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Anthropometric data indicate that the human phenotype is changing. Today's adult is greater in stature, body mass and fat mass. Accurate measurement of body composition is necessary to maintain surveillance of obesity within the population and to evaluate associated interventions. The aim of the present study was to construct and validate generalised equations for percentage body fat (%BF) prediction from anthropometry in 1136 adult men and women. Reference values for %BF were obtained using dual-energy X-ray absorptiometry. Skinfold thickness (SF) at ten sites and girth (G) at seven sites were measured on 736 men and women aged 18–81 years (%BF 5·1–56·8 %). Quantile regression was employed to construct prediction equations from age and log-transformed SF and G measures. These equations were then cross-validated on a cohort of 400 subjects of similar age and fatness. The following generalised equations were found to most accurately predict %BF:
$Men:\,(age\times 0\cdot 1) + (logtricepsSF\times 7\cdot 6) + (logmidaxillaSF\times 8\cdot 8) + (logsuprspinaleSF\times 11\cdot 9) - 11\cdot 3$
(standard error of the estimate: 2·5 %, 95 % limits of agreement: − 4·8, +4·9)
$Women:\,(age\times 0\cdot 1) + (logabdominalG\times 39\cdot 4) + (logmidaxillaSF\times 4\cdot 9) + (logbicepsSF\times 11\cdot 0) + (logmedialcalfSF\times 9\cdot 1) - 73\cdot 5$
(standard error of the estimate: 3·0 %, 95 % limits of agreement: − 5·7, + 5·9) These generalised anthropometric equations accurately predict %BF and are suitable for the measurement of %BF in adult men and women of varying levels of fatness across the lifespan.
This paper is concerned with a stochastic model for the spread of an epidemic with a contact tracing scheme, in which diagnosed individuals may name some of their infectious contacts, who are then removed if they have not been already. Traced individuals may or may not also be asked to name their own contacts. The epidemic is studied by considering an approximating, modified birth-death process with intersibling dependencies, for which a threshold parameter and expressions from which extinction probabilities may be calculated are derived. When all individuals can name their contacts, it is shown that this threshold parameter depends on the infectious period distribution only through its mean. Numerical studies show that the infectious period distribution choice can have a material effect on the threshold behaviour of an epidemic, while the dependencies help reduce spread.
This paper is concerned with the definition and calculation of containment probabilities for emerging disease epidemics. A general multitype branching process is used to model an emerging infectious disease in a population of households. It is shown that the containment probability satisfies a certain fixed point equation which has a unique solution under certain conditions; the case of multiple solutions is also described. The extinction probability of the branching process is shown to be a special case of the containment probability. It is shown that Laplace transform ordering of the severity distributions of households in different epidemics yields an ordering on the containment probabilities. The results are illustrated with both standard epidemic models and a specific model for an emerging strain of influenza.
Background: Subjective Units of Distress Scale (SUDS) ratings are commonly used during exposure tasks in cognitive behavioral treatment (CBT) for anxiety. Aims: The present study examined patterns and predictors of SUDS in a sample of anxiety-disordered youth. Method: Youth (N = 99) aged 7 to 14 (M = 10.4, SD = 1.8) were treated with CBT for social phobia (SP), generalized anxiety disorder (GAD), and/or separation anxiety disorder (SAD). Analyses were conducted using hierarchical linear modeling. Results: Child's peak SUDS and magnitude of change in SUDS significantly increased between sessions. Higher child self-reported pretreatment total Multidimensional Anxiety Scale for Children (MASC) score predicted greater change in SUDS within the first exposure session. Primary GAD diagnosis predicted less increase in change in SUDS between sessions. Conclusions: Results suggest that higher pretreatment total MASC scores are associated with increased first exposure within-session habituation. Additionally, youth with a principal diagnosis of GAD experienced less between-session habituation, perhaps because they may have required more imaginal than in-vivo exposures.
We consider a stochastic model for the spread of an SEIR (susceptible → exposed → infective → removed) epidemic among a population of individuals partitioned into households. The model incorporates both vaccination and isolation in response to the detection of cases. When the infectious period is exponential, we derive an explicit formula for a threshold parameter, and analytic results that enable computation of the probability of the epidemic taking off. These quantities are found to be independent of the exposure period distribution. An approximation for the expected final size of an epidemic that takes off is obtained, evaluated numerically, and found to be reasonably accurate in large populations. When the infectious period is not exponential, but has an increasing hazard rate, we obtain stochastic comparison results in the case where the exposure period is fixed. Our main result shows that as the exposure period increases, both the severity of the epidemic in a single household and the threshold parameter decrease, under certain assumptions concerning isolation. Corresponding results for infectious periods with decreasing hazard rates are also derived.
Experimental wet chemical approaches have been demonstrated in the synthesis of a new chainlike (C60-Fe-C60-Fe)n complex. This structure has been proposed based on 13C solid-state nuclear magnetic resonance, electron paramagnetic resonance, high-resolution transmission electron microscopy, energy-dispersive spectroscopy, and X-ray diffraction. Furthermore, this structure has been shown to have unique binding sites for dihydrogen molecules with the technique of temperature-programmed desorption. The new adsorption sites have binding energies that are stronger than that observed for hydrogen physisorbed on planar graphite, but significantly weaker than a chemical C-H bond. Volumetric measurements at 77 K and 2 bar show a hydrogen adsorption capacity of 0.5 wt%. Interestingly, the BET surface area is ∼31 m2/g after degassing, which is approximately an order of magnitude less than expected given the measured experimental hydrogen capacity. Nitrogen and hydrogen isotherms performed at 75 K also show a marked selectivity for hydrogen over nitrogen for this complex, indicating hidden surface area for hydrogen adsorption.
In this paper we introduce the notion of general final state random variables for generalized epidemic models. These random variables are defined as sums over all ultimately infected individuals of random quantities of interest associated with an individual; examples include final severity. By exploiting a construction originally due to Sellke (1983), exact results concerning the final size and general final state random variables are obtained in terms of Gontcharoff polynomials. In particular, our approach highlights the way in which these polynomials arise via simple probabilistic arguments. For ease of exposition we focus initially upon the single-population case before extending our arguments to multi-population epidemics and other variants of our basic model.
This paper considers a class of epidemic models in which susceptibles may enter or leave the population according to a general continuous time density dependent Markov chain. A sequence of such epidemics indexed by N, the initial number of susceptibles, is constructed on the same probability space as a time-inhomogeneous birth-and-death process. A coupling argument is then used to demonstrate the strong convergence of the sequence of infectives to the birth-and-death process. This result is used to provide a threshold analysis of the epidemic model in question.
This paper considers a model for the spread of an epidemic in a closed population whose members are in either a high-risk or a low-risk activity group. Further, members of the high-risk group may change their behaviour by entering the low-risk group. Both stochastic and deterministic models are examined. A limiting model, appropriate when there is a large number of initially susceptible individuals, is used to provide a threshold analysis. The epidemic is compared to a single group epidemic, and to suitably parametrised two-group epidemics, using a coupling method. The total size distribution and effects of changing the behaviour change rate are considered.
This paper is concerned with a model for the spread of an epidemic in a closed, homogeneously mixing population in which new infections occur at rate f(x, y) and removals occur at rate g(x, y), where x and y are the numbers of susceptible and infective individuals, respectively, and f and g are arbitrary but specified positive real-valued functions. Sequences of such epidemics, indexed by the initial number of susceptibles n, are considered and conditions are derived under which the epidemic processes converge almost surely to a birth and death process as n tends to infinity. Thus a threshold theorem for such an epidemic model is obtained. The results are extended to models which incorporate immigration and emigration of susceptibles. The theory is illustrated by several examples of models taken from the epidemic literature. Generalizations to multipopulation epidemics are discussed briefly.
This paper considers a model for the spread of an epidemic in a closed, homogeneously mixing population in which new infections occur at rate βxy/(x + y), where x and y are the numbers of susceptible and infectious individuals, respectively, and β is an infection parameter. This contrasts with the standard general epidemic in which new infections occur at rate βxy. Both the deterministic and stochastic versions of the modified epidemic are analysed. The deterministic model is completely soluble. The time-dependent solution of the stochastic model is derived and the total size distribution is considered. Threshold theorems, analogous to those of Whittle (1955) and Williams (1971) for the general stochastic epidemic, are proved for the stochastic model. Comparisons are made between the modified and general epidemics. The effect of introducing variability in susceptibility into the modified epidemic is studied.
Audiovisual tapes of emotional situations were shown to 34 schizophrenics and 15 controls who were asked to rate the emotional content of the scenes using an adjective check-list. The schizophrenic patients failed to detect the dominant character of the scenes, and perceived the opposite emotions to those perceived by the controls. Such deviant responses were not related to paranoid symptoms, flattened affect, formal thought disorder, general level of morbidity, or duration of in-patient stay.
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