Introduction
Kidney cancer survivors (KCS) experience a multitude of symptoms, including pain, fatigue, irritability, and sleep disturbance as a result of cancer and its treatment [1]. Many of these symptoms may be attenuated with physical activity (PA) [2]; however, the majority of KCS engage in little to no PA [3]. The American College of Sports Medicine (ACSM) [4] recommends that cancer survivors engage in 150 min of moderate-to-vigorous PA (MVPA) and at least 2 days of strength training (ST) each week. Cancer survivors’, including KCS’, participation in single-modality (i.e., aerobic or strength) guidelines remains low, with even fewer meeting the combined (i.e., aerobic and strength) guidelines. Previously, our research examined the prevalence of each of these guidelines in KCS, reporting that 15.9% of KCS met the aerobic-only guideline, 8.8% met the ST-only guideline, 10.1% met the combined guidelines, and 65.1% met neither guideline [3]. Understanding the factors influencing PA behaviors among cancer survivors is prudent for increasing participation.
Aerobic PA and ST have been independently associated with several health-related improvements such as reductions in fatigue and improved physical functioning, body composition, and quality of life (QoL) [2, 5]. As both aerobic and ST target different physiologic pathways (i.e., cardiorespiratory and musculoskeletal, respectively), it is likely that performing both modalities concurrently may have additive benefits. Until recently, studies have compared only single-modality guidelines to usual care or combined PA to usual care; therefore, research comparing the effects of meeting one guideline to both guidelines on many health and fitness outcomes in cancer populations is inconsistent [3, 6]. However, there is some evidence to suggest that meeting combined guidelines is associated with better QoL for KCS [3]. Examining single modalities independently is limited by the contamination of alternate modalities being incorporated into the analysis of a single guideline. As meeting both single-modality guidelines may provide additional benefits compared with each modality alone, contamination in dichotomized approaches may confound results. Crawford et al. [7] suggest that in order to attenuate this confound, PA guidelines should be stratified into four categories: meeting the aerobic-only, ST-only, combined, and neither guidelines. This approach is optimal for promoting combined PA as it allows researchers to compare correlates of meeting independent and combined guidelines compared with those meeting neither or a single guideline.
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Two studies to date have examined correlates of PA participation in cancer survivors using this paradigm. Crawford et al. [7] found demographic characteristics (e.g., age, BMI, general health) to be correlates of meeting each modality guideline compared with neither guideline and to one another in gynecologic cancer survivors. In addition to demographic and medical variables, Vallerand et al. [8] incorporated modality-specific social-cognitive variables using the multi-process action control framework (M-PAC), a theoretical framework used to examine the discrepancy between intentions and behavior that is commonly seen with health behavior change. Social-cognitive variables differed based on the various guidelines in hematologic cancer survivors. There is some inter-group variation in correlates of PA, suggesting that the motivation to engage in PA may vary based on tumor site-specific experiences. To our knowledge, no studies have yet examined correlates of meeting combined guidelines in KCS.
Additionally, social-ecological models posit that behavior is a result of constant interactions between individuals and their societal and environmental context [9, 10]. Demographic, medical, and social-cognitive correlates of both aerobic and ST have been previously examined in other cancer populations; however, environmental variables have received much less attention.
The purpose of the current study is to examine the demographic, medical, social-cognitive, and environmental correlates of meeting aerobic-only, ST-only, and combined PA guidelines compared with meeting neither guideline, and compared with one another, in KCS.
Methods
Study details and procedures have been reported elsewhere [11]. Briefly, 1985 KCS identified using the Alberta Cancer Registry in 2010 were mailed a cross-sectional, self-administered survey. The survey took approximately 45 min to complete. Eligible participants were ≥ 18 years of age and diagnosed with kidney cancer in Alberta between 1996 and 2010. Ethical approval was obtained from the Alberta Cancer Board Research Ethics Board and the University of Alberta Health Research Ethics Board.
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Measures
Demographic and medical variables
Self-reported demographic, medical, and behavioral variables were collected. Participants provided information regarding personal characteristics (e.g., age, sex), medical (e.g., time since diagnosis, treatment type/status), and behavioral variables (e.g., smoking status).
Physical activity
PA was assessed using a modified version of the validated leisure score index from the Godin Leisure-Time Exercise Questionnaire [12]. The percentage of participants meeting aerobic-only (i.e., ≥ 150 min/week of MVPA), ST-only (i.e., ≥ 2 days/week of any duration), and combined guidelines (i.e., ≥ 150 min/week of MVPA and ≥ 2 days/week of ST) was calculated based on the ACSM [4] guidelines.
Social-cognitive variables
Social-cognitive variables were assessed using a modified version of the theory of planned behavior (TPB) that has been previously implemented in cancer populations [11, 13‐15].
Attitude towards performing regular PA was assessed using four items on a 7-point bipolar, Likert-type scale assessing instrumental (i.e., beneficial/harmful, important/unimportant) and affective attitudes (i.e., enjoyable/unenjoyable, fun/boring). Instrumental and affective attitude scales had good internal consistency (Cronbach’s alpha was 0.77 and 0.81, respectively).
Subjective norm (i.e., injunctive, 2 items; and descriptive, 1 item) was assessed using a three-item, 7-point Likert-type scale. Cronbach’s alpha for injunctive norm was 0.91.
Perceived behavioral control (PBC) was assessed using two items on a 7-point Likert-type scale assessing perceived control/confidence to engage in PA over the next month (Cronbach’s alpha = 0.83). Intention was assessed using two items on a 7-point Likert-type scale measuring intention to engage in regular PA over the next month (Cronbach’s alpha = 0.94). Planning, assessed using a measure developed by Rise et al. [16], examined specific details of how individuals will engage in regular PA over the next month (Cronbach’s alpha = 0.97).
Perceived environment variables
Perceived environment characteristics were determined using items from the Neighborhood Environment Walkability Scale (NEWS) [17] and the International Physical Activity Prevalence Study Environmental Survey Module (IPAPSEM) [18]. Additional measures included availability of exercise equipment at home, access to workout attire, oncologist PA recommendation, and cancer center-provided health education materials.
Built environment variables
Built environment characteristics were determined with geographic information systems-based (GIS) measures. Home location was defined using the geographic centers of the home postal codes, which provides a representation of the local area in urban settings. Missing respondents (n = 162) and respondents from rural postal codes (n = 109) were excluded to prevent misclassification of the residential location [19]. Network buffers, evaluating neighborhood characteristics within walking distance (e.g., streets, pedestrian walkways) were set at 1 km from the center of each participant’s home postal code [20, 21]. Built and social environment variables included median household income, population and park density, number of shopping/recreation centers, and local road/intersection density. Median household income was measured to provide a proxy for neighborhood socioeconomic status (SES) at the dissemination area level with data from the recent census [22]. Population density was calculated by dividing the population count from the census by the geographic area in square kilometers of each 1-km network buffer [22]. The DMTI Route Logistics dataset (2010) was used to determine the data for the remaining built environment variables. Park density was calculated by dividing the total area of public parks (e.g., nature trails, bike paths) by the geographic area of each 1-km network buffer. The number of shopping and recreation centers was measured as the total number of centers within each 1-km network buffer. Local road density was calculated by dividing the entire length of the local roads by the total neighborhood area within each 1-km network buffer. Intersection density was measured by counting the total number of three- or four-way intersections within each 1-km network buffer.
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Statistical analysis
Statistical analyses were performed using SPSS Statistics 24 (IBM Corp., Armonk, NY). Chi-square tests examined associations between demographic, behavioral, and medical variables and meeting the various guidelines. Bonferroni corrected post hoc comparisons were used to determine within-group differences. All variables with a p value of < .10 were entered into separate multivariate, multinomial logistic regression models to predict the probability that a respondent would meet single-modality and combined guidelines compared with meeting neither guideline and to one another. Block 1 included demographic and behavioral variables. Medical variables were entered into block 2. Social-cognitive variables from the TPB were entered into three blocks (blocks 3–5) to account for the TPB structure and causal ordering of the variables. Model fit was determined using the Pearson test (p > .05) and Deviance test (p > .05). Nagelkerke’s R2 determined the amount of variance explained, with larger percentages signifying more variance being explained. Statistical significance was set at p < .05.
Exploratory analyses, using a subsample of 432 KCS, examined environmental correlates of meeting independent and combined guidelines compared with meeting neither guideline and to one another using separate multinomial logistic regression models including perceived and built environmental correlates.
Results
Participant flow through the study has been previously reported [23]. In brief, 651 (92%) of the 703 provided complete social-cognitive data and were included in this analysis.
Table 1 presents the demographic, behavioral, and medical characteristics of KCS stratified by meeting neither, single-modality, and combined guidelines. The sample was predominantly male (62.4%) with a mean age of 64.4 years (SD = 11.0), Caucasian (91.2%), had a mean BMI of 28.6 (SD = 5.2), and had localized kidney cancer (83.3%). Post hoc comparisons of the univariate analysis are presented in Table 2. Table 3 presents the aerobic activity and ST minutes in KCS.
Table 1
Demographic, behavioral, and medical characteristics of kidney cancer survivors meeting neither, aerobic-only, strength-only, or combined guidelines in Edmonton, Alberta, Canada, May, 2010 (N = 651)
Variable | Neither (n = 412) No. (%) | Aerobic-only (n = 108) No. (%) | ST-only (n = 60) No. (%) | Combined (n = 71) No. (%) | p |
|---|---|---|---|---|---|
Overall age (Mean ± SD = 64.4 ± 11.0) | |||||
< 65 years (n = 357) | 222 (53.9) | 69 (63.9) | 22 (36.7) | 44 (62.0) | <.01 |
≥ 65 years (n = 294) | 190 (46.1) | 39 (36.1) | 38 (63.3) | 27 (38.0) | |
Sex | |||||
Male (n = 406) | 267 (64.8) | 63 (58.3) | 37 (61.7) | 39 (54.9) | .32 |
Female (n = 245) | 145 (35.2) | 45 (41.7) | 23 (38.3) | 32 (45.1) | |
Marital status | |||||
Married/common law (n = 515) | 324 (78.6) | 86 (79.6) | 43 (71.7) | 62 (87.3) | .17 |
Not married (n = 136) | 88 (21.4) | 22 (20.4) | 17 (28.3) | 9 (12.7) | |
Education | |||||
Some/completed high school (n = 296) | 214 (51.9) | 40 (37.0) | 25 (41.7) | 17 (23.9) | < .001 |
Some/completed university (n = 355) | 198 (48.1) | 68 (63.0) | 35 (58.3) | 54 (76.1) | |
Employment status | |||||
Employed full-/part-time (n = 201) | 124 (30.1) | 40 (37.0) | 17 (28.3) | 20 (28.2) | .48 |
Unemployed (n = 450) | 288 (69.9) | 68 (63.0) | 43 (71.7) | 51 (71.8) | |
Ethnicity | |||||
White (n = 594) | 371 (90.0) | 99 (91.7) | 55 (91.7) | 69 (97.2) | .27 |
Other (n = 57) | 41 (10.0) | 9 (8.3) | 5 (8.3) | 2 (2.8) | |
BMI (Mean ± SD = 28.6 ± 5.2) | |||||
Healthy weight (n = 161) | 91 (22.1) | 21 (19.4) | 22 (36.7) | 27 (38.0) | <.01 |
Overweight/obese (n = 490) | 321 (77.9) | 87 (80.6) | 38 (63.3) | 44 (62.0) | |
Number of comorbidities | |||||
< 3 (n = 327) | 196 (47.6) | 65 (60.2) | 28 (46.7) | 38 (53.5) | .11 |
≥ 3 (n = 324) | 216 (52.4) | 43 (39.8) | 32 (53.3) | 33 (46.5) | |
Months since diagnosis (Mean ± SD = 68.6 ± 56.0) | |||||
< 60 months (n = 324) | 207 (50.2) | 61 (56.5) | 25 (41.7) | 31 (43.7) | .20 |
≥ 60 months (n = 327) | 205 (49.8) | 47 (43.5) | 35 (58.3) | 40 (56.3) | |
Disease stage | |||||
Localized (n = 542) | 328 (79.6) | 93 (86.1) | 54 (90.0) | 67 (94.4) | <.01 |
Metastatic (n = 109) | 84 (20.4) | 15 (13.9) | 6 (10.0) | 4 (5.6) | |
Surgery treatment | |||||
Yes (n = 635) | 401 (97.3) | 106 (98.1) | 59 (98.3) | 69 (97.2) | .93 |
No (n = 16) | 11 (2.7) | 2 (1.9) | 1 (1.7) | 2 (2.8) | |
Drug treatment | |||||
Yes (n = 86) | 60 (14.6) | 16 (14.8) | 2 (3.3) | 8 (11.3) | .10 |
No (n = 565) | 352 (85.4) | 92 (85.2) | 58 (96.7) | 63 (88.7) | |
Treatment status | |||||
Still receiving treatment (n = 55) | 40 (9.7) | 7 (6.5) | 1 (1.7) | 7 (9.9) | .16 |
Not receiving treatment (n = 596) | 372 (90.3) | 101 (93.5) | 59 (98.3) | 64 (90.1) | |
Current cancer status | |||||
Cancer gone (n = 567) | 348 (84.5) | 96 (88.9) | 58 (96.7) | 65 (91.5) | .03 |
Cancer in body (n = 84) | 64 (15.5) | 12 (11.1) | 2 (3.3) | 6 (8.5) | |
Recurrence | |||||
Yes (n = 51) | 39 (9.5) | 7 (6.5) | 4 (6.7) | 1 (1.4) | .11 |
No (n = 600) | 373 (90.5) | 101 (93.5) | 56 (93.3) | 70 (98.6) | |
Smoking | |||||
Never smoked/ex-smoker (n = 558) | 344 (83.5) | 96 (88.9) | 54 (90.0) | 64 (90.1) | .21 |
Occasional/regular smoker (n = 93) | 68 (16.5) | 12 (11.1) | 6 (10.0) | 7 (9.9) | |
Alcohol consumption | |||||
Never drink (n = 206) | 145 (35.2) | 26 (24.1) | 19 (31.7) | 16 (22.5) | .05 |
Social/regular drinker (n = 445) | 267 (64.8) | 82 (75.9) | 41 (68.3) | 55 (77.5) | |
General health | |||||
Excellent, very good, or good (n = 481) | 278 (67.5) | 89 (82.4) | 46 (76.7) | 68 (95.8) | < .001 |
Fair or poor (n = 170) | 134 (32.5) | 19 (17.6) | 14 (23.3) | 3 (4.2) | |
Table 2
Post hoc comparisons of the univariate analysis examining associations between demographic, behavioral, and medical variables and meeting the single-modality, combined, and neither guideline
Variable | Aerobic-only vs. neither | ST-only vs. neither | Combined vs. neither | Aerobic-only vs. ST-only | Combined vs. aerobic-only | Combined vs. ST-only | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
χ2 | p | χ2 | p | χ2 | p | χ2 | p | χ2 | p | χ2 | p | |
Age | 3.48 | .06 | 6.22 | .01 | 1.60 | .21 | 11.51 | < .008 | 0.07 | .80 | 8.33 | < .008 |
Education | 7.61 | < .008 | 2.21 | .14 | 19.03 | < .001 | 0.35 | .56 | 3.38 | .07 | 4.69 | .03 |
Body mass index | 0.35 | .55 | 6.11 | .01 | 8.34 | < .008 | 6.01 | .01 | 7.54 | < .008 | 0.03 | .87 |
Disease stage | 2.35 | .13 | 3.66 | .06 | 8.85 | < .008 | 0.53 | .47 | 3.08 | .08 | 0.88 | .35 |
Current cancer status | 1.34 | .25 | 6.48 | .01 | 2.45 | .12 | 3.06 | .08 | 0.34 | .56 | 1.49 | .22 |
Alcohol consumption | 4.79 | .03 | 0.29 | .59 | 4.37 | .04 | 1.13 | .29 | 0.06 | .81 | 1.39 | .24 |
General health | 9.19 | < .008 | 2.06 | .15 | 23.87 | < .001 | 0.81 | .37 | 7.10 | < .008 | 10.51 | < .008 |
Table 3
Descriptive statistics for aerobic activity and strength training in kidney cancer survivors in Edmonton, Alberta, Canada, May, 2010 (N = 651)
Variable | Mean ± SD |
|---|---|
Average weekly physical activity in the past month | |
Light minutes | 121.32 ± 272.70 |
Moderate minutes | 74.78 ± 236.53 |
Vigorous minutes | 27.84 ± 77.44 |
Strength training frequency | 0.81 ± 1.77 |
Strength training minutes | 21.76 ± 72.04 |
Physical activity minutesa | 130.46 ± 296.70 |
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Table 4 presents the results from the final models of the multinomial logistic regression analyses comparing correlates of meeting aerobic-only, ST-only, or combined guidelines to neither and to one another. Model 1 included demographic variables. Compared with neither guideline, (a) meeting the aerobic-only (OR = 0.59, 95% CI = 0.38–0.92, p = .02), ST-only (OR = 0.56, 95% CI = 0.32–0.99, p = .05), and combined (OR = 0.30, 95% CI = 0.17–0.55, p < .001) guidelines were associated with having higher education and (b) meeting the ST-only guideline was significantly associated with older age (OR = 0.43, 95% CI = 0.24–0.76, p < .01). Compared with the ST-only guideline, meeting aerobic-only and combined guidelines is significantly associated with a younger age (OR = 3.00, 95% CI = 1.53–5.90, p < .01 and OR = 2.42, 95% CI = 1.16–5.02, p = .02, respectively). Compared with the aerobic-only guideline, meeting combined guidelines was not significantly associated with any variables.
Table 4
Final model of the multivariate, multinomial logistic regression of the demographic, medical, and social-cognitive correlates of meeting the aerobic-only, strength-only, or combined PA guidelines versus neither guideline and versus one another in kidney cancer survivors (N = 651)
Aerobic-only vs. neithera | ST-only vs. neithera | Combined vs. neithera | Aerobic-only vs. ST-onlyb | Combined vs. aerobic-onlyc | Combined vs. ST-onlyb | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
Variable | OR (95% CI) | p | OR (95% CI) | p | OR (95% CI) | p | OR (95% CI) | p | OR (95% CI) | p | OR (95% CI) | p |
Demographic and behavioral | ||||||||||||
Age (< 65 vs. ≥ 65 years) | 1.26 (0.76–.2.09) | .37 | 0.39 (0.21–0.72) | < .01 | 0.86 (0.44–1.70) | .67 | 3.26 (1.60–6.64) | < .01 | 0.69 (0.34–1.39) | .30 | 2.23 (0.99–5.06) | .05 |
Education level (some/completed high school vs. some/completed) | 0.71 (0.44–1.17) | .18 | 0.63 (0.34–1.16) | .14 | 0.47 (0.23–0.96) | .04 | 1.13 (0.57–2.27) | .73 | 0.66 (0.31–1.40) | .27 | 0.74 (0.32–1.73) | .49 |
Alcohol consumption (never drink vs. social/regular drinker) | 0.86 (0.50–1.50) | .60 | 0.87 (0.45–1.68) | .68 | 0.80 (0.37–1.71) | .57 | 0.99 (0.46–2.13) | .99 | 0.93 (0.42–2.06) | .85 | 0.92 (0.38–2.26) | .86 |
Medical | ||||||||||||
Body mass index (healthy weight vs. overweight/obese) | 0.90 (0.50–1.63) | .73 | 2.29 (1.22–4.32) | .01 | 1.72 (0.85–3.46) | .13 | 0.39 (0.19–0.83) | .01 | 1.91 (0.92–3.99) | .09 | 0.75 (0.33–1.69) | .48 |
Disease stage (localized vs. metastatic) | 1.34 (0.64–2.78) | .44 | 1.44 (0.55–3.77) | .46 | 3.76 (1.01–13.91) | .05 | 0.93 (0.31–2.83) | .90 | 2.81 (0.72–10.87) | .14 | 2.62 (0.57–12.12) | .22 |
Current cancer status (cancer gone vs. cancer in body) | 1.14 (0.51–2.53) | .75 | 4.22 (0.94–18.95) | .06 | 0.71 (0.22–2.33) | .57 | 0.27 (0.05–1.36) | .11 | 0.63 (0.18–2.21) | .47 | 0.17 (0.03–1.03) | .05 |
General health (good, very good, excellent vs. poor/fair) | 1.30 (0.70–2.40) | .41 | 1.16 (0.57–2.35) | .69 | 8.12 (2.11–31.23) | < .01 | 1.12 (0.48–2.61) | .79 | 6.26 (1.57–25.01) | < .01 | 7.02 (1.67–29.58) | < .01 |
Theory of planned behavior | ||||||||||||
Affective attitude | 1.19 (0.89–1.58) | .24 | 0.80 (0.59–1.08) | .14 | 0.88 (0.61–1.29) | .52 | 1.48 (1.02–2.14) | .04 | 0.75 (0.50–1.12) | .16 | 1.10 (0.72–1.69) | .65 |
Instrumental attitude | 1.00 (0.67–1.48) | .99 | 1.29 (0.86–1.94) | .22 | 2.79 (1.38–5.65) | < .01 | 0.77 (0.46–1.29) | .33 | 2.80 (1.34–5.85) | < .01 | 2.16 (1.01–4.62) | .05 |
Injunctive norm | 0.91 (0.64–1.31) | .62 | 0.84 (0.58–1.21) | .34 | 0.71 (0.43–1.17) | .18 | 1.09 (0.69–1.74) | .70 | 0.78 (0.46–1.31) | .34 | 0.85 (0.48–1.49) | .57 |
Descriptive norm | 1.03 (0.87–1.22) | .73 | 0.95 (0.79–1.16) | .62 | 0.87 (0.70–1.09) | .24 | 1.08 (0.86–1.36) | .50 | 0.85 (0.67–1.08) | .17 | 0.92 (0.71–1.19) | .52 |
Perceived behavioral control | 1.07 (0.83–1.38) | .60 | 0.72 (0.53–0.97) | .03 | 1.28 (0.87–1.88) | .21 | 1.50 (1.05–2.13) | .03 | 1.19 (0.79–1.80) | .39 | 1.79 (1.15–2.78) | .01 |
Intention | 1.53 (1.16–2.00) | < .01 | 1.48 (1.07–2.06) | .02 | 2.10 (1.37–3.20) | < .01 | 1.03 (0.70–1.51) | .88 | 1.37 (0.88–2.15) | .16 | 1.41 (0.87–2.31) | .17 |
Planning | 1.27 (1.07–1.50) | < .01 | 1.39 (1.11–1.73) | < .01 | 1.37 (1.05–1.79) | .02 | 0.92 (0.71–1.18) | .49 | 1.08 (0.81–1.44) | .61 | 0.99 (0.72–1.36) | .94 |
Model 2 included demographic and medical variables. Compared with neither guideline, (a) meeting the aerobic-only guideline was associated with higher education (OR = 0.59, 95% CI = 0.38–0.93, p = .02) and better health (OR = 1.98, 95% CI = 1.14–3.42, p = .02); (b) meeting the ST-only guideline was significantly associated with higher education (OR = 0.55, 95% CI = 0.31–0.97, p = .04), older age (OR = 0.42, 95% CI = 0.23–0.76, p < .01), and a healthy weight (OR = 2.00, 95% CI = 1.10–3.62, p = .02); and (c) meeting combined guidelines was significantly associated with higher education (OR = 0.31, 95% CI = 0.17–0.56, p < .001), better general health (OR = 8.42, 95% CI = 2.57–27.62, p < .001), a healthy weight (OR = 2.11, 95% CI = 1.20–3.73, p = .01), and localized cancer (OR = 3.58, 95% CI = 1.16–11.04, p = .03). Compared with the ST-only guideline, (a) KCS meeting the aerobic-only guideline were more likely to be younger (OR = 2.91, 95% CI = 1.47–5.76, p < .01) and of a healthy weight (OR = 0.44, 95% CI = 0.22–0.92, p = .03), and (b) those meeting the combined guidelines were significantly more likely to be younger (OR = 2.35, 95% CI = 1.12–4.92, p = .02) and in better health (OR = 6.37, 95% CI = 1.71–23.77, p < .01). Compared with the aerobic-only guideline, KCS in better health (OR = 4.26, 95% CI = 1.20–15.15, p = .03) and at a healthy weight (OR = 2.39, 95% CI = 1.20–4.75, p = .01) were significantly more likely to meet the combined exercise guidelines.
The final model (Model 5) included demographic, medical, and social-cognitive variables. Compared with neither guideline, (a) meeting the aerobic-only guideline was significantly associated with higher planning (OR = 1.27, 95% CI = 1.07–1.50, p < .01), and intentions (OR = 1.53, 95% CI = 1.16–2.00, p < .01); (b) meeting the ST-only guideline was associated with higher intentions (OR = 1.48, 95% CI = 1.07–2.06, p = .02) and planning (OR = 1.39, 95% CI = 1.11–1.73, p < .01), lower PBC (OR = 0.72, 95% CI = 0.53–0.97, p = .03), healthy weight (OR = 2.29, 95% CI = 1.22–4.32, p = .01), and older age (OR = 0.39, 95% CI = 0.21–0.72, p < .01); and (c) meeting the combined guidelines was associated with higher intentions (OR = 2.10, 95% CI = 1.37–3.20, p < .01), planning (OR = 1.37, 95% CI = 1.05–1.79, p = .02), higher instrumental attitudes (OR = 2.79, 95% CI = 1.38–5.65, p < .01), higher education (OR = 0.47, 95% CI = 0.23–0.96, p = .04), better health (OR = 8.12, 95% CI = 2.11–31.23, p < .01), and having localized cancer (OR = 3.76, 95% CI = 1.01–13.91, p = .05).
Compared with the ST-only guideline, (a) meeting the aerobic-only guidelines was associated with higher affective attitudes (OR = 1.48, 95% CI = 1.02–2.14, p = .04), PBC (OR = 1.50, 95% CI = 1.05–2.13, p = .03), younger age (OR = 3.26, 95% CI = 1.60–6.64, p < .01), and being overweight/obese (OR = 0.39, 95% CI = 0.19–0.83, p = .01); and (b) meeting the combined guidelines was associated with higher instrumental attitudes (OR = 2.16, 95% CI = 1.01–4.62, p = .05), PBC (OR = 1.79, 95% CI = 1.15–2.78, p = .01), and better general health (OR = 7.02, 95% CI = 1.67–29.58, p < .01). Compared with meeting the aerobic-only guideline, meeting the combined guidelines was significantly associated with higher instrumental attitudes (OR = 2.80, 95% CI = 1.34–5.85, p < .01) and better health (OR = 6.26, 95% CI = 1.57–25.01, p < .01).
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Exploratory analysis of the perceived and built environment variables revealed that compared with meeting neither guideline (Table 5), KCS with shops within walking distance (OR = 1.35, 95% CI = 1.05–1.73, p = .02) and access to workout attire (OR = 1.71, 95% CI = 1.21–2.42, p < .01) were more likely to meet the aerobic-only guidelines. Compared with meeting neither guideline, meeting the combined guidelines was significantly associated with access to workout attire (OR = 3.08, 95% CI = 1.39–6.85, p < .01). No significant correlates were found for perceived and built environmental variables.
Table 5
Final multinomial logistic regression of environmental correlates of meeting the aerobic-only, strength-only, or combined PA guidelines versus neither guideline and versus one another in kidney cancer survivors (N = 432)
Aerobic-only vs. neithera | ST-only vs. neithera | Combined vs. neithera | Aerobic-only vs. ST-onlyb | Combined vs. aerobic-onlyc | Combined vs. ST-onlyb | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
Variable | OR (95% CI) | p | OR (95% CI) | p | OR (95% CI) | p | OR (95% CI) | p | OR (95% CI) | p | OR (95% CI) | p |
Perceived environment | ||||||||||||
Proximity to retail | 1.35 (1.05–1.73) | .02 | 1.65 (0.78–3.51) | .19 | 1.51 (0.96–2.38) | .08 | 0.82 (0.38–1.76) | .61 | 1.12 (0.69–1.81) | .65 | 0.91 (0.39–2.14) | .83 |
Proximity to recreation | 0.90 (0.64–1.26) | .54 | 3.11 (0.59–16.31) | .18 | 1.32 (0.66–2.63) | .44 | 0.29 (0.05–1.54) | .15 | 1.46 (0.71–3.01) | .30 | 0.42 (0.07–2.48) | .34 |
Quality of walking infrastructure | 0.95 (0.68–1.31) | .74 | 1.55 (0.36–6.66) | .56 | 0.81 (0.44–1.47) | .49 | 0.61 (0.14–2.67) | .51 | 0.85 (0.45–1.61) | .63 | 0.52 (0.11–2.45) | .41 |
Neighborhood aesthetics | 1.14 (0.81–1.60) | .44 | 0.62 (0.23–1.62) | .32 | 1.22 (0.66–2.26) | .52 | 1.86 (0.69–4.99) | .22 | 1.07 (0.56–2.05) | .84 | 1.99 (0.66–5.99) | .22 |
Traffic | 0.89 (0.67–1.18) | .41 | 0.17 (0.02–1.57) | .12 | 0.93 (0.55–1.57) | .79 | 5.37 (0.56–51.20) | .14 | 1.05 (0.61–1.82) | .86 | 5.63 (0.57–55.91) | .14 |
Exercise equipment at home | 0.95 (0.77–1.18) | .66 | 0.83 (0.48–1.43) | .50 | 0.81 (0.57–1.14) | .23 | 1.15 (0.66–2.00) | .63 | 0.85 (0.58–1.22) | .37 | 0.97 (0.52–1.80) | .93 |
Access to workout attire | 1.71 (1.21–2.42) | < .01 | 6.87 (0.80–58.95) | .08 | 3.08 (1.39–6.85) | < .01 | 0.25 (0.03–2.16) | .21 | 1.81 (0.78–4.15) | .17 | 0.45 (0.05–4.35) | .49 |
Oncologist exercise recommendation | 1.16 (0.89–1.52) | .27 | 0.72 (0.29–1.76) | .47 | 1.16 (0.73–1.86) | .53 | 1.62 (0.65–4.03) | .30 | 1.00 (0.61–1.64) | .99 | 1.62 (0.61–4.34) | .33 |
Health education materials at cancer center | 0.78 (0.56–1.09) | .15 | 1.88 (0.79–4.45) | .15 | 0.77 (0.43–1.39) | .39 | 0.42 (0.17–1.02) | .06 | 0.99 (0.53–1.85) | .97 | 0.41 (0.15–1.13) | .09 |
Built environment | ||||||||||||
Median household income | 1.00 (1.00–1.00) | .97 | 1.00 (1.00–1.00) | .30 | 1.00 (1.00–1.00) | .98 | 1.00 (1.00–1.00) | .32 | 1.00 (1.00–1.00) | .97 | 1.00 (1.00–1.00) | .36 |
Population density | 1.00 (1.00–1.00) | .90 | 1.00 (1.00–1.00) | .78 | 1.00 (1.00–1.00) | .68 | 1.00 (1.00–1.00) | .81 | 1.00 (1.00–1.00) | .64 | 1.00 (1.00–1.00) | .64 |
Park density | 0.81 (0.26–2.55) | .72 | 0.95 (0.03–30.60) | .98 | 0.76 (0.08–6.96) | .81 | 0.85 (0.03–29.48) | .93 | 0.93 (0.09–9.72) | .95 | 0.79 (0.02–42.78) | .91 |
Number of shopping centers | 0.97 (0.70–1.35) | .87 | 1.15 (0.35–3.76) | .82 | 0.81 (0.37–1.76) | .59 | 0.85 (0.26–2.80) | .78 | 0.83 (0.37–1.86) | .65 | 0.70 (0.18–2.78) | .61 |
Number of recreation centers | 0.95 (0.82–1.08) | .42 | 0.85 (0.46–1.56) | .59 | 0.73 (0.46–1.16) | .18 | 1.12 (0.60–2.07) | .72 | 0.77 (0.48–1.24) | .28 | 0.86 (0.41–1.82) | .70 |
Local road density | 0.97 (0.89–1.06) | .54 | 1.04 (0.88–1.24) | .61 | 0.94 (0.79–1.13) | .52 | 0.93 (0.78–1.12) | .44 | 0.97 (0.80–1.17) | .74 | 0.90 (0.71–1.15) | .40 |
Intersection density | 1.00 (0.99–1.01) | .93 | 1.00 (0.97–1.03) | .93 | 0.99 (0.97–1.01) | .49 | 1.00 (0.97–1.03) | .95 | 0.99 (0.97–1.02) | .53 | 0.99 (0.96–1.03) | .72 |
Discussion
This study explored the demographic, medical, behavioral, social-cognitive, and environmental correlates of meeting the independent and combined PA guidelines. Consistent with existing literature [7, 8], results indicate that correlates of PA participation are specific to each modality; thus, PA promotion efforts should be individualized to optimize disease- and treatment-related outcomes.
In the final model, demographic variables accounted for 7.2% of the variance in meeting aerobic-only, ST-only, and combined guidelines. Few demographic variables were correlates of meeting the independent or combined guidelines. Similar to previous work [8], compared with meeting neither guideline, meeting the combined guidelines was associated with higher education levels. However, age as a correlate for ST participation in cancer survivors is inconsistent [7, 13], but the results are closely aligned to that of Crawford et al. [7], as older KCS were more likely to meet ST-only guidelines when compared with aerobic-only or neither guideline. ST-only guidelines may be more feasible than aerobic-only guidelines for older cancer survivors as ST-only guidelines can be met with lower intensities. Consistent with a previous study [11], no demographic variables were correlates of meeting aerobic-only guidelines. In previous research, other demographic correlates included meeting independent and combined guidelines include sex, ethnicity, marital status, drinking and smoking status, and having children at home [7, 8, 24‐27]. There is some inter-group variation in correlates of PA, highlighting the importance of examining correlates specific to tumor site.
The addition of medical variables into the model explained 16.5% of the variance in meeting PA guidelines. Consistent with previous literature reporting general health and comorbidity status to be predictive of PA participation [7], KCS meeting combined guidelines were more likely to be in better health, regardless of comparison group. Additionally, having a healthy weight was correlated with KCS meeting ST-only guidelines, but not meeting neither or aerobic-only guidelines. Numerous studies have reported healthy weight to be associated with aerobic and ST participation [13, 24, 26, 28, 29]; however, research comparing one modality to another is scant. It is possible that aerobic activity may be perceived to be more beneficial than ST for overweight/obese KCS. Motivation to be physically active in overweight and obese individuals is often weight loss driven, thus potentially leading to a greater interest in aerobic activity [30, 31]. ST knowledge is lacking [31]; thus, educating KCS about the various benefits of ST and skills necessary to properly and effectively perform ST may increase participation, especially for overweight/obese populations.
Interestingly, although aligned with previous research [7, 8], few cancer-specific variables were associated with meeting the various guidelines. Studies examining single-modality guidelines have reported disease stage, treatment factors (e.g., type and side effects), and symptoms (e.g., fatigue, dyspnea, pain) to be significantly associated with PA participation in various cancer groups [28, 29, 32‐34]. The only significant correlate in the current study was disease stage for KCS meeting combined guidelines compared with meeting neither guideline. Consistent with previous research, healthier, symptom-limited cancer survivors are more likely to engage in more PA [28, 29, 32‐34]. KCS may be in better health as they were primarily cancer-free and further along the cancer survivorship trajectory, consequently, negative treatment-related side effects may have diminished, potentially diluting the independent effects of cancer-related variables on PA participation. Correlates of PA participation may vary based on treatment-related variables and cancer stage; therefore, further research is needed to examine their role in independent and combined PA participation.
Social-cognitive variables accounted for the largest portion of variance (20.5%) in meeting PA guidelines. This is consistent with literature suggesting that social-cognitive variables, specifically intentions, attitudes, planning, and PBC, are predictive of performing PA across guidelines [8, 11, 13, 35, 36]. Compared with KCS meeting neither guideline, those meeting aerobic-only, ST-only, and combined guidelines were each more likely to have greater PA intentions and planning. When comparing guidelines to one another, other TPB constructs such as attitudes and PBC distinguished meeting one guideline from another. It is possible that intention and planning may be more important when promoting PA in inactive populations; however, the decision to perform one modality over another in already active KCS may depend on other psychological factors (e.g., enjoyment or perceived benefits). Targeting TPB constructs may lead to greater PA participation in both active and inactive individuals. Increasing awareness, knowledge, and skills around aerobic activity and ST may elicit stronger, more positive attitudes, and greater intentions, thus, potentially resulting in a greater likelihood of meeting both PA guidelines.
Exploratory analyses of the perceived and built environment correlates to meeting independent and combined guidelines revealed that shops within walking distance and access to workout attire distinguished KCS meeting aerobic-only guidelines from those meeting neither. Meeting the combined guidelines compared with meeting neither was also significantly associated with access to workout attire. Research examining environmental correlates of PA in cancer survivors is limited, especially using this four category approach. Although inconsistent, factors such as perceived access to retail shops, nearby recreation facilities, and availability of home equipment have been found to be associated with PA participation [25, 37, 38]. Providing KCS with information on environments conducive to an active lifestyle may improve PA participation in KCS.
There are some discrepancies between perceived and measured built environmental correlates. This may be resultant of the network buffer radius used in determining built environment. It is also possible that individual perceptions of proximity to shops may differ from actual distances. Using a larger buffer size may yield different results. However, this suggests the importance of examining both perceived and objective measures of environment as they may relate to PA differently, although perceptions may be more influential [39]. Further investigation into the influence of both perceived and built environmental factors and their relationship with one another on PA participation is needed.
This study should be placed in the context of both its strengths and limitations. To our knowledge, this is the first study to examine environmental correlates of meeting each independent and combined guideline in KCS. Additionally, this four-category guideline classification removes any potential contamination common in traditional dichotomized approaches. Study limitations include its cross-sectional design in which causation cannot be determined. Modality-specific TPB variables should be measured in order to accurately assess social-cognitive influence. Further, future studies looking at PA correlates in cancer survivors should assess exercise levels and constructs with consideration of each modality in this four-category PA classification. Also, future studies are needed to further explore environmental variables related to what factors contribute to a supportive environment for PA participation.
In conclusion, results from this study highlight the importance of examining correlates specific to the modality of interest. Factors influencing participation in single-modality and combined guidelines are not generalizable to one another as they may require different motivational antecedents. Current PA behaviors should be addressed when promoting meeting the combined guidelines as motivation may be dependent on the modality being performed. To successfully change PA behaviors, KCS require greater knowledge, skills, and efficacy beliefs towards aerobic activity and ST. Oncology care providers can potentially disseminate educational materials regarding the benefits of PA to cancer survivors, and where PA can be effectively performed [40, 41]. Additionally, healthcare practitioners should strive to develop more comprehensive and targeted PA prescriptions. There is a great deal of heterogeneity across cancer populations (i.e., demographic, treatment, and medical variables); therefore, individualization and precise manipulation of modality, volume, intensity, and frequency is necessary in order to maximize benefits of PA for cancer survivors. Both aerobic PA and ST promotion in cancer survivors should be a priority as they are less likely to meet the guidelines than those with no history of cancer [42].
In understanding the correlates of performing independent and combined guidelines, researchers, clinicians, and interventionists may use this information to then target factors (e.g., attitudes, planning) to increase participation in modalities that are lacking. Exercise prescriptions may then be tailored, not only in terms of individual ability but also to an individual’s motivational level for each modality, thus, potentially increasing the likelihood of PA uptake. Overall, the findings of this study may help inform the design of single-modality and combined PA programs for better health outcomes in cancer survivors.
Acknowledgements
GEF is supported by the Canadian Institutes of Health Research-Public Health Agency of Canada (CIHR-PHAC) Chair in Applied Public Health. KSC is supported by the Canada Research Chairs Program. We thank Carol Russell and Lorraine Cormier from the Alberta Cancer Registry for their assistance in conducting this study.
Compliance with ethical standards
Ethical approval was obtained from the Alberta Cancer Board Research Ethics Board and the University of Alberta Health Research Ethics Board.
Conflict of interest
The authors declare that they have no conflicts of interest.
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