Personalized Activity Intelligence (PAI) for Prevention of Cardiovascular Disease and Promotion of Physical Activity

Biomarkers of aging: from molecules and surrogates to physiology and function

Many countries face an unprecedented challenge in aging demographics. This has led to an exponential growth in research on aging, which, coupled to a massive financial influx of funding in the private and public sectors, has resulted in seminal insights into the underpinnings of this biological process. However, critical validation in humans has been hampered by the limited translatability of results obtained in model organisms, additionally confined by the need for extremely time-consuming clinical studies in the ostensible absence of robust biomarkers that would allow monitoring in shorter time frames. In the future, molecular parameters might hold great promise in this regard. In contrast, biomarkers centered on function, resilience, and frailty are available at the present time, with proven predictive value for morbidity and mortality. In this review, the current knowledge of molecular and physiological aspects of human aging, potential antiaging strategies, and the basis, evidence, and potential application of physiological biomarkers in human aging are discussed.

Mobile Health Biometrics to Enhance Exercise and Physical Activity Adherence in Type 2 Diabetes (MOTIVATE-T2D): a decentralised feasibility randomised controlled trial delivered across the UK and Canada

OBJECTIVES

Assess the feasibility of a mobile health (mHealth)-supported home-delivered physical activity (PA) intervention (MOTIVATE-T2D) in people with recently diagnosed type 2 diabetes (T2D).

DESIGN

Feasibility multicentre, parallel group, randomised controlled trial (RCT).

SETTING

Participants were recruited from England and Canada using a decentralised design.

PARTICIPANTS

Adults (40-75 years) recently diagnosed with T2D (5-24 months).

INTERVENTIONS

Participants were randomised 1:1 to intervention (MOTIVATE-T2D) or active control groups. Participants codesigned 6month- home-delivered, personalised, progressive PA programmes supported by virtual behavioural counselling. MOTIVATE-T2D used biofeedback from wearable technologies to support the programme. The active control group received the same intervention without wearables.

OUTCOMES

The primary outcomes were recruitment rate, retention and adherence to purposeful exercise. Clinical data on effectiveness were collected as exploratory outcomes at baseline, 6 and 12 months, with HbA1c and systolic blood pressure (BP) proposed as primary outcomes for a future full RCT.

RESULTS

n=135 eligible participants expressed an interest in the trial, resulting in 125 participants randomised (age 55±9 years, 48% female, 81% white), a recruitment rate of 93%. Retention at 12 months was 82%. MOTIVATE-T2D participants were more likely to start (OR 10.4, CI 3.4 to 32.1) and maintain purposeful exercise at 6 (OR 7.1, CI 3.2 to 15.7) and 12 months (OR 2.9, CI 1.2 to 7.4). Exploratory clinical outcomes showed a potential effect in favour of MOTIVATE-T2D, including proposed primary outcomes HbA1c and systolic BP (between-group mean differences: HbA1c: 6 months: -5% change from baseline, CI -10 to 2: 12 months: -2% change from baseline, CI -8 to -4; systolic BP: 6 months: -1 mm Hg, CI -5 to 3: 12 months: -4 mm Hg, CI -8 to 1).

CONCLUSIONS

Our findings support the feasibility of delivering the MOTIVATE-T2D mHealth-supported PA intervention for people with recently diagnosed T2D and progression to a full RCT to examine its clinical and cost-effectiveness.

TRIAL REGISTRATION NUMBER

ISRCTN: 14335124; ClinicalTrials.gov: NCT0465353.

Empowerment in Type 2 diabetes: A patient-centred approach for lifestyle change

AIMS

To evaluate the effectiveness of personalized lifestyle intervention service for persons with Type 2 diabetes (T2D), implemented in a real-world setting at two Healthy Life Centers (HLC) in Norway.

METHODS

Persons with T2D were randomized into either an HLC intervention group or a usual care group for 12 weeks. All participants were screened using a questionnaire tool and had one initial patient-centred health conversation at the HLC. In the intervention group, participants chose interventions with support from HLC staff. The usual care group continued independently. Outcome variables were assessed at baseline, 12 weeks, and 24 weeks (if completing two interventions).

RESULTS

110 participants were included (mean age 59.9, 59 % T2D duration < 10 years, 36 % females). There was no significant difference in HbA1c change between intervention and usual care groups (mean difference -1.2 mmol/l, 95 % CI: -3.7 to 1.3, p = 0.33). HbA1c was significantly reduced in both groups (mean reduction 3.8 mmol/l (95 % CI: 2.1 to 5.5, p < 0.001) vs. 2.6 mmol/l (95 % CI: 0.7 to 4.4, p = 0.006), respectively).

CONCLUSIONS

Both the HLC personalized follow-up and usual care groups reduced HbA1c with no significant differences between groups. This suggests that low-threshold municipal healthcare can effectively support lifestyle changes in individuals with T2D.

Association between Activity Quotient and cause-specific mortality - A prospective cohort study of 0.5 million participants in Asia

BACKGROUND

Regular physical activity (PA) is important for reducing the risk of chronic diseases and improving overall health. Activity Quotient (AQ) is a novel metric that translates heart rate during PA into a weekly score, providing an objective measure of an individual's PA. We prospectively examined the association of AQ with cancer and cardiovascular (CVD) mortality outcomes, the two major causes of death, in a Taiwanese population.

METHODS

A cohort of 515,608 healthy adults (52 % women) enrolled in a standard medical screening program was followed for mortality outcomes. The weekly AQ score of each participant was estimated based on self-reported PA intensity and weekly duration, and placed into six categories (0, ≤50, 51-99,100-149, 150-199, or ≥ 200 AQ per week). We used multivariable Cox proportional hazard models adjusted for potential confounders to estimate the hazard ratios (HR) and 95 % confidence intervals (CI).

RESULTS

Higher weekly AQ scores were associated with lower risks of CVD, cancer, and all-cause mortalities. Compared with inactive individuals, HRs (CI) for the association of AQ scores of ≤50, 50-99, 100-149, 150-199, and ≥ 200 were 0.93 (0.89-0.97), 0.91 (0.85-0.96), 0.84 (0.77-0.91), 0.84 (0.74-0.96), and 0.81 (0.73-0.90) with cancer mortality; and 0.88 (0.83-0.93), 0.86 (0.80-0.93), 0.81 (0.73-0.90), 0.71 (0.60-0.85), and 0.73 (0.64-0.84) with CVD mortality, respectively. Subgroup analyses showed that meeting 50 AQ a week was associated with lower risk of disease specific mortality risk across age groups and among individuals with known risk factors. Higher weekly AQ scores were also associated with longer life expectancy, with the highest gains observed among those achieving 150-199 weekly AQ.

CONCLUSION

Our findings show that AQ may be an objective tool for assessing and tracking PA and predicting mortality risks. Encouraging individuals to achieve ≥50 AQ a week could have substantial public health benefits, including lower mortality from major chronic diseases as well as prolonged health- and life expectancy.

Mind the intention-behavior gap: a qualitative study of post-myocardial infarction patients' beliefs and experiences with long-term supervised and self-monitored physical exercise

BACKGROUND

Many post-myocardial infarction (MI) patients struggle with physical activity behavior change (BC) for life-long secondary prevention. There is limited knowledge about factors influencing long-term physical activity BC among post-MI patients. This qualitative study aimed to explore the beliefs and experiences related to post-MI patients' physical activity BC process following a year's participation in a supervised and self-monitored exercise program: the Norwegian Trial of Physical Exercise After MI (NorEx).

METHODS

We conducted a qualitative study, performing in-depth semi-structured interviews with a randomly selected sample of NorEx participants when they were scheduled for cardiopulmonary exercise testing after one year of participation. Interviews were transcribed verbatim and the data was analyzed by applying reflexive thematic analysis.

RESULTS

Seventeen participants (n = 4 female [24%]; median age, 61 years; median time since index MI, 4 years) were recruited and interviewed once. Analysis resulted in four main themes (nine sub-themes): (1) Personal responsibility to exercise (Exercise is safe, Health benefits, Habitual exercise); (2) Peer social support for a sense of safety and belonging (Social exercise, Supervision is preferred); (3) Research participation transformed exercise beliefs (High-intensity exercise is superior, Personal Activity Intelligence (PAI) promotes exercise adherence); and (4) Mind the intention-behavior gap (Initial anxiety, Lack of continued follow-up).

CONCLUSIONS

Several participants reported that they were able to maintain exercise BC during a year's participation in NorEx. Nevertheless, a perceived lack of continued and individualized follow-up made some participants struggle with motivation and self-regulation, leading to an intention-behavior gap. Therefore, our findings suggest there is a need for individualized and continued social support and supervision from health and exercise professionals to maintain long-term exercise BC for secondary prevention among post-MI patients.

TRIAL REGISTRATION

The NorEx study has been registered at ClinicalTrials.gov (NCT04617639, registration date 2020-10-21).

Examining temporal changes in model-optimized parameters using longitudinal hemodynamic measurements

BACKGROUND

We previously applied hemodynamic data to personalize a mathematical model of the circulation expressed as physically interpretable parameters. The aim of this study was to identify patterns in the data that could potentially explain the estimated parameter changes. This included investigating whether the parameters could be used to track the effect of physical activity on high blood pressure. Clinical trials have repeatedly detected beneficial changes in blood pressure after physical activity and uncovered changes in lower level phenotypes (such as stiffened or high-resistance blood vessels). These phenotypes can be characterized by parameters describing the mechanical properties of the circulatory system. These parameters can be incorporated in and contextualized by physics-based cardiovascular models of the circulation, which in combination can become tools for monitoring cardiovascular disease progression and management in the future.

METHODS

Closed-loop and open-loop models of the left ventricle and systemic circulation were previously optimized to data from a pilot study with a 12-week exercise intervention period. Basal characteristics and hemodynamic data such as blood pressure in the carotid, brachial and finger arteries, as well as left-ventricular outflow tract flow traces were collected in the trial. Model parameters estimated for measurements made on separate days during the trial were used to compute parameter changes for total peripheral resistance, systemic arterial compliance, and maximal left-ventricular elastance. We compared the changes in these cardiovascular model-based estimates to changes from more conventional estimates made without the use of physics-based models by correlation analysis. Additionally, ordinary linear regression and linear mixed-effects models were applied to determine the most informative measurements for the selected parameters. We applied maximal aerobic capacity (measured as VO2max ) data to examine if exercise had any impact on parameters through regression analysis and case studies.

RESULTS AND CONCLUSIONS

Parameter changes in arterial parameters estimated using the cardiovascular models correlated moderately well with conventional estimates. Estimates based on carotid pressure waveforms gave higher correlations (0.59 and above when p < 0.05 ) than those for finger arterial pressure. Parameter changes over the 12-week study duration were of similar magnitude when compared to short-term changes after a bout of intensive exercise in the same parameters. The short-term changes were computed from measurements made immediately before and 24 h after a cardiopulmonary exercise test used to measure VO2max . Regression analysis indicated that changes in VO2max did not account for any substantial amount of variability in total peripheral resistance, systemic arterial compliance, or maximal left-ventricular elastance. On the contrary, changes in stroke volume contributed to far more explained variability. The results suggest that more research is required to be able to accurately track exercise-induced changes in the vasculature for people with pre-hypertension and hypertension using lumped-parameter models.

Artificial intelligence in neurology: opportunities, challenges, and policy implications

Neurological conditions are the leading cause of disability and mortality combined, demanding innovative, scalable, and sustainable solutions. Brain health has become a global priority with adoption of the World Health Organization's Intersectoral Global Action Plan in 2022. Simultaneously, rapid advancements in artificial intelligence (AI) are revolutionizing neurological research and practice. This scoping review of 66 original articles explores the value of AI in neurology and brain health, systematizing the landscape for emergent clinical opportunities and future trends across the care trajectory: prevention, risk stratification, early detection, diagnosis, management, and rehabilitation. AI's potential to advance personalized precision neurology and global brain health directives hinges on resolving core challenges across four pillars-models, data, feasibility/equity, and regulation/innovation-through concerted pursuit of targeted recommendations. Paramount actions include swift, ethical, equity-focused integration of novel technologies into clinical workflows, mitigating data-related issues, counteracting digital inequity gaps, and establishing robust governance frameworks balancing safety and innovation.

Development of risk models of incident hypertension using machine learning on the HUNT study data

In this study, we aimed to create an 11-year hypertension risk prediction model using data from the Trøndelag Health (HUNT) Study in Norway, involving 17 852 individuals (20-85 years; 38% male; 24% incidence rate) with blood pressure (BP) below the hypertension threshold at baseline (1995-1997). We assessed 18 clinical, behavioral, and socioeconomic features, employing machine learning models such as eXtreme Gradient Boosting (XGBoost), Elastic regression, K-Nearest Neighbor, Support Vector Machines (SVM) and Random Forest. For comparison, we used logistic regression and a decision rule as reference models and validated six external models, with focus on the Framingham risk model. The top-performing models consistently included XGBoost, Elastic regression and SVM. These models efficiently identified hypertension risk, even among individuals with optimal baseline BP (< 120/80 mmHg), although improvement over reference models was modest. The recalibrated Framingham risk model outperformed the reference models, approaching the best-performing ML models. Important features included age, systolic and diastolic BP, body mass index, height, and family history of hypertension. In conclusion, our study demonstrated that linear effects sufficed for a well-performing model. The best models efficiently predicted hypertension risk, even among those with optimal or normal baseline BP, using few features. The recalibrated Framingham risk model proved effective in our cohort.

Adoption, acceptability and sustained use of digital interventions to promote physical activity among inactive adults: a mixed-method study

Introduction

Despite the positive effects of physical activity (PA) to prevent lifestyle diseases and improve health and well-being, only one-third of Norwegian adults meet the minimum recommendations on PA. Digital interventions to promote PA in inactive adults may improve health and well-being by being available, personalized and adequate. Knowledge on users' adoption, acceptability and sustainability of digital interventions to promote PA is still limited.

Objective

To investigate the adoption, acceptability and sustained use of three digital interventions for promoting PA among inactive adults.

Design

A randomized control trial (ONWARDS) with 183 participants assigned to 3 groups and followed up for 18 months. All participants received a wearable activity tracker with the personalized metric Personal Activity Intelligence (PAI) on a mobile app, two groups received additional access to online training and one group had also access to online social support.

Methods

A mixed-methods approach was used to address the study objective. Acceptability was evaluated through the System Usability Scale (SUS) (n = 134) at 6 months. Adoption and sustained use were evaluated through a set of questions administered at 12 months (n = 109). Individual interviews were performed at 6 months with a sample of participants (n = 18). Quantitative data were analyzed with descriptive statistics, whereas qualitative data were analyzed using the Framework approach.

Results

PAI was the most successful intervention, with satisfactory usability and positive effects on motivation and behavior change, contributing to high adoption and sustained use. Online social support had a high acceptability and sustained use, but the intervention was not perceived as motivational to increase PA. Online training had low adoption, usability and sustained use. The qualitative interviews identified five main themes: (1) overall approach to physical activity, (2) motivation, (3) barriers to perform PA, (4) effects of PA, and (5) usability and acceptability of the digital interventions.

Conclusion

Personalized digital interventions integrating behavior change techniques such as individual feedback and goal setting are more likely to increase acceptability, adoption and sustained use. Future studies should investigate which digital interventions or combinations of different interventions are more successful in promoting PA among inactive adults according to the characteristics and preferences of the users.

Trial registration

Clinical trial registered at ClinicalTrials.gov: NCT04526444.

Occupational Sitting Time, Leisure Physical Activity, and All-Cause and Cardiovascular Disease Mortality

Importance

For the first time, the 2020 World Health Organization guidelines on physical activity recommended reducing sedentary behaviors owing to their health consequences. Less is known on the specific association of prolonged occupational sitting with health, especially in the context of low physical activity engagement.

Objective

To quantify health risks associated with prolonged occupational sitting and to determine whether there is a certain threshold of physical activity that may attenuate it.

Design, Setting, and Participants

This prospective cohort study included participants in a health surveillance program in Taiwan who were followed-up between 1996 and 2017. Data on occupational sitting, leisure-time physical activity (LTPA) habits, lifestyle, and metabolic parameters were collected. Data analysis was performed in December 2020.

Main Outcomes and Measures

The all-cause and cardiovascular disease (CVD) mortality associated with 3 occupational sitting volumes (mostly sitting, alternating sitting and nonsitting, and mostly nonsitting) were analyzed applying multivariable Cox regression models to calculate the hazard ratios (HRs) for all participants and by subgroups, including 5 LTPA levels and a personal activity intelligence (PAI)-oriented metric. Deaths occurring within the initial 2 years of follow-up were excluded to prevent reverse causality.

Results

The total cohort included 481 688 participants (mean [SD] age, 39.3 [12.8] years; 256 077 women [53.2%]). The study recorded 26 257 deaths during a mean (SD) follow-up period of 12.85 (5.67) years. After adjusting for sex, age, education, smoking, drinking, and body mass index, individuals who mostly sat at work had a 16% higher all-cause mortality risk (HR, 1.16; 95% CI, 1.11-1.20) and a 34% increased mortality risk from CVD (HR, 1.34; 95% CI, 1.22-1.46) compared with those who were mostly nonsitting at work. Individuals alternating sitting and nonsitting at work did not experience increased risk of all-cause mortality compared with individuals mostly nonsitting at work (HR, 1.01; 95% CI, 0.97-1.05). For individuals mostly sitting at work and engaging in low (15-29 minutes per day) or no (<15 minutes per day) LTPA, an increase in LTPA by 15 and 30 minutes per day, respectively, was associated with a reduction in mortality to a level similar to that of inactive individuals who mostly do not sit at work. In addition, individuals with a PAI score exceeding 100 experienced a notable reduction in the elevated mortality risk associated with prolonged occupational sitting.

Conclusions and Relevance

As part of modern lifestyles, prolonged occupational sitting is considered normal and has not received due attention, even though its deleterious effect on health outcomes has been demonstrated. In this study, alternating between sitting and nonsitting at work, as well as an extra 15 to 30 minutes per day of LTPA or achieving a PAI score greater than 100, attenuated the harms of prolonged occupational sitting. Emphasizing the associated harms and suggesting workplace system changes may help society to denormalize this common behavior, similar to the process of denormalizing smoking.

Physical Activity, Cardiorespiratory Fitness, and Atherosclerotic Cardiovascular Disease: Part 2

Background

In this second section of our 2-part review on the role of physical activity (PA) and cardiorespiratory fitness (CRF) in preventing and treating atherosclerotic cardiovascular disease (CVD), we expand on topics covered in part 1, including a comparison of moderate-intensity continuous training versus high-intensity interval training, the beneficial role of PA and CRF in heart failure, potential mal-adaptations that may result from extreme endurance exercise regimens, and the incidence of cardiac arrest and sudden cardiac death during marathon running and triathlon participation. Further, we review the principles of exercise prescription for patients with known or suspected CVD, with specific reference to exercise modalities, contemporary guidelines, the minimum exercise training intensity to promote survival benefits, and long-term goal training intensities, based on age-, sex-, and fitness-adjusted targets. Finally, we provide practical "prescription pearls" for the clinician, including a simple rule to estimate metabolic equivalents (METs) during level and graded treadmill walking, research-based exercise training recommendations, using steps per day, MET-minutes per week, and personal activity intelligence to achieve beneficial treatment outcomes, as well as the heart rate index equation to estimate energy expenditure, expressed as METs, during recreational and leisure-time PA.

Summary

This review compares moderate-intensity continuous training and high-intensity interval training, examines the role of PA and CRF in managing heart failure, and discusses the cardiovascular risks associated with extreme endurance exercise. It also provides practical guidelines for exercise prescription tailored to patients with CVD, highlighting advanced exercise prescription strategies to optimize cardiovascular health.

Key Messages

Physicians and healthcare providers should prioritize referring patients to home-based or medically supervised exercise programs to leverage the cardioprotective benefits of regular PA. For most inactive patients, an exercise prescription is essential for improving overall health.

Randomised controlled trial of preconception lifestyle intervention on maternal and offspring health in people with increased risk of gestational diabetes: study protocol for the BEFORE THE BEGINNING trial

INTRODUCTION

Gestational diabetes mellitus (GDM) is associated with increased risk for type 2 diabetes in the mother and cardiometabolic diseases in the child. The preconception period is an optimal window to adapt the lifestyle for improved outcomes for both mother and child. Our aim is to determine the effect of a lifestyle intervention, initiated before and continued throughout pregnancy, on maternal glucose tolerance and other maternal and infant cardiometabolic outcomes.

METHODS AND ANALYSIS

This ongoing randomised controlled trial has included 167 females aged 18-39 years old at increased risk for GDM who are contemplating pregnancy. The participants were randomly allocated 1:1 to an intervention or control group. The intervention consists of exercise (volume is set by a heart rate-based app and corresponds to ≥ 1 hour of weekly exercise at ≥ 80% of individual heart rate maximum), and time-restricted eating (≤ 10 hours/day window of energy intake). The primary outcome measure is glucose tolerance in gestational week 28. Maternal and offspring outcomes are measured before and during pregnancy, at delivery, and at 6-8 weeks post partum. Primary and secondary continuous outcome measures will be compared between groups based on the 'intention to treat' principle using linear mixed models.

ETHICS AND DISSEMINATION

The Regional Committees for Medical and Health Research Ethics in Norway has approved the study (REK 143756). The anonymised results will be submitted for publication and posted in a publicly accessible database of clinical study results.

TRIAL REGISTRATION NUMBER

Clinical trial gov NCT04585581.

Nutrition and Physical Activity Interventions Provided by Nutrition and Exercise Practitioners for the General Population: An Evidence-Based Practice Guideline From the Academy of Nutrition and Dietetics and American Council on Exercise

A nutritious diet and adequate physical activity vitally contribute to disease prevention, but most adults do not meet population-based dietary and physical activity recommendations. Qualified nutrition and exercise practitioners can address challenges to adopting healthy lifestyle behaviors by providing consistent, individualized, and evidence-based education and programming within their professional scopes of practice to improve client outcomes. The objective of this evidence-based practice guideline is to inform practice decisions for nutrition and exercise practitioners providing nutrition and physical activity interventions for adults who are healthy or have cardiometabolic risk factors, but no diagnosed disease. Evidence from a systematic review was translated to practice recommendations using an evidence-to-decision framework by an interdisciplinary team of nutrition and exercise practitioners and researchers. This evidence-based practice guideline does not provide specific dietary or physical activity recommendations but rather informs nutrition and exercise practitioners how they may utilize existing guidelines for the general population to individualize programming for a range of clients. This evidence-based practice guideline provides widely applicable recommendation statements and a detailed framework to help practitioners implement the recommendations into practice. Common barriers and facilitators encountered when delivering nutrition and physical activity interventions, such as adherence to professional scopes of practice; methods to support behavior change; and methods to support inclusion, diversity, equity, and access, are discussed. Nutrition and exercise practitioners can consistently provide individualized, practical, and evidence-based interventions by seeking to understand their clients' needs, circumstances, and values and by co-creating interventions with the client and their allied health team.

Wearable technology and the cardiovascular system: the future of patient assessment

The past decade has seen a dramatic rise in consumer technologies able to monitor a variety of cardiovascular parameters. Such devices initially recorded markers of exercise, but now include physiological and health-care focused measurements. The public are keen to adopt these devices in the belief that they are useful to identify and monitor cardiovascular disease. Clinicians are therefore often presented with health app data accompanied by a diverse range of concerns and queries. Herein, we assess whether these devices are accurate, their outputs validated, and whether they are suitable for professionals to make management decisions. We review underpinning methods and technologies and explore the evidence supporting the use of these devices as diagnostic and monitoring tools in hypertension, arrhythmia, heart failure, coronary artery disease, pulmonary hypertension, and valvular heart disease. Used correctly, they might improve health care and support research.

Continuous Monitoring of Health and Mobility Indicators in Patients with Cardiovascular Disease: A Review of Recent Technologies

Cardiovascular diseases kill 18 million people each year. Currently, a patient's health is assessed only during clinical visits, which are often infrequent and provide little information on the person's health during daily life. Advances in mobile health technologies have allowed for the continuous monitoring of indicators of health and mobility during daily life by wearable and other devices. The ability to obtain such longitudinal, clinically relevant measurements could enhance the prevention, detection and treatment of cardiovascular diseases. This review discusses the advantages and disadvantages of various methods for monitoring patients with cardiovascular disease during daily life using wearable devices. We specifically discuss three distinct monitoring domains: physical activity monitoring, indoor home monitoring and physiological parameter monitoring.

Monitoring variability in parameter estimates for lumped parameter models of the systemic circulation using longitudinal hemodynamic measurements

BACKGROUND

Physics-based cardiovascular models are only recently being considered for disease diagnosis or prognosis in clinical settings. These models depend on parameters representing the physical and physiological properties of the modeled system. Personalizing these parameters may give insight into the specific state of the individual and etiology of disease. We applied a relatively fast model optimization scheme based on common local optimization methods to two model formulations of the left ventricle and systemic circulation. One closed-loop model and one open-loop model were applied. Intermittently collected hemodynamic data from an exercise motivation study were used to personalize these models for data from 25 participants. The hemodynamic data were collected for each participant at the start, middle and end of the trial. We constructed two data sets for the participants, both consisting of systolic and diastolic brachial pressure, stroke volume, and left-ventricular outflow tract velocity traces paired with either the finger arterial pressure waveform or the carotid pressure waveform.

RESULTS

We examined the feasibility of separating parameter estimates for the individual from population estimates by assessing the variability of estimates using the interquartile range. We found that the estimated parameter values were similar for the two model formulations, but that the systemic arterial compliance was significantly different ([Formula: see text]) depending on choice of pressure waveform. The estimates of systemic arterial compliance were on average higher when using the finger artery pressure waveform as compared to the carotid waveform.

CONCLUSIONS

We found that for the majority of participants, the variability of parameter estimates for a given participant on any measurement day was lower than the variability both across all measurement days combined for one participant, and for the population. This indicates that it is possible to identify individuals from the population, and that we can distinguish different measurement days for the individual participant by parameter values using the presented optimization method.

Physical Activity and Cardiorespiratory Fitness as Modulators of Health Outcomes: A Compelling Research-Based Case Presented to the Medical Community

The beneficial health effects and prognostic significance of regular moderate-to-vigorous physical activity (PA), increased cardiorespiratory fitness (CRF), or both are often underappreciated by the medical community and the patients they serve. Individuals with low CRF have higher annual health care costs, higher rates of surgical complications, and are two to three times more likely to die prematurely than their fitter counterparts when matched for risk factor profile or coronary calcium score. Increased levels of habitual PA before hospitalization for acute coronary syndromes are also associated with better short-term cardiovascular outcomes. Accordingly, this review examines these relations and the potential underlying mechanisms of benefit (eg, exercise preconditioning), with specific reference to the incidence of cardiovascular, cancer, and coronavirus diseases, and the prescriptive implications and exercise thresholds for optimizing health outcomes. To assess the evidence supporting or refuting the benefits of PA and CRF, we performed a literature search (PubMed) and critically reviewed the evidence to date. In aggregate, these data are presented in the context of clarifying the impact that regular PA and/or increased CRF have on preventing and treating chronic and infectious diseases, with reference to evidence-based exercise thresholds that the medical community can embrace and promote.

Adherence to unsupervised exercise in sedentary individuals: A randomised feasibility trial of two mobile health interventions

Introduction

Adherence to unsupervised exercise is poor, yet unsupervised exercise interventions are utilised in most healthcare settings. Thus, investigating novel ways to enhance adherence to unsupervised exercise is essential. This study aimed to examine the feasibility of two mobile health (mHealth) technology-supported exercise and physical activity (PA) interventions to increase adherence to unsupervised exercise.

Methods

Eighty-six participants were randomised to online resources (n = 44, females n = 29) or MOTIVATE (n = 42, females n = 28). The online resources group had access to booklets and videos to assist in performing a progressive exercise programme. MOTIVATE participants received exercise counselling sessions supported via mHealth biometrics which allowed instant participant feedback on exercise intensity, and communication with an exercise specialist. Heart rate (HR) monitoring, survey-reported exercise behaviour and accelerometer-derived PA were used to quantify adherence. Remote measurement techniques were used to assess anthropometrics, blood pressure, HbA1c and lipid profiles.

Results

HR-derived adherence rates were 22 ± 34% and 113 ± 68% in the online resources and MOTIVATE groups, respectively. Self-reported exercise behaviour demonstrated moderate (Cohen's d = 0.63, CI = 0.27 to 0.99) and large effects (Cohen's d = 0.88, CI = 0.49 to 1.26) in favour of online resources and MOTIVATE groups, respectively. When dropouts were included, 84% of remotely gathered data were available, with dropouts removed data availability was 94%.

Conclusion

Data suggest both interventions have a positive impact on adherence to unsupervised exercise but MOTIVATE enables participants to meet recommended exercise guidelines. Nevertheless, to maximise adherence to unsupervised exercise, future appropriately powered trials should explore the effectiveness of the MOTIVATE intervention.

Physical activity, cardiorespiratory fitness, and cardiovascular health: A clinical practice statement of the American Society for Preventive Cardiology Part II: Physical activity, cardiorespiratory fitness, minimum and goal intensities for exercise training, prescriptive methods, and special patient populations

The prescription of exercise for individuals with and without cardiovascular disease (CVD) should be scientifically-based yet adapted to the patient. This scientific statement reviews the clinical and physiologic basis for the prescription of exercise, with specific reference to the volume of physical activity (PA) and level of cardiorespiratory fitness (CRF) that confer significant and optimal cardioprotective benefits. Recommendations are provided regarding the appropriate intensity, frequency, and duration of training; the concept of MET-minutes per week; critical components of the exercise session (warm-up, conditioning phase, cool-down); methodologies for establishing the training intensity, including oxygen uptake reserve (V̇O2R), target heart rate derivation and rating perceived exertion; minimum and goal intensities for exercise training; and, types of training activities, including resistance training, adjunctive lifestyle PA, marathon/triathlon training, and high-intensity interval training. In addition, we discuss the rationale for and value of exercise training programs for patients with peripheral artery disease, diabetes mellitus, and heart failure.

Personal Activity Intelligence and Ischemic Heart Disease in a Healthy Population: China Kadoorie Biobank Study

BACKGROUND

Personal Activity Intelligence (PAI) is a physical activity metric that translates heart rate during physical activity into a simple score, where a weekly score of 100 or greater is associated with a lower risk of cardiovascular disease and mortality. Here, we prospectively investigated the association between PAI and ischemic heart disease (IHD) mortality in a large healthy population from China.

METHODS

Using data from the China Kadoorie Biobank, we studied 443,792 healthy adults (60% women). The weekly PAI score of each participant was estimated based on the questionnaire data and divided into four groups (PAI scores of 0, ≤50, 51-99, or ≥100). Adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for fatal IHD and nonfatal myocardial infraction (MI) related to PAI were estimated using Cox proportional hazard regression analyses.

RESULTS

There were 3050 IHD deaths and 1808 MI events during a median follow-up of 8.2 years (interquartile range, 7.3-9.1; 3.6 million person-years). After adjustments for multiple confounders, a weekly PAI score ≥ 100 was associated with a lower risk of IHD (aHR: 0.91 (95% CI: 0.83-1.00)), compared with the inactive group (0 PAI). The corresponding aHR for MI was 0.94 (95% CI: 0.83-1.05). In participants aged 60 years or older at baseline, the aHR associated with a weekly PAI score ≥ 100 was 0.84 (95% CI, 0.75-0.93) for IHD and 0.84 (95% CI, 0.73-0.98) for MI.

CONCLUSION

Among healthy Chinese adults, a weekly PAI score of 100 or greater was associated with a lower risk of IHD mortality across all age groups; moreover, a high PAI score significantly lowered the risk of MI but only in those 60 years and older at baseline. The present findings extend the scientific evidence that PAI may have prognostic significance in diverse settings for IHD outcomes and suggest that the PAI metric may be useful in delineating the magnitude of weekly physical activity needed to reduce the risk of IHD mortality.

Digital interventions to promote physical activity among inactive adults: A study protocol for a hybrid type I effectiveness-implementation randomized controlled trial

Introduction

Physical inactivity is the fourth leading risk factor for global mortality, and inactive adults have a higher risk to develop lifestyle diseases. To date, there is preliminary evidence of the efficacy of fitness technologies and other digital interventions for physical activity (PA) promotion. Intervention studies are needed to test the effectiveness and implementation of innovative PA promotion strategies.

Methods and analysis

The ONWARDS study is a hybrid type I effectiveness-implementation randomized control trial aiming at an inactive and presumably high-risk population living in Northern Norway. One hundred and eighty participants will be assigned to 3 groups in a 1:1:1 ratio and participate for 18 months. Participants in group A will be provided an activity tracker with the personalized metric Personal Activity Intelligence (PAI). Participants in group B will be provided with both an activity tracker with the personalized metric PAI and access to online training videos (Les Mills+) to perform home-based training. Participants in group C will be provided an activity tracker with the personalized metric PAI, home-based online training and additional peer support via social media. The primary objective is to test which combination of interventions is more effective in increasing PA levels and sustaining long-term exercise adherence. Secondary objectives include: proportion of participants reaching PA recommendations; exercise adherence; physical fitness; cardiovascular risk; quality of life; perceived competence for exercise; self-efficacy; social support; usability; users' perspectives on implementation outcomes (adoption, acceptability, adherence, sustainability). The study design will allow testing the effectiveness of the interventions while gathering information on implementation in a real-world situation.

Discussion

This study can contribute to reduce disparities in PA levels among inactive adults by promoting PA and long-term adherence. Increased PA might, in turn, result in better prevention of lifestyle diseases. Digital interventions delivered at home can become an alternative to training facilities, making PA accessible and feasible for inactive populations and overcoming known barriers to PA. If effective, such interventions could potentially be offered through national health portals to citizens who do not meet the minimum recommendations on PA or prescribed by general practitioners or specialists.

Trial registration

https://clinicaltrials.gov/ct2/show/NCT04526444, Registered 23 April 2021, identifier: NCT04526444.

Using Personal Activity Intelligence With Patients in a Clinic Setting

BACKGROUND

Personal Activity Intelligence (PAI) is a novel heart-rate-based metric used to assess cardiorespiratory fitness and quantify physical activity.

OBJECTIVE

The aim of this study was to examine the feasibility, acceptability, and effectiveness of PAI with patients in a clinic setting.

METHODS

Patients (n = 25) from 2 clinics underwent 12 weeks of heart-rate-monitored physical activity interfaced with aPAI Health phone app. We used a pre-post design with the Physical Activity Vital Sign and the International Physical Activity Questionnaire. Feasibility, acceptability, and PAI measures were used to evaluate the objectives.

RESULTS

Twenty-two patients (88%) completed the study. There were significant improvements in International Physical Activity Questionnaire metabolic equivalent task minutes per week ( P = .046) and a decrease in sitting hours ( P = .0001). The Physical Activity Vital Sign activity increase in minutes per week was not significant ( P = .214). Patients achieved a mean PAI score of 116 ± 81.1 and 100 or greater 71% of the days. Most patients (81%) expressed satisfaction with PAI.

CONCLUSIONS

Personal Activity Intelligence is feasible, acceptable, and effective when used with patients in a clinic setting.

Temporal changes in personal activity intelligence and the risk of incident dementia and dementia related mortality: A prospective cohort study (HUNT)

BACKGROUND

The Personal Activity Intelligence (PAI) translates heart rate during daily activity into a weekly score. Obtaining a weekly PAI score ≥100 is associated with reduced risk of premature morbidity and mortality from cardiovascular diseases. Here, we determined whether changes in PAI score are associated with changes in risk of incident dementia and dementia-related mortality.

METHODS

We conducted a prospective cohort study of 29,826 healthy individuals. Using data from the Trøndelag Health-Study (HUNT), PAI was estimated 10 years apart (HUNT1 1984-86 and HUNT2 1995-97). Adjusted hazard-ratios (aHR) and 95%-confidence intervals (CI) for incidence of and death from dementia were related to changes in PAI using Cox regression analyses.

FINDINGS

During a median follow-up time of 24.5 years (interquartile range [IQR]: 24.1-25.0) for dementia incidence and 23.6 years (IQR: 20.8-24.2) for dementia-related mortality, there were 1998 incident cases and 1033 dementia-related deaths. Individuals who increased their PAI score over time or maintained a high PAI score at both assessments had reduced risk of dementia incidence and dementia-related mortality. Compared with persistently inactive individuals (0 weekly PAI) at both time points, the aHRs for those with a PAI score ≥100 at both occasions were 0.75 (95% CI: 0.58-0.97) for incident dementia, and 0.62 (95% CI: 0.43-0.91) for dementia-related mortality. Using PAI score <100 at both assessments as the reference cohort, those who increased from <100 at HUNT1 to ≥100 at HUNT2 had aHR of 0.83 (95% CI: 0.72-0.96) for incident dementia, and gained 2.8 (95% CI: 1.3-4.2, P<0.0001) dementia-free years. For dementia-related mortality, the corresponding aHR was 0.74 (95% CI: 0.59-0.92) and years of life gained were 2.4 (95% CI: 1.0-3.8, P=0.001).

INTERPRETATION

Maintaining a high weekly PAI score and increases in PAI scores over time were associated with a reduced risk of incident dementia and dementia-related mortality. Our findings extend the scientific evidence regarding the protective role of PA for dementia prevention, and suggest that PAI may be a valuable tool in guiding research-based PA recommendations.

FUNDING

The Norwegian Research Council, the Liaison Committee between the Central Norway Regional Health Authority and Norwegian University of Science and Technology (NTNU), Trondheim, Norway.

Wearables in Sports Cardiology

The expanding array and adoption of consumer health wearables is creating a new dynamic to the patient-health-care provider relationship. Providers are increasingly tasked with integrating the biometric data collected from their patients into clinical care. Further, a growing body of evidence is supporting the provider-driven utility of wearables in the screening, diagnosis, and monitoring of cardiovascular disease. Here we highlight existing and emerging wearable health technologies and the potential applications for use within sports cardiology. We additionally highlight how wearables can advance the remote cardiovascular care of patients within the context of the COVID-19 pandemic. Finally, despite these promising advances, we acknowledge some of the significant challenges that remain before wearables can be routinely incorporated into clinical care.

Association Between Personal Activity Intelligence and Mortality: Population-Based China Kadoorie Biobank Study

OBJECTIVE

To prospectively investigate the association between personal activity intelligence (PAI) - a novel metabolic metric which translates heart rate during physical activity into a simple weekly score - and mortality in relatively healthy participants in China whose levels and patterns of physical activity in addition to other lifestyle factors are different from those in high-income countries.

PATIENTS AND METHODS

From the population-based China Kadoorie Biobank study, 443,792 healthy adults were recruited between June 2004 and July 2008. Participant's weekly PAI score was estimated and divided into four groups (PAI scores of 0, ≤50, 51-99, or ≥100). Using Cox proportional hazard analyses, we calculated adjusted hazard ratios (AHRs) for cardiovascular disease (CVD) and all-cause mortality related to PAI scores.

RESULTS

During a median follow-up of 8.2 (interquartile range, 7.3 to 9.1) years, there were 21,901 deaths, including 9466 CVD deaths. Compared with the inactive group (0 PAI score), a baseline weekly PAI score greater than or equal to 100 was associated with a lower risk of CVD mortality, an AHR of 0.87 (95% CI, 0.81 to 0.94) in men, and an AHR of 0.84 (95% CI, 0.78 to 0.92) in women, after adjusting for multiple confounders. Participants with a weekly PAI score greater than or equal to 100 also had a lower risk of all-cause mortality (AHR, 0.93; 95% CI, 0.89 to 0.97 in men, and AHR, 0.93; 95%, 0.88 to 0.98 in women). Moreover, this subgroup gained 2.7 (95% CI, 2.4 to 3.0) years of life, compared with the inactive cohort.

CONCLUSION

Among relatively healthy Chinese adults, the PAI metric was inversely associated with CVD and all-cause mortality, highlighting the generalizability of the score in different races, ethnicities, and socioeconomic strata.

Personal Activity Intelligence e-Health Program in People with Type 2 Diabetes: A Pilot Randomized Controlled Trial

INTRODUCTION

Innovative strategies are needed to enable people with type 2 diabetes (T2D) to self-manage physical activity (PA). Personal Activity Intelligence (PAI) is a new metric that uses the heart rate response to PA to inform the user as to whether they are doing enough PA to reduce the risk of premature mortality. The PAI score reflects PA over the previous 7 d with the goal to maintain a score ≥100. The aim of this study was to investigate the feasibility, acceptability, and efficacy of the PAI e-Health Program in people with T2D.

METHODS

Thirty participants with T2D who were not meeting PA guidelines were randomly assigned to 12 wk of either 1) PAI e-Health Program or 2) PA attention control. The PAI e-Health Program consisted of receiving a wrist-worn heart rate monitor and an app with the PAI metric, and attending 4 × 2 h·wk-1 sessions of exercise and counseling. Feasibility and acceptability of the program were evaluated by achievement of a PAI score ≥100 and participant feedback. Efficacy was determined from changes in glycemic control, cardiorespiratory fitness, exercise capacity (time-on-test), body composition, sleep time, and health-related quality of life.

RESULTS

Program participants in the PAI e-Health Program had a mean ± SD PAI score of 119.7 ± 60.6 and achieved ≥100 PAI on 56.4% of the days. The majority of participants (80%) intended to continue to use PAI monitoring. Compared with control, the PAI group significantly improved their exercise capacity (mean difference, 95% confidence interval) (63 s, 17.9-108.0 s), sleep time (67.2 min, 7.2-127.1 min), total percent body fat (-1.3%, -2.6% to -0.1%), and gynoid fat percent (-1.5%, -2.6 to -0.5).

CONCLUSIONS

The PAI e-Health Program is feasible, acceptable, and efficacious in people with T2D.

Diet, Lifestyle, Smoking

Cardiovascular disease is the leading cause of death globally The past few decades have shown that especially low- and middle-income countries have undergone rapid industrialization, urbanization, economic development and market globalization. Although these developments led to many positive changes in health outcomes and increased life expectancies, they all also caused inappropriate dietary patterns, physical inactivity and obesity. Evidence shows that a large proportion of the cardiovascular disease burden can be explained by behavioural factors such as low physical activity, unhealthy diet and smoking. Controlling these risk factors from early ages is important for maintaining cardiovascular health. Even in patients with genetic susceptibility to cardiovascular disease, risk factor modification is beneficial.Despite the tremendous advances in the medical treatment of cardiovascular risk factors to reduce overall cardiovascular risk, the modern lifestyle which has led to greater sedentary time, lower participation in active transport and time spent in leisure or purposeful physical activity, unhealthy diets and increased exposure to stress, noise and pollution have diminished the beneficial effects of contemporary medical cardiovascular prevention strategies. Therefore attenuating or eliminating these health risk behaviours and risk factors is imperative in the prevention of cardiovascular diseases.

The relationships between step count and all-cause mortality and cardiovascular events: A dose-response meta-analysis

BACKGROUND

A goal of 10,000 steps per day is widely advocated, but there is little evidence to support that goal. Our purpose was to examine the dose-response relationships between step count and all-cause mortality and cardiovascular disease risk.

METHODS

Cochrane Central Register of Controlled Trials, EMBASE, OVID, PubMed, Scopus, and Web of Science databases were systematically searched for studies published before July 9, 2021, that evaluated the association between daily steps and at least 1 outcome.

RESULTS

Sixteen publications (12 related to all-cause mortality, 5 related to cardiovascular disease; and 1 article contained 2 outcomes: both all-cause death and cardiovascular events) were eligible for inclusion in the meta-analysis. There was evidence of a nonlinear dose-response relationship between step count and risk of all-cause mortality or cardiovascular disease (p = 0.002 and p = 0.014 for nonlinearity, respectively). When we restricted the analyses to accelerometer-based studies, the third quartile had a 40.36% lower risk of all-cause mortality and a 35.05% lower risk of cardiovascular event than the first quartile (all-cause mortality: Q1 = 4183 steps/day, Q3 = 8959 steps/day; cardiovascular event: Q1 = 3500 steps/day, Q3 = 9500 steps/day; respectively).

CONCLUSION

Our meta-analysis suggests inverse associations between higher step count and risk of premature death and cardiovascular events in middle-aged and older adults, with nonlinear dose-response patterns.

Mobile Health Biometrics to Enhance Exercise and Physical Activity Adherence in Type 2 Diabetes (MOTIVATE-T2D): protocol for a feasibility randomised controlled trial

INTRODUCTION

Exercise and physical activity (PA) are fundamental to the treatment of type 2 diabetes. Current exercise and PA strategies for newly diagnosed individuals with type 2 diabetes are either clinically effective but unsuitable in routine practice (supervised exercise) or suitable in routine practice but clinically ineffective (PA advice). Mobile health (mHealth) technologies, offering biometric data to patients and healthcare professionals, may bridge the gap between supervised exercise and PA advice, enabling patients to engage in regular long-term physically active lifestyles. This feasibility randomised controlled trial (RCT) will evaluate the use of mHealth technology when incorporated into a structured home-based exercise and PA intervention, in those recently diagnosed with type 2 diabetes.

METHODS AND ANALYSIS

This feasibility multicentre, parallel group RCT will recruit 120 individuals with type 2 diabetes (diagnosis within 5-24 months, aged 40-75 years) in the UK (n=60) and Canada (n=60). Participants will undertake a 6-month structured exercise and PA intervention and be supported by an exercise specialist (active control). The intervention group will receive additional support from a smartwatch and phone app, providing real-time feedback and enabling improved communication between the exercise specialist and participant. Primary outcomes are recruitment rate, adherence to exercise and loss to follow-up. Secondary outcomes include a qualitative process evaluation and piloting of potential clinical outcome measures for a future RCT.

ETHICS AND DISSEMINATION

The trial was approved in the UK by the South East Scotland Research Ethics Committee 01 (20/SS/0101) and in Canada by the Clinical Research Ethics Board of the University of British Columbia (H20-01936), and is being conducted in accordance with the Declaration of Helsinki and Good Clinical Practice. Results will be published in peer-reviewed journals and presented at national and international scientific meetings.

TRIAL REGISTRATION NUMBERS

ISRCTN14335124; ClinicalTrials.gov: NCT04653532.

Effect of personal activity intelligence (PAI) monitoring in the maintenance phase of cardiac rehabilitation: a mixed methods evaluation

BACKGROUND

Personal activity intelligence (PAI) is a single physical activity metric based upon heart rate responses to physical activity. Maintaining 100 PAI/week is associated with a 25% risk reduction in cardiovascular disease mortality and 50 PAI/week provides 60% of the benefits. The effect of utilising this metric within a cardiac population has not been previously investigated. The aim of this study was to determine the effect of PAI monitoring on the amount and/or intensity of physical activity for people in the maintenance phase of cardiac rehabilitation and to explore participants' perceptions of this approach.

METHODS

A concurrent mixed methods approach was undertaken. Participants in the maintenance phase of cardiac rehabilitation monitored PAI for six weeks via a wearable physical activity monitoring device (WPAM). In the first three weeks participants were blinded to their PAI score. A quality-of-life questionnaire (EQ-5D-5L) was completed, and semi-structured interviews conducted to investigate attitudes to PAI monitoring. Daily PAI data was collected throughout the 6-week period.

RESULTS

Twenty participants completed the trial. PAI earned/day was increased after participants could view their data (mean difference: 2.1 PAI/day (95% CI 0.3, 4.0), p = 0.027). The median change in percentage of days participants achieved a Total PAI score of 25 (p = 0.023) and 50 (p = 0.015) were also increased. The mean change in total scores for the EQ-5D-5L and EQVAS were improved after 6 weeks (0.6 ± 1.05; 95% CI (0.11-1.09); p = 0.019); (5.8/100; 95% CI (2.4-9.2); p = 0.002 respectively). Thematic framework analysis identified three global themes (perceptions on the WPAM, PAI and factors affecting exercise). Most participants stated motivation to exercise increased after they could view their PAI data. Many of the participants believed they would continue to use PAI long-term. Others were undecided; the latter primarily due to technical issues and/or preferring devices with greater functionality and attractiveness. All participants would recommend PAI.

CONCLUSION

This exploratory study showed monitoring PAI via a WPAM increased the amount and/or intensity of physical activity within the cardiac population. Participants found PAI interesting, beneficial, and motivating. If technical issues, aesthetics, and functionality of the WPAM were improved, participants may continue to use the approach long-term. PAI may be a viable strategy to assist people with cardiac disease maintain physical activity adherence.

Association between Personal Activity Intelligence (PAI) and body weight in a population free from cardiovascular disease - The HUNT study

BACKGROUND

Personal Activity Intelligence (PAI) is a new metric for physical activity tracking, and is associated with reduced risk of all-cause and cardiovascular mortality. We prospectively investigated whether PAI is associated with lower body weight gain in a healthy population.

METHODS

We included 85,243 participants (40,037 men and 45,206 women) who participated in at least one of three waves of the Trøndelag Health Study (HUNT1: 1984-86, HUNT2: 1995-97, and HUNT3: 2006-08). We used questionnaires to estimate PAI, and linear mixed models to examine body weight according to PAI levels at three study waves. We also conducted regression analyses to assess separate relationships between change in PAI and the combined changes in PAI and physical activity recommendations, according to body weight from HUNT1 to HUNT3.

FINDINGS

Compared with HUNT1, body weight was 8.6 and 6.7 kg higher at HUNT3 for men and women, respectively, but was lower among those with ≥200 PAI at HUNT3. For both sexes, a change from inactive (0 PAI) at HUNT1 to ≥100 weekly PAI-score at HUNT2 and HUNT3, and a ≥100 PAI-score at all three occasions were associated with lower body weight gain, compared with the reference group (0 PAI at all three waves). Importantly, among both sexes, obtaining ≥100 weekly PAI at HUNT1 and HUNT3 was associated with lower body weight gain regardless of adhering to physical activity guidelines.

INTERPRETATION

Adhering to a high PAI over time may be a useful tool to attenuate excessive body weight gain in a population free from cardiovascular disease.

FUNDING

Norwegian Research Council and the Liaison Committee between the Central Norway Regional Health Authority and the Norwegian University of Science and technology.

Exploring use of activity monitors for patients with obesity during weight-loss treatment - a qualitative study

BACKGROUND

Obesity is a major health concern in western countries. In Norway, patients with obesity can attend weight-loss programmes, which focus on changes in dietary and physical activity habits. Use of self-monitoring is advocated when changing dietary and physical activity habits for adults with obesity. This study aimed to explore the experiences of patients with obesity who used activity monitors while attending a weight-loss programme.

METHODS

Patients with body mass index (BMI) > 35 kg/m2 with weight related comorbidities or a BMI > 40 kg/m2 referred to an intermittent weight-loss programme were recruited into this study. They were introduced to one of three different activity monitors, Fitbit Zip™, Mio Fuse™, or Mio Slice™. Semi-structured interviews were performed with patients six months into the weight-loss programme. Thematic analysis was applied when analysing the data.

RESULTS

Of the 29 informants (aged 21 to 66 years) interviewed, 59% were female. Their experience with activity monitors was related to their adherence to the weight-loss programme. Two main themes emerged from the informants stories: 1. "Activity monitors visualize proof of effort or failure to change health habits". 2. "Activity monitors act as a positive or negative enforcer when incorporating change".

CONCLUSIONS

Using activity monitors either strengthens or undermines patients' attempts to change health habits when attending a weight-loss program. Our findings suggest a need for more individualized weight-loss programmes for patients with obesity.

Cardiac Rehab in the COVID Era and Beyond: mHealth and Other Novel Opportunities

Purpose of Review

The COVID-19 pandemic has forced many center-based cardiac rehabilitation (CBCR) programs to close or limit their usual offerings. In order for patients to continue to benefit from CR, programs need to rapidly adapt to the current environment. This review highlights ways CR has evolved, and reviews the history of CR and recent advancements in telemedicine including remote patient monitoring, and mobile health that can be applied to CR.

Recent Findings

Despite that initial studies indicate that home-based CR (HBCR) is safe and effective, HBCR has faced several challenges that have prevented it from becoming more widely implemented. Many previous concerns can now be addressed through the use of new innovations in home-based healthcare delivery.

Summary

Since its inception, CR has become increasingly recognized as an important tool to improve patient mortality and quality of life in a broad range of cardiac diseases. While there has been little need to modify the delivery of CR since the 1950s, COVID-19 now serves as the necessary impetus to make HBCR an equal alternative to CBCR.

Temporal changes in personal activity intelligence and mortality: Data from the aerobics center longitudinal study

BACKGROUND

Personal activity intelligence (PAI) is a metric developed to simplify a physically active lifestyle for the participants. Regardless of following today's advice for physical activity, a PAI score ≥100 per week at baseline, an increase in PAI score, and a sustained high PAI score over time were found to delay premature cardiovascular disease (CVD) and all-cause mortality in a large population of Norwegians. However, the association between long-term temporal change in PAI and mortality in other populations have not been investigated.

OBJECTIVE

To test whether temporal change in PAI is associated with CVD and all-cause mortality in a large population from the United States.

METHODS

We studied 17,613 relatively healthy participants who received at least two medical examinations in the Aerobics Center Longitudinal Study between 1974 and 2002. The participant's weekly PAI scores were estimated twice, and adjusted hazard ratios (AHR) and 95% confidence intervals (CI) for CVD and all-cause mortality related to changes in PAI between baseline and last examination were assessed using Cox proportional hazard regression analyses.

RESULTS

During a median follow-up time of 9.3 years [interquartile range, 2.6-16.6; 181,765 person-years], there were 1144 deaths, including 400 CVD deaths. We observed an inverse linear association between change in PAI and risk of CVD mortality (P=0.007 for linear trend, and P=0.35 for quadratic trend). Compared to participants with zero PAI at both examinations, multivariable-adjusted analyses demonstrated that participants who maintained high PAI scores (≥100 PAI at both examinations) had a 51% reduced risk of CVD mortality [AHR, 0.49: 95% CI, 0.26-0.95)], and 42% reduced risk of all-cause mortality [AHR, 0.58: 95% CI, 0.41-0.83)]. For participants who increased their PAI scores over time (PAI score of zero at first examination and ≥100 at last examination), the AHRs were 0.75 (95% CI, 0.55-1.02) for CVD mortality, and 0.82 (95% CI, 0.69-0.99) for all-cause mortality. Participants who maintained high PAI score had 4.8 (95% CI, 3.3-6.4) years of life gained. For those who increased their PAI score over time, the corresponding years gained were 1.8 years (95% CI, 0.1-3.5).

CONCLUSION

Among relatively healthy participants, an increase in PAI and maintaining a high PAI score over time was associated with reduced risk of CVD and all-cause mortality.

CONDENSED ABSTRACT

Our objective was to investigate the association between temporal changes in PAI and mortality in a large population from the United States. In this prospective cohort study of 17,613 relatively healthy participants at baseline, maintaining a high PAI score and an increase in PAI score over an average period of 6.3 years was associated with a significant reduction in CVD and all-cause mortality. Based on our results, clinicians can easily recommend that patients obtain at least 100 PAI for most favourable protection against CVD- and all-cause mortality, but can also mention that significant benefits also occur at maintaining low-to-moderate PAI levels.

Physical fitness cognition, assessment, and promotion: A cross-sectional study in Taiwan

Introduction

Many health organizations have promoted the importance of the health-related benefits of physical fitness and physical activity. Studies have evaluated effective public health practice aiming to understand the cognition of physical activity among youths and adolescents. However, studies investigating the level of cognition and knowledge of physical fitness among Asian adults are lacking.

Purpose

This study aimed to investigate the self-awareness level of physical fitness and exercise prescription and the demand for physical fitness assessment among Taiwanese adults.

Methods

In January–July 2019, a cross-sectional anonymous survey was conducted using Research Electronic Data Capture to gather data on demographic data, cognition investigation of physical fitness and exercise prescription, cognitive test of physical fitness and exercise prescription, and demand for physical fitness assessment.

Results

The questionnaire was answered by 200 respondents. The rating for cognition investigation of physical fitness was 2.63–3.13 (unclear to mostly clear) and for exercise prescription was 2.05–2.76 (unclear) (rated on a 5-point Likert scale). Results show that lack of awareness was highest for health-related physical fitness, exercise prescription, and exercise progress planning. 98% of subjects did not know the latest recommended guidelines for physical activity, despite most agreeing that physical fitness and exercise are good for health. Most subjects (72%) indicated a willingness to accept self-pay service for physical fitness assessments.

Conclusions

This is the first study to report on the demand for cognition, assessment, and promotion of physical fitness among Taiwanese adults. The study shows that the subjects widely lack knowledge in the cognition of physical fitness and exercise prescription. Furthermore, a self-pay service for the physical fitness assessment and individualized exercise prescription were acceptable to most subjects, especially those undergoing regular health examinations. The findings are encouraging and will aid support for health organizations and professionals in the development and management of promotion strategies on health-related physical fitness in preventive medicine and health promotion.

Personal activity intelligence and mortality - Data from the Aerobics Center Longitudinal Study

IMPORTANCE

Personal activity intelligence (PAI) is a novel activity metric that can be integrated into self-assessment heart rate devices, and translates heart rate variations during exercise into a weekly score. Previous studies relating to PAI have been conducted in the same populations from Norway where the PAI metric has been derived, limiting generalizability of the results.

OBJECTIVE

To test whether PAI is associated with total and cause-specific mortality in a large cohort from the United States.

DESIGN

Aerobics Center Longitudinal Study (ACLS) - a prospective cohort between January 1974 and December 2002 with a mean follow-up of 14.5 years.

SETTING

Population-based.

PARTICIPANTS

56,175 relatively healthy participants (26.5% women) who underwent extensive preventive medical examinations at Cooper Clinic (Dallas, TX).

EXPOSURE

Personal activity intelligence (PAI) score per week was estimated and divided into 4 groups (PAI scores of 0, ≤50, 51-99, and ≥100).

MAIN OUTCOMES AND MEASURES

Total and cause-specific mortality.

RESULTS

During a median follow-up time of 14.9 (interquartile range, 6.7-21.4) years, there were 3434 total deaths including 1258 cardiovascular (CVD) deaths. Compared with the inactive (0 PAI) group, participants with a baseline weekly ≥100 PAI had lower risk of mortality: adjusted hazard ratio (AHR), 0.79: 95% CI, 0.71-0.87 for all-cause mortality, and AHR, 0.72: 95% CI, 0.60-0.87 for CVD mortality among men; AHR, 0.85: 95% CI, 0.64-1.12 for all-cause mortality, and AHR, 0.48: 95% CI, 0.26-0.91 for CVD mortality among women. For deaths from ischemic heart disease (IHD), PAI score ≥100 was associated with lower risk in both men and women (AHR, 0.70: 95% CI, 0.55-0.88). Obtaining ≥100 weekly PAI was also associated with significantly lower risk of CVD mortality in pre-specified age groups, and in participants with known CVD risk factors. Participants with ≥100 weekly PAI gained 4.2 (95% CI, 3.5-4.6) years of life when compared with those who were inactive at baseline.

CONCLUSIONS AND RELEVANCE

PAI is associated with long-term all-cause, CVD, and IHD, mortality. Clinicians and the general population can incorporate PAI recommendations and thresholds in their physical activity prescriptions and weekly physical activity assessments, respectively, to maximize health outcomes.

KEY POINTS

Question: What is the association between personal activity intelligence (PAI), a novel activity metric, and mortality in a large cohort from the United States?

FINDINGS

In this prospective study of 56,175 healthy participants at baseline, followed-up for a mean of 14.5 years, ≥100 PAI score/week was associated with significant 21% lower risk of all-cause and 30% lower risk of CVD mortality in comparison with inactive people. Participants with ≥100 PAI/week lived on average 4.2 years longer compared with inactive. Meaning: PAI is associated with long-term all-cause and CVD mortality. Clinicians and general population may incorporate PAI recommendations into weekly physical activity assessments to maximize CVD prevention.

High-Intensity Training Reduces CVD Risk Factors among Rotating Shift Workers: An Eight-Week Intervention in Industry

Rotating shift work is associated with risk factors for cardiovascular disease (CVD). We have studied the effect of 17 min high-intensity training three times a week over eight weeks on CVD risk factors among shift workers. Sixty-five shift workers from two plants were recruited. They were all deemed healthy at the initial health screening and in 100% work. From plant A, 42 workers, and plant B, 23 workers participated. After the intervention, 56 workers were retested. The intervention group consisted of 19 participants from plant A who had participated in at least 10 sessions. Twenty workers from plant B and 17 workers from plant A that not had taken part in the training were included in the control group. All workers reported physical activity (PA) by questionnaires before and after the training intervention. We measured blood pressure, heart rate, lipids, glycated hemoglobin (HbA1c), and C-reactive protein (CRP) and arterial stiffness. Maximal oxygen uptake (V.O_2max) was assessed by bicycle ergometry. The intervention group favorably differed significantly from the control group in improvement of systolic and diastolic blood pressure and glycated hemoglobin (HbA1c). Short training sessions with 4 min of high-intensity PA, three times a week, for eight weeks among rotating shift workers reduced some CVD risk factors. PA interventions in occupational settings may thus decrease coronary heart disease and stroke incidences in this vulnerable group of workers.

Cardiovascular Health Effects of Shift Work with Long Working Hours and Night Shifts: Study Protocol for a Three-Year Prospective Follow-Up Study on Industrial Workers

There is a plausible association between shift work and cardiovascular disease (CVD), which may be due to disruption of the circadian rhythm causing hormonal changes and metabolic disturbances, resulting in high blood pressure, atherosclerosis, diabetes, and being overweight. However, few studies have investigated the association between several consecutive long work shifts, including night shifts, and risk factors for developing CVD. Moreover, knowledge is lacking on factors that may modify or enhance this suggested relationship. The study period is planned from the third quarter of 2018 to the fourth quarter of 2021, and will involve 125 industrial employees at two Norwegian enterprises producing insulation. The work schedule is either rotating shiftwork (morning, evening, night) or regular day work. At baseline, we will measure blood parameters, including markers of inflammation, lipids, and glycosylated hemoglobin. We will also collect measures of blood pressure, resting heart rate, arterial stiffness, carotid intima-media thickness, and aerobic fitness. At the end of baseline data collection, a subgroup will undergo a supervised high-intensity interval training intervention for eight weeks, initiated by the Occupational Health Service. At one-year follow-up, we repeat baseline measures with added measures of heart rate variability and additional five weeks monitoring of sleep and physical activity, and assessment of respirable dust. At the two year follow-up, we will measure CVD risk factors before and after a planned three-month shutdown in one of the studied plants. We will also assess respirable dust, monitor sleep, and compile a one-year retrospective detailed overview of working hours. A final data collection, similar to the one at baseline, will be carried out after three years. We will use a comprehensive set of methods to identify the effects of shift work with long working hours and night shifts on cardiovascular health. This will provide new knowledge on the association between early manifestations of CVD and occupational exposure to shift work. Further, we can study whether work organization such as extensive overtime, sleep loss, and dust exposure have detrimental effects, and if a three-month cease in shift work or increased physical activity will modify early manifestations of CVD.

Using wearable technology to predict health outcomes: a literature review

Objective

To review and analyze the literature to determine whether wearable technologies can predict health outcomes.

Materials and methods

We queried Ovid Medline 1946 -, Embase 1947 -, Scopus 1823 -, the Cochrane Library, clinicaltrials.gov 1997 – April 17, 2018, and IEEE Xplore Digital Library and Engineering Village through April 18, 2018, for studies utilizing wearable technology in clinical outcome prediction. Studies were deemed relevant to the research question if they involved human subjects, used wearable technology that tracked a health-related parameter, and incorporated data from wearable technology into a predictive model of mortality, readmission, and/or emergency department (ED) visits.

Results

Eight unique studies were directly related to the research question, and all were of at least moderate quality. Six studies developed models for readmission and two for mortality. In each of the eight studies, data obtained from wearable technology were predictive of or significantly associated with the tracked outcome.

Discussion

Only eight unique studies incorporated wearable technology data into predictive models. The eight studies were of moderate quality or higher and thereby provide proof of concept for the use of wearable technology in developing models that predict clinical outcomes.

Conclusion

Wearable technology has significant potential to assist in predicting clinical outcomes, but needs further study. Well-designed clinical trials that incorporate data from wearable technology into clinical outcome prediction models are required to realize the opportunities of this advancing technology.

Machine Learning Algorithms Can Use Wearable Sensor Data to Accurately Predict Six-Week Patient-Reported Outcome Scores Following Joint Replacement in a Prospective Trial

BACKGROUND

Tracking patient-generated health data (PGHD) following total joint arthroplasty (TJA) may enable data-driven early intervention to improve clinical results. We aim to demonstrate the feasibility of combining machine learning (ML) with PGHD in TJA to predict patient-reported outcome measures (PROMs).

METHODS

Twenty-two TJA patients were recruited for this pilot study. Three activity trackers collected 35 features from 4 weeks before to 6 weeks following surgery. PROMs were collected at both endpoints (Hip and Knee Disability and Osteoarthritis Outcome Score, Knee Osteoarthritis Outcome Score, and Veterans RAND 12-Item Health Survey Physical Component Score). We used ML to identify features with the highest correlation with PROMs. The algorithm trained on a subset of patients and used 3 feature sets (A, B, and C) to group the rest into one of the 3 PROM clusters.

RESULTS

Fifteen patients completed the study and collected 3 million data points. Three sets of features with the highest R² values relative to PROMs were selected (A, B and C). Data collected through the 11th day had the highest predictive value. The ML algorithm grouped patients into 3 clusters predictive of 6-week PROM results, yielding total sum of squares values ranging from 3.86 (A) to 1.86 (C).

CONCLUSION

This small but critical proof-of-concept study demonstrates that ML can be used in combination with PGHD to predict 6-week PROM data as early as 11 days following TJA surgery. Further study is needed to confirm these findings and their clinical value.

High-intensity interval training for health benefits and care of cardiac diseases - The key to an efficient exercise protocol

Aerobic capacity, which is expressed as peak oxygen consumption (VO2peak), is well-known to be an independent predictor of all-cause mortality and cardiovascular prognosis. This is true even for people with various coronary risk factors and cardiovascular diseases. Although exercise training is the best method to improve VO2peak, the guidelines of most academic societies recommend 150 or 75 min of moderate- or vigorous- intensity physical activities, respectively, every week to gain health benefits. For general health and primary and secondary cardiovascular prevention, high-intensity interval training (HIIT) has been recognized as an efficient exercise protocol with short exercise sessions. Given the availability of the numerous HIIT protocols, which can be classified into aerobic HIIT and anaerobic HIIT [usually called sprint interval training (SIT)], professionals in health-related fields, including primary physicians and cardiologists, may find it confusing when trying to select an appropriate protocol for their patients. This review describes the classifications of aerobic HIIT and SIT, and their differences in terms of effects, target subjects, adaptability, working mechanisms, and safety. Understanding the HIIT protocols and adopting the correct type for each subject would lead to better improvements in VO2peak with higher adherence and less risk.

Computer-Aided Diagnosis and Clinical Trials of Cardiovascular Diseases Based on Artificial Intelligence Technologies for Risk-Early Warning Model

The use of artificial intelligence in medicine is currently an issue of great interest, especially with regard to the diagnostic or predictive analysis of medical data. In order to achieve the regional medical and public health data analysis through artificial intelligence technologies, spark data analysis is adopted as the research platform for hypertension patients, and artificial intelligence technologies are used to preprocess the data with inconsistency, redundancy, incompleteness, noise and error; Aiming at the unbalanced data sets, the Z-score standard is adopted to convert data into usable form suitable for data mining. And, the application of Logistic, Naive Bayesian regression, and support vector machine based on three groups of different prognosis in severe cases, including stroke, heart failure and renal failure symptoms, establish the risk early warning model for 3 years time. In addition, to select the optimal feature subset based on medicine big-data features, the model simplification and optimization are done in training process, the experimental results show that the feature subset selection can ensure the classification performance similar to the clinical features of the model. Therefore, according to chronic cardiovascular disease, acute cardiovascular events and cardiovascular events caused by critical illness events, we screen out the relevant prognosis of serious illness (stroke, heart failure, renal failure), which is related to the prognosis of serious illness. Targeted prevention has a guiding role and practical significance according to the results of artificial intelligence analysis.

Sedentary Behavior, Exercise, and Cardiovascular Health

Sedentary behavior and physical inactivity are among the leading modifiable risk factors worldwide for cardiovascular disease and all-cause mortality. The promotion of physical activity and exercise training (ET) leading to improved levels of cardiorespiratory fitness is needed in all age groups, race, and ethnicities and both sexes to prevent many chronic diseases, especially cardiovascular disease. In this state-of-the-art review, we discuss the negative impact of sedentary behavior and physical inactivity, as well as the beneficial effects of physical activity /ET and cardiorespiratory fitness for the prevention of chronic noncommunicable diseases, including cardiovascular disease. We review the prognostic utility of cardiorespiratory fitness compared with obesity and the metabolic syndrome, as well as the increase of physical activity /ET for patients with heart failure as a therapeutic strategy, and ET dosing. Greater efforts at preventing sedentary behavior and physical inactivity while promoting physical activity, ET, and cardiorespiratory fitness are needed throughout the healthcare system worldwide and particularly in the United States in which the burden of cardiometabolic diseases remains extremely high.

Personal Activity Intelligence (PAI): A new standard in activity tracking for obtaining a healthy cardiorespiratory fitness level and low cardiovascular risk

Despite all the evidence of health benefits related to physical activity (PA) and cardiorespiratory fitness (CRF), low levels of PA have reached pandemic proportions, and inactivity is the fourth leading cause of death worldwide. Lack of time, and inability to self-manage are often cited as main barriers to getting adequate PA. Recently, a new personalized metric for PA tracking named Personal Activity Intelligence (PAI) was developed with the aim to make it easier to quantify how much PA per week is needed to reduce the risk of premature mortality from non-communicable diseases. PAI can be integrated in self-assessment heart rate devices and defines a weekly beneficial heart rate pattern during PA by considering the individual's sex, age, and resting and maximal heart rates. Among individuals ranging from the general population to subgroups of patients with cardiovascular disease (CVD), a PAI score ≥100 per week at baseline, an increase in PAI score, and a sustained high PAI score over time were found to delay premature death from CVD and all causes, regardless of whether or not the current PA recommendations were met. Importantly, a PAI score ≥100 at baseline, maintaining ≥100 PAIs and an increasing PAI score over time was associated with multiple years of life gained. Moreover, obtaining a weekly PAI ≥100 attenuated the deleterious association between CVD risk factor clustering and prolonged sitting time. PAI and objectively measured CRF (as indicated by VO_2peak) were positively associated in a graded fashion, and individuals with a PAI score between 100 and 150 had expected age and sex specific average VO_2peak values. A PAI score ≥100 was associated with higher VO_2peak in both men (4.1 mL·kg^-1·min^-1; 95% CI, 3.5 to 4.6) and women (2.9 mL·kg^-1·min^-1; 95% CI, 2.4 to 3.3), compared to the reference group of <100 PAI. The combined analysis of PAI, PA and VO_2peak demonstrated that a PAI score ≥100 was associated with high VO_2peak values regardless of meeting or not meeting the current PA recommendations. Collectively, these findings suggest that PAI has the potential to be a useful tool to motivate people to become and stay physically active by quantifying the amount of PA needed to produce significant health benefits.