Using spatiotemporal modulation to draw tactile patterns in mid-air

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Measuring Coverage in MNCH:A Validation Study Linking Population Survey Derived Coverage to Maternal, Newborn, and Child Health Care Records in Rural China

Accurate data on coverage of key maternal, newborn, and child health (MNCH) interventions are crucial for monitoring progress toward the Millennium Development Goals 4 and 5. Coverage estimates are primarily obtained from routine population surveys through self-reporting, the validity of which is not well understood. We aimed to examine the validity of the coverage of selected MNCH interventions in Gongcheng County, China.We conducted a validation study by comparing women's self-reported coverage of MNCH interventions relating to antenatal and postnatal care, mode of delivery, and child vaccinations in a community survey with their paper- and electronic-based health care records, treating the health care records as the reference standard. Of 936 women recruited, 914 (97.6%) completed the survey. Results show that self-reported coverage of these interventions had moderate to high sensitivity (0.57 [95% confidence interval (CI): 0.50-0.63] to 0.99 [95% CI: 0.98-1.00]) and low to high specificity (0 to 0.83 [95% CI: 0.80-0.86]). Despite varying overall validity, with the area under the receiver operating characteristic curve (AUC) ranging between 0.49 [95% CI: 0.39-0.57] and 0.90 [95% CI: 0.88-0.92], bias in the coverage estimates at the population level was small to moderate, with the test to actual positive (TAP) ratio ranging between 0.8 and 1.5 for 24 of the 28 indicators examined. Our ability to accurately estimate validity was affected by several caveats associated with the reference standard. Caution should be exercised when generalizing the results to other settings.The overall validity of self-reported coverage was moderate across selected MNCH indicators. However, at the population level, self-reported coverage appears to have small to moderate degree of bias. Accuracy of the coverage was particularly high for indicators with high recorded coverage or low recorded coverage but high specificity. The study provides insights into the accuracy of self-reports based on a population survey in low- and middle-income countries. Similar studies applying an improved reference standard are warranted in the future

Polish 2010 growth references for school-aged children and adolescents

Growth references are useful in monitoring a child's growth, which is an essential part of child care. The aim of this paper was to provide updated growth references for Polish school-aged children and adolescents and show the prevalence of overweight and obesity among them. Growth references for height, weight, and body mass index (BMI) were constructed with the lambda, mu, sigma (LMS) method using data from a recent, large, population-representative sample of school-aged children and adolescents in Poland (n = 17,573). The prevalence of overweight and obesity according to the International Obesity Taskforce definition was determined with the use of LMSGrowth software. Updated growth references for Polish school-aged children and adolescents were compared with Polish growth references from the 1980s, the Warsaw 1996–1999 reference, German, and 2000 CDC references. A positive secular trend in height was observed in children and adolescents from 7 to 15 years of age. A significant shift of the upper tail of the BMI distribution occurred, especially in Polish boys at younger ages. The prevalence of overweight or obesity was 18.7% and 14.1% in school-aged boys and girls, respectively. The presented height, weight, and BMI references are based on a current, nationally representative sample of Polish children and adolescents without known disorders affecting growth. Changes in the body size of children and adolescents over the last three decades suggest an influence of the changing economical situation on anthropometric indices

Childhood body mass index trajectories: modeling, characterizing, pairwise correlations and socio-demographic predictors of trajectory characteristics

Background: Modeling childhood body mass index (BMI) trajectories, versus estimating change in BMI between specific ages, may improve prediction of later body-size-related outcomes. Prior studies of BMI trajectories are limited by restricted age periods and insufficient use of trajectory information. Methods: Among 3,289 children seen at 81,550 pediatric well-child visits from infancy to 18 years between 1980 and 2008, we fit individual BMI trajectories using mixed effect models with fractional polynomial functions. From each child's fitted trajectory, we estimated age and BMI at infancy peak and adiposity rebound, and velocity and area under curve between 1 week, infancy peak, adiposity rebound, and 18 years. Results: Among boys, mean (SD) ages at infancy BMI peak and adiposity rebound were 7.2 (0.9) and 49.2 (11.9) months, respectively. Among girls, mean (SD) ages at infancy BMI peak and adiposity rebound were 7.4 (1.1) and 46.8 (11.0) months, respectively. Ages at infancy peak and adiposity rebound were weakly inversely correlated (r = -0.09). BMI at infancy peak and adiposity rebound were positively correlated (r = 0.76). Blacks had earlier adiposity rebound and greater velocity from adiposity rebound to 18 years of age than whites. Higher birth weight z-score predicted earlier adiposity rebound and higher BMI at infancy peak and adiposity rebound. BMI trajectories did not differ by birth year or type of health insurance, after adjusting for other socio-demographics and birth weight z-score. Conclusions: Childhood BMI trajectory characteristics are informative in describing childhood body mass changes and can be estimated conveniently. Future research should evaluate associations of these novel BMI trajectory characteristics with adult outcomes

Alternative regression models to assess increase in childhood BMI

<p>Abstract</p> <p>Background</p> <p>Body mass index (BMI) data usually have skewed distributions, for which common statistical modeling approaches such as simple linear or logistic regression have limitations.</p> <p>Methods</p> <p>Different regression approaches to predict childhood BMI by goodness-of-fit measures and means of interpretation were compared including generalized linear models (GLMs), quantile regression and Generalized Additive Models for Location, Scale and Shape (GAMLSS). We analyzed data of 4967 children participating in the school entry health examination in Bavaria, Germany, from 2001 to 2002. TV watching, meal frequency, breastfeeding, smoking in pregnancy, maternal obesity, parental social class and weight gain in the first 2 years of life were considered as risk factors for obesity.</p> <p>Results</p> <p>GAMLSS showed a much better fit regarding the estimation of risk factors effects on transformed and untransformed BMI data than common GLMs with respect to the generalized Akaike information criterion. In comparison with GAMLSS, quantile regression allowed for additional interpretation of prespecified distribution quantiles, such as quantiles referring to overweight or obesity. The variables TV watching, maternal BMI and weight gain in the first 2 years were directly, and meal frequency was inversely significantly associated with body composition in any model type examined. In contrast, smoking in pregnancy was not directly, and breastfeeding and parental social class were not inversely significantly associated with body composition in GLM models, but in GAMLSS and partly in quantile regression models. Risk factor specific BMI percentile curves could be estimated from GAMLSS and quantile regression models.</p> <p>Conclusion</p> <p>GAMLSS and quantile regression seem to be more appropriate than common GLMs for risk factor modeling of BMI data.</p

Associations of vitamin D pathway genes with circulating 25-hydroxyvitamin-D, 1,25-dihydroxyvitamin-D, and prostate cancer:a nested case-control study

Vitamin D pathway single nucleotide polymorphisms (SNPs) are potentially useful proxies for investigating whether circulating vitamin D metabolites [total 25-hydroxyvitamin-D, 25(OH)D; 1,25-dihydroxyvitamin, 1,25(OH)2D] are causally related to prostate cancer. We investigated associations of sixteen SNPs across seven genes with prostate-specific antigen-detected prostate cancer

Quality of care in elder emergency department patients with pneumonia: a prospective cohort study

<p>Abstract</p> <p>Background</p> <p>The goals of the study were to assess the relationship between age and processes of care in emergency department (ED) patients admitted with pneumonia and to identify independent predictors of failure to meet recommended quality care measures.</p> <p>Methods</p> <p>This was a prospective cohort study of a pre-existing database undertaken at a university hospital ED in the Midwest. ED patients ≥18 years of age requiring admission for pneumonia, with no documented use of antibiotics in the 24 hours prior to ED presentation were included. Compliance with Pneumonia National Quality Measures was assessed including ED antibiotic administration, antibiotics within 4 hours, oxygenation assessment, and obtaining of blood cultures. Odds ratios were calculated for elders and non-elders. Logistic regression was used to identify independent predictors of process failure.</p> <p>Results</p> <p>One thousand, three hundred seventy patients met inclusion criteria, of which 560 were aged ≥65 years. In multiple variable logistic regression analysis, age ≥65 years was independently associated with receiving antibiotics in the ED (odds ratio [OR] = 2.03, 95% CI 1.28–3.21) and assessment of oxygenation (OR = 2.10, 95% CI, 1.18–3.32). Age had no significant impact on odds of receiving antibiotics within four hours of presentation (OR 1.10, 95% CI 0.84–1.43) or having blood cultures drawn (OR 1.02, 95%CI 0.78–1.32). Certain other patient characteristics were also independently associated with process failure.</p> <p>Conclusion</p> <p>Elderly patients admitted from the ED with pneumonia are more likely to receive antibiotics while in the ED and to have oxygenation assessed in the ED than younger patients. The independent association of certain patient characteristics with process failure provides an opportunity to further increase compliance with recommended quality measures in admitted patients diagnosed with pneumonia.</p

Centile charts for birthweight for gestational age for Scottish singleton births

<p>Abstract</p> <p>Background</p> <p>Centile charts of birthweight for gestational age are used to identify low birthweight babies. The charts currently used in Scotland are based on data from the 1970s and require updating given changes in birthweight and in the measurement of gestational age since then.</p> <p>Methods</p> <p>Routinely collected data of 100,133 singleton births occurring in Scotland from 1998–2003 were used to construct new centile charts using the LMS method.</p> <p>Results</p> <p>Centile charts for birthweight for sex and parity groupings were constructed for singleton birth and compared to existing charts used in Scottish hospitals.</p> <p>Conclusion</p> <p>Mean birthweight has been shown to have increased over recent decades. The differences shown between the new and currently used centiles confirm the need for more up-to-date centiles for birthweight for gestational age.</p

Reexamining the effects of gestational age, fetal growth, and maternal smoking on neonatal mortality

BACKGROUND: Low birth weight (<2,500 g) is a strong predictor of infant mortality. Yet low birth weight, in isolation, is uninformative since it is comprised of two intertwined components: preterm delivery and reduced fetal growth. Through nonparametric logistic regression models, we examine the effects of gestational age, fetal growth, and maternal smoking on neonatal mortality. METHODS: We derived data on over 10 million singleton live births delivered at ≥ 24 weeks from the 1998–2000 U.S. natality data files. Nonparametric multivariable logistic regression based on generalized additive models was used to examine neonatal mortality (deaths within the first 28 days) in relation to fetal growth (gestational age-specific standardized birth weight), gestational age, and number of cigarettes smoked per day. All analyses were further adjusted for the confounding effects due to maternal age and gravidity. RESULTS: The relationship between standardized birth weight and neonatal mortality is nonlinear; mortality is high at low z-score birth weights, drops precipitously with increasing z-score birth weight, and begins to flatten for heavier infants. Gestational age is also strongly associated with mortality, with patterns similar to those of z-score birth weight. Although the direct effect of smoking on neonatal mortality is weak, its effects (on mortality) appear to be largely mediated through reduced fetal growth and, to a lesser extent, through shortened gestation. In fact, the association between smoking and reduced fetal growth gets stronger as pregnancies approach term. CONCLUSIONS: Our study provides important insights regarding the combined effects of fetal growth, gestational age, and smoking on neonatal mortality. The findings suggest that the effect of maternal smoking on neonatal mortality is largely mediated through reduced fetal growth

Epigenetic prediction of complex traits and mortality in a cohort of individuals with oropharyngeal cancer

Background: DNA methylation (DNAm) variation is an established predictor for several traits. In the context of oropharyngeal cancer (OPC), where 5-year survival is ~ 65%, DNA methylation may act as a prognostic biomarker. We examined the accuracy of DNA methylation biomarkers of 4 complex exposure traits (alcohol consumption, body mass index [BMI], educational attainment and smoking status) in predicting all-cause mortality in people with OPC. Results: DNAm predictors of alcohol consumption, BMI, educational attainment and smoking status were applied to 364 individuals with OPC in the Head and Neck 5000 cohort (HN5000; 19.6% of total OPC cases in the study), followed up for median 3.9 years; inter-quartile range (IQR) 3.3 to 5.2 years (time-to-event—death or censor). The proportion of phenotypic variance explained in each trait was as follows: 16.5% for alcohol consumption, 22.7% for BMI, 0.4% for educational attainment and 51.1% for smoking. We then assessed the relationship between each DNAm predictor and all-cause mortality using Cox proportional-hazard regression analysis. DNAm prediction of smoking was most consistently associated with mortality risk (hazard ratio [HR], 1.38 per standard deviation (SD) increase in smoking DNAm score; 95% confidence interval [CI] 1.04 to 1.83; P 0.025, in a model adjusted for demographic, lifestyle, health and biological variables). Finally, we examined the accuracy of each DNAm predictor of mortality. DNAm predictors explained similar levels of variance in mortality to self-reported phenotypes. Receiver operator characteristic (ROC) curves for the DNAm predictors showed a moderate discrimination of alcohol consumption (area under the curve [AUC] 0.63), BMI (AUC 0.61) and smoking (AUC 0.70) when predicting mortality. The DNAm predictor for education showed poor discrimination (AUC 0.57). Z tests comparing AUCs between self-reported phenotype ROC curves and DNAm score ROC curves did not show evidence for difference between the two (alcohol consumption P 0.41, BMI P 0.62, educational attainment P 0.49, smoking P 0.19). Conclusions: In the context of a clinical cohort of individuals with OPC, DNAm predictors for smoking, alcohol consumption, educational attainment and BMI exhibit similar predictive values for all-cause mortality compared to self-reported data. These findings may have translational utility in prognostic model development, particularly where phenotypic data are not available