SUMMARYThis analysis, designed and executed by Ribble Rivers Trust, identifies areas across England with the greatest levels of diabetes mellitus in persons (aged 17+). Please read the below information to gain a full understanding of what the data shows and how it should be interpreted.ANALYSIS METHODOLOGYThe analysis was carried out using Quality and Outcomes Framework (QOF) data, derived from NHS Digital, relating to diabetes mellitus in persons (aged 17+).This information was recorded at the GP practice level. However, GP catchment areas are not mutually exclusive: they overlap, with some areas covered by 30+ GP practices. Therefore, to increase the clarity and usability of the data, the GP-level statistics were converted into statistics based on Middle Layer Super Output Area (MSOA) census boundaries.The percentage of each MSOA’s population (aged 17+) with diabetes mellitus was estimated. This was achieved by calculating a weighted average based on:The percentage of the MSOA area that was covered by each GP practice’s catchment areaOf the GPs that covered part of that MSOA: the percentage of registered patients that have that illness The estimated percentage of each MSOA’s population with diabetes mellitus was then combined with Office for National Statistics Mid-Year Population Estimates (2019) data for MSOAs, to estimate the number of people in each MSOA with depression, within the relevant age range.Each MSOA was assigned a relative score between 1 and 0 (1 = worst, 0 = best) based on:A) the PERCENTAGE of the population within that MSOA who are estimated to have diabetes mellitusB) the NUMBER of people within that MSOA who are estimated to have diabetes mellitusAn average of scores A & B was taken, and converted to a relative score between 1 and 0 (1= worst, 0 = best). The closer to 1 the score, the greater both the number and percentage of the population in the MSOA that are estimated to have diabetes mellitus, compared to other MSOAs. In other words, those are areas where it’s estimated a large number of people suffer from diabetes mellitus, and where those people make up a large percentage of the population, indicating there is a real issue with diabetes mellitus within the population and the investment of resources to address that issue could have the greatest benefits.LIMITATIONS1. GP data for the financial year 1st April 2018 – 31st March 2019 was used in preference to data for the financial year 1st April 2019 – 31st March 2020, as the onset of the COVID19 pandemic during the latter year could have affected the reporting of medical statistics by GPs. However, for 53 GPs (out of 7670) that did not submit data in 2018/19, data from 2019/20 was used instead. Note also that some GPs (997 out of 7670) did not submit data in either year. This dataset should be viewed in conjunction with the ‘Health and wellbeing statistics (GP-level, England): Missing data and potential outliers’ dataset, to determine areas where data from 2019/20 was used, where one or more GPs did not submit data in either year, or where there were large discrepancies between the 2018/19 and 2019/20 data (differences in statistics that were > mean +/- 1 St.Dev.), which suggests erroneous data in one of those years (it was not feasible for this study to investigate this further), and thus where data should be interpreted with caution. Note also that there are some rural areas (with little or no population) that do not officially fall into any GP catchment area (although this will not affect the results of this analysis if there are no people living in those areas).2. Although all of the obesity/inactivity-related illnesses listed can be caused or exacerbated by inactivity and obesity, it was not possible to distinguish from the data the cause of the illnesses in patients: obesity and inactivity are highly unlikely to be the cause of all cases of each illness. By combining the data with data relating to levels of obesity and inactivity in adults and children (see the ‘Levels of obesity, inactivity and associated illnesses: Summary (England)’ dataset), we can identify where obesity/inactivity could be a contributing factor, and where interventions to reduce obesity and increase activity could be most beneficial for the health of the local population.3. It was not feasible to incorporate ultra-fine-scale geographic distribution of populations that are registered with each GP practice or who live within each MSOA. Populations might be concentrated in certain areas of a GP practice’s catchment area or MSOA and relatively sparse in other areas. Therefore, the dataset should be used to identify general areas where there are high levels of diabetes mellitus, rather than interpreting the boundaries between areas as ‘hard’ boundaries that mark definite divisions between areas with differing levels of diabetes mellitus.TO BE VIEWED IN COMBINATION WITH:This dataset should be viewed alongside the following datasets, which highlight areas of missing data and potential outliers in the data:Health and wellbeing statistics (GP-level, England): Missing data and potential outliersLevels of obesity, inactivity and associated illnesses (England): Missing dataDOWNLOADING THIS DATATo access this data on your desktop GIS, download the ‘Levels of obesity, inactivity and associated illnesses: Summary (England)’ dataset.DATA SOURCESThis dataset was produced using:Quality and Outcomes Framework data: Copyright © 2020, Health and Social Care Information Centre. The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital.GP Catchment Outlines. Copyright © 2020, Health and Social Care Information Centre. The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital. Data was cleaned by Ribble Rivers Trust before use.COPYRIGHT NOTICEThe reproduction of this data must be accompanied by the following statement:© Ribble Rivers Trust 2021. Analysis carried out using data that is: Copyright © 2020, Health and Social Care Information Centre. The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital.CaBA HEALTH & WELLBEING EVIDENCE BASEThis dataset forms part of the wider CaBA Health and Wellbeing Evidence Base.

United Kingdom UK: Diabetes Prevalence: % of Population Aged 20-79 data was reported at 4.280 % in 2017. United Kingdom UK: Diabetes Prevalence: % of Population Aged 20-79 data is updated yearly, averaging 4.280 % from Dec 2017 (Median) to 2017, with 1 observations. United Kingdom UK: Diabetes Prevalence: % of Population Aged 20-79 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: Health Statistics. Diabetes prevalence refers to the percentage of people ages 20-79 who have type 1 or type 2 diabetes.; ; International Diabetes Federation, Diabetes Atlas.; Weighted average;

The percentage of people with diabetes who have received nine care processes. Current version updated: Mar-17 Next version due: Mar-18

This dataset shows the percentage of patients with non-diabetic hyperglycaemia who took up an offer to participate in the NHS Diabetes Prevention Programme (DPP). The indicator reflects engagement with preventative services aimed at reducing the risk of developing type 2 diabetes. Data is sourced from the National Diabetes Audit (NDA) and includes patients registered at participating GP practices.

Rationale

The NHS Diabetes Prevention Programme is a key initiative to reduce the incidence of type 2 diabetes by supporting individuals at high risk through lifestyle interventions. Monitoring the uptake of DPP courses helps assess the reach and effectiveness of the programme and supports efforts to improve early intervention and reduce long-term health complications.

Numerator

The numerator is the number of patients with non-diabetic hyperglycaemia who were offered and did not decline a DPP course, as recorded by GP practices participating in the National Diabetes Audit.

Denominator

The denominator includes all patients with non-diabetic hyperglycaemia registered at GP practices that participated in the National Diabetes Audit.

Caveats

Some individuals with diabetes may be excluded from the dataset if they were not registered with a GP practice at the time of data collection. This may affect the completeness of the data and the accuracy of the reported uptake rate.

External References

More information is available from the following source:

National Diabetes Audit - NDH & DPP

Click here to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.

This dataset presents the relative risk of mortality from diabetic complications. It compares the observed number of deaths among people with diabetes due to specific complications—such as angina, myocardial infarction, heart failure, or stroke—with the expected number of such deaths in the diabetic population. The data is derived from ONS death registrations and modelled estimates from the National Diabetes Audit (NDA).

Rationale

People with diabetes are at increased risk of developing serious cardiovascular complications, which can lead to premature mortality. Monitoring mortality from these complications helps identify disparities in care and outcomes, and supports efforts to improve diabetes management and reduce preventable deaths. This indicator provides a benchmark for evaluating the effectiveness of interventions aimed at reducing cardiovascular risk in people with diabetes.

Numerator

The numerator is the number of people with diabetes, as recorded on their death certificate, who died from complications such as angina, myocardial infarction, heart failure, or stroke.

Denominator

The denominator is the modelled number of people with diabetes who would be expected to die from these complications, based on data from the National Diabetes Audit.

Caveats

No specific caveats are noted for this indicator. However, as with all modelled data, assumptions and estimation methods may influence the accuracy of the expected mortality figures.

External References

More information is available from the following source:

National Diabetes Audit - NHS Digital

Click here to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.

The NHS Diabetes Prevention Programme (NHS DPP) is a joint commitment from NHS England & Improvement, Public Health England (now Office for Health Improvement and Disparities) and Diabetes UK to deliver, at scale, evidence based behavioural interventions that can prevent or delay the onset of type 2 diabetes in adults who have been identified as having non-diabetic hyperglycaemia. This report primarily uses data from English GP practice systems, and data generated by providers of the Diabetes Prevention Programme relating to referrals. The GP data is only for people diagnosed with non-diabetic hyperglycaemia.

The National Diabetes Insulin Pump Audit is part of the National Diabetes Audit (NDA).

The National Diabetes Insulin Pump Audit collects information on the number and characteristics of people with Type 1 diabetes using an insulin pump, the reasons for going on an insulin pump and the outcomes achieved since starting on the pump.

Making clinical audit data transparent

In his transparency and open data letter to Cabinet Ministers on 7 July 2011, the Prime Minister made a commitment to make clinical audit data available from the national audits within the National Clinical Audit and Patient Outcomes Programme.

What information is being made available?

National Diabetes Insulin Pump Audit data for 2016-17 is available at England and Wales, Local Health Board (LHB) and Specialist Diabetes Service level for:

• Participation
• Patient demographics
• Prevalence
• Care process completion
• Treatment targets
• Diabetes characteristics

Using and interpreting the data

Data from the National Diabetes Insulin Pump Audit should not be looked at in isolation when assessing standards of care.

Accessing the data

The data are being made available on the data.gov website. Local Health Boards and Specialist Diabetes Services are identified by organisation code.

What does the data cover?

The audit looks at the following areas:

• Reason for starting on an insulin pump
• Care processes
• Treatment targets
• Structured Education

What period does the data cover?

This data covers the top level findings from the 2016-17 National Diabetes Insulin Pump Audit for the period 1 January 2016 to 31 March 2017. This National Report was published on 14 June 2018.

The National Diabetes Audit (NDA) provides a comprehensive view of diabetes care in England and Wales. It measures the effectiveness of diabetes healthcare against NICE Clinical Guidelines and NICE Quality Standards. This is the Type 1 Diabetes report. It details the findings and recommendations relating to diabetes care process completion, treatment target achievement and structured education for people with type 1 diabetes aged 19 years and over.

This dataset presents the percentage of individuals with type 2 diabetes who have successfully achieved all three key treatment targets recommended by the National Institute for Health and Care Excellence (NICE). These targets include maintaining an HbA1c level of 58 mmol/mol or lower, a blood pressure level of 140/80 mmHg or lower, and, for those at high cardiovascular risk, being prescribed a statin. The dataset provides a valuable measure of effective diabetes management and supports analysis across different population groups and healthcare settings.

Rationale

Achieving all three treatment targets is associated with better health outcomes and reduced risk of diabetes-related complications. This indicator helps assess the quality of diabetes care and supports efforts to improve clinical management and patient outcomes for people living with type 2 diabetes.

Numerator

The numerator includes the number of individuals with type 2 diabetes who have met all three NICE-recommended treatment targets: HbA1c ≤ 58 mmol/mol, blood pressure ≤ 140/80 mmHg, and statin prescription for those at high cardiovascular risk. Data is sourced from the National Diabetes Audit (NDA) and NHS England.

Denominator

The denominator includes all individuals aged 12 and over who are registered with type 2 diabetes at GP practices participating in the National Diabetes Audit. This ensures a consistent and comprehensive population base for calculating the indicator.

Caveats

Data is collected over a 15-month period, from January 1st of the first year to March 31st of the following year. This extended reporting window may affect comparability with other datasets that use different timeframes.

External references

For more information, visit the Public Health England Fingertips Diabetes Profile.

Localities ExplainedThis dataset contains data based on either the resident locality or registered locality of the patient, a distinction is made between resident locality and registered locality populations:Resident Locality refers to individuals who live within the defined geographic boundaries of the locality. These boundaries are aligned with official administrative areas such as wards and Lower Layer Super Output Areas (LSOAs).Registered Locality refers to individuals who are registered with GP practices that are assigned to a locality based on the Primary Care Network (PCN) they belong to. These assignments are approximate—PCNs are mapped to a locality based on the location of most of their GP surgeries. As a result, locality-registered patients may live outside the locality, sometimes even in different towns or cities.This distinction is important because some health indicators are only available at GP practice level, without information on where patients actually reside. In such cases, data is attributed to the locality based on GP registration, not residential address.

Click here to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.

Note: This dataset has been archived as of January 2024 after confirmation from NHS Digital that the source dataset is no longer being updated, and there is not a replacement publication for the diabetic ketoacidosis admissions data. This indicator is one measure of the prevention, identification and management of people at risk of developing diabetes and those with the condition. It shows adverse outcomes as annual numbers of emergency hospital admissions for diabetic ketoacidosis and coma. Emergency admissions to hospital can be avoided by identifying people at risk, primary care services interventions, encouraging better diet and exercise, improving self-monitoring and diabetes control and supporting patients and carers in the management of diabetes in the home. It needs local health and care services working effectively together to support people’s health and independence in the community. Type 2 diabetes (around 90 percent of diabetes diagnoses) is partially preventable - it can be prevented or delayed by lifestyle changes (exercise, weight loss, healthy eating). Earlier detection of type 2 diabetes followed by effective treatment reduces the risk of developing diabetic complications. These include cardiovascular, kidney, foot and eye diseases, meaning considerable illness and reduced quality of life. There are some limitations to this data, as raw counts of hospital episodes are subject to population structures (such as numbers of people in older age groups) and other underlying variations. Counts below 5 are removed from the data. The data is updated annually. Sources: NHS Digital (now part of NHS England) - dataset P02177, and commentary from the Office for Health Improvement and Disparities (OHID) Public Health Outcomes Framework (PHOF) indicator 2.17 Recorded Diabetes.

Making clinical audit data transparent In his transparency and open data letter to Cabinet Ministers on 7 July 2011, the Prime Minister made a commitment to make clinical audit data available from the national audits within the National Clinical Audit and Patient Outcomes Programme. Each year data from the National Diabetes Audit will be made available in CSV format. The data are also being made available on the data.gov website. What information is being made available? Audit participation by Primary Care Trusts (PCTs) Measures about the process of care given to patients. Information about care outcomes and treatment. Information about complications and mortality PCTs are identified by name and their national code. These data do not list individual patient information, nor do they contain any patient identifiable data. The National Diabetes Audit is a high profile, collaborative, national clinical audit for diabetes. The National Diabetes Audit was run by the NHS Information Centre with Diabetes UK and Yorkshire and Humber Public Heath Observatory, commissioned by HQIP. The audit aims to improve the quality of care in people with diabetes. It meets the requirements as set out in the NICE guidelines. The National Diabetes Audit 2010/11 covers the time period from 1 January 2010 up to 31 March 2011 with information from GP Practices and specialist diabetes units in England.

Chronic Health Condition Prevalence in Stockport, UK, 2016

Counts of Hypertension, Anxiety, Diabetes and Other Chronic Health Conditions

By data.world's Admin [source]

About this dataset

This dataset contains crucial information regarding the prevalence of various health conditions affecting Stockport, UK, in June 2016. This dataset will help you better understand the prevalence rates of Hypertension, Anxiety, Depression, Asthma, Obesity, Diabetes, Coronary Heart Disease (CHD), Falls (both accidental and medical-related), Cancer (various forms listed), Chronic Kidney Disease (CKD), Chronic Obstructive Pulmonary Disease (COPD) , Stroke/Trans-Ischaemic Attack and Atrial Fibrillation amongst individuals living in Lower Layer Super Output Areas across Stockport which are grouped by codes. The count of individuals affected by each condition cited is provided along with the GP Registered Population for each LSOA which typically ranges from 1000 to 2000 people per LSOA. This data could be utilized to identify areas most impacted by healthcare related issues from a geographical perspective as well as help provide insight into chronic illnesses that may require further attention throughout Stockport's communities

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How to use the dataset

The data contained in this dataset consists of information on chronic health conditions gathered from Lower Layer Super Output Areas (LSOA) located in Stockport, UK for June 2016. The count information provided pertains to Hypertension, Anxiety, Depression, Asthma, Obesity, Diabetes, Coronary Heart Disease (CHD), Falls, Cancer and Chronic Kidney Disease (CKD), Chronic Obstructive Pulmonary Disease (COPD), Stroke/Trans-Ischaemic Attack and Atrial Fibrillation.

• To get a better understanding of what this dataset looks like we will start by reviewing the columns it contains. The columns contain information about: Lower Layer Super Output Area Code(lsoa11cd), Lower Layer Super Output Area Name(lsoa11nm & lsoa11nmw for Welsh language version) , GP Registered Population(GPRegPop), Hypertension (Hypertens), Anxiety(Anxiety), Depression(Depression) ect .

• To get an overview of what this dataset is about use a summary statistic tool such as mean(), median(), mode() etc to aggregate your data. This can be done by computing each column’s summary statistics separately or by combining them into one table for every condition listed here. This way you can obtain an overview which accurately reflects the overall population distribution pertaining to particular chronic health condition across multiple LSOA's at one time frame only.

• For deeper analysis refine your finding further or delve down into cause and effect make use graphs & charts such as scatter plots or line charts etc,. as well correlational analysis such Joint Analysis/Common Factor Analysis & Multiple Regression Analysis which will give you an insight into co-occurrence frequency or other related variables whcih could play a role in any particular health condition cause and affect outcomes over a period of time allowing further investigation if needed be pertaining suspected underlying causes regarding chronic medical conditions observed .

• Finally it is important that comprehensive datasets are created using wide range factors relevant local determinants before drawing conclusions so allow public bodies with decision making power make informed decisions accordingly when devising strategies for tackling causes associated with specific chronic medical coniditons target population groups required provide assistance towards public welfare goal become more efficient targeting

Research Ideas

• Analyzing the geographic variation of health conditions in Stockport in order to inform public health policy decisions. For example, to identify areas where specific interventions are needed to improve healthcare outcomes, or target resources at particular (at-risk) populations.
• Examining the correlations between different health conditions and identifying potential links or risk factors for developing one condition when another is present.
• Utilizing the GP registered population for each LSOA as a metric for predicting which areas of Stockport are likely to require additional funds or resources in order ensure adequate access to healthcare services for their residents

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more informat...

This set of files contains public data used to validate the grocery data. All references to the original sources are provided below.CHILD OBESITYPeriodically, the English National Health Service (NHS) publishes statistics about various aspects of the health and habits of people living in England, including obesity. The NHS National Child Measurement (NCMP) measures the height and weight of children in Reception class (aged 4 to 5) and year 6 (aged 10 to 11), to assess overweight and obesity levels in children within primary schools. The program is carried out every year in England and statistics are produced at the level of Local Authority (that corresponds to Boroughs in London). We report the data for the school year 2015-2016 (file: child_obesity_london_borough_2015-2016.csv). For the school year 2013-2014, statistics in London are also available at ward-level (file: child_obesity_london_ward_2013-2014.csv)The files are comma-separated and contain the following fields: area_id: the id of the boroughnumber_reception_measured: number of children in reception year measurednumber_y6_measured: number of children in reception year measuredprevalence_overweight_reception: the prevalence (percentage) of overweight children in reception year prevalence_overweight_y6: the prevalence (percentage) of overweight children in year 6prevalence_obese_reception: the prevalence (percentage) of obese children in reception yearprevalence_obese_y6: the prevalence (percentage) of obese children in year 6ADULT OBESITYThe Active People Survey (APS) was a survey used to measure the number of adults taking part in sport across England and included two questions about the height and weight of participants. We report the results of the APS for the year 2012. Prevalence of underweight, healthy weight, overweight, and obese people at borough level are provided in the file london_obesity_borough_2012.csv.The file is comma-separated and contains the following fields: area_id: the id of the boroughnumber_measured: number of people who participated in the surveyprevalence_healthy_weight: the prevalence (percentage) of healthy-weight peopleprevalence_overweight: the prevalence (percentage) of overweight peopleprevalence_obese: the prevalence (percentage) of obese peopleBARIATRIC HOSPITALIZATIONThe NHS records and publishes an annual compendium report about the number of hospital admissions attributable to obesity or bariatric surgery (i.e., weight loss surgery used as a treatment for people who are very obese), and the number of prescription items provided in primary care for the treatment of obesity. The NHS provides both raw counts at the Local Authority level and numbers normalized by population living in those areas. In the file obesity_hospitalization_borough_2016.csv, we report the statistics for the year 2015 (measurements made between Jan 2015 and March 2016).The file is comma-separated and contains the following fields:area_id: the id of the boroughtotal_hospitalizations: total number of obesity-related hospitalizationstotal_bariatric: total number of hospitalizations for bariatric surgeryprevalence_hospitalizations: prevalence (percentage) of obesity-related hospitalizations prevalence_bariatric: prevalence (percentage) of bariatric surgery hospitalizations DIABETESThrough the Quality and Outcomes Framework, NHS Digital publishes annually the number of people aged 17+ on a register for diabetes at each GP practice in England. NHS also publishes the number of people living in a census area who are registered to any of the GP in England. Based on these two sources, an estimate is produced about the prevalence of diabetes in each area. The data (file diabetes_estimates_osward_2016.csv) was collected in 2016 at LSOA-level and published at ward-level.The file is comma-separated and contains the following fields:area_id: the id of the wardgp_patients: total number of GP patients gp_patients_diabetes: total number of GP patients with a diabetes diagnosisestimated_diabetes_prevalence: prevalence (percentage) of diabetesAREA MAPPINGMapping of Greater London postcodes into larger geographical aggregations. The file is comma-separated and contains the following fields:pcd: postcodelat: latitudelong: longitudeoa11: output arealsoa11: lower super output areamsoa11: medium super output areaosward: wardoslaua: borough

This dataset presents the percentage of individuals with type 2 diabetes who have received all eight recommended care processes as defined by the National Diabetes Audit (NDA). These care processes are essential checks and tests that support effective monitoring and management of diabetes. They include measurements and assessments such as body mass index (BMI), blood pressure, smoking status, HbA1c, cholesterol, urine albumin, serum creatinine, and foot examination for nerve and circulation health. The dataset provides a comprehensive view of how well healthcare providers are delivering routine diabetes care.

Rationale

Receiving all eight care processes is associated with improved monitoring and early detection of complications in people with type 2 diabetes. This indicator helps evaluate the consistency and quality of routine diabetes care and supports efforts to enhance patient outcomes through comprehensive clinical assessments.

Numerator

The numerator includes the number of individuals with type 2 diabetes who received all eight care processes within the audit period. These processes are: BMI measurement, blood pressure check, smoking status recording, HbA1c test, cholesterol test, urine albumin test, serum creatinine test, and foot examination for nerve and circulation health. Data is sourced from the National Diabetes Audit (NDA) and NHS England.

Denominator

The denominator includes all individuals registered with type 2 diabetes at GP practices participating in the National Diabetes Audit. This ensures a consistent and representative population base for calculating the indicator.

Caveats

Data is collected over a 15-month period

Localities ExplainedThis dataset contains data based on either the resident locality or registered locality of the patient, a distinction is made between resident locality and registered locality populations:Resident Locality refers to individuals who live within the defined geographic boundaries of the locality. These boundaries are aligned with official administrative areas such as wards and Lower Layer Super Output Areas (LSOAs).Registered Locality refers to individuals who are registered with GP practices that are assigned to a locality based on the Primary Care Network (PCN) they belong to. These assignments are approximate—PCNs are mapped to a locality based on the location of most of their GP surgeries. As a result, locality-registered patients may live outside the locality, sometimes even in different towns or cities.This distinction is important because some health indicators are only available at GP practice level, without information on where patients actually reside. In such cases, data is attributed to the locality based on GP registration, not residential address.

Click here to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.

This dataset provides the percentage of individuals aged 40 to 64 who are registered with type 2 diabetes, based on data from GP practices participating in the National Diabetes Audit (NDA). It offers insights into the burden of type 2 diabetes within this age group and supports efforts to monitor and reduce its prevalence through targeted public health interventions.

Rationale The indicator aims to reduce the prevalence of type 2 diabetes among adults aged 40 to 64. Monitoring this age group is critical, as early detection and management of diabetes can significantly reduce the risk of complications and improve long-term health outcomes.

Numerator The numerator is the number of people aged 40 to 64 who are registered with type 2 diabetes at GP practices that participate in the National Diabetes Audit.

Denominator The denominator is the total number of people registered with type 2 diabetes at participating GP practices, regardless of age.

Caveats The data is collected over a 15-month period, from January 1st of the first year to March 31st of the following year. Individuals not registered with a GP practice at the time of data collection are excluded. From 2022–23 onwards, values are not reported where the denominator is 20 or fewer, to protect confidentiality and ensure data reliability.

External references Public Health England - Fingertips: Prevalence of type 2 diabetes

Click here to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.

This dataset provides the percentage of individuals aged 40 to 64 who are registered with type 2 diabetes, based on data from GP practices participating in the National Diabetes Audit (NDA). It offers insights into the burden of type 2 diabetes within this age group and supports efforts to monitor and reduce its prevalence through targeted public health interventions.

Rationale The indicator aims to reduce the prevalence of type 2 diabetes among adults aged 40 to 64. Monitoring this age group is critical, as early detection and management of diabetes can significantly reduce the risk of complications and improve long-term health outcomes.

Numerator The numerator is the number of people aged 40 to 64 who are registered with type 2 diabetes at GP practices that participate in the National Diabetes Audit.

Denominator The denominator is the total number of people registered with type 2 diabetes at participating GP practices, regardless of age.

Caveats The data is collected over a 15-month period, from January 1st of the first year to March 31st of the following year. Individuals not registered with a GP practice at the time of data collection are excluded. From 2022–23 onwards, values are not reported where the denominator is 20 or fewer, to protect confidentiality and ensure data reliability.

External references Public Health England - Fingertips: Prevalence of type 2 diabetes

Localities ExplainedThis dataset contains data based on either the resident locality or registered locality of the patient, a distinction is made between resident locality and registered locality populations:Resident Locality refers to individuals who live within the defined geographic boundaries of the locality. These boundaries are aligned with official administrative areas such as wards and Lower Layer Super Output Areas (LSOAs).Registered Locality refers to individuals who are registered with GP practices that are assigned to a locality based on the Primary Care Network (PCN) they belong to. These assignments are approximate—PCNs are mapped to a locality based on the location of most of their GP surgeries. As a result, locality-registered patients may live outside the locality, sometimes even in different towns or cities.This distinction is important because some health indicators are only available at GP practice level, without information on where patients actually reside. In such cases, data is attributed to the locality based on GP registration, not residential address.

Click here to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.

Indirectly age and sex standardised ratio of complications associated with diabetes including emergency admissions for diabetic ketoacidosis and lower limb amputation, in people with diabetes. Current version updated: Sep-17 Next version due: Sep-18

The National Diabetes Audit (NDA) provides a comprehensive view of diabetes care in England and Wales. It measures the effectiveness of diabetes healthcare against the National Institute for Health and Care Excellence (NICE) Clinical Guidelines and NICE Quality Standards. This NICE guidance is based on evidence that regular systematic review of people with diabetes and achievement of glucose, blood pressure and cardiovascular risk standards maintains health and reduces long term complications.

The National Diabetes Audit (NDA) and the National Paediatric Diabetes Audit (NPDA) provide a comprehensive view of diabetes care in England and Wales. They measure the effectiveness of diabetes healthcare against NICE Clinical Guidelines and NICE Quality Standards. The Young People with Type 2 Diabetes report aims to document the number of people with type 2 diabetes up to the age of 40 years, their characteristics and the diabetes care they receive. This is important because adverse diabetes and cardiovascular outcomes are more common in people who develop diabetes at an early age and it is thought the numbers are increasing.