Prospective Association Among Diabetes Diagnosis, HbA1c, Glycemia, and Frailty Trajectories in an Elderly Population

Bidirectional relationship between diabetes and frailty in middle-aged and older adults: A systematic review and meta-analysis

BACKGROUND

Diabetes and frailty are prevalent and burdensome in middle-aged and older adults. However, current evidence on their association is inconsistent, and no quantitative meta-analysis exists. We conducted a systematic review and meta-analysis to examine whether diabetes increased the risk of frailty and vice versa.

METHODS

We systematically searched PubMed, Web of Science, Embase, and CINAHL databases from inception to 10 April 2025. Random-effects models were used to calculate pooled odds ratio (OR) and 95 % confidence interval (CI) for cross-sectional analysis and pooled relative risk (RR) for longitudinal analysis. The certainty of evidence was evaluated using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework.

RESULTS

From 8559 non-duplicated records, 31 articles were included. People with diabetes had increased risks of prevalent frailty (OR=2.21, 95 %CI: 1.60-3.06, I2=99.0 %, n = 15; GRADE=Low), prevalent pre-frailty (OR=2.23, 95 %CI: 2.19-2.28, I2=0.0 %, n = 2; GRADE=Very low), and incident frailty (RR=1.50, 95 %CI: 1.36-1.65, I2=0.0 %, n = 7; GRADE=Moderate). Those with pre-frailty (OR=1.95, 95 %CI: 1.61-2.36, I2=0.0 %; GRADE=Very low) but not with frailty (OR=2.28, 95 %CI:0.96-5.46, I2=92.3 %; GRADE=Very low) had increased odds of prevalent diabetes in two studies. In 15 studies, the pooled RRs for incident diabetes were 1.47 (95 %CI: 1.37-1.57, I2=91.0 %; GRADE=Moderate) in pre-frail participants and 1.96 (95 %CI: 1.73-2.23, I2=92.7 %; GRADE=Moderate) in frail participants.

CONCLUSION

Our findings support the bidirectional relationship between diabetes and frailty in middle-aged and older adults, with each condition contributing to the development of the other. This highlights the importance of early detection and integrated management strategies for diabetes and frailty.

Association of frailty and its trajectory with the risk of cancer: evidence from the China health and retirement longitudinal study (CHARLS)

BACKGROUND

Frailty can be identified in both middle-aged and older adults. However, longitudinal studies that examine whether frailty is associated with incident cancer are currently lacking. This study aimed to comprehensively examine the impact of baseline frailty levels and their changing trajectories over time on the risk of cancer.

METHODS

We assessed frailty status using the frailty index based on data from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2020. First, the association between baseline frailty and cancer risk was analyzed using the Cox proportional hazards model. Second, based on the CHARLS data from 2011 to 2020, we used Group-based trajectory modeling (GBTM) to identify trajectories of frailty development during the four follow-up periods from 2011 to 2020. Cox proportional hazards model was used to analyze the association between frailty trajectories and the risk of cancer incidence during the follow-up period.

RESULTS

A total of 17,708 participants were involved at the baseline survey in CHARLS 2011. During a mean follow-up period of 8.05 years, 248 cancer events occurred. Compared with non-frailty individuals, participants in pre-frailty and frailty states had a 34% (hazard ratio [HR]: 1.34, 95% confidence interval [CI]: 1.03-1.75) and 66% (HR: 1.66, 95% CI: 1.07-2.56) increased risk of overall cancer incidence, respectively. Based on repeated measurements from 2011 to 2018, three trajectories of frailty were identified among 9,173 participants. Compared to the low-level stable group, the high-level increase group had the highest risk of cancer, with an associated HR (95% CI) of 5.43 (1.07-5.73). This was followed by the medium-level increase group, with an associated HR (95% CI 2.86 (1.27-6.43). When stratified by sex and age, participants aged ≥ 60 years and female participants in the high-level increase frailty group had a higher risk of developing cancer.

CONCLUSION

Frailty is associated with cancer risk. Medium and high levels of the frailty index are significantly associated with an increased risk of cancer incidence. In addition, more attention should be paid to the risk of cancer in people aged ≥ 60 years and in women with high levels of frailty.

Diabetes mellitus and HbA1c as predictors of mortality in hospitalized COVID-19 patients

BACKGROUND

The role of diabetes mellitus (DM) in hospitalized COVID-19 patients and of HbA1c in hospitalized COVID-19 patients with DM were not studied adequately in the past.

RESEARCH DESIGN AND METHODS

It was a retrospective cohort study. In this study, data from 305 hospitalized COVID-19 patients was analyzed. The study objective was to determine the association of DM with in-hospital mortality in COVID-19 patients. Another study objective was to determine the association of HbA1c with mortality in COVID-19 patients with DM.

RESULTS

In this retrospective study, DM was present in 41.3% (126/305) of the study population. The multivariate Cox regression analysis showed a significant association between DM and mortality (adjusted hazard ratio (aHR): 2.116, 95% CI: 1.088-4.116, p = 0.027). The median HbA1c in diabetic patients was 8.9% (7.5-11.0). HbA1c was found to be associated with mortality in diabetic patients in the multivariate cox-regression analysis (aHR:1.272, 95% CI: 1.028-1.574, p = 0.027). The multivariate Cox regression analysis also showed the association of HbA1c (10.5%≤HbA1c > 10.5%) as a dichotomous variable with in-hospital mortality (aHR: 2.53, 95% CI: 2.606-194.81, p = 0.005) in diabetic patients.

CONCLUSIONS

DM was independently associated with mortality in hospitalized COVID-19 patients in the multivariate analysis. In COVID-19 patients with DM, HbA1c was associated with mortality as a continuous and dichotomous variable in the multivariate analysis.

Geriatric Syndromes in Older Adults With and Without Diabetes: A Systematic Review and Meta-Analysis

PURPOSE

Diabetes prevalence is increasing among older adults globally. The current study aimed to compare geriatric syndrome prevalence in older adults with and without diabetes.

METHOD

Primary research (2011 to 2024) in English, French, or Spanish was included. We used multiple databases following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Pooled log odds ratios (ORs) and prevalence rates were calculated using random-effects models. Sensitivity analysis explored heterogeneity, and publication bias was assessed.

RESULTS

Older adults with diabetes exhibited higher prevalence rates of cognitive impairment (9.13% vs. 4.22%, log OR: 0.1884), depression (8.96% vs. 5.44%, log OR: 0.3543), falls (11.5% vs. 4.47%, log OR: 0.4237), functional impairment (14.2% vs. 10.6%, log OR: 1.02), urinary incontinence (9.72% vs. 4.35%, log OR: 1.3668), frailty (22.8% vs. 12.1%, log OR: 1.3443), and polypharmacy (22.9% vs. 5.78%, log OR: 2.5420). Diabetes was also associated with a higher comorbidity burden.

CONCLUSION

Multidisciplinary strategies addressing diabetes and associated conditions are crucial for older adults with diabetes. Future research should delve into underlying mechanisms and optimize care strategies. [Research in Gerontological Nursing, 18(2), 99-108.].

Frailty, Body Composition, and Glycemic Control in Older Adults with Type 2 Diabetes

The relationship between frailty and glycemic control in older adults with diabetes remains uncertain, mainly due to the fact that previous studies have not accounted for measures of body composition. In older adults with diabetes, we examined the association between three types of frailty measures and glycemic control, while accounting for fat-free mass (FFM) and waist circumference (WC). Eighty older adults (age ≥65, 27 women and 53 men, mean age 80.5 ± 0.6 years) had gait speed, Cardiovascular Health Study Index (CHSI), Rockwood Clinical Frailty Scale (RCFS), and glycosylated hemoglobin (HgA1C) measured. HgA1C showed a negative association only with CHSI (standardized β = -0.255 ± 0.120, p = 0.038), but no association with gait speed or the RCFS. Even after accounting for FFM and WC, we demonstrated a negative association between glycated hemoglobin and increasing frailty in older adults with diabetes.

Association of frailty index with all-cause and cardiovascular mortality with different diabetic status: NHANES 1999-2018

AIMS

The relationship between frailty and mortality among individuals with varying diabetic statuses represents a burgeoning area of concern and scholarly interest within the medical community. However, there are limited studies that explore the relationship between frailty and mortality, as well as cause-specific mortality among individuals with non-diabetes, prediabetes, and diabetes patients. Hence, this study aims to investigate the relationship between the frailty statues and all-cause mortality, as well as cause-specific mortality in individuals with varying diabetic statuses using the data in the NHANES database.

METHODS

The study utilized data from the National Health and Nutrition Examination Survey (NHANES) 1999-2018, incorporating a final sample size of 57, 098 participants. Both univariable and multivariable-adjusted logistic regression analyses, as well as Cox regression analysis were employed to examine the relationship between frailty index (FI) and mortality.

RESULTS

This study, found a significant positive correlation between the frailty and the increased risk of all-cause mortality non-diabetic [OR 4.277, 95%CI (3.982, 4.594), P < 0.001], prediabetic [OR 2.312, 95%CI (2.133, 2.506), P < 0.001], and diabetic patients [OR 3.947, 95%CI (3.378, 4.611), P < 0.001]. This correlation still existed even after adjusting for confounding factors including age, sex, BMI, poverty, fasting insulin, education, smoke, alcohol drink, waist, hypertension, hyperlipidemia, fasting glucose, HbA1c, eGFR, creatinine and total bilirubin. Our result also suggested a significant positive correlation between the frailty index and the increased risk of CVD mortality among non-diabetic [OR 3.095, 95%CI (2.858, 3.352), P < 0.001] and prediabetic [OR 5.985, 95%CI (5.188, 6.904), P < 0.001] individuals. However, in patients with diabetes, the correlation between frailty and CVD mortality lost significance after adjusting for possible confounding factors [OR 1.139, 95%CI (0.794, 1.634), P > 0.05].

CONCLUSION

A nonlinear relationship has been identified between the FI and all-cause mortality, as well as CVD mortality in non-diabetic and pre-diabetic population. In diabetic patients, there was a significant positive correlation between the frailty and the increased risk of all-cause mortality, but not with CVD mortality. Renal function and liver function might potentially acted as an intermediary factor that elevated the risk of CVD mortality in frail patients with diabetes.

Association between non-insulin-based insulin resistance indicators and frailty progression: a national cohort study and mendelian randomization analysis

BACKGROUND

Insulin resistance (IR) is linked to an increased risk of frailty, yet it remains unclear whether the non-insulin-based IR indicators are associated with frailty trajectories and physical function decline. It aimed to examine the associations of triglyceride-glucose (TyG) index, metabolic score for insulin resistance (METS-IR), estimated glucose disposal rate (eGDR) and with long-term deficit-accumulation frailty trajectories and physical function decline.

METHODS

Data from 6722 participants in the China Health and Retirement Longitudinal Study (CHARLS) were analyzed. Baseline TyG index, METS-IR, eGDR, along with the frailty index (FI) over nine years, were calculated. FI trajectories were assessed using group-based trajectory model (GBTM). Logistic regression models were used to analyze the associations between IR indicators with FI trajectory and frailty risk. Restricted cubic splines (RCS) models were utilized to detect potential dose-response associations. Linear mixed-effects model was used to evaluate associations with FI development speed. Age, gender, educational level, marital status, smoking status, drinking status, life satisfaction, social activity and sleep duration were adjusted. Additionally, a two-sample Mendelian randomization (MR) was performed to assess the causality of observed associations.

RESULTS

Three FI trajectories including low-stable frailty, moderate-increasing frailty, and accelerated rising frailty were identified. Regarding the frail risk, each SD increment in TyG index was associated with a 16.1% increase in the risk of frailty (OR = 1.161; 95%CI: 1.092, 1.235). An inverse association was observed for eGDR with the OR (95%CI) being 0.741 (0.696, 0.788). A linear relationship was observed between baseline TyG index and frailty risk (P nonlinear = 0.696), but nonlinear association patterns for eGDR (P nonlinearity < 0.010) and METS-IR (P nonlinearity < 0.010). Each SD increment of TyG index was associated with greater FI increase (β = 0.005 SD/y; 95%CI = 0.002, 0.008 SD/y; P < 0.001). A similar association pattern was observed for METS-IR, and participants in the highest quartile of METS-IR showed significantly greater FI progression, with β value of 0.013 (95% CI = 0.004, 0.022). Each SD increment of eGDR was associated with a slower increase in FI (β=-0.006 SD/y, 95% CI=-0.009, -0.003 SD/y; P < 0.001). Participants in the highest quartile of eGDR presented a lower annual change in FI compared with participants in quartile 1 group during follow-up (β=-0.013 SD/y, 95% CI=-0.022, -0.005 SD/y; P for trend = 0.001). Similar findings were observed for physical function decline. Findings from MR analysis showed a causal relationship between higher TyG index and increased risk of frailty (β = 0.214, 95% CI = 0.079, 0.349; P = 0.002).

CONCLUSIONS

The non-insulin-based IR indicators, including TyG index, METS-IR and eGDR, were independently associated with the frailty progression and physical function decline. Monitoring and managing abnormal glucose metabolism should be recommended as a part of comprehensive strategies to prevent or delay the progression of frailty.

Associations Between Deficit Accumulation Frailty and Baseline Markers of Lifestyle in the U.S. POINTER Trial

BACKGROUND

Multidomain lifestyle interventions may have the potential to slow biological aging as captured by deficit accumulation frailty indices. We describe the distribution and composition of the 49-component frailty index developed by the U.S. POINTER clinical trial team of investigators and assess its cross-sectional associations with sociodemographic factors and markers chosen to be representative of behaviors targeted by the trial's multidomain interventions.

METHODS

We draw baseline data from the 2 111 volunteers enrolled in U.S. POINTER who were ages 60-79 years and at increased risk for cognitive decline. Frailty components were grouped into 9 domains. Associations that frailty index scores and their domains had with behavioral markers were described with correlations and canonical correlation.

RESULTS

The 25th, 50th, and 75th percentiles of the frailty index score distribution were 0.153, 0.189, and 0.235. Higher frailty scores tended to occur among individuals who were older, male, and living in areas of greater deprivation (all p < .001). They were also associated with poorer self-reported diet, less physical activity, and higher Framingham risk scores (all p < .001). Associations were diffusely distributed among the frailty component domains, indicating that no individual domain was dominating associations.

CONCLUSIONS

The U.S. POINTER deficit accumulation frailty index had expected relationships with sociodemographic factors and sensitivity to the behaviors targeted by the trial's interventions. Our analysis supports its use as a secondary outcome to assess whether the multidomain interventions differentially impact an established marker of biological aging. ClinicalTrials.gov Identifier: NCT03688126.

The prevalence of frailty among older adults with maintenance hemodialysis: a systematic

BACKGROUND

To evaluate the epidemiological data on the prevalence of frailty and prefrailty in individuals aged 60 years or older on MHD patients.

METHODS

PubMed, Web of Science, Embase, CNKI, WanFang, CBM, and VIP were searched from inception to February 2023 using combinations of subject words and free words. The methodological quality of all the selected studies was assessed using the Joanna Briggs Institute Critical Appraisal of Epidemiological Studies Checklist and Newcastle‒Ottawa Cohort Quality Assessment Scale. Random effects meta-analysis was used to pool estimates from different studies. Subgroup analysis and meta-regression were performed to explore potential sources of heterogeneity.

RESULTS

Of the 4,190 documents retrieved, 16 observational studies involving 2,446 participants from 8 countries were included in this systematic review. Among older adults receiving MHD, the overall prevalence of frailty and prefrailty was 41% (95% CI = 34-49%) and 37% (95% CI = 26-48%), respectively, with considerable heterogeneity. The pooled prevalence of frailty was greater among individuals aged > 70 years (45%) than among those aged ≤ 70 years (37%). However, subgroup analyses indicated that the confidence intervals for the age group overlap substantially.

CONCLUSION

Our research showed that the prevalence of frailty and prefrailty in older patients with MHD are high.

TRIAL REGISTRATION

The PROSPERO registration number for this study was CRD42023442569.

Prevalence and risk factors of frailty in older adults with diabetes: A systematic review and meta-analysis

OBJECTIVE

This systematic review and meta-analysis aimed to evaluate the prevalence of frailty and pre-frailty in older adults with diabetes; and to identify the risk factors associated with frailty in this population.

DESIGN

Systematic review and meta-analysis.

PARTICIPANTS

24,332 people aged 60 years and older with diabetes.

METHODS

Six databases were searched (PubMed, Embase, the Cochrane Library, Web of Science, China Knowledge Resource Integrated Database, and Chinese Biomedical Database) up to 15 January 2024. Random effects models were used in instances of significant heterogeneity. Subgroup analysis and meta-regression were conducted to identify the potential source of heterogeneity. The Agency for Healthcare Research and Quality (AHRQ) and the Newcastle-Ottawa Scale (NOS) were applied to assess the quality of included studies.

RESULTS

3,195 abstracts were screened, and 39 full-text studies were included. In 39 studies with 24,332 older people with diabetes, the pooled prevalence of frailty among older adults with diabetes was 30.0% (95% CI: 23.6%-36.7%). Among the twenty-one studies involving 7,922 older people with diabetes, the pooled prevalence of pre-frailty was 45.1% (95% CI: 38.5%-51.8%). The following risk factors were associated with frailty among older adults with diabetes: older age (OR = 1.08, 95% CI: 1.04-1.13, p<0.05), high HbA1c (OR = 2.14, 95% CI: 1.30-3.50, p<0.001), and less exercise (OR = 3.11, 95% CI: 1.36-7.12, p<0.001).

CONCLUSIONS

This suggests that clinical care providers should be vigilant in identifying frailty and risk factors of frailty while screening for and intervening in older adults with diabetes. However, there are not enough studies to identify comprehensive risk factors of frailty in older adults with diabetes.

TRIAL REGISTRATION

PROSPERO registration number: CRD42023470933.

Frailty Detection in Older Adults with Diabetes: A Scoping Review of Assessment Tools and Their Link to Key Clinical Outcomes

Objectives: With the increasing prevalence of diabetes and frailty among older adults, there is an urgent need for precision medicine that incorporates comprehensive geriatric assessments, including frailty detection. This scoping review aims to map and synthesize the available evidence on validated tools for detecting pre-frailty and frailty in community-dwelling elderly individuals with diabetes and outpatient diabetes patients. Specifically, it addresses: (1) What validated tools are available for detecting pre-frailty and frailty in this population? (2) How are these tools associated with outcomes such as glycemic control, hypoglycemia, and metabolic phenotypes? (3) What gaps exist in the literature regarding these tools? Methods: The review followed PRISMA-ScR guidelines, conducting a systematic search across PubMed, Cochrane Library, and Web of Science. The inclusion criteria focused on studies involving individuals aged 70 years and older with diabetes, emphasizing tools with predictive capacity for disability and mortality. Results: Eight instruments met the inclusion criteria, including the Frailty Index, Physical Frailty Phenotype, and Clinical Frailty Scale. These tools varied in domains such as physical, psychological, and social aspects of frailty and their association with glycemic control, hypoglycemia, and metabolic phenotypes. The review identified significant gaps in predicting diabetes-related complications and their clinical application. Conclusions: Routine management of older adults with diabetes should incorporate frailty detection, as it is crucial for their overall health. Although widely used, the reviewed tools require refinement to address the unique characteristics of this population. Developing tailored instruments will enhance precision medicine, leading to more effective, individualized interventions for elderly individuals with diabetes.

Long-term changes in frailty and incident type 2 diabetes: A prospective cohort study based on the UK Biobank

AIMS

To estimate the association between long-term changes in frailty and the risk of incident type 2 diabetes (T2DM) and to evaluate the effect of preventing the worsening of frailty on the risk of T2DM.

METHODS

We included 348 205 participants free of baseline T2DM and with frailty phenotype (FP) data from the UK Biobank; among them, 36 175 had at least one follow-up assessment. According to their FP score, participants were grouped into nonfrailty, prefrailty and frailty groups. Frailty assessed at baseline and at follow-up was used to derive the trajectory of frailty (ΔFP). Cox regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs).

RESULTS

Compared with those in the nonfrailty group at baseline, the HRs of T2DM for the prefrailty and frailty groups were 1.38 (95% CI 1.33-1.43) and 1.69 (95% CI 1.59-1.79), respectively (both p < 0.001), in the multivariable-adjusted model. During a median follow-up of 5.4 years after the final assessment, data for 472 T2DM patients were recorded. A 1-point increase in the final FP was associated with a 25% (95% CI 1.14-1.38; p < 0.001) increased risk of T2DM. For the trajectory of frailty, each 0.5-point/year increase in ΔFP was associated with a 52% (95% CI 1.18-1.97; p < 0.001) greater risk of T2DM, independent of the FP score at baseline. Compared with those that remained in the nonfrailty group, the greatest risk of T2DM over time was prefrailty aggravation (HR 3.03, 95% CI 2.00-4.58; p < 0.001). Using the frailty index did not materially change the results.

CONCLUSIONS

Long-term changes in frailty were associated with the risk of incident T2DM, irrespective of baseline frailty status. Preventing the worsening of frailty may reduce T2DM risk.

Long-term insulin resistance is associated with frailty, frailty progression, and cardiovascular disease

BACKGROUND

Insulin resistance and diabetes are associated with an increased risk of frailty, and frailty is associated with cardiovascular disease and premature mortality. We aim to investigate the impact of long-term insulin resistance trajectories on future frailty and cardiovascular risk among young adults.

METHODS

In total, 3168 participants with a 30-year follow-up period. The baseline period covered the first 15 years as the exposure period. Insulin resistance was determined using the homeostasis model assessment for insulin resistance (HOMA-IR), and three trajectories (low, moderate, and high) were constructed. The subsequent 15 years constituted the event accrual period. Frailty was assessed using a deficit accumulation mode, and cardiovascular outcomes were obtained from the 15-year event accrual period.

RESULTS

The mean age of all 3168 participants was 41.0 (37.0-43.0) years, with 1750 (55.2%) being women. Participants in the high level of insulin resistance trajectory had an increased prevalence of frailty (OR: 1.55, 95% CI: 1.05-2.30, P = 0.028). Although no statistically significant associations were observed after full adjustment, single-factor analysis indicated association between the moderate and high trajectories and frailty progression. Additionally, participants with high level of insulin resistance trajectory were associated with an increased risk of cardiovascular disease, coronary heart disease, and stroke. A notable correlation between HOMA-IR trajectory and cardiovascular diseases was still discernible within the subgroup where the frailty index ≥0.12 (HR: 2.12, 95% CI: 1.17-3.83, P = 0.013) (P for interaction >0.05).

CONCLUSIONS

Long-term high level of insulin resistance is associated with high prevalence of frailty, and an increased risk of cardiovascular events. Emphasizing the importance of early prevention and intervention for abnormal glucose metabolism in young adults to prevent frailty and cardiovascular disease.

Heart Failure With Preserved Ejection Fraction and Frailty: From Young to Superaged Coexisting HFpEF and Frailty

Being commonly diagnosed in elderly women and associated with comorbidities as well as ageing-related cardio-vascular changes, heart failure with preserved ejection fraction (HFpEF) has been recently considered as a distinct cardiogeriatric syndrome. Frailty is another frequent geriatric syndrome. HFpEF and frailty share common underlying mechanisms, often co-exist, and represent each other's risk factors. A threshold of 65 years old is usually used to screen patients for both frailty and HFpEF in research and clinical settings. However, both HFpEF and frailty are very heterogenous conditions that may develop at younger ages. In this review we aim to provide a broader overview on the coexistence of HFpEF and frailty throughout the lifetime. We hypothesize that HFpEF and frailty patients' profiles (young, elderly, superaged) represent a continuum of the common ageing process modified by cumulative exposure to risk factors resulting to a presentation of HFpEF and frailty at different ages. We believe, that suggested approach might stimulate assessment of frailty in HFpEF assessment and vice versa regardless of age and early implementation of targeted interventions. Future studies of pathophysiology, clinical features, and outcomes of frailty in HFpEF by age are needed.

Diabetes mellitus and hard braking events in older adult drivers

BACKGROUND

Diabetes mellitus (DM) can impair driving safety due to hypoglycemia, hyperglycemia, diabetic peripheral neuropathy, and diabetic eye diseases. However, few studies have examined the association between DM and driving safety in older adults based on naturalistic driving data.

METHODS

Data for this study came from a multisite naturalistic driving study of drivers aged 65-79 years at baseline. Driving data for the study participants were recorded by in-vehicle recording devices for up to 44 months. We used multivariable negative binomial modeling to estimate adjusted incidence rate ratios (aIRRs) and 95% confidence intervals (CIs) of hard braking events (HBEs, defined as maneuvers with deceleration rates ≥ 0.4 g) associated with DM.

RESULTS

Of the 2856 study participants eligible for this analysis, 482 (16.9%) reported having DM at baseline, including 354 (12.4%) insulin non-users and 128 (4.5%) insulin users. The incidence rates of HBEs per 1000 miles were 1.13 for drivers without DM, 1.15 for drivers with DM not using insulin, and 1.77 for drivers with DM using insulin. Compared to drivers without DM, the risk of HBEs was 48% higher for drivers with DM using insulin (aIRR 1.48; 95% CI: 1.43, 1.53).

CONCLUSION

Older adult drivers with DM using insulin appear to be at increased proneness to vehicular crashes. Driving safety should be taken into consideration in DM care and management.

Frailty and Parkinson's disease: the role of diabetes mellitus

Parkinson's disease (PD) is a chronic neurodegenerative disease associated with a progressive loss of dopaminergic neurons, clinically characterized by motor and non-motor signs. Frailty is a clinical condition of increased vulnerability and negative health outcomes due to the loss of multiple physiological reserves. Chronic hyperglycemia and insulin resistance, which characterize diabetes mellitus (DM), have been reported to alter dopaminergic activity, increase the risk of PD, and influence the development of frailty. Even though diabetes may facilitate the development of frailty in patients with PD, this relationship is not established and a revision of the current knowledge is necessary. Furthermore, the synergy between DM, PD, and frailty may drive clinical complexity, worse outcomes, and under-representation of these populations in the research. In this review, we aimed to discuss the role of diabetes in the development of frailty among patients with PD. We summarized the clinical characteristics and outcomes of patients with concomitant DM, PD, and frailty. Finally, interventions to prevent frailty in this population are discussed.

Associations that Cardiorespiratory Fitness and Body Mass Index Loss Have with Deficit Accumulation Frailty

INTRODUCTION/PURPOSE

Lower cardiorespiratory fitness and obesity may accelerate aging processes. The degree to which changes in fitness and body mass index (BMI) may alter the rate of aging may be important for planning treatment. We assessed cross-sectional and longitudinal associations that cardiorespiratory fitness and BMI had with a deficit accumulation frailty index (FI).

METHODS

Fitness, based on standardized graded exercise tests, and weight to calculate BMI at baseline and year 4 were collected from 3944 participants aged 45-76 yr in the Action for Health in Diabetes (Look AHEAD) randomized controlled clinical trial. A validated 38-item deficit accumulation FI was used as a marker of aging. Associations between baseline and changes in fitness and BMI with changes in FI were assessed using linear models.

RESULTS

Both baseline and 4-yr changes in fitness and BMI were independently associated with 4-yr changes in frailty (all P < 0.001). Mean (95% confidence interval) changes in FI ranged from -0.019 (-0.024, -0.013) for participants in the group with the greatest fitness increase and BMI loss to 0.029 (0.024, 0.034) for participants in the group with the greatest fitness loss and BMI gain. Associations of 4-yr changes in fitness and BMI with FI changes were similar across subgroups based on age, sex, baseline BMI, diabetes duration, and cardiovascular disease history. Increased fitness across 4 yr was associated with less FI accumulation independent of baseline fitness.

CONCLUSIONS

Adults with type 2 diabetes and overweight or obesity may slow aging processes captured by an FI by increasing their cardiorespiratory fitness and losing weight.

Structural determinants and cardiometabolic typologies related to frailty in community-dwelling older adults

Frailty is a geriatric syndrome linked to adverse outcomes. Co-occurring cardiometabolic factors increase frailty risk; however, their distinct combinations (typologies) associated with frailty are unclear. We aimed to identify subgroups of older adults with distinct cardiometabolic typologies and characterize their relationship with structural determinants and frailty to inform tailored approaches to prevent and delay frailty. This study was cross-sectional design and included 7984 community-dwelling older adults (65+ years) enrolled in the Health and Retirement Study (2006 and 2008). Latent class analysis was performed using seven cardiometabolic indicators (abdominal obesity, obesity, low high-density lipoprotein; and elevated blood pressure, blood sugar, total cholesterol, C-reactive protein). Frailty was indicated by ≥3 features (weakness, slowness, fatigue, low physical activity, unintentional weight loss). Logistic regression was used to examine the relationship between structural determinants (gender, race/ethnicity, and education), cardiometabolic typologies, and frailty. Three cardiometabolic subgroups were identified: insulin-resistant (n = 3547), hypertensive dyslipidemia (n = 1246), and hypertensive (n = 3191). Insulin-resistant subgroup members were more likely to be female, non-Hispanic Black, and college non-graduates; hypertensive dyslipidemia subgroup members were more likely to be non-Hispanic Others and report high school education; and hypertensive subgroup members were more likely to be male and college educated (p≤.05). Frailty risk was higher for females, Hispanic or Non-Hispanic Black older adults, and those with lower education (p≤.001). Frailty risk was greater in the insulin-resistant compared to the other subgroups (both aOR=2.0, both p<.001). Findings highlight a need to design tailored interventions targeting cardiometabolic typologies to prevent and delay frailty.

Frailty and risk of microvascular disease in adults with prediabetes

BACKGROUND AND AIMS

To assess the relationship between frailty phenotypes and the risk of MVD among prediabetics in two prospective cohorts.

METHODS

The study included 66,068 and 226 participants with prediabetes from the UK Biobank (UKB) and Chinese Ocular Imaging Project (COIP) in Guangzhou, China, respectively. Frailty was evaluated using the Fried phenotype, which includes weight loss, fatigue, low grip strength, low physical activity, and slow walking pace. The outcome was incident microvascular diseases, including diabetic retinopathy, nephropathy, and neuropathy in UKB, and decline rate of retinal capillary density in COIP. Cox models were used to calculate hazard ratios (HRs) and 95 % confidential intervals (CIs), and mixed linear model was used to determine the β and 95 % CIs.

RESULTS

At baseline, 27,491 (41.6 %) and 3332 (5.0 %) prediabetics were classified as pre-frail and frail, respectively in UKB. During a median follow-up of 8.9 years, 3784 cases of incident microvascular diseases were identified. Pre-frailty and frailty were significantly associated with a higher risk of microvascular diseases (HR 1.21 [1.12, 1.30] for pre-frailty; HR 1.60 [1.42, 1.81] for frailty). Compared to no frailty, the adjusted HRs for frailty were 1.42 (0.73, 2.76) for retinopathy, 1.49 (1.31, 1.70) for nephropathy, and 2.37 (1.69, 3.33) for neuropathy. Fatigue and walking pace were the strongest mediators of frailty and microvascular diseases. In the COIP, the lowest handgrip strength group exhibited 62%-63 % faster annually decline in retinal capillary density compared with the highest group (all P<0.05).

CONCLUSIONS

Each frailty point is important for prediabetics because both pre-frailty and frailty phenotypes are strongly associated with an increased risk of microvascular diseases and its subtypes. Lower handgrip strength presents with faster decline in retinal capillary density.

Associations between modifiable risk factors and frailty: a Mendelian randomisation study

BACKGROUND

Early identification of modifiable risk factors is essential for the prevention of frailty. This study aimed to explore the causal relationships between a spectrum of genetically predicted risk factors and frailty.

METHODS

Univariable and multivariable Mendelian randomisation (MR) analyses were performed to explore the relationships between 22 potential risk factors and frailty, using summary genome-wide association statistics. Frailty was accessed by the frailty index.

RESULTS

Genetic liability to coronary artery disease (CAD), type 2 diabetes mellitus (T2DM), ischaemic stroke, atrial fibrillation and regular smoking history, as well as genetically predicted 1-SD increase in body mass index, systolic blood pressure, diastolic blood pressure, low-density lipoprotein cholesterol, triglycerides, alcohol intake frequency and sleeplessness were significantly associated with increased risk of frailty (all p<0.001). In addition, there was a significant inverse association between genetically predicted college or university degree with risk of frailty (beta -0.474; 95% CI (-0.561 to -0.388); p<0.001), and a suggestive inverse association between high-density lipoprotein cholesterol level with risk of frailty (beta -0.032; 95% CI (-0.055 to -0.010); p=0.004). However, no significant causal associations were observed between coffee consumption, tea consumption, serum level of total testosterone, oestradiol, 25-hydroxyvitamin D, C reactive protein or moderate to vigorous physical activity level with frailty (all p>0.05). Results of the reverse directional MR suggested bidirectional causal associations between T2DM and CAD with frailty.

CONCLUSIONS

This study provided genetic evidence for the causal associations between several modifiable risk factors with lifetime frailty risk. A multidimensional approach targeting these factors may hold a promising prospect for prevention frailty.

Long-term Impact of a 10-Year Intensive Lifestyle Intervention on a Deficit Accumulation Frailty Index: Action for Health in Diabetes Trial

BACKGROUND

Multidomain lifestyle interventions may slow aging as captured by deficit accumulation frailty indices; however, it is unknown whether benefits extend beyond intervention delivery.

METHODS

We developed a deficit accumulation frailty index (FI-E) to span the 10 years that the Action for Health in Diabetes (Look AHEAD) randomized controlled clinical trial delivered interventions (a multidomain lifestyle intervention focused on caloric restriction, increased physical activity, and diet compared to a control condition) and to extend across an additional 8 years post-delivery. The study cohort included 5 145 individuals, aged 45-76 years at enrollment, who had type 2 diabetes and either obesity or overweight.

RESULTS

Overall, FI-E scores were relatively lower among lifestyle participants throughout follow-up, averaging 0.0130 [95% confidence interval: 0.0104, 0.0156] (p < .001) less across the 18 years. During Years 1-8, the mean relative difference between control and lifestyle participants' FI-E scores was 0.0139 [0.0115, 0.0163], approximately 10% of the baseline level. During Years 9-18, this average difference was 0.0107 [0.0066, 0.0148]. Benefits were comparable for individuals grouped by baseline age and body mass index and sex but were not evident for those entering the trial with a history of cardiovascular disease.

CONCLUSIONS

Multidomain lifestyle intervention may slow biological aging long term, as captured by an FI-E. Clinical Trials Registration Number: NCT00017953.

[Study of the links between type 2 diabetes and geriatric criteria]

Type 2 diabetes in the elderly remains a major concern for all healthcare professionals and is itself considered a "global pandemic". Its prevalence is high and will continue to increase in years to come, becoming more and more prevalent in the elderly and very elderly. We offer a general summary of the work focusing on the links between type 2 diabetes and geriatric criteria.

The outcome of frailty in older people with diabetes as a function of glycaemic control and hypoglycaemic therapy: a review

INTRODUCTION

Frailty is an emerging and newly recognized complication of diabetes in older people. However, frailty is not thoroughly investigated in diabetes outcome studies.

AREAS COVERED

This manuscript reviews the effect of glycemic control and hypoglycemic therapy on the incidence of frailty in older people with diabetes.

EXPERT OPINION

Current studies show that both low glycemia and high glycemia are associated with frailty. However, most of the studies, especially low glycemia studies, are cross-sectional or retrospective, suggesting association, rather than causation, of frailty. In addition, frail patients in the low glycemia studies are characterized by lower body weight or lower body mass index (BMI), contrary to those in the high glycemia studies, who are either overweight or obese. This may suggest that frailty has a heterogeneous metabolic spectrum, starting with an anorexic malnourished (AM) phenotype at one end, which is associated with low glycemia and a sarcopenic obese (SO) phenotype on the other end, which is associated with high glycemia. The current little evidence suggests that poor glycemic control increases the risk of frailty, but there is a paucity of evidence to suggest that tight glycemic control would reduce the risk of incident frailty. Metformin is the only well-studied hypoglycemic agent, so far, to have a protective effect against frailty independent of glycemic control in the non-frail older people with diabetes. However, once frailty is developed, the choice of the best hypoglycemic agent for these patients will be affected by the metabolic phenotype of frailty. For example, sodium glucose transporter-2 (SGLT-2) inhibitors and glucagon-like peptide-1 receptor agonists (GLP-1RA) are appropriate in the SO phenotype due to their weight losing properties, while insulin therapy may be considered early in the AM phenotype due to its anabolic and weight gaining benefits. Future studies are still required to further investigate the metabolic effects of frailty on older people with diabetes, determine the most appropriate HbA1c target, and explore the most suitable hypoglycemic agent in each metabolic phenotype of frailty.

Diagnostic accuracy of the FRAIL scale for frailty screening in community-dwelling older adults with diabetes: A cross-sectional study

There is limited evidence on the diagnostic accuracy of the FRAIL scale in community-dwelling older adults with diabetes. This study aimed to validate the diagnostic accuracy and determine the optimal cutoff point of the FRAIL scale in community-dwelling older adults with diabetes using the Fried Frailty Phenotype as the reference standard. A total of 489 community-dwelling older adults with diabetes aged 60 or above were recruited in this cross-sectional study. The FRAIL scale showed good diagnostic accuracy for frailty screening. The optimal cutoff point for frailty screening in older adults with diabetes was 2. The agreement between the FRAIL scale and the Fried Frailty Phenotype was substantial. The FRAIL scale classified more participants as frail (29.24%) than the Fried Frailty Phenotype (22.09%). These findings provide evidence that the FRAIL scale is a valid tool that can be applied to community-dwelling older adults with diabetes.

Metabolic Characteristics of Frail Older People with Diabetes Mellitus-A Systematic Search for Phenotypes

Frailty in older people with diabetes is viewed as one homogeneous category. We previously suggested that frailty is not homogeneous and spans across a metabolic spectrum that starts with an anorexic malnourished (AM) frail phenotype and ends with a sarcopenic obese (SO) phenotype. We aimed to investigate the metabolic characteristics of frail older people with diabetes reported in the current literature to explore whether they fit into two distinctive metabolic phenotypes. We performed systematic review of studies published over the last 10 years and reported characteristics of frail older people with diabetes mellitus. A total of 25 studies were included in this systematic review. Fifteen studies reported frail patients' characteristics that could fit into an AM phenotype. This phenotype is characterised by low body weight, increased prevalence of malnutrition markers such as low serum albumin, low serum cholesterol, low Hb, low HbA1c, and increased risk of hypoglycaemia. Ten studies reported frail patients' characteristics that describe a SO phenotype. This phenotype is characterised by increased body weight, increased serum cholesterol, high HbA1c, and increased blood glucose levels. Due to significant weight loss in the AM phenotype, insulin resistance decreases, leading to a decelerated diabetes trajectory and reduced hypoglycaemic agent use or deintensification of therapy. On the other hand, in the SO phenotype, insulin resistance increases leading to accelerated diabetes trajectory and increased hypoglycaemic agent use or intensification of therapy. Current literature suggests that frailty is a metabolically heterogeneous condition that includes AM and SO phenotypes. Both phenotypes have metabolically distinctive features, which will have a different effect on diabetes trajectory. Therefore, clinical decision-making and future clinical studies should consider the metabolic heterogeneity of frailty.

An Examination of Whether Diabetes Control and Treatments Are Associated With Change in Frailty Index Across 8 Years: An Ancillary Exploratory Study From the Action for Health in Diabetes (Look AHEAD) Trial

OBJECTIVE

The aim of this study was to describe cross-sectional and longitudinal associations between glycated hemoglobin (HbA1c) levels and strategies to control type 2 diabetes with baseline levels and 8-year changes in a deficit accumulation frailty index (FI), a commonly used marker of biological aging.

RESEARCH DESIGN AND METHODS

We conducted exploratory analyses from 4,169 participants, aged 45-76 years, who were followed in the Action for Health in Diabetes (Look AHEAD) randomized controlled clinical trial, pooling data across intervention groups. We related baseline and 8-year levels of HbA1c with FI scores using analyses of variance and covariance. Associations between 8-year changes in FI and the use of diabetes medication classes and weight changes were assessed with control for HbA1c levels. Inverse probability weighting was used to assess bias associated with differential follow-up.

RESULTS

Baseline and average HbA1c levels over time of <7%, as compared with ≥8%, were associated with less increase in FI scores over 8 years (both P ≤ 0.002). After adjustment for HbA1c, use of metformin and weight loss >5% were independently associated with slower increases in frailty.

CONCLUSIONS

Lower HbA1c levels among individuals with diabetes are associated with slower biological aging as captured by a deficit accumulation FI. Strategies to control diabetes through weight loss or metformin use may also slow aging.

Metabolic Impact of Frailty Changes Diabetes Trajectory

Diabetes mellitus prevalence increases with increasing age. In older people with diabetes, frailty is a newly emerging and significant complication. Frailty induces body composition changes that influence the metabolic state and affect diabetes trajectory. Frailty appears to have a wide metabolic spectrum, which can present with an anorexic malnourished phenotype and a sarcopenic obese phenotype. The sarcopenic obese phenotype individuals have significant loss of muscle mass and increased visceral fat. This phenotype is characterised by increased insulin resistance and a synergistic increase in the cardiovascular risk more than that induced by obesity or sarcopenia alone. Therefore, in this phenotype, the trajectory of diabetes is accelerated, which needs further intensification of hypoglycaemic therapy and a focus on cardiovascular risk reduction. Anorexic malnourished individuals have significant weight loss and reduced insulin resistance. In this phenotype, the trajectory of diabetes is decelerated, which needs deintensification of hypoglycaemic therapy and a focus on symptom control and quality of life. In the sarcopenic obese phenotype, the early use of sodium-glucose transporter-2 inhibitors and glucagon-like peptide-1 receptor agonists is reasonable due to their weight loss and cardio-renal protection properties. In the malnourished anorexic phenotype, the early use of long-acting insulin analogues is reasonable due to their weight gain and anabolic properties, regimen simplicity and the convenience of once-daily administration.

Frailty Index was Associated With Adverse Outcomes in Admitted Elderly Patients With Type 2 Diabetes Mellitus

We aimed to investigate the role of the laboratory frailty index (LFI) in diabetic complications and incident disability in admitted older patients with type 2 diabetes mellitus (T2DM). We retrospectively collected the clinical data of older patients with T2DM from December 2018 to May 2020. Frailty was quantified using the LFI, which considers the accumulation of 27 items of abnormal laboratory outcomes. Univariate and multivariate analyses were performed to evaluate the relationship between LFI and diabetes-related adverse outcomes. In total, 293 consecutive older patients with T2DM were recruited for this study. According to the predefined LFI criteria, 110 (37.5%) participants were non-frail, 131 (44.7%) were prefrail, and 52 (17.8%) were frail. Univariate and multivariate analysis revealed that LFI was associated with the diabetic microangiopathy complications (odds ratio for prefrail [ORprefrail] 1.760, 95% confidence interval for prefrail [CIprefrail] 1.019-3.041, P = .043; ORfrail 4.667, 95% CIfrail 2.012-10.826, P < .001) and activities of daily living (ADL) disability (ORprefrail 2.323, 95% CIprefrail 1.209-4.463, P = .011; ORfrail 9.367, 95% CIfrail 4.030-21.775, P < .001), but not with the diabetic macroangiopathy complications and diabetic peripheral neuropathy. Frailty, as determined by the LFI, was proven to be an effective tool for the prediction of diabetic microangiopathy complications and ADL disability.

Association of diabetes mellitus with gait and falls in community-dwelling older adults: Serial mediation of vision and cognition

BACKGROUND/OBJECTIVE

Diabetes mellitus (DM) is associated with walking performance, but potential underlying mechanisms of this association remain unclear. The present study aims to disentangle the pathways linking DM to gait and falls through the serial mediation effect of vision and cognition among the older population.

METHODS

Data were taken from wave 9 (2018-2019) of the English Longitudinal Study of Aging (ELSA), including 5496 participants aged 60 years and older. DM was identified based on medical diagnosis and laboratory tests. Vision and falls were self-reported. Cognition was evaluated using questionnaire. Gait speed was measured by the "timed walking test". Serial mediation analysis was performed using Mplus 8.3.

RESULTS

DM was associated with impaired gait speed (c = 0.085, P < 0.05) and falls (c = 0.061, P < 0.05). The serial mediation model revealed that vision and cognition significantly mediated the association of DM with impaired gait speed, with 17.97% and 23.60% of the total effects explained by vision and cognition respectively, and 3.37% explained by the path through vision and then cognition. Similarly, vision and cognition significantly mediated the association of DM with falls, with 14.99% and 6.67% of the total effects explained by vision and cognition respectively, and 1.67% explained by the path through vision and then cognition.

CONCLUSIONS

These findings contribute to deeper understanding of the mechanism underlying the association of DM with walking performance. Evaluation and intervention targeted at vision and the cognition may be beneficial for improving gait or reducing falls in older adults with DM.

Characteristics of frailty phenotype in Chinese nursing home population and significance of motor function indicators in frailty assessment

The objectives of this study were to analyze the distribution characteristics of frailty phenotypes in older adults of Chinese nursing homes, and to compare some motor function characteristics of older adults in nursing homes between frailty and non-frailty, to determine which motor function and frailty are related. This cross-sectional study included 177 older adults living in nursing homes. Frailty was diagnosed by Fried's phenotype, and motor function assessment characteristics (including muscle tone, ROM, and balance) were also evaluated. Chi-square and logistic regression analyses were performed. Frailty prevalence was 53% in nursing homes in big Chinese cities (average age 82.0 ± 6.1). Low levels of physical activity (90.4% in frail elder), decreased handgrip strength (98.9% in frail elder) and slowed walking speed (100% in frail elder) were the 3 main components of the frailty phenotype of frail adults in nursing homes in China. It is worth noting that 74.7% of the non-frail elders also had reduced handgrip strength. Further analysis showed that balance (P < .001), muscle tone (upper, P = .028, lower, P = .001) and the range of motion (P < .001) were associated with frailty in older adults. The frailty of the elders in Chinese nursing homes was characterized by the decline of motor function. And surprisingly, both frail and non-frail elders were found to have poor strength. Frail nursing home seniors also have body muscle tone, range of motion and balance problems. The elderly of China should focus on strength, stretch and balance training to improve motor function, especially strength training, which is important for prevention frailty.

Association Between Physical Exercise Interventions Participation and Functional Capacity in Individuals with Type 2 Diabetes: A Systematic Review and Meta-Analysis of Controlled Trials

Background

The prevalence of type 2 diabetes mellitus increases with age, and people with type 2 diabetes are more affected by reductions in functional performance. Although exercise interventions are recommended for people with diabetes, it is relevant to assess the effects of different training modes on the available functional outcomes. Therefore, our purpose was to systematically assess the effect of different physical exercise modalities in patients with type 2 diabetes with an average age of 45 years or older on outcomes used to measure functional capacity.

Methods

A systematic review and meta-analysis of controlled trials was conducted. Seven databases were searched from January 1987 to December 2021 (PubMed, Physiotherapy Evidence Database, Cochrane Library, SPORTDiscus, and in grey literature: Open Grey and Google Scholar). Eligible studies should last 8 weeks or longer, comparing structured exercise training and non-exercise control for one out of six pre-specified functional capacity outcomes (Timed Up and Go test, chair stands, walking performance, upper-limb muscle strength, lower-limb muscle strength, physical fitness parameter), in patients with type 2 diabetes, aged ≥ 45 years. The risk of bias was assessed with the Downs & Black checklist. Pooled mean differences were calculated using a random-effects model, followed by sensitivity and meta-regression analyses.

Results

Of 18,112 references retrieved, 29 trials (1557 patients) were included. Among these, 13 studies used aerobic training, 6 studies used combined training, 4 studies used resistance training, 3 studies had multiple intervention arms and 3 studies used other types of training. Exercise training was associated with an increase in functional capacity outcomes, as reflected by changes in 6-min walk test (n = 8) [51.6 m; 95% CI 7.6% to 95.6%; I² 92%], one-repetition maximum leg-press (n = 3) [18.0 kg; 95% CI 4.0% to 31.9%; I² 0%], and maximum oxygen consumption (VO_2max) (n = 20) [2.41 mL/kg·min; 95% CI 1.89% to 2.92%; I² 100%] compared with control groups. In sensitivity and subgroup analyses using VO_2max as outcome and stratified by type of study (randomized and non-randomized controlled clinical trials), duration of diabetes diagnosis, and sex, we observed overlapping confidence intervals. Meta-regression showed no association between glycated hemoglobin (HbA1C) levels and VO_2max [p = 0.34; I² 99.6%; R² = 2.6%]. In addition, the quality of the included studies was mostly low.

Conclusion

The results indicate that structured physical exercise programs might improve functional capacity in patients with type 2 diabetes, except for the upper-limb muscle strength. However, we could not identify potential effect predictors associated with directional summary estimates.

Trial registration This systematic review was registered in the PROSPERO international prospective register of systematic reviews (CRD42020162467); date of registration: 12/15/2019. The review protocol is hosted at the Open Science Framework (OSF) (Preprint https://doi.org/10.31219/osf.io/kpg2m).

Supplementary Information

The online version contains supplementary material available at 10.1186/s40798-022-00422-1.

A study on the prevalence and related factors of frailty and pre-frailty in the older population with diabetes in China: A national cross-sectional study

Objective

To investigate the prevalence of frailty and pre-frailty and its associated factors in Chinese older adults with diabetes through a nationwide cross-sectional study.

Research design and methods

The data were obtained from the Sample Survey of the Aged Population in Urban and Rural China (SSAPUR), conducted in 2015, which was a cross-sectional study involving a nationally representative sample of older adults aged 60 years or more from 31 provinces, autonomous regions, and municipalities in mainland China. Subjects with diabetes were included in this study. Frailty index (FI), based on 33 potential deficits, was used to categorize individuals as robust, pre-frail, or frail.

Results

A total of 18,010 older adults with diabetes were included in this study. The weighted prevalence of frailty and pre-frailty in older adults with diabetes in China was 22.7% (95% CI 22.1-23.3%) and 58.5% (95% CI 57.8-59.2%), respectively. The prevalence of frailty and pre-frailty among older adults with diabetes from different provinces/municipalities/autonomous regions was significantly different. Multinomial logistic regression analysis showed living alone, poor economic status, ADL disability, and comorbidities were strongly correlated with frailty and pre-frailty in older adults with diabetes.

Conclusion

Frailty and pre-frailty are common in older adults with diabetes in China, and exhibit sociodemographic and geographic differences. In the clinical setting of older adults with diabetes, there is a need to increase awareness of frailty and to advance the early diagnosis and intervention of frailty.

Risk factors of frailty and functional disability in community-dwelling older adults: a cross-sectional analysis of the FREEDOM-LNA cohort study

BACKGROUND

Frailty is a geriatric syndrome associated with disability and negative health outcome. To determine the factors associated with frailty and functional disability in older participants living in community in France. We included 753 community-dwelling old participants with available frailty data at baseline.

RESULTS

Overall, 31.9% were frail, 58.3% were prefrail, and 9.8% were robust. The SMAF (French acronym for Functional Autonomy Measurement System) score was significantly lower (mean ± standard deviation: -25.8 ± 11.2) in frail participants compared to prefrail (-14.3 ± 9.7) or robust participants (-8.1 ± 7.0); 82% of frail older participants had limitation in at least one ADL and 97.5% in at least one IADL compared to 54.2 and 76.8%, respectively of pre-frail and 29.7 and 47.3% of robust participants. Age, depression, impaired cognition and diabetes were significantly associated with higher odds of frailty. These variables were also strongly associated with functional disability. Female gender, polypharmacy, and smoking were additional variables significantly associated with degraded SMAF and/or ADL/IADL.

CONCLUSIONS

This study showed that functional disability increased proportionally to frailty, and depression, cognitive decline and diabetes are modifiable risk factors significantly associated with frailty and functional disability.

Frailty trajectory among community-dwelling middle-aged and older adults in Korea: evidence from the Korean Longitudinal Study of Aging

Background

There is no study on the frailty trajectory including both middle-aged and older people, and the understanding of the long-term frailty trajectory is insufficient. This study aimed to identify the frailty trajectory, subgroups of the frailty trajectory, and the predictors that differentiate these subgroups among community-dwelling middle-aged and older adults.

Methods

The participants were 9,775 individuals aged 45 years and older who participated in the Korean Longitudinal Study of Aging (2006–2018). Frailty was measured using a frailty instrument comprising three items: grip strength weakness, exhaustion, and social isolation. Latent growth curve modeling and latent class growth modeling were performed to identify the frailty trajectory and latent classes of the trajectory. Multinomial logistic regression was used to confirm the predictors that classified the latent classes.

Results

Over 12 years, the slope of the frailty trajectory among the participants showed a gradual increase. In addition, there was a difference in the latent class of frailty trajectories among middle-aged and older adults. The middle-aged participants were divided into two groups: maintaining robustness and changing from pre-frailty to robustness. The older adults were divided into three groups: maintaining robustness, maintaining pre-frailty, and changing from the frailty to pre-frailty group. Regular exercise, cognitive dysfunction, and social participation were significant predictors that differentiated each latent class in both middle-aged and older adults; additionally, current smoking and the number of chronic diseases were significant predictors in middle-aged people.

Conclusions

Various subgroups within the frailty trajectory existed among community-dwelling middle-aged and older adults. To reduce frailty, it is necessary to intervene with modifiable factors appropriate for each age group.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-03229-7.

The Association Between Cardiometabolic Risk Factors and Frailty in Older Adults: A Systematic Review

Background and Objectives

Enhanced management and prevention of frailty depend on our understanding of the association between potentially modifiable risk factors and frailty. However, the associations between potentially modifiable cardiometabolic risk factors and frailty are not clear. The purpose of this review was to appraise and synthesize the current evidence examining the associations between the cardiometabolic risk factors and frailty.

Research Design and Methods

Multiple databases, including MEDLINE (via PubMed), Embase (via Elsevier), and Web of Science (via Clarivate), were searched extensively. Studies that examined cardiometabolic risk factors and frailty as main predictors and outcome of interest, respectively, among older adults (≥60 years) were included. The Joanna Briggs Institute critical appraisal tools were used to evaluate the quality of studies. PRISMA (2020) guided this review, and findings were synthesized without meta-analysis. This systematic review was registered in PROSPERO (CRD42021252565).

Results

Twelve studies met the eligibility criteria and were included in the review. Abdominal obesity, hyperglycemia, and multiple co-occurring cardiometabolic risk factors were associated with the increased likelihood of frailty in older adults. There was inconsistency across the studies regarding the associations between dyslipidemia, elevated blood pressure, and frailty.

Discussion and Implications

Understanding the association between cardiometabolic risk factors and frailty can have translational benefits in developing tailored interventions for the prevention and management of frailty. More studies are needed to validate predictive and clinically significant associations between single and specific combinations of co-occurring cardiometabolic risk factors and frailty.

Metabolic phenotypes explain the relationship between dysglycaemia and frailty in older people with type 2 diabetes

BACKGROUND

Dysglycaemia (hyperglycaemia and hypoglycaemia) increase the risk of frailty in older people with diabetes, which appears contradictory. However, the characteristics of patients included in these studies are different and may reflect different metabolic phenotypes of frailty that may explain this apparent contradiction.

AIMS

To review the characteristics of frail patients included in clinical studies that reported an association between dysglycaemia and frailty in order to explore whether there is any metabolic differences in the profile of these patients.

METHODS

A systematic review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) recommendations. Key words around older people, type 2 diabetes mellitus, frailty, hyperglycaemia and low glycaemia were used in the literature search.

RESULTS

Only 8 studies met the inclusion criteria. Four studies investigated the risk of frailty associated with low glycaemia. Two studies showed that hypoglycaemia increased the risk of frailty by 44% (HR 1.60, 95% CI 1.14 to 2.42) and predicted greater level of dependency (p < 0.001), respectively. The other two studies reported that HbA1c inversely correlated with clinical frailty scale (r = -0.31, p < 0.01) and HbA1c < 6.0% was associated with increased risk of disability (3.45, 1.02 to 11.6), respectively. Compared with non-frail patients, those with frailty tended to have lower body weight or body mass index (BMI), have features of malnutrition such as low serum albumin or low total cholesterol and suffer from more comorbidities including dementia. Four studies explored the association of high glycaemia with frailty. Higher HbA1c predicted frailty (OR 1.43, 95% CI 1.045 to 1.97) and positively correlated with Edmonton frail score (r = 0.44, p < 0.001), respectively in two studies. The other two studies found that subjects with HbA1c ≥ 6.5% had the greatest prevalence of frailty (70.3%) and subjects with higher HbA1c at baseline to have a higher frailty level throughout later life, respectively. Compared with non-frail patients, those with frailty tended to have higher body weight, waist circumference and BMI. They also have less physical activity, higher cholesterol level and have more comorbidities.

CONCLUSIONS

Dysglycaemia increases the risk of frailty but the characteristics of patients in these studies suggest different metabolic phenotypes of frailty. Therefore, these metabolic differences in frailty should be taken into consideration in the management of older people with diabetes.

Longitudinal changes of frailty in 8 years: comparisons between physical frailty and frailty index

Background

Few studies have made longitudinal comparisons between frailty phenotype (FP) and frailty index (FI) changes. We aimed to investigate frailty status changes defined by FP and FI concurrently, and to compare the associated factors and incident disability among different combination of FI and FP trajectory groups.

Methods

Data on respondents aged over 50 who completed the 1999, 2003 and 2007 Taiwan Longitudinal Study on Aging (TLSA) surveys (n = 2807) were excerpted. Changes of FI, FP and major time-dependent variables were constructed by group-based trajectory modeling. Logistic regression was used to investigate the associated factors and relationships with incident disability among different frailty trajectories.

Results

We identified four FP trajectories – stably robust, worsened frailty, improved frailty, and stably frail and three FI trajectories – stable FI, moderate increase FI and rapid increase FI. Lower self-rated health, mobility impairment, and depressed mood were associated with unfavorable FP and FI changes (all p < 0.001). Regardless of FP trajectory groups, the moderate and rapid increase FI group had significantly more comorbidities than the stable FI group, and more visual, hearing, oral intake impairment, more difficulty in meeting living expenses, and poorer cognitive function in ≥65-year-olds (all p < 0.05). In addition, the worsened frailty, improved frailty, and stably frail groups had ORs for incident disability of 10.5, 3.0, and 13.4, respectively, compared with the stably robust group (all p < 0.01); the moderate and rapid increase FI groups had 8.4-fold and 77.5-fold higher risk than the stable FI group (both p < 0.001). When combining FI and FP trajectories, risk increased with FI trajectory steepness, independent of FP change (all p < 0.01 in rapid increase FI vs stable FI).

Conclusions

Four FP trajectories (stably robust, worsened frailty, improved frailty, and stably frail) and three FI trajectories (stable FI, moderate increase FI and rapid increase FI) were identified. Lower self-rated health, mobility impairment, and depressed mood were associated with both unfavorable FP and FI trajectories. Nevertheless, even for individuals in stably robust or improved frailty FP groups, moderate or rapid increase in FI, either due to comorbidities, sensory impairment, cognitive deficits, or financial challenges, may still increase the risk of incident disability.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-021-02665-1.

Normal to enhanced intrinsic mitochondrial respiration in skeletal muscle of middle- to older-aged women and men with uncomplicated type 1 diabetes

AIMS/HYPOTHESIS

This study interrogated mitochondrial respiratory function and content in skeletal muscle biopsies of healthy adults between 30 and 72 years old with and without uncomplicated type 1 diabetes.

METHODS

Participants (12 women/nine men) with type 1 diabetes (48 ± 11 years of age), without overt complications, were matched for age, sex, BMI and level of physical activity to participants without diabetes (control participants) (49 ± 12 years of age). Participants underwent a Bergström biopsy of the vastus lateralis to assess mitochondrial respiratory function using high-resolution respirometry and citrate synthase activity. Electron microscopy was used to quantify mitochondrial content and cristae (pixel) density.

RESULTS

Mean mitochondrial area density was 27% lower (p = 0.006) in participants with type 1 diabetes compared with control participants. This was largely due to smaller mitochondrial fragments in women with type 1 diabetes (-18%, p = 0.057), as opposed to a decrease in the total number of mitochondrial fragments in men with diabetes (-28%, p = 0.130). Mitochondrial respiratory measures, whether estimated per milligram of tissue (i.e. mass-specific) or normalised to area density (i.e. intrinsic mitochondrial function), differed between cohorts, and demonstrated sexual dimorphism. Mass-specific mitochondrial oxidative phosphorylation (OXPHOS) capacity with the substrates for complex I and complex II (C_I + II) was significantly lower (-24%, p = 0.033) in women with type 1 diabetes compared with control participants, whereas mass-specific OXPHOS capacities with substrates for complex I only (pyruvate [C_{I pyr}] or glutamate [C_{I glu}]) or complex II only (succinate [C_{II succ}]) were not different (p > 0.404). No statistical differences (p > 0.397) were found in mass-specific OXPHOS capacity in men with type 1 diabetes compared with control participants despite a 42% non-significant increase in C_{I glu} OXPHOS capacity (p = 0.218). In contrast, intrinsic C_I + II OXPHOS capacity was not different in women with type 1 diabetes (+5%, p = 0.378), whereas in men with type 1 diabetes it was 25% higher (p = 0.163) compared with control participants. Men with type 1 diabetes also demonstrated higher intrinsic OXPHOS capacity for C_{I pyr} (+50%, p = 0.159), C_{I glu} (+88%, p = 0.033) and C_{II succ} (+28%, p = 0.123), as well as higher intrinsic respiratory rates with low (more physiological) concentrations of either ADP, pyruvate, glutamate or succinate (p < 0.012). Women with type 1 diabetes had higher (p < 0.003) intrinsic respiratory rates with low concentrations of succinate only. Calculated aerobic fitness (Physical Working Capacity Test [PWC₁₃₀]) showed a strong relationship with mitochondrial respiratory function and content in the type 1 diabetes cohort.

CONCLUSIONS/INTERPRETATION

In middle- to older-aged adults with uncomplicated type 1 diabetes, we conclude that skeletal muscle mitochondria differentially adapt to type 1 diabetes and demonstrate sexual dimorphism. Importantly, these cellular alterations were significantly associated with our metric of aerobic fitness (PWC₁₃₀) and preceded notable impairments in skeletal mass and strength.

Relationship between rotating shift work and white blood cell count, white blood cell differential count, obesity, and metabolic syndrome of nurses

This study investigated the relationship between working rotating shifts and white blood cell (WBC) count, WBC differential count (DC), obesity, and metabolic syndrome of nurses. Samples were obtained from a total of 720 nurses who had received health checkups at a large teaching hospital in Taiwan. Among these nurses, 500 worked rotating shifts, and the remaining 220 nurses worked fixed daytime shifts. We used binary logistic regression to identify the risk factors of obesity or metabolic syndrome. The results indicate that nurses working rotating shifts had a significantly higher WBC count than those working fixed daytime shifts. WBC count was an independent factor relating to an overly large waist circumference or overly high body mass index (BMI) of nurses. For every 10³/μL increase in WBC count, the risk of waist circumference exceeding 90 cm and 80 cm respectively in male and female nurses increased by 46%, and for every 10³/μL increase in WBC count, the risk of a BMI 24 kg/m² in nurses increased by 50%. Similarly, WBC count and work type were independent factors influencing the metabolic syndrome of nurses. For every 10³/μL increase in WBC count, the risk of metabolic syndrome occurring in nurses increased by 65%. Nurses working rotating shifts were at a 3.34 times greater risk of having metabolic syndrome than those working fixed daytime shifts. The mean age of our participants was 29.54 years old, and only approximately 4% of the participants had metabolic syndrome. Among these nurses, we found that high WBC was correlated with an overly large waist circumference and overly high BMI. Furthermore, the nurses working rotating shifts may have been at greater risk of metabolic syndrome than those working fixed daytime shifts, and increases in WBC were also associated with the occurrence of metabolic syndrome.

Digital Health Interventions among People Living with Frailty: A Scoping Review

OBJECTIVES

Digital health interventions (DHIs) are interesting resources to improve various health conditions. However, their use in the older and frail population is still sparse. We aimed to give an overview of DHI used in the frail older population.

DESIGN

Scoping review with PRISMA guidelines based on Population, Concept, and Context.

SETTING AND PARTICIPANTS

We included original studies in English with DHI (concept) on people described as frail (population) in the clinical or community setting (context) and no limitation on date of publication. We searched 3 online databases (PubMed, Scopus, and Web of Science).

MEASURES

We described DHI in terms of purpose, delivering, content and assessment. We also described frailty assessment and study design.

RESULTS

We included 105 studies that fulfilled our eligibility criteria. The most frequently reported DHIs were with the purpose of monitoring (45; 43%), with a delivery method of sensor-based technologies (59; 56%), with a content of feedback to users (34; 32%), and for assessment of feasibility (57; 54%). Efficacy was reported in 31 (30%) studies and usability/feasibility in 57 (55%) studies. The most common study design was descriptive exploratory for new methodology or technology (24; 23%). There were 14 (13%) randomized controlled trials, with only 4 of 14 studies (29%) showing a low or moderate risk of bias. Frailty assessment using validated scales was reported in only 47 (45%) studies.

CONCLUSIONS AND IMPLICATIONS

There was much heterogeneity among frailty assessments, study designs, and evaluations of DHIs. There is now a strong need for more standardized approaches to assess frailty, well-structured randomized controlled trials, and proper evaluation and report. This work will contribute to the development of better DHIs in this vulnerable population.

Partner loss and its effect on frailty trajectories: results from the 13-year follow-up Survey of Health, Ageing and Retirement in Europe (SHARE)

BACKGROUND

Frailty is a geriatric syndrome closely linked to a variety of adverse health outcomes. Thus, it is important to identify factors associated with the development of frailty. It was the aim of this study to examine, if, and to what extent partner loss, a highly stressful life event, affects frailty trajectories of community dwelling adults aged 50 or older.

METHODS

Using six waves of panel data from the Survey of Health, Ageing and Retirement in Europe (SHARE), we investigated the effect of partner loss on frailty trajectories estimating growth curve models. Our sample included 183 502 observations of 83 494 community-dwelling individuals aged 50 or older from 21 European countries collected between 2004 and 2017. Frailty was measured using the validated sex-specific SHARE-Frailty-Instrument including muscular weakness, unintended weight loss, decrease in walking capacity, low physical activity and exhaustion.

RESULTS

Our sample contained 79 874 participants who lived in a partnership during their entire observational period and 3620 participants who lost their partner during their observational period. Both men (β=0.184 (95% CI: -0.017 to 0.386), p=0.073) and women (β=0.237 (95% CI: 0.106 to 0.369), p<0.001) showed initial effects of partner loss on frailty, but while only women gradually recovered over time (β=-0.023 (95% CI: -0.039 to -0.008), p=0.002), among men, the effect of partner loss persisted (β<0.001 (95% CI: -0.029 to 0.029), p=0.998).

CONCLUSION

This study revealed that partner loss is followed by elevated frailty. However, while women's frailty tended to recover from partner loss over time, men's frailty remained elevated. Notable individual differences in the response of frailty trajectories to partner loss suggest the existence of effect modifiers.

Risk factors associated with frailty in older adults with type 2 diabetes: A cross-sectional study

AIMS AND OBJECTIVES

The aims of the study were to (i) estimate the prevalence of frailty among older adults with type 2 diabetes, and (ii) investigate risk factors associated with frailty in the study group.

BACKGROUND

The high prevalence of frailty among older adults and its adverse health impacts including higher risks for physical disabilities and a higher mortality rate is quickly evolving to become an important public health issue.

DESIGN

A cross-sectional design.

METHODS

Data were collected from the Clinical Diabetes Centre of our study group. Frailty was assessed using the Chinese version of the Tilburg frailty indicator. Other questionnaires included Activities of Daily Living, Mini-Mental State Examination, Taiwan Geriatric Depression Scale and Instrumental Activities of Daily Living. Multivariable logistic regression was established to identify factors associated with frailty. The STrengthening the Reporting of OBservational studies in Epidemiology checklist was used preparing the manuscript.

RESULTS

A total of 248 subjects were recruited in this study, a total of 66 participants had frailty (26.6%). Our results showed that factors including age, number of chronic diseases, cerebrovascular accident, renal diseases, frequency of falling, frequency of hyperglycaemia, Activities of Daily Living, depression, Mini-Mental State Examination, and Instrumental Activities of Daily Living ≧1 task disability were correlated with frailty in older adults with type 2 diabetes. After adjusting for confounding factors, multivariate logistic regression analyses showed a significant increase in the probability of frailty by 1.72-times when comparing type 2 diabetes subjects with depression to those without depression.

CONCLUSION

This study revealed that depression is a significant factor associated with the occurrence of frailty among older adults with type 2 diabetes.

RELEVANCE TO CLINICAL PRACTICE

Our results provided strong clinical evidence showing depression as an important factor associated with the risk of frailty in older individuals with type 2 diabetes. We recommend early detection via routine screenings for symptoms of depression during diabetes care to achieve early prevention or the delay of frailty and its implicated adverse health consequences.

Development and Validation of a Nomogram to Predict Frailty Progression in Nonfrail Chinese Community-Living Older Adults

OBJECTIVE

Frailty state progression is common among older adults, so it is necessary to identify predictors to implement individualized interventions. We aimed to develop and validate a nomogram to predict frailty progression in community-living older adults.

DESIGN

Prospective cohort study.

SETTING AND PARTICIPANTS

A total of 3170 Chinese community-living people aged ≥60 years were randomly assigned to a training set or validation set at a ratio of 6:4.

METHODS

Candidate predictors (demographic, lifestyle, and medical characteristics) were used to predict frailty state progression as measured with the Fried frailty phenotype at a 4-year follow-up, and multivariate logistic regression analysis was conducted to develop a nomogram, which was validated internally with 1000 bootstrap resamples and externally with the use of a validation set. The C index and calibration plot were used to assess discrimination and calibration of the nomogram, respectively.

RESULTS

After a follow-up period of 4 years, 64.1% (917/1430) of the participants in the robust group and 26.0% (453/1740) in the prefrail group experienced frailty progression, which included 9.1% and 21.0%, respectively, who progressed to frailty. Predictors in the final nomogram were age, marital status, physical exercise, baseline frailty state, and diabetes. Based on this nomogram, an online calculator was also developed for easy use. The discriminative ability was good in the training set (C index = 0.861) and was validated using both the internal bootstrap method (C index = 0.861) and an external validation set (C index = 0.853). The calibration plots showed good agreement in both the training and validation sets.

CONCLUSIONS AND IMPLICATIONS

An easy-to-use nomogram was developed with good apparent performance using 5 readily available variables to help physicians and public health practitioners to identify older adults at high risk for frailty progression and implement medical interventions.

Spinal Epidural Abscess Patients Have Higher Modified Frailty Indexes Than Back Pain Patients on Emergency Room Presentation: A Single-Center Retrospective Case-Control Study

OBJECTIVE

Spinal epidural abscess (SEA) patients have increased medical comorbidities and risk factors for infection compared with those without SEA. However, the association between frailty and SEA patients has not been documented.

METHODS

A total of 46 SEA patients were randomly paired and matched by age and sex with a control group of patients with back pain who had presented to our emergency department from 2012 to 2017. Statistical analysis identified the risk factors associated with SEA and frailty using the modified frailty index (mFI), and the patients were stratified into robust, prefrail, and frail groups. We examined the value of the mFI as a prognostic predictor and evaluated the classic risk factors (CRFs).

RESULTS

The SEA patients had higher mFIs and CRFs (P = 0.023 and P < 0.001, respectively) and a longer length of stay (22.89 days vs. 1.72 days; P < 0.001). Of the mFI variables, only diabetes had a significant association with SEA (odds ratio [OR], 3.60; P = 0.012). Among the stratified mFI subgroups, a frail ranking (mFI >2) was the strongest risk factor for SEA (OR, 5.18; P = 0.003). A robust ranking (mFI, 0-1) was a weak negative predictor for SEA (OR, 0.41; P = 0.058). The robust patients were also more likely to be discharged to home (OR, 7.58; P = 0.002). Of the CRF variables, only intravenous drug use had a statistically significant association with SEA (OR, 10.72; P = 0.015).

CONCLUSIONS

Patients with SEA were more frail compared with the control back pain patients. Frailty was determined to be an independent risk factor for SEA, outside of the CRFs. The use of the mFI could be potentially useful in predicting the diagnosis, prognosticating, and guiding SEA treatment.

The prevalence of frailty among community-dwelling older adults with diabetes: A meta-analysis

BACKGROUND

Coexistence of frailty and chronic diseases including diabetes is related to a higher risk of adverse health outcomes. There is an increasing interest in the intersection of diabetes and frailty. Understanding the prevalence of frailty in older adults with diabetes is of great importance. However, estimates of the prevalence of frailty among this population varied widely in the relevant literature.

OBJECTIVES

To conduct a systematic review and meta-analysis to estimate the overall prevalence of frailty and prefrailty among community-dwelling older adults with diabetes, and examine the risk factors associated with frailty in this population.

METHODS

PubMed, Web of Science, Embase, Wiley Cochrane Library, and Cumulative Index of Nursing and Allied Health were searched from inception to May 30th, 2020. Investigators assessed eligibility, extracted data and evaluated methodological quality. The pooled prevalence of frailty and prefrailty was calculated using the random-effects model. Meta-regression analysis and subgroup analysis were conducted to explore sources of heterogeneity.

RESULTS

A total of 32 studies met the inclusion criteria, involving 14,450 individuals. The pooled prevalence of frailty and prefrailty in older adults with diabetes was 20.1% (95% CI = 16.0-24.2%) and 49.1% (95%CI = 45.1-53.1%), respectively, with significant heterogeneity across the studies. Frailty was more prevalent in older adults with diabetes than those without diabetes (OR = 1.61, 95%CI = 1.47-1.77, p < 0.001). The pooled prevalence of frailty was lower in studies using Frailty Phenotype to define frailty (16.3%) and conducted in Asia (14.3%). Female gender and unmarried status were risk factors of frailty among this population.

CONCLUSION

Frailty and prefrailty are common in community-dwelling older adults with diabetes. Early screening of frailty and interventions should be integrated into diabetes care for older adults to prevent and reduce the negative effects of frailty at the community level. Better quality longitudinal research is required to examine the temporal relationship between diabetes and frailty.

Association of weight loss and weight loss maintenance following diabetes diagnosis by screening and incidence of cardiovascular disease and all-cause mortality: An observational analysis of the ADDITION-Europe trial

AIMS

Short-term weight loss may lead to remission of type 2 diabetes but the effect of maintained weight loss on cardiovascular disease (CVD) is unknown. We quantified the associations between changes in weight 5 years following a diagnosis of diabetes, and incident CVD events and mortality up to 10 years after diagnosis.

MATERIALS AND METHODS

Observational analysis of the ADDITION-Europe trial of 2730 adults with screen-detected type 2 diabetes from the UK, Denmark and the Netherlands. We defined weight change based on the maintenance at 5 years of weight loss achieved during the year after diabetes diagnosis, and as 5-year overall change in weight. Incident CVD events (n = 229) and all-cause mortality (n = 225) from 5 to 10 years follow-up were ascertained from medical records.

RESULTS

Gaining >2% weight during the year after diabetes diagnosis was associated with higher hazard of all-cause mortality versus maintaining weight [hazard ratio (95% confidence interval): 3.18 (1.30-7.82)]. Losing ≥5% weight 1 year after diagnosis was also associated with mortality, whether or not weight loss was maintained at 5 years: 2.47 (0.99-6.21) and 2.72 (1.17-6.30), respectively. Losing ≥10% weight over 5 years was associated with mortality among those with body mass index <30 kg/m² [4.62 (1.87-11.42)]. Associations with CVD incidence were inconclusive.

CONCLUSIONS

Both weight loss and weight gain after screen-detected diabetes diagnosis were associated with higher mortality, but not CVD events, particularly among participants without obesity. The clinical implications of weight loss following a diagnosis of diabetes probably depend on its magnitude and timing, and may differ by body mass index status. Personalization of weight loss advice and support may be warranted.

Frailty measurement, prevalence, incidence, and clinical implications in people with diabetes: a systematic review and study-level meta-analysis

Background

Frailty, a state of increased vulnerability to adverse health outcomes, is important in diabetes management. We aimed to quantify the prevalence of frailty in people with diabetes, and to summarise the association between frailty and generic outcomes (eg, mortality) and diabetes-specific outcomes (eg, hypoglycaemia).

Methods

In this systematic review and study-level meta-analysis, we searched MEDLINE, Embase, and Web of Science for observational studies published between Jan 1, 2001 (the year of the original publication of the Fried frailty phenotype), to Nov 26, 2019. We included studies that assessed and quantified frailty in adults with diabetes, aged 18 years and older; and excluded conference abstracts, grey literature, and studies not published in English. Data from eligible studies were extracted using a piloted data extraction form. Our primary outcome was the prevalence of frailty in people with diabetes. Secondary outcomes were incidence of frailty and generic and diabetes-specific outcomes. Data were assessed by random-effects meta-analysis where possible and by narrative synthesis where populations were too heterogeneous to allow meta-analysis. This study is registered with PROSPERO, CRD42020163109.

Findings

Of the 3038 studies we identified, 118 studies using 20 different frailty measures were eligible for inclusion (n=1 375 373). The most commonly used measures of frailty were the frailty phenotype (69 [58%] of 118 studies), frailty (16 [14%]), and FRAIL scale (10 [8%]). Studies were heterogenous in setting (88 studies were community-based, 18 were outpatient-based, ten were inpatient-based, and two were based in residential care facilities), demographics, and inclusion criteria; therefore, we could not do a meta-analysis for the primary outcome and instead summarised prevalence data using a narrative synthesis. Median community frailty prevalence using frailty phenotype was 13% (IQR 9-21). Frailty was consistently associated with mortality in 13 (93%) of 14 studies assessing this outcome (pooled hazard ratio 1·51 [95% CI 1·30-1·76]), with hospital admission in seven (100%) of seven, and with disability in five (100%) of five studies. Frailty was associated with hypoglycaemia events in one study (<1%), microvascular and macrovascular complications in nine (82%) of 11 studies assessing complications, lower quality of life in three (100%) of three studies assessing quality of life, and cognitive impairment in three (100%) of three studies assessing cognitive impairment. 13 (11%) of 118 studies assessed glycated haemoglobin finding no consistent relationship with frailty.

Interpretation

The identification and assessment of frailty should become a routine aspect of diabetes care. The relationship between frailty and glycaemia, and the effect of frailty in specific groups (eg, middle-aged [aged <65 years] people and people in low-income and lower-middle-income countries) needs to be better understood to enable diabetes guidelines to be tailored to individuals with frailty.

Funding

Medical Research Council.

Sleep quality and risk of coronary heart disease - a prospective cohort study from the English longitudinal study of ageing

Background: The association between sleep quality and risk of coronary heart disease (CHD) remains unclear in the elderly.

Results: At eight-year follow up, a total of 411 (4.29%) participants developed CHD. Compared with good quality group, the multivariable hazard ratio [HR] (95% confidence interval [CI]) for CHD was 1.393 (1.005, 1.931) for intermediate quality group and 1.913 (1.206, 3.035) for poor quality group. Consistent results were observed in participants with normal sleep duration.

Conclusions: Poor sleep quality may be a novel modifiable risk factor for CHD in the elderly independent of conventional cardiovascular risk factors, even when sleep duration was normal.

Methods: The current study included 9570 CHD-free participants in the English Longitudinal Study of Ageing (ELSA) from wave 4 (2008 to 2009). Incident CHD included new onset angina or myocardial infarction. Sleep quality was measured by a four-item questionnaire. Score ranged from 1 (best) to 4 (poorest). Participants were divided into three groups: good quality (1 ≤ score <2), intermediate quality (2 ≤ score <3) and poor quality (3 ≤ score ≤4). Cox regression model was used to calculate HR for CHD risk according to sleep quality, adjusted for conventional CHD risk factors and sleep duration.