In 2022, the life expectancy for men in London fell to 79.1 years, compared with 80.4 years in 2019, while for women, life expectancy fell from 84.4 years to 83.6 years in the same period. Compared with 1991/93, life expectancy in London has increased by 4.3 years for women, and 5.8 years for men.

This dataset was scraped from London data website. Life expectancy at birth and age 65 by sex. Data for 2000-2002 to 2008-2010 revised on 24 July 2013. Local authorities based on boundaries as of 20...

Life expectancy in the United Kingdom was below 39 years in the year 1765, and over the course of the next two and a half centuries, it is expected to have increased by more than double, to 81.1 by the year 2020. Although life expectancy has generally increased throughout the UK's history, there were several times where the rate deviated from its previous trajectory. These changes were the result of smallpox epidemics in the late eighteenth and early nineteenth centuries, new sanitary and medical advancements throughout time (such as compulsory vaccination), and the First world War and Spanish Flu epidemic in the 1910s.

Between 2021 and 2023, London was the region of the United Kingdom that had the highest average life expectancy for females, at ***** years, while South East England had the highest life expectancy for males at ***** years. By comparison, Scotland had the lowest life expectancy, at ***** for males and ***** for females.

Between 2021 and 2023, life expectancy for women in the United Kingdom was highest in the London borough of Kensington and Chelsea, at 86.46 years, while for men it was highest in Hart, at 83.44.

This series has been discontinued. Life expectancy at birth and age 65 by sex and ward, London borough, region, 1999/03 - 2010/14. The population data used is revised 2002-2010 ONS mid year estimates (MYE) - revised post 2011 Census. Revised population estimates by single year of age for wards can also be found on the ONS website for 2002-2010, 2011, 2012, and 2013. These figures are consistent with the published revised mid-2002 to mid-2010 local authority estimates. Rolling 5-year combined life expectancies are used for wards to reduce the effects of the variability in number of deaths in each year. The same method is applied to higher geographies to enable meaningful comparisons. However, 3-year combined expectancies are published separately on the Datastore for geographical areas that are local authority and above. If the GLA publish revised 2002-2010 population data for wards then these life expectancy figures will also be revised to reflect them. The ONS vital statistics mortality data breaks deaths into 10 year age bands. 5 year age band deaths were modelled using this data. Vital Statistics: Population and Health Reference Tables are available on the ONS website here. The tool for calculating life expectancy is available from Public Health England. The highest age band in the calculator is currently 85+. If the tool is updated with a higher upper age band (ie 90+), this data will be revised to reflect this change. Healthy life expectancy and disability-free life expectancy (1999-2003) at birth have been calculated for wards in England and Wales. These can be found on the ONS website. This data is also presented in the GLA ward profiles.

Period life expectancy for single-year periods, at birth and other age groups at regional and local authority levels in selected constituent countries.

It is only in the past two centuries where demographics and the development of human populations has emerged as a subject in its own right, as industrialization and improvements in medicine gave way to exponential growth of the world's population. There are very few known demographic studies conducted before the 1800s, which means that modern scholars have had to use a variety of documents from centuries gone by, along with archeological and anthropological studies, to try and gain a better understanding of the world's demographic development. Genealogical records One such method is the study of genealogical records from the past; luckily, there are many genealogies relating to European families that date back as far as medieval times. Unfortunately, however, all of these studies relate to families in the upper and elite classes; this is not entirely representative of the overall population as these families had a much higher standard of living and were less susceptible to famine or malnutrition than the average person (although elites were more likely to die during times of war). Nonetheless, there is much to be learned from this data. Impact of the Black Death In the centuries between 1200 and 1745, English male aristocrats who made it to their 21st birthday were generally expected to live to an age between 62 and 72 years old. The only century where life expectancy among this group was much lower was in the 1300s, where the Black Death caused life expectancy among adult English noblemen to drop to just 45 years. Experts assume that the pre-plague population of England was somewhere between four and seven million people in the thirteenth century, and just two million in the fourteenth century, meaning that Britain lost at least half of its population due to the plague. Although the plague only peaked in England for approximately eighteen months, between 1348 and 1350, it devastated the entire population, and further outbreaks in the following decades caused life expectancy in the decade to drop further. The bubonic plague did return to England sporadically until the mid-seventeenth century, although life expectancy among English male aristocrats rose again in the centuries following the worst outbreak, and even peaked at more than 71 years in the first half of the sixteenth century.

The Mayors Health Inequalities Strategy sets out his plans to tackle unfair differences in health to make London a healthier, fairer city. This dataset reports the 14 headline population health indicators that will be used to monitor London’s progress in reducing health inequalities over the next ten years. The themes of the indicators are listed below. The measures will monitor an identified inequality gap between defined populations. Healthy life expectancy at birth – male Healthy life expectancy at birth – female Children born with low birth weight School readiness among children Excess weight in children at age 10-11 (year 6) Excess mortality in adults with serious mental illness Suicide Mortality caused by Particulate Matter (PM2.5) Employment Feeling of belonging to a community (provisional) HIV late diagnosis People diagnosed with TB Adults walking or cycling for two periods of ten minutes each day Smoking

This slide set is an analysis intended to inform Camden and Islington Public Health team and Clinical Commissioning Groups about causes of death contributing to changes in the life expectancy gap over time. Specifically, this analysis shows how the gap in life expectancy between the most and least deprived areas have changed over time in Camden and Islington, and explores what causes of death are contributing to these changes

This slide deck includes a short briefing which summarises key findings from the full analysis ‘Health inequality:’ Closing the life expectancy gap over time?’ for both Camden and Islington.

This dataset comprises enumerations relating to London burials (and baptisms) transcribed from 9,950 extant Weekly Bills of Mortality from 1644 to 1849. Each Bill comprises four main sections containing different types of information for that week: 1) counts - the number of persons buried, dying of plague or christened weekly in each parish from 1644 to 1849. 2) ages - the number of dead persons in all parishes together in each of circa twelve age groups weekly from 1729 to 1849. 3) cods - the number of dead persons in all parishes together ascribed to particular causes of death, ie each 'disease or casualty', weekly from 1644 to 1845. 4) bread - the weight of bread of several types sold at a standard price in London, weekly from 1644 to 1815.

These weekly data on London burials, baptisms, causes of death and bread prices were compiled as part of a research programme exploring long-run changes in England's mortality regime. Today, life expectancy is higher in urban rather than rural areas, but early modern towns and cities were demographic sinks with extraordinarily high mortality, especially among the young and migrants who were essential for city growth. The project investigated how and when cities transformed from urban graveyards into promoters of health between 1600 and 1945. The process of endemicisation and exogenous disease variation is key to the evolution of both urban and non-urban mortality regimes, especially with respect to: infectious diseases among the young, maternal health and adult migrants and their health/immunological status.

In 2023, the life expectancy at birth for women born in the UK was 82.77 years, compared with 78.82 years for men. By age 65 men had a life expectancy of 18.51 years, compared with 20.96 years for women.

BackgroundAs the average life expectancy increases, more people are predicted to have strokes. Recent studies have shown an increasing incidence in certain types of cerebral infarction. We aimed to estimate time trends in incidence, prior risk factors, and use of preventive treatments for ischaemic stroke (IS) aetiological subtypes and to ascertain any demographic disparities.Methods and findingsPopulation-based data from the South London Stroke Register (SLSR) between 2000 and 2015 were studied. IS was classified, based on the underlying mechanism, into large-artery atherosclerosis (LAA), cardio-embolism (CE), small-vessel occlusion (SVO), other determined aetiologies (OTH), and undetermined aetiologies (UND). After calculation of age-, sex-, and ethnicity-specific incidence rates by subtype for the 16-year period, we analysed trends using Cochran-Armitage tests, Poisson regression models, and locally estimated scatterplot smoothers (loess). A total of 3,088 patients with first IS were registered. Between 2000–2003 and 2012–2015, the age-adjusted incidence of IS decreased by 43% from 137.3 to 78.4/100,000/year (incidence rate ratio [IRR] 0.57, 95% CI 0.5–0.64). Significant declines were observed in all subtypes, particularly in SVO (37.4–18; p < 0.0001) and less in CE (39.3–25; p < 0.0001). Reductions were recorded in males and females, younger (

Legacy unique identifier: P01728

See article methods section for description of calculated variables.

The London Borough Profiles help paint a general picture of an area by presenting a range of headline indicator data in both spreadsheet and map form to help show statistics covering demographic, economic, social and environmental datasets for each borough, alongside relevant comparator areas. The London Borough Atlas does the same but provides further detailed breakdowns and time-series data for each borough. The full datasets and more information for each of the indicators are usually available on the London Datastore. A link to each of the datasets is contained in the spreadsheet and map.

London Borough Profiles

On opening the Microsoft Excel version, a simple drop down box allows you to choose which borough profile you are interested in. Selecting this will display data for that borough, plus either Inner or Outer London, London and a national comparator (usually England where data is available). To see the full set of data for all 33 local authorities in London plus the comparator areas in Excel, click the 'Data' worksheet. A chart and a map are also available to help visualise the data for all boroughs (macros must be enabled for the Excel map to function). The data is set out across 11 themes covering most of the key indicators relating to demographic, economic, social and environmental data. Sources are provided in the spreadsheet. Notes about the indicator are provided in comment boxes attached to the indicator names. For a geographical and bar chart representation of the profile data, choose the InstantAtlas version. Choose indicators from the left hand side. Click on the comparators to make them appear on the chart and map. Sources, links to data, and notes are all contained in the box in the bottom right hand corner.

These profiles include data relating to: Population, Households (census), Demographics, Migrant population, Ethnicity, Language, Employment, NEET, DWP Benefits (client group), Housing Benefit, Qualifications, Earnings, Volunteering, Jobs density, Business Survival, Crime, Fires, House prices, New homes, Tenure, Greenspace, Recycling, Carbon Emissions, Cars, Public Transport Accessibility (PTAL), Indices of Multiple Deprivation, GCSE results, Children looked after, Children in out-of-work families, Life Expectancy, Teenage conceptions, Happiness levels, Political control, and Election turnout.

London Borough Atlas

To access even more data at local authority level, use the London Borough Atlas. It contains data about the same topics as the profiles but provides further detailed breakdowns and time-series data for each borough. There is also an InstantAtlas version available.

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. You may also find our small area profiles useful - Ward, LSOA, and "/dataset/msoa-atlas">MS

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) PREVIOUS MSOA BOUNDARIES (2001) 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: - Select a new indicator from the Data box on the left. Select the theme, then indicator and then year to show the data. - To view data just for one borough*, use the filter tool. - The legend settings can be altered by clicking on the pencil icon next to the MSOA tick box within the map legend. - 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.

Description and Purpose

This data companion pack is a resource intended to frame and be read alongside the linked rapid review of evidence for interventions to address the cost of living crisis (available on the Institute of Health Equity website) .

The resource provides intelligence and context on the cost of living crisis in London only, while the accompanying rapid review of evidence for interventions to mitigate the impacts of the rising cost of living on London, contains the recommendations for action.​

1. This pack is intended to provide a high-level overview of the impacts of the costs of living crisis on London and the need Londoners have for support to deal with the cost of living crisis through intelligence available in the public domain.
2. This pack identifies how certain groups in the population already experiencing health inequalities are at greatest risk of poverty and worsening health due to the cost of living crisis.
3. Given there are significant gaps in intelligence available, this pack also highlights these gaps and limitations in our understanding.

Audience

It will be useful for health leaders, analysts, officers, and policy makers from local and regional government, integrated care systems, NHS, academia, VCS organisations and partners across London to support their work to address the costs of living crisis by​

• Advocating for the need for action to address the rising cost of living given impacts on health and health inequalities ​
• Framing the context for the interventions highlighted in the linked rapid review of interventions​
• Engaging communities ​

​Development of this resource

The Institute of Health Equity (IHE), Greater London Authority (GLA) Health, GLA City Intelligence Unit, Office for Health Improvement and Disparities London (OHID), Association of Directors of Public Health London (ADPH), and NHSE have collaboratively produced this report, as part of the Building the Evidence (BTE) programme of work

• The sources of data available and topics included have been identified from existing published data, working in partnership through iterative discussion
• The resource is provided in PDF and PowerPoint format to support colleagues in their work to
• There is no current plan for periodic updates of this resource, though this will be discussed on completion of this programme of work

These ward level well being scores present a combined measure of well-being indicators of the resident population based on 12 different indicators. Where possible each indicator score is compared with the England and Wales average, which is zero. Scores over 0 indicate a higher probability that the population on average will experience better well-being according to these measures. Users can adjust the weight of each indicator depending on what they consider to be the more or less important, thus generating bespoke scores. This is done either by entering a number between 0 and 10. The scores throughout the spreadsheet will update automatically. The tool combines data across a range of themes for the last five years of available data (2009-2013). View the results in the online interactive tool here, The well-being scores are then presented in a ranked bar chart for each borough, and a ward map of London. The spreadsheet also highlights wards in the top and bottom 25 per cent in London. Wards that have shown significant improvement or reduction in their scores relative to the average over the five year period are also highlighted. Borough figures are provided to assist with comparisons. Rankings and summary tables are included. The source data that the tool is based on is included in the spreadsheet. Detailed information about definitions and sources is contained within the spreadsheet. The 12 measures included are: Health Life Expectancy Childhood Obesity Incapacity Benefits claimant rate Economic security Unemployment rate Safety Crime rate Deliberate Fires Education GCSE point scores Children Unauthorised Pupil Absence Families Children in out-of-work households Transport Public Transport Accessibility Scores (PTALs) Environment Access to public open space & nature Happiness Composite Subjective Well-being Score (Life Satisfaction, Worthwhileness, Anxiety, and Happiness) (New data only available since 2011/12) With some measures if the data shows a high figure that indicates better well-being, and with other measures a low figure indicates better well-being. Therefore scores for Life Expectancy, GCSE scores, PTALs, and Access to Public Open Space/Nature have been reversed so that in all measures low scores indicate probable lower well-being. The data has been turned into scores where each indicator in each year has a standard deviation of 10. This means that each indicator will have an equal effect on the final score when the weightings are set to equal. Why should measuring well-being be important to policy makers? Following research by the Cabinet Office and Office for National Statistics, the government is aiming to develop policy that is more focused on ‘all those things that make life worthwhile’ (David Cameron, November 2010). They are interested in developing new and better ways to understand how policy and public services affect well-being. Why measure well-being for local areas? It is important for London policy makers to consider well-being at a local level (smaller than borough level) because of the often huge differences within boroughs. Local authorities rely on small area data in order to target resources, and with local authorities currently gaining more responsibilities from government, this is of increasing importance. But small area data is also of interest to academics, independent analysts and members of the public with an interest in the subject of well-being. How can well-being be measured within small areas? The Office for National Statistics have been developing new measures of national well-being, and as part of this, at a national and regional level, the ONS has published some subjective data to measure happiness. ONS have not measured well-being for small areas, so this tool has been designed to fill this gap. However, DCLG have published a tool that models life satisfaction data for LSOAs based on a combination of national level happiness data, and 'ACORN' data. Happiness data is not available for small areas because there are no surveys large enough for this level of detail, and so at this geography the focus is on objective indicators. Data availability for small areas is far more limited than for districts, and this means the indicators that the scores are based on are not all perfect measures of well-being, though they are the best available. However, by using a relatively high number of measures across a number of years, this increases the reliability of the well-being scores. How can this tool be used to help policy makers? Each neighbourhood will have its own priorities, but the data in this tool could help provide a solid evidence base for informed local policy-making, and the distribution of regeneration funds. In addition, it could assist users to identify the causes behind an improvement in well-being in certain wards, where examples of good practice could be applied elsewhere. Differences to the previous report This is the 2013 edition of this publication, and there is one change from 2012. Indicators of Election turnout has been replaced with a composite score of subjective well-being indicators. This tool was created by the GLA Intelligence Unit. Please contact datastore@london.gov.uk for more information.