The Association of Sedentary Behavior with OSA: A Cross-Sectional Study from NHANES (2007-2008 to 2015-2020)

doi:10.21203/rs.3.rs-3362380/v1

Background

Sedentary behavior (SB) may contribute to obesity and lower extremity fluid retention, which may favor the development of obstructive sleep apnea (OSA). However, linking sedentary behavior to OSA is unclear. The purpose of this study was to determine if there is an association between SB and OSA.

Methods

This secondary analysis included National Health and Nutrition Examination Survey (NHANES) participants (unweighted = 20,727). Weighted sample and multiple logistic regression complex sample analysis techniques were used in this study. Three typical questions for the assessment of OSA have been used in the NHANES questionnaire. A physical activity questionnaire was used to assess SB.

Results

After adjustment for confounders, participants with SB(> 8h/d) had a higher risk of OSA(OR = 1.247,95%CI(1.100-1.414),P = 0.001) compared to SB(0-4h/d). Stratified analysis by gender showed that there was no significant correlation of SB and OSA in men. However, in women, with SB(0-4h/d) as reference, participants with SB(> 8h/d) had a higher risk of OSA (OR = 1.443,95%CI(1.210–1.722),P < 0.001).

Conclusion

Analysis in this study showed a positive correlation between SB and OSA, more pronounced in women. To reduce the risk of OSA, a healthy lifestyle is recommended.

Sedentary Behavior(SB)

Obstructive Sleep Apnea(OSA)

NHANES

Obstructive sleep apnea (OSA) is a condition in which the upper airway repeatedly collapses or completely blocks during sleep. The manifestations of OSA are characterized by a lack of specificity and include snoring, arousals, apneas, and excessive daytime sleepiness (1). Worldwide, 1 billion people between the ages of 30 and 69 may have the disease, according to a recent epidemiological study. Approximately 425 million people are believed to have moderate to severe OSA, which is generally recommended for treatment (2). OSA is generally not well understood in developing countries, and diagnostic and therapeutic modalities are unavailable or not modified for resource-limited settings (3). Approximately $12.4 billion was spent in the United States in 2015 to diagnose and treat OSA (4).

Significant neurocognitive and cardiovascular sequelae are also associated with OSA (5). In humans, physical inactivity affects health. Specifically, sedentary behavior (SB), defined as reclining or sitting and low energy activities such as computer use, driving, screen time and reading (6), Plays a major role in developing CVD(7). Previous epidemiologic studies have shown conflicting results on this issue, with some studies suggesting a positive association(8–10) and others finding no association(11). Saurabh S Thosar et al. argued that shorter sleep was predictive of more time spent sitting during the next day in healthy middle-aged adults, but not in leep apnea patients (12). However, previous studies had a relatively small sample sizes or inadequate adjustment for important confounders (physical activity, BMI, sleep duration eta). In addition, as far as we know, there is little evidence to suggest an association. Therefore, in this study, the purpose of this study was to investigate the correlation of SB with OSA using the National Health and Nutrition Examination Survey (NHANES).

Population of the study

The data analyzed in this study were designed to assess the health and nutritional status of adults and children in the United States from the National Health and Nutrition Examination Survey (NHANES). Since 1999, data have been collected in 2-year cycles by the National Center for Health Statistics (NCHS). The NHANES information collection and methodology have been detailedly elaborated on the website(http://www.cdc.gov/nchs/nhanes.htm), which is accessible(13).

Data from 4 cycles (2007–2008、2015–2020) with a total of 35,680 subjects were analyzed. There were 14,320 samples with missing OSA data that were excluded in my study. Additionally, 633 participants were excluded. These participants had incomplete data on SB. The final sample analyzed in this study was 20,727, all of whom were 16 years of age or older. The flow chart for population screening is as follows. (Fig. 1)

Obstructive Sleep Apnea (OSA)

Obstructive sleep apnea (OSA), according to a previous report, was defined as participants answering “yes” to at least one of the following three NHANES dichotomous questions (14): ①Feeling excessively sleepy during the day 16–30 times per month despite sleeping approximately 7 or more hours per night on weekdays or work nights; ②Gasping, snorting or stopping breathing 3 or more nights per week; ③Snoring 3 or more nights per week.

Sedentary behavior (SB)

The assessment of sedentary behavior in NHANES was a self-report question. The specific question was as follows: getting to and from places, at home, sitting at school, or with friends, including time spent sitting at a desk, reading, traveling in a car or bus, playing cards, watching television, or using a computer. It doesn't account for time spent sleeping. How much time do you usually spend in a sitting position and how much in a lying position on a typical day. Specifically, the above question includes only sitting in the 2015–2020 cycles and refers to sitting or reclining in the 2007–2008 cycles of NHANES. Self-reported sitting or reclining time was classfied as quartiles of < 4 h/d, 4 to < 6 h/d, 6 to 8 h/d, and > 8 h/d(15).

Assessment of other covariates

On the basis of clinical judgment and previous research (13), the following covariates were included: age (year), sex (male/female), race/ethnicity (non-Hispanic black, Mexican American, non-Hispanic white, other race/ethnicity), education level (less than high school, high school, college or more), marital status (never married, married/cohabiting, widowed/separated/divorced), poverty income ratio (PIR). BMI (the measured weight in kilograms is divided by the measured height in meters squared) was divided into three groups (< 25.0, 25.0-<30.0, ≥ 30.0)(16). Smoking status was categorized as never smoker (smoked < 100 cigarettes in lifetime), former smoker (smoked > 100 cigarettes but currently quit smoking), current smoker (smoked > 100 cigarettes and currently smoking)(17). According to past research(18), we defined moderate drinking as 14 or fewer drinks/week for men or 7 or fewer drinks/week for women or 5 or fewer drinks/day on any single day in the past year for bothr men and women. Similarily, we defined heavy drinking as more than 14 drinks/week for men or more than 7 drinks/week for women or 5 or more drinks/day on any single day at least once in the past year for either men or women(18). Physical activity (PA) was categorized as vigorous/moderate exercise (more than 150 minutes/week of moderate-intensity aerobic activity or 75 minutes/week of vigorous-intensity aerobic activity or an equivalent combination of moderate and vigorous activity (1 minute of vigorous-intensity activity is equivalent to 2 minutes of moderate-intensity activity) for a total of at least 150 minutes/week), light activity (less than 150 minutes/week of moderate-intensity aerobic activity or equivalent status)(19). Sleep duration was categorized as inadequate(<7h/d), recommended(7-9h/d), excessive sleep duration(>9h/d)(18). Hypertension and diabetes are also included in the study as covariates. Based on recent research(20), hypertension was either determined by blood pressure measured in NHANES (≥ 130 mm Hg (systolic) or ≥ 80 mm Hg (diastolic)) or self-reported by participants who were diagnosed by a healthcare professional. A history of diabetes was self-reported by participants who were diagnosed by a healthcare professional a health professional or determined by reviewing prescriptions for medications used to treat diabetes.

Statistical Analysis

Both descriptive and regression analyses using weighted samples were conducted in this study. Descriptive analysis expressed categorical variables as weighted percentages (%) with 95% confidence intervals. To calculate the percentages of categorical variables between the groups with and without OSA, weighted chi-squared tests were performed. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for associations between sedentary behavior (SB) and obstructive sleep apnea (OSA) by constructing three multivariable logistic regression models. In model 1, no covariates were adjusted. In model 2, age, sex, and race/ethnicity were adjusted. In model 3, age, sex, race/ethnicity, PA, smoking, drinking, sleep duration, BMI, PIR, education level, and marital status were adjusted. Sedentary behavior was categorized into four levels, and the lowest level was used as the reference. Subgroup analyses stratified by sex were also performed. We conducted all analyses in Stata version 16.0. To account for the sampling design, sample interview weights were applied. P value <0.05 is statistically significant.

Participants' baseline characteristics

Overall, 20,727 participants were eligible for final analysis, and the weighted population was 169,595,999. The individual characteristics of the subjects with and without OSA are shown in Table 1. Of the 20,727 participants analyzed, 10,794 individuals were included in the OSA group and the weighted prevalence was 52.08%. 47.24% of the participants were younger than 44 years and 51.29% were female. In both OSA and non-OSA groups, sex, age, education level, marital status, PIR, alcohol consumption, BMI, HBP, diabetes, PA, SB, sleep duration and smoking were significantly different. Those diagnosed with OSA , According to Table 1, were more likely to be male, younger than 44 years, have a college degree or higher, be married or living with a partner, have a higher PIR, be heavy drinkers, be obese, have a history of HBP or diabetes, engage in moderate to vigorous exercise, sit or recline for 6-8 hours per day, sleep for 7-9 hours per day, and be nonsmokers.

TABLE 1. Baseline participant characteristics(N=20,727)
		Obstructive sleep apnea(OSA)
Characteristics	Total(N=20,727)	No (N=9,933)	Yes(N=10,794)	P-value
Sex				<0.00001
Male	48.71(47.74-49.67)	43.53(42.17-44.91)	53.71(52.37-55.05)
Female	51.29(50.33-52.26)	56.47(55.09-57.83)	46.29(44.95-47.63)
Age				<0.00001
＜44	47.24(46.28-48.20)	54.95(53.57-56.33)	39.78(38.48-41.09)
[44,60)	28.14(27.24-29.07)	23.01(21.78-24.29)	33.11(31.80-34.44)
＞60	24.62(23.82-25.43)	22.03(20.94-23.16)	27.12(25.98-28.29)
Race/Ethnicity				0.52725
Non–hispanic White	64.68(63.88-65.47)	64.81(63.67-65.93)	64.56(63.44-65.66)
Non–hispanic Black	11.39(11.00-11.78)	11.34(10.79-11.90)	11.44(10.9-12.00)
Mexican American	8.75(8.40-9.11)	8.48(7.98-9.00)	9.01(8.51-9.52)
Other Race/ethnicity	15.18(14.65-15.74)	15.38(14.61-16.17)	15.00(14.26-15.77)
Education level				<0.00001
Below high school	13.86(13.33-14.40)	11.84(11.16-12.56)	15.80(15.01-16.63)
High school	22.80(22.00-23.62)	20.48(19.40-21.59)	25.05(23.88-26.25)
College or above	57.87(56.94-58.79)	59.52(58.21-60.82)	56.26(54.94-57.58)
Marital status				<0.00001
Never married	17.00(16.30-17.73)	20.35(19.27-21.47)	13.76(12.88-14.69)
Married/living with partner	61.68(60.77-62.59)	57.05(55.70-58.39)	66.16(64.92-67.38)
Widowed/divorced/Separated	15.84(15.20-16.51)	14.44(13.56-15.37)	17.19(16.27-18.16)
PIR				0.00894
＜1	12.69(12.19-13.22)	12.85(12.13-13.60)	12.54(11.84-13.29)
[1, 3)	32.49(31.65-33.35)	31.40(30.21-32.61)	33.56(32.36-34.77)
≥3	45.50(44.52-46.49)	46.14(44.74-47.55)	44.88(43.50-46.26)
Alcohol Drinkers				<0.00001
Non-drinkers	9.28(8.79-9.79)	10.71(9.96-11.50)	7.90(7.28-8.56)
Moderate alcohol use	37.50(36.56-38.45)	35.80(34.48-37.16)	39.14(37.82-40.47)
Heavy alcohol use	38.51(37.56-39.46)	36.35(35.02-37.71)	40.59(39.26-41.93)
BMI				<0.00001
＜25	28.53(27.66-29.41)	38.36(37.02-39.72)	19.01(17.97-20.10)
[25,30)	30.10(29.22-31.00)	30.37(29.11-31.66)	29.84(28.63-31.09)
≥30	35.47(34.55-36.40)	24.96(23.80-26.15)	45.64(44.30-46.99)
HBP				<0.00001
No	47.26(46.30-48.23)	55.59(54.22-56.94)	39.21(37.89-40.55)
Yes	45.83(44.87-46.79)	36.36(35.05-37.68)	54.99(53.64-56.33)
Diabetes				<0.00001
No	6.95(6.45-7.48)	5.63(5.00-6.33)	8.23(7.48-9.04)
Yes	10.57(10.03-11.14)	7.62(6.96-8.34)	13.43(12.59-14.32)
PA				<0.00001
Light	24.16(23.30-25.04)	26.11(24.85-27.40)	22.28(21.12-23.49)
(Continued)
TABLE1.Continued
		Obstructive sleep apnea(OSA)
Characteristics	Total(N=20,727)	No (N=9,933)	Yes(N=10,794)	P-value
Moderate to Vigorous	29.74(28.85-30.65)	33.13(31.82-34.46)	26.46(25.26-27.70)
SB				0.00097
＜4h	25.60(24.81-26.41)	26.30(25.17-27.47)	24.92(23.84-26.05)
4 to＜6h	24.49(23.67-25.33)	24.78(23.61-25.99)	24.21(23.07-25.39)
6 to 8h	27.89(27.02-28.77)	28.03(26.79-29.30)	27.75(26.55-28.99)
＞8h	22.02(21.19-22.87)	20.89(19.73-22.09)	23.11(21.95-24.32)
Sleep Duration				<0.00001
＜7h	26.04(25.22-26.87)	21.84(20.74-22.97)	30.10(28.90-31.33)
[7,9]	65.79(64.90-66.68)	69.18(67.93-70.40)	62.52(61.23-63.79)
＞9h	7.86(7.41-8.35)	8.70(8.03-9.43)	7.05(6.46-7.70)
Smokers				<0.00001
Never smoker	54.76(53.79-55.72)	59.84(58.49-61.18)	49.84(48.49-51.19)
Former smoker	23.41(22.58-24.27)	19.94(18.82-21.11)	26.77(25.55-28.02)
Current smoker	18.21(17.50-18.95)	14.76(13.84-15.73)	21.55(20.48-22.67)

Values are expressed as % (95% CI) for categorical variables. p Value was calculated using the weighted chi-squared test for categorical variables.

PIR= Poverty in ratio; BMI=Body Mass Indes; HBP=High Blood Pressure; SB=Sedentary Behavior; PA=Physical Activity; CI=Confidence Interval.

Numbers that do not add up to 100% are attributable to missing data.

Associations of SB with OSA

Three sets of weighted logistic regression models were constructed. The relationship between sedentary behavior and OSA is shown in Table 2. In model Ⅰ, adjusted for no covariates; in model Ⅱ, adjusted for age, sex, and race/ethnicity; in model Ⅲ, adjusted for age, sex, race/ethnicity, education level, BMI, physical activity, PIR, alcohol status, smoking status, marital status, and sleep duration. In modelⅠ, with SB <4h/d as a reference, participants with SB >8h/d had a higher OR=1.168 for OSA and 95%CI (1.043-1.307)(p=0.007). However, this correlation was not significant in participants with SB 4 to 6h/d(OR=1.031,95%CI(0.928-1.145),P=0.571) and 6 to 8h/d(OR=1.045,95%CI(0.943-1.157),P=0.401). Furthermore, the trends remained the same after adjustment for age, sex, and race (modelⅡ). When further adjusted for education level, physical activity, smoking status, BMI, PIR, drinking status, marital status, and sleep duration (modelⅢ), the OR was 1.247 and 95%CI(1.100-1.414)(0.001). Prolonged sedentary behavior had a positive association with OSA.

Table 2. The association between Sedentary Behavior and OSA.
	Model Ⅰ OR(95%CI)p-value	Model Ⅱ OR(95%CI)p-value	Model Ⅲ OR(95%CI)p-value
Sedentary Behavior（hours/day）
0 to<4	reference	reference	reference
4 to<6	1.031(0.928-1.145)0.571	1.016(0.913-1.132)0.766	1.063(0.950-1.189)0.290
6 to 8	1.045(0.943-1.157)0.401	1.034(0.932-1.148)0.526	1.066(0.954-1.192)0.257
>8	1.168(1.043-1.307)0.007	1.183(1.053-1.330)0.005	1.247(1.100-1.414)0.001
P for trend	<0.001	<0.001	<0.001
OR, odds ratio; CI, confidence intervals; OSA, Obstructive sleep apnea. Model Ⅰ: adjusted for no covariates. Model Ⅱ: adjusted for age, sex, and race/ethnicity. Model Ⅲ: adjusted for age, sex, race/ethnicity, education level, BMI, physical activity, PIR, alcohol status, smoking status, marital status, and sleep duration.

We also analyzed the associations of sedentary behavior with OSA by sex. However, the association was not significant in men(P＞0.05) when stratified by sex (Table 3). Consistent with the overall analysis, among women, with SB less than 4h/d as reference, participants with SB more than 8h/d had a higher OR=1.443 for OSA and 95%CI (1.21-1.722)(P＜0.001) in model Ⅲ. Association of sedentary behavior with OSA varied by gender. Among those who were sedentary for >8h/d, female gender was significantly associated with higher OSA risk. Sitting or reclining for >8h is a risk factor for OSA in women.

Table 3. The association between Sedentary Behavior and OSA by gender.
	Model Ⅰ OR(95%CI)p-value	Model Ⅱ OR(95%CI)p-value	Model Ⅲ OR(95%CI)p-value
Stratified by gender
Men(n=10209)
0 to<4	reference	reference	reference
4 to<6	0.938(0.807-1.090)0.403	0.909(0.780-1.061)0.228	0.903(0.768-1.062)0.220
6 to 8	0.959(0.826-1.112)0.578	0.927(0.797-1.078)0.323	0.937(0.797-1.102)0.431
>8	0.984(0.835-1.159)0.848	0.965(0.816-1.142)0.680	1.002(0.836-1.201)0.985
Women(n=10518)
0 to<4	reference	reference	reference
4 to<6	1.129(0.974-1.307)0.106	1.125(0.967-1.307)0.126	1.203(1.028-1.407)0.021
6 to 8	1.139(0.988-1.311)0.072	1.140(0.985-1.320)0.079	1.149(0.985-1.341)0.078
>8	1.377(1.178-1.608)<0.001	1.428(1.214-1.679)<0.001	1.443(1.21-1.722)<0.001
OR, odds ratio; CI, confidence intervals; OSA, Obstructive sleep apnea. Model Ⅰ: adjusted for no covariates. Model Ⅱ: adjusted for age, sex, and race/ethnicity. Model Ⅲ: adjusted for age, sex, race/ethnicity, education level, BMI, physical activity, PIR, alcohol status, smoking status, marital status, and sleep duration. The model was not adjusted for the stratification variable itself in the subgroup analysis by sex.

We aimed to investigate the correlation of sedentary behavior with OSA, and the results showed that sedentary behavior may be associated with OSA. Furthermore, after adjusting for important confounders, participants in the group with SB (> 8h/d) had a 1.247 times higher risk of OSA than others with SB (< 4h/d). This finding is in agreement with previous studies(8–10). Although some studies have suggested that SB and OSA are not linked (11), we believe that the reason for this difference may be due to different screening tools. Interestingly, sitting for < 8h/d has no significant effect on OSA, whereas sitting for > 8h/d increases the risk of OSA over time, which was not observed in the previous study.

Rostral fluid shift plays critical role in OSA and central sleep apnea(CSA) progression(21). When you lie in bed during the night, body fluid flows to the neck, increasing the resistance of the UA and causing the UA to collapse, exacerbating OSA. (22). In the population, the severity of OSA is related to posture in 50% of patients (23).We followed the established definition of SB in this study(6) and in addition to contributing to obesity, excessive sitting during the day can lead to fluid retention in the lower body, especially in the legs(24). we consider that the underlying mechanism of SB associated with OSA is that SB cause fluid accumulation in the lower limbs, which promotes the development of OSA during sleep due to rostral fluid shift.

More importantly, there was another notable finding in our study. After stratifying by gender, we found that the association between sedentary behavior and OSA differed by gender. Among those who were sedentary for > 8h/d, being female was significantly associated with a higher risk of OSA. Again, we confirmed a prospective study with similar findings(10). Our study supports that OSA is more common in men(25), while the results of this study also suggest that the association of sedentary behavior with OSA is more pronounced in women. With regard to the latter, the reason for this difference may be the higher estrogen levels in women and warrants further investigation.

There are several strengths in our study. We used the large, representative NHANES population. In addition, the study adjusted for potential social demographic and lifestyle confounders to obtain more robust results. Furthermore, we use weighted sample analyses to examine the association. On this basis, the results were more generalizable. At the same time, several limitations should be noted when interpreting this article. First, we diagnose OSA on the basis of some typical symptoms found in NHANES questionnaire, such as daytime sleepiness, apnea, snoring, etc., so there may be some patients who were not included in the analysis, but using the NHANES database, there have been several studies of OSA(26). Second, the associations varied by sex and the interpretation of these findings is unclear and requires further study. Finally, We cannot establish causality on the basis of this cross-sectional study, and further prospective cohort studies will be necessary to confirm a causal relationship. In our study, the prevalence of OSA in Americans aged 16 years and older is 52.08%, which is much higher than the worldwide OSA prevalent(27). Different screening tools for OSA may be the cause of this phenomenon, but it still underscores the importance of preventing OSA.

In conclusion, our study demonstrated a positive association of SB with OSA after adjustment for anthropometric and clinical potential confounders. Furthermore, the positive effect of SB on OSA was more significant in women. Because the cross-sectional study could not prove causality, to explore the mechanisms underlying the positive association between SB and OSA, further studies are needed.

Acknowledgments

We appreciate the efforts given by participants in the NHANES project.

Funding

This study was supported by the Guiyang Science and Technology Plan Project (Efect of adenoid or tonsil hypertrophy on three-dimensional morphology of palate and its correlation [2023]48-28), and the Guiyang Health and Family Planning Commission (A preliminary study on the position analysis of CR and CO disordered condyle in adult patients with mandibular retraction [2015]041).

Author information

Authors and Affiliations

School of Stomatology, Zunyi Medical University, Zunyi, Guizhou, China

Song Cai, SiYu Li, YaShi Zhou, JuXiang Peng.

Guiyang Stomatological Hospital affiliated to Zunyi Medical University, Guiyang, Guizhou, China.

Song Cai, SiYu Li, YaShi Zhou, JuXiang Peng.

Department of Oral and Maxillofacial Surgery, The Affiliated Stomatological Hospital of Guizhou Medical University, Guiyang, Guizhou, China

JuKun Song

Contributions

Song Cai: Idea hypothesis, find data, data analysis, wrote the manuscript. SiYu Li: Find data, experimental design, proofreading of manuscript. YaShi Zhou: Find data, proofreading of the manuscript. JuKun Song: Proofreading of manuscript, statistical analysis. JuXiang Peng: Statistical analysis, proofreading of the manuscript, major contribution to the discussion.

Corresponding authors

Please correspondence to JuXiang Peng or JuKun Song. Among the corresponding authors, the contribution of JuXiang Peng is greater, followed by JuKun Song.

Statement of Ethics

Conflict of Interest

We emphasize there is no conflict of interest in this study.

Approval of ethics

The NCHS Research Ethics Review Board (ERB) reviewed and approved studies involving human participants.

Informed consent

In accordance with national legislation and institutional requirements, written informed consent was not required for participation in this study.

Data availability

The study analysed publicly available data, which is available here: https://www.cdc.gov/nchs/nhanes/index.htm.

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No competing interests reported.

The Association of Sedentary Behavior with OSA: A Cross-Sectional Study from NHANES (2007-2008 to 2015-2020)

Status:

Journal Publication

Version 1

Abstract

Background

Methods

Results

Conclusion

Figures

Introduction

Materials and methods

Population of the study

Obstructive Sleep Apnea (OSA)

Sedentary behavior (SB)

Assessment of other covariates

Statistical Analysis

Result

Discussion

Conclusion

Declarations

References

Additional Declarations

Status:

Journal Publication

Version 1