This statistic depicts the raw national prevalence of diabetes in the Middle East in 2013, by selected countries. In that year, the raw national prevalence of diabetes Oman was approximately eight percent.

In 2023, there were 22.4 deaths from diabetes mellitus per 100,000 people in the United States. The death rate caused by this condition has fluctuated over the past decades, reaching almost 26 deaths per 100,000 people in the early 2000s, and about 18 deaths in 1980. Prevalence of diabetes In 2022, around 8.4 percent of the adult population in the U.S. had diabetes. In total, around 38 million adults in the United States are currently living with diabetes. Of this total, the vast majority were aged 45 years and older. The states with the highest share of adults with diabetes are West Virginia, Mississippi, and Louisiana. Cure for diabetes? Researchers are helping diabetics put their Type 2 diabetes into remission, where the blood sugar levels are kept within a healthy range. For Type 1, scientists are looking for ways to prevent the immune system’s attack on beta cells, which causes diabetes. These cells, located in the pancreas, produce the insulin people need to live. As of yet, there is no cure for diabetes mellitus; however, scientists are researching ways to make diabetes harmless one day.

The National Diabetes Register was introduced in 2016 by the amendment of Act No. 372/2011 Coll. , on health services and conditions of their provision (Act on Health Services), by Act No. 147/2016 Coll. with effect from 1 July 2016.

It is a new type of register that uses as much as possible already existing data in the healthcare sector, namely the data of the National Register of Reimbursed Health Services (NRHZS), i.e. the administrative data of health insurance companies supplemented by data from laboratories that already exist in their information systems and data collection from nursing staff physicians involved in a referral network of providers or in planned observational studies.

Risk and prognostic factors of the disease, data related to the disease and its treatment, personal and family history of the patient related to the disease, including classification of the type and state of diabetes and laboratory values, provision of dispensary care are processed in the register; data needed to identify the provider diagnosing, treating and providing dispensary care.

The basic statistical unit of the record in the register is the record of diabetes.

The register provides an overview of a population-relevant disease from the point of view of epidemiology, treatment and control of diabetes at a hitherto inaccessible detailed level with minimal effort, as it is mostly the use of already existing data.

Mandatory duties and irreplaceable functions of the register:

• Monitoring the epidemiology of diabetes and its treatment as a socially extremely serious disease affecting a significant part of the population
• Monitoring the quality and outcomes of diabetes care
• Data reporting for EUROSTAT, WHO, OECD databases

Population-based county-level estimates for prevalence of DC were obtained from the Institute for Health Metrics and Evaluation (IHME) for the years 2004-2012 (16). DC prevalence rate was defined as the propor-tion of people within a county who had previously been diagnosed with diabetes (high fasting plasma glu-cose 126 mg/dL, hemoglobin A1c (HbA1c) of 6.5%, or diabetes diagnosis) but do not currently have high fasting plasma glucose or HbA1c for the period 2004-2012. DC 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 HbA1C levels (≥6.5% [48 mmol/mol]) based on self-reported demographic and behavioral characteristics (16). This model was then applied to Behavioral Risk Factor Surveillance System (BRFSS) data to impute high FPG and/or HbA1C status for each BRFSS respondent (16). The second stage used the imputed BRFSS data to fit a series of small area models, which were used to predict county-level prevalence of diabetes-related outcomes, including DC (16). The EQI was constructed for 2006-2010 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). Results are reported as prevalence rate differences (PRD) with 95% confidence intervals (CIs) comparing the highest quintile/worst environmental quality to the lowest quintile/best environmental quality expo-sure metrics. PRDs are representative of the entire period of interest, 2004-2012. Due to availability of DC data and covariate data, not all counties were captured, however, the majority, 3134 of 3142 were utilized in the analysis. 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, K. Price, D. Lobdell, and R. Sargis. Diabetes control is associated with environmental quality in the USA. Endocrine Connections. BioScientifica Ltd., Bristol, UK, 10(9): 1018-1026, (2021).

It was estimated that as of 2022 around 24.4 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 eighth leading cause of death in the United States, accounting for three 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 53 million men and 44 million women in the United States had prediabetes. However, according to the CDC, around 80 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 Hawaii, California, and Alaska.

The prevalence of diabetes in the United States As of 2022, around 8.4 percent of adults in the United States had been diagnosed with diabetes, an increase from six percent in the year 2000. Diabetes is much more common among older adults, with almost a quarter of those aged 65 years and older diagnosed with diabetes, compared to just three percent of those aged 18 to 44 years. The states with the highest prevalence of diabetes among adults are Alabama, Mississippi, and West Virginia, while Colorado and Alaska report the lowest rates. In Alabama, around 17 percent of adults have been diagnosed with diabetes.

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. The 2019-20 audit covers the period 01 January 2019 to 31 March 2020. This is the first NDA report dedicated to people with type 1 diabetes. A new diagnosis validation process, which considers medication as well as recorded diagnosis, has been introduced to try to ensure that only people with true type 1 diabetes are included (see appendix). Results are to be taken in the context of low data submission from specialist services, possibly hampered due to COVID-19.

This is a source dataset for a Let's Get Healthy California indicator at "https://letsgethealthy.ca.gov/. This table displays the prevalence of diabetes in California. It contains data for California only. The data are from the California Behavioral Risk Factor Surveillance Survey (BRFSS). The California BRFSS is an annual cross-sectional health-related telephone survey that collects data about California residents regarding their health-related risk behaviors, chronic health conditions, and use of preventive services. The BRFSS is conducted by Public Health Survey Research Program of California State University, Sacramento under contract from CDPH. This prevalence rate does not include pre-diabetes, or gestational diabetes. This is based on the question: "Has a doctor, or nurse or other health professional ever told you that you have diabetes?" The sample size for 2014 was 8,832. NOTE: Denominator data and weighting was taken from the California Department of Finance, not U.S. Census. Values may therefore differ from what has been published in the national BRFSS data tables by the Centers for Disease Control and Prevention (CDC) or other federal agencies.

Diabetes prevalence (% of population ages 20 to 79) in Myanmar was reported at 7.1 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Myanmar - Diabetes prevalence (% of population ages 20 to 79) - actual values, historical data, forecasts and projections were sourced from the World Bank on March of 2025.

Background: Diabetes mellitus (DM) is a common chronic disorder in children and is caused by absolute or relative insulin deficiency, with or without insulin resistance. There are several different forms of childhood DM. Children can suffer from neonatal diabetes mellitus (NDM), type 1 diabetes (T1DM), type 2 diabetes (T2DM), Maturity Onset Diabetes of the Young (MODY), autoimmune monogenic, mitochondrial, syndromic and as yet unclassified forms of DM. The Middle East has one of the highest incidences of several types of DM in children; however, it is unclear whether pediatric diabetes is an active area of research in the Middle East and if ongoing, which research areas are of priority for DM in children.Objectives: To review the literature on childhood DM related to research in the Middle East, summarize results, identify opportunities for research and make observations and recommendations for collaborative studies in pediatric DM.Methods: We conducted a thorough and systematic literature review by adhering to a list recommended by PRISMA. We retrieved original papers written in English that focus on childhood DM research, using electronic bibliographic databases containing publications from the year 2000 until October 2018. For our final assessment, we retrieved 429 full-text articles and selected 95 articles, based on our inclusion and exclusion criteria.Results: Our literature review suggests that childhood DM research undertaken in the Middle East has focused mainly on reporting retrospective review of case notes, a few prospective case studies, systemic reviews, questionnaire-based studies, and case reports. These reported studies have focused mostly on the incidence/prevalence of different types of DM in childhood. No studies report on the establishment of National Childhood Diabetes Registries. There is a lack of consolidated studies focusing on national epidemiology data of different types of childhood DM (such as NDM, T1DM, T2DM, MODY, and syndromic forms) and no studies reporting on clinical trials in children with DM.Conclusions: Investing in and funding basic and translational childhood diabetes research and encouraging collaborative studies, will bring enormous benefits financially, economically, and socially for the whole of the Middle East region.

In 2021, the global prevalence rate of diabetes among adults figured at 10.5 percent - about 537 million people aged between 20 and 79 years. In China, the prevalence rate amounted to 10.6 percent, indicating a gradual increase over the recent decade. The world's most populous country had the highest number of diabetics in the world.

Who is suffering from diabetes?

Diabetes although a common enough ailment, is far more notorious than one would choose to believe. Affecting a rather large portion of the global population, the disease does not discriminate between the young or old. The main categories of diabetes include type 1, type 2, and gestational diabetes. Type 2 diabetes accounts for the vast majority - around 90 percent of diabetes worldwide, affecting young and older adults. Type 1, on the other hand, is primarily found in children owing to genetics, a family history of diabetes or other external factors.

How is diabetes affecting the Red Dragon?

The economic loss from diabetes is significant. It is now among the top ten leading causes of death worldwide and was estimated to cause about 1.4 million deaths in China in 2021. Between 2015 and 2019, China spent a double more on diabetes-related healthcare. Besides, the prevalence of prediabetes is also alarming. On par with an increasing prevalence rate of diabetes among adults, the average spending per patient for treatment has also been climbing, though still far lower than that in other strong economies. This could mean a huge market potential for diabetes medication and devices in China, especially when the government has planned to raise the public awareness of diabetes, along with national health spending.

Type II diabetes mellitus prevalence by fiscal year (from 2015 to each subsequent year) by sex and age group.

The crude prevalence rate of diabetes is defined as the ratio of respondents that are 18 years or older who have ever been told by a health professional that they had diabetes (other than during pregnancy) over the total number of respondents in the study (excluding those who refused to answer, had a missing answer, or answered “don’t know/not sure”).Prevalence data are derived from Behavioral Risk Factor Surveillance System (BRFSS) (numerator) and population estimates from the U.S. Census Bureau (denominator).The 500 Cities Project seeks to provide city- and census tract-level small area estimates for chronic disease risk factors, health outcomes, and clinical preventive service use for the largest 500 cities in the United States.Data source: CDC (Division of Population Health, National Center for Chronic Disease Prevention and Health Promotion)Date: 2015

The National Diabetes Audit (NDA) provides a comprehensive view of diabetes care in England and Wales. It measures the effectiveness of diabetes healthcare against 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.

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).

The crude prevalence rate of diabetes is the ratio of respondents that are 18 years or older who have ever been told by a health professional that they had diabetes (other than during pregnancy) over the total number of respondents in the study (excluding those who refused to answer, had a missing answer, or answered “don’t know/not sure”). Prevalence data are derived from Behavioral Risk Factor Surveillance System (BRFSS).

The 500 Cities Project seeks to provide city- and census tract-level small area estimates for chronic disease risk factors, health outcomes, and clinical preventive service use for the largest 500 cities in the United States.

Data source: CDC (Division of Population Health, National Center for Chronic Disease Prevention and Health Promotion)

Date: 2017

Background: Diabetes mellitus (DM) is a common chronic disorder in children and is caused by absolute or relative insulin deficiency, with or without insulin resistance. There are several different forms of childhood DM. Children can suffer from neonatal diabetes mellitus (NDM), type 1 diabetes (T1DM), type 2 diabetes (T2DM), Maturity Onset Diabetes of the Young (MODY), autoimmune monogenic, mitochondrial, syndromic and as yet unclassified forms of DM. The Middle East has one of the highest incidences of several types of DM in children; however, it is unclear whether pediatric diabetes is an active area of research in the Middle East and if ongoing, which research areas are of priority for DM in children.Objectives: To review the literature on childhood DM related to research in the Middle East, summarize results, identify opportunities for research and make observations and recommendations for collaborative studies in pediatric DM.Methods: We conducted a thorough and systematic literature review by adhering to a list recommended by PRISMA. We retrieved original papers written in English that focus on childhood DM research, using electronic bibliographic databases containing publications from the year 2000 until October 2018. For our final assessment, we retrieved 429 full-text articles and selected 95 articles, based on our inclusion and exclusion criteria.Results: Our literature review suggests that childhood DM research undertaken in the Middle East has focused mainly on reporting retrospective review of case notes, a few prospective case studies, systemic reviews, questionnaire-based studies, and case reports. These reported studies have focused mostly on the incidence/prevalence of different types of DM in childhood. No studies report on the establishment of National Childhood Diabetes Registries. There is a lack of consolidated studies focusing on national epidemiology data of different types of childhood DM (such as NDM, T1DM, T2DM, MODY, and syndromic forms) and no studies reporting on clinical trials in children with DM.Conclusions: Investing in and funding basic and translational childhood diabetes research and encouraging collaborative studies, will bring enormous benefits financially, economically, and socially for the whole of the Middle East region.

Source: MINISTRY OF HEALTH

Data Last Updated: 15/10/2024

Update Frequency: Ad-Hoc

Footnotes: Data for 2010 are from the National Health Survey. Data for years 2007 and 2013 are from the National Health Surveillance Survey. Data for 2017, 2019, 2020, 2021, 2022 and 2023 are from the National Population Health Survey. The findings of different surveys are not directly comparable, and should be interpreted with caution, because of differences in the survey methodology.

Adapted from: https://tablebuilder.singstat.gov.sg/table/TS/M870401

We propose two new methods to estimate secular trends in the incidence of a chronic disease from a series of prevalence studies and mortality data. One method is a direct inversion formula, the second method is a least squares estimation. Both methods are validated in a simulation study based on data from a diabetes register. The results of the validation show that the proposed methods may be useful in epidemiological settings with sparse resources, where running a register or a series of follow-up studies is difficult or impossible.

BackgroundThe prevalence of type 2 diabetes mellitus (T2DM) is increasing in China. Depression in patients with T2DM interferes with blood glucose management, leads to poor treatment outcomes, and has a high risk of dementia and cardiovascular event. We conducted this systematic review and meta-analysis to evaluate the prevalence of depression in patients with T2DM in China and explore potential risk factors associated with depression in T2DM.MethodsWe conducted a literature search in MEDLINE/PubMed, EMBASE, the Cochrane Library, the Chinese Biomedical Literature Database (CBM), the China National Knowledge Infrastructure (CNKI), the Chinese Science and Technology Periodical Database (VIP), and the Wanfang Database from their inception to February 25, 2022 to include population-based, cross-sectional surveys that investigated the prevalence of depression in Chinese T2DM patients and studied possible risk factors. Gray literature and reference lists were also manually searched. We used the Agency for Healthcare Research and Quality methodology checklist to assess the risk of bias in the included studies. Two reviewers screened studies, extracted data, and evaluated the risk of bias independently. The primary outcome was the pooled prevalence of depression in Chinese T2DM patients, and the secondary outcomes included potential risk factors for depression in T2DM patients. R (version 3.6.1) and Stata (version 12.0) software were used for data synthesis.ResultsWe included 48 reports that identified 108,678 subjects. Among the included reports, 4 were rated as low risk of bias, 40 moderate risks of bias, and 4 high risks of bias. The prevalence of depression in T2DM patients in China was 25.9% (95% CI 20.6%−31.6%). The prevalence of depression was higher in women (OR = 1.36, 95% CI 1.19–1.54), subjects ≥60 years (OR = 1.56, 95% CI 1.14–2.14), with a primary school or lower education (vs. middle or high school education (OR = 1.49, 95% CI 1.16 – 1.92); vs. college degree or higher education (OR = 1.84, 95% CI 1.16 – 2.92), with a duration of T2DM ≥ 10 years (OR = 1.68, 95% CI 1.11–2.54), with complications (OR = 1.90, 95% CI 1.53–2.36), insulin users (OR = 1.46, 95% CI 1.09–1.96) and individuals living alone (OR = 2.26, 95% CI 1.71–2.98). T2DM patients with current alcohol use had a lower prevalence of depression (OR = 0.70, 95% CI 0.58–0.86). Prevalence varied from 0.8 to 52.6% according to different instruments used to detect depression.ConclusionThe prevalence of depression in T2DM patients is remarkable in China. Potential risk factors of depression in T2DM patients included women, age ≥ 60 years, low educational level, complications, duration of diabetes ≥ 10 years, insulin use, and living alone. High-quality epidemiological investigations on the prevalence of depression in Chinese T2DM patients are needed to better understand the status of depression in T2DM.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42020182979.