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PARTNER INFLUENCE, HEALTH VALUES, HEALTH BEHAVIORS"
Please cite as: Skoyen, J. A., Blank, E., Corkery, S. A., & Butler, E. A. (in press). The interplay
of partner influence and individual values predicts daily fluctuations in eating and physical
activity. Journal of Social and Personal Relationships.
The Interplay of Partner Influence and Individual Values Predicts Daily Fluctuations in Eating
and Physical Activity.
Jane A. Skoyen, Elaine Blank, Shannon A. Corkery, Emily A. Butler
University of Arizona
Running head: PARTNER INFLUENCE, HEALTH VALUES, HEALTH BEHAVIORS"
Key words: Eating, exercise, BMI, overweight, obesity, partner influence, health values, gender.
Author Note
Jane A. Skoyen, Department of Psychology, University of Arizona; Elaine Blank,
Department of Psychology, University of Arizona; Shannon A. Corkery, Department of Family
Studies and Human Development, University of Arizona; Emily A. Butler, Department of
Family Studies and Human Development, University of Arizona.
Correspondence concerning this article should be addressed to Jane A. Skoyen,
Department of Psychology, 1503 E. University Blvd., University of Arizona, Tucson, AZ 85719;
jsv@email.arizona.edu.
This research was supported in part by the Frances McClelland Institute for Children,
Youth, and Families, in the Norton School of Family and Consumer Sciences at The University
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of Arizona. Information about the Frances McClelland Institute is available at:
http://McClellandInstitute.arizona.edu.
Abstract
Most people have difficulty maintaining a healthy diet and getting a prescribed amount of
physical activity. What stands in the way? Both social and individual factors play a role
in shaping one’s diet and exercise habits, and close relationships provide a proximal
source of social influence, suggesting the importance of studying these factors in the
context of committed relationships. Sixty-two heterosexual couples reported on health
behavior values (HBV) and completed daily diaries assessing food intake and physical
activity relative to their own normal behavior (e.g. did they eat more or less than normal
that day?) and the helpfulness of health-related influence from their partners. We used a
repeated measures dyadic model to test whether daily partner influence was associated
with variations in eating and exercise and whether the degree of this association was
moderated by couples’ average HBVs or the differences between partners’ HBVs. Men in
couples with high average HBVs ate less than usual in response to positive partner
influence. Also, in such couples, normal weight men engaged in more physical activity
when positively influenced by their partners. However, normal weight men in couples
with low average HBVs engaged in less physical activity when positively influenced by
their partners. Women who valued health less than their partners responded to partner
influence by eating healthier. These results highlight the importance of considering both
social and individual contributors to health behaviors. By identifying the factors shaping
dietary and activity practices, we might add to development of interventions for poor
health habits.
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The Interplay of Partner Influence and Individual Health Values Predicts Daily
Fluctuations in Eating and Physical Activity
Most people know that a healthy diet and exercise are good for them, so why do so few
adhere to a healthy lifestyle? Research indicates that social factors such as romantic partners’
attempts to influence one another (Homish & Leonard, 2008; Lewis & Butterfield, 2007; Lewis
& Rook, 1999; Markey, Gomel, & Markey, 2008; Markey, Markey, & Gray, 2007; Umberson,
1992) and individual factors such as health values and health beliefs (Conner, Kirk, Cade, &
Barrett, 2001; Jackson, Tucker, & Herman, 2007; Laffrey & Isenberg, 2003; Merrill, Friedrichs,
& Larsen, 2002; Peltzer, 2000; Shepherd & Stockley, 1987; Watters & Satia, 2009) shape health
behaviors. However, neither of these factors considered alone provides a satisfactory explanation
for daily variation in health actions. We propose that to accurately capture the combined effect of
social and individual influence on health behaviors, we need to investigate them in the context of
close relationships. This means that we should consider not only the interaction between one
partner’s health behavior values (HBV) and the other partner’s influence, but to also take into
account whether partners’ HBVs are similar or different and whether overall couples’ HBVs are
high or low.
Partner Influence and Health Behaviors
Research shows that romantic partners can have an impact on health behaviors including
eating and exercise (Markey et al., 2007). Relationship partners have been shown to exchange
both positive and negative health habits over time (Homish & Leonard, 2008) and the positive
correlation often found between spouses’ body-mass indexes (BMIs) may be partially due to
their shared eating and exercise habits (Jeffery & Rick, 2002). Although studies conclusively
demonstrate that long-term partners affect each other’s health behaviors (e.g., Homish &
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Leonard, 2008; Lewis & Butterfield, 2007; Lewis & Rook, 1999; Umberson, 1992), they also
suggest that those effects can take various forms. For example, partners may influence each other
both through indirect means such as habit exchange (e.g., Homish & Leonard, 2008; Jeffery &
Rick, 2002), and direct social control by one of the partners (e.g., Lewis & Rook, 1999;
Umberson, 1992). Furthermore, the valence of partner influence may play a role in health
outcomes. Lewis and Rook (1999) reported that positive social control tactics (e.g., rewarding
behavioral change) were related to an increase in health-enhancing behaviors, whereas negative
social control tactics (e.g., inducing guilt) were unrelated to health behavior change, but were
associated with more psychological distress. Similarly, in a study by Tucker and Mueller (2000),
participants whose partners modeled the desired health behavior or provided emotional support
reported these influences as effective. In contrast, the use of strategies such as expression of
negative affect or nagging was associated with less positive and more negative affect and lower
self-esteem in the participants.
Importantly, although there is some objective agreement as to which tactics are effective
or not, there is also considerable between-person variability (e.g. Tucker & Mueller, 2000)
suggesting that an individual’s perception of his or her partner’s influence attempts may play a
role. Specifically, the research on the valence of influence suggests that only influence attempts
perceived in a positive light will have a desirable impact on health behaviors. To address this
issue in the present study, we assessed people’s reports of how helpful they found their partners’
health-related influence to be, rather than the details of what the influence attempt entailed.
Health Values and Health Behaviors
One broadly studied individual-level factor impacting health behaviors is health value.
The diversity of definitions of health values found in the literature, however, calls for a brief
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clarification. The results of studies that define health value as valuing health in general are
mixed. While some demonstrate a connection between health values and health actions such as
maintaining a health-promoting lifestyle (Jackson et al., 2007), taking dietary supplements
(Conner et al., 2001), being a runner (Walsh, 1985), and not being obese (Freedman &
Rubinstein, 2010), others show that HBVs are not associated with physical activity (Laffrey &
Isenberg, 2003) or dietary fat intake (Peltzer, 2000).
Another body of literature addresses valuing specific health-related behaviors (HBV;
e.g., healthy diet and exercise) in staying healthy. The results of these studies generally show that
those who value a specific health behavior, have a positive attitude towards this behavior, or
believe that this behavior is important for staying healthy, are more likely to engage in this
behavior (e.g., Merrill et al., 2002; Peltzer, 2000; Shepherd & Stockley, 1987; Watters & Satia,
2009). However, even specific HBVs do not always translate into health actions. In one study,
73% of all participants strongly agreed that it was important to maintain their health, 76%
strongly believed that what they ate affected their health, and 69% strongly agreed that what they
weigh affects their health; however, 48% of the participants were overweight or obese,
suggesting a possible disconnect between HBVs and health actions (Freedman & Rubinstein,
2010). Similarly, Conner et al. (2001) showed that being concerned about health consequences of
one’s diet was unrelated to dietary supplement use.
Although research evidence supports the link between HBV and behaviors, the lack of
consistency in results suggest the importance of looking at the interplay of HBV and other
factors that have documented relevance to health behavior. Based on existing findings, we can
extrapolate that the connection between health values, health beliefs, and health behaviors may
become stronger as beliefs become more specific (i.e., importance of a specific health behavior
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vs. importance of health in general) and as values become more focused on the individual (i.e.,
the value of health for the respondent vs. for general populations). Indeed, Laffrey and Isenberg
(2003) showed that although physical activity was not related to the relative value of health as
compared to other values, it was associated with perceived importance of exercise in one’s life.
Similarly, Peltzer (2000) found no connection between exercising and avoiding dietary fat and
general health values, but showed that beliefs about avoiding dietary fat and exercising were
associated with corresponding behaviors. Based on these considerations, we conclude that to
capture health values most predictive of specific health behaviors, we would need to assess
values that are related to this specific behavior (vs. overall value of health) in a way that directly
pertains to the individual (vs. the population in general).
The Interactive Effects of Partner Influence and Health Values on Health Behavior
We further suggest that investigating the links between HBV, partner influence, and
health behaviors in a dyadic context may help clarify the circumstances under which partner
influence and individual HBVs may impact health behaviors. For example, we propose that if
and how partner influence is acted on (e.g., following or dismissing the influence) will depend on
whether partners assign similar or divergent values to health behaviors. Based on the idea that
communal coping with health issues increases couples’ ability to deal with health problems
(Lewis et al., 2006; Lyons, Mickelson, Sullivan, & Coyne, 1998; Rohrbaugh, Mehl, Shoham,
Reilly, & Ewy, 2008), we hypothesize that partners with similar values may be more likely to
support each other in engaging in behaviors that are consistent with those values. However, when
partners’ HBVs are different, adhering to health-beneficial activities might be harder and the
outcomes may vary depending on which partner values the behavior more. We suggest that
partners who value specific health behaviors are likely to accept influence from partners who
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share those values, but are less likely to be influenced by partners who are not as committed to
those behaviors. In other words, people who value a health behavior more than their partners do
will not alter this behavior based on partner influence. However, those who do not value health
behaviors as much as their partners might be more willing to accept influence from their more
health-conscious partner.
Hypotheses
Based on the rationale described above, the present study tests the following hypotheses:
H1) In couples with high average HBVs, both partners will be more responsive to each other’s
influence than partners in low-HBV couples. High average values are indicative of both partners
valuing health behaviors at least somewhat, so partners in such couples are more likely to have a
dyadic focus on engaging in those behaviors and being mutually supportive in adhering to them,
making partner influence more likely to have an impact.
H2) People who value health behaviors more than their partners do will be less influenced by
their partners than people who value health behaviors less than their partners. We reason that
those committed to healthy behaviors are not going to change their habits based on influence
from a less health-conscious partner. However, people who rate health behaviors as less
important than their partners are more likely to be influenced by their partner’s stronger values
and respond to partner influence by altering their health behaviors.
Present Study
To test our hypotheses, we collected data from a community sample of heterosexual
couples in committed romantic relationships. We obtained a fairly diverse sample in terms of age
and relationship length. We believe that such a sample is less susceptible to recruitment biases
than would be a convenience sample made up purely of college students. Participants first
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provided demographic data and a baseline measure of health behavior values, height, weight, and
subjective ratings of their own weight. We reasoned that participants’ weight status (as assessed
by BMI) may be affecting their health behaviors and their responsivity to partner influence; if so,
their perceptions of their weight status may be as important as their actual BMI. We therefore
explored whether BMI or perceived weight status moderated the relationship between HBVs,
partner influence, and health behaviors. In addition, based on studied suggesting that people eat
less healthily (deCastro, 1991; Rhodes, Cleveland, Murayi, & Moshfegh, 2007) and engage in
more sedentary behavior (Lake et al., 2009) on weekends vs. weekdays, we accounted for days
of the week in our analyses. Finally, in line with the literature pointing to gender differences in
dietary habits (Beardsworth et al., 2002; Bonds-Raacke, 2006; Morse & Driskel, 2009; Prattala
et al., 2007; Savoca & Miller, 2001; Wardle et al., 1994) and exercise (Darlow & Xu, 2011;
Shifren, Bauserman, & Carter, 1993; Treiber et al., 1991), we explore the possibility of gender
differences for both hypotheses.
One important methodological issue is that accurately reporting absolute amounts or
types of food consumed is notoriously difficult, regardless of whether it is retrospective or in the
context of a daily diary (e.g., Lichtman, Pisarska, Berman, & Pestone, 1992; Maurer et al.,
2006). To avoid this problem we focused upon variability in consumption and physical activity
relative to the participant’s usual behavior, instead of assessing details of the food intake or the
activities. Specifically, participants provided 7 daily reports of how much they had eaten and
how healthy it was, as well as the amount of physical activity they engaged in, all as compared to
their own typical eating and activity. For example, one item we asked them was “Was the
amount of food you ate today more/about the same/less than usual?” This focus on within-person
variability removes the problem of establishing an absolute standard, does not require
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participants to accurately compare themselves to external guidelines, and minimizes response
bias by focusing the participants upon their own variability rather than implied social
comparisons. This method allowed us to test our hypotheses in the context of participants’ daily
lives, as well as minimize memory effects and biases associated with delayed recall. In addition,
by collecting ratings of HBVs from both participants we were able to investigate whether
couples’ combined overall levels of HBVs and the differences between their HBVs interacted
with partner influence to predict daily variation in diet or activity.
Methods
Recruitment and Participants
A community sample of committed heterosexual couples was recruited by offering
academic credit to undergraduate students at the University of Arizona in exchange for
distributing flyers to eligible couples in the community. Both individuals in participating couples
had to be: 1) over the age of 18, 2) willing to participate in the study, and 3) in a romantic
relationship for at least six weeks. On completion, participants were entered into a cash lottery in
which they could win up to $70.
Participants initially included 67 heterosexual couples; however, 5 couples did not
complete any diary data and were excluded. The resulting sample of 62 couples (total N = 124)
ranged in age from 18.8 to 65.5 years (M = 28.3, SD = 12.5); 51% of the couples were living
together, 30.8% were married and 25% had children. Relationship duration ranged from 2
months to 44 years (M = 7.6 years; SD = 10.9 years). Fifty seven percent of the participants
described themselves as European American, 1.6% as Asian American, 1.6% as African
American, 0.8% as Native Hawaiian or Pacific Islander, 4.8% as Native American, and 32% as
Other (predominantly of Hispanic and mixed backgrounds; 2.2% of the data was missing).
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Twenty-eight percent of the sample described themselves as Hispanic. Education levels included
high-school completion or less (12%), some college (58%), a professional or undergraduate
degree (20%), and a graduate degree (10%).
Procedure
Participants received a flyer with instructions to log on to a secure website where they
read a full disclosure invitation and registered for the study. The process of registration included
informed consent. Online instructions asked participants to complete all the baseline and daily
measures individually and to abstain from discussing their answers with their partners. The first
time the participants logged in they completed an initial survey, including demographic variables
and a measure of health behavior values. They were then instructed to return to the website each
day for 7 consecutive days in the evening to complete daily diary measures. The participants
could start logging the data at their convenience, but were asked to do so every day for 7 days
once they had started. Reminder emails were sent to individuals every day of the study
prompting them to work on the questionnaires separately from their partners. We checked the
time stamps of the entries and no two partners’ surveys were filled out simultaneously, or
immediately consecutively, suggesting independent completion by the participants. We later
used these time stamps to determine the day of the week for each diary entry. We used data from
all days when partners reported on their daily activities, yielding an average of 5.0 daily entries
(SD = 1.9, range = 1 to 10; participants in 3 couples logged their data for 8, 9, and 10 days).
Twenty-three percent of participants completed seven or more diary days and completion rate
was not associated with any of the key study variables. The dummy coded variable for
completeness was weakly associated with educational level (r = .27, p = .003) and relationship
duration (r = .21, p = .02). Controlling for these variables did not change the results, so results
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are reported without controlling for them. Additionally, we examined the association between
relationship duration and key study variables and found no significant correlations. In total, there
were 616 observations included in the daily analyses.
Measures
Baseline measures. The participants’ self-reported weight ranged from 97 to 212 pounds
for women (M = 134.6; SD = 24.3) and from 130 to 360 pounds for men (M = 192.7; SD = 43.5).
Participants’ BMIs were calculated using a standard formula: weight (lbs) / height (in)2 x 703.
Resulting BMIs ranged from 15.5 to 35.3 for women (M = 22.8; SD = 4.1) and from 19.3 to 47.4
for men (M = 26.9; SD = 5.2). Among women, 69.4% were normal weight, 9.7% were
underweight, 16.1% overweight, and 4.8% were obese. Thirty-five and a half percent of men
were normal weight, 1.6% underweight, 41.9% overweight, and 21% obese. Compared to
national averages, this sample has a lower prevalence of overweight and obesity, especially for
women. Although literature suggests that self-reported BMIs tend to be slightly underestimated
by both men and women, the correlations between subjective and objectively measured BMIs are
high (ranging between .95 and .98; e.g., Kovalchik, 2001; Mozumdar & Liguori, 2011). These
correlations suggest that self-reported height and weight provide acceptable measures; however,
results should be interpreted with these considerations in mind.
As suggested earlier, because participants’ perception of their own weight may have an
impact on their health behaviors, we asked the participants to rate their own weight on a 1-point
scale ranging from 1 = “very underweight” to 4 = “just right” to 7 = “very overweight.” For
women, responses ranged from “very underweight” to “very overweight;” the average estimate
was 4.6 (SD = 1.1), indicating the estimate between “just right” and “slightly overweight.” For
men, responses ranged from “slightly underweight” to “very overweight.” The average estimate
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of men’s own weight was 4.8 (SD = 1.2), indicating that they rated their weight close to “slightly
overweight” on average.
Health behavior value was calculated as the mean score of two items in the baseline
questionnaire: “How important is it to you to eat a healthy diet?” and “How important is it to you
to engage in regular physical activity?” Both items were measured on a 7-point scale, which
ranged from -3 = “not important at all,” to 3 = “very important.” Although these questions
addressed health importance, as opposed to health value, we have found that in the existing
literature the constructs closest to the ones we are assessing are usually referred to as health
values. To be consistent with this literature, we used primarily “health values” throughout the
paper, though we use health importance and health values interchangeably. The two items were
strongly correlated (r = 0.59, p < .001). They were averaged to create the composite HBV score.
HBV reported by men (M = 1.62, SE = 0.16) was not significantly different from that of women
(M = 1.72, SE = 0.11)1. Partners’ ratings of HBV were weakly positively correlated (r = .25, p =
.006). To assess overall dyadic HBV and between-partner agreement on HBVs, we used
partners’ averaged HBV scores and difference between HBV scores, respectively. The average
HBV for couples was positive (M = 1.69, SD = 0.84, Range = -.5 to 3) and partners were fairly
similar in their HBV, again with a wide range (M difference = 0.10, SD = 1.31, Range = -3 to
4.5).
Daily measures. The daily diaries included assessments of partner health-related
influence, the relative healthiness and amount of food eaten during the day, and the relative
amount of physical activity the participants engaged in during the day. To avoid participant
burden and increase compliance all constructs were assessed with single face valid items. For
each item, participants responded with respect to the time period since they awoke that morning.
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Partner health-related influence was assessed with a single item “Has your partner done
or said anything that made it either easier or harder for you to behave in a healthy way, or in a
way that makes you feel best?” The scale ranged from -2 = “He/she made it much harder” to 2 =
“He/she made it much easier,” and included 0 = “Neutral or not applicable” to capture responses
of people whose partners made no such influence attempts. The average reported daily influence
was .21 (SD = .69) for men and .10 (SD = .21) for women, indicating that most partner influence
was perceived as neutral or helpful. Women’s influence was seen as more helpful by their male
partners (b = 0.23, SE = 0.05) than vice versa (b = 0.11, SE = 0.04; F(1,60) = 4.62, p = .04).
To assess eating behavior relative to each participant’s own normal behavior, participants
reported each day whether they had eaten more, less, or about the same amount as they usually
do using the following scale: -1 = “In the past day, I have eaten less than usual,” 0 = “about the
same amount as usual,” and 1 = “more than usual.” The participants also reported whether the
food they had eaten was -1 = “less healthy than what I normally eat,” 0 = “of about the same
healthiness as what I normally eat,” or 1 = “more healthy than what I normally eat.” The relative
amount of physical activity was assessed on a scale similar to the one above: -1 = “I did less
physical activity than I usually do,” 0 = “I did about the same amount of physical activity as I
usually do,” and 1 = “I did more physical activity than I usually do.”
As expected, the mode of all of the three outcome variables was 0, showing that most of
the time people reported eating the same amount and quality of food as usual, and getting a usual
amount of physical activity. The participants reported eating about the same amount as usual
58% of the time, eating more than usual 16% of the time, and eating less 26% of the time. They
reported eating as healthily as usual 67% of the time, less healthily than usual 22% of the time,
and more healthily than usual 11% of the time. Finally, for exercise the percentages were 56%
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for the usual amount, 29% for less than usual and 15% for more than usual. The intra-class
correlations (ICC) for the item assessing amount of eating was .06, suggesting that 6% of the
variance was due to between-person differences. Similarly, the ICC for eating quality was .12
indicating that 12% of variance was due to between-person differences and for exercise amount,
ICC was .04. These small ICCs show that only a small amount of variance could be explained by
between-person differences.
We included separate reports of relative amount of food eaten, relative healthiness of
food, and relative amount of exercise to assess whether different health behaviors are susceptible
to partner influence among men and women. The correlation between eating amount and eating
quality was low and negative (r = -.15, p = .01 for men and r = -.21, p < .001 for women); the
correlation between eating amount and exercise was small for men (r = .12, p = .04) and not
significant for women (r = - .06, p = n.s.), and between eating healthy and exercise was small for
women (r = .19. p = .001) and not significant for men (r = .08, p = n.s.). The relatively small
correlations and the different correlational patterns for men and women suggested that eating
quality, eating amount, and exercise amount were relatively independent from each other and so
we treated them separately in subsequent analyses.
Statistical Analyses
Data collected from partners over a period of days is subject to multiple sources of
interdependence, including autocorrelation within persons as well as between-partner
correlations of average scores, slopes, and daily fluctuations (Kenny, Kashy, & Cook, 2006;
Laurenceau & Bolger, 2005). This is likely to result in non-independent residuals, therefore
standard regression techniques are inappropriate (Kenny et al., 2006). We thus employed a
longitudinal dyadic model which is detailed in Laurenceau and Bolger (2005). This model
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includes separate fixed and random intercepts for men and women. It also estimates between-
partner correlations of intercepts, slopes, and residuals, while simultaneously modeling
autocorrelation over days within persons. We checked for fixed and random effects of time for
all three outcome variables (eating amount, quality, activity). None of them were significant,
suggesting that monitoring these behaviors did not alter them over the course of the study. Based
on this we did not include time in our models. Having accounted for the various sources of
interdependence, hypothesis testing can be conducted by specifying appropriate fixed effects
models in the same way as is done in standard multiple regression. We used SAS PROC MIXED
to estimate all models. The estimation procedure used by PROC MIXED handles missing data
by including all observations that contain all variables in the model (Singer & Willett, 2003).
The estimation procedure then adjusts degrees of freedom and standard errors to take into
account the actual number of observations included in each analysis. We used person-centered
daily predictor (partner influence) and sample-centered dyad level predictors (average HBV and
the difference of HBV within the couple; Enders & Tofighi, 2007). Model assumptions,
including normality of dependent variables and residuals, were assessed using standard
procedures prior to conducting hypothesis tests.
We used an Average-Difference model for our analyses. This model is a derivative of the
Actor-Partner Interaction Model (APIM) and we chose it for several reasons. First, it perfectly
fits our hypothesis that both shared values and the difference between partners’ values matter.
Kenny et al. (2006) suggest that interactions should be modeled in terms that make the most
theoretical sense, as opposed to being automatically modeled as the product. Since we are
examining the dyadic-level effects of shared versus divergent partner HBV, it is important to
look at the difference scores, which are captured with the average-difference model but not the
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APIM. Second, preliminary analysis showed that actor effects for both participants in the couples
were not statistically different and therefore can be well-represented by the average score.
Furthermore, by including both the average and the difference scores into our analysis we
address concerns about the validity of difference scores used in isolation (Kenny et al., 2006).
Finally, average-difference models contain fewer terms than the APIM, and since our hypotheses
are mainly about interactions, the APIM becomes unwieldy.
We tested our hypotheses with three parallel models: one with eating amount as the
outcome, the second with eating quality, and the third with physical activity as the outcome. All
three models included the main effects of partner influence, couples’ average scores for HBV,
couples’ difference scores for HBV, and the interactions of partner influence with the average
and difference scores. The participants BMIs, subjective ratings of their own weight, and a
dichotomous variable distinguishing weekdays from weekends were included as controls in all
models. In addition, we explored their role as moderators and found one significant interaction
for men (see results). All predictors were treated as fixed effects to limit the complexity of the
model relative to the sample size. The models provide separate estimates for men and women
and so gender is not included as a separate predictor (see Laurenceau & Bolger, 2005, for more
details). Interactions were decomposed following Aiken and West (1991), with high and low
values of the continuous predictors centered at 25 and 75 percentiles. For average couple HBV,
these values correspond to health behaviors being “slightly important” for the 25 percentile and
“moderately important” for the 75 percentile. For the difference in HBV, these values correspond
to health behaviors being somewhat more important for the female partner and health behaviors
being somewhat more important for the male partner. For partner influence, low and high values
corresponded to neutral or no influence and positive influence.
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Results
The Interaction of Partner Influence and Couple Average Health Values
Our first hypothesis was that couples with high average HBV would show more effects of
partner influence than low-HBV couples. Our data show support for this hypothesis for eating
and exercise amounts among men. For eating amount, the interaction of couple average HBV
and partner influence was significant for men, F(1,478) = 9.10, p = .003, but not for women. As
illustrated in Figure 1, men in couples with a high average HBV ate significantly less than their
normal intake on days when they reported more helpful partner influence than when they
reported less helpful partner influence, b = -.15, p = .003. In contrast, men in low-HBV couples
ate about the same regardless of influence, b = .12, n.s.
[FIGURE 1 ABOUT HERE]
For exercise amount, the interaction between couple average HBV, partner influence, and
BMI was significant for men F(1, 467) = 19.98, p < .0001, but not for women. Figure 2 shows
that on days when normal weight men in high-HBV couples received positive partner influence,
they engaged in significantly more physical activity relative to their usual activity than on days
when partner influence was neutral (b = .51, p < .0001). However, normal weight men in low-
HBV couples reported lower physical activity on days when they received positive partner
influence as compared to days when the influence was neutral (b = -.33, p = .03). For
overweight and obese men regardless of HBV, partner influence had no effect. No significant
relationship between partner influence, HBV and amount of physical activity was found for
women.
[FIGURE 2 ABOUT HERE]
The Interaction of Partner Influence and Partner Differences in Health Values
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PARTNER INFLUENCE, HEALTH VALUES, HEALTH BEHAVIORS"
Our second hypothesis was that individuals who valued health behaviors more than their
partners would not be as affected by partner influence as would those who valued health
behaviors less than their partners. This hypothesis received some support. For eating quality, the
interaction between partner differences in HBVs and partner influence was significant for
women F(1, 470) = 5.84, p = .02. As shown in Figure 3, women who reported a higher HBV
than their partners showed no change in their dietary quality in response to their partners’
influence (b = .05, n.s.), but women who reported a lower HBV than their partner reported eating
healthier foods on days when they received positive partner influence (b = .33, p = .02).
[FIGURE 3 ABOUT HERE]
For eating amount, the interaction between partner differences in HBVs and partner
influence was significant for men F(1, 478) = 4.55, p = .03. Figure 4 demonstrates that the slope
for men with higher HBV than their partners is in opposite direction from the slope for men with
lower HBV than their partners (b = -.14, p = .04). Men with lower HBV than partners tended to
eat less on days when they experienced positive partner influence and men with higher HBV
than partners tended to eat more on such days, although at the centering values used for the
analysis, neither slope was significantly different from zero.
[FIGURE 4 ABOUT HERE]
Discussion
Our data suggest that partners influence eating and physical activity under certain
conditions. For couples with high average HBV, on days when men received helpful influence
from their partners, they also reported eating less than normal. Men in high-HBV couples also
reported engaging in more exercise in response to positive partner influence, an effect seen in
normal weight, but not overweight or obese men. Normal weight men in low-HBV couples
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PARTNER INFLUENCE, HEALTH VALUES, HEALTH BEHAVIORS"
reported exercising less on days when they received positive partner influence. Women who did
not value health behaviors as much as their partners responded to helpful influence by eating
healthier that day than normal, but women who were more committed to health behavior than
their partners were less susceptible to partner influence. A similar trend was observed among
men in regard to eating amounts.
Overall we found that women responded to partner influence by changing the quality of
their dietary intake, and men responded by changing the amounts of food intake and exercise.
These gender differences are consistent with previous findings showing that men are less aware
of the content of foods (e.g., Beardsworth et al., 2002) and are less likely to try new foods (e.g.,
Bonds-Raacke, 2006; Savoca & Miller, 2001), whereas women have higher awareness of the
healthiness of foods than men (e.g., Beardsworth et al., 2002) and are more likely to change their
diets in general (e.g., Savoca & Miller, 2001; Timperio et al., 2000). These results highlight that
women may be more informed of food content and more willing to change it in order to maintain
good health. Consequently, findings based on measures that involve knowledge of food content
should be interpreted with caution because the lack of reported changes in eating quality among
men may be reflecting differences in knowledge rather than differences in food consumption.
Similarly, studies on the role of gender in exercise suggest that men and women have
different attitude towards and engagement in physical activity (e.g., Shifren et al.,1993), with
men engaging in more physical activity than women (e.g., Darlow & Xu, 2011; Treiber et al.,
1991). Considering these gender differences in health behaviors, it is not surprising that men and
women would respond differently to partner influence. Specifically, as we observed, women
respond to partner’s supportive influence by using their knowledge about the content of foods
and choosing the ones that are healthier for them (at least according to the information they
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PARTNER INFLUENCE, HEALTH VALUES, HEALTH BEHAVIORS"
have). On the contrary, men, who may be less knowledgeable about the healthiness of certain
foods may respond to partner encouragement by choosing to eat less or exercise more. The
results indicating that men from low-HBV couples respond to helpful partner influence by
exercising less may appear counterintuitive. However, such men may have used exercise as a
way to counterbalance unhealthy eating. With partner influence assessed globally (i.e., it was not
specific to either exercise or eating), these men may have simply bypassed the exercise on days
when their partners were successful in helping them stay on track with their diet. On the
contrary, men in couples with high health behavior values may see merit in exercising per se and
engage in exercise regardless of their dietary intake.
Our finding that a couples’ average HBVs moderated the impact of partner influence on
dietary and activity fluctuations in men but not in women, is intriguing. On the one hand, this
contradicts the general finding that relationship factors such as marital quality and relationship
satisfaction are more significant for the health of women than of men (Coyne et al., 2001;
Kiecolt-Glaser & Newton, 2001; Rohrbaugh, Shoham, & Coyne, 2006). We expected that if
there were a gender difference, it would be in the opposite direction, with women’s health
behaviors being more affected by partner influence than men’s. On the other hand, an important
factor to consider may be not who gets affected by partner influence, but who attempts partner
influence and who is more effective at eliciting change in partner’s behavior. At least two studies
showed that women were significantly more likely to attempt influencing their partners’ health
behavior and used a wider repertoire of social control strategies that potentially allowed them to
be more effective in facilitating health-related change (Tucker & Mueller, 2000; Umberson,
1992). Consistent with these studies, women in our sample had more helpful influence than did
men. Considering that in high-average HBV couples both partners value their health and are
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PARTNER INFLUENCE, HEALTH VALUES, HEALTH BEHAVIORS"
about equally likely to respond to partner influence, if women make more helpful influence
attempts than men it follows that men would make more changes than women. Similar results
were reported by Markey et al. (2008) who showed that women’s, but not men’s, attempts to
regulate their partners’ eating behaviors were associated with their partners’ healthy dieting
behaviors. Furthermore, although people of both genders acknowledge partner influence on their
diets, men believe that their diets are influenced more so than women do (Bock et al., 1998),
suggesting that men might be more amenable to direct partner influence. It is also possible that
because of women’s greater concern about diet and appearance, men may be reluctant to bring
up these topics with their female partners, whereas women may be in a better position to do so2.
The results of the present study also suggest that people with higher HBV than their
partners may remain unresponsive to partner influence, while those with lower HBV may be
more susceptible to influence. Those who valued health less than their partners were more likely
to eat healthier than normal in response to helpful partner influence. These results may be
reflective of the notion that those with strong HBV and deep involvement in a matter are unlikely
to change their behavior based on influence attempted by those who do not share those values.
This is in accord with the idea that people tend to favor the opinions of those who share their
views, and dismiss opinions that do not support their values or identity. In the present study,
women who highly valued health behaviors were therefore unlikely to respond to the influence
of their partners who did not share their commitment to health. However, women with low
HBVs may have been less likely to have strong opinions about health, and may have lacked any
strong health-related identity. Such women may be more likely to be susceptible to partner
influence, especially coming from a partner who is determined and knowledgeable.
Limitations and Future Directions
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PARTNER INFLUENCE, HEALTH VALUES, HEALTH BEHAVIORS"
A central limitation of this study is that single-item measures were used to represent each
of the daily constructs. Although this makes it impossible to assess reliability, we believe that the
advantages of minimizing participant burden by not using multiple-item scales outweighed the
downside. Another potential limitation of this study is that we measured perceived valence of
partner influence without objectively assessing the exact content or form of the influence. This
gave us a good measure of the impact the influence had on the respondent, but did little to
increase our insight into which exact influence behaviors are more likely to be perceived as
supportive versus unhelpful. Nevertheless, the measure we used allowed us to show that helpful
partner influence – regardless of what exactly that means for each given couple – is an important
component of maintaining a healthy lifestyle. In addition, this appears to be especially true for
those who do not have strong HBVs themselves, but who have more health-conscious partners.
One way to obtain more in-depth information on partner influence without increasing participant
burden would be to collect data on provision of support in addition to receipt of partner support.
Another potential shortcoming of this study is that we used the relative quality and
amount of food consumed by the participants and the relative amount of exercise they engaged in
and did not use objective measures reflecting the actual content of participants’ diets or physical
activity. Although such measures may have allowed us to assess the accuracy of participants’
perceptions, they would have also raised the problem that daily monitoring of actual dietary
intake has a documented effect on peoples’ eating behavior (e.g., Hollis et al., 2008). In other
words, recording details of food eaten during the day usually reduces the overall intake and
makes it likely that people would eat healthier foods. Therefore, a detailed food diary for a week
may poorly reflect what participants normally eat, but having the participants report briefly on
their relative dietary quantity and quality allowed us to minimize this effect. The fact that we did
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PARTNER INFLUENCE, HEALTH VALUES, HEALTH BEHAVIORS"
not observe any linear changes in health behaviors over the duration of the study suggests we
were successful in minimizing any monitoring effects.
Another consideration is that the relatively small sample size used in this study may have
limited the statistical power. As completion rates in our study were correlated with educational
levels and relationship duration, our results may be more representative of longer relationships
between those with higher education, thus affecting the generalizability of the results. Additional
results may have emerged with more participants or more complete data, so using a larger
sample is advisable for future studies. Similarly, although our analyses revealed no connection
between relationship duration and any of the key study variables, we acknowledge that
relationship dynamics might be different in long-term married couples versus those just
beginning to date. The relatively small sample size in our study precluded us from obtaining
significant results from married vs. dating subsamples; a larger sample would allow for a
meaningful comparison.
Furthermore, the present sample had a lower percentage of overweight and obesity than
the general US population. If partner influence indeed plays a role in shaping one’s diet and
exercise, a sample with below-average BMI may also have above-average success rate of partner
influence or above-average rates of beneficial responses to partner influence. Future studies
would therefore benefit from using a more representative sample in regard to overweight and
obesity. Research would also benefit from examining measures of relationship quality as
potential moderators of the link between partner influence and health behaviors. Although in the
present study relationship duration did not have any effect on the outcomes, other measures of
relationship quality should be included in future studies. Finally, we acknowledge the limitations
of the BMI measure as the sole determinant of one’s weight-related health (e.g., Nevill, 2006).
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PARTNER INFLUENCE, HEALTH VALUES, HEALTH BEHAVIORS"
However, we chose to use BMI because it is an easily obtainable measure with widely
demonstrated connection with various aspects of health (e.g., Stommel & Schoenborn, 2010).
Conclusions
Our findings suggest that partner influence plays a role in the maintenance of a healthy
diet and physical activity and highlight the importance of dyadic analysis in capturing the
dynamics of health maintenance. Partner influence concerning one’s health behaviors may be
perceived as helpful or unhelpful and peoples’ behaviors are affected accordingly. Men and
women differ both in the helpfulness of their influence and in the changes they themselves
implement when influenced. Consistent with previous research, women had more helpful
influence on their male partners than vice versa and responded to helpful partner influence by
eating healthier foods. Men’s influence was perceived as less helpful and they responded to
helpful partner influence by eating less and changing their amount of exercise. In couples that
highly valued health behaviors, men responded to partner influence more so than did women,
perhaps due to women making more helpful influence attempts overall. Those who valued health
less than their partners were more likely to be influenced than their more health-conscious
partners.
Considering this interplay between both partners’ HBV and partner influences might
sharpen couple interventions by allowing for a more idiosyncratic approach to assessing and
treating couples. The results of studies on couple interventions for weight loss are mixed. Some
studies demonstrate greater weight loss when both partners are treated together or recruited to
support one of the partners’ weight loss (Black, Gleser, & Kooyers, 1990; McLean, Griffin,
Toney, & Hardeman, 2003; Murphy, 1982; Pearce, LeBow, & Orchard, 1981), although others
have found no differences between couple and individual interventions (Black & Lantz, 1984;
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PARTNER INFLUENCE, HEALTH VALUES, HEALTH BEHAVIORS"
Brownell & Stunkard, 1981; Dubbert & Wilson, 1984; Rosenthal et al., 1980). In one study men
were found to lose more weight when treated alone (Wing, Marcus, Epstein, & Jawad, 1991).
Our finding that partner influence interacts with both partners’ HBV and has associated
fluctuations in diet and activity suggests that partner participation in interventions targeting
health behavior changes might be a crucial component in achieving lasting outcomes. To realize
this potential, however, it is important to identify the combination of the partners’ health beliefs
and how that interacts with partner influence to determine health behavior. Doing so might
enable us to better recognize effective strategies for a given couple based on match or mismatch
in their HBV. We might consequently be better able to assist these couples in identifying the
influence strategies that are effective for them.
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Figure 1
Men’s Eating Amount Predicted from Partner Influence and Couple Average Health Behavior
Values.
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Figure 2
Men’s Physical Activity Predicted from Partner Influence, Couple Average Health Behavior
Values, and Body Mass Index (BMI).
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PARTNER INFLUENCE, HEALTH VALUES, HEALTH BEHAVIORS"
Figure 3
Women’s Eating Quality Predicted from Partner Influence and Partner’s Differences in Health
Behavior Values.
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PARTNER INFLUENCE, HEALTH VALUES, HEALTH BEHAVIORS"
Figure 4
Men’s Eating Amount Predicted from Partner Influence and Partner’s Differences in Health
Behavior Values.
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PARTNER INFLUENCE, HEALTH VALUES, HEALTH BEHAVIORS"
Footnotes
1. We conducted cross-sectional comparisons using a standard cross-sectional dyadic model,
which accounted for nesting of persons within-dyads. For repeated measures, we used the time-
varying dyadic model, which accounted for nesting of time within-persons as well as nesting of
persons within-dyads (Kenny, Kashy, & Cook, 2006).
2. We thank an anonymous reviewer for pointing out that men may be reluctant to talk with their
female partners about eating and physical activity due to women’s greater sensitivity and
concern about their diet and appearance.
