A considerable proportion of outdoor physical activity is done on sidewalk/streets. For example, we found that ~70% of adults who walked during the previous week used the sidewalks/streets around their homes. Interventions conducted at geographical levels (e.g., community) and studies examining relationships between environmental conditions (e.g., traffic) and walking/biking, necessitate a reliable measure of physical activities performed on sidewalks/streets. The Block Walk Method (BWM) is one of the more common approaches available for this purpose. Although it utilizes reliable observation techniques and displays criterion validity, it remains relatively unchanged since its introduction in 2006. It is a non-technical, labor-intensive, first generation method. Advancing the BWM would contribute significantly to our understanding of physical activity behavior. Therefore, the objective of the proposed study is to develop and test a new BWM that utilizes a wearable video device (WVD) and computer video analysis to assess physical activities performed on sidewalks/streets. The following aims will be completed to accomplish this objective. Aim 1: Improve the BWM by incorporating a WVD into the methodology. The WVD is a pair of eyeglasses with a high definition video camera embedded into the frames. We expect the WVD to be a viable option for improving the acquisition and accuracy of data collected using the BWM. Aim 2: Advance the WVD-enhanced BWM by applying machine learning and recognition software to automatically extract information on physical activities occurring on the sidewalks/streets from the videos. Methods: Trained observers (one wearing and one not wearing the WVD) will walk together at a set pace along predetermined, 1000 ft. sidewalk/street segments representing low, medium, and high walkable areas. During the walks, the non-WVD observer will use the traditional BWM to record the number of individuals standing/sitting, walking, biking, and running along the segments. The WVD observer will only record a video while walking. Later, two investigators will view the videos to determine the numbers of individuals performing physical activities along the segments. For aim 2, the video data will be analyzed automatically using multiple deep convolutional neural networks (CNNs) to determine the number of humans in a segment as well as the type of physical activities being performed. Bland Altman methods and intraclass correlation coefficients will be used to assess agreement. Potential sources of error such as occlusions (e.g., trees) will be assessed using moderator analyses. We expect the new approach will enhance measurement accuracy while reducing the burden of data collection. In the future, we will expand the capabilities of the WVD-CNNs system to allow for the determination of other characteristics captured by the videos such as caloric expenditure and environmental conditions. Our long-term goal is to substantially improve the assessment of physical activity and our understanding of physical activity behavior.
In 2015, an estimated 340,000 parents of school age children were newly diagnosed with cancer in the U.S. Parental cancer causes significant emotional distress in both diagnosed parents and children. African American (AA) adults experience a disproportionate burden of solid tumor cancers (e.g., breast, prostate, lung, and colon) which puts AA adolescents, a vulnerable population to begin with, at high risk for parental cancer related distress. Treatments have been somewhat successful for younger school age children (ages 7-12) of cancer patients but most treatment studies have included white middle class samples. Differences in attitudes, daily functioning and levels of distress among different ethnic and racial groups are well-documented, yet few culturally sensitive family intervention programs have been developed for AA families coping with cancer. To address this gap, we are conducting a randomized control trial to test a culturally sensitive family-based intervention that targets the parent child relationship in AA families coping with the impact of solid tumor parental cancer. 172 AA families coping with parental cancer are randomized to either a Families Fighting Cancer Together (FFCT) or a parent psycho-education (TAU) control condition. We expect the FFCT condition to improve the developmental adjustment to parental cancer among high-risk AA adolescents. [PI: Adam Davey, PhD]
Coinciding with age-related declines in physical activity (PA), nearly half of mid-life adults also report insufficient sleep. Multi-component interventions aiming to increase PA and improve sleep can evoke synergistic improvements in cardiovascular disease risk. Augmenting the delivery of individually tailored behavior change techniques and behavioral feedback within “smart” platforms can enhance user engagement and motivation that lead to improved PA and sleep behaviors. From this premise, our current study is developing, and testing, the Bio-behavioral Systems to Motivate And Reinforce HearT Health (Be SMART), cloud-based feedback system, on changes in PA and sleep that will be used to inform a larger randomized control trial. We expect the Be SMART condition to lead to a sustained increase in weekly minutes of moderate-to-vigorous physical activity (MVPA) and improved sleep versus those assigned to an active control (Fitbit-only) condition in mid-life adults. This study has the potential to favorably impact public health and inform novel approaches to designing multi-component behavioral interventions. [PI: Gregory Dominick, PhD]
African American (AA) adults are more likely to report insufficient sleep duration (<7 hours) and other sleep deficiencies (e.g., poor sleep quality), and to have advanced Chronic Obstructive Pulmonary Disease (COPD), than Non-Hispanic Whites (NHW) with similar smoking behaviors.
Not known are the multi-level (i.e., individual, social and environmental) factors that predict insufficient sleep duration and other sleep deficiencies, and the extent to which sleep deficiencies predict poorer health outcomes such as continued tobacco use and worsening lung function in AA smokers. To address these knowledge gaps, we are conducting a 5-year prospective cohort study where 400 AA smokers who are aged >39 years, and are prodromal or with early stage COPD, are being enrolled and will have key biological, psychosocial, behavioral, and environmental variables assessed across the study period. We expect to define multi-level phenotypes of risk for sleep deficiencies, continued tobacco use, and worsening lung function in this health disparate population of mid-life AA smokers. [PI: Freda Patterson, PhD]
Developing a Systems-based Approach to Improve Cardiovascular Health in Food Assistance Populations.
Continued cigarette smoking and poor dietary intake are key reasons why 95% of US adults have poor cardiovascular (CV) health: this burden is disproportionately represented in food assistance populations. In partnership with the Food Bank of Delaware, we have developed and are pilot-testing two multi-level systems-based approaches, one to address tobacco use, and one to address dietary choice. Food bank personnel are linked with the Delaware quit-line face-to-face program and are trained to become certified quit-smoking coaches to deliver the free, three-session, face-to-face cessation program that includes 8-weeks of quit-smoking medication at the food-distribution sites. To address dietary choice, food bank personnel are trained to use nudging (a subtle environment change in a food distribution settings designed to make a healthy choice the easy choice) strategies to promote selection of fruits, vegetables, and whole grains. We expect this pilot-study to provide support for our multi-level, systems approach to improving the key CV risk behaviors of tobacco use and poor dietary intake in food assistance populations. [PI’s: Freda Patterson, PhD, and Shannon Robson, PhD, RD, MPH]
Informed policy and decision making during the COVID-19 pandemic benefits from epidemiological models. However, no such models exist that integrate real time data on local population density and movement on the scale of the university and its environs (i.e., Newark). University and City of Newark policy decisions during the continuing COVID-19 pandemic could be based on validated models that incorporate epidemiology with human traffic flow so as to better inform policy decisions as well as enable the rational study of “what-if” scenarios using best available data. This is a unique research program, as there is no current NSF RAPID grant that combines unique methods of data acquisition (drone, wearable video devices) with a local, multivariate population balance model for use in forecasting and policy development. Broader impacts include future use in predictive modeling of active matter.
Dietary Patterns of Socioeconomically and Racially Diverse Populations: Healthy Aging in Neighborhoods of Diversity across the Life Span [HANDLS] Study.
The HANDLS study is part of a fixed cohort of 3,720 community-dwelling African American and white adults aged 30-65. Participants were recruited from 13 pre-determined neighborhoods around Baltimore City. The larger parent study is planned as a 20-year longitudinal study. As a key investigator with the HANDLS study, Dr. Marie Kuczmarski is using data from the larger study to examine the relationships between diet and cardiovascular health of African American and white adults. Study participants have competed two 24-hour dietary recalls. Anthropometric and biochemical data, and demographic and lifestyle factors have also been collected on these individuals. This study is expected to elucidate the extent to which race or income independently or synergistically contribute to the dietary and lifestyle behaviors associated with increased risk for cardiovascular disease. [PI: Marie Kuczmarski, PhD, MPH]
Fructose is a major source of added sugar in the human diet. An unhealthy diet can lead to hypertension and poor cardiovascular health outcomes. The purpose of the current study is to learn about the effects of high and low fructose on cardiovascular health and cognitive function.
To this end, we are conducting a within-subject study where participants who are 65-80 years old and have not been diagnosed with hypertension, diabetes, or heart disease will adhere to three different diets one week of low fructose, one week of high fructose, and two weeks of a control diet; the diets will be assigned to each subject in a random order. Study measures include weekly anthropometrics, fasting blood draw, urine collection, and blood pressure. This study is expected to inform dietary interventions to prevent cardiovascular disease. [PI: Sheau Ching Chai, PhD]
Energy-dense, nutrient poor foods often represent a significant proportion of a preschooler’s diet and the diet of children with overweight and obesity is often more energy-dense as compared to children of a healthy weight. Consumption of energy-dense foods contributes to excessive energy intake, and thus overweight and obesity. Energy density (ED), the number of kilocalories per gram of food can influence both energy intake and diet quality. Food higher in ED increase energy intake and decrease diet quality, and foods lower in ED decrease energy intake and improve diet quality. Observational studies consistently demonstrate these outcomes, yet little research has examined the effect of dietary goals specifically targeting ED. To fill this gap, our study is testing a novel dietary ED approach within a 6-month family-based obesity prevention lifestyle intervention. We are examining its effect on ED, energy intake, diet quality, and zBMI. Forty children (2-5 years-old) at risk for obesity based on having ≥1 parent with obesity are randomized to one of two conditions: a low-ED dietary prescription (≥10 foods/day, ED≤1.0 and ≤2 foods/day, ED≥3.0) or the standard MyPlate recommendations. This study is expected to inform obesity prevention approaches. [PI: Shannon Robson, PhD, RD, MPH]
The purpose of the NIH funded project is to conduct secondary data analyses on a unique and comprehensive data set collected during a randomized controlled trial (RCT) that determined the impact of early formula diet on energy balance, growth, and weight gain. Using data collected from infants and their mothers from 2 weeks to 1.5 years, we will analyze secondary outcomes that fall into three broad categories: biomarkers and risk factors for later obesity; lab-based measures of infant vegetable acceptance and taste genotype; and feeding patterns and practices and nutrient intake. This project will expand our knowledge of early nutritional programming in a contemporary cohort of infants, with goal of improving the health of the next generation of infants who feed formula, many of whom are at risk for later obesity. [PIs: Jillian Trabulsi, PhD, RD and Julie Mennella, PhD]
An unacceptably high percentage of our nation’s low-income, minority youth (< 18 years of age) are not regularly physically active. The presence of quality youth physical activity opportunities (YPAO) enables and encourages physically active lifestyles. Unfortunately, quality YPAOs often are lacking in places where minority youth live, resulting in low activity levels and subsequent health issues that represent significant disparities in our society. Our previous research found that small businesses (< 500 employees), which represent over 99% of all employers, are powerful resources for creating and improving YPAOs. In accordance with the Socioecological Model and established philanthropic principles, we developed an alpha version of an intervention (alpha-i) for increasing small businesses’ involvement with YPAOs. We are now creating a beta version (beta-i) and pilot testing its impact on small business support for YPAOs and YPAO utilization by youth in low-income, minority New Castle County, Delaware neighborhoods. Results from this study are expected to inform a nationally implementable practice for increasing support for YPAOs and strengthen the science of addressing health disparities in socially disadvantaged populations. [PI: Richard Suminski, PhD, MPH]
Reaching Racial/Ethnic Minority Communities to Support Healthy Lifestyle Change: Virtual World Training for Community Health Workers.
The burden of diabetes is greater for racial/ethnic minorities, including African Americans. Overweight and obesity are risk factors for the development of diabetes and are also more prevalent in racial/ethnic minorities. The Diabetes Prevention Program and subsequent translation studies demonstrated the efficacy of a lifestyle intervention on reducing weight and risk of type 2 diabetes. Increasing evidence supports efforts to engage CHWs to help extend our reach to raise awareness about diabetes prevention in underserved communities. Innovative internet-based CHW training programs that are standardized, effective, and scalable could provide a convenient and engaging training model to support the efforts of CHWs. To address this need, we are currently developing, implementing, and evaluating an internet-based 3-dimensional (3-D) virtual world model to remotely deliver a CHW training program (CDC “Road to Health”; RTH) to support CHWs’ efforts in raising awareness about diabetes prevention in African American communities. If our virtual world CHW training model shows promise it could be tailored/adapted for diverse groups and scaled for broad remote dissemination. [PI: Laurie Ruggiero, PhD]
There are an estimated 16 million cancer survivors in the United States and many frequently report long-term treatment side-effects including fatigue, distress, nutritional concerns, and sleep disturbance. Addressing these survivorship issues is a national clinical and community-health priority. To address this need, we are implementing and testing the effects of a tailored wellness in-person and telephonic health coaching program. Trained clinical health coaches assist cancer survivors with physical activity, nutrition, sleep health, and other healthy lifestyle changes to incorporate after a cancer diagnosis. Our hope is to reach 80 cancer survivors in 18 months, and to ultimately inform a model for multi-modal health behavior change in this at-risk group. [PI: Michael Mackenzie, PhD]