Group Differences In Physical Activity Research Articles

Mobile Health Intervention Promoting Physical Activity in Adults Post Cardiac Rehabilitation: Pilot Randomized Controlled Trial.

BackgroundCardiac rehabilitation (CR) is an exercise-based program prescribed after cardiac events associated with improved physical, mental, and social functioning; however, many patients return to a sedentary lifestyle leading to deteriorating functional capacity after discharge from CR. Physical activity (PA) is critical to avoid recurrence of cardiac events and mortality and maintain functional capacity. Leveraging mobile health (mHealth) strategies to increase adherence to PA is a promising approach. Based on the social cognitive theory, we sought to determine whether mHealth strategies (Movn mobile app for self-monitoring, supportive push-through messages, and wearable activity tracker) would improve PA and functional capacity over 2 months.ObjectiveThe objectives of this pilot randomized controlled trial were to examine preliminary effects of an mHealth intervention on group differences in PA and functional capacity and group differences in depression and self-efficacy to maintain exercise after CR.MethodsDuring the final week of outpatient CR, patients were randomized 1:1 to the intervention group or usual care. The intervention group downloaded the Movn mobile app, received supportive push-through messages on motivation and educational messages related to cardiovascular disease (CVD) management 3 times per week, and wore a Charge 2 (Fitbit Inc) activity tracker to track step counts. Participants in the usual care group wore a pedometer and recorded their daily steps in a diary. Data from the 6-minute walk test (6MWT) and self-reported questionnaires were collected at baseline and 2 months.ResultsWe recruited 60 patients from 2 CR sites at a community hospital in Northern California. The mean age was 68.0 (SD 9.3) years, and 23% (14/60) were female; retention rate was 85% (51/60). Our results from 51 patients who completed follow-up showed the intervention group had a statistically significant higher mean daily step count compared with the control (8860 vs 6633; P=.02). There was no difference between groups for the 6MWT, depression, or self-efficacy to maintain exercise.ConclusionsThis intervention addresses a major public health initiative to examine the potential for mobile health strategies to promote PA in patients with CVD. Our technology-based pilot mHealth intervention provides promising results on a pragmatic and contemporary approach to promote PA by increasing daily step counts after completing CR.Trial RegistrationClinicalTrials.gov NCT03446313; https://clinicaltrials.gov/ct2/show/NCT03446313

Pilot Test of an Appreciative Inquiry Intervention in Hypertension Self-management.

We implemented an Appreciative Inquiry (AI) intervention to assist people with hypertension improve diet, physical activity, and blood pressure. In a two-group randomized controlled trial conducted over 12 weeks, 50 participants were recruited at an urban outpatient health care clinic. The intervention used participants' high peak positive experiences to promote behavior change, during two face-to-face individual sessions and three coaching telephone calls. Data were analyzed using test of differences between groups and analysis of covariance controlling for confounding variables. The intervention group had significantly higher levels of ideal self, positive emotions, and self-efficacy for chronic disease management than the control group. No significant group differences in physical activity, diet, or blood pressure. Findings provide empirical evidence about the underlying processes by which AI may promote health behavior change. Future research should examine the effectiveness of this AI intervention in a larger sample of patients and over a longer intervention period.

Differences in Physical Activity and Diet Patterns between Non-Rural and Rural Adults.

Background: It is unclear how rural occupations and lifestyles may play a role in shaping physical activity and diet behaviors that contribute to the rural–urban obesity disparity. Methods: Data come from the prospective and observational South Dakota Rural Bone Health Study, which included adults aged 20–66 years in three groups: (1) non-rural non-Hutterite, (2) rural non-Hutterite, and (3) rural Hutterite. Physical activity data were collected using 7-day physical activity questionnaires, and hours per day in physical activity categories are reported. Diet data were collected using food frequency questionnaires, and food group servings per day (svg/day) are reported. Mixed models were generated to determine group differences in physical activity and diet outcomes, and marginal group means are presented. Results: Among females, both rural groups spent more time in moderate activity (4.8 ± 0.13 h/day and 4.7 ± 0.09 h/day vs. 3.5 ± 0.11 h/day, both p < 0.001) and vigorous activity (0.58 ± 0.03 h/day and 0.53 ± 0.02 h/day vs. 0.43 ± 0.03 h/day, both p < 0.01) and less time sitting (4.4 ± 0.13 h/day and 4.3 ± 0.09 h/day vs. 5.0 ± 0.11 h/day, both p < 0.001) on weekdays than non-rural groups. Hutterite females spent fewer hours in moderate activity (2.6 ± 0.08 h/day vs. 4.5 ± 0.11 h/day, p < 0.001) and vigorous activity (0.18 ± 0.02 h/day vs. 0.46 ± 0.02 h/day, p < 0.001) on weekend days compared to rural females. Hutterite females consumed more fruits (2.2 ± 0.06 svg/day vs. 1.7 ± 0.10 svg/day, p < 0.001) and vegetables (3.6 ± 0.08 svg/day vs. 2.7 ± 0.12 svg/day, p < 0.001) than rural females. Among males, both rural groups spent more time in moderate activity (4.9 ± 0.13 h/day and 6.1 ± 0.12 h/day vs. 3.0 ± 0.16 h/day, both p < 0.001) and less time sitting (4.1 ± 0.13 h/day and 3.4 ± 0.12 h/day vs. 6.0 ± 0.15 h/day, both p < 0.001) on weekdays compared to non-rural groups. Hutterite males spent less time in moderate activity (2.1 ± 0.10 h/day vs. 4.1 ± 0.11 h/day, p < 0.001) and vigorous activity (0.15 ± 0.04 h/day vs. 0.74 ± 0.04 h/day, p < 0.001) on weekend days compared to rural males. Hutterite males consumed more vegetables (3.0 ± 0.10 svg/day vs. 2.0 ± 0.11 svg/day, p < 0.001) than rural males. Conclusions: A rural occupation and lifestyle appear to contribute to differences in physical activity, while traditional rural lifestyle practices contribute to differences in diet.

Knee confidence in youth and young adults at risk of post-traumatic osteoarthritis 3–10 years following intra-articular knee injury

ObjectivesTo examine differences in knee confidence between individuals with a history of youth sport-related knee injury and uninjured controls. DesignHistorical cohort study. MethodsParticipants include 100 individuals who sustained a youth sport-related intra-articular knee injury 3–10 years previously and 100 age-, sex- and sport-matched uninjured controls. Outcomes included: Knee confidence (Knee Osteoarthritis and Outcome Score); fat mass index (FMI; dual-energy X-ray absorptiometry); and weekly physical activity (modified Godin–Shephard Leisure Time Questionnaire). Mean within-pair differences (95% CI) were calculated for all outcomes. Unadjusted and adjusted (FMI and physical activity) conditional (matched-design) logistic regression (OR 95% CI) examined the association between injury history and knee confidence. ResultsMedian age of participants was 22 years (range 15–26) and median age at injury was 16 years (range 9–18). Forty-nine percent (95% CI; 39.0, 59.0) of previously injured participants were bothered by knee confidence, compared to 12% (5.5, 18.5) of uninjured participants. Although there was no between group difference in physical activity, injured participants had higher FMI compared to controls (within-pair difference; (95% CI): 1.05kg/m2; (0.53, 1.57)). Logistic regression revealed that injured participants had 5.0 (unadjusted OR; 95% CI; 2.4, 10.2) and 7.5 times (adjusted OR; 95% CI: 2.7, 21.1) greater odds of being bothered by knee confidence than controls. ConclusionsKnee confidence differs between individuals with a previous youth sport-related knee injury and healthy controls. Knee confidence may be an important consideration for evaluating osteoarthritis risk after knee injury and developing secondary prevention strategies.

The Relationship between Cell Phone Use, Physical Activity, and Sedentary Behavior In Adults above College-age

While there is evidence of a positive relationship between cellular telephone (cell phone) use and sedentary behavior, but not physical activity in college-aged individuals (18-29 years old), these relationships have not been tested in individuals older than college age (≥ 30 years old). This research is warranted as cell phone use is inversely associated with age; thus these relationships may be different in older individuals. PURPOSE: To assess the relationship between cell phone use, physical activity and sedentary behavior in adults older than college age (≥ 30 years old). METHODS: Adults aged 30-63 years (N = 69, 51 ± 8 years old) wore physical activity monitors (accelerometers) for seven days and completed surveys assessing daily cell phone use, physical activity, and sedentary behavior. Pearson’s correlation analyses were performed to assess relationships between cell phone use and age, physical activity, and sedentary behavior. Participants were then split into tertiles based on total cell phone use (low, moderate, and high) and a MANCOVA (sex and age as covariates) was used to determine if there were group differences in physical activity and sedentary behavior. RESULTS: Cell phone use ( = 125.2 ± 146.8 minutes per day) was inversely associated with age (r = - 0.3, p = 0.005). Cell phone use was not associated with objectively- or subjectively-measured physical activity or sedentary behavior (r ≤ 0.1, p ≥ 0.3 for all). There were also no significant differences in physical activity or sedentary behavior between the low, moderate, and high cell phone user groups (F ≤ 2.0, p ≥ 0.12 for all). CONCLUSION: Consistent with previous research, there was an inverse relationship between cell phone use and age. Unlike what has been reported in college-aged individuals, cell phone use was not associated with sedentary behavior in adults older than college age. Because younger individuals are “digital natives” who have been raised with near-constant access to cell phones this may be their sedentary activity of choice. Conversely, adults who are older may prefer other, more traditional forms of sedentary activities such as watching television and using a desktop computer. This may explain the lack of a relationship between cell phone use and sedentary behavior in adults beyond college age.

Physical activity in pediatric onset multiple sclerosis: Validating a questionnaire for clinical practice and research

BackgroundKnowledge regarding physical activity (PA) and its benefits in pediatric onset multiple sclerosis (POMS) is growing and suggests high levels of inactivity. The utility of a validated screening tool for clinical settings is unknown. This study evaluated the Godin Leisure-Time Exercise Questionnaire (GLTEQ) as a measure of PA in POMS. MethodsPOMS patients (n=27) and healthy controls (n=45) wore an accelerometer over a 7-day period and then completed the GLTEQ. ResultsThe GLTEQ captured expected group differences in PA for vigorous, moderate, and moderate-to-vigorous physical activity (MVPA), confirmed by accelerometry. There was a large, positive correlation between GLTEQ and accelerometry scores for vigorous PA in POMS (r=0.736, p=0.001), and a nearly significant and moderate, positive correlation between MVPA scores (r=0.319, p=.053). ConclusionWe provide evidence that supports the validity of GLTEQ scores as measures of vigorous and MVPA in POMS. Researchers and clinicians might adopt this scale for measuring PA.

ICook 4-H: 0 to 24-Month Accelerometer-Derived Physical Activity and Sedentary Time in Youth

To assess accelerometer-derived physical activity (PA) and sedentary time (ST) from 0 to 24-months in iCook 4-H youth. iCook 4-H was a 5-state, randomized control-treatment family-based childhood obesity prevention intervention promoting cooking, eating and playing together. Youth, 9-10 years old, and their main meal preparer participated in the 14-week program followed by monthly newsletters and bi-yearly booster sessions until 24-months. PA and ST were determined for 124 (Intervention=88; Control=36) youth. Youth wore an Actigraph GT3X+ accelerometer for 7 days at 0, 4, 12, and 24-months. Mean daily minutes of ST, light PA (LPA), moderate PA (MPA), vigorous PA (VPA) and moderate-to-vigorous PA (MVPA) were evaluated during waking hours. Between and within group differences from 0 to 24 months were determined using linear mixed models (R, 3.2.3, Vienna, Austria, 2015); p ≤ 0.05. There were no between group differences in PA or ST at any time-point. PA at all intensity levels decreased and ST increased for both groups from 0 to 24-months (p≤0.001). The percent of participants meeting the PA guidelines (60 minutes of MVPA per day) decreased from 0 (60.8% intervention, 84.5% control) to 24-months (16% intervention, 0% control). iCook 4-H was a multicomponent program following 9-10 year old youth for 24-months that focused on cooking skills, mealtime behavior and conversation, and enhancing PA through daily activities. Greater emphasis on developing PA skills, changing environmental factors, and increasing PA both in and after school may be needed to prevent the decrease in PA that occurs as children age into adolescence.

Physical activity, ambulation, and comorbidities in people with diabetes and lower-limb amputation.

We characterized physical activity (PA) and its relation to physical function and number of comorbidities in people with diabetes and transtibial amputation (AMP), people with diabetes without AMP, and nondisabled adults without diabetes or AMP. Twenty-two individuals with type 2 diabetes mellitus (DM) and transtibial amputation (DM+AMP), 11 people with DM, and 13 nondisabled participants were recruited for this cross-sectional cohort study. Measures included PA volume and intensity, a Timed Up and Go test, a 2-min walk test, and number of comorbidities. The nondisabled group performed greater amounts of PA than the DM group, who performed greater amounts of PA than the DM+AMP group. PA was related to physical function in the DM group and in the DM+AMP group, whereas no such relationship existed in the nondisabled group. PA was not related to number of comorbidities in any group. These findings suggest the ability to walk may affect overall performance of PA. Alternately, PA may alleviate walking problems. This possibility is of interest because issues with walking may be modifiable by improved levels and intensity of PA. PA's lack of relation to number of comorbidities suggests that factors beyond multiple morbidities account for group differences in PA.

Effect of exercise referral schemes in primary care on physical activity and improving health outcomes: systematic review and meta-analysis

Objective To assess the impact of exercise referral schemes on physical activity and health outcomes.Design Systematic review and meta-analysis.Data sources Medline, Embase, PsycINFO, Cochrane Library, ISI Web of Science, SPORTDiscus,...

Association between physical activity, insulin resistance, body fat, and leptin in patients after gastric bypass surgery, obese, and non‐obese controls

Physical activity (PA) is inversely related with body fat, insulin resistance (IR), and leptin. However, these associations are not clear in patients after gastric bypass surgery (GBS). We hypothesized an inverse relation between PA, BMI, IR, and leptin; and a positive relation between leptin, BMI, and IR in a group of 9 patients after GBS, 8 obese (Ob), and 7 non‐obese (N‐Ob) controls (age=39.0±5.7, 27.7±6.9, 28.0±10.2 yr, respectively). Subjects wore an accelerometer from 6‐7 days, and underwent measurements of height, weight, DEXA, blood glucose, insulin and leptin. IR was estimated using HOMA. Between group differences in PA, BMI, IR, and leptin were determined with ANOVA; and the relation between these variables was determined with simple linear regressions. Between group differences were observed for BMI (Ob=38.7±1.6, GBS=30.4±1.5, N‐Ob=23.8±1.7 kg/m2), IR (Ob=3.0±0.5, GBS=1.1±0.5, N‐Ob=0.7±0.5), and leptin (Ob=55.9, GBS=28.7±4.5, N‐Ob=5.1±5.6 ng/ml). PA was not different between groups. Inverse associations were observed between PA and BMI (r= ‐ 0.55), and leptin (r= ‐ 0.56); and positive associations were observed between leptin and BMI (r= 0.92), and IR (r= 0.63). PA appears to be associated with the control of obesity and IR possibly via reductions in leptin, a mechanism that requires further study.Funded by NIH CTSA UL1‐RR24150, NIH CTSA KL2‐RR024151

Activity and Barriers in Girls (8-16 yr) Based on Grade and Maturity Status

Minimal research has examined whether the decline in physical activity (PA) among adolescent girls is associated with chronological age (CA) or biological age (BA). To describe the PA levels and perceived barriers to PA of adolescent girls grouped by school grade and maturity status (i.e., early or late maturing) within grades. Two hundred and twenty-one girls (aged 8-16 yr, grades 4-10) wore an Actical accelerometer for 7 d and then completed a semistructured, open-ended questionnaire on perceived barriers to PA over the 7-d period. Predicted age at peak height velocity and recalled age at menarche were used to assess maturity among the elementary and high school girls, respectively. Maturity and grade group differences in PA were assessed using a MANCOVA and independent sample t-test and barriers to PA using chi-squared statistics. Daily minutes spent in moderate to vigorous PA decreased by 40% between grades 4 and 10. Within grade groupings, no differences in PA were found between early and late maturing girls (P > 0.05). Grades 4 to 6 participants cited more interpersonal (i.e., social) barriers. Grades 9 to 10 participants cited more institutional barriers to PA, primarily revolving around the institution of school. No differences were found in types of barriers reported between early and late maturing girls. Because PA and types of perceived barriers to PA were dependent on grade, future research should work to identify the most salient (i.e., frequent and limiting) barriers to PA by CA in youth. Once reliably was identified, multipronged intervention strategies must be tested for effectiveness to help youth cope with their salient barriers.

Explaining physical activity levels from a self-efficacy perspective: the physical activity counseling trial

The Physical Activity Counseling (PAC) trial compared the effects of a 13-week primary care physical activity (PA) intervention that incorporated a PA counselor into a health care practice compared to a control condition on PA over a 25-week period and showed group differences in PA were present at 6 and 13 weeks. The main purpose was to examine the mediating effect of 6-week task and barrier self-efficacy on the intervention versus control group/13-week PA relationships. A secondary purpose was to determine whether task and barrier self-efficacy were significantly related to PA throughout the trial for both groups. Participants were primarily sedentary individuals who received a 2- to 4-min PA intervention from their primary care provider, after which they were randomly assigned to the intervention (n = 61) or control condition (n = 59). Self-reported PA and task (barrier) self-efficacy measures were obtained during (i.e., baseline, 6 and 13 weeks) and after (i.e., 19 and 25 weeks) the intervention in both groups. Six-week task and barrier self-efficacy had a small mediating effect. Furthermore, barrier self-efficacy had a significant relationship with PA throughout the trial, whereas the relationship between task self-efficacy and PA became significantly weaker as the trial progressed. PAC interventions among primarily sedentary individuals should be partly based on barrier and task self-efficacy. However, the stability of the task self-efficacy/PA relationship needs further examination.

Effects of tailoring health messages on physical activity

Computer-tailored printed education can be a promising way of promoting physical activity. The present study tested whether computer-tailored feedback on physical activity is effective and whether there are differences between respondents with low and high motivation to change. Respondents (n = 487) were randomly assigned to a tailored intervention group or a no information control group. Physical activity and determinants were measured at baseline and after 3 months. At post-test, the motivated respondents in the control group were more likely not to meet the recommendation for physical activity than to meet it, and motivated respondents in the experimental group were more likely to engage in transport-related activities and showed more improvement over time for the total activity score than respondents in the control group (beta = 0.24, P = 0.02). Both groups improved their behaviour over time. No group differences in physical activity were found for the unmotivated respondents. The results showed that the effects of the tailored feedback were restricted to respondents who had a positive motivation to change at baseline. Possible explanations could be that unmotivated respondents were unwilling to read and process the information because they felt 'no need to change'. Alternatively, one tailored feedback letter may not have been sufficient for this unmotivated group.

Association of physical activity with body-composition indexes in children aged 6–8 y at varied risk of obesity

Physical inactivity increases the risk of obesity, but the relations between reported levels of physical activity (PA) and measures of body fatness (BF) in children are remarkably inconsistent. We examined the relation between objective measures of PA and body-composition indexes in nonobese children. A cross-sectional study was conducted in 100 children aged 6-8 y who were recruited according to their risk of future obesity: high-risk children had >/=1 obese parent [body mass index (BMI; in kg/m(2)): >30] and low-risk children had 2 nonobese biological parents (BMI: <30). Free-living activity energy expenditure (AEE) and PA level were calculated from 7-d doubly labeled water measurements, time spent in light-intensity activity was assessed by heart rate monitoring, and body composition was determined from isotopic dilution. To adjust for body size, fat mass and fat-free mass were normalized for height and expressed as fat mass index (FMI) and lean mass index (LMI), respectively. High-risk children had significantly higher BMI, LMI, and FMI than did low-risk children, but no group differences in PA were found. AEE and PA level were positively associated with LMI and, after adjustment for sex and fat-free mass, negatively associated with FMI but not with BMI. Boys who spent more than the median time in light-intensity activities had significantly higher FMI than did less sedentary boys. This difference was not observed in girls. AEE and PA level were negatively associated with BF in nonobese children. Accurate measures of body composition are essential to appropriate assessment of relations between PA and obesity risk.

Dopamine D2 Receptor Genotypes And Physical Activity Levels

PURPOSE Dopamine influences physical activity via effects on motor control and motivation. Reduced D2 density has been associated with reduced physical activity. The DRD2 A1 allele is associated with reduced D2 receptors; therefore, this genotype may be associated with a more sedentary lifestyle. We examined the relationship between DRD2 genotypes and objectively measured physical activity and physical fitness. METHODS 31 adult subjects (18 males- mean age 45y; 13 females-mean age 48y) who had DRD2genotyping performed a submaximal cycle ergometer test to estimate aerobic fitness. Subjects walked on a treadmill wearing an accelerometer at an exercise intensity of 3 Mets to determine the accelerometer g value associated with each subject's moderate to vigorous physical activity level (MVPA, ≥3 Mets). They then wore the accelerometers for 2 weekdays and one weekend day to determine free-living physical activity levels. Group differences in physical activity and aerobic fitness were analyzed using a 2 sex × 2 genotype ANOVA. RESULTS Females with an A1 allele engaged in 33% less physical activity than females without an A1 allele (866.2±120.0 vs. 1291.0±96.0 min, p=0.01) due to less low intensity (< 3 Mets) physical activity (766.8±100.9 vs. 1150.1±80.1 min, p=0.005). There was no effect of genotype on MVPA or fitness in females. There was no effect of DRD2 genotype on male total activity time, low intensity physical activity, MVPA or fitness. CONCLUSIONS Females with a dopamine D2 receptor genotype that is associated with fewer D2 receptors have lower objectively measured physical activity levels than females with a genotype associated with a greater number of D2 receptors.

Dopamine D2 Receptor Genotypes And Physical Activity Levels

PURPOSE Dopamine influences physical activity via effects on motor control and motivation. Reduced D2 density has been associated with reduced physical activity. The DRD2 A1 allele is associated with reduced D2 receptors; therefore, this genotype may be associated with a more sedentary lifestyle. We examined the relationship between DRD2 genotypes and objectively measured physical activity and physical fitness. METHODS 31 adult subjects (18 males- mean age 45y; 13 females-mean age 48y) who had DRD2genotyping performed a submaximal cycle ergometer test to estimate aerobic fitness. Subjects walked on a treadmill wearing an accelerometer at an exercise intensity of 3 Mets to determine the accelerometer g value associated with each subject's moderate to vigorous physical activity level (MVPA, ≥3 Mets). They then wore the accelerometers for 2 weekdays and one weekend day to determine free-living physical activity levels. Group differences in physical activity and aerobic fitness were analyzed using a 2 sex × 2 genotype ANOVA. RESULTS Females with an A1 allele engaged in 33% less physical activity than females without an A1 allele (866.2±120.0 vs. 1291.0±96.0 min, p=0.01) due to less low intensity (< 3 Mets) physical activity (766.8±100.9 vs. 1150.1±80.1 min, p=0.005). There was no effect of genotype on MVPA or fitness in females. There was no effect of DRD2 genotype on male total activity time, low intensity physical activity, MVPA or fitness. CONCLUSIONS Females with a dopamine D2 receptor genotype that is associated with fewer D2 receptors have lower objectively measured physical activity levels than females with a genotype associated with a greater number of D2 receptors.