Napping Characteristics and Restricted Participation in Valued Activities Among Older Adults

Napping Characteristics and Restricted Participation in Valued Activities Among Older Adults Abstract Background Napping is associated with both positive and negative health outcomes among older adults. However, the association between particular napping characteristics (eg, frequency, duration, and whether naps were intentional) and daytime function is unclear. Methods Participants were 2,739 community-dwelling Medicare beneficiaries aged ≥65 years from the nationally representative National Health and Aging Trends Study. Participants reported napping frequency, duration, and whether naps were intentional versus unintentional. Restricted participation in valued activities was measured by self-report. Results After adjusting for potential confounders and nighttime sleep duration, those who took intentional and unintentional naps had a greater odds of any valued activity restriction (ie, ≥1 valued activity restriction), compared to those who rarely/never napped (unintentional odds ratio [OR] = 1.34, 95% confidence interval [CI] 1.01, 1.79, intentional OR = 1.49, 95% CI 1.09, 2.04). There was no difference between unintentional napping and intentional napping with respect to any valued activity restriction after adjustment for demographics. Compared to participants napping “some days,” those napping most days/every day had a greater odds of any valued activity restriction (OR = 1.68, 95% CI 1.30, 2.16). Moreover, each 30-minute increase in average nap duration was associated with a 25% greater odds of any valued activity restriction (OR = 1.25, 95% CI 1.10, 1.43). Conclusion Older adults who took more frequent or longer naps were more likely to report activity restrictions, as were those who took intentional or unintentional naps. Additional longitudinal studies with objective measures of sleep are needed to further our understanding of associations between napping characteristics and daytime dysfunction. Sleep, Social participation, Health status, Function Napping is common among older adults and increases in frequency with age (1–3). Between 18% and 49% of older adults nap regularly (2,3), but it is unclear whether napping is harmful or beneficial for this population (4). Among older adults, studies have found associations between napping and poor outcomes such as all-cause mortality (5), diabetes (6), hypertension (7), and cognitive impairment (1,8). Conversely, short-term, laboratory-based experiments have found napping improves cognitive performance (9), and reduces blood pressure in older adults (10). Little is known, however, about the extent to which napping is linked to participation in activities that maximize healthy outcomes in older adults. Participation in social activities is correlated with increased longevity and wellbeing among older adults (11), and fewer depressive symptoms (12). In contrast, lower social activity levels are associated with poorer cognitive health (13), and greater mortality risk (14). The association between social activity and health outcomes may also differ by the type of activity. For instance, a study found that participation in religious groups was associated with reduced mortality risk in older women, but other social activities (eg, volunteering) were not (15). Some studies have demonstrated associations between sleep and social activities. Older adults in the National Health and Aging Trends Study (NHATS) who reported insomnia symptoms had a greater odds of restrictions in valued social activities compared to those reporting no insomnia symptoms (16). Another study found that older adults who participated more often in collective social activities (eg, religious services) had less fragmented sleep, measured by actigraphy (17). However, to our knowledge, there are no studies examining the association between napping and participation in valued social activities in community-dwelling older adults. Napping does not occur uniformly, and individual napping characteristics such as duration and frequency may be modifiable parameters that improve participation in social activities and health outcomes. Alternatively, naps may be markers of conditions that increase older adults’ risk for daytime dysfunction. Studies of the association of specific napping parameters with important outcomes among older adults would enhance understanding of the potential effects of napping on health (4). Thus, we investigated the association of intentional versus unintentional napping, and frequency and duration of napping, with restrictions in valued activities in community-dwelling older adults. Methods Participants We studied participants from the 2013 and 2014 rounds of the NHATS, a nationally representative study of Medicare beneficiaries aged ≥65 years (18). In each of these rounds, a sleep-focused assessment was added to the interviews of a randomly selected subset of participants. After combining cross-sectional data from the two rounds, there were 2,908 participants with napping data. We excluded participants who were not community-dwelling (eg, in nursing homes; n = 56) or reported all activities assessed as “not so important” (n = 113). Our final sample contained 2,739 participants (Round 3 = 1,530; Round 4 = 1,209). A proxy respondent familiar with a participant’s care and health provided predictor and outcome variable data for 164 participants who were unable to respond due to illness, disability, or a language barrier. In sensitivity analyses excluding proxy respondents, overall patterns of findings remained, though associations decreased in magnitude and some results became nonsignificant. Because this was likely due to a loss of power, we included proxy respondents in our final analyses. Measures Napping frequency Participants were asked, “…how often did you take naps during the day?” and were categorized as: non-nappers (“never” or “rarely”; n = 1,219); infrequent nappers (“some days”; n = 758); or frequent nappers (“most days” or “every day”; n = 762). Napping duration and intention Participants who reported napping more frequently than “never” were asked, “On average, how long were these naps?”, and we created an average nap duration variable (in minutes). Participants who reported napping “rarely” were excluded from our analyses of average nap duration. These participants were also asked, “In general, were these naps planned, or did you fall asleep without meaning to?”, with response options “naps planned”; “fell asleep without meaning to” or “both (some planned/some not)”. We classified those reporting falling asleep without meaning to or “both” as unintentional nappers (n = 920) and others as intentional nappers (n = 600). Participants who reported napping “rarely” were also asked about napping intention but were classified as non-nappers. Excessive daytime sleepiness (EDS) Participants were asked about past-month EDS: “…how often did you have trouble staying awake at times during the day when you wanted to be awake?”, with response options “never”; “rarely”; “some days”; “most days”; “every day”. We reclassified these responses as “rarely/never”; “some days”; and “most days/every day”. Nighttime sleep duration Participants were also asked about past-month nighttime sleep duration: “…how many hours of actual sleep did you usually get at night?” Participants reported sleep duration in hours. We did not analyze nighttime sleep duration data for participants who reported “no usual hours or different from night to night” (n = 56). Participation in valued activities Participants were asked whether they considered each of the following activities “very”, “somewhat”, or “not so” important: “visit in person with friends or family not living with you”; “attend religious services”; “participate in clubs, classes, or other organized activities” (excluding religious services); and “go out for enjoyment” (eg, going to a movie or dinner). Activities rated as “very” or “somewhat” important were considered “valued.” A participant’s data were only included for a given activity if it was rated as valued. Participants were also asked whether “health or functioning” kept them from performing each activity in the last month. Those responding “yes” were coded as having a restriction for that activity. Other measures Participants reported demographic and health characteristics. Age was categorized as 65–69 years; 70–74 years; 75–79 years; 80–84 years; 85–89 years; and 90+ years. We categorized race/ethnicity as White, non-Hispanic; Black, non-Hispanic; Hispanic; and Other (Asian, American Indian, Native Hawaiian, Pacific Islander, more than one race/ethnicity). We recoded education as less than high school, high school graduate, or more than high school and used self-reported height and weight to calculate body mass index (BMI; kg/m2; recoded as <18.5 kg/m2 [underweight], 18.5–24.9 kg/m2 [normal weight], 25–29.9 kg/m2 [overweight] or ≥30 kg/m2 [obese]) (19). Participants completed the Patient Health Questionnaire (PHQ)-2 to measure depressive symptoms and the Generalized Anxiety Disorder (GAD)-2 for anxiety symptoms (20). Both are 2-item measures, with responses from 0 to 3 per item. We summed items to obtain a total (0–6) for each measure. Participants also reported whether they had: history of a heart attack; heart disease; high blood pressure; arthritis; osteoporosis; diabetes; stroke; dementia or Alzheimer’s disease; and cancer. We created a categorical variable for number of medical conditions: 0 or 1 (27.0%), 2 (28.1%), 3 (22.9%), and 4 or more (22.0%). Statistical Analyses We computed descriptive statistics for participant characteristics, and compared intentional, unintentional, or non-nappers using chi-square tests for categorical and simple linear regression for continuous variables. Next, we performed logistic regression analyses with napping intention (ie, intentional, unintentional, or non-napping [reference]) as the primary predictor and health or functioning-related restrictions in each valued activity or in any valued activity (ie, ≥1 valued activity) as the outcome. We fit three sets of models adjusting for different covariates: Model 1 demographics (age, race, gender, education); Model 2: Model 1 covariates + physical health (number of medical conditions, BMI category); and Model 3: Model 2 covariates + mental health (GAD-2, PHQ-2 scores) and nighttime sleep duration. For models with napping duration or frequency as the primary predictors, we fit a Model 4: Model 3 covariates + EDS. We performed linear combination postestimation analyses to obtain pairwise comparisons (unintentional vs intentional napping [reference]; frequent vs infrequent napping [reference]). We explored interactions of napping characteristics with EDS, adding interaction terms for Sleepiness × Napping frequency, and for Sleepiness × Average nap duration, to Model 4. An α less than 0.05 indicated statistical significance. When interaction terms were significant or near significant (p < .10), we reported stratified results. Survey weights were applied to render results nationally representative and account for stratification and clustering in the study design. Analyses were performed using Stata version 14.0 (Statacorp, College Station, TX). Results Participant Characteristics Participants’ demographic and health characteristics are presented by napping type in Table 1. Overall, 47.4% of participants were non-nappers, 23.3% reported intentional naps only, and 29.3% reported unintentional naps. Napping type was significantly associated with age, gender, race, education, BMI, PHQ-2 and GAD-2 scores, number of medical conditions, EDS, and nighttime sleep duration (all p’s < .01). Among participants who napped more than rarely, napping intention was significantly associated with napping frequency (p < .02), but not with average nap duration (p = .48). Table 1. Participant Characteristics (weighted row %s)   Total Samplea  Non-Nappers  Intentional Naps  Unintentional Naps    Unweighted N  100% (N = 2,739)  47.4% (n = 1,219)  23.3% (n = 600)  29.3% (n = 920)  p Value  Age          <.001   65–69  11.9  49.3  25.7  25.0     70–74  31.8  53.2  23.7  23.1     75–59  23.0  49.8  21.44  28.8     80–84  17.5  41.7  22.7  35.6     85–89  10.1  38.6  24.0  37.4     90+  5.70  34.6  23.9  41.5    Gender          <.001   Male  41.5  39.3  27.3  33.4     Female  58.5  53.2  20.5  26.3    Race          <.001   White, Non-Hispanic  82.5  48.5  24.7  26.8     Black, Non-Hispanic  7.70  42.4  12.4  45.2     Hispanic  6.10  46.6  18.5  34.9     Other  3.70  39.2  17.6  43.2    Education Level          <.001   <High School  18.5  43.2  18.6  38.2     High School Graduate  25.9  47.5  19.3  33.2     >High School  55.6  49.1  26.4  24.5    BMI (in kg/m2)          <.01   <18.5  1.80  51.2  23.2  25.6     18.5–24.9  31.7  51.3  21.8  26.9     25–29.9  38.3  51.9  21.7  26.4     ≥30.0  28.2  36.3  27.8  35.9    PHQ-2, mean ± SE  0.87 ± 0.03  0.71 ± 0.04  0.83 ± 0.05  1.16 ± 0.05  <.01  GAD-2, mean ± SE  0.81 ± 0.03  0.74 ± 0.04  0.75 ± 0.05  0.96 ± 0.05  <.01  # of Medical Conditions          <.01   0 or 1  27.0  54.8  24.1  21.1   2  28.1  48.9  24.3  26.8   3  22.9  45.6  21.1  33.3   4+  22.0  37.9  23.7  38.4  EDS          <.01   Never/Rarely  64.5  59.9  23.0  17.1   Some Days  24.7  27.1  24.3  48.6   Most Days/Every Day  10.8  20.4  22.6  57.0  Nighttime Sleep Duration (hours), mean ± SE  7.03 ± 0.04  7.01 ± 0.05  7.22 ± 0.07  6.91 ± 0.06  <.01  Nap Frequencyb          <.02   Infrequent  52.7  N/A  41.0  59.0   Frequent  47.3  N/A  47.9  52.1  Average Nap Durationb (minutes), mean ± SE  55.4 ± 1.40  N/A  56.6 ± 1.71  54.4 ± 2.29  .48    Total Samplea  Non-Nappers  Intentional Naps  Unintentional Naps    Unweighted N  100% (N = 2,739)  47.4% (n = 1,219)  23.3% (n = 600)  29.3% (n = 920)  p Value  Age          <.001   65–69  11.9  49.3  25.7  25.0     70–74  31.8  53.2  23.7  23.1     75–59  23.0  49.8  21.44  28.8     80–84  17.5  41.7  22.7  35.6     85–89  10.1  38.6  24.0  37.4     90+  5.70  34.6  23.9  41.5    Gender          <.001   Male  41.5  39.3  27.3  33.4     Female  58.5  53.2  20.5  26.3    Race          <.001   White, Non-Hispanic  82.5  48.5  24.7  26.8     Black, Non-Hispanic  7.70  42.4  12.4  45.2     Hispanic  6.10  46.6  18.5  34.9     Other  3.70  39.2  17.6  43.2    Education Level          <.001   <High School  18.5  43.2  18.6  38.2     High School Graduate  25.9  47.5  19.3  33.2     >High School  55.6  49.1  26.4  24.5    BMI (in kg/m2)          <.01   <18.5  1.80  51.2  23.2  25.6     18.5–24.9  31.7  51.3  21.8  26.9     25–29.9  38.3  51.9  21.7  26.4     ≥30.0  28.2  36.3  27.8  35.9    PHQ-2, mean ± SE  0.87 ± 0.03  0.71 ± 0.04  0.83 ± 0.05  1.16 ± 0.05  <.01  GAD-2, mean ± SE  0.81 ± 0.03  0.74 ± 0.04  0.75 ± 0.05  0.96 ± 0.05  <.01  # of Medical Conditions          <.01   0 or 1  27.0  54.8  24.1  21.1   2  28.1  48.9  24.3  26.8   3  22.9  45.6  21.1  33.3   4+  22.0  37.9  23.7  38.4  EDS          <.01   Never/Rarely  64.5  59.9  23.0  17.1   Some Days  24.7  27.1  24.3  48.6   Most Days/Every Day  10.8  20.4  22.6  57.0  Nighttime Sleep Duration (hours), mean ± SE  7.03 ± 0.04  7.01 ± 0.05  7.22 ± 0.07  6.91 ± 0.06  <.01  Nap Frequencyb          <.02   Infrequent  52.7  N/A  41.0  59.0   Frequent  47.3  N/A  47.9  52.1  Average Nap Durationb (minutes), mean ± SE  55.4 ± 1.40  N/A  56.6 ± 1.71  54.4 ± 2.29  .48  Note: BMI = Body mass index; EDS = Excessive daytime sleepiness; GAD-2 = Generalized Anxiety Disorder-2; PHQ-2 = Patient Health Questionnaire-2. aColumn %. bExcluded non-nappers. View Large Napping Intentionality and Restricted Participation In Model 1, compared to non-nappers, participants reporting intentional and unintentional napping had a higher odds of restrictions in visiting with friends/family (intentional odds ratio [OR] = 1.62, 95% confidence interval [CI] 1.06, 2.48; unintentional OR = 1.99, 95% CI 1.41, 2.82), and unintentional nappers had a greater odds of restrictions in going out for enjoyment (OR = 1.80, 95% CI 1.21, 2.67) (Table 2). However, these associations were not significant in subsequent models. In Models 1 and 2, compared to non-nappers, unintentional nappers had a greater odds of restrictions in participating in clubs/activities (Model 2: OR = 1.69, 95% CI 1.05, 2.71), but not in Model 3. In all three Models, unintentional nappers had a greater odds of restricted religious service attendance than non-nappers (Model 3: OR = 1.42, 95% CI 1.03, 1.96). Compared to non-nappers, those who reported intentional or unintentional naps had a greater odds of any activity restriction in all Models (Model 3: intentional napping OR = 1.34, 95% CI 1.01, 1.79; unintentional napping OR = 1.49, 95% CI 1.09, 2.04). Table 2. Associations of Napping Intentionality With Health/Functioning-Related Restrictions in Valued Activity Participation Napping Type  % With Activity Restriction  Model 1a OR (95% CI)  Model 2b OR (95% CI)  Model 3c OR (95% CI)    Restricted in Visiting with Friends/Family  Non-nappers  5.3  1.00  1.00  1.00  Intentional  7.6  1.62 (1.06, 2.48)*  1.40 (0.91, 2.16)  1.27 (0.78, 2.05)  Unintentional  10.3  1.99 (1.41, 2.82)**  1.45 (0.999, 2.11)  1.32 (0.88, 1.98)    Restricted in Attending Religious Services  Non-nappers  13.7  11.00  1.00  1.00  Intentional  14.8  1.20 (0.87, 1.66)  1.04 (0.75, 1.46)  0.98 (0.67, 1.43)  Unintentional  23.1  1.96 (1.45, 2.64)**  1.50 (1.11, 2.03)**  1.42 (1.03, 1.96)*    Restricted in Participating in Clubs/Activities  Non-nappers  8.04  1.00  1.00  1.00  Intentional  9.33  1.20 (0.77, 1.87)  1.06 (0.68, 1.67)  1.03 (0.62, 1.70)  Unintentional  17.1  2.23 (1.45, 3.44)**  1.69 (1.05, 2.71)*  1.52 (0.94, 2.47)    Restricted in Going Out for Enjoyment  Non-nappers  5.67  1.00  1.00  1.00  Intentional  7.54  1.43 (0.95, 2.14)  1.29 (0.85, 1.95)  1.11 (0.69, 1.77)  Unintentional  10.2  1.80 (1.21, 2.67)**  1.46 (0.97, 2.19)  1.42 (0.92, 2.18)    Restricted in Any Valued Activity  Non-nappers  16.6  1.00  1.00  1.00  Intentional  21.7  1.55 (1.24, 1.93)**  1.41 (1.11, 1.78)**  1.34 (1.01, 1.79)*  Unintentional  30.2  2.09 (1.64, 2.67)**  1.63 (1.23, 2.16)**  1.49 (1.09, 2.04)*  Napping Type  % With Activity Restriction  Model 1a OR (95% CI)  Model 2b OR (95% CI)  Model 3c OR (95% CI)    Restricted in Visiting with Friends/Family  Non-nappers  5.3  1.00  1.00  1.00  Intentional  7.6  1.62 (1.06, 2.48)*  1.40 (0.91, 2.16)  1.27 (0.78, 2.05)  Unintentional  10.3  1.99 (1.41, 2.82)**  1.45 (0.999, 2.11)  1.32 (0.88, 1.98)    Restricted in Attending Religious Services  Non-nappers  13.7  11.00  1.00  1.00  Intentional  14.8  1.20 (0.87, 1.66)  1.04 (0.75, 1.46)  0.98 (0.67, 1.43)  Unintentional  23.1  1.96 (1.45, 2.64)**  1.50 (1.11, 2.03)**  1.42 (1.03, 1.96)*    Restricted in Participating in Clubs/Activities  Non-nappers  8.04  1.00  1.00  1.00  Intentional  9.33  1.20 (0.77, 1.87)  1.06 (0.68, 1.67)  1.03 (0.62, 1.70)  Unintentional  17.1  2.23 (1.45, 3.44)**  1.69 (1.05, 2.71)*  1.52 (0.94, 2.47)    Restricted in Going Out for Enjoyment  Non-nappers  5.67  1.00  1.00  1.00  Intentional  7.54  1.43 (0.95, 2.14)  1.29 (0.85, 1.95)  1.11 (0.69, 1.77)  Unintentional  10.2  1.80 (1.21, 2.67)**  1.46 (0.97, 2.19)  1.42 (0.92, 2.18)    Restricted in Any Valued Activity  Non-nappers  16.6  1.00  1.00  1.00  Intentional  21.7  1.55 (1.24, 1.93)**  1.41 (1.11, 1.78)**  1.34 (1.01, 1.79)*  Unintentional  30.2  2.09 (1.64, 2.67)**  1.63 (1.23, 2.16)**  1.49 (1.09, 2.04)*  Note: See Supplementary Table 1 for sample sizes. CI = Confidence interval; OR = Odds ratio. aModel 1 adjusted for age, race, gender, education category. bModel 2 adjusted for Model 1 covariates + number of medical conditions, BMI category. cModel 3 adjusted for Model 2 covariates + GAD-2, PHQ-2, nighttime sleep duration. *p value < .05; **p value < .01. View Large We also compared the association of unintentional versus intentional napping with activity restrictions. In all three Models, there were no differences between unintentional and intentional nappers in odds of restrictions in visiting with friends/family or going out for enjoyment. However, compared to intentional nappers, unintentional nappers had a greater odds of restricted religious service attendance in Models 1 and 2 (Model 2: OR = 1.44, 95% CI 1.01, 2.03), and in participating in clubs/activities in Model 1 (OR = 1.86, 95% CI 1.14, 3.05); these associations were not significant in subsequent models (Supplementary Table 2). Compared to intentional napping, unintentional napping was associated with a greater odds of any activity restriction in Model 1 (OR = 1.35, 95% CI 1.02, 1.80), but not in subsequent models. Napping Frequency and Restricted Participation Compared to non-nappers, infrequent napping was not associated with restrictions in any individual activities; however, frequent nappers had greater odds of restrictions in each individual activity and any valued activity in Models 1 through 3 (Table 3). In Model 4, which further adjusted for EDS, these associations held for restrictions in visiting with friends/family (OR = 1.83, 95% CI 1.17, 2.84) and any valued activity (OR = 1.66, 95% CI 1.27, 2.18), but not for attending religious services, club/activities participation, or going out for enjoyment. Table 3. Associations of Napping Frequency With Health/Functioning-Related Restrictions in Valued Activity Participation Napping Frequency  Model 1a OR (95% CI)  Model 2b OR (95% CI)  Model 3c OR (95% CI)  Model 4d OR (95% CI)    Restricted in Visiting with Friends/Family  Non-nappers  1.00  1.00  1.00  1.00  Infrequent  1.16 (0.74, 1.82)  0.94 (0.57, 1.56)  0.89 (0.52, 1.52)  0.91 (0.56, 1.47)  Frequent  2.70 (1.88, 3.86)**  2.07 (1.44, 2.97)**  1.80 (1.19, 2.71)**  1.83 (1.17, 2.84)**    Restricted in Attending Religious Services  Non-nappers  1.00  1.00  1.00  1.00  Infrequent  1.23 (0.91, 1.65)  1.02 (0.74, 1.41)  0.97 (0.67, 1.41)  0.82 (0.55, 1.21)  Frequent  2.17 (1.55, 3.03)**  1.71 (1.23, 2.37)**  1.59 (1.14, 2.23)**  1.34 (0.95, 1.88)    Restricted in Participating in Clubs/Activities  Non-nappers  1.00  1.00  1.00  1.00  Infrequent  1.21 (0.80, 1.83)  0.98 (0.63, 1.54)  0.93 (0.58, 1.47)  0.78 (0.48, 1.27)  Frequent  2.46 (1.57, 3.85)**  2.01 (1.25, 3.24)**  1.86 (1.14, 3.03)*  1.54 (0.88, 2.69)    Restricted in Going Out for Enjoyment  Non-nappers  1.00  1.00  1.00  1.00  Infrequent  1.07 (0.70, 1.62)  0.93 (0.60, 1.43)  0.85 (0.54, 1.35)  0.79 (0.52, 1.20)  Frequent  2.38 (1.64, 3.46)**  2.00 (1.36, 2.94)**  1.82 (1.21, 2.73)**  1.54 (0.99, 2.37)    Restricted in Any Valued Activity  Non-nappers  1.00  1.00  1.00  1.00  Infrequent  1.33 (1.07, 1.65)*  1.13 (0.87, 1.47)  1.10 (0.81, 1.48)  0.99 (0.73, 1.35)  Frequent  2.56 (2.03, 3.22)**  2.11 (1.66, 2.67)**  1.88 (1.43, 2.47)**  1.66 (1.27, 2.18)**  Napping Frequency  Model 1a OR (95% CI)  Model 2b OR (95% CI)  Model 3c OR (95% CI)  Model 4d OR (95% CI)    Restricted in Visiting with Friends/Family  Non-nappers  1.00  1.00  1.00  1.00  Infrequent  1.16 (0.74, 1.82)  0.94 (0.57, 1.56)  0.89 (0.52, 1.52)  0.91 (0.56, 1.47)  Frequent  2.70 (1.88, 3.86)**  2.07 (1.44, 2.97)**  1.80 (1.19, 2.71)**  1.83 (1.17, 2.84)**    Restricted in Attending Religious Services  Non-nappers  1.00  1.00  1.00  1.00  Infrequent  1.23 (0.91, 1.65)  1.02 (0.74, 1.41)  0.97 (0.67, 1.41)  0.82 (0.55, 1.21)  Frequent  2.17 (1.55, 3.03)**  1.71 (1.23, 2.37)**  1.59 (1.14, 2.23)**  1.34 (0.95, 1.88)    Restricted in Participating in Clubs/Activities  Non-nappers  1.00  1.00  1.00  1.00  Infrequent  1.21 (0.80, 1.83)  0.98 (0.63, 1.54)  0.93 (0.58, 1.47)  0.78 (0.48, 1.27)  Frequent  2.46 (1.57, 3.85)**  2.01 (1.25, 3.24)**  1.86 (1.14, 3.03)*  1.54 (0.88, 2.69)    Restricted in Going Out for Enjoyment  Non-nappers  1.00  1.00  1.00  1.00  Infrequent  1.07 (0.70, 1.62)  0.93 (0.60, 1.43)  0.85 (0.54, 1.35)  0.79 (0.52, 1.20)  Frequent  2.38 (1.64, 3.46)**  2.00 (1.36, 2.94)**  1.82 (1.21, 2.73)**  1.54 (0.99, 2.37)    Restricted in Any Valued Activity  Non-nappers  1.00  1.00  1.00  1.00  Infrequent  1.33 (1.07, 1.65)*  1.13 (0.87, 1.47)  1.10 (0.81, 1.48)  0.99 (0.73, 1.35)  Frequent  2.56 (2.03, 3.22)**  2.11 (1.66, 2.67)**  1.88 (1.43, 2.47)**  1.66 (1.27, 2.18)**  Note: See Supplementary Table 1 for sample sizes. CI = Confidence interval; OR = Odds ratio. aModel 1 adjusted for age, race, gender, education category. bModel 2 adjusted for Model 1 covariates + number of medical conditions, BMI category. cModel 3 adjusted for Model 2 covariates + GAD-2, PHQ-2, nighttime sleep duration. dModel 4 adjusted for Model 3 covariates + EDS. *p value < .05; **p value < .01. View Large Compared to infrequent nappers, frequent nappers had greater odds of restrictions in each valued activity and any valued activity in Models 1, 2, and 3 (Supplementary Table 3). In Model 4, frequent napping was still associated with restrictions in visiting with friends/family (OR=2.02, 95% CI 1.16, 3.51), attending religious services (OR=1.64, 95% CI 1.11, 2.40), clubs/activities participation (OR=1.97, 95% CI 1.23, 3.14), going out for enjoyment (OR=1.94, 95% CI 1.19, 3.17), and in any valued activity (OR=1.68, 95% CI 1.30, 2.16). Nap Duration and Restricted Participation In Models 1 through 3, except for clubs/activities participation, longer nap duration was associated with restrictions in all valued activities and any activity (Table 4). Nap duration was associated with restrictions in clubs/activities in Model 1 and 2 (Model 2: OR = 1.23, 95% CI 1.03, 1.46), but not in Model 3 or 4. In Model 4, longer nap duration was associated with a greater odds of restrictions in visiting with friends/family (OR = 1.27, 95% CI 1.06, 1.52), attending religious services (OR = 1.18, 95% CI 1.02, 1.37), going out for enjoyment (OR = 1.23, 95% CI 1.06, 1.41), and any activity (OR = 1.25, 95% CI 1.10, 1.43). Table 4. Associations of Nap Duration With Health/Functioning-Related Restrictions in Valued Activity Participation   Model 1a OR (95% CI)  Model 2b OR (95% CI)  Model 3c OR (95% CI)  Model 4d OR (95% CI)    Restricted in Visiting with Friends/Family  Per 30 min  1.39 (1.23, 1.58)**  1.37 (1.19, 1.58)**  1.26 (1.06, 1.50)*  1.27 (1.06, 1.52)*    Restricted in Attending Religious Services  Per 30 min  1.30 (1.13, 1.50)**  1.27 (1.10, 1.47)**  1.18 (1.01, 1.38)*  1.18 (1.02, 1.37)*    Restricted in Participating in Clubs/Activities  Per 30 min  1.23 (1.05, 1.45)**  1.23 (1.03, 1.46)*  1.18 (0.97, 1.45)  1.19 (0.97, 1.45)    Restricted in Going Out for Enjoyment  Per 30 min  1.32 (1.18, 1.49)**  1.30 (1.15, 1.48)**  1.23 (1.07, 1.41)**  1.23 (1.06, 1.41)**    Restricted in Any Valued Activity  Per 30 min  1.35(1.21, 1.51)**  1.31 (1.16, 1.49)**  1.26 (1.10, 1.44)**  1.25 (1.10, 1.43)**    Model 1a OR (95% CI)  Model 2b OR (95% CI)  Model 3c OR (95% CI)  Model 4d OR (95% CI)    Restricted in Visiting with Friends/Family  Per 30 min  1.39 (1.23, 1.58)**  1.37 (1.19, 1.58)**  1.26 (1.06, 1.50)*  1.27 (1.06, 1.52)*    Restricted in Attending Religious Services  Per 30 min  1.30 (1.13, 1.50)**  1.27 (1.10, 1.47)**  1.18 (1.01, 1.38)*  1.18 (1.02, 1.37)*    Restricted in Participating in Clubs/Activities  Per 30 min  1.23 (1.05, 1.45)**  1.23 (1.03, 1.46)*  1.18 (0.97, 1.45)  1.19 (0.97, 1.45)    Restricted in Going Out for Enjoyment  Per 30 min  1.32 (1.18, 1.49)**  1.30 (1.15, 1.48)**  1.23 (1.07, 1.41)**  1.23 (1.06, 1.41)**    Restricted in Any Valued Activity  Per 30 min  1.35(1.21, 1.51)**  1.31 (1.16, 1.49)**  1.26 (1.10, 1.44)**  1.25 (1.10, 1.43)**  Note: See Supplementary Table 1 for sample sizes. Analyses excluded non-nappers. CI = Confidence interval; OR = Odds ratio. aModel 1 adjusted for age, race, gender, education category. bModel 2 adjusted for Model 1 covariates + number of medical conditions, BMI category. cModel 3 adjusted for Model 2 covariates + GAD-2, PHQ-2, nighttime sleep duration. dModel 4 adjusted for Model 3 covariates + EDS. *p value < .05; **p value < .01. View Large EDS By Napping Interactions In exploratory analyses, using Model 4, there was a near-significant interaction term for Napping frequency × Sleepiness for restrictions in visiting with friends/family (p = .08) and a significant Nap duration × Sleepiness interaction term for going out for enjoyment (p < .01). Among those reporting sleepiness rarely/never, compared to infrequent nappers, frequent nappers had a greater odds of restrictions in visiting with friends/family (Supplementary Figure 1a). This association was not significant among those reporting sleepiness some or most days/every day. Longer nap duration was associated with a greater odds of going out for enjoyment restrictions among those reporting sleepiness rarely/never and some days, but not most days/every day (Supplementary Figure 1b). Discussion We evaluated associations between napping characteristics and restricted participation in valued activities in a nationally representative sample of community-dwelling older adults. After adjustment for all covariates, religious service attendance was the only individual activity associated with napping intentionality, with unintentional nappers having a greater odds of restricted religious service attendance than non-nappers. However, compared to non-nappers, both intentional and unintentional nappers had a greater odds of restricted participation in any valued activity after adjustment for demographics, physical and mental health characteristics, and nighttime sleep duration. Similarly, frequent napping (vs non-napping) was associated with a greater odds of restrictions in visiting with friends/family and in any valued activity after accounting for these covariates and EDS. In models limited to nappers, after adjustment for all covariates and EDS, frequent napping was associated with restrictions in each individual activity and any valued activity, while longer nap duration was associated with restrictions in visiting with friends/family, attending religious services, going out for enjoyment, and any valued activity. Together, our results suggest that intentional and unintentional, more frequent, and longer-duration naps are associated with a greater odds of restricted valued-activity participation. Few studies have investigated links between napping and daytime function in community-dwelling older adults. Our findings of associations between napping and health- or functioning-related restrictions in valued activities in a nationally representative community-dwelling sample are consistent with associations reported between daytime sleep and reduced social participation among nursing home residents (21,22). Our results are also in line with studies that have demonstrated associations of napping with difficulties in activities of daily living (23) and instrumental activities of daily living (24) among community-dwelling older adults. On the other hand, some studies have tied napping to better cognitive functioning (9,10). Our study extends prior research, which has primarily characterized napping in terms of duration or frequency by examining napping intentionality. Future studies that consider distinct napping characteristics (eg, intentionality, frequency) may help resolve discrepant findings in this area. There are various plausible explanations for the associations we observed. For example, disturbed nighttime sleep may drive the association between napping and poor health outcomes (25). While our significant findings remained after adjustment for nighttime sleep duration, further research is needed in examining the role of nighttime sleep as a driver of napping-related social participation and other behaviors that improve quality of life. On the other hand, napping may also be a manifestation of EDS, which could lead to restrictions in valued activities, independently of napping. Indeed, other studies in older adults have investigated napping as a marker of EDS. One study found associations between EDS, measured by napping frequency, and greater odds of deficits in activities of daily living (23). In another, 87.5% of EDS cases reported napping, and EDS was associated with reduced social activities (26). In the present study, however, we adjusted for EDS and observed independent associations with restricted participation. Also, after adjustment for covariates, we found no statistically significant differences between intentional napping (which may not reflect EDS) versus unintentional napping (which likely results from EDS (27)) and activity restrictions. Thus, our findings are probably not attributable to EDS alone, and napping, itself, may be a marker of underlying conditions that increase risk for restricted activity participation in older adults. Another possibility is that napping is causally linked to health or functioning-related activity participation. In terms of a mechanism, time spent napping is time not spent engaged in other behaviors that might improve health or functioning, such as physical activity or social engagement. Thus, napping may be a modifiable risk factor for activity restriction simply because it is incompatible with other activities. However, we cannot determine this based on the results of these cross-sectional analyses. We also found that EDS modified some associations. Frequent napping was independently associated with restrictions in visiting friends/family among those reporting the least sleepiness, and nap duration was associated with restrictions in going out for enjoyment, but not among those with the most sleepiness. The reasons for these results are unclear and warrant future research. Fatigue, however, is a factor that may play a role in napping (28). Studies are needed to investigate whether fatigue may drive napping-related daytime dysfunction. Strengths of this study include a large, nationally representative sample of U.S. older adults and the investigation of distinct napping characteristics. However, this study has limitations. First, we were unable to distinguish between daytime and evening napping; nap timing may affect activity participation (29). Additionally, napping was measured by self-report, rather than an objective measure (eg, actigraphy), and did not include assessment of day-to-day variability in napping characteristics. Prior studies have found sleep estimates derived from objective and subjective measures conflict among older adults (29). Investigations using self-report and objective measures of napping and studying whether associations differ by mode of assessment are needed. Further, this study used a cross-sectional observational design, which does not allow us to probe for potential causal links by examining temporal associations. Longitudinal studies are needed in this domain to examine temporal associations that may suggest causal links. Because we are unable to conclude that the association is causal, we cannot recommend against napping based on our results. Nonetheless, clinicians should note that unintentional napping may be a marker of a sleep disorder or over-sedation. Patients reporting unintentional napping should be evaluated to identify underlying causes, including a sleep study to rule out a sleep disorder (30), such as sleep-disordered breathing. In conclusion, we found that unintentional, intentional, frequent, and longer-duration naps are associated with decrements in daytime social functioning and activity participation among older adults. If napping does detract from adaptive participation in valued activities, this would suggest that decreasing napping may promote these healthy behaviors. However, prior to the creation of randomized trials to investigate this possibility, longitudinal studies are needed. Supplementary Material Supplementary data is available at The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences online. Funding This work was supported in part by grants from the National Institute on Aging (U01-AG032947, R01AG050507, R01AG050507-02S1, and T32-AG027668) and the National Institute of Mental Health (T32-MH019934). Conflict of Interest Adam Spira agreed to serve as a consultant to Awarables, Inc. in support of an NIH grant. Acknowledgments The authors thank Ramin Mojtabai, MD, PhD, MPH, for his feedback regarding data analysis, and Maureen Skehan, MSPH, for her assistance with the NHATS data. References 1. Ohayon MM, Vecchierini MF. Daytime sleepiness and cognitive impairment in the elderly population. Arch Intern Med . 2002; 162: 201– 208. doi:10.1001/archinte.162.2.201 Google Scholar CrossRef Search ADS PubMed  2. Ohayon MM, Zulley J. Prevalence of naps in the general population. Sleep Hypn . 1999; 1: 88– 97. 3. Foley DJ, Vitiello MV, Bliwise DL, Ancoli-Israel S, Monjan AA, Walsh JK. Frequent napping is associated with excessive daytime sleepiness, depression, pain, and nocturia in older adults: findings from the National Sleep Foundation ‘2003 Sleep in America’ Poll. Am J Geriatr Psychiatry . 2007; 15: 344– 350. doi: 10.1097/01.JGP.0000249385.50101.67 Google Scholar CrossRef Search ADS PubMed  4. Vitiello MV. We have much more to learn about the relationships between napping and health in older adults. J Am Geriatr Soc . 2008; 56: 1753– 1755. doi: 10.1111/j.1532-5415.2008.01837.x Google Scholar CrossRef Search ADS PubMed  5. Zhong G, Wang Y, Tao T, Ying J, Zhao Y. Daytime napping and mortality from all causes, cardiovascular disease, and cancer: a meta-analysis of prospective cohort studies. Sleep Med . 2015; 16: 811– 819. doi: 10.1016/j.sleep.2015.01.025 Google Scholar CrossRef Search ADS PubMed  6. Fang W, Li Z, Wu Let al.   Longer habitual afternoon napping is associated with a higher risk for impaired fasting plasma glucose and diabetes mellitus in older adults: results from the Dongfeng-Tongji cohort of retired workers. Sleep Med . 2013; 14: 950– 954. doi: 10.1016/j.sleep.2013.04.015 Google Scholar CrossRef Search ADS PubMed  7. Cao Z, Shen L, Wu Jet al.   The effects of midday nap duration on the risk of hypertension in a middle-aged and older Chinese population: a preliminary evidence from the Tongji-Dongfeng Cohort Study, China. J Hypertens . 2014; 32: 1993– 8; discussion 1998. doi: 10.1097/HJH.0000000000000291 Google Scholar CrossRef Search ADS PubMed  8. Cross N, Terpening Z, Rogers NLet al.   Napping in older people ‘at risk’ of dementia: relationships with depression, cognition, medical burden and sleep quality. J Sleep Res . 2015; 24: 494– 502. doi: 10.1111/jsr.12313 Google Scholar CrossRef Search ADS PubMed  9. Campbell SS, Murphy PJ, Stauble TN. Effects of a nap on nighttime sleep and waking function in older subjects. J Am Geriatr Soc . 2005; 53: 48– 53. doi: 10.1111/j.1532-5415.2005.53009.x Google Scholar CrossRef Search ADS PubMed  10. Tamaki M, Shirota A, Tanaka H, Hayashi M, Hori T. Effects of a daytime nap in the aged. Psychiatry Clin Neurosci . 1999; 53: 273– 275. doi: 10.1046/j.1440-1819.1999.00548.x Google Scholar CrossRef Search ADS PubMed  11. Glass TA, de Leon CM, Marottoli RA, Berkman LF. Population based study of social and productive activities as predictors of survival among elderly Americans. BMJ . 1999; 319: 478– 483. doi:10.1136/bmj.319.7208.478 Google Scholar CrossRef Search ADS PubMed  12. Isaac V, Stewart R, Artero S, Ancelin ML, Ritchie K. Social activity and improvement in depressive symptoms in older people: a prospective community cohort study. Am J Geriatr Psychiatry . 2009; 17: 688– 696. doi: 10.1097/JGP.0b013e3181a88441 Google Scholar CrossRef Search ADS PubMed  13. Kotwal AA, Kim J, Waite L, Dale W. Social function and cognitive status: results from a US nationally representative survey of older adults. J Gen Intern Med . 2016; 31: 854– 862. doi: 10.1007/s11606-016-3696-0 Google Scholar CrossRef Search ADS PubMed  14. Agahi N, Parker MG. Leisure activities and mortality: does gender matter? J Aging Health . 2008; 20: 855– 871. doi: 10.1177/0898264308324631 Google Scholar CrossRef Search ADS PubMed  15. Hsu HC. Does social participation by the elderly reduce mortality and cognitive impairment? Aging Ment Health . 2007; 11: 699– 707. doi: 10.1080/13607860701366335 Google Scholar CrossRef Search ADS PubMed  16. Spira AP, Kaufmann CN, Kasper JDet al.   Association between insomnia symptoms and functional status in U.S. older adults. J Gerontol B Psychol Sci Soc Sci . 2014; 69( suppl 1): S35– S41. doi: 10.1093/geronb/gbu116 Google Scholar CrossRef Search ADS PubMed  17. Chen JH, Lauderdale DS, Waite LJ. Social participation and older adults’ sleep. Soc Sci Med . 2016; 149: 164– 173. doi: 10.1016/j.socscimed.2015.11.045 Google Scholar CrossRef Search ADS PubMed  18. Kasper J, Freedman V. National Health and Aging Trends Study User Guide: Rounds 1, 2, 3& 4 Final Release . Baltimore: Johns Hopkins University School of Public Health; 2015. 19. World Health Organization. Global database on Body Mass Index: BMI Classification . 2006. 2015. 20. Kroenke K, Spitzer RL, Williams JB, Löwe B. An ultra-brief screening scale for anxiety and depression: the PHQ-4. Psychosomatics . 2009; 50: 613– 621. doi: 10.1176/appi.psy.50.6.613 Google Scholar PubMed  21. Martin JL, Webber AP, Alam T, Harker JO, Josephson KR, Alessi CA. Daytime sleeping, sleep disturbance, and circadian rhythms in the nursing home. Am J Geriatr Psychiatry . 2006; 14: 121– 129. doi: 10.1097/01.JGP.0000192483.35555.a3 Google Scholar CrossRef Search ADS PubMed  22. Li J, Chang YP, Porock D. Factors associated with daytime sleep in nursing home residents. Res Aging . 2015; 37: 103– 117. doi: 10.1177/0164027514537081 Google Scholar CrossRef Search ADS PubMed  23. Hays JC, Blazer DG, Foley DJ. Risk of napping: excessive daytime sleepiness and mortality in an older community population. J Am Geriatr Soc . 1996; 44: 693– 698. doi:10.1111/j.1532-5415.1996.tb01834.x Google Scholar CrossRef Search ADS PubMed  24. Goldman SE, Stone KL, Ancoli-Israel Set al.   Poor sleep is associated with poorer physical performance and greater functional limitations in older women. Sleep . 2007; 30: 1317– 1324. doi: 10.1093/sleep/30.10.1317 Google Scholar CrossRef Search ADS PubMed  25. Cohen-Mansfield J, Perach R. Sleep duration, nap habits, and mortality in older persons. Sleep . 2012; 35: 1003– 1009. doi: 10.5665/sleep.1970 Google Scholar PubMed  26. Gooneratne NS, Weaver TE, Cater JRet al.   Functional outcomes of excessive daytime sleepiness in older adults. J Am Geriatr Soc . 2003; 51: 642– 649. doi:10.1034/j.1600-0579.2003.00208.x Google Scholar CrossRef Search ADS PubMed  27. Martin JL, Ancoli-Israel S. Napping in older adults. Sleep Med Clin . 2006; 1: 177– 86. doi:10.1016/j.jsmc.2006.04.011 Google Scholar CrossRef Search ADS   28. Picarsic JL, Glynn NW, Taylor CAet al.   Self-reported napping and duration and quality of sleep in the lifestyle interventions and independence for elders pilot study. J Am Geriatr Soc . 2008; 56: 1674– 1680. doi: 10.1111/j.1532-5415.2008.01838.x Google Scholar CrossRef Search ADS PubMed  29. Dautovich ND, McCrae CS, Rowe M. Subjective and objective napping and sleep in older adults: are evening naps “bad” for nighttime sleep? J Am Geriatr Soc . 2008; 56: 1681– 1686. doi: 10.1111/j.1532-5415.2008. 01822.x Google Scholar CrossRef Search ADS PubMed  30. Neikrug AB, Ancoli-Israel S. Sleep disorders in the older adult - a mini-review. Gerontology . 2010; 56: 181– 189. doi: 10.1159/000236900 Google Scholar CrossRef Search ADS PubMed  © The Author(s) 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. 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Abstract

Abstract Background Napping is associated with both positive and negative health outcomes among older adults. However, the association between particular napping characteristics (eg, frequency, duration, and whether naps were intentional) and daytime function is unclear. Methods Participants were 2,739 community-dwelling Medicare beneficiaries aged ≥65 years from the nationally representative National Health and Aging Trends Study. Participants reported napping frequency, duration, and whether naps were intentional versus unintentional. Restricted participation in valued activities was measured by self-report. Results After adjusting for potential confounders and nighttime sleep duration, those who took intentional and unintentional naps had a greater odds of any valued activity restriction (ie, ≥1 valued activity restriction), compared to those who rarely/never napped (unintentional odds ratio [OR] = 1.34, 95% confidence interval [CI] 1.01, 1.79, intentional OR = 1.49, 95% CI 1.09, 2.04). There was no difference between unintentional napping and intentional napping with respect to any valued activity restriction after adjustment for demographics. Compared to participants napping “some days,” those napping most days/every day had a greater odds of any valued activity restriction (OR = 1.68, 95% CI 1.30, 2.16). Moreover, each 30-minute increase in average nap duration was associated with a 25% greater odds of any valued activity restriction (OR = 1.25, 95% CI 1.10, 1.43). Conclusion Older adults who took more frequent or longer naps were more likely to report activity restrictions, as were those who took intentional or unintentional naps. Additional longitudinal studies with objective measures of sleep are needed to further our understanding of associations between napping characteristics and daytime dysfunction. Sleep, Social participation, Health status, Function Napping is common among older adults and increases in frequency with age (1–3). Between 18% and 49% of older adults nap regularly (2,3), but it is unclear whether napping is harmful or beneficial for this population (4). Among older adults, studies have found associations between napping and poor outcomes such as all-cause mortality (5), diabetes (6), hypertension (7), and cognitive impairment (1,8). Conversely, short-term, laboratory-based experiments have found napping improves cognitive performance (9), and reduces blood pressure in older adults (10). Little is known, however, about the extent to which napping is linked to participation in activities that maximize healthy outcomes in older adults. Participation in social activities is correlated with increased longevity and wellbeing among older adults (11), and fewer depressive symptoms (12). In contrast, lower social activity levels are associated with poorer cognitive health (13), and greater mortality risk (14). The association between social activity and health outcomes may also differ by the type of activity. For instance, a study found that participation in religious groups was associated with reduced mortality risk in older women, but other social activities (eg, volunteering) were not (15). Some studies have demonstrated associations between sleep and social activities. Older adults in the National Health and Aging Trends Study (NHATS) who reported insomnia symptoms had a greater odds of restrictions in valued social activities compared to those reporting no insomnia symptoms (16). Another study found that older adults who participated more often in collective social activities (eg, religious services) had less fragmented sleep, measured by actigraphy (17). However, to our knowledge, there are no studies examining the association between napping and participation in valued social activities in community-dwelling older adults. Napping does not occur uniformly, and individual napping characteristics such as duration and frequency may be modifiable parameters that improve participation in social activities and health outcomes. Alternatively, naps may be markers of conditions that increase older adults’ risk for daytime dysfunction. Studies of the association of specific napping parameters with important outcomes among older adults would enhance understanding of the potential effects of napping on health (4). Thus, we investigated the association of intentional versus unintentional napping, and frequency and duration of napping, with restrictions in valued activities in community-dwelling older adults. Methods Participants We studied participants from the 2013 and 2014 rounds of the NHATS, a nationally representative study of Medicare beneficiaries aged ≥65 years (18). In each of these rounds, a sleep-focused assessment was added to the interviews of a randomly selected subset of participants. After combining cross-sectional data from the two rounds, there were 2,908 participants with napping data. We excluded participants who were not community-dwelling (eg, in nursing homes; n = 56) or reported all activities assessed as “not so important” (n = 113). Our final sample contained 2,739 participants (Round 3 = 1,530; Round 4 = 1,209). A proxy respondent familiar with a participant’s care and health provided predictor and outcome variable data for 164 participants who were unable to respond due to illness, disability, or a language barrier. In sensitivity analyses excluding proxy respondents, overall patterns of findings remained, though associations decreased in magnitude and some results became nonsignificant. Because this was likely due to a loss of power, we included proxy respondents in our final analyses. Measures Napping frequency Participants were asked, “…how often did you take naps during the day?” and were categorized as: non-nappers (“never” or “rarely”; n = 1,219); infrequent nappers (“some days”; n = 758); or frequent nappers (“most days” or “every day”; n = 762). Napping duration and intention Participants who reported napping more frequently than “never” were asked, “On average, how long were these naps?”, and we created an average nap duration variable (in minutes). Participants who reported napping “rarely” were excluded from our analyses of average nap duration. These participants were also asked, “In general, were these naps planned, or did you fall asleep without meaning to?”, with response options “naps planned”; “fell asleep without meaning to” or “both (some planned/some not)”. We classified those reporting falling asleep without meaning to or “both” as unintentional nappers (n = 920) and others as intentional nappers (n = 600). Participants who reported napping “rarely” were also asked about napping intention but were classified as non-nappers. Excessive daytime sleepiness (EDS) Participants were asked about past-month EDS: “…how often did you have trouble staying awake at times during the day when you wanted to be awake?”, with response options “never”; “rarely”; “some days”; “most days”; “every day”. We reclassified these responses as “rarely/never”; “some days”; and “most days/every day”. Nighttime sleep duration Participants were also asked about past-month nighttime sleep duration: “…how many hours of actual sleep did you usually get at night?” Participants reported sleep duration in hours. We did not analyze nighttime sleep duration data for participants who reported “no usual hours or different from night to night” (n = 56). Participation in valued activities Participants were asked whether they considered each of the following activities “very”, “somewhat”, or “not so” important: “visit in person with friends or family not living with you”; “attend religious services”; “participate in clubs, classes, or other organized activities” (excluding religious services); and “go out for enjoyment” (eg, going to a movie or dinner). Activities rated as “very” or “somewhat” important were considered “valued.” A participant’s data were only included for a given activity if it was rated as valued. Participants were also asked whether “health or functioning” kept them from performing each activity in the last month. Those responding “yes” were coded as having a restriction for that activity. Other measures Participants reported demographic and health characteristics. Age was categorized as 65–69 years; 70–74 years; 75–79 years; 80–84 years; 85–89 years; and 90+ years. We categorized race/ethnicity as White, non-Hispanic; Black, non-Hispanic; Hispanic; and Other (Asian, American Indian, Native Hawaiian, Pacific Islander, more than one race/ethnicity). We recoded education as less than high school, high school graduate, or more than high school and used self-reported height and weight to calculate body mass index (BMI; kg/m2; recoded as <18.5 kg/m2 [underweight], 18.5–24.9 kg/m2 [normal weight], 25–29.9 kg/m2 [overweight] or ≥30 kg/m2 [obese]) (19). Participants completed the Patient Health Questionnaire (PHQ)-2 to measure depressive symptoms and the Generalized Anxiety Disorder (GAD)-2 for anxiety symptoms (20). Both are 2-item measures, with responses from 0 to 3 per item. We summed items to obtain a total (0–6) for each measure. Participants also reported whether they had: history of a heart attack; heart disease; high blood pressure; arthritis; osteoporosis; diabetes; stroke; dementia or Alzheimer’s disease; and cancer. We created a categorical variable for number of medical conditions: 0 or 1 (27.0%), 2 (28.1%), 3 (22.9%), and 4 or more (22.0%). Statistical Analyses We computed descriptive statistics for participant characteristics, and compared intentional, unintentional, or non-nappers using chi-square tests for categorical and simple linear regression for continuous variables. Next, we performed logistic regression analyses with napping intention (ie, intentional, unintentional, or non-napping [reference]) as the primary predictor and health or functioning-related restrictions in each valued activity or in any valued activity (ie, ≥1 valued activity) as the outcome. We fit three sets of models adjusting for different covariates: Model 1 demographics (age, race, gender, education); Model 2: Model 1 covariates + physical health (number of medical conditions, BMI category); and Model 3: Model 2 covariates + mental health (GAD-2, PHQ-2 scores) and nighttime sleep duration. For models with napping duration or frequency as the primary predictors, we fit a Model 4: Model 3 covariates + EDS. We performed linear combination postestimation analyses to obtain pairwise comparisons (unintentional vs intentional napping [reference]; frequent vs infrequent napping [reference]). We explored interactions of napping characteristics with EDS, adding interaction terms for Sleepiness × Napping frequency, and for Sleepiness × Average nap duration, to Model 4. An α less than 0.05 indicated statistical significance. When interaction terms were significant or near significant (p < .10), we reported stratified results. Survey weights were applied to render results nationally representative and account for stratification and clustering in the study design. Analyses were performed using Stata version 14.0 (Statacorp, College Station, TX). Results Participant Characteristics Participants’ demographic and health characteristics are presented by napping type in Table 1. Overall, 47.4% of participants were non-nappers, 23.3% reported intentional naps only, and 29.3% reported unintentional naps. Napping type was significantly associated with age, gender, race, education, BMI, PHQ-2 and GAD-2 scores, number of medical conditions, EDS, and nighttime sleep duration (all p’s < .01). Among participants who napped more than rarely, napping intention was significantly associated with napping frequency (p < .02), but not with average nap duration (p = .48). Table 1. Participant Characteristics (weighted row %s)   Total Samplea  Non-Nappers  Intentional Naps  Unintentional Naps    Unweighted N  100% (N = 2,739)  47.4% (n = 1,219)  23.3% (n = 600)  29.3% (n = 920)  p Value  Age          <.001   65–69  11.9  49.3  25.7  25.0     70–74  31.8  53.2  23.7  23.1     75–59  23.0  49.8  21.44  28.8     80–84  17.5  41.7  22.7  35.6     85–89  10.1  38.6  24.0  37.4     90+  5.70  34.6  23.9  41.5    Gender          <.001   Male  41.5  39.3  27.3  33.4     Female  58.5  53.2  20.5  26.3    Race          <.001   White, Non-Hispanic  82.5  48.5  24.7  26.8     Black, Non-Hispanic  7.70  42.4  12.4  45.2     Hispanic  6.10  46.6  18.5  34.9     Other  3.70  39.2  17.6  43.2    Education Level          <.001   <High School  18.5  43.2  18.6  38.2     High School Graduate  25.9  47.5  19.3  33.2     >High School  55.6  49.1  26.4  24.5    BMI (in kg/m2)          <.01   <18.5  1.80  51.2  23.2  25.6     18.5–24.9  31.7  51.3  21.8  26.9     25–29.9  38.3  51.9  21.7  26.4     ≥30.0  28.2  36.3  27.8  35.9    PHQ-2, mean ± SE  0.87 ± 0.03  0.71 ± 0.04  0.83 ± 0.05  1.16 ± 0.05  <.01  GAD-2, mean ± SE  0.81 ± 0.03  0.74 ± 0.04  0.75 ± 0.05  0.96 ± 0.05  <.01  # of Medical Conditions          <.01   0 or 1  27.0  54.8  24.1  21.1   2  28.1  48.9  24.3  26.8   3  22.9  45.6  21.1  33.3   4+  22.0  37.9  23.7  38.4  EDS          <.01   Never/Rarely  64.5  59.9  23.0  17.1   Some Days  24.7  27.1  24.3  48.6   Most Days/Every Day  10.8  20.4  22.6  57.0  Nighttime Sleep Duration (hours), mean ± SE  7.03 ± 0.04  7.01 ± 0.05  7.22 ± 0.07  6.91 ± 0.06  <.01  Nap Frequencyb          <.02   Infrequent  52.7  N/A  41.0  59.0   Frequent  47.3  N/A  47.9  52.1  Average Nap Durationb (minutes), mean ± SE  55.4 ± 1.40  N/A  56.6 ± 1.71  54.4 ± 2.29  .48    Total Samplea  Non-Nappers  Intentional Naps  Unintentional Naps    Unweighted N  100% (N = 2,739)  47.4% (n = 1,219)  23.3% (n = 600)  29.3% (n = 920)  p Value  Age          <.001   65–69  11.9  49.3  25.7  25.0     70–74  31.8  53.2  23.7  23.1     75–59  23.0  49.8  21.44  28.8     80–84  17.5  41.7  22.7  35.6     85–89  10.1  38.6  24.0  37.4     90+  5.70  34.6  23.9  41.5    Gender          <.001   Male  41.5  39.3  27.3  33.4     Female  58.5  53.2  20.5  26.3    Race          <.001   White, Non-Hispanic  82.5  48.5  24.7  26.8     Black, Non-Hispanic  7.70  42.4  12.4  45.2     Hispanic  6.10  46.6  18.5  34.9     Other  3.70  39.2  17.6  43.2    Education Level          <.001   <High School  18.5  43.2  18.6  38.2     High School Graduate  25.9  47.5  19.3  33.2     >High School  55.6  49.1  26.4  24.5    BMI (in kg/m2)          <.01   <18.5  1.80  51.2  23.2  25.6     18.5–24.9  31.7  51.3  21.8  26.9     25–29.9  38.3  51.9  21.7  26.4     ≥30.0  28.2  36.3  27.8  35.9    PHQ-2, mean ± SE  0.87 ± 0.03  0.71 ± 0.04  0.83 ± 0.05  1.16 ± 0.05  <.01  GAD-2, mean ± SE  0.81 ± 0.03  0.74 ± 0.04  0.75 ± 0.05  0.96 ± 0.05  <.01  # of Medical Conditions          <.01   0 or 1  27.0  54.8  24.1  21.1   2  28.1  48.9  24.3  26.8   3  22.9  45.6  21.1  33.3   4+  22.0  37.9  23.7  38.4  EDS          <.01   Never/Rarely  64.5  59.9  23.0  17.1   Some Days  24.7  27.1  24.3  48.6   Most Days/Every Day  10.8  20.4  22.6  57.0  Nighttime Sleep Duration (hours), mean ± SE  7.03 ± 0.04  7.01 ± 0.05  7.22 ± 0.07  6.91 ± 0.06  <.01  Nap Frequencyb          <.02   Infrequent  52.7  N/A  41.0  59.0   Frequent  47.3  N/A  47.9  52.1  Average Nap Durationb (minutes), mean ± SE  55.4 ± 1.40  N/A  56.6 ± 1.71  54.4 ± 2.29  .48  Note: BMI = Body mass index; EDS = Excessive daytime sleepiness; GAD-2 = Generalized Anxiety Disorder-2; PHQ-2 = Patient Health Questionnaire-2. aColumn %. bExcluded non-nappers. View Large Napping Intentionality and Restricted Participation In Model 1, compared to non-nappers, participants reporting intentional and unintentional napping had a higher odds of restrictions in visiting with friends/family (intentional odds ratio [OR] = 1.62, 95% confidence interval [CI] 1.06, 2.48; unintentional OR = 1.99, 95% CI 1.41, 2.82), and unintentional nappers had a greater odds of restrictions in going out for enjoyment (OR = 1.80, 95% CI 1.21, 2.67) (Table 2). However, these associations were not significant in subsequent models. In Models 1 and 2, compared to non-nappers, unintentional nappers had a greater odds of restrictions in participating in clubs/activities (Model 2: OR = 1.69, 95% CI 1.05, 2.71), but not in Model 3. In all three Models, unintentional nappers had a greater odds of restricted religious service attendance than non-nappers (Model 3: OR = 1.42, 95% CI 1.03, 1.96). Compared to non-nappers, those who reported intentional or unintentional naps had a greater odds of any activity restriction in all Models (Model 3: intentional napping OR = 1.34, 95% CI 1.01, 1.79; unintentional napping OR = 1.49, 95% CI 1.09, 2.04). Table 2. Associations of Napping Intentionality With Health/Functioning-Related Restrictions in Valued Activity Participation Napping Type  % With Activity Restriction  Model 1a OR (95% CI)  Model 2b OR (95% CI)  Model 3c OR (95% CI)    Restricted in Visiting with Friends/Family  Non-nappers  5.3  1.00  1.00  1.00  Intentional  7.6  1.62 (1.06, 2.48)*  1.40 (0.91, 2.16)  1.27 (0.78, 2.05)  Unintentional  10.3  1.99 (1.41, 2.82)**  1.45 (0.999, 2.11)  1.32 (0.88, 1.98)    Restricted in Attending Religious Services  Non-nappers  13.7  11.00  1.00  1.00  Intentional  14.8  1.20 (0.87, 1.66)  1.04 (0.75, 1.46)  0.98 (0.67, 1.43)  Unintentional  23.1  1.96 (1.45, 2.64)**  1.50 (1.11, 2.03)**  1.42 (1.03, 1.96)*    Restricted in Participating in Clubs/Activities  Non-nappers  8.04  1.00  1.00  1.00  Intentional  9.33  1.20 (0.77, 1.87)  1.06 (0.68, 1.67)  1.03 (0.62, 1.70)  Unintentional  17.1  2.23 (1.45, 3.44)**  1.69 (1.05, 2.71)*  1.52 (0.94, 2.47)    Restricted in Going Out for Enjoyment  Non-nappers  5.67  1.00  1.00  1.00  Intentional  7.54  1.43 (0.95, 2.14)  1.29 (0.85, 1.95)  1.11 (0.69, 1.77)  Unintentional  10.2  1.80 (1.21, 2.67)**  1.46 (0.97, 2.19)  1.42 (0.92, 2.18)    Restricted in Any Valued Activity  Non-nappers  16.6  1.00  1.00  1.00  Intentional  21.7  1.55 (1.24, 1.93)**  1.41 (1.11, 1.78)**  1.34 (1.01, 1.79)*  Unintentional  30.2  2.09 (1.64, 2.67)**  1.63 (1.23, 2.16)**  1.49 (1.09, 2.04)*  Napping Type  % With Activity Restriction  Model 1a OR (95% CI)  Model 2b OR (95% CI)  Model 3c OR (95% CI)    Restricted in Visiting with Friends/Family  Non-nappers  5.3  1.00  1.00  1.00  Intentional  7.6  1.62 (1.06, 2.48)*  1.40 (0.91, 2.16)  1.27 (0.78, 2.05)  Unintentional  10.3  1.99 (1.41, 2.82)**  1.45 (0.999, 2.11)  1.32 (0.88, 1.98)    Restricted in Attending Religious Services  Non-nappers  13.7  11.00  1.00  1.00  Intentional  14.8  1.20 (0.87, 1.66)  1.04 (0.75, 1.46)  0.98 (0.67, 1.43)  Unintentional  23.1  1.96 (1.45, 2.64)**  1.50 (1.11, 2.03)**  1.42 (1.03, 1.96)*    Restricted in Participating in Clubs/Activities  Non-nappers  8.04  1.00  1.00  1.00  Intentional  9.33  1.20 (0.77, 1.87)  1.06 (0.68, 1.67)  1.03 (0.62, 1.70)  Unintentional  17.1  2.23 (1.45, 3.44)**  1.69 (1.05, 2.71)*  1.52 (0.94, 2.47)    Restricted in Going Out for Enjoyment  Non-nappers  5.67  1.00  1.00  1.00  Intentional  7.54  1.43 (0.95, 2.14)  1.29 (0.85, 1.95)  1.11 (0.69, 1.77)  Unintentional  10.2  1.80 (1.21, 2.67)**  1.46 (0.97, 2.19)  1.42 (0.92, 2.18)    Restricted in Any Valued Activity  Non-nappers  16.6  1.00  1.00  1.00  Intentional  21.7  1.55 (1.24, 1.93)**  1.41 (1.11, 1.78)**  1.34 (1.01, 1.79)*  Unintentional  30.2  2.09 (1.64, 2.67)**  1.63 (1.23, 2.16)**  1.49 (1.09, 2.04)*  Note: See Supplementary Table 1 for sample sizes. CI = Confidence interval; OR = Odds ratio. aModel 1 adjusted for age, race, gender, education category. bModel 2 adjusted for Model 1 covariates + number of medical conditions, BMI category. cModel 3 adjusted for Model 2 covariates + GAD-2, PHQ-2, nighttime sleep duration. *p value < .05; **p value < .01. View Large We also compared the association of unintentional versus intentional napping with activity restrictions. In all three Models, there were no differences between unintentional and intentional nappers in odds of restrictions in visiting with friends/family or going out for enjoyment. However, compared to intentional nappers, unintentional nappers had a greater odds of restricted religious service attendance in Models 1 and 2 (Model 2: OR = 1.44, 95% CI 1.01, 2.03), and in participating in clubs/activities in Model 1 (OR = 1.86, 95% CI 1.14, 3.05); these associations were not significant in subsequent models (Supplementary Table 2). Compared to intentional napping, unintentional napping was associated with a greater odds of any activity restriction in Model 1 (OR = 1.35, 95% CI 1.02, 1.80), but not in subsequent models. Napping Frequency and Restricted Participation Compared to non-nappers, infrequent napping was not associated with restrictions in any individual activities; however, frequent nappers had greater odds of restrictions in each individual activity and any valued activity in Models 1 through 3 (Table 3). In Model 4, which further adjusted for EDS, these associations held for restrictions in visiting with friends/family (OR = 1.83, 95% CI 1.17, 2.84) and any valued activity (OR = 1.66, 95% CI 1.27, 2.18), but not for attending religious services, club/activities participation, or going out for enjoyment. Table 3. Associations of Napping Frequency With Health/Functioning-Related Restrictions in Valued Activity Participation Napping Frequency  Model 1a OR (95% CI)  Model 2b OR (95% CI)  Model 3c OR (95% CI)  Model 4d OR (95% CI)    Restricted in Visiting with Friends/Family  Non-nappers  1.00  1.00  1.00  1.00  Infrequent  1.16 (0.74, 1.82)  0.94 (0.57, 1.56)  0.89 (0.52, 1.52)  0.91 (0.56, 1.47)  Frequent  2.70 (1.88, 3.86)**  2.07 (1.44, 2.97)**  1.80 (1.19, 2.71)**  1.83 (1.17, 2.84)**    Restricted in Attending Religious Services  Non-nappers  1.00  1.00  1.00  1.00  Infrequent  1.23 (0.91, 1.65)  1.02 (0.74, 1.41)  0.97 (0.67, 1.41)  0.82 (0.55, 1.21)  Frequent  2.17 (1.55, 3.03)**  1.71 (1.23, 2.37)**  1.59 (1.14, 2.23)**  1.34 (0.95, 1.88)    Restricted in Participating in Clubs/Activities  Non-nappers  1.00  1.00  1.00  1.00  Infrequent  1.21 (0.80, 1.83)  0.98 (0.63, 1.54)  0.93 (0.58, 1.47)  0.78 (0.48, 1.27)  Frequent  2.46 (1.57, 3.85)**  2.01 (1.25, 3.24)**  1.86 (1.14, 3.03)*  1.54 (0.88, 2.69)    Restricted in Going Out for Enjoyment  Non-nappers  1.00  1.00  1.00  1.00  Infrequent  1.07 (0.70, 1.62)  0.93 (0.60, 1.43)  0.85 (0.54, 1.35)  0.79 (0.52, 1.20)  Frequent  2.38 (1.64, 3.46)**  2.00 (1.36, 2.94)**  1.82 (1.21, 2.73)**  1.54 (0.99, 2.37)    Restricted in Any Valued Activity  Non-nappers  1.00  1.00  1.00  1.00  Infrequent  1.33 (1.07, 1.65)*  1.13 (0.87, 1.47)  1.10 (0.81, 1.48)  0.99 (0.73, 1.35)  Frequent  2.56 (2.03, 3.22)**  2.11 (1.66, 2.67)**  1.88 (1.43, 2.47)**  1.66 (1.27, 2.18)**  Napping Frequency  Model 1a OR (95% CI)  Model 2b OR (95% CI)  Model 3c OR (95% CI)  Model 4d OR (95% CI)    Restricted in Visiting with Friends/Family  Non-nappers  1.00  1.00  1.00  1.00  Infrequent  1.16 (0.74, 1.82)  0.94 (0.57, 1.56)  0.89 (0.52, 1.52)  0.91 (0.56, 1.47)  Frequent  2.70 (1.88, 3.86)**  2.07 (1.44, 2.97)**  1.80 (1.19, 2.71)**  1.83 (1.17, 2.84)**    Restricted in Attending Religious Services  Non-nappers  1.00  1.00  1.00  1.00  Infrequent  1.23 (0.91, 1.65)  1.02 (0.74, 1.41)  0.97 (0.67, 1.41)  0.82 (0.55, 1.21)  Frequent  2.17 (1.55, 3.03)**  1.71 (1.23, 2.37)**  1.59 (1.14, 2.23)**  1.34 (0.95, 1.88)    Restricted in Participating in Clubs/Activities  Non-nappers  1.00  1.00  1.00  1.00  Infrequent  1.21 (0.80, 1.83)  0.98 (0.63, 1.54)  0.93 (0.58, 1.47)  0.78 (0.48, 1.27)  Frequent  2.46 (1.57, 3.85)**  2.01 (1.25, 3.24)**  1.86 (1.14, 3.03)*  1.54 (0.88, 2.69)    Restricted in Going Out for Enjoyment  Non-nappers  1.00  1.00  1.00  1.00  Infrequent  1.07 (0.70, 1.62)  0.93 (0.60, 1.43)  0.85 (0.54, 1.35)  0.79 (0.52, 1.20)  Frequent  2.38 (1.64, 3.46)**  2.00 (1.36, 2.94)**  1.82 (1.21, 2.73)**  1.54 (0.99, 2.37)    Restricted in Any Valued Activity  Non-nappers  1.00  1.00  1.00  1.00  Infrequent  1.33 (1.07, 1.65)*  1.13 (0.87, 1.47)  1.10 (0.81, 1.48)  0.99 (0.73, 1.35)  Frequent  2.56 (2.03, 3.22)**  2.11 (1.66, 2.67)**  1.88 (1.43, 2.47)**  1.66 (1.27, 2.18)**  Note: See Supplementary Table 1 for sample sizes. CI = Confidence interval; OR = Odds ratio. aModel 1 adjusted for age, race, gender, education category. bModel 2 adjusted for Model 1 covariates + number of medical conditions, BMI category. cModel 3 adjusted for Model 2 covariates + GAD-2, PHQ-2, nighttime sleep duration. dModel 4 adjusted for Model 3 covariates + EDS. *p value < .05; **p value < .01. View Large Compared to infrequent nappers, frequent nappers had greater odds of restrictions in each valued activity and any valued activity in Models 1, 2, and 3 (Supplementary Table 3). In Model 4, frequent napping was still associated with restrictions in visiting with friends/family (OR=2.02, 95% CI 1.16, 3.51), attending religious services (OR=1.64, 95% CI 1.11, 2.40), clubs/activities participation (OR=1.97, 95% CI 1.23, 3.14), going out for enjoyment (OR=1.94, 95% CI 1.19, 3.17), and in any valued activity (OR=1.68, 95% CI 1.30, 2.16). Nap Duration and Restricted Participation In Models 1 through 3, except for clubs/activities participation, longer nap duration was associated with restrictions in all valued activities and any activity (Table 4). Nap duration was associated with restrictions in clubs/activities in Model 1 and 2 (Model 2: OR = 1.23, 95% CI 1.03, 1.46), but not in Model 3 or 4. In Model 4, longer nap duration was associated with a greater odds of restrictions in visiting with friends/family (OR = 1.27, 95% CI 1.06, 1.52), attending religious services (OR = 1.18, 95% CI 1.02, 1.37), going out for enjoyment (OR = 1.23, 95% CI 1.06, 1.41), and any activity (OR = 1.25, 95% CI 1.10, 1.43). Table 4. Associations of Nap Duration With Health/Functioning-Related Restrictions in Valued Activity Participation   Model 1a OR (95% CI)  Model 2b OR (95% CI)  Model 3c OR (95% CI)  Model 4d OR (95% CI)    Restricted in Visiting with Friends/Family  Per 30 min  1.39 (1.23, 1.58)**  1.37 (1.19, 1.58)**  1.26 (1.06, 1.50)*  1.27 (1.06, 1.52)*    Restricted in Attending Religious Services  Per 30 min  1.30 (1.13, 1.50)**  1.27 (1.10, 1.47)**  1.18 (1.01, 1.38)*  1.18 (1.02, 1.37)*    Restricted in Participating in Clubs/Activities  Per 30 min  1.23 (1.05, 1.45)**  1.23 (1.03, 1.46)*  1.18 (0.97, 1.45)  1.19 (0.97, 1.45)    Restricted in Going Out for Enjoyment  Per 30 min  1.32 (1.18, 1.49)**  1.30 (1.15, 1.48)**  1.23 (1.07, 1.41)**  1.23 (1.06, 1.41)**    Restricted in Any Valued Activity  Per 30 min  1.35(1.21, 1.51)**  1.31 (1.16, 1.49)**  1.26 (1.10, 1.44)**  1.25 (1.10, 1.43)**    Model 1a OR (95% CI)  Model 2b OR (95% CI)  Model 3c OR (95% CI)  Model 4d OR (95% CI)    Restricted in Visiting with Friends/Family  Per 30 min  1.39 (1.23, 1.58)**  1.37 (1.19, 1.58)**  1.26 (1.06, 1.50)*  1.27 (1.06, 1.52)*    Restricted in Attending Religious Services  Per 30 min  1.30 (1.13, 1.50)**  1.27 (1.10, 1.47)**  1.18 (1.01, 1.38)*  1.18 (1.02, 1.37)*    Restricted in Participating in Clubs/Activities  Per 30 min  1.23 (1.05, 1.45)**  1.23 (1.03, 1.46)*  1.18 (0.97, 1.45)  1.19 (0.97, 1.45)    Restricted in Going Out for Enjoyment  Per 30 min  1.32 (1.18, 1.49)**  1.30 (1.15, 1.48)**  1.23 (1.07, 1.41)**  1.23 (1.06, 1.41)**    Restricted in Any Valued Activity  Per 30 min  1.35(1.21, 1.51)**  1.31 (1.16, 1.49)**  1.26 (1.10, 1.44)**  1.25 (1.10, 1.43)**  Note: See Supplementary Table 1 for sample sizes. Analyses excluded non-nappers. CI = Confidence interval; OR = Odds ratio. aModel 1 adjusted for age, race, gender, education category. bModel 2 adjusted for Model 1 covariates + number of medical conditions, BMI category. cModel 3 adjusted for Model 2 covariates + GAD-2, PHQ-2, nighttime sleep duration. dModel 4 adjusted for Model 3 covariates + EDS. *p value < .05; **p value < .01. View Large EDS By Napping Interactions In exploratory analyses, using Model 4, there was a near-significant interaction term for Napping frequency × Sleepiness for restrictions in visiting with friends/family (p = .08) and a significant Nap duration × Sleepiness interaction term for going out for enjoyment (p < .01). Among those reporting sleepiness rarely/never, compared to infrequent nappers, frequent nappers had a greater odds of restrictions in visiting with friends/family (Supplementary Figure 1a). This association was not significant among those reporting sleepiness some or most days/every day. Longer nap duration was associated with a greater odds of going out for enjoyment restrictions among those reporting sleepiness rarely/never and some days, but not most days/every day (Supplementary Figure 1b). Discussion We evaluated associations between napping characteristics and restricted participation in valued activities in a nationally representative sample of community-dwelling older adults. After adjustment for all covariates, religious service attendance was the only individual activity associated with napping intentionality, with unintentional nappers having a greater odds of restricted religious service attendance than non-nappers. However, compared to non-nappers, both intentional and unintentional nappers had a greater odds of restricted participation in any valued activity after adjustment for demographics, physical and mental health characteristics, and nighttime sleep duration. Similarly, frequent napping (vs non-napping) was associated with a greater odds of restrictions in visiting with friends/family and in any valued activity after accounting for these covariates and EDS. In models limited to nappers, after adjustment for all covariates and EDS, frequent napping was associated with restrictions in each individual activity and any valued activity, while longer nap duration was associated with restrictions in visiting with friends/family, attending religious services, going out for enjoyment, and any valued activity. Together, our results suggest that intentional and unintentional, more frequent, and longer-duration naps are associated with a greater odds of restricted valued-activity participation. Few studies have investigated links between napping and daytime function in community-dwelling older adults. Our findings of associations between napping and health- or functioning-related restrictions in valued activities in a nationally representative community-dwelling sample are consistent with associations reported between daytime sleep and reduced social participation among nursing home residents (21,22). Our results are also in line with studies that have demonstrated associations of napping with difficulties in activities of daily living (23) and instrumental activities of daily living (24) among community-dwelling older adults. On the other hand, some studies have tied napping to better cognitive functioning (9,10). Our study extends prior research, which has primarily characterized napping in terms of duration or frequency by examining napping intentionality. Future studies that consider distinct napping characteristics (eg, intentionality, frequency) may help resolve discrepant findings in this area. There are various plausible explanations for the associations we observed. For example, disturbed nighttime sleep may drive the association between napping and poor health outcomes (25). While our significant findings remained after adjustment for nighttime sleep duration, further research is needed in examining the role of nighttime sleep as a driver of napping-related social participation and other behaviors that improve quality of life. On the other hand, napping may also be a manifestation of EDS, which could lead to restrictions in valued activities, independently of napping. Indeed, other studies in older adults have investigated napping as a marker of EDS. One study found associations between EDS, measured by napping frequency, and greater odds of deficits in activities of daily living (23). In another, 87.5% of EDS cases reported napping, and EDS was associated with reduced social activities (26). In the present study, however, we adjusted for EDS and observed independent associations with restricted participation. Also, after adjustment for covariates, we found no statistically significant differences between intentional napping (which may not reflect EDS) versus unintentional napping (which likely results from EDS (27)) and activity restrictions. Thus, our findings are probably not attributable to EDS alone, and napping, itself, may be a marker of underlying conditions that increase risk for restricted activity participation in older adults. Another possibility is that napping is causally linked to health or functioning-related activity participation. In terms of a mechanism, time spent napping is time not spent engaged in other behaviors that might improve health or functioning, such as physical activity or social engagement. Thus, napping may be a modifiable risk factor for activity restriction simply because it is incompatible with other activities. However, we cannot determine this based on the results of these cross-sectional analyses. We also found that EDS modified some associations. Frequent napping was independently associated with restrictions in visiting friends/family among those reporting the least sleepiness, and nap duration was associated with restrictions in going out for enjoyment, but not among those with the most sleepiness. The reasons for these results are unclear and warrant future research. Fatigue, however, is a factor that may play a role in napping (28). Studies are needed to investigate whether fatigue may drive napping-related daytime dysfunction. Strengths of this study include a large, nationally representative sample of U.S. older adults and the investigation of distinct napping characteristics. However, this study has limitations. First, we were unable to distinguish between daytime and evening napping; nap timing may affect activity participation (29). Additionally, napping was measured by self-report, rather than an objective measure (eg, actigraphy), and did not include assessment of day-to-day variability in napping characteristics. Prior studies have found sleep estimates derived from objective and subjective measures conflict among older adults (29). Investigations using self-report and objective measures of napping and studying whether associations differ by mode of assessment are needed. Further, this study used a cross-sectional observational design, which does not allow us to probe for potential causal links by examining temporal associations. Longitudinal studies are needed in this domain to examine temporal associations that may suggest causal links. Because we are unable to conclude that the association is causal, we cannot recommend against napping based on our results. Nonetheless, clinicians should note that unintentional napping may be a marker of a sleep disorder or over-sedation. Patients reporting unintentional napping should be evaluated to identify underlying causes, including a sleep study to rule out a sleep disorder (30), such as sleep-disordered breathing. In conclusion, we found that unintentional, intentional, frequent, and longer-duration naps are associated with decrements in daytime social functioning and activity participation among older adults. If napping does detract from adaptive participation in valued activities, this would suggest that decreasing napping may promote these healthy behaviors. However, prior to the creation of randomized trials to investigate this possibility, longitudinal studies are needed. Supplementary Material Supplementary data is available at The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences online. Funding This work was supported in part by grants from the National Institute on Aging (U01-AG032947, R01AG050507, R01AG050507-02S1, and T32-AG027668) and the National Institute of Mental Health (T32-MH019934). Conflict of Interest Adam Spira agreed to serve as a consultant to Awarables, Inc. in support of an NIH grant. Acknowledgments The authors thank Ramin Mojtabai, MD, PhD, MPH, for his feedback regarding data analysis, and Maureen Skehan, MSPH, for her assistance with the NHATS data. References 1. Ohayon MM, Vecchierini MF. Daytime sleepiness and cognitive impairment in the elderly population. Arch Intern Med . 2002; 162: 201– 208. doi:10.1001/archinte.162.2.201 Google Scholar CrossRef Search ADS PubMed  2. Ohayon MM, Zulley J. Prevalence of naps in the general population. Sleep Hypn . 1999; 1: 88– 97. 3. Foley DJ, Vitiello MV, Bliwise DL, Ancoli-Israel S, Monjan AA, Walsh JK. Frequent napping is associated with excessive daytime sleepiness, depression, pain, and nocturia in older adults: findings from the National Sleep Foundation ‘2003 Sleep in America’ Poll. Am J Geriatr Psychiatry . 2007; 15: 344– 350. doi: 10.1097/01.JGP.0000249385.50101.67 Google Scholar CrossRef Search ADS PubMed  4. Vitiello MV. We have much more to learn about the relationships between napping and health in older adults. J Am Geriatr Soc . 2008; 56: 1753– 1755. doi: 10.1111/j.1532-5415.2008.01837.x Google Scholar CrossRef Search ADS PubMed  5. Zhong G, Wang Y, Tao T, Ying J, Zhao Y. Daytime napping and mortality from all causes, cardiovascular disease, and cancer: a meta-analysis of prospective cohort studies. Sleep Med . 2015; 16: 811– 819. doi: 10.1016/j.sleep.2015.01.025 Google Scholar CrossRef Search ADS PubMed  6. Fang W, Li Z, Wu Let al.   Longer habitual afternoon napping is associated with a higher risk for impaired fasting plasma glucose and diabetes mellitus in older adults: results from the Dongfeng-Tongji cohort of retired workers. Sleep Med . 2013; 14: 950– 954. doi: 10.1016/j.sleep.2013.04.015 Google Scholar CrossRef Search ADS PubMed  7. Cao Z, Shen L, Wu Jet al.   The effects of midday nap duration on the risk of hypertension in a middle-aged and older Chinese population: a preliminary evidence from the Tongji-Dongfeng Cohort Study, China. J Hypertens . 2014; 32: 1993– 8; discussion 1998. doi: 10.1097/HJH.0000000000000291 Google Scholar CrossRef Search ADS PubMed  8. Cross N, Terpening Z, Rogers NLet al.   Napping in older people ‘at risk’ of dementia: relationships with depression, cognition, medical burden and sleep quality. J Sleep Res . 2015; 24: 494– 502. doi: 10.1111/jsr.12313 Google Scholar CrossRef Search ADS PubMed  9. Campbell SS, Murphy PJ, Stauble TN. Effects of a nap on nighttime sleep and waking function in older subjects. J Am Geriatr Soc . 2005; 53: 48– 53. doi: 10.1111/j.1532-5415.2005.53009.x Google Scholar CrossRef Search ADS PubMed  10. Tamaki M, Shirota A, Tanaka H, Hayashi M, Hori T. Effects of a daytime nap in the aged. Psychiatry Clin Neurosci . 1999; 53: 273– 275. doi: 10.1046/j.1440-1819.1999.00548.x Google Scholar CrossRef Search ADS PubMed  11. Glass TA, de Leon CM, Marottoli RA, Berkman LF. Population based study of social and productive activities as predictors of survival among elderly Americans. BMJ . 1999; 319: 478– 483. doi:10.1136/bmj.319.7208.478 Google Scholar CrossRef Search ADS PubMed  12. Isaac V, Stewart R, Artero S, Ancelin ML, Ritchie K. Social activity and improvement in depressive symptoms in older people: a prospective community cohort study. Am J Geriatr Psychiatry . 2009; 17: 688– 696. doi: 10.1097/JGP.0b013e3181a88441 Google Scholar CrossRef Search ADS PubMed  13. Kotwal AA, Kim J, Waite L, Dale W. Social function and cognitive status: results from a US nationally representative survey of older adults. J Gen Intern Med . 2016; 31: 854– 862. doi: 10.1007/s11606-016-3696-0 Google Scholar CrossRef Search ADS PubMed  14. Agahi N, Parker MG. Leisure activities and mortality: does gender matter? J Aging Health . 2008; 20: 855– 871. doi: 10.1177/0898264308324631 Google Scholar CrossRef Search ADS PubMed  15. Hsu HC. Does social participation by the elderly reduce mortality and cognitive impairment? Aging Ment Health . 2007; 11: 699– 707. doi: 10.1080/13607860701366335 Google Scholar CrossRef Search ADS PubMed  16. Spira AP, Kaufmann CN, Kasper JDet al.   Association between insomnia symptoms and functional status in U.S. older adults. J Gerontol B Psychol Sci Soc Sci . 2014; 69( suppl 1): S35– S41. doi: 10.1093/geronb/gbu116 Google Scholar CrossRef Search ADS PubMed  17. Chen JH, Lauderdale DS, Waite LJ. Social participation and older adults’ sleep. Soc Sci Med . 2016; 149: 164– 173. doi: 10.1016/j.socscimed.2015.11.045 Google Scholar CrossRef Search ADS PubMed  18. Kasper J, Freedman V. National Health and Aging Trends Study User Guide: Rounds 1, 2, 3& 4 Final Release . Baltimore: Johns Hopkins University School of Public Health; 2015. 19. World Health Organization. Global database on Body Mass Index: BMI Classification . 2006. 2015. 20. Kroenke K, Spitzer RL, Williams JB, Löwe B. An ultra-brief screening scale for anxiety and depression: the PHQ-4. Psychosomatics . 2009; 50: 613– 621. doi: 10.1176/appi.psy.50.6.613 Google Scholar PubMed  21. Martin JL, Webber AP, Alam T, Harker JO, Josephson KR, Alessi CA. Daytime sleeping, sleep disturbance, and circadian rhythms in the nursing home. Am J Geriatr Psychiatry . 2006; 14: 121– 129. doi: 10.1097/01.JGP.0000192483.35555.a3 Google Scholar CrossRef Search ADS PubMed  22. Li J, Chang YP, Porock D. Factors associated with daytime sleep in nursing home residents. Res Aging . 2015; 37: 103– 117. doi: 10.1177/0164027514537081 Google Scholar CrossRef Search ADS PubMed  23. Hays JC, Blazer DG, Foley DJ. Risk of napping: excessive daytime sleepiness and mortality in an older community population. J Am Geriatr Soc . 1996; 44: 693– 698. doi:10.1111/j.1532-5415.1996.tb01834.x Google Scholar CrossRef Search ADS PubMed  24. Goldman SE, Stone KL, Ancoli-Israel Set al.   Poor sleep is associated with poorer physical performance and greater functional limitations in older women. Sleep . 2007; 30: 1317– 1324. doi: 10.1093/sleep/30.10.1317 Google Scholar CrossRef Search ADS PubMed  25. Cohen-Mansfield J, Perach R. Sleep duration, nap habits, and mortality in older persons. Sleep . 2012; 35: 1003– 1009. doi: 10.5665/sleep.1970 Google Scholar PubMed  26. Gooneratne NS, Weaver TE, Cater JRet al.   Functional outcomes of excessive daytime sleepiness in older adults. J Am Geriatr Soc . 2003; 51: 642– 649. doi:10.1034/j.1600-0579.2003.00208.x Google Scholar CrossRef Search ADS PubMed  27. Martin JL, Ancoli-Israel S. Napping in older adults. Sleep Med Clin . 2006; 1: 177– 86. doi:10.1016/j.jsmc.2006.04.011 Google Scholar CrossRef Search ADS   28. Picarsic JL, Glynn NW, Taylor CAet al.   Self-reported napping and duration and quality of sleep in the lifestyle interventions and independence for elders pilot study. J Am Geriatr Soc . 2008; 56: 1674– 1680. doi: 10.1111/j.1532-5415.2008.01838.x Google Scholar CrossRef Search ADS PubMed  29. Dautovich ND, McCrae CS, Rowe M. Subjective and objective napping and sleep in older adults: are evening naps “bad” for nighttime sleep? J Am Geriatr Soc . 2008; 56: 1681– 1686. doi: 10.1111/j.1532-5415.2008. 01822.x Google Scholar CrossRef Search ADS PubMed  30. Neikrug AB, Ancoli-Israel S. Sleep disorders in the older adult - a mini-review. Gerontology . 2010; 56: 181– 189. doi: 10.1159/000236900 Google Scholar CrossRef Search ADS PubMed  © The Author(s) 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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The Journals of Gerontology Series A: Biomedical Sciences and Medical SciencesOxford University Press

Published: Mar 1, 2018

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