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| ID | Type | Description | Link |
|---|---|---|---|
| R01HL077141 | U.S. NIH Grant/Contract | View source |
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| Name | Class |
|---|---|
| National Heart, Lung, and Blood Institute (NHLBI) | NIH |
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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.
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Low Walkability/Low Income | Participants reside in a low walkability, low income neighborhood | ||
| Low Walkability/High Income | Participants reside in a low walkability, high income neighborhood | ||
| High Walkability/Low Income | Participants reside in a high walkability, low income neighborhood | ||
| High Walkability/High Income | Participants reside in a high walkability, high income neighborhood |
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| Measure | Description | Time Frame |
|---|---|---|
| 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. | at two time points, 6 months apart, which were averaged |
| 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.) | Assessment at baseline and 6 months, with the data across these two time points averaged to increase outcome stability. |
| 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. | Assessment at baseline and 6 months, with the data across these two time points averaged to increase outcome stability. |
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Inclusion criteria:
Exclusion Criteria:
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Residents of selected block groups in King County, WA and the Baltimore region.
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| Name | Affiliation | Role |
|---|---|---|
| Abby King | Stanford University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| San Diego State University | San Diego | California | 92103 | United States | ||
| Stanford University School of Medicine |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 11445760 | Result | Stewart AL, Mills KM, King AC, Haskell WL, Gillis D, Ritter PL. CHAMPS physical activity questionnaire for older adults: outcomes for interventions. Med Sci Sports Exerc. 2001 Jul;33(7):1126-41. doi: 10.1097/00005768-200107000-00010. |
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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.
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| ID | Title | Description |
|---|---|---|
| FG000 | 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. This arm represents the High Walkability/High Income quadrant. |
| FG001 | 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. This arm represents the High Walkability/Low Income quadrant. |
| FG002 | 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. This arm represents the Low Walkability/High Income quadrant. |
| FG003 | 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. This arm represents the High Walkability/Low Income quadrant. |
| Title | Milestones | Reasons Not Completed | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Overall Study |
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| ID | Title | Description |
|---|---|---|
| BG000 | 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. |
| Units | Counts |
|---|---|
| Participants |
|
| Title | Description | Population Description | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Denominator Units Selected | Denominators | Classes |
|---|---|---|---|---|---|---|---|---|---|
| Age, Categorical | Count of Participants |
| Type | Title | Description | Population Description | Reporting Status | Anticipated Posting Date | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Time Frame | Units Analyzed | Denominator Units Selected | Arm/Group Information | Denominators | Classes | Analyses | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 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. | GIS variables were created for all participants enrolled in the study | Posted | Mean | Standard Deviation | units on a scale | at two time points, 6 months apart, which were averaged |
|
2 years, 9 months
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| ID | Title | Description | Deaths (Affected) | Deaths (At Risk) | Serious Events (Affected) | Serious Events (At Risk) | Other Events (Affected) | Other Events (At Risk) |
|---|---|---|---|---|---|---|---|---|
| EG000 | 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. There were no treatment conditions in this cross-sectional observational study. No adverse events were reported. |
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| Title | Organization | Phone | Extension | |
|---|---|---|---|---|
| Dr. Abby C. King | Stanford University | 650-725-5394 | king@stanford.edu |
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| ID | Term |
|---|---|
| D002318 | Cardiovascular Diseases |
| D006331 | Heart Diseases |
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| 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. | Assessment at baseline and 6 months, with the data across these two time points averaged to increase outcome stability. |
| 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). | Assessment at baseline and 6 months, with the data across these two time points averaged to increase outcome stability. |
| Stanford |
| California |
| 94305 |
| United States |
| University of British Columbia-Vancouver | Vancouver | British Columbia | Canada |
| BG001 | 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. |
| BG002 | 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. |
| BG003 | 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. |
| BG004 | Total | Total of all reporting groups |
| Participants |
|
| Age, Continuous | Mean | Standard Deviation | years |
|
| Sex: Female, Male | Count of Participants | Participants |
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| Region of Enrollment | Number | participants |
|
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. |
| OG001 | 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. |
| OG002 | 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. |
| OG003 | 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. |
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| 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.) | Posted | Mean | Standard Deviation | minutes per week | Assessment at baseline and 6 months, with the data across these two time points averaged to increase outcome stability. |
|
|
|
| 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. | Posted | Mean | Standard Deviation | minutes per day | Assessment at baseline and 6 months, with the data across these two time points averaged to increase outcome stability. |
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| 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. | Posted | Mean | Standard Deviation | units on a scale | Assessment at baseline and 6 months, with the data across these two time points averaged to increase outcome stability. |
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| 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). | Posted | Mean | Standard Deviation | units on a scale | Assessment at baseline and 6 months, with the data across these two time points averaged to increase outcome stability. |
|
|
|
| 0 |
| 212 |
| 0 |
| 212 |
| EG001 | 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. There were no treatment conditions in this cross-sectional observational study. No adverse events were reported. | 0 | 251 | 0 | 251 |
| EG002 | 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. There were no treatment conditions in this cross-sectional observational study. No adverse events were reported. | 0 | 220 | 0 | 220 |
| EG003 | 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. There were no treatment conditions in this cross-sectional observational study. No adverse events were reported. | 0 | 179 | 0 | 179 |
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