Deborah Lycett

Weight gain in smokers after quitting cigarettes: meta-analysis

Objective To describe weight gain and its variation in smokers who achieve prolonged abstinence for up to 12 months and who quit without treatment or use drugs to assist cessation. Design Meta-analysis. Data sources We searched the Central Register of Controlled Trials (CENTRAL) and trials listed in Cochrane reviews of smoking cessation interventions (nicotine replacement therapy, nicotinic partial agonists, antidepressants, and exercise) for randomised trials of first line treatments (nicotine replacement therapy, bupropion, and varenicline) and exercise that reported weight change. We also searched CENTRAL for trials of interventions for weight gain after cessation. Review methods Trials were included if they recorded weight change from baseline to follow-up in abstinent smokers. We used a random effects inverse variance model to calculate the mean and 95% confidence intervals and the mean of the standard deviation for weight change from baseline to one, two, three, six, and 12 months after quitting. We explored subgroup differences using random effects meta-regression. Results 62 studies were included. In untreated quitters, mean weight gain was 1.12 kg (95% confidence interval 0.76 to 1.47), 2.26 kg (1.98 to 2.54), 2.85 kg (2.42 to 3.28), 4.23 kg (3.69 to 4.77), and 4.67 kg (3.96 to 5.38) at one, two, three, six, and 12 months after quitting, respectively. Using the means and weighted standard deviations, we calculated that at 12 months after cessation, 16%, 37%, 34%, and 13% of untreated quitters lost weight, and gained less than 5 kg, gained 5-10 kg, and gained more than 10 kg, respectively. Estimates of weight gain were similar for people using different pharmacotherapies to support cessation. Estimates were also similar between people especially concerned about weight gain and those not concerned. Conclusion Smoking cessation is associated with a mean increase of 4-5 kg in body weight after 12 months of abstinence, and most weight gain occurs within three months of quitting. Variation in weight change is large, with about 16% of quitters losing weight and 13% gaining more than 10 kg.

Associations between weight change over 8 years and baseline body mass index in a cohort of continuing and quitting smokers

AIM To examine the association between weight change and baseline body mass index (BMI) over 8 years in a cohort of continuing and quitting smokers. DESIGN Prospective cohort. SETTING Oxfordshire general practices nicotine patch/placebo trial with 8-year follow-up. PARTICIPANTS Eighty-five participants were biochemically proven abstinent at 3, 6, 12 months and 8 years (abstainers). A total of 613 smoked throughout the 8 years (smokers), 26 quit for a whole year but were smoking again by 8 years (relapsed); 116 smoked for the first year but were abstinent at 8 years (late abstainers). MEASUREMENTS Weight and BMI was measured at baseline and at 8 years. Regression models were used to examine weight gain by smoking status and the association of BMI at the time of quitting. FINDINGS Abstainers gained 8.79kg [standard deviation (SD) 6.36; 95% confidence interval (CI) 7.42, 10.17]. Smokers gained 2.24 kg (SD 6.65; 95% CI 1.7, 2.77). Relapsed smokers gained 3.28 kg (SD 7.16; 95% CI 0.328, 6.24). Late abstainers gained 8.33 kg (SD 8.04; 95% CI 6.85, 9.81). The association between baseline BMI and weight change was modified by smoking status. In smokers there was a negative linear association of BMI, while in abstainers a J-shaped curve fitted best. These models estimated weight change over 8 years in abstainers of +9.8 kg, +7.8kg, +10.2kg, +19.4kg and in smokers of +3.9kg, +2.6kg, 1.0kg and -0.8kg, where BMI was 18, 23, 29 and 36, respectively. CONCLUSION Obese smokers gain most weight on quitting smoking, while obese continuing smokers are likely to remain stable or lose weight. Obese quitters have the greatest need for interventions to ameliorate weight gain.

Development and feasibility testing of a smart phone based attentive eating intervention

BackgroundAttentive eating means eating devoid of distraction and increasing awareness and memory for food being consumed. Encouraging individuals to eat more attentively could help reduce calorie intake, as a strong evidence base suggests that memory and awareness of food being consumed substantially influence energy intake.MethodsThe development and feasibility testing of a smartphone based attentive eating intervention is reported. Informed by models of behavioral change, a smartphone application was developed. Feasibility was tested in twelve overweight and obese volunteers, sampled from university staff. Participants used the application during a four week trial and semi-structured interviews were conducted to assess acceptability and to identify barriers to usage. We also recorded adherence by downloading application usage data from participants’ phones at the end of the trial.ResultsAdherence data indicated that participants used the application regularly. Participants also felt the application was easy to use and lost weight during the trial. Thematic analysis indicated that participants felt that the application raised their awareness of what they were eating. Analysis also indicated barriers to using a smartphone application to change dietary behavior.ConclusionsAn attentive eating based intervention using smartphone technology is feasible and testing of its effectiveness for dietary change and weight loss is warranted.

Screening and brief intervention for obesity in primary care: a parallel, two-arm, randomised trial.

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The association between smoking cessation and glycaemic control in patients with type 2 diabetes: A THIN database cohort study

BACKGROUND Smoking increases the risk of developing type 2 diabetes. However, several population studies also show a higher risk in people 3-5 years after smoking cessation than in continuing smokers. After 10-12 years the risk equates to that of never-smokers. Small cohort studies suggest diabetes control deteriorates temporarily during the first year after quitting. We examined whether or not quitting smoking was associated with altered diabetes control in a population study, for how long this association persisted, and whether or not this association was mediated by weight change. METHODS We did a retrospective cohort study (Jan 1, 2005, to Dec 31, 2010) of adult smokers with type 2 diabetes using The Health Improvement Network (THIN), a large UK primary care database. We developed adjusted multilevel regression models to investigate the association between a quit event, smoking abstinence duration, change in HbA1c, and the mediating effect of weight change. FINDINGS 10 692 adult smokers with type 2 diabetes were included. 3131 (29%) quit smoking and remained abstinent for at least 1 year. After adjustment for potential confounders, HbA1c increased by 0·21% (95% CI 0·17-0·25; p<0·001; [2·34 mmol/mol (95% CI 1·91-2·77)]) within the first year after quitting. HbA1c decreased as abstinence continued and became comparable to that of continual smokers after 3 years. This increase in HbA1c was not mediated by weight change. INTERPRETATION In type 2 diabetes, smoking cessation is associated with deterioration in glycaemic control that lasts for 3 years and is unrelated to weight gain. At a population level, this temporary rise could increase microvascular complications. FUNDING National Institute for Health Research School for Primary Care Research.

Trial Protocol: Randomised controlled trial of the effects of very low calorie diet, modest dietary restriction, and sequential behavioural programme on hunger, urges to smoke, abstinence and weight gain in overweight smokers stopping smoking

BackgroundWeight gain accompanies smoking cessation, but dieting during quitting is controversial as hunger may increase urges to smoke. This is a feasibility trial for the investigation of a very low calorie diet (VLCD), individual modest energy restriction, and usual advice on hunger, ketosis, urges to smoke, abstinence and weight gain in overweight smokers trying to quit.MethodsThis is a 3 armed, unblinded, randomized controlled trial in overweight (BMI > 25 kg/m2), daily smokers (CO > 10 ppm); with at least 30 participants in each group. Each group receives identical behavioural support and NRT patches (25 mg(8 weeks),15 mg(2 weeks),10 mg(2 weeks)). The VLCD group receive a 429-559 kcal/day liquid formula beginning 1 week before quitting and continuing for 4 weeks afterwards. The modest energy restricted group (termed individual dietary and activity planning(IDAP)) engage in goal-setting and receive an energy prescription based on individual basal metabolic rate(BMR) aiming for daily reduction of 600 kcal. The control group receive usual dietary advice that accompanies smoking cessation i.e. avoiding feeling hungry but eating healthy snacks. After this, the VLCD participants receive IDAP to provide support for changing eating habits in the longer term; the IDAP group continues receiving this support. The control group receive IDAP 8 weeks after quitting. This allows us to compare IDAP following a successful quit attempt with dieting concurrently during quitting. It also aims to prevent attrition in the unblinded, control group by meeting their need for weight management. Follow-up occurs at 6 and 12 months.Outcome measures include participant acceptability, measured qualitatively by semi-structured interviewing and quantitatively by recruitment and attrition rates. Feasibility of running the trial within primary care is measured by interview and questionnaire of the treatment providers. Adherence to the VLCD is verified by the presence of urinary ketones measured weekly. Daily urges to smoke, hunger and withdrawal are measured using the Mood and Physical Symptoms Scale-Combined (MPSS-C) and a Hunger Craving Score (HCS). 24 hour, 7 day point prevalence and 4-week prolonged abstinence (Russell Standard) is confirmed by CO < 10 ppm. Weight, waist and hip circumference and percentage body fat are measured at each visit.Trial RegistrationCurrent controlled trials ISRCTN83865809

Weight Change Over Eight Years in Relation to Alcohol Consumption in a Cohort of Continuing Smokers and Quitters

INTRODUCTION Stopping smoking results in weight gain. Avoidance of alcohol is often advocated to reduce cues to smoking, but the effect of alcohol consumption on body weight is unclear. METHODS We used regression models to examine weight change by baseline alcohol consumption in quitting and continuing smokers. Weight was measured at baseline and at 8 years, and weekly alcohol consumption was reported at baseline in participants from the Oxfordshire general practices nicotine patch/placebo trial. Of 698 smokers attempting to stop smoking, 85 were abstinent for 8 years and 613 continued to smoke. RESULTS The association between baseline alcohol consumption and weight change depended upon smoking status (p for interaction = .019). In smokers, there was no association with weight change, 0.005 (95% CI: -0.037 to 0.056) kg per UK unit (U) (8 g of ethanol) consumed each week. This was unmodified by gender and baseline body mass index (BMI). In quitters, there was a negative association with weight change, -0.174 (95% CI: -0.315 to -0.034) kg per U consumed each week (unmodified by gender and baseline BMI). Quitters who consumed 14 U (112 g ethanol) a week weighed a mean 2.4 kg less than quitters who did not drink. CONCLUSIONS Quitting smokers who drink more alcohol appear to gain less weight after quitting than those who do not drink. This is consistent across studies, it may be accounted for by unmeasured confounders or it may be that alcohol reduces weight gain. If alcohol reduces weight gain, the advice for quitting smokers must balance the benefits and hazards of alcohol consumption. However, there is currently insufficient evidence to advise quitters who drink little or no alcohol to increase consumption.

Capturing whole person care [editorial]

Biochemical blood levels are one international renal outcome measure. These quantitative data (such as phosphate levels) reflect, in part, dietary intervention and compliance to medical regimens, for example dialysis prescriptions and phosphate binding medication. The numbers demonstrate intervention efficacy, the cornerstone of evidence-based practice (EBP) (Greenhalgh et al., 2014). However, such data misses opportunities to capture the quality of the whole care provided, something that really matters to patients.

Capturing whole person care

Biochemical blood levels are one international renal outcome measure. These quantitative data (such as phosphate levels) reflect, in part, dietary intervention and compliance to medical regimens, for example dialysis prescriptions and phosphate binding medication. The numbers demonstrate intervention efficacy, the cornerstone of evidence-based practice (EBP) (Greenhalgh et al., 2014). However, such data misses opportunities to capture the quality of the whole care provided, something that really matters to patients.

Informal peer-support to self-manage dietary recommendations in chronic kidney disease : a social comparison model approach

Background: Gestational diabetes mellitus (GDM) is a transitory form of diabetes that is first diagnosed during pregnancy. GDM affects about 5% of pregnancies in the United Kingdom (1) and worldwide prevalence is increasing. GDM increases the risk of pregnancy and birth complications and can have long term health consequences for both mother and child . Dietary and lifestyle changes to achieve glycaemic control are effective in reducing adverse pregnancy outcomes . Postpartum screening and continued lifestyle modifications can help manage long-term maternal disease risks. Group clinics have been shown to be a cost-effective approach in management of conditions with increasing patient numbers . The aim of this study was to conduct a service evaluation of the dietitian led group clinic for women diagnosed with GDM; measuring satisfaction, changes in knowledge and confidence and use of other sources of information. Method: A pair of non-validated self-administered pre and post-clinic questionnaires were completed by all women (n = 30) attending the dietitian led GDM group clinic over a four-month period. Wilcoxon signed-rank tests were used to analyse pre and post-clinic knowledge about GDM and confidence in ability to manage dietary modification. Chi-squared goodness of fit was used to examine satisfaction with the group clinic, use of other sources of information and the impact of socioeconomic status. The service evaluation did not require ethical approval. Results: Attending the group clinic resulted in significant increases in knowledge about GDM (n = 26 positive change, p < 0.001) and confidence to manage dietary changes (n = 28 positive change, p < 0.001). There was a significant decrease in knowledge about long-term risk of developing Type 2 diabetes (T2DM) (n = 10 negative change, p = 0.017). A significant number of women were very satisfied with the clinic (n = 19, p = 0.02) and 80% (n = 24) reported that it was beneficial hearing about other women’s experiences. Women were equally distributed across different socioeconomic classes. Prior to the clinic 83% (n = 25) sought information about GDM with 70% (n = 21) reporting that they would following the clinic. The internet and health care professionals were the principal sources of information used. Discussion: The results are consistent with published studies which found that referral to a dietitian or other diabetes educators improved women’s perceptions of their knowledge and confidence to manage changes following GDM diagnosis . It is concerning that the results indicated a reduced knowledge about the future risk of T2DM. It is possible that the need to reassure women and help them adjust to their diagnosis may result in the long-term risks of GDM being down-played. However, as knowledge of T2DM risk was assessed by just one question and the questionnaires were not validated, further investigation is required. Conclusion: Providing information about GDM in a group environment, combined with individually tailored dietetic advice based around blood glucose levels and diet history, was effective in increasing knowledge and confidence to effect lifestyle changes for most women. As postpartum dietetic follow up and lifestyle advice are not currently offered to women attending the group clinic the opportunity to manage the longer-term risks associated with GDM is not being optimised.