Environmental Health Initiatives Research Articles

Visual arsenic detection in environmental waters: Innovating with a naked-eye biosensor for universal application

Arsenic contamination in environmental water sources poses a significant threat to human health, necessitating the development of sensitive and accessible detection methods. This study presents a multidimensional optimization of a bacterial biosensor for the susceptible and deoxyviolacein (DV)-based visual detection of arsenic. The research involved screening six different arsenic resistance (ars) operons and optimizing the genetic circuit to minimize background noise. Introducing an arsenic-specific transport channel enhanced the sensor's sensitivity to 1 nM with a quantitative range from 0.036 to 1.171 μM. The pigment-based biosensor offers a simple colorimetric approach for arsenic detection without complex instrumentation. The preferred biosensor demonstrated characteristics of anti-chelating agent interference, consistently quantified As(III) concentrations ranging from 0.036 to 1.171 μM covering the World Health Organization (WHO) drinking water limit. Innovatively, it effectively detects arsenic in seawater within a linear regression range of 0.071 to 1.125 μM. The biosensor's selectivity for arsenic was confirmed, with minimal cross-response to group 15 metals. Our naked-eye biosensor offers a novel approach for the rapid, on-site detection of arsenic in various water sources. Its simplicity, cost-effectiveness, and versatility make it a valuable tool for environmental monitoring and public health initiatives.

A review of copper-based Fenton reactions for the removal of organic pollutants from wastewater over the last decade: different reaction systems.

In recent years, as global industrialization has intensified, environmental pollution has become an increasingly serious problem. Improving water quality and achieving wastewater purification remain top priorities for environmental health initiatives. The Fenton process is favored by researchers due to its high efficiency and ease of operation. Central to the Fenton process is a catalyst used to activate hydrogen peroxide, rapidly degrading pollutants, improving water quality. Among various catalysts developed, copper-based catalysts have attracted considerable attention due to their affordability, high activity, and stable performance. Based on this, this paper reviews the development of copper-based Fenton systems over the past decade. It mainly involves the research and application of copper-based catalysts in different Fenton systems, including photo-Fenton, electro-Fenton, microwave-Fenton, and ultrasonic-Fenton. This review provides a fundamental reference for the subsequent studies of copper-based Fenton systems, contributing to the goal of transitioning these systems from laboratory research into practical environmental applications.

Artificial intelligence in environmental health and public safety: A comprehensive review of USA strategies

This study explores the transformative role of artificial intelligence (AI) in environmental health and public safety within the USA, focusing on pollution monitoring, emergency response, and sustainable practices for public. With the growing challenges posed by climate change, pollution, and emerging public health threats, the integration of Artificial Intelligence (AI) in environmental health and public safety strategies has become imperative. This comprehensive review explores the diverse array of AI applications implemented in the United States to address environmental issues and enhance public safety measures. The paper analyzes the multifaceted role of AI across various domains, including air and water quality monitoring, disease surveillance, disaster response, and infrastructure resilience. The advancements in AI technologies that have revolutionized data collection, analysis, and prediction in environmental health are examined. Machine learning algorithms, sensor networks, and satellite imagery are examined as tools for real-time monitoring and early detection of environmental hazards. Additionally, the paper investigates the integration of AI in public health surveillance systems, showcasing how predictive analytics and data-driven models contribute to the identification and containment of infectious diseases. Furthermore, the study sheds light on the incorporation of AI in disaster management, emphasizing the role of predictive modeling and risk assessment in optimizing emergency response strategies. The implementation of smart city technologies and intelligent infrastructure systems is discussed, highlighting how AI contributes to enhancing public safety and minimizing the impact of natural disasters. The review also critically evaluates the ethical, legal, and privacy considerations associated with the widespread adoption of AI in environmental health and public safety initiatives. It addresses concerns related to data security, algorithmic biases, and the need for transparent and accountable governance frameworks. Through an in-depth analysis of case studies, policies, and initiatives, this review provides insights into the successes and challenges of AI implementation in the USA. It concludes with recommendations for future research directions and policy considerations to ensure the responsible and effective integration of AI technologies in safeguarding environmental health and public safety. The findings presented in this review contribute to the broader discourse on leveraging AI for sustainable and resilient communities in the face of evolving environmental and public health challenges.

Qualitative communication research with environmental health scientists and stakeholders

Abstract Effective research translation and science communication are necessary for successful implementation of environmental health initiatives to improve public health. The Community Engagement Core (CEC) of the Center for Oceans and Human Health and Climate Change Interactions in the southeastern United States conducted a trio of qualitative studies to assess perceptions, experiences, and training needs relative to science communication and research translation of investigators and stakeholders. Interview transcripts were coded using open and axial coding and analyzed for emergent themes. (1) Interviews were conducted with 13 Center investigators. Most preferred in-person and written communication channels and felt comfortable communicating uncertain findings to the public despite no formal training. They asked for training on plain language messaging for communities, assessment of audience needs, and formatting research findings for various groups. (2) Interviews were conducted with 13 CEC stakeholders to learn more about their research translation needs, communication and dissemination tactics, and experiences interacting with scientists. Findings indicated the need for collaborative scientist-stakeholder training to include plain language development, communication evaluation, and audience engagement. (3) Follow-up interviews with 7 stakeholders examined specific topics of understanding, trust, and access and how those can become barriers or facilitators of public engagement with environmental activities. Findings showed the public may have limited understanding of scientific processes, establishing trust takes time, and ensuring access should be incorporated into all programs. Together, these analyses demonstrate the importance of engaging investigators and partners on all aspects of research. This presentation is relevant to other partner-engaged research and provides insights on practices for equitable and effective stakeholder engagement and collaboration. Key messages • Effective research translation and science communication are necessary for successful implementation of water resources management initiatives. • Qualitative research is important for assessing perceptions, experiences, and training needs relative to science communication and research translation for researchers and community partners.

Air Quality Forecasting Using Deep Learning Framework

Abstract: Air quality is a crucial environmental factor that affects human health and well-being. Accurate forecasting of air quality can aid in mitigating the adverse effects of air pollution. In this research paper, we propose a deep learning-based approach for air quality forecasting. We utilize Convolutional Neural Networks (CNN) and Bidirectional Long Short-Term Memory (BILSTM) models to capture spatial and temporal dependencies in air quality data. The existing system is analyzed, and its limitations are identified. Our proposed solution overcomes these limitations by incorporating deep learning techniques. Experimental results demonstrate the effectiveness of our approach in forecasting air quality, providing valuable insights for environmental management and public health initiatives.

Knowing Your Field Community: Elevating the Human Dimension in Ecological Research and Teaching.

Public health researchers have long been aware of the importance of defining the human community associated with research on environmental health initiatives. However, the field community's human components where applied ecology research is conducted, e.g. diverse participants and perspectives, are often overlooked in environmental problem solving. We outline a framework for elevating the human dimension in defining the field community in applied ecology research and for teaching diverse undergraduate students the skills needed to address Anthropocene environmental concerns. We promote broadening participation and incorporating cultural and racial perspectives in ecology research planning, implementation, and teaching. We use the environmental research problem of concern to identify the diverse human community groups potentially connected to the problem and guide the strategies for incorporating their perspectives in the proposed research project. Which human community, whether local, ethnic, or visiting public community, affects the resource management strategy, i.e. people protect what they love, can change the outcomes of applied ecological research, as well as promote development of a diverse environmental workforce. Broadening participation and perspectives means that the people asking the research questions are also part of the social ecological community processes who choose which questions to pursue to manage the natural resources of the community. Here, we promote research and teaching practices that consider the long-standing multicultural connections to nature to allow all students to pursue their love of nature and its beauty in a safe, comfortable, and mentoring setting. We integrate current human diversity, equity, and inclusion-focused pedagogical knowledge into the Ecological Society of America-endorsed 4DEE multidimensional curricular framework. We provide a faculty action guide to engage and train diverse students in ecological practices that meet the needs of today's environmental problem-solving workforce.

Stakeholders' Perceptions of Environmental and Public Health Risks Associated with Hydrocarbon Activities in and around the Vasilikos Energy Center, Cyprus.

: Background and aimThe Vasilikos Energy Center (VEC) is a large hydrocarbon industrial hub actively operating in Cyprus. There is strong public interest by the communities surrounding VEC to engage with all stakeholders towards the sustainable development of hydrocarbon in the region. The methodological framework of the exposome concept would allow for the holistic identification of all relevant environmental exposures by engaging the most relevant stakeholders in industrially contaminated sites. The main objectives of this study were to: (i) evaluate the stakeholders’ perceptions of the environmental and public health risks and recommended actions associated with the VEC hydrocarbon activities, and (ii) assess the stakeholders’ understanding and interest towards exposome-based technologies for use in oil and gas applications. Methods: Six major groups of stakeholders were identified: local authorities, small-medium industries (SMIs) (including multi-national companies), small-medium enterprises (SMEs), academia/professional associations, government, and the general public residing in the communities surrounding the VEC. During 2019–2021, a suite of stakeholder engagement initiatives was deployed, including semi-structured interviews (n = 32), a community survey for the general public (n = 309), technical meetings, and workshops (n = 4). Results from the semi-structured interviews, technical meetings and workshops were analyzed through thematic analysis and results from the community survey were analyzed using descriptive statistics. Results: Almost all stakeholders expressed the need for the implementation of a systematic health monitoring system for the VEC broader area and its surrounding residential communities, including frequent measurements of air pollutant emissions. Moreover, stricter policies by the government about licensing and monitoring of hydrocarbon activities and proper communication to the public and the mass media emerged as important needs. The exposome concept was not practiced by the SMEs, but SMIs showed willingness to use it in the future as part of their research and development activities. Conclusions: The sustainable development of hydrocarbon exploitation and processing prospects for Cyprus involves the VEC. Continuous and active collaboration and mutual feedback among all stakeholders involved with the VEC is essential, as this may allow future environmental and occupational health initiatives to be formalized.

Navigating to urban environmental health: Professionalized and personalized healthy living assistant based on intelligent health risk management

Facing unbalanced and inadequate urban development, the environmental health risk management (EHRM) try to provide an unbiased scientific assessment and control of risk posed by specific hazards. Shortage of personal exposure scenarios and parameters, dynamic multimedia environment pollution data, multi-target applications, etc. make challenges in current EHRM. The booming smart phone, Internet plus and Internet of things (IoT) technologies provide cost-efficient opportunities for above challenges. Hence, the “EnvironMax” framework, namely a “4M” (multi-scale, multimedia, multi-exposure, multi-target) environmental health risk monitoring & management system, is proposed. EnvironMax is composed of the environmental multimedia data source layer, communication and preprocessing layer, cloud-based environmental health brain layer, and user-oriented healthy living assistant layer. Multi-source data (mainly including Portable IoT + Location Service + application programming interface) based EnvironMax realizes multi-scale and multi-exposure EHRM, especially “4R” (Right Time, Right Place, Right Information, Right Person) EHRM. A testbed with EnvironMax applications, mainly including environmental health navigation, healthy city planning and healthy exercises assistant, are presented to verify the feasibility of the proposed architecture under a case environmental multimedia risk scenarios. Professionalized and Personalized EnvironMax is proved to support scientific urban sustainable development with aim of multilevel users' environmental health initiative management and equity.

How Does Being Solo in Nature Affect Well-Being? Evidence from Norway, Germany and New Zealand.

Background: Solo—being intentionally solitary in nature—is receiving growing attention as a valuable outdoor education program component. Its practice and history have been researched in the context of experiential learning, but few studies have explicitly examined how solo experiences can affect dimensions of well-being. This study investigated a broad range of well-being pathways provided by being solo, based on data from Norway, Germany, and New Zealand. Methods: Using qualitative content analysis (QCA), the solo debrief responses of 40 participants (26 females, age: 19–64 years) were analysed, applying the PERMA-V framework (emotions, engagement, relationship, meaning, achievement, and vitality). Variations in the reports were explored as a function of the national sample, gender, age, prior solo experiences and expectations. Results: The study suggests that hedonic and eudemonic well-being pathways, represented by the six PERMA-V pillars, interrelate strongly. The experience of a range of positive emotions and connecting process during solo highlights two of the most frequent findings related to well-being pathways. The secondary findings suggest minor variations in the well-being pathways for the different national samples, gender and age. Expectations and prior experiences with solo were identified as context factors with minor impact. Further, the data-driven analysis identified specific physical activities, landscape features, sense-activation, perception of time and ‘good’ weather as relevant to the specific experience. Conclusions: Solo experiences provide for well-being-related pathways in a multitude of ways, which highlights the well-being potential of solo implementation across practical fields beyond outdoor education, such as wilderness therapy, and environmental and planetary health initiatives. Future studies should continue to explore solo’s well-being potential in different settings, especially in the context of non-Western samples.

The determinants of complication trajectories in American Indians with type 2 diabetes.

BACKGROUNDWe aimed to determine whether metabolic syndrome (MetS) affects longitudinal trajectories of diabetic complications, including neuropathy, cardiovascular autonomic neuropathy (CAN), and kidney disease in American Indians with type 2 diabetes.METHODSWe performed a prospective study where participants underwent annual metabolic phenotyping and outcome measurements. The updated National Cholesterol Education Program criteria were used to define MetS and its individual components, using BMI instead of waist circumference. Neuropathy was defined using the Michigan Neuropathy Screening Instrument index, CAN with the expiration/inspiration ratio, and kidney disease with glomerular filtration rate. Mixed-effects models were used to evaluate associations between MetS and these outcomes.RESULTSWe enrolled 141 participants: 73.1% female, a mean (±SD) age of 49.8 (12.3), and a diabetes duration of 19.6 years (9.7 years) who were followed for a mean of 3.1 years (1.7 years). MetS components were stable during follow-up except for declining obesity and cholesterol. Neuropathy (point estimate [PE]: 0.30, 95% CI: 0.24, 0.35) and kidney disease (PE: –14.2, 95% CI: –16.8, –11.4) worsened over time, but CAN did not (PE: –0.002, 95% CI: –0.006, 0.002). We found a significant interaction between the number of MetS components and time for neuropathy (PE: 0.05, 95% CI: 0.01–0.10) but not CAN (PE: –0.003, 95% CI: –0.007, 0.001) or kidney disease (PE: –0.69, 95% CI: –3.16, 1.76). Systolic blood pressure (SBP, unit = 10 mmHg) was associated with each complication: neuropathy (PE: 0.23, 95% CI: 0.07, 0.39), CAN (PE: –0.02, 95% CI: –0.03, –0.02), and kidney disease (PE: –10.2, 95% CI: –15.4, –5.1).CONCLUSIONIn participants with longstanding diabetes, neuropathy and kidney disease worsened during follow-up, despite stable to improving MetS components, suggesting that early metabolic intervention is necessary to prevent complications in such patients. Additionally, the number of MetS components was associated with an increased rate of neuropathy progression, and SBP was associated with each complication.FUNDINGThe following are funding sources: NIH T32NS0007222, NIH R24DK082841, NIH R21NS102924, NIH R01DK115687, the Intramural Program of the NIDDK, the NeuroNetwork for Emerging Therapies, the Robert and Katherine Jacobs Environmental Health Initiative, the Robert E. Nederlander Sr. Program for Alzheimer’s Research, and the Sinai Medical Staff Foundation.TRIAL REGISTRATIONClinicalTrials.gov, NCT00340678.

Bridging Silos: A Research Agenda for Local Environmental Health Initiatives.

The environment and public health are managed by separate institutions that often operate in isolation from each other. This system is often referred to as managing in "silos." The resulting lack of coordination, inadequate consideration of cumulative effects, and diffuse targets for change contribute to the persistence of many environmental justice problems. There are many barriers to bridging these silos, particularly at state and federal levels. Local collaborations, however, may have greater potential for changing these systems. There has been limited assessment of successful local environmental health initiatives. This paper explores three case studies of local collaboration: lead poisoning prevention in Rochester, New York; promoting a healthy and equitable built environment in Duluth, Minnesota; and increasing consideration of community health in decisions around the ports of Los Angeles and Long Beach, California. It develops a research agenda to inform future collaborations to improve environmental health equity through local systems change.

1992-P: Metabolic Factors Associated with Cognitive Function and Brain Morphology in Type 2 Diabetes

Background: Pima Indians from the Gila River Indian Community in Arizona, USA, have a high prevalence of type 2 diabetes and have been studied for decades to evaluate the risk factors for and trajectory of diabetic complications. Here, we aimed to identify metabolic factors associated with central nervous system sequelae in this population. Methods: Cognitive performance and ultrastructural brain volumes were determined in Pima Indians via the NIH Toolbox Cognitive Battery (NIHTB-CB) (n=51) and MRI studies (n=40). The NIHTB-CB Composite Score was the primary measure of cognitive function, adjusting for age, sex, race, and education level. MRI derived morphology measures included total cortical volume and white and gray matter volumes. Metabolic factors included duration of diabetes, height, weight, BMI, SBP, DBP, HbA1c, triglycerides, HDL, LDL, and total cholesterol. We performed univariate linear regressions on MRI outcomes and NIHTB-CB Composite Scores as functions of metabolic factors after adjusting for age/sex, and we calculated Pearson’s correlation between each MRI morphology outcome and the Composite Score. Results: Of the 51 subjects who underwent the NIHTB-CB, 40 completed an MRI. Linear regression models revealed that only BMI associated with both total cortical volume (BMI point estimate (PE): -.0007, CI: -.001, -.0002) and total gray matter volume (BMI PE:-.0009, CI: -.001, -.0003). No metabolic factors associated with the NIHTB-CB Composite Score, and the NIHTB-CB Composite Score did not correlate with any morphology measures. Conclusion: Increased BMI was associated with both decreased cortical volume and gray matter volume in this Pima cohort, similar to observations found for obesity in previously published cohorts. Though volume measures and NIHTB-CB scores did not correlate in this study, future work will analyze additional MRI based morphology measures to evaluate correlations with individual NIHTB-CB tests and assess changes over time. Disclosure R.E. Henn: None. E.L. Reynolds: None. A. Patterson: None. R.G. Nelson: None. E.L. Feldman: Consultant; Self; Novartis Pharmaceuticals Corporation. B.C. Callaghan: None. Funding National Institutes of Health (R24DK082841, T32NS0007222); Robert and Katherine Jacobs Environmental Health Initiative; Robert E. Nederlander, Sr. Program for Alzheimer’s Research; National Institute of Diabetes and Digestive and Kidney Diseases; Sinai Medical Staff Foundation

532-P: The Longitudinal Determinants of Diabetic Complications in the Pima Indians of Arizona

The 5 components of the metabolic syndrome (MetS) increase the likelihood of developing diabetes, heart disease, and stroke, but their association with neuropathy and diabetic kidney disease (DKD) is less understood. We examined the longitudinal association between the components of the updated National Cholesterol Education Program criteria for MetS, neuropathy and DKD in Pima Indians with type 2 diabetes, after substituting BMI for waist circumference. The primary outcome for neuropathy was the Michigan Neuropathy Screening Instrument index, for cardiovascular autonomic neuropathy (CAN) was the expiration/inspiration ratio, and for DKD was the Glomerular Filtration Rate. At baseline and during annual follow-up exams, participants underwent metabolic phenotyping and outcome measurements. Linear mixed effects models with a random patient effect were used to evaluate the associations between the number of MetS components and neuropathy, CAN, and DKD outcomes. We also examined mixed models for each outcome with individual MetS components. Between 11/1/2013 and 7/1/2019, we studied 141 Pima Indian subjects, who were followed an average of 3.2 years. The mixed effects models revealed a significant interaction between the number of MetS components and follow-up time for neuropathy (point estimate (PE): 0.07, CI: 0.02-0.11), indicating that the rate of neuropathy increases as the number of MetS components increases. Additionally, we found that neuropathy (year PE: 0.30, CI: 0.24,0.35) and DKD (PE: -14.2, CI: -16.8,-11.4), worsened over time, but CAN did not. The mixed models with individual MetS components revealed SBP was associated with each complication: neuropathy (PE: 0.23, CI: 0.07,0.39), CAN (PE: -0.02, CI: -0.03,-0.02) and DKD (PE: -10.2, CI: -15.4,-5.1). Neuropathy progression was the complication most affected by the number of MetS components. Neuropathy and DKD worsened during follow-up, emphasizing how quickly these complications can change within this population. Disclosure E.L. Reynolds: None. R.G. Nelson: None. G. Akinci: Advisory Panel; Spouse/Partner; Aegerion Pharmaceuticals, Regeneron Pharmaceuticals. Speaker’s Bureau; Spouse/Partner; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, Merck Sharp & Dohme Corp., Novartis AG, Novo Nordisk A/S, Sanofi-Aventis, Servier. R. Henn: None. A. Patterson: None. E.L. Feldman: Consultant; Self; Novartis Pharmaceuticals Corporation. B.C. Callaghan: None. Funding National Institutes of Health (R24DK082841, T32NS0007222, R01DK115687); Program for Neurology Research & Discovery; Robert and Katherine Jacobs Environmental Health Initiative; Robert E. Nederlander, Sr. Program for Alzheimer’s Research; Sinai Medical Staff Foundation

Identifying Needs for Advancing the Profession and Workforce in Environmental Health.

An ever-changing landscape for environmental health (EH) requires in-depth assessment and analysis of the current challenges and emerging issues faced by EH professionals. The Understanding the Needs, Challenges, Opportunities, Vision, and Emerging Roles in Environmental Health initiative addressed this need.After receiving responses from more than 1700 practitioners, during an in-person workshop, focus groups identified and described priority problems and supplied context on addressing the significant challenges facing EH professionals with state health agencies and local health departments. The focus groups developed specific problem statements detailing the EH profession and workforce's prevailing challenges and needs according to 6 themes, including effective leadership, workforce development, equipment and technology, information systems and data, garnering support, and partnerships and collaboration.We describe the identified priority problems and needs and provide recommendations for ensuring a strong and robust EH profession and workforce ready to address tomorrow's challenges.

Checklist of the planktonic marine dinoflagellates of New Zealand

ABSTRACTPlanktonic dinoflagellate records for New Zealand are substantial due to intense monitoring programmes that have taken place on behalf of New Zealand’s biotoxin regulators and the shellfish industry since 1993. At that time a Karenia bloom caused human illnesses and shellfish harvesting ceased until monitoring was instigated. Phytoplankton records are based on morphological identification using light microscopy but are backed up by government funded research programmes which implement techniques such as electron microscopy, DNA sequencing, molecular detection assays and high throughput sequencing of environmental DNA. This checklist will support management of aquaculture industries, recreational shellfish harvests and environmental health initiatives. Some genera are considered benthic or epiphytic, but have lengthy planktonic life stages. Forty-five genera in the class Dinophyceae Fritsch are reported: Akashiwo, Alexandrium, Amphidinium, Amylax, Azadinium, Biecheleria, Bysmatrum, Cachonina, Cochlodinium (synonym: Margalefidinium), Coolia, Dicroerisma, Dinophysis, Diploneis, Diplopsalis, Fragilidium, Glenodinium, Gonyaulax, Gymnodinium, Gyrodinium, Heterocapsa, Karenia, Karlodinium, Lepidodinium, Lingulodinium, Margalefidinium, Ostreopsis, Oxyphysis, Pelagodinium, Pentapharsodinium, Phalacroma, Podolampas, Polarella, Polykrikos, Prorocentrum, Protodinium, Protoodinium, Protoperidinium, Pseliodinium, Scrippsiella, Takayama, Togula, Torodinium, Tripos, Vulcanodinium, Wolosynska. Other genera belonging to the Infraphylum Dinoflagellata also occur in New Zealand waters. They are not in the list but include Noctiluca, Pronoctiluca and Spatulodinium (Class: Noctilucophyceae) and Oxyrrhis (Class: Oxyrrhidophyceae).

Application of Geographic Information Systems to Address Chronic Disease Priorities: Experiences in State and Local Health Departments.

Application of Geographic Information Systems to Address Chronic Disease Priorities: Experiences in State and Local Health Departments.

The environment ontology in 2016: bridging domains with increased scope, semantic density, and interoperation.

BackgroundThe Environment Ontology (ENVO; http://www.environmentontology.org/), first described in 2013, is a resource and research target for the semantically controlled description of environmental entities. The ontology's initial aim was the representation of the biomes, environmental features, and environmental materials pertinent to genomic and microbiome-related investigations. However, the need for environmental semantics is common to a multitude of fields, and ENVO's use has steadily grown since its initial description. We have thus expanded, enhanced, and generalised the ontology to support its increasingly diverse applications.MethodsWe have updated our development suite to promote expressivity, consistency, and speed: we now develop ENVO in the Web Ontology Language (OWL) and employ templating methods to accelerate class creation. We have also taken steps to better align ENVO with the Open Biological and Biomedical Ontologies (OBO) Foundry principles and interoperate with existing OBO ontologies. Further, we applied text-mining approaches to extract habitat information from the Encyclopedia of Life and automatically create experimental habitat classes within ENVO.ResultsRelative to its state in 2013, ENVO's content, scope, and implementation have been enhanced and much of its existing content revised for improved semantic representation. ENVO now offers representations of habitats, environmental processes, anthropogenic environments, and entities relevant to environmental health initiatives and the global Sustainable Development Agenda for 2030. Several branches of ENVO have been used to incubate and seed new ontologies in previously unrepresented domains such as food and agronomy. The current release version of the ontology, in OWL format, is available at http://purl.obolibrary.org/obo/envo.owl.ConclusionsENVO has been shaped into an ontology which bridges multiple domains including biomedicine, natural and anthropogenic ecology, ‘omics, and socioeconomic development. Through continued interactions with our users and partners, particularly those performing data archiving and sythesis, we anticipate that ENVO’s growth will accelerate in 2017. As always, we invite further contributions and collaboration to advance the semantic representation of the environment, ranging from geographic features and environmental materials, across habitats and ecosystems, to everyday objects in household settings.

Implications of construction method and spatial scale on measures of the built environment.

BackgroundResearch surrounding the built environment (BE) and health has resulted in inconsistent findings. Experts have identified the need to examine methodological choices, such as development and testing of BE indices at varying spatial scales. We sought to examine the impact of construction method and spatial scale on seven measures of the BE using data collected at two time points.MethodsThe Children’s Environmental Health Initiative conducted parcel-level assessments of 57 BE variables in Durham, NC (parcel N = 30,319). Based on a priori defined variable groupings, we constructed seven mutually exclusive BE domains (housing damage, property disorder, territoriality, vacancy, public nuisances, crime, and tenancy). Domain-based indices were developed according to four different index construction methods that differentially account for number of parcels and parcel area. Indices were constructed at the census block level and two alternative spatial scales that better depict the larger neighborhood context experienced by local residents: the primary adjacency community and secondary adjacency community. Spearman’s rank correlation was used to assess if indices and relationships among indices were preserved across methods.ResultsTerritoriality, public nuisances, and tenancy were weakly to moderately preserved across methods at the block level while all other indices were well preserved. Except for the relationships between public nuisances and crime or tenancy, and crime and housing damage or territoriality, relationships among indices were poorly preserved across methods. The number of indices affected by construction method increased as spatial scale increased, while the impact of construction method on relationships among indices varied according to spatial scale.ConclusionsWe found that the impact of construction method on BE measures was index and spatial scale specific. Operationalizing and developing BE measures using alternative methods at varying spatial scales before connecting to health outcomes allows researchers to better understand how methodological decisions may affect associations between health outcomes and BE measures. To ensure that associations between the BE and health outcomes are not artifacts of methodological decisions, researchers would be well-advised to conduct sensitivity analysis using different construction methods. This approach may lead to more robust results regarding the BE and health outcomes.Electronic supplementary materialThe online version of this article (doi:10.1186/s12942-016-0044-x) contains supplementary material, which is available to authorized users.

Special Issue on Pacific Health

The World Health Organization (WHO) has defined a healthy island as an island that is committed to, and involved in, a process of achieving a better health and quality of life for its people and healthier physical and social environments in the context of sustainable environment. The main challenges facing island health include the increasing burden of noncommunicable diseases as well as the continuing, and sometimes reemerging, burden of communicable diseases. Human resources for heath in remote areas are always a problem, but it is even more difficult to develop and retain health workers on islands. Some remote island villages, be it in the Pacific region or elsewhere, have only the bare necessities for survival; no electricity, no proper toilets or clean drinking water. In India, for example, the Indian government brings electric power, education, and health services to rural villages. Together with UNICEF, the Indian government is attempting to bring basic health care to isolated island villages, such as those situated along the Brahmaputra River or in the Andaman archipelagoes. But the challenge of small populations, remoteness and an island environment make this difficult. Indonesia and the Philippines have the largest number of islands, countless thousands of them, and providing public health services in these remote island villages is difficult and challenging because of geography, culture, economics, and politics. In the Pacific islands, the “healthy island” concept provides a theoretical underpinning for efforts in health promotion and health protection in island countries. WHO began its healthy island initiatives in 1995. Healthy island initiatives are linked to community commitment and take various forms in several Pacific islands countries. Some initiatives focus on control of specific diseases or health problems, for example, malaria control in the Solomon Islands, environmental health and health promotion initiatives in Fiji, or on water supply and sanitation in Tonga. All these pose a challenge to the coordination of health programs and interventions and the strengthening of public health in these island countries. Binns et al, 1 in their article, discussed the issues and challenges of island health and its impact on public health and illustrated the scope of the problem of island health and how health services in islands required an integrated approach to public health and clinical services. The roles of schools of public health are highlighted in promoting healthy islands. There is a need to develop competency in knowledge and skills and in inculcating a right and positive attitude for island health with the hope of delivering island health leadership in health care. Furthermore, there is a need for intersectoral collaborations, and cooperation is a matter of necessity among Pacific island nations. 2

Joint Bayesian analysis of birthweight and censored gestational age using finite mixture models

Birthweight and gestational age are closely related and represent important indicators of a healthy pregnancy. Customary modeling for birthweight is conditional on gestational age. However, joint modeling directly addresses the relationship between gestational age and birthweight, and provides increased flexibility and interpretation as well as a strategy to avoid using gestational age as an intermediate variable. Previous proposals have utilized finite mixtures of bivariate regression models to incorporate well-established risk factors into analysis (e.g. sex and birth order of the baby, maternal age, race, and tobacco use) while examining the non-Gaussian shape of the joint birthweight and gestational age distribution. We build on this approach by demonstrating the inferential (prognostic) benefits of joint modeling (e.g. investigation of 'age inappropriate' outcomes like small for gestational age) and hence re-emphasize the importance of capturing the non-Gaussian distributional shapes. We additionally extend current models through a latent specification which admits interval-censored gestational age. We work within a Bayesian framework which enables inference beyond customary parameter estimation and prediction as well as exact uncertainty assessment. The model is applied to a portion of the 2003-2006 North Carolina Detailed Birth Record data (n=336129) available through the Children's Environmental Health Initiative and is fitted using the Bayesian methodology and Markov chain Monte Carlo approaches.