Health Equity, Population Health, and Climate Change Adaptation in Ontario, Canada

Climate change holds the potential to exacerbate existing health inequalities, yet understanding how practitioners conceive health equity and health equality has received little attention in the scholarly literature. This contribution utilizes in-depth interviews with public health practitioners from health units across Ontario, Canada to characterize understandings of equity in relation to on-going climate change adaptation work. Perceptions of health equity and associated public health practices are described before discussing the resulting implications for how and why practitioners take up the equity agenda in relation to climate change. In doing so, this work problematizes existing public health tools and competencies and signals the emergence of new practices capable of simultaneously promoting adaptive capacity to climate change and reducing health inequity in Ontario

Improved Glycaemia correlates with liver fat reduction in obese, type 2 diabetes, patients given glucagon-like peptide-1 (GLP-1) receptor agonists

Glucagon-like peptide-1 receptor agonists (GLP-1 RA) are effective for obese patients with type 2 diabetes mellitus (T2DM) because they concomitantly target obesity and dysglycaemia. Considering the high prevalence of non-alcoholic fatty liver disease (NAFLD) in patients with T2DM, we determined the impact of 6 months' GLP-1 RA therapy on intrahepatic lipid (IHL) in obese, T2DM patients with hepatic steatosis, and evaluated the inter-relationship between changes in IHL with those in glycosylated haemoglobin (HbA(1)c), body weight, and volume of abdominal visceral and subcutaneous adipose tissue (VAT and SAT). We prospectively studied 25 (12 male) patients, age 50±10 years, BMI 38.4±5.6 kg/m(2) (mean ± SD) with baseline IHL of 28.2% (16.5 to 43.1%) and HbA(1)c of 9.6% (7.9 to 10.7%) (median and interquartile range). Patients treated with metformin and sulphonylureas/DPP-IV inhibitors were given 6 months GLP-1 RA (exenatide, n = 19; liraglutide, n = 6). IHL was quantified by liver proton magnetic resonance spectroscopy ((1)H MRS) and VAT and SAT by whole body magnetic resonance imaging (MRI). Treatment was associated with mean weight loss of 5.0 kg (95% CI 3.5,6.5 kg), mean HbA(1c) reduction of 1·6% (17 mmol/mol) (0·8,2·4%) and a 42% relative reduction in IHL (-59.3, -16.5%). The relative reduction in IHL correlated with that in HbA(1)c (ρ = 0.49; p = 0.01) but was not significantly correlated with that in total body weight, VAT or SAT. The greatest IHL reduction occurred in individuals with highest pre-treatment levels. Mechanistic studies are needed to determine potential direct effects of GLP-1 RA on human liver lipid metabolism

Addressing the environmental, community and health impacts of resource development: Challenges across scales, sectors and sites

Work that addresses the cumulative impacts of resource extraction on environment, community, and health is necessarily large in scope. This paper presents experiences from initiating research at this intersection and explores implications for the ambitious, integrative agenda of planetary health. The purpose is to outline origins, design features, and preliminary insights from our intersectoral and international project, based in Canada and titled the “Environment, Community, Health Observatory” (ECHO) Network. With a clear emphasis on rural, remote, and Indigenous communities, environments, and health, the ECHO Network is designed to answer the question: How can an Environment, Community, Health Observatory Network support the integrative tools and processes required to improve understanding and response to the cumulative health impacts of resource development? The Network is informed by four regional cases across Canada where we employ a framework and an approach grounded in observation, “taking notice for action”, and collective learning. Sharing insights from the foundational phase of this five-year project, we reflect on the hidden and obvious challenges of working across scales, sectors, and sites, and the overlap of generative and uncomfortable entanglements associated with health and resource development. Yet, although intersectoral work addressing the cumulative impacts of resource extraction presents uncertainty and unresolved tensions, ultimately we argue that it is worth staying with the trouble

Addressing the environmental, community and health impacts of resource development: Challenges across scales, sectors and sites

Work that addresses the cumulative impacts of resource extraction on environment, community, and health is necessarily large in scope. This paper presents experiences from initiating research at this intersection and explores implications for the ambitious, integrative agenda of planetary health. The purpose is to outline origins, design features, and preliminary insights from our intersectoral and international project, based in Canada and titled the “Environment, Community, Health Observatory” (ECHO) Network. With a clear emphasis on rural, remote, and Indigenous communities, environments, and health, the ECHO Network is designed to answer the question: How can an Environment, Community, Health Observatory Network support the integrative tools and processes required to improve understanding and response to the cumulative health impacts of resource development? The Network is informed by four regional cases across Canada where we employ a framework and an approach grounded in observation, “taking notice for action”, and collective learning. Sharing insights from the foundational phase of this five-year project, we reflect on the hidden and obvious challenges of working across scales, sectors, and sites, and the overlap of generative and uncomfortable entanglements associated with health and resource development. Yet, although intersectoral work addressing the cumulative impacts of resource extraction presents uncertainty and unresolved tensions, ultimately we argue that it is worth staying with the trouble

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

What Drives Climate Action in Canada’s Provincial North? Exploring the Role of Connectedness to Nature, Climate Worry, and Talking with Friends and Family

Despite widespread calls to action from the scientific community and beyond, a concerning climate action gap exists. This paper aims to enhance our understanding of the role of connectedness to nature in promoting individual-level climate action in a unique setting where climate research and action are lacking: Canada’s Provincial North. To begin to understand possible pathways, we also examined whether climate worry and talking about climate change with family and friends mediate the relationship between connectedness to nature and climate action. We used data collected via postal surveys in two Provincial North communities, Thunder Bay (Ontario), and Prince George (British Columbia) (n = 628). Results show that connectedness to nature has a direct positive association with individual-level climate action, controlling for gender and education. Results of parallel mediation analyses further show that connectedness to nature is indirectly associated with individual-level climate action, mediated by both climate worry and talking about climate change with family and friends. Finally, results suggest that climate worry and talking about climate change with family and friends serially mediate the relationship between connectedness to nature and with individual-level climate action. These findings are relevant for climate change engagement and action, especially across Canada’s Provincial North, but also in similar settings characterized by marginalization, heightened vulnerability to climate change, urban islands within vast rural and remote landscapes, and economies and social identities tied to resource extraction. Drawing on these findings, we argue that cultivating stronger connections with nature in the places where people live, learn, work, and play is an important and currently underutilized leverage point for promoting individual-level climate action. This study therefore adds to the current and increasingly relevant calls for (re-)connecting with nature that have been made by others across a range of disciplinary and sectoral divides.Other UBCNon UBCReviewedFacultyResearche