Correspondence Between Perceived and Observed Measures of Neighborhood Environmental Supports for Physical Activity

Transcription

1 Journal of Physical Activity and Health 2006, 3, Human Kinetics, Inc. Correspondence Between Perceived and Observed Measures of Neighborhood Environmental Supports for Physical Activity Tegan K. Boehmer, Christine M. Hoehner, Kathleen W. Wyrwich, Laura K. Brennan Ramirez, and Ross C. Brownson Background: Neighborhood environmental supports for physical activity are assessed via telephone surveys (perceived) and environmental audits (observed), but the correspondence between methods is not known. Methods. Surveys (N = 1068) and audits were conducted concurrently in four diverse urban settings to measure recreational facilities, land use, transportation environment, and aesthetics. Agreement was assessed with kappa (κ) statistics. Results. Kappa values ranged from 0.06 to 0.47 for the 28 item-pairs: 17 item-pairs were classified as poor agreement (κ 0.20), 10 as fair (κ = ), and 1 as good (κ = 0.47). The highest agreement was observed for proximity to parks, trails, and various landuse destinations, presence of sidewalks, and measures of neighborhood maintenance and cleanliness. Conclusions. Methodological issues and/or the likelihood of capturing distinct aspects of the environment may explain the generally low correspondence between survey and audit measures. Our findings should help researchers make informed decisions regarding measurement of environmental supports for physical activity. Key Words: agreement, psychometrics, survey, audit, urban Public health researchers have become increasingly interested in the contextual effects of the community environment on health conditions such as physical inactivity and obesity. Identifying factors within the built environment that act as predictors of physical activity may assist in development of population-wide interventions and policies to sustain active lifestyles and thus slow escalating obesity rates. 1 The built environment refers to all human-formed or developed The authors are with Saint Louis University, St. Louis, MO Boehmer, Hoehner, Brennan Ramirez, and Brownson are with the university s Prevention Research Center and Dept of Community Health, School of Public Health. Wyrwich is with the Depts of Research Methodology and Health Services Research. 22

2 Neighborhood Environmental Supports for PA 23 areas within the physical environment, which is broadly categorized by size into macro (sectors common to the wider population) and micro (settings close to the individual). 2 Macroenvironmental influences of obesity and physical activity include urban sprawl, land-use mix, transportation systems, street networks, and population density. 3-5 Within microenvironmental neighborhood settings, access and proximity to facilities (e.g., bike paths, parks, shops), safe streets and paths, aesthetics, and presence of sidewalks may affect walking and bicycling behavior. 6, 7 Two approaches for measuring the micro-level neighborhood environment are telephone surveys and audit instruments. Evidence regarding the association between the environment and physical activity behavior is mostly derived from self-report data or individuals perceptions of their environment. 6, 8 Environmental audit tools, designed to systematically assess physical environmental conditions associated with walking and bicycling, are gaining in popularity within public health Current research indicates that both perceived and objectively measured environmental indicators are associated with physical activity behavior and obesity. 4-6, 8, It is unclear whether there is agreement between measurement methods or whether one method is more relevant for evaluating the suitability of neighborhood environments for physical activity. Survey and audit instruments with strong measurement properties are still in the early stages of development. We identified two studies from different settings that assessed validity of perceived environmental measures against objective data. 15, 16 Since psychometric properties are dependent upon characteristics of the population and environment under investigation, additional studies performed in other settings are crucial to understanding measurement of the environment and its association with physical activity behavior. This study was undertaken to assess the correspondence between telephone surveys and environmental audits in four environmentally and ethnically diverse urban settings. Since neither method is considered a gold standard for evaluating neighborhood environments, the focus here will be on assessing agreement, rather than validity, of these measures. The objectives were two-fold: 1) quantify the level of agreement between telephone survey (perceived) and environmental audit (observed) measures of neighborhood environments, and 2) determine whether agreement differs by respondent characteristics of obesity and physical activity. Methods Study Design A telephone survey and environmental audit were conducted concurrently among higher and lower income areas of St. Louis, Missouri (representing a low-walkable city) and Savannah, Georgia (representing a high-walkable city). Walkability of the two cities was determined by an expert panel representing public health, urban planning, and pedestrian/bicyclists advocates. The four study areas were selected to provide variability in the environmental measures and were matched on number of households, percentage of the population below poverty in 1999, and geographic size (Table 1). 12

3 24 Boehmer et al. Table 1 Study Area and Telephone Respondent Characteristics St. Louis, MO Savannah, GA Study area characteristics Total sample Lowerincome Higherincome Lowerincome Higherincome Number of census tracts Number of street segments Area (sq. miles) % population below poverty* Telephone respondent characteristics Number of respondents % Male % Non-Hispanic black % Some college education % Age group (y) Note. * weighted average by number of households per census tract Data Collection The telephone survey assessed individuals perceptions of five environmental domains (recreational facilities, land use, transportation environment, aesthetics, and social environment), plus demographic characteristics and physical activity behavior (assessed with the International Physical Activity Questionnaire). 17 Environmental items were derived from existing sources that have undergone reliability testing. 7, 16, Data were collected using a modification of the Behavioral Risk Factor Surveillance System sampling scheme and computer-assisted telephone interviewing techniques. 22 Between February and June 2003, 1073 adults in Savannah (n = 600) and St. Louis (n = 473) completed the telephone survey (response rate = 45%). An audit instrument was developed from existing tools to more objectively measure the same five environmental domains along neighborhood street-segments (the length of the road between two consecutive intersections). 11 Between March and May 2003, trained auditors systematically recorded location and attribute information of 1154 street-segments in Savannah (n = 679) and St. Louis (n = 475) using global positioning system technology. Further details regarding instru-

4 Neighborhood Environmental Supports for PA 25 ment development, data collection and cleaning procedures, and reliability testing 11, 12 of the audit tool are available. Geographic information systems (GIS) software (ArcView 8.3, ESRI, Redlands, CA) was used to link the survey and audit data and to summarize the streetsegment audit data within a 400-m radius, or buffer, surrounding each respondent s place of residence. 10 A 400-m distance is equivalent to about a quarter mile, or approximately a 5-min walk. The street-segment count data were summarized as totals (e.g., number of parks within buffer) and ordinal and nominal items were summarized as proportions (e.g., percent of street-segments with no attractive features). A summary measure of physical disorder was calculated for each street segment by adding the weighted responses of eight items (number of beer/liquor bottles or cans, cigarette/cigar butts or packages, condoms, drug-related paraphernalia, garbage, abandoned cars, graffiti, and broken windows, where none = 0, a few = 2, some = 5, and a lot = 9) and summarized within the buffer as the average physical disorder summary score. Measures Survey and audit items that appeared to measure the same component were considered an item-pair. The wording, response options, and categorization of the survey and audit measures are provided by domain in Tables 2 through 5. The social environment was not assessed because the survey and audit items were not comparable. Most environmental survey items had four-level ordinal response scales. The continuous audit measures, derived from summarizing the street-segment data within a 400-m buffer, were initially categorized into four levels to match the response distribution of their corresponding survey measures. Slight cut-off variations were considered to achieve meaningful categories and maximize agreement statistics. The survey and audit measures of sidewalks and bike lanes were dichotomized to reduce small cell size within survey response categories and to simplify interpretation. Survey respondents were also asked how many minutes would it take to walk from home to the nearest of five types of recreational facilities (e.g., park) and 13 types of land-use destinations (e.g., fast food restaurant). The other restaurant and coffee shop destinations were combined into a single item, as were all types of schools (e.g., elementary school, high school, and college), resulting in 11 destination types. Proximity to each recreational facility and destination was assessed dichotomously in both the survey (within 5-min walk) and audit (within 400-m buffer). Overall access measures were created by adding the number of recreational facility types (range, 0 to 5) and destination types (range, 0 to 11) within a 5-min walk or 400-m radius. Since survey respondents were asked about the facility or destination closest to their home, the overall access variables likely underestimate the actual number of facilities or destinations within a 5-min walk. Variables indicating the total number of recreational facilities (range, 0 to 17) and destinations (range, 0 to 131) were available from the audit only; both variables were categorized into four levels based on the distribution of their corresponding survey measures.

5 26 Boehmer et al. Analysis Agreement between survey and audit items was determined by the percent observed agreement and kappa (κ) statistic, which measures the proportion of observed agreement that occurs beyond chance. 23 A weighted kappa was used for ordinal measures to account for partial agreement among ordered categories. 24 The strength of agreement for each item-pair was classified according to the Landis and Koch criteria: poor (κ = 0 to 0.20), fair (κ = 0.21 to 0.40), good (κ = 0.41 to 0.60), substantial (κ = 0.61 to 0.80), or almost perfect (κ = 0.80 to 1.00). 25 Agreement was calculated for the total sample and by three stratification variables: 1) obese (body-mass index 30 kg/m 2, n = 211) versus non-obese (n = 830); 2) recommended physical activity through transportation (walking or bicycling 5 d/wk for at least 30 min/d, n = 182) versus below recommendation (n = 684); and 3) recommended physical activity through leisure-time (walking or moderate activity 5 d/wk for at least 30 min/d or vigorous activity 3 d/wk for at least 20 consecutive min/d, n = 346) versus below recommendation (n = 720). 26 Differences between strata were determined by non-overlapping 95% confidence intervals. Results The final sample consisted of 1068 respondents. Five were excluded whose addresses were invalid or outside the study area. The sample was 34% male, 33% non-hispanic black, and 66% college educated; differences were observed across study areas (Table 1). Measures of agreement were calculated for 28 item-pairs within the environmental domains of recreational facilities, land use, transportation environment, and aesthetics (Tables 2 through 5). Recreational Facilities Percent agreement was relatively high (69 to 82%) for proximity to recreational facilities; however, kappa statistics for these four item-pairs (κ = 0.08 to 0.39) indicated poor agreement for the outdoor pool and fitness center items and fair agreement for the park and trail items (Table 2). Using a 10-min walk cut-off while retaining the 400-m buffer did not improve agreement between measures (κ = 0.08 to 0.24, data not shown). Correspondence was poor (κ = 0.10) for overall access to recreational facilities (four facilities mentioned above plus public recreation centers). Survey items assessing general perceptions of many facilities and equipment available were both paired with the total number of recreational facilities audit measure. Weighted kappa statistics for both item-pairs were negative, indicating no agreement beyond that due to chance. Land Use All 11 proximity to destinations item-pairs had greater than 50% observed agreement, with 5 item-pairs above 75% (Table 3). Kappa statistics revealed poor agreement (κ = 0.12 to 0.16) for 6 destinations (convenience/small grocery store, other restaurant/coffee shop, laundry/dry cleaners, library, place of worship, and schools), fair agreement (κ = 0.21 to 0.38) for 4 destinations (fast food restaurant,

6 Neighborhood Environmental Supports for PA 27 Table 2 Agreement Between Perceived (Survey) and Observed (Audit) Indicators of Recreational Facilities Survey measure Audit measure Agreement Item-pair Category n Category n % Kappa Proximity to recreational facilities Recreational facility within 5-min walk Recreational facility within 400-meter buffer Park 592 Park Trail for walking or biking 307 Trail or path Private indoor fitness center 60 Indoor fitness facility Public swimming pool 119 Outdoor pool Access to recreational facilities Many facilities Equipment available Number of recreational facility types within 5-min walk Number of recreational facility types within 400-meter buffer There are many places to be physically active in my community, not including streets for walking or jogging Total number of recreational facilities within 400-meter buffer Strongly agree Agree Disagree Strongly disagree There is equipment available for physical activity in my community Total number of recreational facilities within 400-meter buffer Strongly agree Agree Disagree Strongly disagree

7 28 Boehmer et al. Table 3 Agreement Between Perceived (Survey) and Observed (Audit) Indicators of Land Use Item-pair Proximity to destinations Access to destinations Many destinations Survey measure Audit measure Agreement Category n Category n % Kappa Destination within 5-min walk Destination within 400-meter buffer Fast food restaurant 213 Fast food restaurant Other restaurant/ coffee shop 308 Other restaurant/ coffee shop Convenience/small grocery store 467 Convenience/small grocery store Supermarket 122 Supermarket Bank/credit union 138 Bank/credit union Pharmacy/drug store 147 Pharmacy/drug store Laundry/dry cleaners 215 Laundry/dry cleaners Post office 43 Post office Library 66 Library Place of worship 540 Place of worship School/college/ School/college/ university 495 university Number of destination types within 5-min walk Number of destination types within 400-meter buffer There are many destinations to go within easy walking distance from my home Total number of destinations within 400-meter buffer Strongly agree 440 > Agree Disagree Strongly disagree

8 Neighborhood Environmental Supports for PA 29 Table 4 Agreement Between Perceived (Survey) and Observed (Audit) Indicators of Transportation Environment Item-pair Sidewalks Bike lanes Public transit Survey measure Audit measure Agreement Category n Category n % Kappa There are sidewalks present on most streets in my community Strongly agree/ agree Strongly disagree/ disagree There are bike lanes present on most streets in my community Strongly agree/ agree Strongly disagree/ disagree It is easy to walk to a bus stop, train or subway station from my home 60% or more of segments have sidewalks on one or both sides of the street 1000 Yes No 43 Bike lane observed on any segment within buffer 303 Yes No 678 % of segments with bus or other transit stop Strongly agree % Agree % 555 Disagree % 32 Strongly disagree 23 0% 39

9 30 Boehmer et al. Table 5 Agreement Between Perceived (Survey) and Observed (Audit) Indicators of Aesthetics Survey measure Audit measure Agreement Item-pair Category n Category n % Kappa Maintenance My neighborhood is well maintained Average physical disorder summary score Strongly agree 409 < Agree Disagree Strongly disagree Cleanliness My neighborhood is generally free from garbage, litter, or broken glass % of segments with none or a little garbage, litter, or broken glass Strongly agree % Agree % 401 Disagree % 207 Strongly disagree % 57 Pleasantness How would you rate your neighborhood as a place to be physically active? % of segments with no attractive features Very pleasant % Somewhat pleasant % 265 Not very pleasant % 117 Not at all pleasant 72 > 80% 17 Sights There are many interesting things to look at while walking in my neighborhood % of segments with no attractive features Strongly agree % Agree % 267 Disagree % 116 Strongly disagree 82 > 80% 17

10 Neighborhood Environmental Supports for PA 31 Table 5 Agreement Between Perceived (Survey) and Observed (Audit) Indicators of Aesthetics (continued) Item-pair Trees Survey measure Audit measure Agreement Category n Category n % Kappa There are trees along the streets in my neighborhood % of segments with no comfort features Strongly agree % Agree % 123 Disagree % 79 Strongly disagree 19 > 80% 33 bank/credit union, pharmacy/drug store, and post office), and good agreement (κ = 0.47) for supermarket. Weighted kappa statistics for overall access to destinations (κ = 0.11) and many destinations (κ = 0.05) indicated poor agreement between survey and audit measures. Transportation Environment Maximum agreement for the sidewalk item-pair (κ = 0.33) was achieved at a 60% cut-off value for the audit item (Table 4). There was poor agreement (κ = 0.17) between bike lane measures. Although survey and audit measures of public transit were fairly comparable, the weighted kappa was extremely low (κ = 0.04) indicating the possibility of no agreement beyond chance. Aesthetics Fair agreement was observed for maintenance (κ = 0.39) and cleanliness (κ = 0.30) item-pairs (Table 5). The pleasantness and sights survey measures were both paired with the attractive features audit item (i.e., presence of architectural design, building variety, vegetation, signage, or open space). The trees survey item was compared with comfort features audit item (i.e., presence of shade trees, benches, or other types of amenities). Using the same classification for the attractive and comfort features items, the kappa statistics for pleasantness, sights, and trees item-pairs wavered around 0.20 (poor to fair agreement). Stratified Analysis In the stratified analysis, only two significant between-strata differences (i.e., non-overlapping 95% CIs) were observed out of 84 comparisons (28 item-pairs 3); fewer than the number expected by chance. Without regard to statistical significance, the stratified analysis revealed a few patterns of differing agreement by obesity, transportation activity, and leisure-time activity. Non-obese persons and those with recommended activity through leisure or transportation appeared to have

11 32 Boehmer et al. higher agreement for proximity to a park, but not other recreational facility types. Contrary to expectations, obese persons had somewhat higher agreement on public transit and bike lane item-pairs and persons with recommended leisure-time activity had lower agreement for sidewalk and bike lane item-pairs. Lastly, persons with recommended transportation activity had slightly higher agreement for aesthetics measures of pleasantness and sights. The magnitude of between-strata differences was 0.1 to 0.2 for the abovementioned examples. Discussion Our study found generally low agreement between perceived and observed measures of the urban neighborhood environment, as assessed by a telephone survey and environmental audit. Kappa values for the 28 item-pairs ranged from 0.06 to 0.47: 2 item-pairs had no agreement (negative kappa), 15 item-pairs had poor agreement (κ = 0 to 0.20), 10 item-pairs had fair agreement (κ = 0.21 to 0.40), and 1 item-pair had good agreement (κ = 0.41 to 0.60). 25 The level of agreement did not differ systematically by individual characteristics of obesity status or physical activity level. Our findings are mostly consistent with two similar studies in different settings. 15, 16 In South Carolina, Kirtland et al. observed poor to fair agreement (κ = 0.02 to 0.37) for 26 perceived neighborhood- and community-level environmental support variables compared to established databases, global positioning system units, telephone interviews, and in-person audits. 16 Using a half-mile neighborhood buffer produced substantially higher agreement than using a 10-mile community buffer. 16 The current study found agreement was not improved using a smaller quarter-mile neighborhood buffer. In a smaller Boston suburb study, Troped et al. reported moderate agreement between self-reported and GIS measures of steep hill (κ = 0.41) and busy street (κ = 0.59) barriers. 15 Agreement may be slightly higher in the latter study because respondents were asked specifically about the route from their home to a particular trail. 15 In our study, three of the five item-pairs with the most promising agreement were dichotomous measures of proximity to parks and trails and presence of sidewalks. Kirtland et al. also found that access to sidewalks and public recreation facilities performed better than other environmental support items. 16 In the landuse domain, the destination types with the highest agreement (e.g., supermarket, pharmacy, post office, and bank) were locations that are generally more familiar, more commonly used, and easier to define. Likewise, Troped et al. concluded that busy street performed better than steep hill because it was easier to define and less subjective. 15 In the aesthetics domain, fair agreement was observed for measures of neighborhood maintenance and cleanliness. These item-pairs may have performed slightly better than others in the aesthetics domain because the corresponding audit measures (i.e., physical disorder summary score and garbage, litter, or broken glass ) were previously found to have substantial inter-rater reliability (κ = 0.73 and 0.76, respectively); whereas attractive and comfort features had low reliability (κ = 0.19 and 0.26, respectively). 11 On the other hand, poor reliability does not explain the low agreement observed in the other domains since all remaining audit items

12 Neighborhood Environmental Supports for PA 33 had substantial or almost perfect inter-rater reliability 11 and most survey items had moderate or substantial test-retest reliability. 21 Methodological Considerations The generally low correspondence between survey and audit measures may result from methodological issues that represent key challenges in our study and the research field in general. First, characteristics of the study area may have resulted in lower kappa statistics due to the high prevalence of some features in urban settings (e.g., sidewalks). Items with little variation generate high amounts of chance agreement, resulting in kappa statistics that may under-estimate the true level of agreement. Also, the categorization of the audit data was based on the distribution of survey responses in our study and may not be applicable in different settings. Second, the usefulness of measurement tools depends upon the clarity and specificity of items. Abstract words such as many, most, and easy necessitate individual interpretation (e.g. It is easy to walk to a bus stop ). Seemingly simple terms such as park or bike lane may be misunderstood if not clearly defined. The objectivity of a few audit items measuring aesthetic quality through attractive and comfort features was questionable. Lastly, the ability to accurately recall how long it takes to walk from home to the nearest recreational facility or destination is dependent upon individual characteristics and activity levels. Inconsistent geographical scope and terminology may also explain low correspondence in some instances. In the telephone survey, aesthetics items referenced respondents neighborhood (defined as streets within a 5-min walk), whereas items from other domains referenced their community (defined as neighborhoods within a 10-min walk). Nevertheless, all audit measures were summarized within a 400-m buffer, corresponding to the survey definition of neighborhood. Similarly, slight wording differences may have reduced agreement between some item-pairs (e.g., private fitness center vs. indoor fitness facility). Lastly, using researcher-defined areas (or buffers) to summarize neighborhood environments has some limitations. First, individuals perceptions of their neighborhood may not be bound by the area within 400 m from their home. It is important to examine other methods for aggregating street-level data that take into account individual perceptions of neighborhood boundaries. Second, audits were performed only within the study area boundaries resulting in missing environmental data for respondents whose buffers extended beyond the audited street segments. The degree to which this study limitation affects agreement varies by type of measure, with sum or count measures being more highly affected than averages and proportions. Distinct Constructs Notwithstanding the methodological issues discussed above, lack of agreement between survey and audit data may reflect true differences in the constructs being measured. Sociological research on neighborhood evaluation suggests that personal perceptions of the neighborhood or community environment are only indirectly linked to objective characteristics. 27 That is, individual perceptions are derived from filtering objective characteristics through standards of evaluation, which are based on past experiences, aspiration levels, adaptation processes, and

13 34 Boehmer et al. individual personality characteristics. 27 Thus, the existence of unique situational and personality characteristics indicates that two individuals in the same environment may perceive it differently. Preliminary evidence suggests that perceived and observed environmental measures may vary in their correlation with physical activity behavior, 12, 15 supporting the idea that perceived and observed indicators capture different constructs of the neighborhood environment. Conclusions The findings from this study underscore the complexities associated with measuring environmental supports for physical activity and understanding the mechanisms through which the environment influences behavior. Additional studies that incorporate both perceived and observed measures of the neighborhood environment and assess their association with physical activity behavior are recommended. Specifically, future research should 1) qualitatively assess how individuals perceive and define their neighborhood environment, 2) determine whether reliable and valid objective measures exist for safety and the social environment, and 3) use complementary methods of gathering objective data (e.g., existing databases, GIS data, or aerial photography). In addition, studies similar to this one should be replicated in settings of various urbanization levels and natural terrains. The lack of correspondence between perceived and observed environmental measures has several practical implications for researchers and practitioners. Environmental interventions that aim to improve activity-friendliness of neighborhoods may not result in desired behavior changes if individuals perceptions differ from the reality of their environment and if these perceptions inhibit activity. Although we recommend the collection of both survey and audit data, the cost may be prohibitive. In this study, the telephone survey cost approximately $21,000 in recurring expenses (plus $4,500 in incentives) and the environmental audit cost approximately $41,000 ($25,000 recurring expenses and $16,000 fixed costs). If non-concordance between perceived and observed measures is confirmed in future studies, researchers may choose whether to evaluate perception or observation of the environment based upon which is more likely to affect behavior, more amenable to change, and more cost efficient. The findings from this study will help researchers make informed decisions regarding measurement of environmental supports for physical activity. Acknowledgments This study was funded through The Robert Wood Johnson Foundation (#046480), including support from the Centers for Disease Control and Prevention (U48/CCU710806, Prevention Research Centers Program). Dr. Wyrwich s work is supported by an Independent Scientist Award from the Agency for Healthcare Research and Quality (K02 HS-11635). The authors are grateful for the contributions of Michael Elliot, Ph.D., Rebeka Cook, Montenia Anderson, Cheryl Kelly, and Brandi Meriwether (Saint Louis University Prevention Research Center) and the support of C. Tracy Orleans and Marla Hollander (The Robert Wood Johnson Foundation).

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