Surface-Based Body Shape Index and Its Relationship with All-Cause Mortality

Background

Obesity is a global public health challenge. In the US, for instance, obesity prevalence remains high at more than one-third of the adult population, while over two-thirds are obese or overweight. Obesity is associated with various health problems, such as diabetes, cardiovascular diseases (CVDs), depression, some forms of cancer, sleep apnea, osteoarthritis, among others. The body mass index (BMI) is one of the best known measures of obesity. The BMI, however, has serious limitations, for instance, its inability to capture the distribution of lean mass and adipose tissue, which is a better predictor of diabetes and CVDs, and its curved (“U-shaped”) relationship with mortality hazard. Other anthropometric measures and their relation to obesity have been studied, each with its advantages and limitations. In this work, we introduce a new anthropometric measure (called Surface-based Body Shape Index, SBSI) that accounts for both body shape and body size, and evaluate its performance as a predictor of all-cause mortality.

Methods and Findings

We analyzed data on 11,808 subjects (ages 18–85), from the National Health and Human Nutrition Examination Survey (NHANES) 1999–2004, with 8-year mortality follow up. Based on the analysis, we introduce a new body shape index constructed from four important anthropometric determinants of body shape and body size: body surface area (BSA), vertical trunk circumference (VTC), height (H) and waist circumference (WC). The surface-based body shape index (SBSI) is defined as follows: SBSI=(H7/4)(WC5/6)BSAVTC(1) SBSI has negative correlation with BMI and weight respectively, no correlation with WC, and shows a generally linear relationship with age. Results on mortality hazard prediction using both the Cox proportionality model, and Kaplan-Meier curves each show that SBSI outperforms currently popular body shape indices (e.g., BMI, WC, waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), A Body Shape Index (ABSI)) in predicting all-cause mortality.

Conclusions

We combine measures of both body shape and body size to construct a novel anthropometric measure, the surface-based body shape index (SBSI). SBSI is generally linear with age, and increases with increasing mortality, when compared with other popular anthropometric indices of body shape.     

Entering a New Era of Body Indices: The Feasibility of a Body Shape Index and Body Roundness Index to Identify Cardiovascular Health Status

Background

The Body Mass Index (BMI) and Waist Circumference (WC) are well-used anthropometric predictors for cardiovascular diseases (CVD), but their validity is regularly questioned. Recently, A Body Shape Index (ABSI) and Body Roundness Index (BRI) were introduced as alternative anthropometric indices that may better reflect health status.

Objective

This study assessed the capacity of ABSI and BRI in identifying cardiovascular diseases and cardiovascular disease risk factors and determined whether they are superior to BMI and WC.

Design and Methods

4627 Participants (54±12 years) of the Nijmegen Exercise Study completed an online questionnaire concerning CVD health status (defined as history of CVD or CVD risk factors) and anthropometric characteristics. Quintiles of ABSI, BRI, BMI, and WC were used regarding CVD prevalence. Odds ratios (OR), adjusted for age, sex, and smoking, were calculated per anthropometric index.

Results

1332 participants (27.7%) reported presence of CVD or CVD risk factors. The prevalence of CVD increased across quintiles for BMI, ABSI, BRI, and WC. Comparing the lowest with the highest quintile, adjusted OR (95% CI) for CVD were significantly different for BRI 3.2 (1.4–7.2), BMI 2.4 (1.9–3.1), and WC 3.0 (1.6–5.6). The adjusted OR (95% CI) for CVD risk factors was for BRI 2.5 (2.0–3.3), BMI 3.3 (1.6–6.8), and WC 2.0 (1.6–2.5). No association was observed for ABSI in both groups.

Conclusions

BRI, BMI, and WC are able to determine CVD presence, while ABSI is not capable. Nevertheless, the capacity of BRI as a novel body index to identify CVD was not superior compared to established anthropometric indices like BMI and WC.     

A New Metric of Inclusive Fitness Predicts the Human Mortality Profile

Biological species have evolved characteristic patterns of age-specific mortality across their life spans. If these mortality profiles are shaped by natural selection they should reflect underlying variation in the fitness effect of mortality with age. Direct fitness models, however, do not accurately predict the mortality profiles of many species. For several species, including humans, mortality rates vary considerably before and after reproductive ages, during life-stages when no variation in direct fitness is possible. Variation in mortality rates at these ages may reflect indirect effects of natural selection acting through kin. To test this possibility we developed a new two-variable measure of inclusive fitness, which we term the extended genomic output or EGO. Using EGO, we estimate the inclusive fitness effect of mortality at different ages in a small hunter-gatherer population with a typical human mortality profile. EGO in this population predicts 90% of the variation in age-specific mortality. This result represents the first empirical measurement of inclusive fitness of a trait in any species. It shows that the pattern of human survival can largely be explained by variation in the inclusive fitness cost of mortality at different ages. More generally, our approach can be used to estimate the inclusive fitness of any trait or genotype from population data on birth dates and relatedness.     

Depression as a Risk Factor for Mortality in Individuals with Diabetes: A Meta-Analysis of Prospective Studies

Objective

To quantify the impact of depression measured by self-reports and depression measured by clinical interview on all-cause mortality in individuals with diabetes and to analyze the strength of both associations, the influence of covariates, and possible differences between studies assessing self-rated depressive symptoms and those using a clinical interview to measure depression as predictors of mortality.

Research Design and Methods

PUBMED and PsycINFO were searched up to July 2013 for prospective studies assessing depression, diabetes and mortality. The pooled hazard ratios were calculated using random-effects models.

Results

Sixteen studies met the inclusion criteria. After adjustment for demographic variables depression measured by self-reports was associated with an increased all-cause mortality risk (pooled HR = 2.56, 95% CI 1.89–3.47), and the mortality risk remained high after additional adjustment for diabetes complications (HR = 1.76, 95% CI 1.45–2.14,). Six studies reporting adjusted HRs for depression measured by clinical interviews supported the results of the other models (HR = 1.49, 95% CI 1.15–1.93).

Conclusions

Both depression measured by self-report and depression measured by clinical interview have an unfavorable impact on mortality in individuals with diabetes. The results, however, are limited by the heterogeneity of the primary studies. It remains unclear whether self-reports or clinical interviews for depression are the more precise predictor.     

Personalized Mortality Prediction Driven by Electronic Medical Data and a Patient Similarity Metric

BackgroundClinical outcome prediction normally employs static, one-size-fits-all models that perform well for the average patient but are sub-optimal for individual patients with unique characteristics. In the era of digital healthcare, it is feasible to dynamically personalize decision support by identifying and analyzing similar past patients, in a way that is analogous to personalized product recommendation in e-commerce. Our objectives were: 1) to prove that analyzing only similar patients leads to better outcome prediction performance than analyzing all available patients, and 2) to characterize the trade-off between training data size and the degree of similarity between the training data and the index patient for whom prediction is to be made.ConclusionsThe present study provides crucial empirical evidence for the promising potential of personalized data-driven decision support systems. With the increasing adoption of electronic medical record (EMR) systems, our novel medical data analytics contributes to meaningful use of EMR data.     

Leg orientation as a clinical sign for pusher syndrome

Background  

Effective control of (upright) body posture requires a proper representation of body orientation. Stroke patients with pusher syndrome were shown to suffer from severely disturbed perception of own body orientation. They experience their body as oriented 'upright' when actually tilted by nearly 20° to the ipsilesional side. Thus, it can be expected that postural control mechanisms are impaired accordingly in these patients. Our aim was to investigate pusher patients' spontaneous postural responses of the non-paretic leg and of the head during passive body tilt.     

Body Fineness Ratio as a Predictor of Maximum Prolonged-Swimming Speed in Coral Reef Fishes

The ability to sustain high swimming speeds is believed to be an important factor affecting resource acquisition in fishes. While we have gained insights into how fin morphology and motion influences swimming performance in coral reef fishes, the role of other traits, such as body shape, remains poorly understood. We explore the ability of two mechanistic models of the causal relationship between body fineness ratio and endurance swimming-performance to predict maximum prolonged-swimming speed (U_max) among 84 fish species from the Great Barrier Reef, Australia. A drag model, based on semi-empirical data on the drag of rigid, submerged bodies of revolution, was applied to species that employ pectoral-fin propulsion with a rigid body at U_max. An alternative model, based on the results of computer simulations of optimal shape in self-propelled undulating bodies, was applied to the species that swim by body-caudal-fin propulsion at U_max. For pectoral-fin swimmers, U_max increased with fineness, and the rate of increase decreased with fineness, as predicted by the drag model. While the mechanistic and statistical models of the relationship between fineness and U_max were very similar, the mechanistic (and statistical) model explained only a small fraction of the variance in U_max. For body-caudal-fin swimmers, we found a non-linear relationship between fineness and U_max, which was largely negative over most of the range of fineness. This pattern fails to support either predictions from the computational models or standard functional interpretations of body shape variation in fishes. Our results suggest that the widespread hypothesis that a more optimal fineness increases endurance-swimming performance via reduced drag should be limited to fishes that swim with rigid bodies.     

Predictive Power of a Body Shape Index for Development of Diabetes,Hypertension, and Dyslipidemia in Japanese Adults: A Retrospective Cohort Study

Background/Objectives

Recently, a body shape index (ABSI) was reported to predict all-cause mortality independently of body mass index (BMI) in Americans. This study aimed to evaluate whether ABSI is applicable to Japanese adults as a predictor for development of diabetes, hypertension, and dyslipidemia.

Subjects/Methods

We evaluated the predictive power of ABSI in a retrospective cohort study using annual health examination data from Chiba City Hall in Japan, for the period 2008 to 2012. Subjects included 37,581 without diabetes, 23,090 without hypertension, and 20,776 without dyslipidemia at baseline who were monitored for disease incidence for 4 years. We examined the associations of standardized ABSI, BMI, and waist circumference (WC) at baseline with disease incidence by logistic regression analyses. Furthermore, we conducted a case-matched study using the propensity score matching method.

Results

Elevated BMI, WC, and ABSI increased the risks of diabetes and dyslipidemia [BMI-diabetes: odds ratio (OR) = 1.26, 95% confidence interval (95%CI) = 1.20−1.32; BMI-dyslipidemia: OR = 1.15, 95%CI = 1.12−1.19; WC-diabetes: OR = 1.24, 95%CI = 1.18−1.31; WC-dyslipidemia: OR = 1.15, 95%CI = 1.11−1.19; ABSI-diabetes: OR = 1.06, 95%CI = 1.01−1.11; ABSI-dyslipidemia: OR = 1.04, 95%CI = 1.01−1.07]. Elevated BMI and WC, but not higher ABSI, also increased the risk of hypertension [BMI: OR = 1.32, 95%CI = 1.27−1.37; WC: OR = 1.22, 95%CI = 1.18−1.26; ABSI: OR = 1.00, 95%CI = 0.97−1.02]. Areas under the curve (AUCs) in regression models with ABSI were significantly smaller than in models with BMI or WC for all three diseases. In case-matched subgroups, the power of ABSI was weaker than that of BMI and WC for predicting the incidence of diabetes, hypertension, and dyslipidemia.

Conclusions

Compared with BMI or WC, ABSI was not a better predictor of diabetes, hypertension, and dyslipidemia in Japanese adults.     

Trunk implanted zinc-bentonite as a source of zinc for apple trees

Summary The feasibility of zinc supply to apples (Malus spp. var. Golden Delicious) by various Zn-bentonite preparations implanted in the trunk was studied. A preliminary experiment included four preparations and was conducted in one plantation in 1980. A larger scale experiment in 1981, tested Zn-bentonite (ZnB) and Zn-bentonite + ZnEDTA (ZnBEA) in four plantations in the south, center and north of Israel. Clay tablets were implanted in holes drilled in the tree trunk in April. The youngest, fully developed leaves on the new growth were sampled periodically and Zn content was determined.ZnB and ZnBEA implanted at the rate of 15 mg Zn/cm trunk circumference significantly increased Zn content above that of the control trees until mid-September. The ZnBEA preparation supported significantly higher leaf concentrations than the ZnB preparation. Peak concentrations in trees treated with the ZnBEA preparation were 75.8, 47.4, 38.4, and 23.7 ppm in the four plantations and occurred in May. The Zn concentration in the youngest leaves decreased during the season but there was evidence that in some cases Zn behaved as a phloem mobile element. Soil, climate and previous zinc treatments affected considerably the Zn concentration found in leaves in the four plantations making it impossible to identify a single critical concentration level.No damage to the trees was observed as a result of the drilling and implantation of the clay tablets. Clay analysis at the end of the season showed that about two-thirds of the Zn added to the trees was used. The amount of Zn supplied per tree in the implantation procedure was 80–90% lower than that supplied in the routine spraying operations.     

The Volume Ratio of Ground Glass Opacity in Early Lung CT Predicts Mortality in Acute Paraquat Poisoning

Background

Pulmonary injury is the main cause of death in acute paraquat (PQ) poisoning. However, whether quantitative lung computed tomography (CT) can be useful in predicting the outcome of PQ poisoning remains unknown. We aimed to identify early findings of quantitative lung CT as predictors of outcome in acute PQ poisoning.

Methods

Lung CT scanning (64-slide) and quantitative CT lesions were prospectively measured for patients after PQ intoxication within 5 days. The study outcome was mortality during 90 days follow-up. Survival curves were derived by the Kaplan-Meier method, and mortality risk factors were analyzed by the forward stepwise Cox regression analysis.

Results

Of 97 patients, 41 (42.3%) died. Among the eight different types of lung CT findings which appeared in the first 5-day of PQ intoxication, four ones discriminated between survivors and non-survivors including ground glass opacity (GGO), consolidation, pneumomediastinum and “no obvious lesion”. With a cutoff value of 10.8%, sensitivity of 85.4% and specificity of 89.3%, GGO volume ratio is better than adopted outcome indicators in predicting mortality, such as estimated amount of PQ ingestion, plasma or urine PQ concentration, acute physiology and chronic health evaluation (APACHE) II and sequential organ failure assessment (SOFA) scores. GGO volume ratios above 10.8% were associated with increased mortality (hazard ratio, 5.82; 95% confidence interval, 4.77-7.09; P < 0.001).

Conclusions

The volume ratio of GGO exceeding 10.8% is a novel, reliable and independent predictors of outcome in acute PQ poisoning.     

A Simple Insightful Approach to Investigating a Hospital Standardised Mortality Ratio: An Illustrative Case-Study

Background

Despite methodological concerns Hospital Standardised Mortality Ratios (HSMRs) are promoted as measures of performance. Hospitals that experience an increase in their HSMR are presented with a serious challenge but with little guidance on how to investigate this complex phenomenon. We illustrate a simple penetrating approach.

Methods

Retrospective analysis of routinely collected hospital admissions data comparing observed and expected deaths predicted by the Dr Foster Unit case mix adjustment method over three years (n = 74,860 admissions) in Shropshire and Telford NHS Trust Hospital (SaTH) constituting PRH (Princess Royal Hospital) and RSH (Royal Shrewsbury Hospital); whose HSMR increased from 99 in the year 2008/09 to 118 in the year 2009/10.

Results

The step up in HSMR was primarily located in PRH (109 to 130 vs. 105 to 118 RSH). Disentangling the HSMR by plotting run charts of observed and expected deaths showed that observed deaths were stable in RSH and PRH but expected deaths, especially at PRH, had fallen. The fall in expected deaths has two possible explanations–genuinely lower risk admissions or that the case-mix adjustment model is underestimating the risk of admissions perhaps because of inadequate clinical coding. There was no evidence that the case-mix profile of admissions had changed but there was considerable evidence that clinical coding process at PRH was producing a lower depth of coding resulting in lower expected mortality.

Conclusion

Knowing whether the change (increase/decrease) in HSMR is driven by the numerator or the denominator is a crucial pivotal first step in understanding a given HSMR and so such information should be an integral part of the HSMR reporting methodology.     

Total Body Adiposity,Triglycerides, and Leg Fat are Independent Risk Factors for Diabetic Peripheral Neuropathy in Chinese Patients with type 2 Diabetes Mellitus

Objective: To evaluate the risk factors associated with diabetic peripheral neuropathy (DPN) in Chinese patients with type 2 diabetes mellitus (T2DM).Methods: Between January 2014 and December 2017, 107 participants who had obesity with T2DM and 349 participants who had normal weight with T2DM, matched for age, sex, and duration of diabetes, were recruited. The clinical and biochemical parameters were measured in each patient. DPN was diagnosed based on neuropathy symptom score and neuropathy deficit score. Motor and sensory nerve conduction velocities were measured by electromyography. Body fat mass was estimated by dual-energy X-ray absorptiometry, while hepatic steatosis was evaluated by ultrasonography.Results: The group with obesity had a significant higher prevalence of DPN (66.62%) than that (46.99%) of the group with normal weight. Compared to the patients with normal weight, the sural sensory nerve in the right lower limbs of the patients with obesity was more susceptible to damage. Hypertriglyceridemia in the patients with obesity was a significant independent risk factor for DPN (odds ratio &lsqb;OR], 3.90 &lsqb;95% confidence interval (CI), 1.01 to 15.02]; P = .04), while the duration of diabetes (OR, 1.33 &lsqb;95% CI, 1.07 to 1.65]; P<.01) and leg subcutaneous fat mass (OR, 0.72 &lsqb;95% CI, 0.57 to 0.90]; P<.01) in the patients with normal weight were independent risk factors for DPN. The presence of obesity alone in patients with T2DM could predict high DPN risk (OR, 3.09 &lsqb;95% CI, 1.11 to 8.65]; P = .04).Conclusion: Reducing total body adiposity and triglyceride levels, as well as avoiding leg subcutaneous fat atrophy, could be new prevention strategies for DPN in Chinese patients with T2DM.Abbreviations: ALB = albumin; ALT = alanine transaminase; AST = aspartate transaminase; AUC = area under the curve; AUCc-p/AUCglu = AUC of C-peptide/AUC of glucose; BMI = body mass index; BP = blood pressure; CI = confidence interval; Cr = creatinine; DBP = diastolic blood pressure; DPN = diabetic peripheral neuropathy; FC-P = fasting C-peptide; FPG = fasting plasma glucose; FFA = free fatty acid; γ-GGT = γ-glutamyl transferase; HbA1c = glycated hemoglobin A1c; HDL-C = high-density-lipoprotein cholesterol; ISI = insulin sensitivity index; ISSI-2 = insulin secretion-sensitivity index-2; LDL-C = low-density-lipoprotein cholesterol; MNCS = motor nerve conduction velocity; OGTT = oral glucose tolerance test; PG = plasma glucose; SAT = subcutaneous adipose tissue; SBP = systolic blood pressure; SNCS = sensory nerve conduction velocity; T2DM = type 2 diabetes mellitus; TC = total cholesterol; TG = triglyceride; UA = uric acid; VAT = visceral adipose tissue; WC = waist circumference     

Evaluation of an Integrated Framework for Biodiversity with a New Metric for Functional Dispersion

Growing interest in understanding ecological patterns from phylogenetic and functional perspectives has driven the development of metrics that capture variation in evolutionary histories or ecological functions of species. Recently, an integrated framework based on Hill numbers was developed that measures three dimensions of biodiversity based on abundance, phylogeny and function of species. This framework is highly flexible, allowing comparison of those diversity dimensions, including different aspects of a single dimension and their integration into a single measure. The behavior of those metrics with regard to variation in data structure has not been explored in detail, yet is critical for ensuring an appropriate match between the concept and its measurement. We evaluated how each metric responds to particular data structures and developed a new metric for functional biodiversity. The phylogenetic metric is sensitive to variation in the topology of phylogenetic trees, including variation in the relative lengths of basal, internal and terminal branches. In contrast, the functional metric exhibited multiple shortcomings: (1) species that are functionally redundant contribute nothing to functional diversity and (2) a single highly distinct species causes functional diversity to approach the minimum possible value. We introduced an alternative, improved metric based on functional dispersion that solves both of these problems. In addition, the new metric exhibited more desirable behavior when based on multiple traits.     

Volume of Distribution of Tritiated Water as a Measure of Total Body Water in Suckling Pigs

The total body water (TBW) was determined, using a method with tritiated water. One litter of 11 piglets was used for the experiment comprising repeated deterimnations during the first 6 weeks of life. The mean TBW defined as the 1½ hours distribution volume of tritium after intraperitoneal injection was found to decrease gradually from 80.1 % of the body-weight at 1 day of age to 72.7 % at 19 days of age and then remained fairly constant. A simple distillation technique for recovering the water from plasma was used. Small variations between pigs of the same age were found. The variations in individual pigs from time to time and the results of duplicate determinations seem reasonable.     

Opposite Contributions of Trunk and Leg Fat Mass with Plasma Lipase Activities: The Hoorn Study

Objective: Lipoprotein lipase (LPL) and hepatic lipase (HL) are essential in hydrolysis of triglyceride‐rich lipoproteins. LPL activity is negatively, whereas HL activity is positively, associated with total body fat. We determined the associations of trunk and leg fat mass with plasma LPL and HL activities in a cross‐sectional study. Research Methods and Procedures: LPL and HL activities were determined in post‐heparin plasma in a sample of 197 men and 209 women, 60 to 87 years of age. A total body DXA scan was performed to determine trunk and leg fat mass. Results: In women, but not in men, trunk fat mass was negatively associated with LPL activity, whereas leg fat mass was positively associated, after mutual adjustment and adjustment for age. Standardized βs (95% confidence interval) for trunk and leg fat mass were ?0.24 (?0.41; ?0.08) and 0.14 (?0.02; 0.31), respectively (interaction by sex, p = 0.03). Larger trunk fat mass was associated with higher HL activity in men [0.48 (0.28; 0.68)] and women [0.40 (0.24; 0.56)]. A negative association of leg fat mass and HL activity was observed in men, although not statistically significant [?0.13 (?0.33; 0.06)], and in women [?0.28 (?0.38; ?0.18)]. Discussion: Abdominal fat is associated with unfavorable and femoral fat with favorable LPL and HL activities in plasma.     

Comprehensive Bee Pathogen Screening in Belgium Reveals Crithidia mellificae as a New Contributory Factor to Winter Mortality

Since the last decade, unusually high honey bee colony losses have been reported mainly in North-America and Europe. Here, we report on a comprehensive bee pathogen screening in Belgium covering 363 bee colonies that were screened for 18 known disease-causing pathogens and correlate their incidence in summer with subsequent winter mortality. Our analyses demonstrate that, in addition to Varroa destructor, the presence of the trypanosomatid parasite Crithidia mellificae and the microsporidian parasite Nosema ceranae in summer are also predictive markers of winter mortality, with a negative synergy being observed between the two in terms of their effects on colony mortality. Furthermore, we document the first occurrence of a parasitizing phorid fly in Europe, identify a new fourth strain of Lake Sinai Virus (LSV), and confirm the presence of other little reported pathogens such as Apicystis bombi, Aphid Lethal Paralysis Virus (ALPV), Spiroplasma apis, Spiroplasma melliferum and Varroa destructor Macula-like Virus (VdMLV). Finally, we provide evidence that ALPV and VdMLV replicate in honey bees and show that viruses of the LSV complex and Black Queen Cell Virus tend to non-randomly co-occur together. We also noticed a significant correlation between the number of pathogen species and colony losses. Overall, our results contribute significantly to our understanding of honey bee diseases and the likely causes of their current decline in Europe.