The effects of qualitatively different acute physical activity interventions in real-world settings on executive functions in preadolescent children

There is growing evidence indicating a positive effect of acute physical activity on cognitive performance in children. Most of the evidence originates, however, from studies in highly controlled laboratory settings. The aim of the present study was to investigate whether the same effects can be found in more real-world settings. We examined the effects of qualitatively different acute physical activity interventions on the three core dimensions of executive functions (updating, inhibition, shifting). In an experimental between-subject design, 219 ten to twelve year-olds were assigned to one of four conditions which varied systematically in physical activation and cognitive engagement. Executive functions were measured before and immediately after the intervention. Contrary to the hypothesis, no effects of acute physical activity with and without cognitive engagement were found on executive functions in the overall sample. Only children with higher fitness and/or higher academic achievement benefitted from the interventions in terms of their updating performance. Thus, the results indicate that it may be more difficult to attain positive effects through acute physical activity in real-world settings than in laboratory settings and that physiological and cognitive requirements may have to be adjusted to individual capacity to make an intervention effective.

Constraining age distributions of groundwater from public supply wells in diverse hydrogeological settings in Scania, Sweden

Twenty-five public supply wells throughout the hydrogeologically diverse region of Scania, southern Sweden are subjected to environmental tracer analysis (³H–³He,⁴He, CFCs, SF₆ and for one well only also ⁸⁵Kr and ³⁹Ar) to study well and aquifer vulnerability and evaluate possibilities of groundwater age distribution assessment. We find CFC and SF₆ concentrations well above solubility equilibrium with modern atmosphere, indicating local contamination, as well as indications of CFC degradation. The tracer-specific complications considerably constrain possibilities for sound quantitative regional ground- water age distribution assessment and demonstrate the importance of initial qualitative assessment of tracer-specific reliability, as well a need for additional, complementary tracers (e.g. ⁸⁵Kr,³⁹Ar and potentially also ¹⁴C). Lumped parameter modelling yields credible age distribution assessments for representative wells in four type aquifers. Pollution vulnerability of the aquifer types was based on the selected LPM models and qualitative age characterisation. Most vulnerable are unconfined dual porosity and fractured bedrock aquifers, due to a large component of very young groundwater. Unconfined sedimentary aquifers are vulnerable due to young groundwater and a small pre-modern component. Less vulnerable are semi-confined sedimentary or dual-porosity aquifers, due to older age of the modern component and a larger pre-modern component. Confined aquifers appear least vulnerable, due an entirely pre-modern groundwater age distribution (recharged before 1963). Tracer complications aside, environmental tracer analyses and lumped parameter modelling aid in vulnerability assessment and protection of regional groundwater resources.

Determinants of Weight Evolution Among HIV-Positive Patients Initiating Antiretroviral Treatment in Low-Resource Settings.

BACKGROUND In resource-limited settings, clinical parameters, including body weight changes, are used to monitor clinical response. Therefore, we studied body weight changes in patients on antiretroviral treatment (ART) in different regions of the world. METHODS Data were extracted from the "International Epidemiologic Databases to Evaluate AIDS," a network of ART programmes that prospectively collects routine clinical data. Adults on ART from the Southern, East, West, and Central African and the Asia-Pacific regions were selected from the database if baseline data on body weight, gender, ART regimen, and CD4 count were available. Body weight change over the first 2 years and the probability of body weight loss in the second year were modeled using linear mixed models and logistic regression, respectively. RESULTS Data from 205,571 patients were analyzed. Mean adjusted body weight change in the first 12 months was higher in patients started on tenofovir and/or efavirenz; in patients from Central, West, and East Africa, in men, and in patients with a poorer clinical status. In the second year of ART, it was greater in patients initiated on tenofovir and/or nevirapine, and for patients not on stavudine, in women, in Southern Africa and in patients with a better clinical status at initiation. Stavudine in the initial regimen was associated with a lower mean adjusted body weight change and with weight loss in the second treatment year. CONCLUSIONS Different ART regimens have different effects on body weight change. Body weight loss after 1 year of treatment in patients on stavudine might be associated with lipoatrophy.

Implementation and Operational Research: Risk Charts to Guide Targeted HIV-1 Viral Load Monitoring of ART: Development and Validation in Patients From Resource-Limited Settings.

BACKGROUND HIV-1 RNA viral load (VL) testing is recommended to monitor antiretroviral therapy (ART) but not available in many resource-limited settings. We developed and validated CD4-based risk charts to guide targeted VL testing. METHODS We modeled the probability of virologic failure up to 5 years of ART based on current and baseline CD4 counts, developed decision rules for targeted VL testing of 10%, 20%, or 40% of patients in 7 cohorts of patients starting ART in South Africa, and plotted cutoffs for VL testing on colour-coded risk charts. We assessed the accuracy of risk chart-guided VL testing to detect virologic failure in validation cohorts from South Africa, Zambia, and the Asia-Pacific. RESULTS In total, 31,450 adult patients were included in the derivation and 25,294 patients in the validation cohorts. Positive predictive values increased with the percentage of patients tested: from 79% (10% tested) to 98% (40% tested) in the South African cohort, from 64% to 93% in the Zambian cohort, and from 73% to 96% in the Asia-Pacific cohort. Corresponding increases in sensitivity were from 35% to 68% in South Africa, from 55% to 82% in Zambia, and from 37% to 71% in Asia-Pacific. The area under the receiver operating curve increased from 0.75 to 0.91 in South Africa, from 0.76 to 0.91 in Zambia, and from 0.77 to 0.92 in Asia-Pacific. CONCLUSIONS CD4-based risk charts with optimal cutoffs for targeted VL testing maybe useful to monitor ART in settings where VL capacity is limited.

Extreme River Floods in Western Switzerland and the Lake of Constance Region in the Period Prior to Instrumental Measurements

The floods that occurred on the Aare and Rhine rivers in May 2015 and the mostly successful handling of this event in terms of flood protection measures are a good reminder of how important it is to comprehend the causes and processes involved in such natural hazards. While the needed data series of gauge measurements and peak discharge calculations reach back to the 19th century, historical records dating further back in time can provide additional and useful information to help understanding extreme flood events and to evaluate prevention measures such as river dams and corrections undertaken prior to instrumental measurements. In my PhD project I will use a wide range of historical sources to assess and quantify past extreme flood events. It is part of the SNF-funded project “Reconstruction of the Genesis, Process and Impact of Major Pre-instrumental Flood Events of Major Swiss Rivers Including a Peak Discharge Quantification” and will cover the research locations Fribourg (Saane R.), Burgdorf (Emme R.), Thun, Bern (both Aare R.), and the Lake of Constance at the locations Lindau, Constance and Rorschach. My main goals are to provide a long time series of quantitative data for extreme flood events, to discuss the occurring changes in these data, and to evaluate the impact of the aforementioned human influences on the drainage system. Extracting information given in account books from the towns of Basel and Solothurn may also enable me to assess the frequency and seasonality of less severe river floods. Finally, historical information will be used for remodeling the historical hydrological regime to homogenize the historical data series to modern day conditions and thus make it comparable to the data provided by instrumental measurements. The method I will apply for processing all information provided by historical sources such as chronicles, newspapers, institutional records, as well as flood marks, paintings and archeological evidence has been developed and successfully applied to the site of Basel by Wetter et al. (2011). They have also shown that data homogenization is possible by reconstructing previous stream flow conditions using historical river profiles and by carefully observing and re-constructing human changes of the river bed and its surroundings. Taken all information into account, peak discharges for past extreme flood events will be calculated with a one-dimensional hydrological model.

Impact of Software Settings on Multiple-Breath Washout Outcomes

BACKGROUND AND OBJECTIVES Multiple-breath washout (MBW) is an attractive test to assess ventilation inhomogeneity, a marker of peripheral lung disease. Standardization of MBW is hampered as little data exists on possible measurement bias. We aimed to identify potential sources of measurement bias based on MBW software settings. METHODS We used unprocessed data from nitrogen (N2) MBW (Exhalyzer D, Eco Medics AG) applied in 30 children aged 5-18 years: 10 with CF, 10 formerly preterm, and 10 healthy controls. This setup calculates the tracer gas N2 mainly from measured O2 and CO2concentrations. The following software settings for MBW signal processing were changed by at least 5 units or >10% in both directions or completely switched off: (i) environmental conditions, (ii) apparatus dead space, (iii) O2 and CO2 signal correction, and (iv) signal alignment (delay time). Primary outcome was the change in lung clearance index (LCI) compared to LCI calculated with the settings as recommended. A change in LCI exceeding 10% was considered relevant. RESULTS Changes in both environmental and dead space settings resulted in uniform but modest LCI changes and exceeded >10% in only two measurements. Changes in signal alignment and O2 signal correction had the most relevant impact on LCI. Decrease of O2 delay time by 40 ms (7%) lead to a mean LCI increase of 12%, with >10% LCI change in 60% of the children. Increase of O2 delay time by 40 ms resulted in mean LCI decrease of 9% with LCI changing >10% in 43% of the children. CONCLUSIONS Accurate LCI results depend crucially on signal processing settings in MBW software. Especially correct signal delay times are possible sources of incorrect LCI measurements. Algorithms of signal processing and signal alignment should thus be optimized to avoid susceptibility of MBW measurements to this significant measurement bias.

Comparison of patients in three different rehabilitation settings after knee or hip arthroplasty: a natural observational, prospective study.

BACKGROUND Patients after primary hip or knee replacement surgery can benefit from postoperative treatment in terms of improvement of independence in ambulation, transfers, range of motion and muscle strength. After discharge from hospital, patients are referred to different treatment destination and modalities: intensive inpatient rehabilitation (IR), cure (medically prescribed stay at a convalescence center), or ambulatory treatment (AT) at home. The purpose of this study was to 1) measure functional health (primary outcome) and function relevant factors in patients with hip or knee arthroplasty and to compare them in relation to three postoperative management strategies: AT, Cure and IR and 2) compare the post-operative changes in patient's health status (between preoperative and the 6 month follow-up) for three rehabilitation settings. METHODS Natural observational, prospective two-center study with follow-up. Sociodemographic data and functional mobility tests, Timed Up and Go (TUG) and Iowa Level of Assistance Scale (ILOAS) of 201 patients were analysed before arthroplasty and at the end of acute hospital stay (mean duration of stay: 9.7 days +/- 3.9). Changes in health state were measured with the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) before and 6 months after arthroplasty. RESULTS Compared to patients referred for IR and Cure, patients referred for AT were significantly younger and less comorbid. Patients admitted to IR had the highest functional disability before arthroplasty. Before rehabilitation, mean TUG was 40.0 s in the IR group, 33.9 s in the Cure group, and 27.5 s in the AT group, and corresponding mean ILOAS was 16.0, 13.0 and 12.2 (50.0 = worst). At the 6 months follow-up, the corresponding effect sizes of the WOMAC global score were 1.32, 1.87, and 1.51 (>0 means improvement). CONCLUSIONS Age, comorbidity and functional disability are associated with referral for intensive inpatient rehabilitation after hip or knee arthroplasty and partly affect health changes after rehabilitation.

Pitfalls of practicing cancer epidemiology in resource-limited settings: the case of survival and loss to follow-up after a diagnosis of Kaposi's sarcoma in five countries across sub-Saharan Africa.

BACKGROUND Survival after diagnosis is a fundamental concern in cancer epidemiology. In resource-rich settings, ambient clinical databases, municipal data and cancer registries make survival estimation in real-world populations relatively straightforward. In resource-poor settings, given the deficiencies in a variety of health-related data systems, it is less clear how well we can determine cancer survival from ambient data. METHODS We addressed this issue in sub-Saharan Africa for Kaposi's sarcoma (KS), a cancer for which incidence has exploded with the HIV epidemic but for which survival in the region may be changing with the recent advent of antiretroviral therapy (ART). From 33 primary care HIV Clinics in Kenya, Uganda, Malawi, Nigeria and Cameroon participating in the International Epidemiologic Databases to Evaluate AIDS (IeDEA) Consortia in 2009-2012, we identified 1328 adults with newly diagnosed KS. Patients were evaluated from KS diagnosis until death, transfer to another facility or database closure. RESULTS Nominally, 22% of patients were estimated to be dead by 2 years, but this estimate was clouded by 45% cumulative lost to follow-up with unknown vital status by 2 years. After adjustment for site and CD4 count, age <30 years and male sex were independently associated with becoming lost. CONCLUSIONS In this community-based sample of patients diagnosed with KS in sub-Saharan Africa, almost half became lost to follow-up by 2 years. This precluded accurate estimation of survival. Until we either generally strengthen data systems or implement cancer-specific enhancements (e.g., tracking of the lost) in the region, insights from cancer epidemiology will be limited.

Exploring professional orientations to community voice in professional practice settings: The IMAP process

The tension between technical experts and the populations they seek to serve is well established in the literature examining professional social problem solving. In this piece, I examine this tension as one between the distinct discursive worlds of technical expertise and community voice. I develop an analytic process, IMAP, for exploring this tension by looking at a wide variety of professional orientations around a relatively fixed concept of community voice. IMAP involves I&barbelow;dentifying social problem solvers, M&barbelow;apping social problem solvers' claims, A&barbelow;nalyzing professional orientations that arise from this mapping, and P&barbelow;redicting, diagnosing, and remediating conflicts. IMAP can be used by analysts external to social problem solving settings or by social problem solvers themselves. The use of IMAP by external experts poses questions of expert alignment with either of the discursive worlds. I examine two cases in public health practice settings: a mobile immunization service and the efforts of a foundation to improve health in an inner-city neighborhood. I develop four modal types that can be anticipated in social problem solving settings or, more specifically, in public health practice. Understanding of these “world views” can enhance mutual understanding between public health professionals and between public health professionals and the communities they seek to serve. IMAP might also address ongoing conflicts to clarify differences in unspoken normative commitments and the impact of these on social problem solving. I discuss implications of the research for public health practice and further research in the area. ^

Comparing the factorial structure, invariance, and predictive validity of transtheoretical model constructs for alcohol use across restricted and unrestricted settings

With substance abuse treatment expanding in prisons and jails, understanding how behavior change interacts with a restricted setting becomes more essential. The Transtheoretical Model (TTM) has been used to understand intentional behavior change in unrestricted settings, however, evidence indicates restrictive settings can affect the measurement and structure of the TTM constructs. The present study examined data from problem drinkers at baseline and end-of-treatment from three studies: (1) Project CARE (n = 187) recruited inmates from a large county jail; (2) Project Check-In (n = 116) recruited inmates from a state prison; (3) Project MATCH, a large multi-site alcohol study had two recruitment arms, aftercare (n = 724 pre-treatment and 650 post-treatment) and outpatient (n = 912 pre-treatment and 844 post-treatment). The analyses were conducted using cross-sectional data to test for non-invariance of measures of the TTM constructs: readiness, confidence, temptation, and processes of change (Structural Equation Modeling, SEM) across restricted and unrestricted settings. Two restricted (jail and aftercare) and one unrestricted group (outpatient) entering treatment and one restricted (prison) and two unrestricted groups (aftercare and outpatient) at end-of-treatment were contrasted. In addition TTM end-of-treatment profiles were tested as predictors of 12 month drinking outcomes (Profile Analysis). Although SEM did not indicate structural differences in the overall TTM construct model across setting types, there were factor structure differences on the confidence and temptation constructs at pre-treatment and in the factor structure of the behavioral processes at the end-of-treatment. For pre-treatment temptation and confidence, differences were found in the social situations factor loadings and in the variance for the confidence and temptation latent factors. For the end-of-treatment behavioral processes, differences across the restricted and unrestricted settings were identified in the counter-conditioning and stimulus control factor loadings. The TTM end-of-treatment profiles were not predictive of drinking outcomes in the prison sample. Both pre and post-treatment differences in structure across setting types involved constructs operationalized with behaviors that are limited for those in restricted settings. These studies suggest the TTM is a viable model for explicating addictive behavior change in restricted settings but calls for modification of subscale items that refer to specific behaviors and caution in interpreting the mean differences across setting types for problem drinkers. ^

Physician and patient determinants of the treatment of sleep difficulties in U.S. outpatient settings

The prevalence of sleep difficulties among the patients seen in the primary care settings is about 30%. This problem increases with age and is more common among females than males. Variations are noticed in prescription choices for different patients with sleep difficulties. Many factors affect a physician's prescription decision while chosen from a wide array of available medications. Both pharmacological and behavioral therapies are available for the treatment of sleep difficulties. It is important to know the impact of use of different types of prescriptions on health outcomes related to sleep difficulties. Thus the knowledge of prescription patterns among different types of patients (e.g. age, gender, race, insurance type etc.) becomes important for determining a clinical guideline. This study is designed to assist in evidence-based policymaking on understanding the variations in physician prescriptions for sleep difficulties and reasons for such variations. ^ A modified version of the model suggested by Eisenberg was used as a theoretical framework for this study to predict the factors influencing treatment of sleep difficulties. Multivariate logistic regression methods were used to analyze the 1996–2001 National Ambulatory Medical Care Survey data. ^ This study found that increased age, female gender, white race, established patients, and mental comorbidity were associated with significantly increased likelihood for prescription of some type of therapy for sleep difficulties in US outpatient settings. Patients with private insurance were associated with lower likelihood of receipt of many therapies. Psychiatrists were more likely to prescribe some kind of treatment as well as more expensive therapies for sleep difficulty as compared to other physician specialties. HMO enrolled patient visits were more likely to be associated with receipt of behavioral therapy. This study also found that 32% of patients with sleep difficulties received no type of therapy during their visits. Only 5% of the patients received behavioral therapy only. Almost three-quarters of the patients receiving some kind of medication prescription were prescribed benzodiazepines. The study results also suggest a need for wider coverage of behavioral therapy by payers in US outpatient settings. ^

An empirical model to estimate the demand for primary care in urban settings

Objective. To measure the demand for primary care and its associated factors by building and estimating a demand model of primary care in urban settings.^ Data source. Secondary data from 2005 California Health Interview Survey (CHIS 2005), a population-based random-digit dial telephone survey, conducted by the UCLA Center for Health Policy Research in collaboration with the California Department of Health Services, and the Public Health Institute between July 2005 and April 2006.^ Study design. A literature review was done to specify the demand model by identifying relevant predictors and indicators. CHIS 2005 data was utilized for demand estimation.^ Analytical methods. The probit regression was used to estimate the use/non-use equation and the negative binomial regression was applied to the utilization equation with the non-negative integer dependent variable.^ Results. The model included two equations in which the use/non-use equation explained the probability of making a doctor visit in the past twelve months, and the utilization equation estimated the demand for primary conditional on at least one visit. Among independent variables, wage rate and income did not affect the primary care demand whereas age had a negative effect on demand. People with college and graduate educational level were associated with 1.03 (p < 0.05) and 1.58 (p < 0.01) more visits, respectively, compared to those with no formal education. Insurance was significantly and positively related to the demand for primary care (p < 0.01). Need for care variables exhibited positive effects on demand (p < 0.01). Existence of chronic disease was associated with 0.63 more visits, disability status was associated with 1.05 more visits, and people with poor health status had 4.24 more visits than those with excellent health status. ^ Conclusions. The average probability of visiting doctors in the past twelve months was 85% and the average number of visits was 3.45. The study emphasized the importance of need variables in explaining healthcare utilization, as well as the impact of insurance, employment and education on demand. The two-equation model of decision-making, and the probit and negative binomial regression methods, was a useful approach to demand estimation for primary care in urban settings.^