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. Author manuscript; available in PMC: 2015 Jan 1.
Published in final edited form as: Sports Med. 2014 Jan;44(1):81–121. doi: 10.1007/s40279-013-0090-5

Table 2.

Prospective studies of all designs investigating the effects of stress on indices of physical activity

Study Sample Participants
(n)		 Theoretical
framework
or model		 Study design Stress measure(s) PA measure(s); data transformation Significant findings, associations, ESs QR
Allard et al.
 2011, [259]		 Public sector employees
M + W
Mean age 45.4 years
 (SD = 10.2)		  3,224 Job strain
Job effort–
 reward
 imbalance		 Prospective
2 years
PA measured
 twice		 Copenhagen
 Psychosocial Q
 (demand–control;
 emotional demands;
 patient care
 emotional demands)
Number of life events
 in last 6 months,
 rated by impact		 1-item survey (4 responses)
Binary respondent classification: inactive at
 follow-up considered “never spent or stopped
 spending more than 4 h on low intensity
 activity or at least 2 h on intense activity per
 week”		 Stress events did not predict change in PA;
 however, stress events did predict change in
 BMI
Less physical inactivity at follow-up predicted by
 higher emotional demands (OR = 0.69; 95 %
 Cl 0.48–0.98) and patient care emotional
 demands (OR = 0.73; 95 % CI 0.56–0.94)
Decision latitude related to higher inactivity at
 follow-up (OR = 1.95; 95 % CI 1.04–3.66)		 6
Bell and Lee
 2006, [260]		 Random sample of
 young adults
W only
Age range 22–27 years		   853 Life
 transitions		 Prospective
4 years
PA only
 measured at
 time 2		 Perceived Stress Q for
 Young Women
Transitions Q		 Active Australia Survey
Summed DUR of walking, moderate and
 vigorous activities
4-category respondent classification: no, low,
 moderate, or high PA		 Age stopping full-time education was associated
 with higher stress (partial r2 = 0.02,
 p < 0.001) and less PA (p < 0.001,
 η2 = 0.028)
Age starting full-time work was associated with
 lower PA (p values <0.001, η2 = 0.036)
Other transitions not related to PA
Note: no analysis to predict PA from perceived
 stress		 7
Brown and
 Siegel,
 1988 [79]		 Students in private high
 school, grades 7–11
W only
Mean age 13 years,
 10 months		   364 Major life
 events		 Prospective
8 months
Two time points		 Life Events Survey DUR of 14 different activities >1×/week
Measured at both time points		 Life event stress at BL and not correlated with
 exercise at time 1 or time 2 (r = −0.03 to
  −0.04)
No other analysis available		 6
Brown and
 Trost, 2003
 [261]		 Australian population
 sample
W only
18–23 years at BL		  7,281 Life
 transitions
Major life
 events		 Prospective
4 years
PA measured
 both times		 Events checklist (no
 validation reported)		 BL and follow-up differed
BL: FREQ of “vigorous” and “less vigorous”
 exercise multiplied by factors of 5 and 3,
 respectively
Binary respondent classification: those above
 score of 15 considered “active”
Follow-up: FREQ and DUR of walking,
 moderate and vigorous PA multiplied by
 factors of 3.5, 4 and 7.5, respectively
Binary respondent classification: “active”
 defined as >600 MET min/week		 Life events and transitions strongly associated
 with activity status at follow-up
Inactivity predicted by marriage (OR = 1.46,
 95 % CI 1.27–1.68), having a first baby
 (OR = 2.27, 95 % CI 1.90–2.59), having
 another baby (OR = 2.06, 95 % CI
 1.70–2.51), all p < 0.0001
Beginning work (OR = 1.15, 95 % CI
 1.03–1.20, p = 0.010).
Becoming a single parent (OR = 1.32, 95 % CI
 1.04–1.67, p = 0.020)
Return to study related to LESS inactivity
 (OR = 0.77, 95 % CI 0.63–0.94, p = 0.009)
Changing work related to LESS inactivity
 (OR = 0.82, 95 % CI 0.74–0.90, p < 0.0001)		 7
Brown et al.,
 2009 [262]		 Australian population
 sample
W only
3 age cohorts: young
 (18–23 years), middle-
 aged (45–50 years),
 and old (70–75 years)
 at BL		 22,595 Life
 transitions
Major life
 events		 Prospective
3 years
PA measured
 both times		 Norbeck Life Event Q
 (modified)		 FREQ and DUR of walking, moderate and
 vigorous PA multiplied by factors of 3.5, 4 and
 7.5, respectively
3-category respondent classification: “no PA”
 (<40 MET min/week), “low” (40–600 MET
 min/week), and “active” (>600 MET min/
 week)		 Life events and transitions associated with
 activity status at follow-up. Associations
 varied by age-cohort (see paper for details)
Transitions associated with decreasing PA (all
 p < 0.001): getting married (OR = 1.27, 95 %
 CI 1.10–1.46), childbirth (OR = 1.67, 95 % CI
 1.43–1.95), illness (OR = 2.23, 95 % CI
 1.83–2.71), surgery (OR = 1.55, 95 % CI
 1.28–1.88), moving to an institution
 (OR = 1.97, 95 % CI 1.05–3.67)
Transitions associated with increasing PA:
 retirement (OR = 1.52, 95 % CI 1.22–1.88,
 p < 0.001), harassment at work (OR = 1.49,
 95 % CI 1.14–1.95, p < 0.01)
Transitions associated with increasing PA
 (p values <0.05): beginning a new personal
 relationship (OR = 1.23, 95 % CI 1.01–1.50),
 changing work conditions (OR = 1.24, 95 %
 CI 1.04–1.48), major personal achievement
 (OR = 1.29, 95 % CI 1.07–1.56), death of a
 spouse/partner (OR = 1.55, 95 % CI
 1.01–2.37), decreased income (OR = 1.20,
 95 % CI 1.04–1.38)		 7
Budden and
 Sagarin,
 2007 [210]		 Working adults from
 diverse occupations
M + W
Age range 18–74 years		   274 Theory of
 Planned
 Behavior		 Prospective
7 days
PA measured
 only at time 2		 Spielberger Job Stress
 Survey		 FREQ and DUR of exercise (2 items) combined
 into 1 composite score
Binary respondent classification: exercise or no
 exercise		 No main effect of occupational stress on PA
 measures
r = −0.10 (composite score) to −0.11 (binary
 score)
Occupational stress did inversely relate to PBC
 to exercise (r = −0.16), thus relating to
 exercise intention and exercise behavior		 7
Burton et al.,
 1999 [263]		 Medicare beneficiaries in
 Maryland, USA
M + W
>65 years
95.9 % of sample
 between 65–84 years
 at BL		  2,507 Behavior
 change
 model		 Prospective
4 years
3 time points
Mutiple waves
 of PA data		 GHQ-12 (emotional
 distress)		 1-item survey
FREQ of activities such as walking briskly,
 gardening, or heavy housework
Binary respondent classification: those
 performing “brisk” PA at least 3 times a week
 considered “active”		 There is a relationship of emotional distress
 measured at the last wave and PA
Distress did not predict initiation of PA
Moderate distress predicted maintenance of
 activity status over 4-year lapse of time
 (OR = 0.43, 95 % CI 0.28–0.67). Severe
 distress did not predict maintenance, however
Low emotional stress, 35.8 % initiate activity,
 69 % maintain; medium emotional stress,
 18.0 % initiate activity, 40 % maintain; high
 emotional stress, 14.6 % initiate activity,
 36.4 % maintain (Table 3 of study)		 6
Burton et al.,
 2010 [273]		 Adults enrolled in
 university worksite
 16-week intervention
M + W
Mean age 36.5 years
 (SD = 8.6)		    16 Resiliency Prospective
Stress/PA
 intervention
 (open trial)
No control
 group
Measures pre/
 post		 Stress subscale from
 DASS-21		 Modified AIHW Survey
Total DUR of PA in previous week
Time weighted by intensity factor
Pedometer step counts over 7 days		 Stress level improved pre-post (p = 0.013)
Pedometer steps and PA survey data did not
 improve pre-post		 6
Castro et al.,
 2002 [145]		 Sedentary caregivers for
 relatives with
 dementia
W only
Age >50 years
Mean age 62.7 years
 (SD = 9.2)		   100 Caregiving
 stress;
 stressed
 population		 Prospective
1 year
Intervention
 (RCT)		 PSS-14
Screen for Caregiver
 Burden
BDI
TMAS		 Exercise adherence
Program retention
Motivational Readiness for PA		 BL PSS and Caregiver Burden does not predict
 PA adherence over 12-month period or months
 of program contact or total phone or mail
 contacts
BL anxiety and depression does predict PA
 adherence
Those who did not complete the trial had higher
 BL stress (mean PSS = 22.5, SD = 4.8) and
 spent more hours at BL in caregiving duties
 (mean = 100.5, SD = 41.7) than those who
 did complete the trial		 7
Chambers
 et al., 2009
 [264]		 Survivors of colorectal
 cancer
M + W		   978 Health stress;
 stressed
 population		 Prospective
3 years post-
 diagnosis
4 waves of PA
 data		 Constructed Meaning
 Scale (cancer threat
 appraisal)
Brief Symptom
 Inventory-18
 (anxiety, depression,
 and somatization)		 Modified Active Australia survey items
Total DUR of PA in previous week for walking,
 moderate PA, or vigorous PA. Time-weighted
 by intensity factor
3-category respondent categorization: inactive
 (0 min/week), insufficiently active
 (1–149 min/week), or sufficiently active
 (>150 min/week)		 Continuous cognitive threat appraisal predicted
 inactive PA (OR = 0.95, 95 % CI 0.9,1.0) and
 insufficiently active PA (OR = 0.96, 95 % CI
 0.9, 1.0). Overall model (p = 0.031)
Previous anxiety predicts increase in low levels
 of PA (<2 h/week) (OR = 1.11, 95 % CI
 1.05–1.19, p = 0.004)
No evidence that the distress and PA association
 changed over time
Depression and cognitive threat did not predict
 increases in PA		 7
Delahanty
 et al., 2006
 [285]		 Individuals in the
 Diabetes Prevention
 Program lifestyle
 intervention
M + W		   274 None Prospective
Intervention
3 waves of PA
 data		 Perceived Stress Q-30
Beck Depression and
 Anxiety Inventories		 Stages of change for exercise (5 items)
Modifiable Activity Q
Data analyzed as: continuous PA and
 dichotomous [coded as meeting guidelines for
 PA (150 min/week)]		 BL perceived stress inversely associated with PA
 at 3 time points: (BL, r = −0.16, p = 0.01;
 1-year PA, r = −0.18, p = 0.003; 2-year PA,
 r = −0.17, p = 0.007)
Similar pattern of results for anxiety and
 depression
Stress did not independently predict PA at any
 time point when depression, self-efficacy, stage
 of change, and other factors were modeled
Depression predicted PA at BL (p = 0.03)
Stress did not alter the gender-PA relationship		 7
Dobkin et al.,
 2005 [291]		 Fibromyalgia patients
W only
Mean age 49.2 years
 (SD = 8.7)		    39 Behavior
 change
 theories		 Prospective
Intervention
3 months
 follow-up
PA measured 3
 times		 WSI Average mins of weekly stretching Stress at BL and during the treatment were the
 best predictors of poor maintenance of
 stretching
Every 1 SD increase in BL stress related to a
 −28.29 min change in stretching at 4, 5, and
 6 months (p < 0.05)
Every 1 SD increase in stress change over
 3 months was related to a decline in stretching
 (−38.58 min) in months 4, 5, and 6 (p < 0.01)
Stress did not impact weekly changes in any
 outcome		 7
Dobkin et al.,
 2006 [289]		 Fibromyalgia patients
W only
Mean age 49.2 years
 (SD = 8.7)		    39 Behavior
 change
 theories		 Prospective
Intervention
12 weeks
PA measured
 12 times		 WSI Daily exercise log recording exercise type,
 FREQ, DUR, and intensity. Energy
 expenditure calculated		 Over 12 weeks, participants with higher BL
 stress reduced their aerobic exercise
 participation at faster rates (p = 0.02) Every
 1 SD increase in stress resulted in a change of
 −3.19 min of aerobic exercise and −11.33
 kcals of energy expenditure
With interactions included in the model, stress
 did not impact initial participation in the
 aerobic exercise program
Those with higher BL stress decreased energy
 expenditure at a higher rate (p = 0.02)		 7
Dougall et al.,
 2011 [286]		 First-year students
M + W
Mean age 20.6 years
 (SD = 5.34)
Age range 17–47 years		   149 Life
 transition		 Prospective
Intervention
 (~13 weeks)
PA measured
 weekly		 PSS-4 1-item scale modified from Godin Leisure Time
 Exercise Q (DUR of strenuous activity)
Approximate number of times a university fitness
 center was utilized
Stage of change for exercise		 Main effect of stress on fitness center use (β =
 −0.10, SE = 0.05, p < 0.05) but not vigorous
 exercise or intention to exercise
Participants with high stress in the later stages of
 change had more PA intention than those in
 earlier stages of change (p < 0.02)
3-way interaction for stress, intervention
 response, and time (p = 0.05). At the end of
 the semester, responders low in stress had
 higher PA
3-way interaction between stress, time, and stage
 of change (p = 0.09). Those in the later stages
 of change for exercise and low in stress had
 higher fitness center use initially		 8
Dunton et al.,
 2009 [265]		 Healthy, community-
 dwelling adults who
 do not regularly
 exercise
M + W
Mean age 60.7 years
 (SD = 8.22)
Age range 50–76 years		    23 None Prospective
2 weeks
Daily diary
 study
PA assessed at
 fixed intervals
 4×/day		 2 items: (1) problematic
 social interaction; (2)
 experience of a
 stressful event
NA (average of ratings
 for: stressed, upset,
 lonely, annoyed,
 tense/anxious, sad,
 discouraged)		 Respondents queried about whether they
 performed 1 of 12 activities (yes/no) and DUR
 if completed
Data transformation: sum of mins for activities
 over 3.0 METs		 Only 10 % of the sample reported a stressful
 event
Stress events did not predict PA (r = 0.09)
NA (subjective stress) did predict MVPA (HLM
 COEFF = −0.09, robust SE = 0.02,
 p < 0.001)
Within-person variance explained by NA was
 0.5 %, and for stress events was 0.8 %		 6
Durrani et al.,
 2012 [124]		 Diagnosed with
 hypertension in
 e-counseling program
Individuals with anxiety
 or traumatic stress
 excluded
M + W		   387 None Prospective
Intervention
4 months
PA assessed
 2 times		 PSS-10
BDI-II		 HPLP-II (used to measure readiness for exercise
 change on a 4-point continuous scale)		 BL stress (r = −0.18; p = 0.001) and
 depression were inversely associated with BL
 readiness to change exercise
Change in stress and depression over the 4-month
 intervention inversely correlated with exercise
 readiness post-intervention (r = −0.17;
 p = 0.01)		 7
Grace et al.,
 2006 [274]		 Healthcare workers from
 3 worksites
Pregnant W
Mean age 39.5 years
 (SD = 7.95)		 243 (201
 non-
 pregnant)		 Role strain Prospective
Case control
PA measured at
 3 time points		 Work-Family Spillover
 Scale		 HPLP-II (8-items for PA) Levels of PA did not vary across groups and did
 not change across the pregnancy and
 postpartum period; however, a trend was
 observed for decreased inactivity during
 maternity leave
Negative work-to-family spillover and negative
 family-to-work spillover was not associated
 with PA at BL (r = −0.07 to 0.03, NS) or at
 the last time point (r = −0.14 to 0.22, NS) in
 either the maternity group or the comparison
 group
When returning to work (final assessment), PA
 was related to positive work-to-family
 spillover		 8
Griffin et al.,
 1993 [191]		 College undergraduates
M + W
Mean age 18.4 years
 (SD = 1.22)		    79 None Naturalistic
Exam stress vs.
 early
 semester (7-
 week period)
No control
 group		 PSS-4 items
Daily Hassles and
 Uplifts
Positive and Negative
 Affect Schedule
Academic demands
 (1 item; 1–7 scale)		 Wellness Inventory of the Lifestyle Assessment
 Q
Exercise subscale items: efforts to maintain
 fitness over past 3 days (“I walked or biked
 whenever possible”; 1–6 response scale)		 PSS related to exercise at start of semester
 (r = −0.22, p < 0.05), but not at the end of
 the semester (r = −0.14)
No association between academic demands,
 academic stress, hassles, or negative affect
 with exercise
Exercise declined from low stress time of
 semester to finals; however, this was NS. Early
 semester: mean = 14.78, SD = 5.19; finals:
 mean = 14.64, SD = 5.78
Among subjects who experienced an increase in
 demands from early semester until finals,
 exercise decreased (but NS)
Early semester: mean = 14.98, SD = 5.27;
 finals: mean = 14.36, SD = 5.57
Among subjects who experienced an increase in
 demands the week before finals (vs. early
 semester), exercise decreased (but NS). Early
 semester: mean = 15.15, SD = 5.19; finals:
 mean = 14.94, SD = 5.37
Exercise increased for those whose academic
 demands remained the same or declined during
 finals (NS)
When controlling for BL exercise, academic
 demands at finals and the week before finals
 did not predict exercise at the second time
 point		 7
Groeneveld
 et al., 2009
 [278]		 Construction workers at
 higher risk for CVD
M only
Mean age 46.1 years
 (SD = 9.3)
Age range 30–65 years		  4,017 None Prospective
Intervention		 Dichotomous: 12
 questions regarding
 tiredness and stress.
 Scored as “yes” if 5
 of 12 statements were
 endorsed		 Binary respondent classification: participation in
 the lifestyle program (yes/no); dropout of
 program (yes/no)		 35.7 % of participants were tired/stressed, while
 only 30.5 % of non-participants were tired/
 stressed
Crude OR = 1.27 (95 % CI 1.08–1.49)
Relationship disappeared in multivariate models
 (age, smoking, type of work, symptoms)
Stress had no relationship with dropout from the
 study (OR = 0.94, 95 % CI 0.56–1.57)		 4
Ho et al.,
 2002 [181]		 Residents of NY metro
 area
M + W
Mean age 46 years
 (SD = 11) for M and
 47 years (SD = 13)
 for W		   244 Life event Retrospective
 and
 prospective
4-month
 follow-up		 Resident of NY after
 World Trade Center
 attack and in World
 Trade Center during
 attack
Level of distress
 (1–10): 1 item		 1 item
3-category respondent classification: exercise
 behavior “still abnormal”, “normalized”, or
 “no initial change”		 Residents exercising 33 % less after attacks
Those actually at the World Trade Center
 exercise 1.5 times less (p = 0.07) than
 residents not the World Trade Center
4 months later, residents of NY were exercising
 13 % less		 6
Hooper and
 Veneziano,
 1995 [288]		 University employees
M + W
Age not reported		   338 None Prospective
Intervention
 (20 weeks)		 1 item from Wellness
 Q, re.: stress at home
 (not validated)		 Binary respondent classification: exercise
 program starters vs. non-starters		 Stress significantly discriminated starters from
 non-starters
Non-starters: 1.34 (SD = 0.57) on stress at home
Starters: 1.22 (SD = 0.44) on stress at home
Both groups expressed an ability to cope with the
 stress		 6
Hull et al.,
 2010 [266]		 Young adults
M + W
Mean age 24.1 years
 (SD = 1.1)		   638 Life
 transition		 Prospective
2 years
PA measured 2
 times		 Cohabitation, marriage,
 parenthood
 transitions		 Past year leisure time PA Q
FREQ and DUR of every type of LTPA activity
 over last year completed at least 10 times
Data expressed as h/week		 Marriage does not impact PA in young adults
Compared with those who stayed with the same
 number of children over the 2-year period,
 having a child (PA change = −3.7, SD = 6.0,
 p = 0.01), having a first child (−3.9,
 SD = 5.6, p = 0.02), and having a subsequent
 child (−3.5, SD = 6.4, p = 0.02) is associated
 with a reduction in PA		 8
Johnson-
 Kozlow
 et al., 2004
 [279]		 College students
M + W
Mean age 24.4 years
 (SD = 0.06)		   338 Life events Prospective
Intervention
1 year
PA measured at
 2 time points		 Life Experiences
 Survey		 7-day PA recall
Data expressed as kcal/kg/week		 44 % of sample was inactive at BL
No direct relationship, but stress by time
 interaction was significant (p = 0.015)
M with higher stress at 1 year had greater
 exercise in the exercise intervention group
 (p = 0.008)
In the control condition, M with low stress
 tended to be more physically active at 1 year
No relationship between stress and PA was
 observed for W		 8
Jones et al.,
 2007 [267]		 Public service workers
M + W
Mean age 40 years
 (W) and 41 years (M)
Age range 18–65 years		   422 Job strain Prospective
 diary study
4 weeks
Daily PA
 measure		 Job Content Q
 (Framingham
 version)
Positive and Negative
 Affect Schedule
Work hours		 2 items: moderate and vigorous exercise (yes/no
 response)
If “yes” response, respondents required to
 describe the exercise		 Daily negative affect had an inverse relationship
 with exercise for M (p = 0.001) but not for W
For M, job demand had an effect on daily
 exercise (β = −0.48, SE = 0.13, t = −1.98,
 p = 0.049). M in low-demand jobs showed
 greater reductions in PA than M in high-
 demand jobs
There was an interaction with negative affect
 (β= 0.22, SE = 0.06, t = 2.37, p = 0.02).
 Negative affect also interacted with job control
 (β= −0.18, SE = 0.05, t = −2.51,
 p = 0.01). When combined with NA, high job
 control can result in less exercise
Long work hours were associated with less
 exercise for W but not for M		 7
Jouper and
 Hassmén,
 2009 [287]		 Adults in Qigong
 exercise program
M + W
Mean age 36.5 years
 (SD = 17)		    87 Tense-
 energy
 model		 Prospective
Non-
 intervention
 exercise
 program		 Stress–Energy Scale Exercise diary (sessions per week)
Concentration on Qigong (1–10 scale, 1 item)
Exercise intention		 Exercise sessions negatively correlated with
 stress (r = −0.22, p < 0.05, 1-tailed test), but
 there was no correlation of stress with exercise
 intention (r = 0.07) or concentration (r =
  −0.16)
Stress predicted exercise session (R2 = 0.03)		 8
King et al.,
 1997 [290]		 Community-dwelling
 adults
M + W
Mean age: M 56.2 years
 (SD = 4.1); W
 57.1 years (SD = 4.3)
Age range 50–65 years		   269 None Prospective
Intervention
RCT
Home- vs.
 group-based
 exercise		 PSS-14
BDI
Taylor Manifest
 Anxiety Scale		 Exercise adherence
Binary respondent classification: “successful”
 adhering over 2 years defined as completing
 >66 % of prescribed workouts		 Stress was a strong predictor at year 2
 (p < 0.0001)
Among persons assigned to either home-based
 program, those initially less stressed
 (PSS <19) were more likely to be successful
 than those initially more stressed (53.9 vs.
 32.4 %, χ2 [1, N = 173] = 7.84, p < 0.01)
Most successful adherers at year 2 were
 (a) home-based exercisers, (b) less stressed,
 (c) more fit, (d) less educated
At year 1, the subgroup with the greatest
 adherence (82.4 %) comprised nonsmokers
 assigned to home-based exercise and reporting
 low stress (PSS <19)
Energy but not anxiety or depression was a
 strong predictor of adherence		 7
LeardMann
 et al., 2011
 [268]		 US Military Service
 personnel
M + W
41.5 % born between
 1960 and 1969		 38,883 None Prospective
3–5 years
PA only
 measured at
 time 2		 PTSD Checklist-
 Civilian Version
 (evaluated twice)		 Items from NHIS. FREQ and DUR of strength
 training, moderate PA and vigorous PA
5-category respondent classification
PA only assessed at follow-up		 Those with new-onset of PTSD symptoms are
 less likely to engage in moderate activity at
 “active” level (OR = 0.71, 95 % CI
 0.60–0.84); less likely to engage in vigorous
 activity at “slightly active” (OR = 0.66, 95 %
 CI 0.49–0.89), “active” (OR = 0.58, 95 % CI
 0.49–0.70), and “very active” (OR = 0.59,
 95 % CI 0.46–0.76) levels; more likely to be
 unable to engage in strength training
 (OR = 2.06, 95 % CI 1.45–2.93)		 6
Lutz et al.,
 2007 [20]		 Blue-collared workers
M + W
Mean age 43.6 years
 (SD = 9.8)		   203 None Prospective
2 months
PA measured at
 2 points		 PSS-10 Godin Leisure Time Exercise Q
PA recalled over the previous month
FREQ of strenuous exercise used for analyses		 In SEM analysis: (a) the stress-to-exercise model
 provided the best fit and was significantly
 different than the stability model; (b) stress and
 PA were not concurrently related at time 1 but
 were concurrently related at time 2; (c) stress at
 time 1 significantly predicted exercise at time 2
 (r = −0.16; path COEFF = −0.13), but
 exercise at time 1 did not predict stress at time
 2 (r = −0.03; path COEFF = −0.02)		 7
Lutz et al.,
 2010 [17]		 Undergraduate
 psychology students
W only
Mean age 19.3 years
 (SD = 2.1)
Age range 17–33 years		    95 None Prospective
6 weeks
PA measured
 each week		 WSI-2 scales used:
 stress FREQ and
 stress intensity		 Exercise diary recorded daily
FREQ, DUR, and perceived intensity of exercise
 were the outcome variables of interest
Stages of change for exercise (each stage
 modeled as a dichotomous variable)		 No main effects of stress events or stress
 intensity on exercise mins per session
When exercise stages were run as dichotomous
 variables, the maintenance stage was a
 significant moderator of the stress event and
 exercise duration relationship (β = 0.52,
 SE = 0.11, t(79) = 4.56, p < 0.001). Similar
 relationship found for exercise frequency
 (β = 0.04, SE = 0.01, t(79) = 4.12,
 p < 0.001) and exercise intensity (β = 0.04,
 SE = 0.01, t(75) = 2.69, p < 0.001)
When exercise stages were run as dichotomous
 variables, the maintenance stage was a
 significant moderator of the stress intensity and
 exercise duration relationship (β = 0.18,
 SE = 0.04, t(79) = 5.00, p < 0.001). Similar
 relationship found for exercise frequency
 (β = 0.012, SE = 0.003, t(79) = −2.265,
 p < 0.05) and exercise intensity (β = 0.01,
 SE = 0.004, t(75) = 1.89, p < 0.062)		 6
Macleod
 et al., 2001
 [414]		 Working Scottish adults
 from 27 worksites
M only
Mean age at first
 screening 48 years		 5,388 (time
 1); 2,595
 (time 2)		 None Prospective
5 years
PA measured
 twice		 Reeder Stress Inventory
 (summary score, 1–8)		 1-item survey for sedentary behavior (h/week)
Binary respondent classification: “sedentary”
 defined as <3 h/week		 At first screening, stress related to more
 sedentary behavior (p = 0.005). 26 % of high-
 stress group was sedentary vs. 19 % of low-
 stress group
Sum of stress at time 1 and 2 and change in stress
 from time 1 to 2 not related to sedentary
 behavior at time 2		 5
Miller et al.,
 2004 [275]		 Healthy young adults
M + W
Mean age 18.3 years
 (SD = 0.9)		    83 None Prospective
13 days
PA measured
 daily		 Salivary cortisol
Daily ratings of
 subjective stress (4×/
 day)		 Paffenberger Activity Scale (1993)
Data analyzed as mins of intense PA		 Daily (cumulative) stress ratings were not
 associated with health behaviors, including
 mins of intense PA (r = −0.04)		 6
Moen et al.,
 2011 [284]		 Best Buy corporate
 headquarters
 employees
M &W
Average age 32 years		   659 Job strain Prospective
Stress
 intervention
 (Results Only
 Work
 Environment
 program) vs.
 control
7 months
PA measured
 twice		 Negative work-home
 spillover
Psychological distress		 Average FREQ of exercise/week over last
 4 weeks		 Results Only Work Environment program
 resulted in no changes in distress vs. control
Negative work-home spillover was related to
 distress (p < 0.001)
Those in control group decrease more in exercise
 overtime (p < 0.05). Thus, stress management
 program may help to attenuate decline in PA
 behavior
Effect mediated by reductions in negative work-
 home spillover (p < 0.05)		 8
Oaten and
 Cheng,
 2005 [192]		 Introduction to
 Psychology students
M + W
Mean age 20 years
Age range 18–50 years		 57: 30 exam
 stress; 27
 control		 Self-
 regulation
 model		 Naturalistic
Exam stress vs.
 early
 semester
Within-person
 and control
 group
 comparison		 GHQ-28 (emotional
 distress)
DASS
PSS-10		 PA 3-item survey: FREQ and DUR over last
 week
“Ease” of exercise regimen (“How easy was it to
 fit exercise into your schedule over the last
 week?”)
All items on 5-point scale		 No difference between groups in exercise
 behavior at BL
Those in exam stress group reported a decline in
 all exercise FREQ (df = 1, 26, F = 71.39,
 p < 0.001), DUR (df = 1, 26, F = 35.71,
 p < 0.001), and reported ease (df = 1, 26,
 F = 31.24, p<0.001) during exam period. No
 means reported
The control group did not change exercise
 behaviors pre to post
No relationship between change in perceived
 stress (PSS) or emotional distress (GHQ) and
 the change in exercise behavior. However,
 residuals of changes in PSS and GHQ were
 related to residuals of changes in exercise
 behavior		 8
O’Connor
 et al., 2009
 [269]		 Government workers
M + W
Mean age 42.6 years
Age range 18–65 years		   422 Diathesis-
 stress
 perspective		 Prospective
Diary study
4 weeks		 Daily hassles:
 respondents reported
 each stressor
 experienced and rated
 each on 0–4 scale
Only FREQ of hassles
 reported		 2-item exercise survey
Daily exercise participation: binary response
 (yes/no)		 Hassles inversely related to exercise participation
 over time (COEFF = −0.055, SE = 0.022,
 p = 0.013, 95 % CI 0.907–0.988)
Participants with average (β = −0.064, t =
 −2.417, p < 0.05) or high (β = −0.149,
 t = −3.93, p < 0.001) levels of order (a facet
 of conscientiousness) exercised more on days
 when they experienced daily hassles		 6
Oman and
 King, 2000
 [184]		 Healthy, sedentary
 adults
M + W
Mean age 56.5 years
 (SD = 4.3)
Age range 50–65 years		   173 Life events Prospective
RCT
 intervention
2 years		 Social Readjustment
 Rating Scale		 Exercise program adherence: (percentage of
 prescribed workouts completed)
Stage of exercise adoption		 Stress not related to adherence in the adoption
 phase (months 1–6)
Life event and exercise adherence were
 associated during the maintenance phase
 regardless of exercise intensity or format
 (home- or class-based)
Months 7–12: F (4, 153) = 3.56, p = 0.008.
Months 13–18: F (4, 140) = 2.52, p = 0.044.
Months 19–24: F (4, 153) = 3.66, p = 0.007		 8
Payne et al.,
 2002 [332]		 British employees
M + W
Age >16 years (32 %
 between 35 and
 44 years)		   213 Job strain,
 Theory of
 planned
 behavior		 Prospective
1-week lag
(PA measured
 only 1×)		 Karasek Job Content Q
Data run as continuous
 and sample divided
 by median split on
 job strain		 Open-ended question for exercise type and DUR:
 “What types of exercise did you do today and
 how long did you devote to each?”
Exercise defined as “taking part in purposeful
 activity which is often structured and pursued
 for health and fitness benefits”
Data run as continuous and dichotomous
Psychological predictors of exercise intention
 also collected (intention, PBC, attitudes,
 norms, etc.)		 No correlation between exercise behavior and
 work barriers (including work stress; r =
 −0.08), job demands (r = −0.11), and job
 control (r = 0.08)
Those with increased work demands have greater
 failure in ability to fulfill their exercise
 intentions (succeeded, M = 3.63, SD = 0.64;
 failed, M = 3.95, SD = 0.57; F (1,
 147) = 7.87, p < 0.01, ES = 0.50)
Intentions were not associated with job strain
Job demands moderated the relationship between
 self-efficacy and the probability of being an
 exercise intender who actually exercised
 (OR = 0.93, 95 % CI 0.87–0.99)
People in high-strain jobs have less exercise self-
 efficacy, PBC, and did less exercise at follow-
 up (however, they did not intend to do any less
 exercise)		 7
Payne et al.,
 2005 [333]		 British employees
M + W
Age range 16–64 years
 (32 % between 35 and
 44 years)		   286 Job strain,
 Theory of
 planned
 behavior		 Prospective
1-week lag
(PA measured
 only 1×)		 Karasek Job Content Q
 (11 items)
Work barriers (hours,
 stress, travel)		 Open-ended question for exercise type and DUR:
 “What types of exercise did you do today and
 how long did you devote to each?”
Exercise defined as “taking part in purposeful
 activity which is often structured and pursued
 for health and fitness benefits”
Data calculated as hours (continuous)		 No direct effect of job demands (r = −0.11) or
 job control (r = −0.03) on exercise behavior
Intention, job demands, and job control
 interacted but only explained 1 % more of the
 variance in exercise behavior
Job demands and control affected exercise
 indirectly by lowering perceptions of perceived
 behavior control over exercise
Job demands did not moderate the intention/
 behavior relationship for exercise		 7
Payne et al.,
 2010 [281]		 Employees
M + W
Age >16 years
(41 % between 25 and
 34 years)		    42 Job strain,
 Theory of
 planned
 behavior		 Prospective
Intervention
Diary study
Daily for
 14 days		 Karasek Job Content Q
Work-related affect
 instrument: anxiety
 and depression		 Open-ended question for exercise type and DUR:
 “What types of exercise did you do today and
 how long did you devote to each?”
Exercise defined as “taking part in purposeful
 activity which increases the heart rate and
 produces at least a light sweat and is often
 structured and pursued for health and fitness
 benefits”
Data transformed to total hours of exercise/day		 No main effect of job demands
Demands moderated the intention/exercise
 relationship (COEFF = −0.10, SE = 0.01,
 p < 0.01, OR = 1.04, 95 % CI 1.01–1.06)
Anxiety and depression had no main effect on
 exercise and did not moderate intention-
 behavior relationships
Note: daily planning intervention backfired
 (people in no intervention group were more
 likely to exercise)		 7
Phongsavan
 et al., 2008
 [276]		 Patients with anxiety
 disorders
M + W
Mean age 39.0 years
 (SD = 11.9)		    73 None Prospective
8 weeks
Exercise and
 CBT
 intervention		 DASS-21 Modified Active Australia survey items
FREQ and DUR of PA in previous week for
 walking, moderate PA, or vigorous PA
3-category respondent categorization: inactive
 (0 min/week), insufficiently active
 (1–149 min/week), or sufficiently active
 (>150 min/week)
Pedometer steps
Exercise compliance vs. non-compliance		 Relationship between exercise (Active Australia
 Survey) and stress not analyzed. Stress and
 pedometer steps association also not reported
Those with higher mean scores on stress were
 more likely to drop out of the PA program, but
 this was not statistically significant
No relationship between stress and PA program
 compliance		 6
Reynolds
 et al., 1990
 [245]		 10th graders from
 California, USA, high
 schools
M + W
Age range 14–16 years
 (median 15 years)		   743 None Prospective
16 months
PA measured at
 BL, 4 and
 16 months		 Situational Stress
 Survey (scale
 included as appendix
 in article)		 FREQ of 19 activities (i.e., ice skating, hiking)
 rated on 1–7 scale. Each rating associated with
 a weight to calculate a total PA score. Score
 represents the total number of times subject
 engaged in >20 min of nonstop PA (scale
 included as appendix in article)		 At month 4, stress predicts less exercise, in W
 only, controlling for BMI and BL PA (β =
 −1.27, F = 6.18, p = 0.01). Stress did not
 predict PA at month 16
No significant correlations between stress and PA
 at either follow-up time point
At month 4, r = −0.09
At month 16, r = −0.03		 6
Rod et al.,
 2009 [270]		 Age-stratified random
 sample of Danish
 adults
M + W
Age range at BL
 20–93 years		  7,066 Allostasis Prospective
10 years
PA measured at
 2 time points		 2-item survey:
 perceived stress
 intensity and FREQ;
 combined into single
 score
Stress only assessed at
 follow-up		 Item inquiring about level of LTPA
Binary respondent classification: active vs.
 inactive		 Those with medium (OR = 1.19, 95 % CI
 1.07–1.32) or high (OR = 2.63; 95 % CI
 2.25–3.08) levels of stress were more likely to
 be physically inactive at BL. 12 % of the low-
 stress group was inactive vs. 26 % of the high-
 stress group
Those stressed were more likely to become
 physically inactive during follow-up than the
 low-stress group (OR = 1.90; 95 % CI
 1.41–2.55)
Those in the high-stress group were not more
 likely than the low-stress group to become
 active (OR = 0.78, 95 % CI 0.48–1.14).
 Authors state “There were no differences in
 the proportions of inactive persons who
 became active during follow-up according to
 stress”		 5
Rodriguez
 et al., 2000
 [271]		 Nulliparous Swedish
 pregnant W
W only
Mean age 27 years
 (SD = 4)		   350 Stressed
 population		 Prospective
32 weeks into
 pregnancy
PA measured at
 2 time points
 (weeks 20
 and 32)		 PSS-11 (Swedish
 version)		 Exercise FREQ (1–5 scale) and DUR over last
 4 weeks
Exercise type queried
Data transformed into single composite score to
 reflect time in exercise/week		 Exercise decreased from pre-pregnancy to week
 20 (p < 0.001). There was no change from
 week 20 to week 32
Stress at week 12 correlated with exercise at
 week 20 (r = −0.20, p < 0.05) but not week
 32 (r = −0.07)
Contemporaneous correlation of stress and
 exercise at week 32 was significant (r =
 −0.11, p < 0.05)
SEM analysis found significant path from stress
 at week 12 to exercise at week 20 (β = −0.20)		 7
Roemmich
 et al., 2003
 [193]		 Children
Boys + girls
Boys mean age
 10.1 years (SD = 1.2)
Girls mean age
 10.1 years (SD = 1.6)
Age range 8–12 years		    25 None Experimental
Laboratory
 stressor (Trier
 Social Stress
 Test) vs.
 neutral
 control
Crossover
 design (order
 randomized
 on 2 separate
 days)		 Visual analogue scale
 for perceived stress
Cardiovascular stress
 reactivity (median
 split)		 Children volitionally cycled at a constant
 moderate intensity over a 30-min post-
 condition period
Data analysis on DUR of cycling; energy
 expenditure from cycling (kcal)		 Significant main effect of stress condition: lesser
 energy expenditure (df = 1, 23, F = 14.97,
 p < 0.001) and exercise minutes (df = 1, 23,
 F = 7.61, p < 0.001). No means for main
 effect reported
Subjects reduced their PA by 21 % on the stress
 condition day
Changes in perceived stress were not correlated
 with changes in exercise behavior (r = −0.19,
 p > 0.35)
Children with high stress reactivity had a greater
 decline than children with low reactivity		 8
Sherman
 et al., 2009
 [185]		 Undergraduate students
M + W
Mean age 20.11 years		 54 (only 17
 analyzed)		 None Naturalistic
Self-rated most
 stressful final
 exam vs.
 period
 2 weeks
 beforehand
No control
 group		 Urinary catecholamines
 (indicator of
 sympathetic system
 activation)
2 items: subjective
 appraisal of exam
 stress (1–4 scale)		 1-item survey: DUR of exercise (min) Note: analysis of stress and exercise was
 exploratory
17 participants reported exercising the night
 before each urine sample was collected
There was a decrease in exercise DUR from the
 pre-test (mean = 61.18, SE = 11.94) to the
 post-test (mean = 30.88, SE = 7.74), F (1,
 16) = 5.67, p = 0.03, η2 = 0.26. Cohen’s
 d = 0.62
Results suggest that students reduced their
 exercise during the midterm exam period		 6
Smith et al.,
 2005 [186]		 Parents of a child with
 and without a cancer
 diagnosis
M + W
Mean age of stressed
 group 35.5 years
 (SD = 9.0)
Age range 19–58 years		    98 Stressed
 population		 Case control
Prospective
Cancer
 diagnosis vs.
 no diagnosis
  3 months
PA measured
 twice
 (2 weeks
 after
 diagnosis and
 3 months
 later)		 PSS-14
Recent Life Changes Q
POMS		 Paffenbarger PA Q
Data expressed as kcal expended/week
Hours of TV viewing/week
Hours of sitting/week		 Overall, the stressed group reported less PA than
 the control group F (1, 94 = 43.38,
 p < 0.0001).
Parents of cancer patients reported only
 400–500 kcal/week of PA vs.
 1,400–1,500 kcal/week in parents of healthy
 children
Group × time interaction significant F (1,
 94 = 6.04, p < 0.05). Parents of cancer
 patients increased their PA over time
 (t (48) = −2.50, p = 0.01), but parents of
 healthy children did not change
ES at time 1 = 1.71; ES at time 2 = 1.13
A group × time interaction was significant for
 TV viewing F (1, 94 = 5.84, p = 0.01).
 Parents of children with an illness watched
 more TV at time 1 but the groups were the
 same at time 2		 9
Smith et al.,
 2008 [272]		 Working adults
 registered in Canadian
 National Population
 Health Study
M + W
Age range 25–60 years		  3,411 Job strain
Chronic
 stress
 exposure		 Prospective
Stress measured
 in 1994
PA measured in
 1996		 Job control subscale of
 Kasarek Job Content
 Q
Wheaton Stress Q (18-
 item): personal,
 environmental,
 financial stress
Composite International
 Diagnostic Interview
 (distress; University
 of Michigan revision)
Household income
 adequacy		 Survey of LTPA and sport
Energy expenditure from time, DUR, and FREQ
 in the last 3 months
PA expressed as kcal/kg/day		 Those in the lowest quartile of job control had
 the greatest level of psychological distress
Low job control measured in 1994 predicted PA
 in 1996 wave (β = −0.065, t = −3.284,
 p = 0.001) even when adjusted for many
 covariates (e.g., BMI, gender, health, back
 pain, education, etc.)
In model comparing all stress exposures, low job
 control (β = −0.052, t = −2.52, p = 0.012)
 and high environmental stress (β = −0.07,
 t = − 2.58, p = 0.010) predicted PA
Relationships of (a) job control and
 (b) environmental stress with self-rated health
 was mediated by PA (p values = 0.026 and
 0.024, respectively)		 6
Sonnentag
 and Jelden,
 2009 [282]		 Police officers in
 Germany
M + W (86 % M)
Mean age 43.8 years
 (SD = 7.7)		    78 Job stress
Self-
 regulation		 Prospective
5 days
2 daily
 measures
 (just after
 work and
 before bed)		 Job stressor measures
Situational constraints
 (i.e., information
 mishaps,
 communication tool
 failures,
 malfunctioning
 computers, etc.)
Profile of Mood
 States—fatigue
 subscale		 Daily recording of DUR of “sport activities”
 (running, cycling, swimming) and sedentary
 activities (watching TV, reading a newspaper,
 doing nothing)		 Time pressure and role ambiguity did not relate
 to indices of sport and PA participation
Situational constraints inversely related to LTPA
 (estimate = −0.159, SE = 0.076, t = −2.106,
 p < 0.05)
Sedentary (low-effort) activities positively
 related to situational constraints
 (estimate = 0.253, SE = 0.111, t = 2.275,
 p < 0.05)
Hours worked inversely related to sedentary
 (low-effort) activities (estimate = −0.098,
 SE = 0.039, t = −2.513, p < 0.05)		 7
Steptoe et al.,
 1996 [187]		 College students
M + W
M mean age 23.0 years
 (SD = 3.2)
W mean
 age = 21.8 years
 (SD = 2.7)		   180 None Naturalistic
Exam stress vs.
 early
 semester
Control group
 comparison		 PSS-10
GHQ-28 (emotional
 distress)		 FREQ and DUR of light, moderate, and vigorous
 PA, including exercise and commuting with a
 bicycle over last week
Light PA not analyzed		 Group × time interaction observed (F = 4.85,
 p < 0.05)
No difference between groups at BL
PA DUR decreased between BL and exam time
 points of semester (p < 0.05)
FREQ of exercise did not change: BL
 mean = 2.1 (SD = 2.1), exam mean = 1.92
 (SD = 2.25); NS
Note: association not influenced by social
 support		 7
Steptoe et al.,
 1998 [188]		 Teachers and nurses
M + W
Nurses’ mean age
 39.7 years (SD = 8.7)
Teachers’ mean age
 43.9 years
 (SD = 11.4)		    44 None Prospective
 diary study
2 weeks of
 highest self-
 rated stress
 vs. 2 lowest
 self-rated
 weeks of
 stress
8 weeks		 PSS-4
Hassles and Uplifts
 Scale		 FREQ, DUR, and type of exercise completed.
 Exercises classified by intensity (moderate/
 vigorous or low-intensity)
Assessed weekly
Exercise coping (for mood regulation); 1 item
 taken from Reasons for Exercise Inventory		 There were no significant differences in exercise
 FREQ or DUR with changes in perceived
 stress, but a trend is seen
FREQ of moderate to vigorous intensity exercise
 decreased during stress (low stress:
 mean = 2.32, SD = 2.3; high stress:
 mean = 1.85, SD = 2.7; ES = 0.20). DUR
 also decreased (low stress: mean = 145.9,
 SD = 194.1; high stress: mean = 115.8,
 SD = 2.7; ES = 0.16)
FREQ of light exercise decreased during stress
 (low stress: mean = 2.56, SD = 2.4; high
 stress: mean = 1.96, SD = 2.8; ES = 0.25).
 DUR also decreased (low stress: mean = 80.7,
 SD = 92.5; high stress: mean = 64.6,
 SD = 55.7; ES =0.17)
Those who exercised to regulate mood did report
 more exercise, however, but this did not
 change with perceived stress
Those who reported using exercise to cope with
 stress exercised more at moderate to vigorous
 intensity (F (1, 28) = 5.32, p < 0.01) and low
 intensity (F (1, 26) = 4.69, p < 0.01) over the
 entire study period, but this did not vary by
 stress
No analysis of hassles and exercise association
 reported		 6
Stetson et al.,
 1997 [189]		 Middle-aged,
 community-residing,
 already exercising on
 their own
W only
Mean age 34.8 years
 (SD = 11.1)		    82 None Prospective
 diary study
Self-rated low
 vs. high stress
 weeks
8 weeks
PA recorded
 daily		 WSI: scores for stress
 FREQ and stress
 impact		 Exercise History and Health Q (developed by
 authors, reliability >0.90, except for walking,
 r = 0.58)
FREQ and DUR for structured list of 8 activities.
 Subjects free to add more activities
Exercise diary: daily recording of exercise plans
 (yes/no), actual exercise (yes/no), type, DUR
 (min), perceived exertion (6–20 scale), and
 enjoyment (1–5 scale)		 69 % of sample reported exercising to cope with
 stress
Stress FREQ associated with exercise DUR
Low-stress weeks: mean = 73.56, SD = 38.10;
 high-stress weeks: mean = 68.06, SD = 31.47
 (p < 0.05; ES = 0.14)
Stress FREQ not associated with exercise FREQ,
 perceived intensity or number of exercise
 omissions
Stress impact associated with exercise omissions
Low-stress weeks: mean = 0.78, SD = 0.72;
 high-stress weeks: mean = 0.94, SD = 0.97
 (p = 0.07; ES = 0.22)
This indicates that high stress resulted in more
 cancelled preplanned exercise sessions
Stress impact not associated with exercise FREQ,
 DUR or perceived intensity		 7
Twisk et al.,
 1999 [280]		 Dutch adults in the
 Amsterdam Growth
 and Health Study
 cohort
M + W
27 years at BL
29 years at follow-up		   166 Life events Prospective
2 years
PA measured
 2×		 Everyday Problem
 Checklist (daily
 hassles)
Life Event List
 (translated Life Event
 Survey)
Ways of Coping
 Checklist		 Open question, interview-based exercise survey:
 weekly exercise DUR and intensity over last
 3 months
Data expressed as METs/week		 Changes in daily hassles positively related to
 increases in PA (standardized β = 0.27, 95 %
 CI 0.13–0.43, p < 0.01)
Association moderated by coping style. Those
 with a rigid coping style expressed association
 (standardized β = 0.08, 95 % CI 0.15–0.49,
 p < 0.01). No association amongst those with a
 flexible coping style
Type A personality interacted with daily hassles
 and PA. Those categorized as low
 (standardized β = 0.50, 95 % CI 0.23–0.77,
 p < 0.01) and high (standardized β = 0.24,
 95 % CI 0.03–0.45, p < 0.05) in type A
 personality had greater PA with more hassles
Life events (FREQ and subjective appraisal) did
 not influence PA		 7
Urizar et al.,
 2005 [89]		 Sedentary, low income,
 diverse (74 % Latina)
 mothers
W only
Mean age 31.7 years
 (SD = 8.8)		    68 Exercise
 barriers		 Prospective
Intervention
10 weeks
PA measured
 2×		 Mother Role Q
 (maternal stress
 survey)
PSS-14		 Stanford 7-Day PA Recall
Data expressed as kcal/kg/day
Intervention program adherence: number of
 classes attended also reported		 Maternal stress FREQ did not decrease with
 intervention (p = 0.06). Also, impact/intensity
 of stress and PSS did not change over
 intervention
Increased PA from BL to 10 weeks was
 associated with decrease in maternal stress
 (r = −0.42, p < 0.01), but maternal stress
 frequency over 10 weeks not related to class
 attendance (r = 0.01, p = 0.97)
Higher maternal stress frequency at BL related to
 less class attendance (β = −0.18, SE = 0.09,
 p = 0.05)
Higher impact/intensity of maternal stress at BL
 related to 10-week PA (β = −0.76,
 SE = 0.30, p = 0.01)
Perceived stress was not associated with PA or
 program adherence		 8
Vitaliano
 et al., 1998
 [190]		 4 groups: caregivers of
 spouses with
 Alzheimer’s vs.
 matched controls (both
 conditions split by
 cancer diagnosis)
M + W
Mean age 66.1, 54.6, 73,
 and 63.2 years		 165 (80
 caregivers)		 Stressed
 population		 Case control
Prospective
15–18 months
PA measured
 2×		 Hassles and Uplifts
 Scale
Hamilton Depression
 Scale		 Exercise scale inquiring about 10 different
 activities
FREQ/week, DUR
Binary respondent classification: dichotomized
 as active (>90 min of exercise/week) or
 inactive		 Caregivers were more depressed (p < 0.001) and
 reported more hassles (p < 0.01) than the
 control group
Caregivers had less PA than controls at both time
 points (p < 0.05)
At time 1 among subjects without cancer,
 caregivers (mean = 1.2; SD = 0.74) had less
 PA than non-caregivers (mean =1.5;
 SD = 0.75; ES = 0.41)
At time 2 among subjects without cancer,
 caregivers (mean = 0.9; SD = 0.71) had less
 PA than non-caregivers (mean = 1.3;
 SD = 0.74; ES = 0.57)		 8
Wilcox and
 King, 2004
 [204]		 Randomly selected older
 adults in a community
 fitness program
M + W
Mean age 70.2 years
 (SD = 4.1)		    97 Life events Prospective
Intervention
12 months		 Social Readjustment
 Rating Scale
 (modified)		 Indicators of exercise adherence: (1) home-base
 exercise participation—daily logs with type,
 FREQ, DUR of exercise sessions; (2) class-
 based exercise participation
Data calculated as average percentage of
 completed assigned/prescribed workouts		 Number of life events (across all 3 assessments)
 was negatively associated with home-based
 exercise participation over the entire 12-month
 period (total sample, r = − 0.17, p <0.05; for
 W, r = −0.19, p = 0.07), but not class-based
 participation (total sample, r = −0.08; W,
 r = −0.20, p = 0.06). Associations between
 life events and exercise participation were not
 significant for M
Life events during months 1–6 were associated
 with adherence to exercise during months 7–12
 for home-based exercise (r = −0.21,
 p = 0.02) but not for class-based exercise
 (r = −0.04). The strongest correlation was
 between life events at months 1–6 and home-
 based exercise participation (r = −0.32,
 p = 0.03)
Subjects who experienced an interpersonal loss
 had lower class-based participation than those
 who did not (62.7 vs. 72.3 %; t (94) = 1.70,
 p < 0.05, ES = −0.38), but home-based
 participation rates were unaffected
 (ES = 0.14). Regression analysis found that
 interpersonal loss predicted class-based
 participation (β = 11.69, SE = 5.83,
 p = 0.02) but not home-based participation
Life events, particularly interpersonal loss,
 appear to have a negative impact on exercise in
 W, and this effect appears greater for class-
 based than for home-based exercise		 8
Williams and
 Lord, 1995
 [277]		 Community-residing
 older adults
W only
Mean age 71.6 years
 (SD = 5.48)
Age range 60–85 years		    69 None Prospective
Exercise
 intervention
12 months		 DASS Adherence to 12 months of exercise (assessed at
 3 terms, including week 10 and at 12 months)
Adherence defined as number of classes attended
Binary respondent classification: exercise
 “continuers” vs. “non continuers”. Those who
 continued the exercise program after the
 intervention were classified as “continuers”		 Adherence to the intervention was not associated
 with BL stress (r = 0.04), depression (r =
 −0.06), or anxiety (r = −0.16)
Mood at 10 weeks did correlate with adherence
 over 12 months (r = 0.39, p < 0.01)
Continuing exercise after the intervention
 (n = 54) was predicted by depression
 (continuers = 2.1, SD = 3.2; non-
 continuers = 4.7, SD = 5.4, ES = 0.81) but
 not stress (continuers = 5.6, SD = 7.1; non-
 continuers = 8.4, SD = 8.5, ES = 0.39)		 6

AIHW Australian Institute of Health and Welfare, BDI Beck Depression Inventory, BMI body mass index, CBT cognitive–behavioral therapy, CI confidence interval, COEFF coefficient, CVD cardiovascular disease, DASS Depression Anxiety Stress Scale, DUR duration, ES effect size, FREQ frequency, GHQ General Health Questionnaire, HLM hierarchical linear modeling, HPLP Health Promotion Lifestyle Profile, LTPA leisure time physical activity, M men, METs metabolic equivalents, MVPA moderate to vigorous physical activity, NA negative affectivity, NHIS National Health Interview Survey, NS not significant, NY New York, OR odds ratio, PA physical activity, PBC perceived behavioral control, POMS Profile of Mood States, PSS Perceived Stress Scale, PTSD post-traumatic stress disorder, Q questionnaire, QR quality assessment rating (1–9 scale; see text), RCT randomized control trial, SD standard deviation, SE standard error, SEM structural equation modeling, TMAS taylor manifest anxiety scale, TV television, W women, WSI Weekly Stress Inventory