Overweight and obesity are common challenges among childhood cancer survivors. Overweight may be disguised, as survivors can have normal weight but high fat percentage (fat%) on dual-energy X-ray absorptiometry (DXA). We aimed to assess prevalence, identify determinants and biomarkers, and assess which method captures overweight best, in a nationwide cohort.

The prevalence of overweight and obesity, primarily defined by body mass index (BMI), was assessed in the DCCSS-LATER cohort of adult survivors treated from 1963-2002, with the LifeLines cohort as reference. The associations between risk factors and overweight metrics were investigated using logistic regression. Additional overweight metrics included DXA fat%, waist circumference (WC), waist/hip ratio (WHR), waist/height ratio (WHtR), and high-molecular-weight (HMW) adiponectin.

A total of 2338 (mean age 35.5 years, follow-up 28.3 years) survivors participated. The overweight prevalence was 46.3% in men and 44.3% in women (obesity 11.2% and 15.9%, morbid obesity 2.4% and 5.4%), with highest rates among brain tumor survivors. Compared to controls, there was no overall increased overweight rate, but this was higher in women > 50 years, morbid obesity in men > 50 years. Overweight at cancer diagnosis (adjusted odds ratio [aOR] = 3.83, 95% CI 2.19-6.69), cranial radiotherapy (aOR = 3.21, 95% CI 1.99-5.18), and growth hormone deficiency (separate model, aOR = 1.61, 95% CI 1.00-2.59) were associated with overweight. Using BMI, WC, WHR, and WHtR, overweight prevalence was similar. Low HMW adiponectin, present in only 4.5% of survivors, was an insensitive overweight marker. Dual-energy X-ray absorptiometry-based classification identified overweight in an additional 30%, particularly after abdominal radiotherapy, total body irradiation, anthracyclines, and platinum.

Overweight occurs in almost half of long-term survivors. There was no overall increased incidence of overweight compared to controls. We identified factors associated with overweight, as well as subgroups of survivors in whom DXA can more reliably assess overweight.

Obesity is the most serious global epidemic and body composition is the main indicator to evaluate obesity. This study aimed to investigate the changing trends of body composition by age and gender in Beijing adults aged 20-60 years and explore the distribution of obesity rates in different age groups of both sexes under different evaluation criteria.

A total of 24,948 adults aged 20-60 years in Beijing, including 10,225 males and 14,192 females, were included, divided into four age groups (20-29, 30-39, 40-49, and ≥ 50 years) with each decade of age as an age group. Body composition indicators (BMI, fat mass, BF%, muscle mass, visceral fat area, and WHR) were measured in all subjects.

BMI and total fat mass peaked in males aged 40-49 years (BMI = 25.75 kg/m2, total fat mass = 17.70 kg). Female BMI, fat mass and BF% all increased significantly with age (p < 0.01). Total muscle peaked in males aged 30-39 years and decreased significantly thereafter (p < 0.0001). Visceral fat area and WHR increased significantly with age in both sexes (p < 0.0001). Age was significantly positively correlated with BMI, BF%, fat mass, WHR, and visceral fat area in both sexes (p < 0.0001), and age was negatively correlated with muscle mass in males (standard β =  - 0.14, p < 0.0001) while positive in female (standard β = 0.05, p < 0.0001). Under the BMI criterion, the obesity rate peaked at 27.33% in males at the age of 20-29 years. Under the BF% criterion, the obesity rate peaked at 17.41% in males at the age of 30-39 years, and increased in females with age. The central obesity rate of both sexes increased with age under the criteria of WHR and visceral fat area.

The results of this study reveal that age- and sex-related patterns of body composition and obesity change among Beijing adults aged 20-60 years may differ across age groups and that such patterns of change should be considered when developing public health strategies.

Non-alcoholic fatty liver disease (NAFLD) has become the most common chronic liver disease worldwide, associated with a high risk of progression to NASH, liver cirrhosis and hepatocarcinoma. Its prevalence is closely related to obesity (understood as adipose-based disease and insulin resistance), which makes that at present NAFLD can be considered a metabolic dysfunction hallmark, regardless of the body mass index. Despite being such a prevalent condition, with such severe consequences, at present there are no reliable biomarkers for its diagnosis or specific treatment. Significant and sustained weight loss, as well as some antidiabetic treatments, has shown promising results for NAFLD but data needs confirmation in larger clinical trials and longer follow-up. Efforts should be made for a better and more accurate baseline diagnosis (including large-scale genetics), identification of patients at higher risk for progression to NASH as well as adequate treatment, to allow us to offer a personalized approach in NAFLD in the context of precision medicine.

To determine the validity of hand-to-foot bioelectrical impedance analysis (HF-BIA) versus body mass index (BMI) to assess overweight and obesity status in adults against a reference method, dual-energy x-ray absorptiometry (DXA).

It is a validation study conducted on 206 Pakistani adults ≥20 years recruited through convenience sampling technique at PNS Shifa Hospital and Jinnah Post Medical Centre, Karachi, Pakistan.

HF-BIA showed better sensitivity of 90.1% and 100% specificity with no false positive, but 9% false negative as compared to BMI which indicated 80.3% sensitivity and 100% specificity with a false-negative rate of 19.6%.HF-BIA also showed better sensitivity 80.9-97.1% with 100% specificity and PPV across all age groups. The correlation coefficient between BMI and DXA bf% (r=0.67) was moderate and less than the correlation coefficient between HF-BIA and DXA bf % (r=0.87). Kappa agreement showed weak to a fair agreement between BMI and DXA bf % (0.1 overall; 0.22 men; 0.14 women) compared to HF-BIA, which had a better agreement between BIA bf% and DXA bf% (0.43 overall; 0.46 men; 0.34 women). HF-BIA bf % demonstrated a better discriminatory power than BMI (AUC of ≥0.91) and was better predictor of body fat than BMI.

HF-BIA is a more accurate method than BMI and may be used consistently throughout the country in primary care and research to identify the fat-based overweight and obese in the Pakistani population.

Chronic pain is associated with anhedonia and decreased motivation. These behavioral alterations have been linked to alterations in the limbic brain and could explain the increased risk for obesity in pain patients. The mechanism of these behavioral changes and how they set in in relation to the development of chronic pain remain however poorly understood. Here we asked how eating behavior was affected in low-back pain patients before and after they transitioned to chronic pain, compared to patients whose pain subsided. Additionally, we assessed how the hedonic perception of fat-rich food, which is altered in chronic pain patients, related to the properties of the nucleus accumbens in this patients' population. We hypothesized that the accumbens would be directly implicated in the hedonic processing of fat-rich food in pain patients because of its well-established role in hedonic feeding and fat ingestion, and its emerging role in chronic pain. Accordingly, we used behavioral assays and structural brain imaging to test sub-acute back pain patients (SBP) and healthy control subjects at baseline and at approximately one-year follow-up. We also studied a sample of chronic low-back pain patients (CLBP) at one time point only. We found that SBP patients who recovered at follow-up (SBPr) and CLBP patients showed disrupted eating behaviors. In contrast, SBP patients who persisted in having pain at follow-up (SBPp) showed intact eating behavior. From a neurological standpoint, only SBPp and CLBP patients showed a strong and direct relationship between hedonic perception of fat-rich food and nucleus accumbens volume. This suggests that accumbens alterations observed in SBPp patients in previous works might protect them from hedonic eating disruptions during the early course of the illness. We conclude that disrupted eating behavior specifically sets in after pain chronification and is accompanied by structural changes in the nucleus accumbens.

Lymphatic pain and swelling due to lymph fluid accumulation are the most common and debilitating long-term adverse effects of cancer treatment. This study aimed to quantify the effects of obesity on lymphatic pain, arm, and truncal swelling. Methods: A sample of 554 breast cancer patients were enrolled in the study. Body mass index (BMI), body fat percentage, and body fat mass were measured using a bioimpedance device. Obesity was defined as a BMI ≥ 30 kg/m2. The Breast Cancer and Lymphedema Symptom Experience Index was used to measure lymphatic pain, arm, and truncal swelling. Multivariable logistic regression models were used to estimate the odds ratio (OR) with 95% confidence interval (CI) to quantify the effects of obesity. Results: Controlling for clinical and demographic characteristics as well as body fat percentage, obesity had the greatest effects on lymphatic pain (OR 3.49, 95% CI 1.87-6.50; p < 0.001) and arm swelling (OR 3.98, 95% CI 1.82-4.43; p < 0.001). Conclusions: Obesity is a significant risk factor for lymphatic pain and arm swelling in breast cancer patients. Obesity, lymphatic pain, and swelling are inflammatory conditions. Future study should explore the inflammatory pathways and understand the molecular mechanisms to find a cure.

Survival of cancer in childhood is increasingly common with modern therapeutic protocols but leads frequently to adverse long-term impacts on health, including metabolic and cardiovascular disease. Changes in body composition, especially an increase in fat mass and a decrease in muscle mass, are found early in patients with pediatric cancer, persist long after treatment has been completed and seem to contribute to the development of chronic disease. This review details the effects of such changes in body composition and reviews the underlying pathophysiology of the development of sarcopenic obesity and its adverse metabolic impact. The authors discuss the particular challenges in identifying obesity accurately in survivors of pediatric cancer using available measurement techniques, given that common measures, such as body mass index, do not distinguish between muscle and adipose tissue or assess their distribution. The authors highlight the importance of a harmonized approach to the assessment of body composition in pediatric cancer survivors and early identification of risk using "gold-standard" measurements. This will improve our understanding of the significance of adiposity and sarcopenia in this population, help identify thresholds predictive of metabolic risk, and ultimately prevent or ameliorate the long-term metabolic and cardiovascular impacts on health experienced by survivors of cancer in childhood.

Weight stigma is associated with poor dietary adherence, yet adherence is essential for weight loss and maintenance. This study aimed to determine differences in dietary adherence and perceived hunger between lean individuals and two groups of individuals with obesity.

In a 6-week outpatient dietary intervention (23 males; aged 48  [SD 14] years), lean participants (n = 23; BMI 23  [SD 2] kg/m² ) received a weight-maintaining energy needs (WMEN) diet, and participants with obesity (BMI 36  [SD 7]) were randomized to either WMEN (n = 18) or a 35% calorie-reduced (CR) diet (n = 19). All food was provided, and multiple adherence and hunger ratings were assessed daily and weekly on an outpatient basis and in person at twice-weekly visits (e.g., 24-hour recall, diaries).

Weight decreased more in the group of CR individuals with obesity (β = -0.301 kg/wk, P = 0.02) compared with the group of lean individuals and the group of WMEN individuals with obesity. However, total percent adherence did not differ between groups (P = 0.60), and hunger scores did not change across groups over time (P = 0.08).

Results indicate that there are no differences in dietary adherence between lean individuals and individuals with obesity and adherence is not associated with adiposity or hunger. Thus, the belief that nonadherence (e.g., lack of willpower) is unique to obesity is untrue and may perpetuate weight bias and stigma.

The aim of this systematic review was to assess the performance of anthropometric tools to determine obesity in the general population (CRD42018086888). Our review included 32 studies. To detect obesity with body mass index (BMI), the meta-analyses rendered a sensitivity of 51.4% (95% CI 38.5-64.2%) and a specificity of 95.4% (95% CI 90.7-97.8%) in women, and 49.6% (95% CI 34.8-64.5%) and 97.3% (95% CI 92.1-99.1%), respectively, in men. For waist circumference (WC), the summary estimates for the sensitivity were 62.4% (95% CI 49.2-73.9%) and 88.1% for the specificity (95% CI 77.0-94.2%) in men, and 57.0% (95% CI 32.2-79.0%) and 94.8% (95% CI 85.8-98.2%), respectively, in women. The data were insufficient to pool the results for waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) but were similar to BMI and WC. In conclusion, BMI and WC have serious limitations for use as obesity screening tools in clinical practice despite their widespread use. No evidence supports that WHR and WHtR are more suitable than BMI or WC to assess body fat. However, due to the lack of more accurate and feasible alternatives, BMI and WC might still have a role as initial tools for assessing individuals for excess adiposity until new evidence emerges.

Obesity is now recognized as a worldwide health issue and has reached epidemic proportions, affecting both developed and developing countries. The World Obesity Federation stated that "Obesity is a chronic relapsing disease process": as a result, obesity has been recognized internationally as a chronic disease. The primary cause of the metabolic syndrome and increase of the cardiovascular risk have been identified in "sick fat", a condition then defined as adiposopathy. Heart attacks, strokes and renal failures are pathologies that have mid-risk factors such as dyslipidemia, hypertension and diabetes, which in turn are caused by obesity, whose primary risk factor is represented by the diet. The aim of the present review is to consider the importance of body composition, together with chronic inflammation and a new gut microbiota data that may turn out to be crucial elements of some target treatment of human obesity.

In this review, we performed research using PubMed database reviewing the evidence in the literature of evidence information regarding the link between obesity and body composition in the development of metabolic disease via inflammation markers and in particular, the new role exerted by gut microbiota.

Several papers were evaluated searching for differences in fat mass and disease risk. We also identified the same papers dealing with differences in body composition and metabolic syndrome. Our attention focuses also on a new frontier of gut microbiota composition in the body weight decrease and anti-inflammatory effects.

To the saving of lean mass, for the prevention of cardiometabolic diseases, also considering the relationship with obesity, it is necessary to reduce the inflammatory state, acting on the gut-microbiota and on the intestinal permeability. To improve the health of the intestinal flora, we propose a 4P medicine and treatment with probiotics, prebiotics, postbiotics, and polyphenols.

Longitudinal assessment of body composition following bariatric surgery allows monitoring of health status. Our aim was to elucidate trends of anthropometric and clinical outcomes 3 years following sleeve gastrectomy (SG).

A prospective cohort study of 60 patients who underwent SG. Anthropometrics including body composition analysis measured by multi-frequency bioelectrical impedance analysis, blood tests, liver fat content measured by abdominal ultrasound and habitual physical activity were evaluated at baseline and at 6 (M6), 12 (M12), and 36 (M36) months post-surgery.

Sixty patients (55% women, age 44.7 ± 8.7 years) who completed the entire follow-up were included. Fat mass (FM) was reduced significantly 1 year post-surgery (55.8 ± 11.3 to 26.7 ± 8.3 kg; P < 0.001) and then increased between 1 and 3 years post-operatively, but remained below baseline level (26.7 ± 8.3 to 33.1 ± 11.1 kg; P < 0.001). Fat free mass (FFM) decreased significantly during the first 6 months (64.7 ± 14.3 to 56.9 ± 11.8 kg; P < 0.001), slightly decreased between M6 and M12 and then reached a plateau through M36. Weight loss "failure" (< 50% excess weight loss) was noticed in 5.0% and 28.3% of patients at M12 and M36, respectively. Markers of lipid and glucose metabolism changed thereafter in parallel to the changes observed in FM, with the exception of HDL-C, which increased continuingly from M6 throughout the whole period analyzed (45.0 ± 10.2 to 59.5 ± 15.4 mg/dl; P < 0.001) and HbA1c which continued to decrease between M12 and M36 (5.5 ± 0.4 to 5.3 ± 0.4%; P < 0.001). There were marked within-person variations in trends of anthropometric and clinical parameters during the 3-year follow-up.

Weight regain primarily attributed to FM with no further decrease in FFM occurs between 1 and 3 years post-SG. FM increase at mid-term may underlie the recurrence of metabolic risk factors and can govern clinical interventions.

Obesity must be considered a real pathology. In the world wide, obesity represent one of the major public health issue associated with increased morbidity and mortality. Overweight or obesity, in fact, significantly increases the risk of contracting diseases, such as: arterial hypertension, dyslipidemia, type 2 diabetes mellitus, coronary heart disease, cerebral vasculopathy, gallbladder lithiasis, arthropathy, ovarian polycytosis, sleep apnea syndrome, and some neoplasms. Despite numerous informative campaigns, unfortunately, the fight against obesity does not seem to work: in the last years, the prevalence continued to increase. The progressive and rapid increase in the incidence of obesity, which has characterized most of the economically advanced countries in the last decade, has been the main stimulus for the research of the mechanisms underlying this pathology and the related disorders. The aims of this review is to provide a revision of the literature in order to define obesity as diseases, secondly to highlight the limits and the inaccuracy of common tools used for the diagnosis of obesity, and as a third thing to strengthen the concept of the complexity of obesity as a disease among political health care providers. Obesity may be viewed as a multifactorial pathology and chronic low-grade inflammatory disease. In fact, people affected by obesity have greater risk of developing comorbility and morbility, respect to healthy. Hence, the absolute therapeutic benefit is directly proportional to the basic risk. So, internationally interest on early diagnosis of obesity is growing to avoid under- and overdiagnosis consequences. Therefore, the consequences are an aggravation of the disease and an increase in obesity related pathology like diabetes, cardiovascular disease, and cancer. The most widely used parameter for diagnosis, body mass index (BMI) is not suitable for assessing the body fat. In fact, several studies demonstrate that BMI alone cannot define obesity, which consists not so much in weight gain as in excess fat mass. The use of suitable tools for the assessment of fat mass percentage combined with clinical and genetic analysis allowed to identify different phenotypes of obesity, which explain the various paradoxes of obesity. It is essential to adopt all possible strategies to be able to combat obesity, ameliorate the suffering of patients, and reduce the social and treatment costs of obesity.

Although obesity negatively influences the metabolic homeostasis of cells within a broad range of tissues, its impact on oocyte metabolism is not fully understood. Prior evidence suggests that obesity increases expression of oocyte genes associated with inflammation, oxidative stress, and lipid metabolism; however, the metabolic impact of these genetic differences is not known. To address this gap, we conducted an exploratory assessment of the follicular fluid (FF) metabolome in eight overweight/obese (OW) and nine normal-weight (NW) women undergoing in vitro fertilization. FF and serum were collected and analyzed by untargeted metabolomics using gas chromatography-quadrupole time-of-flight mass spectrometry and charged-surface hybrid column-electrospray ionization quadrupole time-of-flight tandem mass spectrometry. Untargeted metabolomics identified obesity-associated changes in FF metabolites related to oxidative stress/antioxidant capacity, xenometabolism/amino acid biosynthesis, and lipid metabolism. Discriminant FF metabolites included elevated uric acid, isothreonic acid, one unknown primary metabolite, and six unknown complex lipids in OW compared with NW women. Conversely, 2-ketoglucose dimethylacetal, aminomalonate, two unknown primary metabolites, and two unknown complex lipids were decreased in FF of OW relative to NW women. Indole-3-propionic acid (IPA), a bacteria-derived metabolite, was also decreased in both FF and serum of OW women ( P < 0.05). The significant correlation between antioxidant IPA in serum and FF ( R = 0.95, P < 0.0001) suggests a potential serum biomarker of FF antioxidant status or reflection of the gut metabolism interaction with the follicle. These results suggest that obesity has important consequences for the follicular environment during the preconception period, a window of time that may be important for lifestyle interventions to ameliorate obesity-associated risk factors.

Body composition changes with aging can increase rates of obesity, frailty and impact function. Measuring adiposity using body fat (%BF) or central adiposity using waist circumference (WC) have greater diagnostic accuracy than traditional measures such as body mass index (BMI).

This is an observational study.

This study focused on older community-dwelling participants.

We identified individuals age ≥ 60 years old using the 1999-2004 cross-sectional National Health and Nutrition Survey (NHANES).

The primary analysis evaluated the association between frailty and %BF or WC. Frailty was the primary predictor (robust=referent) and %BF and WC were considered continuous outcomes. Multiple imputation analyses accounted for missing characteristics.

Dual energy x-ray absorptiometry was used to assess %BF and WC was objectively measured. Frailty was defined using an adapted version of Fried's criteria that was self-reported: (low BMI<18.5kg/m2; slow walking speed [<0.8m/s]; weakness [unable to lift 10lbs]; exhaustion [difficulty walking between rooms on same floor] and low physical activity [compared to others]). Robust, pre-frail and frail persons met zero, 1 or 2, and ≥3 criteria, respectively.

Of the 4,984 participants, the mean age was 71.1±0.2 (SE) years and 56.5% were females. We classified 2,246 (50.4%), 2,195 (40.3%), and 541 (9.2%) individuals as robust, pre-frail and frail, respectively. Percent BF was 35.9±0.13, 38.3±0.20 and 40.0±0.46 in the robust, pre-frail and frail individuals, respectively. WC was 99.5±0.32 in the robust, 100.1±0.43 in pre-frail, 104.7±1.17 in frail individuals. Compared to robust individuals, only frail individuals had greater %BF on average (β=0.97±0.43,p=0.03); however, pre-frail and frail individuals had 2.18 and 4.80 greater WC, respectively (β=2.18±0.64,p=0.002, and β=4.80±1.1,p<0.001).

Our results demonstrate that in older adults, frailty and pre-frailty are associated with a greater likelihood of high WC (as dichotomized) and a greater average WC (continuous).

Atherogenic index of plasma (AIP) was found to be one of the strongest markers in predicting the cardiovascular disease (CVD) risk. This study was to determine the AIP and its relationship with other CVD risk factors.

This cross-sectional study was done among 349 staff of a public university in Sarawak. Data were collected using questionnaire, blood sampling, and anthropometric and blood pressure measurement. Data were analyzed using IBM SPSS version 20.

A total of 349 respondents participated with majority females (66.8%), aged 38.5 ± 7.82 years. Nearly 80% of the respondents were overweight and obese, 87.1% with high and very high body fat, and 46.9% with abnormal visceral fat. For AIP category, 8.9% were found to be in intermediate and 16.4% were at high risk. Elevated lipid profile showed that total cholesterol (TC) is 15.5%, low density lipoprotein (LDL) is 16.1%, and triglyceride (TG) is 10.6%. AIP was significantly correlated with body mass index (r=0.25), visceral fat (r=0.37), TC (r=0.22), LDL (0.24), HDL (r=-0.72), TG (r=0.84), glucose (r=0.32), systolic blood pressure (r=0.22), and diastolic blood pressure (r=0.28).

It indicated that AIP is associated with other CVD risk factors. Modification of lifestyle is strongly recommended.

Body mass index (BMI) is a widely used indicator of obesity status in clinical settings and population health research. However, there are concerns about the validity of BMI as a measure of obesity in postmenopausal women. Unlike BMI, which is an indirect measure of obesity and does not distinguish lean from fat mass, dual-energy x-ray absorptiometry (DXA) provides a direct measure of body fat and is considered a gold standard of adiposity measurement. The goal of this study is to examine the validity of using BMI to identify obesity in postmenopausal women relative to total body fat percent measured by DXA scan.

Data from 1,329 postmenopausal women participating in the Buffalo OsteoPerio Study were used in this analysis. At baseline, women ranged in age from 53 to 85 years. Obesity was defined as BMI ≥ 30 kg/m and body fat percent (BF%) greater than 35%, 38%, or 40%. We calculated sensitivity, specificity, positive predictive value, and negative predictive value to evaluate the validity of BMI-defined obesity relative BF%. We further explored the validity of BMI relative to BF% using graphical tools, such as scatterplots and receiver-operating characteristic curves. Youden's J index was used to determine the empirical optimal BMI cut-point for each level of BF% defined obesity.

The sensitivity of BMI-defined obesity was 32.4% for 35% body fat, 44.6% for 38% body fat, and 55.2% for 40% body fat. Corresponding specificity values were 99.3%, 97.1%, and 94.6%, respectively. The empirical optimal BMI cut-point to define obesity is 24.9 kg/m for 35% BF, 26.49 kg/m for 38% BF, and 27.05 kg/m for 40% BF according to the Youden's index.

Results demonstrate that a BMI cut-point of 30 kg/m does not appear to be an appropriate indicator of true obesity status in postmenopausal women. Empirical estimates of the validity of BMI from this study may be used by other investigators to account for BMI-related misclassification in older women.

Narrative review.

Review methods used to measure and classify obesity in individuals with spinal cord injuries (SCI). Outline the strengths and weaknesses of each method used to measure obesity in individuals with SCI.

International.

PubMed was used to identify articles before 2016. Search terms ('obesity' or 'weight status' and 'spinal cord injury'). Filters: adults, English and human. Studies were retained that (1) included participants, 18 years or older, with SCI; (2) took place in inpatient, outpatient or community-based settings and (3) measured obesity status. Unique methods for classifying individuals with SCI as obese were identified and examples are presented.

Methods identified for classifying obesity were as follows: World Health Organization body mass index (BMI) cutoff⩾30 kg m^-2, BMI cutoff ⩾25-29 kg m^-2, and SCI-specific BMI cutoff ⩾22 kg m^-2, waist circumference cutoff (women >102 cm, men >88 cm), percent body fat cutoffs ⩾25% using bioelectrical impedance analysis and dual-energy X-ray absorptiometry, computerized tomography scan visceral fat area ⩾100 cm² and percentage of ideal body weight.

BMI is the most widely used measure of obesity in the SCI literature. Although some studies identified alternative cutoffs or other metrics, there is no standardized obesity classification in SCI. However, research is needed to determine and validate obesity classification specific to SCI due to physiological changes that occur following injury. We recommend that researchers and clinicians proceed with caution and use methodology based on the purpose of measurement.

To describe 1) cross-sectional associations between domain-specific physical activity, sitting time and different measures of overweight/obesity and 2) longitudinal associations between patterns of change in physical activity and overweight/obesity ten years later.

Cross-sectional and longitudinal analyses based on the first and second follow-up of the Swiss cohort study SAPALDIA (SAP) were conducted (SAP2 in 2002/03, SAP3 in 2010/11). Physical activity was assessed by self-report using the long International Physical Activity Questionnaire (IPAQ) and four short questions regarding moderate and vigorous activities. Overweight/obesity were defined based on body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR) and percent body fat based on bioelectric impedance analysis (BIA), all measured objectively. Multivariable logistic regression was used for analyses.

Cross-sectionally, leisure-time and vigorous physical activity were inversely associated with all obesity parameters. Most consistent associations were found with BIA percent body fat. There were no associations between work-related and domestic activities and overweight/obesity. Sitting time was positively associated with BIA percent body fat, but not with BMI, WHR and WHtR. Longitudinally, remaining inactive from SAP2 to SAP3 was associated with obesity and BIA percent body fat at SAP3 and with weight increase, becoming inactive with BIA percent body fat and weight increase.

The results support associations between physical activity and overweight/obesity cross-sectionally and longitudinally. Most consistent associations were found for BIA percent body fat. For prevention purposes, the results indicate that physical activity can have an important contribution to weight management.

To compare type 2 diabetes prevalence among three ethnic groups resident in the Netherlands: Ghanaians, African Surinamese and Dutch origin. Secondly, to determine the contribution of measures of body composition to ethnic differences in type 2 diabetes.

Baseline data from Ghanaian (n=1873), African Surinamese (n=2189) and Dutch (n=2151) origin participants of the HELIUS study (aged 18-70 years) were analyzed. Type 2 diabetes was determined according to the WHO criteria. Logistic regression tested ethnic differences in type 2 diabetes and the contribution of body fat percentage and waist-to-hip ratio.

Among men, type 2 diabetes prevalence was higher in Ghanaians (14.9%) than in African Surinamese (10.4%) and Dutch (5.0%). Among women, type 2 diabetes prevalence in Ghanaian (11.1%) was higher than in Dutch (2.3%), but similar to African Surinamese (11.5%). After adjusting for age, body fat percentage and waist-to-hip ratio, the odds ratios for having type 2 diabetes were 1.55 (95% CI: 1.12-2.15) for Ghanaian men compared with African Surinamese and 4.19 (95% CI: 2.86-6.12) compared with Dutch. Among women these odds ratios were 0.94 (95% CI: 0.70-1.26) and 4.78 (95% CI: 2.82-8.11).

The higher prevalence of type 2 diabetes among Ghanaian compared with African Surinamese men suggests a need to distinguish between African descent populations when assessing their type 2 diabetes risk. The higher odds for type 2 diabetes among Ghanaians cannot be attributed to differences in body composition. Further research on the contribution of lifestyle factors as well as genetic and epigenetic factors is needed to identify the reasons for the observed disparities.

Total body fat percentage (%BF) evaluated by dual energy X-ray absorptiometry (DXA) scans (DXA %BF) is widely recognized as a precise measure of fatness. We aimed to establish national reference curves for DXA %BF, %BF calculated from skinfolds (SF %BF) and waist circumference (WC) in healthy children, and to compare agreement between the different methods.

Based on 11 481 physical examinations (anthropometry) and 1200 DXA scans from a longitudinal cohort of Danish children (n=2647), we established reference curves (LMS-method) for SF %BF, WC (birth to 14 years) and DXA %BF (8-14 years). Age- and sex-specific Z-scores for body mass index (BMI), WC and SF %BF were compared. Sensitivity and specificity were calculated for agreement of WC, SF %BF and BMI with DXA %BF to identify obese children (>+1 s.d.).

%BF differed with age, sex, pubertal stage and social class. SF %BF correlated strongly with DXA %BF (r=0.86). BMI and WC also correlated positively with DXA %BF (Z-scores; r= 0.78 and 0.69). Sensitivity and specificity were 79.5 and 93.8 for SF %BF, 75.9 and 90.3 for BMI and 59.2 and 95.4 for WC.

SF %BF showed the highest correlation and best agreement with DXA %BF in identifying children with excess fat (+1 s.d.).

There is increasing evidence suggesting that WHO body mass index (BMI) cut-off values are outdated and should not be applied to different population. To overcome misclassifications, direct measurements of percentage body fat (PBF) would be a better tool for preobesity and obesity diagnosis. The aim of this study was to analyze the body composition in a adult population in Centre-South of Italy, by age and gender, and to verify the accordance between BMI and PBF cut-off points for health status classification.

The total subject pool cover a total of 4408 participants adults. A completed screening of anthropometry and body composition by Dual X-ray Absorptiometry, (DXA) was assessed on 3.258 subjects.

Distributions and quantitative reliable estimates of PBF, total body fat and lean, according to gender and age are provided. The prevalence of "at risk" subjects (preobese and obese) was 69% and 85%, for men and women respectively, according to PBF cut-off points. The agreement of BMI and PBF categories resulted low for the total and male population, even scarce for female population (all P ≤ 0.001). The false negative classification of BMI was stronger for women than men and for younger than older subjects.

Screening for adiposity in subjects with a normal BMI could better identify those at higher risk for cardiometabolic disturbances and cardiovascular mortality. The herein used cut-offs points of PBF, by age and gender, may provide a useful reference in clinical settings and public health services, in particular for the Italian Caucasian population.

To determine the combined effects of body mass index (BMI) and body fat (BF) on prognosis in coronary heart disease (CHD) to better understand the obesity paradox.

We studied 581 patients with CHD between January 1, 2000, and July 31, 2005, who were divided into low (<25) and high BMI (≥25), as well as low (≤25% men and ≤35% women) and high BF (>25% in men and >35% in women). Four groups were analyzed by total mortality during the 3-year follow-up by National Death Index: low BF/low BMI (n=119), high BF/low BMI (n=26), low BF/high BMI (n=125), and high BF/high BMI (n=311).

During the 3-year follow-up, mortality was highest in the low BF/low BMI group (11%), which was significantly (P<.001) higher than that in the other 3 groups (3.9%, 3.2%, and 2.6%, respectively); using the high BF/high BMI group as a reference, the low BF/low BMI group had a 4.24-fold increase in mortality (confidence interval [CI], 1.76-10.23; P=.001). In multivariate logistic regression for mortality, when entered individually, both high BMI (odds ratio [OR], 0.79; CI, 0.69-0.90) and high BF (OR, 0.89; CI, 0.82-0.95) as continuous variables were independent predictors of better survival, whereas low BMI (OR, 3.60; CI, 1.37-9.47) and low BF (OR, 3.52; CI, 1.34-9.23) as categorical variables were independent predictors of higher mortality.

Although both low BF and low BMI are independent predictors of mortality in patients with CHD, only patients with combined low BF/low BMI appear to be at particularly high risk of mortality during follow-up. Studies are needed to determine optimal body composition in the secondary prevention of CHD.