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A double-blinded, randomized, parallel intervention to evaluate biomarker-based nutrition plans for weight loss: The PREVENTOMICS study.
Aldubayan, MA, Pigsborg, K, Gormsen, SMO, Serra, F, Palou, M, Galmés, S, Palou-March, A, Favari, C, Wetzels, M, Calleja, A, et al
Clinical nutrition (Edinburgh, Scotland). 2022;41(8):1834-1844
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Obesity, and particularly abdominal adiposity, is associated with various metabolic abnormalities. Diet has a vital role in preventing and managing obesity, but evidence from clinical studies demonstrates there is a great interindividual variability in response to the same dietary intervention, which likely indicates that no one diet is superior to another. The aim of this study was to examine the efficacy of the PREVENTOMICS (empowering consumers to PREVENT diet-related diseases through OMICS sciences) platform, incorporated in an e-commerce digital tool, for producing more favourable health outcomes over dietary plans based on general diet recommendations, in subjects with overweight or obesity and elevated waist circumference. This study is a 10-week randomised single-centre, parallel-group, double-blinded intervention study. Participants were allocated in a 1:1 ratio, stratified by cluster to either the intervention group (personalised plan) or the control group (generic recommendations). Results show that there isn’t any additional benefit of personalising dietary plans, over a generic approach, on the change in fat mass and body weight in individuals with overweight or obesity and elevated waist circumference. Accordingly, personalisation of the diet did not significantly improve health parameters beyond the changes induced by the control diet. Participants in both groups lost approximately 3 kg of body weight. Authors conclude that based on their findings evidence to translate personalised nutrition approaches into clinical practice is insufficient.
Abstract
BACKGROUND & AIMS Growing evidence suggests that biomarker-guided dietary interventions can optimize response to treatment. In this study, we evaluated the efficacy of the PREVENTOMCIS platform-which uses metabolomic and genetic information to classify individuals into different 'metabolic clusters' and create personalized dietary plans-for improving health outcomes in subjects with overweight or obesity. METHODS A 10-week parallel, double-blinded, randomized intervention was conducted in 100 adults (82 completers) aged 18-65 years, with body mass index ≥27 but <40 kg/m2, who were allocated into either a personalized diet group (n = 49) or a control diet group (n = 51). About 60% of all food was provided free-of-charge. No specific instruction to restrict energy intake was given. The primary outcome was change in fat mass from baseline, evaluated by dual energy X-ray absorptiometry. Other endpoints included body weight, waist circumference, lipid profile, glucose homeostasis markers, inflammatory markers, blood pressure, physical activity, stress and eating behavior. RESULTS There were significant main effects of time (P < 0.01), but no group main effects, or time-by-group interactions, for the change in fat mass (personalized: -2.1 [95% CI -2.9, -1.4] kg; control: -2.0 [95% CI -2.7, -1.3] kg) and body weight (personalized: -3.1 [95% CI -4.1, -2.1] kg; control: -3.3 [95% CI -4.2, -2.4] kg). The difference between groups in fat mass change was -0.1 kg (95% CI -1.2, 0.9 kg, P = 0.77). Both diets resulted in significant improvements in insulin resistance and lipid profile, but there were no significant differences between groups. CONCLUSION Personalized dietary plans did not result in greater benefits over a generic, but generally healthy diet, in this 10-week clinical trial. Further studies are required to establish the soundness of different precision nutrition approaches, and translate this science into clinically relevant dietary advice to reduce the burden of obesity and its comorbidities. CLINICAL TRIAL REGISTRY ClinicalTrials.gov registry (NCT04590989).
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App-technology to improve lifestyle behaviors among working adults - the Health Integrator study, a randomized controlled trial.
Bonn, SE, Löf, M, Östenson, CG, Trolle Lagerros, Y
BMC public health. 2019;19(1):273
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Lifestyle is the single most important factor to improve health and decrease premature death. Digital solutions for implementing lifestyle change and tracking different types of health data are becoming popular preventative initiatives. The main aim of this study was to evaluate whether a digital platform (The Health Integrator) accessible via a smartphone-app offering lifestyle intervention, with and without additional health coach guidance, can be used to make lifestyle changes and improve health related quality of life in gainfully employed persons. The Health Integrator intervention study is a three-arm parallel randomized controlled trial. Participants were randomized to 1 of 3 groups: 1) intervention using Health Integrator and a monthly telephone session with the health coach during the 3 months of follow-up or 2) intervention using Health Integrator without extra health coach sessions or 3) control group which is not given any lifestyle advise during the intervention period. The study is still ongoing. However, mobile Health has been suggested as one way to take global action as it has the potential to make treatment and prevention widely accessible at a fraction of the current cost. In fact, Health Integrator was developed on the basis of previous research. Current literature shows that multi-component interventions including for example face-to-face counselling or provision of physical activity equipment in addition to an app, were more successful than a stand-alone app intervention.
Abstract
BACKGROUND Mobile health, mHealth is recognized as a strategy to improve lifestyle behaviors. Research targeting specific lifestyle behaviors has shown that interventions using smartphones can be effective. However, few studies have evaluated solutions with multicomponent interventions, tailoring the intervention to the specific needs of the participant using a combination of mHealth and conventional treatment. To accomplish this, we developed Health Integrator, an mHealth platform with services and offers in the areas of diet, physical activity, sleeping habits, stress, alcohol and tobacco use. In the system, the user selects an area of intervention together with a health coach and set weekly goals. This study protocol presents the design and methodology of the Health Integrator Study, a randomized controlled trial to promote improved lifestyle behaviors. METHODS A three-arm parallel randomized controlled trial (1:1:1) is conducted in the Stockholm County, Sweden. In total, 209 employees at a four different companies representing both white and blue collar workers, have been recruited. Participants are randomized to either a control group or to one of two intervention groups receiving a 3-month lifestyle behavior change program including either 1) use of Health Integrator and monthly health coaching sessions or 2) only Health Integrator. At baseline and follow-up after 3- and 6-months, all participants answer questionnaires assessing lifestyle behaviors and quality of life. At baseline and the 3-month follow-up (end of intervention period), weight, height, waist circumference and blood pressure are measured, and all participants wear an Actigraph accelerometer for 7 days to assess physical activity. Blood lipid profile and HbA1c are measured among all participants at baseline. If baseline measures fall outside the normal range, a second measurement is done after 3 months. DISCUSSION The Health Integrator Intervention Study will evaluate if a personalized intervention combining mHealth and conventional programs for lifestyle change, with or without additional health coach sessions, can improve lifestyle behaviors and quality of life. Based on the results from this trial, Health Integrator can easily be implemented within a broad public. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT03579342 . Retrospectively registered, first submitted May 8, 2018.
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The Effect of a Multidisciplinary Lifestyle Intervention on Obesity Status, Body Composition, Physical Fitness, and Cardiometabolic Risk Markers in Children and Adolescents with Obesity.
Seo, YG, Lim, H, Kim, Y, Ju, YS, Lee, HJ, Jang, HB, Park, SI, Park, KH
Nutrients. 2019;11(1)
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Children and adolescents with obesity are at a high risk of being obese in adulthood. The aim of this study was to develop a multidisciplinary lifestyle intervention program targeted at children and adolescents with moderate to severe obesity. The study is based on the Intervention for Childhood and Adolescents Obesity via Activity and Nutrition (ICAAN) – quasi-experimental intervention trial - which recruited 103 participants aged between 6 and sixteen years (63 were boys and 40 girls). The study was based on 2 active treatment groups (usual care group vs exercise group) receiving a 16-week intervention program. Results indicate that children and adolescents with obesity can achieve positive effects on body composition, physical fitness, and cardiometabolic markers, particularly with the exercise intervention. Authors conclude that the moderate-intensity multidisciplinary lifestyle intervention program they developed, can be sustained in the real-world setting and it is applicable to both moderate and severe obesity.
Abstract
This study aimed to develop a multidisciplinary lifestyle intervention program targeted at children and adolescents with moderate to severe obesity, and assess the additional effects of exercise intervention when compared to usual care. Overall, the 103 enrolled participants were ≥85th percentile of age and sex-specific body mass index (BMI). Participants were divided into groups that received 16 weeks of either usual care or exercise intervention. The BMI z-score of the overall completers decreased by about 0.05 after the 16-week intervention (p = 0.02). After the intervention, only the exercise group had a significantly lower BMI z-score than the baseline score by about 0.1 (p = 0.03), but no significant group by time interaction effects were observed. At the 16-week follow-up, significant group by time interaction effects were observed in percentage body fat (%BF) (β = -1.52, 95%CI = -2.58⁻-0.45), lean body mass (LM) (β = 1.20, 95%CI = 0.12⁻2.29), diastolic blood pressure (β = -5.24, 95%CI = -9.66⁻-0.83), high-sensitivity C-reactive protein (β = -1.67, 95%CI = -2.77⁻-1.01), and wall sit test score (β = 50.74, 95%CI = 32.30⁻69.18). We developed a moderate-intensity intervention program that can be sustained in the real-world setting and is practically applicable to both moderate and severe obesity. After interventions, the exercise group had lower %BF and cardiometabolic risk markers, and higher LM and leg muscle strength compared to the usual care group.
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A Randomized Study of the Effects of Additional Fruit and Nuts Consumption on Hepatic Fat Content, Cardiovascular Risk Factors and Basal Metabolic Rate.
Agebratt, C, Ström, E, Romu, T, Dahlqvist-Leinhard, O, Borga, M, Leandersson, P, Nystrom, FH
PloS one. 2016;11(1):e0147149
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Fruits and vegetables intake has been advocated to improve blood lipids profile and reduce risk of cardiovascular disease, diabetes and cancer. However, a low fat diet rich in fruits and vegetables has showed no effect on cardiovascular disease and cancer in a large randomized American trial. This might be due to the high sugar content in fruits, particularly fructose. The aim of this study was to compare the effects of adding either fruits or nuts to the diet of 30 healthy non-obese individuals on liver fat, metabolic rate and cardiovascular risk markers. Authors concluded that the trial only showed small effects on cardiovascular risk factors. Nevertheless, there was a significant change in lipoprotein (fats that transport fats in the blood) levels between the two groups, which tends to give an advantage to the consumption of nuts over fruits. They deduced that increased intake of fruits doesn’t negatively impact cardiovascular disease risk factors in healthy non-obese individuals. However, further research needs to evaluate the effects on obese and insulin-resistant participants.
Abstract
BACKGROUND Fruit has since long been advocated as a healthy source of many nutrients, however, the high content of sugars in fruit might be a concern. OBJECTIVES To study effects of an increased fruit intake compared with similar amount of extra calories from nuts in humans. METHODS Thirty healthy non-obese participants were randomized to either supplement the diet with fruits or nuts, each at +7 kcal/kg bodyweight/day for two months. Major endpoints were change of hepatic fat content (HFC, by magnetic resonance imaging, MRI), basal metabolic rate (BMR, with indirect calorimetry) and cardiovascular risk markers. RESULTS Weight gain was numerically similar in both groups although only statistically significant in the group randomized to nuts (fruit: from 22.15 ± 1.61 kg/m(2) to 22.30 ± 1.7 kg/m(2), p = 0.24 nuts: from 22.54 ± 2.26 kg/m(2) to 22.73 ± 2.28 kg/m(2), p = 0.045). On the other hand BMR increased in the nut group only (p = 0.028). Only the nut group reported a net increase of calories (from 2519 ± 721 kcal/day to 2763 ± 595 kcal/day, p = 0.035) according to 3-day food registrations. Despite an almost three-fold reported increased fructose-intake in the fruit group (from 9.1 ± 6.0 gram/day to 25.6 ± 9.6 gram/day, p<0.0001, nuts: from 12.4 ± 5.7 gram/day to 6.5 ± 5.3 gram/day, p = 0.007) there was no change of HFC. The numerical increase in fasting insulin was statistically significant only in the fruit group (from 7.73±3.1 mIE/L to 8.81±2.9 mIE/L, p = 0.018, nuts: from 7.29±2.9 mIE/L to 8.62±3.0 mIE/L, p = 0.14). Levels of vitamin C increased in both groups while α-tocopherol/cholesterol-ratio increased only in the fruit group. CONCLUSIONS Although BMR increased in the nut-group only this was not linked with differences in weight gain between groups which potentially could be explained by the lack of reported net caloric increase in the fruit group. In healthy non-obese individuals an increased fruit intake seems safe from cardiovascular risk perspective, including measurement of HFC by MRI. TRIAL REGISTRATION ClinicalTrials.gov NCT02227511.