Table 3.
Socio-demographic characteristics of study participants.
| Characteristics | Total study population, N (%) | Never uses an app, N (%) | Any-app user, N (%) | Fitness-app user,1 N (%) | Planning-app user,1 N (%) | ARC Survey2,3 % ± SE% | p-value3: any app vs. none | p-value:3 fitness app vs. else | p-value:3 planning app vs. else | p-value:3 ARC vs. study |
|---|---|---|---|---|---|---|---|---|---|---|
| Total | 95 | 58 (61%) | 37 (39%) | 31 (33%) | 9 (9%) | N = 18 ± 5 | ||||
| Male gender | 68 (72%) | 42 (72%) | 26 (70%) | 24 (77%) | 4 (44%) | 79% ± 16% | 0.820 | 0.470 | 0.112 | 0.528 |
| Age (years)4 | ||||||||||
| Mean ± SD | 35.1 ± 11.5 | 33.9 ± 12.2 | 36.8 ± 10.3 | 36.3 ± 10.3 | 38.1 ± 12.1 | 38.2 ± 3.0 | 0.089 | 0.227 | 0.400 | 0.099 |
| 18-24 | 18 (20%) | 12 (22%) | 6 (16%) | 6 (19%) | 1 (11%) | 11% ± 10% | 0.479 | 0.904 | 0.743 | 0.402 |
| 25-34 | 35 (38%) | 23 (42%) | 12 (32%) | 10 (32%) | 3 (33%) | 33% ± 17% | ||||
| 35-44 | 21 (23%) | 11 (20%) | 10 (27%) | 8 (26%) | 2 (22%) | 24% ± 10% | ||||
| 45-54 | 11 (12%) | 4 (7%) | 7 (19%) | 5 (16%) | 2 (22%) | 26% ± 10% | ||||
| 55-64 | 6 (7%) | 4 (7%) | 2 (5%) | 2 (7%) | 1 (11%) | 6% ± 4% | ||||
| 65+ | 1 (1%) | 1 (2%) | 0 (0%) | 0 (0%) | 0 (0%) | 0% ± 0% | ||||
| Race | ||||||||||
| White | 65 (69%) | 39 (67%) | 26 (72%) | 21 (68%) | 7 (88%) | 79% ± 12% | 0.421 | 0.405 | 0.674 | 0.128 |
| Black | 14 (15%) | 7 (12%) | 7 (19%) | 7 (23%) | 0 (0%) | 21% ± 19% | ||||
| Hispanic or Latino | 4 (4%) | 4 (7%) | 0 (0%) | 0 (0%) | 0 (0%) | 0% ± 0% | ||||
| Asian | 10 (11%) | 7 (12%) | 3 (8%) | 3 (10%) | 1 (13%) | 0% ± 0% | ||||
| Other | 1 (1%) | 1 (2%) | 0 (0%) | 0 (0%) | 0 (0%) | 0% ± 0% | ||||
| Annual household income ($)4 | ||||||||||
| Mean ± SD | 87,230 ± 47,445 | 81,798 ± 49,293 | 96,034 ± 43,679 | 97,200 ± 42,477 | 79,583 ± 46,809 | 84,214 ± 11,182 | 0.187 | 0.156 | 0.598 | 0.919 |
| <19,999 | 8 (11%) | 7 (15%) | 1 (3%) | 1 (4%) | 0 (0%) | 0% ± 0% | 0.531 | 0.383 | 0.721 | 0.037 |
| 20,000-39,999 | 4 (5%) | 3 (6%) | 1 (3%) | 0 (0%) | 1 (17%) | 16% ± 13% | ||||
| 40,000-59,999 | 13 (17%) | 8 (17%) | 5 (17%) | 4 (16%) | 2 (33%) | 25% ± 16% | ||||
| 60,000-74,999 | 13 (17%) | 6 (13%) | 7 (24%) | 7 (28%) | 1 (17%) | 16% ± 16% | ||||
| 75,000-99,999 | 5 (7%) | 4 (9%) | 1 (3%) | 1 (4%) | 0 (0%) | 13% ± 7% | ||||
| 100,000-149,999 | 19 (25%) | 12 (26%) | 7 (24%) | 6 (24%) | 1 (17%) | 23% ± 11% | ||||
| ≥150,000 | 14 (18%) | 7 (15%) | 7 (24%) | 6 (24%) | 1 (17%) | 6% ± 5% | ||||
| Regular access to a private automobile | 63 (79%) | 33 (73%) | 30 (86%) | 25 (86%) | 8 (89%) | 100% ± 0% | 0.271 | 0.266 | 0.273 | 0.001 |
| Own a smartphone or GPS-capable device | 94 (99%) | 57 (98%) | 37 (100%) | 31 (100%) | 9 (100%) | N/A | 1.000 | 1.000 | 1.000 | N/A |
| Area-level median home value ($), Mean (SD) | 259,672 (125,061) | 249,544 (107,493) | 275,386 (148,990) | 263,921 (130,418) | 354,314 (227,897) | N/A | 0.682 | 0.890 | 0.385 | N/A |
| Distance from home to nearest infrastructure (km), Mean (SD) | N/A | N/A | ||||||||
| Hard-surface multi-use trail | 0.97 (1.04) | 1.00 (0.98) | 0.92 (1.14) | 0.99 (1.23) | 0.71 (0.64) | N/A | 0.283 | 0.570 | 0.392 | N/A |
| Protected bike lane | 3.24 (3.64) | 3.19 (3.46) | 3.33 (3.96) | 3.18 (4.04) | 4.00 (3.23) | N/A | 0.930 | 0.676 | 0.184 | N/A |
| Buffered bike lane | 3.10 (3.70) | 3.05 (3.52) | 3.16 (4.03) | 3.05 (4.12) | 3.69 (3.23) | N/A | 0.898 | 0.676 | 0.286 | N/A |
| Conventional bike lane | 0.92 (1.53) | 0.89 (1.53) | 0.96 (1.56) | 0.88 (1.56) | 1.03 (1.48) | N/A | 0.332 | 0.684 | 0.740 | N/A |
| Shared travel lane | 0.98 (1.66) | 0.96 (1.71) | 1.00 (1.61) | 1.14 (1.73) | 0.47 (0.42) | N/A | 0.312 | 0.067 | 0.662 | N/A |
SD, standard deviation; SE, standard error.
1
Three participants used both app types at least on occasion.
2
ARC Survey, 2011 Atlanta Regional Commission Regional Travel Survey. Additional detail can be found in Supplement 1, Section 2.
3
P-values are from two-sided Fisher’s Exact Test for categorical measures or Wilcoxon test for continuous measures.
4
Age was surveyed as an integer; some respondents responded in ten-year categories. Income was surveyed in categories. For both, where a continuous value was not available, continuous analyses used the category midpoint, except for the bottom and top categories, which were set at their inner bound.