Occupation, hours worked, and leisure-time physical activity

Background. International research indicates that blue-collar employees typically exhibit lower rates of leisure-time physical activity. While lack of time and work demands are commonly reported barriers to activity, the extent to which time-at-work mediates the relationship between occupation and leisure-time physical activity is unclear. This study investigated the association between occupation, time spent in paid employment, and participation in leisure-time physical activity. Methods. This was a secondary analysis of cross-sectional data from the 1995 Australian Health Survey, focusing on employed persons ages 18-64 years (n = 24,454), Occupation was coded as per the Australian Standard Classification of Occupations and collapsed into three categories (professional, white-collar, blue-collar). Hours worked was categorized into eight levels, ranging from 1-14 to more than 50 h per week. Participation in leisure-time physical activity was categorized as either insufficient or sufficient for health, consistent with recommended levels of energy expenditure (1600 METS-min/fortnight). The relationship between occupation, hours worked, and leisure-time physical activity was examined using logistic regression. Analyses were conducted separately for male and female, and the results are presented as a series of models that successively adjust for a range of potential covariates: age, living arrangement, smoking status, body mass index, and self-reported health. Results. Individuals in blue-collar occupations were approximately 50% more likely to be classified as insufficiently active. This occupational variability in leisure-time physical activity was not explained by hours worked. There was a suggested relationship between hours worked and leisure-time physical activity; however, this differed between men and women, and was difficult to interpret. Conclusions. Occupational variability in leisure-time physical activity cannot be explained by hours worked. Therefore, reports that work constitutes a barrier to participation should be explored further. Identification of the factors contributing to occupational variability in leisure-time physical activity will add to our understanding of why population subgroups differ in their health risk profiles, and assist in the development of health promotion strategies to reduce rates of sedentariness and health inequalities. (C) 2000 American Health Foundation and Academic Press.

Age-related differences in physical activity levels of young adults

Purpose: To examine age-related differences in the physical activity behaviors of young adults. Methods: We examined rates of participation in vigorous- and moderate-intensity leisure-time activity and walking, as well as an index of physical activity sufficient for health benefits in three Australian cross-sectional samples, for the age ranges of 18-19, 20-24, and 25-29 yr. Data were collected in 1991, 1996, and 1997/8. Results: There was at least a 15% difference in vigorous-intensity leisure-time physical activity from the 18-19 yr to the 25-29 yr age groups, and at least a 10% difference in moderate-intensity leisure-time physical activity. For the index of sufficient activity there was a difference between 9 and 21% across age groups. Differences in rates of walking were less than 8%. For all age groups, males had higher rates of participation for vigorous and moderate-intensity activity than did females, bur females had much higher rates of participation in walking than males. Age-associated differences in activity levels were more apparent for males. Conclusions: Promoting walking and various forms of moderate-intensity physical activities to young adult males, and encouraging young adult females to adopt other forms of moderate-intensity activity to complement walking may help to ameliorate decreases in physical activity over the adult lifespan.

Correlation of habitual physical activity levels with flow mediated dilation of the brachial artery in 5-10 year old children

Endothelial dysfunction is an early key event of atherogenesis. Both fitness level and exercise intervention have been shown to positively influence endothelial function. In a cross-sectional study of 47 children, the relationship between habitual physical activity and flow-mediated dilation (FMD) of the brachial artery was explored. Habitual physical activity levels (PALs) were assessed using a validated stable isotope technique, and FMD of the brachial artery was measured via high-resolution ultrasound. The results showed that habitual physical activity significantly correlated with FMD (r=0.39, P=0.007), and remained the most influential variable on dilation in multivariate analysis. Although both fitness level and exercise intervention have previously been shown to positively influence FMD, this is the first time that a relationship with normal PALs has been investigated, especially, at such a young age. These data support the concept that physical activity exerts its protective effect on cardiovascular health via the endothelium and add further emphasis to the importance of physical activity in childhood.

Comparison of surveys used to measure physical activity

Objective: To compare the level of agreement in results obtained from four physical activity (PA) measurement instruments that are in use in Australia and around the world. Methods: 1,280 randomly selected participants answered two sets of PA questions by telephone. 428 answered the Active Australia (AA) and National Health Surveys, 427 answered the AA and CDC Behavioural Risk Factor Surveillance System surveys (BRFSS), and 425 answered the AA survey and the short International Physical Activity Questionnaire (IPAQ). Results: Among the three pairs of survey items, the difference in mean total PA time was lowest when the AA and NHS items were asked (difference=24) (SE:17) minutes, compared with 144 (SE:21) mins for AA/BRFSS and 406 (SE:27) mins for AA/IPAQ). Correspondingly, prevalence estimates for 'sufficiently active' were similar for AA and NHS (56% and 55% respectively), but about 10% higher when BRFSS data were used, and about 26% higher when the IPAQ items were used, compared with estimates from the AA survey. Conclusions: The findings clearly demonstrate that there are large differences in reported PA times and hence in prevalence estimates of 'sufficient activity' from these four measures. Implications: It is important to consistently use the same survey for population monitoring purposes. As the AA survey has now been used three times in national surveys, its continued use for population surveys is recommended so that trend data ever a longer period of time can be established.

Habitual physical activity and physical activity intensity: their relation to body composition in 5.0-10.5 year old children

Background: Concerns of a decrease in physical activity levels (PALs) of children and a concurrent increase in childhood obesity exist worldwide. The exact relation between these two parameters however has as yet to be fully defined in children. Objective: This study examined the relation in 47 children, aged 5–10.5 y (mean age 8.4plusminus0.9 y) between habitual physical activity, minutes spent in moderate, vigorous and hard intensity activity and body composition parameters. Design: Total energy expenditure (TEE) was calculated using the doubly labelled water technique and basal metabolic rate (BMR) was predicted from Schofield's equations. PAL was determined by PAL=TEE/BMR. Time spent in moderate, vigorous and hard intensity activity was determined by accelerometry, using the Tritrac-R3D. Body fatness and body mass index (BMI) were used as the two measures of body composition. Results: Body fat and BMI were significantly inversely correlated with PAL (r=-0.43, P=0.002 and r=-0.45, P=0.001). Times spent in vigorous activity and hard activity were significantly correlated to percentage body fat (r=-0.44, P=0.004 and r=-0.39, P=0.014), but not BMI. Children who were in the top tertiles for both vigorous activity and hard activity had significantly lower body fat percentages than those in the middle and lowest tertiles. Moderate intensity activity was not correlated with measures of body composition. Conclusions: As well as showing a significant relation between PAL and body composition, these data intimate that there may be a threshold of intensity of physical activity that is influential on body fatness. In light of world trends showing increasing childhood obesity, this study supports the need to further investigate the importance of physical activity for children.

Effects of interventions in health care settings on physical activity or cardiorespiratory fitness

Introduction: This paper reviews studies of physical activity interventions in health care settings to determine effects on physical activity and/or fitness and characteristics of successful interventions. Methods: Studies testing interventions to promote physical activity in health care settings for primary prevention (patients without disease) and secondary prevention (patients with cardiovascular disease [CVD]) were identified by computerized search methods and reference lists of reviews and articles. Inclusion criteria included assignment to intervention and control groups, physical activity or cardiorespiratory fitness outcome measures, and, for the secondary prevention studies, measurement 12 or more months after randomization. The number of studies with statistically significant effects was determined overall as well as for studies testing interventions with various characteristics. Results: Twelve studies of primary prevention were identified, seven of which were randomized. Three of four randomized studies with short-term measurement (4 weeks to 3 months after randomization), and two of five randomized studies with long-term measurement (6 months after randomization) achieved significant effects on physical activity. Twenty-four randomized studies of CVD secondary prevention were identified; 13 achieved significant effects on activity and/or fitness at twelve or more months. Studies with measurement at two time points showed decaying effects over time, particularly if the intervention were discontinued. Successful interventions contained multiple contacts, behavioral approaches, supervised exercise, provision of equipment, and/or continuing intervention. Many studies had methodologic problems such as low follow-up rates. Conclusion: Interventions in health care settings can increase physical activity for both primary and secondary prevention. Long-term effects are more likely with continuing intervention and multiple intervention components such as supervised exercise, provision of equipment, and behavioral approaches. Recommendations for additional research are given.

Participation in recreational physical activity: Why do socioeconomic groups differ?

This qualitative study explored how influences on recreational physical activity (RPA) were patterned by socioeconomic position. Face-to-face interviews were conducted with 10 males and 10 females in three socioeconomic groups (N = 60). Influences salient across all groups included previous opportunities, physical health, social assistance, safety, environmental aesthetics and urban design, physical and health benefits, and barriers of self-consciousness, low skill, and weather/time of year. Influences more salient to the high socioeconomic group included social benefits, achieving a balanced lifestyle, and the barrier of an unpredictable lifestyle. Influences more salient to the high and mid socioeconomic groups included efficacy, perceived need, activity demands, affiliation, emotional benefits, and the barrier of competing demands. Influences more salient to the low socioeconomic group included poor health and barriers of inconvenient access and low personal functioning. Data suggest that efforts to increase RPA in the population should include both general and socioeconomically targeted strategies.

Comparing physical activity questionnaires for youth: Seasonal vs annual format

Background: In large cohort studies of older children, self-report is the only practical way to assess physical activity. Assessing usual activity over the entire year is desirable, but children and adolescents may overestimate activities with high seasonal variability. Use of questionnaires in which individuals report each activity by season may improve accuracy. Methods: A total of 6782 girls and 5110 boys, aged 9–14 years in 1996, completed self-administered activity questionnaires in 1996 and in 1997. In 1996, participants reported the average time spent in each of 17 activities during the previous 12 months; in 1997, we also asked for the average time spent in the previous year, but within each of the four seasons. Results: Girls reported a median of 12.8 hours/week total activity in 1996 and 10.4 hours/week in 1997. For boys, the estimates were 15.5 hours/week and 13.4 hours/week, respectively. Girls and boys within 1-year age strata (e.g., comparison of 10-year olds in 1996 with 10-year olds in 1997) reported an average of 3.7 and 3.1 fewer hours per week, respectively, on the 1997 seasonal format versus the 1996 annual format questionnaire. In longitudinal analyses, the difference between the annual and the seasonal estimates was greater if participants did the activity in fewer seasons in 1997. Conclusions: In comparison to an annual format questionnaire, a seasonal format questionnaire may improve accuracy of self-report of physical activity by reducing over-reporting of activities in which pre-adolescents and adolescents engage in fewer seasons.

Correlates of adults' participation in physical activity: review and update

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Differences in physical activity between black and white girls living in rural and urban areas

This study examined the relationship of race and rural/urban setting to physical, behavioral, psychosocial, and environmental factors associated with physical activity. Subjects included 1,668 eighth-grade girls from 31 middle schools: 933 from urban settings, and 735 from rural settings. Forty-six percent of urban girls and 59% of rural girls were Black. One-way and two-way ANOVAs with school as a covariate were used to analyze the data. Results indicated that most differences were associated with race rather than setting. Black girls were less active than White girls, reporting significantly fewer 30-minute blocks of both vigorous and moderate-to-vigorous physical activity. Black girls also spent more time watching television, and had higher BMIs and greater prevalence of overweight than White girls. However, enjoyment of physical education and family involvement in physical activity were greater among Black girls titan White girls. Rural White girls and urban Black girls had more favorable attitudes toward physical activity. Access to sports equipment, perceived safety of neighborhood, and physical activity self-efficacy were higher in White girls than Black girls.

Life transitions and changing physical activity patterns in young women

Background: Physical activity (PA) patterns are likely to change in young adulthood in line with changes in lifestyle that occur in the transition from adolescence to adulthood. The aim of this study was to ascertain whether key life events experienced by young women in their early twenties are associated with increasing levels of inactivity. Methods: This was a 4-year follow-up of 7281 participants (aged 18 to 23 years at baseline) in the Australian Longitudinal Study of Women's Health, with self-reported measures of PA, life events, body mass index (BMI), and sociodemographic variables. Results: The cross-sectional data indicated no change in PA between baseline (57% active) and follow-up (56% active). However, for almost 40% of the sample, PA category changed between baseline and follow-up, with approximately 20% of the women changing from being active to inactive, and another 20% changing from being inactive to active. After adjustment for age, other sociodemographic variables, BMI, and PA at baseline, women who reported getting married, having a first or subsequent child, or beginning paid work were more likely to be inactive at follow-up than those who did not report these events. Conclusions: The results suggest that life events such as getting married, having children, and starting work are associated with decreased levels of PA in young adult women. Strategies are needed to promote maintenance of activity at the time when most women experience these key life-stage transitions.

Effects of physical activity on emotional well-being among older Australian women - Cross-sectional and longitudinal analyses

Objective: To explore relationships between physical activity and mental health cross-sectionally and longitudinally in a large cohort of older Australian women. Method: Women in their 70s participating in the Australian Longitudinal Study on Women's Health responded in 1996 (aged 70-75) and in 1999 (aged 73-78). Cross-sectional data were analyzed for 10,063 women and longitudinal data for 6472. Self-reports were used to categorize women into four categories of physical activity at each time point as well as to define four physical activity transition categories across the 3-year period. Outcome variables for the cross-sectional analyses were the mental health component score (MCS) and mental health subscales of the Medical Outcomes Study Short Form (SF-36). The longitudinal analyses focused on changes in these variables. Confounders included the physical health component scale (PCS) of the SF-36, marital status, body mass index (BMI) and life events. Adjustment for baseline scores was included for the longitudinal analyses. Results: Cross-sectionally, higher levels of physical activity were associated with higher scores on all dependent variables, both with and without adjustment for confounders. Longitudinally, the effects were weaker, but women who had made a transition from some physical activity to none generally showed more negative changes in emotional well-being than those who had always been sedentary, while those who maintained or adopted physical activity had better outcomes. Conclusion: Physical activity is associated with emotional well-being among a population cohort of older women both cross-sectionally and longitudinally, supporting the need for the promotion of appropriate physical activity in this age group. (C) 2003 Elsevier Science Inc. All rights reserved.