VITAL SIGNS INDICATOR Life Expectancy (EQ6)

FULL MEASURE NAME Life Expectancy

LAST UPDATED April 2017

DESCRIPTION Life expectancy refers to the average number of years a newborn is expected to live if mortality patterns remain the same. The measure reflects the mortality rate across a population for a point in time.

DATA SOURCE State of California, Department of Health: Death Records (1990-2013) No link

California Department of Finance: Population Estimates Annual Intercensal Population Estimates (1990-2010) Table P-2: County Population by Age (2010-2013) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/

U.S. Census Bureau: Decennial Census ZCTA Population (2000-2010) http://factfinder.census.gov

U.S. Census Bureau: American Community Survey 5-Year Population Estimates (2013) http://factfinder.census.gov

CONTACT INFORMATION vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator) Life expectancy is commonly used as a measure of the health of a population. Life expectancy does not reflect how long any given individual is expected to live; rather, it is an artificial measure that captures an aspect of the mortality rates across a population that can be compared across time and populations. More information about the determinants of life expectancy that may lead to differences in life expectancy between neighborhoods can be found in the Bay Area Regional Health Inequities Initiative (BARHII) Health Inequities in the Bay Area report at http://www.barhii.org/wp-content/uploads/2015/09/barhii_hiba.pdf. Vital Signs measures life expectancy at birth (as opposed to cohort life expectancy). A statistical model was used to estimate life expectancy for Bay Area counties and ZIP Codes based on current life tables which require both age and mortality data. A life table is a table which shows, for each age, the survivorship of a people from a certain population.

Current life tables were created using death records and population estimates by age. The California Department of Public Health provided death records based on the California death certificate information. Records include age at death and residential ZIP Code. Single-year age population estimates at the regional- and county-level comes from the California Department of Finance population estimates and projections for ages 0-100+. Population estimates for ages 100 and over are aggregated to a single age interval. Using this data, death rates in a population within age groups for a given year are computed to form unabridged life tables (as opposed to abridged life tables). To calculate life expectancy, the probability of dying between the jth and (j+1)st birthday is assumed uniform after age 1. Special consideration is taken to account for infant mortality.

For the ZIP Code-level life expectancy calculation, it is assumed that postal ZIP Codes share the same boundaries as ZIP Code Census Tabulation Areas (ZCTAs). More information on the relationship between ZIP Codes and ZCTAs can be found at http://www.census.gov/geo/reference/zctas.html. ZIP Code-level data uses three years of mortality data to make robust estimates due to small sample size. Year 2013 ZIP Code life expectancy estimates reflects death records from 2011 through 2013. 2013 is the last year with available mortality data. Death records for ZIP Codes with zero population (like those associated with P.O. Boxes) were assigned to the nearest ZIP Code with population. ZIP Code population for 2000 estimates comes from the Decennial Census. ZIP Code population for 2013 estimates are from the American Community Survey (5-Year Average). ACS estimates are adjusted using Decennial Census data for more accurate population estimates. An adjustment factor was calculated using the ratio between the 2010 Decennial Census population estimates and the 2012 ACS 5-Year (with middle year 2010) population estimates. This adjustment factor is particularly important for ZCTAs with high homeless population (not living in group quarters) where the ACS may underestimate the ZCTA population and therefore underestimate the life expectancy. The ACS provides ZIP Code population by age in five-year age intervals. Single-year age population estimates were calculated by distributing population within an age interval to single-year ages using the county distribution. Counties were assigned to ZIP Codes based on majority land-area.

ZIP Codes in the Bay Area vary in population from over 10,000 residents to less than 20 residents. Traditional life expectancy estimation (like the one used for the regional- and county-level Vital Signs estimates) cannot be used because they are highly inaccurate for small populations and may result in over/underestimation of life expectancy. To avoid inaccurate estimates, ZIP Codes with populations of less than 5,000 were aggregated with neighboring ZIP Codes until the merged areas had a population of more than 5,000. ZIP Code 94103, representing Treasure Island, was dropped from the dataset due to its small population and having no bordering ZIP Codes. In this way, the original 305 Bay Area ZIP Codes were reduced to 217 ZIP Code areas for 2013 estimates. Next, a form of Bayesian random-effects analysis was used which established a prior distribution of the probability of death at each age using the regional distribution. This prior is used to shore up the life expectancy calculations where data were sparse.

Healthy life expectancy (HLE), life expectancy (LE), proportion of life spent in "Good" health and ranks for males at females at birth by upper tier local authority (UTLA).

This MSOA atlas provides a summary of demographic and related data for each Middle Super Output Area in Greater London. The average population of an MSOA in London in 2010 was 8,346, compared with 1,722 for an LSOA and 13,078 for a ward.

The profiles are designed to provide an overview of the population in these small areas by combining a range of data on the population, births, deaths, health, housing, crime, commercial property/floorspace, income, poverty, benefits, land use, environment, deprivation, schools, and employment.

If you need to find an MSOA and you know the postcode of the area, the ONS NESS search page has a tool for this.

The MSOA Atlas is available as an XLS as well as being presented using InstantAtlas mapping software. This is a useful tool for displaying a large amount of data for numerous geographies, in one place (requires HTML 5).

CURRENT MSOA BOUNDARIES (2011)

Excel

Instant Atlas

PREVIOUS MSOA BOUNDARIES (2001)

Excel

Instant Atlas

NB. It is currently not possible to export the map as a picture due to a software issue with the Google Maps background. We advise you to print screen to copy an image to the clipboard.

Tips:

1. - Select a new indicator from the Data box on the left. Select the theme, then indicator and then year to show the data.

2. - To view data just for one borough*, use the filter tool.

3. - The legend settings can be altered by clicking on the pencil icon next to the MSOA tick box within the map legend.

4. - The areas can be ranked in order by clicking at the top of the indicator column of the data table.

Themes included here are Census 2011 Population, Mid-year Estimates, Population by Broad Age, Households, Household composition, Ethnic Group, Country of Birth, Language, Religion, Tenure, Dwelling type, Land Area, Population Density, Births, General Fertility Rate, Deaths, Standardised Mortality Ratio (SMR), Population Turnover Rates (per 1000), Crime (numbers), Crime (rates), House Prices, Commercial property (number), Rateable Value (£ per m2), Floorspace; ('000s m2), Household Income, Household Poverty, County Court Judgements (2005), Qualifications, Economic Activity, Employees, Employment, Claimant Count, Pupil Absence, Early Years Foundation Stage, Key Stage 1, GCSE and Equivalent, Health, Air Emissions, Car or Van availability, Income Deprivation, Central Heating, Incidence of Cancer, Life Expectancy, and Road Casualties.

• The London boroughs are: City of London, Barking and Dagenham, Barnet, Bexley, Brent, Bromley, Camden, Croydon, Ealing, Enfield, Greenwich, Hackney, Hammersmith and Fulham, Haringey, Harrow, Havering, Hillingdon, Hounslow, Islington, Kensington and Chelsea, Kingston upon Thames, Lambeth, Lewisham, Merton, Newham, Redbridge, Richmond upon Thames, Southwark, Sutton, Tower Hamlets, Waltham Forest, Wandsworth, Westminster.

These profiles were created using the most up to date information available at the time of collection (Spring 2014).

You may also be interested in LSOA Atlas and Ward Atlas.

• 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.

• 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).

• 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)

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; andunderstand 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)

This file contains the digital vector centroids for the Live Postcodes in the UK as at February 2025.

The centroids are of every live postcode in the United Kingdom

Contains both Ordnance Survey and ONS Intellectual Property Rights.

Date created: Data first uploaded to Open Ottawa on August 11, 2021.Update frequency: Every 4 weeksAccuracy - Points of consideration for interpretation of the data:Data extracted by Ottawa Public Health from COVaxON, the Ontario provincial repository for vaccinations administered in Ontario and to residents of Ontario, using intellihealth Ontario. COVaxON is a dynamic system that allows for continuous updates. Because these data are a snapshot in time and reflect the most accurate information that OPH has at the time of reporting, the data presented may differ from previous and subsequent reports. A vaccinated individual is attributed to an Ottawa Neighbourhood Study (ONS) neighbourhood based on their postal code and, if postal code is missing, on their address, if available. Residents with a postal code that straddles more than one neighbourhood are allocated to neighbourhoods based on the relative size of the population residing in each of the straddled neighbourhoods. If there is no postal code or address information for an individual believed to reside in Ottawa, the resident is not attributed to a neighbourhood. For this reason, the number of first doses administered by neighbourhood does not sum to the total number of first doses administered among all Ottawa residents. In rural settings, the geographic boundaries of postal codes may span multiple health units. Since a client cannot be shared between health units, each postal code is attributed to a specific health unit by the Ministry of Health. This can cause artificially higher or lower vaccination rates in rural neighbourhoods as some non-Ottawa residents will be attributed to rural Ottawa neighbourhoods and some rural Ottawa residents will be attributed to other health units (i.e., excluded from our Ottawa resident counts. For these reasons, we are continuously monitoring and reviewing neighbourhood attributions in rural neighbourhoods using a client’s residential address, when available, and working with neighbouring health units to identify incorrectly attributed clients.Estimates of the number of residents 5 years of age and older (5+) and 18 years of age and older (18+), by ONS neighbourhood, are based on data provided by ICES using the Registered Persons Database (RPDB), which has basic demographic information for anyone who has an Ontario health card number and had contact with the health care system within 9 years or contact within 3 years for individuals 65 years and older. These estimates reflect the neighbourhood populations as of September 1, 2021.Estimation of these neighbourhood populations was provided by the Institute for Clinical Evaluative Sciences (ICES), which is funded by the Ontario Ministry of Health. Parts of this material are based on data and information compiled and provided by Ontario Ministry of Health, the Canadian Institute for Health Information and Public Health Ontario. The analyses, conclusions, opinions and statements expressed herein are solely those of the authors and do not reflect those of ICES, the OHDP, the funding or data sources; no endorsement is intended or should be inferred.The total 2020 5+ and 18+ population for Ottawa is based on the 2020 estimate from the 2016 Canadian Census and was downloaded from IntelliHealth, Ontario Ministry of Health, on November 29, 2021. Because of the different population data sources, neighbourhood populations and vaccinations will not sum to the totals for Ottawa.Rates with smaller populations are less stable and should be interpreted with caution.Attributes - Data fields:ONS_ID: Ottawa Neighbourhood Study neighbourhood ID number ONS_NAME: Ottawa Neighbourhood Study neighbourhood nameICES_POP_5plus: Number of residents 5 years of age or olderNum_dose1: Number of residents 5 years of age or older who have received at least one dose of vaccinePerc_eligible_dose1: Percent of residents 5 years of age or older who have received at least one dose of vaccineNum_fullyvacc: Number of residents 5 years of age or older who are fully vaccinated (i.e., have received two doses of a two-dose series or a single Johnson & Johnson vaccine)Perc_eligible_fullyvacc: Percent of residents 5 years of age or older who are fully vaccinated (i.e., have received two doses of a two-dose series or a single Johnson & Johnson vaccine)ICES_POP_18plus: Number of residents 18 years of age or olderNum_booster: Number of residents 18 years of older who have received a booster dose of vaccine Perc_eligible_boostervacc: Percent of residents 18 years of age or older who have received a booster doseAuthor: OPH Epidemiology Team & Ottawa Neighbourhood Study TeamAuthor email: OPH-Epidemiology@ottawa.caMaintainer Organization: Epidemiology & Evidence, Ottawa Public Health

This dataset presents the footprint of participation statistics in BreastScreen Australia for women ages 50 to 74, by age group. The national breast cancer screening program, BreastScreen Australia began in 1991. It aims to reduce illness and death from breast cancer using screening mammography for early detection of unsuspected breast cancer in women. The data spans the years of 2014-2016 and is aggregated to Statistical Area Level 3 (SA3) geographic boundaries from the 2011 Australian Statistical Geography Standard (ASGS).

Cancer is one of the leading causes of illness and death in Australia. Cancer screening programs aim to reduce the impact of selected cancers by facilitating early detection, intervention and treatment. Australia has three cancer screening programs:

• BreastScreen Australia

• National Cervical Screening Program (NCSP)

• National Bowel Cancer Screening Program (NBCSP)

The National cancer screening programs participation data presents the latest cancer screening participation rates and trends for Australia's 3 national cancer screening programs. The data has been sourced from the Australian Institute of Health and Welfare (AIHW) analysis of National Bowel Cancer Screening Program register data, state and territory BreastScreen Australia register data and state and territory cervical screening register data.

For further information about this dataset, visit the data source:Australian Institute of Health and Welfare - National Cancer Screening Programs Participation Data Tables.

Please note:

• AURIN has spatially enabled the original data.

• Participation rates represent the percentage of women in the population aged 50-74 screened by BreastScreen Australia over 2 calendar years. The population denominator was the average of the Australian Bureau of Statistics (ABS) Estimated Resident Population (ERP) for females aged 50-74 within the relevant geographical area for the relevant 2-year reporting period.

• An SA3 was assigned to women using a postcode to SA3 correspondence. Because these are based only on postcode, these data will be less accurate than those published by individual states and territories.

• Some postcodes (and hence women) cannot be attributed to an SA3 and therefore these women were excluded from the analysis. This is most noticeable in the Northern Territory but affects all states and territories to some degree.

• SA3s with a numerator less than 20 or a denominator less than 100 have been suppressed.

• SA3 data for the Blue Mountains - South, Christmas Island, Cocos (Keeling) Islands, Cotter - Namadgi, Fyshwick - Piallago - Hume, Illawarra Catchment Reserve, Jervis Bay, and Lord Howe Island were excluded due to reliability concerns from low numbers in these regions.

• Totals may not sum due to rounding.

• BreastScreen Australia changed its target age group from 50-69 years to 50-74 years from July 2013; participation is reported for both the previous and current target age groups to allow comparison of trends with previously reported data.

• Data are preliminary and subject to change.

• The 2014-2015 period covers 1 January 2014 to 31 December 2015, and the the 2015-2016 period covers 1 January 2015 to 31 December 2016.

Abstract copyright UK Data Service and data collection copyright owner.

The Scottish Health Survey (SHeS) series was established in 1995. Commissioned by the Scottish Government Health Directorates, the series provides regular information on aspects of the public's health and factors related to health which cannot be obtained from other sources. The SHeS series was designed to:

• estimate the prevalence of particular health conditions in Scotland;
• estimate the prevalence of certain risk factors associated with these health conditions and to document the pattern of related health behaviours;
• look at differences between regions and between subgroups of the population in the extent of their having these particular health conditions or risk factors, and to make comparisons with other national statistics for Scotland and England;
• monitor trends in the population's health over time;
• make a major contribution to monitoring progress towards health targets.

Each survey in the series includes a set of core questions and measurements (height and weight and, if applicable, blood pressure, waist circumference, urine and saliva samples), plus modules of questions on specific health conditions that vary from year to year. Each year the core sample has also been augmented by an additional boosted sample for children. Since 2008 NHS Health Boards have also had the opportunity to boost the number of adult interviews carried out in their area.

The Scottish Government Scottish Health Survey webpages contain further information about the series, including latest news and publications.

The Scottish Health Survey, 2009 was designed to provide data at a national level about the population living in private households in Scotland. The sample for the 2009 survey, as in previous years, was drawn from the Postcode Address File (PAF). An initial sample of 12,668 addresses was selected and grouped into 503 interviewer batches, with around 45 batches covered each month between January and December 2009. The addresses were comprised three sample types:

• 7,588 formed the main sample, at which adults and children were eligible to be selected for interview
• 4,312 addresses formed an additional child boost sample at which only households containing children aged 0-15 were eligible to participate
• 768 addresses (in Grampian, Fife and Borders) formed the Health Board boost sample, at which only adults were eligible for interview.

Latest edition information

For the sixth edition (July 2021) OECD equivalised income derived variables were added to the individual file. The new variables are: OECD (OECD household score for equivalised income); eqvinc_15 (Equivalised income - OECD score); eqv5_15 (Equivalised Income Quintiles); and eqv10_15 (Equivalised Income Deciles).

Main Topics:

The questionnaire covered: general health, cardio-vascular disease and use of health services, accidents, physical activity, eating habits, fruit and vegetable consumption, smoking and drinking, dental health, dental services, social capital, discrimination and harassment, employment status, stress at work, educational background, national identity, ethnic background, religion, parental social class and health history, and body measurements. Some participants also answered attitudinal questions about their own health.

The nurse visit covered: prescribed medicines, vitamin supplements, nicotine replacement therapy, blood pressure, anxiety, self-harm, food poisoning, waist and hip circumference, demi-span (65+), lung function, blood sample, saliva sample and urine sample.