HUB City Steps was a 2-phase, community-based, lifestyle intervention with multiple components that targeted hypertension risk factors. The first phase was a 6-month noncontrolled, pre/post experimental intervention that was conducted from the end of January to the beginning of August 2010 and is the focus of this article. The second phase consisted of a 12-month maintenance intervention designed to test treatment effects of participants, who were randomized to a low versus high (ie, 4 vs 10) dose of telephone-delivered sessions that used a motivational interviewing approach. A full description of the methods has been published (8,11). All phases of this research were approved by the University of Southern Mississippi’s institutional review board.

Recruitment efforts primarily targeted African American residents in Hattiesburg, a midsized city of nearly 46,000 in southeast Mississippi, where approximately 53% of residents are African American and 42% are white (12). Eligibility criteria included adults aged 18 years or older who were English-speaking, were noninstitutionalized, and resided in the Hattiesburg area. Participants with systolic/diastolic BP of 180/110 mm Hg or higher were directed to obtain immediate medical attention and were disqualified from participation in the study. All others were eligible for participation regardless of BP and hypertension medication regimen. Informed consent and signed medical disclaimer were obtained upon enrollment into the study.

Various PSC, PA, and dietary measures were assessed. The interviewer-administered PSC instruments included measures of self-determination theory (treatment self-regulation for PA and for diet; 15 items each, 4 subscales: amotivation, external regulation, introjection, identification, and integration; score range, 30–150 [13]), processes of change for PA (30 items, 10 subscales: stimulus control, social liberation, reinforcement management, helping relationships, counter conditioning, self-liberation, self-reevaluation, environmental reevaluation, dramatic relief, and consciousness raising; score range, 30–150 [14]), and social support from walking group (11 items, 3 subscales: guidance, reliable alliance, and reassurance of worth) and from coach for PA (12 items, 3 subscales: guidance, reliable alliance, and social integration; score range for both, 23–115 [15]). The 6-minute walk test, an objective, simple, inexpensive, and safe exercise test (16,17), was used as a measure of fitness. The 6-minute walk test is reliable and can discriminate between functional levels in a high-functioning population (18). Physical activity was measured using Yamax pedometers (HRM USA, Inc). Each participant received a pedometer at baseline assessment with stride calibration determined by the 6-minute walk test. Participants had the option of recording daily steps on weekly pedometer diary postcards or by logging on to the intervention’s website. The National Cancer Institute’s 5-Factor Screener was used to assess dietary intake. This valid 18-item screener approximates intakes of fruit, vegetable, and dairy (servings); fiber (g); added sugar (tsp); and calcium (mg) (19,20).

The 6-month active intervention phase included 3 motivational enhancement sessions provided by intervention staff, continuous social support provided by walking coaches and walking groups, weekly pedometer diary self-monitoring, and 5 monthly education sessions (8,9,21). The motivational enhancement sessions implemented were consistent with self-determination theory and processes of change and focused on building internal motivation for change. During motivational enhancement sessions, participants received personalized feedback about various health factors such as weight, BP, cholesterol, BMI (weight in kilograms divided by the square of height in meters), and diet. Participants were given the opportunity to choose which health topics they wanted to discuss with a health coach trained in motivational interviewing (21). Education sessions were approximately 90 minutes; 15 minutes were allotted for group PA, followed by 30 to 45 minutes of nutrition education congruent with Dietary Approaches to Stop Hypertension (22), and 30 minutes of social support enhancement through sharing of successes and challenges. Each session was developed to increase knowledge and facilitate behavior changes by promoting and supporting processes of change.

Statistical analyses were performed using SAS software, versions 9.3 and 9.4 (SAS Institute, Inc). Descriptive measures were used to summarize demographic characteristics, PSCs, and outcome variables. For the PSC scales, Cronbach’s α values were computed as a measure of internal consistency. According to guidance proposed by George and Mallery (23), values greater than or equal to 0.6 indicated acceptable internal consistency for these scales.

For modeling purposes, race was categorized as African American or other (including white and American Indian/Alaska native), marital status was categorized as married or not married (including widowed, divorced, separated, and never married), education was categorized as less than or equal to high school graduate or greater than high school graduate, and income was treated as a continuous variable because of the large number (n = 12) of original categories. Generalized linear mixed models, using maximum likelihood estimation, were used to test for significant time differences in outcomes and PSCs. Maximum likelihood estimation is an approach for handling missing data in repeated measures (24). Time (at baseline and at 3 and 6 months) was modeled as a repeated measure by using a first-order autoregressive covariance structure. Custom contrasts were used to test for significant differences between baseline and 3-month follow-up and between baseline and 6 months follow-up using a Bonferroni correction factor to account for multiple testing.

Generalized linear mixed models also were used to determine significant demographic characteristics and baseline values that predicted changes in PSCs, and to determine whether PSC changes predicted changes in PA and dietary outcomes while accounting for demographic characteristics and baseline values. Five models based on theoretical groupings identified in the literature were built for PA and dietary outcomes. For these models, PSC variables with Cronbach’s α values of less than 0.6 were excluded because of their potential unreliability in this cohort of participants.

Changes between baseline and 3 months and baseline and 6 months were modeled as repeated measures by using a variance component covariance structure. Least squares means were computed to estimate and compare outcome changes. Although we used change in pedometer-determined mean steps per day as a PA outcome, the change was not from baseline to 6 months because no data on baseline steps per day were collected. Therefore, change was calculated as the difference between steps per day reported during the first 2 weeks of the intervention and the remaining weeks (weeks 3–27). Positive changes represent an increase in steps per day between the initial and remaining weeks for the intervention period. Therefore, change in intervention steps per day represents persistence in or maintenance of step-defined PA rather than a true change from a preintervention baseline. Details about the rationale, methods, and use of this steps-per-day indicator can be found elsewhere (10). The significance level of the tests was set at .05 (.025 for multiple comparisons).

Most participants were African American (94%) and female (85%); mean age of participants was 44 years (Table 1). Less than half (42%) were married, more than three-fourths (80%) had some post-high school education, and 27% reported a household income greater than or equal to $50,000 per year. Mean BMI was 35 kg/m² (range, 17–64 kg/m²), and mean BP was 126/83 mm Hg.

Of the 269 baseline participants, 227 (84%) were assessed at 3 months and 190 (71%) were assessed at 6 months follow-up. Comparisons between study noncompleters and completers at 3 months follow-up indicated that noncompleters were significantly younger (36 vs 46 years, P < .001) and had higher mean BMI (37 vs 34 kg/m², P = .01), fat mass (48 vs 42 kg, P = .04), and lean body mass (57 vs 52 kg, P = .04) at baseline than completers (data not shown). Similarly, at 6 months follow-up, study noncompleters were significantly younger (39 vs 47 y, P < .001), had higher mean BMI (37 vs 34 kg/m², P = .01), and lower mean triglycerides (117 vs 137 mg/dL, P = .04) at baseline than completers (data not shown).

Using baseline data, most (21 of 24) of the PSC scales and subscales demonstrated acceptable internal consistency, with Cronbach’s α at or above .60 (23) (Table 2). Unacceptable internal consistency was observed for 3 scales: amotivation for physical activity, dramatic relief, and self-liberation (Cronbach’s α range, 0.44–0.54). For the dietary and PA outcome variables, time differences were apparent only for sugar intake and steps per day. Sugar intake decreased by approximately 3 teaspoons at both follow-up times, while pedometer-determined PA increased by approximately 2,010 steps per day (Table 2).

Of the 21 scales with sufficient internal consistency, time differences were apparent for 10 of the constructs. At follow-up, scores for diet amotivation were significantly lower compared with baseline scores. Conversely, at 3 and 6 months follow-up, scores for coach reassurance of worth, group reliable alliance, group guidance, group social integration, counter-conditioning, helping relationships, social liberation, and stimulus control were significantly higher compared with baseline scores. For reinforcement management, pair-wise comparisons of 3 and 6 months scores to baseline failed to reach significance, although scores were higher at the follow-up times.

Only the 10 constructs with acceptable reliability and significant changes postintervention were included in mixed-model linear regression analyses for changes in PSCs. Sex was a significant predictor of change for diet amotivation (P < .05). A significant decrease was apparent for women, but the change was not significant for men. Marital status was a significant predictor of change for diet amotivation and stimulus control (P < .05). A significant decrease in diet amotivation was apparent for married participants; the significant increase in stimulus control observed for unmarried participants was higher than the significant increase for married participants (1.6 and 0.9 points, respectively). Smoking status was a significant predictor of change for social liberation; the change observed for smokers was higher than the significant increase for nonsmokers (1.2 and .5 points, respectively). Education level was a significant predictor of change for counter-conditioning, helping relationships, and reinforcement management (P < .05). For all 3 constructs, the significant increases observed for participants with less than or equal to a high school degree were greater than the significant increases for participants with more than a high school degree (P < .05). Age predicted change in counter-conditioning, baseline BMI predicted change in group reliable alliance, and both income and baseline BMI predicted change in stimulus control (P < .05).

Results of the mixed-model linear regression analyses for changes in PA and dietary outcomes predicted by PSC changes are presented in Table 3 (all PSC and only significant covariates are reported). For behavioral processes of change, helping relationships and reinforcement management were significant predictors of fitness change. For constructs from self-determination theory, external regulation was a significant positive predictor of changes in both sugar and fiber intake; introjected regulation was a significant negative predictor of change in sugar intake. None of the treatment self-regulation constructs were significant predictors for fitness or intakes of calcium, dairy, and fruits and vegetables. For the cognitive processes of change, consciousness raising was a significant positive predictor of change in fitness. None of the processes of change were significant predictors of change in steps per day. For social support, group guidance was a significant negative predictor of change in steps per day. None of the social support constructs were significant predictors for change in fitness. For all 5 of the fitness models, the baseline fitness value was a significant negative predictor of change (regression coefficients = −.7). That is, participants who scored lower on the fitness test (ie, walked a shorter distance in 6 minutes) at baseline had greater improvements in fitness than did participants who scored higher at baseline. None of the covariates were significant predictors of change for the steps-per-day models. In terms of dietary outcomes, female participants significantly decreased their sugar intake by 3.7 teaspoons and their fiber intake by 0.6 grams, whereas male participants increased both by 2.6 teaspoons and 1.1 gram, respectively. Household income, baseline BMI, and baseline sugar intake were significant predictors of change in sugar intake. Similarly, baseline fiber intake was a significant predictor of change in fiber intake.