Around ** percent of the global adult population suffered from diabetes in 2024 - by the year 2050 this number is expected to rise to ** percent. Diabetes, or diabetes mellitus, refers to a group of metabolic disorders that result in chronic high blood sugar levels. Diabetes can lead to serious health complications, such as cardiovascular disease, chronic kidney disease, and stroke, and is now among the top ten leading causes of death worldwide. Prevalence Diabetes is a global problem affecting many countries. China currently has the largest number of diabetics worldwide, with some *** million people suffering from the disease. However, the highest prevalence of diabetes is found in Pakistan, followed by the Marshall Islands and Kuwait. Rates of diabetes have increased in many countries in recent years, as have rates of obesity, one of the leading risk factors for the disease. Outlook It is predicted that diabetes will continue to be a problem in the future. Africa is expected to see a *** percent increase in the number of diabetics in the region from 2024 to 2050, while North America and the Caribbean are expected to see an increase of ** percent. In 2050, China is predicted to be the country with the highest number of diabetics worldwide, with the United States accounting for the fourth-highest number.

This statistic shows the percentage of the U.S. population aged 20 years and over with diabetes in periods between 1988 and 2018. In the 2015-2018 period, there were some estimated ** * percent of the U.S. population aged 20 years and over with diabetes.

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;

In 2024, around 16 percent of adults between the ages of 20 and 79 had diabetes in Turkey. Other selected countries with a high prevalence of diabetes that year included Mexico, the United States, and Portugal. Diabetes is a metabolic disease that causes high blood sugar levels. Diabetes worldwide In 2024, an estimated 11 percent of the global adult population had diabetes. In concrete numbers, there were about 589 million diabetic adults (20-79 years) worldwide in 2024, and this total is predicted to grow to approximately 852.5 million by the year 2050. Spending per patient The country that spent the most on patients with diabetes in 2024 was Switzerland. At that time, providing for a diabetic patient in Switzerland cost an average of over 12 thousand U.S. dollars. The United States stood in second place, spending about 10,500 U.S. dollars per patient. In the same year, the ten countries by lowest average spending per person with diabetes were all African and Asian countries. Bangladesh had the lowest annual diabetes-related health expenditures per person, with just 74 U.S. dollars.

In 2021, close to ** percent of the population in Pakistan had diabetes. In comparison, Vietnam had the lowest prevalence of diabetic people across the Asia-Pacific region that year, approximately *** percent.

Diabetes prevalence (% of population ages 20 to 79) in United States was reported at 13.7 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. United States - Diabetes prevalence (% of population ages 20 to 79) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Diabetes prevalence in Massachusetts has been steadily increasing.

Number and percentage of persons having been diagnosed with diabetes, by age group and sex.

Indonesia: Diabetes prevalence, percent of population ages 20-79: The latest value from 2021 is 10.6 percent, an increase from 5.1 percent in 2011. In comparison, the world average is 8.60 percent, based on data from 195 countries. Historically, the average for Indonesia from 2011 to 2021 is 7.85 percent. The minimum value, 5.1 percent, was reached in 2011 while the maximum of 10.6 percent was recorded in 2021.

Population-based county-level estimates for diagnosed (DDP), undiagnosed (UDP), and total diabetes prevalence (TDP) were acquired from the Institute for Health Metrics and Evaluation (IHME) for the years 2004-2012 (Evaluation 2017). Prevalence estimates were calculated using a two-stage approach. The first stage used National Health and Nutrition Examination Survey (NHANES) data to predict high fasting plasma glucose (FPG) levels (≥126 mg/dL) and/or hemoglobin A1C (HbA1C) levels (≥6.5% [48 mmol/mol]) based on self-reported demographic and behavioral characteristics (Dwyer-Lindgren, Mackenbach et al. 2016). This model was then applied to Behavioral Risk Factor Surveillance System (BRFSS) data to impute high FPG and/or A1C status for each BRFSS respondent (Dwyer-Lindgren, Mackenbach et al. 2016). The second stage used the imputed BRFSS data to fit a series of small area models, which were used to predict the county-level prevalence of each of the diabetes-related outcomes (Dwyer-Lindgren, Mackenbach et al. 2016). Diagnosed diabetes was defined as the proportion of adults (age 20+ years) who reported a previous diabetes diagnosis, represented as an age-standardized prevalence percentage. Undiagnosed diabetes was defined as proportion of adults (age 20+ years) who have a high FPG or HbA1C but did not report a previous diagnosis of diabetes. Total diabetes was defined as the proportion of adults (age 20+ years) who reported a previous diabetes diagnosis and/or had a high FPG/HbA1C. The age-standardized diabetes prevalence (%) was used as the outcome. The EQI was constructed for 2000-2005 for all US counties and is composed of five domains (air, water, built, land, and sociodemographic), each composed of variables to represent the environmental quality of that domain. Domain-specific EQIs were developed using principal components analysis (PCA) to reduce these variables within each domain while the overall EQI was constructed from a second PCA from these individual domains (L. C. Messer et al., 2014). To account for differences in environment across rural and urban counties, the overall and domain-specific EQIs were stratified by rural urban continuum codes (RUCCs) (U.S. Department of Agriculture, 2015). This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Human health data are not available publicly. EQI data are available at: https://edg.epa.gov/data/Public/ORD/NHEERL/EQI. Format: Data are stored as csv files. This dataset is associated with the following publication: Jagai, J., A. Krajewski, S. Shaikh, D. Lobdell, and R. Sargis. Association between environmental quality and diabetes in the U.S.A.. Journal of Diabetes Investigation. John Wiley & Sons, Inc., Hoboken, NJ, USA, 11(2): 315-324, (2020).

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.

The average for 2021 based on 27 countries was 6.24 percent. The highest value was in Spain: 10.3 percent and the lowest value was in Ireland: 3 percent. The indicator is available from 2000 to 2021. Below is a chart for all countries where data are available.

Diabetes prevalence (% of population ages 20 to 79) in French Polynesia was reported at 25.2 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. French Polynesia - Diabetes prevalence (% of population ages 20 to 79) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Germany DE: Diabetes Prevalence: % of Population Aged 20-79 data was reported at 6.900 % in 2021. This records an increase from the previous number of 5.300 % for 2011. Germany DE: Diabetes Prevalence: % of Population Aged 20-79 data is updated yearly, averaging 6.100 % from Dec 2011 (Median) to 2021, with 2 observations. The data reached an all-time high of 6.900 % in 2021 and a record low of 5.300 % in 2011. Germany DE: 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 Germany – Table DE.World Bank.WDI: Social: Health Statistics. Diabetes prevalence refers to the percentage of people ages 20-79 who have type 1 or type 2 diabetes. It is calculated by adjusting to a standard population age-structure.;International Diabetes Federation, Diabetes Atlas.;Weighted average;

This dataset contains information on the proportion by age, total number, male and female and sex of adults 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.

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;

This dataset presents information on age-sex specific incidence rates of diabetes by First Nations status for Alberta, expressed as per 100,000 population.

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.

Georgia GE: Diabetes Prevalence: % of Population Aged 20-79 data was reported at 7.110 % in 2017. Georgia GE: Diabetes Prevalence: % of Population Aged 20-79 data is updated yearly, averaging 7.110 % from Dec 2017 (Median) to 2017, with 1 observations. Georgia GE: 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 Georgia – Table GE.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 dataset contains number and percentage of diabetes patients in the US during 2013 grouped by ZIP code. The prevalence and incidence of diabetes have increased in the United States in recent decades, no studies have systematically examined long-term, national trends in the prevalence and incidence of diagnosed diabetes.