Despite recent advances in the treatment of obesity, lifestyle medicine remains foundational to the treatment of individuals with obesity, regardless of the modality chosen by the patient with the guidance of the clinician they are working with, including in conjunction with, as appropriate, anti-obesity medications and metabolic surgery. Lifestyle medicine involves the use of diet, exercise, sleep, stress, and other lifestyle modalities in the treatment of disease. Clinicians and health systems should, after a patient-centered discussion with the patient, do their best to ensure access to lifestyle treatments. Gold standard guidelines recommend intensive, multicomponent lifestyle change programs for obesity treatments with evidence-based diet and exercise counseling and established, theoretically driven behavior change components. Clinicians treating obesity should be aware of their own biases, make efforts to reduce stigmatizing experiences in their practice, and address weight stigma in their treatment plans as needed. A variety of dietary patterns can be used to support patients with obesity, and clinicians should make evidence-based but patient-centered recommendations that aim to maximize adherence. Diet and exercise can play an important role in reducing the side effects of treatment and optimizing outcomes in weight loss, attenuating the effects of metabolic adaptation, and weight maintenance. Exercise should be increased gradually to reduce injury with a goal of 200–300 min (approximately 3.3–5 h) of moderate to vigorous intensity exercise per week to maximize weight maintenance effects with exercise prescriptions customized to patients risks. A variety of practice models can be leveraged along with the use of an interdisciplinary team to provide lifestyle medicine care for those with obesity.

We assessed the test validity of the Apple Watch series 6 measure of heart rate variability (HRV) by comparing it with the reference measure assessed via a Biopac 3-lead electrocardiogram (ECG). We recruited 78 healthy adults (aged 20–75 years). HRV was measured using an in-lab protocol while resting, talking, watching a movie, before walking, and after walking. We conducted a synchronized countdown for each condition to guarantee that the recordings would be aligned between the two devices by using event markers in the Biopac at the exact time that the Apple Watch Breathe app began and ended. We assessed test validity using the Bland–Altman method, and both precision and accuracy were estimated using Lin’s concordance correlation coefficient. The highest level of agreement and concordance between devices occurred during rest. We observed near-perfect agreement for R-R intervals and beats per minute (BPM) measures, with mean absolute percentage errors (MAPE) of 1.15% during resting conditions. We observed moderate levels of agreement and concordance for N-N intervals at rest with a MAPE of 31.31% during resting conditions. The Apple Watch provides a high level of validity for measuring R-R intervals and BPM in healthy adults. Further research is needed to determine if HRV measures with the Apple Watch offer a significant opportunity for the surveillance of CVD risk.

Background: Falls and fractures are the leading cause of unintentional injury among older adults, resulting in increased mortality and morbidity, as well as reduced physical function and quality of life. In-person exercise programs aimed at improving strength, balance, and postural control have demonstrated benefits for physical function, quality of life, and fall risk reduction among older adults. Technology-driven approaches can further enhance the accessibility of exercise programs. In particular, digitally delivered programs offer the opportunity to balance risks and benefits while promoting engagement and potentially improving physical function. Objective: The overall aim of this review was to summarize the growing body of research on the efficacy, usability, and safety of these programs in older adults. Methods: MEDLINE via PubMed, the Cochrane Controlled Register of Trials (CENTRAL), and Embase databases were searched for this review. The initial search was conducted in November 2022 and updated in July 2024. Randomized controlled trials, nonrandomized trials, and single-arm pilot studies of at least 6 weeks’ duration reporting digitally delivered exercise for presumptively healthy older adults, taught in real-time (not prerecorded) by a qualified instructor, were included. Interventions targeting specific clinical subpopulations (eg, cardiac rehabilitation, Parkinson disease, chronic obstructive pulmonary disease) were excluded, although common age-related conditions such as hypertension, diabetes, and osteoporosis were included. The review was preregistered via INPLASY (registration number 3773). Results: A total of 4242 studies were screened by title and abstract, with 76 progressing to full-text review. Of these, 23 (30%) met all inclusion criteria, comprising 6 pilot single-arm studies, 5 nonrandomized trials, and 12 randomized trials. Interventions ranged from 6 to 24 weeks, with most lasting 8-12 weeks, and class participation typically occurred 2-3 days per week. Class sizes ranged from as few as 4 to more than 30 participants. Instructor experience varied and included licensed professionals, such as physical therapists, kinesiologists, and certified trainers, as well as laypeople specifically trained for the intervention. A total of 18 out of 23 (78%) studies reported physical outcomes, including balance, strength, and functional measures. Fourteen of these studies reported clinically meaningful improvements following the intervention, most commonly in strength and balance, measured by the 30-second chair stand test and the timed up and go; 20 studies (87%) reported 1 or more observations regarding safety or program usability. Among the studies that provided data on adverse events, most were conducted without injuries or reported only minor injuries. More than 60% of the authors (15/23, 65%) noted in their conclusion statements that participant acceptance of the digital delivery format was high. Conclusions: Overall, these findings demonstrate partial effectiveness in improving physical function related to fall prevention among older adults. Additionally, high attendance, participant enjoyment, and safety highlight the utility of digitally delivered exercise programs for older adults taught in real time. Trial Registration: International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY) INPLASY202280097; https://inplasy.com/inplasy-2022-8-0097/

Background: The Centers for Disease Control and Prevention (CDC) has developed an evidenced based clinical screening tool, Stopping Elderly Accidents, Deaths & Injuries (STEADI) but penetration into routine clinical practice has been slow. To increase screening for falls and fall risk in an internal medicine primary care practice, a patient-centered screening program was integrated into a busy academic clinic. Methods: Over a three month period, Patients were invited to self-screen via a large poster in the waiting room, and complete a STEADI Staying Independent questionnaire, and discuss findings with their healthcare provider. Fall Prevention Booklets were made readily available in clinic exam rooms. Questionnaires and fall prevention booklets, were uniquely numbered, and Epic Slicer-Dicer reports were utilized to evaluate falls screening-related ICD-10 codes determined a priori. Generalized linear modeling calculated difference-in-difference compared with other clinics without this program for rates of coding for fall-related diagnosis codes. Results: In three months, 255 questionnaires were taken; only 5 (2%) were returned for later review. 110 booklets were disseminated from clinic exam rooms. The absolute difference-in-difference in ICD-10 coding was 0.7% compared to other clinics in the same practice, and year before. Generalized linear modeling showed a 4.7% increased impact in screening-related ICD-10 codes, which was statistically significant (P = < .0001) without reported disruption to clinical workflows. Conclusion: There are indicators that patient-centered selective screening at a busy academic practice may have resulted in an increase in falls-related ICD-10 coding. Clinical integration of this program was well received.

Background: Dietary supplement (DS) use is common and increasing among older adults, though much data available on use frequencies are from surveys and performed cross-sectionally. This paper sought to assess the frequency and pattern of dietary supplement use among older adults over time. Methods: A secondary analysis of data from the AAA LongROAD study, a longitudinal prospective cohort study of older adult drivers, using data from baseline and the first two years of follow up included a total of 2990 drivers aged 65–79 years recruited at five study sites across the US from July 2015 to March 2017. Participants underwent baseline and annual evaluations, which included a “brown bag” medication review. DS were identified and categorized according to type and key components. Prevalence and pattern of DS use over time and relationship to demographics were measured with frequency and Chi squared analyses. Results: 84% of participants took at least one dietary supplement during the 2-year study period, and 55% of participants continually reported use. DS accounted for approximately 30% of the total pharmacologic-pill burden in all years. Participants who were White non-Hispanic, female, 75–79 years of age at baseline, and on more non-supplement medications took significantly more dietary supplements (P < 0.05). Vitamin D, multivitamins, calcium, and omega-3 formulations were the most common supplements, with stable use over time. Use of individual herbal supplements and cannabis products was uncommon (< 1% participants per year). Conclusions: DS use among older adults is common and relatively stable over time and contributes to polypharmacy. In clinical settings, providers should consider the influence of DS formulations on polypharmacy, and the associated cost, risk of medication interactions, and effect on medication compliance.