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The association of emotional well-being and marital status
with treatment adherence among patients with hypertension
Ranak B. Trivedi ÆBrian Ayotte ÆDavid Edelman Æ
Hayden B. Bosworth
Accepted: August 25, 2008 ,
ÓSpringer Science+Business Media, LLC 2008
Abstract We were interested in examining the relation-
ship between psychosocial factors and hypertension-related
behaviors. We hypothesized that lower emotional well-
being and unmarried status would be related to higher BP,
poorer medication adherence, greater difficulty adhering to
diet and exercise, and current smoking. In a cross-sectional
design, 636 hypertensive patients completed the Mental
Component Summary (MCS) Scale of the SF-12 and rated
their difficulty with adherence to diet, exercise, and med-
ication-taking. In logistic regression analyses, lower MCS
scores were associated with difficulty adhering to diet
(OR =0.97, p\.05) and exercise (OR =0.97, p\.01),
and current smoking status (OR =0.98, p\.05). Being
married was associated with higher probability of medi-
cation adherence (OR =1.66, p\.01) and a lower prob-
ability of being a current smoker (OR =0.34, p\.0001).
Neither MCS scores nor being married were related to BP
levels in adjusted analyses. Results emphasize the impor-
tance of assessing psychosocial factors to optimize hyper-
tension treatment.
Keywords Adherence Hypertension Emotional well-
being Marital status Lifestyle recommendations
Introduction
Four decades of clinical trials have produced an enor-
mous body of evidence showing that controlling hyper-
tension improves cardiovascular and renal outcomes
(Chobanian et al. 2003; Psaty et al. 2003; The ALLHAT
Officers and Coordinators for the ALLHAT Collaborative
Research Group 2002). The mechanisms for achieving
control, including following medication regimens and
lifestyle recommendations (e.g., diet, exercise, smoking
cessation), are well known and widely accepted (Cho-
banian et al. 2003; Elmer et al. 1995; Lichtenstein et al.
2006; Miller et al. 2002; Sacks et al. 2001; Whelton
et al. 1998). However, many patients do not adhere to
these recommendations. Non-adherence to antihyperten-
sive medications may be as high as 50% (Garfield and
Caro 1999) and has been cited as the principal reason
behind poor hypertension control in the population
(Burnier 2006). Estimates of lifestyle recommendations
also reflect high degrees of non-adherence. In a primary
care setting, (Burt et al. 1995) estimated that only 67%
patients reported adherence to any one of four lifestyle
recommendations (weight management, dietary sodium
reduction, moderate alcohol consumption, and regular
exercise).
While a variety of psychosocial factors are thought to
influence treatment adherence and blood pressure (BP)
control, the effects of emotional well-being are relatively
understudied. Of the studies examining the dimension of
mental health, the focus has been largely on clinical
depression or depressive symptoms. A recent meta-
analysis suggested that depressed patients were three
times more likely to be non-adherent to medical treat-
ment, across medical conditions (DiMatteo et al. 2000).
Less attention has been paid to subclinical emotional
R. B. Trivedi (&)D. Edelman H. B. Bosworth
Department of Medicine, Duke University Medical Center, 2424
Erwin Rd, Hock Plaza Ste 1105, P.O. Box 2720, Durham,
NC 27705, USA
e-mail: Ranak.trivedi@duke.edu
B. Ayotte D. Edelman H. B. Bosworth
Durham Veterans Affairs Medical Center, Durham, NC, USA
123
J Behav Med
DOI 10.1007/s10865-008-9173-4
distress and emotional well-being in medical illness in
general, and hypertension in particular. One study
examined the impact of emotional well-being on medi-
cation adherence (Wang et al. 2002). They found that for
each point change on a depression scale, hypertensive
patients were 7% less likely to adhere to their medica-
tions. Similar to medication adherence, the impact of
emotional health on adherence to lifestyle changes in
hypertension is relatively unknown. This is despite strong
evidence in other chronic illnesses that emotionally
healthy patients show greater adherence to maintaining
lifestyle changes (Daly et al. 2002; DiMatteo et al. 2000;
Koertge et al. 2003; Sherbourne et al. 1992). Lastly,
little is known about the impact of emotional well-being
on BP among individuals with hypertension although
clinical depression has been shown to reduce BP control
(Simonsick et al. 1995). The sparseness of the literature
belies the importance of establishing the impact of
emotional well-being in hypertension since individuals
with hypertension appear to have a poorer quality of life
compared to normotensives (Banegas et al. 2006;Bar-
dage and Isacson 2001; Dimenas et al. 1989; Moum
et al. 1990).
In addition to emotional well-being, marital status may
play an important role in hypertension. Marital status is
considered a measure of social network, and is associated
with improved hypertension control (Caldwell et al.
1983; He et al. 2002). It is speculated that married hy-
pertensives may have better hypertension control partly
through improved adherence to recommendations. While
some studies support this relationship (Kulkarni et al.
2006; Kyngas and Lahdenpera 1999), others have not
found a relationship between marital status and adherence
to treatment recommendations among individuals with
hypertension (Cummings et al. 1982). A recent meta-
analysis of the general medical literature concluded that
adherence to medical recommendations were higher in
married patients (DiMatteo 2004). In light of the evi-
dence in the general medical literature, the relationship
between marital status and treatment adherence deserves
closer scrutiny in hypertension. Furthermore, it is
important to investigate whether marital status is related
to adherence to pharmacological and lifestyle recom-
mendations, as the current state of literature is unable to
answer this question.
The purpose of this study was to examine whether
emotional well-being and marital status were related to
baseline BP levels and adherence to medications and
lifestyle recommendations. Results can be used to further
our understanding regarding psychosocial factors which
may impact adherence to medication and lifestyle chan-
ges.
Methods
Participants
Six hundred and thirty-six hypertensive patients were re-
cruited from two Duke University Medical Center primary
care clinics that were part of the Take Control of Your
Blood Pressure (TCYB) Study (Bosworth et al. 2007).
Briefly, TCYB tested two interventions (tailored behavioral
intervention and BP self-monitoring) in a sample of
hypertensive patients. This study represents secondary,
cross-sectional analyses of the baseline data from TCYB.
Inclusion/exclusion criteria
Patients were included if they had documented hyperten-
sion according to medical records (ICD-9 codes 401.9,
401.0, 401.1), if they were enrolled in one of the two pri-
mary care clinics for at least a year, and if they were using
a hypertensive medication (e.g., ACE inhibitor, beta
blockers). Patients were excluded if they were not on BP
medication, a family member was already enrolled in the
study, they did not live in an eight-county catchment area,
were receiving kidney dialysis, were pregnant or were
planning to be pregnant, had arms that exceeded the BP
cuff limits, had been hospitalized for a stroke, myocardial
infarction, coronary artery revascularization within the last
3 months, had been diagnosed with metastatic cancer, had
been diagnosed with dementia, resided in a nursing home
or received home health care, did not speak or understand
English, were enrolled in another hypertension study, were
not receiving the majority of their healthcare through Duke
University, had severely impaired hearing or speech, and/
or had a history of organ transplant. The final sample was
derived from initially screening 7,646 patients of which
1,325 eligible patients were contacted. Five hundred and
forty-nine patients refused participation. For more details
regarding the study design, refer to (Bosworth et al. 2007).
Measures
Patients underwent a BP screening involving two succes-
sive digitally derived BP values taken by study staff. These
were averaged to determine baseline systolic and diastolic
BP (SBP and DBP, respectively). In addition, each par-
ticipant completed a battery of questionnaires at the time of
their initial visit, described next.
Emotional well-being was measured using the Mental
Component Summary Scale (MCS), a 5-item subscale of
the MOS Short Form 12 (SF-12; (Gandek et al. 1998; Ware
et al. 1996). The MCS subscale is not a diagnostic tool for
depression but rather is a measure of mental health-related
J Behav Med
123
quality of life. Items assess general mental health and its
impact on daily functioning. Answers are provided on
Likert scales tailored to each item. The mean of the MCS is
50, the standard deviation is 10 and the reliability of MCS
ranges from .77 to .97 (Gandek et al. 1998; Ware et al.
1996).
Adherence to medication was assessed using the Self-
reported Medication Taking Scale (Morisky et al. 1986).
This 4-item measure assesses medication-taking behavior.
Respondents rate whether they forget to take medications,
are careless about taking their medications, or stop taking
their medications based on whether they feel better or worse.
Items are rated on a 4-point scale, from ‘‘strongly agree’’ to
‘‘strongly disagree’’. The predictive validity of this measure
is .60 and reliability is 0.85 (Morisky et al. 1986).
As medication non-adherence may also depend on
undesirable side effects, participants were asked to report
whether or not they had experienced any of 16 common
antihypertensive side effects, including dry mouth, sweat-
ing, swelling, and sexual problems.
Adherence to dietary and exercise recommendations
were assessed with one item each, asking respondents to
rate the difficulty of following the recommendation.
Respondents answered on a 1–10 scale, with higher scores
indicating more difficulty in following recommendations.
Smoking status was determined by a single yes/no item
asking whether participants smoked cigarettes at the time
of the assessment.
Finally, a demographic questionnaire was administered
to determine participants’ age, gender, race, and marital
status.
Data analyses
Participants were classified as non-adherent to medications
if they endorsed at least 1 item with ‘‘strongly agree’’ or
‘‘agree’’ on the Self-reported Medication Taking Scale.
Otherwise, participants were considered adherent to med-
ications. This system follows established protocols (Bos-
worth et al. 2006). To determine difficulty adhering to
dietary or exercise recommendations, scores were recoded
such that scores greater than 5 on the 10 point scale indi-
cated greater difficulty with adherence. The cutoff of 5
reflects the median split in our sample for both variables.
Simple correlations were conducted to examine the
relationship between all variables of interest. Pearson’s
correlations were conducted where at least one variable
was continuous. If both variables were categorical, phi
coefficients were calculated to determine the simple cor-
relations.
Dependent variables were baseline SBP, baseline DBP,
adherence to medications, difficulty adhering to dietary
recommendations, difficulty adhering to exercise recom-
mendations, and current smoking status. SBP and DBP
were treated as continuous variables. Adherence to medi-
cations, difficulty adhering to dietary recommendations,
difficulty adhering to exercise recommendations, and cur-
rent smoking status were coded such that analyses yielded
greater probability of being adherent to medications, hav-
ing greater difficulty adhering to dietary and exercise rec-
ommendations, and being a current smoker.
Independent variables were emotional well-being as
measured by the MCS and marital status. Emotional well-
being was treated as a continuous variable such that higher
scores on the MCS represent better emotional well-being.
Marital status was coded as ‘‘married’’ or ‘‘not married’’,
with ‘‘not married’’ as the referent.
Non-Whites have poorer BP control and report poorer
adherence (Bosworth et al. 2006; Bosworth et al. 2008).
Similarly, younger age and male gender are well-estab-
lished predictors of BP and non-adherence (Morris et al.
2006). Therefore, age, race, and gender were included in all
models because not including these in models may poten-
tially bias the results in favor of finding spurious effects.
Age was treated as a continuous variable. The referents for
race and gender were non-white race and male gender,
respectively. In addition, the number of reported side
effects was added to the model where adherence to medi-
cations was the criterion, because side-effects may con-
found medication adherence. Significance was set at
p\.05. All analyses were conducted using SAS 9.1
Ò
(SAS, Cary, NC).
Multiple linear regression analyses were conducted to
test whether emotional well-being and marital status were
associated with baseline SBP and baseline DBP (models 1
and 2, respectively). Logistic regression analyses were
conducted to test whether emotional well-being and marital
status were associated with medication adherence (model
3). Logistic regression analyses were also conducted to test
whether MCS scores and marital status were related to
difficulty adhering to dietary and exercise recommenda-
tions (models 4 and 5, respectively). Lastly, logistic
regression analyses were used to test whether emotional
well-being and marital status were associated with current
smoking status (model 6). MCS scores and marital status
were tested simultaneously in all models. As these were
cross-sectional analyses, the results are presented as asso-
ciations between the independent and dependent variables.
In post hoc analyses, it was hypothesized that the four
adherence variables (adherence to medications, current
smoking, adherence to dietary recommendations, adher-
ence to exercise recommendations) would mediate the
associations of emotional well-being and marital status
with BP control. A series of analyses were conducted
wherein each mediational variable was introduced into
regression analyses where the dependent variables were
J Behav Med
123
either SBP or DBP, and the independent variables were
either emotional well-being or marital status. Using
unstandardized estimates and the corresponding standard
errors, the Sobel test (Sobel 1982) was used to then test for
the significance of the mediational pathways. This method
tests for the significance of the indirect effects by
hypothesizing that there are no differences between the
direct and indirect effects.
Results
Baseline characteristics of this sample, including baseline
SBP and DBP, are presented in Table 1. At baseline, the
mean MCS score was 50.59 (SD =10.7). Fifty-nine percent
of the sample reported medication adherence. Approxi-
mately 16% of participants reported that they were smokers
at the time of assessment. The results of the correlations
between all the variables of interest are shown in Table 2.
The shaded cells represent phi coefficients. As can be seen in
Table 2, higher MCS scores were significantly, but moder-
ately, correlated with lower DBP (r=-.14, p\.001),
better medication adherence (r= .16, p\.001), better
adherence to dietary recommendations (r= .18, p\.001),
better adherence to exercise recommendations (r= .18,
p\.001) and lower incidence of current smoking (r=
-.16, p\.001). Being married was associated with better
medication adherence (r= .19, p\.001), better adherence
to exercise recommendations (r= .10, p\.001), and lower
incidences of current smoking (r=-.18, p\.001).
Examining the zero-order correlations with race revealed
that White participants had greater emotional well-being
(r= .11, p\.01), lower SBP (r=-.19, p\.001), lower
DBP (r=-.23, p\.001), were more likely to be married
(r= .35, p\.01), reported better medication adherence
(r= .27, p\.001), and were more likely to be current
smokers (r= .14, p\.05). Finally, zero-order correlations
with gender showed that males had better emotional well-
being (r= .11, p\.01), were less likely to be married
(r=-.30, p\.01), and had less difficulty adhering to
exercise recommendations (r=-.01, p\.01).
Adjusted regression analyses were conducted to explore
the relationships between emotional well-being, marital
status, and BP. Results of multiple linear regression anal-
yses showed that neither MCS scores nor marital status
were significant correlates of baseline SBP or DBP values
after adjusting for the associations of race, gender and age
(Table 3). Age was associated with higher SBP (p\.05)
but lower DBP (p\.001). Non-white race was associated
with higher baseline SBP and DBP (p’s \.001), and male
gender was associated with higher baseline DBP (p\.01).
Table 1 Baseline characteristics
N636
Age (M ±SD), years 61.25 ±12.32 (range: 25–92 years)
Gender, N(%) 420 female (66%)
Race 48.4% white, 49.06% black, 2.5% other
Married, N(%) 320 (50.47%)
Current smokers, N(%) 130 (16.4%)
Baseline SBP, mmHg 125.0 ±17.7
Baseline DBP, mmHg 71.3 ±10.8
Table 2 Unadjusted zero-order correlations between explanatory and criterion variables
Variables SBP DBP MCS Age Race Marital
status
Medication
adherence
Difficulty
adhering
to diet
Difficulty
adhering
to exercise
Current
smoking
Gender
SBP –
DBP .58*** –
MCS -.06 -.14*** –
Age .04 -.40*** .26*** –
Race -.19*** -.23*** .11** .16*** –
Marital status -.03 -.02 .14*** .02 .35** –
Medication
adherence
-.12** -.16*** .16*** .13** .27*** .19*** –
Difficulty adhering
to diet
-.01 -.02 .18*** .13** .08 .01 .08* –
Difficulty adhering
to exercise
-.01 -.01 .18*** .14*** .06 .10*.09*.39*** –
Current smoking -.05 .06 -.16*** -.17*** .14*-.18*** -.09*.01 -.06 –
Gender -.01 .07 .11** .05 .18** -.30** -.01 -.04 -.01** -.03 –
Italicized cells represent phi co-efficients between two dichotomous variables
*p\.05, ** p\.01, *** p\.001
J Behav Med
123
Table 4shows the results of logistic regression analyses
examining the association between MCS scores and marital
status, and adherence to medication and lifestyle recom-
mendations, after adjusting for age, race, gender and
medication side-effects. The adjusted results indicated that
MCS scores were not associated with medication adher-
ence (p=.12). However, married participants were 66%
more likely to be adherent to medications (OR =1.66,
p\.05), supporting the role of social network in medi-
cation adherence. Participants who reported higher MSC
scores were likely to report less difficulty adhering to
dietary and exercise recommendations. For every 1-point
increase in MCS scores, the probability of having difficulty
adhering to dietary recommendations decreased by 3.1%
(OR =.969, p\.001). Similarly, for every 1-point in-
crease in MCS scores, the probability of having difficulty
adhering to exercise recommendations decreased by 2.8%
(OR =.972, p\.001). Marital status was not significantly
associated with difficulty adhering to dietary or exercise
recommendations (p= .75 and .06, respectively).
With regard to smoking status, each 1 point increase in
MCS scores was associated with a 2.4% decrease in the
probability that the participant was a current smoker
(OR =.976, p\.05). Being married was associated with
a nearly 70% lower likelihood of being a current smoker
(OR =.34, p\.0001).
Consistent with expectations, White participants were
more than two times more likely to report adherence to
medication than non-White participants (OR =2.381,
p\.0001). Each additional side effect was significantly
associated with lower adherence to medications (OR =.930
per side effect, p\.05). Older participants reported less
difficulty adhering to diet (OR =.985, p=.0375) and
exercise recommendations (OR =.972, p\.001). Older
participants were also less likely to be currently smoking
(OR =.970, p\.01). Being female was associated with
greater reported adherence to medications (OR =1.503,
p\.05) and non-smoking status (OR =.504, p\.01).
The multiplicative effects of MCS scores and marital
status were examined in regression analyses by introducing
the interaction term ‘‘MCS 9Marital Status’’ in the anal-
yses described earlier. This interaction term was not a
significant correlate of SBP levels, DBP levels, adherence
to medications, current smoking status, difficulty adhering
to dietary recommendations, or difficulty adhering to
exercise recommendations (p’s [.05). Therefore, models
were refit to retain only the main effects to create parsi-
monious final models.
Table 3 Correlates of baseline blood pressure, adjusted for age, race, and gender
Variable Systolic blood pressure Diastolic blood pressure
bpbp
MCS
a
-.08 .06 -.04 .21
Marital status (married vs. not married) .05 .25 .02 .56
Age .10 \.05 -.37 \.0001
Race (white vs. non-white) -.22 \.0001 -.19 \.0001
Gender (female vs. male) -.02 .66 -.12 \.01
b=Standardized co-efficient
a
Standardized b’s represent the increase in SBP or DBP per 1 unit change in MCS scores
Table 4 Adjusted correlates of adherence to medications and lifestyle recommendations (diet, exercise, and smoking)
Variable Adherence to
medications
OR (95% CI)
Difficulty adhering to
dietary recommendations
OR (95% CI)
Difficulty adhering to
exercise recommendations
OR (95% CI)
Current smoking
status
OR (95% CI)
MCS
a
1.01 (1.00, 1.03) .97*** (.95, .99) .97** (.96, .99) .98* (.96, .99)
Marital status (married vs. not married) 1.66** (1.14, 2.41) 1.06 (.74, 1.52) .70 (.49, 1.01) .34*** (.20, .57)
Age 1.01 (1.00, 1.03) .99* (.97, .999) .98** (.97, .996) .97** (.95, .99)
Race (white vs. non-white) 2.38*** (1.66, 3.41) 1.18 (.83, 1.68) 1.41 (.99, 2.01) .73 (.45, 1.189)
Gender (female vs. male) 1.50* (1.03, 2.20) 1.14 (.80, 1.64) 1.43 (.99, 2.07) .50** (.31, .83)
Medication side effects .93* (.88, .99) – – –
OR =Odds ratio; 95% CI =95% confidence interval
a
ORs represent the probability of having the outcome per 1 unit increase in MCS scores
*p\.05, ** p\.01, *** p\.0001
J Behav Med
123
Based on the bivariate relationships among the vari-
ables, post hoc mediational analyses were conducted as
complete mediation could potentially explain the lack of
relationship between the independent variables and BP
levels. Results of the Sobel test demonstrated that none of
the adherence variables (i.e., medication adherence,
smoking status, difficulty adhering to exercise recommen-
dations, difficulty adhering to dietary recommendations)
were significant mediators of the relationship between
emotional well-being and BP level, or marital status and
BP level (p[.05 for all analyses). This was true for
models that were unadjusted, and those models that were
adjusted for the effects of race, gender, and age.
Discussion
Key findings from this study suggest that emotional well-
being and marital status may play important, but poten-
tially different, roles in hypertension management. Emo-
tional well-being may be important in maintaining
important lifestyle changes, whereas marital status may be
important in maintaining medication adherence and non-
smoking. Neither variable was directly related to BP levels.
Although previous studies have documented the impact of
clinical depression on adherence (Glassman et al. 1990;
Kim et al. 2003; Wang et al. 2002; Wells et al. 1989), this
study is among the first to document that subclinical
emotional distress may be detrimental to adherence to
lifestyle recommendations, including diet, exercise, and
tobacco use, in hypertensive patients.
Despite the presence of a bivariate relationship, emo-
tional well-being was not associated with medication
adherence or DBP in regression analyses after accounting
for the associations of marital status, age, race, gender, and
side-effects with medication adherence of DBP. Notably,
adjusted regression analyses did not reveal a relationship
between emotional well-being and DBP levels above the
effects of age, race, marital status, and gender. The possi-
bility that this lack of relationship may be explained by
mediation through adherence was tested in post hoc anal-
yses. However, none of the mediational pathways were
significant in either adjusted or unadjusted analyses.
These findings may be explained in at least two ways.
First, the zero-order correlations between emotional well-
being and medication adherence, and emotional well-being
and DBP, were small in magnitude. Their lack of signifi-
cance in adjusted regression analyses may indicate the
absence of a true relationship. In other words, the rela-
tionship observed in zero-order correlations may be the
effect of emotional well-being acting as a proxy for race
and gender, especially given that the scores on the MCS
were significantly correlated with both race and gender.
Race and gender are consistent correlates of BP and
adherence. In particular, being White is associated with
better hypertension control (Bosworth et al. 2003; Rehman
et al. 2005). It has been speculated that both biology and
sociology play important roles in this relationship (White
2008). Although gender shares a more complex relation-
ship with BP, studies largely indicate that men are bio-
logically predisposed to higher BP compared to women
(Rosenthal and Oparil 2000). The decision to include these
demographic variables was predicated on this theoretical
framework in an effort to control for their potential con-
founding effects.
Second, it is possible that emotional well-being may not
be related to medication adherence in emotionally healthy,
hypertensive patients with adequate BP control. The dif-
ferential impact of emotional well-being on adherence to
pharmacological versus non-pharmacological recommen-
dations is consistent with previous reports in non-hyper-
tensive patients (DiMatteo et al. 1992; Sherbourne et al.
1992). One possible explanation may lie in the effort
necessary to effect and maintain medication-taking versus
lifestyle behaviors (DiMatteo et al. 2000). The Health
Belief Model (Rosenstock et al. 1988) posits that people
will avoid illness if the preventive action is perceived to be
less negative than the illness itself (Becker and Maiman
1975; Sherbourne et al. 1992). As a patient’s emotional
well-being declines, lifestyle adherence might be aban-
doned prior to medication adherence due to the greater
effort required to maintain lifestyle changes. In our sample
of emotionally healthy patients, the impact of subclinical
emotional distress may be noticeable in adherence to life-
style behaviors but not medications.
These results may be translated into clinically relevant
information. A 10-point change on the MCS represents one
standard deviation in national validation studies (Gandek
et al. 1998). Therefore, a 10 point (or 1 standard deviation)
change in MCS may be associated with a 31% change in
the probability that patients will report difficulty adhering
to dietary recommendations, a 28% change in the proba-
bility that patients will report difficulty adhering to exercise
recommendations, and a 24% change in the probability that
the patient will be a current smoker.
In this sample, being married increased the probability
of being adherent to medications and being a non-smoker.
Spousal assistance may be associated with increased
adherence through providing practical support (e.g.,
reminding patient to take medications) or by improving
patients’ self-concept (Shumaker and Hill 1991). Interest-
ingly, no relationship was found between marital status and
difficulty adhering to dietary and exercise recommenda-
tions. This contradicts earlier studies that have demon-
strated the positive impact of marital status on promoting
diet and exercise changes (Kyngas and Lahdenpera 1999).
J Behav Med
123
Future research will help understand the differential impact
of marital status on adherence to a variety of recommen-
dations in hypertension management.
Results from this study provide further evidence that
assessing emotional distress in a primary care setting may
be an important component of hypertension management.
We speculate that interventions targeting emotional health
may impact adherence to lifestyle recommendations with-
out impacting medication adherence. On the other hand,
interventions enhancing social resources may improve
medication adherence and increase chances of smoking
cessation, but may not mitigate difficulty adhering to die-
tary or exercise recommendations. The latter is consistent
with randomized clinical trials demonstrating that
enhancing the network through follow-up from medical
personnel and a strong physician-patient alliance can im-
prove adherence to medication regimens and smoking
cessation (Cobb et al. 2006; Fuertes et al. 2007; Lumley
et al. 2004; Pi-Sunyer 2006; Stewart et al. 2005). Future
investigations examining treatment adherence should con-
sider the impact of support received by various sources
such as spouses, family or other friends.
This study has certain limitations. First, this study is
based on cross-sectional data which limits any interpreta-
tion regarding causal direction. Therefore, while it is pos-
sible that emotional well-being impacts adherence to
lifestyle recommendations, the reverse also may be true.
Second, adherence was based on self-report rather than an
objective measure, such as pill-counting or pharmacy re-
cords of refills. This may have skewed the data in the
direction of social desirability leading to over-estimated
adherence rates. This is a widely documented limitation of
self-report adherence measures (Bosworth et al. 2006;
Morisky et al. 1986). Although objective measures of
adherence are available, such as microelectric event mon-
itoring, no one method is accepted as the ‘‘gold standard’’
for measuring medication adherence. In the absence of a
‘‘gold standard’’, the Morisky instrument (Morisky et al.
1986) affords ease of administration through a brief, valid,
and reliable measure. As a measure of medication taking
behavior, the Morisky instrument has been used in studies
looking at cross-sectional data as well as prospective
studies (Hamilton 2003; Li et al. 2008). It has been vali-
dated against microelectric event monitoring, with a sen-
sitivity of 72% and specificity of 74% for 80% or more
adherence to tricyclic antidepressants (George et al. 2000).
A third limitation concerns the use of marital status as a
measure of social network. Marital status is a unidimen-
sional measure that does not account for the quality of the
relationship, the type of support (emotional versus instru-
mental), or the presence of other friends or family that may
form a patients’ social network. Fourth, single-item mea-
sures are psychometrically not as reliable or valid com-
pared to multiple item measures of the same construct
(McHorney et al. 1992). In reality, this limitation would
reduce our chances of finding an effect. The robust findings
in this study despite using single-item measures provide
impetus to future investigations using more sophisticated
measures of social network, and adherence to dietary and
exercise recommendations. Finally, findings related to
smoking status should be interpreted with caution, as only
16% of our sample was current smokers.
Despite these limitations, this study adds to the sparse
literature examining the direct impact of psychosocial
factors on BP levels in hypertensive patients. The results
provide preliminary support for the need to assess emo-
tional well-being and the presence of social support in a
primary care setting. Future investigations will help
determine whether early detection of and intervention on
subclinical emotional distress might benefit the hyperten-
sive patient through improved adherence to dietary and
exercise recommendations, and whether enhancing social
support will improve medication adherence.
Acknowledgments This study was supported by NHLBI Grant R01
HL070713, the Pfizer Health Communication Initiative Award, and
the American Heart Association Established Investigator Award, all
awarded to Dr. Hayden Bosworth. Dr. Trivedi is supported by NRSA
Grant 5-T32 HS000079-10. Dr. Ayotte is supported by a post-doctoral
fellowship from the VA Office of Academic Affairs. The views ex-
pressed in this article are those of the authors and do not necessarily
represent the views of the Department of Veterans Affairs. The PI of
the study, Dr. Bosworth, has full access to all of the data in the study
and takes responsibility for the integrity of the data and the accuracy
of the data analysis.
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