Time Out-of-Home and Cognitive, Physical, and Emotional Wellbeing of Older Adults: A Longitudinal Mixed Effects Model

Abstract

Background: Time out-of-home has been linked with numerous health outcomes, including cognitive decline, poor physical ability and low emotional state. Comprehensive characterization of this important health metric would potentially enable objective monitoring of key health outcomes. The objective of this study is to determine the relationship between time out-of-home and cognitive status, physical ability and emotional state.

Methods and findings: Participants included 85 independent older adults, age 65-96 years (M = 86.36; SD = 6.79) who lived alone, from the Intelligent Systems for Assessing Aging Changes (ISAAC) and the ORCATECH Life Laboratory cohorts. Factors hypothesized to affect time out-of-home were assessed on three different temporal levels: yearly (cognitive status, loneliness, clinical walking speed), weekly (pain and mood) or daily (time out-of-home, in-home walking speed, weather, and season). Subject characteristics including age, race, and gender were assessed at baseline. Total daily time out-of-home in hours was assessed objectively and unobtrusively for up to one year using an in-home activity sensor platform. A longitudinal tobit mixed effects regression model was used to relate daily time out-of-home to cognitive status, physical ability and emotional state. More hours spend outside the home was associated with better cognitive function as assessed using the Clinical Dementia Rating (CDR) Scale, where higher scores indicate lower cognitive function (βCDR = -1.69, p<0.001). More hours outside the home was also associated with superior physical ability (βPain = -0.123, p<0.001) and improved emotional state (βLonely = -0.046, p<0.001; βLow mood = -0.520, p<0.001). Weather, season, and weekday also affected the daily time out-of-home.

Conclusions: These results suggest that objective longitudinal monitoring of time out-of-home may enable unobtrusive assessment of cognitive, physical and emotional state. In addition, these results indicate that the factors affecting out-of-home behavior are complex, with factors such as living environment, weather and season significantly affecting time out-of-home. Studies investigating the relationship between time out-of-home and health outcomes may be optimized by taking into account the environment and life factors presented here.

Conflict of interest statement

Competing Interests: The research was funded in part by the Intel Corporation. This does not alter the authors’ adherence to PLOS ONE policies on sharing data and materials.

Figures

Fig 1. Histogram of the daily hours spent outside the home, showing the limit at zero.

A normal distribution curve is plotted as a dashed line to show the data is approximately normally distributed except at and below zero.

Fig 2. Relationship between loneliness and time out-of-home.

a) Probability density of the hours spent outside the home as a function of the UCLA Loneliness Scale. To create this graph, the probability density function is calculated at each value of the UCLA Loneliness Scale using the output from the Tobit model (all other variables are held at their mean or most prevalent value for binary variables). Color represents density, and discrete probabilities were linearly interpolated for graphical clarity. The mean function, μ (black trace) has been overlaid on the plot to show central tendency. As can be seen, the average amount of time spent outside the home given a participant leaves the home decreases from 5.0 hours at a UCLA Loneliness score of 21 (the lowest observed) to 3.7 hours at a UCLA Loneliness score of 56 (the highest observed). b) Probability of leaving the home on a given day as a function of the UCLA Loneliness score. The probability of leaving drops by about 10% across the range of loneliness scores such that the loneliest individual has an 80% probability of leaving on any given day, while the least lonely has a 90% probability of leaving on any given day.