Implausible Values Research Articles

An examination of children's eating behaviours as mediators of the relationship between parents' feeding practices and early childhood body mass index z-scores.

SummaryObjectiveParent's use of restrictive feeding practices is associated with child weight. Similarly, the literature shows that children's eating behaviours are also associated with child weight. Given this interrelationship between children's eating behaviours, restrictive feeding practices and child weight, examination of possible mediator relationships is warranted. This study aimed to examine the relationships between overt restriction and covert restriction with child body mass index z‐scores (BMIz) and determine if children's eating behaviours (satiety responsiveness and food responsiveness) act as mediators.MethodParents of Australian children (n = 977) 2.0–5.0 years of age (49.4% male) provided data in an online survey on child eating behaviours, parent's restrictive feeding practices and child anthropometrics (modified z‐scores were created to screen for biologically implausible values). Correlation analysis was used to determine variables to include in mediation models. Hayes' PROCESS macros in spss was used to examine mediation, controlling for covariates of child BMIz.ResultsOvert restriction was the only parent feeding practice related to child BMIz (B = 0.132, P = 0.04). Mediation analysis showed that the indirect effect of overt restriction on child BMIz (controlling for child age, gender, parent BMI and income) became non‐significant when controlling for food responsiveness, thus suggesting full mediation, explaining 5.75% of the relation.ConclusionOvert restriction and covert restriction have distinctly different relationships with children's eating behaviours. Food responsiveness appears an important intermediary in the relationship between overt restriction and child BMIz.

The effect of socioeconomic deprivation on the association between an extended measurement of unhealthy lifestyle factors and health outcomes: a prospective analysis of the UK Biobank cohort

Combinations of lifestyle factors interact to increase mortality. Combinations of traditional factors such as smoking and alcohol are well described, but the additional effects of emerging factors such as television viewing time are not. The effect of socioeconomic deprivation on these extended lifestyle risks also remains unclear. We aimed to examine whether deprivation modifies the association between an extended score of lifestyle-related risk factors and health outcomes. Data for this prospective analysis were sourced from the UK Biobank, a prospective population-based cohort study. We assigned all participants an extended lifestyle score, with 1 point for each unhealthy lifestyle factor (incorporating sleep duration and high television viewing time, in addition to smoking, excessive alcohol, poor diet [low intake of oily fish or fruits and vegetables, and high intake of red meat or processed meats], and low physical activity), categorised as most healthy (score 0-2), moderately healthy (score 3-5), or least healthy (score 6-9). Cox proportional hazards models were used to examine the association between lifestyle score and health outcomes (all-cause mortality and cardiovascular disease mortality and incidence), and whether this association was modified by deprivation. All analyses were landmark analyses, in which participants were excluded if they had an event (death or cardiovascular disease event) within 2 years of recruitment. Participants with non-communicable diseases (except hypertension) and missing covariate data were excluded from analyses. Participants were also excluded if they reported implausible values for physical activity, sleep duration, and total screen time. All analyses were adjusted for age, sex, ethnicity, month of assessment, history of hypertension, systolic blood pressure, medication for hypercholesterolaemia or hypertension, and body-mass index categories. 328 594 participants aged 40-69 years were included in the study, with a mean follow-up period of 4·9 years (SD 0·83) after the landmark period for all-cause and cardiovascular disease mortality, and 4·1 years (0·81) for cardiovascular disease incidence. In the least deprived quintile, the adjusted hazard ratio (HR) in the least healthy lifestyle category, compared with the most healthy category, was 1·65 (95% CI 1·25-2·19) for all-cause mortality, 1·93 (1·16-3·20) for cardiovascular disease mortality, and 1·29 (1·10-1·52) for cardiovascular disease incidence. Equivalent HRs in the most deprived quintile were 2·47 (95% CI 2·04-3·00), 3·36 (2·36-4·76), and 1·41 (1·25-1·60), respectively. The HR for trend for one increment change towards least healthy in the least deprived quintile compared with that in the most deprived quintile was 1·25 (95% CI 1·12-1·39) versus 1·55 (1·40-1·70) for all-cause mortality, 1·30 (1·05-1·61) versus 1·83 (1·54-2·18) for cardiovascular disease mortality, and 1·10 (1·04-1·17) versus 1·16 (1·09-1·23) for cardiovascular disease incidence. A significant interaction was found between lifestyle and deprivation for all-cause and cardiovascular disease mortality (both pinteraction<0·0001), but not for cardiovascular disease incidence (pinteraction=0·11). Wide combinations of lifestyle factors are associated with disproportionate harm in deprived populations. Social and fiscal policies that reduce poverty are needed alongside public health and individual-level interventions that address a wider range of lifestyle factors in areas of deprivation. None.

Educational disparities in perinatal health in Denmark in the first decade of the 21st century: a register-based cohort study

ObjectiveTo investigate socioeconomic differences in six perinatal health outcomes in Denmark in the first decade of the 21st century.DesignA population-based cohort study.SettingDanish national registries.ParticipantsA total of 646 829 live born...

New approach for the identification of implausible values and outliers in longitudinal childhood anthropometric data

PurposeWe aimed to demonstrate the use of jackknife residuals to take advantage of the longitudinal nature of available growth data in assessing potential biologically implausible values and outliers. MethodsArtificial errors were induced in 5% of length, weight, and head circumference measurements, measured on 1211 participants from the Maternal Vitamin D for Infant Growth (MDIG) trial from birth to 24 months of age. Each child's sex- and age-standardized z-score or raw measurements were regressed as a function of age in child-specific models. Each error responsible for a biologically implausible decrease between a consecutive pair of measurements was identified based on the higher of the two absolute values of jackknife residuals in each pair. In further analyses, outliers were identified as those values beyond fixed cutoffs of the jackknife residuals (e.g., greater than +5 or less than −5 in primary analyses). Kappa, sensitivity, and specificity were calculated over 1000 simulations to assess the ability of the jackknife residual method to detect induced errors and to compare these methods with the use of conditional growth percentiles and conventional cross-sectional methods. ResultsAmong the induced errors that resulted in a biologically implausible decrease in measurement between two consecutive values, the jackknife residual method identified the correct value in 84.3%–91.5% of these instances when applied to the sex- and age-standardized z-scores, with kappa values ranging from 0.685 to 0.795. Sensitivity and specificity of the jackknife method were higher than those of the conditional growth percentile method, but specificity was lower than for conventional cross-sectional methods. ConclusionsUsing jackknife residuals provides a simple method to identify biologically implausible values and outliers in longitudinal child growth data sets in which each child contributes at least 4 serial measurements.

Developing a Novel Parameter Estimation Method for Agent-Based Model in Immune System Simulation under the Framework of History Matching: A Case Study on Influenza A Virus Infection.

Since they can provide a natural and flexible description of nonlinear dynamic behavior of complex system, Agent-based models (ABM) have been commonly used for immune system simulation. However, it is crucial for ABM to obtain an appropriate estimation for the key parameters of the model by incorporating experimental data. In this paper, a systematic procedure for immune system simulation by integrating the ABM and regression method under the framework of history matching is developed. A novel parameter estimation method by incorporating the experiment data for the simulator ABM during the procedure is proposed. First, we employ ABM as simulator to simulate the immune system. Then, the dimension-reduced type generalized additive model (GAM) is employed to train a statistical regression model by using the input and output data of ABM and play a role as an emulator during history matching. Next, we reduce the input space of parameters by introducing an implausible measure to discard the implausible input values. At last, the estimation of model parameters is obtained using the particle swarm optimization algorithm (PSO) by fitting the experiment data among the non-implausible input values. The real Influeza A Virus (IAV) data set is employed to demonstrate the performance of our proposed method, and the results show that the proposed method not only has good fitting and predicting accuracy, but it also owns favorable computational efficiency.

Integration of population census and water point mapping data-A case study of Cambodia, Liberia and Tanzania.

Sustainable Development Goal (SDG) 6 has expanded the Millennium Development Goals' focus from improved drinking-water to safely managed water services. This expanded focus to include issues such as water quality requires richer monitoring data and potentially integration of datasets from different sources. Relevant data sets include water point mapping (WPM), the survey of boreholes, wells and other water points, census and household survey data. This study examined inconsistencies between population census and WPM datasets for Cambodia, Liberia and Tanzania, and identified potential barriers to integrating the two datasets to meet monitoring needs. Literatures on numbers of people served per water point were used to convert WPM data to population served by water source type per area and compared with census reports. For Cambodia and Tanzania, discrepancies with census data suggested incomplete WPM coverage. In Liberia, where the data sets were consistent, WPM-derived data on functionality, quantity and quality of drinking water were further combined with census area statistics to generate an enhanced drinking-water access measure for protected wells and springs. The process revealed barriers to integrating census and WPM data, including exclusion of water points not used for drinking by households, matching of census and WPM source types; temporal mismatches between data sources; data quality issues such as missing or implausible data values, and underlying assumptions about population served by different water point technologies. However, integration of these two data sets could be used to identify and rectify gaps in WPM coverage. If WPM databases become more complete and the above barriers are addressed, it could also be used to develop more realistic measures of household drinking-water access for monitoring.

Automated identification of implausible values in growth data from pediatric electronic health records.

Large electronic health record (EHR) datasets are increasingly used to facilitate research on growth, but measurement and recording errors can lead to biased results. We developed and tested an automated method for identifying implausible values in pediatric EHR growth data. Using deidentified data from 46 primary care sites, we developed an algorithm to identify weight and height values that should be excluded from analysis, including implausible values and values that were recorded repeatedly without remeasurement. The foundation of the algorithm is a comparison of each measurement, expressed as a standard deviation score, with a weighted moving average of a child's other measurements. We evaluated the performance of the algorithm by (1) comparing its results with the judgment of physician reviewers for a stratified random selection of 400 measurements and (2) evaluating its accuracy in a dataset with simulated errors. Of 2 000 595 growth measurements from 280 610 patients 1 to 21 years old, 3.8% of weight and 4.5% of height values were identified as implausible or excluded for other reasons. The proportion excluded varied widely by primary care site. The automated method had a sensitivity of 97% (95% confidence interval [CI], 94-99%) and a specificity of 90% (95% CI, 85-94%) for identifying implausible values compared to physician judgment, and identified 95% (weight) and 98% (height) of simulated errors. This automated, flexible, and validated method for preparing large datasets will facilitate the use of pediatric EHR growth datasets for research.

Effects of arterial input function selection on kinetic parameters in brain dynamic contrast-enhanced MRI

PurposeKinetic parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) were suggested as a possible instrument for multi-parametric lesion characterization, but have not found their way into clinical practice yet due to inconsistent results. The quantification is heavily influenced by the definition of an appropriate arterial input functions (AIF). Regarding brain tumor DCE-MRI, there are currently several co-existing methods to determine the AIF frequently including different brain vessels as sources. This study quantitatively and qualitatively analyzes the impact of AIF source selection on kinetic parameters derived from commonly selected AIF source vessels compared to a population-based AIF model. Material and methods74 patients with brain lesions underwent 3D DCE-MRI. Kinetic parameters [transfer constants of contrast agent efflux and reflux Ktrans and kep and, their ratio, ve, that is used to measure extravascular-extracellular volume fraction and plasma volume fraction vp] were determined using extended Tofts model in 821 ROI from 4 AIF sources [the internal carotid artery (ICA), the closest artery to the lesion, the superior sagittal sinus (SSS), the population-based Parker model]. The effect of AIF source alteration on kinetic parameters was evaluated by tissue type selective intra-class correlation (ICC) and capacity to differentiate gliomas by WHO grade [area under the curve analysis (AUC)]. ResultsArterial AIF more often led to implausible ve >100% values (p<0.0001). AIF source alteration rendered different absolute kinetic parameters (p<0.0001), except for kep. ICC between kinetic parameters of different AIF sources and tissues were variable (0.08–0.87) and only consistent >0.5 between arterial AIF derived kinetic parameters. Differentiation between WHO III and II glioma was exclusively possible with vp derived from an AIF in the SSS (p=0.03; AUC 0.74). ConclusionThe AIF source has a significant impact on absolute kinetic parameters in DCE-MRI, which limits the comparability of kinetic parameters derived from different AIF sources. The effect is also tissue-dependent. The SSS appears to be the best choice for AIF source vessel selection in brain tumor DCE-MRI as it exclusively allowed for WHO grades II/III and III/IV glioma distinction (by vp) and showed the least number of implausible ve values.

A critical assessment of early warning score records in 168,000 patients.

The national early warning score (NEWS) is recommended to detect deterioration in hospitalised patients. In 2013, a NEWS-based system was introduced in a hospital service with over 250,000 annual admissions, generating large amounts of NEWS data. The quality of such data has not been described. We critically assessed NEWS data recorded over 12 months. This observational study included NEWS records from adult inpatients hospitalized in the Capital Region of Denmark during 2014. Physiological variables and the use of supplementary oxygen (NEWS variables) were recorded. We identified implausible records and assessed the distributions of NEWS variable values. Of 2,835,331 NEWS records, 271,103 (10%) were incomplete with one or more variable missing and 0.2% of records containing implausible values. Digit preferences were identified for respiratory rate, supplementation oxygen flow, pulse rate, and systolic blood pressure. There was an accumulation of pulse rate records below 91 beats per minute. Among complete NEWS records, 64% had NEWS ≥ 1; 29% had NEWS ≥ 3; and 8% had NEWS ≥ 6. In a large set of NEWS data, 10% of the records were incomplete. In a system where data were manually entered into an electronic medical record, digit preferences and the accumulation of pulse rate records below 91 beats per minute, which is the limit for NEWS point generation, showed that staff practice influenced the recorded values. This indicates a potential limitation of transferability of research results obtained in such systems to fully automated systems.

Bias Introduced by Rounding in Multiple Imputation for Ordered Categorical Variables

ABSTRACTMultivariate normality is frequently assumed when multiple imputation is applied for missing data. When data are ordered categorical, imputing missing data using the fully normal imputation results in implausible values falling outside of the categorical values. Naïve rounding has been suggested to round the imputed values to their categorical neighbors for further analysis. Previous studies showed that, for binary data, the rounded values can result in biased mean estimation when the population distribution is asymmetric. However, it has been conjectured that as the number of categories increases, the bias will decrease. To investigate this conjecture, the present study derives the formulas for the biases of the mean and standard deviation for ordered categorical variables with naïve rounding. Results show that both the biases of the mean and standard deviation decrease as the number of categories increases from 3 to 9. This study also finds that although symmetric population distributions lead to unbiased means of the rounded values, the standard deviations may still be largely biased. A simulation study further shows that the biases due to naïve rounding can result in substantially low coverage rates for the population mean parameter.

Geographical distribution of sporadic Creutzfeldt-Jakob disease: analysis by municipality in Apulia between 1993 and 2014

Introduction Clustering of sporadic Creutzfeldt-Jakob disease (CJD), a rare fatal neurodegenerative disease with unknown etiology, was investigated in an Italian region. Methods Occurrence of sporadic CJD between 1993 and 2014 was analyzed by municipality in Apulia Region (Italy) using data provided by the Italian Registry of Creutzfeldt-Jakob disease and the Italian Bureau of Statistics. Expected cases by municipality were obtained by internal indirect standardization based on age and gender specific regional incidence rates. We fitted Bayesian hierarchical models with spatially structured and unstructured random components to describe the spatial pattern of the disease and to assess the extent of within and between area clustering. We also evaluated between and within age class (&lt;70; 70+ yrs) clustering by Potthoff-Whittinghill test and search for spatial clusters applying the Kulldorff-Nagarwalla Scan test. Results Between 1993 and 2014, there were 101 incident sporadic CJD cases resident in Apulia (yearly incidence rate: 1.13/1.000.000). 1. The ratio of observed /expected cases ranges by municipality between 0 and 25 – a very implausible value – while the smoothed Bayesian relative risks range between 0.9 to 1.3. There is evidence of between area clustering and two aggregates emerge by this analysis: in the northern, around the city of Foggia; in the middle, in the Valle d’Itria region. 2. No evidence of between or within age class clustering was observed (MonteCarlo p-values within age classes 0.60 and 0.54 respectively). 3. One cluster (MonteCarlo p-value 0.053, 16 cases, 5.3 expected) corresponding to the municipalities of the Valle d’Itria region was detected by the Scan-test analysis. Conclusions Weak evidence of clustering of sporadic CJD was found at a municipality level in an Italian region, but caution is needed in the interpretation of these results.

Perspectives on the intrinsic rate of population growth

Summary The intrinsic rate of population increase (rmax) is a fundamental metric in ecology and evolution of immediate practical application in conservation and wildlife management. I examine the interpretation of rmax by revisiting the theory behind the density‐independent and density‐dependent paradigms. The criticism that density‐independent approaches underestimate rmax per se, often expressed in the field of fisheries, is shown to be theoretically unfounded. The difficulty in estimating rmax is due to lack of knowledge on the depletion level of the population rather than theory. I reviewed a method commonly used to estimate extinction risk of marine and terrestrial populations and show that it has been used incorrectly. I also examined five other methods to calculate rmax, the Euler–Lotka equation, and four other methods derived from it. I used the same data inputs for a suite of 65 shark populations with a broad range of life histories as an example to show that the incorrectly used extinction risk method overestimates rmax. I compared the rmax values for sharks obtained with the incorrectly applied extinction risk method to published values for other vertebrate taxa to further show that this method generates implausible values for this group of predators. I advocate focusing on obtaining estimates of all required vital rates simultaneously when possible while taking into consideration the exploitation history of the population under study as a pragmatic way to provide plausible estimates of rmax. The Euler–Lotka equation and its derivations are recommended for different degrees of data availability, particularly for slow‐ and medium‐growing populations, to provide sensible advice for conservation and management of living vertebrates in situations where a series of credible abundance estimates are not available as is often the case in marine systems. Methods that combine allometry and demography should also be further explored.

Oil Price Elasticities and Oil Price Fluctuations

We study the identification of oil shocks in a structural vector autoregressive (SVAR) model of the oil market. First, we show that the cross-equation restrictions of a SVAR impose a nonlinear relation between the short-run price elasticities of oil supply and oil demand. This relation implies that seemingly plausible restrictions on oil supply elasticity may map into implausible values of the oil demand elasticity, and vice versa. Second, we propose an identification scheme that restricts these elasticities by minimizing the distance between the elasticities allowed by the SVAR and target values that we construct from a survey of relevant studies. Third, we use the identified SVAR to analyze sources and consequences of movements in oil prices. We find that (1) oil supply shocks and global demand shocks explain 50 and 35 percent of oil price fluctuations, respectively; (2) a drop in oil prices driven by supply shocks boosts economic activity in advanced economies, whereas it depresses economic activity in emerging economies; and (3) the selection of oil market elasticities is essential for understanding the source of oil price movements and to measuring the multipliers of oil prices on economic activity.

Challenges in Collating Spirometry Reference Data for South-Asian Children: An Observational Study.

Availability of sophisticated statistical modelling for developing robust reference equations has improved interpretation of lung function results. In 2012, the Global Lung function Initiative(GLI) published the first global all-age, multi-ethnic reference equations for spirometry but these lacked equations for those originating from the Indian subcontinent (South-Asians). The aims of this study were to assess the extent to which existing GLI-ethnic adjustments might fit South-Asian paediatric spirometry data, assess any similarities and discrepancies between South-Asian datasets and explore the feasibility of deriving a suitable South-Asian GLI-adjustment.MethodsSpirometry datasets from South-Asian children were collated from four centres in India and five within the UK. Records with transcription errors, missing values for height or spirometry, and implausible values were excluded(n = 110).ResultsFollowing exclusions, cross-sectional data were available from 8,124 children (56.3% male; 5–17 years). When compared with GLI-predicted values from White Europeans, forced expired volume in 1s (FEV1) and forced vital capacity (FVC) in South-Asian children were on average 15% lower, ranging from 4–19% between centres. By contrast, proportional reductions in FEV1 and FVC within all but two datasets meant that the FEV1/FVC ratio remained independent of ethnicity. The ‘GLI-Other’ equation fitted data from North India reasonably well while ‘GLI-Black’ equations provided a better approximation for South-Asian data than the ‘GLI-White’ equation. However, marked discrepancies in the mean lung function z-scores between centres especially when examined according to socio-economic conditions precluded derivation of a single South-Asian GLI-adjustment.ConclusionUntil improved and more robust prediction equations can be derived, we recommend the use of ‘GLI-Black’ equations for interpreting most South-Asian data, although ‘GLI-Other’ may be more appropriate for North Indian data. Prospective data collection using standardised protocols to explore potential sources of variation due to socio-economic circumstances, secular changes in growth/predictors of lung function and ethnicities within the South-Asian classification are urgently required.

Stunting and its relationship to Obesity in the US affiliated Pacific: a study of the Children's Healthy Living Program

The US Affiliated Pacific (US Pacific) has experienced nutrition transition over the last decades yet the region is not served by national surveys, and prevalence data on nutritional anthropometry are not widely available. The study will examine prevalence of stunting among young children in the US Pacific and its variability among the indigenous ethnic populations and, to examine whether stunting alters the risk for obesity and whether race/ethnicity modifies this relationship. Children were sampled from 51 communities in 11 US Pacific jurisdictions. Child's race was categorized according to the US Office of Management and Budget (OMB): American Indian or Alaska Native (AIAN), Asian, Black, Native Hawaiian or Other Pacific Islander (NHPI), White, and More than one race. Child's race was also examined by an expansion of OMB race/ethnicity groups and included 18 Pacific ethnic categories. Child's height and weight were measured by trained and standardized staff. Stunting was defined as height‐for‐age z score (HAZ) &lt;−2 SDs below the mean. Child's weight status was categorized based on CDC's 2000 reference data as: (1) underweight &lt;5th percentile BMI; (2) Healthy weight, &gt;=5th&lt;84th BMI percentile; (3) Overweight, &gt;=85th &lt;95th BMI percentile and (4) Obese, &gt;=95th BMI percentile. Cutoff values for biologically implausible values were &lt;−5 or &gt;3 for HAZ and &lt;−4 or &gt;5 for BMI z score. Prevalence estimates were weighted to 2010 census population size of children &lt;10 years of age for each community and adjusted for clustering of communities within jurisdictions. Logistic regression was used to examine the relationship between stunting and obesity, controlling for child's age, sex, and race/ethnicity. 5,376 children were studied. 65% were 2–5 years old and 51% were male. 61% were NHPI, 20% were More than one race group, 9% were Asian, 8% were White, 2% were AIAN and 0.3% were Black. Among NHPI, the 10 most prevalent ethnic groups were Samoan (25%), Chamorro (20%), Chuukese (11%), Marshallese (6%), Yapese (6%), Kosraean (5%), Native Hawaiian (5%), Pohnpeian (5%), Palauan (5%), and mixed within NHPI (10%). Filipino was the dominant Asian ethnic group (84%). The adjusted and weighted prevalence of stunting was 2.5% (SE=0.3%), obesity was 13.8% (SE=0.9%), and underweight was 2.5% (SE=0.3%). A significant difference in stunting prevalence was found by child's race/ethnicity (p&lt;0.001), but not by age group (2–5 vs 6–8y) or sex. The highest prevalence of stunting was among Pohnpeian (13%), Marshallese (11%), Kosraean (5%) and Chamorro (3%) children. No stunting was observed among Black or other NHPI (Carolinian, Tongan, Kiribati, Tokelaun, Tahitian, Etc.) children. Very low prevalence was observed among Native Hawaiian (0.3%), Samoan (0.3%), and Filipino (0.7%) children. Logistic regression showed that stunted children were less likely to become obese among all race/ethnic groups (ORs&lt;0.001, p&lt;0.0001) except for Native Hawaiian (OR=5.8; 95% CI: 3.7–9.0) where stunted children were 6 times more likely to become obese compared to non‐stunted children. No significant relationship was observed between stunting and obesity among Samoan and the “More than one race” groups. The Native Hawaiian relationship of stunting to obesity could be related to an earlier historical nutrition transition. Further examination of behaviors and environments that may explain ethnic differences in stunting and its relationship to obesity is warranted.Support or Funding InformationUSDA 2011‐68001‐30335

The prevalence and validity of high, biologically implausible values of weight, height, and BMI among 8.8 million children.

This study assessed the prevalence and consistency of high values of weight, height, and BMI considered to be biologically implausible (BIV) using cut points proposed by WHO among 8.8 million low-income children (13.7 million observations). Cross-sectional and longitudinal analyses were performed among 2- to 4-year-olds who were examined from 2008 through 2011. Overall, 2.7% of the body size measurements were classified as BIVs; 95% of these BIVs were very high. Among the subset of children (3.6 million) examined more than once, most of those who initially had a high weight or BMI BIV also had a high BIV at the second examination; odds ratios were >250. Based on several alternative classifications of BIVs, the current cut points likely underestimate the prevalence of obesity by about 1%. Many of the extremely high values of body size currently flagged as BIVs are unlikely to be errors. Increasing the z-score cut points or using a percentage of the maximum values in the National Health and Nutrition Examination Survey, could improve the balance between removing probable errors and retaining those that are likely correct.

Transaural experiments and a revised duplex theory for the localization of low-frequency tones.

The roles of interaural time difference (ITD) and interaural level difference (ILD) were studied in free-field source localization experiments for sine tones of low frequency (250-750 Hz). Experiments combined real-source trials with virtual trials created through transaural synthesis based on real-time ear canal measurements. Experiments showed the following: (1) The naturally occurring ILD is physically large enough to exert an influence on sound localization well below 1000 Hz. (2) An ILD having the same sign as the ITD modestly enhances the perceived azimuth of tones for all values of the ITD, and it eliminates left-right confusions that otherwise occur when the interaural phase difference (IPD) passes 180°. (3) Increasing the ILD to large, implausible values can decrease the perceived laterality while also increasing front-back confusions. (4) Tone localization is more directly related to the ITD than to the IPD. (5) An ILD having a sign opposite to the ITD promotes a slipped-cycle ITD, sometimes with dramatic effects on localization. Because the role of the ITD itself is altered by the ILD, the duplex processing of ITD and ILD reflects more than mere trading; the effect of the ITD can be reversed in sign.

Validity of the WHO cutoffs for biologically implausible values of weight, height, and BMI in children and adolescents in NHANES from 1999 through 2012

The WHO cutoffs to classify biologically implausible values (BIVs) for weight, height, and weight-for-height in children and adolescents are widely used in data cleaning. We assess 1) the prevalence of these BIVs, 2) whether they were consistent with information on waist circumference, arm circumference, and leg lengths, and 3) the effect of their exclusion on the estimated prevalence of obesity in 2- to 19-y-olds in the NHANES, which is a study in which extreme values were verified when recorded. We conducted cross-sectional analyses in 26,480 children and adolescents in the NHANES from 1999-2000 through 2011-2012. The overall prevalence for a BIV for any body-size measure was 0.9% (n = 277), and almost all BIVs were due to extremely high, rather than low, values. Of 186 subjects who had a high BIV for weight or body mass index (BMI), all but one subject had both arm and waist circumferences that were greater than the sex- and age-specific 95th percentiles; 75% of subjects had circumferences greater than the 99th percentile. Of 63 subjects with a high height BIV, 75% of them had a leg length that was greater than the 95th percentile. The exclusion of children and adolescents with a BIV reduced the overall prevalence of obesity by ∼0.5 percentage points and by 1.7% in non-Hispanic blacks. Most of the extremely high values of weight, height, and BMI flagged as BIVs in the NHANES are very likely correct. The increase of z score cutoffs or the use of an alternative method to detect possible errors could improve the balance between removing incorrect values and retaining extremely high, but accurate, values in other data sets.

Identifying outliers and implausible values in growth trajectory data

PurposeTo illustrate how conditional growth percentiles can be adapted for use to systematically identify implausible measurements in growth trajectory data. MethodsThe use of conditional growth percentiles as a tool to assess serial weight data was reviewed. The approach was applied to 86,427 weight measurements (kg) taken between birth and age 6.5 years in 8217 girls participating in the Promotion of Breast Feeding Intervention Trial in Belarus. A conditional mean and variance was calculated for each weight measurement, which reflects the expected weight at a current visit given the girl's previous weights. Measurements were flagged as outliers if they were more than 4 standard deviation (SD) above or below the expected (conditional) weight. ResultsThe method identified 234 weight measurements (0.3%) from 216 girls as potential outliers. Review of these trajectories confirmed the implausibility of the flagged measurements, and that the approach identified observations that would not have been identified using a conventional cross-sectional approach (±4 SD of the population mean) for identifying implausible values. Stata code to implement the approach is provided. ConclusionsConditional growth percentiles can be used to systematically identify implausible values in growth trajectory data and may be particularly useful for large data sets where the high number of trajectories makes ad hoc approaches unfeasible.

Association of hand grip strength with subjective health and work ability. results of the baseline survey of the lidA study

In the BMBF-funded lidA study - leben in der Arbeit - hand grip strength is taken as an objective measure for describing the health of the study population. The aim is to analyse the association of grip strength with characteristics of subjective health and work ability. During the 1(st) investigation in 2011 there were 6 585 interviews with employed persons born in 1959 and 1965 and subject to social insurance contributions. The survey included aspects of employment and health. The maximum isometric hand grip strength was determined with a dynamometer from a series of 4 measurements. The examination refers to 6 195 employed persons who approved the realisation of the grip strength test. The determinants of grip strength are analysed bivariately based on non-parametric methods and examined concerning their relative importance using a multiple linear regression. In the descriptive analyses statistically significant median differences (p<0.05) appear between men and women as well as persons of the younger and older cohort. After excluding implausible values some statistically significant differences in grip strength can be observed between the categories of current health condition, physical and mental work ability and the number of pain localisations. The trend for the larger grip strength occurrences can be noted in the categories of better health and work ability plus a smaller number of pain localisations. From the combined analysis of the explanatory variables of age, BMI, health and work ability within the estimated regression model results a corrected R² of 0.036 for men or, respectively, 0.05 for women. Between the categories of selected health and work ability related variables some statistically significant differences of grip strength (± 0.0-4.0 kg) were observed. However, the variability of grip strength cannot be explained sufficiently by the data used. Although the results obtained support the preliminary assumptions, the relevance of this matter could not be resolved adequately with the data under consideration. Given that analysing grip strength is important in the individual temporal process, the results will be extended by longitudinal analyses to facilitate the analysis of hand grip strength as predictor of the development of individual health.