Prevalence, Trends, and Correlates of Joint Patterns of Aerobic and Muscle-Strengthening Activity and Sleep Duration: A Pooled Analysis of 359,019 Adults in the National Health Interview Survey 2004–2018

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Stina Oftedal
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Elizabeth G. Holliday
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Amy C. Reynolds
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Jason A. Bennie
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Christopher E. Kline
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Mitch J. Duncan
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Background: Physical activity (PA) and sleep duration have established associations with health outcomes individually but tend to co-occur and may be better targeted jointly. This study aimed to describe the cross-sectional prevalence, trends, and population characteristic correlates of activity-sleep patterns in a population-representative sample of US adults from the National Health Interview Survey (2004–2018). Methods: Participants (N = 359,019) self-reported aerobic and muscle-strengthening activity and sleep duration. They were categorized as “meeting both”/“meeting PA only”/“meeting sleep only”/“meeting neither” of the 2018 US PA guidelines and age-based sleep duration recommendations. Trends in activity-sleep patterns were analyzed using weighted multinomial logistic regression, and correlates were identified using weighted binary Poisson regressions, with P ≤ .001 considered significant. Results: “Meet sleep only” was most prevalent (46.4%) by 2018, followed by “meet neither” (30.3%), “meet both” (15.6%), and “meet PA only” (7.7%). Many significant sociodemographic, biological, and health-behavior correlates of the activity-sleep groups were identified, and the direction and magnitude of these associations differed between groups. Conclusions: Public health campaigns should emphasize the importance of both sufficient PA and sleep; target women and older adults, current smokers, and those with lower education and poorer physical and mental health; and consider specific barriers experienced by minority ethnic groups.

As separate risk factors, physical inactivity and both short and long sleep duration (ie, <7 or >9 h/night) are associated with increased risk of mortality and a range of chronic diseases.17 However, physical inactivity and poor sleep are known to co-occur,810 and emerging evidence shows an additive effect between physical activity (PA) and sleep duration on health outcomes.1115 This is a concern as 80% of adults in the United States do not meet the amounts of aerobic and muscle-strengthening activity recommended in the PA guidelines16,17 and at least 30% do not meet sleep duration recommendations.18,19 The significant prevalence and interconnectedness of PA and sleep duration, and their strong association with health outcomes, underscores the improvement of these behaviors as a key public health priority.

Traditionally, the main focus of public health PA promotion to improve health has been on increasing aerobic PA.20 More recent evidence supports unique, additional health benefits of muscle-strengthening activity, especially for maintaining muscle mass and physical function, and often the greatest benefits come from meeting both activity guidelines.16,2123 This warrants further promotion of the benefits of muscle-strengthening activity. Furthermore, with few exceptions, the importance of getting the right amount of sleep for your age to enhance public health has received limited attention.14,24,25 When considering the significant impact of sleep duration on mortality and chronic disease,47 increased daytime sleepiness contributing to accidents,26 and reductions in cognitive performance and productivity,27 improving sleep duration at the population level represents a significant public health opportunity.

Emerging evidence suggests that PA and sleep have bidirectional associations, and public health promotions targeting both concurrently may be more effective than ones focusing on either behavior alone.28,29 Identifying how specific patterns of PA and sleep duration vary according to population characteristics can assist with identifying groups most at risk of ill health due to poor behaviors. Furthermore, mapping trends of behavior patterns over time supports the development of health policy and monitoring of changes associated with health promotion efforts. Studies to date have focused on correlates and trends of meeting recommendations for either PA or sleep duration.1618,30 This approach limits our knowledge of who is at greatest risk from ill health due to meeting neither recommendation. Therefore, the aims of this study were to use a population-representative sample of US adults to: (1) describe the cross-sectional prevalence and temporal trends of activity-sleep patterns between 2004 and 2018 and (2) describe the sociodemographic, biological, and health behavior–related correlates of the activity-sleep patterns in the pooled 2004–2018 study population.

Methods

We drew data from the 2004 to 2018 National Health Interview Survey (NHIS) as these years collected data on all behaviors of interest. The NHIS is an ongoing, annual, nationally representative cross-sectional household survey of noninstitutionalized individuals in the United States.31 Participants are selected randomly using a stratified multistage probability design, and interviews are conducted face-to-face. The study received ethical approval from the Research Ethics Review Board of the National Center for Health Statistics. All participants provided verbal consent to participate in the survey. Data are publicly available and were downloaded from the Integrated Public Use Microdata Series NHIS database from the Integrated Public Use Microdata Series website.32 A total of 359,019 participants with complete data were included in analyses (n = 85,940 excluded), with each participant contributing data for only a single survey year (Figure 1).

Figure 1
Figure 1

—Sample selection NHIS 2004–2018 (unweighted sample sizes). NHIS indicates National Health Interview Survey.

Citation: Journal of Physical Activity and Health 19, 4; 10.1123/jpah.2021-0682

Meeting PA Guidelines

Participants self-reported duration and frequency of leisure-time, light- and moderate-intensity PA and vigorous-intensity PA that was at least 10 minutes in duration (see Supplementary Table S1 [available online] for a description of all variables). Total weekly minutes of PA was calculated by summing the weekly minutes of light-moderate- and vigorous-intensity activity using standard NHIS procedures.33 Each participant also self-reported the number of times they performed muscle-strengthening activities per week. The psychometric properties of the NHIS-PA questionnaire have not been reported; however, it provides comparable estimates of PA levels relative to other survey instruments that have acceptable validity and reliability,34 and dose–response relationships between PA levels measured using the NHIS-PA questionnaire and mortality have been demonstrated.35 Participants were classified as meeting the 2018 US PA Guidelines if they reported participating in ≥150 minutes of moderate-intensity PA, ≥75 minutes of vigorous-intensity PA, or an equivalent combination of moderate- and vigorous-intensity PA per week, and participated in muscle-strengthening activity ≥2 times per week.36

Sleep Duration

Participants reported their habitual average sleep duration during a 24-hour period in a single survey question. No psychometric data is available on this item, but sleep duration is frequently measured using self-report in cohort studies and consistent associations with a range of health outcomes have been demonstrated.4,5 Participants were classified as meeting the National Sleep Foundation sleep duration recommendations if they were aged 18–64 years and slept between 7 and 9 hours per 24 hours, or if they were aged 65+ years old and reported sleeping 7 to 8 hours per 24 hours.37 Sleeping shorter or longer than the age-specific guidelines was classified as not meeting sleep duration recommendations.

Activity-Sleep Patterns

Four categories of activity-sleep pattern groups were then created using the PA and sleep duration categories: (1) “meet both,” (2) “meet PA only”, (3) “meet sleep only,” and (4) “meet neither.”

Sociodemographic, Biological, and Behavioral Characteristics

Participants reported age, gender, height and body weight, ethnicity, marital status, education, employment status, annual income, smoking history, alcohol consumption history, chronic disease diagnoses (asthma, stroke, diabetes, coronary heart disease, heart attack or myocardial infarction, hypertension, cancer, or emphysema), self-rated health, and psychological distress. These sociodemographic, biological, and behavioral characteristics were chosen due to their known associations with both PA and sleep.1618,30 The subgroup classifications of these characteristics are shown in Table 1 and Supplementary Table S1 (available online). Self-reported height and body weight were used to calculate body mass index (BMI), which was categorized according to World Health Organization criteria.38 Psychological distress over the previous 30 days was assessed using the Kessler−6 Distress scale (K6) and scored using standard US scoring protocols.39 Based on a previous study, a score of 13 or greater indicates a high level of psychological distress and a likely severe mental illness.39

Table 1

Sample Characteristics (Unweighted, N = 359,019)

Unweighted, n (%)Weighted % (95% CI)
Age category, y
 18–64283,656 (79.01)83.37 (83.12 to 83.61)
 65+75,363 (20.99)16.63 (16.39 to 16.88)
Sex
 Male161,959 (45.11)48.86 (48.64 to 49.08)
 Female197,060 (54.89)51.14 (50.92 to 51.36)
Marital status
 Married160,527 (44.71)54.30 (53.91 to 54.69)
 Widowed, divorced, or separated100,920 (28.11)19.26 (19.04 to 19.48)
 Never married97,572 (27.18)26.44 (26.09 to 26.80)
Ethnicity
 Hispanic59,692 (16.63)14.53 (14.13 to 14.95)
 Non-Hispanic white225,801 (62.89)67.90 (67.36 to 68.44)
 Non-Hispanic black50,390 (14.04)11.55 (11.22 to 11.90)
 Other, including mixed23,136 (6.44)6.01 (5.80 to 6.23)
Education
 Did not complete high school56,019 (15.60)13.87 (13.60 to 14.15)
 High school/graduate equivalency degree93,076 (25.93)26.20 (25.92 to 26.49)
 Some college or associate degree108,778 (30.30)30.54 (30.25 to 30.83)
 Bachelor’s degree or higher101,146 (28.17)29.38 (28.94 to 29.84)
Annual income
 $0–$34,999150,586 (41.94)32.34 (31.88 to 32.81)
 $35,000–$74,999110,030 (30.65)31.90 (31.63 to 32.18)
 >$75,00098,403 (27.41)35.75 (35.23 to 36.28)
Employment status
 Employed216,751 (60.37)63.64 (63.31 to 63.96)
 Unemployed15,966 (4.45)4.54 (4.43 to 4.65)
 Retired64,989 (18.10)14.85 (14.61 to 15.10)
 Not in workforce61,313 (17.08)16.97 (16.73 to 17.22)
Smoking status
 Current smoker67,399 (18.78)18.40 (18.15 to 18.65)
 Former smoker80,117 (22.33)21.76 (21.54 to 21.99)
 Never smoker211,287 (58.89)59.84 (59.52 to 60.15)
Alcohol consumption
 Lifetime abstainer75,208 (20.95)20.33 (20.02 to 20.65)
 Former drinker54,936 (15.30)14.00 (13.81 to 14.20)
 Light-to-moderate drinker209,283 (58.29)60.28 (59.94 to 60.62)
 Heavy drinker19,592 (5.46)5.38 (5.27 to 5.50)
Body mass index, kg/m2
 <18.56264 (1.74)1.76 (1.70 to 1.81)
 18.5–24.9125,213 (34.88)35.19 (34.93 to 35.45)
 25–29.9124,475 (34.67)34.73 (34.53 to 34.94)
 >30103,067 (28.71)28.32 (28.06 to 28.58)
Chronic diseases
 No chronic disease192,193 (53.53)56.22 (55.94 to 56.50)
 Has chronic disease diagnosis166,826 (46.47)43.78 (43.50 to 44.06)
 Self-rated health
 Excellent-to-very-good211,285 (58.85)61.79 (61.48 to 62.09)
 Good96,612 (26.91)25.86 (25.65 to 26.08)
 Fair-to-poor51,122 (14.24)12.35 (12.16 to 12.54)
Psychological distress
 Low distress345,901 (96.35)96.73 (96.63 to 96.82)
 High distress13,118 (3.65)3.27 (3.18 to 3.37)
Aerobic activity guideline
 Meets (≥150 min·wk)70,705 (19.69)21.04 (20.76 to 21.32)
 Does not meet (<150 min·wk)288,314 (80.31)78.96 (78.68 to 79.24)
Muscle-strengthening guideline
 Meets (≥2 times/wk)84,020 (23.40)24.69 (24.39 to 24.99)
 Does not meet (<2 sessions/wk)274,999 (76.60)75.31 (75.01 to 75.61)
Sleep duration category
 Short sleep110,064 (30.66)30.09 (29.86 to 30.33)
 Recommended sleep229,041 (63.80)64.83 (64.58 to 65.08)
 Long sleep19,914 (5.55)5.08 (4.98 to 5.18)

Statistical Analysis

Raw NHIS data files were downloaded from Integrated Public Use Microdata Series and imported into Stata (version MP 17.0; StataCorp LLC, College Station, TX) for analysis. All analyses considered the weighted and clustered sampling design of NHIS as previously recommended to enable generalizability of results to the broader US population.40 To apply sampling weights to the pooled sample, the weights were divided by the number of years pooled (15 y) as recommended.40 Characteristics of the sample were reported as unweighted frequency and percentages, and weighted percentages with 95% confidence interval. The characteristics of the included versus excluded samples were compared by reporting weighted percentages and 95% confidence intervals.

To address the first study aim, we examined temporal trends in prevalence of the activity-sleep patterns. Weighted multinomial logistic regression modeling was used to estimate the proportion of the sample occupying each activity-sleep pattern by year, adjusted for all sociodemographic, biological, and behavioral characteristics covariates. The Stata margins command was then used to calculate and plot the adjusted marginal proportions of the sample in each activity-sleep pattern group by year (Figure 2).

Figure 2
Figure 2

—Adjusted and weighted proportions of sample within each combination of physical activity level and sleep duration between 2004 and 2018. “Meet both”: meet both physical activity and sleep duration recommendations. “Meet PA only”: meet physical activity recommendations only. “Meet sleep only”: meet sleep duration recommendations only. “Meet neither”: meet neither physical activity nor sleep duration recommendation. Change between 2004 and 2018: “meet both”: 3.3% (95% CI, 2.5 to 4.2), “meet PA only”: 1.8% (95% CI, 0.1 to 2.4), “meet sleep only”: −6.2% (95% CI, −7.5 to −5.0), and “meet neither”: 1.9% (95% CI, 0.1 to 2.9). CI indicates confidence interval; PA, physical activity.

Citation: Journal of Physical Activity and Health 19, 4; 10.1123/jpah.2021-0682

To address the second study aim, we described correlates of the activity-sleep pattern groups in the pooled 2004–2018 sample. In this analysis, 3 separate binary Poisson regression models with robust error variance were used to estimate adjusted prevalence ratios (APRs) for each of the sociodemographic, biologic, and health behavior-related covariates, for each activity-sleep group. For all 3 analyses, those who met both PA and sleep duration recommendations were used as the reference group to allow the characterization of the 3 activity-sleep groups at risk of poor health outcomes due to meeting only one or neither of the PA or sleep recommendations relative to those meeting both recommendations (ie, meet PA only [1] vs meet both [0]; meet sleep only [1] vs meet both [0]; meet neither [1] vs meet both [0]). Poisson regression was used instead of logistic regression to enable estimation of prevalence (risk) ratios, rather than odds ratios.41

Finally, 3 separate interaction analyses were conducted to assess whether there were differences in trends over time between: (1) men and women; (2) Hispanic, white, and black participants (excluding “other”); and (3) 18–64 and ≥65 year olds. Differences in trends were analyzed by entering an interaction term in the Poisson regressions conducted to address the second aim as described above, using year as a continuous variable assuming linearity, for a total of 9 analyses. To estimate and plot the adjusted and weighted marginal proportions over time for each group, a multinomial logistic regression as described in aim one, was conducted with interaction terms.

Due to the large sample size, a P value of ≤.001 was used to indicate significance. To emphasize clinical (as well as statistical) significance of identified effects, only changes in proportion of prevalence of >5%, and associations where the APR > 1.05 or APR < 0.95, will be discussed.42,43

Results

Sample

Participants in the final sample (n = 359,019) had a mean age of 45.9 (SE: 0.08) years and were similarly likely to be men (48.9%) as women. Included participants were primarily white (67.9%), almost one third had a bachelor’s degree or higher (29.4%), and the majority were employed (63.6%). Only one quarter of the sample (24.7%) met the muscle-strengthening recommendation, almost one half (48.7%) met the aerobic activity recommendation, and nearly two thirds (64.8%) met age-based sleep duration recommendations (see Table 1 for summary statistics). Comparison of characteristics between included and excluded participants can be found in Supplementary Table S2 (available online).

Prevalence and Trends From 2004 Through 2018

Figure 2 displays the adjusted and weighted marginal proportions of participants occupying each PA and sleep pattern by year. The most prevalent pattern was “meet sleep only,” and this decreased from 2004 (52.9%) to 2018 (46.4%) by a total of 6.2% (95% confidence interval, −7.5 to −5.0). This reduction appeared to result from small but statistically significant increases in prevalence of each of the other groups (Figure 2). The second most prevalent pattern was “meet neither,” followed by “meet both” with a 30.3% and 15.6% prevalence in 2018, respectively. The least prevalent pattern in 2018 was “meet PA only” (7.7%).

The marginal change between 2004 and 2018 for each interaction analysis and graphs depicting the trends over time can be found in Supplementary Figures S1–S3 (available online). In short, for women relative to men, the probability of reporting only meeting sleep recommendations (APR = 1.003 [1.002 to 1.005]) and reporting meeting neither recommendation (APR = 1.005 [1.003 to 1.007]) increased slightly between 2004 and 2018. For 18–64 year-olds versus ≥65 year-olds, the probability of reporting only meeting sleep recommendations increased slightly (APR = 1.005 [1.003 to 1.006]), whereas for Hispanics relative to whites, the probability of reporting only meeting sleep recommendations decreased slightly (APR = 0.997 [0.995 to 0.998]).

Associations With Socio-Demographic, Biological, and Behavioral Variables

The associations between covariates and each of the PA and sleep patterns are displayed in Table 2, with the adjusted and weighted characteristics of each PA and sleep pattern group displayed in Supplementary Table S3 (available online). A simplified display of the direction and magnitude of the associations is displayed in Table 3 to aid interpretation.

Table 2

Adjusted and Weighted Prevalence Ratios and Their 95% CI (APR 95%CI) for Sociodemographic and Health-Related Covariates According to Activity-Sleep Group

Reference group: Meet bothaMeet PA onlybMeet sleep onlycMeet neitherd
APR95% CIAPR95% CIAPR95% CI
Survey year1.01(1.01 to 1.01)0.99(0.99 to 1.00)1.00(1.00 to 1.00)
Age (per 10 y)0.99(0.98 to 1.01)1.04(1.03 to 1.04)1.06(1.05 to 1.06)
Gender (ref: Male)Ref
 Female1.00(0.97 to 1.03)1.09(1.08 to 1.10)1.11(1.10 to 1.12)
Marital status (ref: married)
 Widowed/divorced/separated1.17(1.13 to 1.21)0.95(0.95 to 0.96)0.98(0.97 to 0.99)
 Never married/unknown0.97(0.93 to 1.00)0.93(0.93 to 0.94)0.90(0.88 to 0.91)
Ethnicity/race (ref: non-Hispanic white)
 Hispanic1.04(0.99 to 1.08)1.03(1.03 to 1.04)1.06(1.04 to 1.07)
 Non-Hispanic black1.42(1.36 to 1.47)1.01(1.00 to 1.02)1.13(1.11 to 1.14)
 Other race/ethnicity1.18(1.12 to 1.25)1.09(1.08 to 1.10)1.18(1.16 to 1.20)
Education (ref: Bachelor’s degree or higher)
 Some college/ associate degree1.18(1.15 to 1.22)1.09(1.08 to 1.10)1.24(1.22 to 1.26)
 High school or GED1.12(1.07 to 1.16)1.17(1.16 to 1.18)1.36(1.34 to 1.38)
 Did not complete high school1.15(1.08 to 1.22)1.18(1.17 to 1.19)1.35(1.33 to 1.37)
Annual income (ref: >$75,000)
 $35,000–$74,9991.03(0.99 to 1.07)1.08(1.07 to 1.08)1.15(1.14 to 1.17)
 $0–$34,9991.03(0.99 to 1.07)1.09(1.08 to 1.10)1.17(1.16 to 1.19)
Employment status (ref: retired)
 Employed1.16(1.09 to 1.22)1.05(1.04 to 1.06)1.10(1.09 to 1.12)
 Unemployed1.02(0.94 to 1.11)1.02(1.00 to 1.03)1.03(1.00 to 1.05)
 Not in workforce51.00(0.93 to 1.07)1.03(1.02 to 1.04)1.04(1.03 to 1.06)
Smoking status (ref: never smoker)
 Current smoker1.25(1.20 to 1.30)1.11(1.10 to 1.11)1.23(1.21 to 1.24)
 Former smoker1.05(1.01 to 1.09)1.01(1.00 to 1.02)1.04(1.03 to 1.05)
Alcohol consumption (ref: lifetime abstainer)
 Former drinker1.13(1.06 to 1.20)0.95(0.94 to 0.96)0.97(0.96 to 0.98)
 Light-to-moderate drinker1.10(1.05 to 1.16)0.90(0.90 to 0.91)0.89(0.88 to 0.91)
 Heavy drinker1.12(1.05 to 1.20)0.89(0.88 to 0.90)0.89(0.87 to 0.91)
Body mass index (ref: 18.5–24.9 kg/m2)
 <18.5 kg/m20.84(0.72 to 0.98)1.08(1.06 to 1.11)1.14(1.11 to 1.17)
 25–29.9 kg/m21.11(1.08 to 1.15)1.04(1.03 to 1.04)1.08(1.07 to 1.10)
 ≥30 kg/m21.23(1.18 to 1.28)1.10(1.10 to 1.11)1.21(1.20 to 1.23)
Chronic disease (ref: no chronic disease)
 Has chronic disease1.06(1.03 to 1.09)0.99(0.98 to 0.99)1.03(1.02 to 1.04)
Self-rated health (ref: excellent-to-very good)
 Good1.15(1.11 to 1.19)1.09(1.09 to 1.10)1.25(1.24 to 1.26)
 Fair-to-poor1.34(1.27 to 1.42)1.11(1.10 to 1.12)1.28(1.27 to 1.30)
Psychological distress (ref: low distress)
 High distress1.63(1.52 to 1.75)1.03(1.01 to 1.04)1.10(1.09 to 1.12)

Abbreviations: APR, adjusted prevalence ratio; CI, confidence interval; GED, General Education Development.

aMeet both physical activity and sleep duration recommendations. bMeet physical activity recommendations only. cMeet sleep duration recommendations only. dMeet neither physical activity nor sleep duration recommendation. eStudent; home maker/parental leave; due to disability/poor health/other.

Table 3

Direction and Magnitude of Sociodemographic and Health Correlates of Activity-Sleep Groups

Reference group: Meet bothaMeet PA onlybMeet sleep onlycMeet neitherd
Age (per 10 y)nsns+
Gender(ref: male)RefRefRef
 Femalens+++
Marital status (ref: married)RefRefRef
 Widowed/divorced/separated++ns
 Never married/unknownns
Ethnicity/ race (ref: non-Hispanic white)RefRefRef
 Hispanicnsnsns
 Non-Hispanic black++++ns++
 Other race/ethnicity+++++
Education (ref: Bachelor’s degree or higher)RefRefRef
 Some college/ associate degree++++++
 High school or GED++++++++
 Did not complete high school++++++++
Annual income (ref: >$75,000)RefRefRef
 $35,000–$74,999ns+++
 $0–$34,999ns+++
Employment status (ref: retired)RefRefRef
 Employed++ns+
 Unemployednsnsns
 Not in workforceensnsns
Smoking status (ref: never smoker)RefRefRef
 Current smoker++++++++
 Former smokernsnsns
Alcohol consumption (ref: lifetime abstainer)RefRefRef
 Former drinker++nsns
 Light-to-moderate drinker+− −
 Heavy drinker++− −− −
Body mass index (ref: 18.5–24.9 kg/m2)RefRefRef
 <18.5 kg/m2− −+++
 25–29.9 kg/m2++ns+
 ≥30 kg/m2+++++++
Chronic disease (ref: no chronic disease)RefRefRef
 Has chronic disease+nsns
Self-rated health (ref: excellent-to-very good)RefRefRef
 Good++++++
 Fair-to-poor+++++++++
Psychological distress (ref: low distress)RefRefRef
 High distress++++ns+

Abbreviations: APR, adjusted prevalence ratios; PA, physical activity. Note: ns, not significant = APR 0.95−1.05; +, APR 1.06−1.09; ++, APR 1.10−1.19; +++, APR 1.20−1.29; ++++, APR ≥ 1.30; −, APR 0.90−0.94; − −, APR 0.80−0.89; − − −, APR 0.70−0.79.

aMeet both physical activity and sleep duration recommendations. bMeet physical activity recommendations only. cMeet sleep duration recommendations only. dMeet neither physical activity and sleep duration recommendation. eHome maker/parental leave, or due to disability/poor health/other.

P < .001 for all significant associations.

Meets PA Recommendations Only

Relative to the “meet both” group, the “meet PA only” group had a significantly higher prevalence of participants who were widowed; divorced or separated; with black or other ethnicity; with some college or an associate degree, high school or GED (General Education Development) diploma, or less than a high school diploma; who were employed; were current smokers; reported former, light to moderate or heavy alcohol consumption; had a BMI of 25.0 to 29.9 kg/m2 or ≥30 kg/m2; one chronic disease; good or fair-to-poor self-rated health; and high psychological distress relative to their respective reference categories (Tables 2 and 3).

Meets Sleep Recommendations Only

Relative to the “meet both” group, the “meet sleep only” group had a significantly higher prevalence of participants who were female; with “other” ethnicity; with a college or an associate degree, high school, or GED diploma, or less than a high school diploma; who earned $35,000 to $74,999 or $0 to $34,999; were employed; a current smoker; had a BMI < 18.5 or >30.0 kg/m2; and fair-to-poor or good self-rated health relative to their respective reference categories. There was also a significantly lower prevalence of participants who were never married and reported light-to-moderate or heavy alcohol consumption relative their respective reference categories (Tables 2 and 3).

Meets Neither PA nor Sleep Recommendations

Relative to the “meet both” group, the “meet neither” group had a significantly greater prevalence of participants who were older; female; with Hispanic, black, and other ethnicity; with a college or an associate degree, high school or GED diploma, or less than a high school diploma; who earned $35,000 to $74,999 or $0 to $34,999; were employed; were current smokers; had a BMI of 25.0 to 29.9 kg/m2 or ≥30 kg/m2; with good or fair-to-poor self-rated health; and high psychological distress relative to their respective reference categories. There was also a lower prevalence of participants who were never married and reported light-to-moderate or heavy alcohol consumption relative to their respective reference categories (Tables 2 and 3).

Discussion

This study aimed to describe the prevalence, temporal trends, and sociodemographic, biological, and health behavior correlates of 4 activity-sleep patterns in a representative sample of US adults between 2004 and 2018. A key finding was that only 15% of the US population met both the PA and sleep recommendations, indicating that a large proportion of the population could benefit from improving their PA participation, sleep duration, or both. Changes over time were small, and the number of participants in the “meet sleep only” group decreased by 6% from 2004 to 2018, with minor increases in the prevalence of the 3 other groups. There were many sociodemographic, biological, and health behavior correlates of the activity-sleep pattern groups identified; however, the direction and magnitude of these associations differed between groups (Table 3). Given the different sociodemographic characteristics of those who “meet PA only,” “meet sleep only,” and “meet neither” in the population, there is a strong case for targeted public health interventions related to physical inactivity and sleep in our community, which resonate more strongly with the relevant groups impacted.

The prevalence of meeting the combined PA guidelines (ie, both aerobic and muscle-strengthening activity recommendations) has previously been found to have increased between 2008 and 2018 in the NHIS sample.17 This observation is consistent with the findings of the current paper, and both groups which met PA recommendations (“meet both” and “meet PA only”) increased slightly between 2004 and 2018. While this increase in the prevalence of meeting PA guidelines is positive, those who do not concurrently also meet the sleep recommendations have a significantly higher prevalence of chronic disease and high levels of psychological distress. This is in line with other papers where those with high levels of PA, but short or long sleep, have significantly higher risk of poor health outcomes than those with high PA and recommended sleep duration.44,45

Another study that also utilized the NHIS data found that the prevalence of meeting sleep duration recommendations decreased between 2014 and 2017 and that over time, black and Hispanic participants were increasingly more likely to report short sleep than white participants.18 As expected, this is in overall agreement with the findings of the current paper; however, a difference in trends for meeting the sleep duration recommendation was not found for black participants in the current study, perhaps due to the pooling of long and short sleep duration. Overall, there is a net decrease in participants who met the sleep duration recommendations, versus a net increase in participants who met the combined PA recommendations. This may reflect fewer public health campaigns targeting improved sleep relative to improved PA in recent years, and those campaigns targeting sleep are still being refined.4648 The more favorable health profile of those who meet both the PA and sleep recommendations relative to those who meet the PA recommendation only or meet neither recommendation is consistent with studies examining the prospective association of joint PA and sleep on mortality and other health outcomes.15,49 Further investment in educating the population on the importance of appropriate sleep duration and practical strategies on how to obtain the recommended amount of sleep are needed.50

A study that assessed associations of meeting the combined PA guidelines in another large US population-based sample also found the estimated prevalence of meeting the combined PA guidelines was greater in certain population subgroups.16 The findings largely align with the correlations found for the “meet both” group versus the other groups in the current study. However, the current study adds the ability to distinguish between those who concurrently met the PA and sleep duration guidelines and those who met PA guidelines but did not meet sleep duration guidelines. A key difference between these 2 groups was that the participants who only met the PA recommendation had a significantly greater prevalence of participants who were black and had a chronic disease and high psychological distress than those who met both recommendations, despite these 2 groups having a similar profile in terms of age, gender, and income (Tables 2 and 3). Previous research has also shown that the increased prevalence of short sleep duration for black populations persists despite adjusting for relevant confounders such as socioeconomic factors,5154 as well as research reporting disparities in physical and psychological health in black versus white populations even after adjusting for socioeconomic factors.55,56 This may point to challenges beyond lack of awareness surrounding the importance of sleep being the driver behind their lower adherence to sleep guidelines in this population, and research suggests broader socio-ecological factors may play a part in sleep difficulties.57 While the proportion of the sample who only meet the PA recommendation is relatively small (∼8%), they have a greater prevalence of physical and mental health concerns, which warrants further investigation. Additionally, PA is associated with better sleep in the general adult population, but a recent systematic review highlighted the lack of research into whether this effect is modified by demographic factors such as ethnicity,58 which highlights that this is an area in need of further study.

Overall, while a greater proportion of the sample met the sleep duration recommendation than the PA recommendations (65%), a minority (15%) met both PA and sleep recommendations concurrently. We call for future public health interventions that highlight the importance of achieving multiple positive health behaviors simultaneously, as these may be more effective in improving and sustaining population health than those focusing on individual behaviors. However, specific populations may experience different barriers to achieving sufficient PA or sleep, and further research is required to expand our understanding of how interventions can be tailored based on population characteristics.

This study had several strengths, including a large, nationally representative sample with consistent measurement methods and an extensive range of covariates, and examining trends over 15 years. However, all variables were self-reported, which may introduce bias and error. Differential associations between short and long sleepers may have been missed as short and long sleep duration was combined. This was done as only a small proportion of the sample reported long sleep, and to limit the number of behavior pattern combinations. The present study only used self-reported habitual sleep duration, though it is increasingly recognized that multiple additional dimensions of sleep are important to health.59 A further limitation was that the NHIS-PA questionnaire asked about “light- and moderate-” intensity activity combined, which is not in line with the PA guideline recommending ≥150 minutes of “moderate to vigorous” PA per week, and aerobic PA may have been overestimated. The NHIS-PA questionnaire also asks respondents to only report PA that is ≥10 minutes in duration, in accordance with the 2004 PA guidelines. However, the 2018 US PA guidelines do not stipulate a minimum time for an aerobic PA bout, and aerobic PA may have been underestimated. Both these limitations may have led to the associations in the present study being weakened due to incorrect categorization of participants as meeting or not meeting aerobic PA recommendations.

Conclusion

Among a large representative sample of US adults, most do not meet the combined PA and sleep duration recommendations, and those who do not meet both recommendations report poorer health characteristics. Public health campaigns emphasizing the importance of both sufficient PA and sleep should target women and older adults, current smokers, and those with lower education and poorer physical and mental health, as well as consider specific barriers experienced by minority ethnic groups.

Acknowledgments

M.J.D. was supported by a Career Development Fellowship (APP1141606) from the National Health and Medical Research Council.

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Oftedal, Holliday, and Duncan are with the School of Medicine & Public Health, College of Health, Medicine and Wellness, The University of Newcastle, Callaghan, NSW, Australia. Oftedal and Duncan are also with the Priority Research Centre for Physical Activity and Nutrition, The University of Newcastle, Callaghan, NSW, Australia. Reynolds is with the Flinders Health and Medical Research Institute (Sleep Health)/Adelaide Institute for Sleep Health, College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia. Bennie is with the Physically Active Lifestyles Research Group (USQ PALs), Institute for Resilient Regions, University of Southern Queensland, Springfield, QLD, Australia. Kline is with the Department of Health and Human Development, University of Pittsburgh, Pittsburgh, PA, USA.

Oftedal (stina.oftedal@newcastle.edu.au) is corresponding author.
  • Collapse
  • Expand
  • Figure 1

    —Sample selection NHIS 2004–2018 (unweighted sample sizes). NHIS indicates National Health Interview Survey.

  • Figure 2

    —Adjusted and weighted proportions of sample within each combination of physical activity level and sleep duration between 2004 and 2018. “Meet both”: meet both physical activity and sleep duration recommendations. “Meet PA only”: meet physical activity recommendations only. “Meet sleep only”: meet sleep duration recommendations only. “Meet neither”: meet neither physical activity nor sleep duration recommendation. Change between 2004 and 2018: “meet both”: 3.3% (95% CI, 2.5 to 4.2), “meet PA only”: 1.8% (95% CI, 0.1 to 2.4), “meet sleep only”: −6.2% (95% CI, −7.5 to −5.0), and “meet neither”: 1.9% (95% CI, 0.1 to 2.9). CI indicates confidence interval; PA, physical activity.

  • 1.

    Woodcock J, Franco OH, Orsini N, Roberts I. Non-vigorous physical activity and all-cause mortality: systematic review and meta-analysis of cohort studies. Int J Epidemiol. 2010;40(1):121138. PubMed ID: 20630992 doi:10.1093/ije/dyq104

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    Wahid A, Manek N, Nichols M, et al. Quantifying the association between physical activity and cardiovascular disease and diabetes: a systematic review and meta‐analysis. J Am Heart Ass. 2016;5(9):e002495. doi:10.1161/JAHA.115.002495

    • Search Google Scholar
    • Export Citation
  • 3.

    Mammen G, Faulkner G. Physical activity and the prevention of depression: a systematic review of prospective studies. Am J Prev Med. 2013;45(5):649657. PubMed ID: 24139780 doi:10.1016/j.amepre.2013.08.001

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    Itani O, Jike M, Watanabe N, Kaneita Y. Short sleep duration and health outcomes: a systematic review, meta-analysis, and meta-regression. Sleep Med. 2017;32:246256. PubMed ID: 27743803 doi:10.1016/j.sleep.2016.08.006

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Jike M, Itani O, Watanabe N, Buysse DJ, Kaneita Y. Long sleep duration and health outcomes: a systematic review, meta-analysis and meta-regression. Sleep Med Rev. 2018;39:2536. PubMed ID: 28890167 doi:10.1016/j.smrv.2017.06.011

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6.

    Kwok CS, Kontopantelis E, Kuligowski G, et al. Self-reported sleep duration and quality and cardiovascular disease and mortality: a dose-response meta-analysis. J Am Heart Ass. 2018;7(15):e008552. doi:10.1161/JAHA.118.008552

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