Faculty Bibliography

BACKGROUND: Food insecurity (FI) occurs when individuals or households have limited or uncertain access to adequate food. People with FI may find it particularly difficult to eat a balanced diet and manage weight. Individuals who report FI are 1.4 times more likely to have obesity. U.S. Veterans have a greater prevalence of FI compared with the general population (24% vs. 19%). As part of a pilot randomized controlled trial to test the impact of an obesity intervention for Veterans, we explored the prevalence of FI in our sample and assessed the impact of FI on weight outcomes. METHODS: Veterans with a Body Mass Index of greater than or equal to 30 or between 25 and 29.99 with at least one comorbidity were recruited by phone for a pilot study. Participants randomized to the intervention received a technology-assisted health coaching session and follow-up coaching calls; control participants received a VA "healthy living messages" pamphlet. At baseline and 3 months, participants had weight measurements and completed surveys. To measure FI, we used a 6-item Household Food Security Scale (FI = 2 or more affirmative responses). We assessed the impact of FI on variables independent of arm assignment in participants who returned for a 3-month measurement visit (Wilcoxon rank sum tests and Fisher's Exact Test). We also analyzed the role of FI as a moderator between arm and study variables using ANOVA. RESULTS: Out of 31 Veterans who enrolled in the study (Mean age = 53.48, 63% male, mean BMI = 31.72), 10 demonstrated FI at baseline and 25 participants completed 3 month measurements. Independent of the intervention, those with FI (n = 10) lost .01 kg of weight and those without FI (n = 15) lost 1.69 kg at 3-months but the difference was not significant (p = 0.2). Similarly, 0/10 Veterans with FI achieved 2.5% weight loss, compared to 4/15 of those without FI (p = 0.12). Those with FI in the control group gained weight when compared to those without FI (1.04 kg, SD = 1.41 vs. -1.75, SD = 3.96) and those with FI in the intervention lost the same amount of weight as those without FI (-1.59 kg, SD = 0.83, vs. -1.59, SD = 2.27; p = 0.24 for the interaction (not significant)). CONCLUSIONS: FI in Veterans enrolled in a weight management study is high. Participants with FI in the control arm may have gained weight when compared to non-FI participants, while intervention arm participants with FI lost similar amounts of weight to those without FI. This suggests that the intervention may reduce the negative impact of FI. While this pilot study was not powered to show a significant difference, we have amended health coaching protocols to better address FI in our intervention (e.g. screening for FI and linking participants with Supplemental Nutrition Assistance Program (SNAP) benefits and similar resources) hoping to maximize its effectiveness

BACKGROUND: Obesity is under-treated and primary care teams find it difficult to provide effective lifestyle-based weight management counseling. Further, only 10% of eligible patients attendMOVE!, theVAweight management and health promotion program. We developed an intervention called Goals for Eating and Moving (GEM) to improve counseling within primary care (PC) and increase attendance in intensive weight management programs such as MOVE!. METHODS: Veterans with a Body Mass Index of greater than or equal to 30 or between 25 and 29.99 with at least one comorbidity were recruited by phone and randomized toGEMor "Enhanced Usual Care" (EUC). GEMutilizes the Patient Aligned Care Teams (PACTs) within the VA to deliver 5As counseling (Assess, Advise, Agree, Assist and Arrange) to promote modest weight loss and behavior change. Participants use a goal-setting tool to generate tailored materials, which facilitates in-person and phone counseling with health coaches. Coaches support PACTcounseling during regular PC visits and encourage participants to join VA weight management services. Veterans in GEM received the intervention and Veterans in EUC met with a coach to receive the VA "healthy living messages" pamphlet. At baseline and 3 months, participants had weight measurements and completed surveys. We used the Paffenbarger Physical Activity Questionnaire and a 17-item screener to derive fruit and vegetable intake, energy from fat, and dietary fiber. Vegetable intake (leafy greens/salad) and sugar-sweetened beverage were measured as individual items. We performed per-protocol analyses (Wilcoxon Rank sums test and Spearman Correlation) to assess the relationship between GEM and different variables. RESULTS: Thirty-one Veterans (mean age = 53.48, 63% male, mean BMI = 31.72) enrolled and 25 returned at 3-months (1 dropped out and 5 were lost-tofollow up). Those in GEM lost significantly more weight at 3-months (-1.59 kg, SD = 1.76) than those in EUC (-0.63 kg, SD = 3.42, p = 0.03). There were no statistically significant differences in diet and physical activity. For Veterans that received GEM, higher number of phone coaching sessions was correlated with weight loss (Spearman Correlation -0.58, p = 0.09). CONCLUSIONS: This early analysis indicates that GEM promotes small but significant (p = 0.03) weight loss at 3-months and identified the need for high patient retention and engagement, since the number of health coaching calls may correlate with weight loss. Based on this we have refined protocols for phone coaching to ensure that scheduling and reminder calls are patientcentered. This pilot study informed the development of a multi-site cluster- RCT of GEM to begin in June 2017 (NIH # 1R01 DK111928-01)

OBJECTIVE: Adults with serious psychological distress have a high likelihood of mental health problems severe enough to cause serious impairment in social and occupational functioning requiring treatment. These adults visit doctors frequently yet have poor health compared to adults without serious psychological distress. This study examined associations between emotional states of serious psychological distress in relationship to healthcare utilization indicators. A guiding hypothesis was that somatization underlying emotional states contributes to excessive healthcare seeking among adults with serious psychological distress. METHODS: Using 2006-2014 National Health Interview Survey, in adults with serious psychological distress (n=9271), the six states: unable to make efforts, nervousness, hopelessness, sadness, worthlessness and restlessness were assessed in multivariate models in relation to four healthcare utilization indicators: change in the usual place of healthcare, change due to insurance, having seen a healthcare provider in the last 6months and having 10 or more doctor visits in the last 12months. Models were adjusted for sociodemographic variables, having seen a mental health provider, and health conditions. RESULTS: Adults feeling unable to make efforts were more likely to seek healthcare in the last 6months and at least ten times in the last twelve months. Adults feeling hopeless were less likely to be heavy healthcare utilizers. CONCLUSIONS: Predisposing medical conditions do not fully explain healthcare utilization in adults with serious psychological distress. Educating healthcare providers about the emotional states motivating healthcare seeking, and integrating mental healthcare into primary care, may improve the health of adults with serious psychological distress.

BACKGROUND: Obesity disproportionately affects Latina women, but few targeted, technology-assisted interventions that incorporate tailored health information exist for this population. The Veterans Health Administration (VHA) uses an online weight management tool (MOVE!23) which is publicly available, but was not designed for use in non-VHA populations. METHODS: We conducted a qualitative study to determine how interactions between the tool and other contextual elements impacted task performance when the target Latina users interacted with MOVE!23. We sought to identify and classify specific facilitators and barriers that might inform design changes to the tool and its context of use, and in turn promote usability. Six English-speaking, adult Latinas were recruited from an inner city primary care clinic and a nursing program at a local university in the United States to engage in a "Think-Aloud" protocol while using MOVE!23. Sessions were recorded, transcribed, and coded to identify interactions between four factors that contribute to usability (Tool, Task, User, Context). RESULTS: Five themes influencing usability were identified: Technical Ability and Technology Preferences; Language Confusion and Ambiguity; Supportive Tool Design and Facilitator Guidance; Relevant Examples; and Personal Experience. Features of the tool, task, and other contextual factors failed to fully support participants at times, impeding task completion. Participants interacted with the tool more readily when its language was familiar and content was personally relevant. When faced with ambiguity and uncertainty, they relied on the tool's visual cues and examples, actively sought relevant personal experiences, and/or requested facilitator support. CONCLUSIONS: The ability of our participants to successfully use the tool was influenced by the interaction of individual characteristics with those of the tool and other contextual factors. We identified both tool-specific and context-related changes that could overcome barriers to the use of MOVE!23 among Latinas. Several general considerations for the design of eHealth tools are noted.

OBJECTIVE: This study sought to identify rates and predictors of obesity counseling performed by outpatient psychiatrists in the United States. METHODS: The 2005-2010 National Ambulatory Medical Care Surveys provided data from 7,309 outpatient psychiatry visits. Logistic regression was used to examine associations between patient, visit, and practice characteristics and outcomes. RESULTS: Most (81%) visits occurred in a private practice setting. Nine percent (N=657) of visits included measurement of patient body mass index (BMI); 30% of these visits were with patients who met the obesity criterion (BMI >/=30.0 kg/m2). Among visits with obese patients, 16% included exercise counseling, 22% included weight reduction counseling, and 24% included diet or nutrition counseling. Patients with obesity were more likely than patients without obesity to receive diet or nutrition counseling (p<.05) and weight reduction counseling (p<.05), but not exercise counseling. Black patients were significantly less likely to receive any form of counseling (p<.05). CONCLUSIONS: There is a significant need to improve psychiatrists' obesity counseling.

Early childhood is a critical stage for the foundation and development of both the microbiome and host. Early-life antibiotic exposures, cesarean section, and formula feeding could disrupt microbiome establishment and adversely affect health later in life. We profiled microbial development during the first 2 years of life in a cohort of 43 U.S. infants and identified multiple disturbances associated with antibiotic exposures, cesarean section, and formula feeding. These exposures contributed to altered establishment of maternal bacteria, delayed microbiome development, and altered alpha-diversity. These findings illustrate the complexity of early-life microbiome development and its sensitivity to perturbation.

BACKGROUND: Obesity is highly prevalent among Veterans. In the United States, the Veterans Health Administration (VHA) offers a comprehensive weight management program called MOVE!. Yet, fewer than 10 % of eligible patients ever attend one MOVE! visit. The VHA has a patient-centered medical home (PCMH) model of primary care (PC) called Patient-Aligned Care Teams (PACT) at all Veterans Affairs (VA) Medical Centers. PACT teamlets conduct obesity screening, weight management counseling, and refer to MOVE!. As part of a needs assessment to improve delivery of weight management services, the purpose of this study was to assess PACT teamlet and MOVE! staff: 1) current attitudes and perceptions regarding obesity care; 2) obesity-related counseling practices 3) experiences with the MOVE! program; and 4) targets for interventions to improve implementation of obesity care in the PC setting. METHODS: We recruited 25 PACT teamlet members from a single VA study site-11 PC physicians, 5 registered nurses, 5 licensed practical nurses, 1 clerical assistant, and 3 MOVE! staff (2 dietitians, 1 psychologist)-for individual interviews using a combination of convenience and snowball sampling. Audio recorded interviews were professionally transcribed and iteratively coded by two independent reviewers. The analytic process was guided by discourse analysis in order to discover how the participants perceived and provided weight management care and what specific attitudes affected their practices, all as bounded within the organization. RESULTS: Emerging themes included: 1) role perceptions, 2) anticipated outcomes of weight management counseling and programs, and 3) communication and information dissemination. Perceived role among PCPs was influenced by training, whereas personal experience with their own weight management impacted role perception among LPNs/RNs. Attitudes about whether or not they could impact patients' weight outcomes via counseling or referral to MOVE! varied. System-level communication about VHA priorities through electronic health records and time allocation influenced teams to prioritize referral to MOVE! over weight management counseling. CONCLUSION: We found a diversity of attitudes, and practices within PACT, and identified factors that can enhance the MOVE! program and inform interventions to improve weight management within primary care. Although findings are site-specific, many are supported in the literature and applicable to other VA and non-VA sites with PCMH models of care.