Incidence Rate Of Type 2 Diabetes Mellitus Research Articles

Burden of type 2 diabetes mellitus and its risk factors in North Africa and the Middle East, 1990–2019: findings from the Global Burden of Disease study 2019

BackgroundThe prevalence of Type 2 Diabetes Mellitus (T2DM) in the North Africa and Middle East region is alarmingly high, prompting us to investigate the burden and factors contributing to it through the GBD study. Additionally, there is a lack of knowledge about the epidemiological status of T2DM in this region, so our aim is to provide a comprehensive overview of the burden of T2DM and its associated risk factors.MethodsUsing data from the 2019 Global Burden of Disease Study, we calculated the attributable burden of T2DM for each of the 21 countries in the region for the years 1990 and 2019. This included prevalence, mortality, disability-adjusted life years (DALYs), and risk factors.ResultsBetween 1990 and 2019, there was a significant increase in the age-standardized incidence (79.6%; 95% Uncertainty Interval: 75.0 to 84.5) and prevalence (85.5%; [80.8 to 90.3]) rates of T2DM per 100,000 populations. The age-standardized mortality rate (1.7%; [-10.4 to 14.9]), DALYs (31.2%; [18.3 to 42.2]), and years lived with disability (YLDs) (82.6%; [77.2 to 88.1]) also increased during this period. Modifiable risk factors, such as high body mass index (56.4%; [42.8 to 69.8]), low physical activity (15.5%; [9.0 to 22.8]), and ambient particulate matter pollution (20.9%; [15.2 to 26.2]), were the main contributors to the number of deaths.ConclusionThe burden of T2DM, in terms of mortality, DALYs, and YLDs, continues to rise in the region. The incidence rate of T2DM has increased in many areas. The burden of T2DM attributed to modifiable risk factors continues to grow in most countries. Targeting these modifiable risk factors could effectively reduce the growth and disease burden of T2DM in the region.

Nonrestorative Sleep and Type 2 Diabetes Incidence: the Aichi Workers' Cohort Study.

The term "nonrestorative sleep (NRS)" refers to unrefreshed feeling at wake-up and is a domain of poor sleep quality. Previous researches have demonstrated that NRS is linked to a number of diseases and adverse health outcomes, but less is known regarding the link between NRS and diabetes, particularly in Japanese. We studied 3665 middle-aged male participants of the Aichi Workers' Cohort Study who were followed-up from 2002 to 2019. Cox proportional hazards models estimated hazard ratios (HRs) and 95% confidence intervals (CIs) of incident type 2 diabetes mellitus (T2DM) in relation to NRS adjusted for potential confounding variables. During a median follow-up of 14.6 years, 421 type 2 diabetes cases were identified. Participants with NRS had a higher crude incidence rate of T2DM (11.2/1,000 person-years), compared to participants without NRS (9.3/1,000 person-years). In the fully adjusted model, individuals who reported having NRS had a significantly higher risk of developing T2DM (HR: 1.36, 95% CI: 1.10-1.67). The association was observed only in participants under 50 years old (HR: 1.82, 95% CI: 1.36-2.43), not in the older (50 years or older) participants (P for interaction =0.025). In contrast, stratified analyses by the presence of shift work, obesity or sleep duration showed similar associations in all the strata. NRS was associated with higher risk of T2DM in middle-aged Japanese male workers independent of a variety of lifestyle factors and other sleep problems.

Lifestyle behaviour patterns in the prevention of type 2 diabetes mellitus: the Fukushima Health Database 2015–2020

ObjectivesLifestyle behaviours associated with the incidence of type 2 diabetes mellitus (T2DM) need further clarification using health insurance data. Study designThis is a cohort study. MethodsIn 2015, 193,246 participants aged 40–74 years attended the specific health checkups and were observed up to 2020 in Fukushima, Japan. Using the principal component analysis, we identified two patterns from ten lifestyle behaviour questions, namely, the “diet–smoking” pattern (including smoking, alcohol drinking, skipping breakfast, eating fast, late dinner, and snacking) and the “physical activity–sleep” pattern (including physical exercise, walking equivalent activity, walking fast, and sufficient sleep). Then, individual pattern scores were calculated; the higher the scores, the healthier the behaviours. ResultsThe accumulative incidence rate of T2DM was 630.5 in men and 391.9 in women per 100,000 person-years in an average of 4 years of follow-up. Adjusted for the demographic and cardiometabolic factors at the baseline, the hazard ratio (95% confidence interval) of the highest versus lowest quartile scores of the “diet–smoking” pattern for T2DM risk was 0.82 (0.72, 0.92; P for trend = 0.002) in men and 0.87 (0.76, 1·00; P for trend = 0.034) in women; that of the “physical activity–sleep” pattern was 0.92 (0.82, 1·04; P for trend = 0.0996) in men and 0.92 (0.80, 1·06; P for trend = 0.372) in women. The “physical activity–sleep” pattern showed a significant inverse association in non-overweight men. ConclusionsLifestyle behaviour associated with a healthy diet and lack of smoking may significantly lower the risk of T2DM in middle-aged Japanese adults.

The Incidence and Management of Type 2 Diabetes Mellitus After Gestational Diabetes Mellitus.

Gestational diabetes mellitus (GDM) refers to a transient state of impaired glucose tolerance that develops during pregnancy, affecting a significant proportion of expectant mothers globally. This review aimed to comprehensively examine the subsequent incidence and management of type 2 diabetes mellitus (T2DM) in women who have previously experienced GDM. The transition from GDM to T2DM is a well-recognized continuum, with affected women facing an increased risk of developing T2DM postpartum. Several studies have demonstrated that women with a history of GDM face a substantially higher risk of developing T2DM compared to normoglycemic pregnant women. The long-term consequences of developing T2DM following GDM are significant, as it not only affects the health of the mother but also poses risks to the offspring. The most common risk factors associated with the progression of GDM to T2DM include pregnancy at an advanced age, insulin treatment during pregnancy, and delivering an overweight baby. As GDM women are at higher risk of developing T2DM, effective management strategies such as lifestyle changes, postpartum care, breastfeeding, screening tests, and gaining awareness of risk are crucial to mitigate the risk of T2DM in this population. The current review was conducted to guide healthcare providers and women with a history of GDM about the potential risks of T2DM and management strategies to prevent the condition. This review provides a summary of evidence on the incidence rate of T2DM in GDM patients, its associated risk factors, and approaches to mitigate this challenge.

The Risk of Type 2 Diabetes Mellitus according to Changes in Obesity Status in Late Middle-Aged Adults: A Nationwide Cohort Study of Korea.

Although obesity is a well-known risk factor of type 2 diabetes mellitus (T2DM), there is scant data on discriminating the contribution of previous obesity and recent weight gain on developing T2DM. We analyzed the Korean National Health Insurance Service-Health Screening Cohort data from 2002 to 2015 where Korean residents underwent biennial health checkups. Participants were classified into four groups according to their obesity status (body mass index [BMI] ≥25 kg/m2) before and after turning 50 years old: maintaining normal (MN), becoming obese (BO), becoming normal (BN), and maintaining obese (MO). Cox proportional hazards regression model was used to estimate the risk of T2DM factoring in the covariates age, sex, BMI, presence of impaired fasting glucose or hypertension, family history of diabetes, and smoking status. A total of 118,438 participants (mean age, 52.5±1.1 years; men, 45.2%) were prospectively evaluated for incident T2DM. A total of 7,339 (6.2%) participants were diagnosed with T2DM during a follow-up period of 4.8±2.6 years. Incidence rates of T2DM per 1,000 person-year were 9.20 in MN, 14.81 in BO, 14.42 in BN, 21.38 in MO. After factoring in covariates, participants in the groups BN (adjusted hazard ratio [aHR], 1.15; 95% confidence interval [CI], 1.04 to 1.27) and MO (aHR, 1.14; 95% CI, 1.06 to 1.24) were at increased risk of developing T2DM compared to MN, whereas BO (hazard ratio, 1.06; 95% CI, 0.96 to 1.17) was not. Having been obese before 50 years old increased the risk of developing T2DM in the future, but becoming obese after 50 did not. Therefore, it is important to maintain normal weight from early adulthood to prevent future metabolic perturbations.

Growth trajectories in lipid profile and fasting blood sugar in prediabetic people over a 16- year follow-up and future risk of type2 diabetes mellitus: A latent growth modeling approach

ABSTRACT Introduction The current study aimed to investigate whether the pattern of changes in lipid profile and fasting blood sugar (FBS) can predict the future risk of type 2 diabetes mellitus (T2DM) incidence in prediabetic people. Methods In a prospective cohort study, 1228 prediabetic patients were followed from 2003 until 2019 and longitudinal data on lipid indices (CHOL: cholesterol; HDL: high-density lipoprotein; LDL: low-density lipoprotein; TG: triglyceride) and fasting blood sugar (FBS) were recorded. The latent class growth model (LCGM) was used to estimate growth trajectories and to determine distinct subgroups (latent class) with a similar trajectory for lipid profile and FBS over time. The incidence of T2DM in extracted latent classes was compared. Results Finally, 946 people with complete data were included in statistical analysis. Two latent classes were identified based on the change in FBS including high-risk and low-risk classes (class size: 5.2% vs. 94.8%) with T2DM incidence rates 100% and 35.9%, respectively (P < 0.001). Two distinct subgroups were identified based on changes in lipid profile. Latent classes with abnormal TG, CHOL, HDL, and LDL included 18.8%, 21.8%, 38.8%, and 24% of study participants, respectively. The incidence rates of T2DM and remaining prediabetic in abnormal TG latent class were 57.2% and 30.8%, and in abnormal HDL latent class were 41.5% and 31.7% were significantly different from normal latent classes (P < 0.001). While in the extracted latent classes based on CHOL and LDL the incidence rates were not statistically significant differences (P > 0.05). Conclusions We identified two subgroups with high and low risk of future T2DM based on the changes in FBS and lipid profile by applying LCGM. The incidence of T2DM in extracted latent classes was significantly different. LCGM is a reliable approach for predicting the risk of T2DM incidence based on trajectories of risk factors.

Aberrations in carbohydrate metabolism in patients with diagnosed acromegaly - observational study.

Acromegaly is characterized by excessive secretion of growth hormone (GH). The incidence rate of acromegaly is 40 to 70 persons per one million people. Carbohydrate disorders often accompany the above pathology. The aim of this study was to examine the influence of high levels of somatotropin on aberrations in glycaemia in patients with acromegaly, and then a 5-year observation. The study group consisted of 86 patients (48 females and 38 males) with acromegaly diagnosed on the basis of clinical features, elevated insulin-like growth factor 1 (IGF-1) levels, and/or no inhibition of GH ≤ 1 ug/L secretion during 2 hours after an oral glucose load. In the study group type 2 diabetes mellitus (T2DM) was diagnosed in 21 patients (24.4%). There were also 14 cases (16.3%) of the diagnosis of impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) combined. The mean age of participants with concomitant T2DM was 52.1 years, while the mean age of those without carbohydrate metabolism disturbances was 46.1 years. During a 5-year observation, we noticed an increase level of glycated haemoglobin (HbA1c) and new cases of pre-diabetes and T2DM. In patients with acromegaly the incidence rate of T2DM is 3-4 times higher than in the rest of the population, and it increases with age, especially after the patient reaches 55 years old.

Incidence, Morbidity and years Lived With Disability due to Type 2 Diabetes Mellitus in 204 Countries and Territories: Trends From 1990 to 2019

BackgroundWe aimed to examine the descriptive epidemiology and trends in the burden of type 2 diabetes mellitus (T2DM).MethodsData were extracted from the Global Burden of Disease 2019 dataset. Estimated annual percentage changes (EAPCs) were calculated to assess the trends in incidence rate, mortality and disability-adjusted life-years (DALYs) associated with T2DM. Measures were stratified by sex, region, country, age and social development index (SDI) value.ResultsThe global age-standardized incidence rate of T2DM increased from 1990 to 2019, with an EAPC of 1.25 (95% CI, 1.19 to 1.31). In 2019, the highest age-standardized incidence rate of T2DM was observed in high-SDI regions, and the largest increase in this rate from 1990 to 2019 was also in high-SDI regions (EAPC, 1.74;95% CI, 1.57 to 1.90). At the regional level, Central Asia (EAPC, 2.53;95% CI, 2.45 to 2.61) had the largest increase in the age-standardized incidence rate of T2DM from 1990 to 2019. At the national level, Luxembourg (EAPC, 4.51;95% CI, 4.37 to 4.65) and Uzbekistan (EAPC, 3.63; 95% CI, 3.44 to 3.82) had the largest increases in the age-standardized incidence rate of T2DM from 1990 to 2019. The global age-standardized death and DALY rates increased from 1990 to 2019, with EAPCs of 0.26 (95% CI, 0.16 to 0.37) and 0.81 (95% CI, 0.77 to 0.85), respectively. The age-standardized death and DALY rates showed the largest increases in Central Asia, South Asia and Southern Sub-Saharan Africa.ConclusionsGlobally, the age-standardized incidence, death and DALY rates increased from 1990 to 2019. Central Asia, South Asia and Southern Sub-Saharan Africa were found to have the greatest burden of T2DM. Future strategies should focus on these high-risk regions and other high-risk populations.

Time trends in type 2 diabetes mellitus incidence across the BRICS from 1990 to 2019: an age-period-cohort analysis

BackgroundThe incidence rate of type 2 diabetes mellitus (T2DM) is rapidly increasing in Brazil, Russia, India, China, and South Africa (BRICS). The present study analyzed trends in T2DM incidence rate across the BRICS and associations with age, period, and birth cohort.MethodsThe incidence rate was estimated by the data obtained from GBD 2019 (Global Burden of Disease Study 2019) and was analyzed with the age-period-cohort framework. Incidence rates of T2DM (1990–2019) were collected for each 5-year age group (from 25 to 29 to 85–89 age group) stratified by gender from the Global Burden of Disease 2019 Study.ResultsIn 2019, the the incidence rate of T2DM was 280.2 per 100,000 across the BRICS. Between 1990 and 2019, the incidence rate of T2DM among the BRICS population increased by 83.3%. In each period, as age increases, the incidence rate of T2DM in China and Russia first increased and then decreased, while the incidence rate of T2DM in Brazil, India and South Africa first increased and then decreased slightly with age group. Deteriorating period and cohort risks for incidence rate of T2DM were generally found across the BRICS.ConclusionsThe number of diabetic patients in the BRICS countries has continued to increase and the growth rate has been stable in the past 30 years, which is dependent on age and some other environmental factors. Some possible factors influencing T2DM incidence are analyzed and hypotheses generated through the age and period effects.

Non-alcoholic fatty liver disease increases the incidence rate of type 2 diabetes mellitus: a cohort study based on a rural town elderly population of southern Jiangsu

Objective: To investigate the impact of non-alcoholic fatty liver disease (NAFLD) on the incidence of type 2 diabetes mellitus (T2DM) in an elderly population. Methods: A rural elderly population of Kunshan city, Jiangsu Province were used as the research subject. Prior diabetes mellitus, heavy alcohol consumption and incomplete data were excluded from prospective cohort study analysis. Annual physical examination and follow-up were conducted from 2007 to 2016. T2DM onset, death and loss to follow-up visits were observed as the research subject end points. According to the baseline physical examination results, the study subjects were divided into NAFLD and control groups, and further baseline data of both groups were analyzed whether there were match. The cumulative incidence rate of T2DM were statistically analyzed and compared between the two groups. Simultaneously, the relationship between the two groups of various indexes and the newly developed T2DM were analyzed using Kaplan-Meier. The variables with P < 0.1 were selected and incorporated into the Cox proportional hazard regression model. The impact of NAFLD on the incidence of T2DM was analyzed in an elderly population. Results: At baseline, there were statistically significant differences in the distribution of age, sex, waist circumference, body mass index, systolic blood pressure, diastolic blood pressure, direct bilirubin, blood urea nitrogen and triglycerides between NAFLD and non-NAFLD groups. However, fasting blood glucose, serum creatinine, total bilirubin, total cholesterol, low density lipoprotein cholesterol and high-density lipoprotein cholesterol had no statistically significant differences between the two groups. After nine years of follow-up, 207 newly developed T2DM cases, 52 NAFLD cases and 155 control group were selected as the study subjects. The cumulative incidence rates were 4.25%, 10.34%, and 3.55%, respectively. Kaplan-Meier analysis result showed that there were statistically significant differences in the cumulative incidence rates between the two groups from five-year. NAFLD had increased the T2DM risk in an elderly population by approximately 2.14 times (2.14 CI: 1.132 ~ 4.047) at five-year, and then had increased year by year thereafter. Univariate analysis showed that T2DM risk was 2.76 times higher in NAFLD than non-NAFLD groups (95% CI: 2.015 ~ 3.777). After adjustment for gender, age, body mass index, waist circumference, systolic blood pressure, diastolic blood pressure, serum creatinine, triglyceride, total cholesterol, high-density lipoprotein cholesterol and low-density lipoprotein cholesterol, T2DM risk ratio was 1.68 times higher in NAFLD than control groups (95% CI: 1.163 ~ 2.425). Conclusion: NAFLD is an independent long-term risk factor for the T2DM onset in an elderly population.

Association of obesity phenotypes in adolescents and incidence of early adulthood type 2 diabetes mellitus: Tehran lipid and glucose study.

Obesity and metabolic syndrome, which has an increasing prevalence among adolescence, are associated with metabolic abnormalities. This study investigates the role of adolescent obesity phenotypes in predicting the incidence of early adulthood type 2 diabetes mellitus (T2DM). Participants were divided into four obesity phenotypes: Metabolically healthy normal weight (MHNW), metabolically healthy obese (MHO), metabolically unhealthy normal weight (MUNW), and metabolically unhealthy obese (MUO). Multivariate-adjusted hazard ratios (HRs) were calculated for T2DM incidence. In this cohort study, 2306 Tehranian adolescents with an average age of 15.1± 2.4 years were included. The median (IQ 25-75) follow-up was 15.5 (12.8-17.1) years and the median (IQ 25-75) age of participants at the end of follow-up was 30 (26-32) years old. The incidence rate of T2DM during the early adulthood was [1.37 (95% CI: 0.89-2.10)] and [3.18 (95% CI: 2.44-4.16)] per 1000 person per year in boys and girls, respectively. MHO phenotype was not associated with an increased risk of T2DM for both sexes. Adjusted HRs for MUO were [4.30 95% CI (1.48-12.43)] and [3.39 95% CI (1.78-6.45)] in boys and girls, respectively. MUNW phenotype was associated with an increased risk of T2DM only in boys. After adjustment for adulthood BMI, all the phenotypes for both sexes lost their significance, except for boys with MUNW phenotype [HR=3.46 95% CI (1.15-10.45)]. Unhealthy obesity phenotypes; in contrast with MHO; had an increased risk of T2DM incidence, apart from girls with MUNW. After adjusting the adulthood BMI, all phenotypes turn insignificant, except for boys with MUNW.

Incidence and associated factors of type 2 diabetes mellitus onset in the Brazilian HIV/AIDS cohort study

BackgroundPeople living with HIV (PLH) under combined antiretroviral therapy (cART) are at risk of developing type 2 diabetes mellitus (T2DM). ObjectiveWe examined the incidence of T2DM, associated factors and mean time to outcome in PLH under cART. MethodData for this multicenter cohort study were obtained from PLH aged over 18, who started cART in 13 Brazilian sites from 2003 to 2013. Factors associated with incident T2DM were evaluated by Cox multiple regression models. ResultsA total of 6724 patients (30,997.93 person-years) were followed from January 2003 to December 2016. A T2DM incidence rate of 17.3/1000 person-years (95%CI 15.8-18.8) was observed. Incidence of isolated hypertriglyceridemia and impaired fasting glucose (IFG) were 84.3 (95%CI 81.1-87.6) and 14.5/1000 person-years (95%CI 13.2-15.9), respectively. Mean time to T2DM onset was 10.5 years (95%CI 10.3-10.6). Variables associated with incident T2DM were age 40-50 [Hazard Ratio (HR) 1.7, 95%CI 1.4-2.1] and ≥ 50 years (HR 2.4, 95%CI 1.9-3.1); obesity (HR 2.1, 95%CI 1.6-2.8); abnormal triglyceride/HDL-cholesterol ratio (HR 1.8, 95%CI 1.51-2.2). IFG predicted T2DM (HR 2.6, 95%CI 1.7-2.5) and occurred on average 3.3 years before diabetes onset. Exposure to stavudine for ≥ 2 years was independently associated with incident T2DM [HR 1.6, 95%CI 1.0-2.2). ConclusionBrazilian PLH under cART are at significant risk of developing T2DM and share risk factors for diabetes onset with the general population, such as older age, obesity, and having metabolic abnormalities at baseline. Moreover, stavudine use was independently associated with incident T2DM. Identifying PLH at a higher risk of T2DM can help caretakers trigger health promotion and establish specific targets for implementation of preventive measures.

Using real-world data to estimate the changing trends in the prevalence and incidence of type 2 diabetes mellitus in Xiamen of China from 2014 to 2019

BackgroundThe prevalence of diabetes is increasing worldwide. Our study aimed to estimate the changing trends in the prevalence and incidence of diagnosed type 2 diabetes mellitus (T2DM) among Xiamen residents and the floating population using real-world data.MethodWe used real-world data from the System of Xiamen Citizens Health Information from 2014 to 2019 to estimate the changing trends in the prevalence and incidence of diagnosed T2DM. The System included the diagnosis of diabetes and the prescription of hypoglycemic drugs. Prevalent cases of T2DM were individuals who were diagnosed with T2DM and/or using hypoglycemic drugs. Incident cases were individuals with diagnosed T2DM and/or using hypoglycemic drugs in 2014 or 2019 who had not been diagnosed and/or did not use hypoglycemic drugs in the past.ResultsIn 2014 and 2019, the prevalence of T2DM in Xiamen was 4.04 and 4.84%, respectively. In 2014 and 2019, the incidence rate of T2DM in Xiamen was 14.1 per 1000 person-year and 15.0 per 1000 person-year, respectively. There was a significant increase in both the prevalence (Prevalence difference: 0.80, 95%CI 0.76–0.83%, P < 0.001) and the incidence of T2DM (Incidence difference: 0.9, 95%CI 0.7–1.1, P < 0.001). in Xiamen. The prevalence and incidence of T2DM in people aged 18–39 increased significantly (P < 0.001), while the prevalence and incidence of T2DM in people aged 40–69 reduced significantly (P < 0.001).ConclusionsThere was a significant increase in the prevalence and incidence of T2DM in Xiamen from 2014 to 2019 especially among those with younger age.

The Current and Forecasted Status of Type 2 Diabetes in the Arab Society of Israel.

Diabetes mellitus (DM) is considered one of the main causes of mortality, morbidity, and health care expenditures. Effectively treating this disease is of crucial importance and imposes a global challenge. The incidence of Type 2 DM (T2DM) is rapidly rising in both developing and developed countries. The Arab community in Israel is a distinct ethnic group with unique characteristics. Recently, this community has undergone major changes in its lifestyle, adopting the Westernized one, which could have caused an increase in the T2DM incidence rate. This review aims to shed light on various studies undertaken to explore the prevalence of diabetes and determine its current status in the Arab society of Israel, resting on previous and current data. It is presented to highlight the status of diabetes globally and to focus on its current situation in the Arab society of Israel, attempting to forecast its direction in the upcoming decade. Data were obtained from our previous comprehensive socio-economic and health crosssectional surveys for successive periods from 2004 to 2017. These surveys were conducted on the Arab society of Israel by the Galilee Society. Our results showed a progressive increase in the prevalence of T2DM from 3.4% to 7.6% in the Arab society of Israel. This trend is expected to continue rising in the coming decade, and based on our predictions, may exceed 12% in 2030. Substantial and practical health-related actions must be initiated to prevent an increasing number of adults from developing diabetes and its complications.

Risk of type 2 diabetes is increased in nonobese women with polycystic ovary syndrome: the National Health Insurance Service-National Sample Cohort Study

To investigate the relationship between polycystic ovary syndrome (PCOS) and type 2 diabetes mellitus (T2DM) in Korean women. Longitudinal case-control study. Not applicable. PCOS patients aged 15 to 44 years (n = 1,136) and control individuals (n = 5,675), matched 1:5 by age group, income, and region of residence. Not applicable. The occurrence of T2DM. In the PCOS and control groups, 15.7% and 14.4%, respectively, were obese (body mass index ≥25 kg/m2). The incidence rate of T2DM was 15.84/1,000 and 5.80/1,000 person-years in the PCOS and control groups, respectively. The unadjusted hazard ratio (HR) of T2DM in women with PCOS was 2.6-fold higher than that in control individuals. Women with PCOS still had a higher HR of T2DM than did control individuals after adjustment for body mass index, family history of T2DM, physical exercise level, and total cholesterol. PCOS was significantly associated with T2DM in women both with and without obesity. PCOS is independently associated with an increased incidence of T2DM in both obese and nonobese women. Screening for T2DM should be considered for both obese and nonobese women with PCOS in Korea.

Investigation of the Association between 45 Tag SNPs and Type 2 Diabetes Mellitus in Han Chinese Adults: A Prospective Cohort Study

Introduction: The objective of this study was to examine the association between type 2 diabetes mellitus (T2DM) and genes identified in previous genome-wide association studies (GWASs) in rural Han Chinese adults. Methods: This prospective study included 1,832 adults aged ≥18 years in Deqing without diabetes at baseline. The subjects were followed up for 8.7 years on average. We selected 45 susceptible tag single-nucleotide polymorphisms (SNPs) for T2DM that have been identified in GWASs and genotyped. A Cox model was constructed to calculate the adjusted hazard ratios (aHRs) for the association between SNPs and incident T2DM. Results: The incidence rate of T2DM was 12.0 per 1,000 person-years. After adjustment for covariates and a Bonferroni correction, rs17584499 of protein tyrosine phosphatase, receptor-type D (PTPRD), rs11257655 and rs10906115 of cell division cycle 123 gene (CDC123), and rs12970134 of melanocortin-4 receptor (MC4R) were significantly associated with incident T2DM. The aHRs for incident T2DM were 1.75 (95% confidence interval [CI]: 1.28–2.40) and 1.61 (95% CI: 1.27–2.04) in association with an increasing number of T alleles in rs17584499 and rs11257655 under an additive genetic model, and the aHR was 1.72 (95% CI: 1.33–2.22) with an increasing number of A alleles in rs10906115. The aHRs under the dominant model were 1.82 (95% CI: 1.25–2.66) for TT + CT versus CC of rs17584499 and 2.04 (95% CI: 1.47–2.86) for AA + AG versus GG of rs10966115. The aHRs under the recessive model were 2.99 (95% CI: 1.30–6.89) for TT versus CT + CC of rs17584499, 1.92 (95% CI: 1.39–2.70) for TT versus CT + CC of rs11257655, and 2.54 (95% CI:1.22–5.29) for AA versus AG + GG of rs12970134. In addition, an increased incidence of T2DM was significantly associated with the TA haplotype of rs11257655 and rs10906115 (aHR = 1.81, 95% CI: 1.12–2.92), while a decreased incidence was associated with the CG haplotype (aHR = 0.49, 95% CI: 0.35–0.68) and the CT haplotype of rs1111875 and rs5015480 (aHR = 0.61, 95% CI: 0.37–0.98). Conclusion: Variants of the PTPRD, CDC123, and MC4R genes were associated with the T2DM incidence in a rural Han Chinese population.

Incident type 2 diabetes mellitus after initiation of common HIV antiretroviral drugs.

To describe the prevalence and incidence of prediabetes and type 2 diabetes mellitus (T2DM) among people living with HIV (PLHIV) and evaluate the association between antiretroviral therapy (ART) initiation with dolutegravir (DTG), elvitegravir/cobicistat (EVG/c), raltegravir (RAL), or boosted darunavir (bDRV) and incident T2DM. Longitudinal study based on electronic health records of 29 674 PLHIV from the Observational Pharmaco-Epidemiology Research and Analysis (OPERA) cohort. Calculate prevalence of prediabetes and T2DM at regimen initiation. Among PLHIV without prevalent disease, estimate prediabetes and T2DM incidence (Poisson regression) and association between regimen and incident T2DM (multivariate Cox proportional hazards regression). Analyses stratified by ART experience. Among ART-naive and ART-experienced/suppressed PLHIV, the estimated prevalence of prediabetes was 8 and 11%; that of T2DM was 4 and 10%, respectively. The T2DM incidence rate was 9 per 1000 person-years [95% confidence interval (CI): 8-11] among ART-naive and 13 per 1000 person-years (95% CI: 12-15) among ART-experienced/suppressed PLHIV, with no statistically significant differences between regimens. Compared with DTG, no statistically significant association between T2DM risk and regimen was observed among ART-naive on EVG/c [adjusted hazard ratios: 0.70 (95% CI: 0.47-1.05)] or bDRV [0.53 (0.26-1.04)] and ART-experienced/suppressed on EVG/c [0.96 (0.70-1.33)], RAL [1.17 (0.70-1.96)] or bDRV [0.90 (0.57-1.42)]. No increased risk of T2DM was observed with EVG/c, RAL or bDRV compared with DTG in ART-naive and experienced PLHIV. However, despite a large cohort, there was a small number of events and differential risk cannot be excluded.

Non-linear relationship between gamma-glutamyl transferase and type 2 diabetes mellitus risk: secondary analysis of a prospective cohort study.

ObjectiveTo investigate the association between gamma-glutamyl transferase (GGT) and type 2 diabetes mellitus (T2DM) risk.MethodsThis was a secondary analysis based on a publicly available DRYAD dataset that included 15 444 study participants that received medical examinations at a single centre in Japan between 2004 and 2015. Crude, minimally-adjusted and fully-adjusted regression models were used to evaluate the relationship between GGT levels and T2DM risk.ResultsThe study participants (mean ± SD age of 43.72 ± 8.90 years; 8415 of 15 444 [54.49%] were male) were followed-up for a median of 1968 days (5.39 years). After adjusting for potential covariates, a non-linear relationship between the baseline GGT level and T2DM incidence was observed. The inflection point for T2DM risk was 10 IU/l GGT; below this point, the T2DM incidence increased by 1.18-fold per unit change in GGT. Above this point, the association between GGT and the incidence rate of T2DM became nonsignificant.ConclusionBaseline GGT exhibited a non-linear association with T2DM incidence. Elevated GGT levels should be incorporated into routine screening for individuals at high risk of T2DM, allowing for early intervention targeting GGT to potentially reduce T2DM-related morbidity.

Incidence Rate of Type 2 Diabetes Mellitus after Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis of 170,139 Women.

Objective The reported incidence of type 2 diabetes mellitus (T2DM) after gestational diabetes (GDM) varies widely. The purpose of this meta-analysis was to define the incidence rate of T2DM among women with a history of GDM and to examine what might modulate the rate. Research Design and Methods. We searched PubMed and Embase for terms related to T2DM after GDM up to January 2019. Large cohort studies with sample size ≥300 and follow-up duration of at least one year were included. Data from selected studies were extracted, and meta-analysis was performed using the random-effects model. Subgroups analyses were based on the sample size of gestational diabetes, geographic region, maternal age, body-mass index, diagnostic criteria, and duration of follow-up. Results Twenty-eight studies involving 170,139 women with GDM and 34,627 incident cases of T2DM were identified. The pooled incidence of T2DM after GDM was 26.20 (95% CI, 23.31 to 29.10) per 1000 person-years. Women from Asia and those with older age and higher body mass index seem to experience higher risk of developing T2DM. The incidence rate of T2DM was lowest when applying IADPSG (7.16 per 1000 person-years) to diagnose GDM. The risk of developing T2DM after GDM increased linearly with the duration of follow-up. The increments per year of follow-up were estimated at 9.6‰. The estimated risks for T2DM were 19.72% at 10 years, 29.36% at 20 years, 39.00% at 30 years, 48.64% at 40 years, and 58.27% at 50 years, respectively. Conclusions The findings of very high incidence of T2DM after GDM add an important insight into the trajectory of the development of T2DM in the long-term postpartum periods, which could provide evidence for consultant and might motivate more women with GDM to screen for T2DM. This trial is registered with PROSPERO identifier CRD42019128980.

Significant fibrosis predicts new-onset diabetes mellitus and arterial hypertension in patients with NASH

Non-alcoholic fatty liver disease (NAFLD) could play a catalytic role in the development of metabolic comorbidities, although the magnitude of this effect in metabolically healthy patients with NAFLD remains unclear. We assessed the role of biopsy-proven NAFLD on the risk of developing type 2 diabetes mellitus (T2DM) and other metabolic comorbidities (arterial hypertension [AHT], and dyslipidemia) in metabolically healthy patients. We included 178 metabolically healthy-defined by the absence of baseline T2DM, AHT, dyslipidemia-patients with biopsy-proven NAFLD from the HEPAmet Registry (N= 1,030). Hepamet fibrosis score (HFS), NAFLD fibrosis score, and Fibrosis-4 were calculated. Follow-up was computed from biopsy to the diagnosis of T2DM, AHT, or dyslipidemia. During a follow-up of 5.6 ± 4.4 years, T2DM occurred in 9% (16/178), AHT in 8.4% (15/178), low HDL in 9.6% (17/178), and hypertriglyceridemia in 23.6% (42/178) of patients. In multivariate analysis, significant fibrosis predicted T2DM and AHT. Independent variables related to T2DM appearance were significant fibrosis (HR 2.95; 95% CI 1.19-7.31; p= 0.019), glucose levels (p= 0.008), age (p= 0.007) and BMI (p= 0.039). AHT was independently linked to significant fibrosis (HR 2.39; 95% CI 1.14-5.10; p= 0.028), age (p= 0.0001), BMI (p= 0.006), glucose (p= 0.021) and platelets (p= 0.050). The annual incidence rate of T2DM was higher in patients with significant fibrosis (4.4 vs. 1.2 cases per 100 person-years), and increased in the presence of obesity, similar to AHT (4.6 vs. 1.1 cases per 100 person-years). HFS >0.12 predicted the risk of T2DM (25% [4/16] vs. HFS <0.12 4.5% [4/88]; logRank 6.658, p= 0.010). Metabolically healthy patients with NAFLD-related significant fibrosis were at greater risk of developing T2DM and AHT. HFS >0.12, but not NAFLD fibrosis score or Fibrosis-4, predicted the occurrence of T2DM. Patients with biopsy-proven non-alcoholic fatty liver disease and significant fibrosis were at risk of developing type 2 diabetes mellitus and arterial hypertension. The risk of metabolic outcomes in patients with significant fibrosis was increased in the presence of obesity. In addition to liver biopsy, patients at intermediate-to-high risk of significant fibrosis by Hepamet fibrosis score were at risk of type 2 diabetes mellitus.