Changes in body weight and food choice in those attempting smoking cessation: a cluster randomised controlled trial

Diet quality as assessed by the healthy eating index-2020 among different smoking status: an analysis of national health and nutrition examination survey (NHANES) data from 2005 to 2018

BACKGROUND

Combining smoking with poor eating habits significantly elevates the risk of chronic illnesses and early death. Understanding of how dietary quality shifts post-smoking cessation remains limited. The objective of this study is to examine dietary quality - using Healthy Eating Index (HEI - 2020) and its 13 components, among current, former, and never smokers, and particularly the impact of quitting and the duration of cessation on dietary habits.

METHODS

A cross-sectional analysis of 31,569 adults from the National Health and Nutrition Examination Survey (NHANES) 2005-2018 was conducted. Dietary quality was assessed using HEI-2020 scores, which were determined by NIH developed - simple HEI scoring algorithm per person. Smoking status was categorized into current, former, and never smokers, with further subdivisions for current (heavy/light smokers) and former smokers (duration post-cessation). Descriptive analysis and multiple regression models weighted to represent the US population were performed.

RESULTS

The current smoking rate was 19.4%, with a higher prevalence in males (22.5%) than females (17.5%). Current smokers reported statistically significantly lower HEI total score than both former and never smokers. Former smokers exhibited HEI scores similar to those of never smokers. The adjusted HEI total scores for current, former, and never smokers were 49.2, 54.0, and 53.3, respectively, with a statistically significant difference (p < 0.001). Moreover, light smokers had better total HEI score than heavy smokers (46.8 vs. 50.8, p < 0.001, respectively), but former and never smokers scored even higher. Quitting smoking immediately improved dietary quality, with former smokers reaching the dietary levels of never smokers within 5-10 years (53.8 vs. 53.3, p > 0.05, respectively). Compared to current smokers, former smokers tended to consume more beneficial foods (e.g., fruits, vegetables, greens and beans, whole grains, proteins, and fatty acids), while also consuming more sodium and less added sugar.

CONCLUSIONS

Current smokers, particularly heavy smokers, exhibit poorer dietary habits than former and never smokers. The dietary quality of former smokers aligns with never smokers over time, highlighting the positive impact of smoking cessation on diet. This has implications for reducing chronic disease risks associated with poor diet and smoking.

Effectiveness of including weight management in smoking cessation treatments: A meta-analysis of behavioral interventions

INTRODUCTION

The potential of weight gain after smoking cessation reduces the incentive to quit. This meta-analysis examines the efficacy of behavioral interventions for smoking cessation that also address post-cessation weight gain.

METHODS

Medline, Web of Science, PsycINFO, and the Cochrane Central Register of Controlled Trials were searched for randomized controlled trials on behavioral treatments targeting both health outcomes. Six separate meta-analyses were undertaken to assess treatment efficacy on smoking abstinence and weight outcomes at end of treatment (EOT), short-term, and long-term follow-up. Individual and treatment moderators were examined as well as methodological quality and publication bias of studies.

RESULTS

A total of 28 studies were included in the meta-analysis. There was a statistically significant positive impact of treatments addressing both targets on smoking outcomes at EOT (RR = 1.279, 95% CI: 1.096, 1.492, p = .002), but not at follow-ups. Age impacted on EOT abstinence rates Q (1) = 4.960, p = .026) while increasing the number of sessions significantly improved EOT abstinence rates (p = .020). There was no statistically significant impact of these treatments on weight at EOT (Hedges' g = -0.015, 95% CI: -.164, 0.135, p = .849) or follow-ups (short term: Hedges' g = 0.055, 95% CI: -0.060, 0.170, p = .347; long term: Hedges' g = -0.320, 95% CI: -.965, 0.325, p = .331). There were minimal impacts of publication bias, mostly related to sample size, meaning studies including small sample sizes revealed larger effect sizes on abstinence at EOT.

DISCUSSION

Addressing post-cessation weight management in treatments for smoking cessation significantly enhances tobacco abstinence at EOT though it was not found to have a lasting impact after treatment.

Effects of Abstinence Self-Efficacy and Outcome Expectancies of Tobacco Smoking on the Desire to Quit Among Saudi Women: A Cross-Sectional Mediation Analysis

Background

Smoking is one of the major preventable causes of morbidity and mortality and has been associated with numerous illnesses. While smoking is increasing among Saudi women, the characteristics of smoking behavior related to abstinence self-efficacy, which is a belief regarding one’s ability to successfully resist performing a behavior, and outcome expectancies, meaning the anticipated consequences of performing a behavior, are unknown. Therefore, this study aimed to test whether abstinence self-efficacy mediated the relationship between tobacco smoking outcome expectancies and the desire to quit tobacco among Saudi women who smoke.

Methods

This cross-sectional study collected a sample of 211 Saudi women who smoked tobacco, including cigarettes and shisha. A self-administered questionnaire was used to examine several variables, including abstinence self-efficacy, outcome expectancies, and desire to quit tobacco smoking. Mediational path analysis was used to answer the research question. Indirect effects were estimated through a bootstrapping of 10,000.

Results

All 4 constructs of outcome expectancies (negative consequences, positive reinforcement, negative reinforcement, and appetite/weight control) were associated with lower abstinence self-efficacy and desire to quit tobacco smoking. In the mediation analysis, the indirect effect of negative consequences (standardized beta = −.013, SE = .008, 95% CI [−.030, −.001]), negative reinforcement (standardized beta = −.012, SE = .006, 95% CI [−.025, −.001]), and appetite/weight control (standardized beta = −.008, SE = .006, 95% CI [−.022, −.001]) through abstinence self-efficacy were significant, suggesting mediation in the relationship between outcome expectancies and desire to quit tobacco smoking.

Conclusion

Cognitive mechanisms that may explain the desire to quit tobacco smoking among Saudi women were identified. Although future longitudinal studies are required to determine relationships prospectively, targeted interventions that correct tobacco smoking outcome expectancies and boost abstinence self-efficacy skills may reduce tobacco smoking among Saudi women.

Interventions for preventing weight gain after smoking cessation

BACKGROUND

Most people who stop smoking gain weight. This can discourage some people from making a quit attempt and risks offsetting some, but not all, of the health advantages of quitting. Interventions to prevent weight gain could improve health outcomes, but there is a concern that they may undermine quitting.

OBJECTIVES

To systematically review the effects of: (1) interventions targeting post-cessation weight gain on weight change and smoking cessation (referred to as 'Part 1') and (2) interventions designed to aid smoking cessation that plausibly affect post-cessation weight gain (referred to as 'Part 2').

SEARCH METHODS

Part 1 - We searched the Cochrane Tobacco Addiction Group's Specialized Register and CENTRAL; latest search 16 October 2020. Part 2 - We searched included studies in the following 'parent' Cochrane reviews: nicotine replacement therapy (NRT), antidepressants, nicotine receptor partial agonists, e-cigarettes, and exercise interventions for smoking cessation published in Issue 10, 2020 of the Cochrane Library. We updated register searches for the review of nicotine receptor partial agonists.

SELECTION CRITERIA

Part 1 - trials of interventions that targeted post-cessation weight gain and had measured weight at any follow-up point or smoking cessation, or both, six or more months after quit day. Part 2 - trials included in the selected parent Cochrane reviews reporting weight change at any time point.

DATA COLLECTION AND ANALYSIS

Screening and data extraction followed standard Cochrane methods. Change in weight was expressed as difference in weight change from baseline to follow-up between trial arms and was reported only in people abstinent from smoking. Abstinence from smoking was expressed as a risk ratio (RR). Where appropriate, we performed meta-analysis using the inverse variance method for weight, and Mantel-Haenszel method for smoking.

MAIN RESULTS

Part 1: We include 37 completed studies; 21 are new to this update. We judged five studies to be at low risk of bias, 17 to be at unclear risk and the remainder at high risk.  An intermittent very low calorie diet (VLCD) comprising full meal replacement provided free of charge and accompanied by intensive dietitian support significantly reduced weight gain at end of treatment compared with education on how to avoid weight gain (mean difference (MD) -3.70 kg, 95% confidence interval (CI) -4.82 to -2.58; 1 study, 121 participants), but there was no evidence of benefit at 12 months (MD -1.30 kg, 95% CI -3.49 to 0.89; 1 study, 62 participants). The VLCD increased the chances of abstinence at 12 months (RR 1.73, 95% CI 1.10 to 2.73; 1 study, 287 participants). However, a second study  found that no-one completed the VLCD intervention or achieved abstinence. Interventions aimed at increasing acceptance of weight gain reported mixed effects at end of treatment, 6 months and 12 months with confidence intervals including both increases and decreases in weight gain compared with no advice or health education. Due to high heterogeneity, we did not combine the data. These interventions increased quit rates at 6 months (RR 1.42, 95% CI 1.03 to 1.96; 4 studies, 619 participants; I² = 21%), but there was no evidence at 12 months (RR 1.25, 95% CI 0.76 to 2.06; 2 studies, 496 participants; I² = 26%). Some pharmacological interventions tested for limiting post-cessation weight gain (PCWG) reduced weight gain at the end of treatment (dexfenfluramine, phenylpropanolamine, naltrexone). The effects of ephedrine and caffeine combined, lorcaserin, and chromium were too imprecise to give useful estimates of treatment effects. There was very low-certainty evidence that personalized weight management support reduced weight gain at end of treatment (MD -1.11 kg, 95% CI -1.93 to -0.29; 3 studies, 121 participants; I² = 0%), but no evidence in the longer-term 12 months (MD -0.44 kg, 95% CI -2.34 to 1.46; 4 studies, 530 participants; I² = 41%). There was low to very low-certainty evidence that detailed weight management education without personalized assessment, planning and feedback did not reduce weight gain and may have reduced smoking cessation rates (12 months: MD -0.21 kg, 95% CI -2.28 to 1.86; 2 studies, 61 participants; I² = 0%; RR for smoking cessation 0.66, 95% CI 0.48 to 0.90; 2 studies, 522 participants; I² = 0%). Part 2: We include 83 completed studies, 27 of which are new to this update. There was low certainty that exercise interventions led to minimal or no weight reduction compared with standard care at end of treatment (MD -0.25 kg, 95% CI -0.78 to 0.29; 4 studies, 404 participants; I² = 0%). However, weight was reduced at 12 months (MD -2.07 kg, 95% CI -3.78 to -0.36; 3 studies, 182 participants; I² = 0%). Both bupropion and fluoxetine limited weight gain at end of treatment (bupropion MD -1.01 kg, 95% CI -1.35 to -0.67; 10 studies, 1098 participants; I² = 3%); (fluoxetine MD -1.01 kg, 95% CI -1.49 to -0.53; 2 studies, 144 participants; I² = 38%; low- and very low-certainty evidence, respectively). There was no evidence of benefit at 12 months for bupropion, but estimates were imprecise (bupropion MD -0.26 kg, 95% CI -1.31 to 0.78; 7 studies, 471 participants; I² = 0%). No studies of fluoxetine provided data at 12 months. There was moderate-certainty that NRT reduced weight at end of treatment (MD -0.52 kg, 95% CI -0.99 to -0.05; 21 studies, 2784 participants; I² = 81%) and moderate-certainty that the effect may be similar at 12 months (MD -0.37 kg, 95% CI -0.86 to 0.11; 17 studies, 1463 participants; I² = 0%), although the estimates are too imprecise to assess long-term benefit. There was mixed evidence of the effect of varenicline on weight, with high-certainty evidence that weight change was very modestly lower at the end of treatment (MD -0.23 kg, 95% CI -0.53 to 0.06; 14 studies, 2566 participants; I² = 32%); a low-certainty estimate gave an imprecise estimate of higher weight at 12 months (MD 1.05 kg, 95% CI -0.58 to 2.69; 3 studies, 237 participants; I² = 0%).

AUTHORS' CONCLUSIONS

Overall, there is no intervention for which there is moderate certainty of a clinically useful effect on long-term weight gain. There is also no moderate- or high-certainty evidence that interventions designed to limit weight gain reduce the chances of people achieving abstinence from smoking.

Evaluation of Diet Quality Among American Adult Cancer Survivors: Results From 2005-2016 National Health and Nutrition Examination Survey

BACKGROUND

Diet quality among adult cancer survivors is low, and there is minimal information on the Healthy Eating Index (HEI)-2015 score, a measure of diet quality and adherence to the 2015-2020 Dietary Guidelines for Americans, in this population.

OBJECTIVE

This study aimed to examine HEI-2015 total and component scores and associated factors among adult cancer survivors. Also, this study examined which dietary components needed the most change to improve diet quality in this population.

DESIGN

The National Health and Nutrition Examination Survey (NHANES) is an ongoing nationally representative population-based cross-sectional study that is conducted annually.

PARTICIPANTS/SETTING

In all, 1971 adults with a self-reported cancer diagnosis in their lifetime (both individuals with cancer currently and those that are cancer-free) from NHANES 2005-2016 were included in this study.

MAIN OUTCOME MEASURES

HEI-2015 total and 13 component scores were calculated using the simple scoring algorithm method from the average of 2 24-hour recalls.

STATISTICAL ANALYSES

The associations of the HEI-2015 total score with sociodemographic, lifestyle, and health-related factors were analyzed using the least square means comparisons. A multivariable survey regression model was used to identify associations with the HEI-2015 total score after adjustment for potential confounders. The 13 component scores were also compared by participant characteristics to identify target food groups for subgroup-specific nutrition intervention.

RESULTS

The average HEI-2015 total score was 55.6 (95% confidence interval = 54.8-56.4). Factors associated with the HEI-2015 total score included age, race/ethnicity, education, smoking status, body mass index, and oral health status. Overall, poor adherence to the 2015-2020 Dietary Guidelines for Americans was found for most HEI-2015 components, with Whole Grains, Greens and Beans, Sodium, and Fatty Acids components having less than 50% of the maximum possible scores.

CONCLUSIONS

Results indicate poor diet quality among American adult cancer survivors, with significant disparities observed across sociodemographic and lifestyle factors, particularly education levels, body mass index, and smoking status. Nutrition interventions for cancer survivors should consider focusing on improving diet quality by increasing intakes of whole grains and greens and beans, lowering sodium consumption, and achieving a healthy balance of fatty acids (ie, a favorable ratio of unsaturated fats to saturated fats).

An empirical investigation of the impact of smoking on body weight using an endogenous treatment effects model approach: the role of food consumption patterns

BACKGROUND

This study explored the influence of cigarette smoking and food consumption patterns on BMI after adjusting for various socio-demographic characteristics. Since weight-based stereotypes may have an impact on smoking behaviour and both obesity and smoking have been associated with detrimental health effects, an interdependency between them is quite possible.

METHODS

Cross-sectional data were collected via a formal standardized questionnaire administered in personal interviews and two additional self-completion questionnaires from a random sample of 3471 German adults. The empirical framework considered potential endogeneity between smoking and body weight by employing an endogenous treatment effects model with an ordered outcome. The estimations derived from the endogenous treatment effects approach were also compared to the univariate ordered probit model results.

RESULTS

Our findings showed that ignoring potential endogeneity may affect both the statistical significance of the smoking estimate and the direction of the influence of smoking on BMI. Smoking was positively associated with BMI in both male (β = 1.236, p < 0.01) and female (β = 0.634, p < 0.10) participants. Smokers presented a 23.1% higher risk of obesity and a 24.3% lower likelihood of being within a healthy weight range. Male smokers also appeared to have a considerably augmented probability of being obese compared to their female counterparts (23.6% vs 15.1%). The relationship between smoking and BMI may be attributed to dietary practices, since smoking was correlated with poor dietary habits characterized by the frequent intake of more energy-dense foods (meat products and white-toasted bread) and less frequent consumption of healthy food items, such as whole-grain bread, vegetables and fruits. Concerning the impact of eating habits on body weight, frequent consumption of meat products and confectionery was found to have a direct association with BMI in both genders. Furthermore, white-toasted bread consumption was negatively linked with body weight in males (β = - 0.337, p < 0.01).

CONCLUSIONS

Our findings raised questions about the general belief that smoking is an effective weight control tool. Health interventions should be oriented toward a simultaneous decrease in smoking and obesity, since both behaviours seem to be interdependent. Nutrition programmes should also be designed according to the characteristics of different target groups in order to promote a healthy lifestyle.

Quality of life comparison between smokers and non-smokers with chronic pancreatitis

OBJECTIVES

The aim of this study was to evaluate the impact of smoking on quality of life in patients with chronic pancreatitis.

METHODS

This is a cross-sectional study of chronic pancreatitis patients followed at a single institution comparing smokers with non-smokers. The primary outcome was quality of life and secondary outcomes included demographics, drug and alcohol use, anxiety and depression, pain level, nutritional status, and metabolic factors.

RESULTS

48 smokers and 45 non-smokers participated in this study. Smokers had a worse overall quality of life and higher rates of opioid addiction and depression than non-smokers. Smokers also had less racial diversity, lower education levels, and higher amounts of narcotic use than non-smokers. Furthermore, smokers had a lower BMI and a higher proportional use of pancreatic enzyme replacement therapy. Smoking was found to be independently associated with worse quality of life on multivariable regression.

CONCLUSIONS

The worse overall quality of life and higher rates of depression and anxiety create cause for concern in chronic pancreatitis patients who smoke. Smoking cessation should be an important target in chronic pancreatitis patients. Multicenter, multiethnic studies are needed to further elucidate this relationship.

Multiple Risk Behavior Interventions: Meta-analyses of RCTs

CONTEXT

Multiple risk behaviors are common and associated with developing chronic conditions such as heart disease, cancer, or Type 2 diabetes. A systematic review, meta-analysis, and meta-regression of the effectiveness of multiple risk behavior interventions was conducted.

EVIDENCE ACQUISITION

Six electronic databases including MEDLINE, EMBASE, and PsycINFO were searched to August 2016. RCTs of non-pharmacologic interventions in general adult populations were selected. Studies targeting specific at-risk groups (such as people screened for cardiovascular risk factors or obesity) were excluded. Studies were screened independently. Study characteristics and outcomes were extracted and risk of bias assessed by one researcher and checked by another. The Behaviour Change Wheel and Oxford Implementation Index were used to code intervention content and context.

EVIDENCE SYNTHESIS

Random-effects meta-analyses were conducted. Sixty-nine trials involving 73,873 individuals were included. Interventions mainly comprised education and skills training and were associated with modest improvements in most risk behaviors: increased fruit and vegetable intake (0.31 portions, 95% CI=0.17, 0.45) and physical activity (standardized mean difference, 0.25; 95% CI=0.13, 0.38), and reduced fat intake (standardized mean difference, -0.24; 95% CI=-0.36, -0.12). Although reductions in smoking were found (OR=0.78, 95% CI=0.68, 0.90), they appeared to be negatively associated with improvement in other behaviors (such as diet and physical activity). Preliminary evidence suggests that sequentially changing smoking alongside other risk behaviors was more effective than simultaneous change. But most studies assessed simultaneous rather than sequential change in risk behaviors; therefore, comparisons are sparse. Follow-up period and intervention characteristics impacted effectiveness for some outcomes.

CONCLUSIONS

Interventions comprising education (e.g., providing information about behaviors associated with health risks) and skills training (e.g., teaching skills that equip participants to engage in less risky behavior) and targeting multiple risk behaviors concurrently are associated with small changes in diet and physical activity. Although on average smoking was reduced, it appeared changes in smoking were negatively associated with changes in other behaviors, suggesting it may not be optimal to target smoking simultaneously with other risk behaviors.

The effect of tobacco cessation on weight gain, obesity, and diabetes risk

OBJECTIVE

Most smokers gain weight after quitting, and some develop new onset obesity and type 2 diabetes. The purpose of this paper is to synthesize the current science investigating the consequences of tobacco cessation on body weight and diabetes, as well as intervention strategies that minimize or prevent weight gain while still allowing for successful tobacco cessation.

METHODS

Systematic reviews and relevant studies that were published since prior reviews were selected.

RESULTS

Smoking cessation can cause excessive weight gain in some individuals and can be associated with clinically significant outcomes such as diabetes or obesity onset. Interventions that combine smoking cessation and weight control can be effective for improving cessation and minimizing weight gain but need to be tested in specific populations.

CONCLUSIONS

Despite the health benefits of quitting tobacco, post-cessation weight gain and new onset obesity and diabetes are a significant concern. Promising interventions may need to be more widely applied to reduce the consequences of both obesity and tobacco use.

Metabolic effects of smoking cessation

Smoking continues to be the leading cause of preventable death in the USA, despite the vast and widely publicized knowledge about the negative health effects of tobacco smoking. Data show that smoking cessation is often accompanied by weight gain and an improvement in insulin sensitivity over time. However, paradoxically, post-cessation-related obesity might contribute to insulin resistance. Furthermore, post-cessation weight gain is reportedly the number one reason why smokers, especially women, fail to initiate smoking cessation or relapse after initiating smoking cessation. In this Review, we discuss the metabolic effects of stopping smoking and highlight future considerations for smoking cessation programs and therapies to be designed with an emphasis on reducing post-cessation weight gain.

Using realist evaluation to open the black box of knowledge translation: a state-of-the-art review

BACKGROUND

In knowledge translation, complex interventions may be implemented in the attempt to improve uptake of research-based knowledge in practice. Traditional evaluation efforts that focus on aggregate effectiveness represent an oversimplification of both the environment and the interventions themselves. However, theory-based approaches to evaluation, such as realist evaluation (RE), may be better-suited to examination of complex knowledge translation interventions with a view to understanding what works, for whom, and under what conditions. It is the aim of the present state-of-the-art review to examine current literature with regard to the use of RE in the assessment of knowledge translation interventions implemented within healthcare environments.

METHODS

Multiple online databases were searched from 1997 through June 2013. Primary studies examining the application or implementation of knowledge translation interventions within healthcare settings and using RE were selected for inclusion. Varying applications of RE across studies were examined in terms of a) reporting of core elements of RE, and b) potential feasibility of this evaluation method.

RESULTS

A total of 14 studies (6 study protocols), published between 2007 and 2013, were identified for inclusion. Projects were initiated in a variety of healthcare settings and represented a range of interventions. While a majority of authors mentioned context (C), mechanism (M) and outcome (O), a minority reported the development of C-M-O configurations or testable hypotheses based on these configurations. Four completed studies reported results that included refinement of proposed C-M-O configurations and offered explanations within the RE framework. In the few studies offering insight regarding challenges associated with the use of RE, difficulties were expressed regarding the definition of both mechanisms and contextual factors. Overall, RE was perceived as time-consuming and resource intensive.

CONCLUSIONS

The use of RE in knowledge translation is relatively new; however, theory-building approaches to the examination of complex interventions in this area may be increasing as researchers attempt to identify what works, for whom and under what circumstances. Completion of the RE cycle may be challenging, particularly in the development of C-M-O configurations; however, as researchers approach challenges and explore innovations in its application, rich and detailed accounts may improve feasibility.

Smoking-related disease risk, area deprivation and health behaviours

BACKGROUND

Smokers and ex-smokers are at risk of many chronic diseases. However, never smokers and never smokers exposed to environmental tobacco smoke (ETS) are also at risk. Additionally, smoking behaviours and their associated disease risk are socially patterned and positively associated with health inequalities. However, other lifestyle choices also contribute to health inequalities. We aim to assess the contribution of other lifestyle behaviours pertaining to alcohol, physical inactivity and weight to smoking-related disease risk across (i) the socioeconomic spectrum and (ii) smoking status.

METHODS

Smoking-related disease risk is modelled using probit analysis. The results are used to predict disease risk across the socioeconomic dimension and smoking status for a set of healthy and unhealthy behaviours using the administratively linked Scottish Health Surveys and Scottish Morbidity Records.

RESULTS

The results confirm the deprivation gradient in disease risk regardless of smoking status group. Imposition of healthy (unhealthy) lifestyle behaviours decreases (increases) the predicted risk across the deprivation distribution regardless of smoking status providing evidence of the multifaceted health behavioural determinants of disease risk across the deprivation distribution.

CONCLUSION

The results are of policy interest as they suggest that to reduce inequalities in smoking-related diseases, interventions reducing both smoking and other unhealthy behaviours are required.

Eating the elephant whole or in slices: views of participants in a smoking cessation intervention trial on multiple behaviour changes as sequential or concurrent tasks

BACKGROUND

This paper explores smoking cessation participants' perceptions of attempting weight management alongside smoking cessation within the context of a health improvement intervention implemented in Glasgow, Scotland.

METHODS

One hundred and thirty-eight participants were recruited from smoking cessation classes in areas of multiple deprivation in Glasgow and randomised to intervention, receiving dietary advice, or to control groups. The primary outcome of the study was to determine the % change in body weight. Semi-structured interviews were conducted with a purposive sample of 15 intervention and 15 control participants at weeks 6 (during the intervention) and 24 (at the end of the intervention). The current paper, though predominantly qualitative, links perceptions of behaviour modification to % weight change and cessation rates at week 24 thereby enabling a better understanding of the mediators influencing multiple behaviour change.

RESULTS

Our findings suggest that participants who perceive separate behaviour changes as part of a broader approach to a healthier lifestyle, and hence attempt behaviour changes concurrently, may be at comparative advantage in positively achieving dual outcomes.

CONCLUSIONS

These findings highlight the need to assess participants' preference for attempting multiple behaviour changes sequentially or simultaneously in addition to assessing their readiness to change. Further testing of this hypothesis is warranted.

TRIAL REGISTRATION

ISRCTN94961361.