Christina Müller1,2*
Bruno Domokos1,2Tanja Amersbach1,2Eva-Maria Hausmayer1,2Christin Roßmann3
Birgit Wallmann-Sperlich1
Jens Bucksch2- 1Institute of Sport Science, University of Wurzburg, Wurzburg, Germany
- 2Department of Prevention and Health Promotion, Faculty of Natural and Sociological Sciences, Heidelberg University of Education, Heidelberg, Germany
- 3Federal Centre for Health Education, Cologne, Germany
Background: According to socio-ecological theories, physical activity behaviors are linked to the physical and social neighborhood environment. Reliable and contextually adapted instruments are needed to assess environmental characteristics related to physical activity. This work aims to develop an audit toolbox adapted to the German context, to urban and rural settings, for different population groups, and different types of physical activity; and to evaluate its inter-rater reliability.
Methods: We conducted a systematic literature search to collect existing audit tools and to identify the latest evidence of environmental factors influencing physical activity in general, as well as in German populations. The results guided the construction of a category system for the toolbox. Items were assigned to the categories based on their relevance to physical activity and to the German context as well as their comprehensibility. We piloted the toolbox in different urban and rural areas (100 street segments, 15 parks, and 21 playgrounds) and calculated inter-rater reliability by Cohen's Kappa.
Results: The audit toolbox comprises a basic streetscape audit with seven categories (land use and destinations, traffic safety, pedestrian infrastructure, cycling infrastructure, attractiveness, social environment, and subjective assessment), as well as supplementary tools for children and adolescents, seniors and people with impaired mobility, parks and public open spaces, playgrounds, and rural areas. 76 % of all included items had moderate, substantial, or almost perfect inter-rater reliability (κ > 0.4).
Conclusions: The audit toolbox is an innovative and reliable instrument for the assessment of the physical activity friendliness of urban and rural environments in Germany.
1. Introduction
Physical activity, defined as “any bodily movement produced by skeletal muscles that requires energy expenditure,” has significant physical and mental health benefits (1). It reduces the risk of non-communicable diseases like cardiovascular diseases, type 2 diabetes, and cancer, as well as depressive symptoms and anxiety (2–7). However, physical inactivity is a major public health problem worldwide and also prevalent in all age groups in Germany (8–11).
To develop effective interventions, it is important to identify modifiable factors that positively or negatively influence physical activity behaviors. A growing number of studies have shown that beyond individual characteristics (e.g., intention), physical activity behaviors are linked to the physical (referring to the built and natural) and social neighborhood environment, as suggested by socio-ecological theories (12, 13). According to these theories, physical activity in different domains (e.g., occupational, leisure, transportation) is determined by different factors on different levels (i.e., intrapersonal, social, cultural, physical, information, and policy environment). The built environment, which can be defined as any human-made or human-modified features of the physical environment (e.g., buildings, transportation systems, design features, etc.), has gained attention from public health researchers, as interventions on this level potentially impact large proportions of the population (14, 15). A growing number of studies have confirmed that physical activity behaviors are linked to characteristics of the built environment, including accessibility, land use diversity, availability of public transport, aesthetics, infrastructure for walking and cycling, street connectivity, and traffic-related safety (16–20). Studies across different countries suggest that there are some internationally generalizable attributes of the built environment that are consistently associated with physical activity, but there might also be some country-specific influences (21–25). Furthermore, studies suggest that built environment influences differ across age groups. Hence, children, adolescents, adults, and older adults are usually examined as distinct groups, which is also necessary in terms of health reasons and determinants (18, 19, 26).
Children's and adolescents' physical activity is an important factor in their healthy growth and development (27). The World Health Organization (WHO) recommends a minimum of 60 min of moderate-to-vigorous-intensity physical activity (MVPA) per day for children and adolescents (1). In Germany, only small proportions of children and adolescents (22.4% of girls and 29.4% of boys between 3 and 17 years of age) achieve this recommendation, with prevalence continuously decreasing with age (9). Overall, boys accumulate more MVPA than girls (8, 9). Children's and adolescents' physical activity can be categorized into school-based activities (e.g., physical education), organized sports activities (e.g., in sports clubs), non-organized leisure activities (e.g., outdoor play), and active travel (e.g., walking or cycling to school) (28). The outdoor environment around children's and adolescent's homes and schools can contribute to their daily physical activity by offering opportunities for non-organized leisure activities and active travel (29). Outdoor time in general is positively associated with physical activity and negatively associated with sedentary behavior in children and adolescents (30). In addition, there is consistent evidence that active travel to and from school is positively associated with children's and adolescents' physical activity and contributes significantly to daily MVPA levels (31, 32). Environments that support walking and cycling as well as outdoor play can therefore be considered important for children and adolescents (33).
In German adults, 44.8% of women and 51.2% of men meet the WHO recommendation on aerobic physical activity (at least 150 min of moderate-intensity per week) (10). Active travel, including active commuting to work, is an important source of MVPA in adults (31, 34). Consequently, environments that support active travel, such as walking infrastructure (e.g., sidewalks), street connectivity, land-use mix, greater walkability, and proximity of destinations, are consistently associated with adults' physical activity (14).
In older adults, physical activity remains important, as it is known to be one of the key determinants of healthy aging. Physically active older adults have lower risks of falling, cognitive decline, dementia, and Alzheimer's disease (35). Studies have shown that retirement is associated with increases in leisure-time physical activity, (recreational) walking, and home-based activities and decreases in occupational physical activity, active travel, and total physical activity (36). In Germany, only 33.3% of women and 42.6% of men aged 65 and above achieve the WHO recommendations on aerobic physical activity of at least 150 min per week (10). Important domains of older adults' physical activity are home-based activities (e.g., household chores, gardening), leisure-activities (e.g., in sports clubs), and active travel (walking, cycling) (37). In the domain of active travel, walking is very important to maintain mobility with increasing age (38). According to a representative mobility survey, 43% of German adults aged 60 to 69 years, 47% of adults aged 70 to 79 years, and 44% of adults aged 80 years and older walk every day (38). Older adults are likely to spend much of their time in their neighborhoods and use them more intensively than younger adults (39). In addition, they may be more sensitive to physical barriers in the built environment because of age-related functional limitations (40). A systematic review of qualitative studies summarized that certain characteristics of the pedestrian infrastructure (e.g., sidewalk quality and maintenance, slopes, and curbs) and access to rest areas (i.e., benches and public washrooms) are important environmental factors for older adults, which is also supported by quantitative evidence (18, 41).
In recent years, different assessment instruments examining built environment characteristics related to physical activity have been developed, including audit tools (42, 43). Audit tools aim to measure the presence, quantity, and quality of environmental features by direct observation (42). They can be used by researchers as well as community stakeholders and have the potential to facilitate community assessments as part of a systematic planning process to improve environments for physical activity. Data is typically collected in-person using standardized paper forms or digital applications (42). To attain a high degree of independence from the observer, most tools have been tested for inter-rater reliability (42). Different reliable audit tools exist for different environmental contexts (e.g., street segments, parks, or public open spaces). Most of the tools have been developed in the United States, e.g., the Active Neighborhood Checklist (ANC) (44), the Microscale Audit of Pedestrian Streetscapes (MAPS) (45), the Pedestrian Environmental Data Scan (PEDS) (46), or the Rural Active Living Assessment (RALA) (47). Although most of the environmental characteristics assessed by these tools are supposed to have the same meaning in other Western high-income countries like Germany, there are also some culturally specific characteristics. For example, some differences between built environments in Europe and the United States have been described in the literature: European cities are often denser and more centralized than their US counterparts (48). US neighborhoods have historically been designed from an automobile perspective and are often hindering active travel, whereas European countries have been implementing car-restrictive policies and encouraging walking and cycling (e.g., through cycling infrastructure or traffic calming) since the 1970s (49, 50). In addition, a systematic review of the relationship between the physical environment and different domains of physical activity in Europe suggested that some environmental characteristics which are associated with physical activity in US adults might be less relevant for the physical activity of European adults (i.e., access to recreation facilities, aesthetics, and crime- and traffic-related safety) (51). Therefore, alternative measures may be more suitable in the European context (52). Audit tools developed and tested in other countries might not necessarily capture the most relevant characteristics of the physical activity-related built environment in Germany. Audit tools that are adapted to the local context are, on the one hand, less suitable to produce research data for cross-country comparisons, but on the other hand, they are more practicable for local stakeholders. Different audit tools have been tailored to European country-specific contexts, e.g., the Scottish Walkability Assessment Tool (SWAT) (53) or the Cyprus Neighborhood Observation Tool (Cy-NOTes) (54).
Only a few audit tools have been applied in Germany, with a focus on the urban pedestrian environment (55). However, a large proportion—between 15 and 60 percent of the German population lives in rural areas, depending on the applied definition of rurality (56). In Germany, rural areas are either defined as any municipality outside metropolitan areas (57), as any municipality with <5,000 inhabitants (58), or by an index of rurality combining lower density, a higher share of single-family homes, a higher share of agricultural land use and forests, lower demographic potential and lower accessibility of cities and towns (56). Apart from these defining factors, rural areas in Germany are diverse and differences between rural and urban areas in terms of lifestyles are decreasing (59). Although there is no significant difference in the total levels of physical activity of adults living in rural and those living in urban areas, adults in rural areas have lower levels of transport-related physical activity, which can be explained by longer travel distances to workplaces, shops, and other facilities and destinations (34, 60, 61). While older studies have found higher levels of physical activity in children and adolescents in rural compared to urban areas in Germany, a more recent one revealed stronger declines of total physical activity and outdoor play in rural areas, which may be a result of a lack of opportunities (62–65).
Internationally, only a few audit tools have been applied in rural areas [e.g., RALA, Inventories for Community Health Assessment in Rural Towns (ICHART) (47, 66)] and studies have suggested that some unique characteristics of rural areas (e.g., fewer destinations and longer distances) need special attention when assessing the built environment related to physical activity (47, 66, 67).
To the authors' knowledge, there is no comprehensive audit tool suitable to assess the built environment related to different types of physical activity in urban and rural German municipalities. Hence, we aimed (1) to develop an audit toolbox adapted to the German context, urban and rural settings, different population groups, and different types of physical activity, and (2) to evaluate its inter-rater reliability.
2. Materials and methods
The KomBus audit toolbox (KomBus is a German acronym for “Kommunale Bewegungsverhältnisse untersuchen” = assess community environments for physical activity) was developed in four consecutive steps (Figure 1). In the first step, we conducted a systematic literature search to collect existing audit tools. In the second step, we created a category system for the toolbox building on the literature. In the third step, we assigned the content of the identified audit tools to the categories of the category system to receive an overview of relevant items. We then decided which items to include in the first draft of the audit toolbox. In the final fourth step, the first version of the audit toolbox was piloted and tested for inter-rater reliability.
Figure 1. Development process of the KomBus-toolbox.
2.1. Step 1: literature search
By reviewing existing audit instruments, we aimed to identify similarities and differences and derive constructs that can be reliably assessed by an audit tool. This approach has been chosen in the development of other audit tools (66, 68, 69). We identified existing audit tools for assessing community physical activity environments through a literature search in PubMed. The search strategy included keywords related to four different themes (see Supplementary material for the complete list of keywords):
• forms of physical activity (e.g., walk*, cycle*, active play, exercise)
• instruments designed to describe the environment (e.g., observational instrument, assessment tool, checklist)
• environmental attributes relevant to physical activity (e.g., walkability, bikeability, aesthetics, safety)
• study area and spaces (e.g., urban, rural, neighborhood, street*, open space*, green space*, playground)
In addition to the literature search in PubMed, two national databases (SPOLIT, LIVIVO) were searched with the same keywords in German. Detailed information was extracted from the articles on the names and types of the applied audit instruments as well as the geographical context (urban and/or rural context, continent, and country), the population group of interest, and relevant quality criteria (validity and reliability). During this process, bibliographical references of relevant articles were also screened.
2.2. Step 2: development of the category system for the toolbox
The categories for the toolbox were selected from existing categorizations of environmental characteristics assessed by audit tools (43, 70, 71) as well as the domains assessed by the tools identified in step 1 based on their relevance for physical activity and the availability of any evidence for their relevance in Germany. We inspected the results of 17 systematic reviews and one umbrella review on the relationship between characteristics of the built environment and physical activity in different population groups (see Supplementary Tables 2–5) (17–19, 51, 72–85). The selected categories and their evidence base are displayed in Table 1.
Table 1. Selection of categories.
The literature search underlined the idea that a customization according to the investigator's intention (e.g., focusing on seniors or on rural settings) was useful. Therefore, the basic categories were complemented with additional categories sensitive to the peculiarities of specific contexts, settings, and population groups.
2.3. Step 3: item allocation and selection, contextual and cultural adaptation
After the definition of relevant categories and themes, possible items were extracted from the identified existing audit tools and assigned to them. By taking existing reliable and/or validated tools as a basis, we aimed to increase the quality of the KomBus toolbox. To identify the most applicable items for the KomBus toolbox, the following criteria were applied:
• relevance regarding physical activity (leisure activity, active transport) of different target groups (children and adolescents, adults, older adults) (assessment based on systematic reviews)
• relevance for the German context (assessment based on qualitative and quantitative studies from Germany, consideration of national traffic regulations and other country-specific definitions)
• comprehensibility, simplicity, and clarity.
For example, “types of residential buildings” is an item in many existing audit tools (e.g., 44, 53, 66) contributing to the description of the land-use mix and residential density, which are associated with physical activity in different population groups (18, 72, 79, 81, 82). A population-based German study has found a relationship between population density and active travel in adults (34). Therefore, the item “types of residential buildings” was considered to be relevant for the KomBus toolbox. We compared the operationalizations and response options in different audit tools and chose the most appropriate ones, considering the frequency of different residential buildings in German municipalities (see Table 2). Considering these criteria like in the example, the categories of the basic tool and the supplementary tools were filled with items. Eventually, these items were translated into German to generate a draft version of the toolbox ready for piloting.
Table 2. Selection of items (example for types of residential buildings).
2.4. Step 4: piloting and inter-rater reliability
The initial draft of the KomBus-toolbox was field-tested with a focus on feasibility and comprehensibility. Three researchers carried out primal field tests with the toolbox. Besides, a manual containing further explications, definitions, and reference photos was created to assist auditors.
Additional feedback on the toolbox was obtained from student field testers from two different universities. Incorporating feedback from these initial field tests, the tool was revised multiple times before piloting for inter-rater reliability.
In July and August 2021, 100 street segments were assessed using the basic tool and the supplementary tools for children and adolescents and seniors and people with impaired mobility. We determined the minimum number of street segments required for calculating the inter-rater reliability of the basic tool following the recommendations by Bujang and Baharum (86). The mean number of response options (two), the minimum value for the desired kappa coefficient (0.4), the desired power (80.0%), the specified alpha-value (0.05), as well as the assumption that the proportions in each response option are not proportional to each other, determined a minimum sample of 94 street segments (86). Accordingly, we set the sample size at 100 street segments. In addition, 15 parks and 21 playgrounds were assessed using the supplementary tools for parks and public open spaces and playgrounds. Two different auditors independently assessed each street segment, park, and playground. Cities and communities of different sizes were included: Frankfurt on the Main (population: 764,104; density: 3,100/km2), Wurzburg (population: 126,954; density: 1,450/km2), Schweinfurt (population: 53,319; density: 1,500/km2), Karlstadt on the Main (population: 14,930; density: 152/km2), Hoechberg (population: 9,501; density: 1250/km2) and two communities in the rural district Rhoen-Grabfeld (Wuelfershausen an der Saale; population: 1,501; density: 83/km2; Saal an der Saale; population: 1,517; density: 70/km2) (87).
Data was processed with SPSS Statistics (see Supplementary material for the datasets). Inter-rater reliability was calculated for all categorical variables with sufficient variability using Cohen's Kappa statistic (κ), defined as:
where p0 is the relative observed agreement between raters and pe is the hypothetical probability of chance agreement. Kappa values were classified as suggested by Landis and Koch, with almost perfect defined as κ ≥ 0.81, substantial defined as 0.6 < κ ≤ 0.8, moderate defined as 0.4 < κ ≤ 0.6, fair defined as 0.2 < κ ≤ 0.4, slight defined as 0.0 < κ ≤ 0.2, and poor defined as κ < 0.0 (88).
3. Results
3.1. Step 1: literature search
The PubMed search identified 692 articles that were title-screened for relevance. After excluding 440 articles, 252 articles remained for the full-text screening process. Information on the applied audit tools (name and type), the geographical context (urban and/or rural context, continent, and country), the population group of interest, and relevant quality criteria (validity and reliability) was retrieved. In sum, 86 audit instruments were identified across the 252 articles and their references. Additionally, four German tools were identified. The extracted information on the identified tools is summarized in Supplementary Table 1.
3.2. Step 2: category system of the toolbox: “basic tool”and “supplementary tools”
Seven categories were defined as basic categories irrespective of the population group and rurality: (A) land use (B) traffic safety, (C) pedestrian environment, (D) cycling environment, (E) attractiveness,(F) social environment, and (G) subjective assessment. Deriving from the literature search results, the main population groups of interest not fully covered in the basic tool were children and adolescents as well as seniors and people with impaired mobility. Hence, we decided to develop two supplementary tools with specific categories incorporating items of high relevance for those groups. In the case of children and adolescents, the categories were traffic calming and public places and destinations. For seniors and people with impaired mobility, the category demands of people with impaired mobility was added. Two independent supplementary tools were developed for parks and public open spaces and playgrounds. The two supplementary tools were constructed similarly with both tools containing the categories A) access and environment, B) design, amenities, and activities as well as C) condition, cleanliness, and safety. The parks and public open spaces tool was supplemented by the category D) social environment.
Although the definition of rurality is complex and adequate measures are debatable (89), rural settings are often characterized by longer travel distances to destinations and a lower land use mix. Therefore, it was considered useful to develop a supplementary tool for rural areas, which looks beyond the streetscape of a particular segment, considering active travel options to destinations in a travel radius of 20 km.
3.3. Step 3: selected and adapted themes for the “basic tool” and for the “supplementary tools”
The categories and themes of the final version of the “Basic Tool” are displayed in Table 3.
Table 3. Categories and themes of the KomBus basic tool.
The supplementary tools are listed in Table 4. The supplements were designed to be used optionally, depending on the investigators' goal.
Table 4. Categories and themes of the KomBus supplementary tools.
3.4. Step 4: piloting and inter-rater reliability
76 % of all included items had moderate, substantial, or almost perfect inter-rater reliability (Basic Tool: 71%, supplementary tool children and adolescents: 76%, supplementary tool seniors and people with impaired mobility: 100%, supplementary tool parks and public open spaces: 78%, supplementary tool playgrounds: 85%). Table 5 summarizes the results by category.
Table 5. Aggregated results for inter-rater reliability.
4. Discussion
In this study, we developed and tested an audit toolbox adapted to the German context, urban and rural settings, different population groups, and different types of physical activity. The toolbox consists of a basic tool with seven categories (land use and destinations, traffic safety, pedestrian environment, cycling environment, attractiveness, social environment, and subjective assessment) and five supplementary tools (children and adolescents, seniors and people with impaired mobility, parks and public open spaces, playgrounds, and rural areas). Across all parts of the toolbox, most of the items demonstrated at least moderate inter-rater reliability (κ > 0.4). Of the seven categories of the basic tool, the category land use and destinations showed the highest reliability. Of the supplementary tools, the tool seniors and people with impaired mobility showed the highest reliability. The category subjective assessment demonstrated the lowest inter-rater reliability, followed by social environment and pedestrian environment.
To our knowledge, KomBus is the first comprehensive audit toolbox composed of different parts that can be used depending on the context and population group of interest. Compared to other audit instruments [e.g., SWAT, RALA, MAPS (45, 47, 53)], KomBus equally considers the needs of pedestrians and cyclists, taking into account the importance of cycling in Germany. Aspects related to safety from crime, like surveillance or street level windows, were considered less relevant in Germany and were thus not included. Another difference is the integration of open fields for the auditor to note any present destinations, as compared to lists of destinations found in other tools. This is supposed to facilitate the application of the audit in general and particularly in rural areas, where fewer destinations are present, and allows for a more precise description of the present destination.
Since limited access to destinations like schools, shops, recreation facilities, or healthcare services has been described as a barrier to active travel in rural areas (67, 90, 91), we developed a supplementary tool for rural communities to assess active travel options to destinations in a travel radius of 20 km. This supplementary tool is similar to the RALA townwide assessment (47), but allows for a more precise analysis of different travel options (walking, cycling, and public transport), potential barriers (e.g., lack of walking or cycling infrastructure, frequency of public transport), and a greater variety of destinations (e.g., pharmacy or supermarket).
Concerning inter-rater reliability, KomBus is comparable to other audits (42, 46, 92). Similar to other instruments, there were some items with relatively low kappa values. However, some of these can be explained by other reasons than actual low reliability. In some cases, little variation across segments led to low kappa values despite high observer agreement. This applied to most items of the category pedestrian environment with lower inter-rater reliability; e.g., the item “street furniture as permanent obstacle for pedestrians” had an observer agreement of 96 %, but a high prevalence of the “no”-category, which led to a kappa value defining poor inter-rater reliability (93). Other items with lower inter-rater reliability were subject to continuous change, e.g., the number of people present, and changes may have occurred between the assessments of the first and the second auditor. The low inter-rater reliability in the subjective assessment had been anticipated, given the subjective nature of this category.
Based on the results of the reliability testing and the identified reasons for lower kappa statistics, we decided which items should be excluded from the toolbox (items not prevalent in any of the 100 street segments, e.g., gravel as material of sidewalks) and which items required further explanation or clarification (e.g., condition of sidewalks). Despite their relatively low reliability, we decided not to exclude items of the subjective assessment and social environment, as these categories may be of additional value for community stakeholders applying the toolbox in their community.
Recent research has pointed out the potential of virtual audits using Google Street View as reliable, cost-effective, and time-effective alternatives to field audits (94). However, this is currently no viable option in Germany, as coverage is limited, especially outside metropolitan areas. Besides, field audits have some advantages compared to virtual audits: Field audits are more suitable to assess features susceptible to temporal variability (e.g., litter or temporary obstructions), as well as sensory impressions like noise or odors (94). In addition, we advocate for the exposition of the auditor in the real setting as it facilitates the deduction of needs for changes in the environment. The main strength of a field audit is to provide an extensive and accurate description of environmental attributes directly or indirectly influencing physical activity in different communal settings.
Using audit tools to quantify the physical activity friendliness of communities is not an easy process. The application of sum scores used in some other audits (e.g., MAPS), that aim to evaluate the quality of environments in an attempt to quantify favorable and unfavorable factors, was regarded as not expedient for this purpose. This would undermine the fact that the evaluation of attributes being either favorable or unfavorable to physical activity depends on the perspective of the user (e.g., cycling lanes vs. play roads). In place of sum scores, KomBus was complemented with a manual providing interpretation aids. The aids include descriptions of each component, information on evidence of promoting factors of physical activity related to settings and target groups, as well as questions that may help to contemplate measures for improvement.
We would like to mention some limitations. The toolbox was developed and tested by a team of experienced researchers through an extensive review of the literature. However, community stakeholders have not been involved in the development and testing of the toolbox. Although we tested the toolbox in a variety of neighborhoods in cities and villages of different sizes, some of the items lacked variability and could not be assessed for inter-rater reliability. The focus of the pilot test was the inter-rater reliability of the toolbox. To improve its usability for research purposes, future research should take an effort in assessing validity measures such as the internal consistency and the discriminant capacity between categories. Further research is also necessary to test whether levels of physical activity are higher in areas with more favorable activity-friendly environments assessed with the toolbox. This was not part of the current study. Besides, we recommend testing the toolbox in other parts of Germany or in other European countries. Another suggestion for further development would be to test the tool with urban planners, architects, or professionals working in the field of health promotion.
The toolbox is available online as a part of the digital planning tool for physical activity-friendly communities (https://www.aelter-werden-in-balance.de/impulsgeber-bewegungsfoerderung/) recently launched by the German Federal Center for Health Education (BZgA).
5. Conclusions
This paper presents the literature-based development and reliability-testing of the German audit toolbox KomBus considering characteristics of the built environment that are associated with physical activity in different population groups. The toolbox demonstrated moderate to good inter-rater reliability and can be recommended for use by researchers and community stakeholders in German urban and rural areas.
Data availability statement
The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.
Author contributions
CM, BD, BW-S, and JB contributed to the research proposal and design. CM, BD, and TA conducted the literature search and developed the audit toolbox with continuous feedback from BW-S, JB, and CR. CM, BD, and TA conducted the field tests. CM, BD, and E-MH participated in data management. CM and E-MH conducted the reliability analyses. CM and BD drafted the manuscript. TA, E-MH, CR, BW-S, and JB edited the manuscript. All authors read and approved the final manuscript.
Funding
This project was funded by the German Federal Center for Health Education (BZgA) with support from the Association of Private Health Insurance (PKV). This publication was supported by the Open Access Publication Fund of the University of Wuerzburg.
Acknowledgments
The authors would like to thank Claudia Vonstein and Annalena Buβkamp, German Federal Center for Health Education (BZgA) for supporting the project.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpubh.2023.1153088/full#supplementary-material
References
1. World Health Organization. Guidelines on Physical Activity and Sedentary Behavior. Geneva: World Health Organization (WHO). (2020).
2. Warburton DER, Bredin SSD. Health benefits of physical activity: a systematic review of current systematic reviews. Curr Opin Cardiol. (2017) 32:541–56. doi: 10.1097/HCO.0000000000000437
3. Lee I-M, Shiroma EJ, Lobelo F, Puska P, Blair SN, Katzmarzyk PT. Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet. (2012) 380:219–29. doi: 10.1016/S0140-6736(12)61031-9
4. McTiernan A, Friedenreich CM, Katzmarzyk PT, Powell KE, Macko R, Buchner D, et al. Physical activity in cancer prevention and survival: a systematic review. Med Sci Sports Exerc. (2019) 51:1252–61. doi: 10.1249/MSS.0000000000001937
5. Schuch FB, Vancampfort D, Richards J, Rosenbaum S, Ward PB, Stubbs B. Exercise as a treatment for depression: a meta-analysis adjusting for publication bias. J Psychiatr Res. (2016) 77:42–51. doi: 10.1016/j.jpsychires.2016.02.023
6. Schuch FB, Stubbs B, Meyer J, Heissel A, Zech P, Vancampfort D, et al. Physical activity protects from incident anxiety: a meta-analysis of prospective cohort studies. Depress Anxiety. (2019) 36:846–58. doi: 10.1002/da.22915
7. Schuch FB, Vancampfort D, Firth J, Rosenbaum S, Ward PB, Silva ES, et al. Physical activity and incident depression: a meta-analysis of prospective cohort studies. Am J Psychiatry. (2018) 175:631–48. doi: 10.1176/appi.ajp.2018.17111194
8. Bucksch J, Häußler A, Finne E, Schmidt K, Dadacynski K, Sudeck G. Physical activity and dietary habits of older children and adolescents in Germany—Cross-sectional results of the. 2017/18 HBSC study and trends. J Health Monit. (2020) 5:21–36. doi: 10.25646/6900
9. Finger JD, Varnaccia G, Borrmann A, Lange C, Mensink G. Physical activity among children and adolescents in Germany. Results of the cross-sectional KiGGS Wave 2 study and trends. J Health Monit. (2018) 3:23–30. doi: 10.17886/RKI-GBE-2018-023.2
10. Richter A, Schienkiewitz A, Starker A, Krug S, Domanska O, Kuhnert R, et al. Health-promoting behavior among adults in Germany—Results from GEDA 2019/2020-EHIS. J Health Monit. (2021) 6:26–44. doi: 10.25646/8553
11. Guthold R, Stevens GA, Riley LM, Bull FC. Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1·9 million participants. Lancet Glob Health. (2018) 6:e1077–86. doi: 10.1016/S2214-109X(18)30357-7
12. Sallis JF, Cervero RB, Ascher W, Henderson KA, Kraft MK, Kerr J. An ecological approach to creating active living communities. Annu Rev Public Health. (2006) 27:297–322. doi: 10.1146/annurev.publhealth.27.021405.102100
13. Bauman AE, Reis RS, Sallis JF, Wells JC, Loos RJF, Martin BW. Correlates of physical activity: why are some people physically active and others not? Lancet. (2012) 380:258–71. doi: 10.1016/S0140-6736(12)60735-1
14. Prince SA, Lancione S, Lang JJ, Amankwah N, Groh M de, Jaramillo Garcia A, et al. Examining the state, quality and strength of the evidence in the research on built environments and physical activity among adults: An overview of reviews from high income countries. Health Place. (2022) 77:102874. doi: 10.1016/j.healthplace.2022.102874
15. Travert A-S, Sidney Annerstedt K, Daivadanam M. Built environment and health behaviors: deconstructing the black box of interactions—a review of reviews. Int J Environ Res Public Health. (2019) 16:454. doi: 10.3390/ijerph16081454
16. Smith M, Hosking J, Woodward A, Witten K, MacMillan A, Field A, et al. Systematic literature review of built environment effects on physical activity and active transport—An update and new findings on health equity. Int J Behav Nutr Phys Act. (2017) 14:158. doi: 10.1186/s12966-017-0613-9
17. Kärmeniemi M, Lankila T, Ikäheimo T, Koivumaa-Honkanen H, Korpelainen R. The built environment as a determinant of physical activity: a systematic review of longitudinal studies and natural experiments. Ann Behav Med. (2018) 52:239–51. doi: 10.1093/abm/kax043
18. Bonaccorsi G, Manzi F, Del Riccio M, Setola N, Naldi E, Milani C, et al. Impact of the built environment and the neighborhood in promoting the physical activity and the healthy aging in older people: an umbrella review. Int J Environ Res Public Health. (2020) 17:17. doi: 10.3390/ijerph17176127
19. Nordbø ECA, Nordh H, Raanaas RK, Aamodt G. Promoting activity participation and well-being among children and adolescents: a systematic review of neighborhood built-environment determinants. JBI Evid Synth. (2020) 18:370–458. doi: 10.11124/JBISRIR-D-19-00051
20. Tcymbal A, Demetriou Y, Kelso A, Wolbring L, Wunsch K, Wäsche H, et al. Effects of the built environment on physical activity: a systematic review of longitudinal studies taking sex/gender into account. Environ Health Prev Med. (2020) 25:75. doi: 10.1186/s12199-020-00915-z
21. Sallis JF, Cerin E, Kerr J, Adams MA, Sugiyama T, Christiansen LB, et al. Built environment, physical activity, and obesity: findings from the international physical activity and environment network (IPEN) adult study. Annu Rev Public Health. (2020) 41:119–39. doi: 10.1146/annurev-publhealth-040218-043657
22. van Dyck D, Cerin E, Conway TL, Bourdeaudhuij I de, Owen N, Kerr J, et al. Perceived neighborhood environmental attributes associated with adults' transport-related walking and cycling: findings from the USA, Australia and Belgium. Int J Behav Nutri Physical Act. (2012) 9:70. doi: 10.1186/1479-5868-9-70
23. Boakye K, Bovbjerg M, Schuna J, Branscum A, Mat-Nasir N, Bahonar A, et al. Perceived built environment characteristics associated with walking and cycling across 355 communities in 21 countries. Cities. (2023) 132:104102. doi: 10.1016/j.cities.2022.104102
24. Bucksch J, Kopcakova J, Inchley J, Troped PJ, Sudeck G, Sigmundova D, et al. Associations between perceived social and physical environmental variables and physical activity and screen time among adolescents in four European countries. Int J Public Health. (2019) 64:83–94. doi: 10.1007/s00038-018-1172-9
25. Ding D, Adams MA, Sallis JF, Norman GJ, Hovell MF, Chambers CD, et al. Perceived neighborhood environment and physical activity in 11 countries: do associations differ by country? Int J Behav Nutri Physical Act. (2013) 10:57. doi: 10.1186/1479-5868-10-57
26. Cain KL, Millstein RA, Sallis JF, Conway TL, Gavand KA, Frank LD, et al. Contribution of streetscape audits to explanation of physical activity in four age groups based on the microscale audit of pedestrian streetscapes (MAPS). Soc Sci Med. (2014) 116:82–92. doi: 10.1016/j.socscimed.2014.06.042
27. Poitras VJ, Gray CE, Borghese MM, Carson V, Chaput J-P, Janssen I, et al. Systematic review of the relationships between objectively measured physical activity and health indicators in school-aged children and youth. Appl Physiol Nutri Metabol. (2016) 41(6 Suppl. 3):S197–239. doi: 10.1139/apnm-2015-0663
28. Sprengeler O, Wirsik N, Hebestreit A, Herrmann D, Ahrens W. Domain-specific self-reported and objectively measured physical activity in children. Int J Environ Res Public Health. (2017) 14:242. doi: 10.3390/ijerph14030242
29. Kelso A, Reimers AK, Abu-Omar K, Wunsch K, Niessner C, Wäsche H, et al. Locations of physical activity: where are children, adolescents, and adults physically active? A systematic review. Int J Environ Res Public Health. (2021) 18:240. doi: 10.3390/ijerph18031240
30. Gray C, Gibbons R, Larouche R, Sandseter EB, Bienenstock A, Brussoni M, et al. What is the relationship between outdoor time and physical activity, sedentary behaviour, and physical fitness in children? A Systematic Review. Int J Behav Nutri Physical Act. (2015) 12:6455–74. doi: 10.3390/ijerph120606455
31. Prince SA, Lancione S, Lang JJ, Amankwah N, Groh M de, Garcia AJ, et al. Are people who use active modes of transportation more physically active? An overview of reviews across the life course. Transport Rev. (2022) 42:645–71. doi: 10.1080/01441647.2021.2004262
32. Prince SA, Butler GP, Rao DP, Thompson W. Evidence synthesis - Where are children and adults physically active and sedentary? A rapid review of location-based studies. Health Promot Chronic Dis Prev Can. (2019) 39:67–103. doi: 10.24095/hpcdp.39.3.01
33. Prince SA, Lancione S, Lang JJ, Amankwah N, Groh M de, Jaramillo Garcia A, et al. Examining the state, quality and strength of the evidence in the research on built environments and physical activity among children and youth: An overview of reviews from high income countries. Health Place. (2022) 76:102828. doi: 10.1016/j.healthplace.2022.102828
34. Finger JD, Varnaccia G, Gabrys L, Hoebel J, Kroll LE, Krug S, et al. Area-level and individual correlates of active transportation among adults in Germany: a population-based multilevel study. Sci Rep. (2019) 9:1–11. doi: 10.1038/s41598-019-52888-x
35. Cunningham C, Sullivan R, Caserotti P, Tully MA. Consequences of physical inactivity in older adults: a systematic review of reviews and meta-analyses. Scand J Med Sci Sports. (2020) 30:816–27. doi: 10.1111/sms.13616
36. Gropper H, John JM, Sudeck G, Thiel A. The impact of life events and transitions on physical activity: a scoping review. PLoS ONE. (2020) 15:e0234794. doi: 10.1371/journal.pone.0234794
37. Stalling I, Albrecht BM, Doerwald F, Bammann K. Time allocation to active domains, physical activity, and health indicators in older adults: cross-sectional results from the OUTDOOR ACTIVE study. BMC Public Health. (2020) 20:1–11. doi: 10.1186/s12889-020-09708-z
38. Nobis C,. Mobilität in Deutschland- MiD: Analysen zum Radverkehr und Fußverkehr. Studie von infas, DLR, IVT und infas 360 im Auftrag des Bundesministeriums für Verkehr und digitale Infrastruktur (FE-Nr. 70.904/15). Bonn; Berlin (2019). Available online at: www.mobilitaet-in-deutschland.de
39. Buffel T, Verte D, Donder L de, Witte N de, Dury S, Vanwing T, et al. Theorising the relationship between older people and their immediate social living environment. Int J Lifelong Edu. (2012) 31:13–32. doi: 10.1080/02601370.2012.636577
40. Satariano WA, Guralnik JM, Jackson RJ, Marottoli RA, Phelan EA, Prohaska TR. Mobility and aging: new directions for public health action. Am J Public Health. (2012) 102:1508–15. doi: 10.2105/AJPH.2011.300631
41. Moran M, van Cauwenberg J, Hercky-Linnewiel R, Cerin E, Deforche B, Plaut P. Understanding the relationships between the physical environment and physical activity in older adults: a systematic review of qualitative studies. Int J Behav Nutri Physical Act. (2014) 11:1–12. doi: 10.1186/1479-5868-11-79
42. Brownson RC, Hoehner CM, Day K, Forsyth A, Sallis JF. Measuring the built environment for physical activity: state of the science. Am J Prev Med. (2009) 36(Suppl 4):S99–123.e12. doi: 10.1016/j.amepre.2009.01.005
43. Xu Z, Wang Y, Xu Q, Han L, Xu F. Comparative research of audit tools on built environment for active living. Landsc Archit Front. (2020) 8:52–73. doi: 10.15302/J-LAF-1-020025
44. Hoehner CM, Ivy A, Ramirez LKB, Handy S, Brownson RC. Active neighborhood checklist: a user-friendly and reliable tool for assessing activity friendliness. Am J Health Promot. (2007) 21:534–7. doi: 10.4278/0890-1171-21.6.534
45. Millstein RA, Cain KL, Sallis JF, Conway TL, Geremia C, Frank LD, et al. Development, scoring, and reliability of the microscale audit of pedestrian streetscapes (MAPS). BMC Public Health. (2013) 13:403. doi: 10.1186/1471-2458-13-403
46. Clifton KJ, Livi Smith AD, Rodriguez D. The development and testing of an audit for the pedestrian environment. Landsc Urban Plan. (2007) 80:95–110. doi: 10.1016/j.landurbplan.2006.06.008
47. Yousefian A, Hennessy E, Umstattd MR, Economos CD, Hallam JS, Hyatt RR, et al. Development of the rural active living assessment tools: measuring rural environments. Prev Med. (2010) 50:S86–92. doi: 10.1016/j.ypmed.2009.08.018
48. Huang J, Lu XX, Sellers JM, A. global comparative analysis of urban form: applying spatial metrics and remote sensing. Landsc Urban Plan. (2007) 82:184–97. doi: 10.1016/j.landurbplan.2007.02.010
49. Buehler R, Pucher J. Walking and cycling in Western Europe and the United States: trends, policies, and lessons. TR News. (2012) 280:34–42.
50. Adams MA, Ding D, Sallis JF, Bowles HR, Ainsworth BE, Bergman P, et al. Patterns of neighborhood environment attributes related to physical activity across 11 countries: a latent class analysis. Int J Behav Nutr Phys Act. (2013) 10(34). doi: 10.1186/1479-5868-10-34
51. van Holle V, Deforche B, van Cauwenberg J, Goubert L, Maes L, van de Weghe N, et al. Relationship between the physical environment and different domains of physical activity in European adults: a systematic review. BMC Public Health. (2012) 12:807. doi: 10.1186/1471-2458-12-807
52. Grasser G, van Dyck D, Titze S, Stronegger WJ. A European perspective on GIS-based walkability and active modes of transport. Eur J Public Health. (2017) 27:145–51. doi: 10.1093/eurpub/ckw118
53. Millington C, Ward Thompson C, Rowe D, Aspinall P, Fitzsimons C, Nelson N, et al. Development of the Scottish walkability assessment tool (SWAT). Health Place. (2009) 15:474–81. doi: 10.1016/j.healthplace.2008.09.007
54. Kleopa D, Panayiotou A, Kouta C, Middleton N. Content validity of neighbourhood environment audit tool: virtual ethnographic study. Eur J Public Health. (2018) 28(Suppl 4):72. doi: 10.1093/eurpub/cky214.072
55. Ruppert P, Tran MC, Schmidt JA. Walk-Audits in der Stadtplanung und Gesundheitsförderung. In:Niederberger M, Finne E, , editors. Forschungsmethoden in der Gesundheitsförderung und Prävention. Wiesbaden: Springer Fachmedien (2021). p. 651–83. doi: 10.1007/978-3-658-31434-7_24
56. Küpper P,. Abgrenzung und Typisierung ländlicher Räume: Thünen Working Paper 68. Johann Heinrich von Thünen-Institut. (2016). Available online at: https://literatur.thuenen.de/digbib_extern/dn057783.pdf (accessed January 3, 2020).
57. Bundesministerium für Verkehr und digitale Infrastruktur. Regionalstatistische Raumtypologie (RegioStaR). Available online at: https://www.bmvi.de/SharedDocs/DE/Artikel/G/regionalstatistische-raumtypologie.html (accessed December 16, 2020).
58. Bundesinstitut für Bau-, Stadt- und Raumforschung. Raumbeobachtung - Laufende Stadtbeobachtung - Raumabgrenzungen. (2020). Available online at: https://www.bbsr.bund.de/BBSR/DE/forschung/raumbeobachtung/Raumabgrenzungen/deutschland/gemeinden/StadtGemeindetyp/StadtGemeindetyp.html (accessed December 16, 2020).
59. Spellerberg A. Was unterscheidet städtische und ländliche Lebensstile? In:Berger PA, Keller C, Klärner A, Neef R, , editors. Urbane Ungleichheiten. Wiesbaden: Springer Fachmedien. (2014). p. 199–232. doi: 10.1007/978-3-658-01014-0_10
60. Bürkert C. Aktive Mobilität im ländlichen und städtischen Raum: Eine Analyse von Umweltmerkmalen und psychosozialen Faktoren. 1st ed. Wiesbaden: Springer Fachmedien (2019).
61. Wallmann-Sperlich B, Froboese I. Physical activity during work, transport and leisure in Germany—Prevalence and socio-demographic correlates. PLoS ONE. (2014) 9:e112333. doi: 10.1371/journal.pone.0112333
62. Jekauc D, Reimers AK, Wagner MO, Woll A. Prevalence and socio-demographic correlates of the compliance with the physical activity guidelines in children and adolescents in Germany. BMC Public Health. (2012) 12:714. doi: 10.1186/1471-2458-12-714
63. Krause L, Anding C, Kamtsiuris P. Ernährung, bewegung und substanzkonsum von kindern und jugendlichen: repräsentative ergebnisse des landesmoduls thüringen in KiGGS Welle 1. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. (2016) 59:1005–16. doi: 10.1007/s00103-016-2386-8
64. Ortlieb S, Schneider G, Koletzko S, Berdel D, Berg A von, Bauer C-P, et al. Physical activity and its correlates in children: a cross-sectional study (the GINIplus & LISAplus studies). BMC Public Health. (2013) 13:349. doi: 10.1186/1471-2458-13-349
65. Nigg C, Weber C, Schipperijn J, Reichert M, Oriwol D, Worth A, et al. Urban-rural differences in children's and adolescent's physical activity and screen-time trends across 15 years. Health Edu Behav. (2022) 49:789–800. doi: 10.1177/10901981221090153
66. Seguin RA, Lo BK, Sriram U, Connor LM, Totta A. Development and testing of a community audit tool to assess rural built environments: inventories for community health assessment in rural towns. Prev Med Rep. (2017) 7:169–75. doi: 10.1016/j.pmedr.2017.06.008
67. Frost SS, Goins RT, Hunter RH, Hooker SP, Bryant LL, Kruger J, et al. Effects of the built environment on physical activity of adults living in rural settings. Am J Health Promot. (2010) 24:267–83. doi: 10.4278/ajhp.08040532
68. Su M, Du Y, Liu Q, Ren Y, Kawachi I, Lv J, et al. Objective assessment of urban built environment related to physical activity—Development, reliability and validity of the China urban built environment scan tool (CUBEST). BMC Public Health. (2014) 14:109. doi: 10.1186/1471-2458-14-109
69. Malecki KC, Engelman CD, Peppard PE, Nieto FJ, Grabow ML, Bernardinello M, et al. The Wisconsin assessment of the social and built environment (WASABE): a multi-dimensional objective audit instrument for examining neighborhood effects on health. BMC Public Health. (2014) 14:1–15. doi: 10.1186/1471-2458-14-1165
70. Kan HY, Forsyth A, Molinsky J. Measuring the built environment for aging in place: a review of neighborhood audit tools. J Plan Lit. (2020) 35:180–94. doi: 10.1177/0885412220903497
71. Nickelson J, Wang AR, Mitchell QP, Hendricks K, Paschal A. Inventory of the physical environment domains and subdomains measured by neighborhood audit tools: a systematic literature review. J Environ Psychol. (2013) 36:179–89. doi: 10.1016/j.jenvp.2013.07.009
72. Lambert A, Vlaar J, Herrington S, Brussoni M. What is the relationship between the neighbourhood built environment and time spent in outdoor play? A systematic review. Int J Environ Res Public Health. (2019) 16:3840. doi: 10.3390/ijerph16203840
73. Larouche R. Built environment features that promote cycling in school-aged children. Curr Obes Rep. (2015) 4:494–503. doi: 10.1007/s13679-015-0181-8
74. D'Haese S, Vanwolleghem G, Hinckson E, Bourdeaudhuij I de, Deforche B, van Dyck D, et al. Cross-continental comparison of the association between the physical environment and active transportation in children: a systematic review. Int J Behav Nutri Physical Acti. (2015) 12:1–14. doi: 10.1186/s12966-015-0308-z
75. Timperio A, Reid J, Veitch J. Playability: built and social environment features that promote physical activity within children. Curr Obes Rep. (2015) 4:460–76. doi: 10.1007/s13679-015-0178-3
76. van Hecke L, Ghekiere A, Veitch J, van Dyck D, van Cauwenberg J, Clarys P, et al. Public open space characteristics influencing adolescents' use and physical activity: a systematic literature review of qualitative and quantitative studies. Health Place. (2018) 51:158–73. doi: 10.1016/j.healthplace.2018.03.008
77. McGrath LJ, Hopkins WG, Hinckson EA. Associations of objectively measured built-environment attributes with youth moderate–vigorous physical activity: a systematic review and meta-analysis. Sports Med. (2015) 45:841–65. doi: 10.1007/s40279-015-0301-3
78. Ikeda E, Hinckson E, Witten K, Smith M. Associations of children's active school travel with perceptions of the physical environment and characteristics of the social environment: a systematic review. Health Place. (2018) 54:118–31. doi: 10.1016/j.healthplace.2018.09.009
79. Ding D, Sallis JF, Kerr J, Lee S, Rosenberg DE. Neighborhood environment and physical activity among youth: a review. Am J Prev Med. (2011) 41:442–55. doi: 10.1016/j.amepre.2011.06.036
80. Marzi I, Demetriou Y, Reimers AK. Social and physical environmental correlates of independent mobility in children: a systematic review taking sex/gender differences into account. Int J Health Geogr. (2018) 17:1–17. doi: 10.1186/s12942-018-0145-9
81. McCormack GR, Shiell A. In search of causality: a systematic review of the relationship between the built environment and physical activity among adults. Int J Behav Nutri Physical Acti. (2011) 8:1–11. doi: 10.1186/1479-5868-8-125
82. Wang L, Wen C. The relationship between the neighborhood built environment and active transportation among adults: A systematic literature review. Urban Sci. (2017) 1:29. doi: 10.3390/urbansci1030029
83. Carlin A, Perchoux C, Puggina A, Aleksovska K, Buck C, Burns C, et al. A life course examination of the physical environmental determinants of physical activity behavior: a “determinants of diet and physical activity” (DEDIPAC) umbrella systematic literature review. PLoS ONE. (2017) 12:e0182083. doi: 10.1371/journal.pone.0182083
84. Schulz M, Romppel M, Grande G. Built environment and health: a systematic review of studies in Germany. J Public Health. (2018) 40:8–15. doi: 10.1093/pubmed/fdw141
85. Yang Y, Wu X, Zhou P, Gou Z, Lu Y. Towards a cycling-friendly city: an updated review of the associations between built environment and cycling behaviors (2007–2017). J Transport Health. (2019) 14:100613. doi: 10.1016/j.jth.2019.100613
86. Bujang MA, Baharum N. Guidelines of the minimum sample size requirements for Kappa agreement test. Epidemiol Biostat Public Health. (2017) 14:267. doi: 10.2427/12267
87. Gemeindeverzeichnis-Online. Available online at: https://www.statistikportal.de/de/gemeindeverzeichnis (accessed January 3, 2023).
88. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. (1977) 33:159–74. doi: 10.2307/2529310
89. Nelson KS, Nguyen TD, Brownstein NA, Garcia D, Walker HC, Watson JT, et al. Definitions, measures, and uses of rurality: a systematic review of the empirical and quantitative literature. J Rural Stud. (2021) 82:351–65. doi: 10.1016/j.jrurstud.2021.01.035
90. Graham H, Bell S de, Flemming K, Sowden A, White P, Wright K. The experiences of everyday travel for older people in rural areas: a systematic review of UK qualitative studies. J Transp Health. (2018) 11:141–52. doi: 10.1016/j.jth.2018.10.007
91. Sander M, Ochmann, R, Marschall, J, Schiffhorst, G, Albrecht, M,. AOK-Familienstudie 2018: Eine quantitative und qualitative Befragung von Eltern mit Kindern im Alter von 4 bis 14 Jahren. (2018). Available online at: https://www.aok-bv.de/imperia/md/aokbv/hintergrund/dossier/praevention/aok_familienstudie_wb.pdf (accessed January 3, 2023).
92. Pikora TJ, Bull FC, Jamrozik K, Knuiman M, Giles-Corti B, Donovan RJ. Developing a reliable audit instrument to measure the physical environment for physical activity. Am J Prev Med. (2002) 23:187–94. doi: 10.1016/S0749-3797(02)00498-1
93. Sim J, Wright CC. The Kappa statistic in reliability studies: use, interpretation, and sample size requirements. Phys Ther. (2005) 85:257–68. doi: 10.1093/ptj/85.3.257
94. Rzotkiewicz A, Pearson AL, Dougherty BV, Shortridge A, Wilson N. Systematic review of the use of google street view in health research: major themes, strengths, weaknesses and possibilities for future research. Health Place. (2018) 52:240–6. doi: 10.1016/j.healthplace.2018.07.001
95. Brüchert T, Hasselder P, Quentin P, Bolte G. Walking for transport among older adults: a cross-sectional study on the role of the built environment in less densely populated areas in Northern Germany. Int J Environ Res Public Health. (2020) 17:9479doi: 10.3390/ijerph17249479
96. Brüchert T, Quentin P, Bolte G. The relationship between perceived built environment and cycling or e-biking for transport among older adults—A cross-sectional study. PLoS ONE. (2022) 17:e0267314. doi: 10.1371/journal.pone.0267314
97. Hasselder P, Brüchert T, Baumgart S, Bolte G. Destinations fostering older adults' walking for transport: a cross-sectional study from Germany. BMC Geriatrics. (2022) 22:219. doi: 10.1186/s12877-022-02896-w
98. König K, Raue M, D'Ambrosio LA, Coughlin JF. Physical and emotional support of the neighborhood for older adults: a comparison of the United States and Germany. J Environ Psychol. (2019) 62:84–94. doi: 10.1016/j.jenvp.2019.01.008
99. Schicketanz J, Grabenhenrich L, Lakes T. An index for assessing activity friendliness for children in urban environments of Berlin. DIE ERDE–J Geograph Soc Berlin. (2018) 149:1–13. doi: 10.12854/erde-149-54
100. Markevych I, Smith MP, Jochner S, Standl M, Brüske I, Berg A von, et al. Neighborhood and physical activity in German adolescents: GINIplus and LISAplus. Environ Res. (2016) 147:284–93. doi: 10.1016/j.envres.2016.02.023
101. Reimers AK, Wagner M, Alvanides S, Steinmayr A, Reiner M, Schmidt S, et al. Proximity to sports facilities and sports participation for adolescents in Germany. PLoS ONE. (2014) 9:e93059. doi: 10.1371/journal.pone.0093059
102. Moschny A, Platen P, Klaaßen-Mielke R, Trampisch U, Hinrichs T. Barriers to physical activity in older adults in Germany: a cross-sectional study. Int J Behav Nutri Physical Act. (2011) 8:1–10. doi: 10.1186/1479-5868-8-121
103. Sauter A, Curbach J, Rueter J, Lindacher V, Loss J. German senior citizens' capabilities for physical activity: a qualitative study. Health Promot Int. (2019) 34:1117–29. doi: 10.1093/heapro/day077
104. Wallmann B, Bucksch J, Froboese I. The association between physical activity and perceived environment in German adults. Eur J Public Health. (2012) 22:502–8. doi: 10.1093/eurpub/ckr069
105. EUBeKo-Team. Praxisbeispiel Schönauer Rundweg: “Systematische Planung und Umsetzung einer bewegungsfördernden Intervention im städtischen Raum – das Beispiel Mannheim Schönau. Pädagogische Hochschule Heidelberg. (2022). Available online at: https://gesunde-bewegte-kommune.de/files/Praxisbeispiel-Schoenau.pdf (accessed April 11, 2023).
106. EUBeKo-Team. Praxisbeispiel Wülfershausen a. d. Saale. Systematische Planung und Umsetzung einer bewegungsfördernden Intervention im ländlichen Raum – das Beispiel Wülfershausen a. d. Saale. Pädagogische Hochschule Heidelberg. (2022). Available online at: https://gesunde-bewegte-kommune.de/files/Praxisbeispiel-Wuelfershausen_final.pdf (accessed April 11, 2023).
107. Wex I, Geserick M, Leibert T, Igel U, Sobek C, Meigen C, et al. Active school transport in an urban environment:prevalence and perceived barriers. BMC Public Health. (2023) 23(:557. doi: 10.1186/s12889-023-15464-7
108. Seemüller S, Reimers AK, Marzi I. Eine Perspektive von Grundschulkindern auf Bedingungsfaktoren der aktiven und eigenständigen Mobilität – eine qualitative Studie. Forum Kinder- und Jugendsport. (2022) 3:137–49. doi: 10.1007/s43594-022-00080-x
109. Ahrend C, Herget M. Umwelt- und familienfreundliche Mobilität im ländlichen Raum: Handbuch für nachhaltige Regionalentwicklung: Technische Universität Berlin). (2012). Available online at: http://www.ivp.tu-berlin.de/fileadmin/fg93/Forschung/Projekte/Laendlicher_Raum/ufm-handbuch.pdf (accessed December 12, 2023).
110. Domokos B, Faßbender C, Müller C, Paulsen L, Bucksch J, Wallmann-Sperlich B. Planung und Implementierung einer baulichen Maßnahme zur Bewegungsförderung im ländlichen Raum–die Bewegte Dorfrunde “Wülfershausen. Prävention Gesundheitsförderung. (2023) 3:1–7. doi: 10.1007/s11553-023-01014-x
111. Bammann K, Recke C, Albrecht BM, Stalling I, Doerwald F. Promoting physical activity among older adults using community-based participatory research with an adapted PRECEDE-PROCEED model approach: the AEQUIPA/OUTDOOR ACTIVE project. Am J Health Promot. (2021) 35:409–20. doi: 10.1177/0890117120974876
112. Fietkau J, Stojko L, A. system design to support outside activities of older adults using smart urban objects. In: Proceedings of 18th European Conference on Computer-Supported Cooperative Work. (2020).
113. Risser R, Haindl G, Ståhl A. Barriers to senior citizens' outdoor mobility in Europe. Eur J Ageing. (2010) 7:69–80. doi: 10.1007/s10433-010-0146-4
114. Lübs L, Söllner E, Peplies J, van Hoven B, Bammann K. Einfluss der Nachbarschaft auf die körperliche Aktivität im Freien bei 65-−75-Jährigen in Bremen: Ein Mixed-Methods-Ansatz. Gesundheitswesen. (2016) 78(08/09):A16. doi: 10.1055/s-0036-1586526
115. Hahn D, Hanke K, Hofmann H, Kamp U, Krüger T, Neumann C, et al. Kinderreport Deutschland: Rechte von Kindern in Deutschland: Die Bedeutung des Draußenspielens für Kinder. 1. Auflage. Berlin: Deutsches Kinderhilfswerk. (2020).
116. Blinkert B, Weaver E. Residential environment and types of childhood. Human Soc Sci. (2015) 3:159–68. doi: 10.11648/j.hss.20150305.11
117. Bigonnesse C, Mahmood A, Chaudhury H, Mortenson WB, Miller WC, Martin Ginis KA. The role of neighborhood physical environment on mobility and social participation among people using mobility assistive technology. Disabil Soc. (2018) 33:866–93. doi: 10.1080/09687599.2018.1453783
118. Brüchert T, Baumgart S, Bolte G. Social determinants of older adults' urban design preference: a cross-sectional study. Cities health. (2022) 6:360–74. doi: 10.1080/23748834.2020.1870845
119. McCormack GR, Rock M, Toohey AM, Hignell D. Characteristics of urban parks associated with park use and physical activity: a review of qualitative research. Health Place. (2010) 16:712–26. doi: 10.1016/j.healthplace.2010.03.003
120. Zhang R, Wulff H, Duan Y, Wagner P. Associations between the physical environment and park-based physical activity: a systematic review. J Sport Health Sci. (2019) 8:412–21. doi: 10.1016/j.jshs.2018.11.002
121. Cohen DA, Han B, Williamson S, Nagel C, McKenzie TL, Evenson KR, et al. Playground features and physical activity in US neighborhood parks. Prev Med. (2020) 131:105945. doi: 10.1016/j.ypmed.2019.105945
122. Reimers AK, Knapp G. Playground usage and physical activity levels of children based on playground spatial features. J Public Health. (2017) 25:661–9. doi: 10.1007/s10389-017-0828-x
Keywords: built environment, physical activity, reliability, rural, urban, walkability
Citation: Müller C, Domokos B, Amersbach T, Hausmayer E-M, Roßmann C, Wallmann-Sperlich B and Bucksch J (2023) Development and reliability testing of an audit toolbox for the assessment of the physical activity friendliness of urban and rural environments in Germany. Front. Public Health 11:1153088. doi: 10.3389/fpubh.2023.1153088
Received: 28 January 2023; Accepted: 24 July 2023;
Published: 10 August 2023.
Edited by:
Debbie L. Humphries, Yale University, United StatesReviewed by:
Marija Jevtic, University of Novi Sad, SerbiaAlexa Ferdinands, University of Alberta, Canada
Jennifer Brown, University of Alberta, Edmonton, Canada, in collaboration with reviewer AF
Copyright © 2023 Müller, Domokos, Amersbach, Hausmayer, Roßmann, Wallmann-Sperlich and Bucksch. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Christina Müller, Y2hyaXN0aW5hLm11ZWxsZXImI3gwMDA0MDt1bmktd3VlcnpidXJnLmRl