Trial Outcomes & Findings for Understanding the Impact of Neighborhood Type on Physical Activity in Older Adults (NCT NCT00094211)
NCT ID: NCT00094211
Last Updated: 2019-05-28
Results Overview
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.
Recruitment status
COMPLETED
Target enrollment
896 participants
Primary outcome timeframe
at two time points, 6 months apart, which were averaged
Results posted on
2019-05-28
Participant Flow
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.
Participant milestones
| Measure |
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.
|
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.
|
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.
|
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.
|
|---|---|---|---|---|
|
Overall Study
STARTED
|
221
|
259
|
230
|
186
|
|
Overall Study
COMPLETED
|
212
|
251
|
220
|
179
|
|
Overall Study
NOT COMPLETED
|
9
|
8
|
10
|
7
|
Reasons for withdrawal
Withdrawal data not reported
Baseline Characteristics
Understanding the Impact of Neighborhood Type on Physical Activity in Older Adults
Baseline characteristics by cohort
| Measure |
High Walkability/High Income
n=212 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.
|
High Walkability/Low Income
n=251 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.
|
Low Walkability/High Income
n=220 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.
|
Low Walkability/Low Income
n=179 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.
|
Total
n=862 Participants
Total of all reporting groups
|
|---|---|---|---|---|---|
|
Age, Categorical
<=18 years
|
0 Participants
n=5 Participants
|
0 Participants
n=7 Participants
|
0 Participants
n=5 Participants
|
0 Participants
n=4 Participants
|
0 Participants
n=21 Participants
|
|
Age, Categorical
Between 18 and 65 years
|
0 Participants
n=5 Participants
|
0 Participants
n=7 Participants
|
0 Participants
n=5 Participants
|
0 Participants
n=4 Participants
|
0 Participants
n=21 Participants
|
|
Age, Categorical
>=65 years
|
212 Participants
n=5 Participants
|
251 Participants
n=7 Participants
|
220 Participants
n=5 Participants
|
179 Participants
n=4 Participants
|
862 Participants
n=21 Participants
|
|
Age, Continuous
|
76.1 years
STANDARD_DEVIATION 7.1 • n=5 Participants
|
75.7 years
STANDARD_DEVIATION 6.8 • n=7 Participants
|
74.6 years
STANDARD_DEVIATION 6.8 • n=5 Participants
|
75.0 years
STANDARD_DEVIATION 6.5 • n=4 Participants
|
75.4 years
STANDARD_DEVIATION 6.8 • n=21 Participants
|
|
Sex: Female, Male
Female
|
115 Participants
n=5 Participants
|
155 Participants
n=7 Participants
|
109 Participants
n=5 Participants
|
103 Participants
n=4 Participants
|
482 Participants
n=21 Participants
|
|
Sex: Female, Male
Male
|
97 Participants
n=5 Participants
|
96 Participants
n=7 Participants
|
111 Participants
n=5 Participants
|
76 Participants
n=4 Participants
|
380 Participants
n=21 Participants
|
|
Region of Enrollment
United States
|
212 participants
n=5 Participants
|
251 participants
n=7 Participants
|
220 participants
n=5 Participants
|
179 participants
n=4 Participants
|
862 participants
n=21 Participants
|
PRIMARY outcome
Timeframe: at two time points, 6 months apart, which were averagedPopulation: GIS variables were created for all participants enrolled in the study
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.
Outcome measures
| Measure |
High Walkability/High Income
n=221 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.
|
High Walkability/Low Income
n=259 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.
|
Low Walkability/High Income
n=230 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.
|
Low Walkability/Low Income
n=186 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.
|
|---|---|---|---|---|
|
Physical Environment Factors Using Geographic Information Systems [GIS]
|
1.3 units on a scale
Standard Deviation 3.0
|
1.9 units on a scale
Standard Deviation 3.2
|
-2.1 units on a scale
Standard Deviation 1.0
|
-1.6 units on a scale
Standard Deviation 1.2
|
PRIMARY outcome
Timeframe: 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.)
Outcome measures
| Measure |
High Walkability/High Income
n=216 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.
|
High Walkability/Low Income
n=257 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.
|
Low Walkability/High Income
n=228 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.
|
Low Walkability/Low Income
n=182 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.
|
|---|---|---|---|---|
|
Community Healthy Activities Model Program for Seniors (CHAMPS) Self-reported Walking for Errands
|
80.6 minutes per week
Standard Deviation 106.7
|
46.3 minutes per week
Standard Deviation 84.3
|
21.5 minutes per week
Standard Deviation 55.8
|
21.5 minutes per week
Standard Deviation 66.2
|
PRIMARY outcome
Timeframe: 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.
Outcome measures
| Measure |
High Walkability/High Income
n=212 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.
|
High Walkability/Low Income
n=251 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.
|
Low Walkability/High Income
n=220 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.
|
Low Walkability/Low Income
n=179 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.
|
|---|---|---|---|---|
|
Accelerometer Measured Physical Activity
|
17.2 minutes per day
Standard Deviation 18.5
|
8.9 minutes per day
Standard Deviation 12.6
|
13.5 minutes per day
Standard Deviation 15.7
|
10.3 minutes per day
Standard Deviation 15.6
|
PRIMARY outcome
Timeframe: 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.
Outcome measures
| Measure |
High Walkability/High Income
n=212 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.
|
High Walkability/Low Income
n=250 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.
|
Low Walkability/High Income
n=220 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.
|
Low Walkability/Low Income
n=179 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.
|
|---|---|---|---|---|
|
Neighborhood Environment for Walkability Survey (NEWS) - Walking and Cycling Facilities in Neighborhood
|
3.2 units on a scale
Standard Deviation 0.6
|
2.9 units on a scale
Standard Deviation 0.7
|
2.6 units on a scale
Standard Deviation 0.9
|
2.4 units on a scale
Standard Deviation 0.9
|
PRIMARY outcome
Timeframe: 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).
Outcome measures
| Measure |
High Walkability/High Income
n=212 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.
|
High Walkability/Low Income
n=251 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.
|
Low Walkability/High Income
n=220 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.
|
Low Walkability/Low Income
n=179 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.
|
|---|---|---|---|---|
|
Neighborhood Environment for Walkability Survey (NEWS) - Land Use Mix Access
|
3.1 units on a scale
Standard Deviation 0.5
|
2.9 units on a scale
Standard Deviation 0.5
|
2.4 units on a scale
Standard Deviation 0.6
|
2.5 units on a scale
Standard Deviation 0.6
|
Adverse Events
High Walkability/High Income
Serious events: 0 serious events
Other events: 0 other events
Deaths: 0 deaths
High Walkability/Low Income
Serious events: 0 serious events
Other events: 0 other events
Deaths: 0 deaths
Low Walkability/High Income
Serious events: 0 serious events
Other events: 0 other events
Deaths: 0 deaths
Low Walkability/Low Income
Serious events: 0 serious events
Other events: 0 other events
Deaths: 0 deaths
Serious adverse events
Adverse event data not reported
Other adverse events
Adverse event data not reported
Additional Information
Results disclosure agreements
- Principal investigator is a sponsor employee
- Publication restrictions are in place