Underestimation of Standard Errors in Multi-Site Time Series Studies

Multi-site time series studies of air pollution and mortality and morbidity have figured prominently in the literature as comprehensive approaches for estimating acute effects of air pollution on health. Hierarchical models are generally used to combine site-specific information and estimate pooled air pollution effects taking into account both within-site statistical uncertainty, and across-site heterogeneity. Within a site, characteristics of time series data of air pollution and health (small pollution effects, missing data, highly correlated predictors, non linear confounding etc.) make modelling all sources of uncertainty challenging. One potential consequence is underestimation of the statistical variance of the site-specific effects to be combined. In this paper we investigate the impact of variance underestimation on the pooled relative rate estimate. We focus on two-stage normal-normal hierarchical models and on under- estimation of the statistical variance at the first stage. By mathematical considerations and simulation studies, we found that variance underestimation does not affect the pooled estimate substantially. However, some sensitivity of the pooled estimate to variance underestimation is observed when the number of sites is small and underestimation is severe. These simulation results are applicable to any two-stage normal-normal hierarchical model for combining information of site-specific results, and they can be easily extended to more general hierarchical formulations. We also examined the impact of variance underestimation on the national average relative rate estimate from the National Morbidity Mortality Air Pollution Study and we found that variance underestimation as much as 40% has little effect on the national average.

Bayesian Hierarchical Distributed Lag Models for Summer Ozone Exposure and Cardio-Respiratory Mortality

In this paper, we develop Bayesian hierarchical distributed lag models for estimating associations between daily variations in summer ozone levels and daily variations in cardiovascular and respiratory (CVDRESP) mortality counts for 19 U.S. large cities included in the National Morbidity Mortality Air Pollution Study (NMMAPS) for the period 1987 - 1994. At the first stage, we define a semi-parametric distributed lag Poisson regression model to estimate city-specific relative rates of CVDRESP associated with short-term exposure to summer ozone. At the second stage, we specify a class of distributions for the true city-specific relative rates to estimate an overall effect by taking into account the variability within and across cities. We perform the calculations with respect to several random effects distributions (normal, t-student, and mixture of normal), thus relaxing the common assumption of a two-stage normal-normal hierarchical model. We assess the sensitivity of the results to: 1) lag structure for ozone exposure; 2) degree of adjustment for long-term trends; 3) inclusion of other pollutants in the model;4) heat waves; 5) random effects distributions; and 6) prior hyperparameters. On average across cities, we found that a 10ppb increase in summer ozone level for every day in the previous week is associated with 1.25 percent increase in CVDRESP mortality (95% posterior regions: 0.47, 2.03). The relative rate estimates are also positive and statistically significant at lags 0, 1, and 2. We found that associations between summer ozone and CVDRESP mortality are sensitive to the confounding adjustment for PM_10, but are robust to: 1) the adjustment for long-term trends, other gaseous pollutants (NO_2, SO_2, and CO); 2) the distributional assumptions at the second stage of the hierarchical model; and 3) the prior distributions on all unknown parameters. Bayesian hierarchical distributed lag models and their application to the NMMAPS data allow us estimation of an acute health effect associated with exposure to ambient air pollution in the last few days on average across several locations. The application of these methods and the systematic assessment of the sensitivity of findings to model assumptions provide important epidemiological evidence for future air quality regulations.

ESTIMATING TEMPORAL ASSOCIATIONS IN ELECTROCORTICOGRAPHIC (ECoG) TIME SERIES WITH FIRST ORDER PRUNING

Granger causality (GC) is a statistical technique used to estimate temporal associations in multivariate time series. Many applications and extensions of GC have been proposed since its formulation by Granger in 1969. Here we control for potentially mediating or confounding associations between time series in the context of event-related electrocorticographic (ECoG) time series. A pruning approach to remove spurious connections and simultaneously reduce the required number of estimations to fit the effective connectivity graph is proposed. Additionally, we consider the potential of adjusted GC applied to independent components as a method to explore temporal relationships between underlying source signals. Both approaches overcome limitations encountered when estimating many parameters in multivariate time-series data, an increasingly common predicament in today's brain mapping studies.

Seasonal Analyses of Air Pollution and Mortality in 100 U.S. Cities

Time series models relating short-term changes in air pollution levels to daily mortality counts typically assume that the effects of air pollution on the log relative rate of mortality do not vary with time. However, these short-term effects might plausibly vary by season. Changes in the sources of air pollution and meteorology can result in changes in characteristics of the air pollution mixture across seasons. The authors develop Bayesian semi-parametric hierarchical models for estimating time-varying effects of pollution on mortality in multi-site time series studies. The methods are applied to the updated National Morbidity and Mortality Air Pollution Study database for the period 1987--2000, which includes data for 100 U.S. cities. At the national level, a 10 micro-gram/m3 increase in PM(10) at lag 1 is associated with a 0.15 (95% posterior interval: -0.08, 0.39),0.14 (-0.14, 0.42), 0.36 (0.11, 0.61), and 0.14 (-0.06, 0.34) percent increase in mortality for winter, spring, summer, and fall, respectively. An analysis by geographical regions finds a strong seasonal pattern in the northeast (with a peak in summer) and little seasonal variation in the southern regions of the country. These results provide useful information for understanding particle toxicity and guiding future analyses of particle constituent data.

Does tenofovir influence efavirenz pharmacokinetics?

INTRODUCTION: A recent report described a possible interaction between tenofovir (TFV) and efavirenz (EFV). Patients developed neuropsychiatric manifestations upon introduction of TFV on a stable EFV-containing regimen. We evaluated the possibility of a pharmacokinetic interaction between TFV and EFV by assessing cross-sectional and longitudinal data in 169 individuals receiving EFV. RESULTS: EFV plasma area-under-the-curve (AUC) levels were comparable among individuals receiving (n=18) or not receiving TFV (n=151); 57,962 versus 52,293 ng*h/ml. However, under conditions of limited EFV metabolism, that is, the group of 23 individuals carrying two copies of CYP2B6 loss/diminished-function alleles, plasma AUC values were highest among individuals receiving TFV (n=5, 353,031 ng*h/ml), compared with those not receiving TFV (n=18, 180,689 ng*h/ml). Statistical analysis identified both a global, sixfold effect of CYP2B6 loss/diminished function (P < 0.0001) and a significant interaction between the number of loss/diminished-function alleles and the co-medication with TFV (P = 0.009). CONCLUSION: Although there is no clear evidence for a pharmacokinetic interaction between TFV and EFV, we cannot rule out an interaction between these drugs restricted to individuals who are slow EFV metabolizers.

Epidemiology of candidemia in Swiss tertiary care hospitals: secular trends, 1991-2000

Candida species are among the most common bloodstream pathogens in the United States, where the emergence of azole-resistant Candida glabrata and Candida krusei are major concerns. Recent comprehensive longitudinal data from Europe are lacking. We conducted a nationwide survey of candidemia during 1991-2000 in 17 university and university-affiliated hospitals representing 79% of all tertiary care hospital beds in Switzerland. The number of transplantations and bloodstream infections increased significantly (P<.001). A total of 1137 episodes of candidemia were observed: Candida species ranked seventh among etiologic agents (2.9% of all bloodstream isolates). The incidence of candidemia was stable over a 10-year period. C. albicans remained the predominant Candida species recovered (66%), followed by C. glabrata (15%). Candida tropicalis emerged (9%), the incidence of Candida parapsilosis decreased (1%), and recovery of C. krusei remained rare (2%). Fluconazole consumption increased significantly (P<.001). Despite increasing high-risk activities, the incidence of candidemia remained unchanged, and no shift to resistant species occurred.

Growth curves for cardio-metabolic risk factors in children and adolescents

OBJECTIVE: This study developed percentile curves for anthropometric (waist circumference) and cardiovascular (lipid profile) risk factors for US children and adolescents. STUDY DESIGN: A representative sample of US children and adolescents from the National Health and Nutrition Examination Survey from 1988 to 1994 (NHANES III) and the current national series (NHANES 1999-2006) were combined. Percentile curves were constructed, nationally weighted, and smoothed using the Lambda, Mu, and Sigma method. The percentile curves included age- and sex-specific percentile values that correspond with and transition into the adult abnormal cut-off values for each of these anthropometric and cardiovascular components. To increase the sample size, a second series of percentile curves was also created from the combination of the 2 NHANES databases, along with cross-sectional data from the Bogalusa Heart Study, the Muscatine Study, the Fels Longitudinal Study and the Princeton Lipid Research Clinics Study. RESULTS: These analyses resulted in a series of growth curves for waist circumference, total cholesterol, LDL cholesterol, triglycerides, and HDL cholesterol from a combination of pediatric data sets. The cut-off for abnormal waist circumference in adult males (102 cm) was equivalent to the 94(th) percentile line in 18-year-olds, and the cut-off in adult females (88 cm) was equivalent to the 84(th) percentile line in 18-year-olds. Triglycerides were found to have a bimodal pattern among females, with an initial peak at age 11 and a second at age 20; the curve for males increased steadily with age. The HDL curve for females was relatively flat, but the male curve declined starting at age 9 years. Similar curves for total and LDL cholesterol were constructed for both males and females. When data from the additional child studies were added to the national data, there was little difference in their patterns or rates of change from year to year. CONCLUSIONS: These curves represent waist and lipid percentiles for US children and adolescents, with identification of values that transition to adult abnormalities. They could be used conditionally for both epidemiological and possibly clinical applications, although they need to be validated against longitudinal data.

Low self-esteem prospectively predicts depression in adolescence and young adulthood

Low self-esteem and depression are strongly correlated in cross-sectional studies, yet little is known about their prospective effects on each other. The vulnerability model hypothesizes that low self-esteem serves as a risk factor for depression, whereas the scar model hypothesizes that low self-esteem is an outcome, not a cause, of depression. To test these models, the authors used 2 large longitudinal data sets, each with 4 repeated assessments between the ages of 15 and 21 years and 18 and 21 years, respectively. Cross-lagged regression analyses indicated that low self-esteem predicted subsequent levels of depression, but depression did not predict subsequent levels of self-esteem. These findings held for both men and women and after controlling for content overlap between the self-esteem and depression scales. Thus, the results supported the vulnerability model, but not the scar model, of self-esteem and depression.

Social Structural Effects on the Level and Development of the Individual Experience of Anomie in the German Population

Can one observe an increasing level of individual lack of orientation because of rapid social change in modern societies? This question is examined using data from a representative longitudinal survey in Germany conducted in 2002–04. The study examines the role of education, age, sex, region (east/west), and political orientation for the explanation of anomia and its development. First we present the different sources of anomie in modern societies, based on the theoretical foundations of Durkheim and Merton, and introduce the different definitions of anomia, including our own cognitive version. Then we deduce several hypotheses from the theory, which we test by means of longitudinal data for the period 2002–04 in Germany using the latent growth curve model as our statistical method. The empirical findings show that all the sociodemographic variables, including political orientation, are strong predictors of the initial level of anomia. Regarding the development of anomia over time (2002–04), only the region (west) has a significant impact. In particular, the results of a multi-group analysis show that western German people with a right-wing political orientation become more anomic over this period. The article concludes with some theoretical implications.

Comparison of phenotypes of childhood wheeze and cough in 2 independent cohorts

BACKGROUND Among children with wheeze and recurrent cough there is great variation in clinical presentation and time course of the disease. We previously distinguished 5 phenotypes of wheeze and cough in early childhood by applying latent class analysis to longitudinal data from a population-based cohort (original cohort). OBJECTIVE To validate previously identified phenotypes of childhood cough and wheeze in an independent cohort. METHODS We included 903 children reporting wheeze or recurrent cough from an independent population-based cohort (validation cohort). As in the original cohort, we used latent class analysis to identify phenotypes on the basis of symptoms of wheeze and cough at 2 time points (preschool and school age) and objective measurements of atopy, lung function, and airway responsiveness (school age). Prognostic outcomes (wheeze, bronchodilator use, cough apart from colds) 5 years later were compared across phenotypes. RESULTS When using a 5-phenotype model, the analysis distinguished 3 phenotypes of wheeze and 2 of cough as in the original cohort. Two phenotypes were closely similar in both cohorts: Atopic persistent wheeze (persistent multiple trigger wheeze and chronic cough, atopy and reduced lung function, poor prognosis) and transient viral wheeze (early-onset transient wheeze with viral triggers, favorable prognosis). The other phenotypes differed more between cohorts. These differences might be explained by differences in age at measurements. CONCLUSIONS Applying the same method to 2 different cohorts, we consistently identified 2 phenotypes of wheeze (atopic persistent wheeze, transient viral wheeze), suggesting that these represent distinct disease processes. Differences found in other phenotypes suggest that the age when features are assessed is critical and should be considered carefully when defining phenotypes.

Governing individual learning in the transition phase of software maintenance offshoring: a dynamic perspective

Prior studies suggest that clients need to actively govern knowledge transfer to vendor staff in offshore outsourcing. In this paper, we analyze longitudinal data from four software maintenance offshore out-sourcing projects to explore why governance may be needed for knowledge transfer and how governance and the individual learning of vendor engineers inter-act over time. Our results suggest that self-control is central to learning, but may be hampered by low levels of trust and expertise at the outset of projects. For these foundations to develop, clients initially need to exert high amounts of formal and clan controls to enforce learning activities against barriers to knowledge sharing. Once learning activities occur, trust and expertise increase and control portfolios may show greater emphases on self-control.

Cost-effectiveness of point-of-care viral load monitoring of antiretroviral therapy in resource-limited settings: mathematical modelling study

BACKGROUND Monitoring of HIV viral load in patients on combination antiretroviral therapy (ART) is not generally available in resource-limited settings. We examined the cost-effectiveness of qualitative point-of-care viral load tests (POC-VL) in sub-Saharan Africa. DESIGN Mathematical model based on longitudinal data from the Gugulethu and Khayelitsha township ART programmes in Cape Town, South Africa. METHODS Cohorts of patients on ART monitored by POC-VL, CD4 cell count or clinically were simulated. Scenario A considered the more accurate detection of treatment failure with POC-VL only, and scenario B also considered the effect on HIV transmission. Scenario C further assumed that the risk of virologic failure is halved with POC-VL due to improved adherence. We estimated the change in costs per quality-adjusted life-year gained (incremental cost-effectiveness ratios, ICERs) of POC-VL compared with CD4 and clinical monitoring. RESULTS POC-VL tests with detection limits less than 1000 copies/ml increased costs due to unnecessary switches to second-line ART, without improving survival. Assuming POC-VL unit costs between US$5 and US$20 and detection limits between 1000 and 10,000 copies/ml, the ICER of POC-VL was US$4010-US$9230 compared with clinical and US$5960-US$25540 compared with CD4 cell count monitoring. In Scenario B, the corresponding ICERs were US$2450-US$5830 and US$2230-US$10380. In Scenario C, the ICER ranged between US$960 and US$2500 compared with clinical monitoring and between cost-saving and US$2460 compared with CD4 monitoring. CONCLUSION The cost-effectiveness of POC-VL for monitoring ART is improved by a higher detection limit, by taking the reduction in new HIV infections into account and assuming that failure of first-line ART is reduced due to targeted adherence counselling.

Actigraphic monitoring of physical activity in clinical trials in schizophrenia

Schizophrenia is still associated with poor outcome, which is mainly related to negative symptoms, reduced physical activity and low quality of life. Physical activity can be objectively measured without distress using wrist actigraphy. The activity levels during the wake periods of the day have been informative on psychopathology and antipsychotic medication. Several studies demonstrated prominent negative symptoms to be associated with reduced activity levels with strongest correlations in chronic patients. Particularly, the avolition score is correlated with reduced activity levels. Moreover, activity levels differ between DSM-IV schizophrenia spectrum disorders and subtypes as well as between patients treated with olanzapine or risperidone. The longitudinal course of activity levels during an psychotic episode demonstrates considerable variance between subjects. During a psychotic episode patients with low activity levels at baseline experience an amelioration of negative symptoms. In contrast, patients with high activity levels at baseline have stable low negative syndrome scores. Between psychotic episodes less variance is observed. Actigraphy is easily applied in schizophrenia and allows collecting large amounts of crosssectional or longitudinal data. With larger numbers of subjects in controlled trials, continuous recording of activity would foster the detection of different outcome trajectories, which may prove as useful groups to target interventions. In clinical trials, activity monitoring may supplement and validate measures of the negative syndrome and its avolition factor or serve as an outcome marker for physical activity, which is important for metabolic issues and quality of life.

Chronic NSAID use and long-term decline of renal function in a prospective rheumatoid arthritis cohort study

OBJECTIVES Non-steroidal anti-inflammatory drugs (NSAIDs) may cause kidney damage. This study assessed the impact of prolonged NSAID exposure on renal function in a large rheumatoid arthritis (RA) patient cohort. METHODS Renal function was prospectively followed between 1996 and 2007 in 4101 RA patients with multilevel mixed models for longitudinal data over a mean period of 3.2 years. Among the 2739 'NSAID users' were 1290 patients treated with cyclooxygenase type 2 selective NSAIDs, while 1362 subjects were 'NSAID naive'. Primary outcome was the estimated glomerular filtration rate according to the Cockroft-Gault formula (eGFRCG), and secondary the Modification of Diet in Renal Disease and Chronic Kidney Disease Epidemiology Collaboration formula equations and serum creatinine concentrations. In sensitivity analyses, NSAID dosing effects were compared for patients with NSAID registration in ≤/>50%, ≤/>80% or ≤/>90% of assessments. FINDINGS In patients with baseline eGFRCG >30 mL/min, eGFRCG evolved without significant differences over time between 'NSAID users' (mean change in eGFRCG -0.87 mL/min/year, 95% CI -1.15 to -0.59) and 'NSAID naive' (-0.67 mL/min/year, 95% CI -1.26 to -0.09, p=0.63). In a multivariate Cox regression analysis adjusted for significant confounders age, sex, body mass index, arterial hypertension, heart disease and for other insignificant factors, NSAIDs were an independent predictor for accelerated renal function decline only in patients with advanced baseline renal impairment (eGFRCG <30 mL/min). Analyses with secondary outcomes and sensitivity analyses confirmed these results. CONCLUSIONS NSAIDs had no negative impact on renal function estimates but in patients with advanced renal impairment.

Selection and influence effects in defending a victim of bullying: The moderating effects of school context

In this paper we examined whether defenders of victims of school bullying befriended similar peers, and whether the similarity is due to selection or influence processes or both. We examined whether these processes result in different degrees of similarity between peers depending on teachers’ self-efficacy and the school climate. We analyzed longitudinal data of 478 Swiss school students employing actor-based stochastic models. Our analyses showed that similarity in defending behavior among friends was due to selection rather than influence. The extent to which adolescents selected peers showing similar defending behavior was related to contextual factors. In fact, lower self-efficacy of teachers and positive school climate were associated with increased selection effects in terms of defending behavior.