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Evidence is lacking regarding effective and sustainable weight loss approaches for use in the primary care setting. We conducted a 12-week randomized controlled trial to evaluate the short-term efficacy of a web-based weight loss intervention among 101 primary care patients with obesity and hypertension. Patients had access to a comprehensive website that used a moderate-intensity weight loss approach designed specifically for web-based implementation. Patients also participated in four (two in-person and two telephonic) counseling sessions with a health coach. Intent-to-treat analysis showed greater weight loss at 3 months (−2.56 kg; 95% CI −3.60, −1.53) among intervention participants (−2.28 ± 3.21 kg), relative to usual care (0.28 ± 1.87 kg). Similar findings were observed among intervention completers (−3.05 kg; 95% CI −4.24, −1.85). High rates of participant retention (84%) and website utilization were observed, with the greatest weight loss found among those with a high frequency of website logins (quartile 4 vs. 1: −4.16 kg; 95% CI −1.47, −6.84). The intervention's approach promoted moderate weight loss at 12 weeks, though greater weight loss was observed among those with higher levels of website utilization. Efficacious web-based weight loss interventions can be successfully offered in the primary care setting.

Introduction: Obesity treatment is less successful for socioeconomically disadvantaged populations, particularly when delivered in primary care. Digital health strategies can extend the reach of clinical obesity treatments to care settings serving patients at highest risk. Methods: Track was an effectiveness RCT of a 12-month digital weight-loss intervention, embedded within a community health center system. Participants were 351 adult patients (aged 21–65 years) with obesity and hypertension, diabetes, and hyperlipidemia. Patients were randomized to usual care (n = 175) or an intervention (n = 176) comprising app-based self-monitoring of behavior change goals with tailored feedback, a smart scale, dietitian-delivered counseling calls, and clinician counseling informed by app-generated recommendations, delivered via electronic health record. The primary outcome was 12-month weight change. Randomization began on June 18, 2013, final assessments were completed on September 10, 2015. Data analysis was conducted in 2016 and 2017. The trial retained 92% of usual care and 96% of intervention participants at 12 months. Results: The Track intervention produced larger weight losses relative to usual care at 6 months (net effect: −4.4 kg, 95% CI = −5.5, −3.3, p < 0.001) and 12 months (net effect: −3.8 kg, 95% CI = −5.0, −2.5, p < 0.001). Intervention participants were more likely to lose ≥ 5% of their baseline weight at 6 months (43% vs 6%, p < 0.001) and 12 months (40% vs 17%, p < 0.001). Intervention participants completing ≥ 80% of expected self-monitoring episodes (−3.5 kg); counseling calls (−3.0 kg); or self-weighing days (−4.4 kg) lost significantly more weight than less engaged intervention participants (all p < 0.01). Conclusions: A digital obesity treatment, integrated with health system resources, can produce clinically meaningful weight-loss outcomes among socioeconomically disadvantaged primary care patients with elevated cardiovascular disease risk. Trial registration: This study is registered at www.clinicaltrials.gov, NCT01827800.

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BackgroundDespite its health benefits, physical inactivity is pervasive, particularly among those living in lower-income urban communities. In such settings, neighborhood safety may impact willingness to be regularly physically active. We examined the association of perceived neighborhood safety with pedometer-determined physical activity and physical activity self-efficacy.Methods and FindingsParticipants were 1,180 predominantly racial/ethnic minority adults recruited from 12 urban low-income housing complexes in metropolitan Boston. Participants completed a 5-d pedometer data-collection protocol and self-reported their perceptions of neighborhood safety and self-efficacy (i.e., confidence in the ability to be physically active). Gender-stratified bivariate and multivariable random effects models were estimated to account for within-site clustering. Most participants reported feeling safe during the day, while just over one-third (36%) felt safe at night. We found no association between daytime safety reports and physical activity among both men and women. There was also no association between night-time safety reports and physical activity among men (p = 0.23) but women who reported feeling unsafe (versus safe) at night showed significantly fewer steps per day (4,302 versus 5,178, p = 0.01). Perceiving one's neighborhood as unsafe during the day was associated with significantly lower odds of having high physical activity self-efficacy among both men (OR 0.40, p = 0.01) and women (OR 0.68, p = 0.02).ConclusionsResiding in a neighborhood that is perceived to be unsafe at night is a barrier to regular physical activity among individuals, especially women, living in urban low-income housing. Feeling unsafe may also diminish confidence in the ability to be more physically active. Both of these factors may limit the effectiveness of physical activity promotion strategies delivered in similar settings.

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Background: This report examines the outcome data for Project PREVENT, a two-site randomized control trial designed to reduce behavioral risk factors for colorectal cancer among individuals who have been diagnosed with adenomatous colon polyps. Methods: The study sample included 1,247 patients with recent diagnosis of adenomatous colorectal polyps. Within 4 weeks following the polypectomy, participants completed a baseline survey by telephone, and were randomized to either Usual Care (UC) or the PREVENT intervention, which was designed to target multiple risk factors. The intervention consisted of a telephone-delivered intervention plus tailored materials, and focused on the six primary behavioral risk factors for colorectal cancer, including red meat consumption, fruit and vegetable intake, multivitamin intake, alcohol, smoking, and physical inactivity.