Associations of bioelectrical impedance and anthropometric variables among populations and within the full spectrum of malnutrition.

OBJECTIVES: The aim of this study was to evaluate body composition variability assessed by bioimpedance in relation to nutritional status assessed by anthropometry in children and adolescents living in countries characterized by contrasting nutritional conditions. METHODS: The sample was comprised of 8614 children (4245 males; 4369 females), aged 3 to 19 years, from Nepal (477 children), Uganda (488 children and adolescents), UK (297 children and adolescents) and US (7352 children and adolescents). Height-for-age (HAZ) and body mass index-for-age (BAZ) z-scores were calculated according to WHO growth references. Specific bioelectrical impedance vector analysis (BIVA) was used to evaluate body composition variability. In each population sample, the relationship of HAZ and BAZ with bioelectrical outcomes was analysed by confidence ellipses and cubic spline regression, controlling for sex and age. RESULTS: The participants from Uganda and Nepal were more affected by undernutrition, and those from the US and UK by obesity. In all groups, phase angle and specific vector length were weakly associated with HAZ, with null or opposite relationships in the different samples, whereas they were positively associated with BAZ. The stronger association was between vector length, indicative of the relative content of fat mass, and BAZ in the UK and US samples. Confidence ellipses showed that the relationships are more strongly related to phase angle in Nepalese and Ugandan samples. CONCLUSIONS: Bioelectrical values were more strongly associated with BAZ than HAZ values in all population samples. Variability was more related to markers of muscle mass in Ugandan and Nepalese samples and to indicators of fat mass in UK and US samples. Specific BIVA can give information on the variability of body composition in malnourished individuals.

Food drugs as drivers of therapeutic knowledge and the role of chemosensory qualities.

ETHNOPHARMACOLOGICAL RELEVANCE: Chemosensory qualities of botanical drugs are important cues for anticipating physiologic consequences. Whether a botanical drug is used for both, food and medicine, or only as medicine depends on taste preferences, nutritional content, cultural background, and the individual and overall epidemiological context. MATERIAL AND METHODS: We subjected 540 botanical drugs described in De Materia Medica having at least one oral medical application to a tasting panel. The 540 drugs were grouped into those only used for medicine (388) and those also used for food (152). The associations with chemosensory qualities and therapeutic indications were compared across the two groups. We considered 22 experimentally assessed chemosensory qualities and 39 categories of therapeutic use groups. We wanted to know, 1): which chemosensory qualities increase the probability of an orally applied botanical drug to be also used for food ? 2): which chemosensory qualities augment the probability of an orally applied botanical drug to be only used for medicine? and 3): whether there are differences in therapeutic indications between orally applied botanical drugs also used for food (food drugs) and botanical drugs applied exclusively for medicinal purposes (non-food drugs) and, if yes, how the differences can be explained. RESULTS: Chemosensory qualities augmenting the probability of an orally applied botanical drug to be also used for food were sweet, starchy, salty, burning/hot, fruity, nutty, and cooling. Therapeutics used for diarrhoea, as libido modulators, purgatives, laxatives, for expelling parasites, breast and lactation and increasing diuresis, were preferentially sourced from food drugs while drugs used for liver and jaundice, vaginal discharge and humoral management showed significant negative associations with food dugs in ancient Greek-Roman materia medica. CONCLUSION: Therapeutics used for ailments of body organs involved in the digestion of food and the excretion of waste products showed a tendency to be sourced from food drugs. Arguably, the daily consumption of food offered the possibility for observing post-prandial physiologic and pharmacologic effects which led to a high therapeutic versatility of food drugs and the possibility to understand benefits of taste and flavour qualities. The difference in chemosensory qualities between food drugs and non-food drugs is demarcating the organoleptic requirements of food rather than that of medicine.

Transfer Learning in Multiple Hypothesis Testing.

In this investigation, a synthesis of Convolutional Neural Networks (CNNs) and Bayesian inference is presented, leading to a novel approach to the problem of Multiple Hypothesis Testing (MHT). Diverging from traditional paradigms, this study introduces a sequence-based uncalibrated Bayes factor approach to test many hypotheses using the same family of sampling parametric models. A two-step methodology is employed: initially, a learning phase is conducted utilizing simulated datasets encompassing a wide spectrum of null and alternative hypotheses, followed by a transfer phase applying this fitted model to real-world experimental sequences. The outcome is a CNN model capable of navigating the complex domain of MHT with improved precision over traditional methods, also demonstrating robustness under varying conditions, including the number of true nulls and dependencies between tests. Although indications of empirical evaluations are presented and show that the methodology will prove useful, more work is required to provide a full evaluation from a theoretical perspective. The potential of this innovative approach is further illustrated within the critical domain of genomics. Although formal proof of the consistency of the model remains elusive due to the inherent complexity of the algorithms, this paper also provides some theoretical insights and advocates for continued exploration of this methodology.

Model uncertainty quantification in Cox regression.

We consider covariate selection and the ensuing model uncertainty aspects in the context of Cox regression. The perspective we take is probabilistic, and we handle it within a Bayesian framework. One of the critical elements in variable/model selection is choosing a suitable prior for model parameters. Here, we derive the so-called conventional prior approach and propose a comprehensive implementation that results in an automatic procedure. Our simulation studies and real applications show improvements over existing literature. For the sake of reproducibility but also for its intrinsic interest for practitioners, a web application requiring minimum statistical knowledge implements the proposed approach.

Usability of classic and specific bioelectrical impedance vector analysis in measuring body composition of children.

In this study, we aimed to analyse the relationship between body composition and bioelectrical variables in children and adolescents. The sample was composed of 6801 individuals (4035 males; 2766 females) aged 8-20 years included in the National Health and Nutrition Examination Survey (NHANES) years 1999-2004. Classic and specific bioelectrical impedance vector analysis (BIVA) were applied and compared with dual-energy X-ray absorptiometry (DXA) for the evaluation of fat mass (FM) and fat-free mass (FFM), and bioimpedance spectroscopy (BIS) for the evaluation of intra-cellular water (ICW), extra-cellular water (ECW), and total body water (TBW). Fat-free mass index (FFMI) was calculated. Spearman's correlation, regression, and depth-depth analyses were applied. The evaluation of body composition with BIVA agreed well with that of DXA or BIS, independently of sex, age, and ethnicity: classic BIVA was mostly sensitive to differences in TBW, ECW/ICW, whereas specific BIVA to differences in %FM, FFMI, and ECW/ICW. The depth-depth analysis confirmed the associations of classic BIVA (coeff. 0.500, p < 0.001), and specific BIVA (coeff. 0.512, p < 0.001), also considering the significant effect of age (p < 0.001). In classic BIVA the association was slightly stronger in females (by 0.03, p = 0.042) and among Blacks (0.06, p = 0.002), whereas in specific BIVA it was stronger by 0.06 (p < 0.001) in females and similar among ethnic groups. The combined use of the two BIVA approaches represents a valuable tool for complete evaluation of body composition in growth studies, for the prevention and monitoring of malnutrition, and the monitoring of the performance in young athletes.

Segmental body composition estimated by specific BIVA and dual-energy X-ray absorptiometry.

AIMS: The aim of this study was to analyse the association between specific bioelectric impedance vector analysis (BIVA) and dual-energy X-ray absorptiometry (DXA) to assess segmental body composition using DXA as the reference technique. METHODS: The sample comprised 50 young active students who practised or played different sports (25 men, age: 24.37 ± 4.79 y; 25 women, age: 24.32 ± 4.43 y) from the National Institute of Physical Education of Catalonia (INEFC). Anthropometric data (height, weight, arm, waist, and calf circumferences) and bioelectrical measurements (R, ohm; Xc, ohm) were recorded. Body composition was analysed with specific BIVA. DXA was used as the reference method to assess body composition of the whole-body, the trunk, and the limbs. The percentage of fat mass (%FMDXA) and fat-free mass index (FFMIDXA = FFM/length2) were calculated. The agreement between specific BIVA and DXA was evaluated by a depth-depth analysis, two-way ANOVA, and Pearson's correlations. RESULTS: The depth-depth analysis showed a good agreement between DXA and BIVA (F = 14.89, p < 0.001) in both sexes and all body segments. Specific vector length (Zsp; i.e. indicative of %FM) was correlated with %FMDXA in the whole body and all body segments, and the phase angle was correlated with FFMIDXA, with he trunk in women as the only exception. Specific BIVA demonstrated to balance the effect of body size on bioelectrical measurements in both whole and segmental approaches. CONCLUSIONS: Segmental specific BIVA and DXA provided a consistent evaluation of body composition in both sexes, of the whole body and each body segment. The indices %FM and FFMI obtained with DXA were correlated to vector length and phase angle in each segment, respectively. Specific BIVA represents a promising technique for monitoring segmental body composition changes in sport science and clinical applications.

A Dirichlet Process Prior Approach for Covariate Selection.

The variable selection problem in general, and specifically for the ordinary linear regression model, is considered in the setup in which the number of covariates is large enough to prevent the exploration of all possible models. In this context, Gibbs-sampling is needed to perform stochastic model exploration to estimate, for instance, the model inclusion probability. We show that under a Bayesian non-parametric prior model for analyzing Gibbs-sampling output, the usual empirical estimator is just the asymptotic version of the expected posterior inclusion probability given the simulation output from Gibbs-sampling. Other posterior conditional estimators of inclusion probabilities can also be considered as related to the latent probabilities distributions on the model space which can be sampled given the observed Gibbs-sampling output. This paper will also compare, in this large model space setup the conventional prior approach against the non-local prior approach used to define the Bayes Factors for model selection. The approach is exposed along with simulation samples and also an application of modeling the Travel and Tourism factors all over the world.

The relationship among the age at menarche, anthropometric characteristics, and socio-economic factors in Bengali girls from Kolkata, India.

OBJECTIVES: The aim of the study was to measure the causal effect of selected socio-economic factors and anthropometrical characteristics on the menarche occurrence. METHODS: The sample consisted of 2195 Bengali girls (aged 7-21) from middle-class families, from Kolkata city, India. The age at menarche was recorded from the retrospective data and status quo method. The causal effect of anthropometric and socio-economic variables on menarche occurrence was estimated by the nonparametrical analysis of survival probability (survival random forest). RESULTS: In the examined cohort menarche occurred, on average, at 11.8 years of age. The probability of menarche occurrence amplified with the increasing values of factors such as body mass index, height-for-age z-scores, number of family members, household rooms, and toilets, but decreased when expenditures increased. The relation maintained a similar pattern of causal effect with girls' age. CONCLUSIONS: A complex pattern of relationship among sexual development, physique, and socio-economic characteristics was defined. The tendency toward early menarche, along with the observed causal relationships indicate that the analyzed sample is nearing the characteristics and standards of living noted in other middle and even high-income countries in the world.

Nutritional status of Ugandan school-children: The effect of age imprecision.

OBJECTIVES: To analyze the nutritional status of Ugandan school-children in a cross-sectional and longitudinal perspective, considering the effect of age imprecision. MATERIALS AND METHODS: Anthropometric measurements of 831 school-children (381 males and 450 females) were analyzed. A subsample of 246 children was measured in July 2014 and 2015. Stunting (based on height-for-age Z-scores), underweight (weight-for-age), and thinness (body mass index-for-age) prevalence were calculated. Three different ages were used: declared (from schools registers), attributed (based on multiple information sources), and bootstrap (from 10,000 replicates). Significant differences among malnutrition prevalence calculated with different ages and in different groups were assessed by means of bootstrap analysis. Longitudinal analysis was conducted using a paired t test. RESULTS: The mean prevalence of malnutrition calculated with declared, attributed, or bootstrap ages were very similar: stunting (11.9-12.7); underweight (5.4-5.9); thinness (3.3-3.7); and obesity (0.7). Undernutrition was more prevalent among older children, while obesity was mostly associated with young age. Obesity was equally distributed among sexes, while undernutrition was more prevalent among females of up to 10 years of age and males above 10 years. The longitudinal analysis indicated a reduction in underweight and thinness, and an increase in stunting, especially among older children. DISCUSSION: Age imprecision did not significantly affect malnutrition estimates. Despite the decline in the prevalence of thinness and underweight observed over a 1-year period, undernutrition persists, with an observed rise in stunting. On the other hand, obesity is starting to appear. Public health efforts are required to eliminate stunting and address the emerging burden of obesity.

Correction: Energy expenditure in caving.

[This corrects the article DOI: 10.1371/journal.pone.0170853.].

A Markov chain representation of the multiple testing problem.

The problem of multiple hypothesis testing can be represented as a Markov process where a new alternative hypothesis is accepted in accordance with its relative evidence to the currently accepted one. This virtual and not formally observed process provides the most probable set of non null hypotheses given the data; it plays the same role as Markov Chain Monte Carlo in approximating a posterior distribution. To apply this representation and obtain the posterior probabilities over all alternative hypotheses, it is enough to have, for each test, barely defined Bayes Factors, e.g. Bayes Factors obtained up to an unknown constant. Such Bayes Factors may either arise from using default and improper priors or from calibrating p-values with respect to their corresponding Bayes Factor lower bound. Both sources of evidence are used to form a Markov transition kernel on the space of hypotheses. The approach leads to easy interpretable results and involves very simple formulas suitable to analyze large datasets as those arising from gene expression data (microarray or RNA-seq experiments).

P-value calibration in multiple hypotheses testing.

As p-values are the most common measures of evidence against a hypothesis, their calibration with respect to null hypothesis conditional probability is important in order to match frequentist unconditional inference with the Bayesian ones. The Selke, Bayarri and Berger calibration is one of the most popular attempts to obtain such a calibration. This relies on the theoretical sampling null distribution of p-values, which is the well-known Uniform(0,1), but arising only for specific sampling models. We generalize this calibration by considering a sampling null distribution estimated from the data. It is possible to obtain such an empirical null distribution, for instance, in the context of multiple testing in which many p-values come from the null model. Such a context is purely instrumental for the purposes of p-value calibration, and multiple testing still needs to be considered with appropriate techniques. The new calibration proposed here still remains a simple analytic formula like the original one under the Uniform(0,1) and basically provides a stronger interpretation framework for the widely used p-value. Copyright © 2017 John Wiley & Sons, Ltd.

Energy expenditure in caving.

The aim of this study was to determine the energy expenditure of a group of cavers of both genders and different ages and experience during a 10 hour subterranean exploration, using portable metabolimeters. The impact of caving activity on body composition and hydration were also assessed through bioelectrical impedance, and nutritional habits of cavers surveyed. During cave activity, measured total energy expenditure (TEE) was in the range 225-287 kcal/h for women-men (MET = 4.1), respectively; subjects had an energy intake from food in the range 1000-1200 kcal, thus inadequate to restore lost calories. Bayesian statistical analysis estimated the effect of predictive variables on TEE, revealing that experienced subjects had a 5% lower TEE than the less skilled ones and that women required a comparatively larger energy expenditure than men to perform the same task. BIVA (bioelectrical impedance vector analysis) showed that subjects were within the range of normal hydration before and after cave activity, but bioelectrical changes indicated a reduction of extracellular water in men, which might result in hypo-osmolal dehydration in the case of prolonged underground exercise. All these facts should be considered when planning cave explorations, preparing training programs for subjects practising caving, and optimizing a diet for cavers. Further, information gathered through this study could be of value to reduce accidents in caves related to increase in fatigue.

Reverse ethnopharmacology and drug discovery.

ETHNOPHARMACOLOGICAL RELEVANCE: Ethnopharmacological investigations of traditional medicines have made significant contributions to plant-derived drugs, as well as the advancement of pharmacology. Drug discovery from medicinal flora is more complex than generally acknowledged because plants are applied for different therapeutic indications within and across cultures. Therefore we propose the concept of "reverse ethnopharmacology" and compare biomedical uses of plant taxa with their ethnomedicinal and popular uses and test the effect of these on the probability of finding biomedical and specifically anticancer drugs. MATERIALS AND METHODS: For this analysis we use data on taxonomy and medical indications of plant derived biomedical drugs, clinical trial, and preclinical trial drug candidates published by Zhu et al. (2011) and compare their therapeutic indications with their ethnomedicinal and popular uses as reported in the NAPRALERT® database. Specifically, we test for increase or decrease of the probability of finding anticancer drugs based on ethnomedicinal and popular reports with Bayesian logistic regression analyses. RESULTS: Anticancer therapy resulted as the most frequent biomedicinal indication of the therapeutics derived from the 225 drug producing higher plant taxa and showed an association with ethnomedicinal and popular uses in women's medicine, which was also the most important popular use-category. Popular remedies for dysmenorrhoea, and uses as emmenagogues, abortifacients and contraceptives showed a positive effect on the probability of finding anticancer drugs. Another positive effect on the probability of discovering anticancer therapeutics was estimated for popular herbal drugs associated with the therapy of viral and bacterial infections, while the highest effect was found for popular remedies used to treat cancer symptoms. However, this latter effect seems to be influenced by the feedback loop and divulgence of biomedical knowledge on the popular level. CONCLUSION: We introduce the concept of reverse ethnopharmacology and show that it is possible to estimate the probability of finding biomedical drugs based on ethnomedicinal uses. The detected associations confirm the classical ethnopharmacological approach where a popular remedy for disease category X results in a biomedical drug for disease category X but does also point out the existence of cross-over relationships where popular remedies for disease category X result in biomedical therapeutics for disease category Y (Zhu et al., 2011).

The taste of heat: How humoral qualities act as a cultural filter for chemosensory properties guiding herbal medicine.

ETHNOPHARMACOLOGICAL RELEVANCE: Organoleptic properties, and more specifically chemosensory cues, have been shown to guide therapeutic applications of medicinal plants. Humoral qualities, on the other hand, are widely believed to be an abstract concept, mainly applied post hoc to validate therapy. However, the nexus between humoral qualities, chemosensory properties, and medicinal plant uses has never been systematically assessed. AIM OF THE STUDY: To systematically analyse the correlations between chemosensory properties, humoral qualities, and medicinal uses of selected botanical drugs. METHODS: The issue was approached experimentally via an organoleptic testing panel, consisting of Zoque healers in Chiapas, Mexico. The healers smelled and tasted 71 selected herbal drugs and subsequently commented on their humoral qualities and therapeutic uses. The resulting dataset is analysed for correlations between these variables using Bayesian statistics. Qualitative data on the characteristics and role of the hot-cold dichotomy complement the quantitative analysis, facilitating meaningful interpretation. RESULTS AND DISCUSSION: The results reproduce and extend the findings of previous studies, which established specific correlations between chemosensory cues and nosological units. The key predictors of drugs' therapeutic uses, however, are their humoral qualities, which are themselves conditioned by taste and smell. These findings appear to be valid for drug samples known to the participants as well as for unfamiliar samples. Thus, this study establishes the role of the hot-cold dichotomy as an important cultural filter connecting organoleptic properties and therapeutic uses of herbal drugs. CONCLUSIONS: There is considerable cross-cultural consensus in Mesoamerica for the specific correlations described in this study. Given the continued pervasiveness of the hot-cold dichotomy, humoral qualities and the underlying organoleptic properties ought to be increasingly considered in the design of pharmaceutical products as well as public health strategies. Such culturally appropriate adjustments may considerably improve the perceived quality and effectiveness of healthcare.

Physical Capacity and Energy Expenditure of Cavers.

Caves are an extreme environment for humans because of the high humidity, mud, darkness, and slippery conditions. Explorations can last many hours or even days, and require extensive climbing and ropework. Very little is known about the physical capacity of cavers and their energy expenditure (EE) during caving. The physical capacity of 17 (7 females) expert cavers (age 43.9 ± 7.3 years) was assessed during an incremental cycle-ergometer test (IET) with gas exchange analysis. Moreover, a wearable metabolic band (Armband Fit Core) was used to estimate their EE during caving. In terms of physical capacity, the IET showed that cavers had a maximum oxygen uptake (VO2max) of 2,248.7 ± 657.8 ml·min-1 (i.e., 32.4 ± 6.4 ml·kg-1·min-1), while anaerobic threshold (AT) occurred on average at 74.5% of VO2max. Results from caving sessions provided an average time spent in cave of 9.4 ± 1.2 h while the average EE was 268.8 ± 54.8 kcal·h-1, which corresponded to about 40% of VO2max measured during IET. A mean distance of 10.6 ± 2.2 km was covered by subjects. Data from the present investigation provide evidence that cavers have a level of aerobic physical capacity only slightly higher than that of sedentary people, thereby suggesting that a high aerobic fitness is not needed by cavers. Moreover, during caving the EE was on average well below the level of AT. However, in absolute terms, the total EE was elevated (i.e., 2,672.3 ± 576 kcal in total) due to the long time spent in caving.

The asthma-anxiety connection.

BACKGROUND: The literature reports a significant association between various mental disorders and asthma, in particular depression and/or anxiety, with some more robust data regarding anxiety disorders. However, the nature of this association remains largely unclear. OBJECTIVES: (1) To test the hypothesis of a specific association of anxiety and depressive disorder (according to the DSM-IV) with asthma and (2) to test the bidirectional hypothesis of causality between asthma and psychiatric disorders. METHODS: Ninety-six adults were compared with 96 control subjects matched according to main socio-demographic variables (i.e., gender, age, marital status, cohabiting/non-cohabiting, and BMI). Subjects with asthma were divided according to GINA and ACT classifications. All subjects underwent Structured Clinical Interviews for DSM-IV Axis I (SCID-I) diagnosis. RESULTS: Significant association between asthma and lifetime anxiety disorders emerged (OR 3.03; p = 0.003); no significant association with other psychiatric diagnosis emerged. Moreover, lifetime and current anxiety were associated with asthma severity levels (p < 0.01 and p = 0.001 based on age). Asthma preceded anxiety in 48% of cases; in 52% of cases, anxiety preceded asthma, without significant group differences. The risk of asthma, particularly of severe, uncontrolled forms (p < 0.01), resulted higher in lifetime anxiety disorder patients (p = 0.003 and p = 0.001 based on age at onset). Current anxiety increased the risk of asthma, and that of an uncontrolled form (p < 0.05). Asthma increased the risk of lifetime anxiety disorders (p = 0.002 and p = 0.018 using ages). Intermittent asthma increased the risk of lifetime and current anxiety disorders (p < 0.01). CONCLUSIONS: Anxiety disorders, in particular Lifetime Anxiety Disorders, represent the only psychiatric disorder significantly associated with asthma, with a possible bidirectional, anxiety-asthma relationship, each of which can be caused or result from the other.

Birth registration and child undernutrition in sub-Saharan Africa.

OBJECTIVE: In many countries of the world millions of people are not registered at birth. However, in order to assess children's nutritional status it is necessary to have an exact knowledge of their age. In the present paper we discuss the effects of insufficient or imprecise age data on estimates of undernutrition prevalence. DESIGN: Birth registration rates and levels of stunting, underweight and wasting were retrieved from Multiple Indicator Cluster Surveys and Demographic and Health Surveys of thirty-seven sub-Saharan African countries, considering the subdivision in wealth quintiles. The composition of the cross-sectional sample used for nutritional evaluation was analysed using a permutation test. Logistic regression was applied to analyse the relationship between birth registration and undernutrition. The 95 % probability intervals and Student's t test were used to evaluate the effect of age bias and error. RESULTS: Heterogeneous sampling designs were detected among countries, with different percentages of children selected for anthropometry. Further, registered children were slightly more represented within samples used for nutritional analysis than in the total sample. A negative relationship between birth registration and undernutrition was recognized, with registered children showing a better nutritional status than unregistered ones, even within each wealth quintile. The over- or underestimation of undernutrition in the case of systematic over- or underestimation of age, respectively, the latter being more probable, was quantified up to 28 %. Age imprecision was shown to slightly overestimate undernutrition. CONCLUSIONS: Selection bias towards registered children and underestimation of children's age can lead to an underestimation of the prevalence of undernutrition.