Search

Background: A link between diabetes mellitus (DM) and heart failure (HF) has been well-recognized for more than a century. HF is also closely linked to abnormal glucose regulation (AGR) and insulin resistance (IR) in patients without DM and, similarly, these conditions commonly coexist. In epidemiological studies, each condition appears to predict the other. The prevalence of AGR/IR in HF patients without DM is significantly underrecognized and, as yet, the optimal method for screening for these abnormalities in the outpatient setting is unclear.Methods and Results: The purpose of this review is to overview the prevalence and prognostic impact of AGR and IR in HF patients without DM and discuss potential pathophysiological pathways that link these conditions with HF. The severity of glucose intolerance in patients with HF correlates with functional and clinical severity of HF and is an independent predictor of an adverse outcome. It is thought that changes in cardiac metabolism, including a switch from glucose metabolism toward fatty acid metabolism, may in part contribute to the pathophysiological processes associated with HF patients with AGR/IR.Conclusions: We discuss how pharmacological targeting of metabolic pathways in the myocardium of these patients with HF may represent novel therapeutic strategies in these at-risk patients. [ABSTRACT FROM AUTHOR]

Hyperglycaemia is associated with a worse prognosis after myocardial infarction and good blood glucose control in the peri-infarct period has been shown to improve outcome. Our primary study was undertaken with the aims of assessing the prevalence and management of hyperglycaemia in patients admitted with acute chest pain. Ninety-three patients admitted to either Coronary Care (CCU) or Emergency Medical Admission Units (EMAU) with chest pain were studied and of these 14 (15%) had severe hyperglycaemia (> 11.0 mmol/L). Blood glucose was not measured in seven (8%) patients and in only 1/14 (7%) patient were established guidelines for the management of hyperglycaemia applied. A revision of management protocol was undertaken and after 18 months we repeated the review of management of hyperglycaemia. Of 114 patients 22 (21%) had severe hyperglycaemia, blood glucose was not measured in ten (9%) and management guidelines were followed in 13 (65%).A major improvement in management of blood glucose in emergency admissions with chest pain has been demonstrated. Further staff education, discussion and review of protocol are indicated to improve and maintain performance on CCU and EMAU. Copyright (c) 2001 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Obesity-induced lipid overload in cardiomyocytes contributes to profound oxidative stress and cardiomyopathy, culminating in heart failure. In this study, we investigate a novel mechanism whereby lipids accumulate in cardiomyocytes, and seek the relevant treatment strategies. P21-activated kinase 3 (PAK3) was elevated in obese human myocardium, and the murine hearts and cardiomyocytes upon diet- or fatty acid-induced stress, respectively. Mice with cardiac-specific overexpression of PAK3 were more susceptible to the development of cardiac dysfunction upon diet stress, at least partially, because of increased deposition of toxic lipids within the myocardium. Mechanistically, PAK3 promoted the nuclear expression of sterol regulatory element binding protein 1c (SREBP1c) through activation of mammalian target of rapamycin (mTOR) and ribosomal protein S6 kinase β-1 (S6K1) pathway in cardiomyocytes, resulting in abnormal lipid genes profile, accumulation of excessive lipids, and oxidative stress. More importantly, PAK3 knockdown attenuated fatty acid-induced lipotoxicity and cell death in rat and human cardiomyocytes. More importantly, the S6K1 or SREBP1c inhibitor alleviated PAK3-triggered intracellular lipid overload and cardiac dysfunction under obese stress. Collectively, we have demonstrated that PAK3 impairs myocardial lipid homeostasis, while inhibition of cardiac lipotoxicity mitigates cardiac dysfunction. Our study provides a promising therapeutic strategy for ameliorating obesity cardiomyopathy., (© 2024 by the American Diabetes Association.)

Light enhances or disrupts circadian rhythms, depending on the timing of exposure. Circadian disruption contributes to poor health outcomes that increase mortality risk. Whether personal light exposure predicts mortality risk has not been established. We therefore investigated whether personal day and night light, and light patterns that disrupt circadian rhythms, predicted mortality risk. UK Biobank participants (N = 88,905, 62.4 ± 7.8 y, 57% female) wore light sensors for 1 wk. Day and night light exposures were defined by factor analysis of 24-h light profiles. A computational model of the human circadian pacemaker was applied to model circadian amplitude and phase from light data. Cause-specific mortality was recorded in 3,750 participants across a mean (±SD) follow-up period of 8.0 ± 1.0 y. Individuals with brighter day light had incrementally lower all-cause mortality risk (adjusted-HR ranges: 0.84 to 0.90 [50 to 70th light exposure percentiles], 0.74 to 0.84 [70 to 90th], and 0.66 to 0.83 [90 to 100th]), and those with brighter night light had incrementally higher all-cause mortality risk (aHR ranges: 1.15 to 1.18 [70 to 90th], and 1.21 to 1.34 [90 to 100th]), compared to individuals in darker environments (0 to 50th percentiles). Individuals with lower circadian amplitude (aHR range: 0.90 to 0.96 per SD), earlier circadian phase (aHR range: 1.16 to 1.30), or later circadian phase (aHR range: 1.13 to 1.20) had higher all-cause mortality risks. Day light, night light, and circadian amplitude predicted cardiometabolic mortality, with larger hazard ratios than for mortality by other causes. Findings were robust to adjustment for age, sex, ethnicity, photoperiod, and sociodemographic and lifestyle factors. Minimizing night light, maximizing day light, and keeping regular light-dark patterns that enhance circadian rhythms may promote cardiometabolic health and longevity., Competing Interests: Competing interests statement:S.W.C. has consulted for Dyson. A.J.K.P. and S.W.C. are co-founders and co-directors of Circadian Health Innovations PTY LTD. A.J.K.P. and S.W.C. have received research funding from Versalux and Delos. S.W.C. has received research funding from Beacon Lighting. P.O. co-founded Axivity Ltd, and was a director until 2015.

Aims/hypothesis: The aim of this study was to investigate how diabetes mellitus affects longer term outcomes in individuals presenting to hospital with non-ST segment elevation myocardial infarction (NSTEMI)., Methods: We analysed data from 456,376 adults hospitalised between January 2005 and March 2019 with NSTEMI from the UK Myocardial Ischaemia National Audit Project (MINAP) registry, linked with Office for National Statistics death reporting. We compared outcomes and quality of care by diabetes status., Results: Individuals with diabetes were older (median age 74 vs 73 years), were more often of Asian ethnicity (13% vs 4%) and underwent revascularisation (percutaneous coronary intervention or coronary artery bypass graft surgery) (38% vs 40%) less frequently than those without diabetes. The mortality risk for those with diabetes compared with those without was significantly higher at 30 days (HR 1.19, 95% CI 1.15, 1.23), 1 year (HR 1.28, 95% CI 1.26, 1.31), 5 years (HR 1.36, 95% CI 1.34, 1.38) and 10 years (HR 1.39, 95% CI 1.36, 1.42). In individuals with diabetes, higher quality inpatient care, assessed by opportunity-based quality indicator (OBQI) score category ('poor', 'fair', 'good' or 'excellent'), was associated with lower mortality rates compared with poor care (good: HR 0.74, 95% CI 0.73, 0.76; excellent: HR 0.69, 95% CI 0.68, 0.71). In addition, compared with poor care, excellent care in the diabetes group was associated with the lowest mortality rates in the diet-treated and insulin-treated subgroups (diet-treated: HR 0.64, 95% CI 0.61, 0.68; insulin-treated: HR 0.69, CI 0.66, 0.72)., Conclusion/interpretation: Individuals with diabetes experience disparities during inpatient care following NSTEMI. They have a higher risk of long-term mortality than those without diabetes, and higher quality inpatient care may lead to better long-term survival., Competing Interests: Data availability: The data underlying this article were provided by the National Institute for Cardiovascular Outcomes Research (NICOR). Data will be shared on request to the corresponding author with the permission of NICOR. Funding: This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. Authors’ relationships and activities: The authors declare that there are no relationships or activities that might bias, or be perceived to bias, their work. Contribution statement: All authors made substantial contributions to the conception or design of the work or the acquisition, analysis or interpretation of data; and drafting or reviewing the article critically for important intellectual content. All authors approved the final version to be published. MAM is responsible for the integrity of the work as a whole., (© 2024. The Author(s).)

Competing Interests: There are no conflicts of interest.

Aims/hypothesis: Both short and long sleep durations have been linked to higher diabetes risk. However, sleep duration may vary over time, and there has been limited research focusing on individual sleep trajectories and diabetes risk. There are substantial racial disparities in both sleep health and diabetes risk in the USA. Thus, it is important to understand the role of suboptimal sleep patterns in diabetes risk in different racial groups., Methods: We assessed long-term trajectories of sleep duration and incident diabetes in 22,285 Black adults (mean age ± SD, 51.1 ± 8.2 years; 64.8% women) and 13,737 White adults (mean age ± SD, 54.4 ± 9.0 years; 63.8% women) enrolled in the Southern Community Cohort Study. Nine sleep trajectories were derived based on self-reported sleep duration at baseline and after a mean of 5 years of follow-up: normal-normal (reference), short-normal, normal-short, short-short, long-normal, normal-long, long-long, long-short and short-long. Diabetes was reported using a validated questionnaire. Multivariable-adjusted logistic regression was used to determine relationships between sleep trajectories and incident diabetes., Results: When compared with the normal-normal trajectory, suboptimal sleep trajectories were associated with higher likelihoods of developing diabetes (OR; 95% CI: short-normal 1.19; 1.09, 1.31; normal-short 1.14; 1.02, 1.27; short-short 1.17; 1.07, 1.28; long-normal 1.13; 0.98, 1.30; normal-long 1.16; 1.00, 1.34; long-long 1.23; 1.02, 1.48; long-short 1.45; 1.19, 1.77; short-long 1.51; 1.28, 1.77). Stratified analyses by race and socioeconomic status (i.e. education and household income) showed that most suboptimal sleep trajectories were consistently associated with incident diabetes in all sociodemographic subgroups. We also noted potential interaction with race and education for several sleep trajectories (i.e. short-long and normal-short with race; long-long and short-short with education)., Conclusions/interpretation: Adults with suboptimal sleep duration trajectories are more likely to develop incident diabetes. Future research is needed to study how sociodemographic factors modulate this relationship., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Objective: To evaluate the association between irregular sleep duration and incident diabetes in a U.K. population over 7 years of follow-up., Research Design and Methods: Among 84,421 UK Biobank participants (mean age 62 years) who were free of diabetes at the time of providing accelerometer data in 2013-2015 and prospectively followed until May 2022, sleep duration variability was quantified by the within-person SD of 7-night accelerometer-measured sleep duration. We used Cox proportional hazard models to estimate hazard ratios (HRs) for incident diabetes (identified from medical records, death register, and/or self-reported diagnosis) according to categories of sleep duration SD., Results: There were 2,058 incident diabetes cases over 622,080 person-years of follow-up. Compared with sleep duration SD ≤ 30 min, the HR (95% CI) was 1.15 (0.99, 1.33) for 31-45 min, 1.28 (1.10, 1.48) for 46-60 min, 1.54 (1.32, 1.80) for 61-90 min, and 1.59 (1.33, 1.90) for ≥91 min, after adjusting for age, sex, and race. We found a nonlinear relationship (P nonlinearity 0.0002), with individuals with a sleep duration SD of >60 vs. ≤60 min having 34% higher diabetes risk (95% CI 1.22, 1.47). Further adjustment for lifestyle, comorbidities, environmental factors, and adiposity attenuated the association (HR comparing sleep duration SD of >60 vs. ≤60 min: 1.11; 95% CI 1.01, 1.22). The association was stronger among individuals with lower diabetes polygenic risk score (PRS; P interaction ≤ 0.0264) and longer sleep duration (P interaction ≤ 0.0009)., Conclusions: Irregular sleep duration was associated with higher diabetes risk, particularly in individuals with a lower diabetes PRS and longer sleep duration., (© 2024 by the American Diabetes Association.)

Introduction: The COVID-19 pandemic disrupted healthcare delivery and increased cardiovascular morbidity and mortality. This study assesses whether cardiovascular mortality rates in the US have recovered post-pandemic and examines the equity of this recovery across different populations., Methods: We analyzed data from the CDC WONDER database, covering US residents' mortality from 2018-2023. We focused on cardiovascular diseases, categorized by ischemic heart disease (IHD), heart failure (HF), hypertensive diseases (HTN), and cerebrovascular disease. Age-adjusted mortality rates were calculated for three periods: pre-COVID (2018-2019), during COVID (2020-2021), and post-COVID (2022-2023), stratified by demographic and geographic variables., Results: Cardiovascular age-adjusted mortality rates increased by 5.9% during the pandemic but decreased by 3.4% post-pandemic, resulting in a net increase of 2.4% compared to pre-COVID levels. When compared to pre COVID age-adjusted mortality rates, post COVID IHD mortality age-adjusted mortality rates decreased by 5.0%, while cerebrovascular and HTN age-adjusted mortality rates increased by 5.9% and 28.5%, respectively. Men and younger populations showed higher increases in cardiovascular Age-adjusted mortality rates. Geographic disparities were notable, with significant reductions in cardiovascular mortality in the Northeast and increases in states like Arizona and Oregon., Conclusion: The COVID-19 pandemic led to a surge in cardiovascular mortality, with partial recovery post-pandemic. Significant differences in mortality changes highlight the need for targeted healthcare interventions to address inequities across demographic and geographic groups., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: KK has acted as a consultant, speaker or received grants for investigator-initiated studies for Astra Zeneca, Bayer, Novartis, Novo Nordisk, Sanofi-Aventis, Lilly and Merck Sharp & Dohme, Boehringer Ingelheim, Oramed Pharmaceuticals, Pfizer, Roche, Daiichi-Sankyo and Applied Therapeutics. SM has received speaker Honoraria from Lilly and Sanofi, UK., (© 2024 The Authors. Published by Elsevier Inc.)

Background: Emerging evidence supports a link between circadian disruption as measured by higher night-to-night variation in sleep duration and increased risk of cardiovascular disease (CVD). It remains unclear whether this association varies by CVD types or may be modified by average sleep duration and genetic risk for CVD., Methods: Our prospective analysis included 86,219 UK Biobank participants who were free from CVD when completing 7 days of accelerometer measurement in 2013-2016. Sleep irregularity was evaluated by the standard deviation (SD) of accelerometer-measured sleep duration over 7 days. Incident major CVD events, defined as fatal or nonfatal myocardial infarction (MI) and stroke, were identified through linkage to Hospital Episode Statistics data until May 31, 2022. Multivariable-adjusted Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% CIs for associations of sleep duration SD with risk for major CVD events overall and for MI and stroke separately., Results: We documented 2,310 incident cases of major CVD events (MI: 1,183, stroke: 1,175) over 636,258 person-years of follow-up. After adjusting for sociodemographic factors and family history of CVD, the HR (95% CI) associated with a 1-hour increase in sleep duration SD was 1.19 (1.10, 1.27) for CVD (p-trend<0.0001), 1.23 (1.11, 1.35) for MI (p-trend<0.0001), and 1.17 (1.05, 1.29) for stroke (p-trend=0.003). Additional adjustment for lifestyle factors, co-morbidities and sleep-related factors modestly attenuated these associations. Higher sleep irregularity was associated with higher CVD risk irrespective of genetic risk (p-interaction=0.43), but this association was stronger among individuals with longer average sleep duration >8 hours (p-interaction=0.006)., Conclusions: Higher night-to-night variation in accelerometer-measured sleep duration was associated with consistently higher risks for major CVD events. The association did not seem to be modified by genetic risk for CVD and was more pronounced in long sleepers.

Self-reported shorter/longer sleep duration, insomnia, and evening preference are associated with hyperglycaemia in observational analyses, with similar observations in small studies using accelerometer-derived sleep traits. Mendelian randomization (MR) studies support an effect of self-reported insomnia, but not others, on glycated haemoglobin (HbA1c). To explore potential effects, we used MR methods to assess effects of accelerometer-derived sleep traits (duration, mid-point least active 5-h, mid-point most active 10-h, sleep fragmentation, and efficiency) on HbA1c/glucose in European adults from the UK Biobank (UKB) (n = 73,797) and the MAGIC consortium (n = 146,806). Cross-trait linkage disequilibrium score regression was applied to determine genetic correlations across accelerometer-derived, self-reported sleep traits, and HbA1c/glucose. We found no causal effect of any accelerometer-derived sleep trait on HbA1c or glucose. Similar MR results for self-reported sleep traits in the UKB sub-sample with accelerometer-derived measures suggested our results were not explained by selection bias. Phenotypic and genetic correlation analyses suggested complex relationships between self-reported and accelerometer-derived traits indicating that they may reflect different types of exposure. These findings suggested accelerometer-derived sleep traits do not affect HbA1c. Accelerometer-derived measures of sleep duration and quality might not simply be 'objective' measures of self-reported sleep duration and insomnia, but rather captured different sleep characteristics., (© 2024. The Author(s).)

Background: Light at night disrupts circadian rhythms, and circadian disruption is a risk factor for type 2 diabetes. Whether personal light exposure predicts diabetes risk has not been demonstrated in a large prospective cohort. We therefore assessed whether personal light exposure patterns predicted risk of incident type 2 diabetes in UK Biobank participants, using ∼13 million hours of light sensor data., Methods: Participants (N = 84,790, age (M ± SD) = 62.3 ± 7.9 years, 58% female) wore light sensors for one week, recording day and night light exposure. Circadian amplitude and phase were modeled from weekly light data. Incident type 2 diabetes was recorded (1997 cases; 7.9 ± 1.2 years follow-up; excluding diabetes cases prior to light-tracking). Risk of incident type 2 diabetes was assessed as a function of day and night light, circadian phase, and circadian amplitude, adjusting for age, sex, ethnicity, socioeconomic and lifestyle factors, and polygenic risk., Findings: Compared to people with dark nights (0-50th percentiles), diabetes risk was incrementally higher across brighter night light exposure percentiles (50-70th: multivariable-adjusted HR = 1.29 [1.14-1.46]; 70-90th: 1.39 [1.24-1.57]; and 90-100th: 1.53 [1.32-1.77]). Diabetes risk was higher in people with lower modeled circadian amplitude (aHR = 1.07 [1.03-1.10] per SD), and with early or late circadian phase (aHR range: 1.06-1.26). Night light and polygenic risk independently predicted higher diabetes risk. The difference in diabetes risk between people with bright and dark nights was similar to the difference between people with low and moderate genetic risk., Interpretation: Type 2 diabetes risk was higher in people exposed to brighter night light, and in people exposed to light patterns that may disrupt circadian rhythms. Avoidance of light at night could be a simple and cost-effective recommendation that mitigates risk of diabetes, even in those with high genetic risk., Funding: Australian Government Research Training Program., Competing Interests: AJKP and SWC have received research funding from Delos and Versalux. AJKP and SWC are co-directors of Circadian Health Innovations Pty Ltd. SWC has consulted for Dyson. SWC received research funding from Beacon Lighting. MKR has received consulting fees from Eli Lilly. DPW, ACB, CHCY, JML, QX, and RS declare no competing interests relevant to this manuscript., (© 2024 The Authors.)

The COVID-19 pandemic has caused major disruptions in clinical services for people with chronic long-term conditions. In this narrative review, we assess the indirect impacts of the COVID-19 pandemic on diabetes services globally and the resulting adverse effects on rates of diagnosing, monitoring, and prescribing in people with type 2 diabetes. We summarise potential practical approaches that could address these issues and improve clinical services and outcomes for people living with diabetes during the recovery phase of the pandemic., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: A.M. has received speaker fees from Boehringer Ingelheim, AstraZeneca, Abbot, Lupin, Sanofi, Abbott and Jannsen. C.H. has received funding from the following companies for speaker fees, providing education or attendance at conferences: Boehringer Ingelheim, Astra Zeneca, Lilly, MSD, Takeda, Novo Nordisk, Sanofi, Napp, Abbott and Dexcom. J.V. was the National Clinical Director for Diabetes and Obesity at NHS England. K.K. has acted as a consultant, speaker or received grants for investigator-initiated studies for Astra Zeneca, Bayer, Novartis, Novo Nordisk, Sanofi-Aventis, Eli Lilly and Merck Sharp & Dohme, Boehringer Ingelheim, Oramed Pharmaceuticals, Roche and Applied Therapeutics. K.K. is chair of the ethnicity subgroup of the UK Scientific Advisory Group for Emergencies (SAGE) and is a member of SAGE.KKs research group developed the Diabetes Risk Score recommended by NICE for screening for diabetes. DMA reports research grants from AbbVie, Almirall, Celgene, Eli Lilly, Janssen, Novartis, UCB, and the LEO Foundation. M.R has received consulting fees from Eli Lilly and Company. N.K. has received honoraria from Astra Zeneca, Bayer, Novartis, Novo Nordisk, Sanofi-Aventis, Lilly and Merck Sharp & Dohme, Boehringer Ingelheim and Abbott for speaker meetings and advisory boards. N.M. has received funding from the following companies for providing educational sessions, attendance at conferences and for attending advisory boards: Boehringer Ingelheim, Astra Zeneca, Lilly, MSD, Takeda, Novo Nordisk, Sanofi, Napp, Abbott, MyLan, Roche, Ascensia and Dexcom. N.S. has received grants from AstraZeneca, Boehringer Ingelheim, Novartis, and Roche Diagnostics; and consulting fees from Afimmune, Amgen, AstraZeneca, Boehringer Ingelheim, Eli Lilly and Company, Hanmi Pharmaceuticals, Merck Sharp & Dohme, Novartis, Novo Nordisk, Pfizer, and Sanofi. All other authors declare no conflicts of interest., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: The relationship between 24-hour rest-activity rhythms (RARs) and risk for dementia or mild cognitive impairment (MCI) remains an area of growing interest. Previous studies were often limited by small sample sizes, short follow-ups, and older participants. More studies are required to fully explore the link between disrupted RARs and dementia or MCI in middle-aged and older adults., Objective: We leveraged the UK Biobank data to examine how RAR disturbances correlate with the risk of developing dementia and MCI in middle-aged and older adults., Methods: We analyzed the data of 91,517 UK Biobank participants aged between 43 and 79 years. Wrist actigraphy recordings were used to derive nonparametric RAR metrics, including the activity level of the most active 10-hour period (M10) and its midpoint, the activity level of the least active 5-hour period (L5) and its midpoint, relative amplitude (RA) of the 24-hour cycle [RA=(M10-L5)/(M10+L5)], interdaily stability, and intradaily variability, as well as the amplitude and acrophase of 24-hour rhythms (cosinor analysis). We used Cox proportional hazards models to examine the associations between baseline RAR and subsequent incidence of dementia or MCI, adjusting for demographic characteristics, comorbidities, lifestyle factors, shiftwork status, and genetic risk for Alzheimer's disease., Results: During the follow-up of up to 7.5 years, 555 participants developed MCI or dementia. The dementia or MCI risk increased for those with lower M10 activity (hazard ratio [HR] 1.28, 95% CI 1.14-1.44, per 1-SD decrease), higher L5 activity (HR 1.15, 95% CI 1.10-1.21, per 1-SD increase), lower RA (HR 1.23, 95% CI 1.16-1.29, per 1-SD decrease), lower amplitude (HR 1.32, 95% CI 1.17-1.49, per 1-SD decrease), and higher intradaily variability (HR 1.14, 95% CI 1.05-1.24, per 1-SD increase) as well as advanced L5 midpoint (HR 0.92, 95% CI 0.85-0.99, per 1-SD advance). These associations were similar in people aged <70 and >70 years, and in non-shift workers, and they were independent of genetic and cardiovascular risk factors. No significant associations were observed for M10 midpoint, interdaily stability, or acrophase., Conclusions: Based on findings from a large sample of middle-to-older adults with objective RAR assessment and almost 8-years of follow-up, we suggest that suppressed and fragmented daily activity rhythms precede the onset of dementia or MCI and may serve as risk biomarkers for preclinical dementia in middle-aged and older adults., (©Shahab Haghayegh, Chenlu Gao, Elizabeth Sugg, Xi Zheng, Hui-Wen Yang, Richa Saxena, Martin K Rutter, Michael Weedon, Agustin Ibanez, David A Bennett, Peng Li, Lei Gao, Kun Hu. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 07.05.2024.)

Background: People from South Asian heritage are at high risk of type 2 diabetes, but there are limited specific strategies to prevent and manage this condition. The aim was to assess the effectiveness of culturally bespoke lifestyle programmes in South Asians that target weight loss for the prevention or remission of type 2 diabetes mellitus (T2DM)., Methods: We performed a systematic review and meta-analysis of intervention trials. PubMed, Scopus, MEDLINE (EBSCOhost), CINAHL, PsycINFO and CENTRAL were searched. Human intervention trials (randomised controlled trials and quasi-experimental) investigating the effect of lifestyle interventions on the prevention and remission of T2DM in South Asians were included. Studies including participants at risk of T2DM (prevention trials) and having the disease (remission trials) with duration ≥12 weeks were eligible. For prevention trials, the primary outcome was change in weight (kg) from baseline; for remission trials, it was decrease in HbA1c to non-diabetic levels (HbA1c ≤ 6.5%) without diabetes medications. Prevention trials were separated into (i) lifestyle modification advice and (ii) lifestyle modification advice including a supervised physical activity programme., Results: Twenty-four trials were eligible (21 prevention trials and 3 remission trials). In T2DM prevention trials involving only lifestyle modification advice, the mean postintervention difference in weight between intervention and control groups was -0.65 kg (95% confidence interval [CI]: -1.04, -0.26; p = 0.01). Lifestyle modification advice including a physical activity programme was associated with greater decreases in weight: -1.13 kg (95% CI: -2.04, -0.21; p = 0.02). Fasting blood glucose levels were slightly lower in intervention groups for both intervention subtypes, although there was no significant change in HbA1c levels or 2-h plasma glucose levels. Diabetes remission trials showed potential acceptability but were limited in number and involved a small sample size, and some did not include a control group., Conclusions: In South Asians, lifestyle interventions for prevention of T2DM offer only modest impacts on weight and glucose control and will unlikely reduce diabetes incidence. Alternative lifestyle interventions co-designed with members of the communities and aimed at both prevention and remission of T2DM must be urgently considered. Systematic review registration number: PROSPERO CRD42022385174 https://www.crd.york.ac.uk/prospero/display&#95;record.php?RecordID=385174., (© 2024 The Authors. Journal of Human Nutrition and Dietetics published by John Wiley & Sons Ltd on behalf of British Dietetic Association.)

In high-income countries, rates of atherosclerotic complications in type 2 diabetes have declined markedly over time due to better management of traditional risk factors including lipids, blood pressure, and glycemia levels. Population-wide reductions in smoking have also helped lower atherosclerotic complications and so reduce premature mortality in type 2 diabetes. However, as excess adiposity is a stronger driver for heart failure (HF), and obesity levels have remained largely unchanged, HF risks have not declined as much and may even be rising in the increasing number of people developing type 2 diabetes at younger ages. Excess weight is also an underrecognized risk factor for chronic kidney disease (CKD). Based on evidence from a range of sources, we explain how excess adiposity must be influencing most risks well before diabetes develops, particularly in younger-onset diabetes, which is linked to greater excess adiposity. We also review potential mechanisms linking excess adiposity to HF and CKD and speculate on how some of the responsible pathways-e.g., hemodynamic, cellular overnutrition, and inflammatory-could be favorably influenced by intentional weight loss (via lifestyle or drugs). On the basis of available evidence, we suggest that the cardiorenal outcome benefits seen with sodium-glucose cotransporter 2 inhibitors may partially derive from their interference of some of these same pathways. We also note that many other complications common in diabetes (e.g., hepatic, joint disease, perhaps mental health) are also variably linked to excess adiposity, the aggregated exposure to which has now increased in type 2 diabetes. All such observations suggest a greater need to tackle excess adiposity earlier in type 2 diabetes., (© 2024 by the American Diabetes Association.)

Aim: Obesity has a significant impact on all-cause mortality rate and overall health care resource use (HCRU). These outcomes are also strongly linked to age, sex and local deprivation of the population. We aimed to establish the lifetime costs of obesity by demographic group/geographic area using published mortality rates and HCRU use for integrated care boards (ICB) in England in the context of costs of therapeutic intervention., Methods: Population and expected mortality rates by age, sex and deprivation were obtained from national data. Obesity class prevalence was taken from the health of the nation study. The published impact of obesity by age, group, sex and deprivation on mortality and HCRU were applied to estimate life years lost and lifetime HCRU [by sex, age band and body mass index (BMI) class for each ICB]. The year 2019 was chosen as the study basis data to avoid influences of COVID-19 pandemic on obesity rates with application of 2022/23 HCRU values. Outcomes including prevalence, deaths, life years lost, HCRU and lifetime HCRU were compared by age and sex groups across four BMI classes normal/underweight (BMI <25 kg/m 2 ), overweight (25-29.9 kg/m 2 ), obese class I and II (30-39.9 kg/m 2 ), and obese class III (≥40), with benchmarking being set against all population being BMI <25 kg/m 2 overall and by each of the 42 ICBs. We also associated future life with deaths to provide an estimate of 'future life years lost' occurring each year., Results: Total population aged >16 years was 45.4 million (51% female)., Prevalence: 13.7 million (28% of the total adult population) had a BMI ≥30 mg/m 2 and BMI ≥40 kg/m 2 were 1.50 million (12%) of these 1.0 million (68%) were female and of these 0.6 million 40% were women aged 16-49 years. In addition, 35% of those with a BMI ≥40 kg/m 2 were in the top deprivation quintile (i.e. overall 20%). Mortality was based on expected deaths of 518K/year, and modelling suggested that if a BMI <25 kg/m 2 was achieved in all individuals, the death rate would fall by 63K to 455K/year for the English population (12% reduction). For those with a BMI ≥40 kg/m 2 the predicted reduction was 12K deaths (54% lower); while in those aged 16-49 years with a BMI ≥40 kg/m 2 72% of deaths were linked to obesity. For future life years lost, we estimated 2.5 years were lost in people with BMI 30-39.9 kg/m 2 6.7 years when BMI ≥40 kg/m 2 . However, for those aged 16-49 years with a BMI ≥40 kg/m 2 , 8.3 years were lost. HCRU, for weight reduction, the annual HCRU decrease from BMI ≥40 kg/m 2 to BMI 30-39.9 kg/m 2 was £342 per person and from BMI 30-39.9 to 25-29.9 kg/m 2 the reduction was £316/person. However, lifetime costs were similar because of reduced life expectancy for obese individuals. In quality adjusted life years (QALY), overall, 791 689 future life years were lost (13.1% of all) in people with BMI ≥25 kg/m 2 and were related to excess weight. When the NICE £30 000 per QALY value was applied to the estimated total 791 689 future life years lost then the potential QALY value reduction lost was equivalent to £24 billion/year or £522/person in the obese population. For morbidly obese men and women the potential QALY value lost was £2864/person/year. Regarding geography, across the 42 ICBs, we observed significant variation in the prevalence of BMI ≥40 (1.8%-4.3%), excess mortality (11.6%-15.4%) and HCRU linked to higher BMI (7.2%-8.8%). The areas with the greatest impact on HCRU were in the north-west, north-east and Midlands of England, while the south shows less impact., Conclusion: The expected increases in annual HCRU because of obesity, when considered over a lifetime, are being mitigated by the increased mortality of obese individuals. Our data suggest that simple short-term HCRU reduction brought about through BMI reduction will be insufficient to fund additional specialist weight reduction interventions. The HRCUs associated with BMI are not in most cases related to short-term health conditions. They are a cumulative result over a number of years, so for age 16-49 years reducing BMI from ≥40 to 30-39.9 kg/m 2 might show an annual decrease in HCRU/person by £325/year for women and £80/year for men but this might not have immediately occurred within that year. For those aged >70 years reducing BMI from ≥40 to 30-39.9 kg/m 2 might show an annual decrease in HCRU/person by £777/year for women and £796/year for men but also may not be manifest within that year. However, for the morbidly obese men and women, the potential QALY value lost was £2864 per person per year with the potential for these funds to be applied to intensive weight management programmes, including pharmacotherapy., (© 2024 The Authors. Diabetes, Obesity and Metabolism published by John Wiley & Sons Ltd.)