African American - Senior adults with senior children

National Family Caregiver’s Month

Did you know scientific studies show that people who help others are generally healthier themselves?

It’s true! While caregiving can be stressful, there are many health benefits to caregiving that parallel those of volunteerism, perhaps even outweighing the negative impacts of its concomitant stress.

That’s one of the points Dr. David L. Roth, director of the Center on Aging and Health (COAH), makes in a National Family Caregiver’s Month blog he wrote for Johns Hopkins’ Frailty Science team.  Check it out here to get a great overview of research on the stress and benefits of caregiving.

As you may know, Dr. Roth is a leader in the field of research on family caregivers’ health and wellbeing.  Here’s a few influential articles about research on this topic with which he has been involved, and in which you might be interested:

Many COAH researchers are involved in studies to advance understanding about this matter. Keep checking our News section for fresh insights! Meanwhile, please know that we see you, appreciate you, and celebrate you.  Without a doubt, family caregivers are a strong thread running through the great social fabric in America’s beautiful tapestry.

Happy National Family Caregiver’s Month!

image of Sarah Szanton

Dean Sarah Szanton is Elected to NAM

The Center on Aging and Health (COAH)’s team enthusiastically congratulates longtime COAH colleague Sarah Szanton, PhD RN FAAN, Dean, and Patricia M. Davidson Health Equity and Social Justice Endowed Professor at the School of Nursing, upon her election to the National Academy of Medicine (NAM).

NAM is a private, nonprofit institution dedicated to improving “health for all by advancing science, accelerating health equity, and providing independent, authoritative, and trusted advice nationally and globally.”  New NAM members are elected by current members, and with the new inductees in October, 2021, the academy now has 2,100 national and international members. Membership to NAM is not only elite and honorific, it is also significant and impactful.  Leaders from across the United States and around the world consult NAM for expert opinions to shape and implement health policy. Consequently, NAM membership is considered to be the highest national honor possible in medicine.

In their statement listing newly elected members, NAM noted choosing Dean Szanton “for pioneering new approaches to reducing health disparities among low-income older adults.” This statement gives a nod to Dean Szanton’s sterling reputation in co-developing the CAPABLE program, which is currently expanding through Medicare Advantage and Value Based Care and is already available in 45 places across 23 states. CAPABLE has been described as “visionary” and “innovative” for its multidisciplinary and practical approach to helping older adults remain in their own homes, in their beloved communities; the same adjectives can easily be applied to Dean Szanton’s engaging leadership style.

We at COAH know that the nation and the international community are better served with sound advice and expert guidance from Dean Szanton in this very important role as a member of NAM.  The Center celebrates and congratulates Dean Szanton on this remarkable honor and tremendous new role!

To learn more about NAM, click here. You may be interested to know that an astounding 10% of the newly elected NAM members are affiliated with Johns Hopkins; read more about it here.

Jacek K. Erbanek

Multi-day remote measurements of physical activity, mobility, diurnal patterns, and sleep in community-dwelling older adults: Part 2 of a series on the Johns Hopkins Accelerometry Resource Core

Part Two of a two-part series on the important role of accelerometry in aging science.  The Accelerometry Resource Core (ARC) at COAH has been created to help wearable data become one of the pillars of modern medicine and epidemiology by increasing its accessibility to a wide range of health researchers.  To read Part One of this series, click here.  To learn more about the ARC, visit accelerometry.org or reach out to Dr. Urbanek directly: jurbane2@jhu.edu or at wearables @jhu.edu.

For investigators seeking to add wearable accelerometers to their research, the ARC can help with study design, including selecting devices, determining duration and frequency of monitoring, contributing to IRB applications, and contributing to funding proposals. Further, the core provides training for clinical personnel and manuals of operating procedures to ensure proper initialization and distribution of the accelerometers, data management, device maintenance, and redistribution.

All data-related operations within ARC are handled by a proprietary, dedicated data processing platform that guarantees thorough quality control and reproducible results as soon as the next day after the collection. The platform allows for flexible, HIPAA compliant, data transfer procedures that are  driven by existing file-sharing solutions at the collaborator’s institution (e.g., OneDrive, Box, SFTP, and others). After the upload, each data file is downloaded and checked for integrity, including the detection of corrupted files due to a malfunctioning device or unstable network connection. Additionally, the platform checks if the correct data has been uploaded and if the name of the file fits the study-specific convention. If any problems are identified at this stage, ARC staff immediately contacts the field center/clinic to resolve and if possible, avoid future issues of a similar nature.

After the quality control, raw data is archived and passed on for pre-processing. As different accelerometer manufacturers use distinct, proprietary data formats, often requiring dedicated software, the ARC platform has a built-in functionality that allows communication with third-party solutions, despite the generation and type of interface. At this step, data is converted to the universal time-series format that can be then read by popular statistical analysis packages (e.g., R, Python, SAS, Stata). Next, the data is analyzed to detect if and when the accelerometer was removed by the participant during collection. Although most wearable monitors can be worn continuously, participants often choose to remove them for bathing, certain work tasks, or contact-sport activities. Proper pre-processing requires detection of such non-wear periods and, when possible, imputation of the missing data. Also, based on the detected non-wear periods, participant’s adherence to the study protocol is characterized by determining which days can be used to represent free-living movement. Clean accelerometry data is then summarized into a set of characteristics representing volumes and fragmentation of physical activity, circadian rhythms, and sleep. The summary data is next formatted to fit existing research platforms or protocols specific to each study, archived, and shared with coordinating centers.

Processing of voluminous, free-living measurements, often collected in multi-site, longitudinal settings, is challenging not only because of the complexity and sheer size of data but also due to the novelty of technology itself. At the ARC we have streamlined the measurement process and introduced measurement and analytical standards that build the foundation for a wide-scale utilization of wearable accelerometry in health research and clinical practice. To guarantee reproducibility and transparency of scientific results, ARC members created an open-source, freely available software package (ARCTOOLS for R) used in all pre-processing and analytical steps. Thanks to the creation of standards, software tools, and hardware infrastructure ARC has reduced costs for the investigators while maximizing productivity. In most cases, newly collected data is cleaned and processed into the analytical form in just a few days after the initial upload. The ARC platform is currently processing hundreds of new, high-density, multi-day observations every month in the ongoing projects of our collaborators.

After successful data collection, ARC faculty and staff offer help with statistical analyses, including a selection of physical activity characteristics that best address the aims of the study, proper adjustment for potential confounders, statistical modeling, and interpretation of the obtained results. These services are complemented with assistance in manuscript preparation, including outlining the measurement protocols and analytical approach, and interpreting the results.

An example of a Johns Hopkins Accelerometry Resource Core (ARC) partnership: Together with the ENGAGE research lab, which focuses on promoting and improving ambulatory measurement in free-living settings with wearable devices in clinical and research settings, ARC seeks to advance the science and understanding of physical activity, mobility, sleep quality, cardiovascular health, and more through advanced analytics and computational methods.

Members of ARC provide support for the collection and analytics of physical activityheart rate, and ambulatory ECG and blood glucose measurements with wearable devices in multiple large observational studies and clinical trials. In total, ARC has collected and processed multi-day, high-density data in over 11,000 participants. Among ARC’s collaborators are:

 

Jacek K. Erbanek

Multi-day remote measurements of physical activity, mobility, diurnal patterns, and sleep in community-dwelling older adults: Part 1 of a series on the Johns Hopkins Accelerometry Resource Core

Image of physical activity

Part One of a two part series on the important role of accelerometry in aging science. The Accelerometry Resource Core (ARC) at COAH has been created to help wearable data become one of the pillars of modern medicine and epidemiology by increasing its accessibility to a wide range of health researchers. To learn more about the ARC, visit accelerometry.org or reach out to Dr. Urbanek directly: jurbane2@jhu.edu or at wearables@jhu.edu.

In recent years, small wearable devices that collect various biological signals have experienced rapid growth in popularity in research and consumer use. Among the many types of wearable sensors, accelerometers that measure the movement of individuals throughout the day and over multiple days are likely the most common. Devices like Fitbit, Apple Watch, and research-oriented Actigraphs have been implemented in various large observational studies, clinical trials, and interventions. These devices are small, waterproof, non-invasive and, in their recent iteration, can be worn like a watch without the need for removing for sleep or bathing.

Accelerometers, while most commonly associated with workout tracking and step counting, are capable of much more. Advances in mobile technology over the last decade, have led to smaller sensors with increased memory capacity and battery life, and more affordable prices. As a result, modern, research-grade wearable accelerometers can now collect and store three-dimensional, high-frequency data on human movement continuously over multiple days and nights. For the first time, researchers can gain detailed insight into physical activity, mobility, diurnal rhythms, and sleep characteristics in the context of health.

image of Jacek Urbanek and diurnal pattern

Click here to watch a quick video with Dr. Jacek Urbanek demonstrating just one example of data that a wearable device can pick up from simply clapping his hands, and begin to imagine the bench to bedside possibilities that accelerometry can add to research, clinical trials, and patient centered care.

In the aging population, activities of daily living, mobility, and gait speed are often considered as key measures that can predict various health and quality of life outcomes including functional independence, sensory loss, physical frailty, falls, and death. Advances in wearable technology have not only expanded the ability to effectively monitor and improve the understanding of these measures, but also provide for the remote, multi-day collection of data in free-living conditions that are the most natural to the patient. This results in observations that go beyond the in-clinic snapshot and reflect a more accurate spectrum of movement across a variety of contexts. The importance of the remote collection of clinically relevant data has been further emphasized by the recent COVID-19 pandemic that caused significant limitations to in-person healthcare, especially affecting older, at-risk populations.

Wearable accelerometers were brought into the research spotlight by high-impact, large observational studies focused on general populations. The National Health and Nutrition Examination Survey (NHANES) introduced hip-worn devices in 2003 for the assessment of free-living physical activity and continued this measurement though 2006. Further, NHANES resumed the assessment in 2013 with a new generation of wrist-worn Actigraphs. Similarly, the Study of Latinos (SOL) successfully used wearable accelerometers to monitor longitudinal changes of physical activity across study visits, which is now followed by the assessment with the state-of-the-art devices implemented as a part of Peripheral Artery Disease Study of SOL (PASOS). Internationally, in 2013, the UK Biobank introduced a large-scale cross-sectional collection of wrist-worn accelerometry data to characterize physical activity in the population of the United Kingdom. That success motivated more focused observational studies, clinical trials, and interventions to collect data using wearable devices. In aging research studies, the Baltimore Longitudinal Study of Aging (BLSA) pioneered large-scale monitoring of free-living physical activity and sleep characteristics in older adults, shortly followed by the National Health and Aging Trends Study (NHATS). Overall, the multi-day observation of movements of individuals in real-world settings has been found useful in all areas of health research where physical activity, mobility, or sleep may play an important role. In addition to aging, these areas include frailty, cardiovascular health, recovery after a surgery or clinical stressor, weight loss interventions and obesity, HIV/AIDS, chronic kidney disease, and Alzheimer’s disease, among others.

While wearable devices have been successfully implemented in many existing and new research studies, the technology is still novel and rapidly evolving. The Accelerometry Resource Core (ARC) at the Johns Hopkins Center on Aging and Health has been created to help wearable data become one of the pillars of modern medicine’s clinical practice and research, including epidemiology, by increasing its accessibility to a wide range of health researchers. The ARC offers a full range of collaborative services and provides the expertise, tools, and human resources required for the successful implementation of these measurements. The core is currently collaborating with multiple large-, mid-, and small-size studies by overseeing the collection and providing analytical support for wearable data. Among the most recognizable collaborators are the NHATS, Atherosclerosis Risk in Communities (ARIC), Aging, Cognition and Hearing Evaluation in Elders (ACHIEVE), BLSA, Study To Understand Fall Reduction and Vitamin D in You (STURDY), Characterizing Resiliencies to Physical Stressors in Older Adults (SPRING), PASOS, and Chronic Kidney Disease in Children (CKiD). Throughout these collaborations, members of the ARC have collected, processed, and analyzed cross-sectional and longitudinal data from over 5,000 participants, including over 4,000 older individuals, effectively becoming the largest repository of harmonized, sub-second level, wrist accelerometry data in older adults in the United States.

 

Stay tuned for Part Two of this article, coming soon!