Leah Yingling

Community Engagement to Optimize the Use of Web-Based and Wearable Technology in a Cardiovascular Health and Needs Assessment Study: A Mixed Methods Approach

Background Resource-limited communities in Washington, D.C. have high rates of obesity-related cardiovascular disease in addition to inadequate physical activity (PA) facilities and limited Internet access. Engaging community members in the design and implementation of studies to address these health disparities is essential to the success of community-based PA interventions. Objective The objective of the study was to use qualitative and quantitative methods to evaluate the feasibility and acceptability of PA-monitoring wristbands and Web-based technology by predominantly African American, church-based populations in resource-limited Washington, D.C. neighborhoods. Methods To address cardiovascular health in at-risk populations in Washington, D.C., we joined community leaders to establish a community advisory board, the D.C. Cardiovascular Health and Obesity Collaborative (D.C. CHOC). As their first initiative, the Washington, D.C. Cardiovascular Health and Needs Assessment intends to evaluate cardiovascular health, social determinants of health, and PA-monitoring technologies. At the recommendation of D.C. CHOC members, we conducted a focus group and piloted the proposed PA-monitoring system with community members representing churches that would be targeted by the Cardiovascular Health and Needs Assessment. Participants (n=8) agreed to wear a PA-monitoring wristband for two weeks and to log cardiovascular health factors on a secure Internet account. Wristbands collected accelerometer-based data that participants uploaded to a wireless hub at their church. Participants agreed to return after two weeks to participate in a moderated focus group to share experiences using this technology. Feasibility was measured by Internet account usage, wristband utilization, and objective PA data. Acceptability was evaluated through thematic analysis of verbatim focus group transcripts. Results Study participants (5 males, 3 females) were African American and age 28-70 years. Participant wristbands recorded data on 10.1±1.6 days. Two participants logged cardiovascular health factors on the website. Focus group transcripts revealed that participants felt positively about incorporating the device into their church-based populations, given improvements were made to device training, hub accessibility, and device feedback. Conclusions PA-monitoring wristbands for objectively measuring PA appear to be a feasible and acceptable technology in Washington, D.C., resource-limited communities. User preferences include immediate device feedback, hands-on device training, explicit instructions, improved central hub accessibility, and designation of a church member as a trained point-of-contact. When implementing technology-based interventions in resource-limited communities, engaging the targeted community may aid in early identification of issues, suggestions, and preferences. ClinicalTrial Trial Registration: ClinicalTrials.gov NCT01927783; https://clinicaltrials.gov/ct2/show/NCT01927783 (Archived by WebCite at http://www.webcitation.org/6f8wL117u)

Use of Mobile Health Technology in the Prevention and Management of Diabetes Mellitus

Cardiovascular disease is the leading cause of morbidity and mortality globally, with diabetes being an independent risk factor. Adequate diabetes management has proven to be resource-intensive, requiring frequent lab work, primary care and specialist visits, and time-consuming record-keeping by the patient and care team. New mobile health (mHealth) technologies have enhanced how diabetes is managed and care is delivered. While more recent work has investigated mHealth devices as complementary tools in behavioral interventions for diabetes prevention and management, little is still known about the effectiveness of mHealth technology as stand-alone intervention tools for reducing diabetes risk. In addition, more work is needed to identify the role of mHealth technology in treating vulnerable populations to ameliorate cardiovascular health disparities. With advances in mobile health technology development for diabetes prevention and management, these modalities will likely play an increasingly prominent role in reducing cardiometabolic risk for the US population.

Health Insurance Status as a Barrier to Ideal Cardiovascular Health for U.S. Adults: Data from the National Health and Nutrition Examination Survey (NHANES).

Background Little is known about the association between cardiovascular (CV) health and health insurance status. We hypothesized that U.S. adults without health insurance coverage would have a lower likelihood of ideal cardiovascular health. Methods and Results Using National Health and Nutrition Examination Survey (NHANES) data from 2007–2010, we examined the relationship between health insurance status and ideal CV health in U.S. adults aged ≥19 years and <65 (N = 3304). Ideal CV health was defined by the American Heart Association (AHA) as the absence of clinically manifested CV disease and the simultaneous presence of 6–7 “ideal” CV health factors and behaviors. Logistic regression modeling was used to determine the relationship between health insurance status and the odds of ideal CV health. Of the U.S. adult population, 5.4% attained ideal CV health, and 23.5% were without health insurance coverage. Those without health insurance coverage were more likely to be young (p<0.0001), male (p<0.0001), non-white (p<0.0001), with less than a high school degree (p<0.0001), have a poverty-to-income ratio less than 1 (p<0.0001) and unemployed (p<0.0001) compared to those with coverage. Lack of health insurance coverage was associated with a lower likelihood of ideal CV health; however, this relationship was attenuated by socioeconomic status. Conclusions U.S. adults without health insurance coverage are less likely to have ideal CV health. Population-based strategies and interventions directed at the community-level may be one way to improve overall CV health and reach this at-risk group.

Optimizing scoring and sampling methods for assessing built neighborhood environment quality in residential areas

Optimization of existing measurement tools is necessary to explore links between aspects of the neighborhood built environment and health behaviors or outcomes. We evaluate a scoring method for virtual neighborhood audits utilizing the Active Neighborhood Checklist (the Checklist), a neighborhood audit measure, and assess street segment representativeness in low-income neighborhoods. Eighty-two home neighborhoods of Washington, D.C. Cardiovascular Health/Needs Assessment (NCT01927783) participants were audited using Google Street View imagery and the Checklist (five sections with 89 total questions). Twelve street segments per home address were assessed for (1) Land-Use Type; (2) Public Transportation Availability; (3) Street Characteristics; (4) Environment Quality and (5) Sidewalks/Walking/Biking features. Checklist items were scored 0–2 points/question. A combinations algorithm was developed to assess street segments’ representativeness. Spearman correlations were calculated between built environment quality scores and Walk Score®, a validated neighborhood walkability measure. Street segment quality scores ranged 10–47 (Mean = 29.4 ± 6.9) and overall neighborhood quality scores, 172–475 (Mean = 352.3 ± 63.6). Walk scores® ranged 0–91 (Mean = 46.7 ± 26.3). Street segment combinations’ correlation coefficients ranged 0.75–1.0. Significant positive correlations were found between overall neighborhood quality scores, four of the five Checklist subsection scores, and Walk Scores® (r = 0.62, p < 0.001). This scoring method adequately captures neighborhood features in low-income, residential areas and may aid in delineating impact of specific built environment features on health behaviors and outcomes.

Digital Food Records in Community-Based Interventions: Mixed-Methods Pilot Study

Background A pressing need exists to understand and optimize the use of dietary assessment tools that can be used in community-based participatory research (CBPR) interventions. A digital food record, which uses a mobile device to capture the dietary intake through text and photography inputs, is a particularly promising mobile assessment method. However, little is understood about the acceptability and feasibility of digital food records in CBPR and how to best tailor dietary assessment tools to the needs of a community. Objective The objective of our study was to evaluate the acceptability and feasibility of digital food records among church-based populations in resource-limited wards of Washington, DC, USA, using a mixed-methods approach. Methods This community-based pilot study was conducted as part of the Washington, DC Cardiovascular Health and Needs Assessment. Participants (n=17) received a mobile device (iPod Touch) to photodocument their dietary intake for a 3-day digital food record using a mobile app, FitNinja (Vibrent Health). The acceptability of the digital food record was explored through the thematic analysis of verbatim transcripts from a moderated focus group (n=8). In addition, the feasibility was evaluated by the percentage of participants complying with instructions (ie, capturing both before and after meal photos for at least 2 meals/day for 3 days). Results Qualitative themes identified were related to (1) the feasibility and acceptability of the mobile device and app, including issues in recording the dietary information and difficulty with photodocumentation; (2) suggestions for additional support and training experiences; and (3) comparisons with other mobile apps. Overall, the participants accepted the digital food record by demonstrating satisfaction with the tool and intent to continue the use (eg, participants recorded an average of 5.2, SD 7, consecutive days). Furthermore, of the 17 participants, 15 photodocumented at least 1 meal during the study period and 3 fully complied with the digital food record instructions. Conclusions This study demonstrated digital food records as an acceptable tool in CBPR and identified contributors and barriers to the feasibility of digital food records for future research. Engaging community members in the implementation of novel assessment methods allows for the tailoring of technology to the needs of the community and optimizing community-based interventions. Trial Registration ClinicalTrials.gov NCT01927783; https://www.clinicaltrials.gov/ct2/show/NCT01927783 (Archived by WebCite at http://www.webcitation.org/70WzaFWb6)

Clustering of Health Behaviors and Cardiorespiratory Fitness Among U.S. Adolescents

PURPOSE Decreased cardiorespiratory fitness (CRF) is associated with an increased risk of cardiovascular disease. However, little is known how the interaction of diet, physical activity (PA), and sedentary time (ST) affects CRF among adolescents. By using a nationally representative sample of U.S. adolescents, we used cluster analysis to investigate the interactions of these behaviors with CRF. We hypothesized that distinct clustering patterns exist and that less healthy clusters are associated with lower CRF. METHODS We used 2003-2004 National Health and Nutrition Examination Survey data for persons aged 12-19 years (N = 1,225). PA and ST were measured objectively by an accelerometer, and the American Heart Association Healthy Diet Score quantified diet quality. Maximal oxygen consumption (V˙O2​max) was measured by submaximal treadmill exercise test. We performed cluster analysis to identify sex-specific clustering of diet, PA, and ST. Adjusting for accelerometer wear time, age, body mass index, race/ethnicity, and the poverty-to-income ratio, we performed sex-stratified linear regression analysis to evaluate the association of cluster with V˙O2​max. RESULTS Three clusters were identified for girls and boys. For girls, there was no difference across clusters for age (p = .1), weight (p = .3), and BMI (p = .5), and no relationship between clusters and V˙O2​max. For boys, the youngest cluster (p < .01) had three healthy behaviors, weighed less, and was associated with a higher V˙O2​max compared with the two older clusters. CONCLUSIONS We observed clustering of diet, PA, and ST in U.S. adolescents. Specific patterns were associated with lower V˙O2​max for boys, suggesting that our clusters may help identify adolescent boys most in need of interventions.