A Multicomponent Behavioral Intervention to Reduce
Stroke Risk Factor Behaviors
The Stroke Health and Risk Education Cluster-Randomized
Controlled Trial
Devin L. Brown, MD; Kathleen M. Conley, PhD; Brisa N. Sánchez, PhD;
Kenneth Resnicow, PhD; Joan E. Cowdery, PhD; Emma Sais, BS; Jillian Murphy, MPH;
Lesli E. Skolarus, MD; Lynda D. Lisabeth, PhD; Lewis B. Morgenstern, MD
Downloaded from http://stroke.ahajournals.org/ by guest on June 14, 2017
Background and Purpose—The Stroke Health and Risk Education Project was a cluster-randomized, faith-based, culturally
sensitive, theory-based multicomponent behavioral intervention trial to reduce key stroke risk factor behaviors in
Hispanics/Latinos and European Americans.
Methods—Ten Catholic churches were randomized to intervention or control group. The intervention group received a
1-year multicomponent intervention (with poor adherence) that included self-help materials, tailored newsletters, and
motivational interviewing counseling calls. Multilevel modeling, accounting for clustering within subject pairs and
parishes, was used to test treatment differences in the average change since baseline (ascertained at 6 and 12 months) in
dietary sodium, fruit and vegetable intake, and physical activity, measured using standardized questionnaires. A priori,
the trial was considered successful if any one of the 3 outcomes was significant at the 0.05/3 level.
Results—Of 801 subjects who consented, 760 completed baseline data assessments, and of these, 86% completed at least one
outcome assessment. The median age was 53 years; 84% subjects were Hispanic/Latino; and 64% subjects were women.
The intervention group had a greater increase in fruit and vegetable intake than the control group (0.25 cups per day
[95% confidence interval: 0.08, 0.42], P=0.002), a greater decrease in sodium intake (−123.17 mg/d [−194.76, −51.59],
P=0.04), but no difference in change in moderate- or greater-intensity physical activity (−27 metabolic equivalent–
minutes per week [−526, 471], P=0.56).
Conclusions—This multicomponent behavioral intervention targeting stroke risk factors in predominantly Hispanics/
Latinos was effective in increasing fruit and vegetable intake, reaching its primary end point. The intervention also
seemed to lower sodium intake. Church-based health promotions can be successful in primary stroke prevention efforts.
Clinical Trial Registration—URL: http://www.clinicaltrials.gov. Unique identifier: NCT01378780.
(Stroke. 2015;46:2861-2867. DOI: 10.1161/STROKEAHA.115.010678.)
Key Words: behavioral intervention ◼ clinical trial ◼ hypertension ◼ prevention ◼ risk factors ◼ stroke
H
ispanics/Latinos, now the largest minority group in the
United States, have a higher proportion of poorly controlled blood pressure (BP)1 and a greater burden of stroke
than non-Hispanic whites.2 BP, a potent cardiovascular risk
factor, is modified by behaviors such as diet, physical activity, and medication adherence. Because of the higher prevalence of risk factors, less available preventive services, and
less favorable diet and exercise profile of Hispanics/Latinos,
the need for culturally sensitive preventive programs has been
stressed.3,4 Although many studies have been conducted in
African American churches,5–7 few faith-based interventions
have been conducted for Hispanics/Latinos, the majority of
whom are Catholic or a mixed group of Hispanics/Latinos
and non-Hispanic whites.8 The results of studies conducted in
Protestant African American churches may not translate to the
Hispanic/Latino community where culture and attitudes about
health and lifestyle differ.4 Furthermore, implementation of
church-based interventions may differ in Catholic churches,
which have a different structure and policies. We therefore
designed the Stroke Health and Risk Education (SHARE)
project, a church-based, cluster-randomized, behavioral intervention, to reduce stroke risk through reduction in sodium
intake, increase in fruit and vegetable intake, and increase
in physical activity in Hispanics/Latinos and non-Hispanic
Received July 2, 2015; final revision received July 31, 2015; accepted August 10, 2015.
From the Department of Neurology, Stroke Program, University of Michigan, Ann Arbor (D.L.B., E.S., J.M., L.E.S., L.D.L., L.B.M.); Program of
Health Education, School of Health Promotion and Human Performance, Eastern Michigan University, Ypsilanti (K.M.C., J.E.C.); and Departments of
Biostatistics (B.N.S.), Health Behavior and Health Education (K.R.), and Epidemiology (L.D.L., L.B.M.), University of Michigan School of Public Health,
Ann Arbor.
The online-only Data Supplement is available with this article at http://stroke.ahajournals.org/lookup/suppl/doi:10.1161/STROKEAHA.115.010678/-/DC1.
Correspondence to Devin L. Brown, MD, MS, University of Michigan, 1500 E Medical Center Dr, Ann Arbor, MI 48109. E-mail [email protected]
© 2015 American Heart Association, Inc.
Stroke is available at http://stroke.ahajournals.org
DOI: 10.1161/STROKEAHA.115.010678
2861
2862 Stroke October 2015
whites in a biethnic community. Cluster randomization on the
parish level allowed us to encourage social and environmental
change in the parishes and decreased the risk of contamination
of controls by intervention subjects. We report here the main
results of this National Institutes of Health–funded trial.
Methods
Overview
SHARE was a National Institutes of Health–funded, peer-reviewed,
cluster-randomized, church-based primary prevention trial that targeted key behavioral stroke risk factors. Details about the design of
SHARE have been previously published,9 and additional details are
found in the online-only Data Supplement. Briefly, friend or family
member pairs were enrolled (2011–2012) from 10 Catholic parishes
within the Diocese of Corpus Christi, Texas, that were randomized
to either the intervention or control group. This community consists
mainly of non-Hispanic whites and Hispanics/Latinos. The Hispanics/
Latinos, almost all of whom (96%) are US citizens, are predominantly Mexican American and are for the most part nonimmigrant.10
The intervention group received a 1-year multicomponent intervention at the individual level, including culturally sensitive self-help
materials (healthy eating guide, physical activity guide with pedometer, motivational short film, and photo novella about BP control),
≤5 motivational interviewing calls, 2 tailored newsletters, and an ≈2hour workshop designed to teach pairs to provide each other with
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Figure 1. Consolidated Standards of Reporting Trials (CONSORT) flow diagram. *Many subjects who did not participate in the 6 month
assessment did participate in the 12 month assessment.
Brown et al SHARE Trial Results 2863
Table 1. Baseline Characteristics of Study Sample (N=760) by Treatment Group
Treatment (N=411)
Control (N=349)
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Demographics, N (%) unless noted
Age, median (IQR)
53 (44, 65)
51 (43, 63)
Female
256 (62.3)
229 (65.6)
Married or living together
310 (75.4)
233 (66.8)
Education
<HS
51 (12.4)
50 (14.3)
HS
119 (29.0)
101 (28.9)
Some college
154 (37.5)
116 (33.2)
College or more
87 (21.2)
82 (23.5)
Ethnicity
Non-Hispanic white
69 (16.8)
50 (14.3)
Hispanic/Latino
339 (82.5)
297 (85.1)
3 (0.7)
2 (0.6)
Refused
Income ≥$30K
195 (47.4)
162 (46.4)
335 (81.5)
288 (82.5)
Has health insurance
Current employment status
Full time
207 (50.5)
185 (53.0)
Part time
44 (10.7)
34 (9.7)
Not employed
159 (38.8)
130 (37.2)
PHQ-2 screen, median (IQR)
0 (0, 2)
0 (0, 2)
Eat fast food
Never
63 (15.3)
56 (16.0)
<1 per week
54 (13.1)
51 (14.6)
173 (42.1)
157 (45.0)
1–2 per week
3–4 per week
88 (21.4)
57 (16.3)
≥5 per week
33 (8.0)
28 (8.0)
Cardiovascular risk factors, n yes (%)
Atrial fibrillation
24 (5.8)
19 (5.4)
Congestive heart failure
12 (2.9)
6 (1.7)
Coronary artery disease
23 (5.6)
14 (4.0)
Diabetes mellitus
103 (25.1)
69 (19.8)
Heart attack
18 (4.4)
10 (2.9)
Hypertension
198 (48.2)
157 (45.0)
Sleep apnea
52 (12.7)
30 (8.6)
Stroke or TIA
22 (5.4)
15 (4.3)
Current smoking
31 (7.5)
32 (9.2)
Biological or measured exploratory outcomes, median (IQR) unless noted
Weight, kg
85.1 (72.1, 100.7)
81.0 (68.6, 97.5)
Height, m
1.63 (1.56, 1.70)
1.61 (1.56, 1.69)
Body mass index
31.8 (27.8, 36.4)
30.5 (26.9, 36.3)
Waist circumference, cm
105.0 (95.5, 115.0)
103.0 (94.0, 115.0)
Total cholesterol, mg/dL
187 (162, 212)
180 (160, 212)
HDL, mg/dL
50 (42, 61)
52 (44, 60)
LDL, mg/dL
107 (87, 128)
102 (83, 127)
Non-HDLChol, mg/dL
135 (108, 161)
128 (104, 156)
Triglycerides, mg/dL
121 (88, 172)
119 (87, 158)
Fasting glucose, mg/dL
96 (88, 110)
94 (87, 106)
HbA1C, %
5.9 (5.6, 6.3)
5.8 (5.6, 6.2)
Blood pressure category, N (%)
Normal
142 (34.6)
119 (34.1)
Prehypertension
158 (38.5)
142 (40.7)
Stage I
82 (20.0)
72 (20.6)
Stage II
28 (6.8)
16 (4.6)
HDL indicates high-density lipoprotein; HDLChol, high-density lipoprotein cholesterol; IQR, interquartile range; LDL,
low-density lipoprotein; PHQ, patient health questionnaire; and TIA, transient ischemic attack.
2864 Stroke October 2015
Table 2. Baseline Measures, Change From Baseline, and Treatment Effect for the Primary and Secondary Outcomes
Treatment (n=411)
Outcome
Baseline, mean
(SEM)
Change From Baseline
(95% CI)
Control (n=349)
Baseline, mean
(SEM)
Change From Baseline
(95% CI)
Treatment Difference
in Change From
Baseline (95% CI)
P Value
Adjusted P
Value*
Fruit+vegetable, cups per day
2.62 (0.09)
0.11 (−0.00, 0.23)
2.51 (0.10)
−0.14 (−0.26, −0.01)
0.25 (0.08, 0.42)
0.002
0.002
Sodium, mg per day
3137 (76)
−278 (−355, −201)
2988 (83)
−155 (−232, −78)
−123 (−195, −52)
0.04
0.12
MET, minutes per week†
2717 (300)
−163 (−517, 192)
3001 (310)
−135 (−497, 227)
−27 (−526, 471)
0.56
0.72
SBP, mm Hg
125.9 (1.3)
−0.38 (−3.23, 2.47)
125.2 (1.3)
−0.08 (−2.90, 2.74)
−0.30 (−3.81, 3.21)
0.86
0.60
DBP, mm Hg
79.1 (0.9)
−0.98 (−2.00, 0.03)
79.3 (0.9)
0.04 (−0.98, 1.07)
−1.03 (−2.46, 0.40)
0.16
0.17
CI indicates confidence interval; DBP, diastolic blood pressure; MET, metabolic equivalent; and SBP, systolic blood pressure.
*Adjusted for age, sex, and ethnicity. Self-reported outcomes also adjusted for social desirability.
†Of moderate or higher intensity.
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autonomy supportive counseling.9 Materials included relevant biblical quotations and prayers to provide religious relevance and motivation. Motivational interviewing calls were conducted by personnel
trained in motivational interviewing and the SHARE intervention.9
On the cluster level, environmental and social changes at parishes
were also promoted through encouragement of availability of low-sodium foods and fruits and vegetables at parish functions and programs
to encourage healthy cooking and physical activity. The control subjects received skin cancer awareness materials or sunblock at 3 and
9 months to maintain contact every 3 months, including assessments.
They also received holiday cards. The project was approved by the
University of Michigan Institutional Review Board. Written informed
consent was obtained from each individual subject. The trial was registered on clinicaltrials.gov (NCT01378780).
Eligibility
Subjects were eligible if they were Hispanic/Latinos or non-Hispanic
white parishioners of a participating parish, were aged ≥18 years,
spoke English or Spanish, were permanent residents of the Corpus
Christi area, and were able to identify a partner with whom to enroll
(this was relaxed toward the end of the study where the study team
helped facilitate pairs on a few occasions). Known pregnancy was
exclusionary.
Assessments
Home visits, conducted in English or Spanish, with computer-assisted interviews, were used to obtain baseline and 12-month followup data. Six-month outcomes were assessed typically by phone. At
all 3 time points, assessments included (1) the Block 2005 Food
Frequency Questionnaire, a widely used questionnaire that has been
validated in Hispanics/Latinos and non-Hispanic whites,11–13 modified for a 6-month reference period and to include foods often eaten
by Hispanic/Latino populations, and (2) the modified Stanford 7-day
Physical Activity Recall Instrument, which assesses vigorous and
moderate activity levels from work and leisure-time activities14 and
A
has been validated against biological measures and used in Hispanics/
Latinos and non-Hispanic whites.15,16 At baseline and 12 months,
the following assessments were also made in both groups: (1) BP
(the average of the last 2 of 3 measures) using an automated device
(OMRON-HEM-780) and usual techniques,17 (2) fasting blood draw
for a lipid panel, glucose, and glycosylated hemoglobin, (3) height
and weight, (4) waist circumference, and (5) BP medication adherence question (“How often in a typical week have you missed a prescribed dose of your BP medicine or medicines?” assessed with a
5-point response scale ranging from “never” to “very often”),18 and
(6) Self-Determination Theory measures were assessed as exploratory
outcomes and for tailoring purposes and included modified versions
of the Health-Care Climate Questionnaire19 (modified to refer to support from an “important other”), Perceived Competence Scale,19 and
Treatment Self-Regulation Questionnaire (modified to refer to the
3 specific primary outcome measures)19 and a relatedness questionnaire.20 At baseline, the Marlowe–Crowne Social Desirability scale,
a 10-item tool to assess for social desirability response bias, was also
administered.21 As a persistence test of the primary outcomes, the
Block and Stanford questionnaires were also administered by phone
to only the intervention group at 18 months.
Outcomes
Three prespecified coprimary outcomes were dietary sodium, dietary fruit and vegetable intake, and moderate or greater physical
activity. The intervention was determined a priori to be deemed successful (primary end point) if at least one of these outcomes was
significant at a level of 0.05/3 to correct for multiple testing. The
secondary outcome was systolic BP. Biological exploratory outcomes were diastolic BP, low-density lipoprotein, high-density lipoprotein, triglycerides, glucose, glycosylated hemoglobin, body
mass index; behavioral exploratory outcomes were total dietary fat,
saturated fat, BP medication adherence, and measures of the theory-related intermediate outcomes: the Treatment Self-Regulation
Questionnaire, Perceived Competence Scale, and Health-Care
Climate Questionnaire.19
B
Figure 2. Average sodium (A) and fruit and vegetable (B) intake by treatment group and visit. Note
that y-axis does not start at 0.
Brown et al SHARE Trial Results 2865
Table 3. Percent of Participants Who Recall or Used
Intervention Components Among Those Who Responded to
Process Evaluation Questionnaire (n=314)
Variable
%
Individual-level process
Used healthy eating guide
80.0
Used exercise guide
54.5
Watched short film
23.3
Read photo novella
32.5
Recalls receiving MI Calls
0
23.2
1–3
54.1
4–5
22.6
Number of MI calls completed
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0
26.1
1–3
63.7
4–5
10.2
Tailored newsletters
Did not recall receiving any
25.2
Did not read any of received
11.8
Read 1
20.4
Read 2
42.7
Pair-level process
Talked with partner about SHARE goals
≥2 per week
35.5
1 per week to 1 per mo
42.2
<1 per month
22.4
Exercised with partner
≥2 per week
26.8
1 per week to 1per mo
24.3
<1 per month
48.9
Cooked with partner
≥2 per week
49.8
1 per week to 1 per mo
21.4
<1 per month
28.8
Church-level process
Workshop*
Recalls attending
34.4
Did not attend but used mailed workbook
15.0
Attendance recorded
38.5
Recalls parish activities*
None
31.8
Activities supportive of exercise
64.3
Activities supportive of healthy diet
33.4
Both types of activities
29.6
MI indicates myocardial infarction; and SHARE, Stroke Health and Risk
Education.
*Not exclusive categories, do not add to 100.
Statistical Analysis
Details are found in the online-only Data Supplement. We calculated
that 5 churches in each group with an average of 40 pairs each (ie, 800
subjects total) would need to be randomized to detect the projected
differences in change in at least one of the primary outcomes.
Repeated measures models for longitudinal data22 were used to
assess treatment differences in change from baseline for all outcomes
by testing a time by treatment interaction term in a model that included ≤3 observed measures per participant (baseline, 6 month,
and 12 month). This approach enabled us to conduct an intentionto-treat analysis where all observed data were incorporated in the
model fitting under the assumption that missing data from subjects
who dropped out were missing at random. Specifically, the approach
compared the average of the difference between baseline and 6- and
12-month follow-up data when both were available and the difference between baseline and 6- or 12-month follow-up when only one
follow-up measure was available. Those few with only baseline data
were also included in the models using maximum likelihood estimates.22,23 Adjusted analyses were also performed accounting for age,
sex, ethnicity, education, and, for the behavioral outcomes, social
desirability to response bias (Marlowe–Crowne Social Desirability
scale) given that subjects were not blind to treatment condition and
because these factors may explain variance in the outcomes and thus
increase power. Standard procedures were used to eliminate dietary
records that appeared invalid24 and to eliminate outliers for individual
measures. Finally, to examine persistence of behavior changes, we
incorporated data from the 18-month visit among the treatment group
and used data from all visits in both treatment groups within multilevel models to estimate the average of each outcome by treatment
group for each visit. SAS version 9.3 was used for all data analyses.
Results
Of the 801 people consented, 760 (95%) were randomized and
underwent a baseline assessment. Of these, 653 (86%) completed at least one outcome assessment; 28 (3.7%) completed
only the 6-month assessment, 196 (25.8%) completed only the
12-month visit, and 428 (56.3%) completed both the 6- and
12-month assessments. Overall, those who did not complete
either the 6- or the 12-month assessments were similar to the
completers but tended to be a little younger (see Table I in the
online-only Data Supplement). The Consolidated Standards of
Reporting Trials (CONSORT) flow diagram is given in Figure 1.
Baseline characteristics of the intervention and control group
are presented in Table 1; no differences by treatment group were
found (P>0.05 for all). Median age was 53 years (interquartile
range: 44, 64). The majority of subjects were female (64%) and,
by self-report, Hispanic/Latino (84%). Partners were most commonly spouses (56%) followed by a friend (19%), a blood relative (18%), or a study-provided partner (6%).
For the primary outcomes, change from baseline to followup was greater for fruit and vegetable intake (0.25 cups per day
[95% confidence interval (CI): 0.08, 0.42], P=0.002) and sodium
intake (−123 mg/d (95% CI: −195, −52), P=0.04) in the intervention than in the control group. No treatment effect was identified
for moderate- or greater-intensity physical activity (27 metabolic
equivalent–minutes per week [95% CI: −526, 471]; Table 2). In
the intervention group, the intake of fruits and vegetables and
sodium at 18 months was similar to that in the 12-month data
(Figure 2), in support of persistence of a treatment effect.
No treatment effect was identified for the secondary outcome—systolic BP (Table 2). Of the biological exploratory
outcomes, total dietary fat and saturated fat decreased in the
treatment group more than in the control group (Table II in
the online-only Data Supplement). These results were borderline significant in unadjusted analysis and significant (P<0.05)
after adjustment for age, sex, education, and social desirability. No treatment effect was found related to weight, waist circumference, glucose, HbA1C, or lipid panel results (Tables
2866 Stroke October 2015
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II and III in the online-only Data Supplement). Similarly, no
treatment effect was found with respect to medication adherence in those taking BP medications at baseline (Table III in
the online-only Data Supplement). Intra-cluster correlations
for the primary outcomes are reported in Table IV in the
online-only Data Supplement. Within church and pair, intracluster correlations were <0.05.
Although the vast majority of the self-determination theory–related exploratory outcomes had more favorable changes
supportive of behavior change among the treatment group,
only the changes in perceived competence to eat more fruits
and vegetables (change from baseline 0.21 [95% CI: 0.05,
0.37] on a 7-point scale, P=0.01) and lack of motivation for
dietary change (−0.29 [95% CI: −0.52, −0.05] on a 7-point
scale, P=0.02; amotivation subscale of the Treatment SelfRegulation Questionnaire) were statistically significant.
Table 3 presents information about the use of the intervention components by the intervention subjects. Most subjects
completed at least one motivational interviewing call (74%)
and, based on self-report, read one or both newsletters (63%),
used the healthy eating guide (80%), and used the exercise
guide (55%). Among the intervention participants, adjusted
for age, sex, social desirability, ethnicity, and education, there
was no association between the participants recalling that their
parish had an activity supportive of a healthy diet or exercise
and the 3 primary outcomes.
Discussion
This large cluster-randomized trial showed that this multicomponent behavioral intervention was effective in increasing
fruit and vegetable intake among Hispanic/Latino and nonHispanic white Catholic parishioners. The trial successfully
reached its primary end point. The intervention also seemed
to lower sodium intake (P=0.04), despite missing its statistical
threshold. Despite the positive effect on fruit and vegetable
intake, inspection of the differences by group through time
suggests little increase in the intervention group and a decline
in the control group. Thus, some of the effects may have been
staving off a decline in fruit and vegetable intake. In support
of a true intervention effect is the increase in perceived competence to eat fruits and vegetables and increased motivation
for eating a healthy diet—intermediate outcome measures.
Although the estimated magnitude of the difference in fruit
and vegetable intake was modest, observing a treatment difference is promising and is in keeping with modest effects seen
in other church-based interventions based on self-determination theory.6,7 Similarly, the magnitude of sodium reduction
although small was also encouraging. Although the importance of a lower sodium diet has come into question, the most
recent evidence continues to support the benefits of a lower
sodium diet on stroke risk factors.25,26 Furthermore, although
the primary benefits were identified at the conclusion of the
intervention, persistence testing suggested that the improvements in both dietary measures likely lasted at least another 6
months. This, in conjunction with evidence of change in the
self-determination theory constructs (perceived competence
and motivation) known to impact healthy behavioral choices,
is encouraging for long-term benefits of this intervention.
The intervention showed no effect on the third coprimary outcome—physical activity. However, physical activity
among the subjects of this trial at baseline was much higher
than would have been expected based on national data,27 raising the possibility of a ceiling effect.
The most clinically significant biological marker of stroke
risk, BP, was not affected by the intervention, although we lacked
power to detect this association; hence, systolic and diastolic
BPs were secondary and exploratory outcomes. Furthermore,
baseline BPs were relatively low, and our intervention was only
moderate in intensity, particularly for BP. However, 4 MI sessions in a year that targeted medication adherence have been
shown to reduce systolic BP among hypertensive African
Americans28 and 5 calls targeting lifestyle change have also
been shown to reduce BP in treated hypertensive patients.29
To our knowledge, this trial represents the first churchbased behavioral intervention efficacy trial to target multiple
stroke risk behaviors in Hispanics/Latinos, a growing and
aging minority group. Although the intervention was sensitive
to Hispanic/Latino culture, it was also designed to be sensitive to non-Hispanic whites to improve the generalizability of
the intervention and ability to disseminate the program within
churches more broadly.
Limitations to this study exist. The primary outcomes were
self-reported measures and, thus, subject to measurement error
and response bias, given the inability to mask the intervention.
We did, however, account for social desirability response bias
with the use of the Marlowe–Crowne scale.21,30 Outcomes assessors were also not masked. We also used a food frequency questionnaire rather than a 24-hour dietary recall or urinary sodium
measures because of greater feasibility of the food frequency
questionnaires, especially given our large sample. We did not
validate the dietary or physical activity measures against biological measures in this population, although they have been previously validated.15,31,32 Although seasonal variability in dietary
and physical activity habits can influence behaviors, our 1-year
time frame should have mitigated against this. Overall, engagement in the intervention by subjects was less than anticipated.
Although motivational interviewing has been shown to be effective,33,34 we found reaching subjects by phone to be challenging.
Many subjects did not participate in the 6-month assessment,
although most (82%) completed the 12-month assessment.
Conclusions
This rigorously developed and tested behavioral intervention
intended to reduce stroke risk factors showed that a Catholic
Church–based intervention can successfully recruit Hispanics/
Latinos and can improve health behaviors in a predominantly
Hispanic/Latino population. Stroke-related health promotion
interventions that target Hispanics/Latinos are needed. Given
the complexity of the intervention and modest effect sizes, suggesting that this particular intervention may not be reasonable to
disseminate, additional research is needed to identify behavioral
interventions that are potent yet practical to implement widely.
Acknowledgments
We are grateful to the Stroke Health and Risk Education (SHARE)
Community Advisory Board and the Diocese of Corpus Christi for
their partnership.
Brown et al SHARE Trial Results 2867
Sources of Funding
This project was supported by the National Institutes of Health
(R01NS062675 and R01NS062675-S; multiple PIs: Morgenstern/
Brown). The research reported in this publication was also supported in part by the National Center for Advancing Translational
Sciences of the National Institutes of Health under Award Number
UL1TR000433. The content is solely the responsibility of the authors
and does not necessarily represent the official views of the National
Institutes of Health.
Disclosures
None.
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doi: 10.1016/j.cct.2012.02.020.
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2005;55:305–312.
A Multicomponent Behavioral Intervention to Reduce Stroke Risk Factor Behaviors: The
Stroke Health and Risk Education Cluster-Randomized Controlled Trial
Devin L. Brown, Kathleen M. Conley, Brisa N. Sánchez, Kenneth Resnicow, Joan E. Cowdery,
Emma Sais, Jillian Murphy, Lesli E. Skolarus, Lynda D. Lisabeth and Lewis B. Morgenstern
Downloaded from http://stroke.ahajournals.org/ by guest on June 14, 2017
Stroke. 2015;46:2861-2867; originally published online September 15, 2015;
doi: 10.1161/STROKEAHA.115.010678
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1
SUPPLEMENTAL MATERIAL
Supplemental Methods
Assessments
The Block Food Frequency Questionnaire included pictures of portion sizes (1/4, 1/2, 1, 2 cups of food
visualized on plates and bowls) to help facilitate and standardize subject responses.
Intervention Development
The intervention was designed based on Self-Determination Theory, which holds that behavior change is more
likely to occur when three basic needs are met: autonomy, competence, and relatedness. Further, behavior
change decisions driven by autonomous motivation (e.g., that support volition and are linked to personal
meaning) are more enduring than those driven by controlled motivation (e.g., pressure from external others,
guilt, shame, or extrinsic rewards).1, 2 All intervention components in SHARE were designed to meet these
three basic needs and support autonomous motivation. Subjects were enrolled in friend or family member pairs
to capitalize on the natural support inherent to these relationships (relatedness). Each member of the pair
participated in the study individually, and was also expected to provide support to his/her partner. A
Community Advisory Board of Priests and other Catholic leaders within the community provided guidance on
intervention material development to assure cultural, local, and religious relevance and appropriateness.
Motivational interviewing, which is based on principles of SDT, was used to further enhance autonomous
motivation.3, 4 More details about the development of the intervention are found in a previously published
methods paper.5
Recruitment
Recruitment was staggered across churches with the first participant consented on 5/31/11 and the last on
11/28/12. Subjects were recruited by local study team personnel. The project was advertised through church
bulletins, announcements from the pulpit, and through parish liaisons, lay leaders from the church who were
paid to facilitate recruitment. Health fairs were conducted to initiate each parish’s involvement.
Intervention
Motivational interviewing (MI) topics included discussing BP with the subjects’ physician, BP medication
adherence, eating more fruits and vegetables and less sodium, and increasing physical activity. Although the
optimal “dose” of MI is unknown, most studies have used from 1-6 MI sessions;6 while participants describe a
preference for contact 3-4 times per year.7 Tailored newsletter topics included BP medication adherence, diet,
physical activity, and encouragement to provide autonomy support to the SHARE partner.5 Environmental and
social change within the parishes were also promoted through program Parish Health Committees. These
committees were asked to assure that low sodium and fruits and vegetables were available at parish functions
that included food, and to organize group activities related to cooking or physical activity that promote the
SHARE goals. Four of the five intervention churches established such a committee, and two of these
committees were quite active, implementing multiple programs through the year.
Sample size calculations and randomization
We calculated that 5 churches in each group with an average of 40 pairs each (i.e. 800 subjects total) would
need to be randomized to detect the projected differences in change in at least one of the primary outcomes
(548mg8 in sodium intake, 1.5 cups9 of fruits and vegetable consumption, and 0.86kcal/kg/day10 of moderate or
vigorous exercise) with a fixed significance level of 0.05/3, power of 80% (for physical activity and >80% for the
other two outcome), and accounting for 20% dropout, after assessing a range of plausible ICCs11 (0.001,
0.005, 0.01). To place daily cups of fruits and vegetables into context, the typical women over 50 is
recommended to eat 4 total cups of fruits and vegetables.12, 13 Parishes were randomized in a two-step process
by the study statistician using the “sample()” function in R (http://www.R-project.org). Of the 36 parishes in the
Corpus Christi area, 10 were randomly selected to participate, and those participating were then randomized to
treatment assignment. Stratified randomization was used (4 strata based on size (number of families
registered) and income of the parish neighborhood). Parishes were offered participation by local study team
personnel.
2
Analysis
Dietary data were cleaned according to available guidelines.14 Briefly, entire dietary records at a given visit
were excluded if the estimated calories were outside the range 600-3500 for women or 800-4200 for men.
From the remaining records, log transformed values for a given nutrient (distributions were skewed) that were
above the third quartile plus 1.5 the interquartile range (IQR), or below the first quartile minus 1.5 IQR, were
considered invalid and set to missing. Physical activity reports at a given visit were considered invalid and set
to missing if the person reported values outside the 13230-46620 range of METs of total activity (this range
excludes values more extreme than the following: 7 days of sleeping 9 hours each night and light activity for
the remaining 15 hours per day; 7 days of sleeping 6 hours each night, an 8-hour job entailing heavy labor
every day of the week, followed by 4 hours of housework (unlikely)). Bivariate scatterplots among related
variables (e.g., BMI change and waist circumference change) were used to conduct additional data cleaning
and identify implausible values. Values above (below) the top (and bottom) 1% of the distribution of change
from baseline for all outcomes were identified and excluded from primary analyses to minimize their impact on
estimation of variance components (e.g., artificially deflate ICC due to higher residual variance induced by
potential outliers).
Differences in participant characteristics and dropout by treatment group were assessed, while accounting for
clustering of participants within pairs and parishes using multilevel regression as appropriate (see
Supplemental Table I). The time variable was coded as 0 for the baseline visit and 1 for either the 6 or 12
month visit. Hence, the interaction term yielded an estimate of the average of two measures of change: 6
month vs. baseline and 12 month vs baseline. Since the main effect of treatment captured the differences
between groups at baseline, and these can be assumed to be zero in randomized trials, the main effect of
treatment was excluded from the model. Further, it is well known that excluding the main effect of treatment
from the model gives the same results as the classic analysis of covariance when there is no dropout.15
Estimates of differences in change from baseline associated with treatment assignment were obtained using
mixed effects models to account for clustering of observations within individual, individuals within pairs and
pairs within churches. In these models, all available measures (up to three per participant) were considered as
the dependent variable, as previously described.5 First, the correlation structure among repeated observations
was selected using AIC criteria.15 The correlation structures considered included ten different combinations of
random intercepts or random intercept and slopes at the three levels (participant, pair, church). When
intercepts and slopes were both specified, the random effects could have an unrestricted correlation structure
or a variance components structure. If the higher level of the hierarchy (e.g., church) had a more complex
structure (e.g., correlated intercept and slope), then all lower levels also had that structure. This assumes that
if a complex structure is needed at the highest level, then it would most likely also be needed at the lower
levels.
Next, given the chosen covariance structure, the treatment difference in pre-post change was estimated by
fitting a model that included a time indicator variable, which denotes if a given observation was taken at
baseline (zero) or at either the 6 or 12 month visits (one), and the interaction between an intervention indicator
variable (treatment=0 for control and 1 for intervention) and the time indicator. This approach to coding the
time indicator effectively compares the average of the difference between 6 and 12 month visits and the
baseline measure. Adjustment of the change since baseline by the baseline value was achieved by excluding
the treatment indicator from the model.15 In the estimated model (time and time*treatment), the coefficient of
the time indicator is interpreted as the estimated change from baseline for controls; the interaction coefficient
is the treatment difference in the change from baseline comparing intervention to control groups; and the sum
of the coefficients is the estimated change from baseline for the intervention group. The Kenward-Roger
method for calculating degrees of freedom of the test statistics was used.
Valid p-values for all dietary outcomes were obtained from models using log-transformed outcomes, given
residual diagnostics indicated deviations from normality; however, changes from baseline are reported in
natural units to aid interpretation. Similarly, the estimates of absolute change in physical activity are reported
even though modeling approaches that better account for the highly skewed distribution of physical activity
were also examined and did not yield substantively different results. Moderate to vigorous physical activity
exhibited a zero inflated log-normal distribution with 8.6% of participants reporting no moderate or more
3
intense activity. Two-stage models first testing initiation/cessation of moderate or higher activity and then
testing percent changes in the level of activity among those reporting activity were estimated.
For descriptive purposes and to aid in future trials designed using participant pairs, the within-church, withinpair, and within-participant intra-cluster correlations (ICCs) for the measures of change from baseline were
calculated using multilevel models where the dependent variables were the computed differences from
baseline.
4
Supplemental Table I: Baseline characteristics by drop-out status.
All enrolled (N=760)
Completed at least
one outcome
assessment
Dropout (completed
no outcome
assessments)
Demographics, N (%) unless noted
N=653
N=107
Age, median (Q1, Q3)
54 (45, 65)
49 (40, 58)
Female
423 (64.8)
62 (57.9)
Married or living together
467 (71.5)
76 (71.0)
Education
<HS
87 (13.3)
14 (13.1)
HS
182 (27.9)
38 (35.5)
Some College or Tra
234 (35.8)
36 (33.6)
College or more
150 (23.0)
19 (17.8)
Ethnicity
NHW
107 (16.4)
12 (11.2)
MA
541 (82.8)
95 (88.8)
Refused
5 (0.8)
0 (0.0)
Income ≥30K
307 (47.0)
50 (46.7)
Has Health Insurance
547 (83.8)
76 (71.0)
CurEmploymentStatus
Full time
332 (50.9)
60 (56.1)
Part time
63 (9.7)
15 (14.0)
Not employed
257 (39.4)
32 (29.9)
PHQ screen, median (Q1, Q3)
0 (0, 1)
0 (0, 2)
Eat fast food
Never
94 (14.4)
25 (23.4)
<1/week
92 (14.1)
13 (12.1)
1-2/week
290 (44.4)
40 (37.4)
3-4/week
123 (18.8)
22 (20.6)
5 or more/week
54 (8.3)
7 (6.5)
Stroke risk factors, N yes (%)
Atrial fibrillation
37 (5.7)
6 (5.6)
Congestive Heart Failure
17 (2.6)
1 (0.9)
Coronary Artery Disease
35 (5.4)
2 (1.9)
Diabetes
148 (22.7)
24 (22.4)
Heart Attack
25 (3.8)
3 (2.8)
Hypertension
312 (47.8)
43 (40.2)
Sleep Apnea
73 (11.2)
9 (8.4)
Stroke or TIA
32 (4.9)
5 (4.7)
Biological or measured exploratory outcomes, median (Q1, Q3) unless noted
Weight (kg)
82.6 (70.1, 98.6)
79.6 (68.5, 100.4)
Height (meters)
1.63 (1.56, 1.69)
1.63 (1.56, 1.70)
BMI
31.38 (27.33, 36.10) 30.56 (26.82, 34.77)
Waist circumference (cm)
104 (95, 115)
103 (94, 112)
5
Total Cholesterol (mg/dL)
HDL (mg/dL)
LDL (mg/dL)
Triglycerides (mg/dL)
FastingGlucose (mg/dL)
HbA1C (%)
Blood pressure category, N (%)
Normal
Prehypertension
Stage I
Stage II
183 (161, 211)
52 (44, 62)
104 (84, 128)
119 (87, 161)
95 (88, 108)
5.9 (5.6, 6.2)
190 (166, 219)
49 (40, 57)
110 (91, 134)
121 (91, 177)
96 (88, 108)
5.9 (5.5, 6.3)
220 (33.7)
270 (41.3)
126 (19.3)
37 (5.7)
36 (33.6)
35 (32.7)
23 (21.5)
13 (12.1)
6
Supplemental Table II: Baseline measures, change from baseline, and treatment effect for the
continuous biological and dietary exploratory outcomes.
Among control
Among treated
Baseline, mean Change from
(StdErr of mean) baseline, (95%CI)
Baseline, mean Change from
(StdErr of mean) baseline, (95%CI)
Treatment
Difference in
change from
baseline, (95%CI) pvalue
pvalue after
adjustment*
Diet
Total fat, g/day
Saturated fat, g/day
Measured/biological
HBA1c (%)
Triglycerides (mg/dL)
BMI, kg/m2
Fasting Glucose (mg/dL)
HDL (mg/dL)
LDL (mg/dL)
Waist circumference (cm)
Weight (lbs)
91.2 (3.1) -11.54 (-14.26, -8.83)
26.8 (0.8) -3.65 (-4.71, -2.59)
85.3 (3.3)-7.90 (-10.73, -5.08)
25.1 (0.8) -2.28 (-3.37, -1.18)
-3.64 (-6.72, -0.55)
-1.38 (-2.86, 0.11)
0.051
0.050
0.049
0.036
6.3 (0.1) -0.04 (-0.11, 0.02)
147.1 (5.5) -5.98 (-12.21, 0.25)
6.2 (0.1) -0.04 (-0.11, 0.03)
133.7 (5.8) -5.89 (-12.20, 0.42)
-0.00 (-0.09, 0.09)
-0.09 (-8.85, 8.67)
0.93
0.93
>0.05
>0.05
32.8 (0.4)
106.8 (3.6)
52.3 (1.0)
109.2 (2.1)
106.6 (1.0)
193.9 (3.4)
32.4 (0.5) -0.09 (-0.28, 0.10)
105.1 (3.7) 0.73 (-2.61, 4.08)
53.3 (1.0)
0.90 (0.03, 1.78)
105.4 (2.2) 0.33 (-2.23, 2.88)
106.0 (1.1) -0.06 (-0.89, 0.77)
189.1 (3.5) -0.59 (-1.69, 0.51)
-0.07 (-0.33, 0.19)
1.28 (-3.42, 5.98)
-0.02 (-1.23, 1.20)
-1.09 (-4.65, 2.48)
0.71 (-0.46, 1.88)
-0.42 (-1.96, 1.13)
0.61
0.57
0.98
0.55
0.23
0.60
>0.05
>0.05
>0.05
>0.05
>0.05
>0.05
-0.16 (-0.34, 0.03)
2.02 (-1.35, 5.38)
0.89 (0.03, 1.74)
-0.76 (-3.31, 1.79)
0.65 (-0.17, 1.47)
-1.01 (-2.10, 0.09)
*Adjusted for age, sex, ethnicity, education (and for dietary outcomes, social desirability).
7
Supplemental Table III: Baseline and 12 month measures, odds of change from baseline, and treatment
effect for the categorical biological exploratory outcomes.
Treatment
Baseline, n
(%)
BP Med Adherence** Yes
No
Normal
Blood pressure
Prehypertension
Stage I
Stage II
Waist circumference Normal
Elevated
Normal*
BMI
Overweight
Obese
HbA1c
Normal
Pre Diabetes
Diabetes
Normal
Fasting glucose
Pre-diabetes
Diabetes
162 (92.6)
13 (7.4)
142 (34.6)
158 (38.5)
82 (20.0)
28 (6.8)
97 (23.6)
314 (76.4)
49 (11.9)
107 (26.0)
255 (62.0)
117 (29.3)
197 (49.3)
86 (21.5)
241 (60.3)
102 (25.5)
57 (14.3)
OR of
improvement,
12 mo, n comparing 12mo. to
baseline, 95%CI
(%)
130 (96.3) 1.73 (0.66, 4.56)
5 (3.7)
112 (35.7) 1.12 (0.73, 1.71)
122 (38.9)
61 (19.4)
19 (6.1)
59 (18.8)
254 (81.2)
33 (10.5)
92 (29.4)
188 (60.1)
84 (28.0)
158 (52.7)
58 (19.3)
169 (56.3)
84 (28.0)
47 (15.7)
0.19 (0.06, 0.63)
1.68 (0.77, 3.67)
1.31 (0.76, 2.25)
0.69 (0.45, 1.06)
Control
Baseline, n
(%)
123 (95.3)
5 (4.7)
119 (34.1)
142 (40.7)
72 (20.6)
16 (4.6)
89 (25.5)
260 (74.5)
49 (14.1)
116 (33.2)
184 (52.7)
110 (32.1)
163 (47.5)
70 (20.4)
218 (63.6)
81 (23.6)
44 (12.8)
12 mo, n
(%)
122 (96.8)
4 (3.2)
99 (32.0)
120 (38.8)
67 (21.7)
23 (7.4)
71 (23.1)
237 (76.9)
43 (14.0)
103 (33.4)
162 (52.6)
107 (36.6)
135 (46.2)
50 (17.1)
189 (64.3)
69 (23.5)
36 (12.2)
OR of
improvement,
comparing 12mo. to Treatment odds
baseline, 95%CI
ratio, (95%CI)
pvalue
pvalue after
adjustment*
2.03 (0.71, 5.81)
0.85 (0.22, 3.25)
0.81
NA
0.91 (0.66, 1.25)
1.11 (0.72, 1.71)
0.61
0.53
1.10 (0.44, 2.78)
0.17 (0.04, 0.76)
0.02
0.036
1.18 (0.53, 2.63)
1.42 (0.49, 4.10)
0.515
0.327
2.39 (1.34, 4.28)
0.55 (0.25, 1.18)
0.123
0.109
1.25 (0.80, 1.94)
0.56 (0.31, 1.01)
0.055
0.144
* Adjusted for age, sex, ethnicity, education.
**only adjusts for within person clustering due to low number of non-adherents; sample size includes only
those who have at least one BP medication prescription
***includes 3 (treatment) and 1 (control) who were underweight at baseline
NA: Not applicable because could not fit model (numbers too low).
8
Supplemental Table IV: Within church, within enrollment pair, and within participant (longitudinal)
intra-cluster correlations (ICC) for the natural log of each primary outcome measure.
Outcome
Dietary sodium
Dietary fruits and vegetables
Moderate and greater intensity activity
ICCChurch
0.005
<0.001
0.001
ICCPair
0.035
0.009
0.042
ICCParticipant
0.410
0.447
0.243
9
Supplemental References
(1) Markland D, Ryan RM, Tobin VJ, Rollnick S. Motivational Interviewing and Self-Determination Theory. J
Soc Clin Psychol 2005;24:811-31.
(2) Ryan RM, Deci EL. Self-determination theory and the facilitation of intrinsic motivation, social
development, and well-being. Am Psychol 2000;55:68-78.
(3) Resnicow K, McMaster F. Motivational Interviewing: moving from why to how with autonomy support.
Int J Behav Nutr Phys Act 2012;9:19.
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