Social deprivation indices calculated using the 2020 5-year American Community Survey at the county level.

Abstract

Six social deprivation and vulnerability indices (SVI, SDI, NSS7, FDep, ICE) were calculated using the the US Census 2020 5-year American Community Survey data at the census block group, census tract and county geographical levels.

Methodology

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Census Lower Super Output Area boundaries as of 2011, with indices of multiple deprivation statistics (2019)

Publicly available geocoded social determinants of health and mobility datasets used in the analysis of "Chronic Acid Suppression and Social Determinants of COVID-19 Infection".These datasets are required for the analytical workflow shared on Github which demonstrates how the analysis in the manuscript was done using randomly generated samples to protect patient privacy.zcta_county_rel_10.txt - Population and housing density from the 2010 decennial census. Obtained from: https://www2.census.gov/geo/docs/maps-data/data/rel/zcta_county_rel_10.txtcre-2018-a11.csv - Community Resilience Estimates which is is the capacity of individuals and households to absorb, endure, and recover from the health, social, and economic impacts of a disaster such as a hurricane or pandemic. Data obtained from: https://www.census.gov/data/experimental-data-products/community-resilience-estimates.htmlzcta_tract_rel_10.txt - Relationship between ZCTA and US Census tracts (used to map census tracts to ZCTA). Data obtained from: https://www.census.gov/geographies/reference-files/time-series/geo/relationship-files.html#par_textimage_674173622mask-use-by-county.txt - Mask Use By County comes from a large number of interviews conducted online by the global data and survey firm Dynata at the request of The New York Times. The firm asked a question about mask use to obtain 250,000 survey responses between July 2 and July 14, enough data to provide estimates more detailed than the state level. Data obtained from: https://github.com/nytimes/covid-19-data/tree/master/mask-usemobility_report_US.txt - Google mobility report which charts movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential. Data obtained from: https://github.com/ActiveConclusion/COVID19_mobility/blob/master/google_reports/mobility_report_US.csvACS2015_zctaallvars.csv - Social Deprivation Index is a composite measure of area level deprivation based on seven demographic characteristics collected in the American Community Survey (https://www.census.gov/programs-surveys/acs/) and used to quantify the socio-economic variation in health outcomes. Factors are: Income, Education, Employment, Housing, Household Characteristics, Transportation, Demographics. Data obtained from: https://www.graham-center.org/rgc/maps-data-tools/sdi/social-deprivation-index.html

ObjectiveWest Virginia’s (WV) suicide rate is 50% higher than the national average and is the highest in the Appalachian Region. Appalachia has several social factors that have contributed to greater socioeconomic deprivation, a known contributor of suicide. Given WV’s high prevalence of suicide and poverty, the current study aims to examine the relationship between socioeconomic deprivation and suicide rates in WV.MethodsThe Townsend Deprivation Index (TDI), Social Deprivation Index (SDI), and Social Vulnerability Index (SVI) measured socioeconomic deprivation. Negative binomial regression models assessed the relationship between socioeconomic deprivation scores, individual index items, and suicide rates. Model comparisons evaluated the indices’ ability to assess suicide rates. A backward selection strategy identified additional key items for examining suicide rates.ResultsThere was a significant increase in suicide rates for every 10% increase in TDI (β = 0.04; p < 0.01), SDI (β = 0.03; p = 0.04), and SVI scores (β = 0.05; p < 0.01). Household overcrowding and unemployment had a positive linear relationship with suicide in TDI (β = 0.04, p = 0.02; β = 0.07, p = 0.01), SDI (β = 0.10, p = 0.02; β = 0.01, p

Summary statistics from Indices of Multiple Deprivation (IMD). The spreadsheet includes borough data from 2000, 2004 and 2007.

The latest Indices of Deprivation data for 2010 can be found here.

The Index of Multiple Deprivation 2007 combines a number of indicators, chosen to cover a range of economic, social and housing issues, into a single deprivation score for each small area in England. This allows each area to be ranked relative to one another according to their level of deprivation.

Local Concentration is the population weighted average of the ranks of a district’s most deprived LSOAs that contain exactly 10% of the local authority district’s population.

Extent is the proportion of a local authority district’s population living in the most deprived LSOAs in the country.

Income Scale is the number of people who are Income deprived.

Employment Scale is the number of people who are Employment deprived.

Average of LSOA Ranks is the population weighted average of the combined ranks for the LSOAs in a local authority district.

Abstract copyright UK Data Service and data collection copyright owner.

The English Longitudinal Study of Ageing (ELSA) study is a longitudinal survey of ageing and quality of life among older people that explores the dynamic relationships between health and functioning, social networks and participation, and economic position as people plan for, move into and progress beyond retirement. The main objectives of ELSA are to:

• construct waves of accessible and well-documented panel data;
• provide these data in a convenient and timely fashion to the scientific and policy research community;
• describe health trajectories, disability and healthy life expectancy in a representative sample of the English population aged 50 and over;
• examine the relationship between economic position and health;
• investigate the determinants of economic position in older age;
• describe the timing of retirement and post-retirement labour market activity; and
• understand the relationships between social support, household structure and the transfer of assets.

Further information may be found on the the ELSA project website or the Natcen Social Research: ELSA web pages.

Health conditions research with ELSA - June 2021

The ELSA Data team have found some issues with historical data measuring health conditions. If you are intending to do any analysis looking at the following health conditions, then please contact elsadata@natcen.ac.uk for advice on how you should approach your analysis. The affected conditions are: eye conditions (glaucoma; diabetic eye disease; macular degeneration; cataract), CVD conditions (high blood pressure; angina; heart attack; Congestive Heart Failure; heart murmur; abnormal heart rhythm; diabetes; stroke; high cholesterol; other heart trouble) and chronic health conditions (chronic lung disease; asthma; arthritis; osteoporosis; cancer; Parkinson's Disease; emotional, nervous or psychiatric problems; Alzheimer's Disease; dementia; malignant blood disorder; multiple sclerosis or motor neurone disease).

Secure Access Data:Secure Access versions of ELSA have more restrictive access conditions than versions available under the standard End User Licence or Special Licence (see 'Access' section below).
Secure Access versions of ELSA include:

• Primary Data from Wave 8 onwards (SN 8444) includes all the variables in the SL primary dataset (SN 8346) as well as day of birth, combined SIC 2003 code (5 digit), combined SOC 2000 code (4 digit), NS-SEC long version including and excluding unclassifiable and non-workers.
• Pension Age Data from Wave 8 onwards (SN 8445) includes all the variables in the SL pension age data (SN 8375) as well as year reached pension age variable.
• Detailed geographical identifier files for each wave, grouped by identifier held under SN 8423 (Index of Multiple Deprivation Score), SN 8424 (Local Authority District Pre-2009 Boundaries), SN 8438 (Local Authority District Post-2009 Boundaries), SN 8425 (Census 2001 Lower Layer Super Output Areas), SN 8434 (Census 2011 Lower Layer Super Output Areas), SN 8426(Census 2001 Middle Layer Super Output Areas), SN 8435 (Census 2011 Middle Layer Super Output Areas), SN 8427 (Population Density for Postcode Sectors), SN 8428 (Census 2001 Rural-Urban Indicators), SN 8436 (Census 2011 Rural-Urban Indicators).

Where boundary changes have occurred, the geographic identifier has been split into two separate studies to reduce the risk of disclosure. Users are also only allowed one version of each identifier:

• either SN 8424 (Local Authority District Pre-2009 Boundaries) or SN 8438 (Local Authority District Post-2009 Boundaries)
• either SN 8425 (Census 2001 Lower Layer Super Output Areas) or SN 8434 (Census 2011 Lower Layer Super Output Areas)
• either SN 8426 (Census 2001 Middle Layer Super Output Areas) or SN 8435 (Census 2011 Middle Layer Super Output Areas)
• either SN 8428 (Census 2001 Rural-Urban Indicators) or SN 8436 (Census 2011 Rural-Urban Indicators)

English Longitudinal Study of Ageing: Waves 1-10, 2002-2023: Index of Multiple Deprivation Score: Secure Access
This dataset contains an Index of Multiple Deprivation Score variable for each Wave of ELSA to date, and a unique individual serial number variable is also included for matching to the main data files. These data have more restrictive access conditions than those available under the standard End User Licence or Special Licence (see 'Access' section).

Latest edition information
For the second edition (October 2024), data for waves 9 and 10 have been added to the study and data for waves 1 to 8 have been updated.

Main Topics:

This dataset contains an Index of Multiple Deprivation Score variable for each Wave of ELSA to date, as well as a unique individual serial...

This dataset contains a summary measure of the Index of Multiple Deprivation 2010 at local authority district level. It puts the 326 Local Authority Districts into a rank order based the population weighted average rank of all LSOAs in the LAD. A rank of 1 is the most deprived.

Descriptive statistics of county suicide, index scores, and index items.

These indicators are designed to accompany the SHMI publication. The SHMI methodology does not make any adjustment for deprivation. This is because adjusting for deprivation might create the impression that a higher death rate for those who are more deprived is acceptable. Patient records are assigned to 1 of 5 deprivation groups (called quintiles) using the Index of Multiple Deprivation (IMD). The deprivation quintile cannot be calculated for some records e.g. because the patient's postcode is unknown or they are not resident in England. Contextual indicators on the percentage of provider spells and deaths reported in the SHMI belonging to each deprivation quintile are produced to support the interpretation of the SHMI. Notes: 1. There is a shortfall in the number of records for East Lancashire Hospitals NHS Trust (trust code RXR), Harrogate and District NHS Foundation Trust (trust code RCD), and Northern Lincolnshire and Goole NHS Foundation Trust (trust code RJL). Values for these trusts are based on incomplete data and should therefore be interpreted with caution. 2. Data for Royal Surrey County Hospital NHS Foundation Trust (trust code RA2) has been suppressed from publication. This trust had submitted in error a high percentage of records with no secondary care diagnosis codes, this has made their SHMI values highly misleading. 3. A number of trusts are now submitting Same Day Emergency Care (SDEC) data to the Emergency Care Data Set (ECDS) rather than the Admitted Patient Care (APC) dataset. The SHMI is calculated using APC data. Removal of SDEC activity from the APC data may impact a trust’s SHMI value and may increase it. More information about this is available in the SHMI background quality report. 4. Further information on data quality can be found in the SHMI background quality report, which can be downloaded from the 'Resources' section of this page.

Abstract copyright UK Data Service and data collection copyright owner.

The English Longitudinal Study of Ageing (ELSA) study is a longitudinal survey of ageing and quality of life among older people that explores the dynamic relationships between health and functioning, social networks and participation, and economic position as people plan for, move into and progress beyond retirement. The main objectives of ELSA are to:

• construct waves of accessible and well-documented panel data;
• provide these data in a convenient and timely fashion to the scientific and policy research community;
• describe health trajectories, disability and healthy life expectancy in a representative sample of the English population aged 50 and over;
• examine the relationship between economic position and health;
• investigate the determinants of economic position in older age;
• describe the timing of retirement and post-retirement labour market activity; and
• understand the relationships between social support, household structure and the transfer of assets.

Further information may be found on the the ELSA project website or the Natcen Social Research: ELSA web pages.

Health conditions research with ELSA - June 2021

The ELSA Data team have found some issues with historical data measuring health conditions. If you are intending to do any analysis looking at the following health conditions, then please contact elsadata@natcen.ac.uk for advice on how you should approach your analysis. The affected conditions are: eye conditions (glaucoma; diabetic eye disease; macular degeneration; cataract), CVD conditions (high blood pressure; angina; heart attack; Congestive Heart Failure; heart murmur; abnormal heart rhythm; diabetes; stroke; high cholesterol; other heart trouble) and chronic health conditions (chronic lung disease; asthma; arthritis; osteoporosis; cancer; Parkinson's Disease; emotional, nervous or psychiatric problems; Alzheimer's Disease; dementia; malignant blood disorder; multiple sclerosis or motor neurone disease).

Secure Access Data:Secure Access versions of ELSA have more restrictive access conditions than versions available under the standard End User Licence or Special Licence (see 'Access' section below).
Secure Access versions of ELSA include:

• Primary Data from Wave 8 onwards (SN 8444) includes all the variables in the SL primary dataset (SN 8346) as well as day of birth, combined SIC 2003 code (5 digit), combined SOC 2000 code (4 digit), NS-SEC long version including and excluding unclassifiable and non-workers.
• Pension Age Data from Wave 8 onwards (SN 8445) includes all the variables in the SL pension age data (SN 8375) as well as year reached pension age variable.
• Detailed geographical identifier files for each wave, grouped by identifier held under SN 8423 (Index of Multiple Deprivation Score), SN 8424 (Local Authority District Pre-2009 Boundaries), SN 8438 (Local Authority District Post-2009 Boundaries), SN 8425 (Census 2001 Lower Layer Super Output Areas), SN 8434 (Census 2011 Lower Layer Super Output Areas), SN 8426(Census 2001 Middle Layer Super Output Areas), SN 8435 (Census 2011 Middle Layer Super Output Areas), SN 8427 (Population Density for Postcode Sectors), SN 8428 (Census 2001 Rural-Urban Indicators), SN 8436 (Census 2011 Rural-Urban Indicators).

Where boundary changes have occurred, the geographic identifier has been split into two separate studies to reduce the risk of disclosure. Users are also only allowed one version of each identifier:

• either SN 8424 (Local Authority District Pre-2009 Boundaries) or SN 8438 (Local Authority District Post-2009 Boundaries)
• either SN 8425 (Census 2001 Lower Layer Super Output Areas) or SN 8434 (Census 2011 Lower Layer Super Output Areas)
• either SN 8426 (Census 2001 Middle Layer Super Output Areas) or SN 8435 (Census 2011 Middle Layer Super Output Areas)
• either SN 8428 (Census 2001 Rural-Urban Indicators) or SN 8436 (Census 2011 Rural-Urban Indicators)

English Longitudinal Study of Ageing: Waves 1-10, 2002-2023: Census 2001 Lower Layer Super Output Areas: Secure Access
This dataset contains a Census 2001 Lower Layer Super Output Area variable for each Wave of ELSA to date, and a unique individual serial number variable is also included for matching to the main data files. These data have more restrictive access conditions than those available under the standard End User Licence or Special Licence (see 'Access' section).

Latest edition information
For the second edition (October 2024), data for waves 9 and 10 have been added to the study and data for waves 1 to 8 have been updated.

Main Topics:

This dataset contains a Census 2001 Lower Layer Super Output Area variable for each Wave of ELSA to date, as well as an unique...

Abstract copyright UK Data Service and data collection copyright owner.

The English Longitudinal Study of Ageing (ELSA) study is a longitudinal survey of ageing and quality of life among older people that explores the dynamic relationships between health and functioning, social networks and participation, and economic position as people plan for, move into and progress beyond retirement. The main objectives of ELSA are to:

• construct waves of accessible and well-documented panel data;
• provide these data in a convenient and timely fashion to the scientific and policy research community;
• describe health trajectories, disability and healthy life expectancy in a representative sample of the English population aged 50 and over;
• examine the relationship between economic position and health;
• investigate the determinants of economic position in older age;
• describe the timing of retirement and post-retirement labour market activity; and
• understand the relationships between social support, household structure and the transfer of assets.

Further information may be found on the the ELSA project website or the Natcen Social Research: ELSA web pages.

Health conditions research with ELSA - June 2021

The ELSA Data team have found some issues with historical data measuring health conditions. If you are intending to do any analysis looking at the following health conditions, then please contact elsadata@natcen.ac.uk for advice on how you should approach your analysis. The affected conditions are: eye conditions (glaucoma; diabetic eye disease; macular degeneration; cataract), CVD conditions (high blood pressure; angina; heart attack; Congestive Heart Failure; heart murmur; abnormal heart rhythm; diabetes; stroke; high cholesterol; other heart trouble) and chronic health conditions (chronic lung disease; asthma; arthritis; osteoporosis; cancer; Parkinson's Disease; emotional, nervous or psychiatric problems; Alzheimer's Disease; dementia; malignant blood disorder; multiple sclerosis or motor neurone disease).

Secure Access Data:Secure Access versions of ELSA have more restrictive access conditions than versions available under the standard End User Licence or Special Licence (see 'Access' section below).
Secure Access versions of ELSA include:

• Primary Data from Wave 8 onwards (SN 8444) includes all the variables in the SL primary dataset (SN 8346) as well as day of birth, combined SIC 2003 code (5 digit), combined SOC 2000 code (4 digit), NS-SEC long version including and excluding unclassifiable and non-workers.
• Pension Age Data from Wave 8 onwards (SN 8445) includes all the variables in the SL pension age data (SN 8375) as well as year reached pension age variable.
• Detailed geographical identifier files for each wave, grouped by identifier held under SN 8423 (Index of Multiple Deprivation Score), SN 8424 (Local Authority District Pre-2009 Boundaries), SN 8438 (Local Authority District Post-2009 Boundaries), SN 8425 (Census 2001 Lower Layer Super Output Areas), SN 8434 (Census 2011 Lower Layer Super Output Areas), SN 8426(Census 2001 Middle Layer Super Output Areas), SN 8435 (Census 2011 Middle Layer Super Output Areas), SN 8427 (Population Density for Postcode Sectors), SN 8428 (Census 2001 Rural-Urban Indicators), SN 8436 (Census 2011 Rural-Urban Indicators).

Where boundary changes have occurred, the geographic identifier has been split into two separate studies to reduce the risk of disclosure. Users are also only allowed one version of each identifier:

• either SN 8424 (Local Authority District Pre-2009 Boundaries) or SN 8438 (Local Authority District Post-2009 Boundaries)
• either SN 8425 (Census 2001 Lower Layer Super Output Areas) or SN 8434 (Census 2011 Lower Layer Super Output Areas)
• either SN 8426 (Census 2001 Middle Layer Super Output Areas) or SN 8435 (Census 2011 Middle Layer Super Output Areas)
• either SN 8428 (Census 2001 Rural-Urban Indicators) or SN 8436 (Census 2011 Rural-Urban Indicators)

English Longitudinal Study of Ageing: Waves 1-10, 2002-2023: Census 2001 Rural-Urban Indicators: Secure Access
This dataset contains a Census 2001 Rural-Urban Indicator variable for each Wave of ELSA to date, and an unique individual serial number variable is also included for matching to the main data files. These data have more restrictive access conditions than those available under the standard End User Licence or Special Licence (see 'Access' section).

Latest edition information
For the second edition (October 2024), data for waves 9 and 10 have been added to the study and data for waves 1 to 8 have been updated. An Excel Data Dictionary has also been added.

Main Topics:

This dataset contains a Census 2001 Rural-Urban Indicator variable for...

These indicators are designed to accompany the SHMI publication. This publication was updated on 9th August 2024. Data for Royal Surrey County Hospital NHS Foundation Trust (trust code RA2) has been suppressed from publication. This trust had submitted in error a high percentage of records with no secondary care diagnosis codes, this has made their SHMI values highly misleading. They have corrected the data at source, and this is expected to be reflected in the November SHMI publication. The SHMI methodology does not make any adjustment for deprivation. This is because adjusting for deprivation might create the impression that a higher death rate for those who are more deprived is acceptable. Patient records are assigned to 1 of 5 deprivation groups (called quintiles) using the Index of Multiple Deprivation (IMD). The deprivation quintile cannot be calculated for some records e.g. because the patient's postcode is unknown or they are not resident in England. Contextual indicators on the percentage of provider spells and deaths reported in the SHMI belonging to each deprivation quintile are produced to support the interpretation of the SHMI. Notes: 1. Data for Royal Surrey County Hospital NHS Foundation Trust (trust code RA2) has been suppressed from publication. This trust had submitted in error a high percentage of records with no secondary care diagnosis codes, this has made their SHMI values highly misleading. 2. There is a shortfall in the number of records for East Lancashire Hospitals NHS Trust (trust code RXR), Harrogate and District NHS Foundation Trust (trust code RCD), and Northern Lincolnshire and Goole NHS Foundation Trust (trust code RJL). Values for these trusts are based on incomplete data and should therefore be interpreted with caution. 3. Guy’s and St Thomas’ NHS Foundation Trust (trust code RJ1) has a high percentage of records with missing data for the Sex field. Values for this trust should therefore be interpreted with caution. 4. A number of trusts are now submitting Same Day Emergency Care (SDEC) data to the Emergency Care Data Set (ECDS) rather than the Admitted Patient Care (APC) dataset. The SHMI is calculated using APC data. Removal of SDEC activity from the APC data may impact a trust’s SHMI value and may increase it. More information about this is available in the SHMI background quality report. 5. Further information on data quality can be found in the SHMI background quality report, which can be downloaded from the 'Resources' section of this page.

Abstract copyright UK Data Service and data collection copyright owner.

The English Longitudinal Study of Ageing (ELSA) study is a longitudinal survey of ageing and quality of life among older people that explores the dynamic relationships between health and functioning, social networks and participation, and economic position as people plan for, move into and progress beyond retirement. The main objectives of ELSA are to:

• construct waves of accessible and well-documented panel data;
• provide these data in a convenient and timely fashion to the scientific and policy research community;
• describe health trajectories, disability and healthy life expectancy in a representative sample of the English population aged 50 and over;
• examine the relationship between economic position and health;
• investigate the determinants of economic position in older age;
• describe the timing of retirement and post-retirement labour market activity; and
• understand the relationships between social support, household structure and the transfer of assets.

Further information may be found on the the ELSA project website or the Natcen Social Research: ELSA web pages.

Health conditions research with ELSA - June 2021

The ELSA Data team have found some issues with historical data measuring health conditions. If you are intending to do any analysis looking at the following health conditions, then please contact elsadata@natcen.ac.uk for advice on how you should approach your analysis. The affected conditions are: eye conditions (glaucoma; diabetic eye disease; macular degeneration; cataract), CVD conditions (high blood pressure; angina; heart attack; Congestive Heart Failure; heart murmur; abnormal heart rhythm; diabetes; stroke; high cholesterol; other heart trouble) and chronic health conditions (chronic lung disease; asthma; arthritis; osteoporosis; cancer; Parkinson's Disease; emotional, nervous or psychiatric problems; Alzheimer's Disease; dementia; malignant blood disorder; multiple sclerosis or motor neurone disease).

Secure Access Data:Secure Access versions of ELSA have more restrictive access conditions than versions available under the standard End User Licence or Special Licence (see 'Access' section below).
Secure Access versions of ELSA include:

• Primary Data from Wave 8 onwards (SN 8444) includes all the variables in the SL primary dataset (SN 8346) as well as day of birth, combined SIC 2003 code (5 digit), combined SOC 2000 code (4 digit), NS-SEC long version including and excluding unclassifiable and non-workers.
• Pension Age Data from Wave 8 onwards (SN 8445) includes all the variables in the SL pension age data (SN 8375) as well as year reached pension age variable.
• Detailed geographical identifier files for each wave, grouped by identifier held under SN 8423 (Index of Multiple Deprivation Score), SN 8424 (Local Authority District Pre-2009 Boundaries), SN 8438 (Local Authority District Post-2009 Boundaries), SN 8425 (Census 2001 Lower Layer Super Output Areas), SN 8434 (Census 2011 Lower Layer Super Output Areas), SN 8426(Census 2001 Middle Layer Super Output Areas), SN 8435 (Census 2011 Middle Layer Super Output Areas), SN 8427 (Population Density for Postcode Sectors), SN 8428 (Census 2001 Rural-Urban Indicators), SN 8436 (Census 2011 Rural-Urban Indicators).

Where boundary changes have occurred, the geographic identifier has been split into two separate studies to reduce the risk of disclosure. Users are also only allowed one version of each identifier:

• either SN 8424 (Local Authority District Pre-2009 Boundaries) or SN 8438 (Local Authority District Post-2009 Boundaries)
• either SN 8425 (Census 2001 Lower Layer Super Output Areas) or SN 8434 (Census 2011 Lower Layer Super Output Areas)
• either SN 8426 (Census 2001 Middle Layer Super Output Areas) or SN 8435 (Census 2011 Middle Layer Super Output Areas)
• either SN 8428 (Census 2001 Rural-Urban Indicators) or SN 8436 (Census 2011 Rural-Urban Indicators)

English Longitudinal Study of Ageing: Waves 1-10, 2002-2023: Local Authority District Pre-2009 Boundaries: Secure Access
This dataset contains a pre-2009 boundary Local Authority District variable for each Wave of ELSA to date, and a unique individual serial number variable is also included for matching to the main data files. These data have more restrictive access conditions than those available under the standard End User Licence or Special Licence (see 'Access' section).

Latest edition information
For the second edition (October 2024), data for waves 9 and 10 have been added to the study and data for waves 1 to 8 have been updated. An Excel Data Dictionary has also been added.

Main Topics:

This dataset contains a pre-2009 boundary Local Authority District variable...

Results from backward selection strategy: Social Vulnerability Index items.

The data consists of variables that assess the relationship between the county-level measure of SDoH and county-level fatal crash counts among geriatric and non-geriatric road users. We pooled data from the Fatality Analysis Reporting System and limited our analyses to the 3,108 contiguous US counties. The outcome measures were county-level fatal crash counts involving (1) geriatric (65 years and older) road users, (2) non-geriatric road users, and (3) the general population. The predictor variable was the Multidimensional Deprivation Index (MDI), a three-level categorical variable defined as: very highly deprived, highly deprived, and average-to-low deprivation.

Individual index items: Negative binomial regression results.