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PC Scores (pc + score)

Distribution by Scientific Domains

Medical Sciences	57%

Selected Abstracts

The spatial and temporal behaviour of the lower stratospheric temperature over the Southern Hemisphere: the MSU view.

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 4 2001
Part I: data, methodology, temporal behaviour
Abstract The lower stratosphere monthly temperature anomalies over the Southern Hemisphere derived from soundings made by the Microwave Sounding Unit (MSU) between 1979 and 1997 are analysed. Specifically MSU channel 4 temperature retrievals are considered. Principal component (PC) analysis with the S-mode approach is used in order to isolate grid points that covary in a similar manner and to determine the main features of their temporal behaviour. The first six PCs explain 81.3% of the variance and represent the different time variability patterns observed over the Southern Hemisphere for the ten area clusters determined by the method. The most important feature is common to all the PC score pattern,time series and corresponds to a negative linear trend present in almost all the Southern Hemisphere except over New Zealand and surrounding areas. The negative trend is largest over Antarctica. The remaining features of the temporal variability are different for each PC score and therefore for each cluster region over the Southern Hemisphere. The first PC score pattern shows the impact of the Chichón and Mt Pinatubo eruptions that each produced a 2-year warming over the tropical and sub-tropical lower stratosphere. This variability is orthogonal with the behaviour present over Antarctica. There are different anomalies between 1987 (El Niño) and 1988 (La Niña). This second PC does not show any evidence whatsoever of the volcanic eruptions. The semi-annual wave is present in the anomaly recurrence at mid to high latitudes. Over very low latitudes, close to the Equator, the Quasi-Biennial Oscillation (QBO) band of frequency is also present. Copyright © 2001 Royal Meteorological Society [source]

Downscaling temperature and precipitation: a comparison of regression-based methods and artificial neural networks

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 7 2001
J.T. Schoof
Abstract A comparison of two statistical downscaling methods for daily maximum and minimum surface air temperature, total daily precipitation and total monthly precipitation at Indianapolis, IN, USA, is presented. The analysis is conducted for two seasons, the growing season and the non-growing season, defined based on variability of surface air temperature. The predictors used in the downscaling are indices of the synoptic scale circulation derived from rotated principal components analysis (PCA) and cluster analysis of variables extracted from an 18-year record from seven rawinsonde stations in the Midwest region of the United States. PCA yielded seven significant components for the growing season and five significant components for the non-growing season. These PCs explained 86% and 83% of the original rawinsonde data for the growing and non-growing seasons, respectively. Cluster analysis of the PC scores using the average linkage method resulted in eight growing season synoptic types and twelve non-growing synoptic types. The downscaling of temperature and precipitation is conducted using PC scores and cluster frequencies in regression models and artificial neural networks (ANNs). Regression models and ANNs yielded similar results, but the data for each regression model violated at least one of the assumptions of regression analysis. As expected, the accuracy of the downscaling models for temperature was superior to that for precipitation. The accuracy of all temperature models was improved by adding an autoregressive term, which also changed the relative importance of the dominant anomaly patterns as manifest in the PC scores. Application of the transfer functions to model daily maximum and minimum temperature data from an independent time series resulted in correlation coefficients of 0.34,0.89. In accord with previous studies, the precipitation models exhibited lesser predictive capabilities. The correlation coefficient for predicted versus observed daily precipitation totals was less than 0.5 for both seasons, while that for monthly total precipitation was below 0.65. The downscaling techniques are discussed in terms of model performance, comparison of techniques and possible model improvements. Copyright © 2001 Royal Meteorological Society [source]

The spatial and temporal behaviour of the lower stratospheric temperature over the Southern Hemisphere: the MSU view.

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 4 2001
Part II: spatial behaviour
Abstract Monthly lower stratosphere temperature anomalies in a layer centred about 70 hPa, from the MSU data set are analysed for the period 1979,1997. T-mode approach principal component analysis (PCA) is used in order to obtain the leading spatial anomaly patterns and their sequences of occurrence throughout the period under study. Five principal components (PCs) are significantly different from the spatial distribution of noisy data. The patterns given by the PC scores represent ten typical spatial anomaly patterns: five correspond to the direct mode, that is to say anomaly fields with the same sign as the PC score patterns, and five have the opposite sign. The first three PCs represent simple spatial temperature anomaly distributions, with zonal wave 0 to wave 2 wave structures. The following significant PCs, orders four and five, display a more complex spatial behaviour, with wave 3 wave structures. The first two PC's frequency distribution in time, given by the PC loadings time series, do not show noticeable changes throughout the period analysed. The remaining three PCs show changes in their frequency of occurrence that might be associated with the negative trends in the lower stratosphere temperature, as well as to the other different features observed in the real temperature anomaly time series for the grid points in the Southern Hemisphere. The latter are studied with the PCA in the S-mode approach in the companion paper (Compagnucci et al., 2001. International Journal of Climatology21: 419,437). Copyright © 2001 Royal Meteorological Society [source]

Quality-of-life and asthma-severity in general population asthmatics: results of the ECRHS II study

ALLERGY, Issue 5 2008
V. Siroux
Background: Health-related quality-of-life (HRQL) has been poorly studied in large samples of asthmatics from the general population. HRQL and its relationship to asthma-severity were assessed among 900 asthmatics enrolled in the European Community Respiratory Health Survey. Methods: Among asthmatics, 864 completed the short form-36 (SF-36) questionnaire and 477 also completed the Asthma Quality-of-life Questionnaire (AQLQ). A 4-class asthma-severity scale, combining clinical items, forced expiratory volume in 1 s and the level of treatment and the different asthma-severity components (each of the clinical items and hospitalization) were studied in relation to HRQL. Results: Mean SF-36 Physical Component Summary (PCS) and Mental Component Summary (MCS) scores (45.5 and 48.8 respectively) were lower than expected in a general population. The mean total AQLQ score was 5.8. The AQLQ score and to a lesser extent the PCS score were significantly related to the 4-class asthma-severity scale, although the risk of having a lower HRQL score did not vary proportionally across the levels of severity. Asthma-severity had no impact on the MCS score. Asthma attack frequency and hospitalization were associated with both total AQLQ and PCS scores, whereas nocturnal symptoms and lung function were more strongly related to the AQLQ and PCS score respectively. Conclusion: In population-based asthmatics, the specific AQLQ questionnaire, and also to a lesser extent the generic SF-36 questionnaire, were sensitive to asthma-severity. Frequencies of asthma attacks, of nocturnal symptoms and hospitalization for asthma have independent impact on HRQL. [source]

Burden of Medical Illness in Drug- and Alcohol-dependent Persons Without Primary Care

THE AMERICAN JOURNAL ON ADDICTIONS, Issue 1 2004
Israel De Alba M.D., M.P.H.
Little is known about the frequency, severity, and risk factors for disease in drug- and alcohol-dependent persons without primary medical care. Our aims are to assess the burden of medical illness, identify patient and substance dependence characteristics associated with worse physical health, and compare measures of illness burden in this population. This was accomplished through a cross-sectional study among alcohol-, heroin- or cocaine-dependent persons without primary medical care who were admitted to an urban inpatient detoxification unit. The mean age of these patients was 35.7 (SD 7.8) years; 76% were male and 46% were Black. Forty-five percent reported being diagnosed with a chronic illness, and 80% had prior medical hospitalizations. The mean age-adjusted SF-36 Physical Component Summary (PCS) score was lower than the general U.S. population norm (44.1 vs 50.1; p < 0.001). In multivariable analysis, female gender (adjusted mean change in PCS score: ,3.71 points, p = .002), problem use of hallucinogens (,3.51, p = 0.013), heroin (,2.94, p = 0.008), other opiates (,3.20, p = .045), living alone (,3.15, p = .023), having medical insurance (,2.26, p = 0.014) and older age (,.22 points per year, p = 0.001) were associated with worse health. From these data, it seems that alcohol- and drug-dependent persons without primary medical care have a substantial burden of medical illness compared to age- and gender-matched U.S. population controls. While the optimal measure of medical illness burden in this population is unclear, a variety of health measures document this medical illness burden in addicted persons. [source]

Quality of life and depression of people living with type 2 diabetes mellitus and those at low and high risk for type 2 diabetes: findings from the Study to Help Improve Early evaluation and management of risk factors Leading to Diabetes (SHIELD)

INTERNATIONAL JOURNAL OF CLINICAL PRACTICE, Issue 4 2008
S. Grandy
Summary Objectives:, This study compared health-related quality of life (HRQoL) and depression among individuals with type 2 diabetes mellitus (T2D) and those at low or high risk for T2D. Methods:, Respondents in a population-based US 2004 survey reported whether they had T2D (n = 3530) or risk factors for T2D [abdominal obesity, body mass index (BMI) , 28 kg/m2, dyslipidaemia, hypertension and history of cardiovascular disease]. Respondents without T2D were stratified into low risk (0,2 risk factors, n = 5335) and high risk (3,5 risk factors, n = 5051). SF-12 version 2 (SF-12) and Patient Health Questionnaire (PHQ)-9 were used to measure HRQoL and depression. Mean scores were compared across the three groups using analysis of variance. Linear regression identified factors associated with SF-12 Physical and Mental Component Summary scores (PCS and MCS), adjusting for age, gender, race, income, geographic region, household size, BMI and group. Results:, Respondents were mostly women (60%) with mean age of 54 years. Mean PCS scores for T2D and high risk (39.5 and 41.7, respectively) were significantly lower than for low risk (50.6, p < 0.001). After adjustment, high-risk and T2D groups were associated with lower PCS and MCS scores compared with low risk group (p < 0.05). Mean PHQ-9 scores and per cent with moderate-to-severe depression were significantly higher for T2D and high risk than for low risk (p < 0.01). Conclusions:, Health-related quality of life and depression scores in T2D were similar to those at high risk, and indicated significant decrements in physical health and greater depression compared with low-risk respondents. [source]