Body-Weight Fluctuations and Outcomes in Coronary Disease

Association between BMI and cause-specific long-term mortality in acute myocardial infarction patients

Aims

To investigate the association between body mass index (BMI) at acute myocardial infarction (AMI) and all-cause as well as cause-specific long-term mortality.

Methods

The analysis was based on 10,651 hospitalized AMI patients (age 25-84 years) recorded by the population-based Myocardial Infarction Registry Augsburg between 2000 and 2017. The median follow-up time was 6.7 years [IQR: 3.5-10.0)]. Cause-specific mortality was obtained by evaluating the death certificates. In multivariable-adjusted COX regression models using cubic splines for the variable BMI, the association between BMI and cause-specific mortality (all-cause, cardiovascular, ischemic heart diseases, cancer) was investigated. Additionally, a subgroup analysis in three age groups was performed for all-cause mortality.

Results

Overall, there was a statistically significant U-shaped association between BMI at AMI and long-term mortality with the lowest hazard ratios (HR) found for BMI values between 25 and 30 kg/m². For cancer mortality, higher BMI values > 30 kg/m² were not associated with higher mortality. In patients aged <60 years, there was a significant association between BMI values >35 kg/m² and increased all-cause mortality; this association was missing in 60 to 84 years old patients. For all groups and for each specific cause of mortality, lower BMI (<25kg/m²) values were significantly associated with higher mortality.

Conclusions

Overall, a lower BMI - and also a high BMI in patients younger than 60 years - seem to be a risk factors for increased all-cause mortality after AMI. A BMI in a mid-range between 25 and 30 kg/m² is favorable in terms of long-term survival after AMI.

Association of weight change with cardiovascular events and all-cause mortality in obese participants with cardiovascular disease: a prospective cohort study

BACKGROUND

Studies have examined the association between weight change and risk of cardiovascular (CV) outcomes in the general population. However, very few literature reported the association among obese people with established CV disease (CVD) and the factors associated with weight change are not clear. We sought to investigate this using the UK Biobank data.

METHODS

In this large prospective population-based cohort study, absolute interval change scores in weight were calculated between weight measurements at baseline and the follow-up. The estimated HRs with 95% CIs were obtained from the Cox regression models to assess the association between weight change and the risk of CV death, cerebrovascular and ischaemic heart diseases and all-cause mortality.

RESULTS

Of the 8297 obese participants who had CVD with repeated weight measurements, 43.1% were female. The mean age was 56.6 (SD: 7.2) years. The overall median follow-up of the study was 13.9 (IQR: 13.1-14.6) years. 52.7% of the participants had stable weight change (weight loss or gain<5 kg), 14.2% had large weight loss (≥10 kg) and 5.1% had large weight gain (≥10 kg). Compared with stable weight, only large weight gain was associated with an increased risk of CV death and all-cause mortality (fully adjusted HR (95% CI): 3.05 (1.40 to 6.67) for CV death and 1.93 (1.15 to 3.26) for all-cause mortality).

CONCLUSIONS

Among obese individuals with CVD, large weight gain is associated with a higher risk of CV death and all-cause mortality. Further studies are needed to understand the exact mechanisms underlying the associations between weight loss or weight gain and mortality.

A machine-learned model for predicting weight loss success using weight change features early in treatment

Stepped-care obesity treatments aim to improve efficiency by early identification of non-responders and adjusting interventions but lack validated models. We trained a random forest classifier to improve the predictive utility of a clinical decision rule (>0.5 lb weight loss/week) that identifies non-responders in the first 2 weeks of a stepped-care weight loss trial (SMART). From 2009 to 2021, 1058 individuals with obesity participated in three studies: SMART, Opt-IN, and ENGAGED. The model was trained on 80% of the SMART data (224 participants), and its in-distribution generalizability was tested on the remaining 20% (remaining 57 participants). The out-of-distribution generalizability was tested on the ENGAGED and Opt-IN studies (472 participants). The model predicted weight loss at month 6 with an 84.5% AUROC and an 86.3% AUPRC. SHAP identified predictive features: weight loss at week 2, ranges/means and ranges of weight loss, slope, and age. The SMART-trained model showed generalizable performance with no substantial difference across studies.

Digital Intervention for behaviouR changE and Chronic disease prevenTION (DIRECTION): Study protocol for a randomized controlled trial of a web-based platform integrating nutrition, physical activity, and mindfulness for individuals with obesity

Excess body weight, suboptimal diet, physical inactivity, alcohol consumption, sleep disruption, and elevated stress are modifiable risk factors associated with the development of chronic diseases. Digital behavioural interventions targeting these factors have shown promise in improving health and reducing chronic disease risk. The Digital Intervention for behaviouR changE and Chronic disease prevenTION (DIRECTION) study is a parallel group, two-arm, randomized controlled trial evaluating the effects of adding healthcare professional guidance and peer support via group-based sessions to a web-based wellness platform (experimental group, n = 90) compared to a self-guided use of the platform (active control group, n = 90) among individuals with a body mass index (BMI) of 30 to <35 kg/m2 and aged 40-65 years. Obesity is defined by a high BMI. The web-based wellness platform employed in this study is My Viva Plan (MVP)®, which holistically integrates nutrition, physical activity, and mindfulness programs. Over 16 weeks, the experimental group uses the web-based wellness platform daily and engages in weekly online support group sessions. The active control group exclusively uses the web-based wellness platform daily. Assessments are conducted at baseline and weeks 8 and 16. The primary outcome is between-group difference in weight loss (kg) at week 16, and secondary outcomes are BMI, percent weight change, proportion of participants achieving 5% or more weight loss, dietary intake, physical activity, alcohol consumption, sleep, and stress across the study. A web-based wellness platform may be a scalable approach to promote behavioural changes that positively impact health. This study will inform the development and implementation of interventions using web-based wellness platforms and personalized digital interventions to improve health outcomes and reduce chronic disease risk among individuals with obesity.

Hypothalamic Gliosis is Associated With Multiple Cardiovascular Disease Risk Factors

Background

Hypothalamic gliosis is mechanistically linked to obesity and insulin resistance in rodent models. We tested cross-sectional associations between radiologic measures of hypothalamic gliosis in humans and clinically relevant cardiovascular disease risk factors, as well as prevalent coronary heart disease.

Methods

Using brain MRI images from Framingham Heart Study participants (N=867; mean age, 55 years; 55% females), T2 signal intensities were extracted bilaterally from the region of interest in the mediobasal hypothalamus (MBH) and reference regions in the amygdala (AMY) and putamen (PUT). T2 signal ratios were created in which greater relative T2 signal intensity suggests gliosis. The primary measure compared MBH to AMY (MBH/AMY); a positive control ratio (MBH/PUT) also assessed MBH whereas a negative control (PUT/AMY) did not. Outcomes were BMI, HDL-C, LDL-C, fasting triglycerides, and the presence of hypertension (n=449), diabetes mellitus (n=66), metabolic syndrome (n=254), or coronary heart disease (n=25). Dietary risk factors for gliosis were assessed in a prospective analysis. Statistical testing was performed using linear or logistic regression.

Results

Greater MBH/AMY T2 signal ratios were associated with higher BMI (β = 21.5 [95% CI, 15.4-27.6]; P<0.001), higher fasting triglycerides (β = 1.1 [95% CI, 0.6-1.7]; P<0.001), lower HDL-C (β = -20.8 [95% CI, -40.0 to -1.6]; P=0.034), and presence of hypertension (odds ratio, 1.2 [95% CI, 1.1-1.4]; P=0.0088), and the latter two were independent of BMI. Findings for diabetes mellitus were mixed and attenuated by adjusting for BMI. Metabolic syndrome was associated with MBH/AMY T2 signal ratios (odds ratio, 1.3 [95% CI, 1.1-1.6]; P<0.001). Model results were almost uniformly confirmed by the positive control ratios, whereas negative control ratios that did not test the MBH were unrelated to any outcomes (all P≥0.05). T2 signal ratios were not associated with prevalent coronary heart disease (all P>0.05), but confidence intervals were wide. Self-reported percentages of macronutrient intake were not consistently related to future T2 signal ratios.

Conclusions

Using a well-established study of cardiovascular disease development, we found evidence linking hypothalamic gliosis to multiple cardiovascular disease risk factors, even independent of adiposity. Our results highlight the need to consider neurologic mechanisms to understand and improve cardiometabolic health.

The metabolic consequences of 'yo-yo' dieting are markedly influenced by genetic diversity

BACKGROUND

Weight loss can improve the metabolic complications of obesity. However, it is unclear whether insulin resistance persists despite weight loss and whether any protective benefits are preserved following weight regain (weight cycling). The impact of genetic background on weight cycling is undocumented. We aimed to investigate the effects of weight loss and weight cycling on metabolic outcomes and sought to clarify the role of genetics in this relationship.

METHOD

Both C57BL/6 J and genetically heterogeneous Diversity Outbred Australia (DOz) mice were alternately fed high fat Western-style diet (WD) and a chow diet at 8-week intervals. Metabolic measures including body composition, glucose tolerance, pancreatic beta cell activity, liver lipid levels and adipose tissue insulin sensitivity were determined.

RESULTS

After diet switch from WD (8-week) to chow (8-week), C57BL/6 J mice displayed a rapid normalisation of body weight, adiposity, hyperinsulinemia, liver lipid levels and glucose uptake into adipose tissue comparable to chow-fed controls. In response to the same dietary intervention, genetically diverse DOz mice conversely maintained significantly higher fat mass and insulin levels compared to chow-fed controls and exhibited much more profound interindividual variability than C57BL/6 J mice. Weight cycled (WC) animals were re-exposed to WD (8-week) and compared to age-matched controls fed 8-week WD for the first time (LOb). In C57BL/6 J but not DOz mice, WC animals had significantly higher blood insulin levels than LOb controls. All WC animals exhibited significantly greater beta cell activity than LOb controls despite similar fat mass, glucose tolerance, liver lipid levels and insulin-stimulated glucose uptake in adipose tissue.

CONCLUSION

Following weight loss, metabolic outcomes return to baseline in C57BL/6 J mice with obesity. However, genetic diversity significantly impacts this response. A period of weight loss does not provide lasting benefits after weight regain, and weight cycling is detrimental and associated with hyperinsulinemia and elevated basal insulin secretion.

BMI variability and cardiovascular outcomes within clinical trial and real-world environments in type 2 diabetes: an IMI2 SOPHIA study

BACKGROUND

BMI variability has been associated with increased cardiovascular disease risk in individuals with type 2 diabetes, however comparison between clinical studies and real-world observational evidence has been lacking. Furthermore, it is not known whether BMI variability has an effect independent of HbA1c variability.

METHODS

We investigated the association between BMI variability and 3P-MACE risk in the Harmony Outcomes trial (n = 9198), and further analysed placebo arms of REWIND (n = 4440) and EMPA-REG OUTCOME (n = 2333) trials, followed by real-world data from the Tayside Bioresource (n = 6980) using Cox regression modelling. BMI variability was determined using average successive variability (ASV), with first major adverse cardiovascular event of non-fatal stroke, non-fatal myocardial infarction, and cardiovascular death (3P-MACE) as the primary outcome.

RESULTS

After adjusting for cardiovascular risk factors, a + 1 SD increase in BMI variability was associated with increased 3P-MACE risk in Harmony Outcomes (HR 1.12, 95% CI 1.08-1.17, P < 0.001). The most variable quartile of participants experienced an 87% higher risk of 3P-MACE (P < 0.001) relative to the least variable. Similar associations were found in REWIND and Tayside Bioresource. Further analyses in the EMPA-REG OUTCOME trial did not replicate this association. BMI variability's impact on 3P-MACE risk was independent of HbA1c variability.

CONCLUSIONS

In individuals with type 2 diabetes, increased BMI variability was found to be an independent risk factor for 3P-MACE across cardiovascular outcome trials and real-world datasets. Future research should attempt to establish a causal relationship between BMI variability and cardiovascular outcomes.

Adiposity, type 2 diabetes and atherosclerotic cardiovascular disease risk: Use and abuse of the body mass index

The worldwide prevalence of individuals with an elevated body weight has increased steadily over the past five decades. Billions of research dollars have been invested to improve our understanding of the causes and consequences of having an elevated body weight. All this knowledge has, however, failed to influence populational body weight trajectories of most countries around the world. Research on the definition of "obesity" has also evolved. Body mass index (BMI), the most commonly used tool to make its diagnosis, has major limitations. In this review article, we will highlight evidence from observational studies, genetic association studies and randomized clinical trials that have shown the remarkable inter-individual differences in the way humans store energy as body fat. Increasing evidence also suggests that, as opposed to weight inclusive, lifestyle-based approaches, weight-centric approaches advising people to simply eat less and move more are not sustainable for most people for long-term weight loss and maintenance. It is time to recognize that this outdated approach may have produced more harm than good. On the basis of pathophysiological, genetic and clinical evidence presented in this review, we propose that it may be time to shift away from the traditional clinical approach, which is BMI-centric. Rather, emphasis should be placed on actionable lifestyle-related risk factors aiming at improving overall diet quality and increasing physical activity level in the general population.

Adiposity, immunity, and inflammation: interrelationships in health and disease: a report from 24th Annual Harvard Nutrition Obesity Symposium, June 2023

The rapidly evolving field of immunometabolism explores how changes in local immune environments may affect key metabolic and cellular processes, including that of adipose tissue. Importantly, these changes may contribute to low-grade systemic inflammation. In turn, chronic low-grade inflammation affecting adipose tissue may exacerbate the outcome of metabolic diseases. Novel advances in our understanding of immunometabolic processes may critically lead to interventions to reduce disease severity and progression. An important example in this regard relates to obesity, which has a multifaceted effect on immunity, activating the proinflammatory pathways such as the inflammasome and disrupting cellular homeostasis. This multifaceted effect of obesity can be investigated through study of downstream conditions using cellular and systemic investigative techniques. To further explore this field, the National Institutes of Health P30 Nutrition Obesity Research Center at Harvard, in partnership with Harvard Medical School, assembled experts to present at its 24th Annual Symposium entitled "Adiposity, Immunity, and Inflammation: Interrelationships in Health and Disease" on 7 June, 2023. This manuscript seeks to synthesize and present key findings from the symposium, highlighting new research and novel disease-specific advances in the field. Better understanding the interaction between metabolism and immunity offers promising preventative and treatment therapies for obesity-related immunometabolic diseases.

Medical Nutrition Education for Health, Not Harm: BMI, Weight Stigma, Eating Disorders, and Social Determinants of Health

Effective nutrition training is fundamental to medical education. Current training is inadequate and can cause harm to students and patients alike; it leaves physicians unprepared to counsel on nutrition, places undue focus on weight and body mass index (BMI), can exacerbate anti-obesity bias, and increase risk for development of eating disorders, while neglecting social determinants of health and communication skills. Physicians and educators hold positions of influence in society; what we say and how we say it matters. We propose actionable approaches to improve nutrition education to minimize harm and pursue evidence-based, effective, and equitable healthcare.

Identification and validation of lipid metabolism-related key genes as novel biomarkers in acute myocardial infarction and pan-cancer analysis

BACKGROUND

Acute myocardial infarction (AMI) is associated with high morbidity and mortality, and is associated with abnormal lipid metabolism. We identified lipid metabolism related genes as biomarkers of AMI, and explored their mechanisms of action.

METHODS

Microarray datasets were downloaded from the GEO database and lipid metabolism related genes were obtained from Molecular Signatures Database. WGCNA was performed to identify key genes. We evaluated differential expression and performed ROC and ELISA analyses. We also explored the mechanism of AMI mediated by key genes using gene enrichment analysis. Finally, immune infiltration and pan-cancer analyses were performed for the identified key genes.

RESULTS

TRL2, S100A9, and HCK were identified as key genes related to lipid metabolism in AMI. Internal and external validation (including ELISA) showed that these were good biomarkers of AMI. In addition, the results of gene enrichment analysis showed that the key genes were enriched in inflammatory response, immune system process, and tumor-related pathways. Finally, the results of immune infiltration showed that key genes were concentrated in neutrophils and macrophages, and pan-cancer analysis showed that the key genes were highly expressed in most tumors and were associated with poor prognosis.

CONCLUSIONS

TLR2, S100A9, and HCK were identified as lipid metabolism related novel diagnostic biomarkers of AMI. In addition, AMI and tumors may be related through the inflammatory immune response.

An interpretable predictive deep learning platform for pediatric metabolic diseases

OBJECTIVES

Metabolic disease in children is increasing worldwide and predisposes a wide array of chronic comorbid conditions with severe impacts on quality of life. Tools for early detection are needed to promptly intervene to prevent or slow the development of these long-term complications.

MATERIALS AND METHODS

No clinically available tools are currently in widespread use that can predict the onset of metabolic diseases in pediatric patients. Here, we use interpretable deep learning, leveraging longitudinal clinical measurements, demographical data, and diagnosis codes from electronic health record data from a large integrated health system to predict the onset of prediabetes, type 2 diabetes (T2D), and metabolic syndrome in pediatric cohorts.

RESULTS

The cohort included 49 517 children with overweight or obesity aged 2-18 (54.9% male, 73% Caucasian), with a median follow-up time of 7.5 years and mean body mass index (BMI) percentile of 88.6%. Our model demonstrated area under receiver operating characteristic curve (AUC) accuracies up to 0.87, 0.79, and 0.79 for predicting T2D, metabolic syndrome, and prediabetes, respectively. Whereas most risk calculators use only recently available data, incorporating longitudinal data improved AUCs by 13.04%, 11.48%, and 11.67% for T2D, syndrome, and prediabetes, respectively, versus models using the most recent BMI (P < 2.2 × 10-16).

DISCUSSION

Despite most risk calculators using only the most recent data, incorporating longitudinal data improved the model accuracies because utilizing trajectories provides a more comprehensive characterization of the patient's health history. Our interpretable model indicated that BMI trajectories were consistently identified as one of the most influential features for prediction, highlighting the advantages of incorporating longitudinal data when available.

High Variability of Body Mass Index Is Independently Associated With Incident Heart Failure

BACKGROUND

Heart failure (HF) is a serious condition with increasing prevalence, high morbidity, and increased mortality. Obesity is an established risk factor for HF. Fluctuation in body mass index (BMI) has shown a higher risk of cardiovascular outcomes. We investigated the association between BMI variability and incident HF.

METHODS AND RESULTS

In the UK Biobank, we established a prospective cohort after excluding participants with prevalent HF or cancer at enrollment. A total of 99 368 White participants with ≥3 BMI measures during >2 years preceding enrollment were included, with a median follow-up of 12.5 years. The within-participant variability of BMI was evaluated using standardized SD and coefficient of variation. The association of BMI variability with incident HF was assessed using Fine and Gray's competing risk model, adjusting for confounding factors and participant-specific rate of BMI change. Higher BMI variability measured in both SD and coefficient of variation was significantly associated with higher risk in HF incidence (SD: hazard ratio [HR], 1.05 [95% CI, 1.03-1.08], P<0.0001; coefficient of variation: HR, 1.07 [95% CI, 1.04-1.10], P<0.0001).

CONCLUSIONS

Longitudinal health records capture BMI fluctuation, which independently predicts HF incidence.

Association of variabilities in body mass index and waist circumference with newly achieved remission of metabolic dysfunction-associated fatty liver disease

AIMS

Although body weight reduction is recommended to ameliorate nonalcoholic fatty liver disease, the effects of body mass index (BMI) and waist circumference (WC) variability on newly achieved remission of metabolic dysfunction-associated fatty liver disease (MAFLD) remain unclear. We aimed to investigate the longitudinal association between BMI and WC variabilities and newly achieved MAFLD remission in both sexes.

METHODS

Among 26,952 patients, 1823 with MAFLD diagnosed by ultrasonography and with >2 health checkups over >2 years from April 2014 to March 2021 were included in this observational cohort study. A generalized estimation equation model analyzed the association between BMI and WC and newly achieved MAFLD remission according to repeated measures at baseline and the most recent stage.

RESULTS

Rates of MAFLD remission in male and female patients were 7.4 % and 6.0 %, respectively. Regarding decreased BMI variability, newly achieved MAFLD remission prevalence among the subgroups differed significantly between sexes (p < 0.001). In male patients, a decrease in BMI variability of ≥1.5 kg/m2 and WC variability of ≥4.2 cm had adjusted odds ratios (ORs) of 5.215 and 2.820, respectively, for newly achieved MAFLD remission. Among female patients, regular exercise and breakfast consumption were accelerating factors for newly achieved MAFLD remission. Non-invasive liver fibrosis scores significantly differed between MAFLD and newly achieved MAFLD remission, including in the subgroups (p < 0.01 and p < 0.001, respectively).

CONCLUSIONS

Reducing BMI and WC variabilities in male patients and improving lifestyle habits in female patients may accelerate MAFLD remission.

Effects of repeated weight cycling on non-alcoholic steatohepatitis in diet-induced obese mice

Lifestyle interventions remain the treatment of choice for patients with obesity and metabolic complications, yet are difficult to maintain and often lead to cycles of weight loss and regain (weight cycling). Literature on weight cycling remains controversial and we therefore investigated the association between weight cycling and metabolic complications using preexistent obese mice. Ldlr-/-.Leiden mice received a high-fat diet (HFD) for 20 weeks to induce obesity. Subsequently, weight-cycled mice were switched between the healthy chow diet and HFD for four 2-week periods and compared to mice that received HFD for the total study period. Repeated weight cycling tended to decrease body weight and significantly reduced fat mass, whereas adipose tissue inflammation was similar relative to HFD controls. Weight cycling did not significantly affect blood glucose or plasma insulin levels yet significantly reduced plasma free fatty acid and alanine transaminase/aspartate transaminase levels. Hepatic macrovesicular steatosis was similar and microvesicular steatosis tended to be increased upon weight cycling. Weight cycling resulted in a robust decrease in hepatic inflammation compared to HFD controls while hepatic fibrosis and atherosclerosis development were not affected. These results argue against the postulate that repeated weight cycling leads to unfavorable metabolic effects, when compared to a continuous unhealthy lifestyle, and in fact revealed beneficial effects on hepatic inflammation, an important hallmark of non-alcoholic steatohepatitis.

Dissecting the biology of feeding and eating disorders

Feeding and eating disorders (FEDs) are heterogenous and characterized by varying patterns of dysregulated eating and weight. Genome-wide association studies (GWASs) are clarifying their underlying biology and their genetic relationship to other psychiatric and metabolic/anthropometric traits. Genetic research on anorexia nervosa (AN) has identified eight significant loci and uncovered genetic correlations implicating both psychiatric and metabolic/anthropometric risk factors. Careful explication of these metabolic contributors may be key to developing effective and enduring treatments for devastating, life-altering, and frequently lethal illnesses. We discuss clinical phenomenology, genomics, phenomics, intestinal microbiota, and functional genomics and propose a path that translates variants to genes, genes to pathways, and pathways to metabolic outcomes to advance the science and eventually treatment of FEDs.

Long-Term Body Mass Index Variability and Adverse Cardiovascular Outcomes

Importance

Body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) is a commonly used estimate of obesity, which is a complex trait affected by genetic and lifestyle factors. Marked weight gain and loss could be associated with adverse biological processes.

Objective

To evaluate the association between BMI variability and incident cardiovascular disease (CVD) events in 2 distinct cohorts.

Design, Setting, and Participants

This cohort study used data from the Million Veteran Program (MVP) between 2011 and 2018 and participants in the UK Biobank (UKB) enrolled between 2006 and 2010. Participants were followed up for a median of 3.8 (5th-95th percentile, 3.5) years. Participants with baseline CVD or cancer were excluded. Data were analyzed from September 2022 and September 2023.

Exposure

BMI variability was calculated by the retrospective SD and coefficient of variation (CV) using multiple clinical BMI measurements up to the baseline.

Main Outcomes and Measures

The main outcome was incident composite CVD events (incident nonfatal myocardial infarction, acute ischemic stroke, and cardiovascular death), assessed using Cox proportional hazards modeling after adjustment for CVD risk factors, including age, sex, mean BMI, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol, smoking status, diabetes status, and statin use. Secondary analysis assessed whether associations were dependent on the polygenic score of BMI.

Results

Among 92 363 US veterans in the MVP cohort (81 675 [88%] male; mean [SD] age, 56.7 [14.1] years), there were 9695 Hispanic participants, 22 488 non-Hispanic Black participants, and 60 180 non-Hispanic White participants. A total of 4811 composite CVD events were observed from 2011 to 2018. The CV of BMI was associated with 16% higher risk for composite CVD across all groups (hazard ratio [HR], 1.16; 95% CI, 1.13-1.19). These associations were unchanged among subgroups and after adjustment for the polygenic score of BMI. The UKB cohort included 65 047 individuals (mean [SD] age, 57.30 (7.77) years; 38 065 [59%] female) and had 6934 composite CVD events. Each 1-SD increase in BMI variability in the UKB cohort was associated with 8% increased risk of cardiovascular death (HR, 1.08; 95% CI, 1.04-1.11).

Conclusions and Relevance

This cohort study found that among US veterans, higher BMI variability was a significant risk marker associated with adverse cardiovascular events independent of mean BMI across major racial and ethnic groups. Results were consistent in the UKB for the cardiovascular death end point. Further studies should investigate the phenotype of high BMI variability.

The association of long-term trajectories of BMI, its variability, and metabolic syndrome: a 30-year prospective cohort study

Background

Limited data exists on how early-life weight changes relate to metabolic syndrome (MetS) risk in midlife. This study examines the association between long-term trajectories of body mass index (BMI), its variability, and MetS risk in Chinese individuals.

Methods

In the Hanzhong Adolescent Hypertension study (March 10, 1987-June 3, 2017), 1824 participants with at least five BMI measurements from 1987 to 2017 were included. Using group-based trajectory modeling, different BMI trajectories were identified. BMI variability was assessed through standard deviation (SD), variability independent of the mean (VIM), and average real variability (ARV). Logistic regression analyzed the relationship between BMI trajectory, BMI variability, and MetS occurrence in midlife (URL: https://www.clinicaltrials.gov; Unique identifier: NCT02734472).

Findings

BMI trajectories were categorized as low-increasing (34.4%), moderate-increasing (51.8%), and high-increasing (13.8%). Compared to the low-increasing group, the odds ratios (ORs) [95% CIs] for MetS were significantly higher in moderate (4.27 [2.63-6.91]) and high-increasing groups (13.11 [6.30-27.31]) in fully adjusted models. Additionally, higher BMI variabilities were associated with increased MetS odds (ORs for SDBMI, VIMBMI, and ARVBMI: 2.30 [2.02-2.62], 1.22 [1.19-1.26], and 4.29 [3.38-5.45]). Furthermore, BMI trajectories from childhood to adolescence were predictive of midlife MetS, with ORs in moderate (1.49 [1.00-2.23]) and high-increasing groups (2.45 [1.22-4.91]). Lastly, elevated BMI variability in this period was also linked to higher MetS odds (ORs for SDBMI, VIMBMI, and ARVBMI: 1.24 [1.08-1.42], 1.00 [1.00-1.01], and 1.21 [1.05-1.38]).

Interpretation

Our study suggests that both early-life BMI trajectories and BMI variability could be predictive of incident MetS in midlife.

Funding

This work was supported by the National Natural Science Foundation of China No. 82070437 (J.-J.M.), the Clinical Research Award of the First Affiliated Hospital of Xi'an Jiaotong University of China (No. XJTU1AF-CRF-2022-002, XJTU1AF2021CRF-021, and XJTU1AF-CRF-2023-004), the Key R&D Projects in Shaanxi Province (Grant No. 2023-ZDLSF-50), the Chinese Academy of Medical Sciences & Peking Union Medical College (2017-CXGC03-2), and the International Joint Research Centre for Cardiovascular Precision Medicine of Shaanxi Province (2020GHJD-14).

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Glycemic variability evaluated by HbA1c rather than fasting plasma glucose is associated with adverse cardiovascular events

Background

Although studies have shown that glycemic variability is positively associated with an increased risk of cardiovascular disease, few studies have compared hemoglobin A1c (HbA1c) and fasting plasma glucose (FPG) variability with adverse cardiovascular events in patients with type 2 diabetes mellitus (T2DM).

Methods

This was a post hoc analysis of the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study. Cox proportional hazards models were used to explore the relationship between HbA1c or FPG variability and the incidence of major adverse cardiovascular events (MACEs).

Results

In total, 9,547 patients with T2DM were enrolled in this study. During the median 4.6 ± 1.5 years follow-up period, 907 patients developed MACEs. The risk of MACEs increased in the HbA1c variability group in each higher quartile of HbA1c variability (P < 0.01). Compared with those in the first quartile of HbA1c variability, patients in the fourth quartile had a hazard ratio of 1.37 (Model 2, 95% confidence interval: 1.13-1.67) for MACEs. Higher FPG variability was not associated with a higher risk of MACEs in patients with T2DM (P for trend=0.28). A U-shaped relationship was observed between HbA1c and FPG variability, and MACEs. Glucose control therapy modified the relationship between HbA1c and MACEs; participants with higher HbA1c variability receiving intensive glucose control were more likely to develop MACEs (P for interaction <0.01).

Conclusion

In adults with T2DM, the relationship between glycemic variability evaluated using HbA1c and FPG was U-shaped, and an increase in HbA1c variability rather than FPG variability was significantly associated with MACEs. The relationship between HbA1c variability and MACEs was affected by the glucose control strategy, and a higher HbA1c variability was more strongly associated with MACEs in patients receiving an intensive glucose control strategy.

Improving cardiovascular risk prediction through machine learning modelling of irregularly repeated electronic health records

Aims

Existing electronic health records (EHRs) often consist of abundant but irregular longitudinal measurements of risk factors. In this study, we aim to leverage such data to improve the risk prediction of atherosclerotic cardiovascular disease (ASCVD) by applying machine learning (ML) algorithms, which can allow automatic screening of the population.

Methods and results

A total of 215 744 Chinese adults aged between 40 and 79 without a history of cardiovascular disease were included (6081 cases) from an EHR-based longitudinal cohort study. To allow interpretability of the model, the predictors of demographic characteristics, medication treatment, and repeatedly measured records of lipids, glycaemia, obesity, blood pressure, and renal function were used. The primary outcome was ASCVD, defined as non-fatal acute myocardial infarction, coronary heart disease death, or fatal and non-fatal stroke. The eXtreme Gradient boosting (XGBoost) algorithm and Least Absolute Shrinkage and Selection Operator (LASSO) regression models were derived to predict the 5-year ASCVD risk. In the validation set, compared with the refitted Chinese guideline-recommended Cox model (i.e. the China-PAR), the XGBoost model had a significantly higher C-statistic of 0.792, (the differences in the C-statistics: 0.011, 0.006-0.017, P < 0.001), with similar results reported for LASSO regression (the differences in the C-statistics: 0.008, 0.005-0.011, P < 0.001). The XGBoost model demonstrated the best calibration performance (men: Dx = 0.598, P = 0.75; women: Dx = 1.867, P = 0.08). Moreover, the risk distribution of the ML algorithms differed from that of the conventional model. The net reclassification improvement rates of XGBoost and LASSO over the Cox model were 3.9% (1.4-6.4%) and 2.8% (0.7-4.9%), respectively.

Conclusion

Machine learning algorithms with irregular, repeated real-world data could improve cardiovascular risk prediction. They demonstrated significantly better performance for reclassification to identify the high-risk population correctly.

Changes in body mass index and waist circumference and heart failure in type 2 diabetes mellitus

Background

To determine the association of unintentional changes in body mass index (BMI) and waist circumference (WC) with the risk of heart failure (HF) among adults with type 2 diabetes mellitus (T2DM).

Methods

This was a randomized controlled trial (the Action to Control Cardiovascular Risk in Diabetes [ACCORD] study), with a double 2×2 factorial design conducted at 77 clinical centers across the United States and Canada. In total, the study comprised 10,251 patients with T2DM and cardiovascular disease (CVD) or at a high risk of CVD. The outcome of interest in the present analysis was incident HF, defined as the first hospitalization event for HF or death due to HF. Hospitalization for HF was based on documented clinical and radiological evidence. Death due to HF was based on clinical, radiological, or postmortem evidence of HF, with an absence of an acute ischemic event according to clinical or postmortem evidence.

Results

Participants with class III obesity had the smallest BMI and WC changes, followed by those with normal weight, overweight, class I obesity, and class II obesity. Increasing BMI (hazard ratio [HR] per standard deviation increase, 1.24; 95% confidence interval [CI], 1.07-1.45) and WC (1.27; 1.10-1.47) were significantly associated with a higher risk of HF. The relationship between BMI and WC changes and HF formed a J-shaped curve, while stable BMI and WC were associated with lower risks of HF. Compared with participants in the first tertiles of BMI and WC change, those in the third tertiles had HRs of 1.41 (95% CI, 1.07-1.45) and 1.48 (1.12-1.95), respectively.

Conclusion

In conclusion, our findings suggest a noteworthy association between BMI and WC changes among adults with T2DM in HF. We observed a distinctive J-shaped curve in this relationship, indicating that participants with both low and high BMI and WC changes were more susceptible to developing HF.

Trial registration

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

Association between weight variability, weight change and clinical outcomes in hypertension

Objective

The effect of body weight variability (BWV) and body weight change (BWC) in high-risk individuals with hypertension, but without diabetes mellitus (DM) remains unclear. We examined the effect of BWV and BWC on the primary outcome [the composite of myocardial infarction (MI), other acute coronary syndromes, stroke, acute decompensated heart failure (HF), or cardiovascular (CV) death] and all-cause mortality in the Systolic Blood Pressure Intervention Trial (SPRINT).

Methods

In this post-hoc analysis, we used multivariate Cox regression models to examine the risk associated with BWV and BWC for the primary outcome in SPRINT. BWV was defined as the intra-individual average successive variability (ASV). BWC was defined as baseline weight minus final weight.

Results

A total of 8714 SPRINT participants (mean age 67.8 ± 9.4 years, 35.1 % women, 58.9 % Whites) with available data on body weight were included. The median follow-up was about 3.9 years (IQR, 3.3-4.4). In multivariable-adjusted Cox models, each 1 unit standard deviation (SD) of BWV was significantly associated with a higher risk for the primary outcome, all-cause mortality, HF, MI, and stroke [HR(95 % CI)]: 1.13 (1.07-1.19; p < 0.0001), 1.22 (1.14-1.30; p < 0.0001), 1.16 (1.07-1.26; p < 0.001), 1.10 (1.00-1.20; p = 0.047), and 1.15 (1.05-1.27; p = 0.005), respectively. Similarly, each 1 unit SD of BWC was significantly associated with a higher risk of the primary outcome, all-cause mortality, MI, and HF: 1.11(1.02-1.21; p = 0.017), 1.44 (1.26-1.65; p < 0.0001), 1.16 (1.01-1.32; p = 0.041) and 1.19 (1.02-1.40; p = 0.031) respectively. However, there was no significant association with CV death (for both BWV and BWC) or stroke (BWC).

Conclusion

In high-risk hypertension, BWV and BWC were both associated with higher risk of the primary outcome and all-cause mortality. These results further stress the clinical importance of sustained weight loss and minimizing fluctuations in weight in hypertension.

Metaflammation in obesity and its therapeutic targeting

Obesity-associated inflammation is a systemic process that affects all metabolic organs. Prominent among these is adipose tissue, where cells of the innate and adaptive immune system are markedly changed in obesity, implicating these cells in a range of processes linking immune memory to metabolic regulation. Furthermore, weight loss and weight cycling have unexpected effects on adipose tissue immune populations. Here, we review the current literature on the roles of various immune cells in lean and obese adipose tissue. Within this context, we discuss pharmacological and nonpharmacological approaches to obesity treatment and their impact on systemic inflammation.

Single cell RNA-sequencing suggests a novel lipid associated mast cell population following weight cycling

Our recent study showed weight cycled mice have increased adipose mast cells compared to obese mice by single cell RNA-sequencing. Here, we aimed to confirm and elucidate these changes. Further analysis of our dataset showed that our initial mast cell cluster could subcluster into two unique populations: one with very high expression of classical mast cell markers and another with elevated lipid handling and antigen presentation genes. This new mast cell cluster accounted for most of the mast cells in the weight cycled group although it was not possible to detect the different populations by new studies with flow cytometry or Toluidine blue staining in mice, possibly due to a downregulation in classical mast cell genes. Interestingly, a pilot study in humans did suggest the existence of two mast cell populations in subcutaneous adipose tissue from obese women that appear similar to the murine populations detected by sequencing; one of which was significantly correlated with weight variance. Together, these data suggest that weight cycling may induce a unique population of mast cells similar to lipid associated macrophages. Future studies will focus on isolation of these cells to better determine their lineage, differentiation, and functional roles.

Association Between Body Weight Changes and Subsequent Development of Out-of-Hospital Cardiac Arrest: A Population-Based Nested Case-Control Study

BACKGROUND

Body weight is a modifiable demographic factor. Although the association of body mass index (BMI) categories with sudden cardiac death was reported, dynamic changes of BMI and the risk of cardiac arrest remain unknown. This study aimed to evaluate the association between the out-of-hospital cardiac arrest (OHCA) occurrence within a year and the percent changes of BMI preceding the OHCA.

METHODS

This population-based nested case-control study used the National Health Insurance Service Data of Korea. In all, 24,465 patients with non-traumatic OHCA between 2010 and 2018, who underwent national health check-up twice (one within a year and the other within 2-4 years before OHCA) and 32,434 controls without OHCA, were matched for age and sex. The association between the risk of OHCA and BMI percent change stratified by sex was investigated.

RESULTS

All the BMI percent changes of ≥ 5% significantly increased the OHCA occurrence with a reverse J-shaped association. Compared to individuals with a stable weight, those with severe (> 15%) BMI decrease had the highest odds ratio (OR) of 4.29 (95% confidence intervals [CIs], 3.72-4.95) for OHCA occurrence followed by those with moderate (10-15%) weight loss (OR, 2.80; 95% CI, 2.55-3.08) and those with severe (> 15%) weigh gain (OR, 2.24; 95% CI, 1.96-2.57), respectively. The impact of weight loss on the cardiac arrest occurrence was more prominent in men, while the impact of weight gain was more prominent in women.

CONCLUSION

Significant weight changes increase the risk of OHCA within a year with a reverse J-shaped association. Significant weight loss might be a warning sign for OHCA especially for men.

Emerging Medical Therapies for the Treatment of Obesity in Women with Cardiovascular Diseases

PURPOSE OF REVIEW

In this review, the impact of obesity on cardiovascular disease in women and emerging anti-obesity pharmacologic treatments are discussed.

RECENT FINDINGS

Robust evidence demonstrates the burden of obesity across the lifespan in women and links obesity to a diverse set of cardiovascular diseases. Female-specific risk factors including sex hormones and pregnancy factors intersect with obesity and cardiovascular risk. Sustained weight loss has potential for cardiovascular benefits. Recent trials demonstrate cardiovascular benefits of emerging agents with weight loss effects including GLP-1 RA and SGLT2 inhibitors in women. Treatment and prevention strategies for cardiovascular disease in obese women should include integration of weight management strategies including the targeted use of emerging pharmacologic therapies.

Effects of body weight variability on risks of macro- and microvascular outcomes in individuals with type 2 diabetes: The Rio de Janeiro type 2 diabetes cohort

AIMS

To investigate the effects of body weight variability (BWV) on macro- and microvascular outcomes in a type 2 diabetes cohort.

METHODS

BWV parameters were assessed in 684 individuals. Multivariable Cox regressions examined associations between BWV parameters and cardiovascular outcomes (total cardiovascular events [CVEs], major CVEs [MACEs], cardiovascular deaths),all-cause mortality and microvascular outcomes. Interaction/subgroup analyses were performed according to being physically-active/sedentary and having/not lost ≥ 5 % of weight.

RESULTS

Median follow-up was 11 years over which 194 total CVEs (174 MACEs), and 223 all-cause deaths (110 cardiovascular), occurred. There were 215 renal, 152 retinopathy and 167 peripheral neuropathy development/worsening outcomes. In general, increased BWV was associated with higher risks of CVEs, MACEs, all-cause mortality, advanced renal failure and peripheral neuropathy outcomes, but not of microalbuminuria and retinopathy outcomes. On interaction/subgroup analyses, increased BWV was associated with higher risks of outcomes in sedentary individuals and in those who did not lose ≥ 5 % of body weight. In physically-active participants or in those who lost ≥ 5 % weight, the adjusted risks were null or protective.

CONCLUSIONS

Increased BWV was associated with most adverse outcomes; however, in those who were physically-active or consistently losing weight, it was not hazardous and might be even beneficial.

The inverted U-shaped relationship between weight loss percentage and cardiovascular health scores

PURPOSE

Obesity is a significant risk factor for cardiovascular disease; however, the impact of weight loss on cardiovascular health (CVH) in individuals with specific obesity patterns remains incompletely understood. The objective of our study was to investigate the relationship weight loss percentage and CVH scores across individuals with various obesity patterns.

METHODS

Our study utilized data from the National Health and Nutrition Examination Survey conducted between 2007 and 2018, involving a total of 12,835 participants aged 16 years or older, to conduct a cross-sectional analysis. Multiple linear regression and multinomial logistic regression methods were used to assess the correlation between the weight loss percentage and the CVH scores. Additionally, restricted cubic spline analysis was employed to examine the nonlinear relationship between the two variables.

RESULTS

Compared to individuals with a weight loss percentage < 0%, participants with weight loss percentages of 0-5% and 5.1-10% showed improved CVH scores, with β values of 2.85 (95% CI 2.32-3.38) and 2.55 (95% CI 1.69-3.4), respectively. Regarding different obesity patterns, compared to participants with a weight loss percentage < 0%, participants with a weight loss percentage of 0-5% showed an increase in CVH scores in the normal weight and overweight/general obesity (OGO) groups, with β values of 1.45 (95% CI 0.7-2.19) and 1.22 (95% CI 0.46-1.97), respectively. Restricted cubic spline analysis revealed a significant inverted U-shaped relationship between the weight loss percentage and the CVH scores (with optimal CVH scores at 3%).

CONCLUSIONS

There was an inverted U-shaped relationship between weight loss percentage and CVH scores, with moderate weight loss (0-10%, optimal value of 3%) being associated with improved CVH scores, especially among individuals with OGO.

LEVEL V

Opinions of respected authorities, based on descriptive studies, narrative reviews, clinical experience, or reports of expert committees.

Modeling BMI z score lability during childhood as a function of child temperament and genetic risk for obesity

OBJECTIVE

This study aimed to examine whether child genetic risk for obesity and temperament (i.e., negative affectivity, effortful control) accounted for stability versus lability in children's weight status (BMI z score) over time.

METHODS

A total of 561 adopted children (42% female; 56% Caucasian, 13% African American, 11% Latino, and 20% other) and their birth and adoptive parents were followed from birth to age 9 years. The multilevel location-scale model was used to examine whether child genetic risk for obesity and temperament were related to differences in level and lability in child BMI z scores over time.

RESULTS

For the full sample, higher levels of child negative affectivity were associated with greater BMI z score lability, whereas higher levels of effortful control and children's mean-level BMI z scores were related to less lability across childhood. Additional analyses examined associations within groups of children with healthy versus overweight/obesity weight statuses. Within the healthy weight status group only, better effortful control was associated with more stable BMI z scores, whereas genetic risk for higher BMI was associated with more labile BMI z scores.

CONCLUSIONS

These findings provide insights into factors that can be harnessed to redirect unhealthy trajectories as well as factors that may challenge redirection or maintain a healthy trajectory.

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

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

The Effect of Catgut Embedding at Acupoints Versus Nonacupoints in Abdominal Obesity: Protocol for a Multicenter, Double-Blind, 16-Week Randomized Controlled Trial

BACKGROUND

Obesity is an increasing problem worldwide. The effective treatments for obesity mainly include diet, physical activity, behavioral intervention, pharmacotherapy, and bariatric surgery, which all have certain limitations. As a specific type of acupuncture therapy, acupoint catgut embedding (ACE) has gained substantial attention in the management of obesity in recent years. Previous studies suggested that ACE may be an effective obesity treatment. However, the evidence for the efficacy of ACE in abdominal obesity (AO) remains inadequate due to the paucity of high-quality studies.

OBJECTIVE

This study aims to investigate the difference in the effectiveness of catgut embedding at acupoints and catgut embedding at nonacupoints in patients with AO and to further validate the efficacy and safety of ACE for AO.

METHODS

This is a multicenter, double-blind, 16-week randomized controlled trial. A total of 92 eligible participants with AO will be randomly divided into 2 groups (1:1 allocation ratio). The ACE group will receive catgut embedding at acupoints and the control group will receive catgut embedding at nonacupoints. The intervention will be performed every 2 weeks for a total of 6 sessions. Follow-up will be performed every 2 weeks for a total of 2 visits. The primary outcome is waist circumference. Secondary outcomes include body weight, BMI, hip circumference, and the visual analog scale of appetite. Upon the completion of the trial, we will evaluate the effect of catgut embedding at acupoints or nonacupoints on obesity indicators in patients with AO. For treatment outcomes, an intention-to-treat analysis will be performed.

RESULTS

The start of recruitment began in August 2019 and is expected to end in September 2023.

CONCLUSIONS

Although studies have been conducted to demonstrate the effectiveness of ACE in the treatment of obesity, the evidence for the efficacy of ACE in AO remains insufficient due to the quality of the studies. This rigorous normative randomized controlled trial will verify the effect of catgut embedding at acupoints or nonacupoints in patients with AO. The findings will provide credible evidence as to whether ACE is an effective and safe treatment for AO.

TRIAL REGISTRATION

Chinese Clinical Trial Registry ChiCTR1800016947; https://tinyurl.com/2p82257p.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/46863.

High body weight variability is associated with increased risk of depression: a nationwide cohort study in South Korea

BACKGROUND

Body weight variability (BWV) negatively affects the incidence and outcomes of various diseases, but the nature of the association between BWV and depression remains unclear. In this study, we aimed to test the hypothesis that BWV is associated with the risk of new-onset depression.

METHODS

Data from a nationwide population-based cohort in the Korean National Health Insurance Service database were analyzed for 6 598 570 adults with no history of depression and reports of at least three health examinations. BWV was estimated using variability independent of the mean indices and divided into quartiles (Q1 lowest, Q4 highest BWV). Cox proportional hazard models were applied to assess the risk of depression according to the quartile of BWV.

RESULTS

The incident rate for depression from Q1 to Q4 of BWV was 20.7, 20.3, 20.8, and 22.2 per 1000 person-years, respectively. BWV, especially high BWV, was associated with an increased risk of depression after adjusting for age, sex, smoking, alcohol consumption, physical activity, income, diabetes mellitus, hypertension, and dyslipidemia. The hazard ratio (HR) of new-onset depression was highest in Q4 relative to Q1 in the total population (HR 1.12, p < 0.0001) and was higher in women than in men (HR 1.72 v. 1.16, p < 0.0001). In stratified analyses, regardless of obesity or weight change status at baseline, the risk of depression was increased when bodyweight fluctuated highly during follow-up.

CONCLUSIONS

High BWV was associated with an increased risk of depression. Further studies need to evaluate the role of high BWV with respect to the onset of depression.

Weight cycling and risk of clinical adverse events in patients with heart failure with preserved ejection fraction: a post-hoc analysis of TOPCAT

Background

Previous studies hardly evaluated the association of variability of body mass index (BMI) or waist circumference with clinical adverse events and investigated whether weight cycling had an effect on the prognosis of patients with heart failure with preserved ejection fraction (HFpEF).

Methods

This study was a post-hoc analysis of TOPCAT. Three outcomes were evaluated: the primary endpoint, cardiovascular disease (CVD) death, and heart failure hospitalization. Among them, CVD death and hospitalization were outcomes of heart failure. Kaplan-Meier curves were used to describe the cumulative risk of outcome and were tested using the log-rank test. Cox proportional hazards regression models were used to calculate hazard ratios (HRs) and 95%CIs for outcomes. We also performed a subgroup analysis, and several subgroups were compared.

Results

A total of 3,146 patients were included. In the Kaplan-Meier curves, the coefficients of variation of both BMI and waist circumference were grouped according to quartiles, with the Q4 group having the highest cumulative risk (log-rank P < 0.001). In the coefficient of BMI variation and the outcomes, the HRs for group Q4 of coefficient of variation of BMI were 2.35 (95%CI: 1.82, 3.03) for the primary endpoint, 2.40 (95%CI: 1.69, 3.40) for death, and 2.33 (95%CI: 1.68, 3.22) for HF hospitalization in model 3 (fully adjusted model) compared with group Q1. In the coefficient of waist circumference variation and the outcomes, group Q4 had increased hazard of the primary endpoint [HR: 2.39 (95%CI: 1.84, 3.12)], CVD death [HR: 3.29 (95%CI: 2.28, 4.77)], and HF hospitalization [HR: 1.98 (95%CI 1.43, 2.75)] in model 3 (fully adjusted model) compared with group Q1. In the subgroup analysis, there was a significant interaction in the diabetes mellitus subgroup (P for interaction = 0.0234).

Conclusion

Weight cycling had a negative effect on the prognosis of patients with HFpEF. The presence of comorbid diabetes weakened the relationship between waist circumference variability and clinical adverse events.

Differences in Adherence to American Heart Association's Life's Essential 8, Diet Quality, and Weight Loss Strategies Between Those With and Without Recent Clinically Significant Weight Loss in a Nationally Representative Sample of US Adults

Background The American Heart Association defines ideal cardiovascular health based on 8 risk factors (Life's Essential 8 [LE8]); a high LE8 score (range 0-100) reflects greater adherence to their recommendations. Weight status influences cardiovascular health, yet individuals may use detrimental diet and weight loss strategies to improve weight status. We assessed differences in LE8 adherence, diet quality, and weight loss strategies between those with and without a recent history of clinically significant weight loss (CSWL). Methods and Results Data from 2007 to 2016 National Health and Nutrition Examination Survey questionnaires, clinical measures, and 24-hour dietary recalls were assessed to determine LE8 adherence, diet quality (Healthy Eating Index), and weight loss strategies between adults with: (1) intentional CSWL ≥5%; and (2) non-CSWL <5%, weight maintenance, or weight gain over the past 12 months using ANCOVA and chi-square tests. Those with CSWL demonstrated higher scores for diet quality (P=0.014), physical activity (P<0.001), and blood lipids (P<0.001). Those without CSWL reported lower BMI (P<0.001). There were no differences in total LE8 cardiovascular health scores between those with and without CSWL. More individuals with CSWL reported weight loss strategies of exercising (P=0.016); those without CSWL reported skipping meals (P=0.002) and using prescription diet pills (P<0.001). Conclusions Greater adherence to the LE8 recommendations was observed among individuals with CSWL, although overall LE8 scores were low. Future research should address the implementation of evidence-based strategies that improve diet quality while promoting optimal cardiovascular health among those with intent to lose weight.

Long-Term Effect of Weight Regain Following Behavioral Weight Management Programs on Cardiometabolic Disease Incidence and Risk: Systematic Review and Meta-Analysis

BACKGROUND

Behavioral weight management programs (BWMPs) enhance weight loss in the short term, but longer term cardiometabolic effects are uncertain as weight is commonly regained. We assessed the impact of weight regain after BWMPs on cardiovascular risk factors, diabetes, and cardiovascular disease.

METHODS

Trial registries, 11 databases, and forward-citation searching (latest search, December 19) were used to identify articles published in English, from any geographical region. Randomized trials of BWMPs in adults with overweight/obesity reporting cardiometabolic outcomes at ≥12 months at and after program end were included. Differences between more intensive interventions and comparator groups were synthesized using mixed-effects, meta-regression, and time-to-event models to assess the impact of weight regain on cardiovascular disease incidence and risk.

RESULTS

One hundred twenty-four trials reporting on ≥1 cardiometabolic outcomes with a median follow-up of 28 (range, 11-360) months after program end were included. Median baseline participant body mass index was 33 kg/m2; median age was 51 years. Eight and 15 study arms (7889 and 4202 participants, respectively) examined the incidence of cardiovascular disease and type 2 diabetes, respectively, with imprecise evidence of a lower incidence for at least 5 years. Weight regain in BWMPs relative to comparators reduced these differences. One and 5 years after program end, total cholesterol/HDL (high-density lipoprotein) ratio was 1.5 points lower at both times (82 studies; 19 003 participants), systolic blood pressure was 1.5 mm mercury and 0.4 mm lower (84 studies; 30 836 participants), and HbA1c (%) 0.38 lower at both times (94 studies; 28 083 participants). Of the included studies, 22% were judged at high risk of bias; removing these did not meaningfully change results.

CONCLUSIONS

Despite weight regain, BWMPs reduce cardiometabolic risk factors with effects lasting at least 5 years after program end and dwindling with weight regain. Evidence that they reduce the incidence of cardiovascular disease or diabetes is less certain. Few studies followed participants for ≥5 years.

REGISTRATION

URL: https://www.crd.york.ac.uk/PROSPERO/; Unique identifier: CRD42018105744.

High Variability of Body Mass Index Independently Associated with Incident Heart Failure

Background

Heart failure (HF) is a serious condition with increasing prevalence, high morbidity, and increased mortality. Obesity is an established risk factor for cardiovascular diseases, including HF. Fluctuation in body mass index (BMI) has shown a higher risk of cardiovascular outcomes. We investigated the association between BMI variability and incident HF.

Methods

In the UK Biobank, we established a prospective cohort after excluding participants with prevalent HF or cancer at enrollment. A total of 99,368 White (British, Irish, and any other white background) participants with ≥ 3 BMI measures during > 2 years preceding enrollment were included, with a median follow-up of 12.5 years. The within-participant variability of BMI was evaluated using standardized standard deviation (SD) and coefficient of variation (CV). The association of BMI variability with incident HF was assessed using Fine and Gray's competing risk model, and adjusted for age, sex, smoking history, alcohol consumption, diabetes, hypertension, history of heart attack, stroke, atrial fibrillation, lipids, estimated glomerular filtration rate and mean BMI per individual.

Results

In the fully adjusted model, higher BMI variability measured in both SD and CV were significantly associated with higher risk in HF incidence (SD: Hazard Ratio [HR] 1.05, 95% Confidence Interval [CI] 1.02 - 1.07, p = 0.0002; CV: HR 1.06, 95% CI 1.04 - 1.09, p < 0.0001).

Conclusions

Longitudinal health records capture BMI fluctuation, which independently predicts HF incidence. Integration of long-term BMI and other routinely measured health factors may improve risk prediction of HF and other cardiovascular outcomes.

Weight variability and diabetes complications

Body weight is a recognized risk factor for cardiovascular diseases (CVD). More recently, weight variability, i.e. the oscillation of body weight over time, has also been suggested to be independently associated with development of CVD and mortality in subjects without diabetes and in people with both type 1 and type 2 diabetes (T2D). In T2D, weight variability emerged as one of the most relevant risk factors for CVD and it was suggested to interact with the variability of other risk factors to identify people at high cardiovascular risk. In addition, weight variability seems also to confer a higher risk for microvascular complications in people with T2D. While the exact mechanism linking weight variability to CVD is unknown, evidence from experimental models suggests that weight cycling promote an enduring pro-inflammatory program in the adipose tissue. Here we review the clinical evidence relative to the association of weight variability with CVD and microvascular complications of diabetes. We then briefly summarize the alterations proposed to explain this association. Finally, we synthesize the possible strategies, e.g. specific dietetic regimens and available glucose-lowering drugs, to minimize weight fluctuations.

Variability in Lipid Levels and Risk for Cardiovascular Disease: An Electronic Health Record-Based Population Cohort Study

Background Larger within-patient variability of lipid levels has been associated with increased risk of cardiovascular disease (CVD); however, measures of lipid variability require ≥3 measurements and are not currently used clinically. We investigated the feasibility of calculating lipid variability within a large electronic health record-based population cohort and assessed associations with incident CVD. Methods and Results We identified all individuals ≥40 years of age who resided in Olmsted County, MN, on January 1, 2006 (index date), without prior CVD, defined as myocardial infarction, coronary artery bypass graft surgery, percutaneous coronary intervention, or CVD death. Patients with ≥3 measurements of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, or triglycerides during the 5 years before the index date were retained. Lipid variability was calculated using variability independent of the mean. Patients were followed through December 31, 2020 for incident CVD. We identified 19 652 individuals (mean age 61 years; 55% female), who were CVD-free and had variability independent of the mean calculated for at least 1 lipid type. After adjustment, those with highest total cholesterol variability had a 20% increased risk of CVD (Q5 versus Q1 hazard ratio, 1.20 [95% CI, 1.06-1.37]). Results were similar for low-density lipoprotein cholesterol and high-density lipoprotein cholesterol. Conclusions In a large electronic health record-based population cohort, high variability in total cholesterol, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol was associated with an increased risk of CVD, independent of traditional risk factors, suggesting it may be a possible risk marker and target for intervention. Lipid variability can be calculated in the electronic health record environment, but more research is needed to determine its clinical utility.

Body Mass Index Measured Repeatedly over 42 Years as a Risk Factor for Ischemic Stroke: The HUNT Study

BACKGROUND

Higher BMI in middle age is associated with ischemic stroke, but little is known about BMI over adulthood, and the risk for ischemic stroke as most studies relied on a single measurement of BMI.

METHODS

BMI was measured four times over a period of 42 years. We calculated average BMI values and group-based trajectory models and related these to the prospective risk of ischemic stroke after the last examination in Cox models with a follow-up time of 12 years.

RESULTS

A total of 14,139 participants, with a mean age of 65.2 years and 55.4% women, had information on BMI from all four examinations, and we observed 856 ischemic strokes. People with overweight and obesity over adulthood had a higher risk for ischemic stroke with a multivariable-adjusted hazard ratio of 1.29 (95% CI 1.11-1.48) and 1.27 (95% CI 0.96-1.67), respectively, when compared to normal weight participants. Excess weight tended to have stronger effects earlier than later in life. A trajectory of developing obesity throughout life was associated with higher risk than other trajectories.

CONCLUSIONS

High average BMI, especially at an early age, is a risk factor for ischemic stroke. Early weight control and long-term weight reduction for those with high BMI may decrease the later occurrence of ischemic stroke.

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Association of hemoglobin variability with the risk of cardiovascular disease: a nationally representative retrospective cohort study from South Korea

Hemoglobin variability is known to increase cardiovascular mortality in chronic kidney disease, but the association of hemoglobin variability with the risk of cardiovascular disease (CVD) in the general population is yet unclear. This retrospective cohort study based on 'the South Korean National Health Insurance Service database' consisted of 198,347 adults who went through all three health examinations. Hemoglobin variability is defined as the average successive variability of three separate hemoglobin values from each health screening period. Participants were followed up for 6 years to determine the risk of coronary heart disease and stroke. We used multivariate Cox proportional hazards regression to examine the adjusted hazard ratios for CVD according to hemoglobin variability. Per 1 unit increase of hemoglobin variability, the risk for CVD (aHR 1.06, 95% CI 1.02-1.09) and stroke (aHR 1.08, 95% CI 1.03-1.13) increased significantly. The risk-increasing trend was preserved in the low-to-moderate risk group of CVDs (aHR 1.07, 95% CI 1.02-1.11). This result suggests that subjects with high hemoglobin variability who would otherwise be categorized as having low-to-moderate CVD risk may have higher risk of CVD than those with low hemoglobin variability.

Are Current Guidelines Perpetuating Weight Stigma? A Weight-Skeptical Approach to the Care of Patients with Obesity

Significant controversy exists regarding the evidence to support the clinical benefits and risks of weight loss interventions for individuals with obesity. United States Preventative Task Force (USPSTF) guidelines recommend weight loss for all individuals with obesity while weight-neutral models such as Health at Every Size promote weight inclusivity, focusing on body acceptance rather than weight loss. We discuss how lifestyle-based weight-centric paradigms, such as the USPSTF Guidelines, may increase weight stigma and weight cycling, and many of their purported clinical benefits are not supported by existing evidence. However, we also acknowledge the clear benefits of metabolic surgery in high-risk individuals, and the potential benefits for pharmacotherapy for obesity in selected patients. Herein we describe a weight-skeptical approach to the care of patients with obesity that aims to use available evidence to support patient-centered care.

Repercussions of absolute and time-rated BMI "yo-yo" fluctuations on cardiovascular stress-related morbidities within the vascular-metabolic CUN cohort

Aims

The association between body mass index (BMI) fluctuation and BMI fluctuation rate with cardiovascular stress morbidities in a Caucasian European cohort was evaluated to ascertain the impact of weight cycling.

Methods

A total of 4,312 patients of the Vascular-Metabolic CUN cohort (VMCUN cohort) were examined and followed up during 9.35 years ( ± 4.39). Cox proportional hazard ratio analyses were performed to assess the risk of developing cardiovascular stress-related diseases (CVDs) across quartiles of BMI fluctuation, measured as the average successive variability (ASV) (ASV = |BMIt0 - BMIt1| + |BMIt1 - BMIt2| + |BMIt2-BMIt3| +…+ |BMItn - 1 - BMItn|/n - 1), and quartiles of BMI fluctuation rate (ASV/year).

Results

There were 436 incident cases of CVD-associated events involving 40,323.32 person-years of follow-up. A progressively increased risk of CVD in subjects with greater ASV levels was found. Also, a higher level of ASV/year was significantly associated with an increased risk of developing CVD stress independent of confounding factors with a value of 3.71 (95% CI: 2.71-5.07) for those in the highest quartile and 1.82 (95% CI: 1.33-2.50) for those in the third quartile.

Conclusions

The BMI fluctuation rate seems to be a better predictor than BMI fluctuation of the potential development of cardiovascular stress morbidities. The time-rated weight fluctuations are apparently more determinant in increasing the risk of a CVD than the weight fluctuation itself, which is remarkable in subjects under "yo-yo" weight patterns for precision medicine.

Weight variability and cardiovascular outcomes: a systematic review and meta-analysis

The association between body weight variability and the risk of cardiovascular disease (CVD) has been investigated previously with mixed findings. However, there has been no extensive study which systematically evaluates the current evidence. Furthermore, the impact of ethnicity and type 2 diabetes on this phenomena has not yet been investigated. Therefore, the aim of this study was to comprehensively evaluate the effect of weight variability on risk of CVD (any cardiovascular (CV) event, composite CV outcome, CV death, Stroke, Myocardial Infarction) and the influence of ethnicity and type 2 diabetes status on the observed association. A systematic review and meta-analysis was performed according to the meta-analyses of observational studies in epidemiology (MOOSE) guidelines. The electronic databases PubMed, Web of Science, and the Cochrane Library were searched for studies that investigated the relationship between body weight or BMI variability and CV diseases using Medical Subject Headings (MeSH) terms and keywords. The relative risks (RRs) for the outcomes were collected from studies, pooled, and analysed using a random-effects model to estimate the overall relative risk. Of 5645 articles screened, 23 studies with a total population of 15,382,537 fulfilled the prespecified criteria and were included. Individuals in the highest strata of body weight variability were found to have significantly increased risk of any CV event (RR = 1.27; 95% Confidence Interval (CI) 1.17-1.38; P < 0.0001; I² = 97.28%), cardiovascular death (RR = 1.29; 95% CI 1.03-1.60; P < 0.0001; I² = 55.16%), myocardial infarction (RR = 1.32; 95% CI 1.09-1.59; P = 0.0037; I² = 97.14%), stroke (RR = 1.21; 95% CI 1.19-1.24; P < 0.0001; I² = 0.06%), and compound CVD outcomes (RR = 1.36; 95% CI 1.08-1.73; P = 0.01; I² = 92.41%). Similar RRs were observed regarding BMI variability and per unit standard deviation (SD) increase in body weight variability. Comparable effects were seen in people with and without diabetes, in White Europeans and Asians. In conclusion, body weight variability is associated with increased risk of CV diseases regardless of ethnicity or diabetes status. Future research is needed to prove a causative link between weight variability and CVD risk, as appropriate interventions to maintain stable weight could positively influence CVD.

Effect of intensive lifestyle intervention on the association between weight variability and major adverse cardiovascular events in overweight or obese adults with type 2 diabetes mellitus

AIMS/INTRODUCTION

Weight variability is associated with cardiovascular outcomes in diabetic patients. However, whether the guideline-recommended intensive lifestyle intervention (ILI) will affect this association in overweight or obese adults with diabetes is not well established.

MATERIALS AND METHODS

In 3,859 participants from the Action for Health in Diabetes (Look AHEAD) trial, the associations of 4 year weight variability measured by variability independent of the mean (VIM) with major adverse cardiovascular event (MACE) and secondary outcomes in ILI and diabetes support & education (DSE) arm were evaluated.

RESULTS

During a median follow-up of 9.6 years, 255 (12.9%) participants in the ILI arm and 247 (13.2%) participants in the DSE arm developed MACE. Participants with the highest quartile of weight variability (VIM Q4) experienced a 2.23-fold higher risk of MACE compared with the lowest quartile (VIM Q1) in the DSE arm (hazard ratio [HR] 2.23; 95% CI 1.51-3.30). Compared with the lowest weight variability (VIM Q1), participants with the highest weight variability (VIM Q4) were associated with higher risks of secondary cardiovascular composite outcome (HR 1.88; 95% CI 1.20-2.95), all-cause mortality (HR 3.19; 95% CI 1.75-5.82), and myocardial infarction (HR 1.95; 95% CI 1.12-3.37) in the DSE arm.

CONCLUSIONS

Among the overweight or obese individuals with type 2 diabetes mellitus, rising weight variability was independently associated with increased MACE risks in the DSE arm. Therefore, a guideline-recommended ILI strategy for weight loss should be adopted to improve cardiovascular outcomes without worrying about the effect of weight fluctuations.

Tripartite motif-containing protein 31 confers protection against nonalcoholic steatohepatitis by deactivating mitogen-activated protein kinase kinase kinase 7

BACKGROUND AIMS

As a global health threat, NASH has been confirmed to be a chronic progressive liver disease that is strongly associated with obesity. However, no approved drugs or efficient therapeutic strategies are valid, mainly because its complicated pathological processes is underestimated.

APPROACH RESULTS

We identified the RING-type E3 ubiquitin transferase-tripartite motif-containing protein 31 (TRIM31), a member of the E3 ubiquitin ligases family, as an efficient endogenous inhibitor of transforming growth factor-beta-activated kinase 1 (mitogen-activated protein kinase kinase kinase 7; MAP3K7), and we further confirmed that TRIM31 is an MAP3K7-interacting protein and promotes MAP3K7 degradation by enhancing ubiquitination of K48 linkage in hepatocytes. Hepatocyte-specific Trim31 deletion blocks hepatic metabolism homeostasis, concomitant with glucose metabolic syndrome, lipid accumulation, up-regulated inflammation, and dramatically facilitates NASH progression. Inversely, transgenic overexpression, lentivirus, or adeno-associated virus-mediated Trim31 gene therapy restrain NASH in three dietary mice models. Mechanistically, in response to metabolic insults, TRIM31 interacts with MAP3K7 and conjugates K48-linked ubiquitination chains to promote MAP3K7 degradation, thus blocking MAP3K7 abundance and its downstream signaling cascade activation in hepatocytes.

CONCLUSIONS

TRIM31 may serve as a promising therapeutic target for NASH treatment and associated metabolic disorders.