OBJECTIVES: To determine the number of steps taken by older patients in hospital and 1 week after discharge; to identify factors associated with step numbers after discharge; and to examine the association between functional decline and step numbers after discharge.DESIGN: Prospective observational cohort study conducted in 2015-2017.SETTING AND PARTICIPANTS: Older adults (≥70 years of age) acutely hospitalized for at least 48 hours at internal, cardiology, or geriatric wards in 6 Dutch hospitals.METHODS: Steps were counted using the Fitbit Flex accelerometer during hospitalization and 1 week after discharge. Demographic, somatic, physical, and psychosocial factors were assessed during hospitalization. Functional decline was determined 1 month after discharge using the Katz activities of daily living index.RESULTS: The analytic sample included 188 participants [mean age (standard deviation) 79.1 (6.7)]. One month postdischarge, 33 out of 174 participants (19%) experienced functional decline. The median number of steps was 656 [interquartile range (IQR), 250-1146] at the last day of hospitalization. This increased to 1750 (IQR 675-4114) steps 1 day postdischarge, and to 1997 (IQR 938-4098) steps 7 days postdischarge. Age [β = -57.93; 95% confidence interval (CI) -111.15 to -4.71], physical performance (β = 224.95; 95% CI 117.79-332.11), and steps in hospital (β = 0.76; 95% CI 0.46-1.06) were associated with steps postdischarge. There was a significant association between step numbers after discharge and functional decline 1 month after discharge (β = -1400; 95% CI -2380 to -420; P = .005).CONCLUSIONS AND IMPLICATIONS: Among acutely hospitalized older adults, step numbers double 1 day postdischarge, indicating that their capacity is underutilized during hospitalization. Physical performance and physical activity during hospitalization are key to increasing the number of steps postdischarge. The number of steps 1 week after discharge is a promising indicator of functional decline 1 month after discharge.
BACKGROUND: Ambulatory children with Spina Bifida (SB) often show a decline in physical activity leading to deconditioning and functional decline. Therefore, assessment and promotion of physical activity is important. Because energy expenditure during activities is higher in these children, the use of existing pediatric equations to predict physical activity energy expenditure (PAEE) may not be valid. AIMS: (1) To evaluate criterion validity of existing predictions converting accelerocounts into PAEE in ambulatory children with SB and (2) to establish new disease-specific equations for PAEE. METHODS: Simultaneous measurements using the Actical, the Actiheart, and indirect calorimetry took place to determine PAEE in 26 ambulatory children with SB. DATA ANALYSIS: Paired T-tests, Intra-class correlations limits of agreement (LoA), and explained variance (R2) were used to analyze validity of the prediction equations using true PAEE as criterion. New equations were derived using regression techniques. RESULTS: While T-tests showed no significant differences for some models, the predictions developed in healthy children showed moderate ICC’s and large LoA with true PAEE. The best regression models to predict PAEE were: PAEE = 174.049 + 3.861 × HRAR – 60.285 × ambulatory status (R2 = 0.720) and PAEE = 220.484 + 0.67 × Actical counts – 60.717 × ambulatory status (R2 = 0.681). CONCLUSIONS: Existing equations to predict PAEE are not valid for use in children with SB for the individual evaluation of PAEE. The best regression model was based on HRAR in combination with ambulatory status, followed by a new model for the Actical monitor. A benefit of HRAR is that it does not require the use of expensive accelerometry equipment. Further cross-validation of these models is still needed.
