Sex-specific correlates of adult physical activity in an Australian rural community

Factors influencing physical activity: A cross-sectional study of the community-dwelling older adults in a Portuguese rural area

BACKGROUND

There are a variety of intrinsic determinants which are key to understand the reasons for older people to stay (or not) active.

OBJECTIVES

To identify and analyse the factors underlying the physical activity engagement in older Portuguese living in a rural area.

METHODS

A total of 504 community-dwelling older adults (aged ≥65 years) were enrolled in this cross-sectional study. Sociodemographic data, physical activity levels, physical fitness and body composition were analysed.

RESULTS

Gender, age, income level, lower body strength, overweight, muscle mass and sedentarism (sitting time) were significantly associated with different physical activity levels. The multinomial logistic regression pointed out that dynamic balance, BMI and sitting time for moderate levels, as well as muscle mass for high levels, were the main independent factors that seem to influence the engagement in these levels compared to low physical activity levels. Additionally, classification tree analysis confirmed sitting time, dynamic balance and gender as discriminating factors for physical activity levels.

CONCLUSION

Physical fitness-related variables seem to mainly determine the levels of physical activity in the studied population. Thus, nursing care must promote the integration of physical activity into daily life routines of community-dwelling older adults, especially in rural areas.

IMPLICATIONS FOR PRACTICE

The diverse nature of factors influencing physical activity must be taken into account in primary health care, particularly in rural areas. Nursing care for older people must promote the integration of physical activity into daily life routines of community-dwelling older adults.

Student-Led Motivational Interviewing for Physical Activity Promotion among Rural Adults: A Feasibility and Acceptability Trial

In many countries, rural residents have lower life expectancies and poorer health outcomes than urban residents. Adults living in rural Australia have lower physical activity levels than major city counterparts, contributing to this observed health disparity. As physical activity interventions in rural populations have shown minimal success, there is an urgent need for innovative and affordable interventions that facilitate active lifestyles in this vulnerable population. This study assessed the feasibility of physical activity-focused motivational interviewing, delivered by university health sciences undergraduates in a rural Australian region. “Health age” was assessed at baseline (n = 62) from physiological and behavioral measures, immediately followed by the motivational interview, with health age again assessed at 8 weeks follow-up. Mixed methods using a questionnaire (n = 41 at both time points) and one-on-one interview (n = 8) identified aspects of intervention acceptability and feasibility. A large majority rated the motivational interview as meaningful (98%), empathetic (96%), autonomy-focused (88%), and likely to lead to sustained behavior change (98%). Interviews highlighted several potential attitudinal and structural factors that might influence long-term behavior change. Further development of this strategy in rural regions will depend on a deeper understanding of individuals’ and communities’ awareness, attitudes, and beliefs in relation to active lifestyles.

Are people in the bush really physically active? A systematic review and meta-analysis of physical activity and sedentary behaviour in rural Australians populations

Background

Physical inactivity is a major risk factor for non-communicable disease and premature mortality. People who live in rural settings are usually regarded as more physically active than those living in urban areas, however, direct comparisons between these populations are scarce. We aimed to summarise the prevalence of physical inactivity and sedentary behaviour in rural settings in Australia, compared to urban counterparts.

Methods

We searched six databases (AMED, Embase, Medline; CINAHL, SPORTDiscus; and RURAL) and identified 28 observational studies that investigated the levels of physical inactivity and/or sedentary behaviour in adults aged 18 years and over in rural Australia. Random effects meta-analysis was used to generate pooled prevalence estimates.

Results

Physical inactivity was four percentage points (95% confidence interval (CI) = 0.4 to 8) higher in rural populations compared to urban populations. There was a one percentage point (95% CI = -3 to 5) prevalence difference of physical activity in the rural populations. Rural populations reported on average 7.8 hours of sedentary time per day (95% CI = 5 to 10) and the prevalence of high levels of sedentary behaviour (≥to 8 hours per day) was 7% (95% CI = -8 to -7) greater in urban areas compared to rural areas.

Conclusions

People living in rural areas are just as physically inactive as people who live in urban areas. Our findings challenge the popular views that rural lifestyles result in people engaging more frequently in physical activity. Public health campaigns promoting physical activity in rural settings are just as necessary as in urban settings.

Factors influencing interest in recreational sports participation and its rural-urban disparity

Objectives

Recreational sports are important leisure activities. However, most studies investigating barrier factors and motivation for participation in recreational sports have been limited to specific areas (e.g., a city or school) or demographic groups (e.g., adolescents). Therefore, this study set out to gain a more comprehensive understanding of the behavioral and socioeconomic factors influencing interest in recreational sports participation in Taiwan, as well as to evaluate the effect of any urban-rural divide.

Methods

This study analyzed data collected by the “Taiwan Social Change Survey” (program five, wave 3) “Leisure Life” questionnaire. We used hierarchical linear modeling to assess respondent interest in recreational sports participation and evaluated the influence of behavioral factors, socioeconomic factors, and residence location (urban/rural).

Results

Of the 2,146 participants in this study, 50.3% were male, and the average age was 43.9 years. Location of residence (urban/rural) accounted for 35.3% of the variation in interest in recreational sports participation, while the remaining 64.7% came from the individual level. Participants who lived in rural settings were less interested in recreational sports than their urban counterparts. Gender, educational attainment, participation frequency, health-motivated interest, and appearance-motivated interest were also associated with interest in recreational sports participation.

Conclusions

Different communication strategies may be needed to effectively reach different demographic groups. We suggest that future public health campaigns aiming to increase recreational sports participation include tailored interventions and messages to effectively encourage leisure physical activities among all, regardless of demographic boundaries.

Clinical value of self-assessment risk of osteoporosis in Chinese

BACKGROUND

Early detection of high-risk population for osteoporosis is the key to preventing this disease.

METHODOLOGY

In this cross-sectional study a continuous sample of 270 women and 89 men (age: 20-90 years) was divided into four groups by age (≤ 55 or > 55 years) and sex. Participants completed the IOF test. Low-, medium-, and high-risk grades were defined by an OSTA index of greater than -1, -1 to -4, and less than -4, respectively.

RESULTS

Most participants were categorized in the low-risk group (240 people, 66.9%), followed by the medium-risk (102 people, 28.4%) and high-risk groups (17 people, 4.7%). Compared to women, men in both age groups had significantly higher OSTA index and greater numbers of positive answers on the IOF test. 64.3% individuals were susceptible to osteoporosis risk (≥1 positive answers on the IOF test). Multiple regression analysis demonstrated that family history of fragility fracture (OR: 0.503, 95% CI: 0.26-0.97), height loss exceeding 3 cm (OR: 2.51, 95% CI: 1.55-4.05), and earlier menopause (OR: 0.434, 95% CI: 0.19-0.97) were associated with higher risk grades.

CONCLUSIONS

Combined use of the OSTA and IOF test is a simple and effective method for assessing the risk of osteoporosis.