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Background: Citation analysis is a commonly used method for appraising the impact of academic publications within a particular field of study. A gap exists in the citation analysis literature with regard to the topic of direct anterior approach (DAA) hip arthroplasty. The purpose of this study is to identify the 50 most frequently cited publications related to this topic. Methods: The Clarivate Analytics Web of Knowledge database was utilized to search for publications relating to DAA hip arthroplasty. The top 50 most cited articles that met inclusion criteria were recorded and reviewed for various metrics. Results: The top 50 publications were cited a total of 3521 times, with an average of 86.3 total citations per year between 1980 and 2019. 47 of the 50 articles identified had been published since the year 2000. Cohort designs were the most common study type. Conclusions: This analysis provides insight into factors that characterize highly cited articles on the specific topic of DAA hip arthroplasty. These factors include higher levels of evidence, recent publication, and origin in the United States. Citations of DAA hip arthroplasty papers appear to be on the rise. The curation and analysis of this set of 50 articles will provide orthopaedic surgery clinicians, researchers, and residency program directors a guide for quickly isolating influential articles on the topic of DAA hip arthroplasty. This may serve as a quick reference for clinical decision-making, foundation for further research, and curriculum on DAA hip arthroplasty.

Radon is the second-leading cause of lung cancer worldwide. Most indoor exposure occurs by diffusion of soil gas. Radon is also found in well water, natural gas, and ambient air. Pennsylvania has high indoor radon concentrations; buildings are often tested

An individual’s outlook on society can change over time and can be related to both their physical and mental health. Here, we developed an instrument to measure outlooks on the past and future in relation to the present in 413 adults ranging in age from 18 to 80 years. Exploratory and confirmatory factor analyses were conducted on independent samples and test–retest reliability was assessed in a subset of participants. Construct validity of the two past and future scales was assessed by relating them to 1) pre-existing scales measuring related constructs, and 2) beliefs and safety behaviors during the COVID-19 pandemic. The final Bright or Bleak Scale (BOBS) consists of a past and future scale, each with two factors measuring societal and personal outlooks. Brighter future societal and personal outlooks were positively associated with longer future time perspectives, while self-reporting a higher likelihood of already having contracted COVID-19 was related to bleaker past societal and personal outlooks.

Longitudinal studies of the role of community context in childhood obesity are lacking. The objective of this study was to examine associations of community socio economic deprivation (CSD) with trajectories of change in body mass index (BMI) in childhood

An increasing number of immunocompromised individuals are pursuing international travel, and a better understanding of their international travel patterns and pretravel health care is needed. We evaluated the clinical features, itineraries, and pretravel h

The 2019 novel coronavirus disease (COVID-19) has broadly impacted our daily lives. Here, we used a longitudinal approach to investigate older adults’ mood and expectations regarding aging before and during the global pandemic (Study 1). We also examined age differences in mood, expectations regarding aging, COVID-19 attitudes, and loneliness using a cross-sectional approach (Study 2). In Study 1, older adults completed a mood and expectations regarding aging survey up to 2 years prior to the pandemic and again in April, 2020 (during the pandemic). Participants also completed surveys regarding COVID-19 attitudes and loneliness. In Study 2, a United States sample of younger and older adults completed these surveys during the pandemic. Older adults’ mood and expectations regarding aging remained fairly constant, and younger adults showed lower mood and expectations regarding aging than did older adults, despite older adults showing greater concern about COVID-19. Overall, we find that some older adults seem to be resilient with respect to their mood and expectations regarding aging. These findings reveal important preliminary implications for how older adults may be impacted as a result of lifestyle changes necessary for well-being and the well-being of society.

The NAD(P)H quinone oxidoreductase (NQO1:EC 1.6.99.2) is an important biotransformation enzyme system that is also known to metabolize important novel chemotherapeutic compounds. The gene that codes for this enzyme has recently been found to be polymorphic in humans. Here, we describe the ethnic distribution of the polymorphism and note that this may have implications for anti-tumour drug development and use.

Recent research suggests that uric acid may be nephrotoxic at lower levels than previously recognized and that it may be one mechanism for lead-related nephrotoxicity. Therefore, in understanding mechanisms for lead-related nephrotoxicity, it would be of value to determine whether genetic polymorphisms that are associated with renal outcomes in lead workers and/or modify associations between lead dose and renal function are also associated with uric acid and/or modify associations between lead dose and uric acid. We analyzed data on three such genetic polymorphisms: delta-aminolevulinic acid dehydratase (ALAD), endothelial nitric oxide synthase (eNOS), and the vitamin D receptor (VDR). Mean (+/- SD) tibia, blood, and dimercaptosuccinic acid-chelatable lead levels were 37.2 +/- 40.4 microg/g bone mineral, 32.0+/- 15.0 g/dL, and 0.77+/- 0.86 microg/mg creatinine, respectively, in 798 current and former lead workers. Participants with the eNOSAsp allele had lower mean serum uric acid compared with those with the Glu/Glu genotype. Among older workers (age > or = median of 40.6 years), ALAD genotype modified associations between lead dose and uric acid levels. Higher lead dose was significantly associated with higher uric acid in workers with the ALAD1-1 genotype; associations were in the opposite direction in participants with the variant ALAD1-2 genotype. In contrast, higher tibia lead was associated with higher uric acid in those with the variant VDRB allele; however, modification was dependent on participants with the bb genotype and high tibia lead levels. We conclude that genetic polymorphisms may modify uric acid mediation of lead-related adverse renal effects. [ABSTRACT FROM AUTHOR]

Recent research suggests that both uric acid and lead may be nephrotoxic at lower levels than previously recognized. We analyzed data from 803 current and former lead workers to determine whether lead biomarkers were associated with uric acid and whether previously reported associations between lead dose and renal outcomes were altered after adjustment for uric acid. Outcomes included uric acid, blood urea nitrogen, serum creatinine, measured and calculated creatinine clearances, and urinary N-acetyl-ß-d-glucosaminidase (NAG) and retinol-binding protein. Mean (+/- SD) uric acid, tibia lead, and blood lead levels were 4.8 +/- 1.2 mg/dL, 37.2 +/- 40.4 microg/g bone mineral, and 32.0 +/- 15.0 microg/dL, respectively. None of the lead measures (tibia, blood, and dimercaptosuccinic-acid-chelatable lead) was associated with uric acid, after adjustment for age, sex, body mass index, and alcohol use. However, when we examined effect modification by age on these relations, both blood and tibia lead were significantly associated (ß = 0.0111, p < 0.01 and ß = 0.0036, p = 0.04, respectively) in participants in the oldest age tertile. These associations decreased after adjustment for blood pressure and renal function, although blood lead remained significantly associated with uric acid (ß = 0.0156, p = 0.01) when the population was restricted to the oldest tertile of workers with serum creatinine greater than the median (0.86 mg/dL). Next, in models of renal function in all workers, uric acid was significantly (p < 0.05) associated with all renal outcomes except NAG. Finally, in the oldest tertile of workers, associations between lead dose and NAG were unchanged, but fewer associations between the lead biomarkers and the clinical renal outcomes remained significant (p

The enzyme delta-aminolevulinic acid dehydratase (ALAD) , which catalyzes the second step of heme synthesis, can be inhibited by several chemicals, including lead, a potential risk factor for brain tumors, particularly meningioma. In this study we examined whether the ALAD G177C polymorphism in the gene coding for ALAD is associated with risk of intracranial tumors of the brain and nervous system. We use data from a case-control study with 782 incident brain tumor cases and 799 controls frequency matched on hospital, age, sex, race/ethnicity, and residential proximity to the hospital. Blood samples were drawn and DNA subsequently sent for genotyping for 73% of subjects. ALAD genotype was determined for 94% of these samples (355 glioma, 151 meningioma, 67 acoustic neuroma, and 505 controls) . Having one or more copy of the ALAD2 allele was associated with increased risk for meningioma [odds ratio (OR) = 1.6 ; 95% confidence interval (CI) , 1.0-2.6], with the association appearing stronger in males (OR = 3.5 ; 95% CI, 1.3-9.2) than in females (OR = 1.2 ; 95% CI, 0.7-2.2) . No increased risk associated with the ALAD2 variant was observed for glioma or acoustic neuroma. These findings suggest that the ALAD2 allele may increase genetic susceptibility to meningioma. [ABSTRACT FROM AUTHOR]

Background: There is growing concern about climate impacts on human health. However, empirical evidence is lacking regarding future projections of heat-related asthma hospitalizations. This study aimed to project excess emergency hospitalizations for heat-related asthma exacerbation in Japan., Methods: Using Japanese nationwide administrative data from 2011 to 2019, we conducted an ecological time-series quasi-Poisson regression analysis to estimate the heat-related relative risk of emergency hospitalization for asthma over a lag of 0-3 days during the warm season (June to September). Heat exposure was defined as the region-specific daily mean temperature exceeding the locally defined minimum morbidity temperature percentile (MMP). Heat-related excess hospitalizations for asthma were projected under future climate and demographic change scenarios based on Shared Socioeconomic Pathways (SSPs)., Results: We identified 75,829 emergency hospitalizations for asthma. The heat-related relative risk of hospitalization was 1.22 (95% confidence interval (CI): 1.12-1.33) at the 99th percentile temperature relative to the MMP, with the highest estimates for cases aged 0-14 years. Heat-related excess hospitalizations were projected to increase by 6.78 (95%CI: 5.84-7.67) times in 2091-2099 versus 2011-2019 along SSP5-8.5 when constant population structure was assumed. The increasing trend persisted even when the future population decline was considered (4.19 (95%CI: 3.53-4.85) times in 2091-2099 versus 2011-2019 under SSP5-8.5)., Conclusion: Future heat-related impacts on asthma exacerbation are expected to increase in Japan toward the end of this century, even when the future demographic change is considered. Our projections will contribute to resilient health systems adapting to ongoing climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Understanding geographic disparities in type 2 diabetes (T2D) requires approaches that account for communities' multidimensional nature., Methods: In an electronic health record nested case-control study, we identified 15,884 cases of new-onset T2D from 2008 to 2016, defined using encounter diagnoses, medication orders, and laboratory test results, and frequency-matched controls without T2D (79,400; 65,069 unique persons). We used finite mixture models to construct community profiles from social, natural, physical activity, and food environment measures. We estimated T2D odds ratios (OR) with 95% confidence intervals (CI) using logistic generalized estimating equation models, adjusted for sociodemographic variables. We examined associations with the profiles alone and combined them with either community type based on administrative boundaries or Census-based urban/rural status., Results: We identified four profiles in 1069 communities in central and northeastern Pennsylvania along a rural-urban gradient: "sparse rural," "developed rural," "inner suburb," and "deprived urban core." Urban areas were densely populated with high physical activity resources and food outlets; however, they also had high socioeconomic deprivation and low greenness. Compared with "developed rural," T2D onset odds were higher in "deprived urban core" (1.24, CI = 1.16-1.33) and "inner suburb" (1.10, CI = 1.04-1.17). These associations with model-based community profiles were weaker than when combined with administrative boundaries or urban/rural status., Conclusions: Our findings suggest that in urban areas, diabetogenic features overwhelm T2D-protective features. The community profiles support the construct validity of administrative-community type and urban/rural status, previously reported, to evaluate geographic disparities in T2D onset in this geography., Competing Interests: The authors declare that they have no conflicts of interest with regard to the content of this report., (Copyright © 2024 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The Environmental Epidemiology. All rights reserved.)

Improving the quality of life for people with vision impairments has been an important goal in the research and design of assistive devices for several decades. This paper seeks to further that goal by introducing a novel assistive technology platform that leverages real-time 3D spatial audio to promote safe and efficient navigation for people who are blind or visually impaired (PVI). The presented platform, EchoSee, uses modern 3D scanning technology on a mobile device to construct a live, digital 3D map of a user's environment as they move about their surroundings. Spatialized, virtual audio sources (i.e., virtual speakers) are dynamically placed within the digital 3D scan of the world, providing the navigator with a real-time 3D stereo audio "soundscape." The digital 3D map, and its resultant soundscape, are continuously updated as the user moves about their environment. The generated soundscape is played back through headphones connected to the navigator's device. This paper details (1) the underlying technical components and how they were integrated to produce the mobile application that generates a dynamic soundscape on a consumer mobile device, (2) a methodology for analyzing navigation performance with the application, (3) the design and execution of a user study investigating the effectiveness of the presented system, and (4) a discussion of the results of that study along with a proposed future study and possible improvements. Altogether, this paper presents a novel software platform aimed at assisting individuals with vision impairments to navigate and understand spaces safely, efficiently, and independently and the results of a feasibility study analyzing the viability of the approach.

Background: Integrating behavioral health services into pediatric primary care can improve access to care, especially for children marginalized by poverty and racial/ethnic minority status. In primary care, a common presenting concern is attention-deficit/hyperactivity disorder (ADHD). Services in primary care for marginalized children with ADHD typically include medication alone; therapy to improve skills and build relationships is less available. This study evaluates the effectiveness of a behavioral intervention offered through primary care for marginalized families coping with ADHD (Partnering to Achieve School Success, PASS) compared to treatment as usual (TAU)., Method: Three hundred participants will be randomly assigned to PASS or TAU. Participants include children ages 5 to 11 who have ADHD and are from economically marginalized families. PASS is a personalized, enhanced behavioral intervention that includes evidence-based behavior therapy strategies and enhancements to promote family engagement, increase caregiver distress tolerance, and provide team-based care to improve academic and behavioral functioning. TAU includes services offered by primary care providers and referral for integrated behavioral health or community mental health services. Outcomes will be assessed at mid-treatment (8 weeks after baseline), post-treatment (16 weeks), and follow-up (32 weeks) using parent- and teacher-report measures of service use, child academic, behavioral, and social functioning, parenting practices, family empowerment, and team-based care. Mixed effects models will examine between-group differences at post-treatment and follow-up. Analyses will examine the mediating role of parenting practices, family empowerment, and team-based care. Subgroup analyses will examine differential effects of intervention by child clinical characteristics and socioeconomic factors., Discussion: This study is unique in targeting a population of children with ADHD marginalized by low socioeconomic resources and examining an intervention designed to address the challenges of families coping with chronic stress related to poverty., Trial Registration: This study was registered on clinicaltrials.gov (NCT04082234) on September 5, 2019, prior to enrollment of the first participant. The current version of the protocol and IRB approval date is October 4, 2023. Results will be submitted to ClinicalTrials.gov no later than 30 days prior to the due date for the submission of the draft of the final research report to the Patient-Centered Outcomes Research Institute., (© 2024. The Author(s).)

Background: Factor (F)IXa activity has been detected in human plasma and may impact thrombotic risk. Current FIXa activity assays are complex and cumbersome., Objectives: To develop a reproducible enzyme-linked immunosorbent assay (ELISA) using a novel monoclonal antibody that detects total FIXa in human plasma., Methods: A monoclonal antibody was raised against the new N-terminus exposed upon activation of FIX to FIXa by cleavage after R226. This antibody is specific for FIXa protease and does not recognize FIX zymogen or FIXα. The antibody was used to develop a FIXa-specific ELISA capable of quantifying total FIXa (free FIXa and FIXa-antithrombin complex) in human plasma. Total FIXa quantified using the ELISA was compared to that of FIXa-antithrombin quantified using modifications of a previously described ELISA., Results: The FIXa-specific ELISA was reproducible and quantified total FIXa in human plasma. Total FIXa levels correlated with FIXa-antithrombin levels., Conclusion: A monoclonal antibody was developed that specifically detects human FIXa protease. A FIXa-specific ELISA using the new antibody is capable of reproducibly measuring total FIXa in human plasma (both free FIXa and FIXa-antithrombin). This assay should facilitate the evaluation of total FIXa levels in a variety of clinical circumstances., (© 2024 The Author(s).)

Background: Little is known about the effectiveness and cost-effectiveness of train-the-trainer implementation strategies in supporting mental health evidence-based practices in schools, and about the optimal level of support needed for TT strategies., Methods: The current study is part of a larger type 2 hybrid cluster randomized controlled trial. It compares two train-the-trainer strategies, Train-the-Trainer (TT) and Train-the-Trainer plus ongoing consultation for trainers (TT +) on the delivery of a group cognitive behavioral treatment protocol for anxiety disorders. Participants were 33 therapists, 29 supervisors, and 125 students who were at risk for anxiety disorders from 22 urban schools. Implementation outcomes were implementation fidelity and treatment dosage. Student outcomes were child- and parent-reported symptoms of anxiety, child-reported symptoms of depression, and teacher-reported academic engagement. We estimated the cost of implementing the intervention in each condition and examined the probability that a support strategy for supervisors (TT vs TT +) is a good value for varying values of willingness to pay., Results: Therapists in the TT and TT + conditions obtained similarly high implementation fidelity and students in the conditions received similar treatment dosages. A mixed effects modeling approach for student outcomes revealed time effects for symptoms of anxiety and depression reported by students, and emotional disaffection reported by teachers. There were no condition or condition × times effects. For both conditions, the time effects indicated an improvement from pre-treatment to post-treatment in symptoms of anxiety and depression and academic emotional engagement. The average cost of therapist, supervisor, and consultant time required to implement the intervention in each condition was $1002 for TT and $1431 for TT + (p = 0.01). There was a greater than 80% chance that TT was a good value compared to TT + for all values of willingness to pay per one-point improvement in anxiety scores., Conclusions: A TT implementation approach consisting of a thorough initial training workshop for therapists and supervisors as well as ongoing supervision for therapists resulted in adequate levels of fidelity and student outcomes but at a lower cost, compared to the TT + condition that also included ongoing external expert consultation for supervisors., Trial Registration: ClinicalTrials.gov identifier: NCT02651402., (© 2024. The Author(s).)

Background: Exposure to particulate matter ≤2.5 μm in diameter (PM 2.5 ) and ozone (O 3 ) has been linked to numerous harmful health outcomes. While epidemiologic evidence has suggested a positive association with type 2 diabetes (T2D), there is heterogeneity in findings. We evaluated exposures to PM 2.5 and O 3 across three large samples in the US using a harmonized approach for exposure assignment and covariate adjustment., Methods: Data were obtained from the Veterans Administration Diabetes Risk (VADR) cohort (electronic health records [EHRs]), the Reasons for Geographic and Racial Disparities in Stroke (REGARDS) cohort (primary data collection), and the Geisinger health system (EHRs), and reflect the years 2003-2016 (REGARDS) and 2008-2016 (VADR and Geisinger). New onset T2D was ascertained using EHR information on medication orders, laboratory results, and T2D diagnoses (VADR and Geisinger) or report of T2D medication or diagnosis and/or elevated blood glucose levels (REGARDS). Exposure was assigned using pollutant annual averages from the Downscaler model. Models stratified by community type (higher density urban, lower density urban, suburban/small town, or rural census tracts) evaluated likelihood of new onset T2D in each study sample in single- and two-pollutant models of PM 2.5 and O 3 ., Results: In two pollutant models, associations of PM 2.5 , and new onset T2D were null in the REGARDS cohort except for in suburban/small town community types in models that also adjusted for NSEE, with an odds ratio (95% CI) of 1.51 (1.01, 2.25) per 5 μg/m 3 of PM 2.5 . Results in the Geisinger sample were null. VADR sample results evidenced nonlinear associations for both pollutants; the shape of the association was dependent on community type., Conclusions: Associations between PM 2.5 , O 3 and new onset T2D differed across three large study samples in the US. None of the results from any of the three study populations found strong and clear positive associations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Cartilage acidic protein-1 (CRTAC1) is produced by several cell types, including Type 2 alveolar epithelial (T2AE) cells that are targeted by SARS-CoV2. Plasma CRTAC1 is known based on proteomic surveys to be low in patients with severe COVID-19. Using an ELISA, we found that patients treated for COVID-19 in an ICU almost uniformly had plasma concentrations of CRTAC1 below those of healthy controls. Magnitude of decrease in CRTAC1 distinguished COVID-19 from other causes of acute respiratory decompensation and correlated with established metrics of COVID-19 severity. CRTAC1 concentrations below those of controls were found in some patients a year after hospitalization with COVID-19, long COVID after less severe COVID-19, or chronic obstructive pulmonary disease. Decreases in CRTAC1 in severe COVID-19 correlated (r = 0.37, p = 0.0001) with decreases in CFP (properdin), which interacts with CRTAC1. Thus, decreases of CRTAC1 associated with severe COVID-19 may result from loss of production by T2AE cells or co-depletion with CFP. Determination of significance of and reasons behind decreased CRTAC1 concentration in a subset of patients with long COVID will require analysis of roles of preexisting lung disease, impact of prior acute COVID-19, age, and other confounding variables in a larger number of patients., (© 2023 The Authors. Physiological Reports published by Wiley Periodicals LLC on behalf of The Physiological Society and the American Physiological Society.)

Multidrug-resistant (MDR) Pseudomonas aeruginosa has been declared a serious threat by the United States Centers for Disease Control and Prevention. Here, we used whole genome sequencing (WGS) to investigate recurrent P. aeruginosa bloodstream infections in a severely immunocompromised patient. The infections demonstrated unusual, progressive increases in resistance to beta lactam antibiotics in the setting of active treatment with appropriate, guideline-directed agents. WGS followed by comparative genomic analysis of isolates collected over 44 days demonstrated in host evolution of a single P. aeruginosa isolate characterized by stepwise acquisition of two de-novo genetic resistance mechanisms over the course of treatment. We found a novel deletion affecting the ampC repressor ampD and neighboring gene ampE , which associated with initial cefepime treatment failure. This was followed by acquisition of a porin nonsense mutation, OprD , associated with resistance to carbapenems. This study highlights the potential for in-host evolution of P. aeruginosa during bloodstream infections in severely immunocompromised patients despite appropriate antimicrobial therapy. In addition, it demonstrates the utility of WGS for understanding unusual resistance patterns in the clinical context., Competing Interests: Author SM was employed by the company Illumina, Inc, and by the company Delve Bio, Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Spottiswoode, Hao, Sanchez-Guerrero, Detweiler, Mekonen, Neff, Macmillan, Schwartz, Engel, DeRisi, Miller and Langelier.)

Competing Interests: Dr Haemel reports serving as a consultant to CSL Behring and Guidepoint.

Competing Interests: Dr Haemel reports serving as a consultant to CSL Behring and Guidepoint. Authors Gutierrez, Jacobson, Ghatnekar, Virji, Schwartz, Gensler, and Frangos have no conflicts of interest to declare.

Introduction: Inequitable access to leisure-time physical activity (LTPA) resources may explain geographic disparities in type 2 diabetes (T2D). We evaluated whether the neighborhood socioeconomic environment (NSEE) affects T2D through the LTPA environment., Research Design and Methods: We conducted analyses in three study samples: the national Veterans Administration Diabetes Risk (VADR) cohort comprising electronic health records (EHR) of 4.1 million T2D-free veterans, the national prospective cohort REasons for Geographic and Racial Differences in Stroke (REGARDS) (11 208 T2D free), and a case-control study of Geisinger EHR in Pennsylvania (15 888 T2D cases). New-onset T2D was defined using diagnoses, laboratory and medication data. We harmonized neighborhood-level variables, including exposure, confounders, and effect modifiers. We measured NSEE with a summary index of six census tract indicators. The LTPA environment was measured by physical activity (PA) facility (gyms and other commercial facilities) density within street network buffers and population-weighted distance to parks. We estimated natural direct and indirect effects for each mediator stratified by community type., Results: The magnitudes of the indirect effects were generally small, and the direction of the indirect effects differed by community type and study sample. The most consistent findings were for mediation via PA facility density in rural communities, where we observed positive indirect effects (differences in T2D incidence rates (95% CI) comparing the highest versus lowest quartiles of NSEE, multiplied by 100) of 1.53 (0.25, 3.05) in REGARDS and 0.0066 (0.0038, 0.0099) in VADR. No mediation was evident in Geisinger., Conclusions: PA facility density and distance to parks did not substantially mediate the relation between NSEE and T2D. Our heterogeneous results suggest that approaches to reduce T2D through changes to the LTPA environment require local tailoring., Competing Interests: Competing interests: DLL received investigator-initiated research support from Amgen, Inc for work unrelated to this manuscript. All other authors declare that they have no conflicts of interest., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

The capacity of three-dimensional (3D) range geometry acquisition methods to capture high-precision scans at high frame rates increases every year. These improvements have influenced a broadening range of disciplines to implement 3D range geometry capture systems, including telepresence, medicine, the visual arts, and many others. However, its increased popularity, precision, and capture rates have caused mounting pressure on the storage and transmission of 3D range geometry, thus straining their capacities. Compression techniques seek to alleviate this pressure by offering reduced file sizes, while maintaining the levels of precision needed for particular applications. Several such compression methods use sinusoidal modulation approaches to encode floating-point 3D data into conventional 2D red, green, and blue (RGB) images. In some applications, such as telepresence, high precision may only be required in a particular region within a depth scan, thus allowing less important data to be compressed more aggressively. This paper proposes a feature-driven compression method that provides a way to encode regions of interest at higher levels of precision while encoding the remaining data less precisely to reduce file sizes. This method supports both lossless and lossy compression, enabling even greater file-size savings. For example, in the case of a depth scan of a bust, an algorithmically extracted bounding box of the face was used to create a foveated encoding distribution so that the facial region was encoded at higher precisions. When using JPEG 80, the RMS reconstruction error of this novel, to the best of our knowledge, encoding was 0.56 mm in the region of interest, compared to a globally fixed higher precision encoding where the error was 0.54 mm in the same region. However, the proposed encoding achieved a 26% reduction in overall compressed file size compared to the fixed, higher-precision encoding.

Variation in the land use environment (LUE) impacts the continuum of walkability to car dependency, which has been shown to have effects on health outcomes. Existing objective measures of the LUE do not consider whether the measurement of the construct varies across different types of communities along the rural/urban spectrum. To help meet the goals of the Diabetes Location, Environmental Attributes, and Disparities (LEAD) Network, we developed a national, census tract-level LUE measure which evaluates the road network and land development. We tested for measurement invariance by LEAD community type (higher density urban, lower density urban, suburban/small town, and rural) using multiple group confirmatory factor analysis. We determined that metric invariance does not exist; thus, measurement of the LUE does vary across community type with average block length, average block size, and percent developed land driving most shared variability in rural tracts and with intersection density, street connectivity, household density, and commercial establishment density driving most shared variability in higher density urban tracts. As a result, epidemiologic studies need to consider community type when assessing the LUE to minimize place-based confounding., Competing Interests: The authors declare no conflicts of interest relevant to this study., (© 2022. The Authors. GeoHealth published by Wiley Periodicals LLC on behalf of American Geophysical Union.)

Evaluation of geographic disparities in type 2 diabetes (T2D) onset requires multidimensional approaches at a relevant spatial scale to characterize community types and features that could influence this health outcome. Using Geisinger electronic health records (2008-2016), we conducted a nested case-control study of new onset T2D in a 37-county area of Pennsylvania. The study included 15,888 incident T2D cases and 79,435 controls without diabetes, frequency-matched 1:5 on age, sex, and year of diagnosis or encounter. We characterized patients' residential census tracts by four dimensions of social determinants of health (SDOH) and into a 7-category SDOH census tract typology previously generated for the entire United States by dimension reduction techniques. Finally, because the SDOH census tract typology classified 83% of the study region's census tracts into two heterogeneous categories, termed rural affordable-like and suburban affluent-like, to further delineate geographies relevant to T2D, we subdivided these two typology categories by administrative community types (U.S. Census Bureau minor civil divisions of township, borough, city). We used generalized estimating equations to examine associations of 1) four SDOH indexes, 2) SDOH census tract typology, and 3) modified typology, with odds of new onset T2D, controlling for individual-level confounding variables. Two SDOH dimensions, higher socioeconomic advantage and higher mobility (tracts with fewer seniors and disabled adults) were independently associated with lower odds of T2D. Compared to rural affordable-like as the reference group, residence in tracts categorized as extreme poverty (odds ratio [95% confidence interval] = 1.11 [1.02, 1.21]) or multilingual working (1.07 [1.03, 1.23]) were associated with higher odds of new onset T2D. Suburban affluent-like was associated with lower odds of T2D (0.92 [0.87, 0.97]). With the modified typology, the strongest association (1.37 [1.15, 1.63]) was observed in cities in the suburban affluent-like category (vs. rural affordable-like-township), followed by cities in the rural affordable-like category (1.20 [1.05, 1.36]). We conclude that in evaluating geographic disparities in T2D onset, it is beneficial to conduct simultaneous evaluation of SDOH in multiple dimensions. Associations with the modified typology showed the importance of incorporating governmentally, behaviorally, and experientially relevant community definitions when evaluating geographic health disparities., Competing Interests: The authors have declared that no competing interests exist.

Climate change is a worsening global crisis that will continue negatively impacting population health and well-being unless adaptation and mitigation interventions are rapidly implemented. Climate change-related cardiovascular disease is mediated by air pollution, increased ambient temperatures, vector-borne disease and mental health disorders. Climate change-related cardiovascular disease can be modulated by climate change adaptation; however, this process could result in significant health inequity because persons and populations of lower socioeconomic status have fewer adaptation options. Clear scientific evidence for climate change and its impact on human health have not yet resulted in the national and international impetus and policies necessary to slow climate change. As respected members of society who regularly communicate scientific evidence to patients, clinicians are well-positioned to advocate on the importance of addressing climate change. This narrative review summarizes the links between climate change and cardiovascular health, proposes actionable items clinicians and other healthcare providers can execute both in their personal life and as an advocate of climate policies, and encourages communication of the health impacts of climate change when counseling patients. Our aim is to inspire the reader to invest more time in communicating the most crucial public health issue of the 21st century to their patients., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Authors. Published by Elsevier B.V.)

Background: Unconventional natural gas development (UNGD) introduces physical and psychosocial hazards into communities, which could contribute to psychosocial stress in adolescents and an increased risk of internalizing disorders, common and impactful health outcomes., Objectives: To evaluate associations between a 180-day composite UNGD activity metric and new onset of internalizing disorders, overall and separately for anxiety and depressive disorders, and effect modification by sex., Methods: We used a nested case-control design from 2008 to 2016 in 38 Pennsylvania counties using electronic health records from adolescent Geisinger subjects. Cases were defined by at least two diagnoses or medication orders indicating new onset of an internalizing disorder, and controls frequency-matched 4:1 on age, sex, and year. To evaluate associations, we used generalized estimating equations, with logit link, robust standard errors, and an exchangeable correlation structure within community., Results: We identified 7,974 adolescents (65.9% female, mean age 15.0 years) with new onset internalizing disorders. There were no associations when we used data from the entire study period. When restricted to years with higher UNGD activity (2010-2016), comparing the highest to lowest quartile, UNGD activity was associated (odds ratio [95% confidence level]) with new onset internalizing disorders (1.15 [1.06, 1.25]). Associations were slightly stronger for depressive disorders. Associations were only present in females (p = 0.009)., Discussion: This is the first epidemiologic study of UNGD in relation to adolescent mental health, an important health outcome in a potentially susceptible group to the environmental and community impacts of UNGD. UNGD activity was associated with new onset internalizing disorders in females in this large sample in an area of active UNGD., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Introduction: Two studies in Pennsylvania aimed to determine whether community type and community socioeconomic deprivation (CSD) 1) modified associations between type 2 diabetes (hereinafter, diabetes) and COVID-19 hospitalization outcomes, and 2) influenced health care utilization among individuals with diabetes during the COVID-19 pandemic., Methods: The hospitalization study evaluated a retrospective cohort of patients hospitalized with COVID-19 through 2020 for COVID-19 outcomes: death, intensive care unit (ICU) admission, mechanical ventilation, elevated D-dimer, and elevated troponin level. We used adjusted logistic regression models, adding interaction terms to evaluate effect modification by community type (township, borough, or city census tract) and CSD. The utilization study included patients with diabetes and a clinical encounter between 2017 and 2020. Autoregressive integrated moving average time-series models evaluated changes in weekly rates of emergency department and outpatient visits, hemoglobin A 1c (HbA 1c ) laboratory tests, and antihyperglycemic medication orders from 2018 to 2020., Results: In the hospitalization study, of 2,751 patients hospitalized for COVID-19, 1,020 had diabetes, which was associated with ICU admission and elevated troponin. Associations did not differ by community type or CSD. In the utilization study, among 93,401 patients with diabetes, utilization measures decreased in March 2020. Utilization increased in July, and then began to stabilize or decline through the end of 2020. Changes in HbA 1c tests and medication order trends during the pandemic differed by community type and CSD., Conclusion: Diabetes was associated with selected outcomes among individuals hospitalized for COVID-19, but these did not differ by community features. Utilization trajectories among individuals with diabetes during the pandemic were influenced by community type and CSD and could be used to identify individuals at risk of gaps in diabetes care.

Introduction: Geographic disparities in diabetes burden exist throughout the United States (US), with many risk factors for diabetes clustering at a community or neighborhood level. We hypothesized that the likelihood of new onset type 2 diabetes (T2D) would differ by community type in three large study samples covering the US., Research Design and Methods: We evaluated the likelihood of new onset T2D by a census tract-level measure of community type, a modification of RUCA designations (higher density urban, lower density urban, suburban/small town, and rural) in three longitudinal US study samples (REGARDS [REasons for Geographic and Racial Differences in Stroke] cohort, VADR [Veterans Affairs Diabetes Risk] cohort, Geisinger electronic health records) representing the CDC Diabetes LEAD (Location, Environmental Attributes, and Disparities) Network., Results: In the REGARDS sample, residing in higher density urban community types was associated with the lowest odds of new onset T2D (OR [95% CI]: 0.80 [0.66, 0.97]) compared to rural community types; in the Geisinger sample, residing in higher density urban community types was associated with the highest odds of new onset T2D (OR [95% CI]: 1.20 [1.06, 1.35]) compared to rural community types. In the VADR sample, suburban/small town community types had the lowest hazard ratios of new onset T2D (HR [95% CI]: 0.99 [0.98, 1.00]). However, in a regional stratified analysis of the VADR sample, the likelihood of new onset T2D was consistent with findings in the REGARDS and Geisinger samples, with highest likelihood of T2D in the rural South and in the higher density urban communities of the Northeast and West regions; likelihood of T2D did not differ by community type in the Midwest., Conclusions: The likelihood of new onset T2D by community type varied by region of the US. In the South, the likelihood of new onset T2D was higher among those residing in rural communities., Competing Interests: Authors have none to disclose., (© 2022 The Authors.)

Objective: We examined whether relative availability of fast-food restaurants and supermarkets mediates the association between worse neighborhood socioeconomic conditions and risk of developing type 2 diabetes (T2D)., Research Design and Methods: As part of the Diabetes Location, Environmental Attributes, and Disparities Network, three academic institutions used harmonized environmental data sources and analytic methods in three distinct study samples: 1) the Veterans Administration Diabetes Risk (VADR) cohort, a national administrative cohort of 4.1 million diabetes-free veterans developed using electronic health records (EHRs); 2) Reasons for Geographic and Racial Differences in Stroke (REGARDS), a longitudinal, epidemiologic cohort with Stroke Belt region oversampling (N = 11,208); and 3) Geisinger/Johns Hopkins University (G/JHU), an EHR-based, nested case-control study of 15,888 patients with new-onset T2D and of matched control participants in Pennsylvania. A census tract-level measure of neighborhood socioeconomic environment (NSEE) was developed as a community type-specific z-score sum. Baseline food-environment mediators included percentages of 1) fast-food restaurants and 2) food retail establishments that are supermarkets. Natural direct and indirect mediating effects were modeled; results were stratified across four community types: higher-density urban, lower-density urban, suburban/small town, and rural., Results: Across studies, worse NSEE was associated with higher T2D risk. In VADR, relative availability of fast-food restaurants and supermarkets was positively and negatively associated with T2D, respectively, whereas associations in REGARDS and G/JHU geographies were mixed. Mediation results suggested that little to none of the NSEE-diabetes associations were mediated through food-environment pathways., Conclusions: Worse neighborhood socioeconomic conditions were associated with higher T2D risk, yet associations are likely not mediated through food-environment pathways., (© 2022 by the American Diabetes Association.)

The use of three-dimensional (3D) range geometry is expanding across a variety of disciplines ranging from medicine to the visual arts. A large amount of information is available in 3D range geometry, causing some applications to be limited in their ability to effectively store or transmit captured data. To help alleviate this constraint, a variety of 3D range data compression techniques have been proposed. One method, multiwavelength depth (MWD) encoding, smoothly encodes 3D range geometry into the three color channels of a 2D RGB image. To the best of our knowledge, we present a novel compression enhancement to further reduce file sizes that employs image downsampling, MWD encoding, and lossless (e.g., PNG) or lossy (e.g., JPEG) compression. Image upsampling is used to return downsampled encodings to their original resolution from which the 3D information is then decoded. The proposed method is robust to various scales of downsampling and levels of lossy compression. For example, when this method was applied with 50% downsampling and JPEG 85 to an encoding of a 3D face scan, a compression ratio of 68.85:1 versus the raw data was achieved with a global RMS reconstruction accuracy of 98.77%. Experimental results demonstrate that the proposed method can provide substantial file size savings at minimal reduction in overall reconstruction accuracy.

Existing classifications of community type do not differentiate urban cores from surrounding non-rural areas, an important distinction for analyses of community features and their impact on health. Inappropriately classified community types can introduce serious methodologic flaws in epidemiologic studies and invalid inferences from findings. To address this, we evaluate a modification of the United States Department of Agriculture's Rural Urban Commuting Area codes at the census tract, propose a four-level categorization of community type, and compare this with existing classifications for epidemiologic analyses. Compared to existing classifications, our method resulted in clearer geographic delineations of community types within urban areas.

Background: Little is known about risk factors for early (e.g., erythema migrans) and disseminated Lyme disease manifestations, such as arthritis, neurological complications, and carditis. No study has used both diagnoses and free text to classify Lyme disease by disease stage and manifestation., Methods: We identified Lyme disease cases in 2012-2016 in the electronic health record (EHR) of a large, integrated health system in Pennsylvania. We developed a rule-based text-matching algorithm using regular expressions to extract clinical data from free text. Lyme disease cases were then classified by stage and manifestation using data from both diagnoses and free text. Among cases classified by stage, we evaluated individual, community, and health care variables as predictors of disseminated stage (vs. early) disease using Poisson regression models with robust errors. Final models adjusted for sociodemographic factors, receipt of Medical Assistance (i.e., Medicaid, a proxy for low socioeconomic status), primary care contact, setting of diagnosis, season of diagnosis, and urban/rural status., Results: Among 7310 cases of Lyme disease, we classified 62% by stage. Overall, 23% were classified using both diagnoses and text, 26% were classified using diagnoses only, and 13% were classified using text only. Among the staged diagnoses (n = 4530), 30% were disseminated stage (762 arthritis, 426 neurological manifestations, 76 carditis, 95 secondary erythema migrans, and 76 other manifestations). In adjusted models, we found that persons on Medical Assistance at least 50% of time under observation, compared to never users, had a higher risk (risk ratio [95% confidence interval]) of disseminated Lyme disease (1.20 [1.05, 1.37]). Primary care contact (0.59 [0.54, 0.64]) and diagnosis in the urgent care (0.22 [0.17, 0.29]), compared to the outpatient setting, were associated with lower risk of disseminated Lyme disease., Conclusions: The associations between insurance payor, primary care status, and diagnostic setting with disseminated Lyme disease suggest that lower socioeconomic status and less health care access could be linked with disseminated stage Lyme disease. Intervening on these factors could reduce the individual and health care burden of disseminated Lyme disease. Our findings demonstrate the value of both diagnostic and narrative text data to identify Lyme disease manifestations in the EHR., (© 2021. The Author(s).)

Due to the COVID-19 pandemic, most graduate medical education (GME) training programs conducted virtual interviews for prospective trainees during the 2020-2021 application cycle. Many internal medicine (IM) subspecialty fellowship programs hosted virtual interviews for the first time with little published data to guide best practices.To evaluate how IM subspecialty fellowship applicants perceived the virtual interview day experience.We designed a 38-item questionnaire that was sent via email to applicants in eight IM subspecialty programs at a single tertiary academic medical center (University of California, San Francisco) from September-November, 2020.Seventy-five applicants completed the survey (75/244, 30.7%), including applicants from all eight fellowship programs. Most survey respondents agreed that the length of the virtual interview day (mean = 6.4 hours) was long enough to gather the information they needed (n = 65, 86.7%) and short enough to prevent fatigue (n = 55, 73.3%). Almost all survey respondents agreed that they could adequately assess the clinical experience (n = 71, 97.3%), research opportunities (n = 72, 98.6%), and program culture (n = 68, 93.2%). Of the respondents who attended a virtual educational conference, most agreed it helped to provide a sense of the program's educational culture (n = 20, 66.7%). Areas for improvement were identified, with some survey respondents reporting that the virtual interview day was too long (n = 11) or that they would have preferred to meet more fellows (n = 10).Survey respondents indicated that the virtual interview was an adequate format to learn about fellowship programs. These findings can inform future virtual interviews for GME training programs.

Department chairs and division chiefs at research-intensive academic medical centers often find mentoring clinician educators challenging. These faculty constitute the majority of academic physicians. Supporting excellent clinician educators is key to ensuring high-quality patient care and developing tomorrow's physicians. Little has been written for leaders on strategies to advance academic clinician educators' career success. We present a framework to guide chairs, chiefs, and mentors seeking to address clinician educator retention and satisfaction in academic medical centers., (© 2021. This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.)

Background: While there are known individual-level risk factors for kidney disease at time of type 2 diabetes diagnosis, little is known regarding the role of community context. We evaluated the association of community socioeconomic deprivation (CSD) and community type with estimated glomerular filtration rate (eGFR) when type 2 diabetes is diagnosed., Methods: This was a retrospective cohort study of 13,144 adults with newly diagnosed type 2 diabetes in Pennsylvania. The outcome was the closest eGFR measurement within one year prior to and two weeks after type 2 diabetes diagnosis, calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-Epi) equation. We used adjusted multinomial regression models to estimate associations of CSD (quartile 1, least deprivation) and community type (township, borough, city) with eGFR and used adjusted generalized estimating equation models to evaluate whether community features were associated with the absence of diabetes screening in the years prior to type 2 diabetes diagnosis., Results: Of the participants, 1279 (9.7%) had hyperfiltration and 1377 (10.5%) had reduced eGFR. Women were less likely to have hyperfiltration and more likely to have reduced eGFR. Black (versus White) race was positively associated with hyperfiltration when the eGFR calculation was corrected for race but inversely associated without the correction. Medical Assistance (ever versus never) was positively associated with reduced eGFR. Higher CSD and living in a city were each positively associated (odds ratio [95% confidence interval]) with reduced eGFR (CSD quartiles 3 and 4 versus quartile 1, 1.23 [1.04, 1.46], 1.32 [1.11, 1.58], respectively; city versus township, 1.38 [1.15, 1.65]). These features were also positively associated with the absence of a type 2 diabetes screening measure., Conclusions: In a population-based sample, more than twenty percent had hyperfiltration or reduced eGFR at time of type 2 diabetes diagnosis. Individual- and community-level factors were associated with these outcomes., Competing Interests: The authors have no conflicts of interest to report. This publication was made possible by Cooperative Agreement Number DP006296 funded by the US 10.13039/100000030Centers for Disease Control and Prevention, Division of Diabetes Translation. The study sponsor did not have a role in collection, analysis, interpretation of data, writing the report, or in the decision to submit the article for publication., (© 2021 The Authors.)

Neighborhood greenness has been linked to better cardiovascular health, but little is known about its association with biomarkers related to cardiovascular risk. Adverse neighborhood conditions, such as disorder and socioeconomic disadvantage, are associated with higher cardiovascular biomarker levels, but these relationships may differ in neighborhoods with more greenness. This study evaluated cross-sectional associations of validated measures of neighborhood greenness, disorder, and socioeconomic disadvantage with cardiovascular biomarkers in middle-aged and older adults living in Baltimore City. The sample included 500 adults, aged 57-79 years, enrolled in the Baltimore Memory Study and living in Baltimore City during 2009-2010. Multi-level log-gamma regressions examined associations between the three neighborhood characteristics and seven cardiovascular biomarkers. Models additionally evaluated the effect modification by neighborhood greenness on associations of neighborhood disorder and socioeconomic disadvantage with the biomarkers. Adjusting for covariates and neighborhood greenness, greater neighborhood disorder was associated with higher C-reactive protein (exp β = 1.21, SE = 0.11, p = 0.035) and serum amyloid A (exp β = 1.28, SE = 0.12, p = 0.008), while greater neighborhood socioeconomic disadvantage was associated with higher tumor necrosis factor alpha (exp β = 1.24, SE = 0.12, p = 0.019). Higher neighborhood greenness was associated with lower soluble vascular cell adhesion molecule-1, accounting for disorder (exp β = 0.70, SE = 0.10, p = 0.010) and socioeconomic disadvantage (exp β = 0.73, SE = 0.10, p = 0.025). There was no evidence of effect modification among neighborhood characteristics. The findings suggest that neighborhood effects on cardiovascular health may be mediated through cardiovascular biomarker levels, and that socioeconomic disadvantage, disorder, and greenness may each be important features of neighborhoods.

We performed RNA-seq and high-resolution mass spectrometry on 128 blood samples from COVID-19-positive and COVID-19-negative patients with diverse disease severities and outcomes. Quantified transcripts, proteins, metabolites, and lipids were associated with clinical outcomes in a curated relational database, uniquely enabling systems analysis and cross-ome correlations to molecules and patient prognoses. We mapped 219 molecular features with high significance to COVID-19 status and severity, many of which were involved in complement activation, dysregulated lipid transport, and neutrophil activation. We identified sets of covarying molecules, e.g., protein gelsolin and metabolite citrate or plasmalogens and apolipoproteins, offering pathophysiological insights and therapeutic suggestions. The observed dysregulation of platelet function, blood coagulation, acute phase response, and endotheliopathy further illuminated the unique COVID-19 phenotype. We present a web-based tool (covid-omics.app) enabling interactive exploration of our compendium and illustrate its utility through a machine learning approach for prediction of COVID-19 severity., Competing Interests: Declaration of Interests The authors declare no competing interests., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Greenness may impact blood pressure (BP), though evidence is limited among individuals with type 2 diabetes (T2D), for whom BP management is critical. We evaluated associations of residential greenness with BP among individuals with T2D in geographically diverse communities in Pennsylvania. To address variation in greenness type, we evaluated modification of associations by percent forest. We obtained systolic (SBP) and diastolic (DBP) BP measurements from medical records of 9593 individuals following diabetes diagnosis. Proximate greenness was estimated within 1250-m buffers surrounding individuals' residences using the normalized difference vegetation index (NDVI) prior to blood pressure measurement. Percent forest was calculated using the U.S. National Land Cover Database. Linear mixed models with robust standard errors accounted for spatial clustering; models were stratified by community type (townships/boroughs/cities). In townships, the greenest communities, an interquartile range increase in NDVI was associated with reductions in SBP of 0.87 mmHg (95% CI: -1.43, -0.30) and in DBP of 0.41 mmHg (95% CI: -0.78, -0.05). No significant associations were observed in boroughs or cities. Evidence for modification by percent forest was weak. Findings suggest a threshold effect whereby high greenness may be necessary to influence BP in this population and support a slight beneficial impact of greenness on cardiovascular disease risk.

Objectives: To evaluate associations of community types and features with new onset type 2 diabetes in diverse communities. Understanding the location and scale of geographic disparities can lead to community-level interventions., Design: Nested case-control study within the open dynamic cohort of health system patients., Setting: Large, integrated health system in 37 counties in central and northeastern Pennsylvania, USA., Participants and Analysis: We used electronic health records to identify persons with new-onset type 2 diabetes from 2008 to 2016 (n=15 888). Persons with diabetes were age, sex and year matched (1:5) to persons without diabetes (n=79 435). We used generalised estimating equations to control for individual-level confounding variables, accounting for clustering of persons within communities. Communities were defined as (1) townships, boroughs and city census tracts; (2) urbanised area (large metro), urban cluster (small cities and towns) and rural; (3) combination of the first two; and (4) county. Community socioeconomic deprivation and greenness were evaluated alone and in models stratified by community types., Results: Borough and city census tract residence (vs townships) were associated (OR (95% CI)) with higher odds of type 2 diabetes (1.10 (1.04 to 1.16) and 1.34 (1.25 to 1.44), respectively). Urbanised areas (vs rural) also had increased odds of type 2 diabetes (1.14 (1.08 to 1.21)). In the combined definition, the strongest associations (vs townships in rural areas) were city census tracts in urban clusters (1.41 (1.22 to 1.62)) and city census tracts in urbanised areas (1.33 (1.22 to 1.45)). Higher community socioeconomic deprivation and lower greenness were each associated with increased odds., Conclusions: Urban residence was associated with higher odds of type 2 diabetes than for other areas. Higher community socioeconomic deprivation in city census tracts and lower greenness in all community types were also associated with type 2 diabetes., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Growing literature linking unconventional natural gas development (UNGD) to adverse health has implicated air pollution and stress pathways. Persons with heart failure (HF) are susceptible to these stressors., Objectives: This study sought to evaluate associations between UNGD activity and hospitalization among HF patients, stratified by both ejection fraction (EF) status (reduced [HFrEF], preserved [HFpEF], not classifiable) and HF severity., Methods: We evaluated the odds of hospitalization among patients with HF seen at Geisinger from 2008 to 2015 using electronic health records. We assigned metrics of UNGD activity by phase (pad preparation, drilling, stimulation, and production) 30 days before hospitalization or a frequency-matched control selection date. We assigned phenotype status using a validated algorithm., Results: We identified 9,054 patients with HF with 5,839 hospitalizations (mean age 71.1 ± 12.7 years; 47.7% female). Comparing 4th to 1st quartiles, adjusted odds ratios (95% confidence interval) for hospitalization were 1.70 (1.35 to 2.13), 0.97 (0.75 to 1.27), 1.80 (1.35 to 2.40), and 1.62 (1.07 to 2.45) for pad preparation, drilling, stimulation, and production metrics, respectively. We did not find effect modification by HFrEF or HFpEF status. Associations of most UNGD metrics with hospitalization were stronger among those with more severe HF at baseline., Conclusions: Three of 4 phases of UNGD activity were associated with hospitalization for HF in a large sample of patients with HF in an area of active UNGD, with similar findings by HFrEF versus HFpEF status. Older patients with HF seem particularly vulnerable to adverse health impacts from UNGD activity., Competing Interests: Author Disclosures This research was supported by funding from the National Institute of Environmental Health Sciences (NIEHS) Training Grant No. 5T32ES007141-32 to Dr McAlexander and NIEHS Grant ES023675-01 (Principal Investigator: Dr Schwartz). The authors have reported that they have no relationships relevant to the contents of this paper to disclose, (Copyright © 2020 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)