Dataset of 2012-2020 U.S. National- and State-Level Greenhouse Gas Emissions by Sector.

The dataset contains ∼1.1 million records of total greenhouse gases directly emitted annually by economic sectors and households in the US from 2012-2020. Data are given for 16 unique greenhouse gases by 118 aggregate sectors for each state, and as totals by these aggregate sectors as well as by 540 detailed sectors at the national level. The dataset is a product of updated sector attribution models that improve upon the National Greenhouse Gas Industry Attribution Model. This paper provides documentation of the methods used to produce these datasets and proof of validation of the dataset, along with relevant supporting tables, figures, and source code.

"Like fighting a fire with a water pistol": A qualitative study of the work experiences of critical care nurses during the COVID-19 pandemic.

AIM: To understand the experience of critical care nurses during the COVID-19 pandemic, through the application of the Job-Demand-Resource model of occupational stress. DESIGN: Qualitative interview study. METHODS: Twenty-eight critical care nurses (CCN) working in ICU in the UK NHS during the COVID-19 pandemic took part in semi-structured interviews between May 2021 and May 2022. Interviews were guided by the constructs of the Job-Demand Resource model. Data were analysed using framework analysis. RESULTS: The most difficult job demands were the pace and amount, complexity, physical and emotional effort of their work. Prolonged high demands led to CCN experiencing emotional and physical exhaustion, burnout, post-traumatic stress symptoms and impaired sleep. Support from colleagues and supervisors was a core job resource. Sustained demands and impaired physical and psychological well-being had negative organizational consequences with CCN expressing increased intention to leave their role. CONCLUSIONS: The combination of high demands and reduced resources had negative impacts on the psychological well-being of nurses which is translating into increased consideration of leaving their profession. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: The full impacts of the pandemic on the mental health of CCN are unlikely to resolve without appropriate interventions. IMPACT: Managers of healthcare systems should use these findings to inform: (i) the structure and organization of critical care workplaces so that they support staff to be well, and (ii) supportive interventions for staff who are carrying significant psychological distress as a result of working during and after the pandemic. These changes are required to improve staff recruitment and retention. REPORTING METHOD: We used the COREQ guidelines for reporting qualitative studies. PATIENT AND PUBLIC CONTRIBUTION: Six CCN provided input to survey content and interview schedule. Two authors and members of the study team (T.S. and S.C.) worked in critical care during the pandemic.

Increasing uptake of FIT colorectal screening: protocol for the TEMPO randomised controlled trial testing a suggested deadline and a planning tool.

INTRODUCTION: Screening can reduce deaths from colorectal cancer (CRC). Despite high levels of public enthusiasm, participation rates in population CRC screening programmes internationally remain persistently below target levels. Simple behavioural interventions such as completion goals and planning tools may support participation among those inclined to be screened but who fail to act on their intentions. This study aims to evaluate the impact of: (a) a suggested deadline for return of the test; (b) a planning tool and (c) the combination of a deadline and planning tool on return of faecal immunochemical tests (FITs) for CRC screening. METHODS AND ANALYSIS: A randomised controlled trial of 40 000 adults invited to participate in the Scottish Bowel Screening Programme will assess the individual and combined impact of the interventions. Trial delivery will be integrated into the existing CRC screening process. The Scottish Bowel Screening Programme mails FITs to people aged 50-74 with brief instructions for completion and return. Participants will be randomised to one of eight groups: (1) no intervention; (2) suggested deadline (1 week); (3) suggested deadline (2 weeks); (4) suggested deadline (4 weeks); (5) planning tool; (6) planning tool plus suggested deadline (1 week); (7) planning tool plus suggested deadline (2 weeks); (8) planning tool plus suggested deadline (4 weeks). The primary outcome is return of the correctly completed FIT at 3 months. To understand the cognitive and behavioural mechanisms and to explore the acceptability of both interventions, we will survey (n=2000) and interview (n=40) a subgroup of trial participants. ETHICS AND DISSEMINATION: The study has been approved by the National Health Service South Central-Hampshire B Research Ethics Committee (ref. 19/SC/0369). The findings will be disseminated through conference presentations and publication in peer-reviewed journals. Participants can request a summary of the results. TRIAL REGISTRATION NUMBER: clinicaltrials.govNCT05408169.

Bipolar impact and phasing of Heinrich-type climate variability.

During the last ice age, the Laurentide Ice Sheet exhibited extreme iceberg discharge events that are recorded in North Atlantic sediments1. These Heinrich events have far-reaching climate impacts, including widespread disruptions to hydrological and biogeochemical cycles2-4. They occurred during Heinrich stadials-cold periods with strongly weakened Atlantic overturning circulation5-7. Heinrich-type variability is not distinctive in Greenland water isotope ratios, a well-dated site temperature proxy8, complicating efforts to assess their regional climate impact and phasing against Antarctic climate change. Here we show that Heinrich events have no detectable temperature impact on Greenland and cooling occurs at the onset of several Heinrich stadials, and that both types of Heinrich variability have a distinct imprint on Antarctic climate. Antarctic ice cores show accelerated warming that is synchronous with increases in methane during Heinrich events, suggesting an atmospheric teleconnection9, despite the absence of a Greenland climate signal. Greenland ice-core nitrogen stable isotope ratios, a sensitive temperature proxy, indicate an abrupt cooling of about three degrees Celsius at the onset of Heinrich Stadial 1 (17.8 thousand years before present, where present is defined as 1950). Antarctic warming lags this cooling by 133 ± 93 years, consistent with an oceanic teleconnection. Paradoxically, proximal sites are less affected by Heinrich events than remote sites, suggesting spatially complex event dynamics.

Life Cycle Data Interoperability Improvements through Implementation of the Federal LCA Commons Elementary Flow List.

As a fundamental component of data for life cycle assessment models, elementary flows have been demonstrated to be a key requirement of life cycle assessment data interoperability. However, existing elementary flow lists have been found to lack sufficient structure to enable improved interoperability between life cycle data sources. The Federal Life Cycle Assessment Commons Elementary Flow List provides a novel framework and structure for elementary flows, but the actual improvement this list provides to the interoperability of life cycle data has not been tested. The interoperability of ten elementary flow lists, two life cycle assessment databases, three life cycle impact assessment methods, and five life cycle assessment software sources is assessed with and without use of the Federal Life Cycle Assessment Commons Elementary Flow List as an intermediary in flow mapping. This analysis showed that only 25% of comparisons between these sources resulted in greater than 50% of flows being capable of automatic name-to-name matching between lists. This indicates that there is a low level of interoperability when using sources with their original elementary flow nomenclature, and elementary flow mapping is required to use these sources in combination. The mapping capabilities of the Federal Life Cycle Assessment Commons Elementary Flow List to sources were reviewed and revealed a notable increase in name-to-name matches. Overall, this novel framework is found to increase life cycle data source interoperability.

FLOWSA: A Python Package Attributing Resource Use, Waste, Emissions, and Other Flows to Industries.

Quantifying industry consumption or production of resources, wastes, emissions, and losses-collectively called flows-is a complex and evolving process. The attribution of flows to industries often requires allocating multiple data sources that span spatial and temporal scopes and contain varied levels of aggregation. Once calculated, datasets can quickly become outdated with new releases of source data. The US Environmental Protection Agency (USEPA) developed the open-source Flow Sector Attribution (FLOWSA) Python package to address the challenges surrounding attributing flows to US industrial and final-use sectors. Models capture flows drawn from or released to the environment by sectors, as well as flow transfers between sectors. Data on flow use and generation by source-defined activities are imported from providers and transformed into standardized tables but are otherwise numerically unchanged in preparation for modeling. FLOWSA sector attribution models allocate primary data sources to industries using secondary data sources and file mapping activities to sectors. Users can modify methodological, spatial, and temporal parameters to explore and compare the impact of sector attribution methodological changes on model results. The standardized data outputs from these models are used as the environmental data inputs into the latest version of USEPA's US Environmentally Extended Input-Output (USEEIO) models, life cycle models of US goods and services for ~400 categories. This communication demonstrates FLOWSA's capability by describing how to build models and providing select model results for US industry use of water, land, and employment. FLOWSA is available on GitHub, and many of the data outputs are available on the USEPA's Data Commons.

A System for Standardizing and Combining U.S. Environmental Protection Agency Emissions and Waste Inventory Data.

The U.S. Environmental Protection Agency (USEPA) provides databases that agglomerate data provided by companies or states reporting emissions, releases, wastes generated, and other activities to meet statutory requirements. These databases, often referred to as inventories, can be used for a wide variety of environmental reporting and modeling purposes to characterize conditions in the United States. Yet, users are often challenged to find, retrieve, and interpret these data due to the unique schemes employed for data management, which could result in erroneous estimations or double-counting of emissions. To address these challenges, a system called Standardized Emission and Waste Inventories (StEWI) has been created. The system consists of four python modules that provide rapid access to USEPA inventory data in standard formats and permit filtering and combination of these inventory data. When accessed through StEWI, reported emissions of carbon dioxide to air and ammonia to water are reduced approximately two- and four-fold, respectively, to avoid duplicate reporting. StEWI will greatly facilitate the use of USEPA inventory data in chemical release and exposure modeling and life cycle assessment tools, among other things. To date, StEWI has been used to build the recent USEEIO model and the baseline electricity life cycle inventory database for the Federal LCA Commons.

useeior: An Open-Source R Package for Building and Using US Environmentally-Extended Input-Output Models.

useeior is an open-source R package that builds USEEIO models, a family of environmentally-extended input-output models of US goods and services used for life cycle assessment, environmental footprint estimation, and related applications. USEEIO models have gained a wide user base since their initial release in 2017, but users were often challenged to prepare required input data and undergo a complicated model building approach. To address these challenges, useeior was created. In useeior, economic and environmental data are conveniently retrievable for immediate use. Users can build models simply from given or user-specified model configuration and optional hybridization specifications. The assembly of economic and environmental data and matrix calculations are automatically performed. Users can export model results to desired formats. useeior is a core component of the USEEIO modeling framework. It improves transparency, efficiency, and flexibility in building USEEIO models, and was used to deliver the recent USEEIO model.

USEEIO v2.0, The US Environmentally-Extended Input-Output Model v2.0.

USEEIO v2.0 is an environmental-economic model of US goods and services that can be used for life cycle assessment, footprinting, national prioritization, and related applications. This paper describes the development of the model and accompanies the release of a full model dataset as well as various supporting datasets of national environmental totals by US industry. Novel methodological elements since USEEIO v1 models include waste sector disaggregation, final demand vectors for US consumption and production, a domestic form of the model that can be used to separate domestic and foreign impacts, and price adjustment matrices for converting outputs to purchaser price and in various US dollar years. Improvements in modeling national totals of industry and environmental flows are described. The model is validated through reproduction of national totals from input data sources and through analysis of changes from the most recent complete USEEIO model that can be explained based on data updates or method changes. The model datasets can all be reproduced with open source software packages.

A systematic review of behavioural smoking cessation interventions for people with severe mental ill health-what works?

BACKGROUND AND AIMS: People with severe mental ill health smoke more and suffer greater smoking-related morbidity and mortality. Little is known about the effectiveness of behavioural interventions for smoking cessation in this group. This review evaluated randomized controlled trial evidence to measure the effectiveness of behavioural smoking cessation interventions (both digital and non-digital) in people with severe mental ill health. DESIGN: Systematic review and random-effects meta-analysis. We searched between inception and January 2020 in Medline, EMBASE, PsycINFO, CINAHL, Health Management Information Consortium and CENTRAL databases. SETTING AND PARTICIPANTS: Randomized controlled trials (RCTs) assessing the effects of behavioural smoking cessation and reduction interventions in adults with severe mental ill health, conducted in any country, in either in-patient or community settings and published in English. MEASUREMENTS: The primary outcome was biochemically verified smoking cessation. Smoking reduction and changes in mental health symptoms and body mass index (BMI) were included as secondary outcomes. Narrative data synthesis and meta-analysis were conducted and the quality of included studies was appraised using the risk of bias 2 (RoB2) tool. FINDINGS: We included 12 individual studies (16 articles) involving 1861 participants. The first meta-analysis (three studies, 921 participants) demonstrated effectiveness of bespoke face-to-face interventions compared with usual care across all time-points [medium-term: relative risk (RR) = 2.29, 95% confidence interval (CI) = 1.38-3.81; long-term: RR = 1.58, 95% CI = 1.09-2.30]. The second (three studies, 275 participants) did not demonstrate any difference in effectiveness of bespoke digital on-line interventions compared with standard digital on-line interventions (medium-term: RR = 0.87, 95% CI = 0.17-4.46). A narrative overview revealed mixed results when comparing bespoke face-to-face interventions with other active interventions. The methodological quality of studies was mixed, with the majority having some concerns mainly around risk of selective reporting. CONCLUSIONS: Face-to-face bespoke smoking cessation interventions for adults with severe mental ill health appear to be effective when compared with treatment as usual, but evidence is equivocal when compared with other active interventions. There is limited evidence comparing bespoke digital interventions with generic interventions, and we found no studies comparing them with usual treatment.

Annotating unknown species of urban microorganisms on a global scale unveils novel functional diversity and local environment association.

In urban ecosystems, microbes play a key role in maintaining major ecological functions that directly support human health and city life. However, the knowledge about the species composition and functions involved in urban environments is still limited, which is largely due to the lack of reference genomes in metagenomic studies comprises more than half of unclassified reads. Here we uncovered 732 novel bacterial species from 4728 samples collected from various common surface with the matching materials in the mass transit system across 60 cities by the MetaSUB Consortium. The number of novel species is significantly and positively correlated with the city population, and more novel species can be identified in the skin-associated samples. The in-depth analysis of the new gene catalog showed that the functional terms have a significant geographical distinguishability. Moreover, we revealed that more biosynthetic gene clusters (BGCs) can be found in novel species. The co-occurrence relationship between BGCs and genera and the geographical specificity of BGCs can also provide us more information for the synthesis pathways of natural products. Expanded the known urban microbiome diversity and suggested additional mechanisms for taxonomic and functional characterization of the urban microbiome. Considering the great impact of urban microbiomes on human life, our study can also facilitate the microbial interaction analysis between human and urban environment.

Effectiveness of cascade testing strategies in relatives for familial hypercholesterolemia: A systematic review and meta-analysis.

BACKGROUND AND AIMS: Cascade testing in relatives of index cases is the most cost-effective approach to identifying people with familial hypercholesterolemia (FH); however, it is currently unclear which strategy to contact relatives would be the most effective. A systematic review was performed to quantify the effectiveness of different strategies in cascade testing of FH. METHODS: Comprehensive searches of three electronic databases and grey literature sources were done (from inception to May 2020). Screening, data extraction and assessments of methodological quality were made independently by two reviewers. Meta-analyses of proportions were performed using random effects models. Effect measures are reported as percentages with 95% confidence intervals. RESULTS: 24 non-comparative studies were included, of which 11 used a direct, 8 used an indirect, and 5 used a combination of both direct and indirect cascade strategies. The median number of new relatives with FH per known index case was approximately 1. The combination strategy resulted in the largest yields of relatives tested for FH out of those contacted (40%, 95% CI 37%-42%, 1 study) and relatives responding to testing out of those contacted (54%, 1 study); however, the direct strategy had the largest yield of index cases participating in cascade testing out of those with FH confirmed (94%, 8 studies) compared to other strategies (p ≤ 0.01 for all comparisons). CONCLUSIONS: Evidence is limited; however, a combination strategy, which allows the index case to decide on method of contacting relatives, appears to lead to better yields compared to using the direct or indirect strategy.

LCIA Formatter.

Life Cycle Assessment (LCA) is an established and standardized methodology to comprehensively assess environmental and public health metrics across industries and products (International Organization for Standardization, 2006). The United States Environmental Protection Agency (USEPA) is developing an open source LCA tool ecosystem (Ingwersen, 2019). The ecosystem includes tools to automate the creation of life cycle inventory (LCI) datasets, which account for flows to and from nature for steps across the life cycle of products or services, and tools for life cycle impact assessment (LCIA) to support classification and characterization of the cumulative LCI to potential impacts. Impacts are expressed via indicators, either midpoint or endpoint, corresponding to different points on the environmental cause-effect chain model (Frischknecht & Jolliet, 2016). This paper describes a USEPA LCA ecosystem tool 'LCIA formatter' that extracts LCIA information from original source methods and converts the data for interoperability with the rest of the USEPA LCA ecosystem tools.

Exploring the facilitators, barriers, and strategies for self-management in adults living with severe mental illness, with and without long-term conditions: A qualitative evidence synthesis.

BACKGROUND: People living with severe mental illness (SMI) have a reduced life expectancy by around 15-20 years, in part due to higher rates of long-term conditions (LTCs) such as diabetes and heart disease. Evidence suggests that people with SMI experience difficulties managing their physical health. Little is known, however, about the barriers, facilitators and strategies for self-management of LTCs for people with SMI. AIM: To systematically review and synthesise the qualitative evidence exploring facilitators, barriers and strategies for self-management of physical health in adults with SMI, both with and without long-term conditions. METHODS: CINAHL, Conference Proceedings Citation Index- Science, HMIC, Medline, NICE Evidence and PsycInfo were searched to identify qualitative studies that explored barriers, facilitators and strategies for self-management in adults with SMI (with or without co-morbid LTCs). Articles were screened independently by two independent reviewers. Eligible studies were purposively sampled for synthesis according to the richness and relevance of data, and thematically synthesised. RESULTS: Seventy-four articles met the inclusion criteria for the review; 25 articles, reporting findings from 21 studies, were included in the synthesis. Seven studies focused on co-morbid LTC self-management for people with SMI, with the remaining articles exploring self-management in general. Six analytic themes and 28 sub-themes were identified from the synthesis. The themes included: the burden of SMI; living with co-morbidities; beliefs and attitudes about self-management; support from others for self-management; social and environmental factors; and routine, structure and planning. CONCLUSIONS: The synthesis identified a range of barriers and facilitators to self-management, including the burden of living with SMI, social support, attitudes towards self-management and access to resources. To adequately support people with SMI with co-morbid LTCs, healthcare professionals need to account for how barriers and facilitators to self-management are influenced by SMI, and meet the unique needs of this population.

Determinants of Physical Health Self-Management Behaviours in Adults With Serious Mental Illness: A Systematic Review.

Behavioural interventions can support the adoption of healthier lifestyles and improve physical health outcomes, but it is unclear what factors might drive success of such interventions in people with serious mental illness (SMI). We systematically identified and reviewed evidence of the association between determinants of physical health self-management behaviours in adults with SMI. Data about American Association of Diabetes Educator's Self-Care Behaviours (AADE-7) were mapped against the novel Mechanisms of Action (MoA) framework. Twenty-eight studies were included in the review, reporting evidence on 104 determinant-behaviour links. Beliefs about capabilities and beliefs about consequences were the most important determinants of behaviour, especially for being physically active and healthy eating. There was some evidence that emotion and environmental context and resources played a role in determining reducing risks, being active, and taking medications. We found very limited evidence associated with problem solving, and no study assessed links between MoAs and healthy coping. Although the review predominantly identified evidence about associations from cross-sectional studies that lacked validated and objective measures of self-management behaviours, these findings can facilitate the identification of behaviour change techniques with hypothesised links to determinants to support self-management in people with SMI. Systematic Review Registration: PROSPERO, registration CRD42018099553.

Understanding patient factors to increase uptake of cancer screening: a review.

Early detection of cancer through organized screening is a central component of population-level strategies to reduce cancer mortality. For screening programs to be effective, it is important that those invited to screening participate. However, uptake rates are suboptimal in many populations and vary between screening programs, indicating a complex combination of patient factors that require elucidation to develop evidence-based strategies to increase participation. In this review, the authors summarize individual-level (sociodemographic and psychosocial) factors associated with cancer screening uptake and evidence for the effectiveness of behavioral interventions to increase uptake. The authors reflect on current trends and future directions for behavioral cancer screening research to overcome challenges and address unmet needs in reducing cancer mortality.

A global metagenomic map of urban microbiomes and antimicrobial resistance.

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.

The impact of theory-based messages on COVID-19 vaccination intentions: a structured summary of a study protocol for a randomised controlled trial.

OBJECTIVES: Uptake of vaccination against COVID-19 is key to controlling the pandemic. However, a significant proportion of people report that they do not intend to have a vaccine, often because of concerns they have about vaccine side effects or safety. This study will assess the impact of theory-based messages on COVID-19 vaccination intention, drawing on the Necessity-Concerns framework to address previously reported beliefs and concerns about COVID-19 vaccination, and assess whether hypothesised variables (illness coherence, perceived necessity and concerns) mediate change in vaccination intention. TRIAL DESIGN: Prospective, parallel two-arm, individually randomised (1:1) trial. PARTICIPANTS: Adults aged over 18 years, living in Scotland and not vaccinated for COVID-19. A quota sampling approach will be used with the aim of achieving a nationally representative sample on gender, region and ethnic group, with oversampling of individuals with no educational qualifications or with only school-level qualifications. INTERVENTION AND COMPARATOR: Intervention: Brief exposure to online text and image-based messages addressing necessity beliefs and concerns about COVID-19 vaccination. Comparator: Brief exposure to online text and image-based messages containing general information about COVID-19 and COVID-19 vaccination. MAIN OUTCOMES: Primary outcome: Self-reported intention to receive a vaccine for COVID-19 if invited, immediately post-intervention. SECONDARY OUTCOMES: Self-reported COVID-19 illness coherence, perceived necessity of a COVID-19 vaccine and concerns about a COVID-19 vaccine, immediately post-intervention. RANDOMISATION: Quasi-randomisation performed automatically by online survey software, by creating a variable derived from the number of seconds in the minute that the participant initiates the survey. Participants starting the survey at 0-14 or 30-44 seconds in the minute are allocated to the intervention and 15-29 or 45-59 seconds to the comparator. BLINDING (MASKING): Participants will not be blinded to group assignment but will not be informed of the purpose of the study until they have completed the follow-up survey. Investigators will be blinded to allocation as all procedures will be undertaken digitally and remotely without any investigator contact with participants. NUMBERS TO BE RANDOMISED (SAMPLE SIZE): A total of 1,094 will be randomised 1:1 into two groups with 547 individuals in each. TRIAL STATUS: Protocol version number 1.0, 26th February 2021. Recruitment status: Not yet recruiting, set to start April 2021 and end April 2021. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04813770 , 24th March 2021. FULL PROTOCOL: The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol.

Potential Socioeconomic and Environmental Effects of an Expanding U.S. Bioeconomy: An Assessment of Near-Commercial Cellulosic Biofuel Pathways.

This paper showcases the suitability of an environmentally extended input-output framework to provide macroeconomic analyses of an expanding bioeconomy to allow for adequate evaluation of its benefits and trade-offs. It also exemplifies the framework's applicability to provide early design stage evaluations of emerging technologies expected to contribute to a future bioeconomy. Here, it is used to compare the current United States (U.S.) bioeconomy to a hypothetical future containing additional cellulosic ethanol produced from two near-commercial pathways. We find that the substitution of gasoline with cellulosic ethanol is expected to yield socioeconomic net benefits, including job growth and value added, and a net reduction in global warming potential and nonrenewable energy use. The substitution fares comparable to or worse than that for other environmental impact categories including human toxicity and eutrophication potentials. We recommend that further technology advancement and commercialization efforts focus on reducing these unintended consequences through improved system design and innovation. The framework is seen as complementary to process-based technoeconomic and life cycle assessments as it utilizes related data to describe specific supply chains while providing analyses of individual products and portfolios thereof at an industrial scale and in the context of the U.S. economy.

Developing logic models to inform public health policy outcome evaluation: an example from tobacco control.

BACKGROUND: The evaluation of large-scale public health policy interventions often relies on observational designs where attributing causality is challenging. Logic models-visual representations of an intervention's anticipated causal pathway-facilitate the analysis of the most relevant outcomes. We aimed to develop a set of logic models that could be widely used in tobacco policy evaluation. METHODS: We developed an overarching logic model that reflected the broad categories of outcomes that would be expected following the implementation of tobacco control policies. We subsequently reviewed policy documents to identify the outcomes expected to result from the implementation of each policy and conducted a literature review of existing evaluations to identify further outcomes. The models were revised according to feedbacks from a range of stakeholders. RESULTS: The final models represented expected causal pathways for each policy. The models included short-term outcomes (such as policy awareness, compliance and social cognitive outcomes), intermediate outcomes (such as changes in smoking behaviour) and long-term outcomes (such as mortality, morbidity and health service usage). CONCLUSIONS: The use of logic models enables transparent and theory-based planning of evaluation analyses and should be encouraged in the evaluation of tobacco control policy, as well as other areas of public health.