Non Lincolnshire County Council

Population Projections from the Office for National Statistics (ONS). These are the official projections of the future resident population in Lincolnshire. Population projections show estimates of future population sizes for the next 25 years based on recent population trends and Population Mid-Year Estimates (also published on this platform). Please note that although ONS data may show exact numbers, they are estimates so some rounding should be applied. Population projections are produced by the Office for National Statistics (ONS) and are updated every two years.

Digital map boundaries of areas within Lincolnshire. Themes include Administrative, Electoral, Statistical, and Health. These boundary data sets are sourced from Ordnance Survey (OS) and the Office for National Statistics (ONS). They come under the terms of the UK Govt. Open Government Licence (OGL). You can use any of the boundary data sets for any purpose, but you must use the following copyright statements when you reproduce or use this material: - Source: Office for National Statistics licensed under the Open Government Licence v.3.0 - Contains OS data © Crown copyright and database right [year]

The Indices of Deprivation are published nationally by the Ministry of Housing, Communities and Local Government (MHCLG). These are the official indicators of deprivation. As such, wherever they show deprivation in local areas they provide strong and credible evidence to support funding bids and target resources. Deprivation is measured by the Indices of Deprivation on an Index of Multiple Deprivation (IMD), and also in specific domains and sub-domains of deprivation (for example Income, Employment, Education and Skills, etc). Two further datasets are included within this data, for Income Deprivation affecting Children (IDACI) and Older People (IDAOPI). So as well as overall deprivation shown in the IMD, the themed deprivation domains (and sub-domains) can also be used to identify and evidence different elements of deprivation. For example, among the various deprivation issues affecting local communities in Lincolnshire, deprivation in rural access to housing and services can often stand out in the data. There are useful supporting resources to help people understand and use the Indices of Deprivation, please see the source weblink and the additional links provided. These links also provide Deprivation data summaries for Districts, NHS CCGs, Lincolnshire, and the Greater Lincolnshire LEP. Source: Ministry of Housing, Communities and Local Government (MHCLG). The Indices of Deprivation are updated at four-yearly intervals (so until the next update, the data stays current and valid for use).

Population Mid-year Estimates from the Office for National Statistics (ONS). These are the official estimates of the resident population in Lincolnshire. ONS uses information from the census and other data to produce these official mid-year population estimates every year between each census. These figures show how many people live in each local area and the population age-sex structure. This data is updated annually. Although the ONS data shows exact numbers, they are estimates so some rounding should be applied. For current Armed forces populations, two Ministry of Defence links are also shown below. The ONS 2021 Census link has Veterans data. Population Projections data sourced from ONS is also available on this platform. The Source link shown below is to the ONS Nomis website. It has user-friendly data query tools for a broad range of ONS and other datasets from official sources.

There are 3 datasets within this publication showing key aspects of Ethnic Minority Populations in Lincolnshire: Ethnic Groups, Proficiency in English, and Religion. The datasets show 2021 Census estimates of the total resident population with breakouts for these three population categories. These Census 2021 datasets are sourced from the Office for National Statistics (ONS) Nomis website - see the Source link below. Data is shown for Lincolnshire and Districts, and for 2021 Lower Super Output Areas (LSOA). Different geographies and more detailed breakouts of these and other useful datasets, are available at the Source link. The data is updated every 10 years with the next update due from the Census 2031.

This dataset shows Emergency Hospital Admissions for fractured neck of femur, for persons Age 65 and over by Gender. The data source (Office for Health Improvement and Disparities (OHID)) has indicated the following aspects in its commentary. Firstly, hip fracture is a debilitating condition - only one in three sufferers return to their former levels of independence, and one in three ends up leaving their own home and moving to long-term care. Hip fractures are almost as common and as costly to public services as strokes. Mortality from hip fracture is high - about one in ten people with a hip fracture die within a month, and about one in three die within a year. Within the 65 and over age group there are differences in hip fracture rates by Age and Gender. For data breakouts and more information please see the source link. Directly Age-Standardised Rates (DASR) are shown in the data (where numbers are sufficient) so that rates can be directly compared between areas. The DASR calculation applies Age-specific rates to a Standard European population to cancel out possible effects on crude rates due to different age structures among populations, thus enabling direct comparisons of rates. Source: Office for Health Improvement and Disparities (OHID), Public Health Outcomes Framework (PHOF) indicator 4.14i (41401-E13). This data is updated annually.

This data shows premature deaths (Age under 75) from all Cancers, numbers and rates by gender, as 3-year moving-averages. Cancers are a major cause of premature deaths. Inequalities exist in cancer rates between the most deprived areas and the most affluent areas. Directly Age-Standardised Rates (DASR) are shown in the data (where numbers are sufficient) so that death rates can be directly compared between areas. The DASR calculation applies Age-specific rates to a Standard (European) population to cancel out possible effects on crude rates due to different age structures among populations, thus enabling direct comparisons of rates. A limitation on using mortalities as a proxy for prevalence of health conditions is that mortalities may give an incomplete view of health conditions in an area, as ill-health might not lead to premature death. Data source: Office for Health Improvement and Disparities (OHID), indicator ID 40501, E05a. This data is updated annually.

This data shows premature deaths (Age under 75) from Respiratory Disease, numbers and rates by gender, as 3-year range. Smoking is the major cause of chronic obstructive pulmonary disease (COPD), one of the major Respiratory diseases. COPD (which includes chronic bronchitis and emphysema) results in many hospital admissions. Respiratory diseases can also be caused by environmental factors (such as pollution, or housing conditions) and influenza. Respiratory disease mortality rates show a socio-economic gradient. Directly Age-Standardised Rates (DASR) are shown in the data, where numbers are sufficient, so that death rates can be directly compared between areas. The DASR calculation applies Age-specific rates to a Standard (European) population to cancel out possible effects on crude rates due to different age structures among populations, thus enabling direct comparisons of rates. A limitation on using mortalities as a proxy for prevalence of health conditions is that mortalities may give an incomplete view of health conditions in an area, as ill-health might not lead to premature death. Data source: Office for Health Improvement and Disparities (OHID) Public Health Outcomes Framework (PHOF) indicator 4.07i. This data is updated annually.

This data shows premature deaths (Age under 75), numbers and rates by gender, as 3-year moving-averages. All-Cause Mortality rates are a summary indicator of population health status. All-cause mortality is related to Life Expectancy, and both may be influenced by health inequalities. Directly Age-Standardised Rates (DASR) are shown in the data (where numbers are sufficient) so that death rates can be directly compared between areas. The DASR calculation applies Age-specific rates to a Standard (European) population to cancel out possible effects on crude rates due to different age structures among populations, thus enabling direct comparisons of rates. A limitation on using mortalities as a proxy for prevalence of health conditions is that mortalities may give an incomplete view of health conditions in an area, as ill-health might not lead to premature death. Data source: Office for Health Improvement and Disparities (OHID), Public Health Outcomes Framework (PHOF) indicator ID 108. This data is updated annually.

This data shows premature deaths (Age under 75) from Liver Disease, numbers and rates by gender, as 3-year moving-averages. Most liver disease is preventable and much is influenced by alcohol consumption and obesity prevalence, which are both amenable to public health interventions. Directly Age-Standardised Rates (DASR) are shown in the data (where numbers are sufficient) so that death rates can be directly compared between areas. The DASR calculation applies Age-specific rates to a Standard (European) population to cancel out possible effects on crude rates due to different age structures among populations, thus enabling direct comparisons of rates. A limitation on using mortalities as a proxy for prevalence of health conditions is that mortalities may give an incomplete view of health conditions in an area, as ill-health might not lead to premature death. Low numbers may result in zero values or missing data. Data source: Office for Health Improvement and Disparities (OHID), Public Health Outcomes Framework (PHOF) indicator 40601 (E06a). The data is updated annually.