Explore the vast range of titles available.

In the past few decades, the field of physical activity has grown and evolved in scope, depth, visibility and impact around the world. Global progress has been observed in research and practice in physical activity regarding surveillance, health outcomes, correlates/determinants, interventions, translation and policy. The 2012 and 2016 Lancet series on physical activity provide some of the most comprehensive global analysis on various topics within physical activity. Based on the Lancet series and other key developments in the field, literature searches, and expert group meetings and consultation, we provide a global summary on the progress of, gaps in and future directions for physical activity research in the following areas: (1) surveillance and trends, (2) correlates and determinants, (3) health outcomes and (4) interventions, programmes and policies. Besides lessons learnt within each specific area, several recommendations are shared across areas of research, including improvement in measurement, applying a global perspective with a growing emphasis on low-income and middle-income countries, improving inclusiveness and equity in research, making translation an integral part of research for real-world impact, taking an ‘upstream’ public health approach, and working across disciplines and sectors to co-design research and co-create solutions. We have summarised lessons learnt and recommendations for future research as ‘roadmaps’ in progress to encourage moving the field of physical activity towards achieving population-level impact globally.

Industrial Symbiosis (IS) is a collaboration between nearby industrial plants to exchange waste material and energy and achieve economic and environmental benefits that cannot be obtained individually. IS emergence in a cluster requires both technical potentials for material and energy exchange and social readiness for collaboration. In this paper, to gain insight into IS dynamics in emerging industrial clusters; we investigate shared concepts governing actors’ behavior in the form of rules and regulations, and social norms and practices. We implemented the IS dynamics framework to reveal which dynamics are supported either by the legislation or actors’ preferences. The Persian Gulf Mining and Metal Industries Special Economic Zone in Iran is used as a case study. The case study revealed that previous successful collaborations in the cluster were often self-organized, but stakeholders preferred to initiate new IS collaborations if financial incentives and infrastructure are provided. Meanwhile, the institutional analysis showed that institutional arrangements (e.g., pricing and penalties) are not in favor of IS emergence. Even though stakeholders might engage in self-organized IS because of inherent problems such as resource scarcity, the lack of clear and effective institutions could hinder IS. This understanding can help both the government and stakeholders in their strategies for future collaborations under different economic and environmental policies.

Comprehensively mapping the genetic basis of human disease across diverse individuals is a long-standing goal for the field of human genetics 1 – 4 . The All of Us Research Program is a longitudinal cohort study aiming to enrol a diverse group of at least one million individuals across the USA to accelerate biomedical research and improve human health 5 , 6 . Here we describe the programme’s genomics data release of 245,388 clinical-grade genome sequences. This resource is unique in its diversity as 77% of participants are from communities that are historically under-represented in biomedical research and 46% are individuals from under-represented racial and ethnic minorities. All of Us identified more than 1 billion genetic variants, including more than 275 million previously unreported genetic variants, more than 3.9 million of which had coding consequences. Leveraging linkage between genomic data and the longitudinal electronic health record, we evaluated 3,724 genetic variants associated with 117 diseases and found high replication rates across both participants of European ancestry and participants of African ancestry. Summary-level data are publicly available, and individual-level data can be accessed by researchers through the All of Us Researcher Workbench using a unique data passport model with a median time from initial researcher registration to data access of 29 hours. We anticipate that this diverse dataset will advance the promise of genomic medicine for all. A study describes the release of clinical-grade whole-genome sequence data for 245,388 diverse participants by the All of Us Research Program and characterizes the properties of the dataset.

The All of Us Research Program enrolls diverse US participants which provide a unique opportunity to better understand the problem of opioid use. This study aims to estimate the prevalence of opioid use and its association with sociodemographic characteristics from survey data and electronic health record (EHR). A total of 214,206 participants were included in this study who competed survey modules and shared EHR data. Adjusted logistic regressions were used to explore the associations between sociodemographic characteristics and opioid use. The lifetime prevalence of street opioids was 4%, and the nonmedical use of prescription opioids was 9%. Men had higher odds of lifetime opioid use (aOR: 1.4 to 3.1) but reduced odds of current nonmedical use of prescription opioids (aOR: 0.6). Participants from other racial and ethnic groups were at reduced odds of lifetime use (aOR: 0.2 to 0.9) but increased odds of current use (aOR: 1.9 to 9.9) compared with non-Hispanic White participants. Foreign-born participants were at reduced risks of opioid use and diagnosed with opioid use disorders (OUD) compared with US-born participants (aOR: 0.36 to 0.67). Men, Younger, White, and US-born participants are more likely to have OUD. All of Us research data can be used as an indicator of national trends for monitoring the prevalence of receiving prescription opioids, diagnosis of OUD, and non-medical use of opioids in the US. The program employs a longitudinal design for routinely collecting health-related data including EHR data, that will contribute to the literature by providing important clinical information related to opioids over time. Additionally, this data will enhance the estimates of the prevalence of OUD among diverse populations, including groups that are underrepresented in the national survey data.

Background In 2015, GoPA! was launched to monitor progress on Physical Activity (PA) surveillance, policy and research globally. In 2017, the GoPA! started developing a PA Policy Inventory to enable collecting comparable data on PA policy worldwide. Methods The instrument was developed in three stages. Stage-1: Critical assessment of the Policy Inventory version 1.0 was based on a review of other policy instruments/frameworks including: Health enhancing physical activity policy audit tool; the monitoring framework from the EU Recommendation on Health-Enhancing Physical Activity Across Sectors; and the Comprehensive Analysis of Policy on Physical Activity framework. Feedback from 14 GoPA! Country Contacts was received in 2017. Additional critical assessment was conducted from February to May 2019, and four PA policy experts drafted the Policy Inventory version 2.0. Stage-2: Open discussions about the Policy Inventory draft took place between May and August 2019 with seven policy experts. Based on the discussions, the draft questionnaire was revised three times to produce the GoPA! Policy Inventory version 2.0. Stage-3: Ten GoPA! Country Contacts provided their feedback on the Inventory version 2.0. The expert team from Stage 2 reviewed the suggestions and incorporated most of them into the GoPA! Policy Inventory version 3.0. Results The GoPA! Policy Inventory version 3.0 contains: (i) a consent form; (ii) three questions about the respondent; and (iii) 20 questions about physical activity and sedentary behaviour policy. It is available in two formats: (i) an online survey in Qualtrics software; and (ii) an interactive Word document. The instrument collects the information related to: (i) national PA plans/policies; (iii) PA policy implementation; (iv) national recommendations on PA; (v) health surveillance or monitoring system that includes measures of PA; (vi) ministries or departments in national governments with an active role in PA promotion; (vii) quantifiable national targets related to PA; and (viii) comprehensiveness and effectiveness of the overall national PA policy. Conclusions The instrument will be used to collect policy data for the 2020 GoPA! Country Cards to be launched at ISPAH2020 and, may further be used by PA researchers and policy analysts to monitor, audit, assess, and analyse national PA policies.

When applied in large scale to electronic medical record data, the PheWAS approach replicates GWAS associations and reveals potentially new pleiotropic associations. Candidate gene and genome-wide association studies (GWAS) have identified genetic variants that modulate risk for human disease; many of these associations require further study to replicate the results. Here we report the first large-scale application of the phenome-wide association study (PheWAS) paradigm within electronic medical records (EMRs), an unbiased approach to replication and discovery that interrogates relationships between targeted genotypes and multiple phenotypes. We scanned for associations between 3,144 single-nucleotide polymorphisms (previously implicated by GWAS as mediators of human traits) and 1,358 EMR-derived phenotypes in 13,835 individuals of European ancestry. This PheWAS replicated 66% (51/77) of sufficiently powered prior GWAS associations and revealed 63 potentially pleiotropic associations with P < 4.6 × 10 −6 (false discovery rate < 0.1); the strongest of these novel associations were replicated in an independent cohort ( n = 7,406). These findings validate PheWAS as a tool to allow unbiased interrogation across multiple phenotypes in EMR-based cohorts and to enhance analysis of the genomic basis of human disease.

The prevalence, incidence and risk factors of atrial fibrillation (AF) in a large, geographically and ethnically diverse cohort in the United States have not been fully described. We analyzed data from 173,099 participants of the All of Us Research Program recruited in the period 2017-2019, with 92,318 of them having electronic health records (EHR) data available, and 35,483 having completed a medical history survey. Presence of AF at baseline was identified from self-report and EHR records. Incident AF was obtained from EHR. Demographic, anthropometric and clinical risk factors were obtained from questionnaires, baseline physical measurements and EHR. At enrollment, mean age was 52 years old (range 18-89). Females and males accounted for 61% and 39% respectively. Non-Hispanic Whites accounted for 67% of participants, with non-Hispanic Blacks, non-Hispanic Asians and Hispanics accounting for 26%, 4% and 3% of participants, respectively. Among 92,318 participants with available EHR data, 3,885 (4.2%) had AF at the time of study enrollment, while the corresponding figure among 35,483 with medical history data was 2,084 (5.9%). During a median follow-up of 16 months, 354 new cases of AF were identified among 88,433 eligible participants. Individuals who were older, male, non-Hispanic white, had higher body mass index, or a prior history of heart failure or coronary heart disease had higher prevalence and incidence of AF. The epidemiology of AF in the All of Us Research Program is similar to that reported in smaller studies with careful phenotyping, highlighting the value of this new resource for the study of AF and, potentially, other cardiovascular diseases.

Decarbonization of electricity generation can support climate-change mitigation and presents an opportunity to address pollution resulting from fossil-fuel combustion. Generally, renewable technologies require higher initial investments in infrastructure than fossil-based power systems. To assess the tradeoffs of increased up-front emissions and reduced operational emissions, we present, to our knowledge, the first global, integrated life-cycle assessment (LCA) of long-term, wide-scale implementation of electricity generation from renewable sources (i.e., photovoltaic and solar thermal, wind, and hydropower) and of carbon dioxide capture and storage for fossil power generation. We compare emissions causing particulate matter exposure, freshwater ecotoxicity, freshwater eutrophication, and climate change for the climate-change-mitigation (BLUE Map) and business-as-usual (Baseline) scenarios of the International Energy Agency up to 2050. We use a vintage stock model to conduct an LCA of newly installed capacity year-by-year for each region, thus accounting for changes in the energy mix used to manufacture future power plants. Under the Baseline scenario, emissions of air and water pollutants more than double whereas the low-carbon technologies introduced in the BLUE Map scenario allow a doubling of electricity supply while stabilizing or even reducing pollution. Material requirements per unit generation for low-carbon technologies can be higher than for conventional fossil generation: 11–40 times more copper for photovoltaic systems and 6–14 times more iron for wind power plants. However, only two years of current global copper and one year of iron production will suffice to build a low-carbon energy system capable of supplying the world's electricity needs in 2050. Significance Life-cycle assessments commonly used to analyze the environmental costs and benefits of climate-mitigation options are usually static in nature and address individual power plants. Our paper presents, to our knowledge, the first life-cycle assessment of the large-scale implementation of climate-mitigation technologies, addressing the feedback of the electricity system onto itself and using scenario-consistent assumptions of technical improvements in key energy and material production technologies.

Background: Obesity and physical inactivity among children and young people are public health concerns. While numerous interventions to promote physical activity are available, little is known about the most effective ones. This study aimed to summarize the existing evidence on interventions that aim to increase physical activity. Methods: A systematic review of reviews was conducted. Systematic reviews and meta-analyses published from January 2010 until November 2017 were identified through PubMed, Scopus and the Cochrane Library. Two reviewers independently assessed titles and abstracts, performed data extraction and quality assessment. Outcomes as level of physical activity and body mass index were collected in order to assess the efficacy of interventions. Results: A total 30 studies examining physical activity interventions met the inclusion criteria, 15 systematic reviews and 15 meta-analyses. Most studies (N = 20) were implemented in the school setting, three were developed in preschool and childcare settings, two in the family context, five in the community setting and one miscellaneous context. Results showed that eight meta-analyses obtained a small increase in physical activity level, out of which five were conducted in the school, two in the family and one in the community setting. Most promising programs had the following characteristics: included physical activity in the school curriculum, were long-term interventions, involved teachers and had the support of families. Conclusion: The majority of interventions to promote physical activity in children and young people were implemented in the school setting and were multicomponent. Further research is needed to investigate nonschool programs.