Cardiovascular Diseases, Heart Diseases
Conditions
Brief summary
The purpose of this study is to investigate whether seniors living in neighborhoods that are conducive to walking are more physically active than those living in neighborhoods that are less conducive to walking.
Detailed description
BACKGROUND: Despite the recognized benefits of regular physical activity for older adults, people over the age of 65 remain among the most inactive groups of the U.S. population. Efforts to understand the factors influencing physical activity in this important group have been limited primarily to demographic and psychosocial domains. The importance of the neighborhood environment in influencing a host of health, behavioral, and psychosocial outcomes has been recognized. However, to date, no systematic investigation of the relationship between objective and subjective environmental factors and objectively measured physical activity levels among older adults has been undertaken. DESIGN NARRATIVE: This observational study will investigate whether seniors living in neighborhoods conducive to walking are more physically active, after adjusting for socioeconomic status (SES), than those living in neighborhoods less conducive to walking or other forms of physical activity for transportation or recreational purposes. Additional questions of interest concern the moderating effects of physical function and the proportion of seniors living nearby on the relationship between environment and physical activity. The study will take advantage of the sampling, recruitment, and data collection methods of an ongoing NIH-funded research project aimed at integrating public health and urban planning frameworks in studying the impacts of environmental factors on physical activity levels in younger adults. Population-based sampling methods will be used to recruit adults over 65 years of age who are living in more walkable versus less walkable neighborhoods of varying SES levels. Participants will be recruited from Seattle, Washington (n = 600) and Baltimore, Maryland (n = 600). In addition to objectively measured physical environment (using geographic information systems {GIS}) and physical activity levels (using accelerometry), self-reported neighborhood environment, physical activity, and quality of life variables of particular relevance to older adults will be assessed twice during a 12-month period.
Interventions
None listed
Sponsors
National Heart, Lung, and Blood Institute (NHLBI)
Stanford University
Study design
Observational model
COHORT
Time perspective
CROSS_SECTIONAL
Eligibility
Sex/Gender
ALL
Age
65 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Currently living in an apartment, condo, house, or assisted living facility * Able to walk more than 10 feet at a time * Able to speak and read English * Able to complete study surveys (with assistance if necessary)
Exclusion criteria
* Not currently living in one of the areas in which the study will take place
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Physical Environment Factors Using Geographic Information Systems [GIS] | at two time points, 6 months apart, which were averaged | Physical environment factors measured using GIS-derived measures of street connectivity, residential density, and mixed land use in participant block groups and a network buffer around each participant's home. A walkability index was created for a 500 meter street network buffer around participant homes. The walkability index was calculated for each census block group in the regions by summing the z-scores of four macro built environment measures: 1) net residential density, 2) intersection density, 3) retail floor to land area ratio (FAR), and 4) mixed use. A higher scores indicates higher walkability. The minimum value is -4.08 and the maximum value is 12.5. |
| Community Healthy Activities Model Program for Seniors (CHAMPS) Self-reported Walking for Errands | Assessment at baseline and 6 months, with the data across these two time points averaged to increase outcome stability. | A self-report physical activity questionnaire that assesses weekly frequency and duration of various activities typically undertaken by midlife and older adults over the prior 4-week period. Self-reported walking for errands is one physical activity item assessed. The measure has been shown to have good test-retest reliability (stability) and construct and concurrent validity, and has been shown to be sensitive to change in a variety of adult populations. It has seven frequency categories (from less than 1 hour a week to 9 or more hours per week). The minimum value is 0 and the maximal value is variable. (See Stewart AL, Mills KM, King AC, et al. CHAMPS Physical Activity Questionnaire for Older Adults: Outcomes for Interventions. Med Sci Sports Exerc, 33:7, 1126-1141, 2001.) |
| Accelerometer Measured Physical Activity | Assessment at baseline and 6 months, with the data across these two time points averaged to increase outcome stability. | Ambulatory assessment of moderate-to-vigorous physical activity using a validated Actigraph accelerometer. Participants were instructed to wear the accelerometer during waking hours for seven days at each of the two measurement points. The accelerometer was placed over the right hip. Data were cleaned and scored using MeterPlus version 4.0 software. |
| Neighborhood Environment for Walkability Survey (NEWS) - Walking and Cycling Facilities in Neighborhood | Assessment at baseline and 6 months, with the data across these two time points averaged to increase outcome stability. | The scale is walking/cycling facilities which is a mean of 5 items. The minimum value is 1 and the maximum value is 4. Higher scores indicate an environment that is supportive of walking and cycling which is a better outcome. |
| Neighborhood Environment for Walkability Survey (NEWS) - Land Use Mix Access | Assessment at baseline and 6 months, with the data across these two time points averaged to increase outcome stability. | The scale is land use mix access which is a mean of 7 items. The minimum value is 1 and the maximum value is 4. Higher scores indicate easier access to services which is indicative of a high walkability environment (i.e., a better outcome). |
Countries
Canada, United States
Participant flow
Pre-assignment details
896 participants were enrolled in the the study, but 34 dropped out after receiving the study materials and before completing the measures. Therefore, 862 participants provided data for this study.
Participants by arm
| Arm | Count |
|---|---|
| High Walkability/High Income Households were enumerated in King County, WA and in the Baltimore, MD-Washington, DC area based on geographical information systems-derived walkability index and neighborhood-level income. Four quadrants were derived based on these two factors: higher walkability-higher income; higher walkability-lower income; lower walkability-higher income; and lower walkability-lower income neighborhoods. | 212 |
| High Walkability/Low Income Households were enumerated in King County, WA and in the Baltimore, MD-Washington, DC area based on geographical information systems-derived walkability index and neighborhood-level income. Four quadrants were derived based on these two factors: higher walkability-higher income; higher walkability-lower income; lower walkability-higher income; and lower walkability-lower income neighborhoods. | 251 |
| Low Walkability/High Income Households were enumerated in King County, WA and in the Baltimore, MD-Washington, DC area based on geographical information systems-derived walkability index and neighborhood-level income. Four quadrants were derived based on these two factors: higher walkability-higher income; higher walkability-lower income; lower walkability-higher income; and lower walkability-lower income neighborhoods. | 220 |
| Low Walkability/Low Income Households were enumerated in King County, WA and in the Baltimore, MD-Washington, DC area based on geographical information systems-derived walkability index and neighborhood-level income. Four quadrants were derived based on these two factors: higher walkability-higher income; higher walkability-lower income; lower walkability-higher income; and lower walkability-lower income neighborhoods. | 179 |
| Total | 862 |
Baseline characteristics
| Characteristic | High Walkability/Low Income | Low Walkability/High Income | High Walkability/High Income | Low Walkability/Low Income | Total |
|---|---|---|---|---|---|
| Age, Categorical <=18 years | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants |
| Age, Categorical >=65 years | 251 Participants | 220 Participants | 212 Participants | 179 Participants | 862 Participants |
| Age, Categorical Between 18 and 65 years | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants |
| Age, Continuous | 75.7 years STANDARD_DEVIATION 6.8 | 74.6 years STANDARD_DEVIATION 6.8 | 76.1 years STANDARD_DEVIATION 7.1 | 75.0 years STANDARD_DEVIATION 6.5 | 75.4 years STANDARD_DEVIATION 6.8 |
| Region of Enrollment United States | 251 participants | 220 participants | 212 participants | 179 participants | 862 participants |
| Sex: Female, Male Female | 155 Participants | 109 Participants | 115 Participants | 103 Participants | 482 Participants |
| Sex: Female, Male Male | 96 Participants | 111 Participants | 97 Participants | 76 Participants | 380 Participants |
Adverse events
| Event type | EG000 affected / at risk | EG001 affected / at risk | EG002 affected / at risk | EG003 affected / at risk |
|---|---|---|---|---|
| deaths Total, all-cause mortality | — / — | — / — | — / — | — / — |
| other Total, other adverse events | 0 / 212 | 0 / 251 | 0 / 220 | 0 / 179 |
| serious Total, serious adverse events | 0 / 212 | 0 / 251 | 0 / 220 | 0 / 179 |
Outcome results
Primary
Accelerometer Measured Physical Activity
Ambulatory assessment of moderate-to-vigorous physical activity using a validated Actigraph accelerometer. Participants were instructed to wear the accelerometer during waking hours for seven days at each of the two measurement points. The accelerometer was placed over the right hip. Data were cleaned and scored using MeterPlus version 4.0 software.
Time frame: Assessment at baseline and 6 months, with the data across these two time points averaged to increase outcome stability.
| Arm | Measure | Value (MEAN) | Dispersion |
|---|---|---|---|
| High Walkability/High Income | Accelerometer Measured Physical Activity | 17.2 minutes per day | Standard Deviation 18.5 |
| High Walkability/Low Income | Accelerometer Measured Physical Activity | 8.9 minutes per day | Standard Deviation 12.6 |
| Low Walkability/High Income | Accelerometer Measured Physical Activity | 13.5 minutes per day | Standard Deviation 15.7 |
| Low Walkability/Low Income | Accelerometer Measured Physical Activity | 10.3 minutes per day | Standard Deviation 15.6 |
Primary
Community Healthy Activities Model Program for Seniors (CHAMPS) Self-reported Walking for Errands
A self-report physical activity questionnaire that assesses weekly frequency and duration of various activities typically undertaken by midlife and older adults over the prior 4-week period. Self-reported walking for errands is one physical activity item assessed. The measure has been shown to have good test-retest reliability (stability) and construct and concurrent validity, and has been shown to be sensitive to change in a variety of adult populations. It has seven frequency categories (from less than 1 hour a week to 9 or more hours per week). The minimum value is 0 and the maximal value is variable. (See Stewart AL, Mills KM, King AC, et al. CHAMPS Physical Activity Questionnaire for Older Adults: Outcomes for Interventions. Med Sci Sports Exerc, 33:7, 1126-1141, 2001.)
Time frame: Assessment at baseline and 6 months, with the data across these two time points averaged to increase outcome stability.
| Arm | Measure | Value (MEAN) | Dispersion |
|---|---|---|---|
| High Walkability/High Income | Community Healthy Activities Model Program for Seniors (CHAMPS) Self-reported Walking for Errands | 80.6 minutes per week | Standard Deviation 106.7 |
| High Walkability/Low Income | Community Healthy Activities Model Program for Seniors (CHAMPS) Self-reported Walking for Errands | 46.3 minutes per week | Standard Deviation 84.3 |
| Low Walkability/High Income | Community Healthy Activities Model Program for Seniors (CHAMPS) Self-reported Walking for Errands | 21.5 minutes per week | Standard Deviation 55.8 |
| Low Walkability/Low Income | Community Healthy Activities Model Program for Seniors (CHAMPS) Self-reported Walking for Errands | 21.5 minutes per week | Standard Deviation 66.2 |
Primary
Neighborhood Environment for Walkability Survey (NEWS) - Land Use Mix Access
The scale is land use mix access which is a mean of 7 items. The minimum value is 1 and the maximum value is 4. Higher scores indicate easier access to services which is indicative of a high walkability environment (i.e., a better outcome).
Time frame: Assessment at baseline and 6 months, with the data across these two time points averaged to increase outcome stability.
| Arm | Measure | Value (MEAN) | Dispersion |
|---|---|---|---|
| High Walkability/High Income | Neighborhood Environment for Walkability Survey (NEWS) - Land Use Mix Access | 3.1 units on a scale | Standard Deviation 0.5 |
| High Walkability/Low Income | Neighborhood Environment for Walkability Survey (NEWS) - Land Use Mix Access | 2.9 units on a scale | Standard Deviation 0.5 |
| Low Walkability/High Income | Neighborhood Environment for Walkability Survey (NEWS) - Land Use Mix Access | 2.4 units on a scale | Standard Deviation 0.6 |
| Low Walkability/Low Income | Neighborhood Environment for Walkability Survey (NEWS) - Land Use Mix Access | 2.5 units on a scale | Standard Deviation 0.6 |
Primary
Neighborhood Environment for Walkability Survey (NEWS) - Walking and Cycling Facilities in Neighborhood
The scale is walking/cycling facilities which is a mean of 5 items. The minimum value is 1 and the maximum value is 4. Higher scores indicate an environment that is supportive of walking and cycling which is a better outcome.
Time frame: Assessment at baseline and 6 months, with the data across these two time points averaged to increase outcome stability.
| Arm | Measure | Value (MEAN) | Dispersion |
|---|---|---|---|
| High Walkability/High Income | Neighborhood Environment for Walkability Survey (NEWS) - Walking and Cycling Facilities in Neighborhood | 3.2 units on a scale | Standard Deviation 0.6 |
| High Walkability/Low Income | Neighborhood Environment for Walkability Survey (NEWS) - Walking and Cycling Facilities in Neighborhood | 2.9 units on a scale | Standard Deviation 0.7 |
| Low Walkability/High Income | Neighborhood Environment for Walkability Survey (NEWS) - Walking and Cycling Facilities in Neighborhood | 2.6 units on a scale | Standard Deviation 0.9 |
| Low Walkability/Low Income | Neighborhood Environment for Walkability Survey (NEWS) - Walking and Cycling Facilities in Neighborhood | 2.4 units on a scale | Standard Deviation 0.9 |
Primary
Physical Environment Factors Using Geographic Information Systems [GIS]
Physical environment factors measured using GIS-derived measures of street connectivity, residential density, and mixed land use in participant block groups and a network buffer around each participant's home. A walkability index was created for a 500 meter street network buffer around participant homes. The walkability index was calculated for each census block group in the regions by summing the z-scores of four macro built environment measures: 1) net residential density, 2) intersection density, 3) retail floor to land area ratio (FAR), and 4) mixed use. A higher scores indicates higher walkability. The minimum value is -4.08 and the maximum value is 12.5.
Time frame: at two time points, 6 months apart, which were averaged
Population: GIS variables were created for all participants enrolled in the study
| Arm | Measure | Value (MEAN) | Dispersion |
|---|---|---|---|
| High Walkability/High Income | Physical Environment Factors Using Geographic Information Systems [GIS] | 1.3 units on a scale | Standard Deviation 3 |
| High Walkability/Low Income | Physical Environment Factors Using Geographic Information Systems [GIS] | 1.9 units on a scale | Standard Deviation 3.2 |
| Low Walkability/High Income | Physical Environment Factors Using Geographic Information Systems [GIS] | -2.1 units on a scale | Standard Deviation 1 |
| Low Walkability/Low Income | Physical Environment Factors Using Geographic Information Systems [GIS] | -1.6 units on a scale | Standard Deviation 1.2 |