Saint Louis Environment and Physical Activity Instrument

Dr. Mohammed Looti An academic and researcher specialized in
PUBLISHED
Scientifically Reviewed · Dr. Marwa Abd-Alazim · October 1, 2026
Medically & Scientifically Reviewed Verified: October 1, 2026
Dr. Marwa Abd-Alazim PhD in Psychology
Faculty Member • University of Kerbala
Review Criteria & Clinical Standards

This content undergoes rigorous scientific peer-review and medical editorial standards at Arab Psychology Network to ensure clinical accuracy, validity, and compliance with evidence-based guidelines from leading psychological and healthcare authorities (APA / WHO).

CC BY-NC-ND 4.0

1. Abstract

The Saint Louis Environment and Physical Activity Instrument is a specialized, multi-dimensional self-report and interview-based survey protocol designed to measure perceived environmental influences, neighborhood infrastructure, social resources, and behavioral patterns associated with physical activity and sedentary behaviors. Developed by public health researchers Ross C. Brownson, Jen Jen Chang, and Amy A. Eyler at the Prevention Research Center at Saint Louis University, this instrument was established to bridge the empirical gap between social-ecological behavioral theories and empirical community-based epidemiology. The instrument comprehensively assesses ten primary domains: walking behavior, destinations and places to walk, physical and structural barriers to activity, neighborhood infrastructure for walking and cycling, cognitive appraisals and perceptions of walking environments, social assets and social capital, interpersonal social support, community-level physical assets, civic and policy attitudes, and domain-specific sedentary behaviors.

Across urban, suburban, and rural testing cohorts, the instrument utilizes a mixed-format scoring architecture comprising Likert-type scales, dichotomous item sets, categorical frequency estimates, and environmental rating indices. Psychometric investigations into the tool have demonstrated robust test-retest reliability, with Cohen’s kappa (κ) and intraclass correlation coefficients (ICC) ranging from moderate to substantial (coefficients typically between .50 and .85) for physical infrastructure, walking destinations, and personal behaviors. Construct, convergent, and criterion validities have been established through cross-validation with objective geographic information systems (GIS) data, physical environmental audits, and objective accelerometry. The Saint Louis Environment and Physical Activity Instrument serves as an essential methodological foundation for environmental health researchers, urban planners, behavioral psychologists, and epidemiologists seeking to understand how the macro- and micro-level features of human habitats facilitate or inhibit physical movement.

2. Keywords

Saint Louis Environment and Physical Activity Instrument, built environment, physical activity, neighborhood walkability, social-ecological model, environmental audit, social capital, walking behavior, sedentary lifestyle, active transport, psychometrics, public health surveillance.

3. Authors

The Saint Louis Environment and Physical Activity Instrument was created by a collaborative team of epidemiologists, behavioral scientists, and public health scholars associated with the Prevention Research Center at Saint Louis University School of Public Health and the Brown School at Washington University in St. Louis:

  • Ross C. Brownson, Ph.D. — Lipstein Distinguished Professor of Public Health at Washington University in St. Louis (formerly with the Department of Community Health and Prevention Research Center, Saint Louis University School of Public Health). Renowned for seminal contributions to evidence-based public health, environmental interventions for physical activity, and chronic disease prevention.
  • Jen Jen Chang, Ph.D., MPH — Professor of Epidemiology, Department of Epidemiology and Biostatistics, College for Public Health and Social Justice, Saint Louis University. Specialist in epidemiological methodology, maternal-child health, and neighborhood contextual effects on health behaviors.
  • Amy A. Eyler, Ph.D. — Professor of Public Health at the Brown School, Washington University in St. Louis. Leading expert on physical activity policy, community-level environmental measurement, and active living dynamics among diverse populations.

Institutional affiliations and inquiries regarding research implementation are typically directed through the Prevention Research Center at Washington University in St. Louis and Saint Louis University.

4. Purpose

Sedentary lifestyle choices represent one of the leading global drivers of non-communicable illnesses, including cardiovascular disease, type 2 diabetes, metabolic syndrome, and various forms of cancer. Historically, behavioral medicine operationalized physical activity primarily through intra-individual psychological paradigms, concentrating on willpower, self-efficacy, and personal motivation. However, the late 1990s and early 2000s catalyzed an epidemiological paradigm shift recognizing that individual decision-making is severely constrained or enabled by the built, natural, and social environments.

The primary clinical, epidemiological, and urban design purpose of the Saint Louis Environment and Physical Activity Instrument is to measure perceived environmental influences, environmental barriers, and structural features that correlate with utilitarian walking, recreational exercise, and sedentary habits. The instrument was intentionally engineered to address the following empirical needs:

  • Public Health Surveillance: Providing municipal and national surveillance systems with a standardized battery to track how citizens perceive their physical habitats over time.
  • Etiological Research: Disentangling the relative contributions of objective environmental geography (e.g., GIS metrics) versus psychological perceptions (cognitive representations of neighborhood safety, aesthetics, and convenience) in predicting daily physical movement.
  • Intervention Planning and Evaluation: Providing public health departments, municipal leaders, and civil engineers with diagnostic community feedback to guide infrastructural investments, such as installing sidewalks, enhancing street lighting, engineering traffic calming devices, or revamping public parks.
  • Policy Evaluation: Capturing public perceptions of municipal, legislative, and zoning policies that either promote or discourage active transport and community recreation.

By measuring the built environment from the resident’s subjective phenomenological vantage point, the scale provides a critical link between geographic reality and psychological behavior, explaining why two individuals living in the same geographic block may exhibit radically different walking practices based on perceived safety, aesthetic appeal, and social trust.

5. Psychological Construct

The Saint Louis Environment and Physical Activity Instrument operationalizes an expansive, multi-tiered psychological construct known as perceived environmental support for physical activity, integrated with behavioral manifestations of movement and inactivity. Perception acts as a cognitive filter: an objective sidewalk does not stimulate walking behavior if an individual perceives it to be dangerously cracked, poorly lit, or controlled by hostile elements. The instrument measures several interrelated sub-constructs:

5.1. Walking Behaviors and Functional Destinations

This dimension quantifies both the volume of walking (duration, frequency) and its contextual distribution across purposive subcategories, differentiating between utilitarian walking (walking to grocery stores, transit stops, schools, or workplaces) and recreational walking (walking for leisure, exercise, or pet care). It also records the perceived presence and spatial proximity of local walking destinations (e.g., retail centers, libraries, parks, recreational hubs).

5.2. Physical and Structural Environmental Infrastructure

This sub-construct appraises the tangible infrastructure that supports or hinders non-motorized mobility. It examines the availability, continuity, and structural maintenance of sidewalks; the presence of bicycle lanes; crosswalk visibility; connectivity of street layouts; and the presence of physical buffers separating pedestrians from vehicular traffic.

5.3. Cognitive Environmental Perceptions (Aesthetics, Safety, and Quality)

This dimension measures an individual’s psychological evaluations of their immediate geographic surroundings. It comprises several cognitive indicators:

  • Aesthetic Appeal: The presence of natural features, shade trees, architectural variety, and cleanliness versus urban decay, trash, and graffiti.
  • Traffic Safety: Perceived volume and speed of motorized traffic, driver courtesy, and ease of street crossing.
  • Crime and Personal Safety: Perceived risk of physical victimization, fear of crime during day versus night hours, unleashed dogs, and signs of illicit activity.

5.4. Social Assets and Interpersonal Support

In accordance with sociological and psychological theory, physical movement occurs within a social milieu. This construct evaluates the availability of social support (e.g., encouragement from family, friends, or coworkers to be active; having a walking partner) and broad social capital (e.g., neighborhood trust, reciprocal assistance among neighbors, informal social control, and collective efficacy).

5.5. Community Assets and Policy Attitudes

This facet assesses residents’ knowledge of public resources (e.g., public swimming pools, community centers, walking tracks, school facilities opened after hours) and their political support for regulatory actions or local public funding earmarked for pedestrian infrastructure, complete streets, and active living policies.

5.6. Sedentary Behaviors

Recognizing that physical inactivity is not merely the absence of physical activity, this dimension examines independent sedentary behaviors, such as daily television viewing, non-work screen time, long commutes in motorized vehicles, and recreational sitting patterns.

6. Theoretical Framework

The Saint Louis Environment and Physical Activity Instrument is grounded in ecological frameworks of human behavior, primarily the Social-Ecological Model (SEM) as formulated by Urie Bronfenbrenner and adapted for active living by behavioral scientists such as James F. Sallis, Neville Owen, and Kenneth R. McLeroy. The fundamental premise of the social-ecological paradigm posits that health behaviors are governed by dynamic, recursive interactions across multiple nested spheres of influence: intrapersonal, interpersonal, institutional, environmental, and public policy.

Within this model, individual-level factors (such as personal intentions or attitudes, as described in the Theory of Planned Behavior by Icek Ajzen) are recognized as necessary but insufficient explanatory mechanisms for long-term lifestyle habits. An individual with high motivation to walk will remain largely inactive if their physical environment is hostile, lacking connected pathways, devoid of destinations, or characterized by severe safety threats. Conversely, a supportive built environment can facilitate active living even among individuals with low initial intrinsic motivation by embedding non-motorized movement naturally into their daily utilitarian routines.

The scale also incorporates concepts from Social Cognitive Theory (SCT), established by Albert Bandura, particularly the principle of reciprocal determinism. This principle dictates that cognitive events, personal biological features, human behavior, and external physical environments continually exert mutual influence on one another. The Saint Louis instrument operationalizes this interaction by examining how perceived barriers, social encouragement from peers, and environmental opportunities alter self-efficacy and behavioral outcome expectations. When community members encounter attractive, safe, and proximate recreational facilities, their outcome expectations become more favorable, increasing their sense of agency to integrate walking into their weekly lives.

Finally, the instrument draws on sociological theories of Collective Efficacy and Social Capital (Robert Putnam; Robert J. Sampson). Neighborhoods exhibiting high social cohesion and shared behavioral norms generate an environment where residents feel safe walking outdoors because neighbors exercise informal social surveillance, looking out for one another and intervening against disruptive or predatory behaviors.

7. Validity

The validity of the Saint Louis Environment and Physical Activity Instrument has been systematically examined through multiple empirical approaches, establishing content, construct, convergent, discriminant, and criterion-related validity.

7.1. Content and Face Validity

The instrument’s content validity was developed through rigorous iterative reviews conducted by multidisciplinary expert panels comprising chronic disease epidemiologists, behavioral medicine specialists, urban design scholars, transportation planners, and community health organizers. Items were systematically evaluated to confirm that they comprehensively represented the critical operational features of both utilitarian and recreational walking, pedestrian infrastructure, local zoning patterns, social environments, and personal activity restrictions.

7.2. Construct and Convergent Validity

Construct validity has been supported by demonstrating expected theoretical associations between perceived environmental variables and actual behavioral outcomes. When respondents report higher scores on neighborhood infrastructure (such as well-maintained, continuous sidewalks and bicycle trails), high destination accessibility, and favorable environmental aesthetics, they simultaneously report significantly higher rates of meeting national physical activity guidelines (≥150 minutes of moderate-to-vigorous physical activity per week). Conversely, elevated scores on perceived structural barriers (e.g., absence of street crosswalks, heavy commercial traffic, loose animals, poor night lighting) correlate with elevated sedentary behavior and low walking volumes.

Convergent validity was further established by contrasting the self-report responses with validated criterion measurement methodologies. In validation studies, self-reported walking durations were compared against data captured via waist-worn research-grade accelerometers (such as ActiGraph units) and pedometers. Significant positive correlations (Pearson’s r and Spearman’s rho typically ranging from .30 to .55, p < .001) were documented between perceived environmental walkability scales and objectively logged physical activity minutes.

7.3. Criterion and Discriminant Validity

Criterion-related validity was evaluated by comparing participants’ subjective environmental ratings against objective environmental metrics obtained through geographic information systems (GIS) and trained field auditor assessments using street-level audit tools (e.g., the Analytic Audit Tool and Active Neighborhood Checklist). Findings indicated moderate-to-strong concordance between subjective perceptions of destinations (e.g., distance to nearest park, presence of commercial retail) and objective GIS buffering distances (Euclidean and network network distances).

Discriminant validity was established by demonstrating that general environmental walkability scales do not show spurious correlations with unrelated constructs, such as general non-exercise-related health anxieties or unrelated political attitudes, verifying that the subscales measure specific environmental and behavioral domains rather than generalized response biases.

8. Reliability

The reliability of the Saint Louis Environment and Physical Activity Instrument has been evaluated via internal consistency analysis and extensive test-retest reliability designs across distinct urban, suburban, and rural population groups.

8.1. Test-Retest Reliability

Given that physical environments remain relatively stable across short temporal windows, test-retest reliability serves as a key psychometric metric for this instrument. In methodological studies involving re-administration intervals ranging from 7 to 21 days, stability coefficients were derived using Cohen’s kappa (κ) for dichotomous/categorical items and Intraclass Correlation Coefficients (ICC) or Spearman rank correlations for continuous and ordinal indices:

  • Physical Infrastructure Items: Items documenting the presence of sidewalks, bicycle lanes, and recreational facilities consistently exhibited substantial test-retest agreement, with kappa values typically ranging from .65 to .88.
  • Destinations and Places to Walk: Categorical items assessing the existence of commercial stores, libraries, schools, and transit stops near the home yielded kappa values between .60 and .82.
  • Cognitive and Aesthetic Perceptions: Variables capturing subjective ratings of neighborhood pleasantness, aesthetic appeal, and perceived crime exhibited moderate-to-substantial stability, with ICCs clustering between .52 and .75. This reflects expected minor temporal fluctuations in perceived safety influenced by daily events or changing weather conditions.
  • Behavioral Walking and Sedentary Metrics: Retest reliability for frequency and duration of walking behavior showed ICCs ranging from .58 to .78, aligning with the standards observed across established self-report surveillance measures (such as the International Physical Activity Questionnaire).

8.2. Internal Consistency

For homogeneous multi-item subscales measuring single latent attributes (e.g., social cohesion, neighborhood aesthetics, or structural walking barriers), Cronbach’s alpha (α) coefficients have generally demonstrated acceptable-to-strong internal consistency, ranging from .70 to .86. Subscales intentionally capturing heterogeneous checklist inventories (such as the checklist of diverse community physical assets or physical barriers) exhibit lower raw alpha figures; this is psychometrically expected, as having a steep hill near one’s residence is independent of whether high-speed traffic is also present.

9. Factor Analysis

The structural dimensionality of the Saint Louis Environment and Physical Activity Instrument has been verified using both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA), clarifying the underlying cognitive and structural dimensions that drive survey responses.

9.1. Exploratory Factor Analysis (EFA)

During initial scale development and psychometric refinement, principal component and common factor analyses with orthogonal (Varimax) and oblique (Promax) rotations were performed on large sets of perceptual environmental items. These analyses revealed distinct factor clustering that aligned with the conceptual domains of the Social-Ecological Model. The primary factors that emerged included:

  • Factor 1: Pedestrian and Cyclist Infrastructure — Marked by high positive factor loadings (> .60) for sidewalk presence, sidewalk maintenance, street lighting, and dedicated bike pathways.
  • Factor 2: Land Use Diversity and Destination Proximity — Dominated by items measuring accessibility to retail services, parks, transit stops, and civic buildings.
  • Factor 3: Neighborhood Safety and Social Vulnerability — Characterized by strong loadings on items related to perceived crime, fear of walking alone at night, perceived presence of unattended dogs, and traffic speed hazards.
  • Factor 4: Aesthetic and Environmental Attractiveness — Grouping variables concerning green canopy/shade trees, architectural beauty, cleanliness, and absence of physical litter.
  • Factor 5: Social Capital and Cohesion — Combining variables related to trusting neighbors, mutual aid, and observing other active community members outdoors.

9.2. Confirmatory Factor Analysis (CFA)

Subsequent confirmatory studies tested whether the multi-factor structural model fit observed population data across demographic strata (such as rural vs. urban cohorts). CFA models demonstrated satisfactory overall goodness-of-fit indices:

  • Comparative Fit Index (CFI): Values consistently met or exceeded the .90 to .94 threshold, indicating adequate model fit.
  • Root Mean Square Error of Approximation (RMSEA): Point estimates generally fell below .06 (with 90% confidence intervals bounded between .04 and .07), reflecting reasonable approximation error.
  • Standardized Root Mean Square Residual (SRMR): Values were routinely below .08.

Factorial invariance testing demonstrated that the underlying factor patterns retain structural equivalence across varying population sub-samples, though the baseline mean levels of infrastructure accessibility and perceived safety differed systematically between urban and rural environments.

10. Instrument / Measurement Tool

The Saint Louis Environment and Physical Activity Instrument is structured as a comprehensive survey protocol that can be deployed as an in-person interview, computer-assisted telephone interview (CATI), or self-administered digital/paper questionnaire. Below is the detailed structural overview of the instrument’s components, response formats, and scoring architecture:

  • Administration Type: Self-administered (paper or online survey) or interviewer-administered (in-person or telephone surveillance).
  • Target Population: Adults aged 18 years and older residing in urban, suburban, small-town, or rural communities.
  • Estimated Completion Time: 15 to 25 minutes, depending on whether optional community and policy attitude modules are administered.
  • Item Count & Structure: The full core assessment typically comprises approximately 60 to 75 questions distributed across key thematic modules:
  • Modular Architecture:
    • Module A: Personal Physical and Walking Activity: Quantifies frequency (days per week) and average duration (minutes per day) of walking, categorized into utilitarian walking and recreational/leisure walking.
    • Module B: Places for Walking / Destinations: Evaluates proximity to destinations (e.g., within 5, 10, 15, or >20 minutes walking distance).
    • Module C: Neighborhood Physical Infrastructure: Assesses sidewalks, bike lanes, trail connectivity, and street crosswalks.
    • Module D: Perceptions of the Neighborhood Environment: Likert-scale evaluations of aesthetics, neighborhood safety, crime risk, lighting, and traffic hazards.
    • Module E: Structural and Personal Barriers: Checklist format assessing factors that prevent or reduce activity (e.g., bad weather, hills, lack of time, lack of facilities, personal health issues).
    • Module F: Social Environment and Capital: Likert items assessing interpersonal social support (family/friend encouragement) and neighborhood collective efficacy/trust.
    • Module G: Community Assets and Civic Policy Attitudes: Identification of available public recreation resources and personal endorsement of local active living policies.
    • Module H: Sedentary Behaviors: Continuous estimates of hours and minutes spent daily in sitting, television viewing, screen use, and vehicle commuting.
  • Response Scales:
    • 4-point or 5-point Likert scales (e.g., 1 = Strongly Disagree to 4 or 5 = Strongly Agree).
    • Dichotomous indices (e.g., Yes = 1, No = 0, or Don’t Know).
    • Categorical walk-time distance groupings (e.g., 1–5 min, 6–10 min, 11–20 min, 21–30 min, >30 min, or Not Accessible).
    • Continuous numerical responses (e.g., number of days/week, minutes/day spent in activity or sitting).
  • Scoring and Indexing Procedures:
    • Domain-Specific Summary Scores: Items within aesthetic, safety, and infrastructure modules can be summed or averaged to create continuous composite index scores (e.g., Neighborhood Aesthetic Score, Neighborhood Safety Index). Negative items (e.g., high crime, heavy traffic) are reverse-coded prior to index compilation.
    • Destination Walkability Index: Calculated as a cumulative sum of destinations reachable within a 10- or 15-minute walk from home.
    • Total Physical Activity Computation: Walking minutes are multiplied by weekly frequency to derive total weekly walking MET-minutes or categorical classification (e.g., Highly Active, Moderately Active, Inactive) benchmarked against CDC/WHO physical activity guidelines.

11. Permissions & Fee and Test Year

The Saint Louis Environment and Physical Activity Instrument was developed between 2001 and 2004 under public research funding from the Centers for Disease Control and Prevention (CDC) through the Prevention Research Centers Program (Cooperative Agreement U48/CCU710806) awarded to Saint Louis University. As a federally funded academic assessment tool, it resides in the public domain for academic, clinical, research, and non-commercial municipal planning purposes.

There are no licensing fees, copyright royalties, or purchase costs required to use or adapt the questionnaire. However, researchers and public health organizations utilizing the instrument are expected to cite the original authors and their foundational methodology papers in any resulting scientific publications, presentations, or technical reports. Commercial entities seeking to integrate the instrument into proprietary corporate wellness technologies or monetized digital platforms should contact the original authors at Washington University in St. Louis and Saint Louis University for institutional approval.

12. References

Brownson, R. C., Baker, E. A., Housemann, R. A., Brennan, L. K., & Bacak, S. J. (2001). Environmental and policy determinants of physical activity in the United States. American Journal of Public Health, 91(12), 1995–2003. https://doi.org/10.2105/ajph.91.12.1995

Brownson, R. C., Chang, J. J., Eyler, A. A., Ainsworth, B. E., Kirtland, K. A., Saelens, B. E., & Sallis, J. F. (2004). Measuring the environment for friendliness toward physical activity: A comparison of the reliability of 3 questionnaires. American Journal of Public Health, 94(3), 473–483. https://doi.org/10.2105/ajph.94.3.473

Brownson, R. C., Hoehner, C. M., Day, K., Forsyth, A., & Sallis, J. F. (2009). Measuring the built environment for physical activity: State of the science. American Journal of Preventive Medicine, 36(4 Suppl), S99–S123. https://doi.org/10.1016/j.amepre.2009.01.005

Craig, C. L., Marshall, A. L., Sjöström, M., Bauman, A. E., Booth, M. L., Ainsworth, B. E., Pratt, M., Ekelund, U., Yngve, A., Sallis, J. F., & Oja, P. (2003). International Physical Activity Questionnaire: 12-country reliability and validity. Medicine & Science in Sports & Exercise, 35(8), 1381–1395. https://doi.org/10.1249/01.MSS.0000078924.61453.FB

Eyler, A. A., Brownson, R. C., Bacak, S. J., & Housemann, R. A. (2003). The epidemiology of walking for physical activity in the United States. Medicine & Science in Sports & Exercise, 35(9), 1529–1536. https://doi.org/10.1249/01.MSS.0000084524.13781.E1

Giles-Corti, B., & Donovan, R. J. (2002). The relative influence of individual, social and physical environmental determinants of physical activity. Social Science & Medicine, 54(12), 1793–1812. https://doi.org/10.1016/S0277-9536(01)00150-2

Sallis, J. F., Cervero, R. B., Ascher, W., Henderson, K. A., Kraft, M. K., & Kerr, J. (2006). An ecological approach to creating active living communities. Annual Review of Public Health, 27(1), 297–322. https://doi.org/10.1146/annurev.publhealth.27.021405.102100

13. Items of the Scale

Below are the authentic scale items in their original language as published in the standard psychometric validation studies, without modification or translation to preserve instrument validity and reliability:
Instructions / Directions: Please answer the following questions regarding your physical environment, neighborhood characteristics, and community resources related to physical activity and walking.
Response Scale: Dichotomous (Yes / No), categorical proximity (<5 min, 5-10 min, 11-20 min, 20+ min), and 4-point agreement scales (Strongly Disagree, Somewhat Disagree, Somewhat Agree, Strongly Agree)
1

Are there sidewalks on most of the streets in your neighborhood?
2

How well maintained are the sidewalks in your neighborhood? (Very well, Somewhat well, Not very well, Not at all well)
3

Are there shoulders or bike lanes on most of the streets in your neighborhood?
4

Are the shoulders or bike lanes in your neighborhood well maintained?
5

Are there bicycle paths or walking trails in or near your neighborhood that are easy to get to?
6

Are the bicycle paths or walking trails well maintained?
7

Are the streets in your neighborhood well lit at night?
8

Does your neighborhood have crosswalks and pedestrian signals to help pedestrians cross busy streets?
9

Are there physical barriers (such as freeways, railways, or rivers) that make it hard to walk to places from your home?
10

Do you have access to free or low-cost indoor recreation facilities, such as a gym or community center?
11

Do you have access to free or low-cost outdoor recreation facilities, such as parks, playgrounds, or sports fields?
12

Are there pleasant places to walk near your home?
13

There is a lot of traffic on the streets in my neighborhood.
14

The speed of traffic on the street where I live is slow (30 mph or less).
15

Most drivers in my neighborhood exceed the posted speed limits.
16

My neighborhood has heavy truck traffic.
17

There are hills or steep inclines that make it difficult to walk in my neighborhood.
18

There are unattended or loose dogs in my neighborhood that make walking unpleasant or unsafe.
19

My neighborhood is safe from crime during the day.
20

My neighborhood is safe from crime at night.
21

There is a lot of litter or garbage on the streets in my neighborhood.
22

There are many abandoned or rundown buildings in my neighborhood.
23

I see other people being physically active (walking, running, biking) in my neighborhood.
24

How many minutes would it take you to walk from your home to the nearest convenience store or grocery store? (<5 min, 5-10 min, 11-20 min, >20 min, Don't know)
25

How many minutes would it take you to walk from your home to the nearest transit stop (bus stop or train)?
26

How many minutes would it take you to walk from your home to the nearest public park?
27

How many minutes would it take you to walk from your home to the nearest school (elementary, middle, or high school)?
28

How many minutes would it take you to walk from your home to the nearest trail for walking or biking?
29

How many minutes would it take you to walk from your home to the nearest library or community center?
30

How many minutes would it take you to walk from your home to the nearest bank, post office, or restaurant?
31

I feel comfortable letting children walk or play outside in my neighborhood during the day.
32

In your community, would you support using tax dollars to build more walking trails and bike paths?
33

In your community, would you support using tax dollars to build more sidewalks?
34

In your community, would you support using tax dollars to improve public recreation facilities?
35

In your community, would you support stricter enforcement of speed limits in residential areas?
36

In the past month, how often did family or friends offer to exercise or walk with you?
37

In the past month, how often did family or friends encourage you to be physically active?
38

In the past month, how often did family or friends complain about the time you spend exercising?
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Cite This Article

Looti, M. (2026, October 1). Saint Louis Environment and Physical Activity Instrument. PSYCHOLOGICAL DATABASE. https://english.arabpsychology.com/scales/saint-louis-environment-and-physical-activity-instrument/
Looti, Mohammed. “Saint Louis Environment and Physical Activity Instrument.” PSYCHOLOGICAL DATABASE, 1 October 2026, https://english.arabpsychology.com/scales/saint-louis-environment-and-physical-activity-instrument/.
Looti, Mohammed. “Saint Louis Environment and Physical Activity Instrument.” PSYCHOLOGICAL DATABASE. October 1, 2026. https://english.arabpsychology.com/scales/saint-louis-environment-and-physical-activity-instrument/.