The Systematic Multi-domain Alzheimer's Risk Reduction Trial (SMARRT) intervention: A personalized approach to dementia risk reduction.

Background: Addressing modifiable risk factors such as physical inactivity and social isolation could reduce risk of Alzheimer's disease and all-cause dementia, but little is known about which factors individuals are most willing to address or how they prefer to address them.

Objective: To examine and describe behavior change goals set by participants during the Systematic Multi-domain Alzheimer's Risk Reduction Trial (SMARRT).

Methods: In SMARRT, older adults worked with a health coach and nurse over 2 years to set incremental, personalized goals to reduce dementia risk.

Understanding Goal Setting and Behavior Change Mechanics in an Older Adult Sitting Reduction Intervention.

Purpose: We explored intervention fidelity, participant satisfaction, and the goals and reminder strategies participants chose to reduce sitting.

Approach: Mixed methods approach leveraging data collected during study coaching and fidelity monitoring.

Setting: A successful 6-month randomized controlled trial of a sedentary behavior (SB) intervention for adults ≥60 years in Washington, USA.

Understanding resilience: Lifestyle-based behavioral predictors of mental health and well-being in community-dwelling older adults during the COVID-19 pandemic.

Background: Changes in sleep, physical activity and mental health were observed in older adults during early stages of the COVID-19 pandemic. Here we describe effects of the COVID-19 pandemic on older adult mental health, wellbeing, and lifestyle behaviors and explore predictors of better mid-pandemic mental health and wellbeing.

Methods: Participants in the Adult Changes in Thought study completed measures of lifestyle behaviors (e.

Associations of Cognitively Active Versus Passive Sedentary Behaviors and Cognition in Older Adults.

Background: Cognitively stimulating sedentary behavior (SB) may positively impact cognition. This study aimed to (1) describe participation across types of SB among older adults with and without cognitive impairment and (2) examine how baseline SB participation impacts cognition, longitudinally.

Methods: We used National Health and Aging Trends Study data from rounds 6 to 11 for cross-sectional and longitudinal analyses.

Historic Cognitive Function Trajectories as Predictors of Sedentary Behavior and Physical Activity in Older Adults.

Background: We examined whether trajectories of cognitive function over 10 years predict later-life physical activity (PA), sedentary time (ST), and sleep.

Methods: Participants were from the Adult Changes in Thought (ACT) cohort study. We included 611 ACT participants who wore accelerometers and had 3+ measures of cognition in the 10 years prior to accelerometer wear.

Using functional principal component analysis (FPCA) to quantify sitting patterns derived from wearable sensors.

Background: Sedentary behavior (SB) is a recognized risk factor for many chronic diseases. ActiGraph and activPAL are two commonly used wearable accelerometers in SB research. The former measures body movement and the latter measures body posture.

Sitting Time Reduction and Blood Pressure in Older Adults: A Randomized Clinical Trial.

Importance: Practical health promotion strategies for improving cardiometabolic health in older adults are needed.

Objective: To examine the efficacy of a sedentary behavior reduction intervention for reducing sitting time and improving blood pressure in older adults.

Design, Setting, And Participants: This parallel-group randomized clinical trial was conducted in adults aged 60 to 89 years with high sitting time and body mass index of 30 to 50 from January 1, 2019, to November 31, 2022, at a health care system in Washington State.

Neighborhood built and food environment in relation to glycemic control in people with type 2 diabetes in the moving to health study.

Objective: To examine whether built environment and food metrics are associated with glycemic control in people with type 2 diabetes.

Research Design And Methods: We included 14,985 patients with type 2 diabetes using electronic health records from Kaiser Permanente Washington. Patient addresses were geocoded with ArcGIS using King County and Esri reference data.

Co-designing mind-body technologies for sleep with adolescents.

Sleep is critical for well-being, yet adolescents do not get enough sleep. Mind-body approaches can help. Despite the potential of technology to support mind-body approaches for sleep, there is a lack of research on adolescent preferences for digital mind-body technology.

Improving physical activity among prostate cancer survivors through a peer-based digital walking program.

Physical activity is important for prostate cancer survivors. Yet survivors face significant barriers to traditional structured exercise programs, limiting engagement and impact. Digital programs that incorporate fitness trackers and peer support via social media have potential to improve the reach and impact of traditional support.

Prioritizing a research agenda on built environments and physical activity: a twin panel Delphi consensus process with researchers and knowledge users.

Background: The growth of urban dwelling populations globally has led to rapid increases of research and policy initiatives addressing associations between the built environment and physical activity (PA). Given this rapid proliferation, it is important to identify priority areas and research questions for moving the field forward. The objective of this study was to identify and compare research priorities on the built environment and PA among researchers and knowledge users (e.

Effect of Personalized Risk-Reduction Strategies on Cognition and Dementia Risk Profile Among Older Adults: The SMARRT Randomized Clinical Trial.

Importance: Modifiable risk factors are hypothesized to account for 30% to 40% of dementia; yet, few trials have demonstrated that risk-reduction interventions, especially multidomain, are efficacious.

Objective: To determine if a personalized, multidomain risk reduction intervention improves cognition and dementia risk profile among older adults.

Design, Setting, And Participants: The Systematic Multi-Domain Alzheimer Risk Reduction Trial was a randomized clinical trial with a 2-year personalized, risk-reduction intervention.

The Impact of Pandemic-Related Restrictions on Dementia Risk Factors in Older Adults.

Adults aged 65+ are at highest risk for severe COVID-19 outcomes, and prior to the distribution of vaccines in the U.S., were strongly advised to quarantine at home to reduce risk of infection.

Association of Perceived Neighborhood Environments With Cognitive Function in Older Adults.

The current study examined the associations between perceptions of the social and physical neighborhood environments and cognitive function in older adults. This cross-sectional study analyzed 821 adults aged ≥65 years from the Adult Changes in Thought study. Perceived neighborhood attributes were measured by the Physical Activity Neighborhood Environment Scale.

Exploring needs, interests and preferences for digital mind-body tools for adolescents.

Sleep problems are common among adolescents and research on mind-body interventions for sleep is promising. Although technology-based mind-body interventions have been shown to help early adolescents with practicing mind-body approaches, engagement and adherence has been a challenge. Using a Human-Centered Design framework with semi-structured interviews with parent-adolescent dyads, we describe exposure to, interest in, and preferences for digital mind-body technology for sleep.

Analysis of the 24-h activity cycle: An illustration examining the association with cognitive function in the Adult Changes in Thought study.

The 24-h activity cycle (24HAC) is a new paradigm for studying activity behaviors in relation to health outcomes. This approach inherently captures the interrelatedness of the daily time spent in physical activity (PA), sedentary behavior (SB), and sleep. We describe three popular approaches for modeling outcome associations with the 24HAC exposure.

CHAP-Adult: A Reliable and Valid Algorithm to Classify Sitting and Measure Sitting Patterns Using Data From Hip-Worn Accelerometers in Adults Aged 35.

Background: Hip-worn accelerometers are commonly used, but data processed using the 100 counts per minute cut point do not accurately measure sitting patterns. We developed and validated a model to accurately classify sitting and sitting patterns using hip-worn accelerometer data from a wide age range of older adults.

Methods: Deep learning models were trained with 30-Hz triaxial hip-worn accelerometer data as inputs and activPAL sitting/nonsitting events as ground truth.

CHAP-child: an open source method for estimating sit-to-stand transitions and sedentary bout patterns from hip accelerometers among children.

Background: Hip-worn accelerometer cut-points have poor validity for assessing children's sedentary time, which may partly explain the equivocal health associations shown in prior research. Improved processing/classification methods for these monitors would enrich the evidence base and inform the development of more effective public health guidelines. The present study aimed to develop and evaluate a novel computational method (CHAP-child) for classifying sedentary time from hip-worn accelerometer data.

Differences in Weight Gain Following Residential Relocation in the Moving to Health (M2H) Study.

Background: Neighborhoods may play an important role in shaping long-term weight trajectory and obesity risk. Studying the impact of moving to another neighborhood may be the most efficient way to determine the impact of the built environment on health. We explored whether residential moves were associated with changes in body weight.

Exploring Differences in Older Adult Accelerometer-Measured Sedentary Behavior and Resting Blood Pressure Before and During the COVID-19 Pandemic.

Older adults have higher sedentary behavior (SB), lower physical activity, and are particularly susceptible to negative impacts from the COVID-19 pandemic and associated public health restrictions. Pandemic impacts to SB and health, particularly via objective assessment, are not well documented in the literature. Here we described differences in SB, physical activity, and blood pressure (BP) for older adults before and during the pandemic.

Design of digital walking programs that engage prostate cancer survivors: Needs and preferences from focus groups.

The majority of prostate cancer survivors do not meet physical activity (PA) recommendations. Although technology has shown to promote PA, engagement has been a challenge. This mixed method study characterizes survivors' needs and preferences for digital walking programs Through focus groups and surveys, we engaged prostate cancer support groups to describe PA motivators and barriers, interest in improving PA, and preferences for design features of a future digital walking program.

Associations of light physical activity, moderate-to-vigorous physical activity and sedentary behavior with quality of life in men on androgen deprivation therapy for prostate cancer: a quantile regression analysis.

To examine associations of physical activity (PA) and sedentary time (SED) with quality of life (QoL) in men on androgen deprivation therapy (ADT) for prostate cancer. A pooled analysis of 106 men on ADT was conducted. PA and SED were assessed using accelerometers.

Agreement of sedentary behaviour metrics derived from hip-worn and thigh-worn accelerometers among older adults: with implications for studying physical and cognitive health.

Little is known about how sedentary behaviour (SB) metrics derived from hip-worn and thigh-worn accelerometers agree for older adults. Thigh-worn activPAL micro monitors were concurrently worn with hip-worn ActiGraph GT3X+ accelerometers (with SB measured using the 100 count-per-minute (cpm) cut-point; ActiGraph) by 953 older adults (age 77±6.6, 54% women) for 4-to-7 days.

Protocol for a randomized controlled trial of sitting reduction to improve cardiometabolic health in older adults.

Older adults with obesity spend the majority of their waking hours sedentary. Given substantial barriers to regular physical activity in this population, approaches to reduce sedentary time could be an effective health promotion strategy. We present the protocol of a randomized controlled trial to reduce sitting time in older adults with a body mass index of 30 kg/m or above.

Application of Convolutional Neural Network Algorithms for Advancing Sedentary and Activity Bout Classification.

Background: Machine learning has been used for classification of physical behavior bouts from hip-worn accelerometers; however, this research has been limited due to the challenges of directly observing and coding human behavior "in the wild." Deep learning algorithms, such as convolutional neural networks (CNNs), may offer better representation of data than other machine learning algorithms without the need for engineered features and may be better suited to dealing with free-living data. The purpose of this study was to develop a modeling pipeline for evaluation of a CNN model on a free-living data set and compare CNN inputs and results with the commonly used machine learning random forest and logistic regression algorithms.