A six-year longitudinal study of the relationship of physical activity to bone mineral accrual in growing children: The University of Saskatchewan bone mineral accrual study

To investigate the influence of physical activity on bone mineral accrual during the adolescent years, we analyzed 6 years of data from 53 girls and 60 boys. Physical activity, dietary intakes, and anthropometry were measured every 6 months and dual-energy X-ray absorptiometry scans of the total body (TB), lumbar spine (LS), and proximal femur (Hologic 2000, array mode) were collected annually. Distance and velocity curves for height and bone mineral content (BMC) were fitted for each child at several skeletal sites using a cubic spline procedure, from which ages at peak height velocity (PHV) and peak BMC velocity (PBMCV) were identified. A mean age- and gender-specific standardized activity (Z) score was calculated for each subject based on multiple yearly activity assessments collected up until age of PHV. This score was used to identify active (top quartile), average (middle 2 quartiles), or inactive (bottom quartile) groups. Two-way analysis of covariance, with height and weight at PHV controlled for, demonstrated significant physical activity and gender main effects (but no interaction) for PBMCV, for BMC accrued for 2 years around peak velocity, and for BMC at 1 year post-PBMCV for the TB and femoral neck and for physical activity but not gender at the LS (all p < 0.05). Controlling for maturational and size differences between groups, we noted a 9% and 17% greater TB BMC for active boys and girls, respectively, over their inactive peers 1 year after the age of PBMCV. We also estimated that, on average, 26% of adult TB bone mineral was accrued during the 2 years around PBMCV.

Social-cognitive and perceived environment influences associated with physical activity in older Australians

Background, Regular physical activity in older adults can facilitate healthy aging, improve functional capacity, and prevent disease. However, factors associated with physical inactivity in older populations are poorly understood. This study attempts to identify social-cognitive and perceived environmental influences associated with physical activity participation in older populations. Methods. In a randomly selected sample of 449 Australian adults age 60 and older, we assessed self-reported physical activity and a range of social-cognitive and perceived environmental factors. Respondents were classified as sufficiently active and inactive based on energy expenditure estimates (kcal/week) derived from self-reported physical activity. Two logistic regression models, with and without self-efficacy included, were conducted to identify modifiable independent predictors of physical activity. Results. Significantly more males than females were physically active. Physical activity participation was related to age with a greater proportion of those age 65-69 being active than those age 60-64 or 70 or older. High self-efficacy, regular participation of friends and family, finding footpaths safe for walking, and access to local facilities were significantly associated with being active. Conclusion. Identifying predictors of physical activity in older populations, particularly social support, facility access, and neighbourhood safety, can inform the development of policy and intervention strategies to promote the health of older people. (C) 2000 American Health Foundation and Academic Press.

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.

Promoting physical activity among middle-aged and older adults in health care settings

Physical inactivity continues to be a significant public health issue for middle-aged and older adults. This review focuses on physical activity interventions targeting older adults in health care settings. The literature in this area is limited and the results to date disappointing. Much remains to be done to develop effective interventions targeting older adults, especially those from underserved groups. Attention also needs to be paid to maintenance of initial treatment gains and to linking primary-care-based physical activity interventions to community-based resources. Recognition in the social and behavioral sciences of the importance of social-environmental influences on health and health behaviors mandates both a multidisciplinary and a multilevel intervention approach to the problem of physical inactivity.

Developing a reliable audit instrument to measure the physical environment for physical activity

Background: The physical environment plays an important role in influencing participation in physical activity, although which factors of the physical environment have the greatest effect on patterns of activity remain to be determined. We describe the development of a comprehensive instrument to measure the physical environmental factors that may influence walking and cycling in local neighborhoods and report on its reliability. Methods: Following consultation with experts from a variety of fields and a literature search, we developed a Systematic Pedestrian and Cycling Environmental Scan (SPACES) instrument and used it to collect data over a total of 1987 kilometers of roads in metropolitan Perth, Western Australia. The audit instrument is available from the first author on request. Additional environmental information was collected using desktop methods and geographic information systems (GIS) technology. We assessed inter- and intra-rater reliability of the instrument among the 16 observers who collected the data. Results: The observers reported that the audit instrument was easy to use. Both inter- and intra-rater reliability of the environmental scan instrument were generally high. Conclusions: Our instrument provides a reliable, practical, and easy to-use method for collecting detailed street-level data on physical environmental factors that are potential influences on walking in local neighborhoods.

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.

Promoting physical activity to older adults: a preliminary evaluation of three general practice-based strategies

The aim of this study was to explore the feasibility of an exercise scientist (ES) working in general practice to promote physical activity (PA) to 55 to 70 year old adults. Participants were randomised into one of three groups: either brief verbal and written advice from a general practitioner (GP) (G1, N=9); or individualised counselling and follow-up telephone calls from an ES, either with (G3, N=8) or without a pedometer (G2, N=11). PA levels were assessed at week 1, after the 12-wk intervention and again at 24 weeks. After the 12-wk intervention, the average increase in PA was 116 (SD=237) min/wk; N=28, p < 0.001. Although there were no statistically significant between-group differences, the average increases in PA among G2 and G3 participants were 195 (SD=207) and 138 (SD=315) min/wk respectively, compared with no change (0.36, SD=157) in G1. After 24 weeks, average PA levels remained 56 (SD=129) min/wk higher than in week 1. The small numbers of participants in this feasibility study limit the power to detect significant differences between groups, but it would appear that individualised counselling and follow-up contact from an ES, with or without a pedometer, can result in substantial changes in PA levels. A larger study is now planned to confirm these findings.

Physical activity profile in heart failure patients from a Brazilian tertiary cardiology hospital

Background: Physical activity (PA) has proven benefits in the primary prevention of heart diseases such as heart failure (HF). Although it is well known, HF PA habits and physicians` advice have been poorly described. The aim of this study was to investigate if physicians were advising HF patients to exercise and to quantify patients` exercise profiles in a complex cardiology hospital. Methods: All 131 HF patients (80 male, average age 53 +/- 10 years, NYHA class I-V, left ventricular ejection fraction 35 +/- 11%, 35 ischemic, 35 idiopatic , 32 hypertensive and 29 with Chagas disease) went to the hospital for a HF routine check-up. On this occasion, after seeing the physician, we asked the patients if the physician had advised them about PA. Then, we asked them to fill in the international physical activity questionnaire (IPQA) Short Form to classify their PA level. Results: Our data showed a significant difference between patients who had received any kind of PA advice from physicians (36%) and those who had not (64%, p<0.0001). Using the IPAQ criteria, of the 36% of patients who had received advice, 12.4% were classified as low and 23.6% as moderate. Of the 64% of patients who did not receive advice, 26.8% were classified as lowand 37.2% as moderate. Etiology (except Chagas), functional class, ejection fraction, sex and age did not influence the PA profile. Conclusions: Physicians at a tertiary cardiology hospital were not giving patients satisfactory advice as to PA. Our data supports the need to strengthen exercise encouragement by physicians and for complementary studies on this area. (Cardiol J 2010; 17, 2: 143-148)

The Association Between Physical Activity, Productivity, and Health Care Utilization Among Employees in Brazil

Objective: To document the relationship between physical activity, absenteeism, presenteeism, health care utilization, and morbidity among Brazilian automotive workers. Methods: Eligible employees (N = 620) completed a questionnaire. Univariate correlations, multivariate logistic regression, and Pearson`s product-moment correlation coefficient were used. Results: Work absenteeism was associated with physical activity at work (OPA) (odds ratio, [OR] = 1.63, 95% confidence interval [CI] = 1.31 to 2.02) and leisure physical activity time excluding sport (OR = 0.73, 95% CI = 0.58 to 1.00). Health care utilization was associated with OPA (OR = 1.25, 95% CI = 0.99 to 1.58) and leisure physical activity time excluding sport (OR = 0.76, 95% CI = 0.57 to 1.02). Presenteeism showed an indirect relationship with OPA (r = 0.099, P = 0.014). Referred morbidity was associated with OPA (OR = 1.3, 95% CI = 1.06 to 1.61) and sports during leisure time (OR = 0.67, 95% CI = 0.54 to 0.82). Conclusions: Physical activity components seem to have differential relationships to the studied outcomes. Associations measured indicate negative impacts of OPA on absenteeism, health care utilization, and morbidity, although overall physical activity did not show these relationships.