47 research outputs found
Reported versus measured body weight and height of 4-year-old children and the prevalence of overweight
Background: In adults, body weight tends to be underestimated when based on self-reported data. Whether this discrepancy between measured and reported data exists in healthy young children is unclear. We studied whether parental reported body weight and height of 4-year-old children corresponded with measured body weight and height. In addition, we studied the determinants and the consequences of differences between reported and measured data. Methods: Data on body weight and height of 864 4-year-old Dutch children born in 1996/1997 enrolled in the Prevention and Incidence of Asthma and Mite Allergy (PIAMA) birth cohort study were collected via a questionnaire and a medical examination. Overweight was defined according to standard international age and gender specific definitions. Results: Mean differences between measured and reported body weight, height, and body mass index (BMI) were small. Parents of children with a low BMI tended to over report body weight while parents of children with a high BMI tended to underreport body weight. Whereas 9.5% of the children were overweight according to reported BMI, the prevalence of overweight was 13.4% based on measured BMI. Over 45% of the overweight children according to measured BMI were missed when reported BMI was used. Conclusion: These findings suggest that overweight prevalence rates in children are underestimated when based on reported weight and height
Early respiratory and skin symptoms in relation to ethnic background: the importance of socioeconomic status; the PIAMA study
AIMS: To evaluate ethnic differences in the prevalence of respiratory and
skin symptoms in the first two years of life. METHODS: A total of 4146
children participated in the Prevention and Incidence of Asthma and Mite
Allergy (PIAMA) study. Parents completed questionnaires on respirato
Application of an Error Correction Model in Assessment and Forecasting of Energy Consumption in the European Union
In the following framework, efforts of building a model of energy consumption with regard to basic macroeconomic factors such as gross domestic product (GDP), consumer price index (CPI), and demographic variables, have been undertaken. Above-mentioned model, thanks to an error correction mechanism enables to indicate short- and long-term relations between analyzed variables.The spatial and time sample which was chosen for the research, includes data from 1980 β 2005 from the European Union countries. The application of such cross sample and decomposition of absolute term, enables to indicate certain general regularities in analyzed phenomenon, and also typical of particular countries. From empirical point of view, the created model can be used in preparation of simulations and forecasts with planned energy consumption on the national and international level.ΠΡΠ΅Π΄ΠΏΡΠΈΠ½ΡΡΠ° ΠΏΠΎΠΏΡΡΠΊΠ° ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΡ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΏΠΎΡΡΠ΅Π±Π»Π΅Π½ΠΈΡ ΡΠ½Π΅ΡΠ³ΠΈΠΈ Ρ ΡΡΠ΅ΡΠΎΠΌ ΠΌΠ°ΠΊΡΠΎΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ°ΠΊΡΠΎΡΠΎΠ², ΡΠ°ΠΊΠΈΡ
ΠΊΠ°ΠΊ ΠΠΠ, ΠΈΠ½Π΄Π΅ΠΊΡ ΡΠ΅Π½ ΠΏΠΎΡΡΠ΅Π±ΠΈΡΠ΅Π»Ρ, ΠΈ Π΄Π΅ΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
Π΄Π°Π½Π½ΡΡ
. ΠΡΠ΅Π΄Π»Π°Π³Π°Π΅ΠΌΠ°Ρ ΠΌΠΎΠ΄Π΅Π»Ρ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ Ρ ΠΏΠΎΠΌΠΎΡΡΡ ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΠΌΠ° ΠΊΠΎΡΡΠ΅ΠΊΡΠΈΠΈ ΠΎΡΠΈΠ±ΠΎΠΊ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΠΈΡΡ ΠΊΡΠ°ΡΠΊΠΎ- ΠΈ Π΄ΠΎΠ»Π³ΠΎΡΡΠΎΡΠ½ΡΠ΅ ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΡ ΠΌΠ΅ΠΆΠ΄Ρ Π°Π½Π°Π»ΠΈΠ·ΠΈΡΡΠ΅ΠΌΡΠΌΠΈ ΠΏΠ΅ΡΠ΅ΠΌΠ΅Π½Π½ΡΠΌΠΈ. ΠΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½Π° ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΠΎ-Π²ΡΠ΅ΠΌΠ΅Π½Π½Π°Ρ Π²ΡΠ±ΠΎΡΠΊΠ° Π΄Π°Π½Π½ΡΡ
Ρ 1980 ΠΏΠΎ 2005 Π³. ΠΏΠΎ ΡΡΡΠ°Π½Π°ΠΌ ΠΠ²ΡΠΎΠΏΠ΅ΠΉΡΠΊΠΎΠ³ΠΎ Π‘ΠΎΡΠ·Π°. ΠΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΡΠ°ΠΊΠΎΠΉ ΠΏΠ΅ΡΠ΅ΠΊΡΠ΅ΡΡΠ½ΠΎΠΉ Π²ΡΠ±ΠΎΡΠΊΠΈ ΠΈ ΡΠ°Π·Π±ΠΈΠ΅Π½ΠΈΠ΅ Π²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠ³ΠΎ ΠΏΠ΅ΡΠΈΠΎΠ΄Π° ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΠΈΡΡ Π½Π΅ΠΊΠΎΡΠΎΡΡΠ΅ ΠΎΠ±ΡΠΈΠ΅ Π·Π°ΠΊΠΎΠ½ΠΎΠΌΠ΅ΡΠ½ΠΎΡΡΠΈ Π°Π½Π°Π»ΠΈΠ·ΠΈΡΡΠ΅ΠΌΡΡ
ΡΠ²Π»Π΅Π½ΠΈΠΉ, Π° ΡΠ°ΠΊΠΆΠ΅ Π·Π°ΠΊΠΎΠ½ΠΎΠΌΠ΅ΡΠ½ΠΎΡΡΠΈ, ΡΠΈΠΏΠΈΡΠ½ΡΠ΅ Π΄Π»Ρ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΡΡ
ΡΡΡΠ°Π½. Π‘ΠΎΠ·Π΄Π°Π½Π½Π°Ρ ΠΌΠΎΠ΄Π΅Π»Ρ ΠΌΠΎΠΆΠ΅Ρ Π±ΡΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½Π° Π΄Π»Ρ ΠΏΠΎΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠΈ ΠΏΡΠΎΡΠ΅Π΄ΡΡ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΠ»Π°Π½ΠΈΡΡΠ΅ΠΌΠΎΠ³ΠΎ ΡΠ½Π΅ΡΠ³ΠΎΠΏΠΎΡΡΠ΅Π±Π»Π΅Π½ΠΈΡ Π½Π° Π½Π°ΡΠΈΠΎΠ½Π°Π»ΡΠ½ΠΎΠΌ ΠΈ ΠΌΠ΅ΠΆΠ΄ΡΠ½Π°ΡΠΎΠ΄Π½ΠΎΠΌ ΡΡΠΎΠ²Π½ΡΡ
.ΠΠ΄ΡΠΉΡΠ½Π΅Π½ΠΎ ΡΠΏΡΠΎΠ±Ρ ΠΏΠΎΠ±ΡΠ΄ΡΠ²Π°ΡΠΈ ΠΌΠΎΠ΄Π΅Π»Ρ ΡΠΏΠΎΠΆΠΈΠ²Π°Π½Π½Ρ Π΅Π½Π΅ΡΠ³ΡΡ Π· ΡΡΠ°Ρ
ΡΠ²Π°Π½Π½ΡΠΌ ΠΌΠ°ΠΊΡΠΎΠ΅ΠΊΠΎΠ½ΠΎΠΌΡΡΠ½ΠΈΡ
ΡΠ°ΠΊΡΠΎΡΡΠ², ΡΠ°ΠΊΠΈΡ
ΡΠΊ ΠΠΠ, ΡΠ½Π΄Π΅ΠΊΡ ΡΡΠ½ ΡΠΏΠΎΠΆΠΈΠ²Π°ΡΠ°, ΡΠ° Π΄Π΅ΠΌΠΎΠ³ΡΠ°ΡΡΡΠ½ΠΈΡ
Π΄Π°Π½ΠΈΡ
. ΠΠ°ΠΏΡΠΎΠΏΠΎΠ½ΠΎΠ²Π°Π½Π° ΠΌΠΎΠ΄Π΅Π»Ρ Π΄ΠΎΠ·Π²ΠΎΠ»ΡΡ Π·Π° Π΄ΠΎΠΏΠΎΠΌΠΎΠ³ΠΎΡ ΠΌΠ΅Ρ
Π°Π½ΡΠ·ΠΌΡ Π²ΠΈΠΏΡΠ°Π²Π»Π΅Π½Π½Ρ ΠΏΠΎΡ
ΠΈΠ±ΠΎΠΊ Π²ΠΈΠ·Π½Π°ΡΠΈΡΠΈ ΠΊΠΎΡΠΎΡΠΊΠΎ- Ρ Π΄ΠΎΠ²Π³ΠΎΡΡΡΠΎΠΊΠΎΠ²Ρ ΡΡΠΎΡΡΠ½ΠΊΠΈ ΠΌΡΠΆ Π·ΠΌΡΠ½Π½ΠΈΠΌΠΈ, ΡΠΎ Π°Π½Π°Π»ΡΠ·ΡΡΡΡΡΡ. ΠΠΈΠΊΠΎΡΠΈΡΡΠ°Π½ΠΎ ΠΏΡΠΎΡΡΠΎΡΠΎΠ²ΠΎ-ΡΠ°ΡΠΎΠ²Ρ Π²ΠΈΠ±ΡΡΠΊΡ Π΄Π°Π½ΠΈΡ
Π· 1980 ΠΏΠΎ 2005 Ρ. ΠΏΠΎ ΠΊΡΠ°ΡΠ½Π°ΠΌ ΠΠ²ΡΠΎΠΏΠ΅ΠΉΡΡΠΊΠΎΠ³ΠΎ Π‘ΠΎΡΠ·Ρ. ΠΠ°ΡΡΠΎΡΡΠ²Π°Π½Π½Ρ ΡΠ°ΠΊΠΎΡ ΠΏΠ΅ΡΠ΅Ρ
ΡΠ΅ΡΠ½ΠΎΡ Π²ΠΈΠ±ΡΡΠΊΠΈ ΡΠ° ΡΠΎΠ·ΠΊΠ»Π°Π΄Π°Π½Π½Ρ ΡΠ°ΡΠΎΠ²ΠΎΠ³ΠΎ ΠΏΠ΅ΡΡΠΎΠ΄Ρ Π΄ΠΎΠ·Π²ΠΎΠ»ΡΡ Π²ΠΈΠ·Π½Π°ΡΠΈΡΠΈ Π΄Π΅ΡΠΊΡ Π·Π°Π³Π°Π»ΡΠ½Ρ Π·Π°ΠΊΠΎΠ½ΠΎΠΌΡΡΠ½ΠΎΡΡΡ ΡΠ²ΠΈΡΠ°, ΡΠΎ Π°Π½Π°Π»ΡΠ·ΡΡΡΡΡΡ, Π° ΡΠ°ΠΊΠΎΠΆ Π·Π°ΠΊΠΎΠ½ΠΎΠΌΡΡΠ½ΠΎΡΡΡ, ΡΠΈΠΏΠΎΠ²Ρ Π΄Π»Ρ Π²ΠΈΠ·Π½Π°ΡΠ΅Π½ΠΈΡ
ΠΊΡΠ°ΡΠ½. Π ΠΎΠ·ΡΠΎΠ±Π»Π΅Π½Ρ ΠΌΠΎΠ΄Π΅Π»Ρ ΠΌΠΎΠΆΠ½Π° Π²ΠΈΠΊΠΎΡΠΈΡΡΠΎΠ²ΡΠ²Π°ΡΠΈ Π΄Π»Ρ ΠΏΡΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠΈ ΠΏΡΠΎΡΠ΅Π΄ΡΡ ΠΌΠΎΠ΄Π΅Π»ΡΠ²Π°Π½Π½Ρ ΡΠ° ΠΏΡΠΎΠ³Π½ΠΎΠ·ΡΠ²Π°Π½Π½Ρ Π΅Π½Π΅ΡΠ³ΠΎΡΠΏΠΎΠΆΠΈΠ²Π°Π½Π½Ρ, ΡΠΎ ΠΏΠ»Π°Π½ΡΡΡΡΡΡ, Π½Π° Π½Π°ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΎΠΌΡ ΡΠ° ΠΌΡΠΆΠ½Π°ΡΠΎΠ΄Π½ΠΎΠΌΡ ΡΡΠ²Π½ΡΡ
Everolimus Exposure and Early Metabolic Response as Predictors of Treatment Outcomes in Breast Cancer Patients Treated with Everolimus and Exemestane
Imaging- and therapeutic targets in neoplastic and musculoskeletal inflammatory diseas
The TA Framework: Designing Real-time Teaching Augmentation for K-12 Classrooms
Recently, the HCI community has seen increased interest in the design of
teaching augmentation (TA): tools that extend and complement teachers'
pedagogical abilities during ongoing classroom activities. Examples of TA
systems are emerging across multiple disciplines, taking various forms: e.g.,
ambient displays, wearables, or learning analytics dashboards. However, these
diverse examples have not been analyzed together to derive more fundamental
insights into the design of teaching augmentation. Addressing this opportunity,
we broadly synthesize existing cases to propose the TA framework. Our framework
specifies a rich design space in five dimensions, to support the design and
analysis of teaching augmentation. We contextualize the framework using
existing designs cases, to surface underlying design trade-offs: for example,
balancing actionability of presented information with teachers' needs for
professional autonomy, or balancing unobtrusiveness with informativeness in the
design of TA systems. Applying the TA framework, we identify opportunities for
future research and design.Comment: to be published in Proceedings of the 2020 CHI Conference on Human
Factors in Computing Systems, 17 pages, 10 figure
Relationships between performance traits and the expressions of growth hormone, insulin-Like growth facto -I, and insulin in pigs selected for growth or leanness
Selection for growth rate or backfat thickness (BFT) in pigs is related with changes in the blood plasma concentrations of growth hormone (GH) and insulin-like growth factor-I (IGF-I). Two experimental pig selection lines based upon a common commercial Large White (LW) selection line were selected for increased growth rate (F-line), or decreased BFT (L-line), respectively. We report here on the statistical evaluation of the phenotypic relationships between growth rate and BFT on the one hand, and (1) mRNA expression levels of GH and its transcription factor pituitary-specific transcription factor-1 (Pit-1), (2) GH protein plasma pulse pattern components and (3) IGF-I and insulin plasma concentrations on the other hand. Residual regression coefficients (RRC) and residual correlation coefficients (RCC) were used to evaluate the phenotypic residual relations between the traits and the hormone levels. Growth hormone mRNA levels, and to a lesser extent Pit-1 mRNA levels, were inversely related with BFT and growth rate when these traits were fitted separately in the model suggesting that GH is more closely related to the traits than Pit-1. Within line evaluation showed that GH mRNA levels had significant RRC with the performance traits in both lines, while Pit-1 mRNA levels were only significantly related to BFT in the L-line in both analyses. When growth rate and BFT were fitted together in the model GH mRNA levels had also significantly RRC with growth rate and BFT. Growth hormone mRNA levels seem to be more closely related with BFT than with growth rate. Growth rate was inversely related with the GH plasma baseline value in both lines. Growth hormone baseline concentration, and to a lesser extent GH area under the curve, were inversely related to BFT. However, GH level-line-specific effects were only found for the baseline concentration in the F-line. A positive relationship between growth rate and plasma IGF-I concentrations was found in the L-line. These results suggest a relationship between GH mRNA expression and performance traits in pig lines selected for growth rate or against BFT. No such relationship could be found for its pituitary-specific transcription factor. Furthermore, specific components of the GH blood plasma pulse pattern were related to specific performance traits in these selection lines. The IGF-I blood plasma concentrations were related to growth rate in these selection lines
The association between specific activity components and depression in nursing home residents:the importance of the social component
OBJECTIVES: To longitudinally explore the association between activities and depressive symptoms of nursing home (NH) residents, taking into account that each activity may contain multiple components (physical, creative, social, cognitive, and musical). METHOD: Study with a baseline and two follow-ups (four and eight months). Participants were forty physically frail residents of four NHs in the Netherlands. Residents were interviewed about depressive symptoms (CES-D) and activities they conducted over the previous week. Three researchers independently rank ordered each activity on the degree to which it could be regarded as having physical, creative, social, cognitive, and musical components. Accounting for the rank score and the time the resident spent on that activity, residents were categorized per activity component into four levels: absent, low, medium, and high. RESULTS: Mixed models predicting depressive symptoms from individual activity components showed significant associations for the social and cognitive components. Compared with the lowest activity level, the analyses showed fewer depressive symptoms for all higher levels of the social and cognitive components. However, a mixed model adjusted for all activity components showed no unique effect of the cognitive component or other components, while the effects of the social component remained significant. The analyses did not show differences between the time points. CONCLUSION: The results suggest that the effects of activities on depressive symptoms might be mainly explained by their social component. It is, thus, important to always stimulate social involvement and interaction when developing and applying depression interventions. However, intervention research is needed to confirm these findings