Differences in leisure-time physical activity levels between blacks and whites in population-based samples: The Minnesota heart survey

1991 ◽  
Vol 14 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Aaron R. Folsom ◽  
Timothy C. Cook ◽  
J. Michael Sprafka ◽  
Gregory L. Burke ◽  
Stephan W. Norsted ◽  
...  
Keyword(s):  
Physical Activity ◽  
Leisure Time ◽  
Leisure Time Physical Activity ◽  
Population Based ◽  
Activity Levels ◽  
Physical Activity Levels ◽  
Blacks And Whites

How Do Different Occupational Factors Influence Total, Occupational, and Leisure-Time Physical Activity?

2015 ◽  
Vol 12 (2) ◽  
pp. 200-207 ◽  
Author(s):  
Corneel Vandelanotte ◽  
Camille Short ◽  
Matthew Rockloff ◽  
Lee Di Millia ◽  
Kevin Ronan ◽  
...  
Keyword(s):  
Physical Activity ◽  
Leisure Time ◽  
Leisure Time Physical Activity ◽  
Total Physical Activity ◽  
Activity Levels ◽  
Full Time ◽  
Cross Sectional ◽  
Time Activity ◽  
Physical Activity Levels ◽  
The Impact

Background:A better understanding of how occupational indicators influence physical activity levels will aid the design of workplace interventions.Methods:Cross-sectional data were collected from 1194 participants through a telephone interview in Queensland, Australia. The IPAQ-long was used to measure physical activity. Multiple logistic regression was applied to examine associations.Results:Of participants, 77.9% were employed full-time, 32.3% had professional jobs, 35.7% were engaged in shift work, 39.5% had physically-demanding jobs, and 66.1% had high physical activity levels. Participants with a physicallydemanding job were less likely to have low total (OR = 0.25, 95% CI = 0.17 to 0.38) and occupational (OR = 0.17, 95% CI = 0.12 to 0.25) physical activity. Technical and trade workers were less likely to report low total physical activity (OR = 0.44, 95% CI = 0.20 to 0.97) compared with white-collar workers. Part-time (OR = 1.74, 95% CI = 1.15 to 2.64) and shift workers (OR = 1.86, 95% CI = 1.21 to 2.88) were more likely to report low leisure-time activity.Conclusions:Overall, the impact of different occupational indicators on physical activity was not strong. As expected, the greatest proportion of total physical activity was derived from occupational physical activity. No evidence was found for compensation effects whereby physically-demanding occupations lead to less leisure-time physical activity or vice versa. This study demonstrates that workplaces are important settings to intervene, and that there is scope to increase leisure-time physical activity irrespective of occupational background.

Leisure-Time Physical Activity: Association With Activity Levels in Other Domains

2010 ◽  
Vol 7 (4) ◽  
pp. 460-464 ◽  
Author(s):  
Airton J. Rombaldi ◽  
Ana M.B. Menezes ◽  
Mario Renato Azevedo ◽  
Pedro C. Hallal
Keyword(s):  
Physical Activity ◽  
Leisure Time ◽  
Leisure Time Physical Activity ◽  
Population Based ◽  
Cross Sectional Study ◽  
Moderate Intensity ◽  
Activity Levels ◽  
Cross Sectional ◽  
Moderate Intensity Physical Activity ◽  
Intensity Physical Activity

Objectives:To explore whether participation in leisure-time physical activity (LTPA) is associated with participation in occupational, housework, and transport-related physical activity.Methods:Population-based cross-sectional study covering a multistage sample of 972 subjects age 20 to 69 years. Physical activity was measured using the long version of the International Physical Activity Questionnaire. A LTPA score was calculated as follows: min/wk of walking + min/wk of moderate-intensity physical activity + (min/wk of vigorous-intensity physical activity × 2). Similar scores were generated for each domain. For categorical analyses, the scores were divided into 3 categories: 0 min/wk, 10−149 min/wk, and ≥150 min/wk.Results:The proportion of subjects practicing less than 150 min/wk of physical activity in each domain was: leisure-time (69.8%), occupational (58.3%), housework (35.0%), transportation (51.9%). Subjects with a transport-related physical activity score equal to or above 150 min/wk were 40% less likely to be sedentary in leisure-time in comparison with those who did not practice transport-related physical activity. Housework and occupational physical activity were not related to participation in LTPA.Conclusions:Future physical activity campaigns should focus on other domains instead of LTPA alone, particularly supporting transport-related physical activity as a strategy of health promotion.

LEISURE-TIME PHYSICAL ACTIVITY LEVELS AMONG CANADIAN ADOLESCENTS, 1981-1998

2003 ◽  
Vol 35 (Supplement 1) ◽  
pp. S180
Author(s):  
J C. Eisenmann ◽  
P T. Katzmarzyk ◽  
M S. Tremblay
Keyword(s):  
Physical Activity ◽  
Leisure Time ◽  
Leisure Time Physical Activity ◽  
Activity Levels ◽  
Physical Activity Levels

scholarly journals ASSOCIATION BETWEEN SCREEN-BASED SEDENTARY BEHAVIOR AND LEISURE-TIME PHYSICAL ACTIVITY AMONG LITHUANIAN 5–7TH GRADE SCHOOLCHILDREN

2014 ◽  
Vol 1 (3) ◽  
pp. 1-10
Author(s):  
Vaiva Balčiūnienė
Keyword(s):  
Physical Activity ◽  
Sedentary Behavior ◽  
Computer Games ◽  
Internet Use ◽  
Leisure Time ◽  
Leisure Time Physical Activity ◽  
Activity Levels ◽  
Sedentary Behaviors ◽  
Physical Activity Levels ◽  
Tv Watching

Research background. The prevalence of obesity and chronic diseases among adolescents is rising rapidly in many Western European countries, including Lithuania (Zaborskis, Raskilas, 2011; Currie et al., 2012). Physical activity levels of children and adolescents have declined, whereas in contrast sedentary behavior has increased during the last few decades. In this study based on the cities and districts of Lithuanian population, leisure time physical activity and screen-based sedentary behaviors among 5–7th grade schoolchildren were assessed. The aim of the research was to evaluate association between screen-based sedentary behavior and leisure-time physical activity among Lithuanian 5–7th grade schoolchildren. Research methods and organization. Applying nested random selection / sampling method, 1117 schoolchildren of 5–7th grades from ten Lithuanian pro-gymnasiums, gymnasiums and secondary schools located in different cities and districts were selected. The study was conducted in 2013. The respondents were given a Questionnaire to identify schoolchildren’s demographic data, assess physical activity levels (recommended by the WHO) as well as the levels of time for screen-based sedentary behaviors. Results. In the survey it was established that only 23.3 % of schoolchildren were sufficiently physically active during their leisure time. The average length of TV watching was 3.30 ± 1.67 hours, playing computer 3.51 ± 1.86 hours and internet use 3.41 ± 1.85 hours on week-days. 7th grade girls engaged more frequently in TV watching as compared to 7th grade boys (p < 0.01). The time of playing computer games was higher among boys compared to girls (p < 0.001), but the time of internet use was higher among 6th grade girls compared to 6th grade boys (p < 0.05). The main factors that led to the lack of sufficient physical activity were female gender, senior grade and the higher time of playing computer games and searching the internet. Conclusions. The association between the time of screen-based sedentary behaviors and leisure time physical activity were determined. These study results encourage research of the relations between “exergame” and physical activity among schoolchildren. Keywords: physical activity, screen-based sedentary behaviors, schoolchildren.

Sign in / Sign up

Export Citation Format

Share Document