Visit-to-Visit Variability of Fasting Plasma Glucose and the Risk of Cardiovascular Disease and All-Cause Mortality in the General Population

Risk prediction of diabetic retinopathy based on visit-to-visit fasting blood glucose indices

Objective

The long-term glucose monitoring is essential to the risk assessment of diabetic retinopathy (DR), the aim of this study was to investigate the predictive ability of visit-to-visit fasting blood glucose (FBG) indices on the risk of DR.

Methods

This was a community-based, cohort study conducted from 2013 to 2021. DR was diagnosed by digital fundus photography. The FPG indices included FBG, var. Associations of each FBG indices and DR were estimated using multinomial logistic regression models adjusting for confounders, and discrimination was determined by area under the curve (AUC). Predictive utility of different models was compared by changes in AUC, integrated discrimination improvement (IDI), and net reclassification index (NRI).

Results

This study analyzed 5054 participants, the mean age was 46.26 ± 11.44 years, and 2620 (51.84%) were women. After adjustment for confounders, the adjusted odds ratios (ORs) with 95% confidence intervals (CIs) for FBG, SD, CV, VIM, ARV, M-FBG, and cumulative FBG load were 1.62 (1.52-1.73), 2.74 (2.38-3.16), 1.78 (1.62-1.95), 1.11 (0.95-1.29), 1.72 (1.56-1.91), 2.15 (1.96-2.36), and 2.57 (2.31-2.85), respectively. The AUC of the model with separate cumulative FBG load and classical risk factors was 0.9135 (95%CI 0.8890-0.9380), and no substantive improvement in discrimination was achieved with the addition of other FBG indices once cumulative FBG load was in the model.

Conclusions

Cumulative FBG load is adequate for capturing the glucose-related DR risk, and the predictive utility of cumulative FBG load is not significantly improved by adding or replacing other FBG indices in the assessment of DR risk.

Association of Wearable Device-Measured Step Volume and Variability With Blood Pressure in Older Chinese Adults: Mobile-Based Longitudinal Observational Study

BACKGROUND

The paucity of evidence on longitudinal and consecutive recordings of physical activity (PA) and blood pressure (BP) under real-life conditions and their relationships is a vital research gap that needs to be addressed.

OBJECTIVE

This study aims to (1) investigate the short-term relationship between device-measured step volume and BP; (2) explore the joint effects of step volume and variability on BP; and (3) examine whether the association patterns between PA and BP varied across sex, hypertension status, and chronic condition status.

METHODS

This study used PA data of a prospective cohort of 3070 community-dwelling older adults derived from a mobile health app. Daily step counts, as a proxy of step volume, were derived from wearable devices between 2018 and 2022 and categorized into tertiles (low, medium, and high). Step variability was assessed using the SD of daily step counts. Consecutive daily step count recordings within 0 to 6 days preceding each BP measurement were analyzed. Generalized estimation equation models were used to estimate the individual and joint associations of daily step volume and variability with BP. Stratified analyses by sex, the presence of hypertension, and the number of morbidities were further conducted.

RESULTS

A total of 3070 participants, with a median age of 72 (IQR 67-77) years and 71.37% (2191/3070) women, were included. Participants walked a median of 7580 (IQR 4972-10,653) steps and 5523 (IQR 3590-7820) meters per day for a total of 592,597 person-days of PA monitoring. Our results showed that higher levels of daily step volume were associated with lower BP (systolic BP, diastolic BP, mean arterial pressure, and pulse pressure). Compared with participants with low step volume (daily step counts <6000/d) and irregular steps, participants with high step volume (≥9500/d) and regular steps showed the strongest decrease in systolic BP (-1.69 mm Hg, 95% CI -2.2 to -1.18), while participants with medium step volume (6000/d to <9500/d) and regular steps were associated with the lowest diastolic BP (-1.067 mm Hg, 95% CI -1.379 to -0.755). Subgroup analyses indicated generally greater effects on women, individuals with normal BP, and those with only 1 chronic disease, but the effect pattern was varied and heterogeneous between participants with different characteristics.

CONCLUSIONS

Increased step volume demonstrated a substantial protective effect on BP among older adults with chronic conditions. Furthermore, the beneficial association between step volume and BP was enhanced by regular steps, suggesting potential synergistic protective effects of both increased step volume and step regularity. Targeting both step volume and variability through PA interventions may yield greater benefits in BP control, particularly among participants with hypertension and a higher chronic disease burden.

Glycated Hemoglobin Variability Is Associated With Adverse Outcomes in Patients With Heart Failure Irrespective of Diabetic Status

BACKGROUND

The effect of glycated hemoglobin (HbA1c) variability on adverse outcomes in patients with heart failure (HF) is unclear. We aim to investigate the predictive value of HbA1c variability on the risks of all-cause death and HF rehospitalization in patients with HF irrespective of their diabetic status.

METHODS AND RESULTS

Using a previously validated territory-wide clinical data registry, HbA1c variability was assessed by average successive variability (ASV) or SD of all HbA1c measurements after HF diagnosis. Multivariable Cox proportional hazards models were used to estimate the adjusted hazard ratio (HR) and its corresponding 95% CI. A total of 65 950 patients with HF were included in the study. Over a median follow-up of 6.7 (interquartile range, 4.0-10.6) years, 34 508 patients died and 52 446 required HF rehospitalization. Every unit increment of variability in HbA1c was significantly associated with higher HF rehospitalization (HR ASV, 1.20 [95% CI, 1.18-1.23]) and all-cause death (HR ASV, 1.50 [95% CI, 1.47-1.53]). Diabetes significantly modified the association between HbA1c variability and outcomes (Pinteraction<0.001). HbA1c variability in patients with HF without diabetes conferred a higher risk of rehospitalization (HR ASV, 1.92 [95% CI, 1.70-2.17] versus HR ASV, 1.19 [95% CI, 1.17-1.21]), and all-cause death (HR ASV, 3.90 [95% CI, 3.31-4.61] versus HR ASV, 1.47 [95% CI, 1.43-1.50] compared with patients with diabetes).

CONCLUSIONS

HbA1c variability is significantly associated with greater risk of rehospitalization and all-cause death in patients with HF, irrespective of their diabetic status. These observations were more pronounced in patients with HF without diabetes.

Fasting glucose variability and risk of dementia in Parkinson's disease: a 9-year longitudinal follow-up study of a nationwide cohort

Background

Diabetes is associated with an increased risk of Parkinson's disease dementia (PDD); however, it is unknown whether this association is dependent on continuous hyperglycemia, hypoglycemic events, or glycemic variability. We aimed to investigate the relationship between visit-to-visit fasting glucose variability and PDD development in patients with Parkinson's disease (PD).

Methods

Using data from the Korean National Health Insurance Service, we examined 9,264 patients aged ≥40 years with de novo Parkinson's disease (PD) who underwent ≥3 health examinations and were followed up until December 2019. Glucose variability was measured using the coefficient of variation, variability independent of the mean, and average real variability. Fine and Gray competing regression analysis was performed to determine the effect of glucose variability on incident PDD.

Results

During the 9.5-year follow-up period, 1,757 of 9,264 (19.0%) patients developed PDD. Patients with a higher visit-to-visit glucose variability had a higher risk of future PDD. In the multivariable adjusted model, patients with PD in the highest quartile (subdistribution hazard ratio [SHR] = 1.50, 95% CI 1.19 to 1.88), quartile 3 (SHR = 1.29, 95% CI 1.02 to 1.62), and quartile 2 (SHR = 1.30, 95% CI 1.04 to 1.63) were independently associated with a higher risk of PDD than those in the lowest quartile.

Conclusion

We highlighted the effect of long-term glucose variability on the development of PDD in patients with PD. Furthermore, our findings suggest that preventive measures for constant glucose control may be necessary to prevent PDD.

Association of cumulative blood glucose load with cardiovascular risk and all-cause mortality

BACKGROUND

Incorporation both the magnitude and duration of exposure to elevated fasting blood glucose (FBG) into a single risk parameter (cumulative FBG load) for future diseases is intuitively appealing, although a data-based demonstration of the utility of this metric is not available. This study aimed to investigate the associations with cumulative FBG load with the risk of cardiovascular diseases (CVD) and all-cause mortality in the general population.

METHODS

This prospective cohort study included 41,728 participants who were free of CVD and underwent four health examinations from 2006 to 2012. Cumulative FBG load during 2006-2012 was calculated as the area under curve for FBG values ≥ 5.6 mmol/L divided by the total area curve. We also compared the predicting value cumulative FBG load with other FBG metrics.

RESULTS

During a median follow-up of 6.75 years, we identified 2323 cases of CVD and 1724 cases of all-cause mortality. Per 1-standard deviation increase in cumulative FBG load was associated with a 16 % higher risk of CVD (hazard ratio [HR]: 1.16; 95 % confidence interval [CI], 1.13-1.20) and 20 % higher risk of all-cause mortality (HR, 1.20; 95 % CI, 1.16-1.25). For the prediction of cardiovascular outcomes and all-cause mortality, cumulative FBG load outperformed FBG time-in-target, visit-to-visit FBG variability, and mean FBG in terms of C-statistics and reclassification indexes.

CONCLUSIONS

Cumulative FBG load may provide a better prediction of cardiovascular outcomes compared with other FBG metrics in the general population. These findings emphasized the important role of cumulative FBG load in assessing cardiovascular and mortality risk.

Visit-to-Visit Variability in Fasting Blood Glucose Predicts the New-Onset Heart Failure: Results From Two Large Chinese Cohorts

Previous studies have hypothesized an association between higher fasting blood glucose (FBG) and heart failure (HF). However, FBG values fluctuate continuously over time, the association between FBG variability and the risk of HF is uncertain. We investigated the relationship between visit-to-visit variability in FBG and the risk of new-onset HF. This cohort study used data from a prospective Kailuan cohort (recruited during 2006-2007) and a retrospective cohort of family medicine patients from Hong Kong (recruited during 2000-2003) were followed up until December 31st, 2016, and December 31st, 2019, respectively, for the outcome of incident HF. Four indexes of variability were used, including standard deviation (SD), coefficient of variation (CV), variability independent of the mean (VIM), and average real variability (ARV). Cox regression was used to identify HF. In total, 98,554 and 22,217 subjects without preexisting HF from the Kailuan and Hong Kong cohorts were analyzed, respectively, with 1218 cases of incident HF in the former and 4,041 in the latter. Subjects in the highest quartile of FBG-CV had the highest risk of incident HF in both cohorts (Kailuan: HR 1.245, 95% CI 1.055-1.470); Hong Kong: HR 1.362, 95%CI 1.145-1.620; compared with the lowest quartile). Similar results were observed when using FBG-ARV, FBG-VIM, and FBG-SD. Meta-analysis showed similar results (highest versus lowest quartile: HR 1.30, 95%CI 1.15-1.47, P < 0.0001). As observed from 2 large, geographically distinct Chinese cohorts, a higher FBG variability was independently associated with higher risk of incident HF.

Correlation Between Glycemic Variability and Diabetic Complications: A Narrative Review

Diabetes mellitus is a metabolic disorder with a complex etiology in which glycemic dynamics are disturbed and the body is unable to maintain the process of glucose homeostasis through the pancreas. Persistent symptoms of high blood glucose or low blood glucose may lead to diabetic complications, such as neuropathy, nephropathy, retinopathy, and cardiovascular diseases. Glycemic variability which can represent the presence of excessive glycemic excursions is an indicator for evaluating glucose homoeostasis. Limiting glycemic variability has gradually become an emerging therapeutic target in improve diabetes metabolism and prevent associated complications. This article reviews the progress of research on the various quantifiable parameters of glycemic variability and their relationships with vascular lesions and mechanisms.

Effects of metabolic parameters' variability on cardiovascular outcomes in diabetic patients

BACKGROUND

Metabolic abnormalities such as dyslipidemia, glucose and high blood pressure are common in diabetic patients. Visit-to-visit variabilities in these measures have been reported as potential residual cardiovascular risk factors. However, the relationship between these variabilities and their effects on cardiovascular prognosis have not been studied.

METHODS

A total of 22,310 diabetic patients with ≥ 3 measurements of systolic blood pressure (SBP), blood glucose, total cholesterol (TC), and triglyceride (TG) levels during a minimum of three years at three tertiary general hospitals were selected. They were divided into high/low variability groups for each variable based on the coefficient of variation (CV) values. The primary outcome was the incidence of major adverse cardiovascular events (MACE), a composite of cardiovascular death, myocardial infarction, and stroke.

RESULTS

All high CV groups had a higher incidence of MACE than those with low CV (6.0% vs. 2.5% for SBP-CV groups, 5.5% vs. 3.0% for TC-CV groups, 4.7% vs. 3.8% for TG-CV groups, 5.8% vs. 2.7% for glucose-CV groups). In multivariable Cox regression analysis,, high SBP-CV (HR 1.79 [95% CI 1.54-2.07], p < 0.01), high TC-CV (HR 1.54 [95% CI 1.34-1.77], p < 0.01), high TG-CV (HR 1.15 [95% CI 1.01-1.31], p = 0.040) and high glucose-CV (HR 1.61 [95% CI 1.40-1.86], p < 0.01) were independent predictors of MACE.

CONCLUSION

Variability of SBP, TC, TG and glucose are important residual risk factors for cardiovascular events in diabetic patients.

Long-Term Visit-to-Visit Glycemic Variability as a Predictor of Major Adverse Limb and Cardiovascular Events in Patients With Diabetes

Background Peripheral arterial disease (PAD) is a severe complication in patients with type 2 diabetes. Glycemic variability (GV) is associated with increased risks of developing microvascular and macrovascular diseases. However, few studies have focused on the association between GV and PAD. Methods and Results This cohort study used a database maintained by the National Taiwan University Hospital, a tertiary medical center in Taiwan. For each individual, GV parameters were calculated, including fasting glucose coefficient of variability (FGCV) and hemoglobin A1c variability score (HVS). Multivariate Cox regression models were constructed to estimate the relationships between GV parameters and composite scores for major adverse limb events (MALEs) and major adverse cardiovascular events (MACEs). Between 2014 and 2019, a total of 45 436 adult patients with prevalent type 2 diabetes were enrolled for analysis, and GV was assessed during a median follow-up of 64.4 months. The average number of visits and time periods were 13.38 and 157.87 days for the HVS group and 14.27 and 146.59 days for the FGCV group, respectively. The incidence rates for cardiac mortality, PAD, and critical limb ischemia (CLI) were 5.38, 20.11, and 2.41 per 1000 person-years in the FGCV group and 5.35, 20.32, and 2.50 per 1000 person-years in HVS group, respectively. In the Cox regression model with full adjustment, the highest FGCV quartile was associated with significantly increased risks of MALEs (hazard ratio [HR], 1.57 [95% CI, 1.40-1.76]; P<0.001) and MACEs (HR, 1.40 [95% CI, 1.25-1.56]; P<0.001). Similarly, the highest HVS quartile was associated with significantly increased risks of MALEs (HR, 1.44 [95% CI, 1.28-1.62]; P<0.001) and MACEs (HR, 1.28 [95% CI, 1.14-1.43]; P<0.001). The highest FGCV and HVS quartiles were both associated with the development of PAD and CLI (FGCV: PAD [HR, 1.57; P<0.001], CLI [HR, 2.19; P<0.001]; HVS: PAD [HR, 1.44; P<0.001], CLI [HR, 1.67; P=0.003]). The Kaplan-Meier analysis showed significantly higher risks of MALEs and MACEs with increasing GV magnitude (log-rank P<0.001). Conclusions Among individuals with diabetes, increased GV is independently associated with the development of MALEs, including PAD and CLI, and MACEs. The benefit of maintaining stable glycemic levels for improving clinical outcomes warrants further studies.

Change in Serum Uric Acid is a Useful Predictor of All-Cause Mortality among Community-Dwelling Persons

There is limited research on the association between longitudinal variability in serum uric acid (SUA) and all-cause mortality in the general population, although recent studies have suggested that changes in SUA are associated with all-cause mortality in adults. This study aims to examine the association between percentage change in SUA (%dSUA = 100 × (cohort 2 SUA - cohort 1 SUA)/(time × cohort 1 SUA) and all-cause mortality. This study is based on 1,301 participants, of whom 543 were male (63 ± 11 years) and 758 were female (63 ± 9 years). We obtained adjusted relative risk estimates for all-cause mortality and used a Cox proportional hazards model, adjusted for possible confounders, to determine the hazard ratio (HR) and 95% confidence interval (CI) of %dSUA. Of all the participants, 79 (6.1%) were deceased, and of these, 45 were male (8.3%) and 34 were female (4.5%). The multivariable-adjusted HRs (95% CI) for all-cause mortality for the first, second to fourth (reference), and fifth %dSUA quintiles were 3.79 (1.67-8.48), 1.00, and 0.87 (0.29-2.61) for male participants and 4.00 (1.43-11.2), 1.00, and 1.19 (0.46-3.05) for female participants, respectively. Participants with a body mass index of <22 kg/m² had a significantly higher HR, forming a U-shaped curve for the first (HR, 7.59; 95% CI, 2.13-27.0) and fifth quintiles (HR, 2.93; 95% CI, 1.05-8.18) relative to the reference. Percentage change in SUA is independently and significantly associated with future all-cause mortality among community-dwelling persons.

Glucose variability: A physiological correlate of eating disorder behaviors among individuals with binge-spectrum eating disorders

OBJECTIVES

Elevated glucose variability may be one mechanism that increases risk for significant psychological and physiological health conditions among individuals with binge-spectrum eating disorders (B-EDs), given the impact of eating disorder (ED) behaviors on blood glucose levels. This study aimed to characterize glucose variability among individuals with B-EDs compared with age-matched, sex-matched, and body mass index-matched controls, and investigate the association between frequency of ED behaviors and glucose variability.

METHODS

Participants were 52 individuals with B-EDs and 22 controls who wore continuous glucose monitors to measure blood glucose levels and completed ecological momentary assessment surveys to measure ED behaviors for 1 week. Independent samples t-tests compared individuals with B-EDs and controls and multiple linear regression models examined the association between ED behaviors and glucose variability.

RESULTS

Individuals with B-EDs demonstrated numerically higher glucose variability than controls (t = 1.42, p = .08, d = 0.43), although this difference was not statistically significant. When controlling for covariates, frequency of ED behaviors was significantly, positively associated with glucose variability (t = 3.17, p = .003) with medium effect size (f2  = 0.25). Post hoc analyses indicated that binge eating frequency was significantly associated with glucose variability, while episodes of 5+ hours without eating were not.

DISCUSSION

Glucose variability among individuals with B-EDs appears to be positively associated with engagement in ED behaviors, particularly binge eating. Glucose variability may be an important mechanism by which adverse health outcomes occur at elevated rates in B-EDs and warrants future study.

PUBLIC SIGNIFICANCE

This study suggests that some individuals with binge ED and bulimia nervosa may experience elevated glucose variability, a physiological symptom that is linked to a number of adverse health consequences. The degree of elevation in glucose variability is positive associated with frequency of eating disorder behaviors, especially binge eating.

Association of long-term visit-to-visit variability of HbA1c and fasting glycemia with hypoglycemia in type 2 diabetes mellitus

Background

Self-management of blood glucose levels to avoid hypoglycemia is vital for patients with type 2 diabetes mellitus (T2DM). The association between specific metrics of glycemic variability (glycosylated hemoglobin A1c [HbA1c] and fasting plasma glucose [FPG]) and severe hypoglycemia has not been fully studied in patients with T2DM.

Methods

In this post hoc analysis, patients with established T2DM with a high risk of cardiovascular disease were included in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study. The Cox proportional hazards model was used to investigate the relationship between glycemic variability and hypoglycemia requiring medical assistance (HMA) and hypoglycemia requiring any third-party assistance (HAA). The prognostic value of HbA1c/FPG variability for our predefined outcomes was compared using Harrell's C method.

Results

After adjusting for confounders, each increase in HbA1c variability of 1 standard deviation (SD) indicated a higher risk of HAA (hazard ratio [HR]: 1.10; 95% confidence interval [CI]: 1.03-1.16; P < 0.01) and HMA events (HR: 1.11; 95% CI: 1.03-1.20; P < 0.01). Meanwhile, each increase in FPG variability of 1 SD increased the risk of HAA (HR: 1.40; 95% CI: 1.31-1.49; P < 0.01) and HMA events (HR: 1.46; 95% CI: 1.35-1.57; P < 0.01). Meanwhile, models, including FPG variability, had better prognostic value for our predefined outcomes than HbA1c variability (P < 0.01).

Conclusions

Increased visit-to-visit variability in HbA1c and fasting glycemia is associated with a greater risk of severe hypoglycemic events in T2DM patients. FPG variability is a more sensitive indicator than HbA1c variability.

Trial registration

http://www.clinicaltrials.gov. Unique identifier: NCT00000620.

Triglyceride-glucose index variability and incident cardiovascular disease: a prospective cohort study

Background

Recent studies have suggested that triglyceride-glucose (TyG) index is an independent predictor of cardiovascular disease (CVD). However, the impact of long-term visit-to-visit variability in TyG index on the risk of CVD is not known. We aimed to investigate the longitudinal association between baseline and mean TyG index as well as TyG index variability and incident CVD in a Chinese population.

Methods

We included 49,579 participants without previous history of CVD in the Kailuan study who underwent three health examinations (2006, 2008, and 2010) and were followed up for clinical events until 2019. TyG index was calculated as Ln [fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2]. We measured TyG index variability as the SD of the residuals obtained from a linear regression on the three TyG index measurements for each individual. Multivariate-adjusted Cox models were used to estimate the adjusted hazard ratio (aHR) and 95% confidence interval (CI) with incident CVD.

Results

During a median follow-up time of 9.0 years, 2404 developed CVD. The highest tertile (T3) of baseline and mean TyG index were each associated with higher CVD incidence as compared with the lowest tertile (T1): aHR, 1.25; 95% CI 1.11–1.42; and aHR 1.40; 95% CI 1.24–1.58, respectively. Tertile 3 of TyG index variability was associated with increased CVD incidence compared to T1 group (aHR, 1.12; 95% CI 1.01–1.24). Similar findings were observed in a series of sensitivity analyses.

Conclusion

Higher TyG index level and greater TyGindex variability were each independently associated with a higher incidence of CVD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-022-01541-5.

Prevalence of hyperglycemia in masters athletes

Background

Ageing is associated with decreased physical activity, obesity and subsequently an increased risk of developing type 2 diabetes mellitus (T2dm). Master athletes (MA) have initiated exercise or sport later in life or pursued a physically active lifestyle for an extended period. Subsequently, MAs have been proposed as a model of successful ageing as this active lifestyle is associated with health benefits including decreased health risk of chronic diseases and a reduction in premature mortality. Given long-term physical activity/exercise has previously been shown to be protective against hyperglycemia, a risk factor for T2dm, it is plausible that MA may have protective benefit against developing hyperglycemia. Therefore, the aim of this study was to investigate the prevalence of hyperglycemia via fasting plasma glucose (FPG) in MAs competing at the World Masters Games (WMG).

Methods

This cross-sectional, observational survey utilized an online survey using open-source web-based software was used to investigate MAs physiological and medical-related parameters. Over 28,000 MAs competed in the WMG, of which 8,072 MAs completed the survey. Of these MAs, a total of 486 (males 277, females 209; range 27 to 91 years, mean age 55.1 ± 10.2 years) attained recent pathology results which included FPG which was subsequently analyzed for this study. FPG and other outcome variables were compared between genders and to the Australian and United States general population.

Results

Mean FPG for MAs was 5.03 mmol (±1.2, 95% CI [4.9-5.1] mmol) with majority (75.5%) of MAs reporting a normal (<5.5 mmol) FPG, followed by pre-diabetes (20.2%, >5.51 to <5.99 mmol) and abnormal (4.3%, >7.0 mmol). There was no significant difference (P = 0.333) in FPG between genders however, males had a slightly higher (+2.1%) FPG as compared to females (5.08 ± 1.2 mmol (95% CI [4.9-5.22] mmol) versus 4.98 ± 1.1 mmol (95% CI 4.8-5.1 mmol)). The majority of males (71.8%) and females (80.3%) were classified with a normal FPG. With regard to an abnormal FPG level, only 4.0% of males and 4.9% of females were classified abnormal which was suggestive of undiagnosed T2dm. With regard to age by decade, there was no significant difference (P = 0.06-1.00) between age groups and no relationship between the MAs' age and FPG (r = .054, P = 0.24). As a group, MAs had a significantly lower FPG as compared to the Australian (-3.2%, P = 0.005) and United States general populations (-13.9%, P < 0.001).

Conclusions

Most, however not all, MAs were found to have normal glycaemia, with only a small percentage indicating a risk of developing T2dm (i.e., impaired fasting glucose) and a smaller percentage identified with an abnormal FPG, suggestive of T2dm. These findings suggest MAs appear to be at low metabolic risk for developing T2dm based upon FPG and the physical activity/exercise they complete as MAs may indeed be protective against hyperglycemia whilst maintaining an active lifestyle.

Associations Between Device-Measured Physical Activity and Glycemic Control and Variability Indices Under Free-Living Conditions

Background: Disturbances of glycemic control and large glycemic variability have been associated with increased risk of type 2 diabetes in the general population as well as complications in people with diabetes. Long-term health benefits of physical activity are well documented but less is known about the timing of potential short-term effects on glycemic control and variability in free-living conditions. Materials and Methods: We analyzed data from 85 participants without diabetes from the Food & You digital cohort. During a 2-week follow-up, device-based daily step count was studied in relationship to glycemic control and variability indices using generalized estimating equations. Glycemic indices, evaluated using flash glucose monitoring devices (FreeStyle Libre), included minimum, maximum, mean, standard deviation, and coefficient of variation of daily glucose values, the glucose management indicator, and the approximate area under the sensor glucose curve. Results: We observed that every 1000 steps/day increase in daily step count was associated with a 0.3588 mg/dL (95% confidence interval [CI]: -0.6931 to -0.0245), a 0.0917 mg/dL (95% CI: -0.1793 to -0.0042), and a 0.0022% (95% CI: -0.0043 to -0.0001) decrease in the maximum glucose values, mean glucose, and in the glucose management indicator of the following day, respectively. We did not find any association between daily step count and glycemic indices from the same day. Conclusions: Increasing physical activity level was linked to blunted glycemic excursions during the next day. Because health-related benefits of physical activity can be long to observe, such short-term physiological benefits could serve as personalized feedback to motivate individuals to engage in healthy behaviors.

Long-Term Glycemic Variability and Risk of Cardiovascular Events in Type 2 Diabetes: A Meta-Analysis

Long-term glycemic fluctuation has been associated with cardiovascular risk in patients with type 2 diabetes mellitus (T2DM). However, the findings are inconsistent. We performed a meta-analysis to summarize the association between parameters of long-term glycemic variability and risk of cardiovascular events in T2DM patients. Medline, Embase, and Web of Science databases were searched for longitudinal follow-up studies comparing the incidence of cardiovascular events in T2DM patients with higher or lower long-term glycemic variability. A random-effect model incorporating the potential heterogeneity among the included studies was used to pool the results. Twelve follow-up studies with 146 653 T2DM patients were included. The mean follow-up duration was 4.9 years. Pooled results showed that compared to those with the lowest glycemic variability, patients with the highest glycemic variability had significantly increased risk of cardiovascular events, as evidenced by the standard deviation of glycated hemoglobin [HbA1c-SD: relative risk (RR)=1.44, 95% confidence interval (CI): 1.23 to 1.69, p<0.001; I²=70%], HbA1c coefficient of variation (HbA1c-CV: RR=1.46, 95% CI: 1.19 to 1.79. p<0.001; I²=83%), standard deviation of fasting plasma glucose (FPG-SD: RR=1.33, 95% CI: 1.07 to 1.65, p=0.009; I²=0%), and FPG coefficient of variation (FPG-CV: RR=1.29, 95% CI: 1.01 to 1.64, p=0.04; I²=47%). In conclusion, increased long-term glycemic variability may be an independent risk factor for cardiovascular events in T2DM patients.

Significance of Glycemic Variability in Diabetes Mellitus

The goal of diabetes treatment is to maintain good glycemic control, prevent the development and progression of diabetic complications, and ensure the same quality of life and life expectancy as healthy people. Hemoglobin A1c (HbA1c) is used as an index of glycemic control, but strict glycemic control using HbA1c as an index may lead to severe hypoglycemia and cardiovascular death. Glycemic variability (GV), such as excessive hyperglycemia and hypoglycemia, is associated with diabetic vascular complications and has been recognized as an important index of glycemic control. Here, we reviewed the definition and evaluated the clinical usefulness of GV, and its relationship with diabetic complications and therapeutic strategies to reduce GV.

Implications of fasting plasma glucose variability on the risk of incident peripheral artery disease in a population without diabetes: a nationwide population-based cohort study

Background

Diabetes have been known as a traditional risk factor of developing peripheral artery disease (PAD). However, the study evaluating the impact of long-term glycemic variability on the risk of developing PAD is limited, especially in a general population without diabetes.

Methods

We included 152,931 individuals without diabetes from the Korean National Health Insurance Service–Health Screening Cohort. Fasting plasma glucose (FPG) variability was measured using coefficient variance (FPG-CV), standard deviation (FPG-SD), and variability independent of the mean (FPG-VIM).

Results

A total of 16,863 (11.0%) incident cases of PAD were identified during a median follow-up of 8.3 years. Kaplan–Meier curves showed a progressively increasing risk of PAD in the higher quartile group of FPG variability than in the lowest quartile group (log rank P < 0.001). Multivariable Cox proportional hazard analysis showed the hazard ratio for PAD prevalence as 1.11 (95% CI 1.07–1.16, P < 0.001) in the highest FPG-CV quartile than in the lowest FPG-CV quartile after adjusting for confounding variables, including mean FPG. Similar degree of association was shown in the FPG-SD and FPG-VIM. In sensitivity analysis, the association between FPG variability and the risk of developing PAD persisted even after the participants were excluded based on previously diagnosed diseases, including stroke, coronary artery disease, congestive heart failure, chronic kidney disease, or current smokers or drinkers. Subgroup analysis demonstrated that the effects of FPG variability on the risk of PAD were more powerful in subgroups of younger age, regular exercisers, and those with higher income.

Conclusions

Increased long-term glycemic variability may have a significant prognostic effect for incident PAD in individuals without diabetes.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-022-01448-1.

Association between Variability of Metabolic Risk Factors and Cardiometabolic Outcomes

Despite strenuous efforts to reduce cardiovascular disease (CVD) risk by improving cardiometabolic risk factors, such as glucose and cholesterol levels, and blood pressure, there is still residual risk even in patients reaching treatment targets. Recently, researchers have begun to focus on the variability of metabolic variables to remove residual risks. Several clinical trials and cohort studies have reported a relationship between the variability of metabolic parameters and CVDs. Herein, we review the literature regarding the effect of metabolic factor variability and CVD risk, and describe possible mechanisms and potential treatment perspectives for reducing cardiometabolic risk factor variability.

Association between visit-to-visit variability of glycemic indices and lipid profile and the incidence of coronary heart disease in adults with type 2 diabetes

Coronary heart disease (CHD) is one of the major causes of mortality and morbidity in patients with type 2 diabetes mellitus. In this study, we aimed to assess the association between visit-to-visit variability of fasting blood sugar (FBS), HbA1c, blood sugar 2 h post-prandial (BS2hpp), lipid indices, creatinine, systolic and diastolic blood pressure (SBP, DBP) and incident CHD in patients with type 2 diabetes during a median follow-up of ten years. The current case-cohort study consisted of 1500 individuals with type 2 diabetes, followed up for the occurrence of CHD from 2002 to 2019. The patients had at least four annual follow-ups during which glycemic and lipid profile were measured. Co-efficient of variance (CV) for each parameter was calculated by 10-21 measurements. Cox regression analysis was performed to assess the association between CV of glycemic indices, lipid profile, blood pressure, creatinine, weight and incident CHD during the follow-up period. Hazard ratios (HR) were adjusted for the confounding variables. Glycemic indices variability (i.e., CV-HbA1c, CV-FBS, and CV-BS2hpp), were significantly higher in the group with incident CHD (P=0.034, P=0.042, and P=0.044, respectively). Hazard ratios were 1.42 (95 % CI=1.13-2.09) for CV-HbA1c, 1.37 (95 % CI=1.02-2.10) for CV-FBS, and 1.16 (95 % CI=1.01-1.63) for CV-BS2hpp (P=0.012, P=0.046, P=0.038, respectively). Creatinine was significantly higher in the group with incident CHD (P=0.036) and it was significantly associated with higher incidence of CHD (HR=1.14, 95 % CI=1.02-2.17, P=0.048). Visit to visit variability of glycemic indices of the patients with type 2 diabetes is associated with incident CHD independent of their baseline and mean values.

Self-management behavior and fasting plasma glucose control in patients with type 2 diabetes mellitus over 60 years old: multiple effects of social support on quality of life

OBJECTIVE

Elderly patients with type 2 diabetes mellitus are highly vulnerable due to severe complications. However, there is a contradiction in the relationship between social support and quality of life, which warrants further exploration of the internal mechanism. This study assessed the quality of life and its interfering factors in this patient population.

METHODS

In total, 571 patients with type 2 diabetes mellitus over 60 years old were recruited from two community clinics in Heilongjiang Province, China. We collected data on health status, quality of life, self-management behavior, fasting plasma glucose (FPG) level, and social support. Structural equation modeling and the bootstrap method were used to analyze the data.

RESULTS

The average quality of life score was - 29.25 ± 24.41. Poorly scored domains of quality of life were "Psychological feeling" (- 8.67), "Activity" (- 6.36), and "Emotion" (- 6.12). Of the 571 patients, 65.32% had normal FPG, 9.8% had high-risk FPG, 15.94% had good self-management behavior, and 22.07% had poor social support. Significant correlations among social support, self-management behavior, FPG level, and quality of life were noted. A multiple mediator model revealed that social support influenced quality of life in three ways: (1) directly (c' = 0.6831); (2) indirectly through self-management behavior (a1*b1 = 0.1773); and (3) indirectly through FPG control (a2*b2 = 0.1929). Self-management behavior influenced the quality of life directly and indirectly through FPG control.

CONCLUSION

Improving self-management behavior and monitoring hypoglycemia should become priority targets for future intervention. Scheduled social support to self-management projects should be put into the standardized management procedure. Physicians should provide substantial and individualized support to the elderly patients with type 2 diabetes mellitus regarding medication, blood glucose monitoring, and physical exercise.

Visit-to-visit fasting blood glucose variability and lifetime risk of cardiovascular disease: a prospective study

Aims

Previous studies suggested an adverse association between higher fasting blood glucose (FBG) variability and cardiovascular disease (CVD). Lifetime risk provides an absolute risk assessment during the remainder of an individual’s life. However, the association between FBG variability and the lifetime risk of CVD is uncertain.

Objective

We aimed to investigate the effect of the visit-to-visit FBG variability on the lifetime risk of CVD.

Methods

This study included participants from the Kailuan Study who did not have CVD at index ages 35, 45, and 55 years. The FBG variability was defined as the coefficient of variation (CV) of three FBG values that were measured during the examination periods of 2006–2007, 2008–2009, and 2010–2011. We used a modified Kaplan-Merrier method to estimate lifetime risk of CVD according to tertiles of FBG variability.

Results

At index age 35 years, the study sample comprised 46,018 participants. During a median follow-up of 7.0 years, 1889 participants developed CVD events. For index age 35 years, participants with high FBG variability had higher lifetime risk of CVD (32.5%; 95% confidence interval [CI]: 28.9–36.1%), compared with intermediate (28.3%; 95% CI: 25.5 –31.1%) and low (26.3%; 95% CI: 23.0–29.5%) FBG variability. We found that higher FBG variability was associated with increased lifetime risk of CVD in men but not women. Similar patterns were observed at index ages 45 and 55 years.

Conclusions

Higher FBG variability was associated with increased lifetime risk of CVD at each index age. Focusing on the FBG variability may provide an insight to the clinical utility for reducing the lifetime risk of CVD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-021-01397-1.

Visit-to-visit variability in the measurements of metabolic syndrome components and the risk of all-cause mortality, cardiovascular disease, and arterial stiffness

BACKGROUND AND AIMS

The risk of adverse health conditions varied according to the number of metabolic syndrome components. We aimed to evaluate the risk of mortality and incident cardiovascular events according to the number of components with high variability.

METHODS AND RESULTS

A total of 43,737 Kailuan Study participants with ≥3 examinations of waist circumference, fasting blood glucose, systolic blood pressure, triglyceride, and high-density lipoprotein during 2006-2013 were included in the present study. Visit-to-visit variability in each parameter was defined by the intraindividual standard deviation across visits. High variability was defined as the highest quartile of variability. Participants were classified numerically according to the number of high-variability components (e.g., a score of 0 indicated no high-variability component). There were 1551 deaths during a median follow-up of 5.9 years, and 950 incident cardiovascular disease (CVD) cases during a median follow-up of 4.9 years. In the multivariable adjusted model, compared with participants with low variability for all components, participants with ≥3 high-variability components had significantly higher risks for all-cause mortality (hazards ratio [HR], 1.61; 95 % confidence interval [CI], 1.35-1.91) and incident CVD event (HR, 1.45; 95 % CI, 1.16-1.82). Additionally, participants with ≥3 high-variability components had increased odds of arterial stiffness, as measured by brachia-ankle pulse wave velocity (odds ratio [OR], 1.39; 95 % CI, 1.19-1.63).

CONCLUSIONS

Our findings suggest that participants with at least three metabolic parameters with high variability experienced increased risk of CVD and all-cause mortality.

Impact of glycemic variability on coronary and peripheral endothelial dysfunction in patients with coronary artery disease

BACKGROUND

Previous studies have reported that glucose variability leads to endothelial dysfunction and progression of coronary atherosclerosis. However, few studies have directly evaluated the relation between glucose variability and coronary endothelial function in patients with coronary artery disease (CAD).

METHODS

A total of 38 patients with chronic CAD and a history of coronary drug-eluting stent implantation were enroled. Coronary endothelial function was evaluated by measuring the coronary vasoreactivity using quantitative coronary angiography in the segment distal to implanted stent in response to intracoronary acetylcholine (ACh) infusion (10-7 mol/l). Peripheral endothelial function was also assessed with reactive hyperemia index (RHI). The mean amplitude of glycemic excursion (MAGE) was calculated as a primary metric of glucose variability using a flash glucose monitoring system.

RESULTS

Of 38 patients, 17 (45%) had diabetes mellitus. The mean levels of glycated hemoglobin, MAGE, and RHI were 6.3 ± 0.8%, 71.4 ± 29.8 mg/dl, and 1.85 ± 0.63. In the distal segment to coronary stent, lumen diameter was constricted by 0.6 ± 7.3% in response to intracoronary ACh infusion compared to that at baseline. While peripheral endothelial function assessed with RHI was not significantly associated with MAGE (r = -0.16, p = 0.35), coronary endothelial function was correlated with MAGE (r = -0.38, p = 0.02).

CONCLUSION

Greater glucose variability was significantly associated with coronary rather than peripheral endothelial dysfunction in patients with CAD, suggesting an impact of glucose variability on coronary atherosclerosis.

Long-term glucose variability and incident cardiovascular diseases and all-cause mortality events in subjects with and without diabetes: Tehran Lipid and Glucose Study

AIM

To examine whether visit to visit variability (VVV) of fasting plasma glucose (FPG) is associated with incident cardiovascular diseases (CVD) and all-cause mortality in individuals with and without type 2 diabetes (T2D).

METHODS

A total of 4756 participants aged ≥30 years entered the study in 2002-2005 and underwent two subsequent examinations in 2005-2008 and 2008-2011. FPG variability measures included standard deviation (SD), coefficient of variation (CV), average real variability (ARV), and variability independent of mean (VIM). Multivariate Cox proportional hazard models were used to assess the risk of incident CVD and all-cause mortality for each unit increase in different FPG variability measures.

RESULTS

During a median follow-up of 18.14 years after baseline recruitment, 492 incident cardiovascular diseases and 338 all-cause mortality were recorded. Among individuals without T2D, the multivariate-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for incident CVD were 1.02 (1.01-1.04), 1.02 (1.01-1.04), 1.01 (1.00-1.02), and 1.01 (1.00-1.01) for SD, CV, ARV, and VIM, respectively (all P-values <0.05). Among individuals with T2D, the corresponding HRs and 95% CIs for all-cause mortality were 1.01 (1.00-1.02), 1.02 (1.01-1.03), 1.01 (1.00-1.02), and 1.01 (1.00-1.01), respectively (all P-values <0.05).

CONCLUSION

Long-term (VVV) of FPG is significantly associated with increased risk of CVD among participants without T2D, and all-cause mortality among participants with T2D.

Greater daily glucose variability and lower time in range assessed with continuous glucose monitoring are associated with greater aortic stiffness: The Maastricht Study

AIMS

CVD is the main cause of morbidity and mortality in individuals with diabetes. It is currently unclear whether daily glucose variability contributes to CVD. Therefore, we investigated whether glucose variability is associated with arterial measures that are considered important in CVD pathogenesis.

METHODS

We included participants of The Maastricht Study, an observational population-based cohort, who underwent at least 48 h of continuous glucose monitoring (CGM) (n = 853; age: 59.9 ± 8.6 years; 49% women, 23% type 2 diabetes). We studied the cross-sectional associations of two glucose variability indices (CGM-assessed SD [SD_CGM] and CGM-assessed CV [CV_CGM]) and time in range (TIR_CGM) with carotid-femoral pulse wave velocity (cf-PWV), carotid distensibility coefficient, carotid intima-media thickness, ankle-brachial index and circumferential wall stress via multiple linear regression.

RESULTS

Higher SD_CGM was associated with higher cf-PWV after adjusting for demographics, cardiovascular risk factors and lifestyle factors (regression coefficient [B] per 1 mmol/l SD_CGM [and corresponding 95% CI]: 0.413 m/s [0.147, 0.679], p = 0.002). In the model additionally adjusted for CGM-assessed mean sensor glucose (MSG_CGM), SD_CGM and MSG_CGM contributed similarly to cf-PWV (respective standardised regression coefficients [st.βs] and 95% CIs of 0.065 [-0.018, 0.167], p = 0.160; and 0.059 [-0.043, 0.164], p = 0.272). In the fully adjusted models, both higher CV_CGM (B [95% CI] per 10% CV_CGM: 0.303 m/s [0.046, 0.559], p = 0.021) and lower TIR_CGM (B [95% CI] per 10% TIR_CGM: -0.145 m/s [-0.252, -0.038] p = 0.008) were statistically significantly associated with higher cf-PWV. Such consistent associations were not observed for the other arterial measures.

CONCLUSIONS

Our findings show that greater daily glucose variability and lower TIR_CGM are associated with greater aortic stiffness (cf-PWV) but not with other arterial measures. If corroborated in prospective studies, these results support the development of therapeutic agents that target both daily glucose variability and TIR_CGM to prevent CVD.

Glycemic variability and the risk of nonalcoholic fatty liver disease : A nationwide population-based cohort study

AIM

Although few recent studies have reported the association between the glycemic variability and the development of type 2 diabetes mellitus and cardiovascular disease in individuals without diabetes mellitus, the impact of the long-term variability in fasting plasma glucose (FPG) levels on the incident nonalcoholic fatty liver disease (NAFLD) has not been evaluated.

METHODS

The study included 57,636 Korean men and women without NAFLD and diabetes mellitus from the Korean National Health Insurance System cohort. FPG variability was calculated using the coefficient of variation (FPG-CV), standard deviation (FPG-SD), variability independent of the mean (FPG-VIM), and average successive variability (FPG-ASV).

RESULTS

The cumulative incidence of NAFLD demonstrated progressively increasing trends according to the higher quartiles of FPG variability in Kaplan-Meier curves. A multivariable Cox proportional hazard analysis revealed that the hazard ratio for incident NAFLD was 1.15 (95% confidence interval, 1.06-1.24) in the highest quartile of FPG-CV compared with the lowest quartile of FPG-CV after adjusting for various confounding factors, including mean FPG levels. When using FPG-SD, FPG-VIM, and FPG-ASV, the results were similar. The 10-unit increase in FPG variability was associated with a 14% increased risk of NAFLD in the fully adjusted model. Moreover, this effect remained consistent in the subgroup and sensitivity analyses.

CONCLUSION

Increased long-term FPG variability is associated with the development of NAFLD, independent of confounding risk variables including mean FPG levels.

Longitudinal changes in fasting plasma glucose are associated with risk of cancer mortality: A Chinese cohort study

BACKGROUND

Numerous studies have suggested that fasting plasma glucose (FPG) was associated with the risk of mortality. However, relationship on longitudinal changes of FPG with the risk of mortality remained inconsistent.

METHODS

We examined the association of FPG at baseline and its longitudinal changes with risk of mortality based on a cohort study in Yinzhou, China, during 2010-2018. Cox regression models and competing risk models were separately used to examine the association of FPG levels and long-term fluctuation with risk of total and cause-specific mortality.

RESULTS

Subjects who had an impaired fasting glucose or diabetes suffered a higher risk of total mortality than subjects who had a normal fasting glucose (HRs and 95% CIs: 1.17 [1.01-1.35], 1.30 [1.10-1.53], respectively). The HR for total mortality was 1.54 (95% CI: 1.29-1.84) and for cancer mortality was 1.41 (95% CI: 1.04-1.92) in the highest quartile of coefficient of variation of FPG. Trajectory analysis indicated that subjects with a significantly changed FPG suffered a higher risk of total mortality.

CONCLUSION

According to this cohort study, we found that long-term fluctuation of FPG was significantly associated with the risk of total and cancer mortality. Our findings suggest that long-term fluctuation of FPG could be used as an efficient indicator for predicting the subsequent risk of mortality.

Fasting glucose level and all-cause or cause-specific mortality in Korean adults: a nationwide cohort study

BACKGROUND/AIMS

Although people with diabetes have been shown to have higher mortality than people without diabetes, there is a lack of data on the association between fasting glucose (FG) levels and cause-specific mortality rates in the general population.

METHODS

A total of 326,547 Korean adults over 20 years of age, who had received a health checkup between 2006 and 2008 were selected from the Korean National Health Insurance Service sample cohort dataset and followed until 2015. We estimated hazard ratios (HRs) of all-cause mortality and cause-specific mortality relative to various range of FG levels. All causes of death were classified according to International Classification of Diseases (ICD)-10 codes.

RESULTS

During follow-up (mean, 8.5 years), a total of 13,536 deaths (mortality rate 4.89/1,000 person-year) occurred; 4,916 deaths from cancer, 2,133 from cardiovascular disease, 762 from infectious disease, 199 from renal disease, and 5,526 from other causes. The overall mortality rate increased with an increase in FG category (HR, 1.78; 95% confidence interval, 1.65 to 1.92; in the ≥ 160 mg/dL). In addition, a J-shaped associations was found between FG levels and all-cause mortality after adjustment for age, sex, smoking, drinking, physical activity, body mass index, diabetes mellitus medication, hypertension, and dyslipidemia. In particular, the risk of cancer-mortality with high FG levels was increased for men but not women.

CONCLUSION

The risk of all-cause and cause-specific mortality showed the tendency to increase when the FG level was outside of the normal range, indicating a J-shaped relationship, in both men and women.

Associations of Physical Activity Level and Variability With 6-Month Weight Change Among 26,935 Users of Connected Devices: Observational Real-Life Study

Background

Physical activity (PA) is a modifiable lifestyle factor that can be targeted to increase energy expenditure and promote weight loss. However, the amount of PA required for weight loss remains inconsistent. Wearable activity trackers constitute a valuable opportunity to obtain objective measurements of PA and study large populations in real-life settings.

Objective

We aim to study the associations of initial device-assessed PA characteristics (average step counts and step count variability) and their evolution with 6-month weight change.

Methods

We analyzed data from 26,935 Withings-connected device users (wearable activity trackers and digital scales). To assess the initial PA characteristics and their 6-month changes, we used data recorded during the first and sixth 30-day periods of activity tracker use. For each of these periods, we used the monthly mean of daily step values as a proxy for PA level and derived the monthly coefficient of variation (CV) of daily step values to estimate PA level variability. Associations between initial PA characteristics and 6-month weight change were assessed using multivariable linear regression analyses controlled for age, sex, blood pressure, heart rate, and the predominant season. Restricted cubic spline regression was performed to better characterize the continuous shape of the associations between PA characteristics and weight change. Secondary analyses were performed by analyzing the 6-month evolution of PA characteristics in relation to weight change.

Results

Our results revealed that both a greater PA level and lower PA level variability were associated with weight loss. Compared with individuals who were initially in the sedentary category (<5000 steps/day), individuals who were low active (5000-7499 steps/day), somewhat active (7500-9999 steps/day), and active (≥10,000 steps/day) had a 0.21-kg, a 0.52-kg, and a 1.17-kg greater decrease in weight, respectively (95% CI −0.36 to −0.06, −0.70 to −0.33, and −1.42 to −0.93, respectively). Compared with users whose PA level CV was >63%, users whose PA level CV ranged from 51% to 63%, 40% to 51%, and was ≤40%, had a 0.19-kg, a 0.23-kg, and a 0.33-kg greater decrease in weight, respectively (95% CI −0.38 to −0.01, −0.41 to −0.04, and −0.53 to −0.13, respectively). We also observed that each 1000 steps/day increase in PA level over the 6-month follow-up was associated with a 0.26-kg (95% CI −0.29 to −0.23) decrease in weight. No association was found between the 6-month changes in PA level variability and weight change.

Conclusions

Our results add to the current body of knowledge that health benefits can be observed below the 10,000 steps/day threshold and suggest that not only increased mean PA level but also greater regularity of the PA level may play important roles in short-term weight loss.

Stress hyperglycemia may have higher risk of stroke recurrence than previously diagnosed diabetes mellitus

We aim to evaluate the risk of stroke recurrence among non-diabetes mellitus (non-DM), previously diagnosed diabetes mellitus (PDDM), newly diagnosed diabetes mellitus-related hyperglycemia (NDDM-RH) and stress hyperglycemia after minor stroke or TIA. Totally, 3026 patients with baseline fasting glucose and glycated albumin from the CHANCE trial (Clopidogrel in High-Risk Patients with Acute Nondisabling Cerebrovascular Events) were included. Patients were classified as non-DM, PDDM, NDDM-RH and stress hyperglycemia according to the status of glucose metabolism. The primary outcome was stroke recurrence during 90-day follow up. Cox regression was performed to estimate the relationship between the status of glucose metabolism and risk of 90-day stroke recurrence. Compared with PDDM, NDDM-RH had a similar risk of 90-day stroke recurrence (hazard ratios [HR]1.39, 95% confidence intervals [CI] 0.94-2.04), while stress hyperglycemia had approximately a 5.3-fold increased risk of 90-day stroke recurrence after adjusted for confounding covariates (HR 5.32, 95% CI 3.43-8.26). Parallel results were found for 90-day recurrent ischemic stroke and composite events. Compared with PDDM in minor stroke or TIA, a parallel risk of 90-day stroke recurrence were observed for NDDM-RH, while stress hyperglycemia might relate to higher risk of 90-day stroke recurrence.

Visit-to-visit variability of serum uric acid measurements and the risk of all-cause mortality in the general population

Background

Evidence on longitudinal variability of serum uric acid (SUA) and risk of all-cause mortality in the general population is limited, as many prior studies focused on a single measurement of SUA.

Methods

A total of 53,956 participants in the Kailuan study who underwent three health examinations during 2006 to 2010 were enrolled. Variability of SUA was measured using the coefficient of variation (primary index), standard deviation, average real variability, and variability independent of the mean. Cox proportional hazard regressions were used to calculate the hazard ratio (HR) and 95% confidence interval (CI) for the association of variability of SUA with subsequent risk of all-cause mortality, considering its magnitude and the direction and across different baseline SUA categories.

Results

Over a median follow-up of 7.04 years, 2728 participants died. The highest variability of SUA was associated with an increased risk of all-cause mortality, the HR was 1.33 (95% CI, 1.20–1.49) compared with the lowest variability. In this group, both a large fall (HR, 1.28; 95% CI, 1.14–1.44) and rise (HR, 1.18; 95% 1.05–1.32) in SUA were related to risk of all-cause mortality. These associations were similar across different baseline SUA categories. Consistent results were observed in alternative measures of SUA variability. Moreover, individuals with higher variability in SUA were more related to common risk factors than those with stable SUA.

Conclusions

Higher variability in SUA was independently associated with the risk of all-cause mortality irrespective of baseline SUA and direction of variability in the general population.

Triglyceride-glucose index and the risk of stroke and its subtypes in the general population: an 11-year follow-up

Background

Triglyceride-glucose (TyG) index was recently suggested to be a reliable surrogate marker of insulin resistance. We aim to investigate the associations between baseline and long-term TyG index with subsequent stroke and its subtypes in a community-based cohort.

Methods

A total of 97,653 participants free of history of stroke in the Kailuan Study were included. TyG index was calculated as ln (fasting triglyceride [mg/dL] × fasting glucose [mg/dL]/2). Baseline TyG index was measured during 2006–2007. Updated cumulative average TyG index used all available TyG index from baseline to the outcome events of interest or the end of follow up. The outcome was the first occurrence of stroke, including ischemic stroke, intracerebral hemorrhage and subarachnoid hemorrhage. The associations of TyG index with outcomes were explored with Cox regression.

Results

During a median of 11.02 years of follow-up, 5122 participants developed stroke of whom 4277 were ischemic stroke, 880 intracerebral hemorrhage, and 144 subarachnoid hemorrhage. After adjusting for confounding variables, compared with participants in the lowest quartile of baseline TyG index, those in the third and fourth quartile were associated with an increased risk of stroke (adjusted hazard ratio [HR] 1.22, 95% confidence interval [CI] 1.12–1.33, and adjusted HR 1.32, 95% CI 1.21–1.44, respectively, P for trend < 0.001). We also found a linear association between baseline TyG index with stroke. Similar results were found for ischemic stroke. However, no significant associations were observed between baseline TyG index and risk of intracranial hemorrhage. Parallel results were observed for the associations of updated cumulative average TyG index with outcomes.

Conclusions

Elevated levels of both baseline and long-term updated cumulative average TyG index can independently predict stroke and ischemic stroke but not intracerebral hemorrhage in the general population during an 11-year follow-up.

Comprehensive elaboration of glycemic variability in diabetic macrovascular and microvascular complications

Diabetes mellitus is the major risk factor for the development of macrovascular and microvascular complications. It is increasingly recognized that glycemic variability (GV), referring to oscillations in blood glucose levels and representing either short-term or long-term GV, is involved in the pathogenesis of diabetic complications and has emerged as a possible independent risk factor for them. In this review, we summarize the metrics and measurement of GV in clinical practice, as well as comprehensively elaborate the role and related mechanisms of GV in diabetic macrovascular and microvascular complications, aiming to provide the mechanism-based therapeutic strategies for clinicians to manage diabetes mellitus.

Single prognostic cut-off value for admission glycemia in acute myocardial infarction has been used although high-risk stems from hyperglycemia as well as from hypoglycemia (a narrative review)

All original articles and meta-analysis use the single cut-off value to distinguish high-risk hyperglycemic from other acute myocardial infarction (AMI) patients. The mortality rate is 3.9 times higher in non-diabetic AMI patients with admission glycemia ≥6.1mmol compared to normoglycemic non-diabetic AMI patients. On the other hand, admission hypoglycemia in AMI is an important predictor of mortality. Because both admission hypo- and hyperglycemia correspond to higher in-hospital mortality, this graph is recognized as "J or U shaped curve". The review suggests two cut-off values for admission glycemia for risk assessment in AMI instead of single one because hypoglycemia as well as hyperglycemia represents a high-risk factor.

The Association Between Glycemic Variability and Myocardial Infarction: A Review and Meta-Analysis of Prospective Studies and Randomized Trials

Diabetes mellitus is a major risk factor for vascular complications and mortality, glycemic variability (GV) has emerged as a measure of time and magnitude of plasma glucose, its association with cardiovascular complications is controversial. The current study aimed to assess the association of GV with myocardial infarction. An electronic literature search was conducted in PubMed, Medline, and Google Scholar databases for relevant articles. Articles in the English language during the period from 2010 to April 2020 were eligible. The keywords fasting blood glucose variability (FBGV), glucose variability, myocardial infarction, and acute coronary syndrome, were used with the protean OR and AND. Out of the 185 articles retrieved, only seven full texts fulfilled the inclusion and exclusion criteria. The author's name, year of publication, the study type, number of patients, and the results were extracted. There were seven full texts, one from Brazil, one from Australia, two from the USA, and three from Asia. Two were randomized controlled trials and five were prospective cohorts (included 109,058 participants). A significant negative association was found between GV and myocardial infarction, odd ratio (OD) 1.93, 95% CI=1.08-3.44, P-value=0.03, I² for heterogeneity=87%, P-value=0.0001. However, it is difficult to reach a conclusion due to the small number of the included studies and the high heterogeneity observed. Further well-controlled trials using the same methods are needed to resolve the issue.

Effect of Variability in Blood Pressure, Glucose and Cholesterol Concentrations, and Body Weight on Emergency Hospitalization and 30-Day Mortality in the General Population

Background

Variability in blood pressure, glucose concentration, cholesterol concentration, or body weight is associated with a wide range of health outcomes. We hypothesized that high variability in metabolic parameters is associated with an increased risk of emergency hospitalization and mortality.

Methods and Results

Using a nationally representative database from the Korean National Health Insurance System, 8 049 228 individuals who underwent 3 or more health examinations during 2005 to 2010 were followed up until the end of 2016. Variability in fasting blood glucose and total cholesterol concentrations, systolic blood pressure, and body weight was measured using the variability independent of the mean (VIM). High variability was defined as the highest quartile of variability. Subjects were classified according to the number of high variability parameters. The end points of the study were emergency hospitalization and 30‐day mortality. There were 733 387 emergency hospitalizations (9.1%) during a median follow‐up of 5.6±1.2 years. For each metabolic parameter, an incrementally higher risk of emergency hospitalization was observed for higher VIM quartile groups than for the lowest quartile group. Compared with the group with low variability for all 4 parameters, the group with high variability for all 4 parameters had a significantly higher risk for emergency hospitalization (hazard ratio [HR], 1.58; 95% CI, 1.54–1.61) and 30‐day mortality (HR, 2.44; 95% CI, 1.62–3.69), after adjusting for possible confounding factors.

Conclusions

High variability in metabolic parameters was associated with increased risk of emergency hospitalization and short‐term mortality.

Association Between Fasting Glucose Variability in Young Adulthood and the Progression of Coronary Artery Calcification in Middle Age

OBJECTIVE

To investigate whether intraindividual variability of fasting glucose (FG) in young adulthood is associated with coronary artery calcification (CAC) progression in middle age.

RESEARCH DESIGN AND METHODS

We included 2,256 CARDIA (Coronary Artery Risk Development Study in Young Adults) participants with CAC assessment by computed tomography scanner at baseline (2000-2001) and 10 years later (2010-2011). CAC progression was assessed for each individual as the difference of logarithmic CAC scores at follow-up and baseline (log[CAC (follow-up) + 1] - log[CAC (baseline) + 1]). FG variability was defined by the coefficient of variation about the mean FG (FG-CV), the SD of FG (FG-SD), and the average real variability of FG (FG-ARV) during the 10-year follow-up. We investigated the association between FG variability and CAC progression with adjustment for demographics, clinical risk factors, mean FG level, change in FG level, diabetes incidence, and medication use.

RESULTS

After multivariable adjustment, 1-SD increment in FG-CV was associated with worse progression of CAC as demonstrated as percent change in CAC, with incident CAC 5.9% (95% CI 1.0, 10.7) and any CAC progression 6.7% (95% CI 2.3, 11.1) during 10 years. Similar findings were also observed in FG-SD and FG-ARV.

CONCLUSIONS

Higher FG variability during young adulthood was associated with greater CAC progression in middle age, suggesting its value in predicting risk for subclinical coronary artery diseases.

Clinical implications, diagnosis, and management of diabetes in patients with chronic liver diseases

Diabetes mellitus (DM) negatively affects the development and progression of chronic liver diseases (CLD) of various etiologies. Concurrent DM and CLD are also associated with worse clinical outcomes with respect to mortality, the occurrence of hepatic decompensation, and the development of hepatocellular carcinoma (HCC). Unfortunately, early diagnosis and optimal treatment of DM can be challenging, due to the lack of established clinical guidelines as well as the medical complexity of this patient population. We conducted an exploratory review of relevant literature to provide an up-to-date review for internists and hepatologists caring for this patient population. We reviewed the epidemiological and pathophysiological associations between DM and CLD, the impact of insulin resistance on the progression and manifestations of CLD, the pathogenesis of hepatogenic diabetes, as well as the practical challenges in diagnosis and monitoring of DM in this patient population. We also reviewed the latest clinical evidence on various pharmacological antihyperglycemic therapies with an emphasis on liver disease-related clinical outcomes. Finally, we proposed an algorithm for managing DM in patients with CLD and discussed the clinical and research questions that remain to be addressed.

New Simplified Diagnostic Decision Trees for the Detention of Metabolic Syndrome in the Elderly

BACKGROUND

A new simplified method for the detention of metabolic syndrome (MetS) is proposed using two variables (anthropometric and minimally invasive).

METHODS

A study of MetS prevalence was made on a sample of 361 older people. The anthropometric variables analyzed were: blood pressure, body mass index, waist circumference (WC), waist-height ratio, body fat percentage, and waist-hip ratio. A crude and adjusted binary logistic regression was performed, and receiver operating characteristic curves were obtained for determining the predictive capacity of those variables. For the new detection method, decision trees were employed using automatic detection by interaction through Chi-square.

RESULTS

The prevalence of the MetS was of 43.7%. The final decision trees uses WC and basal glucose (BG), whose cutoff values were: for men, WC ≥ 102.5 cm and BG > 98 mg/dL (sensitivity = 67.1%, specificity = 90.3%, positive predictive value = 85%, validity index = 79.9%); and for women, WC ≥ 92.5 cm and BG ≥ 97 mg/dL (sensitivity = 65.9%, specificity = 92.7%, positive predictive value = 87.1%, validity index = 81.3%). In older women the best predictive value of MetS was a WC of 92.5 cm.

CONCLUSIONS

It is possible to make a simplified diagnosis of MetS in older people using the WC and basal capillary glucose, with a high diagnostic accuracy and whose use could be recommended in the resource-poor health areas. A new cutting point in older women for the WC should be valued.

Glycemic variability: adverse clinical outcomes and how to improve it?

Glycemic variability (GV), defined as an integral component of glucose homoeostasis, is emerging as an important metric to consider when assessing glycemic control in clinical practice. Although it remains yet no consensus, accumulating evidence has suggested that GV, representing either short-term (with-day and between-day variability) or long-term GV, was associated with an increased risk of diabetic macrovascular and microvascular complications, hypoglycemia, mortality rates and other adverse clinical outcomes. In this review, we summarize the adverse clinical outcomes of GV and discuss the beneficial measures, including continuous glucose monitoring, drugs, dietary interventions and exercise training, to improve it, aiming at better addressing the challenging aspect of blood glucose management.

The sweet spot: fasting glucose, cardiovascular disease, and mortality in older adults with diabetes: a nationwide population-based study

Background

Growing evidences shows that fasting glucose target should be different according to their health condition in older adults with diabetes. However, there are limited data regarding the relationship between fasting glucose level and health outcomes in Korean older people with diabetes. We aimed to examine the association of fasting glucose with mortality and cardiovascular events in Korean older adults with type 2 diabetes.

Methods

From the Korean National Health Insurance System, 227,938 subjects (aged ≥ 65 years) with type 2 diabetes but no history of cardiovascular events (myocardial infarction or stroke) who underwent ≥ 2 health examinations from 2009 to 2010 and who were followed up until 2017 were identified. The primary exposure variable was the mean fasting glucose level. We estimated the relationship between the baseline fasting glucose level and incidences of all-cause death and cardiovascular events. Comorbidity load was assessed using the Charlson comorbidity index.

Results

Fasting glucose levels and all-cause mortality risk showed a J-shaped relationship regardless of sex and number of comorbidities. Fasting glucose levels associated with the lowest mortality and cardiovascular events were 110–124 and 95–124 mg/dL, respectively. Stratified analysis by comorbidity load using the Charlson comorbidity index revealed higher optimal fasting glucose levels for the lowest cardiovascular events in subjects with Charlson comorbidity index ≥ 3 than in those with Charlson comorbidity index ≤ 2 (119 vs. 112 mg/dL, P = 0.04).

Conclusions

J-shaped relationship existed between fasting glucose and all-cause mortality and cardiovascular events in Korean older adults with diabetes. We identified that fasting glucose levels associated with the lowest mortality and cardiovascular events were 110–124 and 95–124 mg/dL respectively. Increased risk of cardiovascular events with low fasting glucose level (< 95 mg/dL) was noted, especially in patients with high comorbidity. These findings suggested that less stringent targets of fasting glucose may be beneficial especially in older adults with multiple comorbidities.

Association of fasting plasma glucose variability with gestational diabetes mellitus: a nationwide population-based cohort study

OBJECTIVE

Long-term glycemic variability has recently been recognized as another risk factor for future adverse health outcomes. We aimed to evaluate the risk of gestational diabetes mellitus (GDM) according to the prepregnancy long-term fasting plasma glucose (FPG) variability.

RESEARCH DESIGN AND METHODS

A total of 164 053 women who delivered their first baby between January 1, 2012 and December 31, 2015, were selected from the Korean National Health Insurance data. All women underwent at least three national health screening examinations, and the last examination should be conducted within 2 years before their first delivery. GDM was defined as the presence of more than four times of claim of GDM (International Classification of Disease, 10th Revision (ICD-10) O24.4 and O24.9) or prescription of insulin under the ICD-code of GDM. FPG variability was assessed by variability independent of the mean (FPG-VIM), coefficient of variation, SD, and average successive variability.

RESULTS

Among the 164 053 women, GDM developed in 6627 (4.04%). Those in the higher quartiles of FPG-VIM showed a stepwise increased risk of GDM. In fully adjusted model, the ORs for GDM was 1.22 (95% CI 1.14 to 1.31) in women with the highest FPG-VIM quartile compared with those in the lowest quartile. The risk for GDM requiring insulin therapy was 48% increase in women in the highest quartile of FPG-VIM compared with those in the lowest quartile, while that for GDM not requiring insulin therapy was 19% increase. The association between high FPG variability and the risk of GDM was intensified in the obese and aged more than 35 years women.

CONCLUSIONS

Increased FPG variability in the prepregnancy state is associated with the risk of GDM independent of confounding factors. Therefore, prepregnancy FPG variability might be a surrogate marker of the risk of GDM.

Visit-to-Visit Variability of Lipids Measurements and the Risk of Stroke and Stroke Types: A Prospective Cohort Study

BACKGROUND AND PURPOSE

Previous studies suggested increased visit-to-visit variability of total cholesterol (TC) is associated with stroke. This study aimed to investigate the associations of various lipids measurements variability and the risk of stroke and stroke type (ischemic and hemorrhagic stroke).

METHODS

Fifty-one thousand six hundred twenty participants in the Kailuan Study without history of myocardial infarction, stroke, and cancer who underwent three health examinations during 2006 to 2010 were followed for incident stroke. Variability in TC, triglycerides, high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) measurements were measured using the coefficient of variation (CV), standard deviation (SD), variability independent of the mean (VIM), and average real variability (ARV).

RESULTS

During a median of 6.04 years of follow-up, 1,189 incident stroke (1,036 ischemic and 160 hemorrhagic stroke) occurred. In the multivariable-adjusted model, the hazard ratio (HR) comparing participants in the highest versus lowest quartile of CV of HDL-C were 1.21 (95% confidence interval [CI], 1.02 to 1.45; P for trend=0.013) for ischemic stroke. The highest quartile of CV of LDL-C was associated with 2.17-fold risk of hemorrhagic stroke (HR, 2.17; 95% CI, 1.25 to 3.75; P for trend=0.002) compared with the lowest quartile. We did not observe any significant association between TC and triglycerides variability with any of stroke. Consistent.

RESULTS

were obtained when calculating variability index using SD, VIM, or ARV.

CONCLUSIONS

These findings suggest the high visit-to-visit HDL-C and LDL-C variability were associated with an increased incidence of ischemic and hemorrhagic stroke, respectively.

Association between visit-to-visit variability of HbA1c and cognitive decline: a pooled analysis of two prospective population-based cohorts

AIMS/HYPOTHESIS

The aim of this study was to investigate the association between visit-to-visit variability in HbA_1c and cognitive function decline in the elderly population.

METHODS

We performed a pooled analysis of two prospective population-based cohorts (the Health Retirement Study [HRS] and the English Longitudinal Study of Ageing [ELSA]). Cognitive function, including memory and executive function, were assessed at baseline and every 2 years, while HbA_1c levels were assessed at baseline and every 4 years. Visit-to-visit variability (VVV) in HbA_1c was calculated using the CV, SD and variation independent of the mean (VIM) during the follow-up period. Linear mixed models were used to evaluate the association between HbA_1c variability and cognitive function decline with adjustment for demographics, mean HbA_1c, education, smoking, alcohol consumption, BMI, baseline hypertension, baseline diabetes status and HDL-cholesterol.

RESULTS

The study enrolled 6237 participants (58.23% women, mean age 63.38 ± 8.62 years) with at least three measurements of HbA_1c. The median follow-up duration was 10.56 ± 1.86 years. In the overall sample, compared with the lowest quartile of HbA_1c variability, participants in the highest quartile of HbA_1c variability had a significantly worse memory decline rate (-0.094 SD/year, 95% CI -0.185, -0.003) and executive function decline rate (-0.083 SD/year, 95% CI -0.125, -0.041), irrespective of mean HbA_1c values over time. Among individuals without diabetes, each 1-SD increment in HbA_1c CV was associated with a significantly higher rate of memory z score decline (-0.029, 95% CI -0.052, -0.005) and executive function z score decline (-0.049, 95% CI -0.079, -0.018) in the fully adjusted model.

CONCLUSIONS/INTERPRETATION

We observed a significant association between long-term HbA_1c variability and cognitive decline among the non-diabetic population in this study. The effect of maintaining steady glucose control on the rate of cognitive decline merits further investigation.

Relationship between glucose variability evaluated by continuous glucose monitoring and clinical factors, including glucagon-stimulated insulin secretion in patients with type 2 diabetes

AIMS

To evaluate the clinical factors affecting daily and day-to-day glucose variability by using continuous glucose monitoring.

METHODS

We performed a cross-sectional analysis of patients with type 2 diabetes mellitus (T2DM) who underwent a glucagon stimulation test (GST) with 72 h of continuous glucose monitoring. Daily glucose variability was evaluated by mean amplitude of glycemic excursions [MAGE], percentage coefficient of variation for glucose (%CV), and day-to-day glucose variability (mean of daily differences [MODD]) by using continuous glucose monitoring. Correlations of clinical factors, including insulin secretion ability by the GST with MAGE, %CV, and MODD, were analyzed.

RESULTS

In 83 T2DM with insulin therapy, age and hemoglobin A_1c (HbA_1c) correlated with MAGE and %CV, fasting plasma glucose with MAGE and MODD, and increment of C-peptide immunoreactivity (ΔCPR) by GST correlated inversely with MAGE, %CV, and MODD. In 126 T2DM without insulin therapy, age, diastolic blood pressure, and triglycerides correlated with MODD, HbA_1c with MAGE and MODD, and ΔCPR inversely correlated with %CV. Use of α-glucosidase inhibitors inversely correlated with %CV, whereas that of sulfonylurea was associated with MAGE and %CV.

CONCLUSIONS

These results suggest that ΔCPR correlated with stability of glycemic control, whereas poorly controlled diabetes is associated with increase in glucose variability. α-glucosidase inhibitors may be superior to sulfonylureas in reducing the glucose variability in T2DM.

Prevalence of cardiovascular risk factors in non-menopausal and postmenopausal inpatients with type 2 diabetes mellitus in China

BACKGROUND

To investigate the prevalence of cardiovascular disease (CVD) risk factors and assess the 10-year risk of CVD in non-menopausal and postmenopausal women with type 2 diabetes mellitus (T2DM).

METHODS

A total of 569 patients with T2DM at a Chinese tertiary hospital were investigated using the Framingham Risk Score (FRS). We evaluated the 10-year risk of CVD, clinical and menopause characteristics in all subjects.

RESULTS

Among the 569 diabetic patients, the incidence of smoking, dyslipidemia, hypertension, overweight or obesity, and nonalcoholic fatty liver disease (NAFLD) was 0.7, 36.2, 38.1 56.6 and 58.2%, respectively. The usage rate of hypoglycemic agents, antihypertensive agents, lipid modulators and antithrombotic drugs was 88.6, 78.3, 50.0 and 27.1%, respectively. However, only 1.2% of inpatients achieved the three target goals for the control of blood glucose (HbA_1c < 7%), blood pressure (systolic blood pressure < 130 mmHg, diastolic blood pressure < 80 mmHg), and blood lipids (total cholesterol < 174 mg/dL). The 10-year risk of CVD was (1.6 ± 1.5%) and tended to increase along with age (F = 27.726, P <  0.001). For all subjects (n = 569), multiple linear regression analysis showed that menopause (β = 0.275, P <  0.001), low-density lipoprotein cholesterol (LDL-C) (β = 0.212, P <  0.001), fasting plasma glucose (FPG) (β = 0.093, P = 0.018) and waist-to-hip-ratio (β = - 0.078, P = 0.047) were risk factors of 10-year risk of CVD, which may explain the variance of 14.3%. In the postmenopausal group (n = 397), LDL-C (β = 0.227, P <  0.001), FPG (β = 0.139, P = 0.003) and time since menopause (β = 0.230, P <  0.001) were found to be associated with CVD, which may explain the variance of 14.6%.

CONCLUSION

The incidence of dyslipidmia, hypertension, overweight or obesity and NAFLD is high. The level of control of blood glucose, blood pressure, and blood lipids was found to be extremely low and the treatment status was not ideal. Besides menopause, LDL-C, FPG and time since menopause were found to be independent risk factors for the 10-year risk of CVD. Therefore, it is necessary to focus on comprehensive control of multiple risk factors, such as plasma glucose, blood pressure and serum lipid.

Fasting glucose variability in young adulthood and incident diabetes, cardiovascular disease and all-cause mortality

AIMS/HYPOTHESIS

The aim of this study was to determine whether long-term intra-individual variability in fasting glucose (FG) during young adulthood is associated with incident diabetes, cardiovascular disease (CVD) and mortality.

METHODS

We included participants from the Coronary Artery Risk Development in Young Adults (CARDIA) study, ages 18-30 years at baseline (1985-1986) and followed with eight examinations for up to 30 years. Long-term glucose variability was assessed using the CV (CV-FG) and the absolute difference between successive FG measurements (average real variability; ARV-FG). For participants who developed any event (diabetes, CVD or mortality), FG variability measurement was censored at the examination prior to event ascertainment. We estimated HRs for incident diabetes, CVD and mortality with adjustment for demographics, baseline FG, change in FG (censor - baseline) and time-varying education, smoking, alcohol consumption, BMI, physical activity, systolic BP, BP medications, LDL-cholesterol and cholesterol medications (and incident diabetes and diabetes medications for CVD and mortality outcomes).

RESULTS

Among 3769 black and white participants, there were 317 incident diabetes cases (102,677 person-years), 159 incident CVD events (110,314 person-years) and 174 deaths (111,390 person-years). After adjustment, HRs per 1 SD higher ARV-FG were 1.64 (95% CI 1.52, 1.78) for diabetes, 1.15 (95% CI 1.01, 1.31) for CVD and 1.25 (95% CI 1.11, 1.40) for mortality. The HRs per 1 SD higher CV-FG were 1.39 (95% CI 1.21, 1.58) for diabetes, 1.32 (95% CI 1.13, 1.54) for CVD and 1.08 (95% CI 0.92, 1.27) for mortality, after adjustment. The cause-specific HRs per 1 SD higher ARV-FG were 1.29 (95% CI 1.14, 1.47) for non-CVD death and 1.05 (95% CI 0.76, 1.45) for CVD death. We did not observe evidence for effect modification of any association by sex or race.

CONCLUSIONS/INTERPRETATION

Our results suggest that higher intra-individual FG variability during young adulthood before the onset of diabetes is associated with incident diabetes, CVD and mortality.

Glycaemic variability in diabetes: clinical and therapeutic implications

Glycaemic variability is an integral component of glucose homoeostasis. Although it has not yet been definitively confirmed as an independent risk factor for diabetes complications, glycaemic variability can represent the presence of excess glycaemic excursions and, consequently, the risk of hyperglycaemia or hypoglycaemia. Glycaemic variability is currently defined by a large and increasing number of metrics, representing either short-term (within-day and between-day variability) or long-term glycaemic variability, which is usually based on serial measurements of HbA_1c or other measures of glycaemia over a longer period of time. In this Review, we discuss recent evidence examining the association between glycaemic variability and diabetes-related complications, as well as non-pharmacological and pharmacological strategies currently available to address this challenging aspect of diabetes management.