The influence of market deregulation on fast food consumption and body mass index:A cross-national time series analysis

Objective
To investigate the effect of fast food consumption on mean population body mass index (BMI) and explore the possible influence of market deregulation on fast food consumption and BMI.

Methods
The within-country association between fast food consumption and BMI in 25 high-income member countries of the Organisation for Economic Co-operation and Development between 1999 and 2008 was explored through multivariate panel regression models, after adjustment for per capita gross domestic product, urbanization, trade openness, lifestyle indicators and other covariates. The possible mediating effect of annual per capita intake of soft drinks, animal fats and total calories on the association between fast food consumption and BMI was also analysed. Two-stage least squares regression models were conducted, using economic freedom as an instrumental variable, to study the causal effect of fast food consumption on BMI.

Findings
After adjustment for covariates, each 1-unit increase in annual fast food transactions per capita was associated with an increase of 0.033 kg/m2 in age-standardized BMI (95% confidence interval, CI: 0.013–0.052). Only the intake of soft drinks – not animal fat or total calories – mediated the observed association (β: 0.030; 95% CI: 0.010–0.050). Economic freedom was an independent predictor of fast food consumption (β: 0.27; 95% CI: 0.16–0.37). When economic freedom was used as an instrumental variable, the association between fast food and BMI weakened but remained significant (β: 0.023; 95% CI: 0.001–0.045).

Conclusion
Fast food consumption is an independent predictor of mean BMI in high-income countries. Market deregulation policies may contribute to the obesity epidemic by facilitating the spread of fast food.

Detectability of bovine TB using the tuberculin skin test does not vary significantly according to pathogen genotype within Northern Ireland

Strains of many infectious diseases differ in parameters that influence epidemic spread, for example virulence, transmissibility, detectability and host specificity. Knowledge of inter-strain variation can be exploited to improve management and decrease disease incidence. Bovine tuberculosis (bTB) is increasingly prevalent among farmed cattle in the UK, exerting a heavy economic burden on the farming industry and government. We aimed to determine whether strains of Mycobacterium bovis (the causative agent of bTB) identified and classified using genetic markers (spoligotyping and multi-locus VNTR analysis) varied in response to the tuberculin skin test; this being the primary method of bTB detection used in the UK. Inter-strain variation in detectability of M. bovis could have important implications for disease control. The skin test is based on a differential delayed type hypersensitivity (DTH) response to intradermal injections of purified protein derivative (PPD) from M. bovis (PPD-B) and Mycobacterium avium (PPD-A). We searched for an association between skin test response (PPD-B skin rise minus PPD-A skin rise) and M. bovis genotype at the disclosing test in culture-confirmed cases using a field dataset consisting of 21,000 isolates belonging to 63 genotypes of M. bovis from cattle in Northern Ireland. We found no substantial variation among genotypes (estimated responses clustered tightly around the mean) controlling for animal sex, breed and test effects. We also estimated the ratio of skin test detected to undetected cases (i.e. cases only detected at abattoir). The skin test detection ratio varied among abattoirs with some detecting a greater proportion of cases than others but this variation was unrelated to the community composition of genotypes within each abattoir catchment. These two lines of evidence indicate that M. bovis genotypes in Northern Ireland have similar detectability using the skin test.

Factors influencing acquisition of Burkholderia cepacia complex organisms in patients with cystic fibrosis

Burkholderia cepacia complex organisms are important transmissible pathogens found in cystic fibrosis (CF) patients. In recent years, the rates of cross-infection of epidemic strains have declined due to effective infection control efforts. However, cases of sporadic B. cepacia complex infection continue to occur in some centers. The acquisition pathways and clinical outcomes of sporadic B. cepacia complex infection are unclear. We sought to determine the patient clinical characteristics, outcomes, incidence, and genotypic relatedness for all cases of B. cepacia complex infection at two CF centers. We also sought to study the external conditions that influence the acquisition of infection. From 2001 to 2011, 67 individual organisms were cultured from the respiratory samples of 64 patients. Sixty-five percent of the patients were adults, in whom chronic infections were more common (68%) (P = 0.006). The incidence of B. cepacia complex infection increased by a mean of 12% (95% confidence interval [CI], 3 to 23%) per year. The rates of transplantation and death were similar in the incident cases who developed chronic infection compared to those in patients with chronic Pseudomonas aeruginosa infection. Multilocus sequence typing revealed 50 individual strains from 65 isolates. Overall, 85% of the patients were infected with unique strains, suggesting sporadic acquisition of infection. The yearly incidence of nonepidemic B. cepacia complex infection was positively correlated with the amount of rainfall in the two sites examined: subtropical Brisbane (r = 0.65, P = 0.031) and tropical Townsville (r = 0.82, P = 0.002). This study demonstrates that despite strict cohort segregation, new cases of unrelated B. cepacia complex infection continue to occur. These data also support an environmental origin of infection and suggest that climate conditions may be associated with the acquisition of B. cepacia complex infections.

Pseudomonas aeruginosa exhibits frequent recombination, but only a limited association between genotype and ecological setting

Pseudomonas aeruginosa is an opportunistic pathogen and an important cause of infection, particularly amongst cystic fibrosis (CF) patients. While specific strains capable of patient-to-patient transmission are known, many infections appear to be caused by unique and unrelated strains. There is a need to understand the relationship between strains capable of colonising the CF lung and the broader set of P. aeruginosa isolates found in natural environments. Here we report the results of a multilocus sequence typing (MLST)-based study designed to understand the genetic diversity and population structure of an extensive regional sample of P. aeruginosa isolates from South East Queensland, Australia. The analysis is based on 501 P. aeruginosa isolates obtained from environmental, animal and human (CF and non-CF) sources with particular emphasis on isolates from the Lower Brisbane River and isolates from CF patients obtained from the same geographical region. Overall, MLST identified 274 different sequence types, of which 53 were shared between one or more ecological settings. Our analysis revealed a limited association between genotype and environment and evidence of frequent recombination. We also found that genetic diversity of P. aeruginosa in Queensland, Australia was indistinguishable from that of the global P. aeruginosa population. Several CF strains were encountered frequently in multiple ecological settings; however, the most frequently encountered CF strains were confined to CF patients. Overall, our data confirm a non-clonal epidemic structure and indicate that most CF strains are a random sample of the broader P. aeruginosa population. The increased abundance of some CF strains in different geographical regions is a likely product of chance colonisation events followed by adaptation to the CF lung and horizontal transmission among patients.

Rapid single-nucleotide polymorphism-based identification of clonal Pseudomonas aeruginosa isolates from patients with cystic fibrosis by the use of real-time PCR and high-resolution melting curve analysis

Pseudomonas aeruginosa genotyping relies mainly upon DNA fingerprinting methods, which can be subjective, expensive and time-consuming. The detection of at least three different clonal P. aeruginosa strains in patients attending two cystic fibrosis (CF) centres in a single Australian city prompted the design of a non-gel-based PCR method to enable clinical microbiology laboratories to readily identify these clonal strains. We designed a detection method utilizing heat-denatured P. aeruginosa isolates and a ten-single-nucleotide polymorphism (SNP) profile. Strain differences were detected by SYBR Green-based real-time PCR and high-resolution melting curve analysis (HRM10SNP assay). Overall, 106 P. aeruginosa sputum isolates collected from 74 patients with CF, as well as five reference strains, were analysed with the HRM10SNP assay, and the results were compared with those obtained by pulsed-field gel electrophoresis (PFGE). The HRM10SNP assay accurately identified all 45 isolates as members of one of the three major clonal strains characterized by PFGE in two Brisbane CF centres (Australian epidemic strain-1, Australian epidemic strain-2 and P42) from 61 other P. aeruginosa strains from Australian CF patients and two representative overseas epidemic strain isolates. The HRM10SNP method is simple, is relatively inexpensive and can be completed in <3 h. In our setting, it could be made easily available for clinical microbiology laboratories to screen for local P. aeruginosa strains and to guide infection control policies. Further studies are needed to determine whether the HRM10SNP assay can also be modified to detect additional clonal strains that are prevalent in other CF centres.

Burkholderia cepacia complex epidemiology in persons with cystic fibrosis from Australia and New Zealand

The Burkholderia cepacia complex (Bcc) is a group of significant opportunistic respiratory pathogens which affect people with cystic fibrosis. In this study, we sought to ascertain the epidemiology and geographic species distribution of 116 Bcc isolates collected from people with CF in Australia and New Zealand. We performed a combination of recA-based PCR, amplified rDNA restriction analysis (ARDRA), pulsed-field gel electrophoresis and repetitive extragenic palindromic PCR on each isolate. Each Burkholderia cenocepacia isolate was also screened by PCR for the presence of the B. cepacia epidemic strain marker. One hundred and fourteen isolates were assigned to a species using recA-based PCR and ARDRA. B. cenocepacia, B. multivorans and B. cepacia accounted for 45.7%, 29.3% and 11.2% of the isolates, respectively. Strain analysis of B. cenocepacia revealed that 85.3% of the isolates were unrelated. One related B. cenocepacia strain was identified amongst 15 people. Whilst full details of person-to-person contact was not available, all patients attended CF centres in Queensland (Qld) and New South Wales (NSW). Although person-to-person transmission of B. cenocepacia strains has occurred in Australia, the majority of CF-related Bcc infections in Australia and New Zealand are most likely acquired from the environment.

Seroepidemiology of norovirus-associated travelers' diarrhea

Background: Noroviruses (NoVs) are the most common cause of epidemic gastroenteritis, responsible for at least 50% of all gastroenteritis outbreaks worldwide and were recently identified as a leading cause of travelers' diarrhea (TD) in US and European travelers to Mexico, Guatemala, and India.

Methods: Serum and diarrheic stool samples were collected from 75 US student travelers to Cuernavaca, Mexico, who developed TD. NoV RNA was detected in acute diarrheic stool samples using reverse transcription-polymerase chain reaction (RT-PCR). Serology assays were performed using GI.1 Norwalk virus (NV) and GII.4 Houston virus (HOV) virus-like particles (VLPs) to measure serum levels of immunoglobulin A (IgA) and IgG by dissociation-enhanced lanthanide fluorescent immunoassay (DELFIA); serum IgM was measured by capture enzyme-linked immunosorbent assay (ELISA), and the 50% antibody-blocking titer (BT50 ) was determined by a carbohydrate-blocking assay.

Results: NoV infection was identified in 12 (16%; 9 GI-NoV and 3 GII-NoV) of 75 travelers by either RT-PCR or fourfold or more rise in antibody titer. Significantly more individuals had detectable preexisting IgA antibodies against HOV (62/75, 83%) than against NV (49/75, 65%) (p = 0.025) VLPs. A significant difference was observed between NV- and HOV-specific preexisting IgA antibody levels (p = 0.0037), IgG (p = 0.003), and BT50 (p = <0.0001). None of the NoV-infected TD travelers had BT50  > 200, a level that has been described previously as a possible correlate of protection.

Conclusion: We found that GI-NoVs are commonly associated with TD cases identified in US adults traveling to Mexico, and seroprevalence rates and geometric mean antibody levels to a GI-NoV were lower than to a GII-NoV strain.

Knowledge and risk perceptions of the Ebola virus in the United States

Objectives
The Ebola epidemic has received extensive media coverage since the first diagnosed cases of the virus in the US. We investigated risk perceptions of Ebola among individuals living in the US and measured their knowledge of the virus.

Method
US residents completed an online survey (conducted 14–18 November 2014) that assessed their Ebola knowledge and risk perceptions.

Results
Respondents who were more knowledgeable of Ebola perceived less risk of contracting the virus and were less worried about the virus, but also regarded Ebola as more serious than less knowledgeable respondents. The internet served as a major source of additional information among knowledgeable respondents.

Conclusion
The findings suggest that the provision of health information about Ebola may be effective in informing the public about Ebola risks and of preventive measures without curtailing the seriousness of the virus. Policymakers may seek to further exploit the internet as a means of delivering information about Ebola in the US and worldwide.

Progress on core outcomes sets for critical care research

Purpose of review: Appropriate selection and definition of outcome measures are essential for clinical trials to be maximally informative. Core outcome sets (an agreed, standardized collection of outcomes measured and reported in all trials for a specific clinical area) were developed due to established inconsistencies in trial outcome selection. This review discusses the rationale for, and methods of, core outcome set development, as well as current initiatives in critical care.

Recent findings: Recent systematic reviews of reported outcomes and measurement instruments relevant to the critically ill highlight inconsistencies in outcome selection, definition, and measurement, thus establishing the need for core outcome sets. Current critical care initiatives include development of core outcome sets for trials aimed at reducing mechanical ventilation duration; rehabilitation following critical illness; long-term outcomes in acute respiratory failure; and epidemic and pandemic studies of severe acute respiratory infection.

Summary: Development and utilization of core outcome sets for studies relevant to the critically ill is in its infancy compared to other specialties. Notwithstanding, core outcome set development frameworks and guidelines are available, several sets are in various stages of development, and there is strong support from international investigator-led collaborations including the International Forum for Acute Care Trialists.

Infection of donor lymphocytes with human T lymphotrophic virus type 1 (HTLV-I) following allogeneic bone marrow transplantation for HTLV-I positive adult T-cell leukaemia

Human T lymphotrophic virus type 1 (HTLV-I) associated leukaemia has a poor prognosis even with chemotherapy. We describe a patient with adult T-cell leukaemia treated with allogeneic bone marrow transplantation from an HTLV-I negative identical sibling donor. During follow-up after bone marrow transplantation, HTLV-I could be repeatedly isolated inspite of anti-viral prophylaxis. The patient died of an acute encephalitis and HTLV-I could be detected in autopsy material from the brain. By a PCR-based technique using short tandem repeats (STRs) it was shown that the patient's haemopoiesis was of donor origin. This shows the infection of donor cells in vivo by an aetiological agent which has been implicated in the leukaemogenic process for adult T-cell leukaemia.

Multigenerational Undernutrition Increases Susceptibility to Obesity and Diabetes that Is Not Reversed after Dietary Recuperation

People in developing countries have faced multigenerational undernutrition and are currently undergoing major lifestyle changes, contributing to an epidemic of metabolic diseases, though the underlying mechanisms remain unclear. Using a Wistar rat model of undernutrition over 50 generations, we show that Undernourished rats exhibit low birth-weight, high visceral adiposity (DXA/MRI), and insulin resistance (hyperinsulinemic-euglycemic clamps), compared to age-/gender-matched control rats. Undernourished rats also have higher circulating insulin, homocysteine, endotoxin and leptin levels, lower adiponectin, vitamin B12 and folate levels, and an 8-fold increased susceptibility to Streptozotocin-induced diabetes compared to control rats. Importantly, these metabolic abnormalities are not reversed after two generations of unrestricted access to commercial chow (nutrient recuperation). Altered epigenetic signatures in insulin-2 gene promoter region of Undernourished rats are not reversed by nutrient recuperation, and may contribute to the persistent detrimental metabolic profiles in similar multigenerational undernourished human populations.

Whole Genome Sequencing Reveals Local Transmission Patterns of Mycobacterium bovis in Sympatric Cattle and Badger Populations

Whole genome sequencing (WGS) technology holds great promise as a tool for the forensic epidemiology of bacterial pathogens. It is likely to be particularly useful for studying the transmission dynamics of an observed epidemic involving a largely unsampled 'reservoir' host, as for bovine tuberculosis (bTB) in British and Irish cattle and badgers. BTB is caused by Mycobacterium bovis, a member of the M. tuberculosis complex that also includes the aetiological agent for human TB. In this study, we identified a spatio-temporally linked group of 26 cattle and 4 badgers infected with the same Variable Number Tandem Repeat (VNTR) type of M. bovis. Single-nucleotide polymorphisms (SNPs) between sequences identified differences that were consistent with bacterial lineages being persistent on or near farms for several years, despite multiple clear whole herd tests in the interim. Comparing WGS data to mathematical models showed good correlations between genetic divergence and spatial distance, but poor correspondence to the network of cattle movements or within-herd contacts. Badger isolates showed between zero and four SNP differences from the nearest cattle isolate, providing evidence for recent transmissions between the two hosts. This is the first direct genetic evidence of M. bovis persistence on farms over multiple outbreaks with a continued, ongoing interaction with local badgers. However, despite unprecedented resolution, directionality of transmission cannot be inferred at this stage. Despite the often notoriously long timescales between time of infection and time of sampling for TB, our results suggest that WGS data alone can provide insights into TB epidemiology even where detailed contact data are not available, and that more extensive sampling and analysis will allow for quantification of the extent and direction of transmission between cattle and badgers. © 2012 Biek et al.

Adjusting HIV Prevalence Estimates for Non-participation: an Application to Demographic Surveillance

Introduction: HIV testing is a cornerstone of efforts to combat the HIV epidemic, and testing conducted as part of surveillance provides invaluable data on the spread of infection and the effectiveness of campaigns to reduce the transmission of HIV. However, participation in HIV testing can be low, and if respondents systematically select not to be tested because they know or suspect they are HIV positive (and fear disclosure), standard approaches to deal with missing data will fail to remove selection bias. We implemented Heckman-type selection models, which can be used to adjust for missing data that are not missing at random, and established the extent of selection bias in a population-based HIV survey in an HIV hyperendemic community in rural South Africa.

Methods: We used data from a population-based HIV survey carried out in 2009 in rural KwaZulu-Natal, South Africa. In this survey, 5565 women (35%) and 2567 men (27%) provided blood for an HIV test. We accounted for missing data using interviewer identity as a selection variable which predicted consent to HIV testing but was unlikely to be independently associated with HIV status. Our approach involved using this selection variable to examine the HIV status of residents who would ordinarily refuse to test, except that they were allocated a persuasive interviewer. Our copula model allows for flexibility when modelling the dependence structure between HIV survey participation and HIV status.

Results: For women, our selection model generated an HIV prevalence estimate of 33% (95% CI 27–40) for all people eligible to consent to HIV testing in the survey. This estimate is higher than the estimate of 24% generated when only information from respondents who participated in testing is used in the analysis, and the estimate of 27% when imputation analysis is used to predict missing data on HIV status. For men, we found an HIV prevalence of 25% (95% CI 15–35) using the selection model, compared to 16% among those who participated in testing, and 18% estimated with imputation. We provide new confidence intervals that correct for the fact that the relationship between testing and HIV status is unknown and requires estimation.

Conclusions: We confirm the feasibility and value of adopting selection models to account for missing data in population-based HIV surveys and surveillance systems. Elements of survey design, such as interviewer identity, present the opportunity to adopt this approach in routine applications. Where non-participation is high, true confidence intervals are much wider than those generated by standard approaches to dealing with missing data suggest.

Glucagon-like peptide-1 based therapies as a novel approach for chronic heart failure

Glucagon-like peptide-1 (GLP-1) is an endogenous peptide hormone whose metabolic effects have been exploited for glycaemic control in diabetes, but which also exerts important cardiovascular actions. We have recently reported that the GLP-1 mimetic, exendin-4, exerts clear benefits post-myocardial infarction via specific effects on extracellular matrix remodelling which is dysregulated in the diabetic heart (Robinson E et al, Basic Res Cardiol 2015; 110: 20), and have now shown similar cardioprotective actions in experimental diabetes, which are mediated via direct effects on infiltrating macrophages (Tate M et al, Basic Res Cardiol 2015; in press). Taken together with the apparent complexity of GLP-1 signalling and disappointing results of recent cardiovascular trials, our work strongly suggests that selective targeting of GLP-1 may be required in order to realise therapeutic benefit for both diabetic and non-diabetic heart failure patients. This is particularly important given the epidemic increase in the incidence of diabetes which is associated with a markedly enhanced susceptibility to cardiovascular stress.

Anomaly Detection for Data with Spatial Attributes

The problem of detecting spatially-coherent groups of data that exhibit anomalous behavior has started to attract attention due to applications across areas such as epidemic analysis and weather forecasting. Earlier efforts from the data mining community have largely focused on finding outliers, individual data objects that display deviant behavior. Such point-based methods are not easy to extend to find groups of data that exhibit anomalous behavior. Scan Statistics are methods from the statistics community that have considered the problem of identifying regions where data objects exhibit a behavior that is atypical of the general dataset. The spatial scan statistic and methods that build upon it mostly adopt the framework of defining a character for regions (e.g., circular or elliptical) of objects and repeatedly sampling regions of such character followed by applying a statistical test for anomaly detection. In the past decade, there have been efforts from the statistics community to enhance efficiency of scan statstics as well as to enable discovery of arbitrarily shaped anomalous regions. On the other hand, the data mining community has started to look at determining anomalous regions that have behavior divergent from their neighborhood.In this chapter,we survey the space of techniques for detecting anomalous regions on spatial data from across the data mining and statistics communities while outlining connections to well-studied problems in clustering and image segmentation. We analyze the techniques systematically by categorizing them appropriately to provide a structured birds eye view of the work on anomalous region detection;we hope that this would encourage better cross-pollination of ideas across communities to help advance the frontier in anomaly detection.