Association between sleep patterns and symptoms of depression in older adults: a cross-sectional study using data from the National Health and Nutrition Examination Survey 2007-2014

doi:10.21203/rs.3.rs-4679172/v1

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Research Article

Association between sleep patterns and symptoms of depression in older adults: a cross-sectional study using data from the National Health and Nutrition Examination Survey 2007-2014

https://doi.org/10.21203/rs.3.rs-4679172/v1

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Background

To assess the association between sleep behaviour and sleep factors (sleep duration, sleep problems, sleep disturbances) and the risk of depression in older adults.

Methods

A total of 5636 participants (2754 men and 2882 women) aged 60 years and older from the 2007–2014 waves of the National Health and Nutrition Examination Survey (NHANES) were included. Sleep duration, sleep problems, and sleep disorders were assessed in the home by trained interviewers using the Computer-Assisted Personal Interviewing (CAPI) system. The combined sleep behaviours were referred to as 'sleep patterns (healthy, intermediate and poor)', with a 'healthy sleep pattern' defined as sleeping 7–9 hours per night with no self-reported sleep problems or sleep disorders. Intermediate and poor sleep patterns indicated 1 and 2–3 sleep problems, respectively. Logistic multiple linear regression was used to assess the association of sleep factors and sleep patterns with the risk of depressive symptoms.

Results

The overall prevalence of depression was 7.7% among the 5636 participants analysed, with the rate of depression in older women being 1.6 times higher than in older men. Compared with normal sleep duration (7–9 hours), short sleep duration (<7 hours) was associated with a higher risk of depression, but long sleep duration (> 9h) did not reach statistical significance. (Short sleep: OR: 2.04, 95% CI: 1.65–2.52; long sleep: OR: 1.47, 95% CI: 0.87–2.48). Self-reported sleep complaints, whether trouble sleeping or sleep disorder, were significantly associated with depression (sleep disturbance: OR: 0.3, 95% CI: 0.24–0.37; sleep disturbance: OR: 0.35, 95% CI: 0.27–0.45). In addition, the correlations appeared to be higher in people with poor sleep patterns (OR: 5.6, 95% CI: 4.25–7.39).

Conclusion

This nationally representative survey showed a relationship between sleep patterns and depression in older adults.

sleep patterns

depression

older adults

NHANES

The United Nations (UN) Population Division predicts that the geriatric population (aged 60 and over) will increase from 800 million, or 11% of the general population, to 2 billion, or 22% of the population, by 2050^[1]. Depression is the most common mental illness in the world. It has become a major public health problem^[2]. It is well known that depression can lead to reduced quality of life, poor adherence to treatment, increased length of hospital stay and use of health services, and in severe cases, suicide^[3]. Depression is more common than other emotional changes in older people. It is associated with a high mortality rate and pathological comorbidity^[4]. The global prevalence of major depression among older people was 13.3%, 11.9% among older women and 9.7% among older men^[5]. One in two older people receiving care at home had probable depression; 13.4% of the sample had major depression; the study sample included 811 community-dwelling adults aged 60^[6]. In a cross-sectional study, 299 elderly people living in Hanoi, Vietnam, were approached for data collection. Self-reported depression among the elderly was 66.9% (32.8% mild, 30.4% moderate and 3.7% severe)^[7]. The rates of depression were 26.67% and 38.37% for men and women, respectively. The data came from the China Health and Retirement Longitudinal Study (CHARLS) follow-up survey (2011 and 2013–2015), which included 3337 residents aged 45 years or older^[8]. Mental health status significantly increased the level of medical expenditure among the rural elderly in China, contributing to 47.26% of total personal expected medical expenditure^[9].

The prevalence of sleep disorders is higher in older adults. Loud snoring, which is more common in older people, can be a symptom of obstructive sleep apnoea, which puts a person at risk of cardiovascular disease, headaches, memory loss and depression. Restless legs syndrome and periodic limb movement disorder, which disrupt sleep, are more common in older people. Prevalence increases with age: 3.2% in children under 10, 5.2% in young adults and 22.3% in people aged 75 and over^[10]. The pooled prevalence of sleep problems in older Chinese adults was 35.9%, with a total of 47 studies included.^[11]. More than a third of participants aged 65 and over reported suboptimal sleep duration. During an average follow-up of 3.52 years, 1,522 (16.1%) participants from a nationally representative sample of 9,430 adults aged 50 and over developed at least one symptom of insomnia^[12]. Short sleep duration had a greater negative impact on morbidity, with a reduction in health-related quality of life (HRQOL), while long sleep duration had a greater negative impact on mortality^[13].

Other common medical problems of old age such as hypertension, diabetes mellitus, renal failure, respiratory diseases such as asthma, immune disorders, gastroesophageal reflux disease, physical disability, dementia, pain, depression and anxiety are all associated with sleep problems^[14]. Risk factors for depression in older people were aspirin use, being aged 80 years or over, sleep problems and persistent sleep problems, hearing problems, poor eyesight and heart disease^[15]. Sleep problems, short sleep and a combination of the two increase the risk of depressive symptoms in older people: a 6-year follow-up of the English Longitudinal Study of Ageing^[16]. Research suggests that older people in the community who have difficulty sleeping are more likely to suffer from anxiety and depression, and that this lack of sleep may lead to depressive symptoms through its effect on the thickness of the left transverse temporal cortex^[17].Respondents with a diagnosis of depression reported significantly higher rates of diagnosed anxiety and sleep problems than those without depression^[18].

To our knowledge, 2 studies have examined the association between sleep and depression in US adults^{[20, 19]}, but the association in older adults. In this cross-sectional study, we aimed to examine the association between sleep and depression in older adults using data from the National Health and Nutrition Examination Survey (NHANES).

Study design

cross-sectional study.

Study Population

NHANES is a nationally representative survey conducted by the National Center for Health Statistics (NCHS), 24 using stratified, multistage probability cluster sampling to assess the health or nutrition status of the non-institutionalised US population. In this cross-sectional study, we examined publicly available data from participants aged 60 years and older with complete and reliable information (demographics, dietary and health-related behaviours, body measurements, and disease information) collected and extracted from the 2007–2008, 2009–2010, 2011–2012, and 2013–2014 NHANES cycles. The NCHS Research Ethics Review Board approved the NHANES study protocol, and participants provided written informed consent at enrolment. The institutional review board of Jiangnan University Affiliated Hospital determined that the study was exempt because it used publicly available deidentified data, and informed consent was waived. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines.

Data from the NHANES 2007–2014 cycles were analysed, including an initial total of 40617 participants. Exclusion criteria for this study included: (a) participants younger than 60 years (n = 32758), (b) participants with incomplete information on sleep (n = 36) or depression (n = 1052), (c) participants with missing data on education level, marital status, PIR, body mass index, smoking status, alcohol consumption, diabetes, renal failure, hypertension, high cholesterol (n = 1135). A total of 5636 individuals qualified for analysis, as shown in Fig. 1.

Assessment of Sleep Factors and Definition of a Sleep Pattern

Sleep duration was obtained by answering the question "How much sleep do you usually get at night on weekdays or working days? Sleep duration was categorised as short (< 7 hours per night), normal (7–9 hours per night) or long (> 9 hours per night), and 7–9 hours per night was used as the reference group. Response to the question "Have you ever told a doctor or other health professional that you have trouble sleeping?" was used to assess sleep disturbance. Sleep factors (sleep duration, self-reported sleep problems and diagnosed sleep disorders) were included to calculate an overall sleep score. Low-risk sleep was defined as 7–9 hours of sleep per night without sleep problems or sleep disorders. For each sleep factor, low-risk was assigned a score of 1 and high-risk a score of 0. Finally, an overall score ranging from 0 to 3 was obtained and overall sleep pattern was defined as poor sleep pattern (0 ≤ overall sleep score ≤ 1), intermediate sleep pattern (overall sleep score = 2) and healthy sleep pattern (overall sleep score = 3)^[20].

Assessment of depressive symptoms

Depressive symptoms in this study were assessed using the Patient Health Questionnaire-9 (PHQ-9). Trained interviewers administered these questions in the Mobile Examination Centre (MEC) using the Computer Assisted Personal Interview (CAPI) system, which has built-in consistency checks to minimise data entry errors. In addition, the CAPI system includes online help screens to clarify any terms used in the questionnaire.To ensure the quality of the data, approximately 5% of the interviews were recorded and reviewed for quality control purposes. The PHQ-9 consisted of nine questions related to depressive mood, and the total score was calculated by summing the scores for each item. The response categories for the nine-item instrument, "not at all", "several days", "more than half the days" and "almost every day", were given a score ranging from 0 to 3. The PHQ-9 scale had a range of 0 to 27. A score of 10 or more was considered indicative of a depressive state^{[23, 22, 21]}.

Other Covariate

A variety of potential covariates were assessed according to the literature, including age, body mass index (BMI), sex, race/ethnicity, educational level, marital status, poverty income ratio (PIR), smoking status, alcohol consumption, diabetes, renal failure, hypertension, high cholesterol, and depression. BMI was calculated as weight (kg) divided by height squared (kg/m²), sex (male, female), race (Mexican American, other Hispanic, non-Hispanic black, other race including multiracial, non-Hispanic white). Educational level (less than 9th grade, 9-11th grade, 12th grade without diploma, high school graduate/GED or equivalent, some college or AA degree, college graduate or higher), marital status (married/cohabiting, widowed, divorced, separated, never married), poverty income ratio (PIR), with values categorised as either < 1 or ≥ 1^[24]. Smoking status was obtained by answering the question "Have you ever smoked at least 100 cigarettes in your lifetime? Smoking status was categorised as yes (≥ 100 cigarettes in lifetime), no (<100 cigarettes in lifetime)^[25]. Alcohol consumption was assessed by answering the question "Have you had at least 12 drinks/1 yr? Alcohol use was categorised as yes (≥ 12 drinks/1 year), no (<12 drinks/1 year)^[25]. Diabetes was obtained by answering "Has your doctor told you you have diabetes?" and diabetes was categorised as yes, no and borderline^[26]. Kidney failure, high blood pressure and high cholesterol are based on whether doctors reported excessive levels of yes or no.

Statistical Analysis

The Kolmogorov-Smirnov test was used to determine whether variables were normally distributed. Normally distributed variables were presented as mean (standard deviation), while skewed variables were presented as median (interquartile range, 25–75%). Categorical variables were presented as proportions (%). Continuous data were compared using t-tests, and categorical data were compared using the χ² test.

We conducted a stratified analysis combining depression scores and sleep patterns and factors. The relationship between sleep patterns and the likelihood of developing depressive symptoms was examined using multivariable logistic regression models. Model 1 was unadjusted, model 2 adjusted for age, sex, BMI, race, education level, marital status, PIR, model 3 adjusted for age, sex, BMI, race, education level, marital status, PIR, smoking status, alcohol consumption, and model 4 adjusted for all variables including age, sex, BMI, race, education level, marital status, PIR, smoking status, alcohol consumption, diabetes, renal failure, hypertension, high cholesterol. To further explore the relationship between sleep status and depressive symptoms, we performed a subgroup analysis. A statistically significant difference was defined as a bilateral p-value of 0.05. The likelihood ratio test was used to examine interactions between subgroups.

As the sample size was based entirely on the available data, no a priori calculation of statistical power was performed. R software (version 4.2.1; R Foundation for Statistical Computing; http://www.Rproject.org), the R survey package (version 4.1-1), and Free Statistics software (version 1.7.1; Beijing Free Clinical Medical Technology Co., Ltd) were used for analyses. In all analyses, a two-sided p-value < 0.05 was used to indicate statistical significance.

Baseline Characteristics of Participants

Table 1 shows the characteristics of the study population stratified by sleep patterns in NHANES 2007–2014. We found differences between age, BMI, race, education, smoking status, PIR, diabetes mellitus, renal failure, hypertension, high cholesterol, poor sleep and intermediate sleep and healthy sleep (P < 0.001). In addition, participants with healthy sleep patterns were more likely to be female and have a higher BMI. Older adults with poor sleep patterns were more likely to have a history of hypertension and depression than those with healthy sleep patterns.

Table 1

Study sample characteristics by sleep pattern status(n = 5636)
Variables		Sleep Patterns (Col %)
Variables	Total (n = 5636)	Healthy (n = 2577)	Intermediate (n = 1904)	Poor (n = 1155)	P-value
Age, year, Mean ± SD	69.9 ± 6.8	70.4 ± 6.9	69.6 ± 6.9	69.3 ± 6.6	< 0.001
BMI, kg/m², Mean ± SD	29.2 ± 6.3	28.6 ± 5.8	29.0 ± 6.1	30.8 ± 7.3	< 0.001
Gender(n, %)					0.003
Male	2754 (48.9)	1318 (51.1)	911 (47.8)	525 (45.5)
Female	2882 (51.1)	1259 (48.9)	993 (52.2)	630 (54.5)
Race(n, %)					< 0.001
Mexican American	560 ( 9.9)	241 (9.4)	200 (10.5)	119 (10.3)
Other Hispanic	514 ( 9.1)	224 (8.7)	175 (9.2)	115 (10)
Non-Hispanic white	3014 (53.5)	1486 (57.7)	938 (49.3)	590 (51.1)
Non-Hispanic black	1178 (20.9)	452 (17.5)	458 (24.1)	268 (23.2)
Other race	370 ( 6.6)	174 (6.8)	133 (7)	63 (5.5)
Education level (n, %)					< 0.001
< 9th grade	764 (13.6)	321 (12.5)	278 (14.6)	165 (14.3)
9-11th grade	829 (14.7)	367 (14.2)	290 (15.2)	172 (14.9)
High school graduate	1337 (23.7)	574 (22.3)	470 (24.7)	293 (25.4)
Some college or AA degree	1485 (26.3)	679 (26.3)	482 (25.3)	324 (28.1)
College graduate or above	1221 (21.7)	636 (24.7)	384 (20.2)	201 (17.4)
Marital status (n, %)					0.001
Married	3215 (57.0)	1557 (60.4)	1045 (54.9)	613 (53.1)
Widowed	1149 (20.4)	498 (19.3)	397 (20.9)	254 (22)
Divorced	757 (13.4)	325 (12.6)	265 (13.9)	167 (14.5)
Separated	133 ( 2.4)	48 (1.9)	54 (2.8)	31 (2.7)
Never married	262 ( 4.6)	106 (4.1)	98 (5.1)	58 (5)
Living with partner	120 ( 2.1)	43 (1.7)	45 (2.4)	32 (2.8)
PIR(n, %)					< 0.001
<1	893 (15.8)	358 (13.9)	310 (16.3)	225 (19.5)
≥ 1	4743 (84.2)	2219 (86.1)	1594 (83.7)	930 (80.5)
Smoke status(n, %)					0.055
Yes	2889 (51.3)	1285 (49.9)	979 (51.4)	625 (54.1)
No	2747 (48.7)	1292 (50.1)	925 (48.6)	530 (45.9)
Consume alcohol(n, %)					0.413
Yes	3695 (65.6)	1707 (66.2)	1226 (64.4)	762 (66)
No	1941 (34.4)	870 (33.8)	678 (35.6)	393 (34)
Diabetes (n, %)					< 0.001
Yes	1313 (23.3)	518 (20.1)	431 (22.6)	364 (31.5)
No	4108 (72.9)	1967 (76.3)	1402 (73.6)	739 (64)
Borderline	215 ( 3.8)	92 (3.6)	71 (3.7)	52 (4.5)
Failing kidneys (n, %)					< 0.001
Yes	290 ( 5.1)	92 (3.6)	96 (5)	102 (8.8)
No	5346 (94.9)	2485 (96.4)	1808 (95)	1053 (91.2)
Hypertension (n, %)					< 0.001
Yes	3570 (63.3)	1544 (59.9)	1191 (62.6)	835 (72.3)
No	2066 (36.7)	1033 (40.1)	713 (37.4)	320 (27.7)
High cholesterol (n, %)					< 0.001
Yes	3179 (56.4)	1405 (54.5)	1055 (55.4)	719 (62.3)
No	2457 (43.6)	1172 (45.5)	849 (44.6)	436 (37.7)
Depression(n, %)					< 0.001
Yes	436 ( 7.7)	82 (3.2)	144 (7.6)	210 (18.2)
No	5200 (92.3)	2495 (96.8)	1760 (92.4)	945 (81.8)

Table 2 shows the characteristics of participants based on their depression scores in a study that included 5636 individuals, of whom 436 scored 10 or more on the depression scale. The mean age of participants with depression was 67.9 years, which was significantly lower than the mean age of those without depression (70.0 years, p < 0.001). In addition, the proportion of men in the non-depression group was significantly higher than that in the depression group (49.8% vs. 38.3%, p < 0.001), while the proportion of women in the non-depression group was significantly lower than that in the depression group (50.2% vs. 61.7%, p < 0.001). BMI, race, education, marital status, PIR, smoking status, diabetes, renal failure, hypertension and sleep variables also differed significantly between the two groups (p < 0.001).

Table 2

Characteristics of participants by depression status
Variables		Depression(Col%)
Variables	Total (n = 5636)	No (n = 5200)	Yes (n = 436)	P-value
Age, year, Mean ± SD	69.9 ± 6.8	70.0 ± 6.8	67.9 ± 6.5	< 0.001
BMI, kg/m², Mean ± SD	29.2 ± 6.3	29.1 ± 6.2	30.9 ± 7.0	< 0.001
Gender(n, %)				< 0.001
Male	2754 (48.9)	2587 (49.8)	167 (38.3)
Female	2882 (51.1)	2613 (50.2)	269 (61.7)
Race(n, %)				< 0.001
Mexican American	560 ( 9.9)	485 (9.3)	75 (17.2)
Other Hispanic	514 ( 9.1)	450 (8.7)	64 (14.7)
Non-Hispanic white	3014 (53.5)	2823 (54.3)	191 (43.8)
Non-Hispanic black	1178 (20.9)	1094 (21)	84 (19.3)
Other race	370 ( 6.6)	348 (6.7)	22 (5)
Education level (n, %)				< 0.001
< 9th grade	764 (13.6)	661 (12.7)	103 (23.6)
9-11th grade	829 (14.7)	736 (14.2)	93 (21.3)
High school graduate	1337 (23.7)	1245 (23.9)	92 (21.1)
Some college or AA degree	1485 (26.3)	1380 (26.5)	105 (24.1)
College graduate or above	1221 (21.7)	1178 (22.7)	43 (9.9)
Marital status (n, %)				< 0.001
Married	3215 (57.0)	3038 (58.4)	177 (40.6)
Widowed	1149 (20.4)	1044 (20.1)	105 (24.1)
Divorced	757 (13.4)	661 (12.7)	96 (22)
Separated	133 ( 2.4)	108 (2.1)	25 (5.7)
Never married	262 ( 4.6)	235 (4.5)	27 (6.2)
Living with partner	120 ( 2.1)	114 (2.2)	6 (1.4)
PIR(n, %)				< 0.001
<1	893 (15.8)	750 (14.4)	143 (32.8)
≥ 1	4743 (84.2)	4450 (85.6)	293 (67.2)
Smoke status(n, %)				0.001
Yes	2889 (51.3)	2633 (50.6)	256 (58.7)
No	2747 (48.7)	2567 (49.4)	180 (41.3)
Consume alcohol(n, %)				0.765
Yes	3695 (65.6)	3412 (65.6)	283 (64.9)
No	1941 (34.4)	1788 (34.4)	153 (35.1)
Diabetes (n, %)				< 0.001
Yes	1313 (23.3)	1147 (22.1)	166 (38.1)
No	4108 (72.9)	3857 (74.2)	251 (57.6)
Borderline	215 ( 3.8)	196 (3.8)	19 (4.4)
Failing kidneys (n, %)				< 0.001
Yes	290 ( 5.1)	240 (4.6)	50 (11.5)
No	5346 (94.9)	4960 (95.4)	386 (88.5)
Hypertension (n, %)				< 0.001
Yes	3570 (63.3)	3259 (62.7)	311 (71.3)
No	2066 (36.7)	1941 (37.3)	125 (28.7)
High cholesterol (n, %)				< 0.001
Yes	3179 (56.4)	2893 (55.6)	286 (65.6)
No	2457 (43.6)	2307 (44.4)	150 (34.4)
Sleep duration (hours)				< 0.001
<7	2001 (35.5)	1766 (34)	235 (53.9)
7–9	3425 (60.8)	3242 (62.3)	183 (42)
>9	210 ( 3.7)	192 (3.7)	18 (4.1)
Trouble sleeping(n, %)				< 0.001
Yes	1647 (29.2)	1394 (26.8)	253 (58)
No	3989 (70.8)	3806 (73.2)	183 (42)
Sleep disorder(n, %)				< 0.001
Yes	600 (10.6)	492 (9.5)	108 (24.8)
No	5036 (89.4)	4708 (90.5)	328 (75.2)
Sleep Patterns(n, %)				< 0.001
Poor	1155 (20.5)	945 (18.2)	210 (48.2)
Intermediate	1904 (33.8)	1760 (33.8)	144 (33)
Healthy	2577 (45.7)	2495 (48)	82 (18.8)

Association between Sleep Patterns Concentrations and Depressive Symptoms

Table 3 shows the results of the analysis examining the association between sleep patterns and depression scores. The unadjusted model shows a significant association between poor sleep and healthy sleep (OR = 6.76, 95%CI: 5.18–8.82, p < 0.001). Adjusted model 2 for age, sex, BMI, race, education level, marital status, PIR showed a significant association (OR = 6.11, 95%CI: 4.65–8.04, p < 0.001). There was a significant association (OR = 6.02, 95%CI: 4.57–7.92, p < 0.001) when adjusting model 3 for additional factors including smoking status, alcohol consumption. Adjustment model 4 for additional factors including diabetes, renal failure, hypertension, high cholesterol showed a significant association (OR = 5.6, 95%CI: 4.25–7.39, p < 0.001).The unadjusted model shows a significant association between short sleep and long sleep (OR = 6.76, 95%CI: 5.18–8.82, p < 0.001). Adjusted model 2 for age, sex, BMI, race, education level, marital status, PIR showed a significant association (OR = 6.11, 95%CI: 4.65–8.04, p < 0.001). Adjustment model 3 for additional factors including smoking status, alcohol consumption resulted in a significant association (OR = 6.02, 95%CI: 4.57–7.92, p < 0.001).Adjustment model 4 for additional factors including diabetes, renal failure, hypertension, high cholesterol resulted in a significant association (OR = 5.6, 95%CI: 4.25–7.39, p < 0.001).Compared to normal sleep duration (7–9 h), short sleep duration (<7h) were associated with a higher risk of depression, but long sleep duration (>9h) did not reach statistical significance. (Short sleep: OR: 2.04, 95% CI: 1.65–2.52; long sleep: OR: 1.47, 95% CI: 0.87–2.48). Self-reported sleep complaints, whether sleep disturbance or sleep disorder, were significantly associated with depression (sleep disturbance: OR: 0.3, 95% CI: 0.24–0.37; sleep disturbance: OR: 0.35, 95% CI: 0.27–0.45).

Table 3

Multivariate regression analysis of the associate between sleep and depression
Variable	n.total	n.event_%	Model 1	P_value	Model 2	P_value	Model 3	P_value	Model 4	P_value
Sleep Patterns
Healthy	2577.0	82 (3.2)	1(Ref)		1(Ref)		1(Ref)		1(Ref)
Intermediate	1904.0	144 (7.6)	2.49 (1.89 ~ 3.29)	< 0.001	2.32 (1.75 ~ 3.08)	< 0.001	2.3 (1.73 ~ 3.05)	< 0.001	2.28 (1.71 ~ 3.03)	< 0.001
Poor	1155.0	210 (18.2)	6.76 (5.18 ~ 8.82)	< 0.001	6.11 (4.65 ~ 8.04)	< 0.001	6.02 (4.57 ~ 7.92)	< 0.001	5.6 (4.25 ~ 7.39)	< 0.001
Trend. test	5636.0	436 (7.7)	2.62 (2.3 ~ 2.98)	< 0.001	2.49 (2.18 ~ 2.85)	< 0.001	2.47 (2.16 ~ 2.83)	< 0.001	2.38 (2.07 ~ 2.73)	< 0.001
Sleep duration
7 ~ 9	3425.0	183 (5.3)	1(Ref)		1(Ref)		1(Ref)		1(Ref)
<7	2001.0	235 (11.7)	2.36 (1.93 ~ 2.88)	< 0.001	2.07 (1.68 ~ 2.55)	< 0.001	2.08 (1.69 ~ 2.57)	< 0.001	2.04 (1.65 ~ 2.52)	< 0.001
>9	210.0	18 (8.6)	1.66 (1 ~ 2.75)	0.049	1.48 (0.88 ~ 2.5)	0.137	1.45 (0.86 ~ 2.45)	0.165	1.47 (0.87 ~ 2.48)	0.152
Trend. test	5636.0	436 (7.7)	1.8 (1.54 ~ 2.11)	< 0.001	1.64 (1.39 ~ 1.94)	< 0.001	1.64 (1.39 ~ 1.94)	< 0.001	1.63 (1.37 ~ 1.93)	< 0.001
Trouble sleeping
Yes	1647.0	253 (15.4)	1(Ref)		1(Ref)		1(Ref)		1(Ref)
No	3989.0	183 (4.6)	0.26 (0.22 ~ 0.32)	< 0.001	0.27 (0.22 ~ 0.34)	< 0.001	0.28 (0.23 ~ 0.34)	< 0.001	0.3 (0.24 ~ 0.37)	< 0.001
Sleep disorder
Yes	600.0	108 (18)	1(Ref)		1(Ref)		1(Ref)		1(Ref)
No	5036.0	328 (6.5)	0.32 (0.25 ~ 0.4)	< 0.001	0.31 (0.24 ~ 0.4)	< 0.001	0.31 (0.24 ~ 0.4)	< 0.001	0.35 (0.27 ~ 0.45)	< 0.001

Model 1:no adjusted.

Model 2: adjusted for age + gender + BMI + race + education level + marital status + PIR

Model 3: Model 2 + smoke status + consume alcohol

Model 4: Model 3 + diabetes + failing kidneys + hypertension + high cholesterol

Stratifed analyses by age, gender, BMI

In this study we also stratified the analysis by age, gender and BMI. The results are shown in Fig. 2 We found that there was still an association between geriatric depression scores and sleep patterns based on age, sex and BMI. The results showed that people aged 70 years or women with a BMI of 25–30 kg/m² with poor sleep patterns had a higher risk of depression compared with healthy sleep.

To our knowledge, this is the first study of the relationship between sleep behaviour and depression in older age in a large nationally representative study. We found that sleep duration, the presence of sleep problems and sleep disorders were strongly associated with depression. We then learned that too little sleep, a higher proportion of older people with sleep problems or sleep disorders, and older patients with poor sleep patterns were at greater risk of depression.

Among the 436 older depressed patients, older women (61.7%) were about 1.6 times more likely than older men (38.3%). One study reported^[27] that older women reported significantly higher levels of depression than men, which is consistent with our findings. There are many reasons why older women are more likely to be depressed than older men. After the menopause, women's oestrogen levels decrease, which can be associated with increased mood swings and depressive symptoms^[28]. Studies have shown that in^[29], Women may be more sensitive to certain genes that affect the risk of depression. Second, older women may be more likely to experience certain life events, such as living alone and having children away from home, which can increase the risk of depression. Women are more likely to choose social withdrawal or self-attribution when they face problems, and these strategies may be associated with the development of depression. Finally, older women may take on more caring responsibilities at home, which can lead to stress or depression.

Among older people without depression, 73.2% did not have sleep problems and 26.8% did. This suggests that older people with sleep problems are more likely to develop depression. There are many reasons why older people with sleep problems and sleep disorders are more likely to develop depression. Long-term sleep problems cause chronic stress, which is a known risk factor for depression. Lack of sleep can make it harder for the body and brain to recover, increasing mental stress. Sleep disorders can lead to reduced daily activities in older adults, as they may avoid social activities due to fatigue^[30]. This social isolation increases loneliness, which in turn increases the risk of depression^[12]. Sleep problems can affect older adults' quality of life, including daily activities, work productivity and overall well-being. These factors can increase the risk of depression. Inconcentration and reduced performance due to daytime sleepiness may trigger reactive depression, a response to life stressors^[31]. At the same time, older people may have multiple chronic conditions, the management of which can affect sleep and mood, increasing the risk of depression. It is therefore very important to identify and treat sleep problems in older people with sleep disorders to reduce the risk of depression. At the same time, older people with depression also need to be assessed for the presence of sleep disorders and consider treatment options.

Short sleep duration increases the risk of depression in older adults, while longer sleep duration is not statistically significant, which may be related to their physiology. The National Sleep Foundation recommends^[32] For older adults (65 + years), the recommended minimum amount of sleep per night is 7–8 hours. Lack of sleep can lead to moody mood, fatigue, irritability, forgetfulness, cognitive deficits^[33], as well as obesity^[34], diabetes^[35] and hypertension^[36], which may increase the risk of depression in the elderly. With the increase of age, the elderly body function decline, organs and tissues gradually decline, the metabolic capacity of the body, the body control body sleep hormones also began to slowly decline, seriously affect the elderly sleep, lead to difficult to sleep at night, insomnia increased significantly, thus shortening the sleep time at night^[37]. Although studies have shown that sleeping too much or too little can increase the risk of depression, it is natural for older people to lose sleep due to reduced physical function. As the number of older people who sleep too long is not large, it is not statistically significant here.

Older adults with moderate sleep quality had a 2.49 times higher risk of depression than those with healthy sleep quality, while those with poor sleep quality had a 6.76 times higher risk of depression than those with healthy sleep quality. The results remained stable after adjustment for demographics, smoking, alcohol use and comorbidities, suggesting that poor sleep quality increases the risk of depression in older adults. Insomnia is the most common sleep problem in older people, manifesting as difficulty falling asleep, waking up frequently during the night, or waking up early. Insomnia and depression share common risk factors, and both are associated with serotonin and norepinephrine deficiency, hypothalamic-pituitary-adrenal axis hyperactivity, hyperexcitability, disturbed rapid eye movement (REM) sleep, and reduced slow-wave sleep^{[38, 39]}. In addition, poor sleep quality affects older people's cognitive functions, including attention, memory and decision-making, which are also typical of depression^[40]. Studies suggest that poor sleep quality may be a symptom of depression, and that depression may also cause or worsen sleep problems^[41]. This bidirectional relationship means that sleep problems and depressed mood can influence each other, creating a vicious cycle.

Our study used data from a nationally representative sample of the population. The NHANES sampling method ensures that the sample is randomly selected and representative of the entire US population. The current study also has some limitations. First, as a cross-sectional study, the nature of the design does not allow us to determine whether sleep problems caused depression, or depression caused sleep problems, or both may have been influenced by common factors; second, data were collected at a single point in time and could not capture trends in sleep and depression over time. Finally, the reliance on participant self-report may be affected by recall bias, where participants may not be able to accurately recall past sleep or emotional states.

Overall, this study highlights the association between sleep problems and the risk of depression in older adults. Further prospective studies are needed to investigate the causal or bidirectional relationship between sleep quality and risk of depression in older adults. In addition, investigating the genetic associations and underlying mechanisms between sleep and depression in adults is crucial for effective prevention and treatment of depression in older age.

95%CI	95% Confidence Interval
ANOVA	Analysis of Variance
N	Number
NHANES	National Health and Nutrition Examination Survey
OR	Odds Ratio
SD	Standard Deviation
χ²	Chi-square
BMI	body mass index
PIR	Ratio of family income to poverty
SD	Standard Deviation

Acknowlegements

Not applicable.

Authors’ contributions

YN and SY designed the study. YN wrote the manuscript. YN, YS and YJ collected, analyzed and interpreted the data. SY critically reviewed, edited and approved the manuscript. All authors read and approved the final manuscript.

Funding

Not applicable.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the NHANES database, https://wwwn.cdc.gov/nchs/nhanes/.

Declarations

Ethics approval and consent to participate

This study did not need to be approved by the Wuxi Medical College of Jiangnan University, Jiangnan University Affiliated Hospital because the data was accessed from NHANES (a publicly available database). All methods were carried out in accordance with relevant guidelines and regulations (declaration of Helsinki). All individuals provided written informed consent before participating in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Author details

¹Wuxi Medical College of Jiangnan University, No.1800 Lihu Avenue, 214122 Wuxi, Jiangsu Province, People’s Republic of China.²Affiliated Hospital of Jiangnan University,No.1000 Hefeng Road 214122 Wuxi, Jiangsu Province, People’s Republic of China.

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No competing interests reported.

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Association between sleep patterns and symptoms of depression in older adults: a cross-sectional study using data from the National Health and Nutrition Examination Survey 2007-2014

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Assessment of Sleep Factors and Definition of a Sleep Pattern

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Baseline Characteristics of Participants

Association between Sleep Patterns Concentrations and Depressive Symptoms

Stratifed analyses by age, gender, BMI

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