More Than “Just” Walking: An Observational Study of Dog-Related Physical Activities

Dog ownership has been shown to correlate with physical activity (PA). However, knowledge about the intensities of dog-related PA (drPA) is still lacking. To investigate the duration and intensity of drPA in consideration of PA guidelines, an observational study of dog owners (DO) was conducted. For this purpose, DO were recruited in metropolitan and nonmetropolitan regions of Cologne, Germany. A total of 44 male and female DO (18–64 years) without cardiovascular or cardiopulmonary diseases participated in the study. Validated questionnaires were used to determine the PA profile and relationship of DO to their dog. Participants reported their drPA in an activity diary. Steps were determined by a pedometer. A heart rate (HR) monitor was used to analyze HR and percentage of maximum HR (HRmax) during all drPA. Overall, drPA makes up a large part of the duration of the overall PA recorded. HR and percentage of HRmax were significantly lower during dog walking (DW) than during other drPA. Nearly 90% of DW time was performed at light or very light intensity. No correlation between objectively measured PA and attachment to the dog was found. Two single case analyses show that other drPA reach high intensity levels and thus can be rated as moderate to vigorous intensity activities. The current investigation demonstrates that DW alone is insufficient to reach PA guidelines. Consequently, other drPA might have more beneficial effects than DW. In future investigations, the role of other types of drPA on PA levels needs to be taken into consideration to improve PA status in healthy populations

The perception of the neighborhood environment changes after participation in a pedometer based community intervention

<p>Abstract</p> <p>Background</p> <p>The aim of this study was to investigate whether the perception of the neighbourhood environment alters when changing the physical activity behaviour through a pedometer intervention.</p> <p>Findings</p> <p>The intervention was implemented for 15 weeks in a small village in Germany, and was based on the individual baseline activity level. Eighty-two inhabitants participated in the study and completed an environmental questionnaire before and after the intervention. Results showed that after the intervention the participants perceived a lower distance to local facilities, a higher availability of bike lanes and infrastructures, a better maintenance of infrastructure, a better network and a safer traffic situation.</p> <p>Conclusion</p> <p>This suggests that a change in the levels of physical activity merges the levels of exposure to the environment which results in different environmental perceptions.</p

Who uses height-adjustable desks? - Sociodemographic, health-related, and psycho-social variables of regular users

Wallmann-Sperlich B, Bipp T, Bucksch J, Froboese I. Who uses height-adjustable desks? - Sociodemographic, health-related, and psycho-social variables of regular users. International Journal of Behavioral Nutrition and Physical Activity. 2017;14(1): 26

Socio-demographic, behavioural and cognitive correlates of work-related sitting time in German men and women

Background: Sitting time is ubiquitous for most adults in developed countries and is most prevalent in three domains: in the workplace, during transport and during leisure time. The correlates of prolonged sitting time in workplace settings are not well understood. Therefore, the aim of this study was to examine the gender-specific associations between the socio-demographic, behavioural and cognitive correlates of work-related sitting time. Methods: A cross-sectional sample of working German adults (n = 1515; 747 men; 43.5 ± 11.0 years) completed questionnaires regarding domain-specific sitting times and physical activity (PA) and answered statements concerning beliefs about sitting. To identify gender-specific correlates of work-related sitting time, we used a series of linear regressions. Results The overall median was 2 hours of work-related sitting time/day. Regression analyses showed for men (β = -.43) and for women (β = -.32) that work-related PA was negatively associated with work-related sitting time, but leisure-related PA was not a significant correlate. For women only, transport-related PA (β = -.07) was a negative correlate of work-related sitting time, suggesting increased sitting times during work with decreased PA in transport. Education and income levels were positively associated, and in women only, age (β = -.14) had a negative correlation with work-related sitting time. For both genders, TV-related sitting time was negatively associated with work-related sitting time. The only association with cognitive correlates was found in men for the belief ‘Sitting for long periods does not matter to me’ (β = .10) expressing a more positive attitude towards sitting with increasing sitting durations. Conclusions: The present findings show that in particular, higher educated men and women as well as young women are high-risk groups to target for reducing prolonged work-related sitting time. In addition, our findings propose considering increasing transport-related PA, especially in women, as well as promoting recreation-related PA in conjunction with efforts to reduce long work-related sitting times

Physical Activity during Work, Transport and Leisure in Germany - Prevalence and Socio-Demographic Correlates

Background This study aimed 1) to provide data estimates concerning overall moderate- and vigorous-intensity physical activity (MVPA) as well as MVPA during work, transport and leisure in Germany and 2) to investigate MVPA and possible associations with socio-demographic correlates. Methods A cross-sectional telephone survey interviewed 2248 representative participants in the age of 18–65 years (1077 men; 42.4±13.4 years; body mass index: 25.3±4.5kg•m−2) regarding their self-reported physical activity across Germany. The Global Physical Activity Questionnaire was applied to investigate MVPA during work, transport and leisure and questions were answered concerning their demographics. MVPA was stratified by gender, age, body mass index, residential setting, educational and income level. To identify socio-demographic correlates of overall MVPA as well as in the domains, we used a series of linear regressions. Results 52.8% of the sample achieved physical activity recommendations (53.7% men/52.1% women). Overall MVPA was highest in the age group 18–29 years (p<.05), in participants with 10 years of education (p<.05) and in participants with lowest income levels <1.500€ (p<.05). Regression analyses revealed that age, education and income were negatively associated with overall and work MVPA. Residential setting and education was positively correlated with transport MVPA, whereas income level was negatively associated with transport MVPA. Education was the only correlate for leisure MVPA with a positive association. Conclusions The present data underlines the importance of a comprehensive view on physical activity engagement according to the different physical activity domains and discloses a need for future physical activity interventions that consider socio-demographic variables, residential setting as well as the physical activity domain in Germany

MVPA MET-minutes•week⁻¹ in overall MVPA and in the domains work, transport and leisure. Sample is stratified by gender, age, BMI, residential setting, education and income.

<p>Data presents the median and the (quartiles). Statistical difference was set by p<.05.</p>a<p>Age group 18–29 years differs significantly from age group 30–45 years.</p>b<p>Age group 18–29 years differs significantly from age group 46–65 years.</p>c<p>Participants with a BMI of <18.5-kg•m⁻² differ significantly from participants with BMI of 18.5–24.9 kg•m⁻².</p>d<p>Participants with a BMI of 18.5–24.9 kg•m⁻² differ significantly from participants with BMI of 25.0–29.9 kg•m⁻².</p>e<p>Participants with a BMI of 18.5–24.9 kg•m⁻² differ significantly from participants with BMI of>30 kg•m⁻².</p>f<p>Participants living in areas with <5.000 inhabitants differ from participants living in areas 5.00–20.000 inhabitants.</p>g<p>Participants living in areas with <5.000 inhabitants differ from participants living in areas 20.00–100.000 inhabitants.</p>h<p>Participants living in areas with <5.000 inhabitants differ from participants living in areas 100.00–500.000 inhabitants.</p>i<p>Participants living in areas with <5.000 inhabitants differ from participants living in areas>500.000 inhabitants.</p>j<p>Participants living in areas with 5.000–20.000 inhabitants differ from participants living in areas 20.00–100.000 inhabitants.</p>k<p>Participants living in areas with 5.000–20.000 inhabitants differ from participants living in areas 100.000–500.000 inhabitants.</p>l<p>Participants living in areas with 5.000–20.000 inhabitants differ from participants living in areas>500.000 inhabitants.</p>m<p>People living in areas with 20.000–100.000 inhabitants differ from participants living in areas 100.00–500.000 inhabitants</p>n<p>Participants living in areas with 20.000–100.000 inhabitants differ from participants living in areas>500.000 inhabitants.</p>o<p>Participants with no graduation differ from participants with 10 years of education.</p>p<p>Participants with no graduation differ from participants with 12 years of education.</p>q<p>Participants with no graduation differ from participants with 13 years of education.</p>r<p>Participants with no graduation differ from participants with university degree.</p>s<p>Participants with 10 years of education differ from participants with 12 years of education.</p>t<p>Participants with 10 years of education differ from participants with 13 years of education.</p>u<p>Participants with 10 years of education differ from participants with university degree.</p>v<p>Participants with 12 years of education differ from participants with 13 years of education.</p>w<p>Participants with 12 years of education differ from participants with university degree.</p>x<p>Participants with 13 years of education differ from participants with university degree.</p>y<p>Participants with <1.500 € household net income/month differ from participants 1.500–2.999€ household net income/month.</p>z<p>Participants with <1.500 € household net income/month differ from participants>3.000€ household net income/month.</p>aa<p>Participants with 1.500–2.999 € household net income/month differ from participants>3.000€ household net income/month.</p><p>MVPA MET-minutes•week⁻¹ in overall MVPA and in the domains work, transport and leisure. Sample is stratified by gender, age, BMI, residential setting, education and income.</p

Physical Activity and the Perceived Neighbourhood Environment : Looking at the Association the Other Way Around

 The associationbetween physical activity (PA) and variables of the perceived environmentmainly originate from cross-sectional studies that introduced the idea that theenvironment influences the PA level of residents. However, the direction ofcause and effect has not been solved with finality. The aim of this study wasto investigate whether residents’ perception of their proximate environmentdiffers depending on their level of PA in transport and recreation. Weconducted a cross-sectional survey with residents of six different parts of thecity of Cologne, Germany. The sample of 470 adults (52.8% females; mean age =35.5 ± 13.8 years) filled in the Global Physical Activity Questionnaire (GPAQ),as well as the European Environmental Questionnaire ALPHA. To distinguishbetween residents with ‘low’ and ‘high’ PA, we split the samples into two on the basisof the specific median in transport- and recreation-related PA. In the ‘high’ vs. ‘low’ PA group of the overall sample,we noted 4–16% more ‘PA favourable’ environmental perceptions in seven of the15 environmental variables. Multiple linear regression analyses were performed to investigateassociations of socio-demographic correlates and transport- andrecreation-related PA on the dependent variables of the environmentalperception. In this case,levels of PA were significant predictors for eight of the 15 items concerningenvironmental perceptions. Thus, the present study introduces the idea that residents withhigher levels of transport and recreational PA may perceive their environmentin a more ‘PA-favourable’ way than residents with lower levels

Self-reported actual and desired proportion of sitting, standing, walking and physically demanding tasks of office employees in the workplace setting: do they fit together?

Abstract Objective Occupational sitting time in white-collar workers represents a prominent contributor to overall daily sitting time, which is associated with various health risks. Workplace interventions intending to reduce sitting time during work typically focus on replacing sitting with standing. The aim was to investigate and compare actual and desired proportions of time spent sitting, standing, walking, and doing physically demanding tasks at work reported by desk-based workers. Cross-sectional data were collected from German desk-based workers (n = 614; 53.3% men; 40.9 ± 13.5 years). All were interviewed about their self-reported actual and desired level of sitting, standing, walking and physically demanding tasks at work. Results Desk-based workers reported to sit 73.0%, stand 10.2%, walk 12.9% and do physically demanding tasks 3.9% of their working hours. However, the individuals desire to sit, stand, walk and do physically demand tasks significantly different [53.8% sit, 15.8% stand, 22.8% walk, physically demanding tasks (7.7%), p < 0.001]. The present data revealed greatest mismatch between the desk-based workers’ actual and desired time for sitting and walking. Health promotion programs should offer not only options for more standing but also opportunities for more walking within the workplace setting to better match workers’ desires