Introduction Lack of physical activity and disturbed sleep have been linked to older adult’s poor cognitive outcomes; however, little is unknown how they interact to affect cognition long-term. The purpose of this study was to examine the association of baseline sleep duration and physical activity (PA) with change in cognition independently and interactively over four years. Methods The sample included 1126 community-dwelling older adults aged 60+ (mean age 67.1±5.9 years, 51% female) from the 2011 baseline and 2015 follow-up data of the China Health and Retirement Longitudinal Study (CHARLS). All variables were assessed through interviews. Sleep duration was measured with hours per 30-minute interval and categorized as very-short (<5h), short (5-6.5h), normal (7-8.5h), and long (≥9h). PA was calculated based on PA intensity, duration, and number of days. Cognition was a composite score of mental capacity, episodic memory, and visuospatial abilities. Data were analyzed using multiple regression (primary outcome: change in cognition; main independent variables: baseline sleep, PA, and sleep PA interaction). Results At baseline, 19% of participants had very-short sleep duration, 34.4% had short sleep, 39.2% had normal sleep, and 7.2% had long sleep. At follow-up, 57.5% of participants experienced cognitive decline (-3.5±2.5). After controlling for age, gender, education, region, body mass index, smoking, drinking, number of chronic conditions, pain, depression, and cognition at baseline, compared to participants reporting 7-8.5h sleep, those with ≥9h sleep had significantly greater decline in cognition [β=-1.4, 95% CI=2.4, -0.4], while those with <5h sleep [β=-0.5, 95% CI=-1.2, 0.2] and 5-6.5h sleep did not [β=-0.1, 95% CI=-0.7, 0.5]. PA was neither associated with cognitive decline, nor moderated the relationship between sleep duration and cognitive decline. Conclusion Long sleep might be a marker of cognitive decline in older adults. Prospective analysis, using objectively measured PA and sleep should be conducted to further examine these associations. Support National Institute of Nursing Research R00NR016484
variables, suggesting the results were not attributable solely to socioeconomic status. Encouraging people to continue to engage in the cognitive and social activities associated with higher cognitive reserve may increase well-being in later life in terms of quality of life, self-esteem and self-efficacy as well as helping to maintain cognitive function. Scholars have been trying to understand the concept of well-being for hundreds of years. Many experts from multiple disciplines have weighed in on the topic. Our research takes a phenomenological approach, conducting a mixed methods study to explore how people think about and experience well-being. We conducted over 100 semi-structured interviews with people from 18 to 82 years of age. During these interviews, people were asked to describe times in their lives when they experienced particularly high and low wellbeing. In addition, we collected survey data from 222 individuals (27 to 84 years old), assessing the various domains of well-being culled from rigorous analysis of the interviews. Results indicate that well-being is a multi-faceted concept that includes various domains: how people feel physically (e.g., pain experienced, vitality, ability to resist illness), emotional health, social connectedness, stress and resilience, finding purpose and meaning in daily life, taking care of oneself through healthy lifestyles, and several other domains. Older participants (age 60 and older) and younger participants reported similar levels of well-being, in spite of the fact that the older group was more likely to have one or more chronic illnesses. Different domains of well-being were more strongly associated with global ratings of well-being between the groups. For example, being resilient when facing setbacks was more strongly associated with well-being among the older group while physical functioning was more strongly associated among the younger group. The qualitative data illustrates how and why people change their weighting of the domains as they age. WELL-BEING OVER THE LIFE COURSE: CHANGES AND ADAPTATIONS NAPPING FREQUENCY, PLANNED VS.
Introduction Prior studies tying sleep to metabolic syndrome in older adults have mostly used self-report sleep measures. We investigated the association between actigraphic sleep parameters and metabolic syndrome components in well-functioning older adults. Methods We studied 434 participants in the Baltimore Longitudinal Study of Aging (aged 71.1±12.8 years, 41.4% women) with 6.6±1.0 nights of wrist actigraphy and data on metabolic syndrome components: blood triglyceride (TG) level >150 mg/dL; high density lipoprotein (HDL) <50 mg/dL; and waist circumference (WC) >88.9 cm for women and >101.6 cm for men. Sleep parameters were the primary predictors and metabolic syndrome components the outcomes. Logistic regression was performed, and results are expressed as odds ratio (OR) with p-values. Results After adjusting for age, sex, race and education, higher sleep efficiency (SEFF; per 10%) was associated with a lower odds of high WC (SEFF OR=0.60, p=0.01) and, compared to participants in the intermediate total sleep time tertile (5.5 to 6.8 h), those in the shortest tertile (<5.5 h) had a slightly lower odds of high WC (TST OR=0.98, p=0.02). In adjusted models, greater wake after sleep onset (WASO; per 30 min), greater average wake bout length (WBL; per min), and lower SEFF (per 10%) were associated with a greater odds of poor HDL level (<50 mg/dL) (WASO OR=1.37, p=0.05; WBL OR=1.49, p=0.007; SEFF OR=0.72, p=0.04). After further adjustment for BMI and depressive symptoms, only the association between longer WBL and poor HDL level remained significant (OR=1.48, p=0.01). There were no associations between sleep parameters and TG level. Conclusion Among well-functioning older adults, greater WASO but lower TST and SE are associated with poorer metabolic syndrome components. Longitudinal research is needed to evaluate the temporal associations of objectively measured poor sleep and metabolic syndrome components and evaluate the roles of BMI and depressive symptoms in these associations. Support The first author is supported by a Postdoctoral Fellowship by the Intramural Research Program (IRP) at the National Institute on Aging (NIA). This study was supported in part by National Institute on Aging (NIA) grant R01AG050507, the NIA Intramural Research Program (IRP), and Research and Development Contract HHSN-260-2004-00012C.
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