Sedentary Behaviour-A Target for the Prevention and Management of Cardiovascular Disease

Device-based 24-hour movement behaviours in adult phase III cardiac rehabilitation service-users during the COVID-19 pandemic: a mixed-methods prospective observational study

PURPOSE

To examine changes in device-based 24-hour movement behaviours (MB), and facilitators and barriers to physical activity (PA) and exercise, during remotely-delivered cardiac rehabilitation (RDCR).

MATERIALS AND METHODS

This prospective observational study used wrist-worn GENEActiv accelerometers to assess MB of 10 service-users (63 ± 10 years) at the start, middle, and end of three-months of RDCR. Barriers and facilitators to PA and exercise were explored through self-report diaries and analysed using content analysis.

RESULTS

At start, service-users were sedentary for 12.6 ± 0.7 h · day-1 and accumulated most PA at a light-intensity (133.52 ± 28.57 min · day-1) - neither changed significantly during RDCR. Sleep efficiency significantly reduced from start (88.80 ± 4.2%) to the end (86.1 ± 4.76%) of CR, with values meeting health-based recommendations (≥85%). Barriers to RDCR exercise included exertional discomfort and cardiac symptoms, and reduced confidence when exercising alone. Setting meaningful PA goals, self-monitoring health targets, and having social support, facilitated PA and exercise during RDCR.

CONCLUSIONS

Our RDCR programme failed to elicit significant changes in MB or sleep. To increase the likelihood of successful RDCR, it is important to promote a variety of exercise and PA options, target sedentary time, and apply theory to RDCR design, delivery, and support strategies.

Improving Movement Behavior in People after Stroke with the RISE Intervention: A Randomized Multiple Baseline Study

Objective: High amounts of sedentary behavior increase the risk of cardiovascular disease. This study aimed to determine the preliminary effectiveness and feasibility of the RISE intervention to support community-dwelling people with stroke, who are highly sedentary, to reduce and interrupt sedentary time. Additionally, the added value of including participatory support was determined. Methods: A randomized, multiple-baseline study was conducted including 14 participants. All received the RISE intervention, a 15-week blended behavioral intervention in which a primary care physiotherapist provided personalized coaching in the home setting by using behavior-change techniques and the RISE eCoaching system, including an activity monitor and app to provide real time feedback. Half of the participants (randomly allocated) received participatory support from someone from their social network (e.g., partner or close friend) who joined them in the intervention. Preliminary effectiveness was determined with significant changes in total sedentary time and fragmentation (interruption) of sedentary time using a randomization test. Feasibility was assessed by adherence with the intervention protocol, safety, and satisfaction with the intervention. Results: Participants significantly reduced total sedentary time (p = 0.01) by 1.3 h on average and increased their fragmentation (p < 0.01). Subgroup analyses showed significant improvements in both outcomes only in the group with participatory support. Thirteen (92.9%) participants completed the intervention, no related adverse events occurred, and the reported participant satisfaction was sufficient. Conclusions: The RISE intervention appears promising to support people with stroke who are highly sedentary to reduce and interrupt their sedentary time. Participatory support appears to contribute to greater results. Trial registration: ISRCTN international trial registry, 10694741.

Effects of Different Types of Physical Activity on Respiratory Health Parameters in Elderly Males: A Cross-Sectional Study

Background Population aging is a global phenomenon associated with declines in muscle mass, physical activity levels, and respiratory health among elderly individuals. Despite evidence suggesting the benefits of physical activity on respiratory function, there is limited research examining its effects on lung function in the Indian elderly population. Materials and methods This cross-sectional study aimed to investigate the impact of different intensities of physical activity on respiratory health parameters among apparently healthy elderly males aged 60-80 years. Participants were categorized into walking, swimming, and sedentary groups based on their level of physical activity. Anthropometric measurements, cardiovascular parameters, respiratory endurance tests, and spirometry were conducted to assess lung function. Statistical analysis included nonparametric tests to compare the groups. Results Age, height, weight, BMI, waist circumference, and hip circumference were similar across groups, but the waist-to-hip ratio was higher in the sedentary group. Systolic and diastolic blood pressure did not differ significantly, while the pulse rate was lower in the swimming group. The sedentary group exhibited lower respiratory endurance, with a significantly reduced 40 mmHg endurance test and maximum expiratory pressure compared to the walking and swimming groups. Spirometry results showed significant improvements in various parameters, including forced vital capacity (FVC), forced expiratory volume in the first second (FEV1), peak expiratory flow rate (PEFR), forced expiratory flow 25% (FEF-25), and maximum voluntary ventilation (MVV) in the walking and swimming groups compared to the sedentary group. Conclusion Regular physical activity, particularly walking and swimming, appears to positively influence respiratory health parameters among elderly males. Engaging in these activities may enhance respiratory muscle strength and lung function, potentially mitigating age-related declines in pulmonary function and promoting overall well-being.

Interrupting sitting acutely attenuates cardiometabolic risk markers in South Asian adults living with overweight and obesity

PURPOSE

This study examined the acute effects of interrupting sitting with light-intensity walking on postprandial cardiometabolic risk markers in South Asian adults.

METHODS

South Asians with overweight/obesity (n = 19; body mass index [BMI] > 23 kg·m-2) and normal-weight (n = 8; BMI 18.0-22.9 kg·m-2) aged 48.8 ± 5.6 years completed two, 5-h conditions: (1) prolonged sitting (SIT), and (2) interrupted sitting with 5-min bouts of light-intensity walking every 30-min (INT-SIT). Blood samples and resting expired air samples were collected throughout each condition. Statistical analyses were completed using linear mixed models.

RESULTS

In participants with overweight/obesity, postprandial glucose, triglycerides (TAG) and metabolic load index (MLI) over time were lower, whereas resting substrate utilisation and resting energy expenditure (REE) were higher, in INT-SIT than SIT (all p ≤ 0.05). Compared with SIT (0.18 [95% CI 0.13, 0.22] kcal.min-1), INT-SIT (0.23 [95% CI 0.18, 0.27] kcal.min-1) increased postprandial REE iAUC in participants with overweight/obesity (p = 0.04, d = 0.51). Postprandial TAG concentrations over time were lower in INT-SIT versus SIT (p = 0.01, d = 30) in normal-weight participants, with no differences in any other outcomes for this sample group.

CONCLUSION

These findings suggest that interrupting sitting with 5-min bouts of light walking every 30-min acutely attenuates cardiometabolic risk markers among South Asians living with overweight/obesity, whereas limited effects may be seen in individuals with normal-weight.

Study protocol and rationale of "the UP project": evaluating the effectiveness of active breaks on health indicators in desk-based workers

Background

Excessive sedentary time has been negatively associated with several health outcomes, and physical activity alone does not seem to fully counteract these consequences. This panorama emphasizes the essential of sedentary time interruption programs. "The Up Project" seeks to assess the effectiveness of two interventions, one incorporating active breaks led by a professional and the other utilizing a computer application (self-led), of both equivalent duration and intensity. These interventions will be compared with a control group to evaluate their impact on physical activity levels, sedentary time, stress perception, occupational pain, and cardiometabolic risk factors among office workers.

Methods

This quasi-experimental study includes 60 desk-based workers from universities and educational institutes in Valparaiso, Chile, assigned to three groups: (a) booster breaks led by professionals, (b) computer prompts that are unled, and (c) a control group. The intervention protocol for both experimental groups will last 12 weeks (only weekdays). The following measurements will be performed at baseline and post-intervention: cardiometabolic risk based on body composition (fat mass, fat-free mass, and bone mass evaluated by DXA), waist circumference, blood pressure, resting heart rate, and handgrip strength. Physical activity and sedentary time will be self-reported and device-based assessed using accelerometry. Questionnaires will be used to determine the perception of stress and occupational pain.

Discussion

Governments worldwide are addressing health issues associated with sedentary behavior, particularly concerning individuals highly exposed to it, such as desk-based workers. Despite implementing certain strategies, there remains a noticeable gap in comprehensive research comparing diverse protocols. For instance, studies that contrast the outcomes of interventions led by professionals with those prompted by computers are scarce. This ongoing project is expected to contribute to evidence-based interventions targeting reduced perceived stress levels and enhancing desk-based employees' mental and physical well-being. The implications of these findings could have the capacity to lay the groundwork for future public health initiatives and government-funded programs.

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.

Can the bias of self-reported sitting time be corrected? A statistical model validation study based on data from 23 993 adults in the Norwegian HUNT study

BACKGROUND

Despite apparent shortcomings such as measurement error and low precision, self-reported sedentary time is still widely used in surveillance and research. The aim of this study was threefold; (i) to examine the agreement between self-reported and device-measured sitting time in a general adult population; (ii), to examine to what extent demographics, lifestyle factors, long-term health conditions, physical work demands, and educational level is associated with measurement bias; and (iii), to explore whether correcting for factors associated with bias improves the prediction of device-measured sitting time based on self-reported sitting time.

METHODS

A statistical validation model study based on data from 23 993 adults in the Trøndelag Health Study (HUNT4), Norway. Participants reported usual sitting time on weekdays using a single-item questionnaire and wore two AX3 tri-axial accelerometers on the thigh and low back for an average of 3.8 (standard deviation [SD] 0.7, range 1-5) weekdays to determine their sitting time. Statistical validation was performed by iteratively adding all possible combinations of factors associated with bias between self-reported and device-measured sitting time in a multivariate linear regression. We randomly selected 2/3 of the data (n = 15 995) for model development and used the remaining 1/3 (n = 7 998) to evaluate the model.

RESULTS

Mean (SD) self-reported and device-measured sitting time were 6.8 (2.9) h/day and 8.6 (2.2) h/day, respectively, corresponding to a mean difference of 1.8 (3.1) h/day. Limits of agreement ranged from - 8.0 h/day to 4.4 h/day. The discrepancy between the measurements was characterized by a proportional bias with participants device-measured to sit less overestimating their sitting time and participants device-measured to sit more underestimating their sitting time. The crude explained variance of device-measured sitting time based on self-reported sitting time was 10%. This improved to 24% when adding age, body mass index and physical work demands to the model. Adding sex, lifestyle factors, educational level, and long-term health conditions to the model did not improve the explained variance.

CONCLUSIONS

Self-reported sitting time had low validity and including a range of factors associated with bias in self-reported sitting time only marginally improved the prediction of device-measured sitting time.

A large-scale observational study of the causal effects of a behavioral health nudge

Nudges are interventions promoting healthy behavior without forbidding options or substantial incentives; the Apple Watch, for example, encourages users to stand by delivering a notification if they have been sitting for the first 50 minutes of an hour. On the basis of 76 billion minutes of observational standing data from 160,000 subjects in the public Apple Heart and Movement Study, we estimate the causal effect of this notification using a regression discontinuity design for time series data with time-varying treatment. We show that the nudge increases the probability of standing by up to 43.9% and remains effective with time. The nudge's effectiveness increases with age and is independent of gender. Closing Apple Watch Activity Rings, a visualization of participants' daily progress in Move, Exercise, and Stand, further increases the nudge's impact. This work demonstrates the effectiveness of behavioral health interventions and introduces tools for investigating their causal effect from large-scale observations.

Changes in Metabolic Health and Sedentary Behavior in Obese Children and Adolescents

Obesity is becoming more common among children and adolescents. As in adults, obesity in the pediatric population is associated with an increased risk of metabolic disorders and diseases. In the related literature, little attention has been devoted to evaluating how metabolic health and sedentary behavior change in the obese pediatric population. Therefore, this study aimed to assess changes in metabolic health and sedentary behavior in obese children aged 7-12 and adolescents aged 13-17. For this single-center hospital-based prospective observational study, we included 202 Polish children and adolescents aged 7-17 years. We performed blood pressure measurements and collected blood samples to assess metabolic health markers. Based on the performed measurements, we also calculated additional indexes and ratios: BMI, WHtR, ABSI, VAI, and HOMA-IR. The analysis of the results showed clear and significant differences between the study groups. The older boys and girls were identified with higher values of anthropometric ratios, blood pressure, time spent sitting, and lower HDL cholesterol values (p < 0.05). The analysis also revealed a strong-to-moderate correlation between age and anthropometric ratios, blood pressure, HDL cholesterol, and sitting time (p < 0.05). Obese children and adolescents included in this study represent poor metabolic health and are at great risk of developing other metabolic diseases such as type 2 diabetes, hypertension, or metabolic syndrome. This risk increases with age; therefore, a number of preventive and therapeutic actions should be taken in overweight and obese children and adolescents to avoid further metabolic complications.