Bayesian Inference under Cluster Sampling with Probability Proportional to Size

Cluster sampling is common in survey practice, and the corresponding inference has been predominantly design-based. We develop a Bayesian framework for cluster sampling and account for the design effect in the outcome modeling. We consider a two-stage cluster sampling design where the clusters are first selected with probability proportional to cluster size, and then units are randomly sampled inside selected clusters. Challenges arise when the sizes of nonsampled cluster are unknown. We propose nonparametric and parametric Bayesian approaches for predicting the unknown cluster sizes, with this inference performed simultaneously with the model for survey outcome. Simulation studies show that the integrated Bayesian approach outperforms classical methods with efficiency gains. We use Stan for computing and apply the proposal to the Fragile Families and Child Wellbeing study as an illustration of complex survey inference in health surveys

Sprint-interval but not continuous exercise increases PGC-1α protein content and p53 phosphorylation in nuclear fractions of human skeletal muscle

Sprint interval training has been reported to induce similar or greater mitochondrial adaptations to continuous training. However, there is limited knowledge about the effects of different exercise types on the early molecular events regulating mitochondrial biogenesis. Therefore, we compared the effects of continuous and sprint interval exercise on key regulatory proteins linked to mitochondrial biogenesis in subcellular fractions of human skeletal muscle. Nineteen men, performed either 24 min of moderate-intensity continuous cycling at 63% of W-Peak (CE), or 4 x 30-s "all-out" cycling sprints (SIE). Muscle samples (vastus lateralis) were collected pre-, immediately (+0 h) and 3 (+3 h) hours postexercise. Nuclear p53 and PHF20 protein content increased at +0 h, with no difference between groups. Nuclear p53 phosphorylation and PGC-1 alpha protein content increased at +0 h after SIE, but not CE. We demonstrate an exercise-induced increase in nuclear p53 protein content, an event that may relate to greater p53 stability - as also suggested by increased PHF20 protein content. Increased nuclear p53 phosphorylation and PGC-1 alpha protein content immediately following SIE but not CE suggests these may represent important early molecular events in the exercise-induced response to exercise, and that SIE is a time-efficient and possibly superior option than CE to promote these adaptations

Defining estuarine squeeze: the loss of upper estuarine transitional zones against in-channel barriers through saline intrusion

Here we define, for the first time, the concept of estuarine squeeze and lay out recommendations for the consistent use of terminology for this new but critical research area. Climate and catchment-driven reductions in river flow together with rising sea levels are increasing estuarine salinities and driving saltwater into upper estuarine zones. This saline intrusion is exacerbated in regions where land level is falling (i.e. relative sea level rise) and in catchments subject to high freshwater demand and water regulation, which reduces river flow. In unmodified systems, many estuaries would naturally migrate inland in response to sea level rise. However, estuaries are some of the most anthropogenically impacted ecosystems in the world, being settlement and development hubs due to the ecosystem services they provide. To protect these assets, many estuaries have man-made in-channel barriers (such as dams, weirs and sluices) at their inland tidal limits, a trend that is likely to continue in the future to protect against the impacts of climate change. As sea levels rise and river flows reduce, saltwater will move further inland. This increasing saline intrusion will be most detrimental for upper estuarine, low salinity (oligohaline) and tidal freshwater zones, which will progressively become ‘squeezed out’ against these barriers. We have termed this concept ‘estuarine squeeze’ and define this as ‘the progressive loss of extent of upper estuarine tidal freshwater and oligohaline zones against in-channel man-made barriers through saline intrusion and increasing salinities driven by relative sea level rise and/or reductions in river flow’. A lack of research into the structure and functioning of tidal freshwater zones in particular means that the impact of their reduction and/or loss on the wider estuary is unknown. However, there are indications that these zones may play a key role in estuarine biogeochemical cycling, habitat provision, primary and secondary production, food-web functioning, and the provision of trophic subsidies to the brackish estuary and coastal zone. Loss and/or reduction of these zones through estuarine squeeze may therefore result in a net loss of function, with critical implications for the ability of estuaries to continue to provide key ecosystem services into the future

Application of the speed-duration relationship to normalize the intensity of high-intensity interval training

The tolerable duration of continuous high-intensity exercise is determined by the hyperbolic Speed-tolerable duration (S-tLIM) relationship. However, application of the S-tLIM relationship to normalize the intensity of High-Intensity Interval Training (HIIT) has yet to be considered, with this the aim of present study. Subjects completed a ramp-incremental test, and series of 4 constant-speed tests to determine the S-tLIM relationship. A sub-group of subjects (n = 8) then repeated 4 min bouts of exercise at the speeds predicted to induce intolerance at 4 min (WR4), 6 min (WR6) and 8 min (WR8), interspersed with bouts of 4 min recovery, to the point of exercise intolerance (fixed WR HIIT) on different days, with the aim of establishing the work rate that could be sustained for 960 s (i.e. 4×4 min). A sub-group of subjects (n = 6) also completed 4 bouts of exercise interspersed with 4 min recovery, with each bout continued to the point of exercise intolerance (maximal HIIT) to determine the appropriate protocol for maximizing the amount of high-intensity work that can be completed during 4×4 min HIIT. For fixed WR HIIT tLIM of HIIT sessions was 399±81 s for WR4, 892±181 s for WR6 and 1517±346 s for WR8, with total exercise durations all significantly different from each other (P<0.050). For maximal HIIT, there was no difference in tLIM of each of the 4 bouts (Bout 1: 229±27 s; Bout 2: 262±37 s; Bout 3: 235±49 s; Bout 4: 235±53 s; P>0.050). However, there was significantly less high-intensity work completed during bouts 2 (153.5±40. 9 m), 3 (136.9±38.9 m), and 4 (136.7±39.3 m), compared with bout 1 (264.9±58.7 m; P>0.050). These data establish that WR6 provides the appropriate work rate to normalize the intensity of HIIT between subjects. Maximal HIIT provides a protocol which allows the relative contribution of the work rate profile to physiological adaptations to be considered during alternative intensity-matched HIIT protocols

Quantifying Selective Reporting and the Proteus Phenomenon for Multiple Datasets with Similar Bias

Meta-analyses play an important role in synthesizing evidence from diverse studies and datasets that address similar questions. A major obstacle for meta-analyses arises from biases in reporting. In particular, it is speculated that findings which do not achieve formal statistical significance are less likely reported than statistically significant findings. Moreover, the patterns of bias can be complex and may also depend on the timing of the research results and their relationship with previously published work. In this paper, we present an approach that is specifically designed to analyze large-scale datasets on published results. Such datasets are currently emerging in diverse research fields, particularly in molecular medicine. We use our approach to investigate a dataset on Alzheimer's disease (AD) that covers 1167 results from case-control studies on 102 genetic markers. We observe that initial studies on a genetic marker tend to be substantially more biased than subsequent replications. The chances for initial, statistically non-significant results to be published are estimated to be about 44% (95% CI, 32% to 63%) relative to statistically significant results, while statistically non-significant replications have almost the same chance to be published as statistically significant replications (84%; 95% CI, 66% to 107%). Early replications tend to be biased against initial findings, an observation previously termed Proteus phenomenon: The chances for non-significant studies going in the same direction as the initial result are estimated to be lower than the chances for non-significant studies opposing the initial result (73%; 95% CI, 55% to 96%). Such dynamic patters in bias are difficult to capture by conventional methods, where typically simple publication bias is assumed to operate. Our approach captures and corrects for complex dynamic patterns of bias, and thereby helps generating conclusions from published results that are more robust against the presence of different coexisting types of selective reporting

Estimating the incidence of acute infectious intestinal disease in the community in the UK:A retrospective telephone survey

Objectives: To estimate the burden of intestinal infectious disease (IID) in the UK and determine whether disease burden estimations using a retrospective study design differ from those using a prospective study design. Design/Setting: A retrospective telephone survey undertaken in each of the four countries comprising the United Kingdom. Participants were randomly asked about illness either in the past 7 or 28 days. Participants: 14,813 individuals for all of whom we had a legible recording of their agreement to participate Outcomes: Self-reported IID, defined as loose stools or clinically significant vomiting lasting less than two weeks, in the absence of a known non-infectious cause. Results: The rate of self-reported IID varied substantially depending on whether asked for illness in the previous 7 or 28 days. After standardising for age and sex, and adjusting for the number of interviews completed each month and the relative size of each UK country, the estimated rate of IID in the 7-day recall group was 1,530 cases per 1,000 person-years (95% CI: 1135 – 2113), while in the 28-day recall group it was 533 cases per 1,000 person-years (95% CI: 377 – 778). There was no significant variation in rates between the four countries. Rates in this study were also higher than in a related prospective study undertaken at the same time. Conclusions: The estimated burden of disease from IID varied dramatically depending on study design. Retrospective studies of IID give higher estimates of disease burden than prospective studies. Of retrospective studies longer recall periods give lower estimated rates than studies with short recall periods. Caution needs to be exercised when comparing studies of self-reported IID as small changes in study design or case definition can markedly affect estimated rates

Reporting of Human Genome Epidemiology (HuGE) association studies: An empirical assessment

<p>Abstract</p> <p>Background</p> <p>Several thousand human genome epidemiology association studies are published every year investigating the relationship between common genetic variants and diverse phenotypes. Transparent reporting of study methods and results allows readers to better assess the validity of study findings. Here, we document reporting practices of human genome epidemiology studies.</p> <p>Methods</p> <p>Articles were randomly selected from a continuously updated database of human genome epidemiology association studies to be representative of genetic epidemiology literature. The main analysis evaluated 315 articles published in 2001–2003. For a comparative update, we evaluated 28 more recent articles published in 2006, focusing on issues that were poorly reported in 2001–2003.</p> <p>Results</p> <p>During both time periods, most studies comprised relatively small study populations and examined one or more genetic variants within a single gene. Articles were inconsistent in reporting the data needed to assess selection bias and the methods used to minimize misclassification (of the genotype, outcome, and environmental exposure) or to identify population stratification. Statistical power, the use of unrelated study participants, and the use of replicate samples were reported more often in articles published during 2006 when compared with the earlier sample.</p> <p>Conclusion</p> <p>We conclude that many items needed to assess error and bias in human genome epidemiology association studies are not consistently reported. Although some improvements were seen over time, reporting guidelines and online supplemental material may help enhance the transparency of this literature.</p