Tracking of Leisure Time Physical Activity during 28 yr in Adults

DE-PASS Best Evidence Statement (BESt): Determinants of self-report physical activity and sedentary behaviours in children in settings: A systematic review and meta-analyses

Previous physical activity interventions for children (5-12yrs) have aimed to change determinants associated with self-report physical activity behaviour (PAB) and/or sedentary behaviour (SB), however, the associations between these determinants and PAB/SB in different settings are uncertain. The present study aimed to identify modifiable determinants targeted in previous PAB/SB interventions for children. Intervention effects on the determinants and their associations with self-report PAB/SB were assessed across settings. Search of relevant interventions from pre-defined databases was conducted up to July 2023. Randomized and non-randomized controlled trials with modifiable determinants were included. Data extraction and risk of bias assessments were conducted by two independent researchers. Where data could be pooled, we performed Robust Bayesian meta-analyses. Heterogeneity, publication bias and certainty of evidence were assessed. Fifteen studies were deemed eligible to be included. Thirty-seven unique determinants within four settings were identified-school, family, school with family/home, and community with(out) other settings. Ninety-eight percent of determinants belonged to individual/interpersonal determinant categories. Narratively, intervention effects on student perception of teachers' behaviour (school), self-management, perceived barriers, external motivation, exercise intention, parental modeling on SB (school with family/home) and MVPA expectations (community) were weak to strong, however, corresponding PAB/SB change was not evident. There were negligible effects for all other determinants and the corresponding PAB/SB. Meta-analyses on self-efficacy, attitude, subjective norm and parental practice and PAB/SB in two settings showed weak to strong evidence against intervention effect, while the effect on knowledge could not be determined. Similarly, publication bias and heterogeneity for most analyses could not be ascertained. We found no concrete evidence of association between the modifiable determinants and self-report PAB/SB in any settings. This is presumably due to intervention ineffectiveness. Design of future interventions should consider to follow the systems-based approach and identify determinants unique to the context of a setting, including policy and environmental determinants.

Relationship between free-time physical activity and sleep quality in Brazilian university students

Poor sleep quality and low or no free-time physical activity (FTPA) practice are highly prevalent among university students, but the association between these conditions is still unclear. This cross-sectional study analyzed the relationship between FTPA and sleep quality. An online questionnaire was conducted with university students from a public university in southern Brazil in 2019. The weekly frequency of FTPA was self-reported, and sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). Logistic regression and ANCOVA models were performed and adjusted for confounders. Among the 2,626 students analyzed, 52.2% did not practice the FTPA, and 75.6% had poor sleep quality (PSQI > 5). In the adjusted analysis, practicing FTPA 4-7 times/week was associated with poor sleep quality (odds ratio = 0.71; 95% confidence interval = 0.52, 0.97) compared with not practicing FTPA. In addition, those who practiced FTPA had significantly lower means of the global PSQI, subjective sleep quality and duration, sleep disturbances, and daytime dysfunction scores than those who did not practice FTPA. In conclusion, the FTPA may contribute to better sleep quality among university students.

Diversity of change in body mass index and skinfold thickness between different study courses within four years of study among the male students in a university in Poland

Objective: This study examined whether there were significant changes (expectedly increase) in BMI (Body Mass Index), and relative subcutaneous body fat during the four years of study in a university and compared these changes between the students of different courses, viz., Computer science, Law and administration, Humanities and Physical education. Design: This was a prospective follow up study with measurements at two time points with gap of four years. Body mass index, Triceps, subscapular, mid-axillary, abdominal, supra-illiac and medial-calf skinfold thicknesses were measured at two points of time, just after entrance to university and again after completion of four years. Student’s T-test, one-way ANOVA, and repeated measures ANNOVA (two-way) were employed to assess significance of differences in anthropometric measures between groups of students. Setting: The study was conducted at the University of Rzeszów, Poland. Participants: 191 young men university students aged approximately 19.5 years and 24.0 years, at the beginning and after four years, respectively, during this study. Results: Students of all courses underwent increments in BMI, absolute- and relative skinfold thicknesses, except that the students of physical education course did not show change in skinfold thicknesses relative to BMI. Conclusions: It has been concluded that the change in the adiposity profile during the years of study at university varied according to the course types. Further, detailed studies on the nature and cause of such variation occurring between course types may lead to better understanding etiology of overweight and obesity before entering to adult life.

Barriers to high school and university students' physical activity: A systematic review

Physical inactivity commonly occurs throughout one's life, particularly during adolescence and young adulthood. Multiple factors can negatively influence participation in physical activity, but there has been no review examining the barriers to physical activity among high school and university students. Therefore, the aim of this systematic review was to summarize evidence of barriers to the practice of physical activity among high school and university students. The literature search was conducted without time limits using five databases, including CINAHL, Cochrane Library, Embase, PubMed, and Scopus. In total, 59 studies (37 with high school students [n = 22,908] and 22 with university students [n = 15,411]) were included. The main barriers identified in high school and university students were lack of time, lack of motivation, and lack of accessible places. These findings may be useful in designing and implementing evidence-informed interventions and programs for physical activity promotion in students.

How Relevant Is the Place Where First-Year College Students Live in Relation to the Increase in Body Mass Index?

(1) Objective: This study analyzes the evolution of the body mass index (BMI) throughout the academic year associated with changes in the lifestyle associated with the place where students live during the course, lifestyle design, and health strategies for the university community. (2) Methods: A total of 93 first-year nursing students participated in this study. Data were collected throughout the course by administering self-reported questionnaires about eating habits and lifestyles, weight, and height to calculate their BMI and place of residence throughout the course. Data were analyzed using statistical analysis (Mann–Whitney, chi-square, Student’s t-test, repeated-measures analysis of variance, and least significant difference tests). (3) Results: We found that the mean BMI increases significantly throughout the course among all students regardless of sex, age, eating habits, or where they live during the course. At the beginning of the course, the mean BMI was 22.10 ± 3.64. The mean difference between the beginning of the course and the middle has a value of p-value < 0.015 and between the middle of the course and the end a p-value < 0.009. The group that increased the most is found among students who continue to live in the family nucleus rather than those who live alone or in residence. Students significantly changed their eating and health habits, especially those who live alone or in residence. (4) Conclusions: There is an increase in BMI among students. It is necessary to carry out seminars or talks that can help students understand the importance of good eating practices and healthy habits to maintain their weight and, therefore, their health, in the short, medium, and long term and acquire a good quality of life.

Tracking and Changes in Daily Step Counts among Finnish Adults

PURPOSE

This study aimed to investigate the tracking and changes of steps per day in adults and their determinants over 13 yr.

METHODS

A total of 2195 subjects (1236 women) 30-45 yr of age were randomly recruited from the ongoing Cardiovascular Risk in Young Finns Study in 2007 and were followed up in 2020. Steps per day, including both total and aerobic steps per day, were monitored for seven consecutive days with a pedometer in 2007-2008 and 2011-2012 and with an accelerometer in 2018-2020. Tracking was analyzed using Spearman's correlation. Stability and changes of steps per day over time in both low-active and high-active groups (based on median values) were described by percentage agreements, kappa statistics, and logistic regression. Associations of sex, age, and body mass index with the initial number and changes in steps per day were analyzed using linear growth curve modeling.

RESULTS

Tracking correlations of total steps per day at 4-, 9-, and 13-yr intervals were 0.45-0.66, 0.33-0.70, and 0.29-0.60, while corresponding correlations for aerobic steps per day were 0.28-0.55, 0.23-0.52, and 0.08-0.55, respectively. Percentage agreements were higher than 54%, and kappa statistics ranged from slight to fair over time. Compared with the low-active group, the high-active group at baseline had a higher probability of being active later in adulthood. Female sex and higher age were associated directly with the initial number of steps per day and inversely with changes in the number of steps per day. Body mass index was inversely associated with the initial number of steps per day and changes in the number of total steps per day.

CONCLUSION

The 13-yr tracking of steps per day in adulthood was found to be low to moderately high. Daily ambulatory activity is essential to maintaining an active lifestyle throughout adulthood. Changes in the amount of adult steps per day vary by sex, age, and BMI.

Sleep and physical activity in university students: A systematic review and meta-analysis

University students have low levels of physical activity and report disturbances to sleep, which are independently associated with poor health outcomes. Some research suggests that there is a bi-directional relationship between sleep and physical activity in adults. However, the relationship between sleep and physical activity in university students has not yet been evaluated. Therefore, the aim of this systematic review and meta-analysis was to qualitatively synthesise and quantitatively evaluate the evidence for the association between sleep and physical activity in university students. Twenty-nine eligible studies were included, with a total of 141,035 participants (43% men and 57% women). Only four studies used device-based measures of sleep and/or physical activity, with the remainder including self-report measures. Qualitative synthesis found that the majority of studies did not find any association between sleep and physical activity in university students. However, random-effects meta-analysis showed that moderate-to-high intensity physical activity was associated with lower PSQI scores (e.g., better sleep quality) [r = -0.18, 95% CI (-0.37, 0.03), p = 0.100]. Further, a weak negative association between moderate-to-vigorous physical activity level and sleep duration was also found [r = -0.02, 95% CI (-0.16, 0.12), p = 0.760]. As the findings of this review are predominantly derived from cross-sectional investigations, with limited use of device-based measurement tools, further research is needed to investigate the relationship between sleep and physical activity in university students. Future studies should employ longitudinal designs, with self-report and device-based measures, and consider the intensity and time of physical activity as well as records of napping behaviour.

The impact of life events and transitions on physical activity: A scoping review

BACKGROUND

Physical activity (PA) is a fluctuating behavior and prone to change across the life course. Changes in PA may be particularly due to the experience of life events and transitions. For well-timed and successful PA interventions, it is important to understand when and why individuals take up or terminate PA.

OBJECTIVES

This scoping review aims to examine the extent, range, and nature of research on the impact of life events and transitions on PA and to summarize key findings.

METHODS

A systematic literature search was conducted in PubMed, PsycINFO, PsycARTICLES, SPORTDiscus, and Web of Science. Articles were included if they had been published in peer-reviewed journals between 1998 and 2020 and assessed the impact of at least one life event or transition on PA.

RESULTS

107 studies that assessed 72 distinct life events and transitions were included and summarized in ten categories. Events and transitions that are primarily associated with decreases in PA were starting cohabitation, getting married, pregnancy, evolving parenthood, and the transitions from kindergarten to primary school, from primary to secondary school, and from high school to college or into the labor market. Retirement was associated with increases in PA; yet, long-term trajectories across retirement indicated a subsequent drop in activity levels. Divorce was associated with no changes in PA. No trends could be identified for changing work conditions, quitting or losing a job, starting a new relationship, widowhood, moving, and diagnosis of illness.

CONCLUSION

Life events and transitions can be conceptualized as natural interventions that occur across the life course and that are oftentimes associated with changes in PA behavior. Our study indicates that, despite some emerging trends, similar events do not necessarily have similar impacts on PA across individuals. It also shows that the research landscape is characterized by a lack of conceptual clarity and by disparate methodologies, making it difficult to synthesize results across studies.

A prospective study on the effect of self-reported health and leisure time physical activity on mortality among an ageing population: results from the Tromsø study

Background

The prevailing Western ideal of ageing in place, with the option to stay at home as one ages, has led to the development of physical activity guidelines for people of advanced age to increase their quality of life and promote their functional abilities. This study investigates the effect of self-reported health and physical activity on mortality and examines how levels of age-specific physical activity affect self-reported health trajectories in an ageing cohort.

Methods

The sample cohort of the population-based Tromsø Study consists of 24,309 participants aged 25–97 years at baseline. This study involved a survival analysis from 1994 to 2015 and included those who completed two or more surveys (n = 12,241) between 1994 and 2008. The purpose was to examine the relationship between physical activity and self-reported health throughout life using a random coefficient model analysis.

Results

Being sedentary was associated with an increased risk of mortality in the ageing cohort. Subjects who reported neither light physical activity nor hard physical activity had a 57% (OR 1.57, 1.07–2.31) increased risk of all-cause death. Both hard (OR 2.77, 2.35–3.26) and light (OR 1.52, 1.32–1.76) physical activity were positively associated with self-reported health. The effect was age dependent. Vigorous physical activity was most beneficial for individuals younger than 40 years old, while moderate physical activity levels prolonged the period in which good self-reported health was likely.

Conclusions

Poor self-reported health and being sedentary were independently associated with an increased risk of mortality in the participants. Furthermore, physical activity prolonged the period of good self-reported health among older adults in two ways: physical activity habits from early adulthood and onwards were beneficial to self-reported health at an advanced age, and self-reported health was dependent on engagement in moderate intensity physical activity after approximately 65 years of age.

First-year university is associated with greater body weight, body composition and adverse dietary changes in males than females

Background

The transition from high school to university life is a critical time for change, often accompanied by the adoption of negative lifestyle habits including unhealthy nutrition. The purpose of this longitudinal study was to identify sex-specific changes in dietary intake and diet quality, and associated changes in body weight and composition during first-year university.

Methods

Three-hundred and one students (n = 229 females) completed food frequency questionnaires, and had their body weight, body composition, waist and hip circumference measured at the beginning and end of first-year university. Repeated-measures ANOVAs with covariate adjustments were used with variables for sex (between group) and time (within group) to assess these changes.

Results

Students gained body weight and fat during the year (p<0.001). Body mass Index (BMI) also significantly increased (p = 0.032). Males gained more weight (Male:3.8 kg; Female:1.8 kg), fat mass (Male:2.7 kg; Female:1.5 kg), lean mass (Male:1.1 kg; Female:0.3 kg) and BMI (Male:1.2 kg/m²; Female:0.7 kg/m²; p≤0.001 for interactions), and had greater increases in waist circumference (Male:2.7 cm; Female:1.1 cm) and waist:hip ratio (Male:0.02; Female:0.004; p<0.05 for interactions) than females. Energy intake remained the same over the year in both sexes, accompanied by an increase in alcohol (ethanol) in both sexes but more so in males than females (p = 0.011 interaction). Diet quality decreased, characterized by a reduced intake of healthy foods/beverages (p<0.05) in both sexes such as yogurt, cheese, oatmeal, breads, rice, pasta, vegetables, green salad, fruits, steak, fish, nuts and milk, and an increased consumption of unhealthy foods and beverages (p<0.05) such as donuts/cakes, fried chicken, beer and liquor. Significant interactions between sexes indicated that males displayed a more adverse and lower quality eating pattern which included greater intakes of donuts/cakes, fried chicken, beer and liquor, as well as decreased intakes of eggs and vegetables compared to females. Lastly, some dietary intake changes significantly correlated with fat mass and waist circumference change indicating that poor dietary choices were associated with increased adiposity.

Conclusions

Our study demonstrated that during first-year university, both male and female students undergo unfavorable changes in nutrition and body weight/composition that significantly differ between sexes, with males showing more adverse changes. Our results can be used to inform effective sex-specific strategies and interventions to improve dietary habits during the transition to university life.

Physical Activity, Sport Participation, and Perceived Barriers to Engagement in First-Year Canadian University Students

Background: Physical activity (PA) declines during early adulthood with higher rates of inactivity in university students. The authors aimed to examine the frequency, intensity, time, type of PA, and the barriers to PA participation in Canadian students during the first year of university. Methods: Questionnaires assessing PA variables were administered to 301 first-year students at the beginning and end of the academic year. Results: PA decreased over a year. Males engaged in more vigorous activity minutes, more strength training, and more organized sports than females (P < .05). Females participated in more fitness activities than males (P < .05). Intramural (noncompetitive and school organized) sport participation remained constant throughout the year. Significant intrapersonal barriers to PA engagement included stress and perceived self-skill; significant interpersonal barriers included lack of friends and peer influence; and significant structural barriers included homework, class schedule, and overcrowded facilities. Conclusion: PA and sport participation declined, and some differences existed between the sexes. Focus should be placed on reducing the barriers that students' experience that may impact their PA. Interventions/programming to promote different aspects of PA should focus on noncompetitive sport and recreation activities, as well as activities that students can do on their own time. Ensuring the availability of adequate campus facilities is also important.

Uni- and triaxial accelerometric signals agree during daily routine, but show differences between sports

Accelerometers objectively monitor physical activity, and ongoing research suggests they can also detect patterns of body movement. However, different types of signal (uniaxial, captured by older studies, vs. the newer triaxial) and or/device (validated Actigraph used by older studies, vs. others) may lead to incomparability of results from different time periods. Standardization is desirable. We establish whether uniaxial signals adequately monitor routine activity, and whether triaxial accelerometry can detect sport-specific variations in movement pattern. 1402 adolescents wore triaxial Actigraphs (GT3X) for one week and diaried sport. Uni- and triaxial counts per minute were compared across the week and between over 30 different sports. Across the whole recording period 95% of variance in triaxial counts was explained by the vertical axis (5th percentile for R², 91%). Sport made up a small fraction of daily routine, but differences were visible: even when total acceleration was comparable, little was vertical in horizontal movements, such as ice skating (uniaxial counts 41% of triaxial) compared to complex movements (taekwondo, 55%) or ambulation (soccer, 69%). Triaxial accelerometry captured differences in movement pattern between sports, but so little time was spent in sport that, across the whole day, uni- and triaxial signals correlated closely. This indicates that, with certain limitations, uniaxial accelerometric measures of routine activity from older studies can be feasibly compared to triaxial measures from newer studies. Comparison of new studies based on raw accelerations to older studies based on proprietary devices and measures (epochs, counts) will require additional efforts which are not addressed in this paper.

Lifetime risk factors for leisure-time physical inactivity in mid-adulthood

We aimed to identify factors from different life-stages that were associated with inactivity at two adult ages and stability and change between these ages. Leisure-time inactivity (activity frequency <1/wk) was assessed at 33y and 50y in the 1958 British Birth cohort (N = 12,271). We created scores representing several domains, i.e. physical health, mental function, social, family and neighbourhood circumstances at different life-stages, and examined associations with adult inactivity. 31% were inactive at 33y and 50y with 17% deteriorating to, and 18% improving from, inactivity. Adjusting for all domains and life-stages, most concurrent factors were associated with inactivity: e.g. per 1-unit worsening physical status (score range:0-2) ORadjusted for 50y inactivity was 1.56(1.44,1.70). Physical status at 33y was associated with inactivity patterns 33y-to-50y (Relative risk ratios (RRRs) of inactivity persistence and deterioration (vs never inactive) per 1-unit worsening status (score:0-1) were 1.73(1.51,1.99) and 1.28(1.10,1.49) respectively; RRR for improvement (vs persistently inactive) was 0.75(0.63,0.88). Some early-life domain scores were associated with inactivity independent of concurrent factors: e.g. per 1-unit worsening early-life social score (range:0-3) ORadjusted for 50y inactivity was 1.12(1.05,1.19). Highly urbanised neighbourhood in early adulthood was associated with inactivity (e.g. RRRs for persistent inactivity and deterioration were 1.42(1.22,1.65) and 1.15(1.01,1.31) respectively; 0.82(0.68,0.98) for improvement). Concurrent physical and mental function were associated with adult inactivity at two ages; poorer physical status was associated with greater risk of inactivity persistence and deterioration and lower risk of improvement 33y-to-50y. Young adult neighbourhood and early-life social and family circumstances were independently associated with mid-life inactivity.

Correlates of physical activity and sedentary time in young adults: the Western Australian Pregnancy Cohort (Raine) Study

Background

The socioecological model proposes a wide array of factors that influence behaviours. There is a need to understand salient correlates of these activity behaviours in a specific population. However, few studies identified socio-demographic, behavioural, physical, and psychological correlates of objectively-assessed physical activity and sedentary time in young adults.

Methods

This was a cross-sectional analysis of participants in the Raine Study (a pregnancy cohort started in 1989). Australian young adults (mean 22.1 years ± SD 0.6) wore Actigraph GT3X+ accelerometers on the hip 24 h/day for seven days to assess moderate-to-vigorous physical activity (MVPA) and sedentary time (n = 256 women, n = 219 men). Potential correlates were assessed via clinical assessment and questionnaire and included socio-demographic variables (ethnicity, relationship status, work/study status, education, mothers education), health behaviours (food intake, alcohol consumption, smoking status, sleep quality), and physical and psychological health aspects (anthropometrics, diagnosed disorders, mental health, cognitive performance). Backwards elimination (p < 0.2 for retention) with mixed model regressions were used and the gender-stratified analyses were adjusted for demographic variables, waking wear time and number of valid days.

Results

Increased time spent in MVPA was associated with: being single (IRR 1.44 vs in a relationship living together, 95%CI: 1.17, 1.77, p = .001) in women; and better sleep quality in men (lower scores better IRR 0.97, 95%CI: 0.93, 1.00). Less time spent sedentary was associated with: lower mother’s education (− 32.1 min/day, 95%CI -52.9, 11.3, p = 0.002 for having mother with no university degree vs at least a baccalaureate degree) and smoking (− 44.3 min/day, 95%CI: - 72.8, − 15.9, p = .0002) for women; lower education status (− 32.1 min/day, 95%CI: -59.5, − 4.8, p = 0.021 for having no university degree vs at least a baccalaureate degree) and lower depression scores in men (− 2.0, 95%CI: - 3.5, − 0.4, p = 0.014); more alcoholic drinks per week for women (− 1.9 min/day, 95%CI: -3.1, − 0.6, p = 0.003) and men (− 1.0, 95%CI: -1.8, − 0.3, p = 0.007).

Conclusions

Less desirable correlates were associated with positive levels of activity in young Australian adult women and men. Interventions to increase MVPA and decrease sedentary activity in young adults need to specifically consider the life stage of young adults.

Electronic supplementary material

The online version of this article (10.1186/s12889-018-5705-1) contains supplementary material, which is available to authorized users.

The impact of changes in leisure time physical activity on changes in cardiovascular risk factors: results from The Finnmark 3 Study and SAMINOR 1, 1987-2003

Objective: The aim of this study was to examine the associations between changes in leisure time physical activity and changes in cardiovascular risk factors over 16 years and whether they differ between two ethnic groups in Norway.

Methods: Data were extracted from two population-based studies. Altogether, 3671 men and women participated in both surveys, and 30% reported being of Sami ethnicity. Leisure time physical activity was self-reported, and cardiovascular risk factors were measured. ANCOVA analysis was used to examine associations between changes in physical activity and changes in cardiovascular risk factors.

Results: After adjustment for age, sex, smoking, ethnicity and respective baseline values, favourable changes in body mass index (BMI) and levels of triglycerides were most pronounced in those who were active in both surveys (p < 0.05) whereas the opposite was the situation for cholesterol levels (p = 0.003). Changes in systolic blood pressure, diastolic blood pressure and resting heart rate were not significantly associated with change in physical activity. Ethnicity did not influence the associations between physical activity and cardiovascular risk factors.

Conclusion: Traditional cardiovascular risk factors were to a small extent associated with change in leisure time physical activity. Persistent physical activity was associated with beneficial changes in BMI and triglycerides.

Leisure-time physical inactivity and association with body mass index: a Finnish Twin Study with a 35-year follow-up

Background

We investigated the stability and change of leisure-time physical inactivity in adult men and women during a 35-year follow-up. We also analysed the impact of long-term physical inactivity on the development of body mass index (BMI).

Methods

: In this population-based cohort study, 5254 Finnish twin individuals (59% women) participated in four surveys in 1975, 1981, 1990 and 2011. Mean age at baseline was 23.9 years. Individual long-term leisure-time physical activity (LTPA) was categorized into seven classes varying from 'persistently inactive' to 'persistently active'. We used the multivariate multilevel mixed-effects linear regression model and paired-sample t-test in the analyses. Co-twin control design was used for examining within-pair associations.

Results

: Of men 11%, and of women 8%, were persistently inactive. Among both sexes, the mean BMI slope trajectories were steeper among the persistently inactive and those who became inactive than among those who were persistently active. Overall, the inactive participants gained 1.4 kg/m 2 [95% confidence interval (CI) 1.2 to 1.7] more in weight than did the active participants from 1975 to 2011. Among twin pairs discordant for LTPA, the corresponding difference was 1.4 kg/m 2 (95% CI 0.83 to 2.0) in dizygotic pairs and 0.68 kg/m 2 (95% CI 0.05 to1.3) in monozygotic pairs.

Conclusions

Over a 35-year time span from young adulthood, persistently inactive participants and those who had become inactive had greater weight increases than those who were persistently active. This association was also found in twin-pair analyses, although attenuated in monozygotic pairs. This may support the importance of LTPA in weight management, although further causal inference is required.

Investing in college students: the role of the fitness tracker

Fitness trackers are becoming a popular way to encourage physical activity and impact health behaviors. Although many college students may own and use fitness trackers, they remain a high-risk group in terms of rates of obesity and lack of physical activity. In this study, college students were provided with fitness trackers to self-monitor step count. Pre- and post-measures of body composition, resting heart rate and blood pressure, knowledge of physical activity behaviors and perception of wellness were used to determine the impact of the fitness trackers. The research was completed in two phases: phase one with completely voluntary participation and phase two as a part of a required general education wellness course. Results did not indicate a significant change in step count over 12 weeks nor did they show positive change in body measurements; however, there were indicators of activity benefits. Knowledge and perception of wellness were not positively impacted in the voluntary study; however, when the education component was required, some increases in knowledge and perception of wellness were shown in the general education course. Many lessons were learned in the study that should be considered when planning future research with fitness trackers in the college-age setting.

Investigating the Physical Activity Behaviors of Canadian Adults Over Time: Multilevel Sex and Age Group Trajectories Across 2 Decades

BACKGROUND

This study explores changes in the leisure-time physical activities of Canadian adults over time.

METHODS

Using representative panel data from the National Population Health Survey, multilevel analyses of 13,933 respondents aged 18 and older were performed to assess both overall and individual leisure-time physical activity trajectories from 1994 to 2011 and the extent to which these trajectories differ by sex and age groups.

RESULTS

With the exception of those aged 65 and older, there is evidence that as Canadians age their overall levels of physical activity increase over time. However, increases in overall physical activity levels are mainly due to increases in walking, gardening, and home exercise. Increases in these 3 activities in particular compensate for declines in engagement levels over time in most other activities.

CONCLUSIONS

As the demographic shift to an older Canadian population continues, evidence of increasing overall physical activity levels across most age groups in Canada gives reason for optimism.

Association between physical activity levels in mid-life with physical activity in old age: a 20-year tracking study in a prospective cohort

OBJECTIVES

This study aims to examine the tracking and predictability of physical activity in old age from overall physical activity and participation in sport, recreational activity and walking in mid-life.

DESIGN

Prospective population-based cohort study.

SETTING

British Regional Heart Study participants recruited from primary care centres in the UK in 1978-1980.

PARTICIPANTS AND OUTCOME MEASURES

Men (n=3413) self-reported their physical activity at baseline, 12, 16 and 20-year follow-ups and were categorised as inactive or active and having high or low participation in sport, walking and recreational activities. Tracking was assessed using kappa statistics and random effects models. Logistic regression estimated the odds of being active at 20-year follow-up according to physical activity participation in mid-life.

RESULTS

Among 3413 men (mean age at baseline 48.6±5.4 years) with complete data, tracking of overall physical activity was moderate (kappa: 0.23-0.26). Tracking was higher for sports participation (kappa: 0.35-0.38) compared with recreational activity (kappa: 0.16-0.24) and walking (kappa: 0.11-0.15). Intraclass correlation coefficients demonstrated similar levels of stability and only marginally weakened after controlling for covariates. Compared with inactive men, being active at baseline was associated with greater odds of being active at 20-year follow-up (OR 2.7, 95% CI 2.4 to 3.2) after adjusting for sociodemographic, health and lifestyle variables. Playing sport in mid-life was more strongly associated with being active at 20-year follow-up than other domains, particularly when sport participation began earlier in life.

CONCLUSION

Being physically active in mid-life increases the odds of being active in old age. Promoting physical activity in later life might be best achieved by promoting sport participation earlier in the life course.

Stability of physical activity, fitness components and diet quality indices

BACKGROUND

Regular physical activity (PA), a high level of fitness and a high diet quality are positively associated with health. However, information about stability of fitness components and diet quality indices is limited. This study aimed to evaluate stability of those parameters.

METHODS

This study includes 652 adults (men=57.56 (10.28) years; women=55.90 (8.34) years at follow-up) who participated in 2002-2004 and returned for follow-up at the Policy Research Centre Leuven in 2012-2014. Minutes sport per day and Physical activity level (PAL) were calculated from the Flemish Physical Activity Computerized Questionnaire. Cardiorespiratory fitness (CRF), morphological fitness (MORF; body mass index and waist circumference) and metabolic fitness (METF) (blood cholesterol and triglycerides) were used as fitness components. Diet quality indices (Healthy Eating Index-2010 (HEI), Diet Quality Index (DQI), Mediterranean Diet Score (MDS)) were calculated from a diet record. Tracking coefficients were calculated using Pearson/Spearman correlation coefficients (rPearson) and intra-class correlation coefficients (rICC).

RESULTS

In both men (rPearson&ICC=0.51) and women (rPearson=0.62 and rICC=0.60) PAL showed good stability, while minutes sport remained stable in women (rPearson&ICC=0.57) but less in men (rPearson&ICC=0.45). Most fitness components remained stable (r⩾0.50) except some METF components in women. In general the diet quality indices and their components were unstable (r<0.50).

CONCLUSIONS

PAL and the majority of the fitness components remained stable, while diet quality was unstable over 10 years. For unstable parameters such as diet quality measurements are needed at both time points in prospective research.

Secular trends and correlates of physical activity: The Tromsø Study 1979-2008

Background

The aim was to describe secular trends in leisure time physical activity (LTPA) and work related physical activity (WPA) from 1979 to 2008. Additionally, we explored potential cross-sectional and longitudinal correlates of LTPA and WPA.

Methods

Data are collected from 34,898 individuals (49.7% men) aged >20 years who participated in at least one Tromsø Study survey between 1979 and 2008. In each survey, the participants completed a self-administered questionnaire and underwent physical examinations. LTPA and WPA were assessed by the validated “Saltin-Grimby” 4-scale questions. Potential correlates of LTPA and WPA (sex, age, body mass index (BMI), education, smoking, self-reported cardiovascular disease, self-perceived health, and employment status) were tested using ordinal logistic regression.

Results

The age-adjusted prevalence of participants being inactive in leisure time remained relatively stable around 20% from 1979 to 2008 (range 19.9–23.6%). The age-adjusted prevalence of moderate-vigorous LTPA decreased from 23.2% in 1979–80 to 16.0% in 2001, thereafter the prevalence increased to 24.3% in 2007–08 (P <0.05). The age-adjusted prevalence of being mostly sedentary at work increased gradually from 35.5% in 1979–80 to 53.4% in 2007–08 (P <0.05). Sex, age, education, and smoking were identified as cross-sectional correlates of LTPA and WPA (P <0.05). Men had higher odds of engaging in LTPA than women (adjusted OR 1.52 [95% CI 1.39–1.67] in 2007–08), whereas the association between sex and WPA shifted over time. High education level, not being a smoker, and high WPA were associated with high LTPA, whereas low education level, being a smoker, and high levels of LTPA were associated with high WPA (P <0.05). In general, odds of engaging in LTPA and WPA decreased with age (P <0.05). Individuals with healthy BMI had higher odds of being in a higher LTPA level than those who were underweight and obese (P <0.05). Longitudinal analyses identified sex, age, education, smoking, WPA, and LTPA measured in 1979–80 as determinants of LTPA in 2007–08.

Conclusions

In Norwegian adults, the proportion of sedentary WPA increased from 1979 to 2008, whereas the proportion of inactive LTPA remained stable. Being female, older, smoker, obese or underweight, and low education level were associated with low LTPA levels.

Electronic supplementary material

The online version of this article (doi:10.1186/s12889-016-3886-z) contains supplementary material, which is available to authorized users.

The "Saltin-Grimby Physical Activity Level Scale" and its application to health research

The use of a four-level questionnaire to assess leisure time physical activity (PA) and its validation is reviewed in this paper. This questionnaire was first published in 1968 and has then been used by more than 600,000 subjects, especially in different population studies in the Nordic countries. A number of modifications to the questionnaire have been published. These are mostly minor changes, such as adding practical examples of activities to illustrate the levels of PA. Some authors have also added duration requirements that were not included for all levels of PA in the original version. The concurrent validity, with respect to aerobic capacity and movement analysis using objective measurements has been shown to be good, as has the predictive validity with respect to various risk factors for health conditions and for morbidity and mortality.

Association between education and future leisure-time physical inactivity: a study of Finnish twins over a 35-year follow-up

Background

Education is associated with health related lifestyle choices including leisure-time physical inactivity. However, the longitudinal associations between education and inactivity merit further studies. We investigated the association between education and leisure-time physical inactivity over a 35-year follow-up with four time points controlling for multiple covariates including familial confounding.

Methods

This study of the population-based Finnish Twin Cohort consisted of 5254 twin individuals born in 1945–1957 (59 % women), of which 1604 were complete same-sexed twin pairs. Data on leisure-time physical activity and multiple covariates was available from four surveys conducted in 1975, 1981, 1990 and 2011 (response rates 72 to 89 %). The association between years of education and leisure-time physical inactivity (<1.5 metabolic equivalent hours/day) was first analysed for each survey. Then, the role of education was investigated for 15-year and 35-year inactivity periods in the longitudinal analyses. The co-twin control design was used to analyse the potential familial confounding of the effects. All analyses were conducted with and without multiple covariates. Odds Ratios (OR) with 95 % Confidence Intervals (CI) were calculated using logistic and conditional (fixed-effects) regression models.

Results

Each additional year of education was associated with less inactivity (OR 0.94 to 0.95, 95 % CI 0.92, 0.99) in the cross-sectional age- and sex-adjusted analyses. The associations of education with inactivity in the 15- and 35-year follow-ups showed a similar trend: OR 0.97 (95 % CI 0.93, 1.00) and OR 0.94 (95 % CI 0.91, 0.98), respectively. In all co-twin control analyses, each year of higher education was associated with a reduced likelihood of inactivity suggesting direct effect (i.e. independent from familial confounding) of education on inactivity. However, the point estimates were lower than in the individual-level analyses. Adjustment for multiple covariates did not change these associations.

Conclusions

Higher education is associated with lower odds of leisure-time physical inactivity during the three-decade follow-up. The association was found after adjusting for several confounders, including familial factors. Hence, the results point to the conclusion that education has an independent role in the development of long-term physical inactivity and tailored efforts to promote physical activity among lower educated people would be needed throughout adulthood.

Early Life Factors and Adult Leisure Time Physical Inactivity Stability and Change

PURPOSE

Physical inactivity has a high prevalence and associated disease burden. A better understanding of influences on sustaining and changing inactive lifestyles is needed. We aimed to establish whether leisure time inactivity was stable in midadulthood and whether early life factors were associated with inactivity patterns.

METHODS

In the 1958 British birth cohort (n = 12,271), leisure time inactivity (frequency, less than once a week) assessed at 33 and 50 yr was categorized as "never inactive," "persistently inactive," "deteriorating," or "improving." Early life factors (birth to 16 yr) were categorized into three (physical, social, and behavioral) domains. Using multinomial logistic regression, we assessed associations with inactivity persistence and change of factors within each early life domain and the three domains combined with and without adjustment for adult factors.

RESULTS

Inactivity prevalence was similar at 33 and 50 yr (approximately 31%), but 17% deteriorated and 18% improved with age. In models adjusted for all domains simultaneously, factors associated with inactivity persistence versus never inactive were prepubertal stature (8% lower risk/height SD), poor hand control/coordination (17% higher risk/increase on four-point scale), cognition (16% lower/SD in ability) (physical); parental divorce (25% higher), class at birth (7% higher/reduction on four-point scale), minimal parental education (16% higher), household amenities (2% higher/increase in 19-point score (high = poor)) (social); and inactivity (22% higher/reduction in activity on four-point scale), low sports aptitude (47% higher), smoking (30% higher) (behavioral). All except stature, parental education, sports aptitude, and smoking were associated also with inactivity deterioration. Poor hand control/coordination was the only factor associated with improved status (13% lower/increase on four-point scale) versus persistently inactive.

CONCLUSIONS

Adult leisure time inactivity is moderately stable. Early life factors are associated with persistent and deteriorating inactivity over decades in midadulthood but rarely with improvement.

Trajectories of objectively measured physical activity in free-living older men

Supplemental digital content is available in the text.

Background

The steep decline in physical activity (PA) among the oldest old is not well understood; there is little information about the patterns of change in PA and sedentary behaviour (SB) in older people. Longitudinal data on objectively measured PA data can give insights about how PA and SB change with age.

Methods

Men age 70–90 yr, from a United Kingdom population-based cohort wore a GT3X accelerometer over the hip annually on up to three occasions (56%, 50%, and 51% response rates) spanning 2 yr. Multilevel models were used to estimate change in activity. Men were grouped according to achieving ≥150 min·wk⁻¹ of MVPA in bouts of ≥10 min (current guidelines) at two or three time points.

Results

A total of 1419 ambulatory men had ≥600 min wear time on ≥3 d at ≥2 time points. At baseline, men took 4806 steps per day and spent 72.5% of their day in SB, 23.1% in light PA, and 4.1% in moderate-to-vigorous PA (MVPA). Mean change per year was −341 steps, +1.1% SB, −0.7% light PA, and −0.4% MVPA each day (all P < 0.001). A total of 76.3% (n = 1083) never met guidelines (“stable low”), 7.9% (n = 112) consistently met guidelines (“stable high”), 8.2% (n = 116) stopped meeting guidelines by the last occasion (“decreasers”), and 4.9% (n = 69) started meeting guidelines by the last occasion (“increasers”). “Decreasers” spent 69.3% of each day in SB at baseline, which increased by 2% per year (P < 0.005), light activity remained at 23.3% (change, −0.2% per year; P = 0.4), and total MVPA decreased from 7.1% by −1.7% per year, (P < 0.001). The number of sedentary bouts >30 min increased from 5.1 by 0.1 per year (P = 0.02).

Conclusions

Among older adults, the steep decline in total PA occurred because of reductions in MVPA, while light PA is relatively spared and sedentary time and long sedentary bouts increase.

Self-reported moderate-to-vigorous leisure time physical activity predicts less pain and disability over 12 months in chronic and persistent low back pain

BACKGROUND

Physical deconditioning in combination with societal and emotional factors has been hypothesized to compromise complete recovery from low back pain (LBP). However, there is a lack of longitudinal studies designed to specifically investigate physical activity as an independent prognostic factor. We conducted a prognostic study to investigate whether levels of leisure time physical activity are independently associated with clinical outcomes in people seeking care for chronic and persistent LBP.

METHODS

A total of 815 consecutive patients presenting with LBP to an outpatient spine centre in secondary care were recruited. Separate multivariate linear regression analyses were performed to investigate whether levels of leisure time physical activity (i.e., sedentary, light and moderate-to-vigorous leisure time physical activity levels) predict pain and disability at 12-month follow-up, after adjusting for age, pain, episode duration, disability, neurological symptoms, depression and fear of movement.

RESULTS

Final models showed evidence of an association between baseline physical activity and 12-month outcomes (p < 0.001). In both models, the moderate-to-vigorous physical activity group reported less pain and disability compared with the sedentary group.

CONCLUSIONS

Our findings suggest that physical activity levels may have a role in the prognosis of LBP. Specific domains of physical activity warrant further investigation to better understand this association.