Associations between sleep health and obesity and weight change in adults: The Daily24 Multisite Cohort Study.

OBJECTIVES: To examine cross-sectional and longitudinal associations of individual sleep domains and multidimensional sleep health with current overweight or obesity and 5-year weight change in adults. METHODS: We estimated sleep regularity, quality, timing, onset latency, sleep interruptions, duration, and napping using validated questionnaires. We calculated multidimensional sleep health using a composite score (total number of "good" sleep health indicators) and sleep phenotypes derived from latent class analysis. Logistic regression was used to examine associations between sleep and overweight or obesity. Multinomial regression was used to examine associations between sleep and weight change (gain, loss, or maintenance) over a median of 1.66 years. RESULTS: The sample included 1016 participants with a median age of 52 (IQR = 37-65), who primarily identified as female (78%), White (79%), and college-educated (74%). We identified 3 phenotypes: good, moderate, and poor sleep. More regularity of sleep, sleep quality, and shorter sleep onset latency were associated with 37%, 38%, and 45% lower odds of overweight or obesity, respectively. The addition of each good sleep health dimension was associated with 16% lower adjusted odds of having overweight or obesity. The adjusted odds of overweight or obesity were similar between sleep phenotypes. Sleep, individual or multidimensional sleep health, was not associated with weight change. CONCLUSIONS: Multidimensional sleep health showed cross-sectional, but not longitudinal, associations with overweight or obesity. Future research should advance our understanding of how to assess multidimensional sleep health to understand the relationship between all aspects of sleep health and weight over time.

Association of Eating and Sleeping Intervals With Weight Change Over Time: The Daily24 Cohort.

Background We aim to evaluate the association between meal intervals and weight trajectory among adults from a clinical cohort. Methods and Results This is a multisite prospective cohort study of adults recruited from 3 health systems. Over the 6-month study period, 547 participants downloaded and used a mobile application to record the timing of meals and sleep for at least 1 day. We obtained information on weight and comorbidities at each outpatient visit from electronic health records for up to 10 years before until 10 months after baseline. We used mixed linear regression to model weight trajectories. Mean age was 51.1 (SD 15.0) years, and body mass index was 30.8 (SD 7.8) kg/m2; 77.9% were women, and 77.5% reported White race. Mean interval from first to last meal was 11.5 (2.3) hours and was not associated with weight change. The number of meals per day was positively associated with weight change. The average difference in annual weight change (95% CI) associated with an increase of 1 daily meal was 0.28 kg (0.02-0.53). Conclusions Number of daily meals was positively associated with weight change over 6 years. Our findings did not support the use of time-restricted eating as a strategy for long-term weight loss in a general medical population.

Association between health care access and food insecurity among lower-income older adults with multiple chronic conditions in Washington State, USA.

OBJECTIVE: Lower-income older adults with multiple chronic conditions (MCC) are highly vulnerable to food insecurity. However, few studies have considered how health care access is related to food insecurity among older adults with MCC. The aims of this study were to examine associations between MCC and food insecurity, and, among older adults with MCC, between health care access and food insecurity. DESIGN: Cross-sectional study data from the 2019 Behavioral Risk Factor Surveillance System survey. SETTING: Washington State, USA. PARTICIPANTS: Lower-income adults, aged 50 years or older (n 2118). MCC was defined as having ≥ 2 of 11 possible conditions. Health care access comprised three variables (unable to afford seeing the doctor, no health care coverage and not having a primary care provider (PCP)). Food insecurity was defined as buying food that did not last and not having money to get more. RESULTS: The overall prevalence of food insecurity was 26·0 % and was 1·50 times greater (95 % CI 1·16, 1·95) among participants with MCC compared to those without MCC. Among those with MCC (n 1580), inability to afford seeing a doctor was associated with food insecurity (prevalence ratio (PR) 1·83; 95 % CI 1·46, 2·28), but not having health insurance (PR 1·49; 95 % CI 0·98, 2·24) and not having a PCP (PR 1·10; 95 % CI 0·77, 1·57) were not. CONCLUSIONS: Inability to afford healthcare is related to food insecurity among older adults with MCC. Future work should focus on collecting longitudinal data that can clarify the temporal relationship between MCC and food insecurity.

Electronic Health Record-Based Recruitment and Retention and Mobile Health App Usage: Multisite Cohort Study.

BACKGROUND: To address the obesity epidemic, there is a need for novel paradigms, including those that address the timing of eating and sleep in relation to circadian rhythms. Electronic health records (EHRs) are an efficient way to identify potentially eligible participants for health research studies. Mobile health (mHealth) apps offer available and convenient data collection of health behaviors, such as timing of eating and sleep. OBJECTIVE: The aim of this descriptive analysis was to report on recruitment, retention, and app use from a 6-month cohort study using a mobile app called Daily24. METHODS: Using an EHR query, adult patients from three health care systems in the PaTH clinical research network were identified as potentially eligible, invited electronically to participate, and instructed to download and use the Daily24 mobile app, which focuses on eating and sleep timing. Online surveys were completed at baseline and 4 months. We described app use and identified predictors of app use, defined as 1 or more days of use, versus nonuse and usage categories (ie, immediate, consistent, and sustained) using multivariate regression analyses. RESULTS: Of 70,661 patients who were sent research invitations, 1021 (1.44%) completed electronic consent forms and online baseline surveys; 4 withdrew, leaving a total of 1017 participants in the analytic sample. A total of 53.79% (n=547) of the participants were app users and, of those, 75.3% (n=412), 50.1% (n=274), and 25.4% (n=139) were immediate, consistent, and sustained users, respectively. Median app use was 28 (IQR 7-75) days over 6 months. Younger age, White race, higher educational level, higher income, having no children younger than 18 years, and having used 1 to 5 health apps significantly predicted app use (vs nonuse) in adjusted models. Older age and lower BMI predicted early, consistent, and sustained use. About half (532/1017, 52.31%) of the participants completed the 4-month online surveys. A total of 33.5% (183/547), 29.3% (157/536), and 27.1% (143/527) of app users were still using the app for at least 2 days per month during months 4, 5, and 6 of the study, respectively. CONCLUSIONS: EHR recruitment offers an efficient (ie, high reach, low touch, and minimal participant burden) approach to recruiting participants from health care settings into mHealth research. Efforts to recruit and retain less engaged subgroups are needed to collect more generalizable data. Additionally, future app iterations should include more evidence-based features to increase participant use.

Patient engagement strategies for adults with chronic conditions: an evidence map.

BACKGROUND: Patient and family engagement (PFE) has been defined as a partnership between patients, families, and health care providers to achieve positive health care outcomes. There is evidence that PFE is critical to improving outcomes. We sought to systematically identify and map the evidence on PFE strategies for adults with chronic conditions and identify areas needing more research. METHODS: We searched PubMed, CINAHL, EMBASE, and Cochrane, January 2015 to September 2021 for systematic reviews on strategies for engaging patients with chronic conditions and their caregivers. From each review, we abstracted search dates, number and type of studies, populations, interventions, and outcomes. PFE strategies were categorized into direct patient care, health system, and community-policy level strategies. We found few systematic reviews on strategies at the health system, and none at the community-policy level. In view of this, we also searched for original studies that focused on PFE strategies at those two levels and reviewed the PFE strategies used and study findings. RESULTS: We found 131 reviews of direct patient care strategies, 5 reviews of health system strategies, and no reviews of community-policy strategies. Four original studies addressed PFE at the health system or community-policy levels. Most direct patient care reviews focused on self-management support (SMS) (n = 85) and shared decision-making (SDM) (n = 43). Forty-nine reviews reported positive effects, 35 reported potential benefits, 37 reported unclear benefits, and 4 reported no benefits. Health system level strategies mainly involved patients and caregivers serving on advisory councils. PFE strategies with the strongest evidence focused on SMS particularly for patients with diabetes. Many SDM reviews reported potential benefits especially for patients with cancer. DISCUSSION: Much more evidence exists on the effects of direct patient care strategies on PFE than on the effects of health system or community-policy strategies. Most reviews indicated that direct patient care strategies had positive effects or potential benefits. A limitation of this evidence map is that due to its focus on reviews, which were plentiful, it did not capture details of individual interventions. Nevertheless, this evidence map should help to focus attention on gaps that require more research in efforts to improve PFE.

Night eating, weight, and health behaviors in adults participating in the Daily24 study.

BACKGROUND: Night eating syndrome (NES) is associated with adverse health outcomes. This study evaluated the relationship between night eating severity, weight, and health behaviors. METHODS: Participants (N = 1017; 77.6% female, mean Body Mass Index (BMI) = 30.5, SD = 7.8 kg/m2, age = 51.1, SD = 15.0 years) were recruited from three health systems. Participants completed the Night Eating Questionnaire (NEQ) and questionnaires assessing sleep, chronotype, physical activity, diet, weight, and napping. RESULTS: In the overall sample, higher NEQ scores were associated with higher BMI (p < .001) and consumption of sugar-sweetened beverages (p < .001), as well as lower fruit/vegetable consumption (p = .001). Higher NEQ scores were associated with increased odds of having overweight/obesity (p < .001), eating fast food (p < .001), moderate-vigorous physical activity (p = .005), and smoking (p = .004). Participants who exceeded the screening threshold for NES (n = 48, 4.7%) reported elevated BMI (p = .014), an increased likelihood of overweight/obesity (p = .004), greater sugar-sweetened beverages consumption (p < .001), napping less than twice per week (p = .029), shorter sleep duration (p = .012), and a later chronotype (M = 4:55, SD = 2:45). CONCLUSION: Night eating severity was associated with obesity and intake of fast food and sugar-sweetened beverages. Interventions to address night eating and associated behaviors may enhance the efficacy of weight management interventions and promote engagement in positive health behaviors.

Development of a Mobile App for Ecological Momentary Assessment of Circadian Data: Design Considerations and Usability Testing.

BACKGROUND: Collecting data on daily habits across a population of individuals is challenging. Mobile-based circadian ecological momentary assessment (cEMA) is a powerful frame for observing the impact of daily living on long-term health. OBJECTIVE: In this paper, we (1) describe the design, testing, and rationale for specifications of a mobile-based cEMA app to collect timing of eating and sleeping data and (2) compare cEMA and survey data collected as part of a 6-month observational cohort study. The ultimate goal of this paper is to summarize our experience and lessons learned with the Daily24 mobile app and to highlight the pros and cons of this data collection modality. METHODS: Design specifications for the Daily24 app were drafted by the study team based on the research questions and target audience for the cohort study. The associated backend was optimized to provide real-time data to the study team for participant monitoring and engagement. An external 8-member advisory board was consulted throughout the development process, and additional test users recruited as part of a qualitative study provided feedback through in-depth interviews. RESULTS: After ≥4 days of at-home use, 37 qualitative study participants provided feedback on the app. The app generally received positive feedback from test users for being fast and easy to use. Test users identified several bugs and areas where modifications were necessary to in-app text and instructions and also provided feedback on the engagement strategy. Data collected through the mobile app captured more variability in eating windows than data collected through a one-time survey, though at a significant cost. CONCLUSIONS: Researchers should consider the potential uses of a mobile app beyond the initial data collection when deciding whether the time and monetary expenditure are advisable for their situation and goals.

Patient and family engagement strategies for children and adolescents with chronic diseases: A review of systematic reviews.

OBJECTIVE: Patient and family engagement is important for family-centered care, particularly for children and adolescents with chronic disease. We aimed to 1) identify available evidence from systematic reviews on engagement strategies used to help children, adolescents, and their caregivers manage chronic conditions, and 2) identify gaps in the literature. METHODS: We searched PubMed and CINAHL from January 2015 to January 2020 for systematic reviews on patient and family engagement strategies in the pediatrics population (<18 years). Strategies were categorized by direct patient care, health system, and community policy levels. We excluded reviews if interventions were unidirectional or without comparison. RESULTS: We identified 25 systematic reviews. Twenty-two evaluated direct patient care, with 14 (279 unique studies) exclusively in pediatrics and 8 (24 unique studies) that included pediatric results with adults. Three reviews (9 unique studies) evaluated health system strategies. Direct patient care reviews focused on self-management support (n = 16) and shared decisionmaking (n = 6). Asthma was the most frequently evaluated condition (n = 14). CONCLUSIONS AND PRACTICE IMPLICATIONS: Engagement strategies for children and adolescents with chronic disease are focused on direct patient care, particularly for asthma. More research is needed to address engagement for broader populations, expanded outcomes, and at health system and community levels.

What influences the "when" of eating and sleeping?A qualitative interview study.

Timing of eating relative to sleep and endogenous circadian rhythm impacts weight and cardiometabolic health. We used qualitative methods to explore what influences the "when" of eating and sleeping. We conducted 37 one-on-one semi-structured interviews among participants with a body mass index (BMI) ≥ 25 kg/m2 recruited from three internal medicine clinics affiliated with an urban academic hospital. Participants (70.3% Female; 51.4% White; Age range: 21-83 years old) completed measures of social jetlag, physical activity, eating habits, and mobile application use and participated in interviews following a guide developed by the study team. Responses were recorded, transcribed and coded sequentially by two trained researchers using editing-style analysis to identify themes. We identified two main themes, each with subthemes: 1) influences on the "when" of eating and sleeping, with subthemes including social jetlag and being overscheduled, and 2) contextualizing beliefs and perceptions about the "when" of eating and sleeping, with subthemes including perceived recommendations for timing of eating and sleeping, and alignment of behaviors with perceived recommendations. Many participants noted being more flexible in their eating and sleeping times on work-free vs work days. The themes this study identified should be considered when designing interventions that influence the timing of eating and sleeping for weight management.