Sedentary Behavior and Physical Activity of Older Adults

Abstract

High levels of sedentary behavior increase the risk for chronic disease, loss of physical function, disability, and all-cause mortality. Oldest old adults (age 80 and older) and older adults in assisted living are especially at risk for health decline and frailty. Accurate sedentary behavior measurement is critical in order to assess associated health risks and the effectiveness of interventions for reducing sedentary behavior. There is great need for interventions to reduce sedentary behavior and increase light physical activity in older adults in assisted living. This type of intervention could reduce health risks, slow functional decline and frailty, and delay residents’ needs for higher-level care such as a nursing home. The aims of this dissertation are the following: 1) Characterize sedentary behavior in community-dwelling adults age 80 and older by conducting a systematic review and meta-analysis focused on volume of sedentary behavior and factors associated with sedentary behavior in this population; 2) Identify optimal methods for processing objectively measured sedentary behavior data by analyzing ActiGraph vertical axis and vector magnitude data with multiple combinations of filters, non-wear algorithm lengths, and cut-points and by comparing ActiGraph estimates to ActivPAL-measured sedentary time in inactive people with chronic obstructive pulmonary disease; 3) Gather feedback from assisted living residents on a proposed Active for Life in Assisted Living intervention by conducting one-on-one interviews. A secondary aim was to explore contextual factors that may influence how the intervention will be implemented with this population. For aim 1, twenty-one articles were included in the review and meta-analysis showed adults 80 years and older are sedentary for 10.6 hours during the waking day. Although few articles examined factors associated with sedentary behavior in this age group, older age, male gender, non-Hispanic white race/ethnicity, social disadvantage, and declining cognitive function (in men) were associated with increased sedentary time. For aim 2, a secondary data analysis was conducted with a sample of older adults with chronic obstructive pulmonary disease (n=59) who wore ActiGraph and ActivPAL devices for seven days. Thirty techniques for processing ActiGraph sedentary behavior data were compared to ActivPAL-measured sedentary behavior using the Bland-Altman method. The best ActiGraph technique was vector magnitude data with low frequency extension filter, 120-minute non-wear algorithm, and sedentary behavior cut-point of <40 counts/15 seconds (concordance correlation 0.839; mean difference -11.7 minutes/day). For aim 3, one-on-one semi-structured interviews were conducted with 20 assisted living residents. They were presented the proposed Active for Life intervention and asked questions to inform its development. Data were analyzed using content and thematic analysis. Assisted living residents recommended shorter intervention sessions, shorter overall intervention length, and framing the goal of the intervention as increasing light physical activity. The thematic analysis identified factors that could influence intervention implementation, including motivation, safety, beliefs about aging, varying abilities, social influences, and physical activity opportunities in AL. As a whole, the results of this dissertation contribute to our knowledge of sedentary behavior in older adults. Findings highlight the high volume of sedentary behavior in the oldest old, showing opportunity for intervention to reduce sedentary time. We also identified optimal methods for measuring sedentary behavior in older adults, which may guide data processing decisions. In addition, we gathered valuable feedback on a proposed intervention to reduce sedentary behavior of assisted living residents, an important first step in developing an intervention appropriate for this population.PHDNursingUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/171333/1/katewebs_1.pd