212 resultados para hierarchical regression analysis


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Switzerland has the lowest adolescent fertility rate in Western Europe. According to data collected in 1993 as part of the Swiss Multicentre Adolescent Survey on Health, 5% of 1,726 sexually active adolescents in a group of 3,993 15-20-year-old women enrolled in academic or vocational classes had ever been pregnant; most of these women (80%) had terminated their pregnancy. Adolescents who had ever been pregnant did not differ significantly from those who had not by demographic characteristics. Multiple logistic regression analysis identified seven factors associated with pregnancy: having had four or more sexual partners; not having used contraceptives at first intercourse; ever use of less-effective contraceptive methods; having used illicit drugs during the last 30 days; living apart from one's parents; recently experiencing stress; and perceiving a lack of future prospects.

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The aim of this study was to evaluate the use of the pedometer in epidemiologic research on physical activity. Within the framework of a health examination survey in 1988-1989, physical activity was assessed in a representative population sample of 493 men and women aged 25-74 years who were residents of Switzerland. They wore a pedometer for 1 week at work and during leisure time, and the results, converted into steps per day, were compared with answers to a questionnaire. The average number of steps per day decreased from 11,900 to 6,700 and from 9,300 to 7,300 for men and women, respectively, in the youngest to the oldest age groups. For men, categorized according to type of physical activity at work, there was a highly significant difference in the number of steps (p < 0.001), whereas in women the results were associated with leisure-time physical activity (p = 0.003). For both sexes, practicing sports more than once a week was associated with an important increase in steps per day. Analyzing the number of steps according to the day of the week and occupational category produced an unexpected result: Men with a physically active job engaged in more leisure-time physical activity on the weekend. The pedometer proved to be useful in assessing physical activity in a large, free-living population.

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The resting metabolic rate (RMR) and body composition of 130 obese and nonobese prepubertal children, aged 6 to 10 years, were assessed by indirect calorimetry and skin-fold thickness, respectively. The mean (+/- SD) RMR was 4619 +/- 449 kJ.day-1 (164 +/- 31 kJ.kg body weight-1 x day-1) in the 62 boys and 4449 +/- 520 kJ.day-1 (147 +/- 32 kJ.kg body weight-1 x day-1) in the 68 girls. Fat-free mass was the best single predictor of RMR (R2 = 0.64; p < 0.001). Step-down multiple regression analysis, with independent variables such as age, gender, weight, and height, allowed several RMR predictive equations to be developed. An equation for boys is as follows: RMR (kJ.day-1) = 1287 + 28.6 x Weight(kg) + 23.6 x Height(cm) - 69.1 x Age(yr) (R2 = 0.58; p < 0.001). An equation for girls is as follows: RMR (kJ.day-1 = 1552 + 35.8 x Weight (kg) + 15.6 x Height (cm) - 36.3 x Age (yr) (R2 = 0.69; p < 0.001). Comparison between the measured RMR and that predicted by currently used formulas showed that most of these equations tended to overestimate the RMR of both genders, especially in overweight children.

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PURPOSE: The objective was to explore whether a satellite-based navigation system, global positioning system used in differential mode (DGPS), could accurately assess the speed of running in humans. METHODS: A subject was equipped with a portable GPS receptor coupled to a receiver for differential corrections, while running outdoors on a straight asphalt road at 27 different speeds. Actual speed (reference method) was assessed by chronometry. RESULTS: The accuracy of speed prediction had a standard deviation (SD) of 0.08 km x h(-1) for walking, 0.11 km x h(-1) for running, yielding a coefficient of variation (SD/mean) of 1.38% and 0.82%, respectively. There was a highly significant linear relationship between actual and DGPS speed assessment (r2 = 0.999) with little bias in the prediction equation, because the slope of the regression line was close to unity (0.997). CONCLUSION: the DGPS technique appears to be a valid and inconspicuous tool for "on line" monitoring of the speed of displacement of individuals located on any field on earth, for prolonged periods of time and unlimited distance, but only in specific environmental conditions ("open sky"). Furthermore, the accuracy of speed assessment using the differential GPS mode was improved by a factor of 10 as compared to non-differential GPS.

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Purpose: To compare the disease classification using optic nerve head imaging against clinical examination combined with perimetry in the case-finding environment.Methods: During a glaucoma screening event at the University Hospital in Lausanne 148 attendees opted to undergo an extended screening exam consisting of perimetry with Octopus (Haag-Streit, Koeniz, Switzerland), tonometry, gonioscopy, slit-lamp optic nerve head examination and Heidelberg Retinal Tomorgraph (HRT, Heidelberg engineering). Classification criteria of an abnormal clinical exam consisted of a cup to disc ratio > 0.6, other disc abnormality (e.g. notching), closed angles, Van Herrick < ¼ and intraocular pressure >21mmHg. In perimetry a square root loss variance (sLV) >3.0 dB was considered abnormal. Those cases with both an abnormal clinical exam and abnormal perimetric results were considered to be glaucoma suspects. An abnormal HRT exam was a global Moorfields Regression Analysis (MRA) result of "outside normal limits". The results from the worse eye for each instrument are reported.Results: The mean age of the patients was 59.9 years (SD ±14.8years). 46 subjects failed the clinical exam. 55 subjects had sLV>3.0dB. 86 subjects failed one or more of the testing components, 21 subjects failed both the clinical exam and perimetry. Two cases of advanced glaucoma were diagnosed on the day of the event. 20 subjects were referred due to other ocular pathology (10 cataract; 2 AMD; 8 other). 16 subjects were outside normal limits with the HRT, of which 11 failed the clinical exam, 9 failed the perimetric exam and 7 failed all three. HRT had a sensitivity of 33% CI [15%,57%] with a specificity of 93% CI [87%,97%].Conclusions: HRT shows good specificity, however the low sensitivity makes it of limited use in the proposed case finding scenario.

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OBJECTIVE:: To determine whether there are differences in health perception and health care use among adolescents with psychosomatic symptoms (PS), with chronic conditions (CCs), and with both conditions compared with healthy controls. METHODS:: By using the SMASH02 database, 4 groups were created: youths with PS but no CCs (N = 1010); youths with CCs but no PS (N = 497); youths with both psychosomatic symptoms and chronic conditions (PSCC, N = 213); and youths with neither PS nor CC (control, N = 5709). We used χ tests and analysis of variance to compare each variable between the 4 groups. In a second step, all health and health care use variables were included in a multinomial regression analysis controlling for significant (p < .05) background variables and using the control group as the reference. RESULTS:: Overall, PS and PSCC youths were significantly more likely to rate their health as poor, to be depressed, and to have consulted several times their primary health care provider or a mental health professional than their healthy peers. With the exception of being depressed, PSCC adolescents reported worse health perception and higher health care use than CC and PS. CONCLUSIONS:: Although PS youths do not define PS as a CC, it should be considered as one. Moreover, having PS represents an additional burden to chronically ill adolescents. Health professionals dealing with adolescents must be aware of the deleterious health effects that PS can have on adolescents and have this diagnosis in mind to better target the treatment and improve their management.

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BACKGROUND: Prognosis prediction for resected primary colon cancer is based on the T-stage Node Metastasis (TNM) staging system. We investigated if four well-documented gene expression risk scores can improve patient stratification. METHODS: Microarray-based versions of risk-scores were applied to a large independent cohort of 688 stage II/III tumors from the PETACC-3 trial. Prognostic value for relapse-free survival (RFS), survival after relapse (SAR), and overall survival (OS) was assessed by regression analysis. To assess improvement over a reference, prognostic model was assessed with the area under curve (AUC) of receiver operating characteristic (ROC) curves. All statistical tests were two-sided, except the AUC increase. RESULTS: All four risk scores (RSs) showed a statistically significant association (single-test, P < .0167) with OS or RFS in univariate models, but with HRs below 1.38 per interquartile range. Three scores were predictors of shorter RFS, one of shorter SAR. Each RS could only marginally improve an RFS or OS model with the known factors T-stage, N-stage, and microsatellite instability (MSI) status (AUC gains < 0.025 units). The pairwise interscore discordance was never high (maximal Spearman correlation = 0.563) A combined score showed a trend to higher prognostic value and higher AUC increase for OS (HR = 1.74, 95% confidence interval [CI] = 1.44 to 2.10, P < .001, AUC from 0.6918 to 0.7321) and RFS (HR = 1.56, 95% CI = 1.33 to 1.84, P < .001, AUC from 0.6723 to 0.6945) than any single score. CONCLUSIONS: The four tested gene expression-based risk scores provide prognostic information but contribute only marginally to improving models based on established risk factors. A combination of the risk scores might provide more robust information. Predictors of RFS and SAR might need to be different.

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Human papillomavirus type 6 (HPV6) is the major etiological agent of anogenital warts and laryngeal papillomas and has been included in both the quadrivalent and nonavalent prophylactic HPV vaccines. This study investigated the global genomic diversity of HPV6, using 724 isolates and 190 complete genomes from six continents, and the association of HPV6 genomic variants with geographical location, anatomical site of infection/disease, and gender. Initially, a 2,800-bp E5a-E5b-L1-LCR fragment was sequenced from 492/530 (92.8%) HPV6-positive samples collected for this study. Among them, 130 exhibited at least one single nucleotide polymorphism (SNP), indel, or amino acid change in the E5a-E5b-L1-LCR fragment and were sequenced in full. A global alignment and maximum likelihood tree of 190 complete HPV6 genomes (130 fully sequenced in this study and 60 obtained from sequence repositories) revealed two variant lineages, A and B, and five B sublineages: B1, B2, B3, B4, and B5. HPV6 (sub)lineage-specific SNPs and a 960-bp representative region for whole-genome-based phylogenetic clustering within the L2 open reading frame were identified. Multivariate logistic regression analysis revealed that lineage B predominated globally. Sublineage B3 was more common in Africa and North and South America, and lineage A was more common in Asia. Sublineages B1 and B3 were associated with anogenital infections, indicating a potential lesion-specific predilection of some HPV6 sublineages. Females had higher odds for infection with sublineage B3 than males. In conclusion, a global HPV6 phylogenetic analysis revealed the existence of two variant lineages and five sublineages, showing some degree of ethnogeographic, gender, and/or disease predilection in their distribution. IMPORTANCE: This study established the largest database of globally circulating HPV6 genomic variants and contributed a total of 130 new, complete HPV6 genome sequences to available sequence repositories. Two HPV6 variant lineages and five sublineages were identified and showed some degree of association with geographical location, anatomical site of infection/disease, and/or gender. We additionally identified several HPV6 lineage- and sublineage-specific SNPs to facilitate the identification of HPV6 variants and determined a representative region within the L2 gene that is suitable for HPV6 whole-genome-based phylogenetic analysis. This study complements and significantly expands the current knowledge of HPV6 genetic diversity and forms a comprehensive basis for future epidemiological, evolutionary, functional, pathogenicity, vaccination, and molecular assay development studies.

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OBJECTIVES: To measure postabsorptive fat oxidation (F(ox)) and to assess its association with body composition (lean body mass [LBM] and body fat mass [BFM]) and pubertal development. DESIGN: We studied 235 control (male/female ratio = 116/119; age [mean +/- SD]: 13.1 +/- 1.7 years; weight: 45.3 +/- 10.5 kg; LBM: 34.3 +/- 7.1 kg; BFM: 11.0 +/- 4.5 kg) and 159 obese (male/female ratio = 93/66; age: 12.9 +/- 2.1 years; weight: 76.2 +/- 19.1 kg; LBM: 47.4 +/- 10.9 kg; BFM: 28.8 +/- 9.2 kg) adolescents. Postabsorptive F(ox) was calculated from oxygen consumption, carbon dioxide production, and urinary nitrogen as measured by indirect calorimetry and Kjeldahl's method, respectively. Body composition was determined by anthropometry. RESULTS: Postabsorptive F(ox) (absolute value and percentage of resting metabolic rate) was significantly (p < 0.001) higher in the obese adolescents (76.7 +/- 26.3 gm/24 hours, 42.3% +/- 18.7%) than in the control subjects (40.0 +/- 26.3 gm/24 hours, 28.7% +/- 17.0%), even if adjusted for LBM. F(ox) corrected for BFM was similar in control and in obese children, but was significantly lower in girls compared with boys (control male subjects: 62.1 +/- 29.1 gm/24 hours, control female subjects: 51.6 +/- 28.4 gm/24 hours, obese male subjects: 57.3 +/- 29 gm/24 hour, obese female subjects: 45.0 +/- 28.4 gm/24 hours). BFM and LBM showed a significant positive correlation with F(ox). By stepwise regression analysis the most important determinant of F(ox) was BFM in obese and LBM in control children. There was a significant rise in F(ox) during puberty; however, it was mainly explained by changes in body composition. CONCLUSIONS: Obese adolescents have higher F(ox) rates than their normal-weight counterparts. Both LBM and fat mass are important determinants of F(ox).

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We evaluated the accuracy of skinfold thicknesses, BMI and waist circumference for the prediction of percentage body fat (PBF) in a representative sample of 372 Swiss children aged 6-13 years. PBF was measured using dual-energy X-ray absorptiometry. On the basis of a preliminary bootstrap selection of predictors, seven regression models were evaluated. All models included sex, age and pubertal stage plus one of the following predictors: (1) log-transformed triceps skinfold (logTSF); (2) logTSF and waist circumference; (3) log-transformed sum of triceps and subscapular skinfolds (logSF2); (4) log-transformed sum of triceps, biceps, subscapular and supra-iliac skinfolds (logSF4); (5) BMI; (6) waist circumference; (7) BMI and waist circumference. The adjusted determination coefficient (R² adj) and the root mean squared error (RMSE; kg) were calculated for each model. LogSF4 (R² adj 0.85; RMSE 2.35) and logSF2 (R² adj 0.82; RMSE 2.54) were similarly accurate at predicting PBF and superior to logTSF (R² adj 0.75; RMSE 3.02), logTSF combined with waist circumference (R² adj 0.78; RMSE 2.85), BMI (R² adj 0.62; RMSE 3.73), waist circumference (R² adj 0.58; RMSE 3.89), and BMI combined with waist circumference (R² adj 0.63; RMSE 3.66) (P < 0.001 for all values of R² adj). The finding that logSF4 was only modestly superior to logSF2 and that logTSF was better than BMI and waist circumference at predicting PBF has important implications for paediatric epidemiological studies aimed at disentangling the effect of body fat on health outcomes.

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The aim of this study was to investigate influence of traditional cardiovascular risk factors (CVRF) and subclinical atherosclerosis (ATS) burden on early stages of abdominal aortic diameter (AAD) widening among adults. 2,052 consecutive patients (P) (39 % women), mean age 52 ± 13 years, were prospectively screened for CVRF, ATS, and AAD. B-mode ultrasound was used to evaluate the largest AAD and to detect carotid and femoral atherosclerotic plaques. Mean AAD was 15.2 ± 2.8 mm. Atherosclerotic plaques were detected in 71 % of patients. Significant univariate correlation between AAD, traditional CVRF, and ABS was found. However, multiple regression analysis showed that only seven of them were significantly and weakly correlated with AAD (R² = 0.27, p < 0.001). On the other hand, a multivariate logistic analysis was used to evaluate CVRF impact on enlarged AAD ≥25 mm (EAAD) as compared to those with AAD <25 mm. These factors did not account for more than 30 % of interaction (R² = 0.30, p = 0.001). Furthermore, despite a large proportion of patients with high number of CVRF, and subclinical ATS, rate of patients with AAD ≥25 mm was low (1 %) and scattered regardless their CHD risk score or ATS burden. In conclusion, these results suggest that although some traditional CVRF and presence of ATS are associated with early stages of EAAD, other determinants still need to be identified for a better understanding of abdominal aortic aneurysm pathogenesis.

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Counterfeit pharmaceutical products have become a widespread problem in the last decade. Various analytical techniques have been applied to discriminate between genuine and counterfeit products. Among these, Near-infrared (NIR) and Raman spectroscopy provided promising results.The present study offers a methodology allowing to provide more valuable information fororganisations engaged in the fight against counterfeiting of medicines.A database was established by analyzing counterfeits of a particular pharmaceutical product using Near-infrared (NIR) and Raman spectroscopy. Unsupervised chemometric techniques (i.e. principal component analysis - PCA and hierarchical cluster analysis - HCA) were implemented to identify the classes within the datasets. Gas Chromatography coupled to Mass Spectrometry (GC-MS) and Fourier Transform Infrared Spectroscopy (FT-IR) were used to determine the number of different chemical profiles within the counterfeits. A comparison with the classes established by NIR and Raman spectroscopy allowed to evaluate the discriminating power provided by these techniques. Supervised classifiers (i.e. k-Nearest Neighbors, Partial Least Squares Discriminant Analysis, Probabilistic Neural Networks and Counterpropagation Artificial Neural Networks) were applied on the acquired NIR and Raman spectra and the results were compared to the ones provided by the unsupervised classifiers.The retained strategy for routine applications, founded on the classes identified by NIR and Raman spectroscopy, uses a classification algorithm based on distance measures and Receiver Operating Characteristics (ROC) curves. The model is able to compare the spectrum of a new counterfeit with that of previously analyzed products and to determine if a new specimen belongs to one of the existing classes, consequently allowing to establish a link with other counterfeits of the database.

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To assess the effect of weight loss on resting metabolic rate (RMR), the energy expenditure of eight obese prepubertal children (age 9 +/- 1 years; weight 48.7 +/- 9.1 kg; BMI 25.3 +/- 3.9) and of 14 age-matched children of normal body weight (age 9 +/- 1 years; weight 28.8 +/- 5.6 kg; BMI 16.5 +/- 1.7) was measured by indirect calorimetry. The obese children were reinvestigated after a mean weight loss of 5.4 +/- 1.2 kg induced by a six-months mixed hypocaloric diet. Before slimming, the obese group showed a higher daily energy intake than the control group (10.40 +/- 3.45 MJ/day vs 7.97 +/- 2.02 MJ/day respectively; P less than 0.05) but a similar value was observed per unit fat-free mass (FFM) (0.315 +/- 0.032 MJ/kgFFM/day vs 0.329 +/- 0.041 MJ/kgFFM/day respectively). The average RMR of the obese children was greater than that of the control group (5217 +/- 531 kJ/day vs 4477 +/- 506 kJ/day) but similar after adjusting for FFM (4728 +/- 3102 kJ/day vs 4899 +/- 3102 kJ/day). Weight loss resulted in a reduction in RMR (5217 +/- 531 kJ/day vs 4874 +/- 820 kJ/day), each kg of weight loss being accompanied by a decrease of RMR of 64 kJ (15.3 kcal) per day. The changes in RMR induced by weight loss paralleled the changes in FFM. No difference was found in average RQ in obese children vs controls (0.85 +/- 0.03 vs 0.87 +/- 0.03 respectively) and in the obese children before and after weight loss (0.87 +/- 0.02).(ABSTRACT TRUNCATED AT 250 WORDS)

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OBJECTIVE: To explore the potential relationship between fatigue following strokes and poststroke mood, cognitive dysfunction, disability, and infarct site and to determine the predictive factors in the development of poststroke fatigue (PSF) following minor infarcts. METHODS: Ninety-nine functionally active patients aged less than 70 years with a first, nondisabling stroke (NIH Stroke Scale score ≤6 in acute phase and ≤3 after 6 months, modified Rankin Scale score ≤1 at 6 months) were assessed during the acute phase and then at 6 (T1) and 12 months (T2) after their stroke. Scores in the Fatigue Assessment Inventory were described and correlated to age, gender, neurologic and functional impairment, lesion site, mood scores, neuropsychological data, laboratory data, and quality of life at T1 and T2 using a multivariate logistic regression analysis in order to determine which variables recorded at T1 best predicted fatigue at T2. RESULT: As many as 30.5% of the patients at T1 and 34.7% at T2 (11.6% new cases between T1 and T2) reported fatigue. At both 6 and 12 months, there was a significant association between fatigue and a reduction in professional activity. Attentional-executive impairment, depression, and anxiety levels remained associated with PSF throughout this time period, underlining the critical role of these variables in the genesis of PSF. There was no significant association between the lesion site and PSF. CONCLUSION: This study suggests that attentional and executive impairment, as well as depression and anxiety, may play a critical role in the development of PSF.

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BACKGROUND AND PURPOSE: Beyond the Framingham Stroke Risk Score, prediction of future stroke may improve with a genetic risk score (GRS) based on single-nucleotide polymorphisms associated with stroke and its risk factors. METHODS: The study includes 4 population-based cohorts with 2047 first incident strokes from 22,720 initially stroke-free European origin participants aged ≥55 years, who were followed for up to 20 years. GRSs were constructed with 324 single-nucleotide polymorphisms implicated in stroke and 9 risk factors. The association of the GRS to first incident stroke was tested using Cox regression; the GRS predictive properties were assessed with area under the curve statistics comparing the GRS with age and sex, Framingham Stroke Risk Score models, and reclassification statistics. These analyses were performed per cohort and in a meta-analysis of pooled data. Replication was sought in a case-control study of ischemic stroke. RESULTS: In the meta-analysis, adding the GRS to the Framingham Stroke Risk Score, age and sex model resulted in a significant improvement in discrimination (all stroke: Δjoint area under the curve=0.016, P=2.3×10(-6); ischemic stroke: Δjoint area under the curve=0.021, P=3.7×10(-7)), although the overall area under the curve remained low. In all the studies, there was a highly significantly improved net reclassification index (P<10(-4)). CONCLUSIONS: The single-nucleotide polymorphisms associated with stroke and its risk factors result only in a small improvement in prediction of future stroke compared with the classical epidemiological risk factors for stroke.