Plasma circulating microRNAs associated with obesity, body fat distribution, and fat mass: the Rotterdam Study.

BACKGROUND: MicroRNAs (miRNAs) represent a class of small non-coding RNAs that regulate gene expression post-transcriptionally and are implicated in the pathogenesis of different diseases. Limited studies have investigated the association of circulating miRNAs with obesity and body fat distribution and their link to obesity-related diseases using population-based data. METHODS: We conducted a genome-wide profile of circulating miRNAs in plasma, collected between 2002 and 2005, in 1208 participants from the population-based Rotterdam Study cohort. Obesity and body fat distribution were measured as body mass index (BMI), waist-to-hip ratio (WHR), android-fat to gynoid-fat ratio (AGR), and fat mass index (FMI) measured by anthropometrics and Dual X-ray Absorptiometry. Multivariable linear regression models were used to assess the association of 591 miRNAs well-expressed in plasma with these traits adjusted for potential covariates. We further sought for the association of identified miRNAs with cardiovascular and metabolic diseases in the Rotterdam study and previous publications. RESULTS: Plasma levels of 65 miRNAs were associated with BMI, 40 miRNAs with WHR, 65 miRNAs with FMI, and 15 miRNAs with AGR surpassing the Bonferroni-corrected P < 8.46 × 10-5. Of these, 12 miRNAs were significantly associated with all traits, while four miRNAs were associated only with WHR, three miRNAs only with FMI, and miR-378i was associated only with AGR. The most significant association among the overlapping miRNAs was with miR-193a-5p, which was shown to be associated with type 2 diabetes and hepatic steatosis in the Rotterdam Study. Moreover, five of the obesity-associated miRNAs and two of the body fat distribution miRNAs have been correlated previously to cardiovascular disease. CONCLUSIONS: This study indicates that plasma levels of several miRNAs are associated with obesity and body fat distribution which could help to better understand the underlying mechanisms and may have the biomarker potential for obesity-related diseases.

Healthy lifestyle in older adults and life expectancy with and without heart failure.

Several lifestyle factors have been linked to risk for heart failure (HF) and premature mortality. The aim of this study was to estimate the impact of a healthy lifestyle on life expectancy with and without HF among men and women from a general population. This study was performed among 6113 participants (mean age 65.8 ± 9.7 years; 58.9% women) from the Rotterdam Study, a large prospective population-based cohort study. A continuous lifestyle score was created based on five lifestyle factors: smoking status, alcohol consumption, diet quality, physical activity and weight status (assessed 1995-2008). The lifestyle score was categorized into three levels: unhealthy (reference), intermediate and healthy. Gompertz regression and multistate life tables were used to estimate the effects of lifestyle on life expectancy with and without HF in men and women separately at ages 45, 65 and 85 years (follow-up until 2016). During an average follow-up of 11.3 years, 699 incident HF events and 2146 deaths occurred. At the age of 45 years, men in the healthy lifestyle category had a 4.4 (95% CI: 4.1-4.7) years longer total life expectancy than men in the unhealthy lifestyle category, and a 4.8 (95% CI: 4.4-5.1) years longer life expectancy free of HF. Among women, the difference in total life-expectancy at the age of 45 years was 3.4 (95% CI: 3.2-3.5) years and was 3.4 (95% CI: 3.3-3.6) years longer for life expectancy without HF. This effect persisted also at older ages. An overall healthy lifestyle can have a positive impact on total life expectancy and life expectancy free of HF.

Physical activity and sedentary behaviour changes during and after cardiac rehabilitation: Can patients be clustered?

OBJECTIVE: To identify clusters of patients according to changes in their physical behaviour during and after cardiac rehabilitation, and to predict cluster membership. METHODS: The study included 533 patients (mean age 57.9 years; 18.2% females) with a recent acute coronary syndrome who participated in a 12-week multi-disciplinary cardiac rehabilitation programme, within a cohort study design. Physical behaviour (light physical activity, moderate-to vigorous physical activity, step count, and sedentary behaviour) was measured using accelerometry at 4 timepoints. To identify clusters of patients according to changes in physical behaviour during and after cardiac rehabilitation, latent class trajectory modelling was applied. Baseline factors to predict cluster membership were assessed using multinomial logistic regression. RESULTS: During and after cardiac rehabilitation, 3 separate clusters were identified for all 4 physical behaviour outcomes: patients with steady levels (comprising 68-83% of the patients), and improving (6-21%) or deteriorating (4-23%) levels. Main predictor for membership to a specific cluster was baseline physical behaviour. Patients with higher starting physical behaviour were more likely to be a member of clusters with deteriorating levels. CONCLUSION: Separate clusters of physical behaviour changes during and after cardiac rehabilitation could be identified. Clusters were mainly distinguished by baseline physical behaviour level.

Trajectories and Determinants of Physical Activity during COVID-19 Pandemic: A Population-Based Study of Middle-Aged and Elderly Individuals in The Netherlands.

Physical inactivity is a major public health problem, and there are concerns this might have increased during the COVID-19 pandemic. We aimed to identify distinct trajectories of physical activity over a 6-week period after the first restrictive measures and to explore determinants of these trajectories in a population-based cohort of middle-aged and elderly in the Netherlands (n = 5777). We observed that at least 59% of participants did not meet the World Health Organization recommendations for physical activity. Using latent class trajectory analyses over three time points, we identified five distinct trajectories, including four steady trajectories at different levels (very low, low, medium and high) and one increasing trajectory. Using multinomial logistic regression analyses, we observed that, compared to the 'steadily high' trajectory, participants in the 'steadily very low' trajectory were more often older, lower educated, reporting poorer physical health, more depressive symptoms, consuming a less healthy diet, smoking, and lower alcohol use, and were less often retired. A similar pattern of determinants was seen for those in the increasing trajectory, albeit with smaller effect sizes. Concluding, we observed low levels of physical activity that generally remained during the pandemic. The determinants we described can help identify groups that require additional preventive interventions.

Impact of sex differences in co-morbidities and medication adherence on outcome in 25 776 heart failure patients.

AIMS: Health insurance claims (HIC) databases in the Netherlands capture unselected patient populations, which makes them suitable for epidemiological research on sex differences. Based on a HIC database, we aimed to reveal sex differences in heart failure (HF) outcomes, with particular focus on co-morbidities and medication. METHODS AND RESULTS: The Achmea HIC database included 14 517 men and 11 259 (45%) women with a diagnosis treatment code for chronic HF by January 2015. We related their sex, co-morbidities, and medication adherence (medication possession rate >0.8) with the primary endpoint (PE) of all-cause mortality or HF admission during a median follow-up of 3.3 years, using Cox regression. Median age of men and women was 72 and 76 years, respectively. Prevalence of co-morbidities and use of disease-modifying drugs was higher in men; however, medication adherence was similar. At the end of follow-up, 35.1% men and 31.8% women had reached the PE. The adjusted hazard ratio for men was 1.25 (95% confidence interval: 1.19-1.30). A broad range of co-morbidities was associated with the PE. Overall, these associations were stronger in women than in men, particularly for renal insufficiency, chronic obstructive pulmonary disease/asthma, and diabetes. Non-adherence to disease-modifying drugs was related with a higher incidence of the PE, with similar effects between sexes. CONCLUSIONS: In a representative sample of the Dutch population, as captured in a HIC database, men with chronic HF had a 25% higher incidence of death or HF admission than women. The impact of co-morbidities on the outcome was sex dependent, while medication adherence was not.

Heart failure and promotion of physical activity before and after cardiac rehabilitation (HF-aPProACH): a study protocol.

AIMS: Lifestyle changes, such as increasing physical activity (PA), are a cornerstone of treatment of patients with chronic heart failure (HF). However, improving PA in HF patients is challenging, and low participation rates for cardiac rehabilitation (CR) as well as relapse to low PA levels after CR are major issues. We designed a randomized controlled trial to investigate if PA monitoring with motivational feedback before and after centre-based CR in HF patients with reduced ejection fraction (HFrEF) will lead to a clinically meaningful increase in physical fitness. METHODS AND RESULTS: A randomized controlled trial will be conducted in a sample of 180 HFrEF patients (New York Heart Association Class II/III) who are referred to 12-week standard CR. Patients will be randomized (2:1) to (1) standard of care (SoC) plus wearing a PA monitoring device (Fitbit Charge 3) with personalized step goals, feedback and motivation or (2) SoC only. The intervention lasts ±7 months: 4-5 weeks before CR, 12 weeks during CR and 12 weeks after CR. Measurements will take place at three time points. The primary endpoint is the change in the distance in 6-min walking test (6MWT) over the entire study period. Other endpoints include step count, grip strength, quality of life and all-cause mortality or hospitalization. CONCLUSIONS: HF-aPProACH will provide novel information on the effectiveness of remote PA stimulation and feedback before, during and after standard CR using a commercially available device to improve physical fitness in HFrEF patients.