Gastrointestinal complaints in runners are not due to small intestinal bacterial overgrowth

<p>Abstract</p> <p>Background</p> <p>Gastrointestinal complaints are common among long distance runners. We hypothesised that small intestinal bacterial overgrowth (SIBO) is present in long distance runners frequently afflicted with gastrointestinal complaints.</p> <p>Findings</p> <p>Seven long distance runners (5 female, mean age 29.1 years) with gastrointestinal complaints during and immediately after exercise without known gastrointestinal diseases performed Glucose hydrogen breath tests for detection of SIBO one week after a lactose hydrogen breath test checking for lactose intolerance. The most frequent symptoms were diarrhea (5/7, 71%) and flatulence (6/7, 86%). The study was conducted at a laboratory.</p> <p>In none of the subjects a pathological hydrogen production was observed after the intake of glucose. Only in one athlete a pathological hydrogen production was measured after the intake of lactose suggesting lactose intolerance.</p> <p>Conclusions</p> <p>Gastrointestinal disorders in the examined long distance runners were not associated with small intestinal bacterial overgrowth.</p

The effect of surveillance and appreciative inquiry on puerperal infections : a longitudinal cohort study in India

Peer reviewedPublisher PD

Multi-step time series prediction intervals using neuroevolution

Multi-step time series forecasting (TSF) is a crucial element to support tactical decisions (e.g., designing production or marketing plans several months in advance). While most TSF research addresses only single-point prediction, prediction intervals (PIs) are useful to reduce uncertainty related to important decision making variables. In this paper, we explore a large set of neural network methods for multi-step TSF and that directly optimize PIs. This includes multi-step adaptations of recently proposed PI methods, such as lower--upper bound estimation (LUBET), its ensemble extension (LUBEXT), a multi-objective evolutionary algorithm LUBE (MLUBET) and a two-phase learning multi-objective evolutionary algorithm (M2LUBET). We also explore two new ensemble variants for the evolutionary approaches based on two PI coverage--width split methods (radial slices and clustering), leading to the MLUBEXT, M2LUBEXT, MLUBEXT2 and M2LUBEXT2 methods. A robust comparison was held by considering the rolling window procedure, nine time series from several real-world domains and with different characteristics, two PI quality measures (coverage error and width) and the Wilcoxon statistic. Overall, the best results were achieved by the M2LUBET neuroevolution method, which requires a reasonable computational effort for time series with a few hundreds of observations.This article is a result of the project NORTE-01- 0247-FEDER-017497, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). We would also like to thank the anonymous reviewers for their helpful suggestionsinfo:eu-repo/semantics/publishedVersio

Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a Revised Theoretical Model

YesBased on a critical review of the Unified Theory of Acceptance and Use of Technology (UTAUT), this study first formalized an alternative theoretical model for explaining the acceptance and use of information system (IS) and information technology (IT) innovations. The revised theoretical model was then empirically examined using a combination of meta-analysis and structural equation modelling (MASEM) techniques. The meta-analysis was based on 1600 observations on 21 relationships coded from 162 prior studies on IS/IT acceptance and use. The SEM analysis showed that attitude: was central to behavioural intentions and usage behaviours, partially mediated the effects of exogenous constructs on behavioural intentions, and had a direct influence on usage behaviours. A number of implications for theory and practice are derived based on the findings

Impact of the roll out of comprehensive emergency obstetric care on institutional birth rate in rural Nepal

© 2017 The Author(s). Background: Increasing institutional births rates and improving access to comprehensive emergency obstetric care are central strategies for reducing maternal and neonatal deaths globally. While some studies show women consider service availability when determining where to deliver, the dynamics of how and why institutional birth rates change as comprehensive emergency obstetric care availability increases are unclear. Methods: In this pre-post intervention study, we surveyed two exhaustive samples of postpartum women before and after comprehensive emergency obstetric care implementation at a hospital in rural Nepal. We developed a logistic regression model of institutional birth factors through manual backward selection of all significant covariates within and across periods. Qualitatively, we analyzed birth stories through immersion crystallization. Results: Institutional birth rates increased after comprehensive emergency obstetric care implementation (from 30 to 77%, OR 7.7) at both hospital (OR 2.5) and low-level facilities (OR 4.6, p < 0.01 for all). The logistic regression indicated that comprehensive emergency obstetric care availability (OR 5.6), belief that the hospital is the safest birth location (OR 44.8), safety prioritization in decision-making (OR 7.7), and higher income (OR 1.1) predict institutional birth (p ≤ 0.01 for all). Qualitative analysis revealed comprehensive emergency obstetric care awareness, increased social expectation for institutional birth, and birth planning as important factors. Conclusion: Comprehensive emergency obstetric care expansion appears to have generated significant demand for institutional births through increased safety perceptions and birth planning. Increasing comprehensive emergency obstetric care availability increases birth safety, but it may also be a mechanism for increasing the institutional birth rate in areas of under-utilization

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation

Women-focused development intervention reduces delays in accessing emergency obstetric care in urban slums in Bangladesh: a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Recognizing the burden of maternal mortality in urban slums, in 2007 BRAC (formally known as Bangladesh Rural Advancement Committee) has established a woman-focused development intervention, Manoshi (the Bangla abbreviation of mother, neonate and child), in urban slums of Bangladesh. The intervention emphasizes strengthening the continuum of maternal, newborn and child care through community, delivery centre (DC) and timely referral of the obstetric complications to the emergency obstetric care (EmOC) facilities. This study aimed to assess whether Manoshi DCs reduces delays in accessing EmOC.</p> <p>Methods</p> <p>This cross-sectional study was conducted during October 2008 to January 2009 in the slums of Dhaka city among 450 obstetric complicated cases referred either from DCs of Manoshi or from their home to the EmOC facilities. Trained female interviewers interviewed at their homestead with structured questionnaire. <it>Pearson's </it>chi-square test, <it>t</it>-test and Mann-Whitney test were performed.</p> <p>Results</p> <p>The median time for making the decision to seek care was significantly longer among women who were referred from home than referred from DCs (9.7 hours vs. 5.0 hours, p < 0.001). The median time to reach a facility and to receive treatment was found to be similar in both groups. Time taken to decide to seek care was significantly shorter in the case of life-threatening complications among those who were referred from DC than home (0.9 hours vs.2.3 hours, p = 0.002). Financial assistance from Manoshi significantly reduced the first delay in accessing EmOC services for life-threatening complications referred from DC (p = 0.006). Reasons for first delay include fear of medical intervention, inability to judge maternal condition, traditional beliefs and financial constraints. Role of gender was found to be an important issue in decision making. First delay was significantly higher among elderly women, multiparity, non life-threatening complications and who were not involved in income-generating activities.</p> <p>Conclusions</p> <p>Manoshi program reduces the first delay for life-threatening conditions but not non-life-threatening complications even though providing financial assistance. Programme should give more emphasis on raising awareness through couple/family-based education about maternal complications and dispel fear of clinical care to accelerate seeking EmOC.</p

Mechanomyographic amplitude and frequency responses during dynamic muscle actions: a comprehensive review

The purpose of this review is to examine the literature that has investigated mechanomyographic (MMG) amplitude and frequency responses during dynamic muscle actions. To date, the majority of MMG research has focused on isometric muscle actions. Recent studies, however, have examined the MMG time and/or frequency domain responses during various types of dynamic activities, including dynamic constant external resistance (DCER) and isokinetic muscle actions, as well as cycle ergometry. Despite the potential influences of factors such as changes in muscle length and the thickness of the tissue between the muscle and the MMG sensor, there is convincing evidence that during dynamic muscle actions, the MMG signal provides valid information regarding muscle function. This argument is supported by consistencies in the MMG literature, such as the close relationship between MMG amplitude and power output and a linear increase in MMG amplitude with concentric torque production. There are still many issues, however, that have yet to be resolved, and the literature base for MMG during both dynamic and isometric muscle actions is far from complete. Thus, it is important to investigate the unique applications of MMG amplitude and frequency responses with different experimental designs/methodologies to continually reassess the uses/limitations of MMG

Use of multidimensional item response theory methods for dementia prevalence prediction: an example using the Health and Retirement Survey and the Aging, Demographics, and Memory Study.

BACKGROUND: Data sparsity is a major limitation to estimating national and global dementia burden. Surveys with full diagnostic evaluations of dementia prevalence are prohibitively resource-intensive in many settings. However, validation samples from nationally representative surveys allow for the development of algorithms for the prediction of dementia prevalence nationally. METHODS: Using cognitive testing data and data on functional limitations from Wave A (2001-2003) of the ADAMS study (n = 744) and the 2000 wave of the HRS study (n = 6358) we estimated a two-dimensional item response theory model to calculate cognition and function scores for all individuals over 70. Based on diagnostic information from the formal clinical adjudication in ADAMS, we fit a logistic regression model for the classification of dementia status using cognition and function scores and applied this algorithm to the full HRS sample to calculate dementia prevalence by age and sex. RESULTS: Our algorithm had a cross-validated predictive accuracy of 88% (86-90), and an area under the curve of 0.97 (0.97-0.98) in ADAMS. Prevalence was higher in females than males and increased over age, with a prevalence of 4% (3-4) in individuals 70-79, 11% (9-12) in individuals 80-89 years old, and 28% (22-35) in those 90 and older. CONCLUSIONS: Our model had similar or better accuracy as compared to previously reviewed algorithms for the prediction of dementia prevalence in HRS, while utilizing more flexible methods. These methods could be more easily generalized and utilized to estimate dementia prevalence in other national surveys