919 resultados para repeated measures


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BACKGROUND: Western studies have suggested that emotional stress and distress impacted on the morbidity and mortality in people following acute coronary events. Symptoms of anxiety and depression have been associated with re-infarction and death, prolonged recovery and disability and depression may precipitate the client's low self-esteem. This study examined perceived anxiety, depression and self-esteem of Hong Kong Chinese clients diagnosed with acute coronary syndrome (ACS) over a 6-month period following hospital admission. OBJECTIVES: To examine: DESIGN: A prospective, repeated measures design with measures taken on two occasions over a 6-month period; (1) within the 1st week of hospital admission following the onset of ACS and (2) at 6 months follow up. SETTING AND PARTICIPANTS: Convenient sample of 182 voluntary consented clients admitted with ACS to a major public hospital in Hong Kong who could communicate in Chinese, complete questionnaires, cognitive intact, and were haemodynamically stable and free from acute chest pain at the time of interview. METHODS: Baseline data were obtained within 1 week after hospital admission. The follow-up data was collected 6 months after hospital discharge. The Chinese version of the Hospital Anxiety and Depression Scale (HADS), State Self-esteem Scale (SSES), and Rosenberg's Self-Esteem Scale (RSES) were used to assess anxiety and depression, state self-esteem, and trait self-esteem, respectively. RESULTS: Findings suggested gender differences in clients' perception in anxiety, depression and self-esteem. Improvements in clients' perception of these variables were evident over the 6-month period following their acute coronary events. CONCLUSION: The study confirmed the western notion that psychosocial problems are common among coronary clients and this also applies to Hong Kong Chinese diagnosed with ACS. Further studies to explore effective interventions to address these psychosocial issues are recommended.

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We consider rank-based regression models for repeated measures. To account for possible withinsubject correlations, we decompose the total ranks into between- and within-subject ranks and obtain two different estimators based on between- and within-subject ranks. A simple perturbation method is then introduced to generate bootstrap replicates of the estimating functions and the parameter estimates. This provides a convenient way for combining the corresponding two types of estimating function for more efficient estimation.

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The method of generalized estimating equation-, (GEEs) has been criticized recently for a failure to protect against misspecification of working correlation models, which in some cases leads to loss of efficiency or infeasibility of solutions. However, the feasibility and efficiency of GEE methods can be enhanced considerably by using flexible families of working correlation models. We propose two ways of constructing unbiased estimating equations from general correlation models for irregularly timed repeated measures to supplement and enhance GEE. The supplementary estimating equations are obtained by differentiation of the Cholesky decomposition of the working correlation, or as score equations for decoupled Gaussian pseudolikelihood. The estimating equations are solved with computational effort equivalent to that required for a first-order GEE. Full details and analytic expressions are developed for a generalized Markovian model that was evaluated through simulation. Large-sample ".sandwich" standard errors for working correlation parameter estimates are derived and shown to have good performance. The proposed estimating functions are further illustrated in an analysis of repeated measures of pulmonary function in children.

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Objective To demonstrate the potential value of screening for Down's Syndrome using highly correlated repeated measures of serum markers taken in the first and second trimesters of pregnancy. Design A Monte Carlo simulation study. Population Detection rates and false positive rates relating to the maternal age distribution of England and Wales for the period 1996 to 1998 were obtained using marker distributions from the SURUSS study. Results Screening using first trimester nuchal translucency and repeated measures of uE3 and PAPP-A in the first and second trimester has an estimated false positive rate of 0.3% for an 85% detection rate. This should be compared with the integrated test with an estimated false positive rate of 1.2% for the same detection rate. Conclusionsâ?? The performance of repeated measures screening tests, and their acceptability to women, should be assessed in further prospective studies.

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Obesity has been linked with elevated levels of C-reactive protein (CRP), and both have been associated with increased risk of mortality and cardiovascular disease (CVD). Previous studies have used a single ‘baseline’ measurement and such analyses cannot account for possible changes in these which may lead to a biased estimation of risk. Using four cohorts from CHANCES which had repeated measures in participants 50 years and older, multivariate time-dependent Cox proportional hazards was used to estimate hazard ratios (HR) and 95 % confidence intervals (CI) to examine the relationship between body mass index (BMI) and CRP with all-cause mortality and CVD. Being overweight (≥25–<30 kg/m2) or moderately obese (≥30–<35) tended to be associated with a lower risk of mortality compared to normal (≥18.5–<25): ESTHER, HR (95 % CI) 0.69 (0.58–0.82) and 0.78 (0.63–0.97); Rotterdam, 0.86 (0.79–0.94) and 0.80 (0.72–0.89). A similar relationship was found, but only for overweight in Glostrup, HR (95 % CI) 0.88 (0.76–1.02); and moderately obese in Tromsø, HR (95 % CI) 0.79 (0.62–1.01). Associations were not evident between repeated measures of BMI and CVD. Conversely, increasing CRP concentrations, measured on more than one occasion, were associated with an increasing risk of mortality and CVD. Being overweight or moderately obese is associated with a lower risk of mortality, while CRP, independent of BMI, is positively associated with mortality and CVD risk. If inflammation links CRP and BMI, they may participate in distinct/independent pathways. Accounting for independent changes in risk factors over time may be crucial for unveiling their effects on mortality and disease morbidity.

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School playtime provides daily opportunities for children to be active outdoors, but only makes small contributions to physical activity (PA) requirements. Natural environments facilitate unstructured PA and children report a preference for play in nature. Thus, play on the school field might encourage children to be more active during playtime. The primary aim of this study was to examine the impact of the school playing environment on children's PA. Descriptive data and fitness were assessed in 25 children aged 8–9 years from a single primary school. Over two consecutive weeks participants were allocated to either play on the school field or playground during playtime. The order of play in the two areas was randomised and counterbalanced. Moderate to vigorous PA (MVPA) was assessed during playtime on the last two days of each week using accelerometers. There was a significant interaction of environment and sex on MVPA during morning play (F(1,22) = 6.27; P<0.05; np2 = 0.222), but not during lunch (P>0.05; np2 = 0.060) or all of playtime combined (P>0.05; np2 = 0.140). During morning play boys were significantly more active than girls on the playground (t(23) = 1.32; P<0.01; n2 = 0.291), but not on the field (P>0.05; n2 = 0.071). For lunch (F(1,22) = 24,11; P<0.001; np2 = 0.523) and all of playtime combined (F(1,22) = 33.67; P<0.001; np2 = 0.616) there was a significant effect of environment. There was also a significant main effect of sex during lunch (F(1,22) = 11.56; P<0.01; np2 = 0.344) and all of playtime combined (F(1,22) = 12.37; P<0.01; np2 = 0.371). MVPA was higher on the field and boys were more active than girls. Play on the field leads to increases in MVPA, particularly in girls. The promising trend for the effect of the natural environment on MVPA indicates that interventions aimed at increasing MVPA should use the natural environment and that schools should encourage greater use of their natural areas to increase PA.

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Exercising in natural, green environments creates greater improvements in adult's self-esteem than exercise undertaken in urban or indoor settings. No comparable data are available for children. The aim of this study was to determine whether so called ‘green exercise’ affected changes in self-esteem; enjoyment and perceived exertion in children differently to urban exercise. We assessed cardiorespiratory fitness (20 m shuttle-run) and self-reported physical activity (PAQ-A) in 11 and 12 year olds (n = 75). Each pupil completed two 1.5 mile timed runs, one in an urban and another in a rural environment. Trials were completed one week apart during scheduled physical education lessons allocated using a repeated measures design. Self-esteem was measured before and after each trial, ratings of perceived exertion (RPE) and enjoyment were assessed after completing each trial. We found a significant main effect (F (1,74), = 12.2, p<0.001), for the increase in self-esteem following exercise but there was no condition by exercise interaction (F (1,74), = 0.13, p = 0.72). There were no significant differences in perceived exertion or enjoyment between conditions. There was a negative correlation (r = −0.26, p = 0.04) between habitual physical activity and RPE during the control condition, which was not evident in the green exercise condition (r = −0.07, p = 0.55). Contrary to previous studies in adults, green exercise did not produce significantly greater increases in self-esteem than the urban exercise condition. Green exercise was enjoyed more equally by children with differing levels of habitual physical activity and has the potential to engage less active children in exercise.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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This paper considers a wide class of semiparametric problems with a parametric part for some covariate effects and repeated evaluations of a nonparametric function. Special cases in our approach include marginal models for longitudinal/clustered data, conditional logistic regression for matched case-control studies, multivariate measurement error models, generalized linear mixed models with a semiparametric component, and many others. We propose profile-kernel and backfitting estimation methods for these problems, derive their asymptotic distributions, and show that in likelihood problems the methods are semiparametric efficient. While generally not true, with our methods profiling and backfitting are asymptotically equivalent. We also consider pseudolikelihood methods where some nuisance parameters are estimated from a different algorithm. The proposed methods are evaluated using simulation studies and applied to the Kenya hemoglobin data.