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Effect of Smartphone-Based Lifestyle Coaching App on Community-Dwelling Population With Moderate Metabolic Abnormalities: Randomized Controlled Trial.
Cho, SMJ, Lee, JH, Shim, JS, Yeom, H, Lee, SJ, Jeon, YW, Kim, HC
Journal of medical Internet research. 2020;22(10):e17435
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Metabolic disorders are established precursors to cardiovascular disease. The aim of the study was to evaluate the longitudinal effect of smartphone-based health care app on metabolic parameters in a sample of the general population with moderate metabolic abnormalities. The study is a single-blind 3-arm parallel-design randomized controlled trial delivering a 6-month primary prevention program via mobile app. One hundred twenty-nine smartphone users, aged between 30-59 years with at least 2 metabolic abnormalities, have been recruited. Results showed that the simultaneous diet/exercise logging and lifestyle coaching yielded greater body weight reduction, specifically via body fat mass reduction. On the other hand, the systolic blood pressure did not change notably between the 3 groups at any follow-up examinations. Authors conclude that future studies focusing on comparative effectiveness using alternative study designs are needed to integrate these apps in everyday lives and clinic practice.
Abstract
BACKGROUND Metabolic disorders are established precursors to cardiovascular diseases, yet they can be readily prevented with sustained lifestyle modifications. OBJECTIVE We assessed the effectiveness of a smartphone-based weight management app on metabolic parameters in adults at high-risk, yet without physician diagnosis nor pharmacological treatment for metabolic syndrome, in a community setting. METHODS In this 3-arm parallel-group, single-blind, randomized controlled trial, we recruited participants aged 30 to 59 years with at least 2 conditions defined by the Third Report of the National Cholesterol Education Program expert panel (abdominal obesity, high blood pressure, high triglycerides, low high-density lipoprotein cholesterol, and high fasting glucose level). Participants were randomly assigned (1:1:1) by block randomization to either the nonuser group (control), the app-based diet and exercise self-logging group (app only), or the app-based self-logging and personalized coaching from professional dieticians and exercise coordinators group (app with personalized coaching). Assessments were performed at baseline, week 6, week 12, and week 24. The primary outcome was change in systolic blood pressure (between baseline and follow-up assessments). Secondary outcomes were changes in diastolic blood pressure, body weight, body fat mass, waist circumference, homeostatic model of assessment of insulin resistance, triglyceride level, and high-density lipoprotein cholesterol level between baseline and follow-up assessments. Analysis was performed using intention-to-treat. RESULTS Between October 28, 2017 and May 28, 2018, 160 participants participated in the baseline screening examination. Participants (129/160, 80.6%) who satisfied the eligibility criteria were assigned to control (n=41), app only (n=45), or app with personalized coaching (n=43) group. In each group, systolic blood pressure showed decreasing trends from baseline (control: mean -10.95, SD 2.09 mmHg; app only: mean -7.29, SD 1.83 mmHg; app with personalized coaching: mean -7.19, SD 1.66 mmHg), yet without significant difference among the groups (app only: P=.19; app with personalized coaching: P=.16). Instead, those in the app with personalized coaching group had greater body weight reductions (control: mean -0.12, SD 0.30 kg; app only: mean -0.35, SD 0.36 kg, P=.67; app with personalized coaching: mean -0.96, SD 0.37 kg; P=.08), specifically by body fat mass reduction (control: mean -0.13, SD 0.34 kg; app only: mean -0.64, SD 0.38 kg, P=.22; app with personalized coaching: mean -0.79, SD 0.38 kg; P=.08). CONCLUSIONS Simultaneous diet and exercise self-logging and persistent lifestyle modification coaching were ineffective in lowering systolic blood pressure but effective in losing weight and reducing body fat mass. These results warrant future implementation studies of similar models of care on a broader scale in the context of primary prevention. TRIAL REGISTRATION ClinicalTrials.gov NCT03300271; http://clinicaltrials.gov/ct2/show/NCT03300271.
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Dietary patterns and physical activity in the metabolically (un)healthy obese: the Dutch Lifelines cohort study.
Slagter, SN, Corpeleijn, E, van der Klauw, MM, Sijtsma, A, Swart-Busscher, LG, Perenboom, CWM, de Vries, JHM, Feskens, EJM, Wolffenbuttel, BHR, Kromhout, D, et al
Nutrition journal. 2018;17(1):18
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Numerous studies have shown that obese individuals are likely to develop multiple metabolic diseases such as type 2 diabetes and cardiovascular diseases. However, it seems that some obese individuals show no signs & symptoms of conditions associated with metabolic disease. Hence the aim of this study was to compare lifestyle and dietary pattern of obese metabolic healthy and obese metabolic unhealthy individuals. Cross sectional data of 9270 obese individuals between the ages of 30 -69 was gathered and analysed. The result on analysis showed that more than half of the men and more than 1/3rd of the women were metabolically unhealthy. The authors concluded that amongst the obese metabolically healthy individuals physical activity was found to be the common factor.
Abstract
BACKGROUND Diversity in the reported prevalence of metabolically healthy obesity (MHO), suggests that modifiable factors may be at play. We evaluated differences in dietary patterns and physical activity between MHO and metabolically unhealthy obesity (MUO). METHODS Cross-sectional data of 9270 obese individuals (30-69 years) of the Lifelines Cohort Study was used. MHO was defined as obesity and no metabolic syndrome risk factors and no cardiovascular disease history. MUO was defined as obesity and ≥2 metabolic syndrome risk factors. Sex-specific associations of dietary patterns (identified by principal component analysis) and physical activity with MHO were assessed by multivariable logistic regression (reference group: MUO). Analyses were adjusted for multiple covariates. RESULTS Among 3442 men and 5828 women, 10.2% and 24.4% had MHO and 56.9% and 35.3% MUO, respectively. We generated four obesity-specific dietary patterns. Two were related to MHO, and in women only. In the highest quartile (Q) of 'bread, potatoes and sweet snacks' pattern, odds ratio (OR) (95% CI) for MHO was 0.52 (0.39-0.70). For the healthier pattern 'fruit, vegetables and fish', an OR of 1.36 (1.09-1.71) in Q3 and 1.55 (1.21-1.97) in Q4 was found for MHO. For physical activity, there was a positive association between moderate physical activity and vigorous physical activity in the highest tertile and MHO in women and men, respectively (OR 1.19 (1.01-1.41) and OR 2.02 (1.50-2.71)). CONCLUSION The healthier diet -characterized by 'fruit, vegetables and fish'- and moderate physical activity in women, and vigorous physical activity in men may be related to MHO. The (refined) carbohydrate-rich 'bread, potatoes and sweet snacks' dietary pattern was found to counteract MHO in women.