Objective To identify the problems experienced by hemodialysis (HD) patients in attempting to follow the HD diet, and their relation to energy and nutrient intakes. Design Cross-sectional analysis of baseline data from the BalanceWise Study. Setting Community-dwelling adults recruited from outpatient HD centers. Subjects After excluding participants with incomplete dietary analyses (n = 50), 140 community-dwelling African American and white (40/60%) men and women (52/48%) on chronic intermittent HD for at least three months (median three years) were included. Intervention Participant responses, on a 5-point Likert scale ranging from “not at all a problem” to “a very important problem for me”, to 34 questions pertaining to potential barriers to following the HD diet in the previous two months were classified as either a problem (1) or not a problem (2–5). Main Outcome Measure Energy and nutrient intakes determined using the Nutrition Data System for Research® based on three, non-consecutive, unscheduled, two-pass 24-hour dietary recalls collected on one dialysis and one non-dialysis weekday, and one non-dialysis weekend day. Results More than half of participants reported having problems related to specific behavioral factors (e.g., feeling deprived), technical difficulties (e.g., tracking nutrients) and physical condition (e.g., appetite), but issues of time and food preparation, and behavioral factors tended to be most deterministic of reported dietary intakes. Longer duration of HD was associated with lower intakes of protein, potassium, and phosphorus (p <0.05). Conclusion Registered dietitian nutritionists should consider issues of time and food preparation, and behavioral factors in their nutrition assessment of HD patients, and should continually monitor HD patients for changes in protein intake that may occur over time.

Dietary phosphorus restriction is recommended to help control hyperphosphatemia in hemodialysis (HD) patients, but many high-phosphorus foods are important sources of protein. In this review, we examine whether restricting dietary phosphorus compromises protein status in HD patients. Although dietary phosphorus and protein are highly correlated, phosphorus intakes can range up to 600 mg/day for a given energy and protein intake level. Further, the collinearity of phosphorus and protein may be biased because the phosphorus burden of food depends on: (1) the presence of phosphate additives; (2) food preparation method; and (3) bioavailability of phosphorus; which are often unaccounted for in nutrition assessments. Ultimately, we argue that clinically relevant reductions in phosphorus intake can be made without limiting protein intake by avoiding phosphate additives in processed foods, using wet cooking methods such as boiling, and if needed, substituting high-phosphorus foods for nutritionally-equivalent foods that are lower in bioavailable phosphorus.

ImportanceInterindividual variability in postprandial glycemic response (PPGR) to the same foods may explain why low glycemic index or load and low-carbohydrate diet interventions have mixed weight loss outcomes. A precision nutrition approach that estimates personalized PPGR to specific foods may be more efficacious for weight loss.ObjectiveTo compare a standardized low-fat vs a personalized diet regarding percentage of weight loss in adults with abnormal glucose metabolism and obesity.Design, Setting, and ParticipantsThe Personal Diet Study was a single-center, population-based, 6-month randomized clinical trial with measurements at baseline (0 months) and 3 and 6 months conducted from February 12, 2018, to October 28, 2021. A total of 269 adults aged 18 to 80 years with a body mass index (calculated as weight in kilograms divided by height in meters squared) ranging from 27 to 50 and a hemoglobin A1c level ranging from 5.7% to 8.0% were recruited. Individuals were excluded if receiving medications other than metformin or with evidence of kidney disease, assessed as an estimated glomerular filtration rate of less than 60 mL/min/1.73 m2 using the Chronic Kidney Disease Epidemiology Collaboration equation, to avoid recruiting patients with advanced type 2 diabetes.InterventionsParticipants were randomized to either a low-fat diet (&amp;lt;25% of energy intake; standardized group) or a personalized diet that estimates PPGR to foods using a machine learning algorithm (personalized group). Participants in both groups received a total of 14 behavioral counseling sessions and self-monitored dietary intake. In addition, the participants in the personalized group received color-coded meal scores on estimated PPGR delivered via a mobile app.Main Outcomes and MeasuresThe primary outcome was the percentage of weight loss from baseline to 6 months. Secondary outcomes included changes in body composition (fat mass, fat-free mass, and percentage of body weight), resting energy expenditure, and adaptive thermogenesis. Data were collected at baseline and 3 and 6 months. Analysis was based on intention to treat using linear mixed modeling.ResultsOf a total of 204 adults randomized, 199 (102 in the personalized group vs 97 in the standardized group) contributed data (mean [SD] age, 58 [11] years; 133 women [66.8%]; mean [SD] body mass index, 33.9 [4.8]). Weight change at 6 months was −4.31% (95% CI, −5.37% to −3.24%) for the standardized group and −3.26% (95% CI, −4.25% to −2.26%) for the personalized group, which was not significantly different (difference between groups, 1.05% [95% CI, −0.40% to 2.50%]; P = .16). There were no between-group differences in body composition and adaptive thermogenesis; however, the change in resting energy expenditure was significantly greater in the standardized group from 0 to 6 months (difference between groups, 92.3 [95% CI, 0.9-183.8] kcal/d; P = .05).Conclusions and RelevanceA personalized diet targeting a reduction in PPGR did not result in greater weight loss compared with a low-fat diet at 6 months. Future studies should assess methods of increasing dietary self-monitoring adherence and intervention exposure.Trial RegistrationClinicalTrials.gov Identifier: NCT03336411

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.

Diet is a key determinant of several common and serious disease complications in hemodialysis (HD) patients. The recommended balance and variety of foods in the HD diet is designed to limit high potassium and phosphorus foods while maintaining protein adequacy. In this report, we examine the potassium, phosphorus, and protein content of foods, and identify critical challenges, and potential pitfalls when translating nutrient prescriptions into dietary guidelines. Our findings highlight the importance of individualized counseling based on a comprehensive dietary assessment by trained diet professionals, namely renal dietitians, for managing diet-related complications in HD patients.