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This article centers around the development and analysis of machine learning (ML) and deep learning models aimed at enhancing diabetes diagnosis. In the swiftly evolving landscape of data technologies, it becomes crucial to explore the applications of these methods for accurate predictions and improved medical decision-making. Our research encompasses diverse datasets, leveraging state-of-the-art algorithms and technologies for model training and testing. The primary emphasis lies in evaluating the accuracy, sensitivity, and specificity of models within the realm of diabetes diagnosis. The study results reveal significant advancements in disease prediction, underscoring the potential of ML and deep learning in medical applications. This work introduces fresh perspectives on the utilization of computational methods in healthcare and serves as a foundation for prospective research in this domain. [ABSTRACT FROM AUTHOR]

Abstract Background Over time, global health systems have witnessed significant improvements in the delivery and coverage of healthcare services. Nevertheless, the increasing prominence of non-communicable diseases remains a persistent challenge. Diabetes is one such non-communicable chronic disease that poses a threat with respect to both mortality and morbidity. This study investigated the socio-economic determinants and inequalities in the prevalence of diabetes in the Kingdom of Saudi Arabia according to data collected from the 2018 Saudi Family Health Survey conducted by the General Authority for Statistics. Methods The analysis was limited to a sample of 11,528 respondents aged ≥ 18 years, selected across all 13 regions of Saudi Arabia, with complete responses for all variables of interest. Socio-economic determinants in diabetes prevalence were explored with univariate, bivariate, and multivariate logistic regression analyses. Furthermore, inequalities were visualised and quantitatively estimated according to construction of a concentration curve and calculation of the concentration index. Results The prevalence of diabetes among the 11,528 respondents was 11.20%. Age, education, income, and residence area were significant determinants of diabetes prevalence, with a greater risk of diabetes found in older participants (odds ratio [OR]: 12.262, 95% confidence interval [CI]: 9.820–15.313, p < 0.01) compared to younger participants. Inequality analysis showed a negative education-based concentration index (–0.235, p < 0.01), indicating that diabetes prevalence is concentrated among people with relatively less formal education. For males, the income-based concentration index was significantly positive, whereas the education-based concentration index was significantly negative, indicating a greater concentration of diabetes among Saudi men with higher incomes and less education. Conclusion These findings emphasize the need to prioritize policies and strategies for diabetes prevention and control with considerations of the socio-economic inequalities in prevalence. Key areas of focus should include improving education levels across all regions, raising awareness about diabetes and implementing nutritional interventions.

Background: Over time, global health systems have witnessed significant improvements in the delivery and coverage of healthcare services. Nevertheless, the increasing prominence of non-communicable diseases remains a persistent challenge. Diabetes is one such non-communicable chronic disease that poses a threat with respect to both mortality and morbidity. This study investigated the socio-economic determinants and inequalities in the prevalence of diabetes in the Kingdom of Saudi Arabia according to data collected from the 2018 Saudi Family Health Survey conducted by the General Authority for Statistics. Methods: The analysis was limited to a sample of 11,528 respondents aged ≥ 18 years, selected across all 13 regions of Saudi Arabia, with complete responses for all variables of interest. Socio-economic determinants in diabetes prevalence were explored with univariate, bivariate, and multivariate logistic regression analyses. Furthermore, inequalities were visualised and quantitatively estimated according to construction of a concentration curve and calculation of the concentration index. Results: The prevalence of diabetes among the 11,528 respondents was 11.20%. Age, education, income, and residence area were significant determinants of diabetes prevalence, with a greater risk of diabetes found in older participants (odds ratio [OR]: 12.262, 95% confidence interval [CI]: 9.820–15.313, p < 0.01) compared to younger participants. Inequality analysis showed a negative education-based concentration index (–0.235, p < 0.01), indicating that diabetes prevalence is concentrated among people with relatively less formal education. For males, the income-based concentration index was significantly positive, whereas the education-based concentration index was significantly negative, indicating a greater concentration of diabetes among Saudi men with higher incomes and less education. Conclusion: These findings emphasize the need to prioritize policies and strategies for diabetes prevention and control with considerations of the socio-economic inequalities in prevalence. Key areas of focus should include improving education levels across all regions, raising awareness about diabetes and implementing nutritional interventions. [ABSTRACT FROM AUTHOR]

This study aims to optimize the performance of the bagged tree in an ensemble classifier for predicting diabetes prevalence in women. The study used a dataset of 1,888 women with six features: age, BMI, glucose level, insulin level, blood pressure, and pregnancy status. The dataset was divided into training and testing sets with a 70:30 ratio. The bagged tree ensemble classifier was used for the analysis, and five-fold cross-validation was applied. The study found that using all features during training resulted in a 92.3% training accuracy and a 99.5% testing accuracy. However, applying optimization techniques such as feature selection, parameter tuning, and a maximum number of splits improved model performance. Feature selection optimized the accuracy performance by 0.2%, while parameter tuning improved the test accuracy by 0.2%. Moreover, decreasing the maximum number of splits from 1322 to 800 or 600 resulted in an optimized model with 0.1% higher validation accuracy. Finally, the optimized bagged tree models were evaluated using various performance metrics, including accuracy, precision, recall, and F1 score. The study found that Model 1, which used 800 maximum number of splits and 50 learners, outperformed Model 2 in terms of recall and F1 score, while Model 2, which used 600 maximum number of splits and 50 learners, had a higher precision score. The study concludes that optimization techniques can significantly improve the performance of the bagged tree in predicting diabetes prevalence in women. [ABSTRACT FROM AUTHOR]

Estimates of glucose concentrations vary among types of blood samples, which impact on the assessment of diabetes prevalence. Guidelines recommend a conversion factor to calculate plasma glucose from measurements of glucose in whole blood. The American Diabetes Association recommends the use of blood drawing tubes containing sodium fluoride (NaF) and citrate, which have not yet been evaluated regarding possible differences in glucose concentration and conversion factors. Thus, we compared glucose measurements in NaF-citrate plasma and venous whole blood and estimated the impact of differences on diabetes and prediabetes prevalence. Glucose differences were calculated by Bland-Altman analysis with pairwise comparison of glucose measurements from whole blood and NaF-citrate plasma (n=578) in clinical studies of the German Diabetes Center. Subsequently, we computed the impact of the glucose difference on diabetes and prediabetes prevalence in the population-based National Health and Nutrition Examination Survey (NHANES). Even upon conversion of whole blood to plasma glucose concentrations using the recommended conversion factor, mean glucose concentration difference remained 4.72 % higher in NaF-citrate plasma. Applying the higher glucose estimates, increases the population-based diabetes and prediabetes prevalence by 13.67 and 33.97 % or more than 7.2 and 13 million people in NHANES, respectively. Additional economic burden could be about 20 $ billion per year due to undiagnosed diabetes. The recommended conversion factor is not valid for NaF-citrate plasma. Systematic bias of glucose measurements due to sampling type leads to clinically relevant higher estimates of diabetes and prediabetes prevalence. [ABSTRACT FROM AUTHOR]

Background:During the last decade, Germany has seen an increased prevalence and a redistribution from undetected to diagnosed diabetes mellitus. Due to this substantial epidemiological development, the number of people with documented type 2 diabetes was 8.7 million in 2022. An estimated two million undiagnosed subjects are to be added. Beyond that, the life expectancy of diabetic subjects is increasing due to more responsive health systems in terms of care. Possible reasons include improved screening of at-risk individuals, the introduction of HbA1c for diagnosis in 2010, and the higher use of risk scores. Additionally, quality aspects of the laboratory methodology should be taken into consideration.Methods:Epidemiology and clinical management of diabetes in Germany are presented in the light of publications retrieved by a selective search of the PubMed database. Additionally, the data from German external quality assessment (EQA) surveys for the measurands glucose in plasma and HbA1c in whole blood, reviewed from 2010 until 2022, were evaluated. Above this, data concerning the analytical performance of near-patient glucometer devices, according to the ISO norm 15197:2013, were analyzed.Results:Two laboratory aspects are in good accordance with the observation of an increase in the diabetes mellitus prevalence when retrospectively reviewing the period 2010 to 2022: First, the analytical performance according to the ISO norm 15197:2013 of the glucometer devices widely used by patients with diabetes for the glucose self-testing, has improved during this period. Secondly, concerning the EQA program of INSTAND, the number of participating laboratories raised significantly in Germany. The spreads of variations of the specified results for plasma glucose remained unchanged between 2010 and 2022, whereas for HbA1c a significant decrease of the result scattering could be observed.Conclusion:These retrospectively established findings testify to an excellent analytical quality of laboratory diagnostics for glucose and HbA1c throughout Germany which may be involved in a better diagnosis and therapy of previously undetected diabetes mellitus.

Healthcare's evolution amid rapid scientific progress demands the efficient management of extensive data. This has given rise to electronic health passports, which play a crucial role in modern healthcare by providing secure access to comprehensive medical histories. This study, exemplified by diabetes, addresses the mounting global prevalence of this disease, which saw cases soar from 108 million in 1980 to 422 million by 2014, resulting in a 5 % rise in diabetes-related premature mortality from 2000 to 2016. Disease prediction based on patient attributes holds potential to optimize healthcare resource allocation. The research aim is to identify new hidden dependencies and parameters in the diagnosis of diabetes, utilizing machine learning techniques. The first stage of this involves a thorough comparison and optimization of various modeling techniques, from Decision Trees (e.g., Random Forest, Adaboost) to advanced Deep Learning models like CNN, RNN, and LSTM networks, aiming to determine the most effective implementation method. Leveraging a subset of the MIMIC-III Critical Care Database, a comprehensive de-identified health-related dataset, this research provides insights into addressing the escalating diabetes challenge. The study revealed that the Gradient Boosting Machine was the most effective for making diagnoses. In the realm of deep learning, the Recurrent Neural Network (RNN) demonstrated the best results. This work aligns with the broader context of utilizing electronic health passports to enhance healthcare efficiency and decision-making in an era characterized by abundant health data. It is essential to emphasize that this work represents the initial phase of a broader research trajectory, and its continuation will be expounded upon in forthcoming publications. Dataset: https://doi.org/10.13026/C2XW26. Dataset license: PhysioNet Credentialed Health Data Use Agreement 1.5.0.

BACKGROUND. The clinical and epidemiological characteristics of diabetes mellitus (DM) and the quality of its therapy are the key prognostic dominant that determines the organizational aspects of the diabetic service. The continuous dynamic monitoring of DM has been carried out in the Russian Federation (RF) since 1996 through the activities of the Federal Register of Diabetes Mellitus (FDR).AIMS. The aim of our study was to analyze the epidemiological characteristics of DM in the RF (prevalence, morbidity, mortality), the prevalence diabetic of complications, the state of carbohydrate metabolism (level of HbA1c) and the dynamics of the structure of glucose-lowering therapy (GLT) according to the FDR.MATERIALS AND METHODS. The database of FRD (https://www.diaregistry.ru/), 85 regions of the RF. The data are presented as of 01.01.2023 and in dynamics for the period 2010–2022.RESULTS. The total number of DM patients in the RF as of 01.01.2023 was 4 962 762 (3.31% of the population), including: Type 1 (T1) — 5.58% (277.1 ths), T2 — 92.33% (4.58 million), other DM types —2.08% (103 ths). The dynamics of prevalence over the 13-year period (2010→2022) was 146.0→191.0/100 ths people with T1, and 2036.2→3158.8/100 ths people with T2; morbidity in T1 12.3→8.2/100 ths population, in T2 260.1→191.4/100 ths population; мortality: T1 2.1→2.4/100 ths population, T2 41.2→86.1/100 ths of the population. The main cause of death was cardiovascular: in T1 38.6% cases, in T2 — 50.9%. Life expectancy (average age of death of patients): T1 was 52.7 years, the dynamics in males 50.9 → 50.7 years, females 62.1→56.0 years; in T2 — 74.2 years, males 69.5→70.4 years, females 74.2→76.1 years. The dynamic of DM duration from onset to the death: in T1 15.4→19.9 years; in T2 11→11.4 10.2→11.8 years. The proportion of patients with laboratory-measured HbA1c

Background. Diabetes and its complications represent a significant public health burden in the United States. Some communities have disproportionately high risks of the disease. Identification of these disparities is critical for guiding policy and control efforts to reduce/eliminate the inequities and improve population health. Thus, the objectives of this study were to investigate geographic high-prevalence clusters, temporal changes, and predictors of diabetes prevalence in Florida. Methods. Behavioral Risk Factor Surveillance System data for 2013 and 2016 were provided by the Florida Department of Health. Tests for equality of proportions were used to identify counties with significant changes in the prevalence of diabetes between 2013 and 2016. The Simes method was used to adjust for multiple comparisons. Significant spatial clusters of counties with high diabetes prevalence were identified using Tango's flexible spatial scan statistic. A global multivariable regression model was fit to identify predictors of diabetes prevalence. A geographically weighted regression model was fit to assess for spatial non-stationarity of the regression coefficients and fit a local model. Results. There was a small but significant increase in the prevalence of diabetes in Florida (10.1% in 2013 to 10.4% in 2016), and statistically significant increases in prevalence occurred in 61% (41/67) of counties in the state. Significant, high-prevalence clusters of diabetes were identified. Counties with a high burden of the condition tended to have high proportions of the population that were non-Hispanic Black, had limited access to healthy foods, were unemployed, physically inactive, and had arthritis. Significant non-stationarity of regression coefficients was observed for the following variables: proportion of the population physically inactive, proportion with limited access to healthy foods, proportion unemployed, and proportion with arthritis. However, density of fitness and recreational facilities had a confounding effect on the association between diabetes prevalence and levels of unemployment, physical inactivity, and arthritis. Inclusion of this variable decreased the strength of these relationships in the global model, and reduced the number of counties with statistically significant associations in the local model. Conclusions. The persistent geographic disparities of diabetes prevalence and temporal increases identified in this study are concerning. There is evidence that the impacts of the determinants on diabetes risk vary by geographical location. This implies that a one-size-fits-all approach to disease control/prevention would be inadequate to curb the problem. Therefore, health programs will need to use evidence-based approaches to guide health programs and resource allocation to reduce disparities and improve population health. [ABSTRACT FROM AUTHOR]

Background Diabetes and its complications represent a significant public health burden in the United States. Some communities have disproportionately high risks of the disease. Identification of these disparities is critical for guiding policy and control efforts to reduce/eliminate the inequities and improve population health. Thus, the objectives of this study were to investigate geographic high-prevalence clusters, temporal changes, and predictors of diabetes prevalence in Florida. Methods Behavioral Risk Factor Surveillance System data for 2013 and 2016 were provided by the Florida Department of Health. Tests for equality of proportions were used to identify counties with significant changes in the prevalence of diabetes between 2013 and 2016. The Simes method was used to adjust for multiple comparisons. Significant spatial clusters of counties with high diabetes prevalence were identified using Tango’s flexible spatial scan statistic. A global multivariable regression model was fit to identify predictors of diabetes prevalence. A geographically weighted regression model was fit to assess for spatial non-stationarity of the regression coefficients and fit a local model. Results There was a small but significant increase in the prevalence of diabetes in Florida (10.1% in 2013 to 10.4% in 2016), and statistically significant increases in prevalence occurred in 61% (41/67) of counties in the state. Significant, high-prevalence clusters of diabetes were identified. Counties with a high burden of the condition tended to have high proportions of the population that were non-Hispanic Black, had limited access to healthy foods, were unemployed, physically inactive, and had arthritis. Significant non-stationarity of regression coefficients was observed for the following variables: proportion of the population physically inactive, proportion with limited access to healthy foods, proportion unemployed, and proportion with arthritis. However, density of fitness and recreational facilities had a confounding effect on the association between diabetes prevalence and levels of unemployment, physical inactivity, and arthritis. Inclusion of this variable decreased the strength of these relationships in the global model, and reduced the number of counties with statistically significant associations in the local model. Conclusions The persistent geographic disparities of diabetes prevalence and temporal increases identified in this study are concerning. There is evidence that the impacts of the determinants on diabetes risk vary by geographical location. This implies that a one-size-fits-all approach to disease control/prevention would be inadequate to curb the problem. Therefore, health programs will need to use evidence-based approaches to guide health programs and resource allocation to reduce disparities and improve population health.

[Display omitted] • We report higher prevalence of diabetes than previous Hungarian estimates. • 18.3% of women and 23.5% of men with diabetes were undiagnosed. • Men in their forties had a higher risk of being undiagnosed with diabetes. • Employment status and education level were not associated with being undiagnosed. • Universal health care could provide equitable access to diabetes diagnosis. To estimate prevalence of diagnosed (dDM) and undiagnosed diabetes (uDM) in Hungary and investigate determinants of uDM. Data was obtained from the nationally representative H-UNCOVER study. As laboratory measurements were available for 11/19 Hungarian counties, n = 5,974/17,787 people were eligible. After exclusions, 5,673 (representing 4,976,097 people) were included. dDM was defined by self-reporting, while uDM as negative self-reporting and elevated fasting glucose (≥7 mmol/l) and/or HbA1c (≥48 mmol/mol). Logistic regression for complex samples was used to calculate comparisons between dDM and uDM adjusted for age and BMI. Diabetes prevalence was 12.0 %/11.9 % (women/men, 95 %CI:10.7–13.4 %/10.7–13.2 %), while 2.2 %/2.8 % (1.7–2.8 %/2.2–3.6 %) of women/men were uDM. While the proportion of uDM vs. dDM was similar for women ≥ 40, men in their forties had the highest odds for uDM. Neither unemployment (women/men OR:0.58 [0.14–2.45]/0.50 [0.13–1.92]), nor education level (tertiary vs. primary; women/men OR: 1.16 [0.53–2.56]/ 0.53 [0.24–1.18]) were associated with uDM. The risk of uDM was lower in both sexes with chronic morbidities. We report higher prevalence of diabetes and undiagnosed diabetes than previous Hungarian estimates. The finding that socioeconomic factors are not associated to uDM suggests that universal health care could provide equitable access to diabetes diagnosis. [ABSTRACT FROM AUTHOR]

BACKGROUND. One of the priority directions in the development of the health care system is to reduce the medical and social damage caused by the increase in the prevalence of diabetes mellitus (DM). From this point of view, the development of a diabetes register is very important as the main information and analytical platform for clinical and epidemiological monitoring of diabetes in the Russian Federation (RF).AIMS. The aim of our study was to analyze a dynamic (2016–2020) of the epidemiological characteristics of diabetes mellitus in the Russian Federation (prevalence, morbidity, mortality), the prevalence of complications, the level of HbA1c and the dynamics of the structure of glucose-lowering therapy (GLT) according to the Federal Diabetes Register (FDR).MATERIALS AND METHODs. The database of FRD (http://diaregistry.ru) 84 regions of the RF. The data are presented in dynamics 2016→2020.RESULTS. The total number of DM patients in the RF as of 01.01.2021 was 4,799,552 (3.23% of the population), including: Type 1 (T1) — 5.5% (265.4 ths) , T2 — 92.5% (4.43 million), other DM types — 2.0% (99.3 ths). The dynamics of prevalence was 168.7→180.9/100 ths people with T1, and 2709 → 3022/100 ths people with T2; morbidity in T1 10.5→7.7/100 ths population, in T2 219.6→154.2/100 ths population. Age and sex characteristics: the proportion of men in T1 — 54%, in T2 — 30%; the max proportion of patients with T1 at the age of 30–39 years, T2 65–69 years. Mortality: T1 3.0 → 2.7/100 ths population, T2 87.7→93.9/100 ths of the population, the main cause of death was cardiovascular: in T1 38,1% cases, in T2 — 52,0%. Life expectancy (average age of death of patients): T1 was 53.2years, the dynamics in males 50.7 → 50.5years, ­females 58.7→55.2years; in T2 — 73.5 years, males 70.2→70.1years, females 75.7→75.4 years. The dynamic of DM duration until the death: in T1 17.4→19.0 years; in T2 11→11.4 years. The incidence of diabetic complications in T1 and T2 patients: neuropathy 43.3% and 24.4%, nephropathy (CKD) 25.9% and 18.4%, retinopathy 31.7% and 13.5%, respectively. The ­proportion of ­patients with HbA1c

The Hmong, an ethnic group in Laos, immigrated to the United States at the end of the Vietnam War. Minnesota and California have the largest Hmong populations. Hmong were historically farmers and hunter-gatherers with inadequate food supply in Laos. Here in America, with a surplus of food and a sedentary lifestyle, the Hmong are at increased risk for diabetes, hence the Thrifty Gene Hypothesis. This retrospective study compares the prevalence and control of diabetes mellitus-type 2 between the Hmong and other ethnic and racial groups at the Health And Life Organization (HALO) clinic in Sacramento, California. A total of 9,285 charts were reviewed. The Hmong had the highest prevalence but poorest control of diabetes mellitus when compared with the Laotian, Vietnamese, Blacks, Whites, and Hispanics (chi-square p-value

Abstract Background Despite Israel’s universal health coverage, disparities in health services provision may still exist. We aimed to assess socioeconomic disparities in diabetes prevalence and quality of care among Israeli children, and to assess whether these changed over time. Methods We used repeated cross-sectional analyses in the setting of the National Program for Quality Indicators in Community Healthcare. The data were derived from electronic medical records from Israel’s four health maintenance organizations. The study population included all Israeli children aged 2–17 years in 2011–2018 (2018: N = 2,404,856). Socio-economic position (SEP) was measured using Central Bureau of Statistics data further updated by a private company (Points Business Mapping Ltd), and grouped into 4 categories, ranging from 1 (lowest) to 4 (highest). We used logistic regression to assess the association of SEP with diabetes prevalence, diabetes clinic visits, hemoglobin A1C (HbA1C) testing, and poor glycemic control (HbA1c > 9%), and assessed whether these changed over time. Results Diabetes prevalence increased with age and SEP, with a total of 3019 children with diabetes. SEP was positively associated with visiting a specialized diabetes clinic (age and sex adjusted Odds Ratio (aORSEP 4 vs. 1 2.45, 95% Confidence Interval (CI) 1.67–3.69)). Although children in higher SEPs were less likely to undergo HbA1c testing (aORSEP 4 vs. 1 0.54, 95% CI 0.40–0.72), they were also less likely to have poor glycemic control (aORSEP 4 vs. 1 0.25, 95% CI 0.18–0.34). Disparities were especially apparent among children aged 2–9 (6.5% poor glycemic control in SEP 4 vs. 38.2% in SEP 1). Poor glycemic control decreased over time, from 44.0% in 2011 to 34.1% in 2018. Conclusions While poor glycemic control rates among children have improved, they remain high compared to rates in adults. Additionally, substantial socioeconomic gaps remain. It is eminent to study the causes of these disparities and develop policies to improve care provided to children in the lower SEP levels, to promote health equity.

Diabetes mellitus is a disease associated with many complications leading to premature death. The aim of this study was to estimate prevalence of type 2 diabetes (T2D), and the proportion of the population unaware of the condition, in association with modifiable risk factors. Data from the Hellenic National Nutrition and Health Survey were used (n = 3773 adults, 40.8% men) and were obtained by trained personnel. Diabetes mellitus disease status was categorized as per the International Classification of Diseases codes (10th version). A subsample from the two main metropolitan areas was used to assess T2D and impaired fasting glucose (IFG) (n = 990; 38.2% men) from plasma analysis. The prevalence of T2D in the population was 5.2% in total, reaching 13.7% in adults aged >60 years (no sex differences). IFG was observed in 27.3% of adults in the two metropolitan areas, and 40% were unaware of having T2D in this subsample. The likelihood of having T2D significantly increased with age and body weight, whereas it decreased with higher educational level and physical activity (P for all <0.001). The high T2D prevalence in adults, especially among the older age-groups, suggests a major public health problem in Greece. • Impaired fasting glucose was observed in 27.3% of adults in the two metropolitan areas, and 40% were unaware of having T2D. • Odds of T2D significantly increased with age and body weight, and decreased with educational level and physical activity. • The population prevalence of T2D was found 5.2% in total, reaching 13.7% in adults aged >60 years (no sex differences). [ABSTRACT FROM AUTHOR]

Diabetes is a major chronic disease that was the seventh leading cause of death in the United States in 2017. Although diabetes self-management education (DSME) programs have been implemented to promote patients' self-management skills, the disease continues to grow and some regions have a heavier burden of diabetes diagnoses than others. Focusing on the unbalanced diabetes prevalence across counties, this study aims to identify regional distribution of diabetes education programs in Texas counties, and explore whether diabetes prevalence is worse in certain counties that are geographically isolated from DSME programs. Data from the Centers for Disease Control and Prevention, American Diabetes Association, and American Association of Diabetes Educators were analyzed using ESRI ArcGIS software. When the authors geocoded 167 DSME programs in Texas, it was found that 47 programs (28.7%) were concentrated in 1 single county, and only 49 counties (19.3%) of the total counties (n = 254) had at least 1 DSME program. It also was revealed that the 25 counties (10%) with the highest diabetes prevalence had only 4 DSME programs (2.4%), indicating that there are still marginalized areas with no access to diabetes education programs. Considering the distance from each county's center to the nearest DSME program and diabetes prevalence, 3 counties were identified as diabetes education deserts. When designing, implementing, and evaluating strategies to reduce the burden of diabetes, policy makers and health care providers should account for the existing regional disparity in diabetes education and its impact on diabetes prevalence. [ABSTRACT FROM AUTHOR]

Purpose Of Review: Latin America is the scenario of great inequalities where about 32 million human beings live with diabetes. Through this review, we aimed at describing the current state of the prevalence, awareness, treatment, and control of diabetes mellitus and completion of selected guidelines of care across Latin America and identify opportunities to advance research that promotes better health outcomes.Recent Findings: The prevalence of diabetes mellitus has been consistently increasing across the region, with some variation: higher prevalence in Mexico, Haiti, and Puerto Rico and lower in Colombia, Ecuador, Dominican Republic, Peru, and Uruguay. Prevalence assessment methods vary, and potentially underestimating the real number of persons with diabetes. Diabetes unawareness varies widely, with up to 50% of persons with diabetes who do not know they may have the disease. Glycemic, blood pressure, and LDL-C control and completion of guidelines to prevent microvascular complications are not consistently assessed across studies, and the achievement of control goals is suboptimal. On the other hand, multiple interventions, point-of-care/rapid assessment tools, and alternative models of health care delivery have been proposed and tested throughout Latin America. The prevalence of diabetes mellitus continues to rise across Latin America, and the number of those with the disease may be underestimated. However, some local governments are embedding more comprehensive diabetes assessments in their local national surveys. Clinicians and public health advocates in the region have proposed and initiated various multi-level interventions to address this enormous challenge in the region. [ABSTRACT FROM AUTHOR]

Epidemiological evidence for the link between long-term exposure to air particulate matter (PM2.5) and occurrence of type 2 diabetes (T2D) is limited such that little is known about the effect of PM2.5 exposure and adult T2D prevalence. Thus, the aim of this ecological study is to evaluate the contribution of ambient PM2.5 exposure to the adult T2D prevalence in the large population of Iran. The study was conducted based on Iran's large-scale cross-sectional surveilling non-communicable diseases (NCDs) risk factors (Timpka et al. 2015b). A total of 31,050 participants were enrolled in three sequential processes of study using cluster random sampling. PM2.5 data in the urban area of 31 provinces of Iran were acquired from Tehran Air Quality Control Company (AQCC) and the Department of Environment (DoE) of Iran during 2012–2016. Moreover, major and minor diabetes risk factors were considered; the Pearson correlation and a stepwise regression model were performed to estimate associations between risk factors and diabetes and prediabetes prevalence. The results showed T2D prevalence was more frequent among women (10.61%) than men (9.35%). A weak positive correlation was observed between PM2.5 level and diabetes prevalence with a correlation coefficient of 0.275, although there was no significant association between PM2.5 value and prediabetes prevalence. Moreover, none of the variables included in the regression model could predict the prevalence of diabetes and prediabetes. According to our study results, it can be suggested that investigating the association between PM2.5 exposure and T2D prevalence at individual level may provide a better understanding of PM2.5 exposure and the risk of T2D prevalence. [ABSTRACT FROM AUTHOR]

Purpose: To develop a nomogram for predicting 5-year incidence of type 2 diabetes (T2D) in Chinese adults. Methods: This is a retrospective cohort study from a prospectively collected database. We included a total 32,766 adults free of T2D at baseline with a median follow-up of 3 years. Univariate and multivariate Cox regression analyses were applied to identify independent predictors. A nomogram was constructed to predict 5-year incident rate of T2D based on the multivariate analysis results. Harrell's C-indexes and calibration plots were used to evaluate the accuracy of the nomogram in both internal and external validations. Results: The overall prevalence of T2D was 2.1%. Participants were randomly divided into a training set (n = 21,844) and a validation set (n = 10,922). After multivariate analysis in the training set, age, sex, BMI, hypertension, dyslipidemia, smoking status, and family history were found as risk predictors and integrated into the nomogram. Harrell's C-indexes were 0.815 (95% CI: 0.797–0.834) and 0.779 (95% CI: 0.747–0.811) in the training and validation sets, respectively. The calibration plots demonstrated good agreement between the estimated probability and the actual observation. Conclusion: Our nomogram could be a simple and reliable tool for predicting 5-year risk of developing T2D in high-risk Chinese. Through the model, early identifying high-risk individuals is helpful for timely intervention to reduce the incidence of T2D. [ABSTRACT FROM AUTHOR]

Objectives: Web information systems may serve as a diagnostic tool for the Internet users and they also support the epidemiological work of doctors and health care providers. As part of this study, a system has been created for detecting and calculating cardiovascular risk. The aim of this study has been the comparison of cardiovascular risk factors and calculated fatal cardiovascular risk in 2 periods of time: 2004–2009 and 2010–2015 in Poland, as determined via the Internet. Material and Methods: The “Ryzyko program” (“Risk program”) is available on the website of the Medical University of Gdańsk. To assess the cardiovascular death risk in a 10-year period, the algorithm of the SCORE (Systematic Coronary Risk Evaluation) project was used and 30 402 results of the algorithm have been analyzed. Results: Over 30 402 webpage visitors entered the required data and received the outcome. More than 78% of the Internet users who had entered the data, received a recommendation for medical check-up. Significant differences between the data collected in 2004– 2009 and 2010–2015 were noticed. Hypercholesterolemia prevalence (67.3% vs. 70.8%; p < 0.001), mean total cholesterol concentration in blood (5.60±1.65 mml/l vs. 5.66±1.35 mml/l; p < 0.001), prevalence of hypertension (36.6% vs. 35.3%; p = 0.039), mean systolic blood pressure (131.5±20.3 mm Hg vs. 132.6±18.0 mm Hg; p < 0.001), prevalence of declared smoking (30.7% vs. 26.5%; p < 0.001), declared diabetes mellitus (DM) (6.4% vs. 9.7%; p < 0.001), and declared coronary artery disease (CAD) (7.2% vs. 14.1%; p < 0.001), respectively. Conclusions: The prevalence of cardiovascular risk factors has changed during the observed period of time. Online automatic gathering of new data by “Ryzyko program” provides up-to-date observations. Int J Occup Med Environ Health 2017;30(3):499–510

Diabetes has become a critical population health issue in the United States. Although researchers have focused on diabetes prevalence at the individual level, few studies address community contexts of diabetes prevalence at the county level. The objective of this study is to explore the association between community characteristics and diabetes prevalence in 254 counties in Texas. Using 3 countywide data sets in 2012, the authors measured county-level community characteristics, including social, environmental, and health behavior factors, and examined how these county-level factors are associated with diabetes prevalence. Multivariate ordinary least squares models weighted with population of county were used for estimation. Rurality, physical inactivity prevalence, and obesity prevalence were positively associated with diabetes prevalence, while the percentage of nonphysician health care professionals was negatively associated with diabetes prevalence. The findings indicate that environmental and health behaviors are significantly associated with a high prevalence of diabetes, but more nonphysician health care professionals, including nurse practitioners, may mitigate diabetes prevalence. This study highlights the significance of community factors in diabetes prevalence and provides insights for diabetes prevention programs with nonphysician health care professionals. [ABSTRACT FROM AUTHOR]

Indigenous populations around the world have a higher health disparity and an increased risk of diabetes. Scientific literature on the prevalence of diabetes in India is not available, and the current work is a pilot study to explore the risk of diabetes in one such indigenous population in India. This is a cross-sectional survey and screening study. The study took place in a remote tribal hamlet of Machuru in South India. A door-to-door survey was conducted in the hamlet with a population of 555. The Indian Diabetes Risk Score (IDRS) questionnaire was completed by 160 individuals older than 25 years. Capillary blood glucose levels were measured to compare the glycaemic status with the predicted IDRS. Of 160 adults who completed the questionnaire, 37 were at high risk (23.13%) as per the IDRS, 52 at medium risk (32.5%) and 71 at low risk (44.38%). None of the respondents knew their family history of diabetes owing to the lack of awareness about the condition. Interestingly, the villagers had a sedentary lifestyle owing to their unique family dynamics but a healthy diet. Five participants were diagnosed with diabetes, and 18 were diagnosed with impaired fasting glucose or prediabetes. The IDRS might not be an accurate measure to understand the risk of diabetes in this particular population owing to their unique family dynamics and a lack of awareness about diabetes. The best possible way to assess the diabetes risk might be through blood examination. • Diabetes risk assessment using the IDRS was difficult in this indigenous population owing to multiple factors. • The particular population has sedentary lifestyle after the age of 30 years. • None of the respondents of the IDRS questionnaire knew their family history of diabetes. • The indigenous population had a reduced prevalence of type 2 diabetes compared with the country's average. • Their healthy diet and sleep patterns might possibly have reduced prevalence of type 2 diabetes. [ABSTRACT FROM AUTHOR]

The 2019 Diabetes Atlas delineated both accomplishments and challenges in diabetes care in Taiwan between 2005 and 2014. The series reported that Taiwan had significantly improved aspects of care quality for patients with diabetes. For example, the mortality rate decreased, the difference between the life expectancies of patients with diabetes and those of the general population decreased, and the rates of hospitalization because of heart diseases, cerebrovascular diseases, chronic kidney diseases, and unsatisfactory glycemic control decreased. However, despite these achievements, the 2019 Diabetes Atlas also reported some substantial challenges that have not been overcome. For example, the incidence of diabetes among women aged <19 years and 20-39 years increased by 27% and 33%, respectively. Furthermore, a high prevalence of macrovascular complications, a continuous increase in the dialysis prevalence rates among men with diabetes of all ages, and a low participation rate (<20%) of patients with diabetes in the pay-for-performance program were observed. The publication of the 2019 Diabetes Atlas is a milestone that demonstrates a strong will in medical societies to improve the quality of diabetes care. We expect this initiative can be reorganized every 5 years to report the results of continuous monitoring and surveillance and update the epidemiological features of diabetes in Taiwan. [ABSTRACT FROM AUTHOR]

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Over the previous 30 years, the status of diabetes has changed from being considered as a mellow issue of the elderly to one of the significant reasons for morbidity and mortality influencing the young and moderately aged individuals. The aim of the study was to estimate the prevalence of type 2 diabetes mellitus (T2DM) and impaired fasting glycemia (IFG) in the adult population, age ≥ 20 years of District Srinagar and determine its sociodemographic and lifestyle correlates. The study was conducted among the adult population of District Srinagar with a sample size of 580. A three-stage cluster random sampling design was used, and study participants were selected using a Kish grid method. Sociodemographic data, anthropometric data, and other data were collected as per the pretested semi-structured proforma. The participants were then subjected to fasting venous blood glucose estimation. The American Diabetes Association (ADA) criteria 2015 were used for classifying the subjects as normal, pre-diabetic, and diabetics. The prevalence of T2DM was 9.8% and that of IFG was 22.2%,the majority of them (9.1%) had known T2DM. The prevalence of IFG and T2DM was statistically associated with increasing age (p < 0.001), marital status (p < 0.001), educational status (p < 0.001), high chocolates and carbonated drinks consumption (p < 0.001), level of physical inactivity (p < 0.05), body mass index (p < 0.001), family history of T2DM (p < 0.001), and smoking behavior and hypertension (p < 0.001). Our analysis suggests an increase in the prevalence of T2DM in District Srinagar. [ABSTRACT FROM AUTHOR]

To develop risk scores for predicting the prevalence of diabetes in the Lao population. This was a cross-sectional study of both men and women (age 30 to 70 years) living in rural villages of the Vientiane municipality in the Lao PDR. Multiple logistic regressions with backward stepwise selection were used; the diabetes risk score was derived from the β-coefficient. Performance of the score was determined by the area under the receiver operating characteristic curve (AUC), the sensitivity, the specificity, and the positive predictive value for the specified cut-off value. The prevalence of undiagnosed diabetes was 7%. The factors included in the predictive in model were 17 (40 to 70 years of age) + 14 (high waist circumference) + 11 (hypertension) + 7 (family history of diabetes). A cut-off point of risk scores of 29.5 out of 49 produced the optimal sum, leading to a sensitivity of 0.75, a specificity of 0.55, a positive predictive value of 17.8%, and an AUC of 0.70. Data suggested that the combination of age, waist circumference, hypertension, and family history of diabetes could be utilized to identify Lao individuals at high risk of undiagnosed diabetes. The generalizability for other Lao population needs further investigation. [ABSTRACT FROM AUTHOR]

This paper assesses concordance and inconsistency among three small area estimation methods that are currently providing county-level health indicators in the United States. The three methods are multi-level logistic regression, spatial logistic regression, and spatial Poison regression, all proposed since 2010. Diabetes prevalence is estimated for each county in the continental United States from the 2012 sample of Behavioral Risk Factor Surveillance System. The mapping results show that all three methods displayed elevated diabetes prevalence in the South. While the Pearson correlation coefficients among three model-based estimates were all above 0.60, the highest one was 0.80 between the multilevel and spatial logistic methods. While point estimates are apparently different among the three small area estimate methods, their top and bottom of quintile distributions are fairly consistent based on Bangdiwala’s B-statistic, suggesting that outputs from each method would support consistent policy making in terms of identifying top and bottom percent counties.

Aims: To find diabetes prevalence of diagnosed cases, stratified by gender, age, and urban/rural municipalities in the Republic of Macedonia, based on data derived from the National eHealth System.Methods: The National eHealth System was searched for all patients with ICD-10 diagnoses E10-E14 in their electronic healthcare records. Data records from the National eHealth System contained patient's gender, date of birth, place of living, and ICD-10 code.Results: Total number of diagnosed diabetes cases was 84,568: 36,119 males (42.7%) and 48,449 females (57.3%). Diabetes prevalence of diagnosed cases in population 20-79 years was 5.0% (n = 78,233; N = 1,562,203), prevalence was higher in females than in males (4.6% vs 3.4%); in rural than in urban municipalities (5.6% vs 3.6%), and was highest in the age group 60-79 years (14.6%).Conclusion: These were the first findings on diabetes prevalence of diagnosed cases in the Republic of Macedonia derived from the National eHealth System, stratified by age, gender, and urban/rural municipalities. These data could enable more precise estimations of the total diabetes prevalence in the country, including both diagnosed and undiagnosed cases, and further analysis of the risk factors leading to higher diabetes prevalence in females and rural municipalities in the Republic of Macedonia. [ABSTRACT FROM AUTHOR]

Introduction: There has been no nationwide health (diabetes) survey in Nigeria since 1992, when a diabetes mellitus (DM) prevalence of 2.2% was reported. We aimed to determine the prevalence of and risk factors for DM in Nigeria by performing a systematic review and meta-analysis.Methods: We searched Medline, EMBASE, PubMed, PapersFirst, the Cochrane Library, Scopus, Bioline, African Journals Online, Institute of Scientific Information, and Google Scholar from the year 1990 to 2017. Using MeSH headings, the terms “diabetes mellitus,” “risk factors,” “prevalence,” and “Nigeria” as well as variations thereof were searched for. The last search was performed on 26 November 2017. We only included studies that utilized the random plasma glucose test, the fasting plasma glucose test, the oral glucose tolerance test (OGTT), or HbA1c to diagnose DM. A total of 23 studies (n = 14,650 persons) were evaluated. A random effects model was used to estimate the pooled prevalence of DM. We estimated the overall pooled prevalence of DM and subgroup-specific DM prevalences while accounting for inter-study and intra-study variability/heterogeneity.Results: The overall pooled prevalence of DM was 5.77% (95% CI 4.3-7.1). The pooled prevalences of DM in the six geopolitical zones of Nigeria were 3.0% (95% CI 1.7-4.3) in the north-west, 5.9% (95% CI 2.4-9.4) in the north-east, 3.8% (95% CI 2.9-4.7) in the north-central zone, 5.5% (95% CI 4.0-7.1) in the south-west, 4.6% (95% CI 3.4-5.9) in the south-east, and 9.8% (95% CI 7.2-12.4) in the south-south zone. Risk factors for the pooled prevalence of DM were a family history of DM (4.6%; 95% CI 3.5-5.6); urban dwelling (6.0%; 95% CI 4.3-7.8); unhealthy dietary habits (8.0%; 95% CI 5.4-10.5); cigarette smoking (4.4%; 95% CI 1.3-10.2); older age (6.6%; 95% CI 4.5-8.7); physical inactivity (4.8%; 95% CI 3.2-6.4); and obesity (5.3%; 95% CI 3.8-6.9).Conclusion: There has been an increase in the prevalence of DM in Nigeria. All regions of the country have been affected, with the highest prevalence seen in the south-south geopolitical zone. Urban dwelling, physical inactivity, advanced age, and unhealthy diet are important risk factors for DM among Nigerians. A national diabetes care and prevention policy is highly recommended. [ABSTRACT FROM AUTHOR]

Aims: To describe the prevalence and management of diabetes among immigrants according to ethnic group and duration of stay, compared to Italian citizens.Methods: Diabetic immigrant and Italian residents aged 20-69 years in the administrative database of the Lombardy Region. Immigrants were classified by region of origin and as long-term residents (LTR) and short-term residents (STR). Age- and sex-adjusted prevalence and indicators of diabetes management were calculated for immigrants by region of origin and by length of stay using Cox proportional models.Results: In 2010 19,992 immigrants (mean age 49.1 ± 10.8, 53.7% males) and 195,049 Italians (mean age 58.7 ± 9.3, 61.1 males) with diabetes were identified. Immigrants had a higher adjusted diabetes prevalence than Italians (OR 1.48; 95% CI 1.45-1.50). STR received significantly fewer recommended cardiovascular drugs (antiplatelets, statins and ACE-inhibitors/ARBs) than Italians, although prescription was higher among LTR from some ethnic groups. Immigrants were less likely to be seen by a diabetologist and to do at least one HbA1c test per year. Although the recommended tests/visits were more often done for the LTR than the STR, in the majority of ethnic groups these indicators were still far from optimal.Conclusion: The prevalence and management of diabetes differ between immigrants and Italians, although some improvement can be seen among LTR. [ABSTRACT FROM AUTHOR]

Introduction: Since the year 2000, IDF has been measuring the prevalence of diabetes nationally, regionally and globally.Aim: To produce estimates of the global burden of diabetes and its impact for 2017 and projections for 2045.Methods: A systematic literature review was conducted to identify published studies on the prevalence of diabetes, impaired glucose tolerance and hyperglycaemia in pregnancy in the period from 1990 to 2016. The highest quality studies on diabetes prevalence were selected for each country. A logistic regression model was used to generate age-specific prevalence estimates or each country. Estimates for countries without data were extrapolated from similar countries.Results: It was estimated that in 2017 there are 451 million (age 18-99 years) people with diabetes worldwide. These figures were expected to increase to 693 million) by 2045. It was estimated that almost half of all people (49.7%) living with diabetes are undiagnosed. Moreover, there was an estimated 374 million people with impaired glucose tolerance (IGT) and it was projected that almost 21.3 million live births to women were affected by some form of hyperglycaemia in pregnancy. In 2017, approximately 5 million deaths worldwide were attributable to diabetes in the 20-99 years age range. The global healthcare expenditure on people with diabetes was estimated to be USD 850 billion in 2017.Conclusion: The new estimates of diabetes prevalence, deaths attributable to diabetes and healthcare expenditure due to diabetes present a large social, financial and health system burden across the world. [ABSTRACT FROM AUTHOR]

Objective Diabetes mellitus affects almost one in 10 individuals in Germany. So far, little is known about the diabetes prevalence in maximum care hospitals. We assessed the diabetes prevalence, proportion of undiagnosed cases, the effectiveness of diabetes screening in a university hospital, the consequences for hospital stay and acquired complications. Research Design and Methods Over a 4 week period we determined HbA1c from 3 733 adult patients which were hospitalized at the university hospital of Tuebingen and had an available blood sample. Diabetes diagnosis was defined as HbA1c ≥ 6.5 % and/or previously documented diabetes diagnosis, prediabetes was defined as HbA1c ≥ 5.7 % and < 6.5 % without history of previous diabetes. Results 23.68 % of the patients had prediabetes and 22.15 % had diabetes with a high variation between the specialised departments (range 5–43 %). The rate of unknown diabetes was 3.7 %, the number needed to screen was 17 in patients older than 50 years. Patients with diabetes had a prolonged hospital stay compared to the mean length of stay for their diagnosis related group (diabetes: 1.47 ± 0.24 days; no diabetes: − 0.18 ± 0.13 days, p = 0.0133). The prevalence of hospital acquired complications was higher in diabetic patients (diabetes: 197 of 630; no diabetes: 447 of 2 459, p < 0.0001). Conclusions Every fourth patient in the university hospital had diabetes and every second had either prediabetes or diabetes. It is also worthwhile to screen for unknown diabetes in patients over the age of 50. The high prevalence and negative consequences of diabetes require screening and intensified specialized diabetes treatment in hospitals. [ABSTRACT FROM AUTHOR]

Physical inactivity is one of the risk factors of diabetes. In addition, physical inactivity is attributed to urbanization-related factors, such as poverty, which is also one of the risk factors of diabetes. We hypothesized that physical inactivity is a mediator in the association between diabetes and poverty, and that spatial heterogeneity exists in these relationships. This study adopted a spatiotemporal modelling approach to conduct this mediator analysis. From 2004-2011, data were collected at the county level in 48 contiguous states (with a total of 3,109 counties) from the Behavioral Risk Factor Surveillance System (BRFSS) and American Community Survey. Poverty percentage significantly affected physical inactivity prevalence and diabetes prevalence in two separate models. Using a model with both physical inactivity and poverty percentages as independent variables, we verified that physical inactivity prevalence is a significant mediator. In this model, physical inactivity prevalence resulted in a significant positive association with diabetes prevalence, and the influence of poverty percentage on diabetes prevalence was significantly reduced (P=0.0009). An advanced spatiotemporal analysis revealed that 32.65% of counties having a significant positive association between diabetes prevalence and physical inactivity prevalence also had a significant positive association between physical inactivity prevalence and poverty percentage. Those counties were also likely located in the South and Southeast of USA. In summary, the findings of this study demonstrate the mediating effect of physical inactivity between diabetes and poverty. When implementing diabetes prevention in communities with higher poverty, appropriate strategies to reduce the cost burden of physical activity programmes should be considered.

ObjectivesThis report examined the impact and extent that spatial access to primary care physicians (PCPs) and social neighbourhood-/community-level factors have on diabetes prevalence for Toronto and Chicago.MethodsThe two-step floating catchment area method was used to compute spatial access scores. Bivariate correlation and multivariate linear regression identified the factors that were associated with, and/or predicted, diabetes prevalence.ResultsPotential spatial access to PCPs had no strong associations with diabetes prevalence. Low socio-economic status factors and certain ethnic groups were strongly associated with diabetes prevalence for both cities. For Toronto, South American place of birth, households below poverty and high school-level education predicted diabetes prevalence. African ethnicity and households below poverty predicted diabetes prevalence for Chicago.ConclusionAlthough this report found no strong association between diabetes prevalence and access to PCPs, contextual factors significant in past individual-level diabetes studies were associated with diabetes prevalence at the neighbourhood/community level for Toronto and Chicago. [ABSTRACT FROM PUBLISHER]

Objectives: Web information systems may serve as a diagnostic tool for the Internet users and they also support the epidemiological work of doctors and health care providers. As part of this study, a system has been created for detecting and calculating cardiovascular risk. The aim of this study has been the comparison of cardiovascular risk factors and calculated fatal cardiovascular risk in 2 periods of time: 2004-2009 and 2010-2015 in Poland, as determined via the Internet.Material and Methods: The "Ryzyko program" ("Risk program") is available on the website of the Medical University of Gdańsk. To assess the cardiovascular death risk in a 10-year period, the algorithm of the SCORE (Systematic Coronary Risk Evaluation) project was used and 30 402 results of the algorithm have been analyzed.Results: Over 30 402 webpage visitors entered the required data and received the outcome. More than 78% of the Internet users who had entered the data, received a recommendation for medical check-up. Significant differences between the data collected in 2004- 2009 and 2010-2015 were noticed. Hypercholesterolemia prevalence (67.3% vs. 70.8%; p < 0.001), mean total cholesterol concentration in blood (5.60±1.65 mml/l vs. 5.66±1.35 mml/l; p < 0.001), prevalence of hypertension (36.6% vs. 35.3%; p = 0.039), mean systolic blood pressure (131.5±20.3 mm Hg vs. 132.6±18.0 mm Hg; p < 0.001), prevalence of declared smoking (30.7% vs. 26.5%; p < 0.001), declared diabetes mellitus (DM) (6.4% vs. 9.7%; p < 0.001), and declared coronary artery disease (CAD) (7.2% vs. 14.1%; p < 0.001), respectively.Conclusions: The prevalence of cardiovascular risk factors has changed during the observed period of time. Online automatic gathering of new data by "Ryzyko program" provides up-to-date observations. Int J Occup Med Environ Health 2017;30(3):499-510. [ABSTRACT FROM AUTHOR]

Background: Business owners in the Republic of Korea must take part in the workers' general health examination. However, there have been few formal analyses of the uptake of this examination by employees. In the present study, we examined the rates of participation in medical examinations according to age group, health insurance type, and enterprise size, and then compared these results with those of the national general health screening. Furthermore, we determined the distribution of patients with abnormal results for diabetes and hypertension, and outlined the significance and history of domestic health examinations. Methods: We started by comparing participation rates extracted from the among health examination data of the National Health Insurance Service from 2006-2013 by sex, age, insurance type, and enterprise size of workplace health insurance beneficiaries (i.e., those whose insurance is provided by their workplace). In addition, we analyzed the prevalence rates of abnormal results for hypertension and diabetes, and explored the history and significance of health examinations in the Republic of Korea. Results: The overall participation rate in the primary health examination in 2006 was 56%, and this increased to 72% in 2013. However, the rates of the secondary screening did not increase much. Among workplace policyholders (i.e., those whose insurance is provided by their workplace), the participation rates of workers in enterprises with less than 50 employees were lower than were those in enterprises with 50 or more employees. Notably, the rates and odds ratios of patients with abnormal results for diabetes and hypertension were relatively high, particularly among those working in smaller enterprises. Conclusions: Although the workers' general health examination has been replaced with the national general health screening, it remains necessary to ensure uniform health management services among all workers in the Republic of Korea. This can, in turn, promote occupational health and improve working conditions throughout the Republic of Korea. [ABSTRACT FROM AUTHOR]

Clinical and epidemiological research has reported a strong association between diabetes and obesity. However, whether increased diabetes prevalence is more likely to appear in areas with increased obesity prevalence has not been thoroughly investigated in the United States (US). The Bayesian structured additive regression model was applied to identify whether counties with higher obesity prevalence are more likely clustered in specific regions in 48 contiguous US states. Prevalence data adopted the small area estimate from the Behavioral Risk Factor Surveillance System. Confounding variables like socioeconomic status adopted data were from the American Community Survey. This study reveals that an increased percentage of relative risk of diabetes was more likely to appear in Southeast, Northeast, Central and South regions. Of counties vulnerable to diabetes, 36.8% had low obesity prevalence, and most of them were located in the Southeast, Central, and South regions. The geographic distribution of counties vulnerable to diabetes expanded to the Southwest, West and Northern regions when obesity prevalence increased. This study also discloses that 7.4% of counties had the largest average in predicted diabetes prevalence compared to the other counties. Their average diabetes prevalence escalated from 8.7% in 2004 to 11.2% in 2011. This study not only identifies counties vulnerable to diabetes due to obesity, but also distinguishes counties in terms of different levels of vulnerability to diabetes. The findings can provide the possibility of establishing targeted surveillance systems to raise awareness of diabetes in those counties.

Aims: Epidemiological data regarding diabetes in Greece are based on regional, small-scale studies. We aimed to identify all citizens with prescribed pharmacological treatment for diabetes, to further explore type 1 diabetes prevalence and describe pharmacological treatment patterns in type 2 diabetes.Methods: The electronic prescription database of the National Organization for Health Care Services Provision was used to identify individuals who received at least two prescriptions with an ICD-10 code relevant to diabetes, dispensed between June 1st, 2014 and May 31st, 2015. Type-1 diabetes was defined in those receiving at least two fully-reimbursable insulin prescriptions with an ICD-10 code of E10 (insulin-dependent diabetes).Results: The study population consisted of 10,222,779 individuals, accounting for 95% of the Greek population. Prevalence of medication-prescribed diabetes was 7.0% (720,764 individuals), ranging from 0.08% in children and adolescents, to 8.2% in adults, and 30.3% in those ⩾75years old. Prevalence of type 1 diabetes was 0.24%, with a clear male predominance and more than half of cases developing after 14years of age. Metformin was the most frequently prescribed medication (77.4%) in type-2 diabetes followed by DPP-4 inhibitors (44.8%) and sulphonylureas (34.5%), while insulin was used by 19.4% of patients.Conclusions: This nation-wide real-world data analysis on medication-prescribed diabetes demonstrates that the current prevalence in Greece is 7.0%, with wide age variation and high figures in older adults. Identification of pharmacological patterns among patients with type 2 diabetes is a valuable guide in policy-makers' efforts to balance a cost-effective, quality-acceptable disease management. [ABSTRACT FROM AUTHOR]

Recent research supports a link between diabetes and fine particulate matter (≤ 2.5 μg in diameter; PM 2.5 ) in both laboratory and epidemiology studies. However, research investigating the potential relationship of the spatial vulnerability of diabetes to concomitant PM 2.5 levels is still sparse, and the level of diabetes geographic disparities attributed to PM 2.5 levels has yet to be evaluated. We conducted a Bayesian structured additive regression modeling approach to determine whether long-term exposure to PM 2.5 is spatially associated with diabetes prevalence after adjusting for the socioeconomic status of county residents. This study utilizes the following data sources from 2004 to 2010: the Behavioral Risk Factor Surveillance System, the American Community Survey, and the Environmental Protection Agency. We also conducted spatial comparisons with low, median-low, median-high, and high levels of PM 2.5 concentrations. When PM 2.5 concentrations increased 1 μg/m 3 , the increase in the relative risk percentage for diabetes ranged from − 5.47% (95% credible interval = − 6.14, − 4.77) to 2.34% (95% CI = 2.01, 2.70), where 1323 of 3109 counties (42.55%) displayed diabetes vulnerability with significantly positive relative risk percentages. These vulnerable counties are more likely located in the Southeast, Central, and South Regions of the U.S. A similar spatial vulnerability pattern for concentrations of low PM 2.5 levels was also present in these same three regions. A clear cluster of vulnerable counties at median-high PM 2.5 level was found in Michigan. This study identifies the spatial vulnerability of diabetes prevalence associated with PM 2.5 , and thereby provides the evidence needed to prompt and establish enhanced surveillance that can monitor diabetes vulnerability in areas with low PM 2.5 pollution. [ABSTRACT FROM AUTHOR]

Objectives There is paucity of information on cost implications of chronic diseases, such as diabetes mellitus, in developing countries, which is needed for well-informed policies and decisions. The objectives of the study were to evaluate cost of illness among diabetes mellitus patients and determine its probable national cost implications. Methods The study was carried out in a tertiary health institution in the Niger Delta region. It involved a cross-sectional retrospective drug utilisation evaluation and cost of illness analysis among 400 diabetes mellitus patients with a societal perspective. Key findings Three hundred and twenty-one patients (80.3%) met the study criteria. Glycaemic control was very poor in 68.5% of the patients and more than three-quarters had one or more complications or concurrent illnesses. The average direct cost of illness per patient with type 2 diabetes alone was NG45 531.19 ( US$284.57), while that of type 1 diabetes mellitus alone was NGN100 032.89 ( US$625.21). Participants with both type 2 diabetes and hypertension had NGN59 607.66 ( US$372.55) as their average annual cost of illness, whereas the average cost for those with type 1 diabetes and hypertension combined was NGN114 109.36 ( US$713.18). Annual national direct cost of illness for type 2 patients is in the range of NGN262 billion ( US$1 639 122 840.00), while that of type 1 is estimated to be NGN18 billion ( US$112 537 001.25). Conclusion The cost implication of diabetes mellitus is huge, policies to ensure evidence-based, cost-effective management and strategies to reduce the sky-rocketing prevalence should be put in place. [ABSTRACT FROM AUTHOR]

Aim To examine the available evidence about the epidemiology, health, social, and economic impact of diabetes in Pacific Island Countries and Territories (PICTs). Methods We conducted a systematic review of the peer-reviewed literature published in English from January 1990 to January 2014, and relevant technical reports. Results A total of 1548 articles were identified of which 35 studies of type 2 diabetes met the inclusion criteria. Eighteen technical reports were also included. We found no articles reporting on type 1 diabetes or gestational diabetes that met the inclusion criteria. The prevalence, risk factors and complications of diabetes were substantial. Diabetes prevalence rate of around 40% was common. Physical inactivity, overweight and obesity were leading risk factors. High rates of diabetes complications were reported e.g. up to 69% retinopathy. Poor clinical outcomes were also reported with over 70% not meeting glycaemic control targets and approximately 50% not meeting blood pressure and cholesterol targets. Conclusion This review highlights the burden of diabetes in PICTs and the need for more intensive interventions to improve the quality and outcomes of diabetes care. Overall, further research is needed to monitor secular diabetes trends in PICTs using standardised criteria for diagnosing diabetes and its complications. [ABSTRACT FROM AUTHOR]

AIM: The aim of this study was to compare two nationwide cross-sectional studies of diabetes prevalence in Bulgaria (2006 and 2012) and to assess its dynamics. MATERIAL AND METHODS: The two studies included 2396 and 2033 subjects, respectively. The International Diabetes Federation (IDF) diagnostic criteria were applied, and the data were weighed for type of settlement and age. RESULTS: Diabetes prevalence was found to be 7.9% in 2006 and 9.55% in 2012, P = 0.06, showing an increase of 20.9%. The absolute increase was 0.9% in the females and 2.3% in the males (P < 0.09). The increase was the largest in those aged 50-59: [9.4%, 2006 vs. 15.7%, 2012, P < 0.01]. Diabetes prevalence increased in the 20-60-year olds by 6.8% and decreased in the elderly by 6.1%. Obesity increased from 26.7 to 32.7%, P < 0.02. CONCLUSIONS: A significant increase in diabetes prevalence was found that necessitates healthcare measures and resources for community-based awareness and prevention programs. [ABSTRACT FROM AUTHOR]

Background With increasing diabetes prevalence worldwide, an impending diabetes "pandemic" has been reported. However, definitions of incident cases and the population at risk remain varied and ambiguous. This study analyzed trends in mortality and screening that contribute to diabetes prevalence and incidence, distinguishing between new incident cases and newly detected cases. Methods In an integrated provider-and-payer-system covering 53% of Israel's population, a composite diabetes case-finding algorithm was built using diagnoses, lab tests, and antidiabetic medication purchases from the organization's electronic medical record database. Data were extracted on adult members aged 26+ each year from January 1, 2004 through December 31, 2012. Rates of diabetes prevalence, incidence, screening, and mortality were reported, with incidence rates evaluated among the total, "previously-screened," and "previouslyunscreened" at-risk populations. Results There were 343,554 diabetes cases in 2012 (14.4%) out of 2,379,712 members aged 26+. A consistent but decelerating upward trend in diabetes prevalence was observed from 2004- 2012. Annual mortality rates among diabetics decreased from 13.8/1000 to 10.7/1000 (p = 0.0002). Total population incidence rates declined from 13.3/1000 in 2006 to 10.8/1000 in 2012 (p < 0.0001), with similar incidence trends (13.2/1000 to 10.2/1000; p = 0.0007) among previously-screened at-risk members, and a rise in testing rates from 53.0% to 66.7% (p = 0.0004). The previously-unscreened group decreased 28.6%, and the incidence rates within this group remained stable. Conclusions The increase in diabetes prevalence is decelerating despite declining mortality and increasing testing rates. A decline in previously-screened incident cases and a shrinking pool of previously-unscreened members suggests that diabetes trends in Israel are moving toward equilibrium, rather than a growing epidemic. [ABSTRACT FROM AUTHOR]

Abstract: Purpose: Few models have been developed specifically for the epidemiology of diabetes. Diabetes incidence is critical in predicting diabetes prevalence. However, reliable estimates of disease incidence rates are difficult to obtain. The aim of this study was to propose a mathematical framework for predicting diabetes prevalence using incidence rates estimated within the model using body mass index (BMI) data. Methods: A generic mechanistic model was proposed considering birth, death, migration, aging, and diabetes incidence dynamics. Diabetes incidence rates were determined within the model using their relationships with BMI represented by the Hill equation. The Hill equation parameters were estimated by fitting the model to National Health and Nutrition Examination Survey (NHANES) 1999–2010 data and used to predict diabetes prevalence pertaining to each NHANES survey year. The prevalences were also predicted using diabetes incidence rates calculated from the NHANES data themselves. The model was used to estimate death rate parameters and to quantify sensitivities of prevalence to each population dynamic. Results: The model using incidence rate estimates from the Hill equations successfully predicted diabetes prevalence of younger, middle-aged, and older adults (prediction error, 20.0%, 9.64%, and 7.58% respectively). Diabetes prevalence was positively associated with diabetes incidence in every age group, but the associations among younger adults were stronger. In contrast, diabetes prevalence was more sensitive to death rates in older adults than younger adults. Both diabetes incidence and prevalence were strongly sensitive to BMI at younger ages, but sensitivity gradually declined as age progressed. Younger and middle aged adults diagnosed with diabetes had at least a two-fold greater risk of death than their nondiabetic counterparts. Nondiabetic older adults were found to be under slightly higher death risk (0.079) than those diagnosed with diabetes (0.073). Conclusions: The proposed model predicts diagnosed diabetes incidence and prevalence reasonably well using the link between BMI and diabetes development risk. Ethnic group and gender-specific model parameter estimates could further improve predictions. Model prediction accuracy and applicability need to be comprehensively evaluated with independent data sets. [Copyright &y& Elsevier]

Purpose: Little research has focused on the social patterning of diabetes among African Americans. We examined the relationship between socioeconomic status (SES) and the prevalence, awareness, treatment, and control of diabetes among African Americans. Methods: Education, income and occupation were examined among 4,303 participants (2,726 women and 1,577 men). Poisson regression estimated relative probabilities (RP) of diabetes outcomes by SES. Results: The prevalence of diabetes was 19.6% in women and 15.9% in men. Diabetes awareness, treatment, and control were 90.0%, 86.8%, and 39.2% in women, respectively, and 88.2%, 84.4%, and 35.9% in men, respectively. In adjusted models, low-income men and women had greater probabilities of diabetes than high-income men and women (RP, 1.94; 95% confidence interval [CI], 1.28–2.92; and RP, 1.35; 95% CI, 1.04–1.74, respectively). Lack of awareness was associated with low education and low occupation in women (RP, 2.28; 95%CI 1.01–5.18; and RP, 2.62; 95% CI, 1.08–6.33, respectively) but not in men. Lack of treatment was associated with low education in women. Diabetes control was not patterned by SES. Conclusions: Diabetes prevalence is patterned by SES, and awareness and treatment are patterned by SES in women but not men. Efforts to prevent diabetes in African Americans need to address the factors that place those of low SES at higher risk. [Copyright &y& Elsevier]

Abstract: Introduction: Diabetes is a major cause of morbidity and mortality and its global prevalence is growing rapidly. A simple and robust approach to estimate the prevalence of diabetes is essential for governments to set priorities on how to meet the challenges of the disease. The International Diabetes Federation has developed a methodology for generating country-level estimates of diabetes prevalence in adults (20–79 years). Methods: Using country-level data sources from peer-reviewed studies, national health statistics reports, commissioned studies on diabetes prevalence, and unpublished data obtained through personal communication, we use logistic regression to generate estimates of the prevalence of diabetes. An approach matching countries on ethnicity, geography, and income group is used to fill in gaps where original data sources are not available. The methodology also uses changes in urbanization and population to generate estimates and projections on the prevalence of diabetes in adults. Conclusion: Diabetes prevalence estimates are very sensitive to the data from which they are derived. The revised IDF methodology for estimating diabetes prevalence is a transparent, reproducible approach that will be updated annually. It takes data-driven approaches to filling in gaps where data are not available and where assumptions have to be made. It uses a qualification system to rank data sources so that only the highest quality data are used. [Copyright &y& Elsevier]

Abstract: Aims/hypothesis: To estimate the prevalence and the direct cost of pharmacologically-treated diabetes in Italy. Methods: The ARNO observatory database, containing the 20-year medical prescriptions of over 10 million Italian people, was used. Ten-year longitudinal data were available in 22 Local Health Districts (LHD). Subjects were classified as having diabetes when prescribed glucose-lowering drugs (oral agents or insulin) (311,979 individuals in 2006). The direct cost was calculated as the sum of drug use, financial compensation by LHD for the inpatient (hospital DRG) and outpatient activities (consultations, laboratory tests, radiology, etc.), all regulated by government contracts. Individuals with diabetes were compared with pharmacologically-treated subjects without diabetes, pair-matched for age, sex and general practitioner. Results: In the 10-year period, the prevalence of pharmacologically-treated diabetes increased from 3.08% to 4.45% (P for trend, <0.001). The average pro capita cost totaled €2,589 in 2006 (95% confidence interval (CI), 2,584–2,594), corresponding to a rate ratio vs. no-diabetes of 1.54 (95% CI, 1.50–1.56). The cost of drugs was € 827 (rate ratio, 1.80 vs. no-diabetes; 95% CI, 1.79–1.82), that of service use, € 488 (rate ratio, 1.07 (0.93–1.25). Only 20% of the pharmaceutical cost was due to glucose-lowering drugs, a percentage stable through the years. The cost of any hospital admission, as defined by DRGs, was independent of diabetes, but the overall cost was much higher in diabetes due to much higher admission rates. Cardiovascular complications and renal failure accounted for the large majority of excess hospital cost. Conclusion: The direct economic burden of pharmacologically-treated diabetes on the National Health System is very high, due to the growing prevalence of disease and the cost of complications. [Copyright &y& Elsevier]