The relationship between sleep and physical activity in nonagenarians and centenarians

Abstract

This article is published in Open Access under the Creative Commons Attribution license, which allows use, distribution, and reproduction in any medium, without restrictions, as long as the original work is correctly cited. Sleep in nonagenarians and centenarians Geriatr Gerontol Aging. 2021;15:e0210062 2 INTRODUCTION The fastest growing age group in Brazil is nonagenarians and centenarians. Between the last two censuses, the age group ≥ 90 years grew by almost 80%, which was higher than older adults (42%) and the general population (12%).1 The aging process is slow, gradual, and affects all aspects of an individual’s life. It involves biopsychosocial losses, increased nutritional risk, chronic diseases, sleep disorders, psychological and mood changes (dementia and depression), and vulnerability to social conditions (low income, isolation). These situations contribute to greater physical inactivity, lower quality of life, and a worsening of general health.2 The sleep-wake cycle influences quality of life. The benefits of good quality sleep in older adults are reflected in biological, psychological, emotional, intellectual, and social levels.3 However, it appears that sleep is often impaired among older adults. Poor sleep quality can cause tiredness and decreased concentration, response speed (a risk factor for falls) and intellectual capacity, in addition to memory loss, cognitive impairment, dementia, anxiety and irritability. In older adults it can also increase the risk of respiratory and allergic diseases, worsen cardiovascular diseases, and affect glucose metabolism, hypertension, physiological stress, obesity, and the immune system.4-6 Physical activity, considered beneficial for sleep quality, is subdivided into four dimensions: leisure (exercise and sports), active commuting, domestic activities, and work activities. The first dimension can be classified as planned, structured, and repetitive exercise to maintain health, while the other three are unstructured and performed spontaneously throughout the day.2 Consistent physical activity provides numerous benefits, including improved sleep, functionality, and cognition, reduced polypharmacy and risk of falls, and improved independence and autonomy, in addition to psychological benefits, such as reduced depression and more frequent social contact. In addition to improving postural stability, it is effective in treating pain and has significant effects on muscle mass and strength. A minimum of 150 minutes of regular physical activity per week is recommended for healthy living. Therefore, regular physical activity is considered a great ally in quality longevity, contributing to active aging. Because exercise recommendations may not apply to nonagenarians, few studies have investigated their effects in this population.7-9 Thus, the present study sought to associate physical activity with sleep quality in nonagenarians and centenarians. METHODS This study is a descriptive cross-sectional analysis of secondary data from the initial assessment of a descriptive longitudinal cohort study called Multidisciplinary Home Care in Longevity (AMPAL), which was conducted in the city of Porto Alegre, Brazil and involved nonagenarians and centenarians. The study was approved by the Pontifical Catholic University of Rio Grande do Sul Research Ethics Committee (opinion 1.639.961/2016, CAEE 59906216.0.0000.5336). All participants or family members provided written informed consent prior to participation. The cohort was initially assessed between June and November 2016, with nonagenarians and centenarians evaluated in randomly selected households in Porto Alegre’s 17 fiscal regions. The target sample was 240 nonagenarians and centenarians, which corresponded to 5% of the 4800 estimated residents in this age group in 2016. The initial evaluation received funding from the Porto Alegre Municipal Fund for Older Adults. Data were collected through digital forms with automatic data entry created using the TELEform tool and were subsequently stored in an Excel database. TELEform can audit data, ensuring correct entry. The study’s sampling methodology and instruments were published by Rigo and Bós,10 and included exercise frequency (“Did you engage in any type of physical exercise or sports in the last three months?”, considered yes if at least once a week) and questions related to the sleep quality (“How was your sleep in the past six months: difficulty falling asleep; difficulty staying asleep; restless sleep; daytime sleepiness or no change?”). Sleep quality was assessed using questions from the Pittsburgh Sleep Quality Index11 and was considered altered in participants who reported one or more difficulty. Participants who could not answer the question, either due to difficulties in understanding (cognitive impairment) or communication (hearing loss), were excluded from the sample. Caregivers and family members did not respond for the participants. Sociodemographic data were also collected, including sex, race, education, marital status, age group and living arrangements, ie, the person with whom the participant lives. Sociodemographic and clinical variables were treated categorically, and a homogeneity test for the variables was unnecessary. The data were initially analyzed as absolute and relative frequencies, and χ2 was used to test the associations between physical activity, the different components of sleep quality, and sociodemographic and clinical characteristics. Possible associations between sleep quality and sociodemographic and clinical characteristics were also tested. Variables with significance levels lower than 10% (p < 0.10) in the descriptive analyses were included in the logistic regression to determine the risk of altered sleep quality and its relationship with physical activity. The data were analyzed in Epi Info 7.2.3.1, a public domain software package available from the U.S. Centers for Disease Aguirre FB, Gazola AA, Araujo VAF, Bós AJG Geriatr Gerontol Aging. 2021;15:e0210062 3 Control and Prevention. Significance levels < 5% (p < 0.05) were considered statistically significant, while those between 5 and 10% were considered as indicative of statistical significance.12 RESULTS The initial assessment involved 245 participants, of whom 12 were excluded due to cognitive or communicative inability to answer all the questions, particularly those about self-perceived health. Thus, a total of 233 participants were included in the analysis. Table 1 shows the relationship between physically active (60 participants) and inactive (173) participants and sleep quality. The sample was predominantly women (73%), of whom 21.8% were physically active, which was significantly lower than the men (36.5%; p = 0.02). The centenarians had a lower frequency of physical activity than the nonagenarians, but not significantly so (p = 0.37). Non-Whites had a lower activity level than Whites (p = 0.75) and single participants had a lower activity level than married ones (p = 0.86). Regarding living arrangements, those who lived with a caregiver had a higher frequency of physical activity (42.1%), which was indicative of significance (p = 0.09). Participants with high school or higher education more frequently reported being physically active (33%, p = 0.44). Although not significantly so (p = 0.37), sleep components were worse among the physically inactive, since 77% of those who with altered sleep patterns were physically inactive. Of those with problems falling sleep, 66% were physically inactive (p = 0.05). Of those who reported drowsiness or apathy, 83%) were physically inactive (p = 0.03). Table 2 shows the relationship between sleep quality and sociodemographic and clinical characteristics. Altered sleep patterns were more prevalent in women (56%), than men (46%; p = 0.18). Age group was not significantly associated with sleep quality (p = 0.73), but the prevalence of sleep problems increased according to age group: 52% among those 90 to 94 years old, 56% among those 95 to 99 years old, and 57% among centenarians. The variable race, dichotomized as White or Non-White, was not significantly associated with sleep disturbance (p = 0.82). Regarding marital status, the sleep disorder rate among divorced participants was 16.67% and was much higher among married (54.9%) single (54.55%) and widowed (53.61%) participants. The variable that had the most significant relationship with sleep disorders was education level (p = 0.07). It was observed that 75% of the illiterate and 54% of those with complete primary school had altered sleep patterns. The rate of altered sleep was lower among those with high school or higher education (42%). Altered sleep was less prevalent among those who lived with a caregiver (40%), especially compared to those who lived with a family member (54.55%, p = 0.51). Regarding self-perceived health, there was a positive correlation between sleep disorders and worsening self-perceived health: 49% in those with excellent or good health, 59% in those with normal health, and 67% in those with poor or very poor health (p = 0.16). Table 3 compares the chance of good sleep quality with physical activity or inactivity, adjusted for sociodemographic Table 1. Physical activity, sociodemographic characteristics, and sleep quality in nonagenarians and centenarians in Porto Alegre, Brazil, 2016. Physical activity No (%) Yes (%) Total (%) p-value