Do in-person and computer-based brief alcohol interventions reduce tobacco smoking among general hospital patients? Secondary outcomes from a randomized controlled trial.

BACKGROUND: At-risk alcohol use and tobacco smoking often co-occur. We investigated whether brief alcohol interventions (BAIs) among general hospital patients with at-risk alcohol use may also reduce tobacco smoking over 2 years. We also investigated whether such effects vary by delivery mode; i.e. in-person versus computer-based BAI. METHODS: A proactively recruited sample of 961 general hospital patients with at-risk alcohol use aged 18 to 64 years was allocated to three BAI study groups: in-person BAI, computer-based BAI, and assessment only. In-person- and computer-based BAI included motivation-enhancing intervention contacts to reduce alcohol use at baseline and 1 and 3 months later. Follow-ups were conducted after 6, 12, 18 and 24 months. A two-part latent growth model, with self-reported smoking status (current smoking: yes/no) and number of cigarettes in smoking participants as outcomes, was estimated. RESULTS: Smoking participants in computer-based BAI smoked fewer cigarettes per day than those assigned to assessment only at month 6 (meannet change = - 0.02; 95% confidence interval = - 0.08-0.00). After 2 years, neither in-person- nor computer-based BAI significantly changed smoking status or number of cigarettes per day in comparison to assessment only or to each other (ps ≥ 0.23). CONCLUSIONS: While computer-based BAI also resulted in short-term reductions of number of cigarettes in smoking participants, none of the two BAIs were sufficient to evoke spill-over effects on tobacco smoking over 2 years. For long-term smoking cessation effects, multibehavioural interventions simultaneously targeting tobacco smoking along with at-risk alcohol use may be more effective. TRIAL REGISTRATION NUMBER: NCT01291693.

Patient motivation and preferences in changing co-occurring health risk behaviors in general hospital patients.

OBJECTIVES: More than 60% of general hospital patients report ≥ 2 health risk behaviors (HRBs), i.e. tobacco smoking, at-risk alcohol use, unhealthy diet, and/or insufficient physical activity. This study investigates a) the association between numbers of HRBs and motivation to change, b) patient preferences for receiving feedback on HRBs, and c) patients' expected gain in quality of life if behavior change made. METHODS: In 2020/2021, 256 18-64-year-old general hospital patients (72.1% of eligibles) reported on their motivation to change each of their HRBs. Associations between HRB number and motivation were assessed using multivariate linear regressions. Participants ranked HRBs concerning their interest in receiving feedback and concerning their expected gain in quality of life if behavior change occurred. RESULTS: Higher HRB number was negatively related to motivation among at-risk alcohol users (p = 0.034); 24.6% expected gain in their quality of life from behavior change. Participants overall appeared more favorable to feedback about vegetable/fruit intake and physical activity. CONCLUSIONS: Unhealthier lifestyle may be accompanied by decreased motivation to change in at-risk alcohol users. In case of co-occurring HRBs, asking patients for expected gain in quality of life may help guiding intervention target. PRACTICE IMPLICATIONS: Relying on patient selection only, may often leave substance-use unaddressed.

Health behaviors of general hospital patients with at-risk alcohol use: Change over two years after discharge.

OBJECTIVE: Little is known about the natural course of health-related behaviors such as tobacco smoking, at-risk alcohol use, vegetable and fruit intake and physical activity in general hospital patients after discharge. The aim was to investigate whether patients identified with at-risk alcohol use change their health-related behaviors over two years. METHODS: Eighteen to 64-year-old patients with at-risk alcohol use were identified through systematic screening as part of a randomized controlled trial. Patients with indication of an alcohol use disorder were excluded. Data of patients who received treatment as usual were analyzed (n = 220). Alcohol use, tobacco smoking, vegetable/ fruit intake, physical activity and body-mass-index were assessed at baseline, after 6, 12, 18, and 24 months. Latent growth models were calculated. RESULTS: Twenty-four months after discharge, participants reported less physical activity (p = .04), a higher body-mass-index (p = .01), no change in vegetable/ fruit intake (p = .11) and smoking status (p = .87), fewer cigarettes per week among smokers (p < .001), and less alcohol use (p < .001) compared to baseline. CONCLUSIONS: The data revealed that patients with at-risk alcohol use increased or did not change energy-balance related behaviors and decreased substance-use related behaviors over 2 years after hospitalization. These findings underline the need of implementing multi-behavioral interventions into routine care.

Investigating the Association Between the Co-Occurrence of Behavioral Health Risk Factors and Sick Days in General Hospital Patients.

Objectives: To investigate the co-occurrence of 4 behavioral health risk factors (BHRFs), namely tobacco smoking, alcohol at-risk drinking, physical inactivity and unhealthy diet and their association with sick days prior to hospitalization in general hospital patients. Methods: Over 10 weeks (11/2020-04/2021), all 18-64-year-old patients admitted to internal medicine, general and trauma surgery, and otorhinolaryngology wards of a tertiary care hospital were systematically approached. Among 355 eligible patients, 278 (78.3%) participated, and 256 (72.1%) were analyzed. Three BHRF sum scores were determined, including current tobacco smoking, alcohol use, physical inactivity and 1 of 3 indicators of unhealthy diet. Associations between BHRF sum scores and sick days in the past 6 months were analyzed using multivariate zero-inflated negative binomial regressions. Results: Sixty-two percent reported multiple BHRFs (≥2). The BHRF sum score was related to the number of sick days if any (p = 0.009) with insufficient vegetable and fruit intake as diet indicator. Conclusion: The majority of patients disclosed multiple BHRFs. These were associated with sick days prior to admission. The findings support the need to implement interventions targeting multiple BHRFs in general hospitals.

Proactive automatised lifestyle intervention (PAL) in general hospital patients: study protocol of a single-group trial.

INTRODUCTION: The co-occurrence of health risk behaviours (HRBs, ie, tobacco smoking, at-risk alcohol use, insufficient physical activity and unhealthy diet) increases the risks of cancer, other chronic diseases and mortality more than additively; and applies to more than half of adult general populations. However, preventive measures that target all four HRBs and that reach the majority of the target populations, particularly those persons most in need and hard to reach are scarce. Electronic interventions may help to efficiently address multiple HRBs in healthcare patients. The aim is to investigate the acceptance of a proactive and brief electronic multiple behaviour change intervention among general hospital patients with regard to reach, retention, equity in reach and retention, satisfaction and changes in behaviour change motivation, HRBs and health. METHODS AND ANALYSIS: A pre-post intervention study with four time points is conducted at a general hospital in Germany. All patients, aged 18-64 years, admitted to participating wards of five medical departments (internal medicine A and B, general surgery, trauma surgery, ear, nose and throat medicine) are systematically approached and invited to participate. Based on behaviour change theory and individual HRB profile, 175 participants receive individualised and motivation-enhancing computer-generated feedback at months 0, 1 and 3. Intervention reach and retention are determined by the proportion of participants among eligible patients and of participants who continue participation, respectively. Equity in reach and retention are measured with regard to school education and other sociodemographics. To investigate satisfaction with the intervention and subsequent changes, a 6-month follow-up is conducted. Descriptive statistics, multivariate regressions and latent growth modelling are applied. ETHICS AND DISSEMINATION: The local ethics commission and data safety appointee approved the study procedures. Results will be disseminated via publication in international scientific journals and presentations on scientific conferences. TRIAL REGISTRATION NUMBER: NCT05365269.

The Role of Tobacco Smoking in the Efficacy of Brief Alcohol Intervention: Results from a Randomized Controlled Trial.

This study investigated whether tobacco smoking affected outcomes of brief alcohol interventions (BAIs) in at-risk alcohol-drinking general hospital patients. Between 2011 and 2012 among patients aged 18−64 years, 961 patients were allocated to in-person counseling (PE), computer-based BAI containing computer-generated individual feedback letters (CO), and assessment only. PE and CO included contacts at baseline, 1, and 3 months. After 6, 12, 18, and 24 months, self-reported reduction of alcohol use per day was assessed as an outcome. By using latent growth curve models, self-reported smoking status, and number of cigarettes per day were tested as moderators. In PE and CO, alcohol use was reduced independently of smoking status (IRRs ≤ 0.61, ps < 0.005). At month 24, neither smoking status nor number of cigarettes per day moderated the efficacy of PE (IRR = 0.69, ps > 0.05) and CO (IRR = 0.85, ps > 0.05). Up to month 12, among persons smoking ≤ 19 cigarettes per day, the efficacy of CO increased with an increasing number of cigarettes (ps < 0.05). After 24 months, the efficacy of PE and CO that have been shown to reduce drinking did not differ by smoking status or number of cigarettes per day. Findings indicate that efficacy may differ by the number of cigarettes in the short term.

Differential effects of protein intake versus intake of a defined oligopeptide on FGF-21 in obese human subjects in vivo.

BACKGROUND: FGF-21 is described as a powerful metabolic regulator with beneficial effects including glucose-lowering and improvement of insulin sensitivity without hypoglycaemia. On the other hand, FGF-21 is activated when muscle and other tissues are stressed by external effects or internal cellular pathogens that lead to shortcomings in metabolic balance. Previous results suggested that FGF-21 could be a promising target to develop future metabolic therapeutics. PURPOSE: The present study was performed to gain deeper insight into the regulation of FGF-21 by protein metabolism in obese human subjects. METHODS: FGF-21 serum concentrations were measured in a cohort of n = 246 obese humans ± type 2 diabetes mellitus (T2DM) (median age 53.0 [46.0; 60.0] years and BMI 40.43 [35.11; 47.24] kg/m2) and related to the nutritional protein intake. In addition, the effect of a novel oligopeptide purified from a ß-casein hydrolysate on FGF-21 was examined in vitro in liver cells and in vivo in a human intervention study with the main focus on metabolic inflammation including 40 mainly obese subjects (mean age 41.08 ± 9.76 years, mean BMI 38.29 ± 9.4 kg/m2) in a randomized 20 weeks double-blind cross-over design. MAIN FINDINGS: In the cohort analysis, FGF-21 serum concentrations were significant lower with higher protein intake in obese subjects without T2DM but not in obese subjects with T2DM. Furthermore, relative methionine intake was inversely related to FGF-21. While global protein intake in obesity was inversely associated with FGF-21, incubation of HepG2 cells with a ß-casein oligopeptide increased FGF-21 expression in vitro. This stimulatory effect was also present in vivo, since in the clinical intervention study treatment of obese subjects with the ß-casein oligopeptide for 8 weeks significantly increased FGF-21 serum levels from W0 = 23.86 pg/mL to W8 = 30.54 pg/mL (p < 0.001), while no increase was found for placebo. CONCLUSION: While the total nutritional protein intake is inversely associated with FGF-21 serum levels, a purified and well characterised oligopeptide is able to induce FGF-21 serum levels in humans. These findings suggest a differential role of various components of protein metabolism on FGF-21, rather than this factor being solely a sensor of total nutritional protein intake.