The National Child Development Study (NCDS) is a continuing longitudinal study that seeks to follow the lives of all those living in Great Britain who were born in one particular week in 1958. The aim of the study is to improve understanding of the factors affecting human development over the whole lifespan.

The NCDS has its origins in the Perinatal Mortality Survey (PMS) (the original PMS study is held at the UK Data Archive under SN 2137). This study was sponsored by the National Birthday Trust Fund and designed to examine the social and obstetric factors associated with stillbirth and death in early infancy among the 17,000 children born in England, Scotland and Wales in that one week. Selected data from the PMS form NCDS sweep 0, held alongside NCDS sweeps 1-3, under SN 5565.

Survey and Biomeasures Data (GN 33004):
To date there have been ten attempts to trace all members of the birth cohort in order to monitor their physical, educational and social development. The first three sweeps were carried out by the National Children's Bureau, in 1965, when respondents were aged 7, in 1969, aged 11, and in 1974, aged 16 (these sweeps form NCDS1-3, held together with NCDS0 under SN 5565). The fourth sweep, also carried out by the National Children's Bureau, was conducted in 1981, when respondents were aged 23 (held under SN 5566). In 1985 the NCDS moved to the Social Statistics Research Unit (SSRU) - now known as the Centre for Longitudinal Studies (CLS). The fifth sweep was carried out in 1991, when respondents were aged 33 (held under SN 5567). For the sixth sweep, conducted in 1999-2000, when respondents were aged 42 (NCDS6, held under SN 5578), fieldwork was combined with the 1999-2000 wave of the 1970 Birth Cohort Study (BCS70), which was also conducted by CLS (and held under GN 33229). The seventh sweep was conducted in 2004-2005 when the respondents were aged 46 (held under SN 5579), the eighth sweep was conducted in 2008-2009 when respondents were aged 50 (held under SN 6137), the ninth sweep was conducted in 2013 when respondents were aged 55 (held under SN 7669), and the tenth sweep was conducted in 2020-24 when the respondents were aged 60-64 (held under SN 9412).

A Secure Access version of the NCDS is available under SN 9413, containing detailed sensitive variables not available under Safeguarded access (currently only sweep 10 data). Variables include uncommon health conditions (including age at diagnosis), full employment codes and income/finance details, and specific life circumstances (e.g. pregnancy details, year/age of emigration from GB).

Four separate datasets covering responses to NCDS over all sweeps are available. National Child Development Deaths Dataset: Special Licence Access (SN 7717) covers deaths; National Child Development Study Response and Outcomes Dataset (SN 5560) covers all other responses and outcomes; National Child Development Study: Partnership Histories (SN 6940) includes data on live-in relationships; and National Child Development Study: Activity Histories (SN 6942) covers work and non-work activities. Users are advised to order these studies alongside the other waves of NCDS.

From 2002-2004, a Biomedical Survey was completed and is available under End User Licence (EUL) (SN 8731) and Special Licence (SL) (SN 5594). Proteomics analyses of blood samples are available under SL SN 9254.

Linked Geographical Data (GN 33497):
A number of geographical variables are available, under more restrictive access conditions, which can be linked to the NCDS EUL and SL access studies.

Linked Administrative Data (GN 33396):
A number of linked administrative datasets are available, under more restrictive access conditions, which can be linked to the NCDS EUL and SL access studies. These include a Deaths dataset (SN 7717) available under SL and the Linked Health Administrative Datasets (SN 8697) available under Secure Access.

Multi-omics Data and Risk Scores Data (GN 33592)
Proteomics analyses were run on the blood samples collected from NCDS participants in 2002-2004 and are available under SL SN 9254. Metabolomics analyses were conducted on respondents of sweep 10 and are available under SL SN 9411.

Additional Sub-Studies (GN 33562):
In addition to the main NCDS sweeps, further studies have also been conducted on a range of subjects such as parent migration, unemployment, behavioural studies and respondent essays. The full list of NCDS studies available from the UK Data Service can be found on the NCDS series access data webpage.

How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:
For information on how to access biomedical data from NCDS that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.

Further information about the full NCDS series can be found on the Centre for Longitudinal Studies website.

The National Child Development Deaths Dataset, 1958-2014: Special Licence Access contains data on known deaths among members of the NCDS birth cohort from 1958 to 2013. Information on deaths has been taken from the records maintained by the organisations responsible for the study over the life time of the study: the National Birthday Trust Fund, the National Children’s Bureau (NCB), the Social Statistics Research Unit (SSRU) and the CLS. The information has been gleaned from a variety of sources, including death certificates and other information from the National Health Service Central Register (NHSCR), and from relatives and friends during survey activities and cohort maintenance work by telephone, letter and e-mail. It includes all deaths up to 31st December 2013. In only 6 cases are the date of death unknown. By the end of December 8.7 per cent of the cohort were known to have died.

The National Child Development Study Response and Outcomes Dataset, 1958-2013 (SN 5560) covers other responses and outcomes of the cohort members and should be used alongside this dataset.

For the 3rd edition (July 2018) an updated version of the data was deposited. The new edition includes data on known deaths among members of the National Child Development Study (NCDS) birth cohort up to 2016. The user guide has also been updated.

Annual data on death registrations by single year of age for the UK (1974 onwards) and England and Wales (1963 onwards).

United Kingdom UK: Death Rate: Crude: per 1000 People data was reported at 9.100 Ratio in 2016. This records a decrease from the previous number of 9.200 Ratio for 2015. United Kingdom UK: Death Rate: Crude: per 1000 People data is updated yearly, averaging 11.300 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 12.200 Ratio in 1963 and a record low of 8.700 Ratio in 2011. United Kingdom UK: Death Rate: Crude: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United Kingdom – Table UK.World Bank.WDI: Population and Urbanization Statistics. Crude death rate indicates the number of deaths occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

This dataset as reported to the Rural Payments Agency contains cattle that died at slaughterhouses, cattle born before 1 July 1996 which were not registered until 2000, death registrations that have passed initial Cattle Tracing System validation checks, Applications received for cattle born in Great Britain. Attribution statement:

Annual data on deaths registered by age, sex and selected underlying cause of death. Tables also provide both mortality rates and numbers of deaths over time.

Mean, median and modal ages at death in the UK and its constituent countries, 2001 to 2003 and 2016 to 2018.

This dataset as reported to the Rural Payments Agency contains information on Passport applications that have passed initial CTS validation checks, Passport applications made for cattle born in Great Britain, Registered cattle where the passport has been returned to BCMS for amendment, Animals that died in Great Britain.

Life expectancy at birth for males and females for Middle Layer Super Output Areas (MSOAs), Leicester: 2016 to 2020The average number of years a person would expect to live based on contemporary mortality rates.For a particular area and time period, it is an estimate of the average number of years a newborn baby would survive if he or she experienced the age-specific mortality rates for that area and time period throughout his or her life.Life expectancy figures have been calculated based on death registrations between 2016 to 2020, which includes the first wave and part of the second wave of the coronavirus (COVID-19) pandemic.

This is the number of people of all ages killed or seriously injured (KSI) in road traffic accidents, in an area, adjusted. This indicator includes only casualties who are fatally or seriously injured and these categories are defined as follows:

Fatal casualties are those who sustained injuries which caused death less than 30 days after the accident; confirmed suicides are excluded.

Seriously injured casualties are those who sustained an injury for which they are detained in hospital as an in-patient, or any of the following injuries, whether or not they are admitted to hospital: fractures, concussion, internal injuries, crushings, burns (excluding friction burns), severe cuts and lacerations, severe general shock requiring medical treatment and injuries causing death 30 or more days after the accident.

An injured casualty is recorded as seriously or slightly injured by the police on the basis of information available within a short time of the collision. This generally will not reflect the results of a medical examination, but may be influenced according to whether the casualty is hospitalised or not. Hospitalisation procedures will vary regionally.

Slight injuries are excluded from the total, such as a sprain (including neck whiplash injury), bruise or cut which are not judged to be severe, or slight shock requiring roadside attention.

Police forces use one of two systems for recording reported road traffic collisions; the CRaSH (Collision Recording and Sharing) or COPA (Case Overview Preparation Application). Estimates are calculated from figures which are as reported by police. Since 2016, changes in severity reporting systems for a large number of police forces mean that serious injury figures, and to a lesser extent slight injuries, are not comparable with earlier years. As a result, both adjusted and unadjusted killed or seriously injured statistics are available. Further information about the reporting systems can be found here.

Areas with low resident populations but have high inflows of people or traffic may have artificially high rates because the at-risk resident population is not an accurate measure of exposure to transport. This is likely to affect the results for employment centres e.g. City of London and sparsely populated rural areas which have high numbers of visitors or through traffic. Counts for Heathrow Airport are included in the London Region and England totals only.

From the publication of the 2023 statistics onwards, casualty rates shown in table RAS0403 to include rates based on motor vehicle traffic only. This is because the department does not consider pedal cycle traffic to be robust at the local authority level.

Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

These statistics provide details of the deaths reported on by the IPCC in each financial year, and also present figures on those suicides following release from police custody which were reported to the IPCC. Data can be updated annually, so please use the trend figures from the latest report.

Each year, there are audits to assess maternal & foetal outcomes across the UK. In 2016-18, 217 women died during or up to six weeks after pregnancy, from causes associated with their pregnancy, among 2,235,159 women giving birth in the UK. 9.7 women per 100k died during pregnancy or up to six weeks after childbirth or the end of pregnancy. There was an increase in the overall maternal death rate in the UK between 2013-15 & 2016-18. Assessors judged that 29% of women who died had good care. However, improvements in care which may have made a difference to the outcome were identified for 51% of women who died. Birmingham has a higher than average maternal & foetal death rate. This dataset includes detailed information about the reasons pregnant women seek acute care, & their care pathways & outcomes. PIONEER geography: The West Midlands (WM) has a population of 5.9m & includes a diverse ethnic, socio-economic mix. There is a higher than average % of minority ethnic groups. WM has the youngest population in the UK with a higher than average birth rate. There are particularly high rates of physical inactivity, obesity, smoking & diabetes. 51.2% of babies born in Birmingham have at least one parent born outside of the UK, this compares with 34.7% for England. Each day >100k people are treated in hospital, see their GP or are cared for by the NHS. EHR: University Hospitals Birmingham NHS Foundation Trust (UHB) is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & 100 ITU beds. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”. Scope: Pregnant or post-partum women from 2015 onwards who attended A&E in Queen Elizabeth hospital. Longitudinal & individually linked, so that the preceding & subsequent health journey can be mapped & healthcare utilisation prior to & after admission understood. The dataset includes highly granular patient demographics (including gestation & postpartum period), co-morbidities taken from ICD-10 & SNOMED-CT codes. Serial, structured data pertaining to process of care (admissions, wards, practitioner changes & discharge outcomes), presenting complaints, physiology readings (temperature, blood pressure, NEWS2, SEWS, AVPU), referrals, all prescribed & administered treatments & all outcomes. Available supplementary data: More extensive data including granular serial physiology, bloods, conditions, interventions, treatments. Ambulance, 111, 999 data, synthetic data. Available supplementary support: Analytics, Model build, validation & refinement; A.I.; Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.

This file contains the exemplar list of historic strings together with the ICD10h codes and descriptions associated with the ICD10h (Historic cause of death coding and classification scheme for individual-level causes of death). ICD10h has been designed by the authors to aid the coding and classification of causes of death recorded on historic individual death records and associated files include a manual, the list of codes, descriptions and values of a general categorisation, and a categorisation for infant mortality. The ICD10h system is based on the 10th revision of the International Classification of Diseases - 2016 version (ICD10 - 2016), and combines ICD10 codes (without modification) with new codes for archaic/historic terms.

The data was derived from the following projects/deposited data: Determining the Demography of Victorian Scotland Through Record Linkage, ESRC RES-000-23-0128 held at the Cambridge Group for the History of Population and Social Structure, University of Cambridge; P. Gunn and R. Kippen, ‘Household and Family Formation in Nineteenth-Century Tasmania, Dataset of 195 Thousand Births, 93 Thousand Deaths and 51 Thousand Marriages Registered in Tasmania, 1838-1899’, 2008.

The resource creation was supported by the following projects: Digitising Scotland/Scottish Health Informatics Project (funded by the ESRC); Studying Health in Port Cities (funded by The Netherlands Organisation for Scientific Research); The Great Leap (funded by COST-Action CA22116).

SHARING/ACCESS INFORMATION

This resource is available under a CC BY licence.

Recommended citation for this dataset: Historic cause of death coding and classification scheme for individual-level causes of death – English language historic strings [https://doi.org/10.17863/CAM.109962]

Please see the associated resources: Historic cause of death coding and classification scheme for individual-level causes of death – manual [https://doi.org/10.17863/CAM.109960] Historic cause of death coding and classification scheme for individual-level causes of death – Codes [https://doi.org/10.17863/CAM.109961] Historic cause of death coding and classification scheme for individual-level causes of death – Infant Categorisations [https://doi.org/10.17863/CAM.109963]

ICD10h is a research tool created to facilitate the study of historical cause of death records and should not be used for any official purpose. It is based on the International Classification of Diseases, 10th Revision (ICD-10) version 2016 (Geneva: World Health Organization 2016) but is not a recognised version or extension of ICD-10 and is not authorised by WHO. However we have consulted with WHO: they recognise that ICD10h is a useful academic methodology and have not raised any objections to its creation. Data coded using ICD10h are not directly comparable with data coded in ICD-10, and the underlying or primary cause of death derived using the ICD10h methodology may be different from the underlying cause derived in ICD-10 according to the WHO rules. Please note that ICD-10 version 2016 is not the most recent version of ICD-10; and that WHO now recommend the use of ICD-11; a more advanced and detailed classification.

DATA & FILE OVERVIEW

ICD10h_HistoricStringsEnglish.xlsx Excel file consisting of 2 worksheets: 1) ReadMe sheet 2) HistoricStringsEnglish

Separate csv file for 2) containing the same information.

This file builds on a previous, unpublished version of ICD10h (dating from 2020).

METHODOLOGICAL INFORMATION

The data were hand-coded and subject to stringent algorithm-assisted tests.

DATA-SPECIFIC INFORMATION FOR: HistoricStringsEnglish

Number of variables: 7

Number of cases/rows: 3306

Variable List: ID_HistoricStrings (unique ID for HistoricStrings table) HistoricString (Historic cause of death string as encountered in records) ICD10h (ICD10h code) ICD10hInjury (additional ICD10h code for injuries) ICD10hDescription (ICD10h description) ICD10hInjuryDescription (additional ICD10h description for injuries) CancerMalignancyFlag (0=not a neoplasm; 1=no information on malignancy; 2=stated to be malignant; 3=stated to be benign; 4=stated to be of uncertain behaviour)

Abstract copyright UK Data Service and data collection copyright owner.The National Child Development Study (NCDS) is a continuing longitudinal study that seeks to follow the lives of all those living in Great Britain who were born in one particular week in 1958. The aim of the study is to improve understanding of the factors affecting human development over the whole lifespan. The NCDS has its origins in the Perinatal Mortality Survey (PMS) (the original PMS study is held at the UK Data Archive under SN 2137). This study was sponsored by the National Birthday Trust Fund and designed to examine the social and obstetric factors associated with stillbirth and death in early infancy among the 17,000 children born in England, Scotland and Wales in that one week. Selected data from the PMS form NCDS sweep 0, held alongside NCDS sweeps 1-3, under SN 5565. Survey and Biomeasures Data (GN 33004):To date there have been nine attempts to trace all members of the birth cohort in order to monitor their physical, educational and social development. The first three sweeps were carried out by the National Children's Bureau, in 1965, when respondents were aged 7, in 1969, aged 11, and in 1974, aged 16 (these sweeps form NCDS1-3, held together with NCDS0 under SN 5565). The fourth sweep, also carried out by the National Children's Bureau, was conducted in 1981, when respondents were aged 23 (held under SN 5566). In 1985 the NCDS moved to the Social Statistics Research Unit (SSRU) - now known as the Centre for Longitudinal Studies (CLS). The fifth sweep was carried out in 1991, when respondents were aged 33 (held under SN 5567). For the sixth sweep, conducted in 1999-2000, when respondents were aged 42 (NCDS6, held under SN 5578), fieldwork was combined with the 1999-2000 wave of the 1970 Birth Cohort Study (BCS70), which was also conducted by CLS (and held under GN 33229). The seventh sweep was conducted in 2004-2005 when the respondents were aged 46 (held under SN 5579), the eighth sweep was conducted in 2008-2009 when respondents were aged 50 (held under SN 6137) and the ninth sweep was conducted in 2013 when respondents were aged 55 (held under SN 7669). Four separate datasets covering responses to NCDS over all sweeps are available. National Child Development Deaths Dataset: Special Licence Access (SN 7717) covers deaths; National Child Development Study Response and Outcomes Dataset (SN 5560) covers all other responses and outcomes; National Child Development Study: Partnership Histories (SN 6940) includes data on live-in relationships; and National Child Development Study: Activity Histories (SN 6942) covers work and non-work activities. Users are advised to order these studies alongside the other waves of NCDS.From 2002-2004, a Biomedical Survey was completed and is available under End User Licence (EUL) (SN 8731) and Special Licence (SL) (SN 5594). Proteomics analyses of blood samples are available under SL SN 9254.Linked Geographical Data (GN 33497): A number of geographical variables are available, under more restrictive access conditions, which can be linked to the NCDS EUL and SL access studies. Linked Administrative Data (GN 33396):A number of linked administrative datasets are available, under more restrictive access conditions, which can be linked to the NCDS EUL and SL access studies. These include a Deaths dataset (SN 7717) available under SL and the Linked Health Administrative Datasets (SN 8697) available under Secure Access.Additional Sub-Studies (GN 33562):In addition to the main NCDS sweeps, further studies have also been conducted on a range of subjects such as parent migration, unemployment, behavioural studies and respondent essays. The full list of NCDS studies available from the UK Data Service can be found on the NCDS series access data webpage. How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:For information on how to access biomedical data from NCDS that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.Further information about the full NCDS series can be found on the Centre for Longitudinal Studies website. The National Child Development Study (NCDS) originated in the ‘Perinatal Mortality Survey’, which examined social and obstetric factors associated with still birth and infant mortality among over 17,000 babies born in Britain in the week 3-9 March 1958. Surviving members of this birth cohort have been surveying on eight further occasions in order to monitor their changing health, education, social and economic circumstances – in 1965 (age 7), 1969 (age 11), 1974 (age 16), 1981 (age 23), 1991 (age 33), 1999/2000 (age 41/42), 2004/05 (age 46/47), 2008/09 (age 50) and 2013/14 (age 55). There have also been surveys of sub-samples of the cohort, the most recent occurring in 1995 (age 37), when a 10% representative sub-sample was assessed for difficulties with basic skills. Finally, during 2002-04, 9,340 NCDS cohort members participated in a biomedical survey, carried out by qualified nurses.

This dataset as reported to the Rural Payments Agency contains information on Passport applications that have passed initial CTS validation checks, Passport applications made for cattle born in Great Britain, Registered cattle where the passport has been returned to BCMS for amendment, Animals that died in Great Britain. Attribution statement:

This dataset describes environmental conditions at 135 Saiga antelope calving sites (from a total of 214) in Kazakhstan where the predictor variables required for the modelling were available at sufficient resolution. Data collected included climatic variables associated with haemorrhagic septicaemia in the literature, including humidity, temperature and precipitation. Indicators of vegetation biomass, phenology and length of the winter preceding calving were represented using the Normalised Difference Vegetation Index (NDVI), snow depth and snow presence data. Saiga antelope are susceptible to mass mortality events (MME), the most severe of which are caused by haemorrhagic septicaemia following infection by the bacteria Pasteurella multocida. These die-off events tend to occur in May during calving, when saigas gather in dense aggregations. As the bacteria is a commensal organism, which may live harmlessly in the respiratory tract of the saiga, it is believed that an environmental trigger is involved in a shift to virulence in the pathogen or reduction in immune-competence in the host. The attached data show environmental conditions at a set of calving sites of the Betpak-dala population of saigas. This population, one of three in Kazakhstan, is located in the central provinces of the country and is the only one in which massive haemorrhagic septicaemia outbreaks have been recorded. At most of the recorded sites, calving progressed normally, whilst at others mass mortality events occurred during calving or just afterwards, namely in 1981, 1988 and 2015. A set of environmental predictor variables was used to model the probability of an MME at calving aggregations. The dataset, modelling process and results are described in Kock et al. (2018): http://advances.sciencemag.org/content/4/1/eaao2314 A related shapefile of the full set of 214 sites, and metadata concerning site characteristics and the provenance of the location data is available at: https://catalogue.ceh.ac.uk/id/8ad12782-e939-4834-830a-c89e503a298b The attached dataset and site metadata in the above-mentioned Shapefile attribute table can be combined using the variable ID in order to merge the environmental data with information on the calving and MME sites.

ICD10h2024.2 (this version, published June 2025) incorporates the following changes: - Manual: new preface to list changes to files; changes relating to code changes; a small number of other corrections and improvements. - Masterlist (see 2025MasterlistChanges): 9 new codes added, 5 codes deleted, and 17 changes made to ICD10 or ICD10h descriptions. - Transferfile (see 2025TransferfileChanges): 47 errors were fixed. - InfantCat (see 2025InfantCatChanges): 17 ICD10h codes were updated. - Historic Strings English (see 2025HistoricStringsEnglishChanges): 14 changes were made to ICD10h or ICD10hInjury codes were made. ICD10hDescription and ICD10hInjuryDescription columns were deleted.

This file contains the infant death categorisations associated with the ICD10h (Historic cause of death coding and classification scheme for individual-level causes of death). ICD10h has been designed by the authors to aid the coding and classification of causes of death recorded on historic individual death records and associated files include a manual, the list of codes, descriptions and values of a general categorisation, and exemplar list of historic strings together with the ICD10h codes. The ICD10h system is based on the 10th revision of the International Classification of Diseases - 2016 version (ICD10 - 2016), and combines ICD10 codes (without modification) with new codes for archaic/historic terms.

The data was derived from the following projects/deposited data: Determining the Demography of Victorian Scotland Through Record Linkage, ESRC RES-000-23-0128 held at the Cambridge Group for the History of Population and Social Structure, University of Cambridge; P. Gunn and R. Kippen, ‘Household and Family Formation in Nineteenth-Century Tasmania, Dataset of 195 Thousand Births, 93 Thousand Deaths and 51 Thousand Marriages Registered in Tasmania, 1838-1899’, 2008.

The resource creation was supported by the following projects: Digitising Scotland/Scottish Health Informatics Project (funded by the ESRC); Studying Health in Port Cities (funded by The Netherlands Organisation for Scientific Research); The Great Leap (funded by COST-Action CA22116).

SHARING/ACCESS INFORMATION

This resource is available under a CC BY licence.

Recommended citation for this dataset: Alice Reid, Eilidh Garrett, Maria Hiltunen Maltesdotter, Angelique Janssens, 2024, ICD10h: Historic cause of death coding and classification scheme for individual-level causes of death – Infant Categorisations [https://doi.org/10.17863/CAM.109963]

Please see the associated resources: Historic cause of death coding and classification scheme for individual-level causes of death – manual [https://doi.org/10.17863/CAM.109960] Historic cause of death coding and classification scheme for individual-level causes of death – Codes [https://doi.org/10.17863/CAM.109961] Historic cause of death coding and classification scheme for individual-level causes of death – English language historic strings [https://doi.org/10.17863/CAM.109962]

ICD10h is a research tool created to facilitate the study of historical cause of death records and should not be used for any official purpose. It is based on the International Classification of Diseases, 10th Revision (ICD-10) version 2016 (Geneva: World Health Organization 2016) but is not a recognised version or extension of ICD-10 and is not authorised by WHO. However we have consulted with WHO: they recognise that ICD10h is a useful academic methodology and have not raised any objections to its creation. Data coded using ICD10h are not directly comparable with data coded in ICD-10, and the underlying or primary cause of death derived using the ICD10h methodology may be different from the underlying cause derived in ICD-10 according to the WHO rules. Please note that ICD-10 version 2016 is not the most recent version of ICD-10; and that WHO now recommend the use of ICD-11; a more advanced and detailed classification.

DATA & FILE OVERVIEW

ICD10h_InfantCat.xlsx Excel file consisting of 2 worksheets: 1) ReadMe sheet 2) InfantCat

Separate csv file for 2) containing the same information.

This file builds on a previous, unpublished version of ICD10h (dating from 2020). InfantCat2024 provides an updated version of the previous categorisation (InfantCat2020). Please see the Manual for detail of the changes.

METHODOLOGICAL INFORMATION

The data were hand-coded and subject to stringent algorithm-assisted tests.

DATA-SPECIFIC INFORMATION FOR: InfantCat

Number of variables: 4

Number of cases/rows: 14088

Variable List: IDMasterlist (unique ID number, same as Masterlist table) ICD10h (ICD10h code ) Infantcat2024 (Infantcat2024 category) Infantcat2020 (Infantcat2020 category)

Population figures over a 25-year period, including births, deaths and migration by sex for regions and local authorities in England. 2022-based datasets are the latest projection.

As a result of the continued annual growth in global air traffic passenger demand, the number of airplanes that were involved in accidents is on the increase. Although the United States is ranked among the 20 countries with the highest quality of air infrastructure, the U.S. reports the highest number of civil airliner accidents worldwide. 2020 was the year with more plane crashes victims, despite fewer flights The number of people killed in accidents involving large commercial aircraft has risen globally in 2020, even though the number of commercial flights performed last year dropped by 57 percent to 16.4 million. More than half of the total number of deaths were recorded in January 2020, when an Ukrainian plane was shot down in Iranian airspace, a tragedy that killed 176 people. The second fatal incident took place in May, when a Pakistani airliner crashed, killing 97 people. Changes in aviation safety In terms of fatal accidents, it seems that aviation safety experienced some decline on a couple of parameters. For example, there were 0.37 jet hull losses per one million flights in 2016. In 2017, passenger flights recorded the safest year in world history, with only 0.11 jet hull losses per one million flights. In 2020, the region with the highest hull loss rate was the Commonwealth of Independent States. These figures do not take into account accidents involving military, training, private, cargo and helicopter flights.

Live births and stillbirths annual summary statistics, by sex, age of mother, whether within marriage or civil partnership, percentage of non-UK-born mothers, birth rates and births by month and mothers' area of usual residence.

Absolute deprivation differences (ADt,r), per 100,000 people, in age-standardised fitted incidence rates in 2001 and 2016 for all regions in England and both genders; 95% credible intervals in brackets.