Andrea T. Kozak

Overview of the relationship between pain and obesity: What do we know? Where do we go next?

Overweight/obesity and pain are significant problems of increasing prevalence; understanding the relationship between the two is the focus of a growing body of research. Findings from this review support a likely relationship between increasing weight and pain conditions such as osteoarthritis and low back pain. Longitudinal studies suggest overweight/obesity early in life is a risk factor for pain, and the co-occurrence of pain and overweight/obesity negatively affects quality of life. The mechanism of relationship is unknown but is hypothesized to include mechanical and metabolic abnormalities, possibly secondary to lifestyle choices. Observations from a few studies demonstrate that treatments for obesity reduce pain secondary to weight loss. Few studies examine both pain and weight as primary outcomes, and variability in measurement makes comparisons and conclusions difficult. Research should focus on expanding knowledge about mechanisms of the relationship between pain and obesity, testing explanatory models addressing their co-occurrence, and developing treatments that most effectively target this comorbidity.

Multiple behavior changes in diet and activity: A randomized controlled trial using mobile technology

BACKGROUND Many patients exhibit multiple chronic disease risk behaviors. Research provides little information about advice that can maximize simultaneous health behavior changes. METHODS To test which combination of diet and activity advice maximizes healthy change, we randomized 204 adults with elevated saturated fat and low fruit and vegetable intake, high sedentary leisure time, and low physical activity to 1 of 4 treatments: increase fruit/vegetable intake and physical activity, decrease fat and sedentary leisure, decrease fat and increase physical activity, and increase fruit/vegetable intake and decrease sedentary leisure. Treatments provided 3 weeks of remote coaching supported by mobile decision support technology and financial incentives. During treatment, incentives were contingent on using the mobile device to self-monitor and attain behavioral targets; during follow-up, incentives were contingent only on recording. The outcome was standardized, composite improvement on the 4 diet and activity behaviors at the end of treatment and at 5-month follow-up. RESULTS Of the 204 individuals randomized, 200 (98.0%) completed follow-up. The increase fruits/vegetables and decrease sedentary leisure treatments improved more than the other 3 treatments (P < .001). Specifically, daily fruit/vegetable intake increased from 1.2 servings to 5.5 servings, sedentary leisure decreased from 219.2 minutes to 89.3 minutes, and saturated fat decreased from 12.0% to 9.5% of calories consumed. Differences between treatment groups were maintained through follow-up. Traditional dieting (decrease fat and increase physical activity) improved less than the other 3 treatments (P < .001). CONCLUSIONS Remote coaching supported by mobile technology and financial incentives holds promise to improve diet and activity. Targeting fruits/vegetables and sedentary leisure together maximizes overall adoption and maintenance of multiple healthy behavior changes.

Integrating Technology Into Standard Weight Loss Treatment: A Randomized Controlled Trial

BACKGROUND A challenge in intensive obesity treatment is making care scalable. Little is known about whether the outcome of physician-directed weight loss treatment can be improved by adding mobile technology. METHODS We conducted a 2-arm, 12-month study (October 1, 2007, through September 31, 2010). Seventy adults (body mass index >25 and ≤40 [calculated as weight in kilograms divided by height in meters squared]) were randomly assigned either to standard-of-care group treatment alone (standard group) or to the standard and connective mobile technology system (+mobile group). Participants attended biweekly weight loss groups held by the Veterans Affairs outpatient clinic. The +mobile group was provided personal digital assistants to self-monitor diet and physical activity; they also received biweekly coaching calls for 6 months. Weight was measured at baseline and at 3-, 6-, 9-, and 12-month follow-up. RESULTS Sixty-nine adults received intervention (mean age, 57.7 years; 85.5% were men). A longitudinal intent-to-treat analysis indicated that the +mobile group lost a mean of 3.9 kg more (representing 3.1% more weight loss relative to the control group; 95% CI, 2.2-5.5 kg) than the standard group at each postbaseline time point. Compared with the standard group, the +mobile group had significantly greater odds of having lost 5% or more of their baseline weight at each postbaseline time point (odds ratio, 6.5; 95% CI, 2.5-18.6). CONCLUSIONS The addition of a personal digital assistant and telephone coaching can enhance short-term weight loss in combination with an existing system of care. Mobile connective technology holds promise as a scalable mechanism for augmenting the effect of physician-directed weight loss treatment. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00371462.

Relationship of body mass index in young adulthood and health-related quality of life two decades later: the Coronary Artery Risk Development in Young Adults study

Objective:The expanding overweight and obesity epidemic notwithstanding, little is known about their long-term effect on health-related quality of life (HRQoL). The main objective of this study was to investigate whether overweight (body mass index (BMI) 25 to <30 kg m−2) and obese (BMI ⩾30 kg m−2) young adults have poorer HRQoL 20 years later.Methods:We studied 3014 participants in the Coronary Artery Risk Development in Young Adults (CARDIA) study, a longitudinal, community-dwelling, biracial cohort from four cities. BMI was measured at baseline and 20 years later. HRQoL was assessed by the Physical Component Summary (PCS) and the Mental Component Summary (MCS) scores of the Medical Outcomes Study 12-Item Short-Form Health Survey at year 20. Higher PCS or MCS scores indicate better HRQoL.Results:Mean year 20 PCS score was 52.2 for normal weight participants at baseline, 50.3 for overweight and 46.4 for obese (P-trend <0.001). This relation persisted after adjustment for baseline demographics, general health, and physical and behavioral risk factors and after further adjustment for 20-year changes in risk factors. No association was observed for MCS scores (P-trend 0.43).Conclusion:Overweight and obesity in early adulthood are adversely associated with self-reported physical HRQoL, but not mental HRQoL 20 years later.

The more pain I have, the more I want to eat: obesity in the context of chronic pain.

Providers frequently report pain as a barrier to weight loss, and initial evidence suggests individuals with chronic pain and obesity experience reduced treatment success. However, scant evidence informs our understanding of how this comorbidity negatively influences treatment outcome. More effective programs might be designed with (i) insight into the patients experience of comorbid chronic pain and obesity and (ii) improved understanding of the behavioral linkages between the experience of pain, engagement in health behaviors, and obesity treatment outcomes. Thirty adult primary care patients with mean BMI = 36.8 (SD 8.9) and average 0–10 pain intensity = 5.6 (SD 1.9) participated in semistructured, in‐depth interviews. Transcriptions were analyzed using the constant comparative method. Five themes emerged indicating that patients with comorbid chronic pain and obesity experience: depression as magnifying the comorbid physical symptoms and complicating treatment; hedonic hunger triggered by physical pain and associated with depression and shame; emotional or “binge” eating in response to pain; altered dietary choices in response to pain; and low self‐efficacy for physical activity due to pain. Individuals with chronic pain and obesity may be less responsive to traditional interventions that fail to address the symbiotic relationship between the two conditions. These individuals are at‐risk for depressive symptoms and eating and activity patterns that sustain the comorbidity and make treatment problematic, and they may respond to pain with behaviors that promote weight gain, poor health and low mood. Further research is needed to examine behavioral mechanisms that promote comorbid pain and obesity, and to develop targeted treatment modules.

Make Better Choices (MBC): Study design of a randomized controlled trial testing optimal technology-supported change in multiple diet and physical activity risk behaviors

BackgroundSuboptimal diet and physical inactivity are prevalent, co-occurring chronic disease risk factors, yet little is known about how to maximize multiple risk behavior change. Make Better Choices, a randomized controlled trial, tests competing hypotheses about the optimal way to promote healthy change in four bundled risk behaviors: high saturated fat intake, low fruit and vegetable intake, low physical activity, and high sedentary leisure screen time. The study aim is to determine which combination of two behavior change goals - one dietary, one activity - yields greatest overall healthy lifestyle change.Methods/DesignAdults (n = 200) with poor quality diet and sedentary lifestyle will be recruited and screened for study eligibility. Participants will be trained to record their diet and activities onto a personal data assistant, and use it to complete two weeks of baseline. Those who continue to show all four risk behaviors after baseline recording will be randomized to one of four behavior change prescriptions: 1) increase fruits and vegetables and increase physical activity, 2) decrease saturated fat and increase physical activity, 3) increase fruits and vegetable and decrease saturated fat, or 4) decrease saturated fat and decrease sedentary activity. They will use decision support feedback on the personal digital assistant and receive counseling from a coach to alter their diet and activity during a 3-week prescription period when payment is contingent upon meeting behavior change goals. They will continue recording on an intermittent schedule during a 4.5-month maintenance period when payment is not contingent upon goal attainment. The primary outcome is overall healthy lifestyle change, aggregated across all four risk behaviors.DiscussionThe Make Better Choices trial tests a disseminable lifestyle intervention supported by handheld technology. Findings will fill a gap in knowledge about optimal goal prescription to facilitate simultaneous diet and activity change. Results will shed light on which goal prescription maximizes healthful lifestyle change.Trial RegistrationClinical Trials Gov. Identifier NCT00113672

Beyond alcohol and drug addiction. Does the negative trait of low distress tolerance have an association with overeating

Low distress tolerance is an inability to withstand negative emotions. The connection between low distress tolerance and addiction to cigarettes, alcohol, and illegal drugs has been established. The purpose of the current study was to extend this work to overeating, which is an important symptom of food addiction. We investigated whether low distress tolerance was related to overeating as measured by the emotional and external eating scales of the Dutch Eating Behavior Questionnaire and the disinhibition scale of the Three-Factor Eating Questionnaire. Participants were 225 college students with a median age of 19; 32% were overweight or obese. Linear regression models adjusting for sex and BMI demonstrated significant inverse associations among distress tolerance and emotional eating (P = 0.001), external eating (P = 0.002), and disinhibition (P < 0.001). These initial results suggest the importance of additional research in the area of low distress tolerance, overeating, and food addiction.

PDA+: A Personal Digital Assistant for Obesity Treatment - An RCT testing the use of technology to enhance weight loss treatment for veterans

BackgroundObese adults struggle to make the changes necessary to achieve even modest weight loss, though a decrease in weight by as little as 10% can have significant health benefits. Failure to meet weight loss goals may in part be associated with barriers to obesity treatment. Wide-spread dissemination of evidence-based obesity treatment faces multiple challenges including cost, access, and implementing the programmatic characteristics on a large scale.AimsThe PDA+: A Personal Digital Assistant for Obesity Treatment randomized controlled trial (RCT) was designed to test whether a PDA-based behavioral intervention enhances the effectiveness of the existing group weight loss treatment program at VA Medical Centers Managing Overweight/Obese Veterans Everywhere (MOVE!). We also aim to introduce technology as a way to overcome systemic barriers of traditional obesity treatment.Methods/DesignVeterans enrolled in the MOVE! group at the Hines Hospital VAMC with BMI ≥ 25 and ≤ 40 and weigh < 400 pounds, experience chronic pain (≥ 4 on the NRS-I scale for ≥ 6 months prior to enrollment) and are able to participate in a moderate intensity exercise program will be recruited and screened for eligibility. Participants will be randomized to receive either: a) MOVE! treatment alone (Standard Care) or b) Standard Care plus PDA (PDA+). Those randomized to PDA+ will record dietary intake, physical activity, and weight on the PDA. In addition, they will also record mood and pain intensity, and receive biweekly telephone support for the first 6-months of the 12-month study. All participants will attend in-person lab sessions every three months to complete questionnaires and for the collection of anthropomorphic data. Weight loss and decrease in pain level intensity are the primary outcomes.DiscussionThe PDA+ trial represents an important step in understanding ways to improve the use of technology in obesity treatment. The trial will address barriers to obesity care by implementing effective behavioral components of a weight loss intervention and delivering high intensity, low cost obesity treatment. This RCT also tests an intervention approach supported by handheld technology in a population traditionally considered to have lower levels of technology literacy.Trial RegistrationClinicalTrials.gov: NCT00371462

Intention-to-treat analyses in behavioral medicine randomized clinical trials

BackgroundIntention-to-treat (ITT) is an analytic approach where all randomized participants are included in analyses and in their originally assigned condition, regardless of adherence or protocol deviation.PurposeThe present study aimed to determine whether reporting and correct use of ITT in behavioral medicine randomized clinical trials (RCTs) published in behavioral journals has improved in recent years.MethodITT and related analytic conventions were examined in behavioral medicine RCTs (N = 87) published in Annals of Behavioral Medicine, Health Psychology, and the Journal of Consulting and Clinical Psychology in the years 2000–2003 and then again in 2006–2007. Logistic regression analyses tested whether ten indicators associated with ITT were being used increasingly over time. Also tested was whether reporting and correct use of ITT improved following the adoption of Consolidated Standards of Reporting Clinical Trials (CONSORT) statement.ResultsResults revealed that less than half of RCTs (42%) used ITT analyses correctly. Over time, reporting of sample size estimation and primary outcome as well as use of the term “ITT” to describe analyses improved; however, correct implementation of ITT did not. Improvement was not specifically attributable to CONSORT adoption.ConclusionInvestigators’ claims of using ITT analyses have increased over time, but correct use of ITT has not.

Technology-based interventions for weight management: current randomized controlled trial evidence and future directions.

Obesity is a prevalent health care issue associated with disability, premature morality, and high costs. Behavioral weight management interventions lead to clinically significant weight losses in overweight and obese individuals; however, many individuals are not able to participate in these face-to-face treatments due to limited access, cost, and/or time constraints. Technological advances such as widespread access to the Internet, increased use of smartphones, and newer behavioral self-monitoring tools have resulted in the development of a variety of eHealth weight management programs. In the present paper, a summary of the most current literature is provided along with potential solutions to methodological challenges (e.g., high attrition, minimal participant racial/ethnic diversity, heterogeneity of technology delivery modes). Dissemination and policy implications will be highlighted as future directions for the field of eHealth weight management.