An actigraphic study comparing community dwelling poor sleepers with non-demented care home residents

Sleep disturbances are a common problem among institutionalized older people. Studies have shown that this population experiences prolonged sleep latency, increased fragmentation and wake after sleep onset, more disturbed circadian rhythms, and night-day reversal. However, studies have not examined the extent to which this is because of individual factors known to influence sleep (such as age) or because of the institutional environment. This article compares actigraphic data collected for 14 days from 122 non-demented institutional care residents (across ten care facilities) with 52 community dwelling poor sleepers >65 yrs of age. Four dependent variables were analyzed: (i) “interdaily stability” (IS); (ii) “intradaily variability” (IV); (iii) relative amplitude (RA) of the activity rhythm; and (iv) mean 24?h activity level. Data were analyzed using a fixed-effect, single-level model (using MLwiN). This model enables comparisons between community and institutional care groups to be made while conditioning out possible “individual” effects of “age,” “sex,” “level of dependency,” “level of incontinence care,” and “number of regular daily/prescribed medications.” After controlling for the effects of a range of individual level factors, and after controlling for unequal variance across groups (heteroscedascity), there was little difference between community dwelling older adults and institutional care residents in IS score, suggesting that the stability of day-to-day patterns (such as bed get-up, lunch times, etc.) is similar within these two resident groups. However, institutional care residents experienced more fragmented rest/wake patterns (having significantly higher IV scores and significantly lower mean activity values). Our findings strongly suggest that the institutional care environment itself has a negative association with older people's rest/wake patterns; although, longitudinal studies are required to fully understand any causal relationships