The Area Deprivation Index (ADI) can show where areas of deprivation and affluence exist within a community. The ADI is calculated with 17 indicators from the American Community Survey (ACS) having been well-studied in the peer-reviewed literature since 2003, and used for 20 years by the Health Resources and Services Administration (HRSA). High levels of deprivation have been linked to health outcomes such as 30-day hospital readmission rates, cardiovascular disease deaths, cervical cancer incidence, cancer deaths, and all-cause mortality. The 17 indicators from the ADI encompass income, education, employment, and housing conditions at the Census Block Group level.The ADI is available on BigQuery for release years 2018-2020 and is reported as a percentile that is 0-100% with 50% indicating a "middle of the nation" percentile. Data is provided at the county, ZIP, and Census Block Group levels. Neighborhood and racial disparities occur when some neighborhoods have high ADI scores and others have low scores. A low ADI score indicates affluence or prosperity. A high ADI score is indicative of high levels of deprivation. Raw ADI scores and additional statistics and dataviz can be seen in this ADI story with a BroadStreet free account.Much of the ADI research and popularity would not be possible without the excellent work of Dr. Amy Kind and colleagues at HIPxChange and at The University of Wisconsin Madison.This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery. Learn more

Abstract

ADI: An index of socioeconomic status for communities. Dataset ingested directly from BigQuery.

Documentation

The Area Deprivation Index (ADI) can show where areas of deprivation and affluence exist within a community. The ADI is calculated with 17 indicators from the American Community Survey (ACS) having been well-studied in the peer-reviewed literature since 2003, and used for 20 years by the Health Resources and Services Administration (HRSA). High levels of deprivation have been linked to health outcomes such as 30-day hospital readmission rates, cardiovascular disease deaths, cervical cancer incidence, cancer deaths, and all-cause mortality. The 17 indicators from the ADI encompass income, education, employment, and housing conditions at the Census Block Group level.

The ADI is available on BigQuery for release years 2018-2020 and is reported as a percentile that is 0-100% with 50% indicating a "middle of the nation" percentile. Data is provided at the county, ZIP, and Census Block Group levels. Neighborhood and racial disparities occur when some neighborhoods have high ADI scores and others have low scores. A low ADI score indicates affluence or prosperity. A high ADI score is indicative of high levels of deprivation. Raw ADI scores and additional statistics and dataviz can be seen in this ADI story with a BroadStreet free account.

Dataset source: https://help.broadstreet.io/article/adi/

Area Deprivation Index state score in 2020. The Area Deprivation Index (ADI) ranks neighborhoods on the basis of socioeconomic disadvantage in the areas of income, education, employment, and housing quality. Areas with greater disadvantage are ranked higher. National scores are normalized to the whole country, and state scores are normalized to a particular state. Higher Area Deprivation Index scores have been shown to correlate with worse health outcomes in measures such as life expectancy. This index was created by researchers at the University of Wisconsin-Madison based on a methodology originally developed by the Health Resources and Services Administration. Areas on this map are ranked against other areas within the state. State scores represent deciles. In other words, they are divided into 10 groups of the same size, where 1 is the lowest rate of disadvantage and 10 is the highest.

Associations between individual-level variables and SARS-CoV-2 infection in Baton Rouge and New Orleans.

The Area Deprivation Index (ADI) can show where areas of deprivation and affluence exist within a community. The ADI is calculated with 17 indicators from the American Community Survey (ACS) having been well-studied in the peer-reviewed literature since 2003, and used for 20 years by the Health Resources and Services Administration (HRSA). High levels of deprivation have been linked to health outcomes such as 30-day hospital readmission rates, cardiovascular disease deaths, cervical cancer incidence, cancer deaths, and all-cause mortality. The 17 indicators from the ADI encompass income, education, employment, and housing conditions at the Census Block Group level.The ADI is available on BigQuery for release years 2018-2020 and is reported as a percentile that is 0-100% with 50% indicating a "middle of the nation" percentile. Data is provided at the county, ZIP, and Census Block Group levels. Neighborhood and racial disparities occur when some neighborhoods have high ADI scores and others have low scores. A low ADI score indicates affluence or prosperity. A high ADI score is indicative of high levels of deprivation. Raw ADI scores and additional statistics and dataviz can be seen in this ADI story with a BroadStreet free account.Much of the ADI research and popularity would not be possible without the excellent work of Dr. Amy Kind and colleagues at HIPxChange and at The University of Wisconsin Madison.This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery. En savoir plus

The area deprivation index (ADI) represents a geographic area-based measure of the socioeconomic deprivation experienced by a neighborhood. Higher index values represent higher levels of deprivation and associated with an increased risk of adverse health and health care. It includes factors for the theoretical domains of income, education, employment, and housing quality.

The Area Deprivation Index (ADI) can show where areas of deprivation and affluence exist within a community. The ADI is calculated with 17 indicators from the American Community Survey (ACS) having been well-studied in the peer-reviewed literature since 2003, and used for 20 years by the Health Resources and Services Administration (HRSA). High levels of deprivation have been linked to health outcomes such as 30-day hospital readmission rates, cardiovascular disease deaths, cervical cancer incidence, cancer deaths, and all-cause mortality. The 17 indicators from the ADI encompass income, education, employment, and housing conditions at the Census Block Group level.The ADI is available on BigQuery for release years 2018-2020 and is reported as a percentile that is 0-100% with 50% indicating a "middle of the nation" percentile. Data is provided at the county, ZIP, and Census Block Group levels. Neighborhood and racial disparities occur when some neighborhoods have high ADI scores and others have low scores. A low ADI score indicates affluence or prosperity. A high ADI score is indicative of high levels of deprivation. Raw ADI scores and additional statistics and dataviz can be seen in this ADI story with a BroadStreet free account.Much of the ADI research and popularity would not be possible without the excellent work of Dr. Amy Kind and colleagues at HIPxChange and at The University of Wisconsin Madison.This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery. Weitere Informationen

Introduction: The spread of Coronavirus Disease 2019 (COVID-19) across the United States has highlighted the long-standing nationwide health inequalities with socioeconomically challenged communities experiencing a higher burden of the disease. We assessed the impact of neighborhood socioeconomic characteristics on the COVID-19 prevalence across seven selected states (i.e., Arizona, Florida, Illinois, Maryland, North Carolina, South Carolina, and Virginia).Methods: We obtained cumulative COVID-19 cases reported at the neighborhood aggregation level by Departments of Health in selected states on two dates (May 3rd, 2020, and May 30th, 2020) and assessed the correlation between the COVID-19 prevalence and neighborhood characteristics. We developed Area Deprivation Index (ADI), a composite measure to rank neighborhoods by their socioeconomic characteristics, using the 2018 US Census American Community Survey. The higher ADI rank represented more disadvantaged neighborhoods.Results: After controlling for age, gender, and the square mileage of each community we identified Zip-codes with higher ADI (more disadvantaged neighborhoods) in Illinois and Maryland had higher COVID-19 prevalence comparing to zip-codes across the country and in the same state with lower ADI (less disadvantaged neighborhoods) using data on May 3rd. We detected the same pattern across all states except for Florida and Virginia using data on May 30th, 2020.Conclusion: Our study provides evidence that not all Americans are at equal risk for COVID-19. Socioeconomic characteristics of communities appear to be associated with their COVID-19 susceptibility, at least among those study states with high rates of disease.

The risk of thromboembolism and bleeding before initiation of oral anticoagulant (OAC) in atrial fibrillation patients is estimated by CHA 2 DS 2 -VASc and HAS-BLED scoring system, respectively. Patients’ socioeconomic status (SES) could influence these risks, but its impact on the two risk scores' predictive performance with respect to clinical events remains unknown. Our objective was to determine if patient SES defined by area deprivation index (ADI), in conjunction with CHA 2 DS 2 -VASc and HAS-BLED scores, could guide oral anticoagulation therapy. Methods and Findings The study cohort included newly diagnosed patients with AF who were treated with warfarin. The cohort was stratified by the time in therapeutic range of INR (TTR), ADI, CHA 2 DS 2 -VASc, and HAS-BLED risk scores. TTR and ischemic and bleeding events during the first year of therapy were compared across subpopulations. Among 7274 patients, those living in the two most deprived quintiles (ADI ≥60%) had a significantly higher risk of ischemic events and those in the most deprived quintile (ADI≥80%) had a significantly increased risk of bleeding events. ADI significantly improved the predictive performance of CHA 2 DS 2 -VASc but not HAS-BLED risk scores. Conclusion ADI can predict increased risk for ischemic and bleeding events in the first year of warfarin therapy in patients with incident AF.

PurposePatient satisfaction surveys are pivotal in evaluating healthcare quality and enhancing patient care. Understanding the factors influencing patient engagement with these surveys in radiation oncology can guide improvements in patient-centered care.MethodsThis retrospective study analyzed data from radiation oncology patients at a large multi-site single-institution center from May 2021 to January 2024. We assessed the influence of demographic, clinical, and socioeconomic factors on the likelihood of survey participation using univariate (UVA) and multivariable (MVA) logistic regression analyses. Factors included age, gender, race, socioeconomic status (SES) via Area Deprivation Index (ADI), language, marital status, smoking, employment, insurance type, mental health disorders (MHD), comorbidity index (CCI), and cancer type.ResultsIn a comprehensive analysis of 11,859 patients, most were female (57.2%), over 65 years old (60.7%), and primarily insured by Medicare (45.9%). MVA showed that higher socioeconomic disadvantage significantly decreased survey participation (ADI third tertile vs. first tertile OR=0.708, p

The Austempered Ductile Iron (ADI) casting market is experiencing robust growth, driven by increasing demand across various sectors. The automotive industry, particularly heavy trucks and cars, remains a dominant application segment, leveraging ADI's superior strength-to-weight ratio and fatigue resistance. The railway industry is also a significant contributor, with ADI castings finding use in crucial components demanding high durability and reliability. Other applications, such as construction equipment and agricultural machinery, are experiencing rising adoption, further fueling market expansion. The market's growth is propelled by advancements in ADI manufacturing techniques, leading to improved material properties and cost-effectiveness. Furthermore, stringent emission regulations and the drive towards fuel efficiency are pushing the adoption of lighter-weight components, thus boosting the demand for ADI castings. The market is segmented by ADI grade, with ADI Grade 3-4 currently holding the largest market share due to its versatile properties and wide applicability. However, higher-grade ADI castings are witnessing increasing adoption in niche applications requiring enhanced performance. While raw material price fluctuations and potential supply chain disruptions pose challenges, the overall market outlook remains positive, with a projected continued growth trajectory over the forecast period. Competition is intense, with several established players vying for market dominance. However, opportunities exist for smaller players focusing on specialized applications or geographic regions to gain a foothold. Geographic expansion, particularly in rapidly developing economies of Asia Pacific and South America, is expected to significantly contribute to future market growth. The global ADI casting market, estimated at $5 billion in 2025, is projected to expand at a CAGR of approximately 6% from 2025 to 2033. This growth is underpinned by the aforementioned drivers and trends, while restraints such as high initial investment costs for ADI production and the availability of alternative materials are expected to be partially mitigated by technological advancements and cost optimization strategies within the industry. The North American market currently holds a substantial share, due to a well-established automotive industry and robust infrastructure. However, the Asia-Pacific region is poised for significant growth, driven by rapid industrialization and increasing automotive production in countries like China and India. European markets maintain a consistent share, reflecting established manufacturing bases and demanding quality standards.

Introduction: Neighborhood socioeconomic status (NSES) has been linked with overall health, and this study will evaluate whether NSES is cross-sectionally associated with cognition in non-Hispanic Whites (NHW) and Mexican Americans (MA) from the Health and Aging Brain: Health Disparities Study (HABS-HD). Methods: The HABS-HD is a longitudinal study conducted at the University of North Texas Health Science Center. The final sample analyzed (n=1312) were 50 years or older, with unimpaired cognition, and underwent an interview, neuropsychological examination, imaging, and blood draw. NSES was measured using the national area deprivation index (ADI) percentile ranking, which considered socioeconomic variables. Executive function and processing speed were assessed by the trail making tests (A and B) and the digit-symbol substitution test, respectively. Linear regression was used to assess the association of ADI and cognitive measures. Results: MA were younger, more likely to be female, less educated, had higher ADI scores, performed worse on trails B (all p

BackgroundDisparities in cancer outcomes persist between racial, ethnic, and socioeconomic groups. One potential cause is lack of appropriate representation in dose-finding clinical trials. We investigated the extent of disparities in phase I clinical trials and recent changes in the setting of institutional efforts to mitigate disparities, legislative interventions, FDA guidance for sponsors and the COVID-19 pandemic.MethodsWe performed a retrospective review of patients enrolled in phase I clinical trials at the University of Colorado Cancer Center in 2018–2019 and 2022-2023. We collected demographics, area deprivation index (ADI), tumor type and other clinical variables. Differences between cohorts were evaluated with t-tests, chi-Square test, or Fisher exact test. Progression-free survival (PFS) and overall survival (OS) were calculated using the Kaplan-Meier method. Hazard ratios (HR), confidence intervals (CI) and p-values were derived using the Cox-proportional hazards method.ResultsA total of 361 patients were included (209 and 152 in the 2018–2019 and 2022–2023 cohorts, respectively). The population consisted of 85.0% White, 3.3% Asian, 1.4% Black, 0.3% Native Hawaiian or Pacific Islander and no American Indian/Alaskan Native (AIAN) patients by race, and 9.1% Hispanic by ethnicity. The most common tumor type was colorectal cancer (18.3%). Compared to 2018-2019, we observed increases in non-English speakers from 1.9% (4/209) to 6.6% (10/152) (p = 0.028) and in translated informed consent forms (ICFs) from 1.4% (3/209) to 5.9% (9/152) (p = 0.033) in 2022-2023. There were no significant changes in race, ethnicity, insurance, or tumor type, although there was a moderate increase in Hispanic patients from 8.1% to 10.5%. There were no differences in clinical outcomes by race, ethnicity, or ADI scores in the overall study population. However, in the most common cancer type, colorectal cancer, higher ADI scores were associated with decreased median PFS and OS.ConclusionThe interventions resulted in an increase in accrual of non-English speaking patients, however, there was not yet a significant change in overall race and ethnicity. Our study confirms poorer outcomes for patients with higher ADI scores. Further research is warranted to understand disparities in clinical trial accrual, and intervention is needed to improve outcomes for disadvantaged patients.

Minder International Publishers

The global Austempered Ductile Iron (ADI) casting market is experiencing robust growth, driven by increasing demand across diverse sectors. The automotive industry, a major consumer of ADI castings due to their superior strength-to-weight ratio and fatigue resistance, is a key driver. This is further amplified by the rising adoption of electric vehicles (EVs) and the need for lightweight components to enhance fuel efficiency and range. Beyond automotive, ADI castings find applications in construction machinery, agricultural equipment, and industrial components, contributing to the market's expansion. The market is characterized by a moderate level of competition among established players, with both large multinational corporations and specialized regional manufacturers participating. Technological advancements focused on optimizing casting processes and enhancing the material properties of ADI are also pushing growth. While supply chain disruptions and fluctuating raw material prices pose challenges, the overall outlook for the ADI casting market remains positive. We estimate the market size in 2025 to be approximately $2.5 billion, growing at a compound annual growth rate (CAGR) of 6% between 2025 and 2033, resulting in a market size of approximately $4.2 billion by 2033. This growth projection accounts for the expected increase in demand across various sectors and ongoing technological improvements. Factors influencing market growth include the increasing adoption of lightweight materials in various industries, driven by sustainability concerns and performance improvements. Furthermore, government regulations promoting fuel efficiency and emission reductions in the transportation sector are indirectly fueling demand for ADI castings. However, challenges remain, including the need for specialized manufacturing processes and the potential for higher initial production costs compared to other casting materials. Despite these restraints, the superior properties of ADI castings, coupled with ongoing research and development in this field, are expected to maintain a strong growth trajectory over the forecast period. The market segmentation reflects a broad spectrum of applications, with automotive and machinery segments expected to dominate, followed by industrial and other niche sectors. The geographic distribution shows a concentration in developed regions, though emerging markets are expected to contribute significantly to growth in the coming years.

Additional file 2: Table S2.1. Characteristics of study participants at time point 1 (T1) stratified by Area Deprivation Index (ADI). Results: Summary statistics displaying variable distribution, mean, standard deviation, median, and 1st and 3rd quartiles. We tested for differences between low and high ADI groups using chi-square, T, or Wilcoxon rank-sum tests as appropriate. Analysis performed on Area Deprivation Index-stratified (ADI-stratified) T1 data (Low ADI, N = 102); High ADI, N = 104). Table S2.2. Characteristics of study participants at time point 2 (T2) stratified by Area Deprivation Index (ADI). Results: Summary statistics displaying variable distribution, mean, standard deviation, median, and 1st and 3rd quartiles. We tested for differences between low and high ADI groups using chi-square, T, or Wilcoxon rank-sum tests as appropriate. Analysis performed on Area Deprivation Index-stratified (ADI-stratified) T2 data (Low ADI, N = 143); High ADI, N = 123).

Journal of Educational Review (JER)

Austempered Ductile Iron (ADI) is a cast iron with high potential to substitute cast steel due to the lighter weight, higher tensile strength and significantly lower manufacturing cost. This material has a microstructure consist of acicular ferrite and high carbon enriched retained austenite which will to partially transform to martensite under plastic deformation. During the conventional compression tests, the samples present a barrelling effect which is produced by the friction between platens and samples. This generates a triaxial stress state different from the ideal uniaxial stress condition. We propose to determinate the evolution of martensite fraction and the strain field on ADI compressed samples under different plastic strain using Energy-selective neutron imaging.

This report details the field acquisition and data processing, inversion and interpretation stages of the Walparuta geophysical program conducted in December 2021. The work was focussed on the Walparuta Project area, located 20 km north of Manna... This report details the field acquisition and data processing, inversion and interpretation stages of the Walparuta geophysical program conducted in December 2021. The work was focussed on the Walparuta Project area, located 20 km north of Manna Hill township on the Barrier Highway, South Australia. Here most of the previously reported past mineral exploratory work had been focussed around the historic Walparuta copper mine, with limited modern exploration done in the surrounding country. Due to the complexity of the geological setting and paucity of modern geophysical data available to use, Longreach determined that obtaining new high resolution geophysical data was required to for the company to be able to better map the subsurface geology and assess its IOCG mineral potential. After receiving Accelerated Discovery Initiative Round 2 funding assistance from DEM, a ground gravity survey was conducted for Longreach by Daishsat Geodetic Surveyors Pty Ltd in early December 2021, with a total of 1346 new stations read at 75 m intervals along lines spaced 75 m and 150 m apart, to give complete coverage of the project area. Shortly after the ground gravity survey acquisition was completed, a high resolution (20 m flight line spacing) helicopter-borne magnetic / radiometric survey was conducted for Longreach by AeroSystems Australia Pty Ltd, to produce 840 line km of data covering the project area. Overall, the quality of the resulting field data was good for both the magnetic / radiometric and ground gravity surveys. The survey methods used have been demonstrated to have been accurate, reliable and conducted to the highest standards with modern calibrated acquisition equipment run by professional, experienced staff utilising proven acquisition techniques and quality control procedures. The final data product acceptance QA/QC, verification, processing and geophysical inversion steps were subsequently conducted for Longreach by independent geophysical consultants Terra Resources. Interpretation of the surveys' data was performed in-house by Longreach. A 3D geological model covering a 6 km E-W x 3 km N-S extent was later constructed for Longreach by Kenex, using the licensee's detailed interpreted 2D map of the solid geology underlying EL 6484, plus inputs from the interpreted newly acquired geophysical data. Longreach is of the opinion that this ADI Project now completed in the Walparuta Inlier area using grant funds obtained from the SA Government has proven its value through generating immediate IOCG drill targets suitable for follow-up exploration. The spatial and inferred geological aspects of these targets will now be interrogated to select to best advantage the drilling method / rig type, locations, inclinations and orientations of the planned holes. More +

The Air Data Indicator (ADI) market is experiencing robust growth, driven by increasing demand for advanced avionics systems across both commercial and general aviation sectors. The market, valued at approximately $500 million in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 6% from 2025 to 2033. This growth is fueled by several key factors: the ongoing trend towards equipping aircraft with more sophisticated and integrated flight instrumentation, the increasing adoption of glass cockpits that leverage ADIs for enhanced situational awareness, and stringent safety regulations mandating reliable air data systems. Furthermore, technological advancements leading to lighter, more efficient, and cost-effective ADIs are also contributing to market expansion. Key players like Mid-Continent Instruments and Avionics, LX Navigation, and Aerosonic Corporation are driving innovation, introducing new features such as improved accuracy, enhanced reliability, and integration with other avionics components. Competition is expected to intensify as manufacturers strive to offer superior products with advanced capabilities and better price-performance ratios. Despite the positive growth trajectory, the market faces certain challenges. The high initial cost of implementing advanced ADI systems can be a barrier for some smaller operators. Furthermore, maintaining compatibility with existing aircraft systems and addressing potential integration complexities also pose challenges. However, these challenges are being mitigated by technological advancements that reduce costs and improve ease of integration. The market segmentation is currently dominated by commercial aviation, but the general aviation segment is expected to witness significant growth in the coming years as a result of increased adoption of newer technologies. Geographical expansion, particularly in developing economies with burgeoning aviation sectors, will offer further opportunities for growth within the ADI market. The forecast period suggests sustained growth, emphasizing the long-term prospects for this essential component of modern aviation.