Dataset Information

Physical activity equivalent labeling vs. calorie labeling: a systematic review and meta-analysis.

ABSTRACT:

Background

Many countries are trying to identify strategies to control obesity. Nutrition labeling is a policy that could lead to healthy food choices by providing information to consumers. Calorie labeling, for example, could lead to consumers choosing lower calorie foods. However, its effectiveness has been limited. Recently, physical activity equivalent labeling (i.e., displaying calories in terms of estimated amount of physical activity to burn calories) has been proposed as an alternative to the calorie-only label. The aim of this review was to identify and evaluate the published literature comparing effects on health behavior between physical activity equivalent labeling and calorie-only labeling.

Method

We searched the following databases: Pubmed/medline, Scopus, Web of science, Agris, Cochrane library, Google Scholar. We also searched along with reference lists of included articles. Articles that were published between 1 January 2000 and 31 October 2016 were eligible for inclusion provided they reported on studies that examined the effects of both types of labeling and included at least one outcome of interest. Mean and standard deviations of the included results were combined using a fixed-effect model. The difference in calories purchased between people exposed to physical activity labeling and calorie-only labeling was calculated as weighted mean difference by using a fixed-effect model.

Result

The difference of calories ordered between physical activity label and calorie label groups was not statistically significant (SMD: -0.03; 95% CI: -0.13, 0.07). The difference of calories ordered between physical activity label and calorie label according to real vs unreal (e.g. web-based) condition was 65 Kcal fewer in real-world settings.

Conclusion

Physical activity calorie equivalent labeling in minutes does not significantly reduce calories ordered compared to calorie-only labeling.

SUBMITTER: Seyedhamzeh S

PROVIDER: S-EPMC6137736 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Physical activity equivalent labeling vs. calorie labeling: a systematic review and meta-analysis.

Seyedhamzeh Shirin S Bagheri Minoo M Keshtkar Abbas Ali AA Qorbani Mostafa M Viera Anthony J AJ

The international journal of behavioral nutrition and physical activity 20180914 1

<h4>Background</h4>Many countries are trying to identify strategies to control obesity. Nutrition labeling is a policy that could lead to healthy food choices by providing information to consumers. Calorie labeling, for example, could lead to consumers choosing lower calorie foods. However, its effectiveness has been limited. Recently, physical activity equivalent labeling (i.e., displaying calories in terms of estimated amount of physical activity to burn calories) has been proposed as an alter ...[more]

PMID: 30217210

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Project description:BACKGROUND:Smartphone apps are a promising tool for delivering accessible and appealing physical activity interventions. Given the large growth of research in this field, there are now enough studies using the "gold standard" of experimental design-the randomized controlled trial design-and employing objective measurements of physical activity, to support a meta-analysis of these scientifically rigorous studies. OBJECTIVE:This systematic review and meta-analysis aimed to determine the effectiveness of smartphone apps for increasing objectively measured physical activity in adults. METHODS:A total of 7 electronic databases (EMBASE, EmCare, MEDLINE, Scopus, Sport Discus, The Cochrane Library, and Web of Science) were searched from 2007 to January 2018. Following the Population, Intervention, Comparator, Outcome and Study Design format, studies were eligible if they were randomized controlled trials involving adults, used a smartphone app as the primary or sole component of the physical activity intervention, used a no- or minimal-intervention control condition, and measured objective physical activity either in the form of moderate-to-vigorous physical activity minutes or steps. Study quality was assessed using a 25-item tool based on the Consolidated Standards of Reporting Trials checklist. A meta-analysis of study effects was conducted using a random effects model approach. Sensitivity analyses were conducted to examine whether intervention effectiveness differed on the basis of intervention length, target behavior (physical activity alone vs physical activity in combination with other health behaviors), or target population (general adult population vs specific health populations). RESULTS:Following removal of duplicates, a total of 6170 studies were identified from the original database searches. Of these, 9 studies, involving a total of 1740 participants, met eligibility criteria. Of these, 6 studies could be included in a meta-analysis of the effects of physical activity apps on steps per day. In comparison with the control conditions, smartphone apps produced a nonsignificant (P=.19) increase in participants' average steps per day, with a mean difference of 476.75 steps per day (95% CI -229.57 to 1183.07) between groups. Sensitivity analyses suggested that physical activity programs with a duration of less than 3 months were more effective than apps evaluated across more than 3 months (P=.01), and that physical activity apps that targeted physical activity in isolation were more effective than apps that targeted physical activity in combination with diet (P=.04). Physical activity app effectiveness did not appear to differ on the basis of target population. CONCLUSIONS:This meta-analysis provides modest evidence supporting the effectiveness of smartphone apps to increase physical activity. To date, apps have been most effective in the short term (eg, up to 3 months). Future research is needed to understand the time course of intervention effects and to investigate strategies to sustain intervention effects over time.

Project description:BACKGROUND: Physical activity may protect against bladder cancer through several biologic pathways, such as enhanced immune function and decreased chronic inflammation. Physical activity may also indirectly prevent bladder cancer by reducing obesity. A sizeable number of epidemiologic studies have examined the association between physical activity and bladder cancer, but the available evidence has not yet been formally summarised using meta-analysis. METHODS: We performed a systematic literature review and meta-analysis of English-language studies published from January 1975 through November 2013. We followed the PRISMA guidelines and used a random effects model to estimate the summary risk estimates for the association between physical activity and bladder cancer. RESULTS: A total of 15 studies with 5,402,369 subjects and 27,784 bladder cancer cases were included. High vs low levels of physical activity were related to decreased bladder cancer risk (summary relative risk (RR)=0.85, 95% confidence interval (CI)=0.74-0.98; I(2)=83%; P-value for heterogeneity across all studies<0.001). Results were similar for cohort studies (RR=0.89, 95% CI=0.80-1.00; I(2)=64%) and case-control studies (RR=0.71, 95% CI=0.43-1.16; I(2)=87%; P-value for difference=0.108) and they were comparable for women (RR=0.83, 95% CI=0.73-0.94; I(2)=0%) and men (RR=0.92, 95% CI=0.82-1.05; I(2)=67; P-value for difference=0.657). Findings were also comparable for recreational (RR=0.81, 95% CI=0.66-0.99; I(2)=77%) and occupational physical activity (RR=0.90, 95% CI=0.76-1.0; I(2)=76%; P-value for difference=0.374), and they were largely consistent for moderate (RR=0.85, 95% CI=0.75-0.98; I(2)=76%) and vigorous activity (RR=0.80, 95% CI=0.64-1.00;I(2)=87%; P-value for difference=0.535). CONCLUSIONS: Physical activity is associated with decreased risk of bladder cancer. Further studies are required to assess the relations of intensity, frequency, duration, and timing in life of physical activity to bladder cancer risk.

Project description:BackgroundThe range of benefits associated with regular physical activity participation is irrefutable. Despite the well-known benefits, physical inactivity remains one of the major contributing factors to ill-health throughout industrialized countries. Traditional lifestyle interventions such as group education or telephone counseling are effective at increasing physical activity participation; however, physical activity levels tend to decline over time. Consumer-based wearable activity trackers that allow users to objectively monitor activity levels are now widely available and may offer an alternative method for assisting individuals to remain physically active.ObjectiveThis review aimed to determine the effects of interventions utilizing consumer-based wearable activity trackers on physical activity participation and sedentary behavior when compared with interventions that do not utilize activity tracker feedback.MethodsA systematic review was performed searching the following databases for studies that included the use of a consumer-based wearable activity tracker to improve physical activity participation: Cochrane Controlled Register of Trials, MEDLINE, PubMed, Scopus, Web of Science, Cumulative Index of Nursing and Allied Health Literature, SPORTDiscus, and Health Technology Assessments. Controlled trials of adults comparing the use of a consumer-based wearable activity tracker with other nonactivity tracker-based interventions were included. The main outcome measures were physical activity participation and sedentary behavior. All studies were assessed for risk of bias, and the Grades of Recommendation, Assessment, Development, and Evaluation system was used to rank the quality of evidence. The guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement were followed. A random-effects meta-analysis was completed on the included outcome measures to estimate the treatment effect of interventions that included an activity tracker compared with a control group.ResultsThere was a significant increase in daily step count (standardized mean difference [SMD] 0.24; 95% CI 0.16 to 0.33; P<.001), moderate and vigorous physical activity (SMD 0.27; 95% CI 0.15 to 0.39; P<.001), and energy expenditure (SMD 0.28; 95% CI 0.03 to 0.54; P=.03) and a nonsignificant decrease in sedentary behavior (SMD -0.20; 95% CI -0.43 to 0.03; P=.08) following the intervention versus control comparator across all studies in the meta-analyses. In general, included studies were at low risk of bias, except for performance bias. Heterogeneity varied across the included meta-analyses ranging from low (I2=3%) for daily step count through to high (I2=67%) for sedentary behavior.ConclusionsUtilizing a consumer-based wearable activity tracker as either the primary component of an intervention or as part of a broader physical activity intervention has the potential to increase physical activity participation. As the effects of physical activity interventions are often short term, the inclusion of a consumer-based wearable activity tracker may provide an effective tool to assist health professionals to provide ongoing monitoring and support.

Project description:Background:The body of evidence related to the effect of physical activity monitor-based interventions has grown over the recent years. However, the effect of physical activity monitor-based interventions in older adults remains unclear and should be systematically reviewed. Objective:The objective of this systematic review was to estimate the effect of physical activity monitor-based interventions on physical activity behavior in participants aged 65 and above. Subsequently we explored the effect on body mass index, physical capacity, and health-related quality of life and finally the impact of patient- and intervention characteristics. Methods:Searches in MEDLINE, EMBASE, SPORTDiscus, CINAHL, and CENTRAL were performed on April 26, 2018. No publication date filters were applied. References of eligible studies were scrutinized and relevant journals were hand-searched. Randomized controlled trials and randomized cross-over trials investigating the effect of a physical activity monitor-based intervention on physical activity were included. Studies were included if the mean age of the participants was above 65?years, and participants could walk independently with or without walking aids. The Cochrane handbook was used as a template for extracting data and the RoB 2.0 tool was used to assess risk of bias. Random-effects meta-analysis using Hedges g, were used to pool the study results. The main outcome of this study was physical activity. Results:Twenty-one studies with 2783 participants were included. The median participant age in the studies was 70.5?years, the median percentage of male participants was 42%, and the median baseline daily step count was 5268. Physical activity monitor-based interventions had a moderate effect (SMD?=?0.54, 95% CI: 0.34 to 0.73) compared to control interventions, corresponding to an average increase of 1297 steps per day in the intervention groups. No impact of patient and intervention characteristics on the effect estimates were found. Short conclusion:Low quality of evidence was found for a moderate effect of physical activity monitor-based interventions on physical activity compared with control interventions. More studies with higher research methodology standards are required. PROSPERO registration:CRD42018083648.

Dataset Information

Physical activity equivalent labeling vs. calorie labeling: a systematic review and meta-analysis.

Background

Method

Result

Conclusion

Publications

Physical activity equivalent labeling vs. calorie labeling: a systematic review and meta-analysis.

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