Rate: Age-adjusted death rate, number of deaths due to diabetes, per 100,000 population.

Definition: Deaths with diabetes as the underlying cause of death (ICD-10 codes: E10-E14).

Data Sources:

(1) Death Certificate Database, Office of Vital Statistics and Registry, New Jersey Department of Health

(2) Population Estimates, State Data Center, New Jersey Department of Labor and Workforce Development

This dataset contains information on the total proportion of adults diagnosed with diabetes, collected from the system of health-related telephone surveys, the Behavioral Risk Factor Surveillance System (BRFSS), conducted in more than 400,000 patients, from 50 states in the US, the District of Columbia and three US territories.

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.

Provisional death counts of diabetes, coronavirus disease 2019 (COVID-19) and other select causes of death, by month, sex, and age.

India IN: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data was reported at 19.800 NA in 2016. This records a decrease from the previous number of 20.000 NA for 2015. India IN: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data is updated yearly, averaging 21.200 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 23.400 NA in 2000 and a record low of 19.800 NA in 2016. India IN: 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 India – Table IN.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;

Deaths 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

It was estimated that as of 2023, around **** million people in the United States had been diagnosed with diabetes. The number of people diagnosed with diabetes in the U.S. has increased in recent years and the disease is now a major health issue. Diabetes is now the seventh leading cause of death in the United States, accounting for ******percent of all deaths. What is prediabetes? A person is considered to have prediabetes if their blood sugar levels are higher than normal but not high enough to be diagnosed with type 2 diabetes. As of 2021, it was estimated that around ** million men and ** million women in the United States had prediabetes. However, according to the CDC, around ** percent of these people do not know they have this condition. Not only does prediabetes increase the risk of developing type 2 diabetes, but also increases the risk of heart disease and stroke. The states with the highest share of adults who had ever been told they have prediabetes are California, Hawaii, and New Mexico. The prevalence of diabetes in the United States As of 2023, around *** percent of adults in the United States had been diagnosed with diabetes, an increase from ****percent in the year 2000. Diabetes is much more common among older adults, with around ** percent of those aged 60 years and older diagnosed with diabetes, compared to just ****percent of those aged 20 to 39 years. The states with the highest prevalence of diabetes among adults are West Virginia, Mississippi, and Louisiana, while Utah and Colorado report the lowest rates. In West Virginia, around ** percent of adults have been diagnosed with diabetes.

Nigeria NG: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data was reported at 22.500 % in 2016. This stayed constant from the previous number of 22.500 % for 2015. Nigeria NG: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data is updated yearly, averaging 22.900 % from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 25.500 % in 2000 and a record low of 22.500 % in 2016. Nigeria NG: 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 Nigeria – Table NG.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;

United States US: Diabetes Prevalence: % of Population Aged 20-79 data was reported at 10.790 % in 2017. United States US: Diabetes Prevalence: % of Population Aged 20-79 data is updated yearly, averaging 10.790 % from Dec 2017 (Median) to 2017, with 1 observations. United States US: 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 USA – Table US.World Bank: 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;

This is historical data. The update frequency has been set to "Static Data" and is here for historic value. Updated 8/14/2024.

Number of deaths among Maryland residents for which diabetes mellitus was the underlying cause of death. This includes deaths coded to the following International Classification of Diseases codes: ICD-3 (1920-1929) -- 57 ICD-4 (1930-1938) -- 59 ICD-5 (1939-1948) -- 61 ICD-6 (1949-1957) -- 260 ICD-7 (1958-1967) -- 260 ICD-8 (1968-1978) -- 250 ICD-9 (1979-1998) -- 250 ICD-10 (1999-present) -- E10-E14.

Note: This dataset is historical only and there are not corresponding datasets for more recent time periods. For that more-recent information, please visit the Chicago Health Atlas at https://chicagohealthatlas.org.

This dataset contains the annual number of hospital discharges, crude hospitalization rates with corresponding 95% confidence intervals, and age-adjusted hospitalization rates with corresponding 95% confidence intervals, for the years 2000 – 2011, by Chicago U.S. Postal Service ZIP code or ZIP code aggregate. See the full description at http://bit.ly/Os5wnn.

This dataset tracks the updates made on the dataset "Public Health Statistics- Diabetes hospitalizations in Chicago, 2000 - 2011" as a repository for previous versions of the data and metadata.

Nigeria NG: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data was reported at 20.900 NA in 2016. This records an increase from the previous number of 20.800 NA for 2015. Nigeria NG: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data is updated yearly, averaging 21.000 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 22.600 NA in 2000 and a record low of 20.800 NA in 2015. Nigeria NG: 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 Nigeria – Table NG.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;

Saudi Arabia SA: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data was reported at 16.400 % in 2016. This records a decrease from the previous number of 16.500 % for 2015. Saudi Arabia SA: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data is updated yearly, averaging 17.900 % from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 18.900 % in 2000 and a record low of 16.400 % in 2016. Saudi Arabia SA: 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 Saudi Arabia – Table SA.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;

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

Age-adjusted rate of diabetes deaths by sex, race/ethnicity, age; trends if available. Source: Santa Clara County Public Health Department, VRBIS, 2007-2016. Data as of 05/26/2017; U.S. Census Bureau; 2010 Census, Tables PCT12, PCT12H, PCT12I, PCT12J, PCT12K, PCT12L, PCT12M; generated by Baath M.; using American FactFinder; Accessed June 20, 2017. METADATA:Notes (String): Lists table title, notes and sources.Year (Numeric): Year of data.Category (String): Lists the category representing the data: Santa Clara County is for total population, sex: Male and Female, race/ethnicity: African American, Asian/Pacific Islander, Latino and White (non-Hispanic White only); age categories as follows: 18 to 24, 25 to 34, 35 to 44, 45 to 54, 55 to 64, 65 to 74, 75 to 84, 85+; United States.Rate per 100,000 people (Numeric): Rate of diabetes deaths. Rates for age groups are reported as age-specific rates per 100,000 people. All other rates are age-adjusted rates per 100,000 people.

BackgroundData on the future diabetes burden in Scandinavia is limited. Our aim was to project the future burden of diabetes in Sweden by modelling data on incidence, prevalence, mortality, and demographic factors.MethodTo project the future burden of diabetes we used information on the prevalence of diabetes from the national drug prescription registry (adults ≥20 years), previously published data on relative mortality in people with diabetes, and population demographics and projections from Statistics Sweden. Alternative scenarios were created based on different assumptions regarding the future incidence of diabetes.ResultsBetween 2007 and 2013 the prevalence of diabetes rose from 5.8 to 6.8% in Sweden but incidence remained constant at 4.4 per 1000 (2013). With constant incidence and continued improvement in relative survival, prevalence will increase to 10.4% by year 2050 and the number of afflicted individuals will increase to 940 000. Of this rise, 30% is accounted for by changes in the age structure of the population and 14% by improved relative survival in people with diabetes. A hypothesized 1% annual rise in incidence will result in a prevalence of 12.6% and 1 136 000 cases. Even with decreasing incidence at 1% per year, prevalence of diabetes will continue to increase.ConclusionWe can expect diabetes prevalence to rise substantially in Sweden over the next 35 years as a result of demographic changes and improved survival among people with diabetes. A dramatic reduction in incidence is required to prevent this development.

Ivory Coast CI: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data was reported at 28.200 NA in 2016. This records a decrease from the previous number of 28.500 NA for 2015. Ivory Coast CI: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data is updated yearly, averaging 27.700 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 28.500 NA in 2015 and a record low of 25.200 NA in 2000. Ivory Coast CI: 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 Ivory Coast – Table CI.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;

United States US: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data was reported at 17.500 NA in 2016. This records an increase from the previous number of 17.200 NA for 2015. United States US: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data is updated yearly, averaging 17.500 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 21.600 NA in 2000 and a record low of 17.200 NA in 2015. United States US: 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 States – Table US.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;

Time series data for the statistic Mortality from CVD, cancer, diabetes or CRD between exact ages 30 and 70 (%) and country Poland. Indicator Definition: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).The indicator "Mortality from CVD, cancer, diabetes or CRD between exact ages 30 and 70 (%)" stands at 17.00 as of 12/31/2021, the lowest value at least since 12/31/2001, the period currently displayed. Regarding the One-Year-Change of the series, the current value constitutes a decrease of -3.95 percent compared to the value the year prior.The 1 year change in percent is -3.95.The 3 year change in percent is -6.59.The 5 year change in percent is -8.60.The 10 year change in percent is -15.00.The Serie's long term average value is 20.72. It's latest available value, on 12/31/2021, is 17.95 percent lower, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2021, to it's latest available value, on 12/31/2021, is +0.0%.The Serie's change in percent from it's maximum value, on 12/31/2000, to it's latest available value, on 12/31/2021, is -32.00%.