DOI: https://doi.org/10.21203/rs.3.rs-2853657/v1
Olfactory is closely associated with many diseases, and sleep is the foundation of good health. While the relationship between sleep and olfactory has been reported in numerous studies, there has been relatively little research on whether sleep duration has an effect on smell, so we aimed to evaluate the relationship between sleep duration and olfactory. This study used cross-sectional data from people over 40 years old who took part in the National Health and Nutrition Examination Survey between 2011 and 2012, collecting details on their severe sleep duration, self-report olfactory changes, and several other essential variables. There were 2844 participants, with 23.7% (675/2844) discovering olfactory alterations. Compared with individuals with less than 6 hours of sleep, the adjusted OR values for sleep duration and olfactory dysfunction in 6 to 8 hours of sleep, and more than 8 hours of sleep were 0.7 (95% CI: 0.56–0.88, p = 0.003), and 0.66 (95% CI: 0.52–0.85, p = 0.001), respectively. The association between sleep duration and olfactory dysfunction is an L-shaped curve (nonlinear, p = 0.023). The OR of developing migraine was 0.89 (95% CI: 0.801–0.996, p = 0.042) in participants with sleep seven hours/day. The link between sleep duration and olfactory dysfunction in US adults is L-shaped, with an inflection point of roughly 7 hours/day.
Olfaction plays an important role in the daily lives of patients, and a disturbance of the olfaction is generally felt as a severe decline in quality of life 1. About 22% of the general population complains of a lack of smell, and 5% of these people are anosmic2, 3. The coronavirus-19 (COVID-19) is not initially associated with olfactory or gustatory disorders, but recent reports suggest that these symptoms are prevalent in patients who suffer from the disease in Europe 4, 5. The COVID-19 pandemic has raised important concerns about the chemical senses. Risk factors for olfactory disorders such as age, heavy alcohol consumption, cigarettes, diabetes, neurodegenerative diseases, cancer, drugs, and trauma. Olfactory dysfunction is an early indicator of neurodegenerative diseases, including Alzheimer's, Parkinson's, and Huntington's 6, and also predicts mortality in cognitively intact older adults 7– 10. With olfaction being an indicator of neurodegeneration, aging, and death, it is important to determine the underlying mechanisms of these relationships to understand health trajectories.
Sleep is fundamental to a person's physical health. Generally speaking, the optimal
sleep time is about 6 to 8 hours11. As we know, unhealthy sleep habits can lead to several unhealthy effects. Studies have reported the relationship between sleep duration and health, such as cardiovascular disease, neurodegenerative disease, cognitive impairment, mortality, etc. Since sleep duration and olfactory impairment are also associated with health, we tried to explore whether sleep duration is also associated with olfactory dysfunction. Until now several studies have investigated the link between sleep disorders and Olfactory sensation. Previous studies have reported that sleep deprivation delays the regeneration of olfactory sensory neurons12, olfactory dysfunction, and probable rapid eye movement sleep behavior disorder with early Parkinson's disease progression13, sleep plays essential roles in olfactory system through circuit reorganization and memory consolidation14. This study focuses on the relationship between weekday sleep duration (including sleep deprivation and excessive sleep) and olfactory dysfunction, with the hope of reducing the occurrence of olfactory dysfunction to some extent.
In this study, data was obtained from the official NHANES website:HTTPS://www.cdc.Gov/nchs/nhanes/NHANES .We conducted a cross-sectional study among 2844 US adults aged ≥ 40 years old who enrolled in smell component in the National Health and Nutrition Examination Survey (NHANES) between 2011 and 2012 (Fig. 1). Participants were excluded if they were pregnant or breastfeeding. By National Institutes of Health policy, such analysis involving de-identified data that was not directly in contact with participants was not considered human subjects study and was not subject to institutional review board review.
A smell questionnaire was used to collect data on the perceived smell alterations, and the complete questionnaire, codebook, and data are publicly available on line. Self-reported smell alteration was defined based on three questions: if the individual had a problem smelling last year, had changed the ability to smell since 25, or had smelled phantom odor last year A positive response on any of these questions resulted in a positive score for olfactory alteration. The dichotomous measure [‘yes’ or ‘no’] for olfactory alteration was the outcome variable in data analyses. his classification has shown excellent test–retest reliability over 6 months15 and good correspondence with clinically supported risk factors.16Classification with this index has reasonable specificity (78. 1%) and modest sensitivity (54.4%) in the identification of anosmia/severe hyposmia using a single screening measure 17specificity/expected sensitivity profile of conditions such as olfactory dysfunction which are rarely measured.18
Participants self-reported the amount of sleep on the weekday or regular workday. In 2011–2012, sleep duration was created from a question asked of NHANES participants about participants' usual sleep hours: "How much sleep do you get (hours)?"For our study, we classified these according to the recommendations of the American National Sleep Foundation and previous studies into short sleep (< 6 h/d), regular sleep (6–8 h/d), and long sleep duration (≥ 8 h/d).
Demographic: Standardized questionnaires were used to collect information on age(years), s ex(male/female), race/ethnicity(Mexican American, other Hispanic, non-Hispanic white, non-Hispanic black or other), education(below high school high school and some college or above), marital status(married, living with a partner or not married), annual family income, smoking status, alcoholic intake, work activity, physical activity, and health report .The status of alcohol was established based on a question: "Had at least 12 alcoholic beverages per year?"Alcohol status was created from a question: “Had at least 12 alcohol drinks a year?” For work activity, the inactive group was defined as those who did not report leisure time work activity, the moderate and vigorous activity groups were created based on a question: “Does your work involve moderate-intensity activity that causes small increases in breathing or heart rate such as brisk walking or carrying light loads for at least 10 minutes continuously?” and “Does your work involve vigorous-intensity activity that causes large increases in breathing or heart rate like carrying or lifting heavy loads, digging or construction work for at least 10 minutes continuously?” respectively. For physical activity, the inactive group was defined as those with no reported leisure time physical activity, and the moderate and vigorous activity groups were created from a question: “In a typical week do you do any moderate-intensity sports, fitness, or recreational activities that cause a small increase in breathing or heart rate such as brisk walking, bicycling, swimming, or volleyball for at least 10 minutes continuously?” and “In a typical week do you do any vigorous-intensity sport s, fitness, or recreational activities that cause large increases in breathing or heart rate like running or basketball for at least 10 minutes continuously?” respectively.Self-control was dichotomic (excellent/very good/good versus fair/poor). The interview questions also focused on the life stories of the following individuals: tonsillectomy; persistent cold/flu in the past 12 months? loss of consciousness from head injury;broken nose or other serious injury to face or skull .Body mass index (BMI) was calculated by dividing weight in kilograms by height in meters squared (kg/m2) .According to the 2017 American College of Cardiology/American Heart Association hypertension guidelines ,hypertension was defined as being currently taking antihypertensive drugs, or if not, having systolic blood pressure level ≥ 130mmHg and/or diastolic blood pressure level ≥ 80
mmHg19.Diabetes was defined as having been diagnosed with diabetes or currently taking insulin or taking diabetes pills, or having a hemoglobin A1c level ≥ 6.5% or fasting plasma glucose level ≥ 126 mg/dl21.Prediabetes was defined as the absence of diabetes but a hemoglobin A1c level of 5.7–6.4%, a fasting plasma glucose level of 100 mg/dl to 125 mg/dl, or a 2-hour plasma glucose level of 140 mg/dl to 199 mg/dl20.Dyslipidemia was defined as having a doctor's diagnosis or currently taking cholesterol-lowering drugs,or having a triglyceride level ≥ 150 mg/dl or high-density lipoprotein cholesterol level < 40 mg/dl based on recommendations by the National Cholesterol Education Program Adult Treatment Panel III21.
The data are expressed as the average standard deviation (SD) for continuous variables and the frequency or percentage of categorical variables.For baseline characteristics analysis, the statistical differences between olfactory dysfunction were tested with one-way ANOVA for continuous variables and chi-square test for categorical variables.Odds ratios (OR) and 95% CIs were calculated for OD incidents with sleep using logistic regression models.We used unadjusted and multivariate adjusted models.In this study, the Logistic models were adjusted for sex, age, race, education, marital status, and annual family income, BMI, alcohol status, and smoking status, hypertension, diabetes, dyslipidemia, work activity, physical activity, broken nose or other serious injury to face or skull, tonsillectomy, loss of consciousness from head injury, cold/flu and self-rated fair/poor health.Tests for trend were conducted with linear regression by dividing sleep duration into three groups (< 6 hours, 6 to 8 hours, and ≥ 8 hours) as a continuous variable in the models.
A generalized additive model was used to evaluate the nonlinear relationship between sleep duration and OD. We further developed a two-piece wise linear regression model based on the smoothing curve to identify the threshold effect and adjust for potential confounders.The threshold level of sleep duration was determined using a recurrence method, including selecting the turning point along a predefined interval, and choosing the turning point that yielded the maximum likelihood model.A log-likelihood ratio test was used to compare the two-piece linear regression model with the one-line linear model.
All the analyses were performed with the statistical software packages R (http://www.R-project.org, The R Foundation) and Free Statistics software versions 1.7 .A two-sided P value < 0.05 was considered to be statistically significant.
The 2844 participants included in the study were 1,465 women (51.5%) and 1,379 men (48.5%), with an average age (SD) of 59 6 ( 11.9) years.Participants with self-reported OD were more likely to be female, low annual family income, former smokers, hypertensive, dyslipidemia, non-diabetic, non-prediabetes and to drink more alcohol.Adults who had an Excellent/ Very Good/ Good Health self-evaluation had significantly.
greater reported frequency of olfactory alteration.In addition, a higher frequency of olfactory alteration has been reported in people with a history of severe loss of consciousness following a tonsillectomy caused by a persistent cold or flu and a serious head or face injury.Short sleep duration patients have higher chance of olfactory dysfunction.The subjects' baseline characteristics are summarized in Table 1.Univariate analysis demonstrated that age, annual family income, smoking, work activity, BMI, self-reported dyslipidemia, tonsillectomy, persistent cold or flu lasted 12 months? loss of consciousness from head injury, broken nose or other serious injury to face or skull were associated with migraines (Table 2).Table 3 presents the association between sleep duration and self-reported OD. The odds ratios (95% confidence intervals) of self-reported OD was different between mid-range and long sleep durations compared to short sleep durations. Adjusted OR values for self-reported ODs and duration of sleep are 0.77 (0.61 ~ 0.99, p = 0.039) and 0.69 (0.53 ~ 0.9, p = 0.006), respectively. This illustrated that OD incidence rose by 7% for every 1 h increase in sleep duration.
Table 1 Baseline characteristics of the study participants
|
Characteristics |
Self-Reported Olfactory Dysfunction |
|||
|
All participants (n = 2844) |
NO (n = 2169) |
YES (n = 675) |
p |
|
|
Gender n (%) |
|
|
0.84 |
|
|
Male |
1379 (48.5) |
1054 (48.6) |
325 (48.1) |
|
|
Female |
1465 (51.5) |
1115 (51.4) |
350 (51.9) |
|
|
Age(years), Mean ± SD |
59.6 ± 11.9 |
59.3 ± 12.0 |
60.5 ± 11.8 |
0.031 |
|
Race/ethnicity, n (%) |
|
|
0.02 |
|
|
Mexican American |
224 ( 7.9) |
168 (7.7) |
56 (8.3) |
|
|
Other Hispanic |
307 (10.8) |
232 (10.7) |
75 (11.1) |
|
|
Non-Hispanic White |
1133 (39.8) |
835 (38.5) |
298 (44.1) |
|
|
Non-Hispanic Black |
800 (28.1) |
624 (28.8) |
176 (26.1) |
|
|
Other Race |
380 (13.4) |
310 (14.3) |
70 (10.4) |
|
|
Education,n (%) |
|
|
0.291 |
|
|
below high school |
732 (25.7) |
544 (25.1) |
188 (27.9) |
|
|
high school |
626 (22.0) |
476 (21.9) |
150 (22.2) |
|
|
some college or above |
1486 (52.3) |
1149 (53) |
337 (49.9) |
|
|
Marital status,n (%) |
|
|
0.223 |
|
|
married |
2422 (85.2) |
1859 (85.7) |
563 (83.4) |
|
|
living with partner |
123 ( 4.3) |
94 (4.3) |
29 (4.3) |
|
|
not married |
299 (10.5) |
216 (10) |
83 (12.3) |
|
|
Annual family income (dollar), Median (IQR) |
7.0 (4.0, 12.0) |
7.0 (5.0, 13.0) |
6.0 (4.0, 10.0) |
< 0.001 |
|
Smoking status, n (%) |
|
|
0.003 |
|
|
Former smokers |
2309 (81.2) |
1787 (82.4) |
522 (77.3) |
|
|
Current smoking |
535 (18.8) |
382 (17.6) |
153 (22.7) |
|
|
Alcohol status, n (%) |
|
|
0.484 |
|
|
Yes |
1996 (70.2) |
1515 (69.8) |
481 (71.3) |
|
|
No |
848 (29.8) |
654 (30.2) |
194 (28.7) |
|
|
Work activity, n (%) |
|
|
0.138 |
|
|
Inactive |
1881 (66.1) |
1455 (67.1) |
426 (63.1) |
|
|
Moderate |
865 (30.4) |
639 (29.5) |
226 (33.5) |
|
|
Vigorous |
98 ( 3.4) |
75 (3.5) |
23 (3.4) |
|
|
Physical activity, n (%) |
|
|
0.134 |
|
|
Inactive |
1625 (57.1) |
1217 (56.1) |
408 (60.4) |
|
|
Moderate |
1104 (38.8) |
861 (39.7) |
243 (36) |
|
|
Vigorous |
115 ( 4.0) |
91 (4.2) |
24 (3.6) |
|
|
BMI (kg/m2 ), Mean ± SD |
29.5 ± 6.8 |
29.3 ± 6.8 |
29.9 ± 6.9 |
0.049 |
|
Hypertension, n (%) |
|
|
0.556 |
|
|
No |
945 (33.2) |
727 (33.5) |
218 (32.3) |
|
|
Yes |
1899 (66.8) |
1442 (66.5) |
457 (67.7) |
|
|
Dyslipidemia, n (%) |
|
|
< 0.001 |
|
|
No |
1114 (39.2) |
893 (41.2) |
221 (32.7) |
|
|
Yes |
1730 (60.8) |
1276 (58.8) |
454 (67.3) |
|
|
Diabetes, n (%) |
|
|
0.232 |
|
|
No |
2135 (75.1) |
1640 (75.6) |
495 (73.3) |
|
|
Yes |
709 (24.9) |
529 (24.4) |
180 (26.7) |
|
|
Prediabetes, n (%) |
|
|
0.783 |
|
|
No |
2558 (89.9) |
1949 (89.9) |
609 (90.2) |
|
|
Yes |
286 (10.1) |
220 (10.1) |
66 (9.8) |
|
|
Self-reported health condition , n (%) |
|
|
< 0.001 |
|
|
Excellent, very good, good |
2094 (73.6) |
1654 (76.3) |
440 (65.2) |
|
|
Fair, Poor |
750 (26.4) |
515 (23.7) |
235 (34.8) |
|
|
Cold/flu for >1 month, n (%) |
|
|
< 0.001 |
|
|
Yes |
179 ( 6.3) |
109 (5) |
70 (10.4) |
|
|
No |
2665 (93.7) |
2060 (95) |
605 (89.6) |
|
|
Tonsils removed, n (%) |
|
|
0.031 |
|
|
Yes |
703 (24.7) |
515 (23.7) |
188 (27.9) |
|
|
No |
2141 (75.3) |
1654 (76.3) |
487 (72.1) |
|
|
Loss of consciousness from head injury, n (%) |
|
|
< 0.001 |
|
|
Yes |
361 (12.7) |
238 (11) |
123 (18.2) |
|
|
No |
2483 (87.3) |
1931 (89) |
552 (81.8) |
|
|
Serious head/face injury, n (%) |
|
|
< 0.001 |
|
|
Yes |
418 (14.7) |
285 (13.1) |
133 (19.7) |
|
|
No |
2426 (85.3) |
1884 (86.9) |
542 (80.3) |
|
|
Sleep duration (hours), n (%) |
|
|
0.002 |
|
|
< 6 |
487 (17.1) |
342 (15.8) |
145(21.5) |
|
|
6 - 8 |
1389 (48.8) |
1071(49.4) |
318 (47.1) |
|
|
≥ 8 |
968( 34.0) |
756(34.9) |
212(31.4) |
|
Abbreviations: BMI, body mass index.
|
Variable |
OR_95CI |
P_value |
|---|---|---|
|
Gender |
||
|
Male |
Reference |
|
|
Female |
1.02 (0.86 ~ 1.21) |
0.84 |
|
Age |
1.01 (1 ~ 1.02) |
0.031 |
|
Race/ethnicity |
||
|
Mexican American |
Reference |
|
|
Other Hispanic |
0.97 (0.65 ~ 1.45) |
0.88 |
|
Non-Hispanic White |
1.07 (0.77 ~ 1.49) |
0.685 |
|
Non-Hispanic Black |
0.85 (0.6 ~ 1.2) |
0.343 |
|
Other Race |
0.68 (0.45 ~ 1.01) |
0.055 |
|
Education |
||
|
below high school |
Reference |
|
|
high school |
0.91 (0.71 ~ 1.17) |
0.465 |
|
some college or above |
0.85 (0.69 ~ 1.04) |
0.118 |
|
Marital status |
||
|
married |
Reference |
|
|
living with partner |
1.02 (0.66 ~ 1.56) |
0.932 |
|
not married |
1.27 (0.97 ~ 1.66) |
0.084 |
|
Annual family income |
0.96 (0.94 ~ 0.98) |
< 0.001 |
|
Smoking status |
||
|
Former smokers |
Reference |
|
|
Current smoking |
1.37 (1.11 ~ 1.69) |
0.003 |
|
Alcohol status |
||
|
Yes |
Reference |
|
|
No |
0.93 (0.77 ~ 1.13) |
0.484 |
|
Work activity |
||
|
Inactive |
Reference |
|
|
Moderate |
1.21 (1 ~ 1.46) |
0.047 |
|
Vigorous |
1.05 (0.65 ~ 1.69) |
0.85 |
|
Physical activity |
||
|
Inactive |
Reference |
|
|
Moderate |
0.84 (0.7 ~ 1.01) |
0.063 |
|
Vigorous |
0.79 (0.49 ~ 1.25) |
0.31 |
|
BMI |
1.01 (1 ~ 1.03) |
0.049 |
|
Hypertension |
||
|
No |
Reference |
|
|
Yes |
1.06 (0.88 ~ 1.27) |
0.556 |
|
Dyslipidemia |
||
|
No |
Reference |
|
|
Yes |
1.44 (1.2 ~ 1.72) |
< 0.001 |
|
Diabetes |
||
|
No |
Reference |
|
|
Yes |
1.13 (0.93 ~ 1.37) |
0.232 |
|
Prediabetes |
||
|
No |
Reference |
|
|
Yes |
0.96 (0.72 ~ 1.28) |
0.783 |
|
Self-reported health condition |
||
|
Excellent, very good, good |
Reference |
|
|
Fair, Poor |
1.72 (1.42 ~ 2.07) |
< 0.001 |
|
Cold/flu for > 1 month |
||
|
Yes |
Reference |
|
|
No |
0.46 (0.33 ~ 0.63) |
< 0.001 |
|
Tonsils removed |
||
|
Yes |
Reference |
|
|
No |
0.81 (0.66 ~ 0.98) |
0.031 |
|
Head injury |
||
|
Yes |
Reference |
|
|
No |
0.55 (0.44 ~ 0.7) |
< 0.001 |
|
Serious head/face injury |
||
|
Yes |
Reference |
|
|
No |
0.62 (0.49 ~ 0.77) |
< 0.001 |
|
Sleep duration |
0.92(0.87 ~ 0.98) |
0.007 |
|
Crude |
Model I |
Model II |
Model III |
|||||
|---|---|---|---|---|---|---|---|---|
|
OR(95%CI) |
P value |
OR(95%CI) |
P value |
OR(95%CI) |
P value |
OR(95%CI) |
P value |
|
|
Sleep duration |
0.92 (0.87 ~ 0.98) |
0.007 |
0.91 (0.86 ~ 0.97) |
0.003 |
0.92 (0.86 ~ 0.98) |
0.009 |
0.93 (0.87 ~ 0.99) |
0.023 |
|
Hours of Sleep |
||||||||
|
< 6 |
Ref |
Ref |
Ref |
Ref |
||||
|
6 ~ 8 |
0.7 (0.56 ~ 0.88) |
0.003 |
0.72(0.57 ~ 0.91) |
0.006 |
0.74 (0.59 ~ 0.95) |
0.016 |
0.77 (0.61 ~ 0.99) |
0.039 |
|
≥ 8 |
0.66(0.52 ~ 0.85) |
0.001 |
0.64(0.49 ~ 0.82) |
0.001 |
0.66(0.51 ~ 0.85) |
0.001 |
0.69 (0.53 ~ 0.9) |
0.006 |
|
Trend test |
0.003 |
0.001 |
0.002 |
0.008 |
||||
Model I：adjusted for gender,age,race/ethnicity,education,marital status,annual family income,smoking status,alcohol status,work activity,physical activity and BMI；
Model II：adjusted for model I plus hypertension,dyslipidemia,diabetes,prediabetes and self-reported health condition；
Model III：adjusted for model II plus cold/flu for >1 month,tonsils removed,head injury and serious head/face injury.
Fig.2 presents a non-linear association between self-reported OD and sleep duration after adjusting for potential confounding factors.In our study, the P-value for the non-linear test was less than 0.028 (Table 4).We found an inflection point at about 7 hours.On the left side of the inflection point, the OR was 0.89 (OR: 0.89, 95%CI: 0.801–0.996, p < 0.028) .On the right side of the inflection point, the OR was 1. 19 (OR:1. 19, 95%CI: 0.97– 1.455, p = 0.096).It suggests that the risk of self-reported OD is reduced by 0. 11% with every 1 hour increase in everyday.Then longer than 7 hours is not significant between OD and sleep duration.This means that the risk of OD no longer decreases with increasing sleep hours.
|
Outcome |
OR (95% CI) |
P value |
|---|---|---|
|
One - line linear regression model |
0.93 (0.87 ~ 0.99) |
0.023 |
|
Two - piecewise linear regression model |
||
|
Sleep duration < 7 hours |
0.89(0.801 ~ 0.996) |
0.042 |
|
Sleep duration ≥ 7 hours |
1.19 (0.97 ~ 1.455) |
0.096 |
|
Log - likelihood ratio test |
< 0.028 |
Notes:adjusted for gender,age,race/ethnicity,education,marital status,annual family income,smoking status,alcohol status,work activity,physical activity，BMI，hypertension,dyslipidemia,diabetes,prediabetes，self-reported health condition，cold/flu for >1 month,tonsils removed,head injury and serious head/face injury.
In the Fig.2, the solid line indicates the estimated risk of self-reported OD, and the dotted lines represent point-wise 95% confidence interval adjusted for gender, age, race/ethnicity, education, marital status, annual family income, smoking status, alcohol status, work activity, physical activity, BMI, hypertension, dyslipidemia, diabetes, prediabetes, self-reported health condition, cold/flu for > 1 month, tonsils removed, loss of consciousness from head injury;broken nose or other serious injury to face or skull.
This cross-sectional study of American adults showed an L-shaped relationship between sleep duration and self-reported OD, with an inflexion point of almost 7 hours per day.
Sleep alterations and olfactory disturbances have been reported in Parkinson's13, 22, 23 、and psychiatric disorders24, 25 as a diagnosis of disease, predicting disease progression in many papers. Ramos26 study reveals the effect of sleep rhythm changes on olfactory sensation, Hsu27finds olfactory deprivation leads to reduced sleep, Li, R28 revealed that adenosine A(2A) receptors (A(2A) Rs) in olfactory nodules have a critical role in sleep regulation. Only few experts have studied whether changes in sleep duration lead to a change in olfaction. V. Eloesa McSorley 29 found
that a long periods of sleep (more than 8 hours) were found to contribute to olfactory disturbances in a population of 354 elderly people. J McNeil 30 discovery sleep deprivation was found to lead to the develop of olfactory impairment in 18populations, but this study did not suggest a specific sleep duration. NHANES provides a unique possibility for our study to assess the relationship between sleep duration and olfaction, as well as the dose-response relationship between the both, with full adjustment for the analysis of large samples and numerous covariates.
An adequate sleep is essential for good health, and studies have found that the length of sleep is associated with many diseases. Lu Dong31 found that 8 hours of sleep reduces depression, Wei Chen32 findings show that 6.5 hours is the optimal amount of sleep to reduce the risk of chest pain, Shan Yin33 study finds 7–9 hours of sleep may reduce kidney stones. Our study included a large sample of people and found an L-shaped relationship between sleep duration and olfactory impairment, suggesting that the optimal sleep duration for olfactory effects in people is 7 hours.
Sleep deprivation raises the risk of developing olfactory dysfunction, and the possible mechanisms include: The first is that sleep deprivation is associated with a decrease in the regenerative capacity of olfactory sensory neurons through a possible lower activity of quinone dehydrogenase 1(NQO 1) in the olfactory epithelium( 12);2. Sleep, especially slow wave sleep, modulation of synaptic connectivity 34 and survival 35of OB neurons known to be critical for precise odor discrimination 36, 37. Our study do have some important limitations. First, the data are cross-sectional and we were unable to extend cause-and-effect results. In addition, we could not analyze why people slept longer or shorter, and the types of hours they slept differently. This is because our study included only one item asking about the average number of hours of sleep per day. The reasons for sleep deprivation may be related to different demographics or physical conditions of individuals, such as low socioeconomic status or inability to sleep while being in illness. Further research on these subtle Factors is needed, therefore, to d relevant and effective sleep health interventions.
In conclusion, there is an L-shaped association between sleep duration and the prevalence of self-reported olfactory disorders in adults in the United States, with an inflection point of approximately 7 hours. The results of this study raise concerns about the relationship between sleep duration and olfactory disorders.
Disclosure
The author reports no conflicts of interest in this work.
Data Availability:
The datasets generated and analysed during the current study are available inthe[NHNAES] repository, [NHANES Questionnaires, Datasets, and RelatedDocumentation (cdc.gov)]