Age- and sex-specific prevalence of diabetes and impaired glucose regulation in 11 Asian cohorts

Age-Related Glucose Intolerance Is Associated with Impaired Insulin Secretion in Community-Dwelling Japanese Adults: The Kumamoto Koshi Study

Background/Objectives: Glucose tolerance progressively declines with age. However, the effects of aging on insulin secretion and insulin sensitivity in Japanese subjects are unclear. Methods: We conducted an oral glucose tolerance test (OGTT) in residents aged between 22 and 85 years in Koshi City, Kumamoto Prefecture, Japan, to clarify the characteristics of insulin secretion and insulin sensitivity in older adults. Participants were recruited using a flyer, and the OGTT was performed after an overnight fast (12-16 h) between 8:00 and 10:30 am. Results: HOMA-IR and the Matsuda index are indices of insulin action. No correlation of age with HOMA-IR or the Matsuda index was found, whereas HOMA-β, the insulinogenic index, and the disposition index, all indices of insulin secretion, were negatively correlated with age in all participants and in individuals with normal glucose tolerance. Multiple regression analysis showed that age was an explanatory factor for insulin secretion. Conclusions: Impaired insulin secretion may contribute to age-related glucose intolerance in Japanese individuals.

Use of Machine Learning to Predict Individual Postprandial Glycemic Responses to Food Among Individuals With Type 2 Diabetes in India: Protocol for a Prospective Cohort Study

BACKGROUND

Type 2 diabetes (T2D) is a leading cause of premature morbidity and mortality globally and affects more than 100 million people in the world's most populous country, India. Nutrition is a critical and evidence-based component of effective blood glucose control and most dietary advice emphasizes carbohydrate and calorie reduction. Emerging global evidence demonstrates marked interindividual differences in postprandial glucose response (PPGR) although no such data exists in India and previous studies have primarily evaluated PPGR variation in individuals without diabetes.

OBJECTIVE

This prospective cohort study seeks to characterize the PPGR variability among individuals with diabetes living in India and to identify factors associated with these differences.

METHODS

Adults with T2D and a hemoglobin A1c of ≥7 are being enrolled from 14 sites around India. Participants wear a continuous glucose monitor, eat a series of standardized meals, and record all free-living foods, activities, and medication use for a 14-day period. The study's primary outcome is PPGR, calculated as the incremental area under the curve 2 hours after each logged meal.

RESULTS

Data collection commenced in May 2022, and the results will be ready for publication by September 2025. Results from our study will generate data to facilitate the creation of machine learning models to predict individual PPGR responses and to facilitate the prescription of personalized diets for individuals with T2D.

CONCLUSIONS

This study will provide the first large scale examination variability in blood glucose responses to food in India and will be among the first to estimate PPGR variability for individuals with T2D in any jurisdiction.

TRIAL REGISTRATION

Clinical Trials Registry-India CTRI/2022/02/040619; https://tinyurl.com/mrywf6bf.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/59308.

Assessing the validity of METS-IR for predicting the future onset of diabetes: an analysis using time-dependent receiver operating characteristics

BACKGROUND

The Metabolic Insulin Resistance Score (METS-IR) is a non-invasive proxy for insulin resistance (IR) that has been newly developed in recent years and has been shown to be associated with diabetes risk. Our aim was to assess the predictive value of METS-IR for the future development of diabetes and its temporal differences in people of different sex, age, and body mass index (BMI).

METHODS

The current study included 15,453 baseline non-diabetic subjects in the NAGALA cohort and then grouped according to the World Health Organization's (WHO) recommended criteria for age and BMI. Multivariate Cox regression and time-dependent receiver operator characteristics (ROC) curves were used to analyze the value of METS-IR in assessing and predicting the risk of diabetes in people of different sexes, ages, and BMIs.

RESULTS

373 individuals developed diabetes during the observation period. By multivariate COX regression analysis, the development of future diabetes was significantly associated with increased METS-IR, and this positive association was stronger in women than in men and in individuals < 45 years than in individuals ≥ 45 years; while no significant differences were observed between non-obese and overweight/obesity individuals. Using time-dependent ROC analysis we also assessed the predictive value of METS-IR for future diabetes at a total of 11-time points between 2 and 12 years. The results showed that METS-IR had a higher predictive value for the future development of diabetes in women or individuals < 45 years of age compared to men or individuals ≥ 45 years of age for almost the entire follow-up period. Furthermore, across different BMI categories, we also found that in the short term (3-5 years), METS-IR had a higher predictive value for the development of diabetes in individuals with overweight/obesity, while in the medium to long term (6-12 years), METS-IR was more accurate in predicting the development of diabetes in non-obese individuals.

CONCLUSIONS

Our study showed that METS-IR was independently associated with the development of future diabetes in a non-diabetic population. METS-IR was a good predictor of diabetes, especially for women and individuals < 45 years old for predicting the future risk of developing diabetes at all times.

Assessing blood sugar measures for predicting new-onset diabetes and cardiovascular disease in community-dwelling adults

PURPOSE

Diabetes mellitus (DM) is a global health concern linked to various complications, including cardiovascular disease (CVD). However, long-term follow-up studies on the risk of DM and CVD using different blood glucose assessment methods in the general Korean population are lacking. This study aimed to assess the predictive abilities of fasting plasma glucose (FPG), 2-h oral glucose tolerance test (OGTT), and glycosylated hemoglobin (HbA1c) for new-onset DM and high CVD risk in a middle-aged and older Korean population.

METHODS

This study used data from the Korean Genome and Epidemiology Study, a population-based prospective cohort. Blood sugar measures (FPG, OGTT, and HbA1c) were examined. The primary endpoint was the development of new-onset DM, and CVD risk was evaluated using the Framingham risk score. The predictive abilities for new-onset DM based on glycemic values were evaluated using Harrell's Concordance index and 95% confidence intervals.

RESULTS

Among the 10,030 participants, data of 6813 participants without DM at baseline were analyzed. The study revealed that OGTT outperformed FPG and HbA1c in predicting new-onset DM. The combination of FPG and HbA1c did not significantly enhance predictions for DM compared with OGTT alone. OGTT also outperformed FPG and HbA1c in predicting high CVD risk, and this difference remained significant even after adjusting for additional confounders.

CONCLUSION

OGTT has superior predictive capabilities in identifying new-onset DM and high CVD risk in the Korean population. This suggests that relying solely on individual blood sugar measures may be insufficient for assessing DM and CVD risks.

Diabetes Risk Factors in People With HIV Receiving Pitavastatin Versus Placebo for Cardiovascular Disease Prevention : A Randomized Trial

BACKGROUND

REPRIEVE (Randomized Trial to Prevent Vascular Events in HIV) led to new guidelines for statin use among people with HIV (PWH) with low to moderate risk for atherosclerotic cardiovascular disease (ASCVD). Little is known about the natural history of diabetes mellitus (DM) or mechanisms contributing to statin effects on DM among this population.

OBJECTIVE

To determine the contribution of known DM risk factors to excess risk for DM with pitavastatin in REPRIEVE.

DESIGN

Phase 3, primary ASCVD prevention trial over a median of 5.6 years of follow-up. (ClinicalTrials.gov: NCT02344290).

SETTING

Global, multicenter trial.

PARTICIPANTS

7731 PWH aged 40 to 75 years with low to moderate ASCVD risk (by the pooled cohort equations from the American College of Cardiology and American Heart Association) without DM at study entry.

INTERVENTION

Random 1:1 assignment to pitavastatin, 4 mg daily, or placebo.

MEASUREMENTS

New-onset DM was determined at each visit by clinical diagnosis requiring initiation of medication treatment for DM. The incidence of new-onset DM was assessed in relation to predefined demographic and metabolic risk factors, stratified by treatment group. Treatment effects of pitavastatin on progression to new DM in key subgroups were determined.

RESULTS

Participants with at least 3 DM risk factors (vs. no risk factors) had increased risk for DM in each treatment group (incidence rate, 3.24 per 100 person-years [PY] vs. 0.34 per 100 PY [pitavastatin] and 2.66 per 100 PY vs. 0.27 per 100 PY [placebo]). The incidence of DM was highest in South Asia. In adjusted analyses, high body mass index, prediabetes, and metabolic syndrome components were strongly associated with new-onset DM (all P < 0.005).

LIMITATION

Pitavastatin was the only statin assessed; DM was assessed clinically.

CONCLUSION

Metabolic risk factors, including prediabetes and obesity, contributed to new-onset DM in statin- and placebo-treated participants. A clinically significant effect of pitavastatin on DM was seen primarily among those with multiple risk factors for DM at entry. Strategies targeting key metabolic risk factors, like obesity and prediabetes, may help protect against DM among PWH.

PRIMARY FUNDING SOURCE

National Heart, Lung, and Blood Institute of the National Institutes of Health.

Remnant cholesterol, but not other traditional lipids or lipid ratios, is independently and positively related to future diabetes risk in Chinese general population: A 3 year cohort study

AIMS

Very few cohort studies are available about the relation between remnant cholesterol (RC) and diabetes. Based on a prospective cohort survey, this research aimed at investigating if high RC was related to a future diabetes risk in the Chinese population, as well as to compare the association between RC, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), triglycerides (TG), TG/HDL-C, LDL-C/HDL-C, TC/HDL-C, and non-high-density lipoprotein cholesterol (non-HDL-C), and future diabetes risk.

MATERIALS AND METHODS

6,700 baseline normoglycemic participants of the REACTION study's Beijing center were recruited in 2011-2012 and followed up in 2015. Multivariate Cox regression analyses were performed to explore the relationship of RC, HDL-C, LDL-C, TC, TG, LDL-C/HDL-C, TG/HDL-C, TC/HDL-C, and non-HDL-C and a future diabetes risk.

RESULTS

After potential confounders were adjusted for, only RC (HR 1.134, 95% CI 1.016-1.267, P = 0.025) was positively related to a future diabetes risk, and only HDL-C (HR 0.728, 95% CI 0.578-0.918, P = 0.007) was negatively related to a future diabetes risk. The rest of the lipid parameters were not related to a future risk of diabetes. Sensitivity and stratification analyses revealed that the relation between RC and future diabetes risk was stable. RC and future diabetes risk were still positively correlated even when the HDL-C was ≥1.04 mmol/L (HR 1.167, 95% CI 1.050-1.297, P = 0.004).

CONCLUSIONS

It was RC, but not other lipid parameters, that was independently and positively related to a future risk of diabetes among the Chinese general population. Moreover, the relationship between RC and diabetes risk was stable, even with appropriate levels of HDL-C.

Role of dietary interventions on microvascular health in South-Asian Surinamese people with type 2 diabetes in the Netherlands: A randomized controlled trial

BACKGROUND/OBJECTIVES

We investigated whether dietary interventions, i.e. a fasting mimicking diet (FMD, Prolon®) or glycocalyx mimetic supplementation (EndocalyxTM) could stabilize microvascular function in Surinamese South-Asian patients with type 2 diabetes (SA-T2DM) in the Netherlands, a patient population more prone to develop vascular complications.

SUBJECTS/METHODS

A randomized, placebo controlled, 3-arm intervention study was conducted in 56 SA-T2DM patients between 18 and 75 years old, for 3 consecutive months, with one additional follow up measurement 3 months after the last intervention. Sublingual microcirculation was assessed with SDF-imaging coupled to the GlycoCheckTM software, detecting red blood cell velocity, capillary density, static and dynamic perfused boundary region (PBR), and the overall microvascular health score (MVHS). Linear mixed models and interaction analysis were used to investigate the effects the interventions had on microvascular function.

RESULTS

Despite a temporal improvement in BMI and HbA1c after FMD the major treatment effect on microvascular health was worsening for RBC-velocity independent PBRdynamic, especially at follow-up. Glycocalyx supplementation, however, reduced urinary MCP-1 presence and improved both PBRdynamic and MVHSdynamic, which persisted at follow-up.

CONCLUSIONS

We showed that despite temporal beneficial changes in BMI and HbA1c after FMD, this intervention is not able to preserve microvascular endothelial health in Dutch South-Asian patients with T2DM. In contrast, glycocalyx mimetics preserves the microvascular endothelial health and reduces the inflammatory cytokine MCP-1.

CLINICAL STUDY REGISTRATION

NCT03889236.

International Diabetes Federation Position Statement on the 1-hour post-load plasma glucose for the diagnosis of intermediate hyperglycaemia and type 2 diabetes

Many individuals with intermediate hyperglycaemia (IH), including impaired fasting glycaemia (IFG) and impaired glucose tolerance (IGT), as presently defined, will progress to type 2 diabetes (T2D). There is confirmatory evidence that T2D can be prevented by lifestyle modification and/or medications, in people with IGT diagnosed by 2-h plasma glucose (PG) during a 75-gram oral glucose tolerance test (OGTT). Over the last 40 years, a wealth of epidemiological data has confirmed the superior value of 1-h plasma glucose (PG) over fasting PG (FPG), glycated haemoglobin (HbA1c) and 2-h PG in populations of different ethnicity, sex and age in predicting diabetes and associated complications including death. Given the relentlessly rising prevalence of diabetes, a more sensitive, practical method is needed to detect people with IH and T2D for early prevention or treatment in the often lengthy trajectory to T2D and its complications. The International Diabetes Federation (IDF) Position Statement reviews findings that the 1-h post-load PG ≥ 155 mg/dL (8.6 mmol/L) in people with normal glucose tolerance (NGT) during an OGTT is highly predictive for detecting progression to T2D, micro- and macrovascular complications, obstructive sleep apnoea, cystic fibrosis-related diabetes mellitus, metabolic dysfunction-associated steatotic liver disease, and mortality in individuals with risk factors. The 1-h PG of 209 mg/dL (11.6 mmol/L) is also diagnostic of T2D. Importantly, the 1-h PG cut points for diagnosing IH and T2D can be detected earlier than the recommended 2-h PG thresholds. Taken together, the 1-h PG provides an opportunity to avoid misclassification of glycaemic status if FPG or HbA1c alone are used. The 1-h PG also allows early detection of high-risk people for intervention to prevent progression to T2D which will benefit the sizeable and growing population of individuals at increased risk of T2D. Using a 1-h OGTT, subsequent to screening with a non-laboratory diabetes risk tool, and intervening early will favourably impact the global diabetes epidemic. Health services should consider developing a policy for screening for IH based on local human and technical resources. People with a 1-h PG ≥ 155 mg/dL (8.6 mmol/L) are considered to have IH and should be prescribed lifestyle intervention and referred to a diabetes prevention program. People with a 1-h PG ≥ 209 mg/dL (11.6 mmol/L) are considered to have T2D and should have a repeat test to confirm the diagnosis of T2D and then referred for further evaluation and treatment. The substantive data presented in the Position Statement provides strong evidence for redefining current diagnostic criteria for IH and T2D by adding the 1-h PG.

Diabetes in South Asians: Uncovering Novel Risk Factors With Longitudinal Epidemiologic Data: Kelly West Award Lecture 2023

South Asian populations have a higher prevalence and earlier age of onset of type 2 diabetes and atherosclerotic cardiovascular diseases than other race and ethnic groups. To better understand the pathophysiology and multilevel risk factors for diabetes and cardiovascular disease, we established the Mediators of Atherosclerosis in South Asians Living in America (MASALA) study in 2010. The original MASALA study cohort (n = 1,164) included 83% Asian Indian immigrants, with an ongoing expansion of the study to include individuals of Bangladeshi and Pakistani origin. We have found that South Asian Americans in the MASALA study had higher type 2 diabetes prevalence, lower insulin secretion, more insulin resistance, and an adverse body composition with higher liver and intermuscular fat and lower lean muscle mass compared with four other U.S. race and ethnic groups. MASALA study participants with diabetes were more likely to have the severe hyperglycemia subtype, characterized by β-cell dysfunction and lower body weight, and this subtype was associated with a higher incidence of subclinical atherosclerosis. We have found several modifiable factors for cardiometabolic disease among South Asians including diet and physical activity that can be influenced using specific social network members and with cultural adaptations to the U.S. context. Longitudinal data with repeat cardiometabolic measures that are supplemented with qualitative and mixed-method approaches enable a deeper understanding of disease risk and resilience factors. Studying and contrasting Asian American subgroups can uncover the causes for cardiometabolic disease heterogeneity and reveal novel methods for prevention and treatment.

Differential effect of interventions in patients with prediabetes stratified by a machine learning-based diabetes progression prediction model

AIM

To investigate whether stratifying participants with prediabetes according to their diabetes progression risks (PR) could affect their responses to interventions.

METHODS

We developed a machine learning-based model to predict the 1-year diabetes PR (ML-PR) with the least predictors. The model was developed and internally validated in participants with prediabetes in the Pinggu Study (a prospective population-based survey in suburban Beijing; n = 622). Patients from the Beijing Prediabetes Reversion Program cohort (a multicentre randomized control trial to evaluate the efficacy of lifestyle and/or pioglitazone on prediabetes reversion; n = 1936) were stratified to low-, medium- and high-risk groups using ML-PR. Different effect of four interventions within subgroups on prediabetes reversal and diabetes progression was assessed.

RESULTS

Using least predictors including fasting plasma glucose, 2-h postprandial glucose after 75 g glucose administration, glycated haemoglobin, high-density lipoprotein cholesterol and triglycerides, and the ML algorithm XGBoost, ML-PR successfully predicted the 1-year progression of participants with prediabetes in the Pinggu study [internal area under the curve of the receiver operating characteristic curve 0.80 (0.72-0.89)] and Beijing Prediabetes Reversion Program [external area under the curve of the receiver operating characteristic curve 0.80 (0.74-0.86)]. In the high-risk group pioglitazone plus intensive lifestyle therapy significantly reduced diabetes progression by about 50% at year l and the end of the trial in the high-risk group compared with conventional lifestyle therapy with placebo. In the medium- or low-risk group, intensified lifestyle therapy, pioglitazone or their combination did not show any benefit on diabetes progression and prediabetes reversion.

CONCLUSIONS

This study suggests personalized treatment for prediabetes according to their PR is necessary. ML-PR model with simple clinical variables may facilitate personal treatment strategies in participants with prediabetes.

A nomogram model for predicting 5-year risk of prediabetes in Chinese adults

Early identification is crucial to effectively intervene in individuals at high risk of developing pre-diabetes. This study aimed to create a personalized nomogram to determine the 5-year risk of pre-diabetes among Chinese adults. This retrospective cohort study included 184,188 participants without prediabetes at baseline. Training cohorts (92,177) and validation cohorts (92,011) were randomly assigned (92,011). We compared five prediction models on the training cohorts: full cox proportional hazards model, stepwise cox proportional hazards model, multivariable fractional polynomials (MFP), machine learning, and least absolute shrinkage and selection operator (LASSO) models. At the same time, we validated the above five models on the validation set. And we chose the LASSO model as the final risk prediction model for prediabetes. We presented the model with a nomogram. The model's performance was evaluated in terms of its discriminative ability, clinical utility, and calibration using the area under the receiver operating characteristic (ROC) curve, decision curve analysis, and calibration analysis on the training cohorts. Simultaneously, we also evaluated the above nomogram on the validation set. The 5-year incidence of prediabetes was 10.70% and 10.69% in the training and validation cohort, respectively. We developed a simple nomogram that predicted the risk of prediabetes by using the parameters of age, body mass index (BMI), fasting plasma glucose (FBG), triglycerides (TG), systolic blood pressure (SBP), and serum creatinine (Scr). The nomogram's area under the receiver operating characteristic curve (AUC) was 0.7341 (95% CI 0.7290-0.7392) for the training cohort and 0.7336 (95% CI 0.7285-0.7387) for the validation cohort, indicating good discriminative ability. The calibration curve showed a perfect fit between the predicted prediabetes risk and the observed prediabetes risk. An analysis of the decision curve presented the clinical application of the nomogram, with alternative threshold probability spectrums being presented as well. A personalized prediabetes prediction nomogram was developed and validated among Chinese adults, identifying high-risk individuals. Doctors and others can easily and efficiently use our prediabetes prediction model when assessing prediabetes risk.

Changes in the preoperative ocular surface flora with an increase in patient age: A surveillance analysis of bacterial diversity and resistance to fluoroquinolone

PURPOSE

This study analyzed the relationship between patient age and the prevalence and fluoroquinolone susceptibility of gram-positive cocci from the ocular surface flora before ophthalmic surgery.

METHODS

This surveillance study included scraped samples from the conjunctival sac of 8923 eyes of 5490 patients (70.0 ± 13.7 years) without ocular infection before ophthalmologic surgery between August 2018 and December 2020. A review of microbiological records regarding patient age was used to determine the number of isolates and gram-positive species obtained, as well as their fluoroquinolone susceptibility. Fluoroquinolone susceptibility was determined using the Clinical and Laboratory Standards Institute protocols of broth microdilution. Statistical analysis was performed using a generalized additive model and a log-linear model.

RESULTS

In total, 9,894 bacterial isolates obtained from scraped samples from the patients were analyzed. The detected species were Staphylococcus epidermidis (31.0%), Staphylococcus aureus (6.1%), Staphylococcus lugdunensis (3.9%), Enterococcus faecalis (5.8%), Corynebacterium species (31.7%), and Cutibacterium acnes (7.5%) and others. The number of species isolated from the ocular surface was increased at the rate of 1.018 per 10 years of age (p < 0.0001). S. epidermidis, S. lugdunensis, E. faecalis, and Corynebacterium species were isolated more often with an increase in patient age. The levofloxacin resistance ratio of methicillin-sensitive S. epidermidis and Corynebacterium species increased at the rate of 1.204 and 1.087 respectively with a 10-year increase in age (both p < 0.0001).

CONCLUSION

Gram-positive bacteria in the ocular surface flora (OSF) exhibited gradual changes in diversity and fluoroquinolone resistance with an increase in patient age. It is important to monitor the OSF of the patients before ophthalmologic surgery to prevent refractory ocular postoperative infection.

Cardiovascular complications of diabetes: role of non-coding RNAs in the crosstalk between immune and cardiovascular systems

Diabetes mellitus, a group of metabolic disorders characterized by high levels of blood glucose caused by insulin defect or impairment, is a major risk factor for cardiovascular diseases and related mortality. Patients with diabetes experience a state of chronic or intermittent hyperglycemia resulting in damage to the vasculature, leading to micro- and macro-vascular diseases. These conditions are associated with low-grade chronic inflammation and accelerated atherosclerosis. Several classes of leukocytes have been implicated in diabetic cardiovascular impairment. Although the molecular pathways through which diabetes elicits an inflammatory response have attracted significant attention, how they contribute to altering cardiovascular homeostasis is still incompletely understood. In this respect, non-coding RNAs (ncRNAs) are a still largely under-investigated class of transcripts that may play a fundamental role. This review article gathers the current knowledge on the function of ncRNAs in the crosstalk between immune and cardiovascular cells in the context of diabetic complications, highlighting the influence of biological sex in such mechanisms and exploring the potential role of ncRNAs as biomarkers and targets for treatments. The discussion closes by offering an overview of the ncRNAs involved in the increased cardiovascular risk suffered by patients with diabetes facing Sars-CoV-2 infection.

Assessing temporal differences in the predictive power of baseline TyG-related parameters for future diabetes: an analysis using time-dependent receiver operating characteristics

BACKGROUND

It is known that measuring the triglyceride glucose (TyG) index and TyG-related parameters [triglyceride glucose-body mass index (TyG-BMI), triglyceride glucose-waist circumference (TyG-WC), and triglyceride glucose-waist to height ratio (TyG-WHtR)] can predict diabetes; this study aimed to compare the predictive value of the baseline TyG index and TyG-related parameters for the onset of diabetes at different future periods.

METHODS

We conducted a longitudinal cohort study involving 15,464 Japanese people who had undergone health physical examinations. The subject's TyG index and TyG-related parameters were measured at the first physical examination, and diabetes was defined according to the American Diabetes Association criteria. Multivariate Cox regression models and time-dependent receiver operating characteristic (ROC) curves were constructed to examine and compare the risk assessment/predictive value of the TyG index and TyG-related parameters for the onset of diabetes in different future periods.

RESULTS

The mean follow-up period of the current study cohort was 6.13 years, with a maximum of 13 years, and the incidence density of diabetes was 39.88/10,000 person-years. In multivariate Cox regression models with standardized hazard ratios (HRs), we found that both the TyG index and TyG-related parameters were significantly and positively associated with diabetes risk and that the TyG-related parameters were stronger in assessing diabetes risk than the TyG index, with TyG-WC being the best parameter (HR per SD increase: 1.70, 95% CI 1.46, 1.97). In addition, TyG-WC also showed the highest predictive accuracy in time-dependent ROC analysis for diabetes occurring in the short-term (2-6 years), while TyG-WHtR had the highest predictive accuracy and the most stable predictive threshold for predicting the onset of diabetes in the medium- to long-term (6-12 years).

CONCLUSIONS

These results suggest that the TyG index combined with BMI, WC, and WHtR can further improve its ability to assess/predict the risk of diabetes in different future periods, where TyG-WC was not only the best parameter for assessing diabetes risk but also the best risk marker for predicting future diabetes in the short-term, while TyG-WHtR may be more suitable for predicting future diabetes in the medium- to long-term.

Lower-than-normal glycemic levels to achieve optimal reduction of diabetes risk among individuals with prediabetes: A prospective cohort study

AIMS/HYPOTHESIS

To determine whether lower than currently accepted glycemic levels could lead to optimal risk reduction of incident diabetes among individuals with prediabetes.

METHODS

We enrolled 9903 individuals with prediabetes and 16,902 individuals with normoglycemia from a prospective cohort participating health check-ups between 2006 and 2017. While classifying fasting glucose into <5.0, 5.0-5.5, and 5.6-6.9 mmol/L and postprandial glucose into <6.7, 6.7-7.7, and 7.8-11.0 mmol/L, we grouped fasting/postprandial glucose into five categories (<5.0/<6.7, <5.0/6.7-7.7, 5.0-5.5/<6.7, 5.0-5.5/6.7-7.7 mmol/L, 5.6-6.9/7.8-11.0 mmol/L). The primary outcome was incident diabetes.

RESULTS

In individuals with prediabetes, the presence of a baseline fasting glucose <5.0 mmol/L or a postprandial glucose <6.7 mmol/L led to a greater risk reduction of incident diabetes with hazard ratios of 0.34 (95% confidence interval, 0.27-0.42) and 0.47 (0.41-0.54), respectively, relative to a fasting glucose 5.6-6.9 mmol/L and a postprandial glucose 7.8-11.0 mmol/L. For individuals with prediabetes having fasting/postprandial glucose <5.0/<6.7 mmol/L, the incidence of 6.4 (4.7-8.8) per 1000 person-years corresponded to that of 5.8 (4.2-8.0) per 1000 person-years for individuals with normoglycemia having 5.0-5.5/6.7-7.7 mmol/L.

CONCLUSIONS/INTERPRETATION

Given that lower-than-normal glycemic levels were plausible for optimal risk reduction of diabetes, stringent glycemic management could be beneficial for diabetes prevention among individuals with prediabetes.

Management of diabetic dyslipidemia in Indians: Expert consensus statement from the Lipid Association of India

In 2021 an estimated 74 million individuals had diabetes in India, almost all type 2 diabetes. More than half of patients with diabetes are estimated to be undiagnosed and more 90% have dyslipidemia that is associated with accelerated development of atherosclerotic cardiovascular disease (ASCVD). Patients of Indian descent with diabetes have multiple features that distinguish them from patients with diabetes in Western populations. These include characteristics such as earlier age of onset, higher frequency of features of the metabolic syndrome, more prevalent risk factors for ASCVD, and more aggressive course of ASCVD complications. In light of the unique features of diabetes and diabetic dyslipidemia in individuals of Indian descent, the Lipid Association of India developed this expert consensus statement to provide guidance for management of diabetic dyslipidemia in this very high risk population. The recommendations contained herein are the outgrowth of a series of 165 webinars conducted by the Lipid Association of India across the country from May 2020 to July 2021, involving 155 experts in endocrinology and cardiology and an additional 2880 physicians.

An examination of causal associations and shared risk factors for diabetes and cardiovascular diseases in the East Asian population: A Mendelian randomization study

BACKGROUND

One of the major contributors to disability and mortality among diabetics is cardiovascular disease (CVD), with coronary artery disease (CAD) as the most prevalent type. However, previous studies have provided controversial evidence linking diabetes to other types of CVDs, such as atrial fibrillation (AF). In addition, the risk factors that predispose people to the risk of diabetes and its complications differ across ethnicities, but the disease risk profiles in the East Asian population have been less investigated.

METHODS

The causal association between type 2 diabetes (T2D) and two types of CVDs (i.e., AF and CAD) in the East Asian population was first studied using Mendelian randomization (MR) analyses. Next, we examined the causal effect of 49 traits on T2D and CAD to identify their separate and shared risk factors in East Asians. A causal mediation analysis was performed to examine the role of T2D in mediating the relationship between the identified shared risk factors and CAD.

RESULTS

T2D was causally associated with CAD, but not AF, in East Asians. A screening of the risk factors indicated that six and 11 traits were causally associated with T2D and CAD, respectively, with suggestive levels of evidence. Alkaline phosphatase (ALP) was the only trait associated with both T2D and CAD, as revealed by the univariable MR analyses. Moreover, the causal association between ALP and CAD no longer existed after adjusting T2D as a covariable in the causal mediation study.

CONCLUSION

Our study highlights the risk profiles in the East Asian population, which is important in formulating targeted therapies for T2D and CVDs in East Asians.

Unraveling female reproductive senescence to enhance healthy longevity

In a society where women often want successful careers and equal opportunities to men, the early nature of ovarian aging often forces women to make difficult life choices between career and family development. Fertility in women begins to decline after the age of 37 years and it is rare for pregnancies to occur after 45. This reproductive decline in women is inevitable and culminates in menopause, which is a major driver of age-related diseases. In a world where biomedical advances are leading to modifiable biological outcomes, it is time to focus on mitigating female reproductive senescence to maintain fertility and preserve age-related hormonal functions, with the goal of providing increased life choices and enhancing healthspan. To date, reproductive longevity research remains an understudied field. More needs to be done to unravel the biology of the ovarian follicles, which are the functional units of reproductive lifespan and are comprised of cell types including the oocyte (female gamete) and a group of specialized supporting somatic cells. Biological attempts to maintain the quality and quantity of follicles in animal models through manipulating pathways involved in aging can potentially prolong female reproductive lifespan and healthspan. Here, we summarize the molecular events driving ovarian aging and menopause and the interventional strategies to offset these events. Developing solutions to female reproductive senescence will open doors to discover ways to enhance true healthy longevity for both men and women.

Sex-differences in insulin sensitivity and insulin secretion in subjects with impaired fasting glucose and impaired glucose tolerance

AIMS

To assess sex-related differences in whole-body insulin sensitivity and insulin secretion in a group of Caucasian subjects with varying degrees of glucose tolerance.

METHODS

Sex-related differences in insulin sensitivity using the hyperinsulinemic-euglycemic clamp technique and insulin secretion using validated indexes obtained during an oral glucose tolerance test were examined among 570 non-diabetic offspring individuals having only one parent with type 2 diabetes. Participants were classified as having with NGT, isolated impaired fasting glucose (IFG), isolated impaired glucose tolerance (IGT) and combined IFG/IGT.

RESULTS

Isolated IFG, isolated IGT, and combined IFG/IGT women exhibited greater relative differences in BMI, waist circumference, and insulin-stimulated glucose disposal than their male counterparts. Formal tests for glucose tolerance status × sex interaction were statistically significant for BMI (P = 0.05) waist circumference (P = 0.04), and insulin-stimulated glucose disposal (P = 0.01) suggesting a sex-specific association. By contrast, tests for glucose tolerance status × sex interaction regarding both insulinogenic and disposition indexes were not significant.

CONCLUSIONS

This study suggests that deterioration of glucose homeostasis in women is associated with a greater fat accumulation and worsening in insulin sensitivity as compared with men.

Younger Age and Albuminuria are Associated with Proliferative Diabetic Retinopathy and Diabetic Macular Edema in the South Indian GeNetics of DiAbeTic Retinopathy (SIGNATR) Study

Purpose: The purpose of the South Indian GeNetics of DiAbeTic Retinopathy (SIGNATR) Study is to identify non-genetic and genetic risk factors associated with diabetic retinopathy (DR). This report examines the non-genetic risk factors for DR in South Indian patients.Methods: Participants with South Indian ancestry and type 2 diabetes (T2D) were included from two sources: the Sankara Nethralaya Diabetic Retinopathy and Molecular Genetics Study (SN-DREAMS) and prospective recruitment at Sankara Nethralaya affiliates. Fundus photography and optical coherence tomography (OCT) were obtained on participants. Fundus images were graded for DR severity and OCTs were graded for center-involved diabetic macular edema (ciDME). Multivariate analyses were performed using stepwise logistic regression to assess effects of the demographic and clinical factors on proliferative DR (PDR) and DME.Results: Among the 2941 participants with DR grading, participants with PDR were more likely to be younger [odds ratio (OR)=0.95], men (OR = 1.83), have a longer duration of diabetes (OR = 1.10), have a higher hemoglobin A1c (OR = 1.12), have albuminuria (OR = 5.83), have hypertension (OR = 1.69), have a higher HDL (OR = 1.02) and a lower total cholesterol (OR = 0.99) (all p < 0.05). Among the 483 participants with gradable OCT scans, participants who had ciDME were more likely to be younger (OR = 0.97), men (OR = 2.80), have a longer duration of diabetes (OR = 1.06), have lower triglycerides (OR = 0.99), and have albuminuria (OR = 3.12) (all p < 0.05).Conclusions: Younger age, male sex, longer duration of diabetes, higher HbA1c, and presence of albuminuria were identified as risk factors for PDR and DME in a South Indian population with T2D.

Experiences of barriers to self-monitoring and medication-management among Indian patients with type 2 diabetes, their primary family-members and physicians

OBJECTIVES

This study explored the subjective accounts of the main barriers to self-monitoring of blood-glucose (SMBG) and medication-management among Indian patients with type 2 diabetes (T2DM), their primary family-members (PFMs) and physicians.

METHODS

Using convenience sampling, patients with T2DM, their PFMs, and physicians, residing in a South Indian capital city, were recruited for semi-structured, audio-recorded interviews. Thematic analysis was used to analyze the data.

RESULTS

Fifty patients (female = 14; mean age = 42.5 years) and their PFMs (female = 38; mean age = 39 years), and 25 physicians (female = 4; mean age = 49.8 years) were recruited. Three superordinate themes were identified: (i) complex medication-regimen: confusion, forgetting and reduced motivation, (ii) family recommendations of alternative therapies due to the social pressures of avoiding stigma, intrusiveness and being misrepresented for injecting insulin, and (iii) an expensive illness: choosing to spend money on only medication.

DISCUSSION

Implications of the findings highlight the need to (i) train physicians in communication and empathy skills, (ii) empower patients to communicate their barriers to physicians through triadic communication models and question-prompt lists, (iii) educate communities on the benefits of insulin for managing T2DM to reduce stigma, and (iv) equip communities with information about health insurance to address the financial toll of T2DM management.

Newly diagnosed diabetes based on an oral glucose tolerance test predicts cardiovascular outcomes in patients with coronary artery disease: An observational study

Diabetes is prevalent in patients with coronary artery disease (CAD). Using the oral glucose tolerance test (OGTT), abnormal glucose regulation can be detected early in CAD patients without known diabetes. In the present study, we assessed the impact of abnormal glucose regulation on the long-term cardiovascular outcomes of patients with established CAD. Patients hospitalized for a scheduled angiography due to angina were enrolled in Taichung Veterans General Hospital. Fasting plasma glucose (FPG) and 2-hour postload glucose (2hPG) were assessed using the OGTT. Hemoglobin A1c (HbA1c) and other biochemical analyses were assessed using fasting blood samples. During a median follow-up period of 4.6 years, a composite of all-cause mortality, nonfatal myocardial infarction, and nonfatal stroke was recorded as the primary endpoint. In 682 enrolled patients who completed the follow-up, there were 16 myocardial infarction events, 12 stroke events, and 58 deaths as composite endpoints. According to FPG and 2hPG, patients with newly diagnosed diabetes had a 2-fold higher risk for the composite endpoint than those in the normal glucose group (hazard ratio [HR], 2.011; 95% confidence interval (CI), 1.101-3.673; P = .023); however, prediabetes was not significantly associated with the composite endpoint (HR, 1.452; 95% CI, 0.788-2.675; P = .232). On the other hand, patients with diabetes diagnosed by FPG and HbA1c did not have a significantly higher risk for the composite endpoint than those in the normal glucose group (HR, 1.321; 95% CI, 0.686-2.545; P = .405). A 2hPG ≥7.8 mmol/L was a significant predictor for the composite endpoint (odds ratio, 1.743; 95% CI, 1.060-2.863; P = .028) after adjusting for age, sex, and estimated glomerular filtration rate. Diabetes, but not prediabetes, detected via OGTT is associated with a significantly increased risk for the composite endpoint in patients with established CAD. The 2hPG provided a greater predictive power for the composite endpoint than fasting glucose and HbA1c.

Absence of a sexual dimorphism in postprandial glucose metabolism after administration of a balanced mixed meal in healthy young volunteers

BACKGROUND/OBJECTIVES

A different ability to regulate glucose homeostasis between men and women may contribute to their difference in diabetes prevalence and in its predisposing conditions. Data on this issue are controversial because of heterogeneous protocols and insufficient control of confounders affecting glucose metabolism like age, body composition, and physical activity level. To clarify this issue, we compared among sexes the postprandial glucose metabolism after the administration of a balanced mixed meal normalized to daily energy expenditure.

SUBJECTS/METHODS

Thirty-six healthy young volunteers (18 men and 18 women; age, 23.9 ± 2.8 years; BMI, 21.9 ± 1.7 kg/m²) were recruited for the experiment. After overnight fast, subjects consumed a mixed meal providing 40% of daily energy expenditure (60% carbohydrates, 25% lipids, 15% proteins) estimated multiplying resting energy expenditure, obtained by Harris & Benedict equation, for the corresponding physical activity level. Blood was sampled at 0, 10, 20, 30, 45, 60, 90, 120, and 180 min and serum concentrations of glucose, insulin, and C-peptide were measured.

RESULTS

Fasting serum glucose concentrations were lower in women than in men, while fasting insulin and C-peptide concentrations did not differ between sexes. Linear mixed models did not show any significant effect of sex and sex # time interaction on postprandial serum glucose, insulin, and C-peptide concentrations. The comparison of areas under the curve between the sexes revealed similar glycemic, insulinemic, and C-peptide postprandial responses between men and women.

CONCLUSIONS

Our results do not support the hypothesis of a sexual dimorphism in the regulation of carbohydrate metabolism in young when a mixed meal normalized on individual daily energy expenditure is ingested.

Impact of Risk Factors on Short and Long-Term Maternal and Neonatal Outcomes in Women With Gestational Diabetes Mellitus: A Prospective Longitudinal Cohort Study

AIMS

Universal screening of gestational diabetes mellitus (GDM) in women with no risk factors (RF) for GDM remains controversial. This study identified the impact of the presence of RF on perinatal and postpartum outcomes.

METHODS

This prospective cohort study included 780 women with GDM. GDM RF included previous GDM, first grade family history of type 2 diabetes, high-risk ethnicity and pre-pregnancy overweight/obesity (OW/OB). Outcomes included obstetrical, neonatal and maternal metabolic parameters during pregnancy and up to 1 year postpartum.

RESULTS

Out of 780 patients, 24% had no RF for GDM. Despite this, 40% of them needed medical treatment and they had a high prevalence of glucose intolerance of 21 and 27% at 6-8 weeks and 1-year postpartum, respectively. Despite similar treatment, women with RF had more neonatal and obstetrical complications, but they had especially more frequent adverse metabolic outcomes in the short- and long-term. The most important RF for poor perinatal outcome were previous GDM and pre-pregnancy OW/OB, whereas high-risk ethnicity and pre-pregnancy OW/OB were RF for adverse postpartum metabolic outcomes. Increasing number of RF were associated with worsened perinatal and long-term postpartum outcomes except for pregnancy-induced hypertension, C-section delivery and neonatal hypoglycaemia.

CONCLUSION

Women with no RF had a high prevalence of adverse perinatal and postpartum outcomes, while the presence of RF particularly increased the risk for postpartum adverse metabolic outcomes. This calls for a RF-based long-term follow-up of women with GDM.

Trends in the diabetes incidence and mortality in India from 1990 to 2019: a joinpoint and age-period-cohort analysis

Introduction

Globally, a metabolic disorder like Diabetes is considered as one of the largest global health issues, as it accounts for the majority of the disease burden and happens to be one of the leading causes of mortality as well as reduced life expectancy across the world. As in 2019, India is home to the second-largest number (77 million) of Diabetic adults and the number of people affected has been increasing rapidly over the years. Termed as "the diabetes capital of the world," with every fifth diabetic in the world being an Indian, there is an urgent need to address many critically significant challenges posed by Diabetes in India, like, increasing prevalence among young people in urban areas, less awareness among people, high cost of disease management, limited healthcare facilities, suboptimal diabetes control etc. In Indian context, not enough attempts have been made to observe and understand the long-term pattern of diabetes incidence and mortality. This study aims to provide deep insights into the recent trends of diabetes incidence and mortality in India from 1990 to 2019.

Materials and methods

This is an observational study based on the most recent data from the Global Burden of Disease (GBD) Study 2019. We extracted numbers, age-specific and age-standardized incidence and mortality rates of diabetes (from 1990 to 2019) from the Global Health Data Exchange. The average annual percentage changes in incidence and mortality were analysed by joinpoint regression analysis; the net age, period, and cohort effects on the incidence and mortality were estimated by age-period-cohort analysis.

Results

During the study period, age-standardized incidence and mortality rates of diabetes in India experienced an upsurge in numbers, the incidence rate increased from 199.14 to 317.02, and consequently, mortality increased from 22.30 to 27.35 per 100,000 population. The joinpoint regression analysis showed that the age-standardized incidence significantly rose by 1.63 % (95 % CI: 1.57 %, 1.69 %) in Indian males and 1.56 % in Indian females (95 % CI: 1.49 %, 1.63 %) from 1990 to 2019. On the other hand, the age-standardized mortality rates rose by 0.77 % (95 % CI: 0.24 %, 1.31 %) in Indian males and 0.57 % (95 % CI: -0.54 %, 1.70 %) in Indian females. For age-specific rates, incidence increased in most age groups, with exception of age groups 5-9, 70-74, 75-79 and 80-84 in male, and age groups 5-9, 75-79 and 80-84 in female. Mortality in male saw a decreasing trend till age group 20-24, whereas in female, the rate decreased till age group 35-39. The age effect on incidence showed no obvious changes with advancing age, but the mortality significantly increased with advancing age; period effect showed that both incidence and mortality increased with advancing time period; cohort effect on diabetes incidence and mortality decreased from earlier birth cohorts to more recent birth cohorts, while incidence showed no material changes from 1975 to 1979 to 2000-2004 birth cohort.

Conclusions

Mortality of diabetes decreased in younger age groups but increased in older age groups; however, Incidence increased in most age groups for both male and female. The net age or period effect showed an unfavourable trend while the net cohort effect presented a favourable trend. Aging was likely to drive a continued increase in the mortality of diabetes. Timely population-level interventions aiming for health education, lifestyle modification with special emphasis on the promotion of physical activity and healthy diet should be conducted, especially for male and earlier birth cohorts at high risk of diabetes.

The Impact of Diabetes on Productivity in India

OBJECTIVE

Diabetes increases the risk of premature mortality and considerably impacts on work productivity. We sought to examine the impact of diabetes in India, in terms of excess premature mortality, years of life lost (YLL), productivity-adjusted life years (PALYs) lost, and its associated economic impact.

RESEARCH DESIGN AND METHODS

A life table model was constructed to examine the productivity of the Indian working-age population currently aged 20-59 years with diabetes, followed until death or retirement age (60 years). The same cohort was resimulated, hypothetically assuming that they did not have diabetes. The total difference between the two cohorts, in terms of excess deaths, YLL and PALYs lost reflected the impact of diabetes. Data regarding the prevalence of diabetes, mortality, labor force dropouts, and productivity loss attributable to diabetes were derived from published sources.

RESULTS

In 2017, an estimated 54.4 million (7.6%) people of working-age in India had diabetes. With simulated follow-up until death or retirement age, diabetes was predicted to cause 8.5 million excess deaths (62.7% of all deaths), 42.7 million YLL (7.4% of total estimated years of life lived), and 89.0 million PALYs lost (23.3% of total estimated PALYs), equating to an estimated Indian rupee 176.6 trillion (U.S. dollars 2.6 trillion; purchasing power parity 9.8 trillion) in lost gross domestic product.

CONCLUSIONS

Our study demonstrates the impact of diabetes on productivity loss and highlights the importance of health strategies aimed at the prevention of diabetes.

22-year trends in dysglycemia and body mass index: A population-based cohort study in Savitaipale, Finland

AIMS

We describe a 22-year prospective observational population-based study that determined the prevalence and incidence of type 2 diabetes (T2D) and intermediate hyperglycaemia (IH), obesity, hypertension, and disorders of lipid metabolism in a middle-age population in the Finnish municipality of Savitaipale.

METHODS

1151 people participated in the baseline survey in 1996-1999, following two follow-up examinations, in 2007-2008 and 2018-2019. Follow-up studies comprised clinical measurements, 2-h oral glucose tolerance test and other biochemistry, questionnaires, and registry data.

RESULTS

The prevalence of T2D quadrupled to 27% and the proportion of normoglycemic people decreased from 73% to 44% while IH increased only slightly during the 22-year follow-up. A large proportion of people who died between the surveys were diabetic. The mean body mass index (BMI) did not, whereas mean waist circumference increased significantly, by 5-6 cm (P = 0.001) during the 22 years. Systolic blood pressure increased by 13-15 mmHg from baseline (P = 0.0001) but diastolic blood pressure did not. The mean plasma levels of total and LDL-cholesterol decreased 10.8% and 8.9% in women (P = 0.001), 21.5% and 22.2% in men (P = 0.001), respectively, while HDL-cholesterol and triglycerides remained stable. The proportion of those achieving targets in the treatment of dyslipidaemia increased significantly (P < 0.001).

CONCLUSIONS

In this 22-year prospective follow-up study of in middle-aged Europeans with high participation rates, the progression of dysglycaemia to overt diabetes with aging was rapid, even without a significant change in BMI.

Is Colectomy Associated with the Risk of Type 2 Diabetes in Patients without Colorectal Cancer? A Population-Based Cohort Study

Type 2 diabetes might be influenced by colonic disease; however, the association between colonic resection and type 2 diabetes has rarely been discussed. This population-based cohort study explored the association between colectomy and type 2 diabetes in patients without colorectal cancer. A total of 642 patients who underwent colectomy for noncancerous diseases at any time between 2000 and 2012 in the National Health Insurance Research Database of Taiwan were enrolled. The enrolled patients were matched with 2568 patients without colectomy at a 1:4 ratio using a propensity score that covered age, sex, and comorbidities. The risk of type 2 diabetes was assessed using a Cox proportional hazards model. The mean (standard deviation) follow-up durations in colectomy cases and non-colectomy controls were 4.9 (4.0) and 5.6 (3.6) years, respectively; 65 (10.1%) colectomy cases and 342 (15.5%) non-colectomy controls developed type 2 diabetes. After adjustment, colectomy cases still exhibited a decreased risk of type 2 diabetes (adjusted HR = 0.80, 95% CI: 0.61–1.04). A stratified analysis for colectomy type indicated that patients who underwent right or transverse colectomy had a significantly lower risk of developing type 2 diabetes (adjusted HR = 0.57, 95% CI: 0.34–0.98). In the present study, colectomy tended to be at a reduced risk of type 2 diabetes in patients without colorectal cancer, and right or transverse colectomies were especially associated with a significantly reduced risk of type 2 diabetes.

A Narrative Review of Human Clinical Trials on the Impact of Phenolic-Rich Plant Extracts on Prediabetes and Its Subgroups

Phenolic-rich plant extracts have been demonstrated to improve glycemic control in individuals with prediabetes. However, there is increasing evidence that people with prediabetes are not a homogeneous group but exhibit different glycemic profiles leading to the existence of prediabetes subgroups. Prediabetes subgroups have been identified as: isolated impaired fasting glucose (IFG), isolated impaired glucose tolerance (IGT), and combined impaired fasting glucose and glucose intolerance (IFG/IGT). The present review investigates human clinical trials examining the hypoglycemic potential of phenolic-rich plant extracts in prediabetes and prediabetes subgroups. Artemisia princeps Pampanini, soy (Glycine max (L.) Merrill) leaf and Citrus junos Tanaka peel have been demonstrated to improve fasting glycemia and thus may be more useful for individuals with IFG with increasing hepatic insulin resistance. In contrast, white mulberry (Morus alba Linn.) leaf, persimmon (Diospyros kaki) leaf and Acacia. Mearnsii bark were shown to improve postprandial glycemia and hence may be preferably beneficial for individuals with IGT with increasing muscle insulin resistance. Elaeis guineensis leaf was observed to improve both fasting and postprandial glycemic measures depending on the dose. Current evidence remains scarce regarding the impact of the plant extracts on glycemic control in prediabetes subgroups and therefore warrants further study.

Biomarkers of geroprotection and cardiovascular health: An overview of omics studies and established clinical biomarkers in the context of diet

The slowdown, inhibition, or reversal of age-related decline (as a composite of disease, dysfunction, and, ultimately, death) by diet or natural compounds can be defined as dietary geroprotection. While there is no single reliable biomarker to judge the effects of dietary geroprotection, biomarker signatures based on omics (epigenetics, gene expression, microbiome composition) are promising candidates. Recently, omic biomarkers started to supplement established clinical ones such as lipid profiles and inflammatory cytokines. In this review, we focus on human data. We first summarize the current take on genetic biomarkers based on epidemiological studies. However, most of the remaining biomarkers that we describe, whether omics-based or clinical, are related to intervention studies. Then, because of their promising potential in the context of dietary geroprotection, we focus on the effects of berry-based interventions, which up to now have been mostly described employing clinical markers. We provide an aggregation and tabulation of all the recent systematic reviews and meta-analyses that we could find related to this topic. Finally, we present evidence for the importance of the "nutribiography," that is, the influence that an individual's history of diet and natural compound consumption can have on the effects of dietary geroprotection.

Definition and Classification of Diabetes and Prediabetes and Emerging Data on Phenotypes

Diabetes diagnosis has important implications for individuals. Diagnostic criteria for fasting and 2-hour plasma glucose and HbA1c are universally agreed. Intermediate hyperglycemia/prediabetes is a risk factor for diabetes and cardiovascular disease. Because risk is a continuum, determining cut-point is problematic and reflected in significant differences in recommended fasting glucose and HbA1c criteria. Many types of diabetes are recognized. Diabetes classification systems are limited by a lack of understanding of etiopathogenetic pathways leading to diminished β-cell function. The World Health Organization classification system is designed to assist clinical care decisions. Newly recognized phenotypic clusters of diabetes might inform future classification systems.

Heritability Estimation and Environmental Risk Assessment for Type 2 Diabetes Mellitus in a Rural Region in Henan, China: Family-Based and Case-Control Studies

Objective: The prevalence of type 2 diabetes mellitus (T2DM) varies greatly in different regions and populations. This study aims to assess the heritability and environmental risk factors of T2DM among rural Chinese adults.

Methods: Thousand five hundred thirty three participants from 499 extended families, which included 24 nuclear families, were recruited in the family-based study to assess the heritable risk of T2DM. Heritability of T2DM was estimated by the Falconer method. Using conditional logistic regression model, couple case-control study involving 127 couples were applied to assess the environmental risk factors of T2DM.

Results: Compared with the Henan Rural Cohort, T2DM was significantly clustered in the nuclear families (OR: 8.389, 95% CI: 5.537–12.711, P < 0.001) and heritability was 0.74. No association between the heredity of T2DM and sex was observed between the extended families and the Henan Rural Cohort. Besides, results from the couple case-control study showed that physical activity (OR: 0.482, 95% CI: 0.261–0.893, P = 0.020) and fat intake (OR: 3.036, 95% CI: 1.070–8.610, P = 0.037) was associated with T2DM, and the proportion of offspring engaged in medium and high physical activity was higher than that of mothers in mother-offspring pairs.

Conclusion: People with a family history of T2DM may have a higher risk of developing T2DM, however, there was no difference in genetic risk between males and females. Adherence to active physical activity and low fat intake can reduce the risk of T2DM.

Quality-of-Life Determinants in People with Diabetes Mellitus in Europe

This study aims to analyze self-perceived health and lifestyles in the European Union Member States Iceland, Norway, and the United Kingdom, examining associations with diabetes prevalence; and to identify the demographic, economic and health variables associated with diabetes in this population. We performed a cross-sectional study of 312,172 people aged 15 years and over (150,656 men and 161,516 women), using data collected from the European Health Interview Survey (EHIS). The EHIS includes questions on the health status and health determinants of the adult population, as well as health care use and accessibility. To estimate the magnitudes of the associations with diabetes prevalence, we fitted multivariate logistic models. The EHIS data revealed a prevalence of diabetes in Europe of 6.5% (n = 17,029). Diabetes was associated with being physically inactive (OR 1.14; 95% CI 1.02–1.28), obese (OR 2.75; 95% CI 2.60–2.90), male (OR 1.46; 95% CI 1.40–1.53) and 65–74 years old (OR 3.47; 95% CI 3.09–3.89); and having long-standing health problems (OR 7.39; 95% CI, 6.85–7.97). These results were consistent in the bivariate and multivariate analyses, with an area under the receiver operating characteristic curve of 0.87 (95% CI 0.87–0.88). In a large European health survey, diabetes was clearly associated with a poorer perceived quality of life, physical inactivity, obesity, and other comorbidities, as well as non-modifiable factors such as older age and male sex.

Association of hypertension and incident diabetes in Chinese adults: a retrospective cohort study using propensity-score matching

BACKGROUND

Reliable quantification of the relationship between hypertension and diabetes risk is limited, especially among Chinese people. We aimed to investigate the association between hypertension and the risk of diabetes in a large cohort of the Chinese population.

METHODS

This was a retrospective propensity score-matched cohort study among 211,809 Chinese adults without diabetes at baseline between 2010 and 2016. The target independent and dependent variable were hypertension at baseline and incident diabetes during follow-up respectively. The propensity score matching using a non-parsimonious multivariable logistic regression was conducted to balance the confounders between 28,711 hypertensive patients and 28,711 non-hypertensive participants. The doubly robust estimation method was used to investigate the association between hypertension and diabetes.

RESULTS

In the propensity-score matching cohort, diabetes risk increased by 11.0% among hypertensive patients (HR = 1.110, 95% confidence interval (CI): 1.031-1.195, P = 0.00539). And diabetes risk dropped to 8.3% among hypertensive subjects after adjusting for the propensity score (HR = 1.083, 95%CI: 1.006-1.166, P = 0.03367). Compared to non-hypertensive participants with low propensity score, the risk of incident diabetes increased by 2.646 times among hypertensive patients with high propensity score (HR = 3.646, 95%CI: 2.635-5.045, P < 0.0001).

CONCLUSION

Hypertension was associated with an 11.0% increase in the risk of developing diabetes in Chinese adults. And the figure dropped to 8.3% after adjusting the propensity score. Additionally, compared to non-hypertensive participants with low propensity scores, the risk of incident diabetes increased by 2.646 times among hypertensive patients with high propensity scores.

Applying latent class analysis to risk stratification of incident diabetes among Chinese adults

OBJECTIVE

To use latent class analysis to identify unobservable subpopulations amongst the heterogeneous population and explore the relationship between subpopulations and incident diabetes among Chinese adults.

METHODS

The retrospective study included 32,312 Chinese adults without diabetes at baseline. Latent class indicators included demographic and clinical variables. The outcome was incident diabetes. The relationship between latent class and outcome was evaluated with Cox proportional hazard regression analysis.

RESULTS

After screening, the two-class latent class model best fits the population. Participants in class 2 are characterized by higher age, body mass index, systolic and diastolic blood pressure, fasting plasma glucose, total cholesterol, triglyceride, low-density lipoprotein cholesterol, serum creatinine, serum urea nitrogen, alanine aminotransferase, and a higher proportion of males, ever/current smokers and drinkers, but lower high-density lipoprotein cholesterol and a lower proportion of family history of diabetes. The risk of diabetes in class 2 was 5.451 times (HR: 6.451, 95%CI: 4.179-9.960, P < 0.00001) and 5.264 times (HR: 6.264, 95%CI: 4.680-8.385, P < 0.00001) higher than that in class 1 during 3-year and 5-year follow-up, respectively.

CONCLUSIONS

We used latent class analysis to identify two distinct subpopulations with differential risk of diabetes during 3-year and 5-year follow-up.

Incidence and pathophysiology of diabetes in South Asian adults living in India and Pakistan compared with US blacks and whites

INTRODUCTION

We compared diabetes incidence in South Asians aged ≥45 years in urban India (Chennai and Delhi) and Pakistan (Karachi), two low-income and middle-income countries undergoing rapid transition, with blacks and whites in the US, a high-income country.

RESEARCH DESIGN AND METHODS

We computed age-specific, sex-specific and body mass index (BMI)-specific diabetes incidence from the prospective Center for Cardiometabolic Risk Reduction in South Asia Study (n=3136) and the Atherosclerosis Risk in Communities Study (blacks, n=3059; whites, n=9924). We assessed factors associated with incident diabetes using Cox proportional hazards regression.

RESULTS

South Asians have lower BMI and waist circumference than blacks and whites (median BMI, kg/m²: 24.9 vs 28.2 vs 26.0; median waist circumference, cm 87.5 vs 96.0 vs 95.0). South Asians were less insulin resistant than blacks and whites (age-BMI-adjusted homeostatic model assessment of insulin resistance, µIU/mL/mmol/L: 2.30 vs 3.45 vs 2.59), and more insulin deficient than blacks but not whites (age-BMI-adjusted homeostasis model assessment of β-cell dysfunction, µIU/mL/mmol/L: 103.7 vs 140.6 vs 103.9). Age-standardized diabetes incidence (cases/1000 person-years (95% CI)) in South Asian men was similar to black men and 1.6 times higher (1.37 to 1.92) than white men (26.0 (22.2 to 29.8) vs 26.2 (22.7 to 29.7) vs 16.1 (14.8 to 17.4)). In South Asian women, incidence was slightly higher than black women and 3 times (2.61 to 3.66) the rate in white women (31.9 (27.5 to 36.2) vs 28.6 (25.7 to 31.6) vs 11.3 (10.2 to 12.3)). In normal weight (BMI <25 kg/m²), diabetes incidence adjusted for age was 2.9 times higher (2.09 to 4.28) in South Asian men, and 5.3 times (3.64 to 7.54) in South Asian women than in white women.

CONCLUSIONS

South Asian adults have lower BMI and are less insulin resistant than US blacks and whites, but have higher diabetes incidence than US whites, especially in subgroups without obesity. Factors other than insulin resistance (ie, insulin secretion) may play an important role in the natural history of diabetes in South Asians.

Prevalence of Type 2 Diabetes among Patients Visiting Nepal Police Hospital in Kathmandu: A Descriptive Cross-sectional Study

Introduction:

The growing prevalence of diabetes mellitus (DM) is a critical threat for global health, including in Nepal, especially in Kathmandu District, where diabetic patients are increasing in hospitals catastrophically. This study tends to assess the prevalence rate of type 2 diabetes among admitted patients visiting a hospital in Kathmandu.

Methods:

An electronic chart review was done to assess the prevalence of type 2 diabetes in Nepal Police hospital, Kathmandu, Nepal. Ethical approval was taken from the Nepal Health Research Council. Considering eligibility criteria, 8631 cases from 4 May 2018 to 31 August 2020 were observed. The calculated sample size was 500. However, all diabetic cases, i.e., 576, were processed and analyzed using Python and later visualized using MS Excel.

Results:

The overall prevalence rate of type 2 diabetes was 6.67%. The prevalence rate was seen higher among males (7.5%). Similarly, a high prevalence rate was seen among 64-73 years, i.e., 15.10%.

Conclusions:

The findings showed a high prevalence rate of type 2 diabetes. Older age groups are at high risk. Urgent public health interventions including lifestyle modification measures are required to reduce the extra burden of type 2 diabetes.

Changes Induced by Mind-Body Intervention Including Epigenetic Marks and Its Effects on Diabetes

Studies have evidenced that epigenetic marks associated with type 2 diabetes (T2D) can be inherited from parents or acquired through fetal and early-life events, as well as through lifelong environments or lifestyles, which can increase the risk of diabetes in adulthood. However, epigenetic modifications are reversible, and can be altered through proper intervention, thus mitigating the risk factors of T2D. Mind-body intervention (MBI) refers to interventions like meditation, yoga, and qigong, which deal with both physical and mental well-being. MBI not only induces psychological changes, such as alleviation of depression, anxiety, and stress, but also physiological changes like parasympathetic activation, lower cortisol secretion, reduced inflammation, and aging rate delay, which are all risk factors for T2D. Notably, MBI has been reported to reduce blood glucose in patients with T2D. Herein, based on recent findings, we review the effects of MBI on diabetes and the mechanisms involved, including epigenetic modifications.

Remnant Cholesterol is an Independent Predictor of New-Onset Diabetes: A Single-Center Cohort Study

PURPOSE

Remnant cholesterol (RC) is the cholesterol of triglyceride-rich lipoproteins, which has a high degree of atherogenic effect. To date, epidemiological evidence supports that higher RC levels lead to a greater risk of adverse cardiovascular events in patients with diabetes, but the nature of the association between RC levels and diabetes risk remains unclear. This study was designed to assess the association of RC with the risk of new-onset diabetes and to investigate whether there is a causal relationship between the two.

PATIENTS AND METHODS

The subjects included 15,464 individuals of the general population who participated in a health examination. Subjects were quartered according to the RC quartile, and the Cox proportional hazard model was used to assess the independent association between RC and new-onset diabetes.

RESULTS

During an average observation period of 6.13 years, 2.41% of the subjects were diagnosed with new-onset diabetes. Kaplan-Meier analysis showed that the 13-year cumulative diabetes rates corresponding to the RC quartile were 8.62%, 2.49%, 12.78%, and 17.91%. Multivariate Cox regression analysis indicated that higher RC levels were independently associated with an increased risk of new-onset diabetes (HR: 2.44, 95% CI: 1.50-3.89). Additionally, according to the results of receiver operating characteristic curve analysis, RC had the largest area under the curve (0.7314) compared to traditional lipid parameters in predicting new-onset diabetes.

CONCLUSION

These results indicated that RC is an important independent predictor of new-onset diabetes in the general population.

Machine Learning for Predicting the 3-Year Risk of Incident Diabetes in Chinese Adults

Purpose: We aimed to establish and validate a risk assessment system that combines demographic and clinical variables to predict the 3-year risk of incident diabetes in Chinese adults. Methods: A 3-year cohort study was performed on 15,928 Chinese adults without diabetes at baseline. All participants were randomly divided into a training set (n = 7,940) and a validation set (n = 7,988). XGBoost method is an effective machine learning technique used to select the most important variables from candidate variables. And we further established a stepwise model based on the predictors chosen by the XGBoost model. The area under the receiver operating characteristic curve (AUC), decision curve and calibration analysis were used to assess discrimination, clinical use and calibration of the model, respectively. The external validation was performed on a cohort of 11,113 Japanese participants. Result: In the training and validation sets, 148 and 145 incident diabetes cases occurred. XGBoost methods selected the 10 most important variables from 15 candidate variables. Fasting plasma glucose (FPG), body mass index (BMI) and age were the top 3 important variables. And we further established a stepwise model and a prediction nomogram. The AUCs of the stepwise model were 0.933 and 0.910 in the training and validation sets, respectively. The Hosmer-Lemeshow test showed a perfect fit between the predicted diabetes risk and the observed diabetes risk (p = 0.068 for the training set, p = 0.165 for the validation set). Decision curve analysis presented the clinical use of the stepwise model and there was a wide range of alternative threshold probability spectrum. And there were almost no the interactions between these predictors (most P-values for interaction >0.05). Furthermore, the AUC for the external validation set was 0.830, and the Hosmer-Lemeshow test for the external validation set showed no statistically significant difference between the predicted diabetes risk and observed diabetes risk (P = 0.824). Conclusion: We established and validated a risk assessment system for characterizing the 3-year risk of incident diabetes.

A prediction nomogram for the 3-year risk of incident diabetes among Chinese adults

Identifying individuals at high risk for incident diabetes could help achieve targeted delivery of interventional programs. We aimed to develop a personalized diabetes prediction nomogram for the 3-year risk of diabetes among Chinese adults. This retrospective cohort study was among 32,312 participants without diabetes at baseline. All participants were randomly stratified into training cohort (n = 16,219) and validation cohort (n = 16,093). The least absolute shrinkage and selection operator model was used to construct a nomogram and draw a formula for diabetes probability. 500 bootstraps performed the receiver operating characteristic (ROC) curve and decision curve analysis resamples to assess the nomogram's determination and clinical use, respectively. 155 and 141 participants developed diabetes in the training and validation cohort, respectively. The area under curve (AUC) of the nomogram was 0.9125 (95% CI, 0.8887-0.9364) and 0.9030 (95% CI, 0.8747-0.9313) for the training and validation cohort, respectively. We used 12,545 Japanese participants for external validation, its AUC was 0.8488 (95% CI, 0.8126-0.8850). The internal and external validation showed our nomogram had excellent prediction performance. In conclusion, we developed and validated a personalized prediction nomogram for 3-year risk of incident diabetes among Chinese adults, identifying individuals at high risk of developing diabetes.

Trends in the process and outcome indicators of type 2 diabetes care: a cohort study from Eastern Finland, 2012-2017

Background

Evidence-based guidelines include concrete treatment targets that can be used as process and outcome indicators in the evaluation of the quality of healthcare services and diabetes care. Quality improvement can be evaluated by monitoring longitudinal trends in the care indicators on the system level. The aim of this study is to describe trends in the processes and outcomes of care among people with type 2 diabetes in North Karelia, Finland.

Methods

The data consist of all adults with type 2 diabetes (identified from the EHRs using ICD-10 codes) who used primary or specialized care services in North Karelia during 2012–2017. The diabetes care was evaluated using the measurement activity, treatment levels, and the achievement of the treatment targets for HbA1c and LDL as care indicators. Logistic and linear models with generalized estimating equations were used to assess the differences between years, sexes, and age groups.

Results

The proportion of patients with annual measurement varied between 75.8 and 78.1% for HbA1c and between 67.4 and 69.1% for LDL during a five-year follow-up. The changes in average levels were moderate: a 0.2% (2 mmol/mol) increase for HbA1c and a 0.1 mmol/l decrease for LDL. Anyway, the proportion of patients meeting the treatment target for HbA1c decreased from 72.7 to 67.3% (age-adjusted decrease: 5.7%p, 95% CI: 4.5–6.9) and for LDL it increased from 53.4 to 59.5% (age-adjusted increase: 5.6%p, 95% CI: 4.2–7.0). Women were measured and met the HbA1c target level more often compared with men. Conversely, men met the LDL target level more often than women, and the age-adjusted difference between sexes increased smoothly from 7.9%p to 11.7%p.

Conclusions

The achievements in relation to type 2 diabetes care in North Karelia are very good, but no major improvement was observed during follow-up. HbA1c levels had a rising tendency and LDL levels declining tendency indicating quality improvement in LDL management, but challenges in further improvement in glucose control.

Cultural and life style practices associated with low inflammatory physiology in Japanese adults

Japan is an exceptionally healthy East Asian country with extended longevity. In addition, the typical levels of several proinflammatory proteins, including both C-reactive protein (CRP) and interleukin-6 (IL-6), are often reported to be low when compared to American and European populations. This analysis determined if blood levels of CRP and IL-6 were associated with 4 cultural practices reflective of Japanese behavior and customs -- drinking tea, eating seafood, consuming vegetables, and partaking in relaxing baths regularly - among 382 adults living in Tokyo. Regression models controlled for demographic factors, adiposity (BMI), physical exercise, smoking, alcohol use, and chronic illness (e.g., diabetes). Consuming a Japanese diet was associated with significantly lower CRP and IL-6 levels. More frequent bathing was associated with lower IL-6, but not specifically predictive of low CRP. This study has confirmed prior evidence for low inflammatory activity in Japanese adults and its association with several behavioral practices common in Japan.

Epidemiologically and Socio-economically Optimal Policies via Bayesian Optimization

Mass public quarantining, colloquially known as a lock-down, is a non-pharmaceutical intervention to check spread of disease. This paper presents ESOP (Epidemiologically and Socio-economically Optimal Policies), a novel application of active machine learning techniques using Bayesian optimization, that interacts with an epidemiological model to arrive at lock-down schedules that optimally balance public health benefits and socio-economic downsides of reduced economic activity during lock-down periods. The utility of ESOP is demonstrated using case studies with VIPER (Virus-Individual-Policy-EnviRonment), a stochastic agent-based simulator that this paper also proposes. However, ESOP is flexible enough to interact with arbitrary epidemiological simulators in a black-box manner, and produce schedules that involve multiple phases of lock-downs.

Dysglycemia risk score in Saudi Arabia: A tool to identify people at high future risk of developing type 2 diabetes

AIMS/INTRODUCTION

To develop a non-invasive risk score to identify Saudis having prediabetes or undiagnosed type 2 diabetes.

METHODS

Adult Saudis without diabetes were recruited randomly using a stratified two-stage cluster sampling method. Demographic, dietary, lifestyle variables, personal and family medical history were collected using a questionnaire. Blood pressure and anthropometric measurements were taken. Body mass index was calculated. The 1-h oral glucose tolerance test was carried out. Glycated hemoglobin, fasting and 1-h plasma glucose were measured, and obtained values were used to define prediabetes and type 2 diabetes (dysglycemia). Logistic regression models were used for assessing the association between various factors and dysglycemia, and Hosmer-Lemeshow summary statistics were used to assess the goodness-of-fit.

RESULTS

A total of 791 men and 612 women were included, of whom 69 were found to have diabetes, and 259 had prediabetes. The prevalence of dysglycemia was 23%, increasing with age, reaching 71% in adults aged ≥65 years. In univariate analysis age, body mass index, waist circumference, use of antihypertensive medication, history of hyperglycemia, low physical activity, short sleep and family history of diabetes were statistically significant. The final model for the Saudi Diabetes Risk Score constituted sex, age, waist circumference, history of hyperglycemia and family history of diabetes, with the score ranging from 0 to 15. Its fit based on assessment using the receiver operating characteristic curve was good, with an area under the curve of 0.76 (95% confidence interval 0.73-0.79). The proposed cut-point for dysglycemia is 5 or 6, with sensitivity and specificity being approximately 0.7.

CONCLUSION

The Saudi Diabetes Risk Score is a simple tool that can effectively distinguish Saudis at high risk of dysglycemia.

Triglyceride to high-density lipoprotein cholesterol ratio is associated with incident diabetes in men: A retrospective study of Chinese individuals

AIMS/INTRODUCTION

Dyslipidemia is commonly present in type 2 diabetes mellitus patients. Recently, the triglyceride : high-density lipoprotein cholesterol (TG/HDL-C) ratio, a novel parameter of lipid abnormality, has been seen as an independent predictor for incident diabetes. However, the correlation of the TG/HDL-C ratio with incident diabetes in the Chinese population and how this relationship is impacted by sex have been rarely studied. In the present study, the correlation of the TG/HDL-C ratio with incident diabetes is investigated between different sexes of the Chinese population.

MATERIALS AND METHODS

A total of 116,855 participants who were free of diabetes at baseline were enrolled in the study. The participants were grouped by the median value (0.82) of the TG/HDL-C ratio. Then, participants were further analyzed according to their sex. Cumulative incidence and person-years incidence were used to express the incidence rate. The predictive value of the TG/HDL-C ratio for incident diabetes was probed by the Cox regression proportional hazards model.

RESULTS

The mean age of the participants was 44.1 ± 12.9 years, and 53% of participants (n = 62,868) were the men. A total of 2,685 incident diabetes cases occurred during the 3.1 years of the median follow-up period. The cumulative incidence in total incident diabetes patients, men and women was 2.30% (2.21-2.38%), 3.01% (2.87-3.14%) and 1.47% (1.37-1.57%), respectively. After the adjustment of multivariate factors, the multivariate Cox regression analysis results showed that a higher TG/HDL-C ratio was the independent predictive factor of incident diabetes in men (hazard ratio 1.30, 95% confidence interval 1.03-1.64), compared with women (hazard ratio 0.85, 95% confidence interval 0.53-1.38).

CONCLUSIONS

Among the Chinese population, the TG/HDL-C ratio is an independent predictor for incident diabetes in male patients.