Faculty Bibliography

Weight loss reduces the risk of type 2 diabetes mellitus (T2D) in overweight and obese individuals. Although the physiological response to food varies among individuals, standard dietary interventions use a "one-size-fits-all" approach. The Personal Diet Study aims to evaluate two dietary interventions targeting weight loss in people with prediabetes and T2D: (1) a low-fat diet, and (2) a personalized diet using a machine-learning algorithm that predicts glycemic response to meals. Changes in body weight, body composition, and resting energy expenditure will be compared over a 6-month intervention period and a subsequent 6-month observation period intended to assess maintenance effects. The behavioral intervention is delivered via mobile health technology using the Social Cognitive Theory. Here, we describe the design, interventions, and methods used.

BACKGROUND:Insulin titration is typically done face-to-face with a clinician; however, this can be a burden for patients due to logistical issues associated with in-person clinical care. The Mobile Insulin Titration Intervention (MITI) used basic cell phone technology including text messages and phone calls to help patients with diabetes find their optimal basal insulin dose (OID). OBJECTIVE:To evaluate sociodemographic and clinical correlates of reaching OID, text message response rate, and days needed to reach OID. METHODS:Primary care providers referred patients to MITI and nurses delivered the program. Three multivariable regression models quantified relationships between various correlates and primary outcomes. RESULTS:The sample included 113 patients from 2 ambulatory clinics, with a mean age of 50 years (SD = 10), 45% female, 79% Hispanic, 43% unemployed, and 46% uninsured. In regression models, baseline fasting blood glucose (FBG) was negatively associated with odds of reaching OID and 100% text responses, and positively associated with days to reach OID, p < .05). CONCLUSIONS:Patients with higher baseline FBG levels were less successful across outcomes and may need additional supports in future mHealth diabetes programs. PRACTICAL IMPLICATIONS/CONCLUSIONS:Basic cell phone technology can be used to adjust patients' insulin remotely, thereby reducing logistical barriers to care.

Favourable body composition has been associated with higher dietary protein intake. However, little is known regarding this relationship in a population of Chinese Americans (CHA), who have lower BMI compared with other populations. The aim of the present study was to assess the relationship between dietary protein intake, fat mass (FM) and fat-free mass (FFM) in CHA. Data were from the Chinese American Cardiovascular Health Assessment (CHA CHA) 2010-2011 (n 1707); dietary intake was assessed using an adapted and validated FFQ. Body composition was assessed using bioelectrical impedance analysis. The associations between protein intake (% energy intake) and BMI, percentage FM (FM%), percentage FFM (FFM%), FM index (FMI) and FFM index (FFMI) were examined using multiple linear regression adjusted for age, sex, physical activity, acculturation, total energy intake, sedentary time, smoking status, education, employment and income. There was a significant positive association between dietary protein and BMI (B = 0·056, 95 % CI 0·017, 0·104; P = 0·005), FM (B = 0·106, 95 % CI 0·029, 0·184; P = 0·007), FM% (B = 0·112, 95 % CI 0·031, 0·194; P = 0·007) and FMI (B = 0·045, 95 % CI 0·016, 0·073; P = 0·002). There was a significant negative association between dietary protein and FFM% (B = -0·116, 95 % CI -0·196, -0·036; P = 0·004). In conclusion, higher dietary protein intake was associated with higher adiposity; however, absolute FFM and FFMI were not associated with dietary protein intake. Future work examining the relationship between protein source (i.e. animal) and body composition is warranted in this population of CHA.

BACKGROUND:The Mobile Insulin Titration Intervention (MITI) program helps patients with type 2 diabetes find their correct basal insulin dose without in-person care. Requiring only basic cell phone technology (text messages and phone calls), MITI is highly accessible to patients receiving care in safety-net settings. MITI was shown in a randomized controlled trial (RCT) to be efficacious at a New York City (NYC) safety-net clinic where patients often have challenges coming for in-person care. In 2016, MITI was implemented as usual care at Bellevue Hospital (the site of the original RCT) and at Gouverneur Health (a second NYC safety-net clinic) under 2 different staffing models. OBJECTIVE:This implementation study examined MITI's transition into real-world settings. To understand MITI's flexibility, generalizability, and acceptability among patients and providers, we evaluated whether MITI continued to produce positive outcomes in expanded underserved populations, outside of an RCT setting. METHODS:Patients enrolled in MITI received weekday text messages asking for their fasting blood glucose (FBG) values and a weekly titration call. The goal was for patients to reach their optimal insulin dose (OID), defined either as the dose of once-daily basal insulin required to achieve either an FBG of 80-130 mg/dL (4.4-7.2 mmol/L) or as the reaching of the maximum dose of 50 units. After 12 weeks, if OID was not reached, the patients were asked to return to the clinic for in-person care and titration. MITI program outcomes, clinical outcomes, process outcomes, and patient satisfaction were assessed. RESULTS:levels fell from 11.4% (101 mmol/mol) to 10.0% (86 mmol/mol), P<.001. Process outcomes show that 90.1% of MITI's text message prompts received a response, nurses connected with patients 81.9% of weeks to provide titration instructions, and 85% of attending physicians made at least one referral to the MITI program. Satisfaction surveys showed that most patients felt comfortable sharing information over text and felt the texts reminded them to take their insulin, check their sugar, and make healthy food choices. CONCLUSIONS:This implementation study showed MITI to have continued success after transitioning from an RCT program into real-world settings. MITI showed itself to be flexible and generalizable as it easily fits into a second site staffed by general medical clinic-registered nurses and remained acceptable to patients and staff who had high levels of engagement with the program.

Patients with complex chronic diseases usually must make multiple lifestyle changes to limit and manage their conditions. Numerous studies have shown that education alone is insufficient for engaging people in lifestyle behavior change, and that theory-based behavioral approaches also are necessary. However, even the most motivated individual may have difficulty with making lifestyle changes because of the information complexity associated with multiple behavior changes. The goal of the current Healthy Hearts and Kidneys study was to evaluate, different mobile health (mHealth)-delivered intervention approaches for engaging individuals with type 2 diabetes (T2D) and concurrent chronic kidney disease (CKD) in behavior changes. Participants were randomized to 1 of 4 groups, receiving: (1) a behavioral counseling, (2) technology-based self-monitoring to reduce information complexity, (3) combined behavioral counseling and technology-based self-monitoring, or (4) baseline advice. We will determine the impact of randomization assignment on weight loss success and 24-hour urinary excretion of sodium and phosphorus. With this report we describe the study design, methods, and approaches used to assure information security for this ongoing clinical trial. Clinical Trials.gov Identifier: NCT02276742.

Introduction/UNASSIGNED:Given mounting calls to disclose biomarker test results to research participants, we explored factors underlying decisions by patients with mild cognitive impairment to receive amyloid imaging results. Methods/UNASSIGNED:Prospective, qualitative interviews were conducted with 59 participants (30 = mild cognitive impairment patients, 29 = care partners) from the scan arm of a randomized controlled trial on the effects of amyloid PET results disclosure in an Alzheimer Disease Research Center setting. Results/UNASSIGNED:Sixty-three percent of the participants were female, with an average age of 72.9 years, and most had greater than a high school level of education (80%). Primary motivations included: (1) better understanding one's mild cognitive impairment etiology and prognosis to plan ahead, and (2) learning one's brain amyloid status for knowledge's sake, regardless of whether the information is actionable. Most participants demonstrated an adequate understanding of the scan's limitations, yet instances of characterizing amyloid PET as a definitive test for Alzheimer's disease occurred. Mention of potential drawbacks, such as negative psychological outcomes, was minimal, even among care partners. Discussion/UNASSIGNED:Findings demonstrate a risk of disproportionate focus on possible benefits of testing among amyloid scan candidates and suggest a need to clearly emphasize the limitations of amyloid PET when counseling cognitively impaired patients and their families before testing. Future research should examine whether minimizing drawbacks at the pre-imaging stage has adverse consequences on results disclosure.

Persons receiving treatment for weight loss often demonstrate heterogeneity in lifestyle behaviors and health outcomes over time. Traditional repeated measures approaches focus on the estimation and testing of an average temporal pattern, ignoring the interindividual variability about the trajectory. An alternate person-centered approach, group-based trajectory modeling, can be used to identify distinct latent classes of individuals following similar trajectories of behavior or outcome change as a function of age or time and can be expanded to include time-invariant and time-dependent covariates and outcomes. Another latent class method, growth mixture modeling, builds on group-based trajectory modeling to investigate heterogeneity within the distinct trajectory classes. In this applied methodologic study, group-based trajectory modeling for analyzing changes in behaviors or outcomes is described and contrasted with growth mixture modeling. An illustration of group-based trajectory modeling is provided using calorie intake data from a single-group, single-center prospective study for weight loss in adults who are either overweight or obese.

Self-monitoring of lung function, vital signs, and symptoms is crucial for lung transplant recipients (LTRs) to ensure early detection of complications and prompt intervention. This study sought to identify patterns and correlates of adherence to self-monitoring among LTRs over the first 12 months post-discharge from transplant. This study analyzed existing data from the usual care arm participants of a randomized clinical trial who tracked self-monitoring activities using paper-and-pencil logs. Adherence was calculated as the percent of days LTRs recorded any self-monitoring data per interval: hospital discharge-2 months, 3-6 months, and 7-12 months. The sample (N=91) was mostly white (87.9%), male (61.5%), with a mean age of 57.2±13.8 years. Group-based trajectory analyses revealed two groups: (i) moderately adherent with slow decline (n=29, 31.9%) and (ii) persistently nonadherent (n=62, 68.1%). Multivariate binary logistic regression revealed the following baseline factors increased the risk in the persistently nonadherent group: female (P=.035), higher anxiety (P=.008), and weaker sense of personal control over health (P=.005). Poorer physical health over 12 months were associated with increased risk in the persistently nonadherent group (P=.004). This study highlighted several modifiable factors for future interventions to target, including reducing post-transplant anxiety, and strengthening sense of personal control over health in LTRs.