To reduce deaths from diabetes.

Mortality from diabetes (ICD-10 E10-E14 equivalent to ICD-9 250). To reduce deaths from diabetes. Legacy unique identifier: P00300

United Kingdom UK: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data was reported at 10.900 % in 2016. This records a decrease from the previous number of 11.200 % for 2015. United Kingdom UK: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data is updated yearly, averaging 12.200 % from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 16.400 % in 2000 and a record low of 10.900 % in 2016. United Kingdom UK: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s UK – Table UK.World Bank: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted Average;

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.

Portugal had the highest prevalence of diabetes in Europe among their adult population with **** percent living with diabetes, as of 2024, Croatia followed with the second-highest share at **** percent. Conversely, Ireland was the country with the lowest prevalence of diabetes in Europe at *** percent. Diabetes-related deaths The highest number of diabetes-related deaths in Europe, at almost ******, was recorded in Germany in 2024. Italy and France followed, with roughly *******and ****** deaths, respectively. Diabetes risk factors in Europe One of the major contributing factors to type 2 diabetes is being overweight or obese. As of 2022, Greece had the highest share of overweight population across Europe, with *****percent. The lack of sports and exercise is also another risk factor. As of 2022, Portugal was the European country with the highest share of people never exercising or engaging in sports, with ** percent.

United Kingdom UK: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data was reported at 12.900 NA in 2016. This records a decrease from the previous number of 13.300 NA for 2015. United Kingdom UK: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data is updated yearly, averaging 14.600 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 20.000 NA in 2000 and a record low of 12.900 NA in 2016. United Kingdom UK: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male 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. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

Years of Life Lost (YLL) as a result of death from diabetes. Directly age-Standardised Rates (DSR) per 100,000 population Source: Office for National Statistics (ONS) Publisher: Information Centre (IC) - Clinical and Health Outcomes Knowledge Base Geographies: Local Authority District (LAD), Government Office Region (GOR), National, Strategic Health Authority (SHA) Geographic coverage: England Time coverage: 2005-07, 2007 Type of data: Administrative data

BackgroundEstimated glucose disposal rate (eGDR) was a novel non-insulin-based marker of insulin resistance (IR), which had been used in many studies to evaluate the clinical prognosis of diabetes. However, the association of eGDR with atrial fibrillation (AF), heart failure (HF) and cardiovascular mortality in patients with diabetes remains unclear.MethodsThe study utilized UK Biobank data from 31,733 participants. Kaplan-Meier curves and Log-rank tests assessed AF, HF, and cardiovascular mortality incidence. Multivariate Cox models and restricted cubic splines analyzed the associations of eGDR with these outcomes. Polygenic Risk Score (PRS) analysis evaluated the joint effects of eGDR and PRS. Boruta algorithm filtered key predictive variables. Subgroup analysis was performed using cardiovascular high-risk factors, and mediation analysis explored the relationships of eGDR with the outcomes.ResultsSubjects with higher eGDR were more likely to be female, younger, more physically active, non-smoker, and non-drinker. The cumulative incidence of AF, HF, and cardiovascular mortality in the higher quartiles of GDR were significantly lower than those in the lowest quartile (log-rank P < 0.001 for all). eGDR exhibited an independent negative linear correlation with the risk of AF (HR = 0.94, 95% CI: 0.91-0.96), HF (HR = 0.78, 95% CI: 0.74-0.82), and cardiovascular mortality (HR = 0.86, 95% CI: 0.83-0.88) risk. eGDR made the most significant contribution to the predicted outcomes. In diabetic patients with high genetic susceptibility, high eGDR could reduce the risk of AF (HR = 0.68, 95% CI: 0.51-0.90), HF (HR = 0.43, 95% CI: 0.29-0.62), and cardiovascular mortality (HR = 0.30, 95% CI: 0.22-0.42). Mediation analysis demonstrated that 10.7%, 7.9%, and 10.3% of the relationship between eGDR and AF, HF, and cardiovascular mortality among individuals with diabetes were mediated by eGFR, respectively.ConclusionsThis study demonstrated that higher eGDR levels were associated with a decreased risk of AF, HF, and cardiovascular mortality. Therefore, eGDR may serve as a valuable tool for predicting the risk of AF, HF, and cardiovascular mortality in patients with diabetes.

Forecast: Diabetes Mellitus Mortality in the UK 2024 - 2028 Discover more data with ReportLinker!

UK: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data was reported at 9.000 NA in 2016. This records a decrease from the previous number of 9.200 NA for 2015. UK: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data is updated yearly, averaging 9.800 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 12.900 NA in 2000 and a record low of 9.000 NA in 2016. UK: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female 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. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

Actual value and historical data chart for United Kingdom Mortality From Cvd Cancer Diabetes Or Crd Between Exact Ages 30 And 70 Percent

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Background: Diabetes mellitus affects over 3.9 million people in the United Kingdom (UK), with over 2.6 million people in England alone. More than 1 million people living with diabetes are acutely admitted to hospital due to complications of their illness every year. Cardiovascuar disease is the most prevalent cause of morbidity and mortality in people with diabetes. Diabetic retinopathy (DR) is a common microvascular complication of type 1 and type 2 diabetes and remains a major cause of vision loss and blindness in those of working age. This dataset includes the national screening diabetic grade category (seven categories from R0M0 to R3M1) from the Birmingham, Solihull and Black Country DR screening program (a member of the National Health Service (NHS) Diabetic Eye Screening Programme) and the University Hospitals Birmingham NHS Trust cardiac outcome data.

Geography: The West Midlands has a population of 5.9 million. The region includes a diverse ethnic, and socio-economic mix, with a higher than UK average of minority ethnic groups. It has a large number of elderly residents but is the youngest population in the UK. There are particularly high rates of diabetes, physical inactivity, obesity, and smoking.

Data sources:
1. The Birmingham, Solihull and Black Country Data Set, University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom. They manage over 200,000 diabetic patients, with longitudinal follow-up up to 15 years, making this the largest urban diabetic eye screening scheme in Europe. 2. The Electronic Health Records held at University Hospitals Birmingham NHS Foundation Trust is one of the largest NHS Trusts in England, providing direct acute services and specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds and 100 ITU beds. UHB runs a fully electronic healthcare record for systemic disease.

Scope: All Birmingham, Solihull and Black Country diabetic eye screened participants who have been admitted to UHB with a cardiac related health concern from 2006 onwards. Longitudinal and individually linked with their diabetic eye care from primary screening data and secondary care hospital cardiac outcome data including • Demographic information (including age, sex and ethnicity) • Diabetes status • Diabetes type • Length of time since diagnosis of diabetes • Visual acuity • The national screening diabetic screening grade category (seven categories from R0M0 to R3M1) • Diabetic eye clinical features • Reason for sight and severe sight impairment • ICD-10 and SNOMED-CT codes pertaining to cardiac disease • Outcome

Website: https://www.retinalscreening.co.uk/

Up to 30% of older adults (aged 65 years and older) have been diagnosed with Diabetes mellitus. Older diabetics are more likely to experience complications like heart disease, stroke, kidney problems, and nerve damage, leading to higher hospital admission rates.  When managing older diabetic patients, healthcare professionals need to consider factors like frailty, polypharmacy (multiple medications), and potential cognitive impairments. 

This dataset includes 83,303 people and 366,035 spells, designed to support research which improves diabetic emergency and unplanned care in older adults. It includes highly granular patient demographics & co-morbidities taken from ICD-10 & SNOMED-CT codes. Serial, structured data pertaining to acute care process, presenting complaints, admissions, microbiology results, referrals, all physiology readings (pulse, blood pressure, respiratory rate, oxygen saturations and others), all blood results (urea, albumin, platelets, white blood cells and others). Includes all prescribed & administered treatments and all outcomes. Linked images are also available (radiographs, CT scans, MRI).

Geography: The West Midlands (WM) has a population of 6 million & includes a diverse ethnic & socio-economic mix. 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 & > 120 ITU bed capacity. 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”.

Data set availability: Data access is available via the PIONEER Hub for projects which will benefit the public or patients. This can be by developing a new understanding of disease, by providing insights into how to improve care, or by developing new models, tools, treatments, or care processes. Data access can be provided to NHS, academic, commercial, policy and third sector organisations. Applications from SMEs are welcome. There is a single data access process, with public oversight provided by our public review committee, the Data Trust Committee. Contact pioneer@uhb.nhs.uk or visit www.pioneerdatahub.co.uk for more details.

Available supplementary data: Matched controls; ambulance and community data. Unstructured data (images). We can provide the dataset in OMOP and other common data models and can build synthetic data to meet bespoke requirements.

Available supplementary support: Analytics, model build, validation & refinement; A.I. support. Data partner support for ETL (extract, transform & load) processes. Bespoke and “off the shelf” Trusted Research Environment (TRE) build and run. Consultancy with clinical, patient & end-user and purchaser access/ support. Support for regulatory requirements. Cohort discovery. Data-driven trials and “fast screen” services to assess population size

Deaths registered in England and Wales in 2020 and how they compared with the five-year average (2015 to 2019), based on finalised 2020 mortality data. The figures are broken down by cause, place of death, age group, sex and deprivation.

1The first number relates to the total number of women included in the analyses, while the second relates to the number of men.HRs for all-cause and cause-specific mortality by glycated haemoglobin and diagnosed diabetes category, stratified by sex.

1 Normoglycaemic/no diabetes: those who neither indicated diabetes nor had a raised HbA1C measurement (

Background.

Diabetes mellitus affects over 3.9 million people in the United Kingdom (UK), with over 2.6 million people in England alone. Each year more than 1 million people with diabetes are acutely admitted to hospital due to complications of their illness. This includes Diabetic emergencies such as Diabetic Comas, Hypoglycaemia, Diabetic ketoacidosis, and Diabetic Hyperosmolar Hyperglycaemic State. Diabetic emergency management is often not compliant with national guidelines, and there is a pressing need to improve patient care. This dataset includes 65,506 people and 168,706 spells, designed to support research which improves diabetic emergency and unplanned care.

Other causes for admission include diabetic ulcers, neuropathies, kidney disease and associated co-morbidities such as infection, cerebrovascular disease and cardiovascular disease. This dataset includes acute all diabetic admissions to University Hospitals Birmingham NHS Trust from 2000 onwards refreshed to include new admissions as they occur.

PIONEER geography The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix.

EHR. 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 & an expanded 250 ITU bed capacity during COVID. 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: All patients admitted to hospital from year 2002 and onwards, curated to focus on Diabetes. 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 & co-morbidities taken from ICD-10 & SNOMED-CT codes. Serial, structured data pertaining to acute care process (timings, staff grades, specialty review, wards and triage). Along with presenting complaints, outpatients admissions, microbiology results, referrals, procedures, therapies, all physiology readings (pulse, blood pressure, respiratory rate, oxygen saturations and others), all blood results(urea, albumin, platelets, white blood cells and others). Includes all prescribed & administered treatments and all outcomes. Linked images are also available (radiographs, CT scans, MRI).

Available supplementary data: Matched controls; ambulance, OMOP 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.

Background: Diabetes mellitus affects over 3.9 million people in the United Kingdom (UK), with over 2.6 million people in England alone. More than 1 million people living with diabetes are acutely admitted to hospital due to complications of their illness every year. Complications include Diabetic emergencies such as Diabetic Comas, Hypoglycaemia, Diabetic ketoacidosis and Diabetic Hyperosmolar Hyperglycaemic State. Diabetic retinopathy (DR) is a common microvascular complication of type 1 and type 2 diabetes and remains a major cause of vision loss and blindness in those of working age. This dataset includes acute all diabetic admissions to University Hospitals Birmingham NHS Trust from 2000 onwards with linked eye data including the national screening diabetic grade category (seven categories from R0M0 to R3M1) from the Birmingham, Solihull and Black Country DR screening program (a member of the National Health Service (NHS) Diabetic Eye Screening Programme) and the University Hospitals Birmingham NHS Trust Ophthalmology clinic at Queen Elizabeth Hospital, Birmingham .

Geography: The West Midlands has a population of 5.9 million. The region includes a diverse ethnic, and socio-economic mix, with a higher than UK average of minority ethnic groups. It has a large number of elderly residents but is the youngest population in the UK. There are particularly high rates of diabetes, physical inactivity, obesity, and smoking.

Data sources:
1. The Birmingham, Solihull and Black Country Data Set, University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom. They manage over 200,000 diabetic patients, with longitudinal follow-up up to 15 years, making this the largest urban diabetic eye screening scheme in Europe. 2. The Electronic Health Records held at University Hospitals Birmingham NHS Foundation Trust is one of the largest NHS Trusts in England, providing direct acute services and specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds and 100 ITU beds. UHB runs a fully electronic healthcare record both for systemic disease as well as the Ophthalmology records.

Scope: All hospitalised patients admitted to UHB with a diabetes related health concern from 2000 onwards. Longitudinal and individually linked with their diabetic eye care from primary screening data and secondary care ophthalmology data including • Demographic information (including age, sex and ethnicity) • Diabetes status • Diabetes type • Length of time since diagnosis of diabetes • Visual acuity • The national screening diabetic screening grade category (seven categories from R0M0 to R3M1) • Diabetic eye clinical features • Reason for sight and severe sight impairment • ICD-10 and SNOMED-CT codes pertaining to diabetes • Diagnosis for the acute/emergency admission • Co-morbid conditions • Medications • Outcome

英国 UK: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male在2016达12.900 NA，相较于2015的13.300 NA有所下降。英国 UK: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male数据按每年更新，2000至2016期间平均值为14.600 NA，共5份观测结果。该数据的历史最高值出现于2000，达20.000 NA，而历史最低值则出现于2016，为12.900 NA。CEIC提供的英国 UK: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male数据处于定期更新的状态，数据来源于World Bank，数据归类于Global Database的英国 – Table UK.World Bank.WDI: Health Statistics。

In 2021, **** percent of deaths from strokes in the UK were attributable to high blood pressure, also known as hypertension. Furthermore, **** percent of deaths were attributable to high LDL cholesterol, while ** percent of stroke deaths were due to diabetes.