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Behavioral Medicine Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/vbmd20
Dietary Self-monitoring in Patients with Obstructive Sleep Apnea a
a
b
a
Megan M. Hood , Lisa M. Nackers , Brighid Kleinman , Joyce Corsica & Shawn N. Katterman a
a
Rush University Medical Center
b
Bellarmine University Accepted author version posted online: 25 Nov 2013.Published online: 04 Sep 2014.
To cite this article: Megan M. Hood, Lisa M. Nackers, Brighid Kleinman, Joyce Corsica & Shawn N. Katterman (2014) Dietary Self-monitoring in Patients with Obstructive Sleep Apnea, Behavioral Medicine, 40:4, 154-158, DOI: 10.1080/08964289.2013.842534 To link to this article: http://dx.doi.org/10.1080/08964289.2013.842534
PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http:// www.tandfonline.com/page/terms-and-conditions
BEHAVIORAL MEDICINE, 40: 154–158, 2014 Copyright Ó Taylor & Francis Group, LLC ISSN: 0896-4289 print / 1940-4026 online DOI: 10.1080/08964289.2013.842534
Dietary Self-monitoring in Patients with Obstructive Sleep Apnea Megan M. Hood and Lisa M. Nackers Rush University Medical Center
Brighid Kleinman
Downloaded by [University of Utah] at 21:57 25 November 2014
Bellarmine University
Joyce Corsica and Shawn N. Katterman Rush University Medical Center
Self-monitoring of food intake is a cornerstone of behavioral weight loss interventions, but its use has not been evaluated in the treatment of obese patients with obstructive sleep apnea (OSA). This pilot study described patterns of adherence to dietary self-monitoring in obese patients with OSA and determined associations between self-monitoring and weight loss, psychosocial functioning, and adherence to continuous positive airway pressure treatment. Participants completed a 6-week behavioral weight loss intervention focused on dietary selfmonitoring. Approximately one-third of participants were adherent to self-monitoring throughout the course of the intervention and experienced more weight loss than those who did not self-monitor regularly. More frequent dietary self-monitoring also appeared to be associated with adherence to other health behaviors. These preliminary data suggest that use of dietary self-monitoring may be beneficial for promoting weight loss and adherence to other important health behaviors in OSA patients.
Keywords: adherence, multiple behavior change, obstructive sleep apnea, self-monitoring, weight loss
Obesity affects one-third of the adult population in the United States1 and is an important risk factor for the development of obstructive sleep apnea (OSA).2,3 Approximately 70% of patients with OSA are obese.4 Weight loss serves as a key treatment strategy for the management of OSA in obese individuals.2,5,6 Dietary and lifestyle interventions are highly recommended by expert panels7 given evidence of their positive impact on weight loss and OSA symptoms.5,6,8 Achieving long-term weight loss in the context of a comorbid medical condition may present particular challenges for individuals with OSA. Identifying intervention strategies that promote weight loss in this population is therefore an important goal for improving health and sleep functioning for these patients. Correspondence should be addressed to Megan M. Hood, PhD, 1645 W. Jackson, Suite 400, Chicago, IL 60622. E-mail: megan_hood@ rush.edu
Self-monitoring of dietary intake, or deliberately and carefully attending to and recording one’s eating behavior, is considered one of the cornerstones of behavioral weight loss treatment and has consistently been found to increase the amount of weight lost and maintained long-term.9–13 Greater frequency of self-monitoring has been associated with larger reductions in weight.13 The majority of weight loss studies of patients with OSA have utilized methods involving increased risk (eg, bariatric surgery) or high cost (eg, use of meal replacements or pharmacology).2,8,13 A small number have reported prescribing dietary self-monitoring as a component of a broader intervention, such as the Sleep AHEAD study,14 yet little is known about patterns of adherence to self-monitoring and the effects of this key behavioral strategy15 in this population. Dietary self-monitoring is typically used as a component of a comprehensive behavioral weight loss intervention, but has been shown to be effective in producing weight loss even with no16 or
Downloaded by [University of Utah] at 21:57 25 November 2014
DIETARY SELF-MONITORING WITH OBSTRUCTIVE SLEEP APNEA
minimal17 additional behavioral treatments. Given its consistent positive associations with weight loss as well as its very low cost, evaluating the patterns and effects of dietary self-monitoring for patients with OSA is warranted. Adhering to dietary self-monitoring and condition-specific treatment behaviors such as use of continuous positive airway pressure (CPAP) treatment can be difficult. Multiple Health Behavior Change theory suggests that motivation, self-efficacy, and the ability to self-regulate may be transferred from one health-promoting behavior to another.18 Therefore, individuals with OSA who have been asked to adhere to one behavior, such as to CPAP treatment, may have a greater likelihood of adopting and adhering to additional health interventions, such as dietary self-monitoring. Yet, the relationship between these key treatment behaviors is currently unclear. Moreover, because dietary self-monitoring has not been reported in an OSA population, it is unknown whether specific demographic or psychological factors may impact adherence to self-monitoring for these patients. Examining dietary self-monitoring in patients with OSA may be a promising step in developing low-cost and effective weight loss strategies for this population. Understanding patterns of adherence to dietary self-monitoring in OSA patients may aid in determining the feasibility and acceptability of this intervention. This pilot study was designed to determine the pattern of adherence to dietary self-monitoring and the association between self-monitoring adherence and short-term weight loss in patients with OSA. Additional goals were to evaluate the association between demographic and psychosocial variables with self-monitoring adherence and to describe the relationship between self-monitoring and CPAP adherence in this population.
METHODS Participants and Procedure Participants were recruited through flyers posted in an accredited sleep center in an urban academic medical center. Individuals were eligible if they had been previously diagnosed with OSA via overnight polysomnogram, were currently using or initiating use of a CPAP device, and had a BMI between 30 and 50 kg/m2. Exclusionary criteria included: current treatment for another major sleep disorder, current diagnosis of an eating-related psychological or sleep disorder, diagnosis of a major psychological disorder not stabilized with medication or treatment, or current participation in a formal behavioral or pharmacological weight loss program or taking physician-prescribed or over the counter medications that are linked to increased or decreased appetite. This study was approved by the institutional review board.
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During a baseline assessment visit, participants completed a consent process, were weighed on a medical scale, and completed psychosocial questionnaires. Participants then received daily dietary self-monitoring forms to be used for six weeks, a self-help weight loss manual (The Beck Diet Solution Weight Loss Workbook),19 and a food and beverage calorie guide (The Calorie King Calorie Fat & Carbohydrate Counter).20 Participants also received verbal and written instructions for using the workbook and calorie guide from a research coordinator trained in providing nutritional education. Participants were trained to measure or estimate portion sizes and calorie content using the resources provided. They were asked to record all food and beverage intake as close as possible to the time of consumption to increase accuracy of recording. Participants were instructed to begin dietary monitoring the next day and to mail their self-monitoring forms in pre-stamped envelopes to the study coordinator each week for six weeks. Participants also received brief (< 5 minutes) weekly reminder phone calls prompting them to mail in their self-monitoring forms for the week. Participants then completed a 6-week post-treatment and 12week follow-up assessment. During these assessments, participants were weighed and completed study questionnaires and CPAP use data were obtained. Measures At the initial visit, participants completed demographic forms and were weighed on a medical scale in light clothing without shoes. Self-monitoring Forms Self-monitoring forms were designed to match the daily dietary intake forms used in the weight loss manual that was provided to participants. Forms included space for participants to write the type, quantity, and calorie content of all food or drink consumed. Epworth Sleepiness Scale (ESS) The Epworth Sleepiness Scale (ESS)21 is an 8-item selfreport measure of daytime sleepiness. Total scores range from 0 to 24. The ESS has high internal consistency (Cronbach’s alpha D 0.8819 in the standardization sample and 0.87 in the present study sample). Medical Outcomes Study General Adherence Scale (MOS-GA) The Medical Outcomes Study General Adherence Scale (MOS-GA)22 is a 5-item self-report measure of adherence to general medical recommendations. The MOS-GA has acceptable to high internal consistency
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reliability (alpha D 0.8121 in the standardization sample and 0.94 in the present study sample).
RESULTS Sample Characteristics
Beck Depression Inventory–Second Edition (BDI-II) Beck Depression Inventory–Second Edition (BDI-II)23 is a 21-item self-report measure that assesses the severity of depressive symptomatology in the last two weeks. The BDI-II yields a coefficient alpha of 0.9224 in the standardization sample and 0.93 in the present study sample.
Study participants (N D 22) were generally middle-aged (M D 53.68 yr, SD D 10.15) with some college education (M D 15.02 yr, SD D 3.36) and were fairly equally split between genders (55% F, N D 12). Half of the sample was African American (N D 11), 23% were Caucasian (N D 5), 13% were Hispanic (N D 3), and 13% endorsed “other” for their ethnicity (N D 3). Self-monitoring Adherence Patterns
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CPAP Adherence Data CPAP adherence was measured via download from the participant’s CPAP memory card. The CPAP download provided detailed information regarding CPAP use (eg, days used, number of hours used per night, etc.). For the purposes of this study, percentage of nights CPAP was used for greater than 4 hours per night (the standard measure of CPAP adherence25) was recorded.
Coding and Statistical Analysis Daily self-monitoring forms were coded as “submitted/ completed” or “blank/missing.” Forms were considered “completed” if any details about food intake were noted for the day (ie, if any self-monitoring occurred), which is both consistent with coding schemes used in the literature13,15 and supported by research that suggests that the process of self-monitoring may be more important than the level of detail recorded.26 Baseline value substitution was used to account for missing weight loss data for 7 participants for whom 12-week weight data were not available due to attrition. This assumes that given typical recidivism after weight loss, participants who were lost to follow up returned to baseline weight.27 Data were analyzed using SPSS software. Descriptive statistics were calculated to describe the sample and the pattern of adherence to self-monitoring over the 6 week intervention. Independent samples t tests compared 12week weight loss by self-monitoring adherence status. Pearson correlations using data from all participants (n D 22) were used to determine the relationship between self-monitoring adherence and demographic and psychosocial variables potentially associated with adherence. Data used in these analyses were obtained from participants in the intervention arm of a randomized pilot study comparing the intervention described above to a usual-care control. Between-group comparisons on weight and CPAP adherence outcomes can be found in Hood et al.28
The pattern of self-monitoring across the 42-day study period is displayed in Figure 1. On average, participants completed 43% of the self-monitoring forms. The highest rates of adherence to self-monitoring were observed during the first 14 days of the study, and participants who continued to self-monitor after this time remained adherent to self-monitoring throughout the study period. The adherence pattern in this sample was bimodal, such that 68% (n D 15) of participants completed less than one third of their daily self-monitoring forms (range 0 to 14 days completed) and 32% (n D 7) of participants completed at least 93% of their daily self-monitoring forms (range 39 to 42 days completed). Therefore for further analyses, self-monitoring adherence was coded dichotomously, as SM-non-adherent (completed less than 15 days of forms) or SM-adherent (completed 39 or greater days of forms). Self-monitoring Adherence and Weight Loss SM-adherent participants achieved a mean weight loss of 3.37 lbs (SD D 4.43), while SM-non-adherent participants experienced a weight gain of 0.81 lbs (SD D 3.56). Weight loss was significantly different between the two groups, t (20) D 2.38, p D .03, with a large effect size (Cohen’s d D 1.04).
FIGURE 1 Self-Monitoring Adherence by Day.
DIETARY SELF-MONITORING WITH OBSTRUCTIVE SLEEP APNEA
Predictors of Adherence to Self-monitoring Dietary self-monitoring adherence status was moderately positively correlated with general adherence (Table 1). Adequate CPAP adherence, defined as use of CPAP for four hours or more for at least 70% of days,25 was observed in 57% of the total sample for whom CPAP data was available at 12 weeks (total N D 14), with 68% of SM-adherent and 50% of SM-non-adherent participants exhibiting adequate adherence. Statistical comparisons between self-monitoring adherence groups by CPAP adherence status were not performed due to small sample size (n < 5 per cell).
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DISCUSSION This pilot study investigated adherence to dietary selfmonitoring and its associations with short-term weight loss and adherence to health behaviors in obese individuals with OSA who enrolled in a brief pilot weight loss intervention. There were three key findings. First, on average participants completed 43% of self-monitoring records, with one-third of participants displaying very good adherence throughout the course of the intervention. This suggests that dietary self-monitoring may be a feasible behavior change strategy in this population. Although suboptimal, the frequency of self-monitoring reported in the present study is fairly consistent with rates found in other studies in which participants completed 17%–60% of available self-monitoring logs, with adherence decreasing over time.eg,15,29,30 The minimalcontact model of treatment used in our intervention, while cost-effective, may have contributed to lower adherence rates as a result of less accountability to a provider. Congruent with previous reports,15,29 adherence in the present study declined over time; however, those participants who adhered to self-monitoring after two weeks were more likely to maintain adherence over the course of the intervention and lost more weight. This is consistent with other studies that suggest that early behavioral adherence is associated with better maintenance of lifestyle habits.15,31 Use of supplemental intervention strategies to target early non-adherers by TABLE 1 Correlations with Self-Monitoring Adherence Status Variable Body mass index (BMI) Age Sex Education Daytime sleepiness General adherence Depression
Pearson correlation
p
.03 .04 .04 ¡.26 ¡.11 .38 .06
ns ns ns ns ns .08 ns
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providing additional support and treatment, such as those used in some novel obesity interventions,32 may prove useful for patients with OSA. Second, participants who adhered to dietary self-monitoring lost significantly more weight at the end of the intervention, which indicates that self-monitoring may be an effective strategy for at least short-term weight loss for patients with OSA, consistent with results found with other obese populations.13 Self-monitoring serves as a potentially cost-effective and low-risk behavioral weight loss intervention method and has been shown to increase self-regulation to promote habit changes,33 which may result in long-term weight loss success.11,13 Larger scale studies investigating the long-term impact of self-monitoring on weight loss for patients in OSA are warranted. Third, participants who adhered to dietary self-monitoring appeared to exhibit higher levels of adherence to other health behaviors, including CPAP adherence and selfreported general adherence to medical treatment. This suggests the possibility of pre-existing psychological factors that favor the establishment of early adherence to healthy behaviors34 or transfer of lessons learned in other health behavior contexts,16 consistent with Multiple Health Behavior Change theory.18 Daytime sleepiness was not associated with self-monitoring adherence in this small sample at baseline, which is somewhat inconsistent with other studies that have found daytime sleepiness to be associated with poor adherence across a variety of health behaviors.35,36 Further investigation of the role of daytime sleepiness as well as other potential physiological and psychological mechanisms of change of behavioral weight loss interventions in both non-OSA and OSA patients will help clarify the ways in which these interventions are effective and identify individual factors that may warrant more intensive intervention. This pilot study demonstrates initial support of a novel targeted investigation of the effects of dietary self-monitoring with OSA patients. It provides important information regarding the feasibility of utilizing behavioral techniques to promote weight loss among patients with OSA. Additionally, given the self-help format of the piloted intervention, the results suggest that low-cost and easily disseminable interventions may be effective for at least short-term weight loss for OSA patients. Limitations of this pilot study include its small sample size, which limited our ability to fully assess associations between demographic, psychosocial, and adherence variables and our ability to use more sophisticated methods for managing missing data, though it provides initial data that can be used to support larger future investigations of these associations. In addition, participants did not receive feedback on self-monitoring or dietary intake, which supported the low-cost goal of the intervention but could have contributed to poor adherence. Future research should assess whether the inclusion of feedback may serve as a reinforcer
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to promote self-efficacy and increase adherence to selfmonitoring in these patients. CONCLUSIONS The findings from this pilot study suggest that self-monitoring of dietary intake is feasible for OSA patients and may be predictive of short-term weight loss. Thus, it may serve as a useful and cost-effective behavioral technique to promote health behavior change in obese patients with OSA.
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REFERENCES [1] Flegal KM, Carroll MD, Ogden CL, Curtin LR. Prevalence and trends in obesity among US adults, 1999–2008. JAMA. 2010;303:235–241. [2] Cowan DC, Livingston E. Obstructive sleep apnea syndrome and weight loss: Review. Sleep Disord. 2012: doi:10.1155/2012/163296. [3] Li C, Ford ES, Zhao G, Croft JB, Balluz LS, Mokdad AH. Prevalence of self-reported clinically diagnosed sleep apnea according to obesity status in men and women: National Health and Nutrition Examination Survey, 2005–2006. Prev Med. 2010;51:18–23. [4] Romero-Corral A, Caples SM, Lopez-Jimenez F, Somers VK. Interactions between obesity and obstructive sleep apnea: implications for treatment. Chest. 2010;137:711–719. [5] Anandam A., Akinnusi M, Kufel T, Porhomayon J, El-Solh AA. Effects of dietary weight loss on obstructive sleep apnea: a metaanalysis. Sleep and Breathing. 2012; doi:10.1007/s11325-012-0677-3. [6] Tuomilehto H, Seppa J, Uusitupa M. Obesity and obstructive sleep apnea: clinical significance of weight loss. Sleep Med Rev. 2012; doi:10.1016/j.smrv.2012.08.002. [7] Epstein LJ, Kristo D, Strollo PJ, et al. Adult obstructive sleep apnea task force of the American Academy of Sleep Medicine: clinical guideline for the evaluation, management and long-term care of obstructive sleep apnea in adults. J Clin Sleep Med. 2009;5:263–276. [8] Thomasouli M, Brady EM, Davies MJ, et al. The impact of diet and lifestyle management strategies for obstructive sleep apnea in adults: A systematic review and meta-analysis of randomized controlled trials. Sleep Breath. 2013; doi:10.1007/s11325-013-0806-7. [9] Smith CF, Wing RR. New directions in behavioral weight loss programs. Diabetes Spectrum. 2000;13:142–150. [10] Wing RR. Behavioral approaches to the treatment of obesity. In: Bray G, Bonchard C, James PI, eds. Handbook of Obesity. New York, NY: Marcel Dekker; 1998:853–873. [11] Baker RC, Kirschenbaum DS. Self-monitoring may be necessary for successful weight control. Behav Ther. 1993;24:377–394. [12] Bornstein PH, Hamilton SB, Bornstein MT. Self monitoring procedures. In Ciminero AR, Calhoun CS, Adams HE, eds. Handbook of Behavioral Assessment. New York, NY: Wiley; 1986:176–222. [13] Burke LE, Swigart V, Turk MW, Derro N, Ewing LJ. Experiences of self-monitoring: successes and struggles during treatment for weight loss. Qual Health Res. 2009;19:815–828. [14] Foster GD, Borradaile KE, Sanders MH, et al. A randomized study on the effects of weight loss on obstructive sleep apnea among obese patients with type 2 diabetes: the Sleep AHEAD study. Arch Intern Med. 2009;169:1619–1626.
[15] Krukowski RA, Harvey-Berino J, Bursac Z, Ashikaga T. Patterns of success: online self-monitoring in a web-based behavioral weight control program. Health Psychol. 2013;32:164–170. [16] Romanczyk RG. Self-monitoring in the treatment of obesity: parameters of reactivity. Behav Ther. 1974;5:531–540. [17] Carels RA, Young KM, Coit C, Clayton AM, Spencer A, Hobbs M. Can following the caloric restriction recommendations from the Dietary Guidelines for Americans help individuals lose weight? Eating Behav. 2008;9:328–335. [18] Lippke S, Nigg CR, Maddock JE. Health-promoting and health-risk behaviors: theory-driven analyses of multiple health behavior change in three international samples. Int J Behav Med. 2012;19:1–13. [19] Beck JS. The Beck Diet Solution Weight Loss Workbook. Birmingham, AL: Oxmoor House; 2007. [20] Borushek A. The CalorieKingÒ Calorie, Fat & Carbohydrate Counter. Costa Mesa, CA: Family Health Publications; 2011. [21] Johns MR. Reliability and factor analysis of the Epworth Sleepiness Scale. Sleep. 1992;15:376–381. [22] Stewart AL, Ware JE. Measuring Functional Status and Well-being: The Medical Outcomes Study Approach. Durham, NC: Duke University Press; 1992. [23] Hays RD. The medical Outcomes Study (MOS) measures of patient adherence; 2009. http://www.rand.org/health/surveys_tools/mos/ mos_adherence.html. Accessed September 16, 2009. [24] Beck AT, Steer RA, Brown GK. Manual for the Beck Depression Inventory-II. San Antonio, TX: Psychological Corporation; 1996. [25] Kribbs NB, Pack A, Kline L, Smith PL, Schwartz AR, Schubert NM, Redline S, Dinges DF. Objective measurement of patterns of nasal CPAP use by patients with obstructive sleep apnea. Am Rev Respir Dis. 1993;147:887. [26] Helsel DL, Jakicic JM, Otto AD. Comparison of techniques for selfmonitoring eating and exercise behaviors on weight loss in a correspondence-based intervention. JADA. 2007;107:1807–1810. [27] Ware JH. Interpreting incomplete data in studies of diet and weight loss. N Engl J Med. 2003;348:2136–2137. [28] Hood MM, Corsica J, Cvengros J, Wyatt, J. Impact of a brief dietary self-monitoring intervention on weight change and CPAP adherence in patients with obstructive sleep apnea. J Psychosom Res. 2013;74:170–174. [29] Acharya SD, Elci OU, Sereika SM, et al. Adherence to a behavioral weight loss treatment program enhances weight loss and improvements in biomarkers. Patient Prefer Adher. 2009;3:151–160. [30] Tate DF, Wing RR, Winett RA. Using internet technology to deliver a behavioral weight loss program. JAMA. 2001;285:1172–1177. [31] Warziski MT, Sereika SM, Styn MA, Music E, Burke LE. Changes in self-efficacy and dietary adherence: the impact on weight loss in the PREFER study. J Behav Med. 2008;31:81–92. [32] Jakicic JM, Tate DF, Lang W, et al. Effect of a stepped-care intervention approach on weight loss in adults: a randomized clinical trial. JAMA. 2012;307:2617–2626. [33] Kanfer FH. Self-monitoring: methodological limitations and clinical applications. J Consult Clin Psychol. 1970;35:148–152. [34] Bogg T, Roberts BW. Conscientiousness and health-related behaviors: a meta-analysis of the leading behavioral contributors to mortality. Psychol Bull. 2004;130:887–919. [35] Shapiro GK, Shapiro CM. Factors that influence CPAP adherence: an overview. Sleep Breath. 2010;14:323–335. [36] Chasens ER, Korytkowski M, Sereika SM, Burke LE. Effect of poor sleep quality and excessive daytime sleepiness on factors associated with diabetes self-management. Diabetes Educ. 2013;39:74–82.
Behavioral Medicine Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/vbmd20
Dietary Self-monitoring in Patients with Obstructive Sleep Apnea a
a
b
a
Megan M. Hood , Lisa M. Nackers , Brighid Kleinman , Joyce Corsica & Shawn N. Katterman a
a
Rush University Medical Center
b
Bellarmine University Accepted author version posted online: 25 Nov 2013.Published online: 04 Sep 2014.
To cite this article: Megan M. Hood, Lisa M. Nackers, Brighid Kleinman, Joyce Corsica & Shawn N. Katterman (2014) Dietary Self-monitoring in Patients with Obstructive Sleep Apnea, Behavioral Medicine, 40:4, 154-158, DOI: 10.1080/08964289.2013.842534 To link to this article: http://dx.doi.org/10.1080/08964289.2013.842534
PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http:// www.tandfonline.com/page/terms-and-conditions
BEHAVIORAL MEDICINE, 40: 154–158, 2014 Copyright Ó Taylor & Francis Group, LLC ISSN: 0896-4289 print / 1940-4026 online DOI: 10.1080/08964289.2013.842534
Dietary Self-monitoring in Patients with Obstructive Sleep Apnea Megan M. Hood and Lisa M. Nackers Rush University Medical Center
Brighid Kleinman
Downloaded by [University of Utah] at 21:57 25 November 2014
Bellarmine University
Joyce Corsica and Shawn N. Katterman Rush University Medical Center
Self-monitoring of food intake is a cornerstone of behavioral weight loss interventions, but its use has not been evaluated in the treatment of obese patients with obstructive sleep apnea (OSA). This pilot study described patterns of adherence to dietary self-monitoring in obese patients with OSA and determined associations between self-monitoring and weight loss, psychosocial functioning, and adherence to continuous positive airway pressure treatment. Participants completed a 6-week behavioral weight loss intervention focused on dietary selfmonitoring. Approximately one-third of participants were adherent to self-monitoring throughout the course of the intervention and experienced more weight loss than those who did not self-monitor regularly. More frequent dietary self-monitoring also appeared to be associated with adherence to other health behaviors. These preliminary data suggest that use of dietary self-monitoring may be beneficial for promoting weight loss and adherence to other important health behaviors in OSA patients.
Keywords: adherence, multiple behavior change, obstructive sleep apnea, self-monitoring, weight loss
Obesity affects one-third of the adult population in the United States1 and is an important risk factor for the development of obstructive sleep apnea (OSA).2,3 Approximately 70% of patients with OSA are obese.4 Weight loss serves as a key treatment strategy for the management of OSA in obese individuals.2,5,6 Dietary and lifestyle interventions are highly recommended by expert panels7 given evidence of their positive impact on weight loss and OSA symptoms.5,6,8 Achieving long-term weight loss in the context of a comorbid medical condition may present particular challenges for individuals with OSA. Identifying intervention strategies that promote weight loss in this population is therefore an important goal for improving health and sleep functioning for these patients. Correspondence should be addressed to Megan M. Hood, PhD, 1645 W. Jackson, Suite 400, Chicago, IL 60622. E-mail: megan_hood@ rush.edu
Self-monitoring of dietary intake, or deliberately and carefully attending to and recording one’s eating behavior, is considered one of the cornerstones of behavioral weight loss treatment and has consistently been found to increase the amount of weight lost and maintained long-term.9–13 Greater frequency of self-monitoring has been associated with larger reductions in weight.13 The majority of weight loss studies of patients with OSA have utilized methods involving increased risk (eg, bariatric surgery) or high cost (eg, use of meal replacements or pharmacology).2,8,13 A small number have reported prescribing dietary self-monitoring as a component of a broader intervention, such as the Sleep AHEAD study,14 yet little is known about patterns of adherence to self-monitoring and the effects of this key behavioral strategy15 in this population. Dietary self-monitoring is typically used as a component of a comprehensive behavioral weight loss intervention, but has been shown to be effective in producing weight loss even with no16 or
Downloaded by [University of Utah] at 21:57 25 November 2014
DIETARY SELF-MONITORING WITH OBSTRUCTIVE SLEEP APNEA
minimal17 additional behavioral treatments. Given its consistent positive associations with weight loss as well as its very low cost, evaluating the patterns and effects of dietary self-monitoring for patients with OSA is warranted. Adhering to dietary self-monitoring and condition-specific treatment behaviors such as use of continuous positive airway pressure (CPAP) treatment can be difficult. Multiple Health Behavior Change theory suggests that motivation, self-efficacy, and the ability to self-regulate may be transferred from one health-promoting behavior to another.18 Therefore, individuals with OSA who have been asked to adhere to one behavior, such as to CPAP treatment, may have a greater likelihood of adopting and adhering to additional health interventions, such as dietary self-monitoring. Yet, the relationship between these key treatment behaviors is currently unclear. Moreover, because dietary self-monitoring has not been reported in an OSA population, it is unknown whether specific demographic or psychological factors may impact adherence to self-monitoring for these patients. Examining dietary self-monitoring in patients with OSA may be a promising step in developing low-cost and effective weight loss strategies for this population. Understanding patterns of adherence to dietary self-monitoring in OSA patients may aid in determining the feasibility and acceptability of this intervention. This pilot study was designed to determine the pattern of adherence to dietary self-monitoring and the association between self-monitoring adherence and short-term weight loss in patients with OSA. Additional goals were to evaluate the association between demographic and psychosocial variables with self-monitoring adherence and to describe the relationship between self-monitoring and CPAP adherence in this population.
METHODS Participants and Procedure Participants were recruited through flyers posted in an accredited sleep center in an urban academic medical center. Individuals were eligible if they had been previously diagnosed with OSA via overnight polysomnogram, were currently using or initiating use of a CPAP device, and had a BMI between 30 and 50 kg/m2. Exclusionary criteria included: current treatment for another major sleep disorder, current diagnosis of an eating-related psychological or sleep disorder, diagnosis of a major psychological disorder not stabilized with medication or treatment, or current participation in a formal behavioral or pharmacological weight loss program or taking physician-prescribed or over the counter medications that are linked to increased or decreased appetite. This study was approved by the institutional review board.
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During a baseline assessment visit, participants completed a consent process, were weighed on a medical scale, and completed psychosocial questionnaires. Participants then received daily dietary self-monitoring forms to be used for six weeks, a self-help weight loss manual (The Beck Diet Solution Weight Loss Workbook),19 and a food and beverage calorie guide (The Calorie King Calorie Fat & Carbohydrate Counter).20 Participants also received verbal and written instructions for using the workbook and calorie guide from a research coordinator trained in providing nutritional education. Participants were trained to measure or estimate portion sizes and calorie content using the resources provided. They were asked to record all food and beverage intake as close as possible to the time of consumption to increase accuracy of recording. Participants were instructed to begin dietary monitoring the next day and to mail their self-monitoring forms in pre-stamped envelopes to the study coordinator each week for six weeks. Participants also received brief (< 5 minutes) weekly reminder phone calls prompting them to mail in their self-monitoring forms for the week. Participants then completed a 6-week post-treatment and 12week follow-up assessment. During these assessments, participants were weighed and completed study questionnaires and CPAP use data were obtained. Measures At the initial visit, participants completed demographic forms and were weighed on a medical scale in light clothing without shoes. Self-monitoring Forms Self-monitoring forms were designed to match the daily dietary intake forms used in the weight loss manual that was provided to participants. Forms included space for participants to write the type, quantity, and calorie content of all food or drink consumed. Epworth Sleepiness Scale (ESS) The Epworth Sleepiness Scale (ESS)21 is an 8-item selfreport measure of daytime sleepiness. Total scores range from 0 to 24. The ESS has high internal consistency (Cronbach’s alpha D 0.8819 in the standardization sample and 0.87 in the present study sample). Medical Outcomes Study General Adherence Scale (MOS-GA) The Medical Outcomes Study General Adherence Scale (MOS-GA)22 is a 5-item self-report measure of adherence to general medical recommendations. The MOS-GA has acceptable to high internal consistency
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reliability (alpha D 0.8121 in the standardization sample and 0.94 in the present study sample).
RESULTS Sample Characteristics
Beck Depression Inventory–Second Edition (BDI-II) Beck Depression Inventory–Second Edition (BDI-II)23 is a 21-item self-report measure that assesses the severity of depressive symptomatology in the last two weeks. The BDI-II yields a coefficient alpha of 0.9224 in the standardization sample and 0.93 in the present study sample.
Study participants (N D 22) were generally middle-aged (M D 53.68 yr, SD D 10.15) with some college education (M D 15.02 yr, SD D 3.36) and were fairly equally split between genders (55% F, N D 12). Half of the sample was African American (N D 11), 23% were Caucasian (N D 5), 13% were Hispanic (N D 3), and 13% endorsed “other” for their ethnicity (N D 3). Self-monitoring Adherence Patterns
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CPAP Adherence Data CPAP adherence was measured via download from the participant’s CPAP memory card. The CPAP download provided detailed information regarding CPAP use (eg, days used, number of hours used per night, etc.). For the purposes of this study, percentage of nights CPAP was used for greater than 4 hours per night (the standard measure of CPAP adherence25) was recorded.
Coding and Statistical Analysis Daily self-monitoring forms were coded as “submitted/ completed” or “blank/missing.” Forms were considered “completed” if any details about food intake were noted for the day (ie, if any self-monitoring occurred), which is both consistent with coding schemes used in the literature13,15 and supported by research that suggests that the process of self-monitoring may be more important than the level of detail recorded.26 Baseline value substitution was used to account for missing weight loss data for 7 participants for whom 12-week weight data were not available due to attrition. This assumes that given typical recidivism after weight loss, participants who were lost to follow up returned to baseline weight.27 Data were analyzed using SPSS software. Descriptive statistics were calculated to describe the sample and the pattern of adherence to self-monitoring over the 6 week intervention. Independent samples t tests compared 12week weight loss by self-monitoring adherence status. Pearson correlations using data from all participants (n D 22) were used to determine the relationship between self-monitoring adherence and demographic and psychosocial variables potentially associated with adherence. Data used in these analyses were obtained from participants in the intervention arm of a randomized pilot study comparing the intervention described above to a usual-care control. Between-group comparisons on weight and CPAP adherence outcomes can be found in Hood et al.28
The pattern of self-monitoring across the 42-day study period is displayed in Figure 1. On average, participants completed 43% of the self-monitoring forms. The highest rates of adherence to self-monitoring were observed during the first 14 days of the study, and participants who continued to self-monitor after this time remained adherent to self-monitoring throughout the study period. The adherence pattern in this sample was bimodal, such that 68% (n D 15) of participants completed less than one third of their daily self-monitoring forms (range 0 to 14 days completed) and 32% (n D 7) of participants completed at least 93% of their daily self-monitoring forms (range 39 to 42 days completed). Therefore for further analyses, self-monitoring adherence was coded dichotomously, as SM-non-adherent (completed less than 15 days of forms) or SM-adherent (completed 39 or greater days of forms). Self-monitoring Adherence and Weight Loss SM-adherent participants achieved a mean weight loss of 3.37 lbs (SD D 4.43), while SM-non-adherent participants experienced a weight gain of 0.81 lbs (SD D 3.56). Weight loss was significantly different between the two groups, t (20) D 2.38, p D .03, with a large effect size (Cohen’s d D 1.04).
FIGURE 1 Self-Monitoring Adherence by Day.
DIETARY SELF-MONITORING WITH OBSTRUCTIVE SLEEP APNEA
Predictors of Adherence to Self-monitoring Dietary self-monitoring adherence status was moderately positively correlated with general adherence (Table 1). Adequate CPAP adherence, defined as use of CPAP for four hours or more for at least 70% of days,25 was observed in 57% of the total sample for whom CPAP data was available at 12 weeks (total N D 14), with 68% of SM-adherent and 50% of SM-non-adherent participants exhibiting adequate adherence. Statistical comparisons between self-monitoring adherence groups by CPAP adherence status were not performed due to small sample size (n < 5 per cell).
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DISCUSSION This pilot study investigated adherence to dietary selfmonitoring and its associations with short-term weight loss and adherence to health behaviors in obese individuals with OSA who enrolled in a brief pilot weight loss intervention. There were three key findings. First, on average participants completed 43% of self-monitoring records, with one-third of participants displaying very good adherence throughout the course of the intervention. This suggests that dietary self-monitoring may be a feasible behavior change strategy in this population. Although suboptimal, the frequency of self-monitoring reported in the present study is fairly consistent with rates found in other studies in which participants completed 17%–60% of available self-monitoring logs, with adherence decreasing over time.eg,15,29,30 The minimalcontact model of treatment used in our intervention, while cost-effective, may have contributed to lower adherence rates as a result of less accountability to a provider. Congruent with previous reports,15,29 adherence in the present study declined over time; however, those participants who adhered to self-monitoring after two weeks were more likely to maintain adherence over the course of the intervention and lost more weight. This is consistent with other studies that suggest that early behavioral adherence is associated with better maintenance of lifestyle habits.15,31 Use of supplemental intervention strategies to target early non-adherers by TABLE 1 Correlations with Self-Monitoring Adherence Status Variable Body mass index (BMI) Age Sex Education Daytime sleepiness General adherence Depression
Pearson correlation
p
.03 .04 .04 ¡.26 ¡.11 .38 .06
ns ns ns ns ns .08 ns
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providing additional support and treatment, such as those used in some novel obesity interventions,32 may prove useful for patients with OSA. Second, participants who adhered to dietary self-monitoring lost significantly more weight at the end of the intervention, which indicates that self-monitoring may be an effective strategy for at least short-term weight loss for patients with OSA, consistent with results found with other obese populations.13 Self-monitoring serves as a potentially cost-effective and low-risk behavioral weight loss intervention method and has been shown to increase self-regulation to promote habit changes,33 which may result in long-term weight loss success.11,13 Larger scale studies investigating the long-term impact of self-monitoring on weight loss for patients in OSA are warranted. Third, participants who adhered to dietary self-monitoring appeared to exhibit higher levels of adherence to other health behaviors, including CPAP adherence and selfreported general adherence to medical treatment. This suggests the possibility of pre-existing psychological factors that favor the establishment of early adherence to healthy behaviors34 or transfer of lessons learned in other health behavior contexts,16 consistent with Multiple Health Behavior Change theory.18 Daytime sleepiness was not associated with self-monitoring adherence in this small sample at baseline, which is somewhat inconsistent with other studies that have found daytime sleepiness to be associated with poor adherence across a variety of health behaviors.35,36 Further investigation of the role of daytime sleepiness as well as other potential physiological and psychological mechanisms of change of behavioral weight loss interventions in both non-OSA and OSA patients will help clarify the ways in which these interventions are effective and identify individual factors that may warrant more intensive intervention. This pilot study demonstrates initial support of a novel targeted investigation of the effects of dietary self-monitoring with OSA patients. It provides important information regarding the feasibility of utilizing behavioral techniques to promote weight loss among patients with OSA. Additionally, given the self-help format of the piloted intervention, the results suggest that low-cost and easily disseminable interventions may be effective for at least short-term weight loss for OSA patients. Limitations of this pilot study include its small sample size, which limited our ability to fully assess associations between demographic, psychosocial, and adherence variables and our ability to use more sophisticated methods for managing missing data, though it provides initial data that can be used to support larger future investigations of these associations. In addition, participants did not receive feedback on self-monitoring or dietary intake, which supported the low-cost goal of the intervention but could have contributed to poor adherence. Future research should assess whether the inclusion of feedback may serve as a reinforcer
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to promote self-efficacy and increase adherence to selfmonitoring in these patients. CONCLUSIONS The findings from this pilot study suggest that self-monitoring of dietary intake is feasible for OSA patients and may be predictive of short-term weight loss. Thus, it may serve as a useful and cost-effective behavioral technique to promote health behavior change in obese patients with OSA.
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