Dataset Information

Combining diaries and accelerometers to explain change in physical activity during a lifestyle intervention for adults with pre-diabetes: A PREVIEW sub-study.

ABSTRACT: Self-report and device-based measures of physical activity (PA) both have unique strengths and limitations; combining these measures should provide complementary and comprehensive insights to PA behaviours. Therefore, we aim to 1) identify PA clusters and clusters of change in PA based on self-reported daily activities and 2) assess differences in device-based PA between clusters in a lifestyle intervention, the PREVIEW diabetes prevention study. In total, 232 participants with overweight and prediabetes (147 women; 55.9 ± 9.5yrs; BMI ≥25 kg·m-2; impaired fasting glucose and/or impaired glucose tolerance) were clustered using a partitioning around medoids algorithm based on self-reported daily activities before a lifestyle intervention and their changes after 6 and 12 months. Device-assessed PA levels (PAL), sedentary time (SED), light PA (LPA), and moderate-to-vigorous PA (MVPA) were assessed using ActiSleep+ accelerometers and compared between clusters using (multivariate) analyses of covariance. At baseline, the self-reported "walking and housework" cluster had significantly higher PAL, MVPA and LPA, and less SED than the "inactive" cluster. LPA was higher only among the "cycling" cluster. There was no difference in the device-based measures between the "social-sports" and "inactive" clusters. Looking at the changes after 6 months, the "increased walking" cluster showed the greatest increase in PAL while the "increased cycling" cluster accumulated the highest amount of LPA. The "increased housework" and "increased supervised sports" reported least favourable changes in device-based PA. After 12 months, there was only minor change in activities between the "increased walking and cycling", "no change" and "increased supervised sports" clusters, with no significant differences in device-based measures. Combining self-report and device-based measures provides better insights into the behaviours that change during an intervention. Walking and cycling may be suitable activities to increase PA in adults with prediabetes.

SUBMITTER: Klos L

PROVIDER: S-EPMC10956823 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature

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Combining diaries and accelerometers to explain change in physical activity during a lifestyle intervention for adults with pre-diabetes: A PREVIEW sub-study.

Klos Leon L Stratton Gareth G Mackintosh Kelly A KA McNarry Melitta A MA Fogelholm Mikael M Drummen Mathijs M Macdonald Ian I Martinez J Alfredo JA Navas-Carretero Santiago S Handjieva-Darlenska Teodora T Bogdanov Georgi G Gant Nicholas N Poppitt Sally D SD Silvestre Marta P MP Brand-Miller Jennie J Muirhead Roslyn R Schlicht Wolfgang W Huttunen-Lenz Maija M Brodie Shannon S Jalo Elli E Westerterp-Plantenga Margriet M Adam Tanja T Siig Vestentoft Pia P Tikkanen Heikki H Quist Jonas S JS Raben Anne A Swindell Nils N

PloS one 20240321 3

Self-report and device-based measures of physical activity (PA) both have unique strengths and limitations; combining these measures should provide complementary and comprehensive insights to PA behaviours. Therefore, we aim to 1) identify PA clusters and clusters of change in PA based on self-reported daily activities and 2) assess differences in device-based PA between clusters in a lifestyle intervention, the PREVIEW diabetes prevention study. In total, 232 participants with overweight and pr ...[more]

PMID: 38512828

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Project description:BackgroundTo better support participants to achieve long-lasting results within interventions aiming for weight loss and maintenance, more information is needed about the maintenance of behavioral changes. Therefore, we examined whether perceived stress predicts the maintenance of changes in eating behavior (flexible and rigid restraint of eating, disinhibition, and hunger).MethodsThe present study was a secondary analysis of the PREVIEW intervention including participants with overweight (BMI ≥ 25 kg/m2) at baseline and high risk of type 2 diabetes (n = 1311). Intervention included a 2-month low-energy diet phase and a 34-month subsequent weight maintenance phase. The first 6 months were considered an active behavior change stage and the remaining 2.5 years were considered a behavior maintenance stage. Eating behavior was measured using the Three Factor Eating Questionnaire and stress using the Perceived Stress Scale. The associations between stress and eating behavior were analyzed using linear mixed effects models for repeated measurements.ResultsPerceived stress measured after the active behavior change stage (at 6 months) did not predict changes in eating behavior during the behavior maintenance stage. However, frequent high stress during this period was associated with greater lapse of improved flexible restraint (p = 0.026). The mean (SD) change in flexible restraint from 6 to 36 months was -1.1 (2.1) in participants with frequent stress and -0.7 (1.8) in participants without frequent stress (Cohen's ds (95% CI) = 0.24 (0.04-0.43)). Higher perceived stress at 6 months was associated with less flexible restraint and more disinhibition and hunger throughout the behavior maintenance stage (all p < 0.001).ConclusionsPerceived stress was associated with features of eating behavior that may impair successful weight loss maintenance. Future interventions should investigate, whether incorporating stress reduction techniques results in more effective treatment, particularly for participants experiencing a high stress level.

Project description:PurposeOnset of type 2 diabetes (T2D) is often gradual and preceded by impaired glucose homeostasis. Lifestyle interventions including weight loss and physical activity may reduce the risk of developing T2D, but adherence to a lifestyle change is challenging. As part of an international T2D prevention trial (PREVIEW), a behavior change intervention supported participants in achieving a healthier diet and physically active lifestyle. Here, our aim was to explore the influence of this behavioral program (PREMIT) on social-cognitive variables during an 8-week weight loss phase.MethodsPREVIEW consisted of an initial weight loss, Phase I, followed by a weight- maintenance, Phase II, for those achieving the 8-week weight loss target of ≥ 8% from initial bodyweight. Overweight and obese (BMI ≥25 kg/m2) individuals aged 25 to 70 years with confirmed pre-diabetes were enrolled. Uni- and multivariate statistical methods were deployed to explore differences in intentions, self-efficacy, and outcome expectancies between those who achieved the target weight loss ("achievers") and those who did not ("non-achievers").ResultsAt the beginning of Phase I, no significant differences in intentions, self-efficacy and outcome expectancies between "achievers" (1,857) and "non-achievers" (163) were found. "Non-achievers" tended to be younger, live with child/ren, and attended the PREMIT sessions less frequently. At the end of Phase I, "achievers" reported higher intentions (healthy eating χ2(1)=2.57; P <0.008, exercising χ2(1)=0.66; P <0.008), self-efficacy (F(2; 1970)=10.27, P <0.005), and were more positive about the expected outcomes (F(4; 1968)=11.22, P <0.005).ConclusionAlthough statistically significant, effect sizes observed between the two groups were small. Behavior change, however, is multi-determined. Over a period of time, even small differences may make a cumulative effect. Being successful in behavior change requires that the "new" behavior is implemented time after time until it becomes a habit. Therefore, having even slightly higher self-efficacy, positive outcome expectancies and intentions may over time result in considerably improved chances to achieve long-term lifestyle changes.

Project description:BackgroundLow-energy diets (LEDs) comprise commercially formulated food products that provide between 800 and 1200 kcal/day (3.3-5 MJ/day) to aid body weight loss. Recent small-scale studies suggest that LEDs are associated with marked changes in the gut microbiota that may modify the effect of the LED on host metabolism and weight loss. We investigated how the gut microbiota changed during 8 weeks of total meal replacement LED and determined their associations with host response in a sub-analysis of 211 overweight adults with pre-diabetes participating in the large multicentre PREVIEW (PREVention of diabetes through lifestyle intervention and population studies In Europe and around the World) clinical trial.MethodsMicrobial community composition was analysed by Illumina sequencing of the hypervariable V3-V4 regions of the 16S ribosomal RNA (rRNA) gene. Butyrate production capacity was estimated by qPCR targeting the butyryl-CoA:acetate CoA-transferase gene. Bioinformatics and statistical analyses, such as comparison of alpha and beta diversity measures, correlative and differential abundances analysis, were undertaken on the 16S rRNA gene sequences of 211 paired (pre- and post-LED) samples as well as their integration with the clinical, biomedical and dietary datasets for predictive modelling.ResultsThe overall composition of the gut microbiota changed markedly and consistently from pre- to post-LED (P = 0.001), along with increased richness and diversity (both P < 0.001). Following the intervention, the relative abundance of several genera previously associated with metabolic improvements (e.g., Akkermansia and Christensenellaceae R-7 group) was significantly increased (P < 0.001), while flagellated Pseudobutyrivibrio, acetogenic Blautia and Bifidobacterium spp. were decreased (all P < 0.001). Butyrate production capacity was reduced (P < 0.001). The changes in microbiota composition and predicted functions were significantly associated with body weight loss (P < 0.05). Baseline gut microbiota features were able to explain ~25% of variation in total body fat change (post-pre-LED).ConclusionsThe gut microbiota and individual taxa were significantly influenced by the LED intervention and correlated with changes in total body fat and body weight in individuals with overweight and pre-diabetes. Despite inter-individual variation, the baseline gut microbiota was a strong predictor of total body fat change during the energy restriction period.Trial registrationThe PREVIEW trial was prospectively registered at ClinicalTrials.gov ( NCT01777893 ) on January 29, 2013.

Project description:BackgroundPrevious physical activity and sedentary behaviour studies during the pandemic have largely utilized online surveys, with known limitations including recall bias. Employing both device-based and self-reported measurements may provide a more comprehensive picture of both behaviours. Physical activity and sedentary behaviour research in adolescents is still limited in low- and middle-income countries (LMICs), including Indonesia. Male adolescents had been identified as more active than females but have had a greater decrease in physical activity during the pandemic. The present study aimed to investigate the quantity, temporal patterns, contexts, and biopsychosocial factors of physical activity and sedentary behaviour during the COVID-19 pandemic in a small group of male Indonesian adolescents.MethodsMale adolescents (n = 5; 14-15 years old) from Yogyakarta wore accelerometers and automated wearable cameras for four days, and completed diaries and interviews in November 2020.ResultsParticipants' activity was dominated by light intensity (67% of all physical activity). Sedentary behaviour was high; accelerometer, school days: 456 ± 145 min (78 ± 10% of wear time), non-school days: 344 ± 160 min (79 ± 17% of wear time); camera, school days: 176 ± 101 min (81 ± 46% of wear time), non-school days: 210 ± 165 min (86 ± 67% of wear time). Sedentary behaviour was mainly done during school hours on school days and from late afternoon to evening on non-school days. Screen time was largely for leisure purposes and action games were most favoured. Smartphones were the most used device, mainly used in a solitary context in the bedroom. Non-screen-based sedentary behaviour was consistently low. Interviews suggested that during the pandemic, supporting factors for physical activity are: self-determination, enjoyment, parental support, and physical education; meanwhile, factors influencing screen time are: educational demands, device and internet availability, screen time opportunities, parental control, social facilitators, phone notifications, and emotional state.ConclusionsMost participants were not able to stay active during the pandemic. Using digital platforms may be beneficial to shift some screen-based sedentary behaviour to 'screen-based' or 'screen-prompted' physical activity.Supplementary informationThe online version contains supplementary material available at 10.1186/s44167-022-00014-0.

Project description:BackgroundPeople with dysvascular lower limb amputation (LLA) achieve one-third of the recommended steps per day and experience severe disability. Although physical function improves with rehabilitation after dysvascular LLA, physical activity remains largely unchanged, and factors contributing to limited daily step count are unknown.ObjectivesTo identify factors that contribute to daily step count after dysvascular LLA.DesignCross-sectional, secondary data analysis.SettingOutpatient rehabilitation facilities.ParticipantsFifty-eight patients with dysvascular major LLA (age: 64 ± 9 years, body mass index: 30 ± 8 kg/m2 , male: 95%, transtibial LLA: 95%).MethodsData were collected by a blinded assessor after dysvascular LLA. Candidate explanatory variables included (1) demographics, (2) LLA characteristics, (3) comorbidities and health behaviors, and (4) physical function. Variables with univariate associations with log steps/day (transformed due to non-normality) were included in a multiple linear regression model using backward elimination to identify factors that explained significant variability in log steps/day.Primary outcome measureThe primary outcome, daily step count, was measured with accelerometer-based activity monitors worn by participants for 10 days.ResultsParticipants took an average (± SD) of 1450 ± 1309 steps/day. After backward elimination, the final model included four variables explaining 62% of the overall daily step count (P < .0001): 2-minute walk distance (32%), assistive device use (11%), cardiovascular disease (10%), and pre-amputation walking time (11%).ConclusionsAverage daily step count of 1450 steps/day reflects the lowest category of sedentary behavior. Physical function, cardiovascular disease, and pre-amputation walking time explain 62% of daily step count after dysvascular LLA. Although physical rehabilitation commonly focuses on improving physical function, interventions to increase daily step count after dysvascular LLA should also consider chronic disease and health behaviors that predate LLA.Level of evidenceIII.

Project description:BackgroundA behavioral lifestyle intervention program with goals of increasing physical activity (PA) and losing weight was shown to be efficacious for preventing type 2 diabetes and decreasing risk for cardiovascular disease in the U.S. Diabetes Prevention Program (DPP). Modified versions of the DPP lifestyle intervention are being translated into diverse community settings and have been successful in decreasing weight and improving metabolic markers. However, comprehensive evaluations of PA levels within these community translation intervention efforts are rare.PurposeTo evaluate the effectiveness of a DPP-based community lifestyle intervention for improving PA levels.Methods223 overweight adults at-risk for type 2 diabetes and/or cardiovascular disease were randomized (immediate or 6-month delayed-start) to a 12-month DPP-based lifestyle intervention. Past-month PA level was assessed at baseline and post-intervention with the Modifiable Activity Questionnaire. Simple and mixed-effects regression models were used to determine changes in PA level between and within groups over time.ResultsThe between-group mean difference for change in PA levels from baseline to 6 months indicated significantly greater improvement in the intervention compared to the delayed-start group [+6.72 (SE=3.01) MET-hrs/week; p=0.03]. Examining combined within-group change from baseline to post-intervention, mean PA levels significantly increased by +14.69 (SE=1.43) and +9.50 (SE= 1.40) MET-hrs/week at 6 and 12 months post-intervention, respectively. This PA change offset to approximately +10 MET-hrs/week at both 6 and 12 months after adjusting for baseline PA level and season (all; p<0.01). Other than season, sex impacted on change in PA level.ConclusionsThis community-based lifestyle intervention significantly increased PA levels among overweight adults at risk for type 2 diabetes and cardiovascular disease, even after adjusting for key variables.Clinicaltrialsgov identifierNCT01050205.

Dataset Information

Combining diaries and accelerometers to explain change in physical activity during a lifestyle intervention for adults with pre-diabetes: A PREVIEW sub-study.

Publications

Combining diaries and accelerometers to explain change in physical activity during a lifestyle intervention for adults with pre-diabetes: A PREVIEW sub-study.

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