Evaluating the efficacy of mindfulness and acceptance-based treatment components for weight loss: Protocol for a multiphase optimization strategy trial

Intraday relations between physical activity and energy intake among behavioral weight loss participants

OBJECTIVE

Weight loss results from a negative energy balance, when energy intake (EI) is less than energy expended, e.g., from physical activity (PA). However, PA may impact energy balance beyond energy expenditure alone, through indirect effects on eating behavior. Yet, no research has examined if engaging in PA-a central component of most weight loss programs-is associated with same-day EI among individuals with overweight/obesity pursuing weight loss.

METHOD

Adults (N = 101) with overweight/obesity in a weight loss program were prescribed a reduced-calorie diet and PA regimen (250 min of moderate-to-vigorous PA at midtreatment). For 3 weeks at midtreatment, PA and EI were measured via an accelerometer and self-monitoring app, respectively. Multilevel models examined within-person relations between PA and EI preceding PA ("pre-PA"), acutely following PA ("acute post-PA," the 2 hr following PA), in the time following the acute post-PA period ("remaining time in day"), and across entire PA days ("full-day"), relative to non-PA matched time periods.

RESULTS

EI was higher in the pre-PA and acute post-PA periods. There were no reliable differences in EI during the remaining time in day nor across the full-day on PA days versus within-subject matched non-PA days. There also was insufficient evidence to suggest EI pre-PA, post-PA, or across entire PA days, relative to non-PA matched time periods, was associated with percent weight change.

CONCLUSIONS

Findings suggest that engaging in PA was associated with different within-person EI patterns compared to non-PA days, though there was little evidence to support that these patterns relate to weight change. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Meditation for the primary and secondary prevention of cardiovascular disease

BACKGROUND

Interventions incorporating meditation to address stress, anxiety, and depression, and improve self-management, are becoming popular for many health conditions. Stress is a risk factor for cardiovascular disease (CVD) and clusters with other modifiable behavioural risk factors, such as smoking. Meditation may therefore be a useful CVD prevention strategy.

OBJECTIVES

To determine the effectiveness of meditation, primarily mindfulness-based interventions (MBIs) and transcendental meditation (TM), for the primary and secondary prevention of CVD.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, three other databases, and two trials registers on 14 November 2021, together with reference checking, citation searching, and contact with study authors to identify additional studies.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) of 12 weeks or more in adults at high risk of CVD and those with established CVD. We explored four comparisons: MBIs versus active comparators (alternative interventions); MBIs versus non-active comparators (no intervention, wait list, usual care); TM versus active comparators; TM versus non-active comparators.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane methods. Our primary outcomes were CVD clinical events (e.g. cardiovascular mortality), blood pressure, measures of psychological distress and well-being, and adverse events. Secondary outcomes included other CVD risk factors (e.g. blood lipid levels), quality of life, and coping abilities. We used GRADE to assess the certainty of evidence.

MAIN RESULTS

We included 81 RCTs (6971 participants), with most studies at unclear risk of bias. MBIs versus active comparators (29 RCTs, 2883 participants) Systolic (SBP) and diastolic (DBP) blood pressure were reported in six trials (388 participants) where heterogeneity was considerable (SBP: MD -6.08 mmHg, 95% CI -12.79 to 0.63, I2 = 88%; DBP: MD -5.18 mmHg, 95% CI -10.65 to 0.29, I2 = 91%; both outcomes based on low-certainty evidence). There was little or no effect of MBIs on anxiety (SMD -0.06 units, 95% CI -0.25 to 0.13; I2 = 0%; 9 trials, 438 participants; moderate-certainty evidence), or depression (SMD 0.08 units, 95% CI -0.08 to 0.24; I2 = 0%; 11 trials, 595 participants; moderate-certainty evidence). Perceived stress was reduced with MBIs (SMD -0.24 units, 95% CI -0.45 to -0.03; I2 = 0%; P = 0.03; 6 trials, 357 participants; moderate-certainty evidence). There was little to no effect on well-being (SMD -0.18 units, 95% CI -0.67 to 0.32; 1 trial, 63 participants; low-certainty evidence). There was little to no effect on smoking cessation (RR 1.45, 95% CI 0.78 to 2.68; I2 = 79%; 6 trials, 1087 participants; low-certainty evidence). None of the trials reported CVD clinical events or adverse events. MBIs versus non-active comparators (38 RCTs, 2905 participants) Clinical events were reported in one trial (110 participants), providing very low-certainty evidence (RR 0.94, 95% CI 0.37 to 2.42). SBP and DBP were reduced in nine trials (379 participants) but heterogeneity was substantial (SBP: MD -6.62 mmHg, 95% CI -13.15 to -0.1, I2 = 87%; DBP: MD -3.35 mmHg, 95% CI -5.86 to -0.85, I2 = 61%; both outcomes based on low-certainty evidence). There was low-certainty evidence of reductions in anxiety (SMD -0.78 units, 95% CI -1.09 to -0.41; I2 = 61%; 9 trials, 533 participants; low-certainty evidence), depression (SMD -0.66 units, 95% CI -0.91 to -0.41; I2 = 67%; 15 trials, 912 participants; low-certainty evidence) and perceived stress (SMD -0.59 units, 95% CI -0.89 to -0.29; I2 = 70%; 11 trials, 708 participants; low-certainty evidence) but heterogeneity was substantial. Well-being increased (SMD 0.5 units, 95% CI 0.09 to 0.91; I2 = 47%; 2 trials, 198 participants; moderate-certainty evidence). There was little to no effect on smoking cessation (RR 1.36, 95% CI 0.86 to 2.13; I2 = 0%; 2 trials, 453 participants; low-certainty evidence). One small study (18 participants) reported two adverse events in the MBI group, which were not regarded as serious by the study investigators (RR 5.0, 95% CI 0.27 to 91.52; low-certainty evidence). No subgroup effects were seen for SBP, DBP, anxiety, depression, or perceived stress by primary and secondary prevention. TM versus active comparators (8 RCTs, 830 participants) Clinical events were reported in one trial (201 participants) based on low-certainty evidence (RR 0.91, 95% CI 0.56 to 1.49). SBP was reduced (MD -2.33 mmHg, 95% CI -3.99 to -0.68; I2 = 2%; 8 trials, 774 participants; moderate-certainty evidence), with an uncertain effect on DBP (MD -1.15 mmHg, 95% CI -2.85 to 0.55; I2 = 53%; low-certainty evidence). There was little or no effect on anxiety (SMD 0.06 units, 95% CI -0.22 to 0.33; I2 = 0%; 3 trials, 200 participants; low-certainty evidence), depression (SMD -0.12 units, 95% CI -0.31 to 0.07; I2 = 0%; 5 trials, 421 participants; moderate-certainty evidence), or perceived stress (SMD 0.04 units, 95% CI -0.49 to 0.57; I2 = 70%; 3 trials, 194 participants; very low-certainty evidence). None of the trials reported adverse events or smoking rates. No subgroup effects were seen for SBP or DBP by primary and secondary prevention. TM versus non-active comparators (2 RCTs, 186 participants) Two trials (139 participants) reported blood pressure, where reductions were seen in SBP (MD -6.34 mmHg, 95% CI -9.86 to -2.81; I2 = 0%; low-certainty evidence) and DBP (MD -5.13 mmHg, 95% CI -9.07 to -1.19; I2 = 18%; very low-certainty evidence). One trial (112 participants) reported anxiety and depression and found reductions in both (anxiety SMD -0.71 units, 95% CI -1.09 to -0.32; depression SMD -0.48 units, 95% CI -0.86 to -0.11; low-certainty evidence). None of the trials reported CVD clinical events, adverse events, or smoking rates.

AUTHORS' CONCLUSIONS

Despite the large number of studies included in the review, heterogeneity was substantial for many of the outcomes, which reduced the certainty of our findings. We attempted to address this by presenting four main comparisons of MBIs or TM versus active or inactive comparators, and by subgroup analyses according to primary or secondary prevention, where there were sufficient studies. The majority of studies were small and there was unclear risk of bias for most domains. Overall, we found very little information on the effects of meditation on CVD clinical endpoints, and limited information on blood pressure and psychological outcomes, for people at risk of or with established CVD. This is a very active area of research as shown by the large number of ongoing studies, with some having been completed at the time of writing this review. The status of all ongoing studies will be formally assessed and incorporated in further updates.

A randomized trial examining the effect of yoga on dietary lapses and lapse triggers following behavioral weight loss treatment

Background

Dietary lapses can hinder weight loss and yoga can improve self-regulation, which may protect against lapses. This study examined the effect of yoga on dietary lapses, potential lapse triggers (e.g., affective states, cravings, dietary temptations), and reasons for initiating eating following weight loss treatment.

Methods

Sixty women with overweight/obesity (34.3 ± 3.9 kg/m2) were randomized to a 12 week yoga intervention (2x/week; YOGA) or contact-matched control (cooking/nutrition classes; CON) following a 12-week behavioral weight loss program. Participants responded to smartphone surveys (5x/day) over a 10-day period at baseline, 12, and 24 weeks to assess lapses and triggers.

Results

At 24 weeks, YOGA and CON differed on several types of lapses (i.e., less eating past full, eating more than usual, loss of control when eating, self-identified overeating, difficulty stopping eating in YOGA), and YOGA was less likely to eat to feel better or in response to stress (ps < 0.05). YOGA also reported less stress and anxiety and more positive affect (ps < 0.01); dietary temptations and cravings did not differ from CON.

Conclusion

Yoga resulted in fewer dietary lapses and improved affect among women with overweight/obesity following weight loss. While preliminary, findings suggest that yoga should be considered as a potential component of weight loss treatment to target dietary lapses.

A systematic review of ecological momentary assessment studies of appetite and affect in the experience of temptations and lapses during weight loss dieting

Dietary temptations and lapses challenge control over eating and act as barriers toward successful weight loss. These are difficult to assess in laboratory settings or with retrospective measures as they occur momentarily and driven by the current environment. A better understanding of how these experiences unfold within real-world dieting attempts could help inform strategies to increase the capacity to cope with the changes in appetitive and affective factors that surround these experiences. We performed a narrative synthesis on the empirical evidence of appetitive and affective outcomes measured using ecological momentary assessment (EMA) during dieting in individuals with obesity and their association with dietary temptations and lapses. A search of three databases (Scopus, Medline, and PsycInfo) identified 10 studies. Within-person changes in appetite and affect accompany temptations and lapses and are observable in the moments precipitating a lapse. Lapsing in response to these may be mediated through the strength of a temptation. Negative abstinence-violation effects occur following a lapse, which negatively impact self-attitudes. Engagement in coping strategies during temptations is effective for preventing lapses. These findings indicate that monitoring changes in sensations during dieting could help identify the crucial moments when coping strategies are most effective for aiding with dietary adherence.

Sharing digital self-monitoring data with others to enhance long-term weight loss: A randomized controlled trial

BACKGROUND

Participants in behavioral weight loss (BWL) programs increasingly use digital tools to self-monitor weight, physical activity, and dietary intake. Data collected with these tools can be systematically shared with other parties in ways that might support behavior change.

METHODS

Adults age 18 to 70 with overweight/obesity (BMI 27-50 kg/m2) will enroll in a remotely delivered, 24-month BWL program designed to produce and maintain a 10% weight loss. Participants will be asked to use a wireless body weight scale, wearable activity sensor, and dietary intake app daily. All participants will receive individual and group counseling, engage in text messaging with members of their group, and appoint a friend or family member to serve in a support role. A 2x2x2 factorial design will test the effects of three types of data sharing partnerships: 1) Coach Share: The behavioral coach will regularly view digital self-monitoring data and address data observations. 2) Group Share: Participants will view each other's self-monitoring data in small-group text messages. 3) Friend/Family Share: A friend or family member will view the participant's data via automated message. The primary outcome is weight loss at 24 months. Mediators and moderators of intervention effects will be tested.

CONCLUSION

This study will provide a clear indication of whether data sharing can improve long-term weight loss. This study will be the first to discern the mechanisms of action through which each type of data sharing may be beneficial, and elucidate conditions under which the benefits of data sharing may be maximized.

The role of everyday activities on likelihood of dietary lapse: an ecological momentary assessment study

Developing a more nuanced understanding of factors predicting risk of dietary lapse (i.e., instances of non-adherence to a reduced calorie diet) is important, because dietary lapses contribute to suboptimal weight outcomes. The study investigated, for the first time, how various everyday activities affected likelihood of dietary lapses at two timescales-both in-the-moment, and in the hours after engaging in an activity. Participants (N = 107) with overweight/obesity in a behavioral weight loss program completed ecological momentary assessment surveys on dietary adherence and daily activities for 3 weeks at mid-treatment. Generalized estimating equations revealed that socializing predicted greater concurrent lapse risk, while work/school, doing chores, cooking, or practicing a spiritual activity/prayer/meditation were associated with reduced lapse risk. In terms of subsequent effects, cooking and indoor hobbies were associated with greater lapse risk in the next few hours, whereas spiritual activity/meditation was associated with reduced risk. Certain activities may have affected concurrent and subsequent lapse risk due to: their influence on the presence of tempting food, the compatibility of engaging in the activity and eating simultaneously, and the reward reaped from the activity (potentially reducing desire for food-related reward). Findings speak to the importance of attending to the timescale of relationships between activities and lapses, which has clinical implications for providing nuanced and optimally timed interventions for overweight/obesity.

Testing reward processing models of obesity using in-the-moment assessments of subjective enjoyment of food and non-food activities

OBJECTIVE

Although altered reward processing is proposed to play a key role in obesity maintenance, the role of food enjoyment and enjoyment of non-food naturally rewarding activities ("non-food enjoyment") in obesity maintenance remains unknown. This study examined how food and non-food enjoyment were associated with baseline body mass index (BMI) and weight loss (WL) following year-long behavioral WL treatment.

METHODS

At baseline, participants (MAge = 51.81; 73.8 % White, N = 279) with overweight/obesity completed a 7-day ecological momentary assessment (EMA) protocol inquiring about pleasure/enjoyment derived from eating and non-food activities over the past few hours. Participants also completed retrospective self-report measures of food/non-food enjoyment. With linear regressions, associations between EMA food/non-food enjoyment and BMI and post-treatment WL were examined. Race was included as a covariate.

RESULTS

EMA and retrospective food/non-food enjoyment measures had modest concordance, providing preliminary psychometric support for the EMA measures. Partially consistent with hypotheses, greater EMA food enjoyment was associated with lower BMI (B = -1.03, p = .01) and with greater WL, though the latter association was not statistically significant (B = 1.15, p = .07). Exploratory analyses suggested that race was associated with food enjoyment (non-White participants had greater food enjoyment than White participants, d = 0.81, p = .005), and that race may have affected associations between food enjoyment and weight outcomes. Associations between non-food enjoyment and weight outcomes were small and nonsignificant (ps > .93).

CONCLUSIONS

Results suggest enjoyment from food, but not from non-food domains, is associated with weight outcomes.

Optimizing an mHealth Intervention to Change Food Purchasing Behaviors for Cancer Prevention: Protocol for a Pilot Randomized Controlled Trial

BACKGROUND

Dietary intake is a powerful modifiable factor that influences cancer risk; however, most US adults do not adhere to dietary guidelines for cancer prevention. One promising pathway for improving dietary adherence is targeting grocery shopping habits. Interventions might facilitate healthy grocery choices, with a combination of mHealth and traditional methods, by promoting the salience of dietary goals while shopping, enhancing motivation to make dietary changes, and increasing household support for healthy food purchasing.

OBJECTIVE

This pilot study will assess feasibility and acceptability of intervention components designed to improve adherence to dietary guidelines for cancer prevention (preliminary aim). The primary aim of the study is to quantify the effect of each intervention component, individually and in combination, on dietary intake (primary aim) and grocery store food purchases (exploratory aim). Mediation analyses will be conducted to understand the mechanisms of action (goal salience, motivation, and household support-secondary aims). The overarching goal is to optimize an mHealth intervention to be tested in a future fully powered clinical trial.

METHODS

The study enrolled adults (N=62) with low adherence to dietary recommendations for cancer prevention. In a 20-week program, all participants attend a nutrition education workshop and receive weekly educational messages through an app. A factorial design is used to test 4 intervention components: (1) location-triggered messages: educational messages are delivered when arriving at grocery stores; (2) reflections on the benefits of change: content is added to messages to encourage reflection on anticipated benefits of healthy eating, and participants attend an additional workshop session and 3 coach calls on this topic; (3) coach monitoring: food purchases are monitored digitally by a coach who sends personalized weekly app messages and conducts 3 coaching calls that focus on feedback about purchases; and (4) household support: another adult in the household receives messages designed to elicit support for healthy food purchasing, and support is addressed in 3 coach calls and an extra workshop session attended by the index participant and household member. Assessments are completed at weeks 0, 10, and 20 using self-report measures, as well as objective capture of grocery data from the point of purchase using store loyalty accounts.

RESULTS

The National Cancer Institute funded this study (R21CA252933) on July 7, 2020. Participant recruitment began in the spring of 2021 and concluded with the successful enrollment of 62 participants. Data collection is expected to be completed in the summer of 2022, and results are expected to be disseminated in the summer of 2023.

CONCLUSIONS

The results of this study will inform the development of scalable interventions to lower cancer risk via changes in dietary intake.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04947150; https://clinicaltrials.gov/ct2/show/NCT04947150.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/39669.