Article Title



Lauren C. Bates-Fraser, Emma Cowley, Lee Stoner, FACSM, Erik D. Hanson, FACSM. The University of North Carolina Chapel Hill, Chapel Hill, NC.

BACKGROUND: The average U.S adult spends most of the waking day engaging in sedentary behavior (SB), which is concerning considering the strong positive association between SB and chronic disease risk. Cancer survivors are particularly susceptible to the negative consequences of SB, considering they already have elevated chronic disease risk. To develop effective SB reduction interventions, we first need to understand the behavior. One challenge is that SB occurs in a variety of contexts, including occupational (O), transport (T), television viewing (TV), leisure time screen/computer (C), or other. The objective of this study was to investigate SB context and clustering in U.S. adults with and without cancer. METHODS: We surveyed a convenience sample of 1,588 adults (aged >18 years) residing in the US from 2020-2022. Participants self-reported cancer history and SB context including O, T, TV, C, and other in hours per day for weekdays (WD-SB) and weekends (WE-SB). Z-scores were calculated for SB. Cluster analysis was conducted using a two-step method including agglomerative hierarchical clustering with squared Euclidean distance and visual inspection to identify the number of clusters followed by K-means clustering. Clusters were labeled via distinguishing SB contexts (high >0.5, low: <-0.5). Partial eta-squared (η2) measured effect size (small: 0.01, medium: 0.06, large: 0.14 respectively) and ANOVA was used to compare group by cluster. RESULTS: 233 cancer survivors (48 ± 19 yr., 52% female, 73% employed, 15+ cancer types) and 1,355 individuals without cancer (45 ± 18 yr., 64% female, 57% employed) completed the survey. Cancer participants engaged in 11.4 ± 6.3 WD-SB and 10.9 ± 5.6 WE-SB. Non-cancer individuals engaged in 10.6. ± 6.3 WD-SB and WE-SB. Cluster analysis identified 4 SB-context clusters with a small effect (η2: 0.01, p= 0.03). Cluster 1 served as the reference group and was characterized by the least amount of SB in all contexts (34% cancer). Cluster 2 included the most cancer survivors, exhibited high O, T, TV, C and moderate other for WD-SB and WE-SB (39% cancer, p=0.03). Cluster 3 exhibited low O, moderate T, TV, C, and high other WD-SB/WE-SB (6% cancer, p=0.03). Cluster 4 exhibited moderate O and TV and very low T, C, or other WD-SB/WE-SB (21% cancer, p=0.01). CONCLUSIONS: The largest number of cancer survivors were in the highest SB cluster across all contexts (cluster 2). However, the lowest SB cluster (cluster 1) had the second largest population of cancer survivors, suggesting some report low amounts of SB. SB context did not vary from WD to WE and cancer survivors are highly sedentary amongst all contexts. Objective accelerometry data are needed to confirm these findings. Future interventions should potentially target SB contexts most amenable to change such as TV or C because these contexts have fewer barriers to change.

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