Psychosocial and environmental factors associated with physical activity among city dwellers in regional Queensland
Introduction
Physical inactivity is a major modifiable risk factor for many preventable diseases [1] and is widespread throughout many industrialized nations [1], [2], [3]. Attempts to address low physical activity levels have often been guided by research focused on the individual, largely neglecting the environment as an influence of behavior [4]. This focus on small group or individual-level interventions has raised concern regarding the ability to initiate positive changes in physical activity at the level of the population [5]. The physical environment has been identified as having the potential to influence the activity levels of large segments of the population [6] and has become a focus of recent research [7]. Results of research examining the environment's influence on physical activity suggest that accessibility and aesthetics are important influences of activity [7], [8]. Findings that the built environment can effect activity decisions by providing cues and opportunities for activity to occur [9], [10] emphasize the need for more research regarding the associations between environment and individual levels of physical activity.
The use of a social–ecological framework can better address the study of health-related physical activity at the population level as this approach acknowledges the influence of environment on activity [11]. The framework also allows for the incorporation of the numerous identified determinants of physical activity [12]. Research examining environmental influences on activity needs to address both the inter- and intrapersonal influences of activity [13] as the environment does not exact its influence on behavior separate from individual determinants of behavior [11]. Although within ecological models the term environment has been referred to ‘as any space outside the person’ [13], recent research has focused on the physical characteristics of the neighborhood environment [8]. The neighborhood environment has been conceptualized as an area equal to several city blocks [14] and has recently been operationalized as an area within a radius less than 0.9 km from one's residence [15]. Previous research [16], [17] supports the use of small geographic areas relative to the person's place of residence when examining the environment's influence on activity. When examining the environment, several studies [18], [19] have found that infrastructure such as shops and walking paths within walking distance of the home is positively associated with increased levels of walking. This suggests that accessible infrastructure may influence lower intensity activities. To date, however, these associations have not been empirically tested using objective measures of distance.
One of the principal methods of obtaining objective measures of distance is through the application of Geographic Information Systems (GIS) data. GIS allows for several of the methodological inaccuracies of self-report environmental measures to be overcome and increases the quantity and quality of environmental measures available to researchers [20]. For example, although self-reported perceptions of dogs and active people within the neighborhood have been positively associated with activity [21], self-report measures do not accurately measure the number of dogs or active people within the neighborhood. GIS allows for the combination of local government and CATI survey databases to provide more accurate determination of the prevalence of such characteristics within a predefined geographic area. GIS can also be applied to physical activity research to determine Euclidian and street network distances between origins and destinations to create measures of connectivity [23] used to determine the accessibility of destinations [24]. Although current research regarding environmental influences on physical activity is beginning to give us a clearer picture of these associations, the presence of methodological issues limit confidence in the findings. There remains a need to integrate objectively determined measures with subjective self-report data to obtain a clearer understanding of the association between the environment and physical activity. GIS allows this type of information to be used to improve our knowledge in this area.
Studies examining environmental influences on activity have increased in recent times. However, the majority of these studies assess the environment using self-report measures of the environment, while few studies have utilized GIS-derived measures of the environment to objectively quantify the associations found using self-report measures. Research has demonstrated that influences on activity encompass variables from personal, social, psychological, and environmental domains [3], [7], and it has been recommended that research should utilize models that incorporate these influences [4], [13]. Consistent with these suggestions, the current study uses a social–ecological framework to examine the relationships between self-reported and GIS-derived measures of the environment and two selected measures of physical activity—a criterion level of activity participation for health and participation in any recreational walking.
Section snippets
Design
Cross-sectional self-report data regarding physical activity obtained by means of a Computer-Assisted-Telephone-Interview (CATI) survey were combined with GIS-generated data relating to the physical environment surrounding the respondent's residential address. Integrated data sets were used to determine the association between GIS-derived objective measures of environmental attributes and self-report ratings of other environmental measures and two measures of physical activity-attaining
Analysis
A series of logistic regression analyses were performed using SPSS version 10.1, to examine the self-reported and GIS-derived measures of the environment associated with physical activity in the previous week. Two measures of physical activity were examined: ‘sufficient’ physical activity and ‘any’ recreational walking. In each model, sociodemographic variables of age, income, gender, BMI, social support for physical activity, and self-efficacy were adjusted for, as these are known to be
Prevalence of physical activity
Of the 1,281 CATI survey respondents, 94.7% (1,215) of residential locations were able to be geocoded. Descriptive statistics are presented in Table 1. Within the total study population, 57.9% of respondents were categorized as sufficiently active to derive health benefits. Persons in the 18- to 29-year-old age group had the highest proportions of active people (66.1%) compared to any other age group. The lowest educational grouping (below grade 10 education) had the lowest prevalence of
Discussion
There is now a focus on understanding the modifiable determinants of activity [4] through the use of ecological models of health behavior [13], which are capable of integrating the many identified correlates of activity [12]. The current research incorporated demographic, psychological, social, and environmental domains in the study of the correlates of participating in sufficient activity and participating in recreational walking in the previous week. A unique aspect of this research is the
Conclusion
Suggestions for research to examine the environment in the presence of inter- and intrapersonal influences have been made previously [13], and those environmental variables that achieved significance in the current study did so even when adjusting for these important psychosocial and demographic variables. This research demonstrates that new and important contributions can be made to the literature using this approach, which is required when assessing environmental influences on activity
Acknowledgements
Funding for this study was provided by Queensland Health as part of 10,000 Steps Rockhampton. GIS analysis was performed on behalf of the authors by Land Information Systems at Rockhampton City Council.
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