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Background Auto-brewery syndrome (ABS), also known as Gut Fermentation Syndrome and Endogenous Ethanol Fermentation, is afflicting people worldwide, but little is known about ABS patients’ demographics, health history, lifestyle factors, and diet. Method We conducted a broad-based case–control survey study on 52 patients known to have a diagnosis of ABS and their household members. The research compares the symptomatic group (N = 28) to the asymptomatic group (N = 18) regarding lifestyle and health, diet, and medical history. Results With a response rate of 88% and using rank-sum tests, the data demonstrate that patients with ABS have significant differences compared to people without ABS in lower quality bowel movements ( P = .048), more frequent bowel movements ( P = .038), more reports of malodorous breath ( P = .0001), and self-classify as having poorer health ( P = .009). Furthermore, participants with ABS consume more water ( P = .038), consume less tea and coffee ( P = .033), eat fewer dairy products ( P = .0185), eat less candy ( P = .032), eat out less and rely on food prepared at home ( P = .043), have more aversion to starch ( P = .008), and have more food sensitivities ( P = .043) than the group without ABS. The ABS group also reports more diarrhea ( P = .048), higher amounts of yeast in their gastrointestinal tract ( P = .015), and using acne medication for a longer time ( P = .037) than the control group. Conclusion Patients with ABS have significant differences in their lifestyle and health, diet, and medical history compared to non-ABS participants and these differences warrant further research.

Background Stress and obesity are interrelated and common among low-income adults. Mind–body interventions have been shown to reduce psychological distress and have been incorporated into many weight loss interventions. However, few of these programs have incorporated a telephone coaching component. Objective We designed and piloted a novel weight loss telephone coaching intervention for this population and examined its effectiveness on weight loss and improvements in health behaviors in obese community health center patients. Methods This was a 6-month, single-arm, prospective, pre–post pilot study. The study took place at a community health center near Boston, Massachusetts. Participants were 27 overweight and obese community health center patients. The intervention consisted of one in-person intake with the registered dietitian, trained in mind–body approaches, and approximately 1 phone coaching session every 2 weeks for 6 consecutive months. Anthropometric data consisted of weight, body mass index (BMI), and blood pressure. Questionnaires consisted of the Perceived Stress Scale-10 item, the CIGNA Healthy Eating Survey, Section H: Behavioral Eating, a physical activity questionnaire, and a nutritional habits questionnaire. We used paired samples t tests to assess pre–post changes in weight, BMI, blood pressure, perceived stress, behavioral eating, and physical activity. We also conducted semistructured exit interviews to learn about participants’ experiences in this program. Results There was a trend toward weight reduction ( P

Purpose: This descriptive study aims to describe the levels of mobility in community-dwelling older Koreans with chronic illnesses, and to examine the associations of their mobility with sleep patterns, physical activity and physical symptoms including fatigue and pain. Methods: The participants were a total of 384 community-dwelling older adults recruited from three senior centers in Seoul, Korea. Measures included mobility assessed using 6-minute walk test (6MWT), physical activity behavior, sleep profiles, fatigue and pain. Data were collected from July to December 2012. Results: The mean 6MWT distance was 212.68 meters. Over 90% of the study participants (n = 373) were classified as having impaired mobility using 400 meters as the cutoff point diagnostic criteria of normal mobility in 6MWT. The 6MWT distance was 246.68 meters for participants in their 60s, 212.32 meters for those in their 70s, and 175.54 meters for those in their 80s. Significant predictors of mobility included younger age, taking mediation, regular physical activity, female gender, higher income, higher fatigue and better perception on sleep duration, which explained 18% of the total variance of mobility. Conclusions: A high-risk group for mobility limitation includes low income, sedentary older men who are at risk for increased fatigue and sleep deficit. Further research should incorporate other psychological and lifestyle factors such as depression, smoking, drinking behavior, and/or obesity into the prediction model of mobility to generate specific intervention strategies for mobility enhancement recommendations for older adults.