Dietary Intakes of Patients with Alcohol Use Disorder During a 4-Week Protocol on an Inpatient Treatment Unit Found to Meet Dietary Reference Intakes for Macronutrients, but Have Variability in Energy Balance and Adequacy of Micronutrient Intake.

BACKGROUND: Despite literature supporting the importance of diet during rehabilitation, minimal research quantifies dietary intake during treatment for alcohol use disorder (AUD). OBJECTIVE: The aim was to quantify dietary intake and energy balance of patients with AUD during inpatient treatment. DESIGN: This was a secondary analysis of data from a 4-week observational protocol. Participants self-selected food from a room service menu. Dietary intake was recorded by patients and reviewed by nutrition staff. To quantify nutrient and food group intake, data were coded into Nutrition Data Systems for Research software, versions 2016 and 2017. Daily average intake was calculated for all dietary variables. PARTICIPANTS/SETTING: Participants (n = 22) were adults seeking treatment for AUD at the National Institutes of Health Clinical Center (Bethesda, MD) between September 2016 and September 2017 and who were enrolled in a study examining the microbiome during AUD rehabilitation. Four participants discontinued protocol participation before study week 4 and were not included in analyses examining change over time. MAIN OUTCOME MEASURES: Weight change, daily energy, and macronutrient and select micronutrient intakes were the main outcome measures included. STATISTICAL ANALYSES PERFORMED: Mean differences in intake and weight were assessed using nonparametric tests. RESULTS: Sixty-four percent of participants were male; mean ± SD age was 46.3 ± 13.0 years, mean ± SD body mass index (calculated as kg/m2) was 23.9 ± 2.5, and mean intake was 2,665 kcal/d (consisting of 45.9% carbohydrate, 34.9% fat, and 19.1% protein). Eighty percent or more of this sample met the Estimated Average Requirement for 10 of 16 micronutrients assessed. Male participants consumed more energy than estimated needs (P = .003) and gained a mean ± SD of 2.67 ± 1.84 kg (P = .006) when an outlier with weight loss and acute pancreatitis was removed from analysis. Female participants did not gain weight or consume more than estimated energy needs. CONCLUSIONS: Overall macronutrient intake was within recommended ranges, but intake of other dietary components and weight gain were variable, supporting the need for individualized nutrition care during AUD treatment.

Longitudinal gut microbiome changes in alcohol use disorder are influenced by abstinence and drinking quantity.

Many patients with alcohol use disorder (AUD) consume alcohol chronically and in large amounts that alter intestinal microbiota, damage the gastrointestinal tract, and thereby injure other organs via malabsorption and intestinal inflammation. We hypothesized that alcohol consumption and subsequent abstinence would change the gut microbiome in adults admitted to a treatment program. Stool and oral specimens, diet data, gastrointestinal assessment scores, anxiety, depression measures and drinking amounts were collected longitudinally for up to 4 weeks in 22 newly abstinent inpatients with AUD who were dichotomized as less heavy drinkers (LHD, <10 drinks/d) and very heavy drinkers (VHD, 10 or more drinks/d). Next-generation 16 S rRNA gene sequencing was performed to measure the gut and oral microbiome at up to ten time points/subject and LHD and VHD were compared for change in principal components, Shannon diversity index and specific genera. The first three principal components explained 46.7% of the variance in gut microbiome diversity across time and all study subjects, indicating the change in gut microbiome following abstinence. The first time point was an outlier in three-dimensional principal component space versus all other time points. The gut microbiota in LHD and VHD were significantly dissimilar in change from day 1 to day 5 (p = .03) and from day 1 to week 3 (p = .02). The VHD drinking group displayed greater change from baseline. The Shannon diversity index of the gut microbiome changed significantly during abstinence in five participants. In both groups, the Shannon diversity was lower in the oral microbiome than gut. Ten total genera were shared between oral and stool in the AUD participants. These data were compared with healthy controls from the Human Microbiome Project to investigate the concept of a core microbiome. Rapid changes in gut microbiome following abstinence from alcohol suggest resilience of the gut microbiome in AUD and reflects the benefits of refraining from the highest levels of alcohol and potential benefits of abstinence.

Adults with alcohol use disorder may overreport dietary intake using the 1-year Diet History Questionnaire II.

Minimal recent research explores how alcohol use disorder (AUD) affects dietary intake during periods of alcohol consumption. Therefore, we aimed to assess the feasibility and utility of a computerized food frequency questionnaire, the Diet History Questionnaire II (DHQ II), to quantify dietary intake in adults with AUD. Participants were adult men and women seeking treatment for AUD at the National Institutes of Health Clinical Center. Participants (N = 21) were enrolled in an observational study examining the microbiome in AUD. The Web-based DHQ II, reflecting dietary intake over the past year, was administered to participants within 2 weeks of admission to an inpatient alcohol rehabilitation program. Descriptive data are reported as mean ±â€¯SEM. Analyses were run in the Statistical Package for the Social Sciences, and P < .05 was considered significant. Participants (67% male) were 46.3 ±â€¯2.8 years old with a body mass index of 23.8 ±â€¯0.6 kg/m2. Average energy intake was 27961.7 ±â€¯3205.8 kj, alcohol intake was 4723.0 ±â€¯75.8 g (45% kcal), carbohydrate intake was 514.3 ±â€¯66.8 g (31% kcal), fat intake was 101.2 ±â€¯13.6 g (16% kcal), and protein intake was 122.8 ±â€¯17.0 g (8% kcal). In this population of adults with AUD, DHQ II results showed energy and micronutrient intakes that were higher than, but macronutrient distribution that was similar to, previous findings in similar populations.