A cognitive-behavioral weight control program improves eating and smoking behaviors in weight-concerned female smokers

Cognitive behavioral therapy for lifestyle changes in patients with obesity and type 2 diabetes: a systematic review and meta-analysis

The aim of this systematic review and meta-analysis was to examine the contribution of cognitive behavioral therapy (CBT) to the implementation of lifestyle changes, considering health-related and behavioral outcomes. A systematic literature review was performed using multiple databases (PsycInfo, PubMed and MEDLINE). The inclusion criteria comprised randomised controlled trials of CBT for lifestyle changes in patients with obesity and/or type 2 diabetes. The quality of study reporting was assessed with the revised Cochrane Collaboration's risk of bias tool. A meta-analysis was conducted on studies with appropriate outcomes. Nine randomised controlled trials, with a total sample size of 902 participants, met the inclusion criteria. The meta-analysis has shown a medium, significant effect size of CBT interventions for weight loss and weight maintenance, and a low, non-significant effect size of CBT interventions for reducing glycated hemoglobin (HbA1c) levels. A separate, combined, meta-analysis for all nine calculated effect sizes has yielded a medium and significant overall effect size for the model. Our review of the studies about the effectiveness of CBT in implementing lifestyle changes has, in comparison to usual control groups, proven the efficacy of CBT interventions in implementing lifestyle changes, especially for weight loss and weight maintenance.

Effectiveness of diet quality indices in measuring a change in diet quality over time: a systematic review and meta-analysis of randomized controlled trials

CONTEXT

Diet quality indices (DQIs) were developed to score and rank adherence to dietary patterns in observational studies, but their use to measure changes in diet quality in intervention trials is becoming common in the literature.

OBJECTIVE

This systematic review and meta-analysis aimed to assess the effectiveness of DQIs to measure change in diet quality in intervention trials.

DATA SOURCES

MEDLINE, CINAHL, Embase, and the Cochrane Central Register of Controlled Trials databases were searched from January 1994 to June 2020. Two reviewers independently completed full-text screening. Eligible studies were randomized controlled trials that used validated a priori DQIs to measure change in diet quality in adults.

DATA EXTRACTION

Data were extracted by an independent reviewer and reviewed by the research team. Risk of bias was assessed by the Cochrane Collaboration's Risk of Bias 2.0 tool.

DATA ANALYSIS

The 34 included studies (52% of reviewed studies, 0.6% of initially identified studies) used 10 different DQIs, 7 of which were able to measure significant change in diet quality. Meta-analyses of pooled results demonstrated change in the Healthy Eating Index (MD 5.35; 95%CI, 2.74-7.97; P < 0.001) and the Mediterranean Dietary Adherence Screener (MD 1.61; 95%CI, 1.00-2.23; P < 0.001) scores. DQIs were more likely to measure change in diet quality if they reflected the diet pattern being implemented, if the intervention was significantly different from the baseline and control diets, and if the study was adequately powered to detect change.

CONCLUSION

DQIs are responsive to change in diet quality in intervention trials when the index used reflects the dietary changes made and the study is adequately powered. The appropriate selection of a DQI to suitably match dietary changes and study populations is important for future dietary intervention trials.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration no. CRD42020181357.

Understanding daily life experiences of women who smoke: The role of smoking-related weight control expectancies

Smoking-related weight control expectancies are a motivational factor for maintaining cigarette use, particularly among women. Yet, less research has investigated the physiological and behavioral daily life weight-related experiences of women with smoking-related weight control expectancies. Increased research could contribute to understanding of maintenance factors for this group of smokers as well as unique intervention targets. Female smokers completed a baseline survey of smoking-related weight control expectancies and 35-days of ecological momentary assessment of physiological (i.e., smoking-related reduction in hunger, end-of-day perceived weight gain and bloating) and behavioral (i.e., daily exercise and sitting) weight-related experiences. Higher smoking-related weight control expectancies were associated with perceived smoking-related reductions in hunger and end-of-day perceived weight gain. Smoking-related weight control expectancies did not significantly associate with end-of-day bloating, daily exercise, or sitting. Given these findings, smoking-related weight control expectancies may maintain smoking in order to reduce hunger and to cope with perceived fluctuations in weight in daily life. It is critical for smoking cessation programs to assess smoking-related weight control expectancies and implement targeted treatments for these women.

Prevalence of obesity among U.S. population with substance dependence

AIM

To investigate associations between substance dependence and obesity.

METHODS

Obesity (body mass index ≥ 30 kg/m²) status and the status of dependence on heroin, stimulant, marijuana, nicotine and alcohol (past-month status for nicotine and past-year status for all others) were identified from the U.S. National Survey on Drug Use and Health (NSDUH, 2015-2017) datasets. SAS Surveylogistic regression was used to estimate adjusted odds ratio (AOR) for the association between each substance dependence and obesity, adjusting for potentially confounding effects of sociodemographic factors and health condition.

RESULTS

It was estimated that 10.6 % of noninstitutional U.S. residents aged 12 years or older were nicotine-dependent, 3.0 % alcohol-dependent, 1.0 % marijuana-dependent, 0.6 % stimulant-dependent, and 0.2 % heroin-dependent. Heroin-dependent individuals had 59 % lower odds of obesity relative to their non-dependent counterparts (AOR = 0.41; 95 % CI: 0.28-0.60; p < 0.0001). Lower odds of obesity were also noted for marijuana-dependent (AOR = 0.64; 95 % CI: 0.56-0.73; p < 0.0001), nicotine-dependent (AOR = 0.68; 95 % CI: 0.64-0.72; p < 0.0001) and alcohol-dependent (AOR = 0.77, 95 % CI: 0.69-0.84; p < 0.0001) individuals, but not statistically significant for stimulant-dependent individuals (AOR = 0.84; 95 % CI: 0.68-1.02; p = 0.0825).

CONCLUSIONS

Heroin, marijuana, nicotine and alcohol dependence were associated with lower odds of obesity than their non-dependence counterparts. Main findings based on 2015-2017 NSDUH are consistent with findings from our prior report based on clinical trials data from National Institute on Drug Abuse Clinical Trials Network, and other epidemiological evidence in the literature. These findings can alert substance abuse treatment professionals to monitor weight change, especially among weight-concerned substance abusers.

Weight Management Interventions for Adults With Overweight or Obesity: An Evidence Analysis Center Scoping Review

The objectives of this evidence scoping review were to identify and characterize studies investigating weight management interventions provided by a registered dietitian nutritionist or international equivalent (RDN) among adults with overweight or obesity. A medical librarian conducted an electronic literature search in 6 databases-MEDLINE (Ovid), Embase (Ovid), PyscINFO (Ovid), Cochrane CENTRAL (Ovid), Cochrane Database of Systematic Reviews (Ovid), and CINAHL (Ebsco). Except for narrative review, gray literature, and case study or report, all types of peer-reviewed articles published between January 2008 and April 26, 2019 were eligible. Two content advisors, who are experts in adult weight management, guided the process and reviewed the search plan and findings. The literature search resulted in 30,551 records with 16 additional records identified through other sources. A total of 29,756 records were excluded during the first round of screening due to duplication or irrelevancy. Of the 811 full-text articles that were screened, 139 met the criteria and were included. Approximately 51% and 43% of the studies were conducted in the community setting and in the United States or Canada, respectively. Over 97% of the studies were clinical or quasi-experimental trials. A total of 6 different intervention delivery modes were reported, which resulted in 22 combinations of the modes of delivery. RDNs delivered the weight management intervention (especially the nutrition component) in all studies, but some (61%) also involved an interdisciplinary team to deliver other components of the intervention. The average length of the intervention was about 10 months with a follow-up that ranged from 0 to 9 years. The commonly reported outcomes were anthropometrics, endocrine, and cardiovascular measures; dietary intake; and physical activity. Based on the scoping review, there were systematic reviews and evidence-based practice guidelines on weight management interventions but none of them met the a priori inclusion or exclusion criteria. Therefore, it would be beneficial to conduct a systematic review and develop an evidence-based practice guideline on adult weight management interventions provided by an RDN to guide practitioners and to evaluate their effects on health and nutrition-related outcomes.

Six Month Abstinence Heterogeneity in the Best Quit Study

BACKGROUND

Understanding the characteristics of smokers who are successful in quitting may help to increase smoking cessation rates.

PURPOSE

To examine heterogeneity in cessation outcome at 6 months following smoking cessation behavioral counseling with or without weight management counseling.

METHODS

2,540 smokers were recruited from a large quitline provider and then randomized to receive proactive smoking cessation behavioral counseling without or with two versions of weight management counseling. A Classification and Regression Tree (CART) analysis was conducted to identify the individual pretreatment and treatment characteristics of groups of smokers with different quitting success (as measured by point prevalence of self-reported smoking of any amount at 6 months).

RESULTS

CART analysis identified 10 subgroups ranging from 25.5% to 70.2% abstinent. The splits in the CART tree involved: the total number of counseling and control calls received, whether a smoking cessation pharmacotherapy was used, and baseline measures of cigarettes per day, confidence in quitting, expectation that the study would help the participant quit smoking, the motivation to quit, exercise minutes per week, anxiety, and lack of interest or pleasure in doing things. Costs per quitter ranged from a low of $US270 to a high of $US630. Specific treatment recommendations are made for each group.

CONCLUSIONS

These results indicate the presence of a substantial variation in abstinence following treatment, and that the total extent of contact via counseling calls of any type and baseline characteristics, rather than assigned treatment, were most important to subgroup membership and abstinence. Tailored treatments to subgroups who are at high risk for smoking following a quit attempt could increase successful smoking cessation.

Interleukin-6 and body mass index, tobacco use, and sleep in gynecologic cancers

OBJECTIVE

Elevated body mass index (BMI), tobacco use, and sleep disturbance are common health concerns among women with gynecologic cancers. The extent to which these factors are associated with systemic inflammation in gynecologic cancers is unknown. This is a significant literature gap given that (a) chronic, systemic inflammation may mediate relationships between behavioral health factors and cancer outcomes; and (b) elevated BMI, tobacco use, and sleep disturbances can be modified via behavioral interventions. This study examined Interleukin-6 (IL-6) relations with BMI, tobacco use history, and sleep disturbances in patients undergoing surgery for suspected gynecologic cancer.

METHOD

Participants were 100 women (M age = 58.42 years, SD = 10.62 years) undergoing surgery for suspected gynecologic cancer. Smoking history was determined by participant self-report. Sleep quality/disturbance was assessed via the Pittsburgh Sleep Quality Index. BMI was abstracted from electronic health records. Presurgical serum IL-6 concentrations were determined using Enzyme-Linked Immunosorbent Assay.

RESULTS

Controlling for the cancer type and stage, regression analyses revealed higher BMI, β = 0.258, p = .007, and former/current smoking status, β = 0.181, p = .046, were associated with higher IL-6. IL-6 did not differ between former and current smokers, β = 0.008, p = .927. Global sleep quality, sleep latency, and sleep efficiency were not associated with IL-6.

CONCLUSIONS

Higher BMI and any history of tobacco use predicted higher IL-6 among women undergoing surgery for suspected gynecologic cancers. Cognitive-behavioral interventions targeting primary and secondary obesity and tobacco use prevention may reduce systemic inflammation and optimize cancer outcomes in this population. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Predictors of reduced smoking quantity among recovering alcohol dependent men in a smoking cessation trial

INTRODUCTION

Adults with alcohol dependence (AD) have exceptionally high smoking rates and poor smoking cessation outcomes. Discovery of factors that predict reduced smoking among AD smokers may help improve treatment. This study examined baseline predictors of smoking quantity among AD smokers in a pharmacotherapy trial for smoking cessation.

METHODS

The sample includes male, AD smokers (N = 129) with 1-32 months of alcohol abstinence who participated in a 12-week trial of medication (topiramate vs. placebo) and adjunct counseling with 6 months of follow-up. Baseline measures of nicotine dependence, AD severity, psychopathology, motivation to quit smoking, and smoking-related cognitions were used to predict smoking quantity (cigarettes per day) at post-treatment and follow-up.

RESULTS

Overall, the sample had statistically significant reductions in smoking quantity. Greater nicotine dependence (Incidence rate ratios (IRRs) = 0.82-0.90), motivation to quit (IRRs = 0.65-0.85), and intrinsic reasons for quitting (IRRs = 0.96-0.98) predicted fewer cigarettes/day. Conversely, greater lifetime AD severity (IRR = 1.02), depression severity (IRRs = 1.05-1.07), impulsivity (IRRs = 1.01-1.03), weight-control expectancies (IRRs = 1.10-1.15), and childhood sexual abuse (IRRs = 1.03-1.07) predicted more cigarettes/day.

CONCLUSIONS

Smokers with AD can achieve large reductions in smoking quantity during treatment, and factors that predict smoking outcomes in the general population also predict greater smoking reductions in AD smokers. Treatment providers can use severity of nicotine dependence and AD, motivation to quit, smoking-related cognitions, and severity of depression to guide treatment and improve outcomes among AD smokers.

Prevalence of obesity for opioid- and stimulant-dependent participants in substance use treatment clinical trials

AIMS

To estimate obesity prevalence among drug-dependent individuals and to compare prevalence across different types of drug dependence.

METHODS

1596 opioid- and/or stimulant-dependent participants were extracted from six clinical trials within the National Drug Abuse Treatment Clinical Trials Network of the National Institute on Drug Abuse (NIDA CTN) to estimate obesity prevalence among drug-dependent users. Age-, sex-, and race-matched National Health and Nutrition Examination Survey (NHANES) samples were used as a general population reference. Standardized prevalence ratios (SPRs) were calculated to compare the CTN sample to NHANES as well as to compare within the CTN sample. Logistic regression estimated associations between the type of drug dependence and obesity.

RESULTS

The standardized obesity prevalence among the drug-dependent CTN trial participants was 67% of expected for age-, sex- and race-matched NIHANES participants (SPR = 0.67, 95% CI: 0.60-0.74). Obesity was least prevalent among opioid-dependent-only participants (SPR = 0.36, 95% CI: 0.27-0.46 compared to the NHANES, and SPR = 0.33, 95% CI: 0.23-0.46 compared to the stimulant-dependent-only participants). Compared to stimulant-dependent-only users (p < 0.0001), the odds of obesity were 67% lower among opioid-dependent-only users (adjusted odds ratio [AOR] = 0.33, 95% CI: 0.23-0.46) and 33% lower among opioid and stimulant-co-dependent users (AOR = 0.67, 95%CI: 0.49-0.90) after controlling for age, sex, race, education and employment pattern.

CONCLUSIONS

The prevalence of obesity among drug-dependent clinical trial participants was lower than the general population, and lowest among opioid-dependent-only users, suggesting an inverse relationship between obesity prevalence and drug dependence, most notable among opioid-dependent-only users.

Simultaneous vs. sequential treatment for smoking and weight management in tobacco quitlines: 6 and 12 month outcomes from a randomized trial

BACKGROUND

Smoking cessation often results in weight gain which discourages many smokers from quitting and can increase health risks. Treatments to reduce cessation-related weight gain have been tested in highly controlled trials of in-person treatment, but have never been tested in a real-world setting, which has inhibited dissemination.

METHODS

The Best Quit Study (BQS) is a replication and "real world" translation using telephone delivery of a prior in-person efficacy trial.

DESIGN

randomized control trial in a quitline setting. Eligible smokers (n = 2540) were randomized to the standard 5-call quitline intervention or quitline plus simultaneous or sequential weight management. Regression analyses tested effectiveness of treatments on self-reported smoking abstinence and weight change at 6 and 12 months.

RESULTS

Study enrollees were from 10 commercial employer groups and three state quitlines. Participants were between ages 18-72, 65.8% female, 68.2% white; 23.0% Medicaid-insured, and 76.3% overweight/obese. The follow-up response rate was lower in the simultaneous group than the control group at 6 months (p = 0.01). While a completers analysis of 30-day point prevalence abstinence detected no differences among groups at 6 or 12 months, multiply imputed abstinence showed quit rate differences at 6 months for:simultaneous (40.3%) vs. sequential (48.3%), p = 0.034 and simultaneous vs. control (44.9%), p = 0.043. At 12 months, multiply imputed abstinence, was significantly lower for the simultaneous group (40.7%) vs. control (46.0%), p < 0.05 and vs. sequential (46.3%), p < 0.05. Weight gain at 6 and 12 months was minimal and not different among treatment groups. The sequential group completed fewer total calls (3.75) vs. control (4.16) and vs. simultaneous group (3.83), p = 0.01, and fewer weight calls (0.94) than simultaneous (2.33), p < 0.0001. The number of calls completed predicted 30-day abstinence, p < 0.001, but not weight outcomes.

DISCUSSION

This study offers a model for evaluating population-level public health interventions conducted in partnership with tobacco quitlines.

CONCLUSIONS

Simultaneous (vs. sequential) delivery of phone/web weight management with cessation treatment in the quitline setting may adversely affect quit rate. Neither a simultaneous nor sequential approach to addressing weight produced any benefit on suppressing weight gain. This study highlights the need and the challenges of testing intensive interventions in real-world settings.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT01867983 . Registered: May 30, 2013.

Smoking Trajectories during the Perinatal Period and Their Risk Factors: The Nationally Representative French ELFE (Etude Longitudinale Française Depuis l’Enfance) Birth Cohort Study

BACKGROUND

In France, rates of perinatal smoking are among the highest worldwide; however, perinatal smoking trajectories and associated factors have still not been adequately researched.

METHODS

Among women participating in the French nationally representative etude longitudinale française depuis l'enfance birth cohort (n = 15,540), perinatal smoking trajectories were estimated using group-based modelling. Associated characteristics were studied using multinomial logistic regression.

RESULTS

Four trajectories were identified: non-smokers (59%), quitters (20%), persistent moderate (12%) and persistent heavy (9%) smokers. Older age, being native French, low socioeconomic position, persistent psychological difficulties and alcohol use in pregnancy, lack of social support, partner's smoking, mistimed pregnancy, and child formula feeding at birth were associated with persistent heavy smoking. Most of these factors were also associated, but to a lesser extent, with persistent moderate smoking, except for age and migrant status, which had opposite effects. Women who successfully lost weight prior to pregnancy had higher levels of quitting smoking.

CONCLUSION

Women's long-term smoking trajectories vary in terms of initial tobacco consumption level but also in relation to socio-demographic, psychological, behavioral and partner characteristics. Health professionals in contact with pregnant smokers should address perceived risks and benefits of smoking, including partner's smoking and weight-gain concerns.

Effectiveness of a Group Support Lifestyle Modification (GSLiM) Programme among Obese Adults in Workplace: A Randomised Controlled Trial

BACKGROUND

There was an increasing trend in the prevalence of obesity and its comorbidities over the past decades in Malaysia. Effective intervention for obesity remains limited. This study aimed to compare the effectiveness of a group based lifestyle modification programme amongst obese individuals with an existing dietary counseling programme.

METHODS

We recruited one hundred and ninety four overweight and obese (BMI>27.5 kg/m2) employees from a local university. They were randomly allocated to either Group Support Lifestyle Modification (GSLiM) (intervention)(n = 97) or dietary counseling (comparison)(n = 97). The GSLIM activities included self monitoring, cognitive-behaviour sessions, exercise as well as dietary change advocacy, which were conducted through seminars and group sessions over 24 weeks. The comparison group was given dietary counselling once in 12 weeks. Both groups were followed up for additional 12 weeks to check for intervention effect sustenance. Anthropometric and biochemical parameters were measured at baseline, 12, 24 and 36 weeks; while dietary intake, physical activities, psychological measures and quality of life measured at baseline, 24 and 36 weeks. Data analysis was conducted using ANOVA repeated measures with intention to treat principle.

RESULTS

The participants were predominantly women with mean (standard deviation) age of 40.5 (9.3) years. A total of 19.6% of the participants in GSLiM achieved 6% weight loss compared to 4.1% in the comparison group (Risk Ratio 4.75; 95% CI: 1.68, 13.45). At 24 weeks, the retention rate was 83.5% for GSLiM and 82.5% for comparison group. GSLiM participants also achieved significant improvement in total weight self-efficacy score, negative emotions and physical discomfort subscales, MDPSS friend subscale and all domains in quality of life. Participants in the comparison group experienced reduction in negative self-thoughts.

CONCLUSION

The GSLiM programme proved to be more effective in achieving targeted weight loss, improving weight self-efficacy, friend social support, and quality of life compared to dietary counseling.

TRIAL REGISTRATION

Iranian Registry of Clinical Trials IRCT201104056127N1.

Comparative effectiveness of adding weight control simultaneously or sequentially to smoking cessation quitlines: study protocol of a randomized controlled trial

Background

Prevalence of multiple health risk behaviors is growing, and obesity and smoking are costly. Weight gain associated with quitting smoking is common and can interfere with quit success. Efficacy of adding weight management to tobacco cessation treatment has been tested with women in group sessions over an extended period of time, but has never been tested in real-world settings with men and women seeking help to quit. This paper describes the Best Quit study which tests the effectiveness of delivering tobacco and weight control interventions via existing quitline infrastructures.

Methods

Eligible and consenting smokers (n = 2550) who call a telephone quitline will be randomized to one of three groups; the standard quitline or standard quitline plus a weight management program added either simultaneously or sequentially to the tobacco program. The study aims to test: 1) the effectiveness of the combined intervention on smoking cessation and weight, 2) the cost-effectiveness of the combined intervention on cessation and weight and 3) theoretically pre-specified mediators of treatment effects on cessation: reduced weight concerns, increased outcome expectancies about quitting and improved self-efficacy about quitting without weight gain.

Baseline, 6 month and 12 month data will be analyzed using multivariate statistical analyses and groups will be compared on treatment adherence, quit rates and change in weight among abstinent participants. To determine if the association between group assignment and primary outcomes (30-day abstinence and change in weight at 6 months) is moderated by pre-determined baseline and process measures, interaction terms will be included in the regression models and their significance assessed.

Discussion

This study will generate information to inform whether adding weight management to a tobacco cessation intervention delivered by phone, mail and web for smokers seeking help to quit will help or harm quit rates and whether a simultaneous or sequential approach is better at increasing abstinence and reducing weight gain post quit. If proven effective, the combined intervention could be disseminated across the U.S. through quitlines and could encourage additional smokers who have not sought cessation treatment for fear of gaining weight to make quit attempts.

Trial registration

Clinicaltrials.gov NCT01867983. Registered: May 30, 2013

Electronic supplementary material

The online version of this article (doi:10.1186/s12889-016-3231-6) contains supplementary material, which is available to authorized users.

Lifestyle factors and multimorbidity: a cross sectional study

BACKGROUND

Lifestyle factors have been associated mostly with individual chronic diseases. We investigated the relationship between lifestyle factors (individual and combined) and the co-occurrence of multiple chronic diseases.

METHODS

Cross-sectional analysis of results from the Program of Research on the Evolution of a Cohort Investigating Health System Effects (PRECISE) in Quebec, Canada. Subjects aged 45 years and older. A randomly-selected cohort in the general population recruited by telephone. Multimorbidity (3 or more chronic diseases) was measured by a simple count of self-reported chronic diseases from a list of 14. Five lifestyle factors (LFs) were evaluated: 1) smoking habit, 2) alcohol consumption, 3) fruit and vegetable consumption, 4) physical activity, and 5) body mass index (BMI). Each LF was given a score of 1 (unhealthy) if recommended behavioural targets were not achieved and 0 otherwise. The combined effect of unhealthy LFs (ULFs) was evaluated using the total sum of scores.

RESULTS

A total of 1,196 subjects were analyzed. Mean number of ULFs was 2.6 ± 1.1 SD. When ULFs were considered separately, there was an increased likelihood of multimorbidity with low or high BMI [Odd ratio (95% Confidence Interval): men, 1.96 (1.11-3.46); women, 2.57 (1.65-4.00)], and present or past smoker [men, 3.16 (1.74-5.73)]. When combined, in men, 4-5 ULFs increased the likelihood of multimorbidity [5.23 (1.70-16.1)]; in women, starting from a threshold of 2 ULFs [1.95 (1.05-3.62)], accumulating more ULFs progressively increased the likelihood of multimorbidity.

CONCLUSIONS

The present study provides support to the association of lifestyle factors and multimorbidity.

A multicomponent lifestyle intervention produces favourable changes in diet quality and cardiometabolic risk indices in hypercholesterolaemic adults

BACKGROUND

To date, there are no dietary intervention studies available jointly examining the changes produced in cardiometabolic risk indices and diet quality assessed with the Healthy Eating Index 2005 (HEI-2005). The present study aimed to evaluate the effect of a 3-month multicomponent lifestyle intervention on several cardiometabolic risk indices, physical activity levels and diet quality.

METHODS

A total sample of 108 hypercholesterolaemic adults (40-60 years old) were randomised to two intervention groups provided with and instructed to consume daily: (i) plain milk (n = 37) or (ii) enriched milk (n = 40) respectively; both groups were attending a 3-month dietary counselling programme. For the needs of the present study both intervention groups were analysed together IG: n = 77) and were compared against a control group following usual diet (CG: n = 31).

RESULTS

Regarding diet quality HEI scores for 'milk' (P = 0.021), 'dark green/orange vegetables and legumes' (P = 0.050) and 'total HEI score' (P = 0.045) were improved in the IG compared to the CG. The IG also improved 'whole grains' and 'calories from solid fats, alcoholic beverages and added sugars' scores compared to their baseline values. Both groups improved the 'total vegetable' HEI score. Regarding physical activity levels and cardiometabolic risk indices, the IG significantly increased the daily number of steps (P = 0.005) and decreased body weight (P = 0.021), body mass index (P = 0.019) and waist circumference (P = 0.027) to a higher extent compared to the changes observed in the CG. Moreover, the IG significantly decreased systolic (P = 0.001) and diastolic blood pressure (P = 0.050) compared to baseline values.

CONCLUSIONS

The present study revealed that this 3-month lifestyle and nutrition counselling intervention programme appears to have favourable effects on diet quality, physical activity levels, anthropometric and certain cardiometabolic risk indices.

Weight change in control group participants in behavioural weight loss interventions: a systematic review and meta-regression study

Background

Unanticipated control group improvements have been observed in intervention trials targeting various health behaviours. This phenomenon has not been studied in the context of behavioural weight loss intervention trials. The purpose of this study is to conduct a systematic review and meta-regression of behavioural weight loss interventions to quantify control group weight change, and relate the size of this effect to specific trial and sample characteristics.

Methods

Database searches identified reports of intervention trials meeting the inclusion criteria. Data on control group weight change and possible explanatory factors were abstracted and analysed descriptively and quantitatively.

Results

85 trials were reviewed and 72 were included in the meta-regression. While there was no change in control group weight, control groups receiving usual care lost 1 kg more than control groups that received no intervention, beyond measurement.

Conclusions

There are several possible explanations why control group changes occur in intervention trials targeting other behaviours, but not for weight loss. Control group participation may prevent weight gain, although more research is needed to confirm this hypothesis.

[The role of risk propensity in smokers and overweight people]

INTRODUCTION

The aim of this study is to investigate the nature of the link associating the risk propensity of smoking and overweight. For example, a person who is a smoker and obese does not have to be more prone to risk than another person who is obese and a non-smoker.

MATERIAL AND METHODS

The data was taken from the German Questionnaire on Personality and Daily (Cross section for the period 2005). This questionnaire was selected because it collects individual data on the sociodemographic characteristic, behaviours, risk attitudes, lottery games, and health status. Our main contribution is to analyse the role of risk propensity taking into account smoking and overweight.

RESULTS

Risk propensity encourages smoking, and to smoke and be overweight are positively associated. When the role of the unobserved characteristics are greater, the lower is the correlation between smoking and overweight. Although the risk propensity is an important determining factor of individual behaviour (smoking and overweight), its inclusion does not decrease the influence of personal circumstances and conditions. The need to define other measurements to be able to analyse the risk propensity of risk specific to risk behaviour is also highlighted.

DISCUSSION

To reduce the number of smokers would require interventions in life styles. Given that overweight is an important determining factor in the decision to smoke, to encourage healthy behaviours, such as physical exercise or balanced diets, could improve the health status of the population on reducing obesity rates, and consequently the number of smokers.

Evidence-based treatments for smoking cessation

Cigarette smoking continues to be the leading preventable cause of death in the United States. Nurse practitioners play an important role in implementing effective smoking cessation treatments and educating patients about the associated risks of smoking.

Behavioral transitions and weight change patterns within the PREMIER trial

Little is known about the transition in behaviors from short-term weight loss to maintenance of weight loss. We wanted to determine how short-term and long-term weight loss and patterns of weight change were associated with intervention behavioral targets. This analysis includes overweight/obese participants in active treatment (n = 507) from the previously published PREMIER trial, an 18-month, multicomponent lifestyle intervention for blood pressure reduction, including 33 intervention sessions and recommendations to self-monitor food intake and physical activity daily. Associations between behaviors (attendance, recorded days/week of physical activity, food records/week) and weight loss of ≥5% at 6 and 18 months were examined using logistic regression. We characterized the sample using 5 weight change categories (weight gained, weight stable, weight loss then relapse, late weight loss, and weight loss then maintenance) and analyzed adherence to the behaviors for each category, comparing means with ANOVA. Participants lost an average of 5.3 ± 5.6 kg at 6 months and 4.0 ± 6.7 kg (4.96% of body weight) by 18 months. Higher levels of attendance, food record completion, and recorded days/week of physical activity were associated with increasing odds of achieving 5% weight loss. All weight change groups had declines in the behaviors over time; however, compared to the other four groups, the weight loss/maintenance group (n = 154) had statistically less significant decline in number of food records/week (48%), recorded days/week of physical activity (41.7%), and intervention sessions attended (12.8%) through 18 months. Behaviors associated with short-term weight loss continue to be associated with long-term weight loss, albeit at lower frequencies. Minimizing the decline in these behaviors may be important in achieving long-term weight loss.

A Review of Multiple Health Behavior Change Interventions for Primary Prevention

Most individuals engage in multiple unhealthy lifestyle behaviors with the potential for negative health consequences. Yet most health promotion research has addressed risk factors as categorically separate entities, and little is known about how to effectively promote multiple health behavior change (MHBC). This review summarizes the recent literature (January 2004 to December 2009) on randomized clinical trials evaluating MHBC interventions for primary prevention. Combining all the studies across all the reviews, fewer than 150 studies were identified. This is a fraction of the number of trials conducted on changing individual behavioral risks. Three primary behavioral clusters dominated: (1) the energy balance behaviors of physical activity and diet; (2) addictive behaviors like smoking and other drugs; and (3) disease-related behaviors, specifically cardiovascular disease (CVD) and cancer related. Findings were largely disappointing for studies of diet and physical activity, particularly with youth. Treating 2 addictions, including smoking, resulted in greater long-term sobriety from alcohol and illicit drugs. MHBC intervention effects were stronger and more consistent for cancer prevention than CVD prevention. MHBC interventions offer a new paradigm for broader, more comprehensive health promotion; however, the potential value in maximizing intervention impact is largely unmet.

A Review of Multiple Health Behavior Change Interventions for Primary Prevention

Most individuals engage in multiple unhealthy lifestyle behaviors with the potential for negative health consequences. Yet most health promotion research has addressed risk factors as categorically separate entities, and little is known about how to effectively promote multiple health behavior change (MHBC). This review summarizes the recent literature (January 2004 to December 2009) on randomized clinical trials evaluating MHBC interventions for primary prevention. Combining all the studies across all the reviews, fewer than 150 studies were identified. This is a fraction of the number of trials conducted on changing individual behavioral risks. Three primary behavioral clusters dominated: (1) the energy balance behaviors of physical activity and diet; (2) addictive behaviors like smoking and other drugs; and (3) disease-related behaviors, specifically cardiovascular disease (CVD) and cancer related. Findings were largely disappointing for studies of diet and physical activity, particularly with youth. Treating 2 addictions, including smoking, resulted in greater long-term sobriety from alcohol and illicit drugs. MHBC intervention effects were stronger and more consistent for cancer prevention than CVD prevention. MHBC interventions offer a new paradigm for broader, more comprehensive health promotion; however, the potential value in maximizing intervention impact is largely unmet.