Body dissatisfaction predicts poor behavioral weight loss treatment adherence in overweight Mexican American women

Body Image 23 (2017) 155–161

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Body dissatisfaction predicts poor behavioral weight loss treatment adherence in overweight Mexican American women Julia L. Austin 1 , Kelsey N. Serier, Ruth E. Sarafin, Jane Ellen Smith ∗ University of New Mexico, Department of Psychology, MSC03 2220, Albuquerque, NM 87131, United States

a r t i c l e

i n f o

Article history: Received 22 March 2017 Received in revised form 10 August 2017 Accepted 15 August 2017 Keywords: Body dissatisfaction Body image Overweight Mexican American Attendance Adherence

a b s t r a c t Poor adherence poses a major barrier to the success of behavioral weight loss (BWL) programs, particularly for overweight Mexican American women. Given the high prevalence and costs of overweight/obesity, factors that contribute to attendance and adherence problems should be identified, especially in ethnic minority populations. The current study examined the role of pre-treatment body dissatisfaction and depression in predicting attendance and adherence in a BWL intervention. Ninetynine overweight/obese Mexican American women enrolled in the intervention and completed baseline measures. Eighty-one of the women attended at least one treatment session and provided measures of dietary and physical activity adherence. Simultaneous linear regression analyses suggested that although higher levels of body dissatisfaction and depression each played unique roles in predicting poorer attendance, only body dissatisfaction predicted adherence. Specifically, higher body dissatisfaction predicted poorer treatment adherence. Findings highlight the importance of addressing body dissatisfaction early in BWL treatment to increase attendance and adherence. © 2017 Elsevier Ltd. All rights reserved.

1. Introduction Nearly 67% of women in the United States are overweight, and 37% of this subgroup is obese (Yang & Colditz, 2015). Overweight and obesity are associated with certain medical conditions, and women have a greater relative risk of some of these co-morbidities (i.e., type 2 diabetes, coronary artery disease) compared to men (Guh et al., 2009; National Institutes of Health, 2000). There is also an increased risk of breast, endometrial, and ovarian cancer in overweight and obese women compared to average weight women (Guh et al., 2009). Overall, excess weight and associated co-morbidities result in increased mortality and a substantial public health concern (Borrell & Samuel, 2014; Lehnert, Sonntag, Konnopka, Riedel-Heller, & König, 2013). Women are more likely than men to perceive themselves as overweight/obese, experience greater dissatisfaction with weight, and engage in more weight loss attempts (Cash & Hicks, 1990; Fiske, Fallon, Blissmer, & Redding, 2014; Yaemsiri, Slining, & Agarwal, 2011). In fact, approximately 75% of overweight/obese women report weight control attempts in the prior year (Yaemsiri et al., 2011). Yet many of these attempts appear unsuccessful, as approximately 50% of participants enrolled in behavioral weight loss (BWL)

∗ Corresponding author. E-mail address: [email protected] (J.E. Smith). 1 Currently at The Palo Alto Psychology Group, 417 Tasso Street, Palo Alto, CA 94301, United States. http://dx.doi.org/10.1016/j.bodyim.2017.08.002 1740-1445/© 2017 Elsevier Ltd. All rights reserved.

interventions return to their baseline weight within five years. Furthermore, dieting can even predict future weight gain (Lowe, Doshi, Katterman, & Feig, 2013; Wadden, Butryn, & Byrne, 2004). BWL interventions have been widely tested and demonstrate positive outcomes for individuals that continue to attend and adhere to the intervention (Alhassan, Kim, Bersamin, King, & Gardner, 2008; Anderson, Konz, Frederick, & Wood, 2001; Dansinger, Gleason, Griffith, Selker, & Schaefer, 2005; Franz et al., 2007). Many studies of weight loss outcomes, however, do not include measures of adherence (Lemstra, Bird, Nwankwo, Rogers, & Moraros, 2016). When incorporated, measures of adherence have varied widely. Examples include caloric intake (Alhassan et al., 2008), fruit/vegetable consumption (Anton, Perri, & Riley, 2000), self-assessments of dietary adherence (Dansinger et al., 2005), and amount of time spent exercising (Kruger, Lee, Ainswirth, & Macera, 2008). Nonetheless, adherence overall appears to be a highly influential factor in BWL intervention efficacy. For example, in a study comparing four popular diet approaches, adherence to any approach predicted better outcome than any specific diet strategy (Dansinger et al., 2005). Considering the consequences and variable outcomes for those who enroll in BWL interventions, researchers have searched for factors that predict attendance and adherence. Numerous factors have been implicated, but the definitiveness of these conclusions is limited due to the small number of studies, the high variability in both definitions of adherence and assessment measures for the construct, conflicting results, and high correlations between predictors (Lemstra et al., 2016).

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The current study primarily was interested in the role of two of these predictors, body dissatisfaction and depression, in predicting attendance and adherence in BWL treatment. Psychological predictors were the focus because there is evidence to suggest that they are better predictors of BWL treatment adherence compared to demographic factors (Moroshko, Brennan, & O’Brien, 2011). The attitudinal/evaluative aspect of body image; namely, body dissatisfaction (Cash & Pruzinsky, 2002; Jakatdar, Cash, & Engle, 2006), was examined along with depression given their high cooccurrence with overweight and obesity (Luppino et al., 2010; Schwartz & Brownell, 2004), and research suggesting their potentially detrimental effects on BWL efficacy (Teixeira, Going, Sardinha, & Lohman, 2005; Wing, Phelan, & Tate, 2002). Since brief interventions exist for both variables (Cash, 2008; Lewinsohn, Biglan, & Zeiss, 1976), these interventions possibly could be incorporated into the existing BWL treatments, if indicated, in an effort to increase attendance and adherence. 1.1. Potential contributions of body dissatisfaction and depression Previous research has demonstrated that body dissatisfaction and depression are associated with BWL intervention efficacy. Several studies have found that body dissatisfaction is related to decreased BWL efficacy (Elfhag & Rössner, 2010; Kiernan, King, Kraemer, Stefanick, & Killen, 1998; Teixeira et al., 2002, 2006), yet other research indicates that body dissatisfaction actually increases BWL efficacy (Traverso, Ravera, Lagattolla, Testa, & Adami, 2000). There is limited prior research regarding body dissatisfaction and attendance and adherence variables, but body dissatisfaction generally is associated with less physical activity (Kruger et al., 2008) and less healthful eating (Anton et al., 2000). Similarly, Gagnon-Girouard et al. (2009) found that body dissatisfaction was associated with overeating in a sample of weight preoccupied women. Thus, there seems to be an association between body dissatisfaction and important behavior changes associated with BWL efficacy. The current study provides a direct test of body dissatisfaction on attendance and adherence in a standard BWL intervention for Mexican American women. Regarding depression, considerable research has shown that higher depression scores are associated with decreased adherence to health care interventions (see Wing et al., 2002). Specifically, higher depressive symptomatology has been associated with poorer adherence to dietary and exercise interventions (Ciechanowski, Katon, & Russo, 2000; Ziegelstein et al., 2000) and diabetes self-care regimens (McKellar, Humphreys, & Piette, 2004). Yet the relationship between depression and adherence is not unidirectional. Depression symptoms and adherence reciprocally influence one another, such that depression increases non-adherence and adherence lessens depression (Wing et al., 2002). To further complicate the issue, body dissatisfaction and depression are highly correlated constructs, which makes it difficult to ascertain which psychological variable accounts for the most variance in BWL efficacy (Joiner, Wonderlich, Metalsky, & Schmidt, 1995; Keel, Mitchell, Davis, & Crow, 2001). Studies have not routinely assessed their contributions to BWL outcomes simultaneously. These clarifications are particularly important in identifying individuals at risk of failure in BWL interventions, and for driving treatment recommendations. 1.2. Attendance and adherence problems in Mexican American and Hispanic/Latino women Another poorly understood aspect of the overweight-obesity epidemic is the disparity in prevalence and consequences between ethnic and racial groups, specifically Hispanics/Latinos and non-

Hispanic Whites (Wang & Beydoun, 2007). Hispanics/Latinos, particularly Mexican American women, display higher rates of overweight and obesity than non-Hispanic Whites (Ogden, Carroll, Fryer, & Flegal, 2015), and have a higher prevalence of diabetes and cardiovascular risk factors (Caballero, 2007; Mitchell, Stern, Haffner, Hazuda, & Patterson, 1990). Current BWL interventions consistently are less effective for Hispanic participants (Lindberg & Stevens, 2007; Weiss, Galuska, Khan, Gillepse, & Serdula, 2007). More generally, racial and ethnic minorities report lower adherence to dietary and physical activity recommendations compared to non-Hispanic Whites (Baker, Schootman, Barnidge, & Kelly, 2006; Kirkpatrick, Dodd, Reedy, & Krebs-Smith, 2012; Zhao, Ford, Li, & Mokdad, 2008). Several studies have sought to address this disparity over the years by creating culturally-adapted weight loss and health behavior interventions (Corsino et al., 2012; Foreyt, Ramirez, & Cousins, 1991; Lindberg et al., 2012; Pekmezi et al., 2009; Rocha-Goldberg et al., 2010), but many of these interventions still exhibited low attendance (Corsino et al., 2012) and low rates of adherence to dietary (Parikh et al., 2010) and exercise recommendations (Keller & Cantue, 2008; Poston et al., 2001). The current body of literature on attendance and adherence to weight loss interventions among Hispanics is limited, and no study appears to have specifically examined predictors of attendance and adherence to a standard BWL intervention in Hispanic women. Using pre-treatment predictors to examine adherence to a BWL intervention, rather than attrition or weight loss, may provide a more nuanced understanding of BWL efficacy. This may be particularly important in ethnic minority populations that consistently have decreased weight loss outcomes (Wadden et al., 2009).

1.3. The current study Considering the lack of efficacy of culturally adapting BWL treatments for Hispanic populations, it appeared worthwhile to investigate the effects of psychological factors, specifically depression and body dissatisfaction, on adherence and attendance. Most previous studies demonstrating associations between depression, body dissatisfaction, and BWL attendance and adherence used non-Hispanic White samples or they did not specify the ethnic/racial make-up of the sample. Thus, there is some question about whether these results generalize to Hispanic women. Understanding these factors may be of particular significance given the similar rates of body dissatisfaction (Shaw, Ramirez, Trost, Randall, & Stice, 2004) and the higher rates of depression among Hispanic women compared to non-Hispanic White women (Kessler et al., 2003). The current study examined the role of body dissatisfaction and depression in attendance and adherence for Mexican American women enrolled in a BWL intervention. Despite some inconsistencies in the literature, we hypothesized that higher levels of body dissatisfaction and depression would be associated with poorer treatment attendance and adherence. Studies have not examined the relative contributions of depression and body dissatisfaction in BWL intervention attendance and adherence in a Mexican American sample. Still, research has suggested that body dissatisfaction is the most consistent source of psychological distress among those with overweight/obesity (Rosen, 1996). Body dissatisfaction often precedes or exacerbates depressive symptoms, as suggested in the dual pathway model by Stice (2002). Previous work has found support for this model among an obese patient population (Wardle, Waller, & Rapoport, 2001). Thus, we hypothesized that when body dissatisfaction and depression were considered simultaneously as predictors of attendance and adherence, body dissatisfaction would be a more consistent predictor.

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2. Method 2.1. Participants Data were collected as part of a non-randomized study that examined a culture-influenced predictor (“familism”; family comes first) of attendance, adherence, and weight loss in a BWL intervention (Austin, Smith, Gianini, & Campos-Melady, 2013). Overweight Mexican American women were recruited from a metropolitan area in the Southwest United States. Inclusionary criteria included: (1) age 18–65 years, (2) self-identification as Mexican heritage (e.g., Mexican American or Chicana), (3) proficiency in English, and (4) body mass index (BMI) ≥25 and ≤40. A BMI upper limit of 40 was to ensure the safety of participants in a BWL that incorporated a physical activity component (see review, Wadden & Osei, 2002). Exclusionary criteria included: (1) pregnant, (2) residence more than 50 miles from the study site, and (3) enrollment in another weight loss treatment or use of weight loss medications. Also, individuals completed the Physical Activity Readiness Questionnaire (PAR-Q), which assesses the risk of increasing physical activity (Brownell, 2004). Individuals who answered “yes” to any PAR-Q questions needed a letter of clearance from a medical professional before participating. Altogether 192 individuals contacted the researcher. Of those, 59 (30.73%) were deemed ineligible during the phone screen due to: BMI >40 (n = 34), not of Mexican heritage (n = 15), BMI <25 (n = 5), use of a weight loss aide (n = 1), >65 years old (n = 1), non-female (n = 1), non-English speaker (n = 1), and residence >50 miles from the site (n = 1). Another five individuals reported time conflicts for the groups. All 128 potential participants were scheduled for a pretreatment assessment, but 23 failed to attend and five were excluded due to a measured BMI >40. The initial treatment sample included 100 women. One participant was excluded from analyses because she did not complete the BDI (A different participant had been excluded from the original study, Austin et al., 2013, for failing to complete the main familism scale). Thus, attendance was analyzed with 99 participants. Of those 99, 18 failed to complete at least one treatment session, leaving 81 for adherence analyses. 2.2. Treatment protocol The 16 weekly sessions took place in groups of 6–16 participants and lasted one hour each. Groups were led by advanced clinical psychology graduate students who were under the supervision of a licensed clinical psychologist with a specialty in eating disorders/obesity. Treatment for all participants followed the LEARN (Lifestyle, Exercise, Attitudes, Relationships and Nutrition) program (Brownell, 2004). The first session was an orientation, and it included the distribution of materials (manual, pedometer). The 12 treatment sessions started with a discussion of the weekly calorie and step goal assignments (see below), and the use of behavioral strategies to address problems in meeting goals. Sessions next covered the lessons outlined in the LEARN manual, such as behavioral approaches to nutrition, physical activity, motivation, stimulus control, and social support. The final two treatment sessions entailed reviewing material, practicing skills, and addressing maintenance. 2.3. Measures 2.3.1. Anthropometric characteristics Height and weight were measured using a physician’s scale. Participants were weighed in light indoor clothing with shoes removed. BMI was calculated: weight in kilograms/(height in meters2 ).

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2.3.2. Demographics This questionnaire was designed to obtain information about age, education, number of children, income, occupational status, and marital status. Participants also were asked about their Spanish language fluency and generational status. 2.3.3. The Body Shape Questionnaire (BSQ; Cooper, Taylor, Cooper, & Fairburn, 1987) This 34-item questionnaire measures body dissatisfaction. On a 6-point Likert scale (1 = never, 6 = always) participants rate experiences of feeling fatness or discomfort with certain parts/aspects of their shape. Scores can range from 34 to 204, with higher scores indicating greater body dissatisfaction. The measure has demonstrated good concurrent and discriminant validity (Cooper et al., 1987). In the current study, Cronbach’s ˛ = .95. The BSQ appeared promising for our Mexican American sample, given its demonstrated measurement equivalence across ethnic groups (Warren et al., 2008). 2.3.4. Beck Depression Inventory-II (BDI-II; Beck, Steer, & Brown, 1996) The 21-item BDI-II measures cognitive, affective, and physical symptoms of depression. Participants select one of four response patterns (0–3 Likert scale) that denote depression symptomatology over the past two weeks. Total scores range from 0 to 64, with scores above 20 indicating clinically significant depression. The BDI-II has demonstrated good test-retest reliability and convergent validity (Beck et al., 1996). The BDI-II achieved a Cronbach’s ˛ = .91 in the current sample. 2.3.5. Attendance and treatment adherence measures Weekly attendance was tracked for all 16 sessions. For adherence monitoring, participants were asked to record daily calorie intake and number of steps. These logs were submitted and reviewed by the therapists during the treatment weeks, starting with week #4. These goals were monitored for 10 weeks of the treatment protocol; 70 days total. If participants missed a session they could turn in the logs the following week or submit them by mail, email, or fax. Logs more than one week overdue were counted as incomplete and a failure to meet the daily goal (Wadden, Berkowitz, Sarwer, Prus-Wisniewski, & Steinberg, 2001). In line with the guidelines in the LEARN program (Brownell, 2004), adherence was defined as the number of days (range: 0–70) a participant met her step goals and calorie goals. Step goals were met if the participant walked at least 4000 steps per day and increased by 200 steps daily (1400 steps weekly) as recorded by a pedometer and starting in week #4 (Brownell, 2004). Calorie goals were met if the participant’s daily calorie range was between 1000–1500 calories. Although the LEARN program designates 1200 calories/day as a reasonable goal for most overweight women in these programs (Brownell, 2004) and it was the target presented to the current study’s participants, the current program built in flexibility to accommodate individual differences. 2.4. Procedure This study was approved by the local university’s Institutional Review Board. Participants were recruited via flyers, newspaper advertisements, and online postings about a weight loss treatment study. Interested individuals contacted the researcher via phone and were screened for eligibility. A demographics interview and the PAR-Q were part of the phone screen. Individuals deemed eligible were scheduled for a pre-treatment assessment at a local community health center. Participants were informed of the protected status of health information, signed consent forms, and filled out the demographic and psychological assessment measures.

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Table 1 Correlations among psychological variables and adherence measures.

BDI (N = 99) Pre-treatment BMI (N = 99) Attend (N = 81) Step goals (N = 81) Calorie goals (N = 81)

BSQ

BDI

Pre-treatment BMI

Attend

Step goals

.52** .24* −.31** −.27* −.27*

−.04 −.31** −.21* −.25*

−.09 −.04 −.07

.63** .56**

.80**

Note: BSQ = Body Shape Questionnaire, BDI = Beck Depression Inventory. * p < .05. ** p < .01.

Participants’ height and weight also were recorded. All enrolled participants were scheduled for the LEARN treatment (16 one-hour groups). Attendance and adherence were monitored throughout treatment. All participants were contacted by phone after their first and second missed sessions. 2.5. Data analysis MPLUS version 7.3 (Muthén & Muthén, 2014) was used for all analyses. Linear regression analyses used depression and body dissatisfaction to predict attendance and adherence outcomes. Only one participant had missing data on the variables of interest. Given the small amount of missing data, listwise deletion was used. Furthermore, listwise deletion gives reliable results when using regression analyses (Little & Rubin, 2002). Sample size therefore changed for the outcome measures. 3. Results

Table 2 Summary of simultaneous linear regression analyses for psychological variables adherence to a behavioral weight loss treatment. Adherence variables

N

Attendance BSQ BDI Calorie goals BSQ BDI Step goals BSQ BDI

99

b

SE

t

p

ˇ

−.03 −.11

.02 .06

−2.10 −2.02

.04 .04

−.21 −.20

−.10 −.27

.05 .20

−2.05 −1.37

.04 .17

−.19 −.14

−.12 −.21

.06 .28

−2.16 −0.74

.03 .46

−.21 −.10

R2 .13

81

.09

81

.08

Note: BSQ = Body Shape Questionnaire, BDI = Beck Depression Inventory.

on 9.78 (SD = 17.55) of the possible 70 days (13.97%, range 0-68) and met their calorie goals on 7.58 (SD = 15.30) days (10.83%, range 0–68).

3.1. Participant demographic characteristics

3.4. Relationship between psychological variables and treatment attendance and adherence

Participants had a mean age of 45.1 years (SD = 12.1; range = 20–65). Over half the sample was married (56%) and most participants identified as mothers (89%). On average, the women had two children (M = 1.96, SD = 1.14), with over half of all participants reporting that their children lived at home (52%). The mean age of children residing at home was 11.65 (SD = 5.82; ages 4 months to 23 years). Regarding employment, 54% were employed full-time and 16% part-time, 12% were homemakers, 11% were unemployed, and 7% were retired. Median household income was $43,000. A total of 37% of the women had earned a bachelor’s degree or greater, 10% had an associate’s degree, 16% had a trade school certificate, and 36% had a high school degree or less. At baseline, 81% of participants were obese (BMIs ≥ 30) and 19% were overweight (BMIs = 25–29.99). The majority of the sample self-identified primarily as “Mexican American” or “Chicana” (92%) and 8% identified as “Mexican.” A majority reported third generational status or higher (73%). Half of the sample spoke Spanish very well (50%) and one-third of the women said Spanish was their first language (29%). Women in the sample also co-identified with the following heritages: Native American (13%), European (12%), African American (1%), and Chinese American (1%).

Baseline BSQ was significantly correlated with number of sessions attended and adherence outcomes, with greater BSQ scores (more body dissatisfaction) associated with poorer attendance and adherence (Table 1). Similarly, baseline depression level was significantly related to treatment attendance and adherence, with higher BDI scores associated with poorer attendance and adherence. Although BSQ and BDI were highly correlated, they did not meet threshold for multicollinearity. Thus, each predictor can be thought of as having a unique relationship to attendance and adherence (Tabachnick & Fidell, 2013). Attendance and adherence measures were highly positively correlated with one another, suggesting that participants who attended more sessions showed better adherence to the treatment. We also examined the relationship between pre-treatment BMI and measures of attendance and adherence, given previous research which suggests that body dissatisfaction increases with increasing BMI (Hill & Williams, 1998). Pre-treatment BMI was not significantly associated with attendance or adherence, suggesting that the effect of body dissatisfaction on adherence was independent of BMI.

3.2. Baseline psychological characteristics Participants’ BSQ mean was 116.37 (SD = 30.11, range 57–187), which suggests moderate levels of body dissatisfaction at baseline, on average (Cooper & Taylor, 1988). The average baseline BDI was 13.31 (SD = 9.13, range 0–45), which is indicative of minimal depressive symptoms (Beck et al., 1996). 3.3. Treatment attendance, adherence, and outcomes On average, participants attended 6.0 sessions out of a possible 14 treatment sessions (SD = 4.97). Participants met their step goals

3.5. Linear regression To understand the direct effects of depression and body dissatisfaction on treatment attendance and adherence, linear regression analyses were conducted with BDI and BSQ included as simultaneous predictors. The overall model for each outcome was significant: attendance (F (2,96) = 6.95, p = .002); calorie goals (F (2,78) = 3.73, p = .03); and step goals (F (2,78) = 3.27, p = .04). Body dissatisfaction remained a significant predictor of attendance and both adherence outcomes. However, depression was a significant predictor of only attendance when body dissatisfaction was included as a predictor (Table 2). The R2 values from these linear regression analyses suggest that there was a moderate effect of body dissatisfaction and

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depression on attendance and adherence. Post-hoc power analysis revealed that with the current sample sizes and observed effects, the power to detect a significant effect was .93 for attendance, .70 for calorie goals, and .64 for step goals. The power for the calorie and step goals analyses was somewhat less than the recommended minimum power of .80, therefore non-significant results should be interpreted with caution (Cohen, 1969). 4. Discussion 4.1. Summary of findings This study provided additional support for the effect of pretreatment body dissatisfaction and depression on participant adherence in BWL treatment. Moreover, this study expands on research by: (1) delineating these associations in Mexican American women, and (2) showing that body dissatisfaction is a more consistent predictor of treatment adherence than depression in this sample. In terms of a context for our sample, the Mexican American women in our study experienced similar levels of body dissatisfaction compared to other samples presenting for BWL treatment (Grilo, Wilfley, Brownell, & Rodin, 1994; Teixeira et al., 2004). And although our participants had minimal depressive symptoms (on average), some BWL intervention studies have found that even when their samples presented with an average of minimal depressive symptoms, each additional point on the BDI was associated with lower success in the intervention (Fabricatore et al., 2009). 4.2. Significance of the role of body dissatisfaction Poor treatment adherence is pronounced in Latinos and poses a major barrier to the success of BWL treatments (Alhassan et al., 2008; Domel, Alford, Cattlet, Rodriguez, & Gench, 1992; Foreyt et al., 1991; Lindberg et al., 2012). Prior work has tailored obesity interventions for Latino adults by adding culturally-adapted components (see review by Perez et al., 2013), and yet many of these interventions still reported limited adherence. Similar to previous research with Latinas, participants in the current study experienced comparatively poor attendance (Corsino et al., 2012) and treatment adherence (Parikh et al., 2010; Poston et al, 2001). On average, participants attended fewer than half the treatment sessions and seldom reported meeting their calorie and step goals. The analyses from this study should be interpreted within the context of these overall low adherence values. Previous studies have investigated the role of pre-treatment body dissatisfaction on BWL efficacy (Kiernan et al., 1998; Teixeira et al., 2002), but this appears to be the first to directly test the influence of pre-treatment body dissatisfaction on treatment attendance and adherence. Furthermore, prior research has confounded body dissatisfaction with related constructs, particularly depression, which has been an important psychological variable in predicting adherence in other weight loss studies (Wing et al., 2002). This study disentangled those effects, showing that although both constructs played a unique role in attendance, only pre-treatment body dissatisfaction predicted adherence measures. These results suggest that body dissatisfaction may be the more informative measure when predicting BWL intervention attendance and adherence, at least among Mexican American women. Moreover, given the strong bivariate correlations between depression and attendance/adherence, yet its non-significance when included in a simultaneous regression with body dissatisfaction, these results suggest a potentially mediated relationship. Future studies should investigate this relationship to determine whether body dissatisfaction mediates the effect of depression on treatment attendance and adherence.

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These results seem to suggest the need to include therapy for body dissatisfaction in BWL treatment. However, when Ramirez and Rosen (2001) compared a weight management program with and without body image therapy (which focused on body dissatisfaction and overvaluation of size/shape), they found no group differences in post-treatment body image or weight loss. Still, it is difficult to draw conclusions from this study because: (1) it was not clear at what point during weight management treatment the body image therapy was introduced, and (2) participants who dropped out of treatment had significantly higher levels of body dissatisfaction compared to treatment-completers. If those who dropped out did so before the introduction of the body image component, those remaining would not have benefited as highly from this component, thus explaining its null effects. This interpretation, combined with results presented here, suggest it may be important to include body image therapy at the beginning of a weight loss program in order to help individuals adhere to treatment and ultimately lose weight. 4.3. Limitations and conclusion This study has several limitations. First, the results were found in a select group of Mexican American women and therefore generalizations are limited. The women were English speaking, had higher SES and more education, were less likely to be of immigrant status, and were more acculturated compared to the general population of Mexican Americans in the United States (Austin et al., 2013). Second, only one measure of body image was used in the current study. Researchers have established body image as a multi-dimensional construct that consists of emotional, cognitive, and behavioral components (Cash & Pruzinsky, 2002; Hrabosky et al., 2009). It is not possible to conclude that other facets of body image (e.g., perceptual, investment in appearance) would show similar relationships with these adherence variables in Mexican American women. Third, the sample size was relatively small, which limited our power to detect change. However, this problem is expected when one specifically is studying adherence to BWL interventions; interventions that previous research suggests pose significant challenges to adherence (Dansinger et al., 2005). In spite of low power, we detected a significant effect of body dissatisfaction on attendance and dietary/physical activity adherence, which speaks to the robustness of the findings. Fourth, the R2 values in the regression analyses are quite low. This suggests that there is still a lot of variance in attendance and adherence that is not explained by body dissatisfaction and depression. Future studies should examine other predictors and their relative contributions to attendance and adherence. These results highlight the difficulty in finding a consistent set of predictors for BWL efficacy (Moroshko et al., 2011). Finally, the study examined only baseline predictors of adherence. Future studies should examine how baseline predictors of adherence relate to long term weight maintenance. The findings from this study highlight the importance of addressing body dissatisfaction early in BWL treatment, and more generally suggest a need to focus on participant psychological variables to increase attendance and adherence. This approach may be especially important for addressing disparities in the effectiveness of standard obesity interventions, especially for ethnically or racially diverse populations. Acknowledgments The research was supported in part by an American Psychological Association Minority Fellowship Program Dissertation Grant, a University of New Mexico Graduate Research and Development

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Grant, and a University of New Mexico Robert Wood Johnson Foundation Center for Health Policy Dissertation Fellowship. References Alhassan, S., Kim, S., Bersamin, A., King, A. C., & Gardner, C. D. (2008). Dietary adherence and weight loss success among overweight women: Results from the A TO Z weight loss study. International Journal of Obesity, 32, 985–991. http://dx.doi. org/10.1038/ijo.2008.8 Anderson, J., Konz, E., Frederick, R., & Wood, C. (2001). Long-term weight-loss maintenance: A meta-analysis of US studies. American Journal of Clinical Nutrition, 74, 579–584. Anton, S. D., Perri, M. G., & Riley, J. R. (2000). Discrepancy between actual and ideal body images: Impact on eating and exercise behaviors. Eating Behaviors, 1, 153–160. http://dx.doi.org/10.1016/S1471-0153(00)00015-5 Austin, J. L., Smith, J. E., Gianini, L., & Campos-Melady, M. (2013). Attitudinal familism predicts weight management adherence in Mexican–American women. Journal of Behavioral Medicine, 36, 259–269. http://dx.doi.org/10.1007/s10865-0129420-6 Baker, E. A., Schootman, M., Barnidge, E., & Kelly, C. (2006). The Role of Race and Poverty in Access to Foods That Enable Individuals to Adhere to Dietary Guidelines. Preventing Chronic Disease, 3(3), A76. http://www.cdc.gov/pcd/issues/ 2006/jul/05 0217.htm Beck, A. T., Steer, R. A., & Brown, G. K. (1996). Beck Depression Inventory-II. San Antonio, TX: The Psychological Corporation. Borrell, L. N., & Samuel, L. (2014). Body mass index categories and mortality risk in US adults: The effect of overweight and obesity on advancing death. American Journal of Public Health, 104, 512–519. http://dx.doi.org/10.2105/AJPH.2013. 301597 Brownell, K. D. (2004). The LEARN program for weight management (10th ed.). Dallas, TX: American Health Publishing Company. Caballero, A. E. (2007). Type 2 diabetes in the Hispanic or Latino population: Challenges and opportunities. Current Opinion in Endocrinology, Diabetes and Obesity, 14, 151–157. http://dx.doi.org/10.1097/MED.0b013e32809f9531 Cash, T. (2008). The body image workbook: An eight-step program for learning to like your looks. New Harbinger Publications. Cash, T. F., & Hicks, K. L. (1990). Being fat versus thinking fat: Relationships with body image, eating behaviors, and well-being. Cognitive Therapy and Research, 14, 327–341. http://dx.doi.org/10.1007/BF01184000 Cash, T. F. & Pruzinsky, T. (Eds.). (2002). Body image: A handbook of theory, research and clinical practice. New York: Guilford Press. Ciechanowski, P. S., Katon, W. J., & Russo, J. E. (2000). Depression and diabetes: Impact of depressive symptoms on adherence, function, and costs. Archives of Internal Medicine, 160, 3278–3285. http://dx.doi.org/10.1001/archinte.160.21.3278 Cohen, J. (1969). Statistical power analysis for the behavioral sciences. San Diego, CA: Academic Press. Cooper, P. J., & Taylor, M. J. (1988). Body image disturbance in bulimia nervosa. The British Journal of Psychiatry, 153, 32–36. Cooper, P. J., Taylor, M. J., Cooper, Z., & Fairburn, C. G. (1987). The development and validation of the Body Shape Questionnaire. International Journal of Eating Disorders, 6, 485–494. http://dx.doi.org/10.1002/1098-108X(198707)6:4<485::AIDEAT2260060405>3.0.CO;2-O Corsino, L., Rocha-Goldberg, M. P., Batch, B. C., Ortiz-Melo, D. I., Bosworth, H. B., & Svetkey, L. P. (2012). The Latino Health Project: Pilot testing a culturally adapted behavioral weight loss intervention in obese and overweight Latino adults. Ethnicity & Disease, 22, 51–57. Dansinger, M. L., Gleason, J. A., Griffith, J. L., Selker, H. P., & Schaefer, E. J. (2005). Comparison of the Atkins, Ornish, Weight Watchers, and Zone diets for weight loss and heart disease risk reduction: A randomized trial. Journal of the American Medical Association, 293, 43–53. http://dx.doi.org/10.1001/jama.293.1.43 Domel, S. B., Alford, B. B., Cattlett, H. N., Rodriguez, M. L., & Gench, B. E. (1992). A pilot weight control program for Hispanic women. Journal of the American Dietetic Association, 92, 1270–1271. Elfhag, K., & Rössner, S. (2010). Initial weight loss is the best predictor for success in obesity treatment and sociodemographic liabilities increase risk for drop-out. Patient Education and Counseling, 79, 361–366. http://dx.doi.org/10.1016/j.pec. 2010.02.006 Fabricatore, A. N., Wadden, T. A., Moore, R. H., Butryn, M. L., Heymsfield, S. B., & Nguyen, A. M. (2009). Predictors of attrition and weight loss success: Results from a randomized controlled trial. Behaviour Research and Therapy, 47, 685–691. http://dx.doi.org/10.1016/j.brat.2009.05.004 Fiske, L., Fallon, E. A., Blissmer, B., & Redding, C. A. (2014). Prevalence of body dissatisfaction among United States adults: Review and recommendations for future research. Eating Behaviors, 15, 357–365. http://dx.doi.org/10.1016/j. eatbeh.2014.04.010 Foreyt, J. P., Ramirez, A. G., & Cousins, J. H. (1991). Cuidando El Corazon—A weightreduction intervention for Mexican Americans. The American Journal of Clinical Nutrition, 53, 1639S–1641S. Franz, M. J., VanWormer, J. J., Crain, A. L., Boucher, J. L., Histon, T., Caplan, W., . . . & Pronk, N. P. (2007). Weight-loss outcomes: A systematic review and metaanalysis of weight-loss clinical trials with a minimum 1-year follow-up. Journal of the American Dietetic Association, 107, 1755–1767. http://dx.doi.org/10.1016/ j.jada.2007.07.017 Gagnon-Girouard, M. P., Bégin, C., Provencher, V., Tremblay, A., Boivin, S., & Lemieux, S. (2009). Can we apply the dual-pathway model of overeating to a popula-

tion of weight-preoccupied overweight women? International Journal of Eating Disorders, 42, 244–252. http://dx.doi.org/10.1002/eat.20614 Grilo, C. M., Wilfley, D. E., Brownell, K. D., & Rodin, J. (1994). Teasing, body image, and self-esteem in a clinical sample of obese women. Addictive Behaviors, 19, 443–450. http://dx.doi.org/10.1016/0306-4603(94)90066-3 Guh, D. P., Zhang, W., Bansback, N., Amarsi, Z., Birmingham, C. L., & Anis, A. H. (2009). The incidence of co-morbidities related to obesity and overweight: A systematic review and meta-analysis. BMC Public Health, 9, 88. http://dx.doi.org/10.1186/ 1471-2458-9-88 Hill, A. J., & Williams, J. (1998). Psychological health in a non-clinical sample of obese women. International Journal of Obesity, 22, 578–583. Hrabosky, J. I., Cash, T. F., Veale, D., Neziroglu, F., Soll, E. A., Garner, D. M., . . . & Phillips, K. A. (2009). Multidimensional body image comparisons among patients with eating disorders, body dysmorphic disorder, and clinical controls: A multisite study. Body Image, 6, 155–163. http://dx.doi.org/10.1016/j.bodyim.2009.03.001 Jakatdar, T. A., Cash, T. F., & Engle, E. K. (2006). Body-image thought processes: The development and initial validation of the Assessment of Body-Image Cognitive Distortions. Body Image, 3, 325–333. http://dx.doi.org/10.1016/j.bodyim.2006. 09.001 Joiner, T. E., Jr., Wonderlich, S. A., Metalsky, G. I., & Schmidt, N. B. (1995). Body dissatisfaction: A feature of bulimia, depression, or both? Journal of Social and Clinical Psychology, 14, 339–355. http://dx.doi.org/10.1521/jscp.1995.14.4.339 Keel, P. K., Mitchell, J. E., Davis, T. L., & Crow, S. J. (2001). Relationship between depression and body dissatisfaction in women diagnosed with bulimia nervosa. International Journal of Eating Disorders, 30, 48–56. http://dx.doi.org/10.1002/ eat.1053 Keller, C. S., & Cantue, A. (2008). Camina por Salud: Walking in Mexican-American women. Applied Nursing Research, 21, 110–113. http://dx.doi.org/10.1016/j.apnr. 2006.12.003 Kessler, R. C., Berglund, P., Demler, O., Jin, R., Koretz, D., Merikangas, K. R., . . . & Wang, P. S. (2003). The epidemiology of major depressive disorder: Results from the National Comorbidity Survey Replication (NCS-R). JAMA, 289, 3095–3105. http:// dx.doi.org/10.1001/jama.289.23.3095 Kiernan, M., King, A. C., Kraemer, H. C., Stefanick, M. L., & Killen, J. D. (1998). Characteristics of successful and unsuccessful dieters: An application of signal detection methodology. Annals of Behavioral Medicine, 20, 1–6. http://dx.doi.org/10.1007/ BF02893802 Kirkpatrick, S. I., Dodd, K. W., Reedy, J., & Krebs-Smith, S. M. (2012). Income and race/ethnicity are associated with adherence to food-based dietary guidance among US adults and children. Journal of the Academy of Nutrition and Dietetics, 112, 624–635. http://dx.doi.org/10.1016/j.jand.2011.11.012 Kruger, J., Lee, C. D., Ainsworth, B. E., & Macera, C. A. (2008). Body size satisfaction and physical activity levels among men and women. Obesity, 16, 1976–1979. http://dx.doi.org/10.1038/oby.2008.311 Lehnert, T., Sonntag, D., Konnopka, A., Riedel-Heller, S., & König, H. H. (2013). Economic costs of overweight and obesity. Best Practice & Research Clinical Endocrinology and Metabolism, 27, 105–115. http://dx.doi.org/10.1016/j.beem. 2013.01.002 Lemstra, M., Bird, Y., Nwankwo, C., Rogers, M., & Moraros, J. (2016). Weight loss intervention adherence and factors promoting adherence: a meta-analysis. Patient Preference and Adherence, 10, 1547–1599. http://dx.doi.org/10.2147/PPA. S103649 Lewinsohn, P. M., Biglan, A., & Zeiss, A. M. (1976). Behavioral treatment of depression. In P. Davidson (Ed.), Behaviour management of anxiety, depression and pain (pp. 91–146). New York: Brunner/Mazel. Lindberg, N. M., & Stevens, V. J. (2007). Review: Weight-loss interventions with Hispanic populations. Ethnicity & Disease, 17, 397–402. Lindberg, N. M., Stevens, V. J., Vega-López, S., Kauffman, T. L., Calderón, M. R., & Cervantes, M. A. (2012). A weight-loss intervention program designed for Mexican–American women: Cultural adaptations and results. Journal of Immigrant and Minority Health, 14, 1030–1039. http://dx.doi.org/10.1007/s10903012-9616-4 Little, R. J., & Rubin, D. B. (2002). Statistical analysis with missing data. Hoboken, NJ: John Wiley & Sons. Lowe, M. R., Doshi, S. D., Katterman, S. N., & Feig, E. H. (2013). Dieting and restrained eating as prospective predictors of weight gain. Frontiers in Psychology, 4 http:// dx.doi.org/10.3389/fpsyg.2013.00577 Luppino, F. S., de Wit, L. M., Bouvy, P. F., Stijnen, T., Cuijpers, P., Penninx, B. W., & Zitman, F. G. (2010). Overweight, obesity, and depression: A systematic review and meta-analysis of longitudinal studies. Archives of General Psychiatry, 67, 220–229. http://dx.doi.org/10.1001/archgenpsychiatry.2010.2 McKellar, J. D., Humphreys, K., & Piette, J. D. (2004). Depression increases diabetes symptoms by complicating patients’ self-care adherence. The Diabetes Educator, 30, 485–492. Mitchell, B. D., Stern, M. P., Haffner, S. M., Hazuda, H. P., & Patterson, J. K. (1990). Risk factors for cardiovascular mortality in Mexican American and non-Hispanic White: The San Antonio Heart Study. American Journal of Epidemiology, 131, 423–433. http://dx.doi.org/10.1093/oxfordjournals.aje.a115517 Moroshko, I., Brennan, L., & O’Brien, P. (2011). Predictors of dropout in weight loss interventions: A systematic review of the literature. Obesity Reviews, 12, 912–934. http://dx.doi.org/10.1111/j.1467-789X.2011.00915.x Muthén, L. K., & Muthén, L. (2014). Mplus [computer software]. Los Angeles, CA: Muthén & Muthén. National Institutes of Health. (2000). National Heart, Lung and Blood Institute, North American Association for the Study of Obesity: The practical guide: Identification,

J.L. Austin et al. / Body Image 23 (2017) 155–161 evaluation, and treatment of overweight and obesity in adults. Bethesda, MD: National Institutes of Health. Ogden, C. L., Carroll, M. D., Fryar, C. D., & Flegal, K. M. (2015). Prevalence of obesity among adults and youth: United States, 2011–2014. NCHS Data Brief, 219, 1–8. Parikh, P., Simon, E. P., Fei, K., Looker, H., Goytia, C., & Horowitz, C. R. (2010). Results of a pilot diabetes prevention intervention in East Harlem, New York City: Project HEED. American Journal of Public Health, 100, S232–S239. http://dx.doi.org/10. 2105/AJPH.2009.170910 Pekmezi, D. W., Neighbors, C. J., Lee, C. S., Gans, K. M., Bock, B. C., Morrow, K. M., . . . & Marcus, B. H. (2009). A culturally adapted physical activity intervention for Latinas: A randomized controlled trial. American Journal of Preventive Medicine, 37, 495–500. http://dx.doi.org/10.1016/j.amepre.2009.08.023 Perez, L. G., Arredondo, E. M., Elder, J. P., Barquera, S., Nagle, B., & Holub, C. K. (2013). Evidence-based obesity treatment interventions for Latino adults in the US: A systematic review. American Journal of Preventive Medicine, 44, 550–560. http:// dx.doi.org/10.1016/j.amepre.2009.08.023 Poston, C., Walker, S., Haddock, C. K., Olvera, N. E., Suminski, R. R., Reeves, R. S., . . . & Foreyt, J. P. (2001). Evaluation of a culturally appropriate intervention to increase physical activity. American Journal of Health Behavior, 25, 396–406. http://dx.doi. org/10.5993/AJHB.25.4.5 Ramirez, E. M., & Rosen, J. C. (2001). A comparison of weight control and weight control plus body image therapy for obese men and women. Journal of Consulting and Clinical Psychology, 69, 440–446. http://dx.doi.org/10.1037//0022-006X.69. 3.440 Rocha-Goldberg, M. D. P., Corsino, L., Batch, B., Voils, C. I., Thorpe, C. T., Bosworth, H. B., & Svetkey, L. P. (2010). Hypertension Improvement Project (HIP) Latino: Results of a pilot study of lifestyle intervention for lowering blood pressure in Latino adults. Ethnicity & Health, 15, 269–282. http://dx.doi.org/10.1080/ 13557851003674997 Rosen, J. C. (1996). Improving body image in obesity. In J. K. Thompson (Ed.), Body image, eating disorders, and obesity (pp. 425–440). Washington, DC: American Psychological Association. Schwartz, M. B., & Brownell, K. D. (2004). Obesity and body image. Body Image, 1, 43–56. http://dx.doi.org/10.1016/S1740-1445(03)00007-X Shaw, H., Ramirez, L., Trost, A., Randall, P., & Stice, E. (2004). Body image and eating disturbances across ethnic groups: More similarities than differences. Psychology of Addictive Behaviors, 18, 12–18. http://dx.doi.org/10.1037/0893-164X.18. 1.12 Stice, E. (2002). Risk and maintenance factors for eating pathology: A meta-analytic review. Psychological Bulletin, 128, 825–848. http://dx.doi.org/10.1037/00332909.128.5.825 Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Boston: Pearson. Teixeira, P. J., Going, S. B., Houtkooper, L. B., Cussler, E. C., Martin, C. J., Metcalfe, L. L., . . . & Lohman, T. G. (2002). Weight loss readiness in middle-aged women: Psychosocial predictors of success for behavioral weight reduction. Journal of Behavioral Medicine, 25, 499–523. http://dx.doi.org/10.1023/A:1020687832448 Teixeira, P. J., Going, S. B., Houtkooper, L. B., Cussler, E. C., Metcalfe, L. L., Blew, R. M., . . . & Lohman, T. G. (2006). Exercise motivation, eating, and body image variables as predictors of weight control. Medicine & Science in Sports & Exercise, 38, 179–188. http://dx.doi.org/10.1249/01.mss.0000180906.10445.8d Teixeira, P. J., Going, S. B., Sardinha, L. B., & Lohman, T. G. (2005). A review of psychosocial pre-treatment predictors of weight control. Obesity Reviews, 6, 43–65. http://dx.doi.org/10.1111/j.1467-789X.2005.00166.x Teixeira, P. J., Palmeira, A. L., Branco, T. L., Martins, S. S., Minderico, C. S., Barata, J. T., . . . & Sardinha, L. B. (2004). Who will lose weight? A reexamination of predictors

161

of weight loss in women. International Journal of Behavioral Nutrition and Physical Activity, 1 http://dx.doi.org/10.1186/1479-5868-1-12 Traverso, A., Ravera, G., Lagattolla, V., Testa, S., & Adami, G. F. (2000). Weight loss after dieting with behavioral modification for obesity: The predicting efficiency of some psychometric data. Eating and Weight Disorders-Studies on Anorexia, Bulimia and Obesity, 5, 102–107. http://dx.doi.org/10.1007/BF03327485 Wadden, T. A., Berkowitz, R. I., Sarwer, D. B., Prus-Wisniewski, R., & Steinberg, C. (2001). Benefits of lifestyle modification in the pharmacologic treatment of obesity. Archives of Internal Medicine, 161, 218–227. http://dx.doi.org/10.1001/ archinte.161.2.218 Wadden, T. A., Butryn, M. L., & Byrne, K. J. (2004). Efficacy of lifestyle modification for long-term weight control. Obesity Research, 12, 151S–162S. http://dx.doi.org/10. 1038/oby.2004.282 Wadden, T. A., & Osei, S. (2002). The treatment of obesity: An overview. In T. A. Wadden & A. J. Stunkard (Eds.), Handbook of obesity treatment (pp. 229–248). New York: Guilford. Wadden, T. A., West, D. S., Neiberg, R. H., Wing, R. R., Ryan, D. H., Johnson, K. C., . . . & Vitolins, M. Z. (2009). One-year weight losses in the Look AHEAD study: Factors associated with success. Obesity, 17(4), 713–722. http://dx.doi.org/10.1038/oby. 2008.637 Wang, Y., & Beydoun, M. A. (2007). The obesity epidemic in the United States—Gender, age, socioeconomic, racial/ethnic, and geographic characteristics: A systematic review and meta-regression analysis. Epidemiologic Reviews, 29, 6–28. http://dx.doi.org/10.1093/epirev/mxm007 Wardle, J., Waller, J., & Rapoport, L. (2001). Body dissatisfaction and binge eating in obese women: The role of restraint and depression. Obesity, 9, 778–787. http:// dx.doi.org/10.1038/oby.2001.107 Warren, C. S., Cepeda-Benito, A., Gleaves, D. H., Moreno, S., Rodriguez, S., Fernandez, M. C., . . . & Pearson, C. A. (2008). English and Spanish versions of the Body Shape Questionnaire: Measurement equivalence across ethnicity and clinical status. International Journal of Eating Disorders, 41, 265–272. http://dx.doi.org/10.1002/ eat.20492 Weiss, E. C., Galuska, D. A., Khan, L. K., Gillespie, C., & Serdula, M. K. (2007). Weight regain in US adults who experienced substantial weight loss, 1999–2002. American Journal of Preventive Medicine, 33, 34–40. http://dx.doi.org/10.1016/j. amepre.2007.02.040 Wing, R. R., Phelan, S., & Tate, D. (2002). The role of adherence in mediating the relationship between depression and health outcomes. Journal of Psychosomatic Research, 53, 877–881. http://dx.doi.org/10.1016/S0022-3999(02)00315-X Yaemsiri, S., Slining, M. M., & Agarwal, S. K. (2011). Perceived weight status, overweight diagnosis, and weight control among US adults: The NHANES 2003–2008 Study. International Journal of Obesity, 35, 1063–1070. http://dx.doi.org/10.1038/ ijo.2010.229 Yang, L., & Colditz, G. A. (2015). Prevalence of overweight and obesity in the United States, 2007-2012. Journal of the American Medical Association: Internal Medicine, 175, 1412–1413. http://dx.doi.org/10.1001/jamainternmed.2015.2405 Zhao, G., Ford, E. S., Li, C., & Mokdad, A. H. (2008). Compliance with physical activity recommendations in US adults with diabetes. Diabetic Medicine, 25, 221–227. http://dx.doi.org/10.1111/j.1464-5491.2007.02332.x Ziegelstein, R. C., Fauerbach, J. A., Stevens, S. S., Romanelli, J., Richter, D. P., & Bush, D. E. (2000). Patients with depression are less likely to follow recommendations to reduce cardiac risk during recovery from a myocardial infarction. Archives of Internal Medicine, 160, 1818–1823. http://dx.doi.org/10.1001/archinte.160.12. 1818