Population based cancer incidence rates were abstracted from National Cancer Institute, State Cancer Profiles for all available counties in the United States for which data were available. This is a national county-level database of cancer data that are collected by state public health surveillance systems. All-site cancer is defined as any type of cancer that is captured in the state registry data, though non-melanoma skin cancer is not included. All-site age-adjusted cancer incidence rates were abstracted separately for males and females. County-level annual age-adjusted all-site cancer incidence rates for years 2006–2010 were available for 2687 of 3142 (85.5%) counties in the U.S. Counties for which there are fewer than 16 reported cases in a specific area-sex-race category are suppressed to ensure confidentiality and stability of rate estimates; this accounted for 14 counties in our study. Two states, Kansas and Virginia, do not provide data because of state legislation and regulations which prohibit the release of county level data to outside entities. Data from Michigan does not include cases diagnosed in other states because data exchange agreements prohibit the release of data to third parties. Finally, state data is not available for three states, Minnesota, Ohio, and Washington. The age-adjusted average annual incidence rate for all counties was 453.7 per 100,000 persons. We selected 2006–2010 as it is subsequent in time to the EQI exposure data which was constructed to represent the years 2000–2005. We also gathered data for the three leading causes of cancer for males (lung, prostate, and colorectal) and females (lung, breast, and colorectal). The EQI was used as an exposure metric as an indicator of cumulative environmental exposures at the county-level representing the period 2000 to 2005. A complete description of the datasets used in the EQI are provided in Lobdell et al. and methods used for index construction are described by Messer et al. The EQI was developed for the period 2000– 2005 because it was the time period for which the most recent data were available when index construction was initiated. The EQI includes variables representing each of the environmental domains. The air _domain includes 87 variables representing criteria and hazardous air pollutants. The water _domain includes 80 variables representing overall water quality, general water contamination, recreational water quality, drinking water quality, atmospheric deposition, drought, and chemical contamination. The land _domain includes 26 variables representing agriculture, pesticides, contaminants, facilities, and radon. The built _domain includes 14 variables representing roads, highway/road safety, public transit behavior, business environment, and subsidized housing environment. The sociodemographic environment includes 12 variables representing socioeconomics and crime. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Human health data are not available publicly. EQI data are available at: https://edg.epa.gov/data/Public/ORD/NHEERL/EQI. Format: Data are stored as csv files. This dataset is associated with the following publication: Jagai, J., L. Messer, K. Rappazzo , C. Gray, S. Grabich , and D. Lobdell. County-level environmental quality and associations with cancer incidence#. Cancer. John Wiley & Sons Incorporated, New York, NY, USA, 123(15): 2901-2908, (2017).
The United States Cancer Statistics (USCS) online databases in WONDER provide cancer incidence and mortality data for the United States for the years since 1999, by year, state and metropolitan areas (MSA), age group, race, ethnicity, sex, childhood cancer classifications and cancer site. Report case counts, deaths, crude and age-adjusted incidence and death rates, and 95% confidence intervals for rates. The USCS data are the official federal statistics on cancer incidence from registries having high-quality data and cancer mortality statistics for 50 states and the District of Columbia. USCS are produced by the Centers for Disease Control and Prevention (CDC) and the National Cancer Institute (NCI), in collaboration with the North American Association of Central Cancer Registries (NAACCR). Mortality data are provided by the Centers for Disease Control and Prevention (CDC), National Center for Health Statistics (NCHS), National Vital Statistics System (NVSS).
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This map shows the incidence rate per 100,000 for all cancer types by county. Counties are shaded based on quartile distribution. The lighter shaded counties have lower cancer incidence rates. The darker shaded counties have higher cancer incidence rates. New York State Community Health Indicator Reports (CHIRS) were developed in 2012, and are updated annually to consolidate and improve data linkages for the health indicators included in the County Health Assessment Indicators (CHAI) for all communities in New York. The CHIRS present data for more than 300 health indicators that are organized by 15 different health topics. Data if provided for all 62 New York State counties, 11 regions (including New York City), the State excluding New York City, and New York State. For more information, check out: http://www.health.ny.gov/statistics/chac/indicators/. The "About" tab contains additional details concerning this dataset.
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This map shows the incidence rate per 100,000 of lung and bronchus cancer by county. Counties are shaded based on quartile distribution. The lighter shaded counties have lower incidence rates of lung and bronchus cancer. The darker shaded counties have higher incidence rates of lung and bronchus cancer. New York State Community Health Indicator Reports (CHIRS) were developed in 2012, and are updated annually to consolidate and improve data linkages for the health indicators included in the County Health Assessment Indicators (CHAI) for all communities in New York. The CHIRS present data for more than 300 health indicators that are organized by 15 different health topics. Data if provided for all 62 New York State counties, 8 regions (including New York City), the State excluding New York City, and New York State. For more information, check out: http://www.health.ny.gov/statistics/chac/indicators/. The "About" tab contains additional details concerning this dataset.
Medical Service Study Areas (MSSAs)As defined by California's Office of Statewide Health Planning and Development (OSHPD) in 2013, "MSSAs are sub-city and sub-county geographical units used to organize and display population, demographic and physician data" (Source). Each census tract in CA is assigned to a given MSSA. The most recent MSSA dataset (2014) was used. Spatial data are available via OSHPD at the California Open Data Portal. This information may be useful in studying health equity.Age-Adjusted Incidence Rate (AAIR)Age-adjustment is a statistical method that allows comparisons of incidence rates to be made between populations with different age distributions. This is important since the incidence of most cancers increases with age. An age-adjusted cancer incidence (or death) rate is defined as the number of new cancers (or deaths) per 100,000 population that would occur in a certain period of time if that population had a 'standard' age distribution. In the California Health Maps, incidence rates are age-adjusted using the U.S. 2000 Standard Population.Cancer incidence ratesIncidence rates were calculated using case counts from the California Cancer Registry. Population data from 2010 Census and SEER 2015 census tract estimates by race/origin (controlling to Vintage 2015) were used to estimate population denominators. Yearly SEER 2015 census tract estimates by race/origin (controlling to Vintage 2015) were used to estimate population denominators for 5-year incidence rates (2013-2017)According to California Department of Public Health guidelines, cancer incidence rates cannot be reported if based on <15 cancer cases and/or a population <10,000 to ensure confidentiality and stable statistical rates.Spatial extent: CaliforniaSpatial Unit: MSSACreated: n/aUpdated: n/aSource: California Health MapsContact Email: gbacr@ucsf.eduSource Link: https://www.californiahealthmaps.org/?areatype=mssa&address=&sex=Both&site=AllSite&race=&year=05yr&overlays=none&choropleth=Obesity
In 2022, Australia had the fourth-highest total number of skin cancer cases worldwide and the highest age-standardized rate, with roughly 37 cases of skin cancer per 100,000 population. The graph illustrates the rate of skin cancer in the countries with the highest skin cancer rates worldwide in 2022.
SEER Limited-Use cancer incidence data with associated population data. Geographic areas available are county and SEER registry. The Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute collects and distributes high quality, comprehensive cancer data from a number of population-based cancer registries. Data include patient demographics, primary tumor site, morphology, stage at diagnosis, first course of treatment, and follow-up for vital status. The SEER Program is the only comprehensive source of population-based information in the United States that includes stage of cancer at the time of diagnosis and survival rates within each stage.
This is a linked dataset between drinking water data and cancer data. Drinking Water Data: County-level concentrations of arsenic from CWSs between 2000 and 2010 were collected from the Center for Disease Control and Prevention’s (CDC) National Environmental Public Health Tracking Network (NEPHTN) (Centers for Disease Control and Prevention, 2018a). Annual mean drinking water arsenic concentrations from 2000 to 2010 were available for a total of 87,662 samples from 75,453 CWS from 26 states, representing 1,425 counties. For samples identified as non-detects, the most frequently reported values were 0.5 ppb and 1 ppb, with a range of 0 ppb to 10 ppb. For non-detect samples reported as zero, the value was substituted with a constant of 0.25 ppb (Almberg et al., 2017; Bulka et al., 2016). Of the samples that were reported as non-detects, 10.87% were reported as zeros. Cancer Data: County-level cancer counts and incidence rates for bladder, colorectal, and kidney cancers were acquired from the National Cancer Institute (NCI) and CDC’s State Cancer Profiles for 2011 through 2015 for adults (age ≥ 50) to match the counties with exposure data (National Cancer Institute and Centers for Disease Control and Prevention, 2018a). We utilized the time period 2011-2015 to provide a lag following the exposure period of 2000-2010. The State Cancer Profiles provide age-adjusted county-level cancer incidence, prevalence, mortality rates and average annual counts for 20 different types of cancers and select demographics (National Cancer Institute and Centers for Disease Control and Prevention, 2018b). Counties where there were less than 16 reported cases in a specific county, sex, and/or race category were suppressed to ensure confidentiality and stability of rate estimates (National Cancer Institute and Centers for Disease Control and Prevention, 2018a). This dataset is associated with the following publication: Krajewski, A., M. Jimenez, K. Rappazzo, D. Lobdell, and J. Jagai. Aggregated Cumulative County Arsenic in Drinking Water and Associations with Bladder, Colorectal, and Kidney Cancers, Accounting for Population Served. Journal of Exposure Science and Environmental Epidemiology. Nature Publishing Group, London, UK, 31(6): 979-989, (2021).
Medical Service Study Areas (MSSAs)As defined by California's Office of Statewide Health Planning and Development (OSHPD) in 2013, "MSSAs are sub-city and sub-county geographical units used to organize and display population, demographic and physician data" (Source). Each census tract in CA is assigned to a given MSSA. The most recent MSSA dataset (2014) was used. Spatial data are available via OSHPD at the California Open Data Portal. This information may be useful in studying health equity.Age-Adjusted Incidence Rate (AAIR)Age-adjustment is a statistical method that allows comparisons of incidence rates to be made between populations with different age distributions. This is important since the incidence of most cancers increases with age. An age-adjusted cancer incidence (or death) rate is defined as the number of new cancers (or deaths) per 100,000 population that would occur in a certain period of time if that population had a 'standard' age distribution. In the California Health Maps, incidence rates are age-adjusted using the U.S. 2000 Standard Population.
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This publication reports on newly diagnosed cancers registered in England in addition to cancer deaths registered in England during 2020. It includes this summary report showing key findings, spreadsheet tables with more detailed estimates, and a methodology document.
This statistic shows the rate of registrations of newly diagnosed cases of ovarian cancer per 100,000 population in England in 2020, by region. With a rate of 22.4 newly diagnosed females with ovarian cancer per 100,000 population in 2020, the regions most affected by ovarian cancer was North West.
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ObjectivesCompared to other racial and ethnic groups, little to no disaggregated cancer incidence data exist for subgroups of non-Hispanic Blacks (NHBs), despite heterogeneity in sociodemographic characteristics and cancer risk factors within this group. Our objective was to examine age-adjusted cancer incidence by nativity and birthplace among NHB cancer cases diagnosed in New Jersey.MethodsRace, ethnicity, and birthplace data from the New Jersey State Cancer Registry were used to classify NHB cancer cases diagnosed between 2005-2017. Thirteen waves of population estimates (by county, nativity, gender, age-group) were derived from the American Community Survey using Integrated Public-Use Microdata to approximate yearly demographics. Age-adjusted cancer incidence rates (overall and by site) by birthplace were generated using SEER*Stat 8.3.8. Bivariate associations were assessed using chi-square and Fisher’s exact tests. Trend analyses were performed using Joinpoint 4.7.ResultsBirthplace was available for 62.3% of the 71,019 NHB cancer cases. Immigrants represented 12.3%, with African-born, Haitian-born, Jamaican-born, ‘other-Caribbean-born’, and ‘other-non-American-born’ accounting for 18.5%, 17.7%, 16.5%, 10.6%, and 36.8%, respectively. Overall, age-adjusted cancer incidence rates were lower for NHB immigrants for all sites combined and for several of the top five cancers, relative to American-born NHBs. Age-adjusted cancer incidence was lower among immigrant than American-born males (271.6 vs. 406.8 per 100,000) and females (191.9 vs. 299.2 per 100,000). Age-adjusted cancer incidence was lower for Jamaican-born (114.6 per 100,000) and other-Caribbean-born females (128.8 per 100,000) than African-born (139.4 per 100,000) and Haitian-born females (149.9 per 100,000). No significant differences in age-adjusted cancer incidence were observed by birthplace among NHB males. Age-adjusted cancer incidence decreased for all sites combined from 2005-2017 among American-born males, immigrant males, and American-born females, while NHB immigrant female rates remained relatively stable.ConclusionsThere is variation in age-adjusted cancer incidence rates across NHB subgroups, highlighting the need for more complete birthplace information in population-based registries to facilitate generating disaggregated cancer surveillance statistics by birthplace. This study fills a knowledge gap of critical importance for understanding and ultimately addressing cancer inequities.
Financial overview and grant giving statistics of American Cancer Society
In 2024, Merck & Co.’s Keytruda generated nearly ** billion U.S. dollars, making it the number one ranking cancer drug worldwide in terms of revenue. Other oncology products among the top ten included Revlimid, Opdivo, and Tagrisso. Pharmaceutical outlook Cancer drug Keytruda is already exceeding original projections in terms of revenue. Pharmaceutical sales numbers are forecast to be the highest in North America by 2028. It is predicted that sales numbers will reach around *** billion U.S. dollars in this region, which would be nearly three times the sales numbers expected from the runner-up, the European Union. Cancer cases by gender Specific types of cancer are more common among certain genders. Worldwide, breast cancer accounted for approximately a quarter of all new cancer cases among females of all ages in 2022. Lung cancer was the second most common type for women. For men, lung and prostate cancer were the most common types that year. Some ** percent of new male cases involved lung cancer, while about ** percent were prostate cancer cases.
Financial overview and grant giving statistics of Antrim County High Tea for Breast Cancer
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Colombia CO: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data was reported at 18.300 NA in 2016. This records a decrease from the previous number of 18.500 NA for 2015. Colombia CO: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data is updated yearly, averaging 19.800 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 22.900 NA in 2000 and a record low of 18.300 NA in 2016. Colombia CO: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Colombia – Table CO.World Bank.WDI: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;
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The North American cancer therapy market, currently valued at approximately $XX million (estimated based on available data and market trends for similar markets), is projected to experience robust growth, exhibiting a compound annual growth rate (CAGR) of 8.10% from 2025 to 2033. This expansion is fueled by several key drivers, including the rising prevalence of various cancer types, an aging population increasing susceptibility, and continuous advancements in cancer therapies. The market is segmented by treatment type (chemotherapy, targeted therapy, immunotherapy, hormonal therapy, and others), cancer type (blood, breast, prostate, gastrointestinal, gynecologic, respiratory/lung, and others), and end-user (hospitals, specialty clinics, and cancer/radiation therapy centers). Immunotherapy and targeted therapies are experiencing particularly rapid growth, driven by their increased efficacy and targeted approach, minimizing side effects compared to traditional chemotherapy. Growth is further propelled by substantial investments in research and development, leading to the approval of innovative cancer drugs and therapies. However, high treatment costs, potential treatment side effects, and variations in healthcare access across the region present some challenges to market expansion. The United States dominates the North American market, followed by Canada and Mexico. However, Mexico's market is expected to witness faster growth than Canada due to increasing healthcare infrastructure development and growing awareness of advanced cancer treatments. Key players such as Bayer AG, Novartis AG, Amgen Inc., Merck & Co. Inc., Roche, AstraZeneca, Bristol Myers Squibb, Eli Lilly, Johnson & Johnson, and Pfizer are driving innovation and competition within the market, continually introducing new and improved therapies. Strategic collaborations, mergers, and acquisitions further contribute to market dynamism. The forecast period of 2025-2033 anticipates consistent growth, driven by the continued development of personalized medicine approaches and ongoing efforts to improve early cancer detection and screening. This will likely translate into a significant increase in the market size, reaching an estimated value of $YY million by 2033 (estimated based on the provided CAGR and market dynamics). This estimate considers the current market valuation and projects future growth based on the provided CAGR, taking into account industry trends and market dynamics. Recent developments include: In September 2022, Eli Lilly and Company announced that the United States Food and Drug Administration (FDA) has approved Retevmo (selpercatinib, 40 mg & 80 mg capsules) for adult patients with locally advanced or metastatic solid tumors with a rearranged during transfection (RET) gene fusion that has progressed on or following prior systemic treatment or who have no satisfactory alternative treatment options., In August 2022, the United States Food and Drug Administration approved Enhertu (fam-trastuzumab-deruxtecan-nxki), an IV infusion for the treatment of patients with unresectable (unable to be removed) or metastatic (spread to other parts of the body) HER2-low breast cancer.. Key drivers for this market are: Rising Prevalence of Cancer, Strong R&D Initiatives from Key Players and the Government; Growing Government Initiatives for Cancer Awareness. Potential restraints include: Fluctuation in Reimbursement Policies, High Cost of Cancer Therapies. Notable trends are: The Target Therapy Segment is Expected to show the Fastest Growth During the Forecast Period.
The Human Papillomavirus (HPV) test is a crucial technology for cervical cancer prevention because it enables programs to identify women with high-risk HPV infection who are at risk of developing cervical cancer. Current U.S. Preventive Services Task Force recommendations include cervical cancer screening every three years with cervical cytology alone or every five years with either high-risk HPV testing alone or high-risk HPV testing combined with cytology (co-testing). In Argentina, 7,548 new cervical cancer cases are diagnosed each year with 3,932 deaths attributed to this cause. Our study aims to show the clinical implementation of a cervical cancer screening program by concurrent HPV testing and cervical cytology (co-testing); and to evaluate the possible cervical cancer screening scenarios for Latin America, focusing on their performance and average cost. A cervical cancer screening five year program via co-testing algorithm (Hybrid-2-Capture/cytology) was performed on women aged 30-65 years old at a university hospital. Statistical analysis included a multinomial logistic regression, and two cancer screening classification alternatives were tested (cytology-reflex and HPV-reflex). A total of 2,273 women were included, 91.11% of the participants were double-negative, 2.55% double-positive, 5.90% positive-Hybrid-2-Capture-/negative-cytology, and 0.44% negative-Hybrid-2-Capture/positive-cytology. A thorough follow-up was performed in the positive-Hybrid-2-Capture group. Despite our efforts, 21 (10.93%) were lost, mainly because of changes on their health insurance coverage which excluded them from our screening algorithm. Of the 171 women with positive-Hybrid-2-Capture results and follow-up, 68 (39.77%) cleared the virus infection, 64 (37.43%) showed viral persistence, and 39 (22.81%) were adequately treated after detection via colposcopy/biopsy of histological HSIL (High-Grade Squamous Intraepithelial Lesion). The prevalence of high-risk HPV in this population was 192 women (8.45%), with HSIL histology detection rates of 17.32 per 1,000 screened women. A multinomial logistic regression analysis was performed over the women with positive-Hybrid-2-Capture considering the follow up (clearance, persistence and HSIL) as dependent variable, and the cytology test results (positive- or negative-cytology and Atypical Squamous Cells of Undetermined Significance, ASC-US) as independent variable. The model supported a direct association between cytology test results and follow up: negative-cytology/clearance, ASC-US/persistence, and positive-cytology/HSIL with the following probabilities of occurrence for these pairs 0.5, 0.647 and 0.647, respectively. Cytology could be considered a prognostic-factor in women with a positive-Hybrid-2-Capture. These findings suggest that the introduction of co-testing could diminish the burden of cervical cancer in low-and middle-income-countries, acting as a tool against inequity in healthcare.
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
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CO: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data was reported at 13.500 NA in 2016. This records a decrease from the previous number of 13.700 NA for 2015. CO: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data is updated yearly, averaging 15.100 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 18.600 NA in 2000 and a record low of 13.500 NA in 2016. CO: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Colombia – Table CO.World Bank.WDI: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;
Population based cancer incidence rates were abstracted from National Cancer Institute, State Cancer Profiles for all available counties in the United States for which data were available. This is a national county-level database of cancer data that are collected by state public health surveillance systems. All-site cancer is defined as any type of cancer that is captured in the state registry data, though non-melanoma skin cancer is not included. All-site age-adjusted cancer incidence rates were abstracted separately for males and females. County-level annual age-adjusted all-site cancer incidence rates for years 2006–2010 were available for 2687 of 3142 (85.5%) counties in the U.S. Counties for which there are fewer than 16 reported cases in a specific area-sex-race category are suppressed to ensure confidentiality and stability of rate estimates; this accounted for 14 counties in our study. Two states, Kansas and Virginia, do not provide data because of state legislation and regulations which prohibit the release of county level data to outside entities. Data from Michigan does not include cases diagnosed in other states because data exchange agreements prohibit the release of data to third parties. Finally, state data is not available for three states, Minnesota, Ohio, and Washington. The age-adjusted average annual incidence rate for all counties was 453.7 per 100,000 persons. We selected 2006–2010 as it is subsequent in time to the EQI exposure data which was constructed to represent the years 2000–2005. We also gathered data for the three leading causes of cancer for males (lung, prostate, and colorectal) and females (lung, breast, and colorectal). The EQI was used as an exposure metric as an indicator of cumulative environmental exposures at the county-level representing the period 2000 to 2005. A complete description of the datasets used in the EQI are provided in Lobdell et al. and methods used for index construction are described by Messer et al. The EQI was developed for the period 2000– 2005 because it was the time period for which the most recent data were available when index construction was initiated. The EQI includes variables representing each of the environmental domains. The air _domain includes 87 variables representing criteria and hazardous air pollutants. The water _domain includes 80 variables representing overall water quality, general water contamination, recreational water quality, drinking water quality, atmospheric deposition, drought, and chemical contamination. The land _domain includes 26 variables representing agriculture, pesticides, contaminants, facilities, and radon. The built _domain includes 14 variables representing roads, highway/road safety, public transit behavior, business environment, and subsidized housing environment. The sociodemographic environment includes 12 variables representing socioeconomics and crime. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Human health data are not available publicly. EQI data are available at: https://edg.epa.gov/data/Public/ORD/NHEERL/EQI. Format: Data are stored as csv files. This dataset is associated with the following publication: Jagai, J., L. Messer, K. Rappazzo , C. Gray, S. Grabich , and D. Lobdell. County-level environmental quality and associations with cancer incidence#. Cancer. John Wiley & Sons Incorporated, New York, NY, USA, 123(15): 2901-2908, (2017).