevalence of combined nutritional indicators were 35.3% (BMI + WHR) and 26.8% (BMI + WC). Female sex and hypertension increased the chances of a combination of both indicators, while being unmarried decreased the chances. The prevalence of BMI + WHR was higher in the 40-59 year age range and the prevalence of BMI + WC was higher in the 40-49 year age range. Less schooling increased the chances of the combined BMI + WHR indicator and watching television for more than two hours/day increased the chances of the BMI + WC indicator. The high prevalence of combined nutritional indicators indicate the need of diet promotion actions to prevent obesity.

Physical activity, obesity and risk of cardiovascular disease in middle-aged men during a median of 30 years of follow-up.

We aimed to investigate associations between combinations of body mass index (BMI)-categories, levels of physical activity and long-term risk of cardiovascular disease. At age 50 years, cardiovascular risk factors were assessed in 2196 participating men of the ULSAM-study. This investigation was repeated at age 60, 70, 77 and 82 years. Being physically active (PA) was defined as three hours of recreational or hard physical training per week. The men were categorized according to BMI/PA-status, as PA/normal weight (n = 593 at baseline), non-PA/normal weight (BMI < 25 kg/m(2), n = 580), PA/overweight (n = 418), non-PA/overweight (BMI 25-30 kg/m(2), n = 462), PA/obese (n = 62), non-PA/obese (BMI >30 kg/m(2), n = 81). We used updated data on BMI and physical activity obtained at all examinations. During follow-up (median 30 years) 850 individuals suffered a cardiovascular disease (myocardial infarction, stroke or heart failure). Using updated data on BMI/PA categories, an increased risk for cardiovascular disease was seen with increasing BMI, but a high physical activity was associated with a lower risk of cardiovascular disease within each BMI category: non-PA/normal weight (hazard ratio (HR) 1.31, 95% confidence interval (CI) 1.04-1.66), PA/overweight (HR 1.52, 95% CI 1.20-1.94), non-PA/overweight (HR 1.65, 95% CI 1.31-2.07) PA/obese (HR 2.05, 95% CI 1.44-2.92) and non-PA/obese (HR 2.39, 95% CI 1.74-3.29), using PA/normal weight men as referent. Although physical activity was beneficial at all levels of BMI regarding the risk of future cardiovascular disease, there was still a substantial increased risk associated with being overweight or obese during 30 years of follow-up.

Development and internal validation of a prognostic model to predict recurrence free survival in patients with adult granulosa cell tumors of the ovary

ObjectiveModels to predict the probability of recurrence free survival exist for various types of malignancies, but a model for recurrence free survival in individuals with an adult granulosa cell tumor (GCT) of the ovary is lacking. We aimed to develop and internally validate such a prognostic model. MethodsWe performed a multicenter retrospective cohort study of patients with a GCT. Demographic, clinical and pathological information were considered as potential predictors. Univariable and multivariable analyses were performed using a Cox proportional hazards model. Using backward stepwise selection we identified the combination of predictors that best predicted recurrence free survival. Discrimination (c-statistic) and calibration were used to assess model performance. The model was internally validated using bootstrapping techniques to correct for overfitting. To increase clinical applicability of the model we developed a nomogram to allow individual prediction of recurrence free survival. ResultsWe identified 127 patients with a GCT (median follow-up time was 131months (IQR 70-215)). Recurrence of GCT occurred in 81 out of 127 patients (64%). The following four variables jointly best predicted recurrence free survival; clinical stage, Body Mass Index (BMI), tumor diameter and mitotic index. The model had a c-statistic of 0.73 (95% CI 0.66–0.80) and showed accurate calibration. ConclusionsRecurrence free survival in patients with an adult GCT of the ovary can be accurately predicted by a combination of BMI, clinical stage, tumor diameter and mitotic index. The introduced nomogram could facilitate in counseling patients and may help to guide patients and caregivers in joint decisions on post-treatment surveillance.

Screening models using multiple markers for early detection of late-onset preeclampsia in low-risk pregnancy

BackgroundOur primary objective was to establish a cutoff value for the soluble fms-like tyrosine kinase 1(sFlt-1)/placental growth factor (PlGF) ratio measured using the Elecsys assay to predict late-onset preeclampsia in low-risk pregnancies. Our secondary objective was to evaluate the ability of combination models using Elecsys data, second trimester uterine artery (UtA) Doppler ultrasonography measurements, and the serum fetoplacental protein levels used for Down’s syndrome screening, to predict preeclampsia.MethodsThis prospective cohort study included 262 pregnant women with a low risk of preeclampsia. Plasma levels of pregnancy-associated plasma protein-A (PAPP-A) and serum levels of alpha-fetoprotein, unconjugated estriol, human chorionic gonadotropin, and inhibin-A were measured, and sFlt-1/PlGF ratios were calculated. All women underwent UtA Doppler ultrasonography at 20 to 24 weeks of gestation.ResultsEight of the 262 women (3.0%) developed late-onset preeclampsia. Receiver operating characteristic curve analysis showed that the third trimester sFlt-1/PlGF ratio yielded the best detection rate (DR) for preeclampsia at a fixed false-positive rate (FPR) of 10%, followed by the second trimester sFlt-1/PlGF ratio, sFlt-1 level, and PlGF level. Binary logistic regression analysis was used to determine the five best combination models for early detection of late-onset preeclampsia. The combination of the PAPP-A level and the second trimester sFlt-1/PlGF ratio yielded a DR of 87.5% at a fixed FPR of 5%, the combination of second and third trimester sFlt-1/PlGF ratios yielded a DR of 87.5% at a fixed FPR of 10%, the combination of body mass index and the second trimester sFlt-1 level yielded a DR of 87.5% at a fixed FPR of 10%, the combination of the PAPP-A and inhibin-A levels yielded a DR of 50% at a fixed FPR of 10%, and the combination of the PAPP-A level and the third trimester sFlt-1/PlGF ratio yielded a DR of 62.5% at a fixed FPR of 10%.ConclusionsThe combination of the PAPP-A level and the second trimester sFlt-1/PlGF ratio, and the combination of the second trimester sFlt-1 level with body mass index, were better predictors of late-onset preeclampsia than any individual marker.

Insulin resistance and metabolic syndrome in normal-weight individuals

We performed this study to investigate the prevalences of insulin resistance and metabolic syndrome (MetS) in a Chinese population with normal weight. We also examined whether fat mass is associated with insulin resistance and MetS in normal-weight individuals. Data were drawn from a cross-sectional study in China. Subjects with diabetes were excluded. The prevalences of insulin resistance and MetS were calculated. Multivariate logistic regression analysis was performed repeated separately for body mass index (BMI) and waist circumference (WC) in both men and women. We also used the combination of BMI and WC to predict insulin resistance and MetS. 8.55 % of normal-weight men and 12.62 % of normal-weight women had insulin resistance. 7.41 % of normal-weight men and 10.24 % of normal-weight women had MetS. WC was associated with incident insulin resistance and MetS independent of BMI in both men and women. BMI was independently associated with incident MetS in women. Normal-weight individuals with insulin resistance and/or MetS are not rare in the Chinese population. Fat mass is associated with insulin resistance and MetS in normal-weight subjects. The current findings support using both BMI and WC in clinical practice.

Prediction of Pancreatic Anastomotic Failure After Pancreatoduodenectomy

To determine whether remnant pancreatic volume (RPV), subcutaneous/visceral adipose tissue(SAT/VAT) area, and skeletal muscle (SM) area calculated from preoperative computed tomography (CT) can predict the occurrence of pancreatic anastomotic failure (PAF) after pancreatoduodenectomy (PD). Increased body mass index, small main pancreatic duct, and soft pancreatic texture are well-established predictors of PAF after PD. The impact on PAF of anthropomorphic measurements, such as RPV and body composition, is unknown. In 173 patients undergoing PD from 2004 to 2009, cross sections of SAT/VAT/SM area were quantitated volumetrically, respectively, from preoperative CT. RPV was calculated from the CT as the sum of pancreatic tissue area to the left of the presumed pancreatic transection site. The predictive ability for multiple models using combinations of body mass index, RPV, SAT/VAT area, SM area, main pancreatic duct size, and pancreatic gland texture was described using a concordance index (c-index). Clinically relevant PAF occurred in 22 patients (13%). Multivariate logistic regression analysis identified RPV (P = 0.0012), VAT area (P = 0.0003), and SM area (P = 0.0006) as independent predictors of PAF. Using previously identified risk factors, the best 2-predictor model (body mass index and pancreatic duct size) resulted in a c-index of 0.748. Using anthropomorphic factors, however, the 2-predictor model using VAT and SM areas revealed a superior c-index of 0.959. Our 2-predictor model using VAT area and SM area based on volumetric quantification using preoperative CT may offer clinical benefit as an objective prognostic measure to predict clinically relevant PAF after PD.

Educational differences in self-rated physical fitness among Finns

BackgroundThe high educated live longer and healthier lives when compared to the low educated. Physical fitness as a health indicator reflects the level of physical activity along with other health-influencing factors such as obesity, smoking, chronic diseases and individual training effects. Studies support that self-rated physical fitness correlates with objectively measured physical fitness well. However, the educational differences in self-rated physical fitness are not known.MethodsOur aim was to study educational differences in self-rated physical fitness in Finnish population. The data were collected in 2007 for a cross-sectional population based National FINRISK Study. The analyzed data included 2722 men and 3108 women aged 25 to 74 years. Statistical method was ordinal logistic regression.ResultsLonger educational career was associated with better self-rated physical fitness. The educational differences in self-rated physical fitness were largely explained by health behavior. Leisure-time physical activity explained fully and body mass index partly the educational differences in self-rated physical fitness among men. The combination of body mass index, history of chronic diseases and smoking explained the differences fully among men and partly among women. Leisure-time, occupational and commuting physical activities, body mass index, history of chronic diseases and smoking together explained all educational differences in self-rated physical fitness among both genders.ConclusionsAlthough educational differences in self-rated physical fitness were found, they were explained by health behavior related factors. Leisure-time physical activity offered the strongest single explanation for the educational differences in self-rated physical fitness. Thus, possibilities for leisure-time physical activity should be increased especially among the low educated.