Tera L. Fazzino

Comparison of categorical alcohol dependence versus a dimensional measure for predicting weekly alcohol use in heavy drinkers

BACKGROUND The DSM specifies categorical criteria for psychiatric disorders. In contrast, a dimensional approach considers variability in symptom severity and can significantly improve statistical power. The current study tested whether a categorical, DSM-defined diagnosis of Alcohol Dependence (AD) was a better fit than a dimensional dependence measure for predicting change in alcohol consumption among heavy drinkers following a brief alcohol intervention (BI). DSM-IV and DSM-5 alcohol use disorder (AUD) measures were also evaluated. METHODS Participants (N=246) underwent a diagnostic interview after receiving a BI, then reported daily alcohol consumption using an Interactive Voice Response system. Dimensional AD was calculated by summing the dependence criteria (mean=4.0; SD=1.8). The dimensional AUD measure was a summation of positive Alcohol Abuse plus AD criteria (mean=5.8; SD=2.5). A multi-model inference technique was used to determine whether the DSM-IV categorical diagnosis or dimensional approach would provide a more accurate prediction of first week consumption and change in weekly alcohol consumption following a BI. RESULTS The Akaike information criterion (AIC) for the dimensional AD model (AIC=7625.09) was 3.42 points lower than the categorical model (AIC=7628.51) and weight of evidence calculations indicated there was 85% likelihood that the dimensional model was the better approximating model. Dimensional AUD models fit similarly to the dimensional AD model. All AUD models significantly predicted change in alcohol consumption (ps=.05). CONCLUSION A dimensional AUD diagnosis was superior for detecting treatment effects that were not apparent with categorical and dimensional AD models.

Heavy Drinking in Young Adulthood Increases Risk of Transitioning to Obesity

INTRODUCTION Heavy episodic alcohol use during young adulthood may contribute to excess weight gain and transition from healthy weight to overweight/obesity. This study is the first to evaluate the association between heavy episodic drinking during early adulthood and transition to overweight/obese status 5 years later using data from the U.S. National Longitudinal Study of Adolescent to Adult Health. METHODS The study used data from Waves III and IV, when participants were aged 18-26 and 24-32 years, respectively. The final sample consisted of 7,941 participants with measured height/weight who reported ever drinking alcohol. Multinomial logistic regression models tested the association between heavy episodic drinking and risk of transitioning to an unhealthy weight class. RESULTS Heavy episodic drinking was associated with 41% higher risk of transitioning from normal weight to overweight (relative risk ratio, 1.41; 95% CI=1.13, 1.74; p=0.002) and 36% higher risk of transitioning from overweight to obese by Wave IV (relative risk ratio, 1.36; 95% CI=1.09, 1.71; p=0.008), compared with individuals not drinking heavily, while accounting for covariates. Heavy episodic drinking was associated with 35% higher risk of maintaining obesity (relative risk ratio, 1.35; CI=1.06, 1.72; p=0.016) and gaining excess weight (OR=1.20, 95% CI=1.03, 1.39, p=0.02). CONCLUSIONS Regular heavy episodic drinking in young adulthood is associated with higher risk of gaining excess weight and transitioning to overweight/obesity. Obesity prevention efforts should address heavy drinking as it relates to caloric content and risk of transitioning to an unhealthy weight class.

Diet Quality of Breast Cancer Survivors after a Six-Month Weight Management Intervention: Improvements and Association with Weight Loss

ABSTRACT Purpose: Obesity and diet quality are two distinct lifestyle factors associated with morbidity and mortality among breast cancer survivors. The purposes of this study were to examine diet quality changes during a weight loss intervention among breast cancer survivors and to examine whether diet quality change was an important factor related to weight loss. Methods: Participants were overweight/obese breast cancer survivors (n = 180) participating in a weight loss intervention. Diet quality scores were calculated using the Healthy Eating Index (HEI)-2010. Paired sample t-tests were run to examine change in diet quality, and a latent difference model was constructed to examine whether change in diet quality was associated with weight change. Results: Participants significantly improved diet quality (P = 0.001) and lost 13.2 ± 5.8% (mean ± SD) of their weight (P = 0.001). Six-month HEI score was significantly associated with weight loss, controlling for baseline BMI (P = 0.003). Improvement in diet quality was also significantly associated with weight loss (P = 0.01). Conclusion: Our findings indicate that a weight loss intervention can result in both clinically significant weight loss and improvement in diet quality, and that improved diet quality is predictive of weight loss. Both weight loss and diet quality are implicated in longevity and quality of life for breast cancer survivors.

A Test of the DSM-5 Severity Scale for Alcohol Use Disorder

BACKGROUND For the DSM-5-defined alcohol use disorder (AUD) diagnosis, a tri-categorized scale that designates mild, moderate, and severe AUD was selected over a fully dimensional scale to represent AUD severity. The purpose of this study was to test whether the DSM-5-defined AUD severity measure was as proficient a predictor of alcohol use following a brief intervention, compared to a fully dimensional scale. METHODS Heavy drinking primary care patients (N=246) received a physician-delivered brief intervention (BI), and then reported daily alcohol consumption for six months using an Interactive Voice Response (IVR) system. The dimensional AUD measure we constructed was a summation of all AUD criteria met at baseline (mean=6.5; SD=2.5). A multi-model inference technique was used to determine whether the DSM-5 tri-categorized severity measure or a dimensional approach would provide a more precise prediction of change in weekly alcohol consumption following a BI. RESULTS The Akaike information criterion (AIC) for the dimensional AUD model (AIC=7623.88) was four points lower than the tri-categorized model (AIC=7627.88) and weight of evidence calculations indicated there was 88% likelihood the dimensional model was the better approximating model. The dimensional model significantly predicted change in alcohol consumption (p=.04) whereas the DSM-5 tri-categorized model did not. CONCLUSION A dimensional AUD measure was superior, detecting treatment effects that were not apparent with tri-categorized severity model as defined by the DSM-5. We recommend using a dimensional measure for determining AUD severity.

An experimental test of assessment reactivity within a web-based brief alcohol intervention study for college students.

OBJECTIVE Web-based brief alcohol intervention (WBI) programs have efficacy in a wide range of college students and have been widely disseminated to universities to address heavy alcohol use. In the majority of efficacy studies, web-based research assessments were conducted before the intervention. Web-based research assessments may elicit reactivity, which could inflate estimates of WBI efficacy. The current study tested whether web-based research assessments conducted in combination with a WBI had additive effects on alcohol use outcomes, compared to a WBI only. METHODS Undergraduate students (n=856) from universities in the United States and Canada participated in this online study. Eligible individuals were randomized to complete 1) research assessments+WBI or 2) WBI-only. Alcohol consumption, alcohol-related problems, and protective behaviors were assessed at one-month follow up. RESULTS Multiple regression using 20 multiply imputed datasets indicated that there were no significant differences at follow up in alcohol use, alcohol-related problems, or protective behaviors used when controlling for variables with theoretical and statistical relevance. A repeated measures analysis of covariance revealed a significant decrease in peak estimated blood alcohol concentration in both groups, but no differential effects by randomized group. There were no significant moderating effects from gender, hazardous alcohol use, or motivation to change drinking. CONCLUSIONS Web-based research assessments combined with a web-based alcohol intervention did not inflate estimates of intervention efficacy when measured within-subjects. Our findings suggest universities may be observing intervention effects similar to those cited in efficacy studies, although effectiveness trials are needed.

Change in Physical Activity During a Weight Management Intervention for Breast Cancer Survivors: Association with Weight Outcomes: Physical Activity Change and Weight Loss

This study examined the effects of a group phone‐based weight management intervention on change in physical activity as measured via accelerometer and self‐report in rural breast cancer survivors. The study also evaluated the role of physical activity on clinically meaningful cut points for weight loss (baseline to 6 months) and weight loss maintenance (6 to 18 months).

Recruiting 9126 Primary Care Patients by Telephone: Characteristics of Participants Reached on Landlines, Basic Cell Phones, and Smartphones

In primary care, collecting information about patient health behaviors between appointments can be advantageous. Physicians and researchers who embrace phone-based technology may find valuable ways to monitor patient-reported outcome measures of health (PROM). However, the level of phone technology sophistication should be tailored to the phone use of the population of interest. Despite the growing use of telephones as a means to gather PROM, little is known about phone use among primary care patients. As part of an ongoing study, the authors recruited primary care patients (N = 9126) for a health behavior screening study by calling them on the primary contact number listed in their medical record. The current study evaluated the frequency with which individuals were reached on landlines, basic cell phones, and smartphones, and examined participant characteristics. The majority of participants (63%) used landlines as their primary contact. Of the 37% using cell phones on the recruitment call, most (71%) were using smartphones. Landline users were significantly older than cell phone users (61.4 vs. 46.2 years; P = .001). Cell phone use did not differ significantly between participants with a college education and those without (37% vs. 38%; P = .82); however, smartphone use did differ (61% vs. 77%; P = .01). The majority of participants sampled used landlines as their primary telephone contact. Researchers designing phone-based PROM studies for primary care may have the broadest intervention reach using interactive voice response telephone technology, as patients could report health outcomes from any type of phone, including landlines. (Population Health Management 2016;19:212-215).

Protocol for the Rural Engagement in Primary Care for Optimizing Weight Reduction (RE-POWER) Trial: Comparing three obesity treatment models in rural primary care.

Obesity disproportionately affects rural residents in the United States, and primary care has the potential to fill a major gap in the provision of weight management services for rural communities. The objective of this cluster-randomized pragmatic trial is to evaluate the comparative effectiveness of three obesity treatment models in rural primary care: the Intensive Behavior Therapy fee-for-service (FFS) model reimbursed by Medicare, a team-based model that recognizes the patient-centered medical home (PCMH) as a preferred delivery approach, and the centralized disease management (DM) model, in which phone-based counseling is provided outside of the primary care practice. We hypothesize that the PCMH and DM treatments will be more effective than FFS in reducing weight at 24 months. Thirty-six practices from the rural Midwestern U.S. are randomized to deliver one of the three interventions to 40 patients (N=1440) age 20 to 75 with a BMI 30-45 kg/m(2). In the FFS arm, primary care providers and their personnel counsel patients to follow evidence-based weight loss guidelines using the Medicare-designated treatment schedule. In the PCMH arm, patients receive a comprehensive weight management intervention delivered locally by practice personnel using a combination of in-person and phone-based group sessions. In the DM arm, the same intervention is delivered remotely by obesity treatment specialists via group conference calls. The primary outcome is weight loss at 24 months. Additional measures include fasting glucose, lipids, quality of life indicators, and implementation process measures. Findings will illuminate effective obesity treatment intervention(s) in rural primary care.

Brief Intervention for Heavy Drinking in Primary Care: Role of Patient Initiation.

Background:Alcohol brief intervention (BI) in primary care (PC) is effective, but remains underutilized despite multiple efforts to increase provider-initiated BI. An alternative approach to promote BI is to prompt patients to initiate alcohol-related discussions. Little is known about the role of patients in BI delivery. Objectives:To determine the characteristics of PC patients who reported initiating BI with their providers, and to evaluate the association between the initiator (patient vs provider) and drinking after a BI. Methods:In the context of clinical trial, patients (n = 267) who received BI during a PC visit reported on the manner in which the BI was initiated, readiness to change, demographics, and recent history of alcohol consumption. Drinking was assessed again at 6-months after the BI. Results:Fifty percent of patients receiving a BI reported initiating the discussion of drinking themselves. Compared with those who reported a provider-initiated discussion, self-initiators were significantly younger (43.7 years vs 47.1 years; P = 0.03), more likely to meet Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria for current major depression (24% vs 14%; P = 0.04), and more likely to report a history of alcohol withdrawal symptoms (68% vs 52%; P < 0.01). Baseline readiness to change, baseline consumption rates, and current DSM-IV alcohol dependence were not different between groups. In the 2 to 3 weeks after BI, self-initiators reported greater decreases in drinks per week (5.7 vs 2.4; P = 0.02), and drinking days per week (1.0 vs 0.3; P = 0.002). At 6-month follow-up, self-initiators showed significantly greater reductions in weekly drinking compared to those whose provider initiated the BI (P = 0.002). Conclusions:Patient- and provider-initiated BI occurred with equal frequency, and patient-initiated BIs were associated with greater reductions in alcohol use. Future efforts to increase the BI rate in PC should include a focus on prompting patients to initiate alcohol-related discussions.

Weight fluctuation during adulthood and weight gain since breast cancer diagnosis predict multiple dimensions of body image among rural breast cancer survivors.

Obesity and weight gain after breast cancer treatment are common among survivors, yet the relationship between weight and body image has received little attention. The purpose of the current study was to examine the relationship between current body mass index, weight gain since diagnosis, and largest weight fluctuation in adulthood with six dimensions of body image among overweight/obese breast cancer survivors.