Objective: Given the critical role of behavior in preventing and treating chronic diseases, it is important to accelerate the development of behavioral treatments that can improve chronic disease ...prevention and outcomes. Findings from basic behavioral and social sciences research hold great promise for addressing behaviorally based clinical health problems, yet there is currently no established pathway for translating fundamental behavioral science discoveries into health-related treatments ready for Phase III efficacy testing. This article provides a systematic framework for developing behavioral treatments for preventing and treating chronic diseases. Method: The Obesity-Related Behavioral Intervention Trials (ORBIT) model for behavioral treatment development features a flexible and progressive process, prespecified clinically significant milestones for forward movement, and return to earlier stages for refinement and optimization. Results: This article presents the background and rationale for the ORBIT model, a summary of key questions for each phase, a selection of study designs and methodologies well-suited to answering these questions, and prespecified milestones for forward or backward movement across phases. Conclusions: The ORBIT model provides a progressive, clinically relevant approach to increasing the number of evidence-based behavioral treatments available to prevent and treat chronic diseases.
Despite major efforts to reduce atherosclerotic cardiovascular disease (ASCVD) burden with conventional risk factor control, significant residual risk remains. Recent evidence on non-traditional ...determinants of cardiometabolic health has advanced our understanding of lifestyle–disease interactions. Chronic exposure to environmental stressors like poor diet quality, sedentarism, ambient air pollution and noise, sleep deprivation and psychosocial stress affect numerous traditional and non-traditional intermediary pathways related to ASCVD. These include body composition, cardiorespiratory fitness, muscle strength and functionality and the intestinal microbiome, which are increasingly recognized as major determinants of cardiovascular health. Evidence points to partially overlapping mechanisms, including effects on inflammatory and nutrient sensing pathways, endocrine signalling, autonomic function and autophagy. Of particular relevance is the potential of low-risk lifestyle factors to impact on plaque vulnerability through altered adipose tissue and skeletal muscle phenotype and secretome. Collectively, low-risk lifestyle factors cause a set of phenotypic adaptations shifting tissue cross-talk from a proinflammatory milieu conducive for high-risk atherosclerosis to an anti-atherogenic milieu. The ketone body ß-hydroxybutyrate, through inhibition of the NLRP-3 inflammasome, is likely to be an intermediary for many of these observed benefits. Adhering to low-risk lifestyle factors adds to the prognostic value of optimal risk factor management, and benefit occurs even when the impact on conventional risk markers is discouragingly minimal or not present. The aims of this review are (a) to discuss novel lifestyle risk factors and their underlying biochemical principles and (b) to provide new perspectives on potentially more feasible recommendations to improve long-term adherence to low-risk lifestyle factors.
Childhood obesity has emerged as an important public health problem in the United States and other countries in the world. Currently 1 in 3 children in the United States is afflicted with overweight ...or obesity. The increasing prevalence of childhood obesity is associated with emergence of comorbidities previously considered to be "adult" diseases including type 2 diabetes mellitus, hypertension, nonalcoholic fatty liver disease, obstructive sleep apnea, and dyslipidemia. The most common cause of obesity in children is a positive energy balance due to caloric intake in excess of caloric expenditure combined with a genetic predisposition for weight gain. Most obese children do not have an underlying endocrine or single genetic cause for their weight gain. Evaluation of children with obesity is aimed at determining the cause of weight gain and assessing for comorbidities resulting from excess weight. Family-based lifestyle interventions, including dietary modifications and increased physical activity, are the cornerstone of weight management in children. A staged approach to pediatric weight management is recommended with consideration of the age of the child, severity of obesity, and presence of obesity-related comorbidities in determining the initial stage of treatment. Lifestyle interventions have shown only modest effect on weight loss, particularly in children with severe obesity. There is limited information on the efficacy and safety of medications for weight loss in children. Bariatric surgery has been found to be effective in decreasing excess weight and improving comorbidities in adolescents with severe obesity. However, there are limited data on the long-term efficacy and safety of bariatric surgery in adolescents. For this comprehensive review, the literature was scanned from 1994 to 2016 using PubMed using the following search terms: childhood obesity, pediatric obesity, childhood overweight, bariatric surgery, and adolescents.
The combined role of important environmental factors as a single lifestyle index in predicting non-alcoholic fatty liver disease (NAFLD) risk is not fully assessed. Therefore, we aimed to investigate ...the association of healthy lifestyle factor score (HLS) with the odds of NAFLD in Iranian adults.
This case-control study was conducted on 675 participants, aged ≥ 20-60 years, including 225 new NAFLD cases and 450 controls. We measured dietary intake information using a validated food frequency questionnaire and determined diet quality based on the alternate healthy eating index-2010(AHEI-2010). The score of HLS was calculated based on four lifestyle factors, including a healthy diet, normal body weight, non-smoking, and high physical activity. An ultrasound scan of the liver was used to detect NAFLD in participants of the case group. Logistic regression models were used to determine the odds ratios(ORs) and 95% confidence interval(CI) of NAFLD across tertiles of HLS and AHEI.
Mean ± SD age of the participants were 38.13 ± 8.85 years. The Mean ± SD HLS in the case and control groups was 1.55 ± 0.67 and 2.53 ± 0.87, respectively. Also, the Mean ± SD AHEI in the case and control groups was 48.8 ± 7.7 and 54.1 ± 8.1, respectively. Based on the age and sex-adjusted model, the odds of NAFLD were decreased across tertiles of AHEI (OR:0.18;95%CI:0.16-0.29,P
<0.001) and HLS(OR:0.03;95%CI:0.01-0.05,P
<0.001). Also, in the multivariable model, the odds of NAFLD were decreased across tertiles AHEI (OR:0.12;95%CI:0.06-0.24,P
<0.001) and HLS(OR:0.02;95%CI:0.01-0.04,P
<0.001).
Our findings reported that higher adherence to lifestyle with a higher score of HLS was associated with decreased odds of NAFLD. Also, a diet with a high AHEI score can reduce the risk of NAFLD in the adult population.
Prevention of childhood obesity is an international public health priority given the significant impact of obesity on acute and chronic diseases, general health, development and well-being. The ...international evidence base for strategies to prevent obesity is very large and is accumulating rapidly. This is an update of a previous review.
To determine the effectiveness of a range of interventions that include diet or physical activity components, or both, designed to prevent obesity in children.
We searched CENTRAL, MEDLINE, Embase, PsychINFO and CINAHL in June 2015. We re-ran the search from June 2015 to January 2018 and included a search of trial registers.
Randomised controlled trials (RCTs) of diet or physical activity interventions, or combined diet and physical activity interventions, for preventing overweight or obesity in children (0-17 years) that reported outcomes at a minimum of 12 weeks from baseline.
Two authors independently extracted data, assessed risk-of-bias and evaluated overall certainty of the evidence using GRADE. We extracted data on adiposity outcomes, sociodemographic characteristics, adverse events, intervention process and costs. We meta-analysed data as guided by the Cochrane Handbook for Systematic Reviews of Interventions and presented separate meta-analyses by age group for child 0 to 5 years, 6 to 12 years, and 13 to 18 years for zBMI and BMI.
We included 153 RCTs, mostly from the USA or Europe. Thirteen studies were based in upper-middle-income countries (UMIC: Brazil, Ecuador, Lebanon, Mexico, Thailand, Turkey, US-Mexico border), and one was based in a lower middle-income country (LMIC: Egypt). The majority (85) targeted children aged 6 to 12 years.Children aged 0-5 years: There is moderate-certainty evidence from 16 RCTs (n = 6261) that diet combined with physical activity interventions, compared with control, reduced BMI (mean difference (MD) -0.07 kg/m
, 95% confidence interval (CI) -0.14 to -0.01), and had a similar effect (11 RCTs, n = 5536) on zBMI (MD -0.11, 95% CI -0.21 to 0.01). Neither diet (moderate-certainty evidence) nor physical activity interventions alone (high-certainty evidence) compared with control reduced BMI (physical activity alone: MD -0.22 kg/m
, 95% CI -0.44 to 0.01) or zBMI (diet alone: MD -0.14, 95% CI -0.32 to 0.04; physical activity alone: MD 0.01, 95% CI -0.10 to 0.13) in children aged 0-5 years.Children aged 6 to 12 years: There is moderate-certainty evidence from 14 RCTs (n = 16,410) that physical activity interventions, compared with control, reduced BMI (MD -0.10 kg/m
, 95% CI -0.14 to -0.05). However, there is moderate-certainty evidence that they had little or no effect on zBMI (MD -0.02, 95% CI -0.06 to 0.02). There is low-certainty evidence from 20 RCTs (n = 24,043) that diet combined with physical activity interventions, compared with control, reduced zBMI (MD -0.05 kg/m2, 95% CI -0.10 to -0.01). There is high-certainty evidence that diet interventions, compared with control, had little impact on zBMI (MD -0.03, 95% CI -0.06 to 0.01) or BMI (-0.02 kg/m2, 95% CI -0.11 to 0.06).Children aged 13 to 18 years: There is very low-certainty evidence that physical activity interventions, compared with control reduced BMI (MD -1.53 kg/m2, 95% CI -2.67 to -0.39; 4 RCTs; n = 720); and low-certainty evidence for a reduction in zBMI (MD -0.2, 95% CI -0.3 to -0.1; 1 RCT; n = 100). There is low-certainty evidence from eight RCTs (n = 16,583) that diet combined with physical activity interventions, compared with control, had no effect on BMI (MD -0.02 kg/m2, 95% CI -0.10 to 0.05); or zBMI (MD 0.01, 95% CI -0.05 to 0.07; 6 RCTs; n = 16,543). Evidence from two RCTs (low-certainty evidence; n = 294) found no effect of diet interventions on BMI.Direct comparisons of interventions: Two RCTs reported data directly comparing diet with either physical activity or diet combined with physical activity interventions for children aged 6 to 12 years and reported no differences.Heterogeneity was apparent in the results from all three age groups, which could not be entirely explained by setting or duration of the interventions. Where reported, interventions did not appear to result in adverse effects (16 RCTs) or increase health inequalities (gender: 30 RCTs; socioeconomic status: 18 RCTs), although relatively few studies examined these factors.Re-running the searches in January 2018 identified 315 records with potential relevance to this review, which will be synthesised in the next update.
Interventions that include diet combined with physical activity interventions can reduce the risk of obesity (zBMI and BMI) in young children aged 0 to 5 years. There is weaker evidence from a single study that dietary interventions may be beneficial.However, interventions that focus only on physical activity do not appear to be effective in children of this age. In contrast, interventions that only focus on physical activity can reduce the risk of obesity (BMI) in children aged 6 to 12 years, and adolescents aged 13 to 18 years. In these age groups, there is no evidence that interventions that only focus on diet are effective, and some evidence that diet combined with physical activity interventions may be effective. Importantly, this updated review also suggests that interventions to prevent childhood obesity do not appear to result in adverse effects or health inequalities.The review will not be updated in its current form. To manage the growth in RCTs of child obesity prevention interventions, in future, this review will be split into three separate reviews based on child age.
Child and adolescent overweight and obesity has increased globally, and can be associated with significant short- and long-term health consequences. This is an update of a Cochrane review published ...first in 2003, and updated previously in 2009. However, the update has now been split into six reviews addressing different childhood obesity treatments at different ages.
To assess the effects of diet, physical activity and behavioural interventions (behaviour-changing interventions) for the treatment of overweight or obese children aged 6 to 11 years.
We searched CENTRAL, MEDLINE, Embase, PsycINFO, CINAHL, LILACS as well as trial registers ClinicalTrials.gov and ICTRP Search Portal. We checked references of studies and systematic reviews. We did not apply any language restrictions. The date of the last search was July 2016 for all databases.
We selected randomised controlled trials (RCTs) of diet, physical activity, and behavioural interventions (behaviour-changing interventions) for treating overweight or obese children aged 6 to 11 years, with a minimum of six months' follow-up. We excluded interventions that specifically dealt with the treatment of eating disorders or type 2 diabetes, or included participants with a secondary or syndromic cause of obesity.
Two review authors independently screened references, extracted data, assessed risk of bias, and evaluated the quality of the evidence using the GRADE instrument. We contacted study authors for additional information. We carried out meta-analyses according to the statistical guidelines in the Cochrane Handbook for Systematic Reviews of Interventions.
We included 70 RCTs with a total of 8461 participants randomised to either the intervention or control groups. The number of participants per trial ranged from 16 to 686. Fifty-five trials compared a behaviour-changing intervention with no treatment/usual care control and 15 evaluated the effectiveness of adding an additional component to a behaviour-changing intervention. Sixty-four trials were parallel RCTs, and four were cluster RCTs. Sixty-four trials were multicomponent, two were diet only and four were physical activity only interventions. Ten trials had more than two arms. The overall quality of the evidence was low or very low and 62 trials had a high risk of bias for at least one criterion. Total duration of trials ranged from six months to three years. The median age of participants was 10 years old and the median BMI z score was 2.2.Primary analyses demonstrated that behaviour-changing interventions compared to no treatment/usual care control at longest follow-up reduced BMI, BMI z score and weight. Mean difference (MD) in BMI was -0.53 kg/m
(95% confidence interval (CI) -0.82 to -0.24); P < 0.00001; 24 trials; 2785 participants; low-quality evidence. MD in BMI z score was -0.06 units (95% CI -0.10 to -0.02); P = 0.001; 37 trials; 4019 participants; low-quality evidence and MD in weight was -1.45 kg (95% CI -1.88 to -1.02); P < 0.00001; 17 trials; 1774 participants; low-quality evidence.Thirty-one trials reported on serious adverse events, with 29 trials reporting zero occurrences RR 0.57 (95% CI 0.17 to 1.93); P = 0.37; 4/2105 participants in the behaviour-changing intervention groups compared with 7/1991 participants in the comparator groups). Few trials reported health-related quality of life or behaviour change outcomes, and none of the analyses demonstrated a substantial difference in these outcomes between intervention and control. In two trials reporting on minutes per day of TV viewing, a small reduction of 6.6 minutes per day (95% CI -12.88 to -0.31), P = 0.04; 2 trials; 55 participants) was found in favour of the intervention. No trials reported on all-cause mortality, morbidity or socioeconomic effects, and few trials reported on participant views; none of which could be meta-analysed.As the meta-analyses revealed substantial heterogeneity, we conducted subgroup analyses to examine the impact of type of comparator, type of intervention, risk of attrition bias, setting, duration of post-intervention follow-up period, parental involvement and baseline BMI z score. No subgroup effects were shown for any of the subgroups on any of the outcomes. Some data indicated that a reduction in BMI immediately post-intervention was no longer evident at follow-up at less than six months, which has to be investigated in further trials.
Multi-component behaviour-changing interventions that incorporate diet, physical activity and behaviour change may be beneficial in achieving small, short-term reductions in BMI, BMI z score and weight in children aged 6 to 11 years. The evidence suggests a very low occurrence of adverse events. The quality of the evidence was low or very low. The heterogeneity observed across all outcomes was not explained by subgrouping. Further research is required of behaviour-changing interventions in lower income countries and in children from different ethnic groups; also on the impact of behaviour-changing interventions on health-related quality of life and comorbidities. The sustainability of reduction in BMI/BMI z score and weight is a key consideration and there is a need for longer-term follow-up and further research on the most appropriate forms of post-intervention maintenance in order to ensure intervention benefits are sustained over the longer term.
Adolescent overweight and obesity has increased globally, and can be associated with short- and long-term health consequences. Modifying known dietary and behavioural risk factors through behaviour ...changing interventions (BCI) may help to reduce childhood overweight and obesity. This is an update of a review published in 2009.
To assess the effects of diet, physical activity and behavioural interventions for the treatment of overweight or obese adolescents aged 12 to 17 years.
We performed a systematic literature search in: CENTRAL, MEDLINE, Embase, PsycINFO, CINAHL, LILACS, and the trial registers ClinicalTrials.gov and ICTRP Search Portal. We checked references of identified studies and systematic reviews. There were no language restrictions. The date of the last search was July 2016 for all databases.
We selected randomised controlled trials (RCTs) of diet, physical activity and behavioural interventions for treating overweight or obesity in adolescents aged 12 to 17 years.
Two review authors independently assessed risk of bias, evaluated the overall quality of the evidence using the GRADE instrument and extracted data following the guidelines of the Cochrane Handbook for Systematic Reviews of Interventions. We contacted trial authors for additional information.
We included 44 completed RCTs (4781 participants) and 50 ongoing studies. The number of participants in each trial varied (10 to 521) as did the length of follow-up (6 to 24 months). Participants ages ranged from 12 to 17.5 years in all trials that reported mean age at baseline. Most of the trials used a multidisciplinary intervention with a combination of diet, physical activity and behavioural components. The content and duration of the intervention, its delivery and the comparators varied across trials. The studies contributing most information to outcomes of weight and body mass index (BMI) were from studies at a low risk of bias, but studies with a high risk of bias provided data on adverse events and quality of life.The mean difference (MD) of the change in BMI at the longest follow-up period in favour of BCI was -1.18 kg/m
(95% confidence interval (CI) -1.67 to -0.69); 2774 participants; 28 trials; low quality evidence. BCI lowered the change in BMI z score by -0.13 units (95% CI -0.21 to -0.05); 2399 participants; 20 trials; low quality evidence. BCI lowered body weight by -3.67 kg (95% CI -5.21 to -2.13); 1993 participants; 20 trials; moderate quality evidence. The effect on weight measures persisted in trials with 18 to 24 months' follow-up for both BMI (MD -1.49 kg/m
(95% CI -2.56 to -0.41); 760 participants; 6 trials and BMI z score MD -0.34 (95% CI -0.66 to -0.02); 602 participants; 5 trials).There were subgroup differences showing larger effects for both BMI and BMI z score in studies comparing interventions with no intervention/wait list control or usual care, compared with those testing concomitant interventions delivered to both the intervention and control group. There were no subgroup differences between interventions with and without parental involvement or by intervention type or setting (health care, community, school) or mode of delivery (individual versus group).The rate of adverse events in intervention and control groups was unclear with only five trials reporting harms, and of these, details were provided in only one (low quality evidence). None of the included studies reported on all-cause mortality, morbidity or socioeconomic effects.BCIs at the longest follow-up moderately improved adolescent's health-related quality of life (standardised mean difference 0.44 ((95% CI 0.09 to 0.79); P = 0.01; 972 participants; 7 trials; 8 comparisons; low quality of evidence) but not self-esteem.Trials were inconsistent in how they measured dietary intake, dietary behaviours, physical activity and behaviour.
We found low quality evidence that multidisciplinary interventions involving a combination of diet, physical activity and behavioural components reduce measures of BMI and moderate quality evidence that they reduce weight in overweight or obese adolescents, mainly when compared with no treatment or waiting list controls. Inconsistent results, risk of bias or indirectness of outcome measures used mean that the evidence should be interpreted with caution. We have identified a large number of ongoing trials (50) which we will include in future updates of this review.
A healthy lifestyle during adolescence is associated with insulin sensitivity or liver enzyme levels and thus might contribute to the prevention of non-alcoholic fatty liver disease (NAFLD). ...Therefore, we examined the association between adherence to a hypothesis-based lifestyle score including dietary intake, physical activity, sedentary behaviour, sleep duration and BMI in adolescence and fatty liver indices in early adulthood. Overall, 240 participants of the DOrtmund Nutritional and Anthropometric Longitudinally Designed study completed repeated measurements of lifestyle score factors during adolescence (females: 8·5–15·5 years, males: 9·5–16·5 years). Multivariable linear regression models were used to investigate the association between adolescent lifestyle scores and NAFLD risk (hepatic steatosis index (HSI) and fatty liver index (FLI)) in early adulthood (18–30 years). Participants visited the study centre 4·9 times during adolescence and achieved on average 2·8 (min: 0·6, max: 5) out of five lifestyle score points. Inverse associations were observed between the lifestyle score and fatty liver indices (HSI: ß=−5·8 % (95 % CI −8·3, −3·1), P < 0·0001, FLI: ß=−32·4 % (95 % CI −42·9, −20·0), P < 0·0001) in the overall study population. Sex-stratified analysis confirmed these results in men, while inverse but non-significant associations were observed in women (P > 0·05). A higher lifestyle score was associated with lower HSI and FLI values, suggesting that a healthy lifestyle during adolescence might contribute to NAFLD prevention, predominantly in men. Our findings on repeatedly measured lifestyle scores in adolescents and their association with NAFLD risk in early adulthood warrant confirmation in larger study populations.
This review and meta-analysis aimed to describe the existing literature on interventions for bipolar disorder (BD) targeting the 6 pillars of Lifestyle Psychiatry: diet, physical activity (PA), ...substance use (SU), sleep, stress management, and social relationships (SR). Randomized Controlled Trials that examined the efficacy of lifestyle interventions targeting improvement in depressive/(hypo)manic symptom severity, lifestyle patterns, functioning, quality of life, and/or circadian rhythms were included. The systematic review included 18 studies, while the meta-analysis included studies targeting the same lifestyle domains and outcomes. Sleep (n = 10), PA (n = 9), and diet (n = 8) were the most targeted domains, while SU, SM and SR were least targeted (n = 4 each). Combined diet and PA interventions led to significant improvements in depressive symptoms (SMD: −0.46; 95%CI: −0.88, −0.04; p = 0.03), and functioning (SMD: −0.47; 95%CI: −0.89, −0.05; p = 0.03). Sleep interventions also led to significant improvements in depressive symptoms (SMD: −0.80; 95%CI: −1.21, −0.39; p < 0.01). Future research should focus on developing more multidimensional lifestyle interventions for a potentially greater impact on clinical and functional outcomes of BD.
•Lifestyle interventions for BD mostly target diet, exercise, and sleep.•Multidimensional interventions are more effective than single-domain interventions.•Interventions on sleep, diet and exercise improve depressive symptoms and functioning.•Lack of multidimensional interventions targeting the six main domains of lifestyle.
To summarize the recent scientific evidence regarding the wellness-promoting capacity of the Mediterranean lifestyle (ML), with a special focus on physical, social and environmental wellness.
...Narrative review of English-language publications in PubMed, Scopus and Embase, from 1 January 2010 to 31 October 2018.
Prospective cohort studies, interventional studies, meta-analyses and reviews of those investigating the effect of at least one component of the ML on wellness parameters.
General population.
Although an explicit definition of ML is missing, compliance with various combinations of its components improves metabolic health and protects against or ameliorates disease state. However, there is heterogeneity in the healthy behaviours that the ML-focused studies include in their design and the way these are assessed. Also, despite that features of the ML could contribute to other wellness dimensions, there are no studies exploring the effect this healthy lifestyle could confer to them.
Chronic lifestyle diseases are of multifactorial aetiology and they warrant multifaceted approaches targeting the general way of living. ML, if thoroughly evaluated, can provide a valuable tool to holistically promote health and wellness.
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